Conference Proceedings

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1 Conference Proceedings

2 Proceedings of 4 th International Conference on Chemical Engineering 2014 Department of Chemical Engineering Bangladesh University of Engineering and Technology (BUET) Dhaka-1000, Bangladesh

3 Technical Sub-Committee Prof. Dil Afroza Begum Mr. Sirajul Haque Khan Dr. Mohidus Samad Khan Proceedings Sub-Committee Prof. M.A.A. Shoukat Choudhury Dr. Shoeb Ahmed Dr. Kazi Bayzid Kabir Dr. Mohidus Samad Khan 2014, Chemical Engineering Department, BUET, Dhaka-1000, Bangladesh Disclaimer No responsibility is assumed by the publisher for any injury and/or damage to persons or property as a matter of product liability, negligence or otherwise, or from any use or operation of any methods, products, instructions or ideas contained in the material herein. The opinions expressed in the papers contained in this Proceedings are the sole responsibility of the authors. ICChE 2014 has no means of verifying the authenticity of claims made by the authors in their papers. All Technical Sessions Papers have been fully peer-reviewed by appropriately qualified independent referees. Compiled by Proceedings Sub-Committee of ICChE 2014 ISBN ii

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5 Table of Contents Technical Sessions Articles ICChE14102 Electrochemical investigation of corrosion behavior of Al-6Si-0.5Mg (-2Cu) alloys in 0.1M NaCl solution (simulated sea water) - A. Hossain; M. A. Gafur; F. Gulshan; A. S. W. Kurny ICChE14103 ICChE14104 ICChE14105 ICChE14107 ICChE14109 Electrochemical investigation of corrosion behavior of Al-6Si-0.5Mg (-2Ni) alloys in NaCl solution (simulated sea water) - A. Hossain; R. Qadir; F. Gulshan; A. S. W. Kurny Application of Multi Criteria Decision Making (MCDM) methods for selection of Green fuel for Clean climate based on experimental data: A Holistic approach -Swarup Paul; Bijan Sarkar; P. K. Bose Estimation of Mineral Content in Some Selected Fish of Bangladesh - Md. Abdullah Al Mamun; Ruhina Binta A Ghani; Md.Tazul Islam; Sheikh Nazrul Islam Copper immobilized Platinum Electrocatalyst for the Effective Reduction of Nitrate in a Low Conductive Medium: mechanism, adsorption thermodynamics and stability -Alam M. Mahbubul, Uddin S.M. Nizam, Rashed M. Abu, Hasnat M. Abul 3D Heat Transfer through a Solar Collector Utilizing Nanofluids -Rehena Nasrin; Salma Parvin; M.A. Alim ICChE14111 A System Analysis Approach for Modeling the Deliverability Of a Gas Condensate Well - Tanvir Ahmed; Farhana Akter; Mohammad Mojammel Huque ICChE14112 ICChE14113 ICChE14115 ICChE14133 ICChE14139 ICChE14140 ICChE14141 ICChE14142 ICChE14146 ICChE14147 ICChE14152 Reserve Estimation of the Producing Gas Sands of a Gas Condensate Reservoir in Bangladesh -Tanvir Ahmed; Farhana Akter Effect of Chemical Reaction on Heat and Mass Transfer in a Parallel Plate Reactor Channel with Heated Cylinders - Salma Parvin; Rehena Nasrin; M. A. Alim; N. F. Hossain Production Optimization of Well HBJ#06 of Habiganj Gas Field -Tahmilur Rahman; Farhana Akter Network Analysis: West Zone Gas Transmission Pipeline Network in Bangladesh - S. M. Amir Hossain; Mohammad Mojammel Huque; Mohammed Mahbubur Rahman Study of Photo Catalytic and Antibacterial Activity of Ag/B/N CO-Doped TiO2 / CNT Composite Films - M. M. R. Mazumder; M. S. Islam; M. A Hossain; E. Mahmud; D. R. Sarker; Z. Rahman; F. Begum; H. R. Chowdhury; M. N. Uddin; D. K. Saha; M. A. B. H. Susan Alarm Allocation for an Event-Based Alarm System - Pradeep Dalpatadu; Salim Ahmed; Faisal Khan Continuous-Time Identification Using Sinusoidal Response: A Comparative Study for Input Design - Shaikh Fahim, Salim Ahmed; Syed Imtiaz Reduction of Magnetite Ore Fines with Hydrogen -Saikat Kumar Kuila; Shamik Chaudhuri; Ritayan Chatterjee; Dinabandhu Ghosh 3D Flexible Supercapacitor Electrodes via Layer by Layer Assembly of Graphene-Polyaniline Nanostructures - Mahbub Hassan; Vincent.G. Gomes Effect of External Shading and Window Glazing on Energy Consumption of Buildings in Bangladesh - Md. Jahangir Alam; Mohammad Ariful Islam; Biplob Kumar Biswas Effect of Pharmaceutical Industry Effluents on Seed Germination and Seedling Growth of Some Cultivated Crops - Shamim Ahmed Hira; Md. Mizanur Rahman ICChE14153 Analyzing Annulus Pressure Build-up to Assess Well Integrity - A. Rashid Hasan 102 ICChE14155 ICChE14160 ICChE14164 Removal of the Reactive Dye from the Waste Water by Batch and Column Adsorption: Batch and Kinetic Modeling - M. R. Khan; T. K. Deb; K. Islam; M. R. Karim Characterizing Dental Erosion Potential of Beverages and Bottled Drinking Water - Fatima Enam; Mehnaz Mursalat; Upoma Guha; Nirupam Aich; Muzahidul Islam Anik; Mohidus Samad Khan Toxicity of Textile Mill Effluents - Khaliqur Rahman; Akber Hakim; AKM Ahsanul Islam; Afrina Samain iv

6 ICChE14170 Synthesis, Development & Characterization of Cobalt Modified Ordered Mesoporous Carbon for PEM Fuel Cell - Khondker N. Sultana; Ahmed L. Fadhel; Vishwanath Deshmane; Debasish Kuila; Shamsuddin Ilias ICChE14172 Study of Textile Sludge Treatment Using Incineration Techniques - Salma A. Iqbal; A. K. M. Abdul Quader; Iqbal Mahmud ICChE14173 Resource Recovery from Spent Zinc Carbon Dry Cell using Hydrometallurgical Technique - Md. Hasib Al Mahbub; Nandini Deb; Shamsul Abedin; Muhammad Raisul Abedin; Mohidus Samad Khan ICChE14177 Pipeline Leak Detection Using Particle Filter - B. M. Sirajeel Arifin; Zukui Li, Sirish L. Shah 144 ICChE14178 ICChE14179 ICChE14180 ICChE14184 A Study on Chitosan and Its Derivatives as Eco-Friend Jute Fibre Modifier Obtained from Prawn Shell Waste - Md. Mofakkharul Islam; Md. Waliul Islam; Md. Ibrahim H. Mondal Modification of Cotton Fibre with Functionalized Silane Coupling Agents - Md. Khademul islam; Md. Raihan Sharif; Md. Ibrahim H. Mondal Low Cost Carboxymethyl Cellulose Preparation from Agro Waste on the Basis of Particle Size - Md. Saifur Rahman; Md. Ibrahim H. Mondal A Systems Engineering Approach for Automated Irrigation - Jannatun Nahar; Jinfeng Liu; Sirish L. Shah ICChE14185 Nutrition Value Analysis of Artificially Ripened Banana (Bari-1 hybrid banana, Musa Spp.) - A. H. M. Sazedur Rahman, Md. Nazibul Islam, Mollik Yousuf Imtiaz, Abdullah Faisal Pasha, Mehnaz Mursalat, Sabrina Shawreen Alam, Mohidus Samad Khan ICChE14187 ICChE14189 ICChE14190 ICChE14191 ICChE14192 ICChE14193 ICChE14197 ICChE14199 ICChE14201 Material and Leaching Characterization of Municipal Solid Waste Incineration (MSWI) Ashes: An Approach toward Sustainable Waste Management - Kazi Tasneem; Boo Hyun Nam; Jongwan Eun Feasibility of Removal of Hexavalent Chromium using a Mix of Fish Scales - Syeda Tajin Ahmed; Fatima Enam; Md. Mominur Rahman Effect of Mesoporous Support on H2 Production via Methanol Steam Reforming in the Presence of Cu and Zn Catalysts - Richard Y. Abrokwah; Vishwanath G. Deshmane; Sri Lanka Owen; William Dade; Sara Al-Salihi; Debasish Kuila Comparative Analysis of Chitosan Production Methods and its Optimization - S.M. Zayadul Islam, Sheikh Md. Enayetul Babar Molecular Simulation of Antibody-Antigen Interactions using 3D Homology Modelling and Docking - Mohidus Samad Khan, M.A. Whitehead, and Theo G.M. van de Ven Detection of Causality Between Industrial Alarm Data Based on Transfer Entropy - Weijun Yu; Fan Yang Simulation of Eastern Refinery Production - Mohammad Hasibul Hasan; Tania Hossain; Quazi Azizul Hassan; Sabrina Khan; M. T. Sowgath Dispersion Modelling of Accidental Release of Chlorine Gas - Rajesh Paul; Animesh Mondal; M. A. A. Shoukat Choudhury Minimisation of Water Usage in Industry Using Water Cascade Analysis: A Winery Case Study - Nicholas Nyamayedenga; Iqbal M. Mujtaba ICChE14204 Potential Benefits, Hazards and Prevention of Gas Hydrate - M. A. Rahman; A. Amin; S. Ahmed; S. Imtiaz ICChE14205 An Approach for Quantitative Estimation of Long Range Transport of Fine Particulate Matter Entering Bangladesh - Bilkis A. Begum; Md. Nasiruddin; Philip K. Hopke; Andreas Markwitz ICChE14206 Assessment of Water Quality of Bhairab River in Bangladesh - Z. H. Khan; U. K. Navera; R. Rahman ICChE14207 ICChE14208 Comparative Study of Nonlinearity Measures Using Routine Operation Data - Malik M Tahiyat ; M A A Shoukat Choudhury Permit-To-Work (Ptw) System: A Case Study of Bangora Gas Plant - Chowdhury Mohammad Touhid Amin, Sultana R Syeda v

7 ICChE14122 ICChE14150 ICChE14151 ICChE14157 ICChE14166 ICChE14171 ICChE14181 ICChE14149 Student Sessions Articles Utilization of Banana Pseudo-Stem in Production of Mineral SAP Drinks, Flour and Liquid Detergent - Seefat Farzin; Fouzia Hasan Nowrin; Md. Mominur Rahman Biogas Production From Anaerobic Co-Digestion Of Cow Manure With Kitchen Waste And Water Hyacinth - Salma A. Iqbal; Farzana Tasnim; Aminur Rashid Chowdhury Production of Biofuel from Agricultural Wastes - Raka Islam; Rayhana Nayema Sohel; M.A.A. Shoukat Choudhury Adsorptive Removal of Methylene blue by Rubber Leaf Powder - Md. Akhtarul Islam; Md. Tamez Uddin; Sourav Chowdhury; MD. Yasin Development of an Algorithm to Calculate Heart Rate from the Blood Pressure Data Obtained using Oscillometric Algorithm - Noor Mohammed; Sumon Saha; M. Zakir Hossain Food Safety: Critical Analysis of Conventional, Alternative and Optimum Food Preservation Techniques for Bangladesh - Md. Mezbah Uddin Oyon; Sadat Kamal Amit; Rezwanul Islam; Rizwanr Rahman Abeer Comparing the Performance of Programmable Logic Controller and Microcontroller in a simple tank system - Sheikh Waheed Baksh; Sayed Abu Sufyan; M. A. A. Shoukat Choudhury HVAC System: An Indispensable Rudiment for Qualitative Medicine Production - Khalida Binte Harun; Razib Hasan; Arif Morshed Azad vi

8 Technical Sessions

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10 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh ELECTROCHEMICAL INVESTIGATION OF CORROSION BEHAVIOR OF Al-6Si-0.5Mg (-2Cu) ALLOYS IN 0.1M NaCl SOLUTION (SIMULATED SEA WATER) A. Hossain 1*, M. A. Gafur 2, F. Gulshan 1, ASW Kurny 1 1 Department of Materials and Metallurgical Engineering, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh 2 Senior Engineer, Pilot Plant and Process Development Centre (PP & PDC), BCSIR Laboratories, Dhaka, Bangladesh The corrosion behavior of thermally treated Al-6Si-0.5Mg (-2Cu) alloys in 0.1M NaCl solution (simulated sea water) was investigated using potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) techniques. Scanning Electron Microscopy (SEM) was employed to characterize the corroded surface and to observe the extent of pitting. Pronounced effect of pitting was observed in presence of Cl - for Al-6Si-0.5Mg-2Cu. The potentiodynamic polarization curves reveal that Al-6Si-0.5Mg-2Cu alloy is more prone to corrosion than the Al-6Si-0.5Mg alloy. But the EIS test result showed that corrosion resistance or charge transfer resistance (Rct) of Al-6Si-0.5Mg-2Cu was higher than the Al-6Si-0.5Mg alloy. The magnitude of open circuit potential (OCP), corrosion potential (Ecorr) and pitting corrosion potential (Epit) in the NaCl solution were shifted in the more noble direction due to 2wt% addition of Cu into Al-6Si- 0.5Mg alloy. 1. INTRODUCTION Aluminium and its alloys are considered to be highly corrosion resistant under the majority of service conditions (Fontana and Greene, 1987). The various grades of pure aluminum are the most resistant, followed closely by the Al-Mg and Al-Mn alloys. Next in order after them are Al-Mg-Si and Al-Si alloys. The alloys containing copper are the least resistant to corrosion (Zor et. al., 2010); but this can be improved by coating each side of the copper containing alloy with a thin layer of highly pure aluminium and gaining a three ply metal (Alclad). This cladding acts as a mechanical shield and offers sacrificial protection (Scamans et. al., 1989).When aluminum surfaces are exposed to atmosphere, a thin invisible oxide (Al 2 O 3 ) skin forms, which protects the metal from further corrosion in many environments (Fontana and Greene, 1987). This film protects the metal from further oxidation unless this coating is destroyed, and the material remains fully protected against corrosion (Scamans et. al., 1989). The composition of an alloy and its thermal treatment are important to determine the susceptibility of the alloy to corrosion (Czechowski, 2007, Abdulwahab et. al., 2011). Over the years a number of studies have been carried out to assess the effect of Cu content and the distribution of second phase intermetallic particles on the corrosion behavior of Al alloys. The distribution of Cu in the microstructure affects the susceptibility to localized corrosion. Intergranular corrosion (IGC) is generally believed to be associated with Cu containing grain boundary precipitates and the precipitates free zones (PFZ) along grain boundaries (Svenningsen and Larsen, 2006, Svenningsen et al., 2006, Larsen and Walmsley, 2006). In heat treatable Al-Si-Mg (-Cu) series alloys, the susceptibility to localized corrosion [pitting and / or intergranular (IGC)] and the extent of attack are mainly controlled by the type, amount and distribution of the precipitates which form in the alloy during any thermal or thermomechanical treatment performed during manufacturing processes (Svenningsen et. al., 2006, Svenningsen and Larsen, 2006, Svenningsen and Larsen, 2006, Svenningsen et al., 2006, Larsen and Walmsley, 2006). * Corresponding Author: A. Hossain ah_buetmmesgfl@live.com

11 Depending on the composition of the alloy and parameters of the heat treatment process, these precipitates form in the bulk of the grain, or in the bulk as well as grain boundaries. As indicated by several authors, the precipitates formed by heat treatment in Al-Si-Mg alloys containing Cu are the θ (Al 2 Cu) Q-phase (Al 4 Mg 8 Si 7 Cu 2 ), β-phase (Mg 2 Si) and free Si if Si content in the alloy exceeds the Mg 2 Si stoichiometry (Zhan et. al., 2008, Larsen et. al., 2010, Zor et. al., 2010). The present study is an attempt to investigate the corrosion behavior of Al-6Si-0.5Mg (-2Cu) alloys in 0.1M NaCl solution (simulated sea water) and to examine corroded surfaces by optical and scanning electron microscope. 2. EXPERIMENTAL 2.1 Materials Preparation The Al-6Si-0.5Mg (-2Cu) alloys were prepared by melting Al-7Si-0.3Mg (A356) alloys and adding Al and Cu into the melt. The melting operation was carried out in a gas fired clay graphite crucible furnace and the alloys were cast in a permanent steel mould. After solidification the alloys were homogenized (at 500 o C for 24hr), solution treated ( at 540 o C for 2hr) and finally artificially aged ( at 225 o C for 1hr). Afterwards heat treatment rectangular samples (50mm 2 or 10mm x 5mm) were prepared for metallographic observation and subsequent electrochemical test. De-ionized water and analytical grade sodium chloride (NaCl) were used for the preparation of 0.1M solution. All measurements were carried out at room temperature. 2.2 Potentiodynamic Polarization Measurements A computer-controlled Gamry Framework TM Series G 300 and Series G 750 Potentiostat/ Galvanostat/ZRA were used for the electrochemical measurements. The Potentiodynamic polarization studies were configured in cells, using three-electrode assembly: a saturated calomel reference electrode, a platinum counter electrode and the sample in the form of coupons of exposed area of 0.50 cm 2 or 10mm x 5mm as working electrode. Only one 10mm x 5mm surface was exposed to the test solution while the other surfaces were covered with Teflon tape. The system was allowed to establish a steady-state open circuit potential (OCP). The potential range selected was -1 to +1V and measurements were made at a scan rate of 0.50mV/s. The corrosion current (Icorr), corrosion potential (Ecorr), pitting corrosion potential (Epit) and corrosion rate (mpy) were calculated from Tafel curve. The tests were carried out at room temperature in solutions containing 0.1M of NaCl at a fixed and neutral ph value. The corroded samples were cleaned in distilled water and examined under optical light microscope (OLM) and scanning electron microscope (SEM). 2.3 Electrochemical Impedance Measurements During the potentiodynamic polarization test, three electrode cell arrangements were also used for electrochemical impedance measurements. Rectangular samples (10mm x 5mm) were connected with copper wire and were adopted as working electrode. EIS tests were performed in 0.1M NaCl solution at room temperature over a frequency range of 100 khz to 0.2Hz, using a 5mV amplitude sinusoidal voltage. The 10mm x 5mm sample surface was immersed in 0.1M NaCl solution (corrosion medium). All the measurements were performed at the open circuit potential (OCP). The test cells were maintained at room temperature and the NaCl solution was refreshed regularly during the whole test period. The impedance spectra were collected, fitting the experimental results to an equivalent circuit (EC) with the use of Echem Analyst TM data analysis software. The solution resistance (Rs), polarization resistance or charge transfer resistance (Rct) and double layer capacitance (Cp) of the thermal treated alloys were evaluated. 3. RESULTS AND DISCUSSION 3.1 Impedance Measurements Table 1 shows the Electrochemical Impedance Spectroscopy (EIS) test results. Alloy Al-6Si- 0.5Mg Al-6Si- 0.5Mg- 2Cu Table 1: Impedance test results Rs (Ω) Rct (kω) Rct (kω) Cp (µf) OCP (V/SC E) The open circuit potential (OCP) with the exposure time of aged Al-6Si-0.5Mg (-2Cu) alloys in 0.1M NaCl solution is shown in Table1. Large fluctuations in open circuit potential for the alloys were observed during the time of 100s exposure. 2

12 After a period of exposure the OCP fluctuation decreased and reached steady state. The steady state OCP of Cu free alloy (Al-6Si-0.5Mg) is V and it is the higher negative OCP value between the alloys under investigation. The occurrence of a positive shift in OCP ( V) in the Al-6Si- 0.5Mg alloy containing 2wt% Cu indicates the existence of anodically controlled reaction. The OCP values mainly depend on the chemical compositions and thermal history of the alloys. The data obtained were modeled and the equivalent circuit that best fitted to the experimental data is shown in Fig. 1. Rs represent the ohmic solution resistance of the electrolyte. Rct and Cp are the charge transfer resistance and electrical double layer capacitance respectively, which correspond to the Faradaic process at the alloy/media interface. Fig. 2 shows the Nyquist diagram (suggested equivalent circuit model shown in Fig. 1) of the Al- 6Si-0.5Mg (-2Cu) alloys in 0.1M NaCl in deionized water. In Nyquist diagram, the imaginary component of the impedance (Z") against real part (Z') is obtained in the form of capacitive-resistive semicircle for each sample. Fig. 3 shows the experimental EIS results in Bode magnitude diagram for Al-6Si-0.5Mg (-2Cu) alloys. Bode plots show the total impedance behavior against applied frequency. At high frequencies, only the very mobile ions in solution are excited so that the solution resistance (Rs) can be assessed. At lower intermediate frequencies, capacitive charging of the solid-liquid interface occurs. The capacitive value Cp can provide very important information about oxide properties when passivation occurs or thicker oxides are formed on the surface. At low frequency, the capacitive charging disappears because the charge transfer of electrochemical reaction can occur and this measured value of the resistance corresponds directly to the corrosion rate. For this reason, this low frequency impedance value is referred to as polarization or charge transfer resistance (Rct). The solution resistance (Rs) of the alloys varies from 40-51Ω (Table 1) and these values are very similar to each other. So there are insignificant changes of Rs values for the alloys during EIS testing. The Rs values are negligible with respect to Rct and the electrolyte behaves as a good ionic conductor. Impedance measurements showed that in 0.1M NaCl solution, adding 2wt% Cu in the Al- 6Si-0.5Mg alloy increases the charge transfer resistance (Rct). For the Cu free Al-6Si-0.5Mg alloy, the charge transfer resistance (Rct) value in 0.1M NaCl solution is 15.57kΩ, and this is increased to 28.33kΩ with the addition of 2wt% Cu to the Al-6Si-0.5Mg alloy. The increase in the charge transfer resistance indicates an increase in the corrosion resistance of the alloy with Cu addition. The double layer capacitance (Cp) of the Cu free Al-6Si-0.5Mg alloy is 1.259µF, which exhibit the lower value between the alloys investigated. The double layer capacitance (2.012µF) of Al-6Si-0.5Mg alloy increased with an addition of 2wt% Cu. Fig.1: Electrical equivalent circuit used for fitting of the impedance data of Al-6Si-0.5Mg (-2Cu) alloys in 0.1M NaCl solution Fig. 2: Nyquist plots for the peakaged Al-6Si- 0.5Mg (-2Cu) alloys in simulated sea water Fig. 3: Bode plots for the peakaged Al-6Si-0.5Mg (-2Cu) alloys in simulated sea water 3

13 3.2 Potentiodynamic Polarization Measurements Table 2 shows the potentiodynamic polarization test results obtained from the electrochemical tests. Table 2: Potentiodynamic polarization test results Alloy Al-6Si- 0.5Mg Al-6Si- 0.5Mg-2Cu Icorr (µa) Ecorr( mv) Epit (mv) Corr. rate (mpy) Fig. 4: Potentiodynamic polarization curves of aged Al-6Si-0.5Mg (-2Cu) alloys in 0.1M NaCl solution Potentiodynamic polarization curves of Al-6Si- 0.5Mg (-2Cu) alloys in 0.1M NaCl solution are shown in Fig. 4. Anodic current density of Al-6Si- 0.5Mg alloy increased with Cu addition. The addition of Cu caused the formation of microgalvanic cells in α-aluminum matrix. The different intermetallic compounds (like Mg 2 Si, Al 2 Cu etc.) can lead to the formation of micro-galvanic cells because of the difference of corrosion potential between intermetallics and α-aluminum matrix. Park [13] has also reported that the addition of Cu increased the corrosion potential of a number of Al- Cu-Si alloys. For the Cu free Al-6Si-0.5Mg alloy corrosion potential is -764mV, which is the higher negative potential between the alloys investigated. With the addition of 2wt% Cu, the corrosion potential of the alloy shifted towards more positive values (-586mV). Pitting potential (Epit) of the Cu content alloy also shifted towards more positive region (from -480mV to -353mV). Potentiodynamic tests showed that in 0.1M NaCl solution, addition of Cu in the Al-6Si-0.5Mg alloy increases the corrosion current (Icorr). For the Cu free Al-6Si-0.5Mg alloy, the corrosion current (Icorr) in 0.1M NaCl solution is measured 6.3µA, and this increased to 20.30µA with the addition of 2wt% Cu to the Al-6Si-0.5Mg alloy and the corresponding corrosion rate increases for the alloy (Alloy-2 =17.05mpy). 3.3 Microstructural Investigation The microstructure of some selected as-corroded samples was observed under OLM and SEM. There was evidence of corrosion products of intermetallic compounds in all the samples examined. Besides, several pits were visible in all the samples examined. It is probable that the pits are formed by the intermetallics dropping out from the surface due to the dissolution of the surrounding matrix. However, it is also possible that the pits are caused by selective dissolution of the intermetallic/or particles of the second phase precipitates. Osorio et al. (Osório et. al., 2011) have demonstrated that in Al-Cu-Si alloys, a more finely and homogeneously distributed Al 2 Cu and needlelike Si particles in the ternary eutectic mixture, tend to improve the corrosion resistance mainly due to the galvanic protection of both Al 2 Cu and Si phases (Osório et. al., 2011). Although it has also been reported (Osório et. al., 2011, Osório et. al., 2007) that fine Si particles tends to decrease the corrosion resistance of binary Al-Si alloys when associated with the Al 2 Cu intermetallic phase, a better galvanic protection is provided for finer Al-Cu-Si alloy microstructures. It was also reported that the ternary eutectic mixture consisting of Al + Al 2 Cu + Si phases is nobler than the Al-matrix and Al-phase in the eutectic mixture (Osório et. al., 2011). Modified Al-Si eutectic α-al Pits Fig. 5: OLM image showing the damaged surface morphology of as-corroded T6 aged Al-6Si-0.5Mg in 0.1M NaCl solution 4

14 Pits and predominantly pitting corrosion as obtained by the OLM and SEM. Samples were characterized by OLM and SEM followed by potentiodynamic polarization tests. The peak-aged Cu free alloy (Al- 6Si-0.5Mg) exhibited pits on their surface (Figs. 5 and 6), which apparently had nucleated randomly. Conversely, the exposed surface of the alloys exhibited a corrosion product covering the surface after polarization. All the micrographs (Figs. 5-8) also showed that there was no corrosion in the fragmented and modified Al-Si eutectics. 4. CONCLUSIONS Fig. 6: SEM image showing the damaged surface morphology of as-corroded T6 aged Al-6Si-0.5Mg in 0.1M NaCl solution Modified Al-Si eutectic α-al Fig. 7: OLM image show the damage surface morphology of as-corroded T6 aged Al-6Si-0.5Mg- 2Cu in 0.1M NaCl solution Corrosion product Pits Fig. 8: SEM image showing the damaged surface morphology of as-corroded T6 aged Al-6Si-0.5Mg- 2Cu in 0.1M NaCl solution Consequently, the forms of corrosion in the studied Al-6Si-0.5Mg (-2Cu) alloys are slightly uniform The following conclusions may be drawn from the above investigation: 1. The EIS tests have shown that the additions of 2wt% Cu into Al-6Si-0.5Mg alloy tend to increase the excellent corrosion resistance of Al-6Si-0.5Mg alloy in simulated sea water. 2. The linear polarization and Tafel extrapolation plot showed that the corrosion current (Icorr) and corrosion rate (mpy) increased with the addition of 2wt%Cu into Al-6Si-0.5Mg alloy. 3. The open circuit potential (OCP), corrosion potential (Ecorr) and pitting corrosion potential (Epit) in the simulated sea water were shifted in the more noble direction due to 2wt% Cu additions into Al-6Si-0.5Mg alloy. 4. The forms of corrosion in the studied Al-6Si- 0.5Mg (-2Cu) alloys were pitting corrosion as obtained from the microstructures study with pits observations. REFERENCES 1. Abdulwahab, M. Madugul, I.A. Yaro, S.A. and Popoola, A.P.I.( 2011), Degradation Behavior of High Chromium Sodium-Modified A Type Al-Si-Mg Alloy in Simulated Seawater Environment, Journal of Minerals & Materials Characterization & Engineering, 10(6), pp Czechowski, M. (2007), Effect of anodic polarization on stress corrosion cracking of some aluminium alloy, Adv. Mater Sci, 7(1), pp Fontana, M. G. and Greene, N.D. (1987), Corrosion Engineering, McGraw-Hill book Company, New York, pp Larsen, M. H. and Walmsley, J. C. (2006), Significance of low copper content on grain boundary nanostructure and intergranular corrosion of AlMgSi (Cu) model alloys, Mater. Sci. Forum, , pp Larsen, M. H., Walmsley, J. C., Lunder, O. and Nisancioglu, K.( 2010), Effect of Excess 5

15 Silicon and Small Copper Content on Intergranular Corrosion of 6000-Series Aluminum Alloys, J. Electrochem. Soc., 157, pp Osório, W.R., Cheung, N., Spinelli, J.E. and Garcia. A. (2007), The effects of a eutectic modifier on microstructure and surface corrosion behavior of Al Si hypoeutectic alloys, J. Solid State Electrochem, 11, pp Osório, W. R., Moutinho, D. J., Peixoto, L. C., Ferreira, I.L. and Garcia. A. (2011), Macro segregation and microstructure dendritic array affecting the electrochemical behaviour of ternary Al-Cu-Si alloys, Electrochimica Acta, 56, pp Osório, W. R., Peixoto, L. C., Moutinho, D. J., Gomes, L. G., Ferreira, I.L. and Garcia. A. (2011), Corrosion Resistance of Directionally Solidified Al-6Cu-1Si and Al-8Cu-3Si Alloys Castings, Materials and Design, 32(7), pp Scamans, G.M., Hunter, J.A., Holroyd, N.J.H. (1989), Corrosion of aluminium a new approach. Proc. of 8th Inter. Light metals Congress, pp , Leoban Wien. 10. Svenningsen, G., Larsen, M.H., Nordlien, J.H. and Nisancioglu, K. (2006), Effect of high temperature heat treatment on intergranular corrosion of Al-Mg-Si(Cu) model alloy, Corros. Sci., 48, pp Svenningsen, G. and Larsen, M.H. (2006), Effect of artificial aging on intergranular corrosion of extruded Al-Mg-Si alloy with small Cu content, Corros. Sci., 48, pp Svenningsen, G. and Larsen, M.H. (2006), Effect of thermomechanical history on intergranular corrosion of extruded AlMgSi(Cu) model alloy, Corros. Sci., 48, pp Svenningsen, G., Lein, J.E., Bjorgum, A., Nordlien, J.H. and Nisancioglu, K. (2006), Effect of low copper content and heat treatment on intergranular corrosion of model AlMgSi alloys, Corros. Sci., 48, pp Zhan, H. Mo, J. M. C. Hannour, F., Zhuang, L., Terryn, H. and de Wit, J. H. W. (2008), The influence of copper content on intergranular corrosion of model AlMgSi(Cu) alloys, Materials and Corrosion, 59, pp Zor, S., Zeren, M., Ozkazance, H., and Karakulak, E. (2010), Effect of Cu content on the corrosion of Al-Si eutectic alloys in acidic solution, Anti-Corrosion Methods and Materials,57(4),pp

16 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh ELECTROCHEMICAL INVESTIGATION OF CORROSION BEHAVIOR OF Al-6Si-0.5Mg (-2Ni) ALLOYS IN 0.1M NaCl SOLUTION (SIMULATED SEA WATER) A. Hossain 1*, R. Qadir 2, F. Gulshan 1, ASW Kurny 1 1 Department of Materials and Metallurgical Engineering, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh 2 Engineer, Pilot Plant and Process Development Centre (PP & PDC), BCSIR Laboratories, Dhaka, Bangladesh The heat-treated Al-6Si-0.5Mg (-2Ni) alloy s electrochemical corrosion characteristics have been studied in simulated seawater. The thermal treatment (T6) consists of solution treatment, quenching and ageing. The corrosion behavior of thermal treated Al-6Si-0.5Mg (-2Ni) alloys in 0.1M NaCl solution was investigated by electrochemical potentiodynamic polarization technique consisting of linear polarization method using the fit of Tafel plot and electrochemical impedance spectroscopy (EIS) techniques. Generally, from the linear polarization, the corrosion rate decreases in terms of thermally treated Al-6Si-0.5Mg-2Ni alloy. The corrosion behavior of the Al-6Si-0.5Mg-2Ni alloy in the simulated sea water (0.1M NaCl solution) showed better resistance than the Al-6Si-0.5Mg alloy. The EIS test results also showed that the change in charge transfer resistance (Rct) is insignificant with the addition of 2wt% Ni to Al-6Si-0.5Mg alloy. The magnitude of the noble shift in the open circuit potential (OCP), corrosion potential (Ecorr) and pitting corrosion potential (Epit) increased with the addition of 2wt% Ni to Al-6Si-0.5Mg alloy. Consequently, the forms of corrosion in the studied alloys are slightly uniform and predominantly pitting corrosion as obtained from the scanning electron microscopy (SEM) study. ` 1. INTRODUCTION Aluminium and its alloys are considered to be highly corrosion resistant under the majority of service conditions (Fontana and Greene, 1987). The various grades of pure aluminum are the most resistant, followed closely by the Al-Mg and Al-Mn alloys. Next in order after them are Al-Mg-Si and Al-Si alloys. The alloys containing copper are the least resistant to corrosion (Zor et. al., 2010); but this can be improved by coating each side of the copper containing alloy with a thin layer of highlypure aluminium, and gaining a three ply metal (Alclad). This cladding acts as a mechanical shield and offers sacrificial protection (Scamans et. al., 1989).When aluminum surfaces are exposed to atmosphere, a thin invisible oxide (Al 2 O 3 ) skin forms, which protects the metal from further corrosion in many environments (Fontana and Greene, 1987). This film protects the metal from further oxidation unless this coating is destroyed, and the material remains fully protected against corrosion (Scamans et. al., 1989). The composition of an alloy and its thermal treatment are important to determine the susceptibility of the alloy to corrosion (Czechowski, 2007, Abdulwahab et. al., 2011). In Ni-containing alloys the eutectic phase E consists of more or less soft eutectic Al (αe) and hard eutectic Si and Al 3 Ni (Asghar et. al., 2010). When Ni is added to the Al-Si system, the eutectic transformation is characterized by a simultaneous formation of eutectic Si and Al 3 Ni and consequently, eutectic Si and Al 3 Ni form a geometrically entangled system. During the course of a solution treatment eutectic Al 3 Ni does not significantly change its shape, as can be metallographically observed. Furthermore, in the presence of Ni-aluminides the loss of interconnectivity of eutectic Si is significantly reduced (Stadlerl et. al., 2011, Stadlerl et. al., 2012). In solution, treated Al-Si-Mg alloys containing up to 2% Ni,the positive effect of Ni is much more * Corresponding Author: A. Hossain ah_buetmmesgfl@live.com

17 prominent, especially with respect to the yield strength. While Ni-containing alloys the contiguity of the eutectic Si and Al 3 Ni is more or less preserved due to the presence of Ni-aluminides, the spheroidization of the eutectic Si in the Ni-free alloy (AlSi 12 Mg) results in its reduced contiguity and thus reduced strength (Stadlerl et. al., 2011, Stadlerl et. al., 2012). In this study electrochemical measurements were recorded to characterize the electrochemical behavior of the Al-6Si-0.5Mg (-2Ni) alloys. The corroded surfaces of alloys were examined after exposure using both optical light microscope (OLM) and scanning electron microscope (SEM) to understand better the corrosion mechanisms. 2. EXPERIMENTAL 2.1 Materials Preparation The Al-6Si-0.5Mg (-2Ni) alloys were prepared by melting Al-7Si-0.3Mg (A356) alloy and adding Al and Ni into the melts. The melting operation was carried out in a gas-fired clay-graphite crucible furnace and the alloys were cast in a permanent steel mould. After solidification the alloys were homogenized ( at 500 o C for 24hr), solution treated (540 o C for 2hr) and finally artificially aged (at 225 o C for 1hr). Afterwards heat treatment rectangular samples (50mm 2 or 10mm x 5mm) were prepared for metallographic observation and subsequent electrochemical test. De-ionized water and analytical reagent grade sodium chloride (NaCl) were used for the preparation of 0.1M solution. All measurements were carried out at room temperature. 2.2 Potentiodynamic Polarization Measurements A computer-controlled Gamry Framework TM Series G 300 and Series G 750 Potentiostat/ Galvanostat/ZRA were used for the electrochemical measurements. The Potentiodynamic polarization studies were configured in cells, using three-electrode assembly: a saturated calomel reference electrode, a platinum counter electrode and the sample in the form of coupons of exposed area of 50 mm 2 (10mm x 5mm) as working electrode. Only one 10mm x 5mm surface was exposed to the test solution while the other surfaces were covered with Teflon tape. The system was allowed to establish a steady-state open circuit potential (OCP). The potential range selected was -1 to +1V and measurements were made at a scan rate of 0.50mV/s. The corrosion current (Icorr), corrosion potential (Ecorr), pitting corrosion potential (Epit) and corrosion rate (mpy) were calculated from Tafel curve. The tests were carried out at room temperature in solutions containing 0.1M of NaCl at a fixed and neutral ph value. The corroded samples were cleaned in distilled water and examined under optical light microscope (OLM) and scanning electron microscope (SEM). 2.3 Electrochemical Impedance Measurements During the potentiodynamic polarization test, three electrode cell arrangements were also used for electrochemical impedance measurements. Rectangular samples (10mm x 5mm) were connected with copper wire and were adopted as working electrode. EIS tests were performed in 0.1M NaCl solution at room temperature over a frequency range of 100 khz to 0.2Hz using a 5mV amplitude sinusoidal voltage. The 10mm x 5mm sample surface was immersed in 0.1M NaCl solution (corrosion medium). All the measurements were performed at the open circuit potential (OCP). The test cells were maintained at room temperature and the NaCl solution was refreshed regularly during the whole test period. The impedance spectra were collected, fitting the experimental results to an equivalent circuit (EC) with the use of Echem Analyst TM data analysis software. The solution resistance (Rs), polarization resistance or charge transfer resistance (Rct) and double layer capacitance (Cp) of the thermal treated alloys were evaluted. 3. RESULTS AND DISCUSSION 3.1 Impedance Measurements Table 1 shows the Electrochemical Impedance Spectroscopy (EIS) test results. Alloy Al-6Si- 0.5Mg Al-6Si- 0.5Mg- 2Ni Table 1: EIS test results Rs (Ω) Rct (kω) Cp (µf) OCP (V/SCE) The open circuit potential (OCP) with the exposure time of aged Al-6Si-0.5Mg (-2Ni) alloys in 0.1M NaCl solution is shown in Table 1. Large fluctuations in open circuit potential for the alloys 8

18 were seen during the time of 100s exposure. After a period of exposure the OCP fluctuation decreased and reached steady state. The steady state OCP of Ni free alloy (Al-6Si-0.5Mg) is V and it is the higher negative OCP value between the alloys under investigation. The occurrence of a positive shift in OCP ( V) in the Al-6Si-0.5Mg alloy containing 2wt% Ni indicates the existence of anodically controlled reaction. The OCP values mainly depend on the chemical compositions and thermal history of the alloys. The data obtained were modeled and the equivalent circuit that best fitted to the experimental data is shown in Fig.1. Rs represent the ohmic solution resistance of the electrolyte. Rct and Cp are the charge transfer resistance and electrical double layer capacitance respectively, which correspond to the Faradaic process at the alloy/media interface. Fig. 2 shows the Nyquist diagrams (suggested equivalent circuit model shown in Fig. 1) of the Al- 6Si-0.5Mg (-2Ni) alloys in 0.1M NaCl in deionized water. In Nyquist diagrams, the imaginary component of the impedance (Z") against real part (Z') is obtained in the form of capacitive-resistive semicircle for each sample. Fig. 3 shows the experimental EIS results in Bode magnitude diagram for Al-6Si-0.5Mg (-2Ni) alloys. Bode plots show the total impedance behavior against applied frequency. At high frequencies, only the very mobile ions in solution are excited so that the solution resistance (Rs) can be assessed. At lower intermediate frequencies, capacitive charging of the solid-liquid interface occurs. The capacitive value Cp can provide very important information about oxide properties when passivation occurs or thicker oxides are formed on the surface. At low frequency, the capacitive charging disappears because the charge transfer of electrochemical reaction can occur and this measured value of the resistance corresponds directly to the corrosion rate. For this reason, this low frequency impedance value is referred to as polarization or charge transfer resistance (Rct). The solution resistances (Rs) of the alloys (Table. 1) are very similar to each other. So there are insignificant changes of Rs values for the alloys during EIS testing. The Rs values are negligible with respect to Rct and the electrolyte behaves as a good ionic conductor. Impedance measurements showed that in 0.1M NaCl solution, adding 2wt% Ni in the Al-6Si-0.5Mg alloy decreases the charge transfer resistance (Rct). For the Ni free Al-6Si- 0.5Mg alloy, the charge transfer resistance (Rct) value in 0.1M NaCl solution is 15.57kΩ, and this is decreased to 14.44kΩ with the addition of 2wt% Ni to the Al-6Si-0.5Mg alloy. The decrease in the charge transfer resistance indicates a decrease in the corrosion resistance of the alloy with Ni addition. The double layer capacitance (Cp) of the Ni free Al-6Si-0.5Mg alloy is 1.259µF, which exhibit the lower value between the alloys investigated. The double layer capacitance (1.645µF) of Al-6Si- 0.5Mg alloy increased with an addition of 2wt% Ni. Fig.1: Electrical equivalent circuit used for fitting of the impedance data of Al-6Si-0.5Mg (-2Ni) alloys in 0.1M NaCl solution Fig. 2: Nyquist plots for the peakaged Al-6Si- 0.5Mg (-2Ni) alloys in simulated sea water Fig. 3: Bode plots for the peakaged Al-6Si-0.5Mg (-2Ni) alloys in simulated sea water 9

19 3.2 Potentiodynamic Polarization Measurements Table 2 shows the potentiodynamic polarization test results obtained from the electrochemical tests. Potentiodynamic polarization curves of Al-6Si- 0.5Mg (-2Ni) alloys in 0.1M NaCl solution are shown in Fig. 4. Table 2: Potentiodynamic polarization test results Alloy Al-6Si- 0.5Mg Al-6Si- 0.5Mg-2Ni Icorr (µa) Ecorr (mv) Epit (mv) Corr. rate (mpy) Anodic current density of Al-6Si-0.5Mg alloy increased with Ni addition. The addition of Ni caused the formation of micro-galvanic cells in α- Al matrix. The different intermetallic compounds (like Mg 2 Si, Al 3 Ni etc.) can lead to the formation of micro-galvanic cells because of the difference of corrosion potential between intermetallics and α- aluminum matrix. With the addition of 2wt% Ni, the corrosion potential of the alloy shifted towards more positive value (-720mV). Pitting potential (Epit) of the Ni content alloys also shifted towards more positive values (from -480mV to -426mV). Potentiodynamic tests showed that in 0.1M NaCl solution, addition of Ni in the Al-6Si-0.5Mg alloy decreases the corrosion current (Icorr). For the Ni free Al-6Si-0.5Mg alloy, the corrosion current (Icorr is measured in 0.1M NaCl solution is 6.3µA, and this decreased to 2.54µA with the addition of 2wt% Ni to the Al-6Si-0.5Mg alloy and the corresponding corrosion rate decreases for the alloy (Alloy-2 =2.132mpy). 3.3 Microstructural Investigation The microstructures of some selected as-corroded samples were observed under OLM and SEM. There was evidence of corrosion products of intermetallic compounds in all the samples examined. Besides, several pits were visible in the Ni free sample examined. It is probable that the pits are formed by the intermetallics dropping out from the surface due to the dissolution of the surrounding matrix. However, it is also possible that the pits are caused by selective dissolution of the intermetallic/or particles of the second phase precipitates. Modified Al-Si eutectic α-al Fig. 5: OLM image show the damage surface morphology of as-corroded T6 aged Al-6Si-0.5Mg in 0.1M NaCl solution Pits Pits Fig. 6: SEM image show the damage surface morphology of as-corroded T6 aged Al-6Si-0.5Mg in 0.1M NaCl solution Fig. 4: Potentiodynamic polarization curves of aged Al-6Si-0.5Mg (-2Ni) alloys in 0.1M NaCl solution 10

20 Modified Al-Si eutectic α-al Fig. 7: OLM image show the damage surface morphology of as-corroded T6 aged Al-6Si-0.5Mg- 2Ni in 0.1M NaCl solution Fig. 8: SEM image show the damage surface morphology of as-corroded T6 aged Al-6Si-0.5Mg- 2Ni in 0.1M NaCl solution Consequently, the forms of corrosion in the studied Al-6Si-0.5Mg-2Ni alloys are slightly uniform and predominantly no severe pitting corrosion obtained by the OLM and SEM. Samples were characterized by OLM and SEM followed by potentiodynamic polarization tests. The heat treated Ni free alloy (Al-6Si-0.5Mg) exhibited pits on their surface (Fig.5 and Fig.6), which apparently had nucleated randomly. Conversely, the exposed surface of the alloys exhibited a corrosion product covering the surface after polarization. All the micrographs (Figs. 5-8) also showed that there was no corrosion in the fragmented and modified Al-Si eutectics and Ni containing eutectics (Al 3 Ni). 4. CONCLUSIONS The following conclusions may be drawn from the above investigation: 1. The EIS tests have shown that the additions of 2wt% Ni into Al-6Si-0.5Mg alloy tend to slightly decrease the corrosion resistance of Al- 6Si-0.5Mg alloy in simulated sea water. 2. The linear polarization and Tafel extrapolation plot show that the corrosion current (Icorr) and corrosion rate (mpy) decrease with the addition of 2wt% Ni into Al-6Si-0.5Mg alloy. 3. The open circuit potential (OCP), corrosion potential (Ecorr) and pitting corrosion potential (Epit) in the simulated sea water were shifted in the more noble direction due to 2wt% Ni additions into Al-6Si-0.5Mg alloy. REFERENCES 1. Abdulwahab, M. Madugul, I.A. Yaro, S.A. and Popoola, A.P.I.( 2011), Degradation Behavior of High Chromium Sodium-Modified A Type Al-Si-Mg Alloy in Simulated Seawater Environment, Journal of Minerals & Materials Characterization & Engineering, 10(6), pp Asghar, Z., Requena, G. and Kubel, F. (2010), The role of Ni and Fe aluminides on the elevated temperature strength of an AlSi12 alloy, Mater. Sci. and Eng. A, 527, pp Czechowski, M. (2007), Effect of anodic polarization on stress corrosion cracking of some aluminium alloy, Adv. Mater Sci, 7(1), pp Fontana, M. G. and Greene, N.D. (1987), Corrosion Engineering, McGraw-Hill book Company, New York, pp Scamans, G.M., Hunter, J.A., Holroyd, N.J.H. (1989), Corrosion of aluminium a new approach. Proc. of 8th Inter. Light metals Congress, pp , Leoban Wien. 6. Stadlerl, F., Antrekowitsch, H., Fragner, W., Kaufmann, H. and Uggowitzer, P. J. (2011), The effect of Ni on the high-temperature strength of Al-Si cast alloys, Mater. Sci. Forum, 690, pp Stadlerl, F., Antrekowitsch, H., Fragner, W., Kaufmann, H. and Uggowitzer, P. J. (2012), Effect of main alloying elements on the strength of Al-Si cast alloys at elevated temperatures, International Journal of Cast Metals Research, 25(4), pp Zor, S., Zeren, M., Ozkazance, H., and Karakulak, E. (2010), Effect of Cu content on the corrosion of Al-Si eutectic alloys in acidic solution, Anti-Corrosion Methods and Materials, 57(4), pp

21 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh APPLICATION OF MULTI CRITERIA DECISION MAKING (MCDM) METHODS FOR SELECTION OF GREEN FUEL FOR CLEAN CLIMATE BASED ON EXPERIMENTAL DATA: A HOLISTIC APPROACH Swarup Paul 1, Bijan Sarkar 2, P.K.Bose 3 1 Research Scholar, School of Automotive Engineering, Jadavpur University,Kolkata, India. 2 Professor and Former Head, Production Engineering Department, Jadavpur University, Kolkata. India. 3 Professor and Former Director, NIT Agartala. Tripura. India. Energy which presents itself in its various forms and facet, is widely utilized by mankind in every aspect of life.. We, the civilized society of the 21st century, cannot afford to pass a single moment without using energy in some form or other. The usage of energy is expanding exponentially everywhere due to rapid industrialization and motorization which are indices of advancement of our society. But at the same time we cannot ignore the fact that our resources have been dwindling at a rapid stride owing to random and indiscriminate use of energy.. Most of the applications of energy is based on conventional energy which is produced by burning of fossil fuel. The major concerns related to energy are: gradual delpetion of fossil fuel which has finite store in our earth crust and harmful combustion effects on our environment. Keeping in line with the above mentioned scenario, the present work is aimed at: making society free from pollution by choosing the most appropriate green fuel. The experiment has been performed with five Tree Borne Oils (TBOs): Neem (Azadirachtaindica), Karanja (Pongamia Pinnata), Mahua (Madhuca indica), Castor (Ricinus communis) and Jatropha (Jatropha curcus). In order to reduce viscosity, each of the TBOs is blended with mineral diesel at a ratio of 20:80 by volume. Various physical, chemical and thermal properties of the blended fuels along with mineral diesel have been measured by standard apparatus. A four stroke, single cylinder, water cooled compression ignition engine was run with all the blended fuels as well as by diesel separately. Results of respective performances and emissions have been recorded and analyzed. To select the most appropriate fuel blend out of the five blends multi criteria decision making tools TOPSIS and VIKOR have been applied. Important six criteria have been chosen by Pareto analysis. Criteria weightage have been assigned by applying Delphi method. It is seen from the results that fuel- Neem is the most appropriate one. Thereby, it can be concluded that nonedible oil-neem can be used with mineral diesel to keep our environment clean and MCDM method can successfully be applied in order to choose the right alternative. 1. PRIOR ARTS 1.1 On the use of Biofuels Use of biofuels in engines is not a new concept. In fact, Rudolf Diesel, the inventor of diesel engine, used biofuel (Vegetable oil) in the first engine invented by him in But gradually people around the world were dependent entirely on fossil fuels. The significance of using biofuels was also realized during the world war II and also during oil crisis in the 1970s. But a serious attempt was initiated during the last decade on the use of biofuel. Global scenario of biofuel use was reviewed by many researchers (Radha et. al., 2008, Ramadhas et. al., 2004, Kumar and Sharma, 2008). Experimental studies on vegetable oils as diesel engine fuels are gradually gaining attention now-a-days. Researchers are giving their utmost efforts to find vegetable oils. Their experimental studies involve various vegetable oils (Savariraj et. al., 2012, Kapilan et. al., 2009). Some nonedible vegetable oils and production methods of biodiesel from these non edible oils are discussed by some researchers (Murugesan et. al., 2009, Awolu et. al., 2013). Among various non edible oils Karanja is reported to be the promising alternative one according to many researchers (Mishra and Murthy, 2011, Dwivedi and Sharma, 2013). Another promising nonedible oil is Mahua which has been experimentally investigated by many researchers (Puhan et. al., 2007, Lenin et. al., 2013). They * Corresponding Author: P.K Bose, pkb32@yahoo.com

22 operated engine with biodiesel produced from these oils and diesel blend of different concentrations. They analyzed engine performance, emissions and combustion in detail. Neem has occupied a significant position in the field of alternative fuel research (Aransiola et. al., 2012, Ragit et. al., 2010). Literatures are there covering a huge number of work highlighting Neem The researches include, biodiesel production from neem feed stock (Elango and Senthilkumar, 2010), their performance, combustion and emission results and their comparative analysis with those of diesel (Yadav and Shrivastava, 2012, Senthilkumar et. al., 2012). All the scientific findings motivate the use of Neem biodiesel though exact percentage of it with mineral diesel differs as per conclusions arrived at by different researchers (Nithyananda et. al., 2013). Besides analyzing the performance, combustion, emissions of different fuels, studies have also been performed on optimum injection pressure and timing, nozzle geometry, proper atomization of the fuels etc. by a few researchers (Khandelwal et. al., 2013). It is also found in literature that some of the experimental investigations have been conducted with the combination of different fuels blends (Anbumani and Singh, 2010). As a matter of fact, different researchers chose different oils, primarily nonedible oils, for their experiments. But none of them is reported specifically on the selection of a particular fuel when they worked with different fuels or a suitable blend among different blends they used. Even though it creates a paradoxical scenario when results of different aspects are discussed, but a final opinion is essential towards making a policy or use of biofuel in future 1.2 On the use of MCDM methods Decision making is important in all spheres of life. It is more important in real life engineering problems where a right choice is essential. A wrong selection encompasses catastrophic failure and huge economic loss. Multi Criteria Decision Making methods are very powerful and effective to select the best option. As per discussions in various literatures it is found that researchers and engineers used MCDM methods in various engineering and real life problems. Jingzhu Wei and Xiangyi Lin (Jingzhuwei and Lin, 2008) described working steps of VIKOR method in detail. VIKOR method can determine a compromise solution, by using utility weight and compared with TOPSIS and SAW, the most important difference is the usage of the utility weight and the value of the utility weight can be adjusted according to the attitude of decision makers. They highlighted the advantage of VIKOR method by an empirical case as well. Gwo-HshiungTzeng et al (Tzeng et. al., 2005) applied multicriteria analysis to select the most suitable substitute bus for Taiwan urban areas. They considered several types of fuels as alternative fuel modes. They applied and compared TOPSIS and VIKOR methods to determine the best compromised alternative fuel mode. AHP is used to determine the relative weights of evaluation criteria. Lee-Ing Tong et al (Tong et. al., 2007) studied optimization of multi response processes using the VIKOR method. They mentioned that the application of most of the Taguchi method optimized only a single response. When more than one response is to be optimized, engineers usually set the optimal factor level from their experience. Jih-Jeng Huang et al (Huang et. al., 2009) proposed a revised VIKOR model for multiple criteria decision making. They discussed their proposed method by citing two examples. Some researchers (Zandi and Roghanian, 2013, Opricovic and Tzeng, 2007) illustrated application of the VIKOR method through numerical examples. In 2012, Yusuf Tansellc applied integrated TOPSIS and DOE method to solve different computer integrated real manufacturing selection problems (TanselIc, 2012) Extensive literature reviews show the wide applicability of MCDM methods in diverse fields of engineering problems. At the same time it is well-nigh impossible to find the application of MCDM methods for biofuel selection in any literature. However, significant research works on biofuels are going on now-a-days throughout the world. The present paper attempts to minimize the gap between selection of the most appropriate biofuel-diesel blend using MCDM method and use of biofuel for a better socioeconomic structure as well as clean environment. TOPSIS and VIKOR, effective MCDM techniques, are used here for ranking different biofuel-diesel blends together with diesel. These are applied on real life experimental data. So, the present work has added a new dimension towards an approach for making decision on the blending ratio of biofuel and diesel in the field of alternative fuel research as well. 2. MATERIALS AND METHODS 2.1 Experimental fuel Preparation Five types of nonedible Tree Borne Oils were taken into consideration for this study. Each experimental fuel has been characteristically explained in the Table 1 below, where nomenclature of the fuels like K20 means 20% of Karanja TBO is mixed with 80% of mineral diesel by volume and so on. It can be mentioned that these five fuel blends are taken into consideration as five alternatives at the time of formulating decision matrix for the application of MCDM methods. 13

23 Sl. NO Table 1: Different Experimental Fuels Experimental fuels 1 Karanja (Pongamia Pinnata) 2 Neem(Azadirachtai ndica) 3 Jatropha (Jatropha curcus) 4 Mahua (Madhuca indica) 5 Castor (Ricinus communis) Different blends prepared Altern atives K20 A 1 N20 A 2 J20 A 3 M20 A 4 C20 A Properties of the Experimental fuels Various physical, chemical and thermal properties of the experimental fuels are measured by standard apparatus and presented in Table 2 below. Table 2: Properties of the fuels experimented N20 M20 K20 C20 J20 Density Viscosity Flash Fire Aniline Cloud Pour Calorific (gm/c.c) (cst at point point point point point value 40 o C) ( o C) ( o C) ( o C) ( o C) ( o C) (KJ/Kg) x x x x x EXPERIMENTAL PROCEDURE The engine used for the experiment was direct injection (DI), single cylinder, four stroke and water cooled diesel engine. It was connected to eddy current type dynamometer for loading and was assembled with necessary measuring devices for combustion pressure and crank angle measurements. The filtered TBOs were blended with commercial diesel oil in required proportion to reduce its viscosity. Before carrying out actual experiment, the engine was allowed to run for about minutes. Upon starting, the engine was operated with pure diesel alone and then run by the vegetable oilsblends. All the experiments were conducted at a compression ratio of 17.5 (rated CR) with diesel and vegetable oil. After reaching the stable operating condition, experimental data regarding fuel and air consumption at various temperature, voltages were recorded after generating in the host computer for every loading point. During the experiment of the engine, its load varied as 0%, 20%, 40%, 60% and 80% However, the data of 60% load condition are taken into account for this study. The experimental engine specification is shown in Table 3 and lay out of the test set up is shown in Fig. 1. Table 3: Engine specifications Make Kirloskar Number of Single cylinders Cooling medium Water cooled Type of stroke Four stroke Compression ratio 17.5 Rated power 7.5 kw Dynamometer Type Eddy Current with loading unit Bore and Stroke 80 mm and 110 mm Method of Hand start with starting cranking Alignment Vertical Speed 1500 rpm Fuel injection 23 0 before TDC 14

24 to take the most effective sub parameter(s) involving all dependent parameters on overall performance of the engine. This strategy is adopted with experts opinion in this problem and consequently, six criteria are selected. The various criteria selected for this present studies are shown in the following Table 4. A close look into the selected criteria manifests that all of these are non-beneficial in nature which means that lower the value, the better the environmental effect and engine performance. Since the present problem is related to the environment, all the important criteria taken into consideration in this research work explicitly show that lower values are preferable. Table 4: Various selected Criteria Fig. 1: Schematic layout of test setup 3.1 Methodologies Applied In the present computational work two MCDM methods are applied. The first one is TOPSIS and the second one is VIKOR. Analytic Hierarchy Process (AHP) is used in order to find the weightage of each criterion where as TOPSIS and VIKOR are used for ranking the alternatives. While calculating weightage of each criterion by applying AHP method, relative importance of each criterion in the pair wise comparison matrix is chosen based on extensive literature review followed by validation of different experts. The space constraint compels one to incorporate the working steps of AHP, TOPSIS and VIKOR methods. Although, these can be accessed through MCDM literatures. 4. SELECTION OF CRITERIA In the research area of alternative fuels in IC engine there are a lot of criteria on which an engine s overall efficiency depends. Some criteria are more important while some are Mathematically, overall performance of the engine (η overall ) can be written as η overall = f( FP, EP, EE,EC) where, FP= fuel properties; EP= engine performance; EE= engine emissions; EC= engine combustion. There are numerous fuel properties, engine performance, emissions and combustion parameters. Though experiment has been conducted to measure all the above mentioned parameters, it is quite a difficult task to consider all the criteria at a time while developing a model in the computational portion. With a view to selecting the best alternative, most rational way to choose the criteria would be Name of the criterion C 1: Viscosity (cst ) C 2: Brake sp fuel consumption(kg/kwh) C 3: Exhaust Gas Temperature ( 0 C) C 4: Unburnt Hydrocarbon (PPM. Vol.) C 5 : Carbon monoxide(% Vol.) C 6 : Nitrogen Oxides (% Vol.) Nature of the criterion Non beneficial (-) Non beneficial (-) Non beneficial (-) Non beneficial (-) Non beneficial (-) Non beneficial (-) 4. RESULTS AND DISCUSSIONS The variations of selected parameters viz. viscosity, BSFC, exhaust gas temperatures, unburnt hydrocarbons, carbon -di-oxide and oxides of nitrogen of five alternatives with varying loads are presented through figs. 2 to 7. It is observed that the viscosity of alternative A 5 is maximum and A 4 is minimum. Viscosity of A 2 is slightly higher than A 4. BSFC is the highest for A 5 and it is exceptionally higher than other alternatives. Alternative A 2 shows the minimum BSFC. Exhaust gas temperatures of the alternatives A 3 and A 1 exhibit the highest and lowest values respectively. For other three alternatives Exhaust gas temperatures differ significantly. Unburnt hydro carbon emissions are the highest for alternative A 2 and the lowest for alternative A 4. Other three alternatives show significant variation. In case of both CO 2 and NOx emissions, alternative A 1 shows the maximum and A 4 shows the minimum. For CO 2 emissions other three alternatives differ significantly whereas for NOx emissions vary marginally. Now considering the present scenario it is not an easy task to comment on the best choice among the five alternatives. Experimental results of five alternatives w.r.t six criteria make a 15

25 Unburnt Hydrocarbon Exhaust Gas Temp. BSFC Nox Viscosity CO2 confusing situation to opt for the best. To decide the best choice, it would be relevant to judge if the performance is better or worse while blending a TBO with mineral diesel. This type of decision is essential for using a particular biofuel in the midst of different kinds of existing biofuels produced after decade long experiments. Keeping in view this significant scenario the decision making part is adopted in the present study just to highlight the process of selecting the best choice A1 A2 A3 A4 A5 Alternatives Fig. 2: Viscosities of different experimental fuels A1 A2 A3 A4 A5 Alternatives Fig. 3: BSFCs of different experimental fuels A1 A2 A3 A4 A5 Alternatives Fig. 4 : Exhaust Gas Temp of different fuels A1 A2 A3 A4 A5 Alternatives Fig. 5: Unburnt hydrocarbons of different fuels Fig. 6: CO 2 of different experimental fuels A1 A2 A3 A4 A5 Alternatives 0 A1 A2 A3 A4 A5 Alternatives Fig. 7: NOx emissions of different fuels Now with the experimental data of various parameters against five alternatives the decision matrix has been formulated. The weights of relative importance of the criteria are assigned using Analytic Hietrarchy Process (AHP) method as explained earlier. The following matrix has been prepared as a part of decision making. Table-5: Pair wise comparison matrix 1 1 ½ 1/3 1/5 ¼ 1 1 ½ ½ ¼ 1/ /3 1/5 ½ /3 ¼ Viscosity is equally important as brake specific fuel consumption. So, the value of viscosity w.r.t BSFC is assigned to 1 and on the other hand the value of BSFC w.r.t viscosity is obviously 1. Unburnt hydrocarbon is moderately important than viscosity and as a result of this viscosity is assigned to the value of 1/3. Similarly, the relative importance of other criteria can be explained. Here it should be mentioned that these values are to be assigned in a judicious manner after taking experts opinion. The weights of each criterion are calculated following the standard procedure and they are: [C 1 ] w =0.059; [C 2 ] w =0.061;[C 3 ] w =0.093;[C 4 ] w =0.140;[C 5 ] w = ; [C 6 ] w = The value of λ max = and 16

26 CR= (<10%). Good consistencies among the assigned values in the pair wise comparison matrix was observed After calculating the weights of criteria applying AHP method, the next step is to apply TOPSIS and VIKOR methods. The resulting relative closeness ( C i ) in case of TOPSIS and VIKOR values(q i ) are shown in the following Table 5 and Table 6 respectively. Based on the values, it is observed that the blend designated as A 1 is the best choice among the other fuel blends under the given conditions. The ranking of biofuel blends obtained are A 1 - A 2- A 5- A 3 - A 4 and A 1 - A 2- A 5- A 4 - A 3 as per TOPSIS and VIKOR methods respectively. Here K20 fuel performance is the best under the given conditions. 5. CONCLUSIONS The present studies comprise both experimental and computational techniques. The novelty exists in both the matters. Applications of TBOs in lieu of biodiesel are, of course, unique. Application of MCDM methods on real experimental data with a view to choosing the best one has added a new dimension to both alternative fuels and MCDM application areas meaningfully. Based on experimental and computational techniques performed in the present studies the following conclusions can be drawn. Lower concentration of TBOs with diesel can be applied in CI engines instead of biodiesel production and subsequent use with a view to minimizing cost and complexity of biodiesel production from TBOs. Application of both MCDM methods viz. TOPSIS and VIKOR show alternative A 1 is the best choice whereas alternative A 4 is the worst. Though five nonedible TBOs have been taken into consideration in this study, other nonedible TBOs may also be considered for experimentation. In this present study, six parameters have been selected emphasizing the criteria effecting overall performance. But any number of criteria may be taken into consideration. In that case ranking of alternatives may change. But the results obtained for the present study are based on the selected six criteria. Other MCDM methods can be applied to verify the results obtained. Therefore, the present studies are not only useful for using TBOs in CI engines but also for selecting a TBO or its blend with diesel in a holistic manner Table-6: Ranking of alternatives PROMETHEE VIKOR Alternatives Relative Ranking VIKOR value ( Q i ) Ranking closeness (C i ) A 1 I I A 2 II II A 3 IV V A 4 V IV A 5 III III REFERENCES 1. Radha,K.K.., Sarada,S.N., and, Rajagopal, K.., (2008) Alternative Fuels For a Single Cylinder Direct Injection Diesel Engine, IEEE-First International Conference on Emerging Trends in engineering and Technology, pp Ramadhas,A.S.,Jayaraj,S.,and Muraleedharan, C., (2004) Use of vegetable oil as IC engine fuels- A review Renewable Energy 29, pp Kumar,Ashwani., Sharma, Satyawati., (2011), Potential non-edible oil resources as biodiesel feedstock: An Indian Perspective, Renewable and Sustainable Energy Reviews,15,pp Savariraj,S., Ganapathy,T. and Saravanan, C.G., (2012) Performance and emission characteristics of diesel engine using high-viscous vegetable oil, International Journal of Ambient Energy, 33(4), pp Kapilan,N., Babu,T.P. Ashok and Reddy, R.P., (2009) Improvement of performance of vegetable oil fuelled agricultural diesel engine Bulgarian Journal of Agricultural Science, 15 (6), pp Murugesan,A.,Umarani,C.,T.R.,Chinnusamy., Krishnan,M., Subramanian.,R., Chezhain,N.Neduz, (2009), Production and analysis of bio-diesel from non-edible oils-a review, Renewable and Sustainable Energy Reviews,13 pp

27 7. Awolu,Olugbenga Olufemi., and Layokun, IEEE-International Conference on Advances in Stephen Kolawole, (2013) Optimization of Engineering, Science and Management, two-step transesterification production of pp biodiesel from neem (Azadirachta indica) 17. Nithyananda,B. S., Anand, A., and Prakash, G. oil,international jounal of Energy and V. Naveen., (2013) Performance Study on Environmental Engineering,4:39,pp.1-9. Diesel Engine Using Different Blends of Neem 8. Misra,R.D. and Murthy, M.S., (2011) Biodiesel,International Journal of Engineering, Comparative Performance Evaluation of Research and Applications, 3(4), Karanja Vegetable oil and Karanja Biodiesel Blends with Diesel in C.I. Engine, IEEE First conference on Clean Energy and Technology, pp pp Khandelwal, Shikha., Chauhan, Rita Yadav., and Shrivastava,Prashant, (2013) Analysis and evaluation of operating variables for the yield 9. Dwivedi,Gaurav.,and Sharma,M.P., (2013) of Karanja and neem oil-based biodiesel Performance evaluation of diesel engine using production, International Journal of biodiesel from pongamia oil International Journal on Renewable Energy Research, 3(2), pp Puhan,Sukumar.,Nagaraj,G.,Vedaraman,N., and Ramabramhman B.V., (2007) Mahua oil (madhuca Indica oil ) derivatives as a renable fuel for diesel engine system in India : Aperformance and emission comparative study Sustainable Energy, 10,pp Anbumani,K.., and Singh,A.P., (2010) Performance of mustered and neem oil blends with diesel fuel in CI. Engine, APRN Journal of Engineering and Applied Sciences, 5( 4), pp Jingzhuwei and Lin,Xiangyi., (2008) The multiple attribute decision making VIKOR International journal of Green energy, 4: method and it s application,ieee Tzeng,GwoHshiung.,Lin,Chengwei.,Oprecovic 11. Lenin,A. Haiter., Ravi,R. and Thyagarajan, K., (2013) Performance characteristics of a diesel engine using mahua biodiesel as alternative fuel,serafim, (2005) Multi Criteria analysis of alternative fuel buses for public transportation Energy policy, 33pp Iranica Journal of Energy and Environment Tong,Lee-Ing., chen,chi-chan.,and Wang (2): Aransiola,E.F., Betiku, E., Ikhuomoregbe, DIO., and Ojumu,TV., (2012) Production of,chung.ho, (2007) optimisation of Multi response processes using the VIKOR method Int.JAdv.Manuf. Technol 31 : biodiesel from crude neem oil feed stock and its 23. Huang,Jih-Jeng., Tzeng,Gwo-Hshiung.,and emissions from internal combustion engine, Hsiliu,Hsiang., (2009) A revised VIKOR African Journal of Biotechnology, vol. 11(22), model for multiple criteria decision pp Ragit, S.S., Mohapatra,S.K.., and Kundu, K., making-the perspective of Regret Theory CCIS35, pp , (2010) Performance and emission evaluation 24..Zandi,A., and Roghanian,E., (2013) of a diesel engine fueled with methyl ester of neem oil and filtered neem oil, Journal of Scientific and Industrial Research, vol. 69, pp. Extension of fuzzy ELECTRE based on VIKOR method computer and Industrial engineering Opricovic,Serafim., Tzeng, GwoHshiung., 14. Elango,T. and Senthilkumar, T., (2010) (2007) Extended VIKOR method in effect of methyl esters of neem and diesel oil comparison without outranking methods blends on the combustion and emission characteristics of a CI. Engine, ARPN Journal of Engineering and Applied Science, 5(10), pp European Journal of Operational Research 178 pp TanselIc,Yusuf., (2012) An experimental design approach using TOPSIS method for the 15. Yadav,Dharmendra. and Shrivastava, Nitin., selection of computer. Integrated (2012) Experimental Investigation of manufacturing technologies Robotics and performance parameters of Single Cylinder four Stroke DI Diesel Engine Operating on neem oil Biodiesel Blends, Research and computer Integrated manufacturing 28pp. Development,,International Journal of Automobile Engineering Research and Development (IJAuERD) 2(3),pp Senthilkumar,R., Ramadoss, K.. and Prabu, M., (2012) Emission and Performance Characteristics of Single Cylinder Diesel Engine Fuelled With Neem Biodiesel,, 18

28 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh ESTIMATION OF MINERAL CONTENT IN SOME SELECTED FISHES OF BANGLADESH Md.Abdullah Al Mamun 1 andruhinabinta A Ghani 2 1 Department of Food Technology and Nutrition Science, Noakhali Science and Technology University, Sonapur-3814, Noakhali. 2 Health Nutrition and Population program, BRAC 2, BRAC Centre, 75Mohakhali, Dhaka-1212 Md.Tazul Islam 3 3 Department of Food Technology and Nutrition Science, Noakhali Science and Technology University, Sonapur-3814, Noakhali. Professor Sheikh Nazrul Islam, Ph.D. 4 4 Institute of Nutrition and Food Science, University of Dhaka, Dhaka-1000 This study presents the content of moisture and essential minerals in some indigenous fishes of our country. Bangladesh is an agro based country blessed with inland water in the form of ponds, canals, ditches, flat and plain Haors ( water bodies formed due to natural depression), Baors (oxbow lake),rivers, estuaries etc. covering an area of million hectares. This happens to be an excellent ecological condition for the propagation of fishes (BBS,1994). About 63% animal s protein is supplied by fish (DOF, 2002). These indigenous fishes are much popular for their taste (Moniruzzamman, 2000). In the study, moisture content was determined by following the AOAC (1984) method as described by Gopalan(1976) while minerals such as Fe, Ca, Zn, Cu, and Mg were determined by Atomic Absorption Spectrophotometer (AA- 6800) after appropriate digestion of samples. 1. INTRODUCTION The fishes namely Ketchki (coria soborna), Mola (Amblypharyngodon mola), Poah (Panna microdon), Tilapia (Oreochromis mossambic), Silvercarp (Hypohthalmichthys molitrix), Ruhi (Labeo rohita), Takhi (Channa punctatus) and Pangas(Pangasius pangasius) are belong to fresh water and are widely available in the market.. The above mentioned fishes are commonly consumed by all classes of people in Bangladesh. Fresh water fishes are an important source of essential macro and micronutrients. Information of the chemical composition of fish in respect to the nutritive value is important to compare with other source of animal protein, such as meat and poultry products (stansby, 1954). From recently conducted epidemiological, clinical and nutritional studies on animal and human, it is accepted that fish fat contains high amount of unsaturated fatty acids which are help prevent atherosclerosis, cardiovascular diseases, aging and certain forms of cancers (kinsella, 1988; Morris and Culkin, 1989). Fishes are considered to be an excellent source of animal protein with all essential dietary amino acids. They contain important minerals like iron, calcium, phosphorous, zinc, copper, magnesium and vitamins. Fishes meet the protein requirement of the people of Bangladesh to a great extent. The minimum per capita per day protein requirement of the people in Bangladesh has been estimated to be g, of which 15g should be of animal origin. Fish contributes to about eighty percent (80 %) of the total animal protein intake (Rahman and Ali, 1986). There are about species of fishes that contribute enormously to the supply of essential nutrients in Bangladeshi diet chart (Zafri& Ahmed, 1981). Small indigenous fishes like Mola and Dhela are rich in vitamin -A. These small fishes are fair sources of essential minerals in our diet (Marufa, 1998). Generally, fresh water fishes are more popular than marine fishes in Bangladesh. The low level acceptance of marine fish may be due to the fact that the Bangladeshi peoples are more used to fresh water fishes and also that marine fish are not uniformly available in every region of the country (Islam, 1983). The consumption of fishes rises with increasing income. Groups subjected to low income maintain their consumption of fish * Corresponding Author: Sheikh Nazrul Islam sheikhnazrul09@gmail.com

29 majorly by catching fishes or to a lesser extent by buying them. The high income class mostly depends on market supply of big and more expensive species, The consumption of these fishes reflect higher social status as well(thilsted and Hassan 1996, ISPAN, 1993). Fish is a wellaccepted food item in traditional Bengali diet. Therefore, proper information on the mineral composition of the selected fishes is necessary for being aware of the health benefits associated with these fishes. The purpose of the study was to estimate the nutritional composition especially the minerals and their role in health of human being. 1.1 Objective Dietary assessment is regarded as one of the important methods for determining the nutritional status of an individual or a community. Dietary assessment has to be done based on a local food composition data, which is specific for a particular region, because the nutrient content of food materials may differ greatly due to regional variation. Rice and fish are our staple food. In spite of the huge consumption of fish by our people, information regarding the content of their essential minerals and vitamins are scarcely available as scientific literature. Thereby, it is necessary to generate scientific data regarding the dietary intake of essential minerals and vitamins. The existing available information on this issue is obsolete, which was estimated fifty years ago. The foodstuffs were not even analyzed for essential micronutrients like, vitamins and minerals. This situation calls for an updated study on these nutritional values 2. METHODS AND MATERIALS 2.1 Identification The fish were identified with local and scientific names. 2.2 Sampling Immediately after the procurement from the market, the fishes were washed with distilled water and the surface water was drained out. Weight of the fish was recorded upon purchasing. Next, they were processed in the usual manner, which involves removal of scales, fins and visceras.. Then they were filleted from both sides. Afterwards, the processed fish were washed with de-ionized water. The whole processed fish was later dissected and each portion was de-boned as much as possible. The edible portion was separated and minced in a mechanical grinder. Two gram of samples in duplicate from each portion were taken for the determination of moisture. Rest of minced sample was collected and wet weight was recorded. Next, the sample was dried in an oven at 105 C and the dry weight of the sample was recorded. The dry sample was then ground in a mechanical grinder. Nutrient analysis was conducted using the dry samples and the parameters were later readjusted for wet weight. 2.3 Biochemical analysis of selected fish Two types of nutrients content of the selected fishes have been analyzed Such as, moisture and minerals (Zn, Fe, Ca, Mg, Cu and P) 2.4 Estimation of moisture and dry factor of selected fish. Moisture was determined by following the AOAC (1984) method as described by Gopalan(1976). At first, weight of the crucible was made constant and 2-4 gram of fresh sample was taken in crucible. The crucible was then placed inside an oven at C for 3 to 4 hours. Afterwards, the crucible containing sample was weighed in an electric balance (Mettler Toledo, AB 104) and was heated in an oven until constant weight was reached everytime. The crucible was cooled in desiccators before weighing. Calculation: Moisture content was determined as follows using the oven drying procedure. % of moisture= Initial weight (g) Final weight (g) X 100 Weight of the fresh sample Where, Initial weight = Sample weight + Crucible weight (before heating) Final weight = Sample weight + Crucible weight (after heating) fresh weight Drying factor = dry weight Moisture content was determined as follows using the oven drying procedure. 2.5 Estimation of minerals (zn, fe, ca, mg, cu and p) in selected fish. Minerals such as Fe, Ca, Zn, Cu, and Mg were determined by Atomic Absorption method using Spectrophotometer (AA-6800) after appropriate digestion of samples Wet digestion (used for ca, mg, zn, cu and fe determination) Wet digestion with oxidizing acids is the most commonly adopted sample preparation procedure. It is primarily used in the preparation of samples for subsequent analysis of specific minerals. It has the advantage of being effective on both inorganic and organic materials. It often destroys or remove the sample matrix, thus helps to reduce or eliminates a number of interferences. As lower temperature is considered, little loss of volatile minerals occurs during wet digestion. Most wet digestion 20

30 procedures are conducted under extreme conditions of temperature or reagent used. 3. PRINCIPLE Simple wet digestion is a method of converting the components of a matrix into simple chemical forms. This digestion is produced by supplying energy, such as heat; by using a chemical reagent, such as an acid; or by a combination of the two methods. The reagents nature will depend on the matrix. This method prepares plant tissue for the quantitative determination of the concentration of calcium, copper, iron, magnesium, phosphorus, potassium, sodium and zinc and trace elements using a nitric-per chloric (HNO 3 -HClO 4 ) acid 4. PROCEDURE About 500mg of the dry sample was placed into 25mL conical flask, 6mL HNO 3 acid was added and kept at room temperature overnight to predigest the sample. The sample with HNO 3 acid into a digestion block port was then heated at 150 C for 60 minutes to remove red fume, Afterwards, it was cooled at room temperature. 2mL of HCLO 4 acid was added to the sample and placed again into a digestion block port at a block temperature of 215 C for 2 hours. Then the sample was cooled in a hood for 20 minutes and 10mL de-ionized water was added on hot plate (90 C). The solution was mixed up well using a vortex stirrer, Next it was cooled, and diluted in a 50mL volumetric flask. The solution was filtered to remove all particulate matter in the digest prior to analysis. Calculation of mineral contents Calculation: mg/100g = Actual concentration x dilution factor 10 x sample weight x dry factor (D.F) Where, Drying factor = Fresh wt. / Dry wt Instrument setting for mineral analysis 5. STATISTICAL ANALYSIS Mean and S.D were determined for all nutrients under present study. Statistical analysis was accomplished by using SPSS (SPSS/PC+ Version 12.0: SPSS Inc., Chicago). 6. RESULTS Moisture content, in the study, was found to be in lowest (71.90g %) for pangas and highest (80.73g %) for Ketchki. Moisture content ranged grom to 0.8g% for selected eight species. Zinc content in were found to be 0.63mg% for Tilapia and 3.00 mg% for Mola. Zinc content for Ketchi is relatively high (5.21mg %), while for Tilapia it is relatively low (0.63mg %).Iron content in fish was found to 0.23mg% for Tilapia and 0.30 mg% for Silvercarp. Iron content is relatively high ( mg %) for Ketchi and Mola, but comparatively low ( mg %) for Tilapia and Poa. Magnesium content in fish was found to be mg% for Tilapia and 29.15mg% for Poa. Magnesium content was relatively high ( %) for Ketchki and Mola, while the content was pretty low (20.75mg %) for Pangas. Calcium content in fish was measured to be in a range of 7.61% (for Pangas ) and 5.54mg% (for Tilapia). Calcium content is relatively high ( mg %) for Mola, and Ketchi, while relatively low (11.82mg %) for Silvercarp. The content of copper in fish was found to lowest (0.02 mg %) for Poah and highest (12.37 mg %) for Pangas. The copper content for Tilapia and Ketchi was found to be in a comparable range ( mg %). Amongst the fishes analyzed in present study, some fish stand out as good sources for minerals. Mola stands out to be a good source of zinc, calcium, magnesium and copper While Tilapia stands out to be a fair source of protein, magnesium and calcium. Pangas turns out to be rich in iron, magnesium, and calcium. Tilapia appears to be a fairly good source for protein, iron, zinc, calcium. Element Wavelength (nm) Fe Ca Zn Cu Mg

31 Table 1: Mineral and moisture content in Kachki, Mola, Poah, Tilapia, Silvercrap, Ruhi, Takhi, Pangas fish Name of the fish Mean (± SD) Mineral Content (mg %) Mean (± SD) (g %) Local Scientific Ca Mg Fe Cu Zn Moisture Ketchki Coria soborna* (0.37) (1.98) 3.02 (0.29) 4.42(0.06) 5.21(0.01) (0.09) Mola Amblypharyngodonmola* (2.88) (1.58) 2.50(0.11) 2.78(0.07) 3.00(0.05) (0.48) Poah Pannamicrodon (0.68) (1.22) 0.25 (0.01) 0.02(0.02) 0.62(0.03) (0.42) Tilapia Oreochromismossambic 5.54(0.05) (0.1) 0.23 (0.00) 8.10(0.1) 0.63(0.0) (2.0) Silvercarp Hypohthalmichthysmolitrix* (1.66) (1.39) 0.30 (0.01) 0.34(0.06) 0.97(0.02) (0.2) Ruhi Labeorohita* (1.39) (1.3) 1.480(0.03) 0.15(0.02) 1.17(0.02) (0.66) Taki Channapunctatus (1.12) (0.11) 0.39 (0.01) 0.16(0.06) 1.15(0.06) (0.04) Pangas Pangasiuspangasius* 7.61 (0.27) (0.54) 0.5 (0.01) 12.37(0.4) 0.62(0.01) (1.63) * Hamilton-Buchanan, 1822 Bleeker, 1842 Peter, 1852 Bloch&Schneider, 1801 ^Moisture content of selected fish species in g per 100g edible portions. ^Mineral content of selected fish species in mg per 100g edible portions. 7. CONCLUSIONS The selected fishes are rich in contents from nutritional point of view especially in terms of mineral content. Detailed findings of mineral content of these fishes are important in orde to evaluate their nutritional quality About 63% of protein and essential trace minerals come from fishes (DOF, 2002), However, the "Food Composition Table" in Bangladesh does not have sufficient information regarding the content of essential minerals in our local foodstuffs. Therefore, the present finding is expected to contribute positively towards the enrichment and updating of our already existing "Food Composition Table". This will help conduct an accurate dietary assessment of these nutrients in our country. 8. REFERENCES 1. AOCA, (1984). Association of Official Analytic Chemist, 14th edition, William's. 2. BBS, (1994), Bangladesh Bureau of Statistics, Statistical Year book of Bangladesh Govt. of Bangladesh, Bangladesh Secretariat, Dhaka, pp: DOF (Department of Fisheries, Government of the People s Republic of Bangladesh), (2002)Fisheries Resource information of Bangladesh, pp: Gopalan, C, (1976), A manual of Laboratory techniques. National Institute of Nutrition. Indian Council of Medical Research, Hyderabad, India. 5. Islam, A (1983), A Report on Aquatic Culture. Bangladesh Fisheries Resources Survey System, (2), PP Kinsella JE (1988), Food lipids and fatty acids: importance in food quality, nutrition, and health. Food Technol42: Marufa, R. (1998), Mineral content in small indigenous Fish of Bangladesh. Institute of Nutrition and Food Science. Dhaka University. 8. Moniruzzaman, M. (2002), Investigation diseases of some small indigenous fresh water fishes of Bangladesh. M.S thesis, BAU, Mymensingh. 9. Morris RJ, Culkin F (1989) Fish. In: Ackman RG (ed) Mannebiogenic lipids, fats, and oils Vol 11. CRC Press Inc, Boca Raton, FL, p Rahman, M.L and M. H. Ali (1986), A study on the Credit and Marketing Aspects of Pond Fisheries in two Districts of Bangladesh. Bureau of Socio-economic Research andtraining, Bangladesh Agricultural University, Mymensingh, Stansby, M.E. and Olcott. S.H. (1963), Composition offish. Industrial FisheriesTechnology,Reinhold publishing Corporation N.Y. PP: Thilsted, S.F1 and Hassan, N., (1996), The Nutritional of importance of small Indigenous Fish in Bangladesh-Policy Implications for Aquaculture. 13. Zafri, A. and Ahmad, K. (1981), Studies on the Vitamin-A content of fresh water fisher: Content & distribution of Vitamin-A in Mola and Dhela, Bang. Journal of Biol. Science.10:39. 22

32 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh COPPER IMMOBILIZED PLATINUM ELECTROCATALYST FOR THE EFFECTIVE REDUCTION OF NITRATE IN A LOW CONDUCTIVE MEDIUM: MECHANISM, ADSORPTION THERMODYNAMICS AND STABILITY Alam M. Mahbubul, Uddin S.M. Nizam, Rashed M. Abu, Hasnat M. Abul * Department of Chemistry, School of Physical Sciences, Shahjalal University of Science and Technology, Sylhet-3114, Bangladesh The electrolytic reduction of NO 3 and its intermediate NO 2 in neutral medium was performed on a Cu immobilized Pt surface. The voltammetric investigations showed that the bare Cu electrode has little effect on nitrate reduction reactions (NRR), whereas an enhanced catalytic effect (i.e. a positive shift of the peak potential and an increased reduction current) was observed when Cu particles were immobilized onto Pt surface. At the Cu Pt electrode surface, the NRR process was observed to occur via a two step reaction mechanism, with transfers of 2 and 6 electrons in the first and second steps, respectively. Similar results were obtained by chronoamperometric (CA) studies. Closer NRR mechanistic studies at the as prepared Cu Pt electrode revealed concentration dependent kinetics with a critical nitrate ion concentration of 0.02M. Moreover, NRR proceeded via a simple adsorption desorption mechanism following a Langmuir isotherm with an adsorption Gibbs free energy of KJ mol 1 (1 st step) and KJ mol 1 (2 nd step). By means of a Pt Nafion Cu Pt type reactor without any supporting electrolyte, bulk electrolysis was performed to identify nitrate reduction products. It was found that after 180 min of electrolysis, 51% of NO 3 was converted into NO 2 intermediate. This percentage decreased to 30% in CO 2 buffered conditions. The electrocatalysis of nitrate ion on Cu Pt electrode surface showed no apparent surface poisoning as confirmed by its stability after excessive CV runs. This was further supported by surface analysis and morphology of the as prepared catalyst with scanning electron microscopy (SEM) and energy dispersive X ray (EDX) analysis. 1. INTRODUCTION The nitrate reduction reaction (NRR) is essential to counter agricultural and waste disposals that are continuously contributing toward the percentage of nitrates accumulating in groundwater. Besides pollution control, NRR is also significantly important for the synthesis of various nitrogenous compounds. However, controlled synthesis of specific products (such as NO 2, NO, N 2 O, NH 2 OH, NH 3 and N 2 ) by reducing nitrate ions is challenging [1 5]. Nowadays, three types of nitrate reduction processes have been developed: (i) catalytic hydrogenation (ii) nitrate reduction by microorganisms into gaseous nitrogen and (iii) electrochemical heterogeneous catalytic reduction of nitrate ions [4 9] that can be used for denitrification of drinking water [10 25]. The electrocatalytic process is more advantageous than the other processes since (i) electrode materials can be prepared in situ under particular experimental conditions and (ii) nitrate/nitrite ions can be selectively reduced to desired products. To date, several metal substrates (Sn, Pt, Pd, Cu, Ag, Rh etc.) have been investigated as electrodes, with the aim to attain effective nitrate reduction reaction. Among these, Cu has been proven to exhibit excellent electrocatalytic activity both in acidic [19] and basic media [20, 22, 24]. To our knowledge, fewer research articles have been published on NRR in a neutral medium. In a previous study, it was reported that on pure Ag surface, the electrolysis of nitrate ion produces NO 2 ions only by means of electron transfer (ET) reactions in presence of KCl [10]. In another study, it has been shown that Ag immobilized noble metal catalysts (i.e. Ag Pt, Ag Pd) exhibit divergent catalytic roles in a sandwich type reactor at ph 7 [18]. Ying Lou et al., conducted NRR experiments using an amorphous Pd Ni P alloy electrode where ammonia was found to be the major product in neutral medium [11]. Katsounaros et al. reported * Corresponding Author: Hasnat M. Abul, mah-che@sust.edu

33 that Sn is a highly nitrogen-selective cathode in the neutral medium that requires very high overpotential, though [12]. Furthermore, Rh-based electrode is reported to be an excellent electrocatalyst for the electrochemical reduction of NO 3 and NO 2 [17,25]. In addition to the choice of electrode material, the experimental setup of the electrolysis reactor plays an important role. For instance, the sandwich type (M Nafion M, M = Pt, Pd, Pt Pd) reactors have been successfully used for selective oxidations of various organic compounds [26 30]. Recently, the use of a sandwich type reactor was reported(m Nafion M X; X = Rh [17] or Ag [18]). Despite their efficient electrocatalytic activities, Rh and Ag electrodes are expensive, in addition to their stability issues. On the other hand, it is reported that Cu is an effective catalyst for NRR and the corresponding ET mechanism is well investigated, both in acidic and basic media. However, to the best of our knowledge, NRR mechanism at a Cu Pt electrode surface under neutral conditions has not yet been reported. In this work, the applicability of a Cu Pt electrode for the selective reduction of NO 3 and its intermediate NO 2 in neutral media using a Pt Nafion Cu Pt reactor has been reported.. The electrocatalytic activity of the as prepared Cu Pt electrode has been compared with that of a pure Cu surface. The kinetic mechanism and thermodynamic stability of Cu Pt electrode electrocatalysis in attaining effective reduction of NO 3 has also been discussed. 2. EXPERIMENTAL 2.1. Chemicals, solutions and electrodes All chemicals and reagents used were of analytical grade and were used as supplied by Sigma Aldrich without further purification. All solutions were prepared using milli-q water. The Cu and Pt were used as working electrodes. In all experiments, the electrode surfaces were polished and washed properly. The Cu-deposited Pt electrode was freshly prepared, before each experiment as described below. For electrochemical measurements, an Ag AgCl (sat. KCl) and a Pt wire were used as reference and counter electrodes, respectively Cu Pt electrode preparation and electrochemical measurements An electrochemical workstation (CH Instrument series) and an Autolab PGSTAT128N instrument (Metrohm Autolab B.V.) were used to carry out all electrochemical measurements. All experiments were conducted at room temperature ( 23 C) and under N 2 -atmosphere in a conventional threeelectrode cell. In order to prepare Cu Pt electrode as a catalyst, a Pt disk (2 mm diameter) was placed in a 0.01 M CuSO 4 solution. The potential was then cycled four times between 0 and 1.0 V at a scan rate of 100 mv s 1. This resulted in the electrodeposition of Cu layer on the Pt surface. Prior to the use for NRR, the as prepared electrode was washed thoroughly with water and the potential was swept repeatedly between 0 and 1.5 V in a 0.05 M KCl solution until stable cyclic voltammograms were obtained. The NRR experiments were carried out in nitrate containing 0.05 M KCl solution, where the total volume of the electrolytic solution was maintained constant at 20 ml. For cyclic voltammetric experiments, the potential range used was 0.1 V to 1.6 V. At more negative overpotentials, a very strong hydrogen evolution reaction (HER) was observed. To attain equilibrium state in all electrochemical measurement, the rest potential was maintained at 0.1 V for 30 s prior to potential scanning Preparation of the electrode-membrane assembly Pt film was prepared over Nafion-117 membrane (Du Pont). A Nafion membrane of 2 cm 3 cm was sand blasted, dried at 110 C and immersed in 200 ml of 7.5 mm solutions of H 2 [PtCl 6 ] for chemical deposition of the noble metal. A mixed solution of 2.0 M NaBH 4 and 4.0 M NaOH was then added at a rate of 2.0 ml/h to the membrane containing system, under continuous heating ranging from 35 C up to 60 C at a rate of 5 C /h and magnetic stirring at a rate of 150 rpm. Consequently, the deposition of Pt film on both sides of the Nafion membrane was achieved within 12 h. Finally, the metal membrane assembly (MEA) was thoroughly washed using 0.01 M HNO 3 and deionized water to remove unreacted reagents or debris. In all cases, the total geometric area of the cathode was 6 cm 2 with a surface resistivity of less than 10 Ω cm 1. The as-prepared Pt immobilized Nafion membrane was installed in a reactor in such a way that Pt Nafion Pt sandwich type structure of the cell was configured, and the volume of each compartment was 10 ml. The modifier metal (Cu) was deposited electrochemically onto the Pt surfaces to fabricate an asymmetric type reactor (Pt Nafion Cu Pt, Fig. 1). A deposition current of ca. 50 ma (Ecell = V) was passed through 10 ml of a 10 mm CuSO 4 5H 2 O solution for one to several minutes by means of a DC source. According to a previous study, a 20 at.% Cu on Pt surface was found to show the best reduction activity [15]. Therefore, Cu content on Pt surface 24

34 was controlled by the deposition time. The as prepared metal-membrane assembly was rinsed with ultra-pure water before its use in nitrate reduction reactions.the Cu Pt electrode composition was determined by X-ray fluorescence analysis. Fig.1. Schematic illustration of the electrocatalytic reactor used for the reduction of NO Bulk electrolysis The electrocatalytic reduction of NO 3 /NO 2 in aqueous solutions was carried out using the sandwich type double chamber Pt Nafion M reactor (Fig. 1). The cathode (Cu Pt) and anode (Pt) compartments were separated by the H + conducting Nafion membrane with a geometric area of 6 cm 2 for each side of the membrane. The distance between anode and cathode was assumed to be the same as the thickness of the Nafion membrane (i.e. 180 µm). The cathode and the anode compartments were filled with 8 ml aqueous solution of KNO 3 and water, respectively. To perform the electrolysis, the reactor was connected with a potentiostatic system. In order to analyze changes in concentration of NO + 3, NO 2 and NH 4 as a function of time, a 20 µl of the solution in the cathode compartment was collected at a constant interval and diluted to 5 ml. The concentration changes of NO 3, NO 2 and NH + 4 were measured by an ICA-2000 model (DKK-TOA Corporation) ion chromatograph Surface Characterization Surface morphology of the Cu deposits was characterized using a scanning electron microscope (SEM) (Leo Supra 50 VP); elemental analysis of the prepared Cu Pt electrode was carried out by energy dispersive X-ray spectroscopy (EDX) (Oxford INCA 400). 3. Results and discussion 3.1. Electrocatalytic activities toward the NRR Fig. 2 shows the cyclic voltammogram (CV) obtained at a Pt electrode in a 0.01 M CuSO 4 aqueous solution recorded at a scan rate of 100 mv s 1. A single well-shaped cathodic peak was observed at 0.6 V corresponding to the reductive deposition of Cu metal onto the Pt substrate. The voltammetric behavior of the prepared Cu Pt electrode in 0.05 M KCl is shown in Fig. 3. As anticipated, only hydrogen evolution is observed at high negative overpotentials (E 1.15 V), showing a significant negative shift of 350 mv compared to bare Pt, which reflects the deactivation of hydrogen evolution reaction (HER) active sites due to deposited Cu layer. This was further confirmed by measuring the CV at a pure Cu electrode, which showed insignificant HER before 1.35 V. This broadening of the potential window would clearly be advantageous toward the investigated NRR. Fig. 4 shows the CVs recorded in a 0.05 M KCl solution containing either 5.0 mm KNO 3 or 5.0 mm KNO 2 at bare Cu and Cu Pt electrodes. A significant feature in these voltammograms is the enhancement of the catalytic activity for nitrate reduction at the as prepared Cu Pt catalyst observed (a) in the positive shift of the main NRR peak from 1.51 V to 1.21 V at bare Cu and Cu Pt electrodes, respectively, which is interestingly almost at the same potential shift observed for HER as described earlier, and (b) in a 2.5 times increase of the respective peak current from 2.5 ma cm 2 to 6.4 ma cm 2. An additional interesting feature of Fig. 4 is the shape change in the CV recorded for KNO 3 with the Cu Pt electrode with two well-defined peaks and a broad cathodic wave at 0.52 (E1), 0.83 (E2) and 1.21 V (E3). In the case of Cu electrode, the observed corresponding potential values were 0.65, 0.95 and 1.51 V. All these observations imply that new catalytic sites were developed due to Cu layer deposited onto the Pt surface, enhancing the NRR. 25

35 Fig. 2. Cyclic voltammogram of Pt electrode in a 0.01 M CuSO4 solution at a scan rate of 100 mv s 1. Fig. 3. Cyclic voltammograms of Pt, Cu Pt and Cu electrodes in a 0.05 M KCl solution recorded at a scan rate of 50 mv s 1. Fig. 4. Cyclic voltammograms of 5 mm KNO 3 recorded at Cu and Cu Pt electrodes (solid lines) and 5 mm KNO 2 at Cu Pt electrode (dotted line) in 0.05 M KCl solution at a scan rate of 50 mv s 1. Fig. 5. Linear plots of peak current (J p ) vs. square root of scan rate (v 1/2 ) at E2 (5 mm KNO M KCl) and at E3 (5 mm KNO M KCl) recorded at Cu Pt electrode NRR pathways To elucidate the NRR mechanism at the as prepared Cu Pt electrode in the present work conditions, it was essential to analyze the CV profiles of nitrate and nitrite ions as shown in Fig. 4. In the absence of nitrate/nitrite ions, only the peak appearing at 0.52 V (E1) has been observed and assigned to the reduction of Cu(II) species. The remaining reduction waves (E2) and the major reduction peak (E3) concerning NO 3 ions, in Fig. 4, can clearly be attributed to different electron transfer steps. To elucidate the nature of these steps, CV of KNO 3 was compared with that of KNO 2 under similar experimental conditions. It is clear from Fig. 4 that the reductive wave (E2) is absent in the case of KNO 2, while the remainder of the CV matches very well with that of KNO 3. This observation suggests that during the reductive scan, NO 3 ions were probably converted into NO 2 ions at (E2). The number of electrons transferred in the different steps of an irreversible diffusion-controlled process can be determined from the relationship between the peak current and the scan rate (v) [31]: J p = ( ) nα 1/2 CD 1/2 o v 1/2 (1) where, J p is the peak current density (A cm 2 ), n is the number of electrons, (α = 0.47) [20,23] is the transfer coefficient, C is the bulk concentration of nitrate ions (mol cm 3 ) and D o is the diffusion coefficient ( cm 2 s 1 ) [20]. Fig. 5 shows the linear plots of J p vs. v 1/2 fitted to peak (E2) (w.r.t 5 mm KNO 3 ) and (E3) (w.r.t 5 mm KNO 2 ). From the slopes of the best fit, the values of n were evaluated as 1.8 and 6.1 at (E2) and (E3) peaks, respectively. Consequently, the following mechanism is proposed for NRR in the present work conditions: at peak(e2) : NO 3 ads + H 2 O ads + 2e NO 2 ads + 2OH ads (2) at peak(e3) : NO 2 ads + 5H 2 O ads + 6e NH 3ads + 7OH ads (3) 26

36 nitrate concentration. After subtraction of the background currents, the peak currents were determined and the results are shown in Fig. 7. It is clearly noticeable that, at low concentrations the peak currents increased linearly as a function of nitrate concentration. Then, a deviation from this linearity occurred at concentrations higher than a critical value of 0.02 M. This observation may suggest that the kinetics of NRR is different below and above this critical concentration. Accordingly, the kinetic order (γ) of NRR process was estimated below and above this critical concentration. Fig. 6. Chronoamperograms recorded at the Cu Pt electrode in N 2 -saturated 0.05 M KCl solution containing 5 mm KNO 3 (a) and 5 mm KNO 2 (b) at potential steps of 0.8 and 1.2 V respectively. Insets show the plots of J vs. t 1/2 plots with respective linear regressions. To support these assumptions, single-step chronoamperometry (CA) experiments were carried out by stepping the potentials to the values of (E2) and (E3) for a period of 20 s in each case of KNO 3 and KNO 2 as shown in Fig. 6. The results were interpreted using the Cottrel equation [31]: J p = nfd o 1/2 Cπ 1/2 t 1/2 (4) where, C is the bulk concentration (mol cm 3 ), D o is the diffusion coefficient ( cm 2 s 1 ) [20], n is the number of electrons, F is the Faraday constant (96,485 C mol 1 ), t is the time (s) of the potential. The insets of Fig. 6 show respective plots of J p vs. t 1/2 along with the corresponding best-fitting linear regression with an (R 2 ) value of and 0.977, respectively. From the slopes of these lines, it was possible to compute the number of electrons transferred in each case as n = 2.3 and n = 5.6 at peaks (E2) and (E3), respectively. These results are in very good agreement with the CV-derived ones, which support the proposed mechanism (cf. Eqs. (2) and (3)) Kinetics and thermodynamics Nitrate Concentration dependent CVs were recorded at the Cu Pt electrode at a scan rate of 50 mv s 1. As expected, the peak currents at (E2) and (E3) (indicated in Fig. 4) increased with increasing Fig. 7. Variations of E2 and E3 peak currents (J p ) with KNO 3 concentrations in 0.05 M KCl solution at Cu Pt electrode. The CVs were recorded at a scan rate of 50 mv s 1. From the slope of log( I p ) versus log[no 3 ] the kinetic order of an electrochemical reaction can be estimated according to following equation [12,20]: log I p = log k + γ log[no 3 ] (5) where k is the kinetic rate constant and γ is the kinetic order. It was found that the order of the reaction changed from 0.96 and 0.99 at [NO 3 ] < 0.02 M to 0.50 at [NO 3 ] > 0.02 M at (E2) and (E3), respectively. The change in the order of the reaction from unity to a fraction at higher concentrations ensures that the electroactive species adsorb on the electrode surface prior to the electron transfer step [11]. Since adsorption desorption equilibrium plays an important role for heterogeneous catalytic processes, the adsorption free energy of nitrate ions on the Cu Pt electrode surface was calculated. Several authors adopted Langmuir isotherm to evaluate nitrate adsorption related constants [11,25,32 34]. It can be inferred that at the peak potentials (i.e. at E2 and E3), the peak current density is related to the extent of surface concentration of NO 3 ions [25,33] and adsorption equilibrium constant (K) according to the equation: = + (6) 27

37 where J p is the peak current density at any concentration of NO 3 and J p,max at its maximum concentration. Linear plots (R 2 = 0.99) of [NO 3 ]/J p versus [NO 3 ] associated with peaks (E2) and (E3), at the Cu Pt electrode surface are presented in Fig. 8. From the values of the intercepts and slopes as per Eq. (11), the adsorption equilibrium constant (K) were found to be and M 1 at (E2) and (E3), respectively. complex species that may result in catalytic hydrogenation of nitrate ions as shown in reactions ((2) and (3)). It can be assumed that the observed electrocatalytic activities for the NRR on the Cu Pt cathode surface of the reactor are attributed to mixed mode (i.e. hydrogenation and electron transfer) reaction trails. Fig. 8. Langmuir adsorption Isotherms of nitrate ions at Cu Pt electrode (data was extracted from Fig. 7). The adsorption free energy (Δ ad G ) of NO 3 ions onto Cu Pt electrode surface was then calculated from the relationship Δ ad G = RTln K and found to be and kj mol 1 at (E2) and (E3), respectively. Adsorption of electro-active species onto the electrode surface is a prerequisite condition for a heterogeneous electrochemical process. Therefore, the larger negative value of Δ ad G obtained in the present work conditions accounts for the superior catalytic activity of Cu Pt electrode Bulk electrolysis Fig. 9A shows the concentration profile during the electrolysis of a 0.05 M KNO 3 solution carried out using a Cu Pt cathode (12 at.% Cu particles) in the absence of any supporting electrolyte, where 0.1 A DC was passed through the membrane reactor (Fig. 1). When Pt film alone was employed as cathode material, the reaction was very slow (k < min 1 ). Pronounced catalytic activities were obtained after Cu was deposited onto the Pt surface. Several studies have reported that Cu Pt electrode materials are ideal for catalytic hydrogenation of nitrate ions [4 5,33 35]. In the present case, once the reactor was connected with the DC power source, vigorous hydrogen evolution was noticed. Under the applied potential conditions, water molecules are oxidized at the anode surface producing oxygen and H + ions. The latter migrated to the cathode surface through the conducting Nafion membrane. Since Pt has efficient adsorption capacity, H + would potentially form Cu Pt H Fig. 9. Concentration profiles of 0.05 M KNO 3 electrolysis in absence (A) and in presence (B) of CO 2 buffer system. Cathode: 12 at.% Cu on Pt, constant current: 0.1 A. On the other hand, under unbuffered electrolysis conditions, the ph of the medium increased from 6.9 to 13 within 30 min. This is because, NRR takes place by yielding hydroxyl ions as side products (see reactions (2) and (3)). In order to minimize the ph effects, the electrolysis experiment was next carried out under buffered conditions, where a flow of CO 2 was passed through the cathode chamber, which maintained a constant ph of 6.3 throughout the entire course of electrolysis. The reduction profile of a 0.05 M nitrate solution under buffered conditions is displayed in Fig. 9B. Under unbuffered conditions, the value of first order rate constant (k) was evaluated as min 1, which increased to min 1 in the presence of CO 2 buffer system. Regarding the products selectivity, an unbuffered system yielded nitrite (51%) and ammonia (23%) as the major 28

38 products. Under buffered conditions, these values decreased to 30% and 13%, respectively. The mass balance of nitrate, nitrite and ammonia indicates that unbuffered and buffered processes yielded 26% and 57% nonionic products (e.g. N 2, NH 2 OH), respectively. By analyzing samples of the gaseous phase, the evolution of molecular nitrogen was detected, although it could not be quantified exactly. At the end of the electrolysis, the catholyte was analyzed for hydroxylamine but the existence of this product could not be determined. This means that, besides nitrite and ammonia, the remainders of the products were gaseous. The increase in the value of k and the decrease of nitrite selectivity suggests that both nitrate and nitrite reductions were positively influenced by the CO 2 buffer action; the mechanism of how this influence happened needs further scrutiny. The density functional theory (DFT) studies report that for a pure Pt electrocatalyst, Pt OH is easily formed on the surface of Pt [36]. Thus the adsorbed OH species (produced at E2 and E3) may shield the mass transfer process. Sullivan et al. [37] reported that CO 2 molecules are effectively adsorbed onto Pt surface. Therefore, it could be assumed that the competitive affinity of CO 2 molecules toward Pt surface might have decreased the surface concentration of Pt OH species thus creating more room for nitrate ions to be adsorbed on the Pt Cu surface. Most probably, when CO 2 was purged through the catholyte, the following processes occurred in the cathode chamber: CO 2 + H 2 O H 2 CO 3 (7) H 2 CO 3 + OH H 2 O + HCO 3 (8) HCO 3 + OH 2 H 2 O + CO 3 (9) As the produced hydroxyl ions were consumed by the CO 2 buffer action the surface concentration of OH species must have become sufficiently low inhibiting the formation of unfavorable Pt OH species. Although CO 2 purging accelerates the NRR process, the mechanism is quite complex. Therefore, more active catalysts and reaction conditions were explored. Finally, the stability of the electrode assembly was examined. For this purpose, three consecutive electrolyses (180 min long) were carried out under unbuffered conditions using the same electrode assembly; the results show very similar outcomes in terms of both rate constant and product selectivity. This proves that the as prepared Cu Pt electrode is quite stable in attaining an effective NRR in neutral medium Surface analysis The surface analyses of the prepared Cu Pt electrode were carried out using energy-dispersive X-ray analysis (EDX) and scanning electron microscope (SEM). The deposited Cu layer showed a globular shape and the related EDX spectra confirmed that a bimetallic catalyst was indeed formed with a composition of ca. 68 at.% Cu, 22 at.% Pt and 10 at.% oxygen. For the investigation of any possible change in the surface morphology of the as prepared Cu Pt electrode upon NRR, SEM/EDX analysis was conducted after extensive electrolysis experiments both in the absence and in the presence of nitrate ions. After the first electrolysis in the background electrolyte (i.e. in the absence of nitrate), the Cu content was decreased (by ca. 2 3%). However, in the presence of nitrate ions there was no measurable change in the Cu content. This observation suggests that the slight decrease in Cu content was not due to NRR but rather could likely be attributed to the removal of some loosely bonded Cu particles accompanying HER. 4. CONCLUSION The effective catalytic NRR in neutral media was reported at a Cu Pt electrode prepared via the electrochemical deposition of Cu layer onto a Pt electrode surface. Several advantages of Cudeposited Pt electrode over pure Cu electrode were observed including a significant increase in cathodic current densities of 250% and a 300 mv positive shift of the effective NRR peak potential. Results from cyclic voltammetric measurements have shown that the NRR occurs via a two-step reduction mechanism and the number of electrons transferred in each step was confirmed by chronoampoerometry. A first two-electron step was followed by a second six-electron step to produce NO 2 and NH 3, respectively. Investigations of the reaction kinetics and thermodynamics proved that the observed effective NRR occurred preliminarily via an adsorption step followed by a subsequent electrochemical process. The introduction of CO 2 to the bulk electrolyte and the inclusion of Pd to the Cu Pt electrode improved the catalytic activities of NRR. Interestingly, no surface poisoning was observed at the as-prepared Cu Pt electrode in all experimental conditions performed in this study. In addition, the surface stability of Cu Pt electrodes was proved by using electrochemical and surface analysis techniques. ACKNOWLEDGEMENT University Grants Commission (UGC) of Bangladesh is highly acknowledged for financial support (Grant No. 29

39 6(76)/UGC/RSP/BKA/Chemistry(16)/2013/9844; M.A. Hasnat). Professor Masato Machida, Department of Chemical Engineering, Kumamoto University, Japan is acknowledged for supplying several required materials. Very special thanks to The Third Word Academy of Sciences (TWAS) for their support. REFERENCES 1. Ayala, L.O. Leal, L. Ferrer, V. Cerdà, Microchem. J. 100 (2012) J.W. Peel, K.J. Reddy, B.P. Sullivan, J.M. Bowen, Water Res. 37 (2003) N.F. Gray, Drinking Water Quality: Problems and Solutions, Wiley and Sons Ltd., New York, O.S.G.P. Soares, J.J.M. Órfão, J. Ruiz- Martínez, J. Silvestre-Albero, A. Sepúlveda- 5. Escribano, M.F.R. Pereira, Chem. Eng. J. 165 (2010) S. Kerkeni, E. Lamy-Pitara, J. Barbier, Catal. Today 75 (2002) G.C.C. Yang, H.-L. Lee, Water Res. 39 (2005) A. Garron, F. Epron, Water Res. 39 (2005) M.Z. Kassaee, E. Motamedi, A. Mikhak, R. Rahnemaie, Chem. Eng. J. 166 (2011) S. Mossa Hosseini, B. Ataie-Ashtiani, M. Kholghi, Desalination 276 (2011) M. Saiful Alam, M.A. Hasnat, M.A. Rashed, Md. Rezwan Miah, Islam S.M. Saiful, Electrochim. Acta 76 (2012) Y. Lou, Y. Shao, P. Li, Z. Li, Z. Niu, J. Electroanal. Chem. 624 (2008) Katsounaros, D. Ipsakis, C. Polatides, G. Kyriacou, Electrochim. Acta 52 (2006) M. Machida, K. Sato, I. Ishibashi, M.A. Hasnat, K. Ikeue, Chem. Commun. 0 (2006) M.A. Hasnat, M.R. Karim, M. Machida, Catal. Commun. 10 (2009) M.A. Hasnat, I. Ishibashi, K. Sato, R. Agui, T. Yamaguchi, K. Ikeue, M. Machida, 19. Bull. Chem. Soc. Jpn. 81 (2008) M.A. Hasnat, R. Agui, S. Hinokuma, T. Yamaguchi, M. Machida, Catal. Commun (2009) M.A. Hasnat, M.A. Islam, S.M. Borhanuddin, M.R.U. Chowdhury, M. Machida, J. Mol. Catal. A: Chem. 317 (2010) M.A. Hasnat, M.S. Alam, M.H.M.-U. Karim, M.A. Rashed, M. Machida, Appl. Catal. B: Environ. 107 (2011) G.E. Dima, A.C.A. de Vooys, M.T.M. Koper, J. Electroanal. Chem (2003) D. Reyter, D. Bélanger, L. Roué, Electrochim. Acta 53 (2008) S.N. Pronkin, P.A. Simonov, V.I. Zaikovskii, E.R. Savinova, J. Mol. Catal. A: Chem. 265 (2007) D. Reyter, G. Chamoulaud, D. Bélanger, L. Roué, J. Electroanal. Chem. 596 (2006) M.A. Hasnat, M.A. Rashed, S. Ben Aoun, S.M. Nizam Uddin, M. Saiful Alam, S. Amertharaj, R.K. Majumder, N. Mohamed, J. Mol. Catal. A: Chem (2014) G.E. Badea, Electrochim. Acta 54 (2009) O. Brylev, M. Sarrazin, D. Bélanger, L. Roué, Appl. Catal. B: Environ. 64 (2006) Z. Ogumi, S. Ohashi, Z. Takehara, Electrochim. Acta 30 (1985) Z. Ogumi, H. Yamashita, K. Nishio, Z.I. Takehara, S. Yoshizawa, Electrochim. Acta (1983) K. Otuska, I. Yamanaka, Appl. Catal. 26 (1986) G.R. Dieckmann, S.H. Langer, J. Appl. Electrochem. 27 (1997) G.R. Dieckmann, S.H. Langer, Electrochim. Acta 44 (1998) A.J. Bard, L.R. Faulkner, Electrochemical Methods: Fundamentals and Applications, 38. Wiley, New York, H. Ju, D. Leech, J. Electroanal. Chem. 484 (2000) B.K. Simpson, D.C. Johnson, Electroanalysis 16 (2004) M. Khairy, D.K. Kampouris, R.O. Kadara, C.E. Banks, Electroanalysis 22 (2010) N. Barrabés, J. Just, A. Dafinov, F. Medina, J.L.G. Fierro, J.E. Sueiras, P. Salagre, Y. Cesteros, Appl. Catal. B 62 (2006) J. Greeley, J.K. Nørskov, M. Mavrikakis, Annu. Rev. Phys. Chem. 53 (2002) B.P. Sullivan, Platinum Met. Rev. 33 (1989)

40 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh 3D HEAT TRANSFER THROUGH A SOLAR COLLECTOR UTILIZING VARIOUS NANOFLUIDS Rehena Nasrin, Salma Parvin and M.A. Alim Department of Mathematics, Bangladesh University of Engineering and Technology, Dhaka-1000, Bangladesh Solar energy is one of the best sources of renewable energy with minimal adverse impact on the environment. The forced convection in solar collector turned out to be a very significant topic of research during the past few decades. Commercial applications of solar collectors include swimming pool, space heating, car washes, military laundry facilities and eating establishments. Solar water heating systems are cost effective in comparison to other water heating systems that are expensive to operate. Solar collectors are most feasible in regions that have access to sunlight and are temperate at the same time. A 3D heat transfer model has been developed in which the experiment deals with direct sunlight, incident on transparent glass cover of a flat plate solar collector (FPSC). Various nanofluids namely water/copper oxide, water/alumina, water/copper and water/silver are considered heat transfer medium through flat plate solar collector. The governing partial differential equations have been solved using finite element method with Galerkin s weighted residual technique. In order to evaluate the temperature profile within the collector, the energy balance equation and heat transport equation have been solved numerically. Rate of heat transfer, average temperature, collector efficiency, mid-height temperature, mean velocity and mean outlet temperature for various nanofluids and base fluid (clear water) through the collector have been presented. It is observed from the study that the water based nanofluid with copper nanoparticles is more effective for the enhancement of heat transfer rate and collector efficiency in terms of cost effectiveness. 1. INTRODUCTION Solar energy, the radiant light and heat from the sun, have been harnessed by man since ancient times using a range of newly evolved technologies. Solar flat plate collectors are commonly used for domestic and industrial purposes and have the largest commercial application amongst various existing solar collectors. This is mainly due to their simple design as well as low maintenance cost. The fluids with solid-sized nanoparticles suspended in them are called nanofluids. The nanoparticles are applied in thermal filed in order to enhance transfer of heat from solar collectors to tanks with luggage compartments and also to induce proficiency of coolants in transformers. Karanth et al. (2011) numerically simulated a solar flat plate collector using Discrete Transfer Radiation Model. A 3D model of the collector involving a water pipe, an absorber plate, glass top and the air gap in-between the absorber plate and the glass top was modeled to facilitate conduction, convection and radiation simultaneously. Bég et al. (2011) performed a non-similar experiment which deals with mixed convection heat and species transfer along an inclined solar energy collector surface with cross diffusion effects, where the resulting governing equations were transformed and then solved numerically using the local nonsimilarity method and Runge-Kutta shooting quadrature. Manjunath et al. (2011) analyzed three dimensional conjugate heat transfers through unglazed solar flat plate collector. They used finned tubes and the heat transfer due to solar irradiation to the fluid medium, increased with an accelerated mass flow rate. Vestlund (2012) studied gas-filled flat plate solar collector. The gases examined were argon, krypton and xenon in his thesis paper. Manjunath et al. (2012) performed comparative study of solar dimple plate collector with flat plate collector. Their result described that the average exit water temperature was marked by an improvement of about 5.5 C for a dimple solar collector as compared to that of a flat plate solar collector. CFD analysis of solar flat plate collector was conducted by Ingle et al. (2013). He attempted to present numerical simulation of solar collector developed exclusively for grape drying. CFD * Corresponding Author: R. Nasrin rehena@math.buet.ac.bd

41 analysis of triangular absorber tube of a solar flat plate collector was performed by Basavanna and Shashishekar (2013). Here, the numerical results obtained using the experimentally measured temperatures have been compared with the temperatures determined by the CFD model. Very recently, Parvin et al. (2014) analyzed heat transfer and entropy generation through nanofluid filled direct absorption solar collector. The results presented in their study provided a useful source of reference for enhanced forced convection heat transfer performance, simultaneously reducing the entropy generation. Tagliafico et al. (2014) reviewed dynamic thermal models and CFD analysis for flat-plate thermal solar collectors. A review of solar collector models was presented, including a proper classification and description of main characteristics and performances in their study. Nasrin and Alim (2014) developed a semiempirical relation for forced convective analysis through a solar collector. A new correlation was derived from their results, which proved to be easy to use for heat transfer purposes. From the above literature review it can be attributed that a very few 3D numerical studies have been completed using the traditional fluids (water, gas, air etc.). It is necessary to monitor the variation of collector efficiency using different nanofluids along with the economic and environmental aspects. 2. PROBLEM FORMULATION A schematic diagram of the system in three dimensional as well as cross sectional view considered in the study is shown in Fig. 1. The system consists of a flat plate solar collector. The working fluid in the collector is water-based nanofluid containing different nanoparticles. The nanoparticles are generally spherical in shape and the diameter taken is 5 nm. The nanofluid is considered a single phase flow and surfactant analysis is neglected. The solar collector is a metal box with highly transparent and anti-reflected glass cover (glazing) on top and a dark colored copper absorber plate at the bottom. The dimensions of the absorber plate are 1m, 0.15m and m. The riser pipe has an inner diameter of 0.01m and a thickness of m. Coefficients of heat absorption and emission of copper absorber are 95% and 5% respectively. A trapezium shaped bonding conductance is located in the middle and placed at a distance one-third of the width of the absorber plate. It covers the three-fourth part of the riser pipe. It was as long as the absorber plate and tube and is made of copper metal. The computational domain is the copper absorber plate containing fluid passing through copper riser pipe with bonding conductance. The riser pipe is generally ultrasonically welded to the absorber plate. Fig. 1: Schematic diagram of the solar collector It can be considered that the flow is threedimensional and viscous dissipation is negligible. The nanofluids are assumed incompressible and the flow is considered to be laminar. It regarded that the water and nanoparticles are in thermal equilibrium and no slip occurs between them. Only steady state case is considered. The governing 3D equations are as follows: u v w 0 x y z u u u p u u u nf u v w nf x y z x x y z v v v p v v v nf u v w nf x y z y x y z w w w p w w w nf u v w nf x y z z x y z T T T nf 1 T T T u v w x y z f Pr x y z k Ta Ta T a 0 C p a x y z where, k C is the thermal nf nf p nf diffusivity, 1 is the density, nf f s Cp 1 Cp Cp capacitance, is the heat nf f s nf f is the viscosity of Brinkman Model (Pak and Cho, 1998), the thermal 32

42 conductivity of Maxwell Garnett (MG) model (1904) is k nf k f k 2k 2 k k s f f s k 2k k k s f f s The boundary conditions of the computation domain are: at all solid boundaries of the riser pipe: u = v = w = 0 at the solid-fluid interface: T T kf ka N N fluid solid at the inlet boundary of the riser pipe: T Tin, w = w in at the outlet boundary: convective boundary condition p = 0 at the top surface of the absorber: heat flux Ta ka q I U L T in Tamb z T at the other surfaces of absorber plate: a 0 N T at the outer boundary of riser pipe: a 0 N at the outer boundary of bonding conductance: T a 0 N ν f Here Pr is the Prandtl number and N is the α f distances either along x or y or z directions acting normal to the surface. The following dimensionless quantities are used to calculate rate of heat transfer x y z T Tin k f X, Y, Z, D D D qd The average heat transfer rate of the collector can be written as Nu S Nu ds k nf ds ds DL k f X Y Z s where L is the height of absorber tube. The mean bulk temperature and mean velocity of the fluid inside the collector may be written as T V av av v v v v TdV 4 2 dv DL VdV 4 2 dv DL v v S TdV and VdV where V and V are the volume of the absorber tube and magnitude of mean velocity respectively. The measure of a flat plate collector performance (17) is the collector efficiency (η) defined as the ratio of the useful energy gain (Q usfl ) to the incident solar energy. The instantaneous thermal efficiency of the collector is: useful gain Q F A I U T T usfl available energy AI AI F F U R R L R L in amb T in T I where I is solar radiation, T in and T amb are input and ambient temperatures, U l is local heat transfer coefficient, w in is input velocity of fluid, is transmission coefficient of glass cover and is absorption coefficient of absorber. amb 3. NUMERICAL FORMULATION The Galerkin finite element method by Taylor and Hood (1973) and Dechaumphai (1999) is used to solve the non-dimensional governing equations with boundary conditions in the study. Conservation equations have been solved using the finite element method to yield the velocity and temperature fields of the water flow in the absorber tube and the temperature fields of the absorber plate. The equation of continuity has been used as a constraint due to mass conservation and this restriction may be used to find the pressure distribution. The penalty finite element method is used to solve the governing equations, where the pressure p is eliminated by a penalty constraint. The continuity equation is automatically fulfilled for large values of this penalty constraint. Then the velocity components (u, v, w) and temperatures (T, T a ) are expanded by setting a basis. The Galerkin finite element technique yields the subsequent nonlinear residual equations. Gaussian quadrature technique has been used to evaluate the integrals in these equations. The non-linear residual equations are solved using Newton Raphson method in order to determine the coefficients of the expansions. The convergence of solutions is assumed when the relative error for each variable between consecutive iterations is recorded below the convergence n 1 n -6 criterion, such that 1.0e, where n is the number of iteration and Ψ is a function of u, v, w, T and T a. 3.1 Mesh Generation In finite element method, the mesh generation is the technique todivide a domain into a set of subdomains, called finite elements, control volume etc. 33

43 The discrete locations are defined by the numerical grid, where the variables are to be calculated. It is basically a discrete representation of the geometric domain for the problem to be solved. The computational domains with irregular geometries by a collection of finite elements make the method a valuable practical tool for the solution of boundary value problems arising in various fields of engineering. Fig. 2 displays the finite 3D element mesh of the present physical domain. Fine mesh size is chosen for this geometry. The thermophysical properties of water and nanoparticles are taken from Ogut (2009) and are given in Table 1. A 3D software named Comsol Multiphysics 4.3 is used to develop the 3D model. Fig. 2: Mesh generation of the collector Table 1. Thermo-physical properties of water and different nanoparticles at 295K Properties Water Ag Cu Al 2 O 3 CuO C p (J/kgK) (kg/m 3 ) k (W/mK) 10 6 (Ns/ m 2 ) α 10 7 (m 2 /s) Mesh Generation The arrangement of discrete points throughout the domain is called a grid. The determination of a proper grid for the flow through a given geometric shape is important. The process of determining such a grid is called grid generation. The grid generation is a significant consideration in CFD. Finite element method can be applied to unstructured grids. This is because the governing equations in this method are written in integral form and numerical integration can be carried out directly on the unstructured grid domain in which no coordinate transformation is required. The three dimensional computational domain is modeled using finite element mesh as shown in Fig. 2. The complete domain consists of 14,20,465 elements which include the riser tube and absorber plate. The mesh is composed of tetrahedron element with ten nodes. The grid independence test is performed to check quality of mesh on the solution. The influence of further refinement does not change the result by more than 1.25 % which is regarded as the appropriate mesh quality for computation. 4. RESULTS AND DISCUSSION Finite element simulation is applied to perform the analysis of laminar forced convection temperature and fluid flow through a riser pipe of a flat plate solar collector filled with different nanofluids. Effect of the solid volume fraction ( ) on heat transfer and collector efficiency of solar collector has been studied. In Dhaka, tilt angle of solar collector is 23.8, the mean solar irradiation (I) is W/m 2. The values of are taken as 0%, 1%, 2% and 3%, where mass flow rate m = 0.02 Kg/s, the area of collector A = 1.8 m 2, Pr = 6.6 and I = 230 W/m 2 are chosen as fixed. The plots of Nu, T av, mean velocity, mean outlet temperature (T out ), mid-height temperature of water- Cu nanofluid and η (%) versus solid volume fraction of four different nanofluids as well as base fluid are depicted in Fig. 3(i)-(vi). The rate of heat transfer mechanism is maximum for water-ag nanofluid. And then Nu devalues water-cu, water- Al 2 O 3, water-cuo nanofluids respectively. Heat transfer rate increases by 20%, 18%, 11% and 9% with the variation of from 0% to 2% respectively for Ag, Cu, Al 2 O 3 and CuO nanoparticles. Here Nu remains constant for water with the variation of. For all nanofluids mean Nusselt number rises sharply from 0% to 2% and heat transfer rate remains nearly constant during the escalation of from 2% to 3%. Thus, it is not always useful to introduce more solid volume fraction of nanoparticle with base fluid. The mean bulk temperature (T av ) grows sequentially for. It is well known that thermal conductivity of Ag nanoparticle is higher than others. Higher thermal conductivity is capable of carrying more heat. Thus average bulk temperature of water-ag nanofluid was found to be higher in Fig. 3(ii). There is no change of water ( = 0%) due to the deviation of nanoparticles volume fraction. The temperature of water-copper nanofluid in the middle of riser pipe is depicted in Fig. 3(iii). The fluid enters from the inlet and having received heat form solid surfaces of the riser exits from the outlet of the flat plate solar collector. The temperature 34

44 increases upto 2% with growing remains unchanged afterwards. The mean outlet temperature of fluids through a flat plate solar collector is shown in Fig. 3(iv). The mean output temperature grows up with increasing upto 2% and then remains constant. The sub-domain mean velocity field is shown in Fig. 3(v). Pure water has higher velocity than nanofluid. As density of nanoparticles are greater than water, their velocity decreases. With increasing solid volume fraction of nanoparticles velocity of nanofluid devalues. Fig. 3: Effect of nanofluids on (i) Nu, (ii) T av, (iii) T, (iv) T out (v) V av and (vi) 5. CONCLUSION The water-ag nanofluid with 2% solid volume fraction has the highest rate of heat transfer. The collector efficiency rises from 36% to 52 for water- Ag nanofluid for increasing from 0% to 2%. The temperature of all nanofluids increases steadily while passing through the pipe. Water/Cu nanofluid may be used for heat transfer medium through solar collector because Cu nanoparticles are more cost effective than Ag nanoparticles. REFERENCES 1. Karanth, K.V., Manjunath, M.S. and Sharma, N.Y. (2011), Numerical simulation of a solar flat plate collector using discrete transfer radiation model (DTRM) a CFD approach, Proc. of the World Cong. on Engg., London, U.K. 2. Bég, OA., Bakier, A., Prasad, R. and Ghosh, SK., (2011), Numerical modelling of nonsimilar mixed convection heat and species transfer along an inclined solar energy collector surface with cross diffusion effects, World J. of Mech., 1, pp Manjunath, M.S, Karanth, K.V. and Sharma, N.Y. (2011), Three dimensional numerical analysis of conjugate heat transfer for enhancement of thermal performance using finned tubes in an economical unglazed solar flat plate collector, Proc. of the World Cong. on Engg., London, U.K. 4. Vestlund, J., (2012), Gas-filled flat plate solar collector, Ph. D. Thesis, Building Services Engg., Dept. of Energy and Environ., Chalmers University of Technology, Gothenburg, Sweden. 5. Manjunath, M.S, Karanth, K.V. and Sharma, N.Y. (2012), A comparative CFD study on solar dimple plate collector with flat plate collector to augment the thermal performance, World Academy of Sci., Engg. and Tech., 6, pp Ingle, P.W., Pawar, A.A., Deshmukh, B.D. and Bhosale, K.C., (2013), CFD analysis of solar flat plate collector, Int. J. of Emerg. Techn. and Adv. Engg., 3 (4), pp Basavanna, S. and Shashishekar, K.S., (2013), CFD analysis of triangular absorber tube of a solar flat plate collector, Int. J. Mech. Eng. & Rob. Res., 2 (1), pp Parvin, S., Nasrin, R. and Alim, M.A., (2014), Heat transfer and entropy generation through nanofluid filled direct absorption solar collector, Int. J. of Heat and Mass Transf., 71, pp Tagliafico, I.A., Scarpa, F., Rosa, M.D. (2014), Dynamic thermal models and CFD analysis for flat-plate thermal solar collectors a review, Renew. and Sust. Energy Rev., 2 (30), pp Nasrin, R. and Alim, M.A.(2014), Semiempirical relation for forced convective 35

45 analysis through a solar collector, Solar Energy, 105, pp Pak, BC. and Cho, Y. (1998), Hydrodynamic and heat transfer study of dispersed fluids with submicron metallic oxide particle, Exp. Heat Trans., 11, pp Maxwell-Garnett, JC. (1904), Colours in metal glasses and in metallic films, Philos. Trans. Roy. Soc. A, 203, pp Taylor, C. and Hood, P. (1973), A numerical solution of the Navier-Stokes equations using finite element technique, Computer and Fluids, 1, pp Dechaumphai, P. (1999), Finite Element Method in Engineering, 2nd ed., Chulalongkorn University Press, Bangkok. 15. Ogut, EB. (2009), Natural convection of waterbased nanofluids in an inclined enclosure with a heat source, Int. J. of Thermal Sciences, 48 (11), pp

46 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh A SYSTEM ANALYSIS APPROACH FOR MODELING THE DELIVERABILITY OF A GAS CONDENSATE WELL Tanvir Ahmed, Farhana Akter and Mohammad Mojammel Huque Department of Petroleum and Mineral Resources Engineering, BUET, Dhaka This paper describes the modeling procedure for determining the deliverability of a gas production system in a vertical well. The deliverability or performance of a gas production system is represented by the production rate, which depends on the reservoir s deliverability while producing fluids at the sand face and the well s vertical lift performance (VLP). The reservoir s deliverability (fluid flow through porous media) can be modeled with accuracy by a reservoir simulator and the VLP of a well can be predicted using a well model. A well model is an essential component of any production system analysis. This model requires a relationship that describes the inflow of fluid to the wellbore and the VLP curve that determines well deliverity. For the analysis of Well -1, a gas condensate reservoir located in the eastern part of Bangladesh, was selected for the case study. This well has been functioning since 1983 and is a gas condensate producer with a condensate gas ratio (CGR) of 8 to 11 STB/MMscf and water gas ratio (WGR) of 0.1 to 0.4 STB/MMscf. It has a production rate of 20 MMscfd gas and the producing well head pressure is 2680 psig with 4.5 inch tubing. The production rate calculated by the model for a given wellhead and reservoir pressure is within 2.5% of the real field data. This study shows the optimum operating flow rate to be 22 MMscfd, optimum separator condition of 700 psig, and optimum separator temperature 70o F with a well head pressure measuring 2766 psig. This model can be used for predicting future well performance. 1. INTRODUCTION The essential components of any gas production system are: the reservoir, the wellbore, tubing and casing, Packers, Chokes and valves, the flow line and separators. During the flow of fluids through the system pressure losses occur at various points (Fig. 1). These pressure losses govern the deliverability of the system. The most effective method of calculating the pressure drop at any point is the NODAL analysis in which the production system is separated into several nodes for efficient calculation of the pressure losses (Beggs, 2003). An Integrated petroleum production system model can be divided into three separate modules: a reservoir simulator, the well models and the surface production, processing and transportation network. A well model simulates the flow of fluids from the sandface to the wellhead. There are various empirical correlations available for the tubing flow performance (or VLP) assessment. As the applicability of the correlations depends on the prevailing conditions in the well, there is no universal correlation for this. The selection of a particular correlation, therefore, requires engineering judgment and coherence /to the real field production data. Once a correlation is selected, it is required to adjust it with the performance of a specific well. The well selected for case study is located in one of the major gas fields of Bangladesh. There are three main gas zones in the field ranging from about 2280 m to 3045m below the surface. The gas sands are referred as the Upper ( ft), Middle ( ft) and Lower ( ft) gas sands. The production from this well started in 1983 as well-01 (WELL-1) was opened to function as a dual producer from the UGS and LGS. In 1988 it stopped producing from the UGS and due to excessive water production (500 STB/d) and high WGR (40 STB/MMSCF), the production from the LGS was stopped. Workover project was undertaken to complete the well in the MGS in Since then the well is reported to be under production. A total of BCF gas, MSTB of condensate has been produced from this well (upto September, 2010). An industry standard software package was used to set up the well model. * Corresponding Author: Farhana Akter, farhana_akter@pmre.buet.ac.bd

47 2. METHODOLOGY The primary objective of a well model is to match and predict well performance accurately. This is accomplished by formulating the governing equations of fluid flow through the entire production system. The mathematical relationship, for the ease of application, can be divided into two parts at the sandface (solution node): inflow and outflow. The inflow of fluids to the wellbore, also known as the Inflow Performance Relationship (IPR), represents the reservoir s deliverability to produce at the sandface. The outflow denotes the Vertical Lift Performance (VLP) or tubing performance of the well. These relationships are shown by curves and the intersection of the IPR and VLP curve defines the system s deliverability as shown in Fig. 2. size/valves/restrictions), surface flow line data (length, ID, safety valves/restrictions etc.) and the separator operating conditions. Based on the availability of the fluid property data either a Black oil model or a Compositional model can be set up. The compositional model uses an equation of state (EOS) to determine the composition and fluid phase under varying pressure and temperature conditions. The modelling procedure is outlined in Fig PVT input A compositional retrograde gas condensate model was set up. The composition is given in Table 1. The phase diagram for this composition confirmed that the reservoir fluid was retrograde condensate (Danesh, 1998) and the saturation pressure was about 2750 psig at the reservoir temperature which means at reservoir condition the fluid was single phase gas. The Peng-Robinson EOS method was selected for PVT calculation. For the separator pressure and temperature of 510 psig and 95 o F respectively, the measured GOR was SCF/STB (CGR= STB/MMSCF). The calculated Gas-Oil-ratio (GOR) was SCF/STB (condensate-gas-ratio, CGR= STB/MMSCF), which was showed congruence with the measured data. Fig. 1: Pressure losses at various components in the production system (Beggs, 2003) Fig. 2: Determination of system flow capacity In order to generate the VLP and IPR curves and set up a well model, it is required to input reservoir rock and fluid property data: porosity, permeability, fluid type and PVT properties; Well geometry/configurations: well type (vertical/directional), wellbore radius, completion type, completion interval, tubing and casing ID, position and specification of SSSV/flow restrictions, wellbore flow type (tubing/annular/ tubing+ annular); well test data: Average reservoir pressure, wellhead pressure and corresponding flow rates; wellhead assembly (choke Fig. 3: Well modelling procedure (Petroleum Experts, 2003) Fig. 4: Phase diagram of the reservoir fluid 38

48 Table 1. Reservoir fluid composition used in the well model Component Mole percent N CO C C C ic nc ic nc C C Total= Inflow Performance Relationship (IPR) For IPR calculation, Petroleum Experts method was selected. This method uses a multiphase pseudo pressure function to calculate the inflow of fluids. The data from a well test are tabulated below: Table 2. Data for IPR Parameter Input values Reservoir pressure psig Reservoir Temp o F WGR 0.21 STB/MMSCF Total GOR SCF/STB Permeability 148 md Reservoir Thickness 90 feet Wellbore Radius feet Skin factor 3 65 feet (from a depth of Perforation interval , and ft.) Reservoir porosity 0.21 The model history matched with a multi-rate drawdown test data as shown in Table-3. The data of Test Rate 1 were used to adjust the VLP correlation and the IPR. Then the adjusted model was used to reproduce Test Rate 2. Table 3. Well test data (November 2007) Parameter Test Rate 1 Test Rate 2 Gas Rate (MMSCFD) Wellhead Press. (Psig) Wellhead Temp. ( o F) WGR (STB/MMSCF) GOR (STB/MMSCF) Gauge depth (ft) Gauge Pressure (Psig) A number of correlations are available for the tubing flow calculation ( Economides et. al., 1994, Brill and Mukherjee, 1999) for different fluid. The Hagedorn-Brown correlation, the Beggs and Brill correlation and Petroleum experts 2 were selected for analysis as shown in Figure 6. The correlation comparison was run to check the applicability of selected correlations and choose the best one. It also provided a check on the well test data. If the measured pressure deviates too much from the correlation, it means the well test data are incorrect or the model set-up is wrong. In this case there was a reasonable agreement between the correlation and well test data. The IPR curve in Figure 5 shows that the Open flow potential of the well was 373 MMSCFD with a skin value of 3. Fig. 6: Correlation comparison plot Fig. 5: IPR curve for the well 2.3 Model Validation The correlations were adjusted by non-linear regression for fluid properties as well as frictional loss component in the vertical lift performance, so that they match the real field production (Petroleum Experts, 2003). Table-4 summarizes the results of the regression. Petroleum experts 2 correlation required less adjustment for fluid properties and was selected for this model. IPR was tuned so that the intersection of VLP and IPR fit the well test rate measurement. Using the 39

49 adjusted correlation, the model calculated the deliverability of the well for the wellhead pressures of the Test Rate 1 and Test Rate 2. Table 5 lists the matching data. Correlation Hagedorn Brown Beggs and Brill Petroleum Experts 2 Pwh (Psig) Table 4. Correlation comparison PVT correction Friction loss correction Standard Deviation Table 5. Matching comparison Measured Gas Rate (MMSCFD) Calculated % difference The model is validated with around 2.5% error in the gas production rate. Finally this model was used for the optimization analysis. 3. OPTIMIZATION OF THE PRODUCTION SYSTEM COMPONENTS Typically production engineers have used nodal system analysis and liquid load up rate calculations along with rules of thumb to analyze well performance choose the optimum from a set of different alternates (Schlumberger, 2014, Hams, 2005). 3.1 Optimum Separator Condition The selection of separator pressure and temperature generally depends on the sales line pressure, compression facility and its capacity and mostly on the pressure and temperature that yield the maximum amount of condensate. From the well test report it was found that the separator was operated at psig and o F. Finally the processed gas is boosted up to around 1000 psig to be fed into the national transmission grid. The compositional analysis with PVTP was used to find the optimum separator condition. Table 6 shows the effect of temperature with the separator operating pressure for condensate production. The optimum operating condition for the separator would have been psig and 70 o F. 3.2 Effect of Tubing Size Table 7 shows the effect of tubing sizes on flow rate for wellhead pressure, P wh = 2780 psig. The flow rate can be increased by increasing the tubing size but a tubing size too large might lead to liquid loading in the future. Table 6: CGR for different separator operating conditions Condensate Gas Ratio (STB/MMSCF) at Temperature separator pressures (psig) ( o F) 500 psig 700 psig 900 psig 1000 psig Table 7: Flow rates for different tubing sizes Tubing size (inch) Flow rate (MMSCFD) (existing) (casing production) In this study, the gas production rate was constrained by the gas processing facility. The produced gas was being processed through a 30 MMSCFD Solid desiccant (Silica gel) dehydration plant. At the same time production from WELL-5 was also processed by this plant. The production from WELL-5 was in the range of 6-10 MMSCFD. Therefore the maximum production rate for WELL- 1 was in the range of MMSCFD. The production rate should be maintained in the best possible way so that the flowing bottom hole pressure does not fall below the Dew point pressure and ensures the maximum condensate recovery [ 8]. Assuming an average flow rate of 22 MMSCFD, the sensivity of wellhead pressure is shown in Table 8 for different tubing size. A larger tubing size would have been able to maintain this flow rate for longer period of time at a high wellhead pressure. Table 8. Pwh for different tubing size for 22 MMSCFD gas flow rate Flowing Wellhead Tubing size (inch) Pressure, P wh (psig) The Effects of Perforation Interval and Skin Factor 40

50 The sensivity analysis for skin factor and perforation interval is shown in Table 9. For a given wellhead pressure, increasing the perforation interval does not improve the productivity but removal of skin would have slightly increased the flow rate. Table 9. The effects of perforation interval and skin factor, Pwh=2780 psig Perforation interval (ft) 65 (existing) 90 (net pay) 4. DISCUSSION Flow rates (MMSCFD) for different Skin factors S = 3 S= 0 S= -5 (existing) When the flowing wellbore pressure or reservoir pressure falls below the dew point pressure, the composition of the reservoir fluid changes as liquid dropout starts in the reservoir and until the critical saturation is reached the liquid will not flow. This change in composition will require a change in the IPR and VLP calculation methods. Therefore, this model will have to be adjusted using well test data periodically as reservoir pressure changes. 5. CONCLUSION The constructed well model simulated the actual production and was accurate within a range of 2.5% of the real field production. The well was not producing at its optimum capacity during the time of the well test. The production rate can be increased by increasing the capacity of the gas processing facility, operating the separator at the optimum parameters, increasing perforation interval and removing skin. Considering the small effect of the skin in production rate, removing skin is not necessary at present operating condition. However, this may affect the production significantly if and when condensate banking occurs in future. Therefore, workover and well stimulation can be considered in near future. The existing tubing size (4.5 inch) will be acceptable considering larger tubing might suffer from liquid loading problem once reservoir pressure becomes lower. The optimum production rate is found to be 22 MMSCFD and optimum separator temperature is 70oF with an operating pressure of 700 psig. This well model can be linked to a numerical reservoir simulator in order to perform prediction of future production scenario and also optimization of the production system REFERENCES 1. Beggs, H. Dale (2003), Production Optimization using nodal analysis, 2nd edition, OGCI, Petroskills. 2. PROSPER Operation Manual, Petroleum Experts, Danesh, A. (1998), PVT and Phase Behavior of Petroleum Reservoir Fluids, Elsevier. 4. Economides, M. J., Hill, A. D. and Economides, C. E. (1994), Petroleum Production Systems, Prentice Hall, NJ. 5. Brill, P. and Mukherjee, H. (1999), Multiphase flow in wells, SPE. 6. Pipesim Well Performance Modeling, Schlumberger, Hams, K.K. SPE, ConocoPhillips, Better Result Using Integrated Production Models for Gas Wells, SPE 93648, presented in SPE Production and Operation Symposium, Oklahoma, USA Shi, C., Home, R. N. and Li, K. (2006), Optimizing the Productivity of Gas/Condensate Wells, SPE , presented in SPE Annual Technical Conference, Texas, USA,

51 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh RESERVE ESTIMATION OF THE PRODUCING GAS SANDS OF A GAS CONDENSATE RESERVOIR IN BANGLADESH Tanvir Ahmed and Farhana Akter Department of Petroleum and Mineral Resources Engineering, BUET, Dhaka Reserve estimation is the process by which the economically recoverable hydrocarbons in a field, area, or region are evaluated quantitatively. It is the pre-requisite for the development and planning of a gas field. Simultaneously it plays a vital role for predicting future production performance and formulating depletion scenarios. The common techniques for reserve estimation are the material balance method, the production declinecurve analysis andand the volumetric reserve estimation. The material balance method is simply the law of conservation of mass, which not only estimates the gas initially in place (GIIP) and recoverable reserve but also provides insights on the reservoir drive mechanism. The decline curve analysis method, which is generally applied to single well, assumes that the future production will follow the past trends and uses the production data to fit an empirical rate/time decline equation to estimate GIIP in the drainage area of the well. Various decline type curves are also available that use analytical solutions of the diffusivity equation. In this study both of these methods and their modified forms, based on their applicability, are used to estimate the GIIP of the upper gas sand (UGS) and the middle gas sand (MGS) of a gas field in Bangladesh. The analysis suggested that the UGS might be under water drive. The results were compared and concurred with the volumetric estimates earlier made. The total reserve obtained from above mentioned methods for the producing gas sands was ranging from 1.7 to TCF. 1. INTRODUCTION Hydrocarbon reserves are defined as the volume of hydrocarbon accumulation commercially recoverable under a given economic condition and available technology. As economy changes and technology advances with time the reserve for a field also changes making the estimation of reserves a continuous study. Therefore, the general practice is to revise the estimated reserves as more data becomes available. Since the development and planning as well as the future performance and depletion strategies of a gas/oil field greatly depend on the available reserve, this decisive parameter necessitates to be known as accurately as possible. The reservoir selected for case study is located in the eastern part of the country. The field is a gas condensate field and has been contributing increasingly to the national gas grid over the years since it was brought on stream in There are three main gas zones (Upper, Middle and Lower) in the field at depths ranging from about 2280m to 3045m below the surface. There has been significant variation of the thicknesses of the gas sands well to well. The porosity-permeability properties of the sand reservoirs are good to excellent. By October 2009, 482 BCF gas with MMSTB condensate and 1.138MMSTB of water has been produced. Currently there are 6 producing wells in the field and the average daily production is 64 MMSCFD. There were variations in the GIIP and reserves estimates reported in different studies (by the volumetric method). Table-1 summarizes the results. Table-1: GIIP and reserves estimated by different studies [2, 3]. Study by IKM (1989) Welldrill (1991) HCU- NPD (2002) GIIP (BCF) MGS Reserve (BCF) GIIP (BCF) UGS Reserve (BCF) (2P) (2P) 967 * Corresponding author: Farhana Akter farhana_akter@pmre.buet.ac.bd

52 2. MATERIAL BALANCE ANALYSIS 2.1 Material balance on MGS production: The production from MGS started on May 1995 from the well-3. The production from this well stopped on March 2004 due to excessive water production. Up to 2009, two wells (well-1 and well- 4) were under production. The production data (Table-2) were used to construct a P/Z plot [6] (Fig-1). Most of the average reservoir pressure points were calculated from the Shut-in wellhead pressure by average temperature and pressure method [5]. The linear trend of the points was extrapolated to calculate the GIIP. The GIIP for the MGS was BCF. Time (d/m/y) Table 2: Data for P/Z analysis Reservoir Pressure (psig) G p (MMSCF) P/Z (psig) 12/5/ /4/ /11/ /1/ /8/ /12/ /7/ A complete production system analysis was performed and from the production forecast for different depletion scenarios the recovery factor was found to be within 75-80% for this gas sand at an abandonment well head pressure of psig. Therefore the reserve for this gas sand was estimated at BCF. production from both UGS and LGS. In 1995 the production from well-1 was stopped because of excessive water production. According to the data available up to October 2009, there were three producing wells (well-2, well-3, and well-6) in the UGS. The P/Z plot for the UGS production showed the GIIP of 5.49 TCF which was more than twice the volumetric estimates earlier made. The initial reservoir pressure was 3318 psig and according to the well test analysis report on December 2007, the average reservoir pressure was 3215 psig. The pressure decline was only 3.10% of the initial reservoir pressure. The gas sand had been producing for 24 years and by this time BCF gas along with 1.73 MMSTB condensate was produced. Also, it was reported that the GWC was at 7670 feet depth from the surface [2, 3]. So, the pressure maintenance must have been due to the presence of an aquifer. The reservoir structure was described as a four way dip closure so the aquifer could not be radial or linear. From the core log report it was observed that there was approximately 1100 feet of water bearing sand below the UGS, but there was no conclusive information about the existence or the extent of the aquifer. Analysis was continued assuming a bottom-waterdrive system with a finite acting (an aquifer with sealed boundary) aquifer model. The Hurst-van- Everdingen modified method was selected for water influx calculation. The aquifer model was adjusted by non-linear regression to match the production and the GIIP was calculated from the F/E t vs. W e /E t plot [1, 6]. Fig. 1: P/Z plot for MGS. 2.2 Material balance on UGS production: The gas production from this gas sand started on June 1983 as the well-1, a dual producer, started Fig. 2: P/Z plot for UGS Finite acting aquifer model: From trial and error calculation by regression analysis the amount of water influx, Gas-in-place, aquifer volume and aquifer permeability were calculated. The F/E t vs. W e /E t plot (Fig. 4) was drawn with the calculated 43

53 water influx and a straight line was obtained with unit slope. The GIIP was found to be TCF. The analytical method plot (Fig.3) showed the results of the regression analysis. Fig. 3: Analytical method plot. A production system analysis for the UGS showed that with the existing depletion strategy the ultimate recovery ranged from 65-72% of the GIIP so the recoverable reserve ranged from 998 to 1105 BCF. The abandonment reservoir pressure ranged from psig. of 1000 psia. The results of different methods are summarized in table APPLICATION OF ADVANCED METHODS 3.1 Overview The advanced methods used in this study includes the Blasingame type curves (Ref), Agarwal- Gardener(Ref) type curves and the flowing material balance method (flowing P/Z method and Agarwal- Gardner flowing material balance analysis). These methods are generally applied on a single well basis i.e. they are applied to estimate the gas in place and reserves in the drainage area of a producing well. In a multi well pool with no pressure support, simultaneous production from the wells will lead to virtual no-flow boundaries which will result in boundary dominated flow for the wells as long as the depletion strategy remains the same. Summation of the reserves for the producing wells will give the reserves of the entire pool or reservoir [4, 5]. 3.2 Advanced methods applied on WELL-1 production The production data were used for the rate transient analysis. The production data plotted on Blasingame type curve plot (Fig.5) showed inconsistency and were scattered. However, the downward trend of the data towards the single stem of the curves suggested boundary dominated flow. Fig. 4: F/E t vs. W e /E t plot. Inconsistent and unreliable points were filtered and from production history the data of the most stable production interval were selected for the calculation of the gas-in-place and reserve for this well. From the matching, the GIIP in the drainage area was found to be BCF with an expected ultimate recovery of 569 BCF with a recovery factor of 76% for abandonment wellhead pressure Fig. 5: WELL-1 production data plotted on Blasingame type curves. Production data plotted on Agarwal-Gardner type curves had similar trend as in the Blasingame type curve plot (Fig. 5). This was because the type curves were generated from the same basic principles of reservoir engineering. Once again, filtered data were used for analysis. The data points 44

54 matching with the single depletion stem of the type curves was the sign of boundary-dominated-flow. This validated the applicability of the advanced methods. Fig. 8: Flowing P/Z method plot. Fig. 6: Blasingame type curve analysis on WELL-1 production data suggested boundary dominated flow. Fig. 9: Agarwal-Gardner flowing material balance analysis plot (WELL-1). Fig. 7: Agarwal-Gardner type curve analysis on WELL-1 production data. 3.3 Advanced methods applied on WELL-4 production Similar methodology (as well-1) was followed for the production data analysis of KTL-4 in the advanced methods. Most of the production data points were excluded by the data filtering process. The remaining data followed the declining trend of the single stem on the Blasingame and Agarwal- Gardner type curves plot (Fig. 10 and Fig. 11) which is indicative of pseudo-steady-state flow regime i.e. the boundary effect. The Flowing P/Z method and Agarwal-Gardner flowing material balance analysis are alternate analyses based on the same principle of boundary dominated flow equations. Therefore, both of the analysis should agree on the results, in other words if a good match is obtained in Agarwal-Gardner flowing material balance analysis plot then the Flowing P/Z method plot must have a good match, similar trend with the data points and vice versa. For this well the two plots were compatible (Fig. 8 and Fig. 9). Also, both of them had downward data trend indicating boundary dominated flow regime. Fig. 10: WELL-4 production data had a good match in Blasingame type curve plot. 45

55 The production data from WELL-2, WELL-3 and WELL-6 were entered in Blasingame type curve analysis plot. The insufficiency and poor quality of the data didn t permit further analysis in advanced methods. 4. DISCUSSION Fig. 11: Agarwal-Gardner type curve analysis on WELL-4 production data. The matching and results of Agarwal-Gardner flowing material balance analysis and Flowing P/Z method plot (Fig. 12 and 13) also showed consistency with the declining trend of the data present, validating the applicability of the methods. Fig. 12: Agarwal-Gardner flowing material balance analysis plot (WELL-4). The material balance calculation mostly depends on the accuracy of the production data and average reservoir pressure. In this analysis most of the reservoir pressure points are calculated from shut-in wellhead pressure with the assumption that the shut-in bottom-hole pressure equals the reservoir pressure, which is a good approximation for a reservoir with good transmissibility. The aquifer model for the UGS material balance analysis is only a mathematical model that matched the production history but the calculated parameters couldn t be verified as there was not enough relevant data available. Nevertheless with more future production data this model can be justified or adjusted to produce more accurate results. For better GIIP and reserve estimates the following points should be considered: Production data should be properly recorded and analyzed for future use in reserve estimation. Well tests should be performed to determine the average reservoir pressure and reservoir properties. Particularly, it is imperative to take extensive pressure survey in the upper gas sand for the identification of the reservoir drive mechanism. The water bearing zone in contact with the UGS should be investigated for the identification of the source of pressure support and possible aquifer parameters for the development of proper reservoir model. 5. CONCLUSION Fig. 13: Flowing P/Z method plot (WELL-4). In this study, reserves were estimated from production engineering perspective regardless of the prevailing economic and operating regulations. The reserves estimated for MGS using the different methods showed convergence and the estimated reserves for UGS was realistic considering the previous estimates in volumetric methods. 46

56 Analysis Name Table-4: Summary of Advanced method analysis on WELL-1 Original Gas-In- Place (MMMscf) Ultimate Recoverable Gas (MMMscf) Cumulative Gas Production (MMMscf) Remaining Recoverable Gas (MMMscf) Gas Recovery Factor (%) FMB-Gas Gas-AG-Radial Gas-Blasingame-Radial Analysis Name Table-5: Summary of Advanced method analysis on WELL- Original Gas-In- Place (MMMscf) Ultimate Recoverable Gas (MMMscf) Cumulative Gas Production (MMMscf) Remaining Recoverable Gas (MMMscf) Gas Recovery Factor (%) FMB-Gas Gas-AG-Radial Gas-Blasingame-Radial Analysis Name WELL-1 GIIP (BCF) Table-6: Summary of advanced methods analysis. WELL-4 GIIP (BCF) GIIP WELL- 1+GIIP WELL-4 (BCF) WELL-3 produced gas before abandonment (BCF) GIIP of MGS (BCF) Ultimate Recoverable Gas (BCF) FMB-Gas Gas-AG- Radial Gas- Blasingame- Radial REFERENCES 1. B.C. Craft and Ronald E. Hawkins (1991), Applied Petroleum Reservoir Engineering, Prentice Hall, NJ. 2. Badrul Imam (2005), Energy Resources of Bangladesh, University Grants Commission of Bangladesh. 3. Bangladesh Gas Reserve Estimation 2003 (2004), HCU-NPD. 4. Chi U. Ikoku (1992), Natural Gas Reservoir Engineering, Krieger Publishing Company, Florida. 5. Jhon Lee and Robert A. Wattenbargar (1996), Gas Reservoir Engineering, SPE Textbook Series, Volume 5, TX USA. 6. L. P. Dake (1978), Fundamentals of Reservoir Engineering, Elsevier, Amsterdam. 7. Petrobangla Annual Report SGFCL well summary report. NOMENCLATURE: G = GIIP = Gas initially in place (BCF/TCF) G p =Cumulative Gas Production (MMSCF) TCF = Trillion cubic feet BCF =Billion standard cubic feet MMSCFD= Million standard cubic feet per day UGS = Upper Gas Sand MGS = Middle Gas Sand GWC = Gas Water Contact 47

57 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh EFFECT OF CHEMICAL REACTION ON HEAT AND MASS TRANSFER IN A PARALLEL PLATE REACTOR CHANNEL WITH HEATED CYLINDERS Salma Parvin*, Rehena Nasrin, M.A. Alim and N. F. Hossain Department of Mathematics, Bangladesh University of Engineering and Technology, Dhaka-1000, angladesh The effect of chemical reaction on double-diffusive mixed convection in a parallel plate reactor channel with constant heat source is analyzed numerically. The fluid flow enters from the left inlet and exits from the right. After entering the reactor, the fluid passes four constantly and uniformly heated cylinders. The developed mathematical model is governed by two-dimensional continuity, momentum, energy and concentration equations. The governing equations, written in non-dimensional form are solved by using Galerkin finite element method with triangular grid discretization system. Numerical simulations are carried out for different combinations of the reaction parameter and results are presented in terms of velocity temperature and concentration distributions. The velocity, temperature, concentration and rate of heat and mass transfer are evaluated numerically for different values of reaction parameter. 1. INTRODUCTION Mixed convection heat and mass transfer problems with chemical reaction are of importance in many processes and have, therefore, received a considerable attention in recent years. Heat and mass transfer occur simultaneously in various processes including drying, evaporation at the surface of a water body, energy transfer in a wet cooling tower and the flow in a desert cooler, in chemical reaction engineering etc. Combined heat and mass transfer from a horizontal channel with an open cavity heated from below is numerically examined by Brown and Lai [1]. Parvin et al. [2] analyzed, numerically, the effect of doublediffusive natural convection of a water Al 2 O 3 nanofluid in a partially heated enclosure with Soret and Dufour coefficients. Azad et al. [3] investigated double diffusive mixed convection in an open channel with a circular heater on the bottom wall. They found that, average Nusselt number at the heat source decreases and overall mass transfer rate in terms of average Sherwood number increases with the rising of Lewis number. Muthucumaraswamy and Ganesan [4] studied the effect of chemical reaction and injection on flow characteristics in an unsteady upward motion of an isothermal plate. Deka et al. [5] studied the effect of the first order homogeneous chemical reaction on the process of an unsteady flow past an infinite vertical plate with a constant heat and mass transfer. Chamkha [6] studied the MHD flow of a numerical of uniformly stretched vertical permeable surface in the presence of heat generation/absorption and a chemical reaction. He assumed that the plate is embedded in a uniform porous medium and moves with a constant velocity in the flow direction in the presence of a transverse magnetic field. Ibrahim et al. [7] studied the effect of chemical reaction and radiation absorption on the unsteady MHD free convection flow past a semi-infinite vertical permeable moving plate with heat source and suction. Kesavaiah et al [8] studied the effect of the chemical reaction and radiation absorption on an unsteady MHD convective heat and mass transfer flow past a semiinfinite vertical permeable moving plate embedded in a porous medium with heat source and suction. Heat and mass transport in tubular packed reactors at reacting and non-reacting conditions was analyzed by Koning [9] where the most common models of wall-cooled tubular packed bed reactors were presented. The two dimensional axial plug flow model was used for a water gas shift reactor to compare heat conduction or mass diffusion with convective effect. Kugai [10] studied heat and mass transfer in fixed-bed tubular reactor. The two dimensional axial plug flow model was used for a water gas shift reactor to compare heat conduction or mass diffusion with convective effect in his study. * Corresponding author: Salma Parvin salpar@math.buet.ac.bd

58 In this paper, the effect of chemical reaction on mixed convective heat and mass transfer flow of a viscous electrically conducting fluid through a parallel plate reactor channel in the presence of constant heat source is investigated. The governing equations are solved by using Galerkin finite element technique. The velocity, temperature, concentration and rate of Heat and Mass transfer are discussed for different variations of reaction parameter. 2. ANALYSIS 2.1. Physical Model The domain under analysis is, as sketched in Figs. 1(a)-(b), a two-dimensional cross section of a reactor channel of length L and height H with four heated tubes each of radius r, suffering the influence of a gravitational field. The centers of the heaters are located at (L/5, H/2), (2L/5, H/2), (3L/5, H/2) and (4L/5, H/2). The heaters are maintained at constant and uniform temperature T h. The air flow is entering from the left with velocity U i, temperature T i and concentration C i, then passes the tubes and then the polluted hot air exhausted from the outlet opening at the right. Continuity equation U V 0 X Y X-momentum equation 2 2 U U P 1 U U U V 2 2 X Y X Re X Y Y-momentum equation 2 2 V V P 1 V V U V Ri NC 2 2 X Y Y Re X Y Energy equation U V H 2 2 X Y RePr X Y Concentration equation 2 2 C C 1 C C U V KC 2 2 X Y RePrLe X Y The above equations are non-dimensionalized by using the following dimensionless variables x y u v p X, Y, U, V, P, L L Ui Ui U T Ti c Ci, C T T c h i 2 i and the dimensionless parameters are Reynolds number (Re), Grashof number (Gr), Richardson number (Ri), Prandtl number (Pr), Lewis number (Le), the buoyancy ratio (N), heat source parameter (γ) and chemical reaction parameter (K) and they are defined as follows: Fig-1(a). 3-D geometry of the considered reactor Fig-1(b). Schematic diagram of the problem 2.2. Mathematical Model The governing mass, momentum, energy and species conservation equations have been presented by Deng et al. [11] for double-diffusive mixed convective flows driven by the combined effect of the internal buoyancy induced from temperature and concentration differences and the external mechanical driven forced flow from the inlet port. Using the Boussinesq approximation, the dimensionless governing equations under steadystate condition are given by: 3 UL g i T Th Ti L Gr Re Gr Ri 2 2,, Re, c ch ci 2 Pr Le N QL, D T Th Ti,,, 2 kl K D where,, D, k and Q are kinematic viscosity, thermal diffusivity, solutal diffusivity, reaction coefficient and strength of heat generating source respectively. The buoyancy ratio measures the relative importance of solute and thermal diffusion in creating the density difference to drive the flow. It is clear that N is zero for pure thermally driven flows and infinity for pure solute driven flows. The boundary conditions are at the inlet: U 1, V C 0 C 1, 0 at the circular tube walls: n, 49

59 C 0 0 at other surfaces: n, n at all solid boundaries: U V 0 where n is the non-dimensional distances normal to the surfaces. The average Nusselt and Sherwood number may be expressed as 1 S 2 2 Nu ds S X Y 0 and in region between the circular heater and the channel wall. The streamlines become more condensed along the middle of the channel due to increasing chemical reaction effect. This indicates higher velocity S C C Sh ds S X Y where S is the non-dimensional heated/contaminant surface. length of the Fig-2. Effect of K on streamlines 3.COMPUTATIONAL METHODOLOGY Galerkin weighted residual method of finite element formulation is used to solve the governing equations for the present work. The application of this technique is well documented by Zienkiewicz and Taylor [12]. The nonlinear parametric solution technique is chosen to solve the governing equations. This approach will result in substantially fast convergence assurance. In addition, the absolute convergence criteria are set to be 10-4 for velocities, energy and concentration. Fig-3. Effect of K on isotherms 4. RESULTS AND DISCUSSION The present investigation was carried out for chemical reaction parameter K (= 0.01, 0.1, 1 and 5) with Ri = 1, Re = 100, Pr = 0.7, Le = 1, N = 1, γ = 5. Now in the following section, a detailed description of mixed convection with heat and mass transfer in a parallel plate reactor is given in terms of streamline, thermal and concentration contours for different H. In addition, the results for both average Nusselt and average Sherwood numbers at various H will be presented. The effect of K on the streamlines, isotherms and iso-concentrations is exhibited in Figs 2-4. In fact, the analysis is performed at pure mixed convection regime by fixing Ri = 1. The values of chemical reaction parameter, 0.01, 0.1, 1 and 5, are chosen to examine the evolution of streamline, isotherm and concentration patterns. It is observed from Fig. 2, that there is a common trend of the development of streamlines with generating chemical reaction. The streamlines are almost parallel to the channel wall and condensed Fig-4. Effect of K on iso-concentrations From Fig 3, it is observed that isothermal lines have considerable change due to the variation of K. When there is small generating chemical reaction, lower density of isothermal lines appear at the outlet portion of the channel. But for higher values of K, appearance of these lines is more at the right side. It is seen from the figure that, at the highest value of K, the lower temperature lines remain at the left potion where as the higher temperature lines at the right exit port. Temperature gradient at the heat source becomes lower for increasing chemical reaction in the fluid. This happens because higher temperature of the fluid produces lower temperature difference between the heat source and the fluid. It 50

60 is also clear that the higher temperature gradient exists at the first heater from the inlet and sequentially it reduces for the second, third and fourth. Fig. 4 shows the iso-concentration lines which have also substantial change due to generating chemical reaction. Iso-concentration lines spreads all over the channel. As chemical reaction increases, these lines depart to the exit port. Higher concentration causes lower concentration gradient which indicates lower mass transportation. This phenomenon is logical because generating chemical reaction causes higher velocity which leads to more concentration transfer. Fig-7. Effect of K on average velocity Fig-5. Effect of K on heat transfer Fig-8. Effect of K on average temperature and concentration Fig. 5depicts the average heat transfer Nu at the four consecutive heaters for different K. Highest heat transfer rate is observed for the first heater and sequentially these values reduce for second, third and fourth heater/contaminant. This phenomenon is very logical because the flow intensity becomes lower for the last heater due to the obstacles. Increasing K decreases the value of Nu due to lowering the temperature difference. Fig-6. Effect of K on mass transfer The average mass transfer Sh at the inlet port for different chemical reaction parameter is shown in Fig. 6. Reduced mass transfer rate is observed for increasing the chemical reaction parameter. 51

61 The average velocity magnitude V av, temperature Ɵ av and concentration C av in the domain of the reactor are presented in Figs It is observed that the average velocity increases due to the increase in the chemical reaction. Average temperature and concentration rises for higher values of K. The values of mean temperature are lower than that of concentration which indicates temperature gradient is higher than the concentration gradient. This agrees with the phenomena displayed in Figs CONCLUSIONS Double-diffusive mixed convection laminar flow in a parallel plate reactor with four heated cylinders for generating chemical reaction has been studied. The following major conclusions are drawn: Increasing K has significant effects on flow, temperature and concentrations. Lower temperature and concentration gradient observed for higher K. Both heat and mass transfer reduce for rising values of K. In general the effect of chemical reaction plays an important role in both heat and mass transfer for such reactor type. REFERENCES 1. Brown, N. and Lai, F., (2005), Correlations for combined heat and mass transfer from an open cavity in a horizontal channel, International Communications in Heat and Mass Transfer, Vol. 32(8), pp , 2. Parvin Salma, Nasrin Rehena, Alim, M.A. and Hossain, N.F., (2012), Double-diffusive natural convection in a partially heated enclosure using a nanofluid, Heat Transfer Asian Research, 41 (6), pp Azad, A.K., Munshi, M.J.H. and Rahman M.M., (2013), Double Diffusive Mixed Convection in a Channel with a Circular Heater, Procedia Engineering,Vol. 56, pp Muthucumaraswamy, R., Ganesan, P., (2001), Effect of the chemical reaction and injection on flow characteristics in an unsteady upward motion of an isothermal plate, J. Appl. Mech. Tech. Phys., Vol. 42, pp Das, U.N., Deka, R., Soundalgekar, V.M., (1994), Effects of mass transfer on flow past an impulsively started infinite vertical plate with constant heat flux and chemical reaction, Forschung in Ingenieurwesen, Vol. 60, pp Chamka, A.J., (2003), MHD flow of a numerical of uniformly stretched vertical permeable surface in the presence of heat generation/absorption and a chemical reaction. Int. Comm. Heat and Mass Transf., Vol. 30, pp Ibrahim, F.S., Elaiw, A.M., Bakr, A.A., (2008), Effect of chemical reaction and radiation absorption on the unsteady MHD free convection flow past a semi-infinite vertical permeable moving plate with heat source and suction, Comm. in Nonlinear Sci. and Num. Simul., Vol.13, pp Kesavaiah, DC.H., Satyanarayana, P.V. and Venkataramana, S., (2011), Effects of the chemical reaction and radiation absorption on an unsteady MHD convective heat and mass transfer flow past a semi-infinite vertical permeable moving plate embedded in a porous medium with heat source and suction. Int.J. of Appl. Math. and Mech., Vol. 7(1), pp Koning, B., (2002), Heat and mass transport in tubular packed bed reactors at reacting and nonreacting conditions, Ph.D. Thesis, University of Twente, Netherland. 10. Kugai, J., (2008), Heat and mass transfer in fixed-bed tubular reactor, May 1st Deng, Q., Zhou, J., Mei C., and Shen, Y., (2004), Fluid, heat and contaminant transport structures of laminar double diffusive mixed convection in a two-dimensional ventilated enclosure, International Journal of Heat and Mass Transfer, Vol. 47( 24), pp Zienkiewicz, O. and Taylor, R., (2000), The finite element method, Butterworth-Heinemann, 5th edition,

62 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh PRODUCTION OPTIMIZATION OF WELL HBJ#06 OF HABIGANJ GAS FIELD Tahmilur Rahman and Farhana Akter Department of Petroleum and Mineral Resources Engineering, BUET, Dhaka For different gas reservoirs, production optimization is a key factor to increase the production rate and reduce the production cost. Due to drilling work and continuous production, skin is formed. This reduces permeability near wellbore. Unplanned well design, tubing diameter, low perforation ratio with pay zone cause problems during production time. Different optimization procedures along with appropriate changes of well configuration may increase the production rate. Habiganj Gas Field is one of the high performance gas reservoirs in Bangladesh. High permeability, strong water drive, two phase steady state flow are the major characteristics of the field. This paper investigates the performances, production system of Habiganj Gas Field Well no. 06 and shows the optimization procedures due to present conditions and for future also, when reservoir will be at declining mode. Rocks and fluid properties have been calculated to understand the reservoir and fluid behavior. IPR and VLP curves show well deliverability. For optimization, applying removal techniques of skin and increasing permeability, changing tubing diameter and perforation height, maintaining wellhead pressure of the well, provide a new optimized well deliverability. Currently well no 06 is producing gas at the rate of 21 MMSCF per day, this work exhibited results for a newly optimized production rate of MMSCFD. 1. INTRODUCTION High production rate of a gas well a gives rise to a number of problems like sand production, water coning, sea page and even damage of the reservoir structures (Economides et. al., 1994). To achieve the optimum production rate and overcome the production oriented problems, an approach to production optimization is necessary for these gas reservoirs. Production optimization is the maximum recovery from a reservoir applying different stimulation techniques and optimization methods (Beggs, 1991). IPR-VLP curve intersection provides the optimum production rate or well deliverability. There are various key factors effecting the flow rate and other parameters. By changing those parameters and maintaining a balance among well deliverability, reservoir rocks & fluid properties, equipment capacity and overall production system, new optimized production rate can be achieved. This involves the petroleum production system and corresponding reservoir fluid properties (Craft and Hawkins, 1991). Pressure is a very important parameter which is used at different parts of deliverability calculation (McCain, 1933). The objectives of the total work are finding the optimum production rate, ensuring maximum recovery, utilizing the reservoir for maximum time and ensuring the longevity of the equipment. Production rate could not be operated at any random value and reservoir rocks-fluid properties, well type, well equipment, reservoir pressure etc. should be considered. So, by considering and calculating all the concerning parameters, optimum production rate could be achieved. Application of different optimization methods and techniques like matrix acidizing, acid fracturing, hydraulic fracturing etc. and changes of various key values of the production system provide new IPR-VLP curves as well as new optimized production rate. Proper treatment and maintenance ensure the utilization of the reservoir for maximum time. Proper conduction of the flow rate and bottom hole flowing pressure keep the reservoir structure sustainable. As a result, the life of the reservoir increases (Kumar, 1987). * Corresponding Author: Second B. Author, somebody@somewhere.com

63 2. METHODS & MATERIALS 2.1 Production Optimization For production optimization, firstly, reservoir well deliverability calculation is necessary. From Inflow Performance Relationship (IPR) and Vertical Lifting Performance (VLP) curve intersection, well deliverability is calculated. Inflow performance relationship involves the conditions and parameters of reservoir, on the other hand vertical lift performance involves the production well. In both inflow and out flow, fluid flows due to pressure difference (Dake, 1999) IPR Curve Generation Inflow performance relationship is defined as the functional relationship between the production rate of the reservoir and the bottom hole flowing pressure. IPR is defined in the pressure range between the average reservoir pressure and atmospheric pressure (Economides et. al., 1994). The graphical representation of bottom hole flowing pressure (P wf ) and production rate (q) is called Inflow Performance Relationship (IPR). Equation of IPR for gas reservoir is stated below (Craft and Hawkins, 1991): Here: P i = initial pressure, P wf = bottomhole flowing pressure, = average viscosity, Z = gas compressibility factor, k = permeability, h = reservoir height (pay zone), r e = radius of reservoir, r w = production tube diameter, s = skin, q = production rate 2.3. VLP Curve Generation Vertical flow performance is the well s ability to produce under a constant surface pressure constraint. For a well subjected to production, it is referred as tubing intake or outflow performance (Economides et. al., 1994). Two methods are used for calculating pressure drop: (1) Modified Hagedorn and Brown Method (mh-b) : Hagedorn and Brown developed the following pressure- gradient equation for vertical multiphase flow (Economides et. al., 1994) (2) The Beggs and Brill Method This method is applicable for horizontal wells (Economides et. al., 1994). = potential loss + frictional loss 2.4. Well Deliverability Determination At first, IPR and VLP curve have been generated. Thereafter, they were combined to determine the well deliverability or optimum production rate. The intersection of two curves provides expected production rate (q) and bottom hole flowing pressure (P wf ) or well deliverability Removal of Skin Reservoirs often get damaged during drilling near wellbore and skin is formed. It can be determined by well test analysis, which is normally carried out as routine, immediately after completing the well (Bassiouni, 1994). If S is determined positive, the formation damage needs to be reduced. As a result of a successful acid job, the skin factor can be reduced to zero or may even become negative (Guo et. al., 2007) Increasing the Well Penetration (h) The well was completed across the total formation thickness and thus the flow was entirely radial. If the well is not fully penetrated, a distortion of the radial flow pattern close to the well is observed that gives rise to an additional pressure drawdown. By increasing the well penetration, production rate can be increased (Beggs, 1984). 3. RESULTS & DISCUSSION 3.1 IPR-VLP Generation & Well Deliverability Determination The Inflow performance Relationship (IPR) curve shows that the change of pressure with respect to gas production rate is very low because of strong water drive and large permeability. For Vertical Lift Performance (VLP) curve generation, Beggs & Brill method and Hagedorn & Brown Method are applied to calculate pressure gradients. The flow is determined intermittent and distributed for Beggs & Brill method and Hagedrown & Brown method respectively. Beggs & Brill method shows large bottomhole flowing pressure and Hagedrown & Brown method shows moderate bottomhole flowing pressure. 54

64 At present, well no 6 is producing gas at an average production rate of 21 MMSCFD (Petrobangla, 2009). After stimulation, according to the Beggs & Brill method well deliverability is found 26.5 MMSCFD. On the other hand, in Hagedorn & Brown method well deliverability is 28.5 MMSCFD. So, in both case, it is found that the well is producing less than its capacity. Beggs & Brill method is recommended for the wells which are not near vertical while Hagedorn & Brown method is applicable for any types of well (Economides et. al., 1994). Well no 06 is a vertical well. So, from the next steps of calculations Hagedorn & Brown method will be used. Change of skin, effects the bottom hole flowing pressure of inflow performance relationship (IPR). Skin is a function of IPR; so, IPR curve shifts but VLP curve remains constant. Considering skin= -2, the new deliverability is found by Hagedorn & Brown Method is 29.5 MMSCFD. Due to the change of skin, production rate increases only 1MMSCFD. The reservoir has a large permeability, but change in skin is likely to increase the production rate in future. Fig. 3. Optimization by removal of skin (Hagedorn & Brown Method) Fig. 1. Well deliverability determination by Beggs & Brill method By Change in Tubing Diameter and Wellhead Pressure: Case 1: Increasing Tubing Diameter and Wellhead Pressure Unchanged: At present, tubing diameter of well no 6 is only 3.5 inch or 0.29 feet and wellhead pressure is 1270 psia. But all of the well diameters of Habiganj Gas Field are more than 3.5 inch except well no 5 (deviated well). Well head pressure is required to maintain properly while changing the tubing diameter. 4 inch tubing diameter could be used without any change of wellhead pressure and it provides well deliverability measuring MMSCFD. Case 2: Increasing both Tubing Diameter and Wellhead Pressure: 4.5 inch of tubing diameter can be used with wellhead pressure of 1277 psia. The corresponding well deliverability is MMSCFD. Fig. 2. Well deliverability determination by Hagedorn & Brown method 3.2. Optimization By Removal of Skin: The nearby wellbore of well no 6 has a skin factor of 8. By matrix acidizing, skin near wellbore can be removed. For tubing diameter of 4 inch and wellhead pressure 1270 psia, well deliverability is found to be 52 MMSCFD. On the other hand, for a tubing diameter 4.5 inch and wellhead pressure 1277 psia well deliverability is measured to be 50 MMSCFD. Even though for the production rate is higher for the first case, considering situations in the future the second one should be preferred. In the near 55

65 future, the pressure is likely to fall. So, for maintaining a better production rate 4.5 inch diameter should be considered as it would provide more area for production. Hence case 2 should be taken into account for further calculations. Added to that, Acid fracturing is not applicable for the field. On the other hand water injection, gas injections are also not necessary because a decline in reservoir pressure is very negligible due to its strong water drive (Ertekin et. al., 2001). The thickness of upper gas sand is 1083 feet; gas pay zone is 800 feet but perforation of the well is only 430 feet. For the proposed 750 feet perforation height, the well production rate is obtained 50.25MMSCFD. Though the production rate is changed a little, the higher perforation height will turn out to be helpful for the production when the resrvior pressure declines. After applying all optimization techniques, new well deliverability is obtained. For Hagedorn & Brown method the new well deliverability is MMCFD. Fig. 4. Optimization by changing tubing diameter (Hagedorn & Brown) Changing Perforation Height: At present the perforation height of well no 6 is 430 feet, whereas the pay zone is 800 feet. The ratio of perforation height and pay zone is low. For a perforation height of 750 feet, well deliverability is found to be MMSCFD. It seems the production rate increases a bit, however, the cause of this low impact is nothing but strong permeability and water drive of the reservoir. Whenever pressure falls, a high perforation height is required. Basically, this change speeds up the production. For optimization, only four parameters are changed, skin, tubing diameter, perforation height and wellhead pressure. Changing the value of skin would effect less at the moment, but this change will help to keep up the production rate in future and at the same time it is also important for well maintenance. Two tubing diameter is considered for optimization; 4 inch and 4.5 inch where the corresponding wellhead pressure is 1270 psig (present value unchanged) and 1277 psig respectively. For the change of tubing pressure new production rate obtained turned out to be 52MMSCFD and 50 MMSCFD respectively. Though 4 inch tubing diameter is providing higher production rate, 4.5 inch tubing diameter is better. Because of the increased diameter fluid will get more area to flow. The permeability of the reservoir is significantly high that there is a little scope of increasing the permeability for now. Fig. 5. Optimization by increasing perforation (Hagedorn & Brown) Table 1. Summary of optimization outputs Types (S) (D) inch (P tf ) psia (P) feet (Q) MMSCFD Current Situation of Well-06 Beggs & Brill Method Hagedorn & Brown Method Removal of Skin Change in Diameter & P tf (Case 1) Change in Diameter & P tf (Case 2) Change in Perforation

66 4. RECOMMENDATIONS For better performance proper maintenance and monitoring of the well is necessary. Whenever production is on run, several unexpected situations may arise. So, monitoring of the production well should be the utmost priority. Well test analysis would be one of the proper maintenance techniques. No well test has been conducted at Habiganj Gas Filed well no 06 since the beginning, it has been under continuous production for a long time. And this is likely to hamper the well performance. Well test analysis provides damages or skin near wellbore, permeability and overall condition of the well. Then well maintenance will be easier. Continuous production also damages reservoir, even sand is produced. Two of the wells of this gas field are now out of order for excessive sand and water production. As a result, other functioning well requires shutdown for some days and pressure build up tests are needed to be performed. Skin could be protected by using gravel pack and could be removed by a few stimulation techniques. It is necessary for the well to operate at optimum production rate. 5. CONCLUSIONS Throughout the entire procedure of this work, four different parameters have been changed. The most effective was changing tubing diameter as the production rate of the well depends upon the area and the velocity of the fluid. Well deliverability changes more significantly when the tubing is changed than change of skin, perforation or wellhead pressure. Whenever, the reservoir faces the declining mode, the perforation height may be considered another important factor. All of the parameters included in the work can be changed for the better performance of the well. REFERENCES 1. Economides, M. J., Hill, A. D. and Economides, C. E. (1994), Petroleum Production Systems, Prentice Hall, NJ.. 2. Beggs, H. D. (1991), Production Optimization Using Nodal Analysis, OGCI Publications, Tulsa, USA 3. Craft, B.C. and Hawkins, R.E. (1991), Applied Petroleum Reservoir Engineering, Prentice Hall, NJ, USA 4. McCain, W.D. (1933), The Properties of Petroleum Properties, Penn Well Books, Oklahama, USA 5. Kumar, S. (1987), Gas Production Engineering, Gulf Publishing Company, Houston, USA 6. Dake, L.P. (1999), Fundamentals of Reservoir Engineering, Elsevier, Amsterdam, The Netherlands 7. Bassiouni, Z. (1994), Theory, Measurement and Interpretation of Well Log, Society of Petroleum Engineers, Texus, USA 8. Guo, B., Lyons, W.C. and Ghalambor, A. (2007), Petroleum Production Engineering-A Computer Assisted Approach, Gulf Professional Publishing, Burlington, USA 9. Beggs, H. D. (1984), Gas Production Operations, OGCI Publications, Tulsa, USA 10. Ertekin, T., Abu-Kassem, J.H. and King, G.R. (2001), Basic Applied Reservoir Simulation, Society of Petroleum Engineers, Texas, USA 11. Petrobangla (2009), Annual Report, Petrobangla, Dhaka, Bangladesh 57

67 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh NETWORK ANALYSIS: WEST ZONE GAS TRANSMISSION PIPELINE NETWORK IN BANGLADESH S. M. AMIR HOSSAIN 1, Mohammad Mojammel Huque & Mohammed Mahbubur Rahman 2 1 Gas Transmission Company Limited (GTCL 2 Petroleum & Mineral Resources Engineering Department, BUET The natural gas transmission network in the western zone of Bangladesh currently comprises of 246 kilometer of pipeline. About 120 MMCFD, which is 5% of the total gas production, is supplied through this network. The Government has plans to supply gas to more areas in the north and south western regions of the country. About 177 kilometer of pipeline stretching from Iswardi to Khulna except Padma river crossing has already been constructed for this purpose and will be connected to the existing network soon. Thus natural gas will be available to Kushtia, Jhenaidah, Jessore and Khulna districts. A compressor station is also being erected at Elenga to boost the pressure and throughput of gas through this network. Detail study is needed on the west zone gas transmission network regarding pressure drop along the pipeline and availability of gas at various offtakes. Prediction of pressure drop along the pipeline in a network is very important as it indicates the pipeline efficiency, volumes available at various offtakes, maximum possible distance of transmission for a given up stream pressure, effect of compressors, etc. This kind of study requires numerical simulation with powerful computational resources. This paper presents some results from the simulation study of the west zone gas transmission network. A virtual model is constructed, which includes both the existing and new extensions to the network. The model is first validated by matching with the existing network using known data. Then simulation runs are performed to investigate the issues mentioned above. In addition, sensitivity studies are performed to investigate the effects of supply-demand fluctuations. Commercial software package PIPESIM TM is used for this work. Elenga is the starting node of the network. The existing pressure at this point is 400 psig. Results indicate that, with this upstream pressure, it is possible to supply about 205 MMCFD of gas including Khulna while maintaining the necessary pressure for the distribution companies. If the upstream pressure at Elenga is raised to 650 psig with the help of the compressors established at Ashuganj, which is further upstream, it would be possible to transmit about 380 MMCFD of gas at required pressure. The compressors at Elenga would further raise the pressure from 650 to 1,000 psig, increasing the transmission capacity to MMCFD. The maximum demand projected in near future is about 400 MMCFD. Thus it can be concluded that the compressors established at Ashuganj is well enough to supply this volume of gas to the West Zone. 1. INTRODUCTION In Bangladesh, National Gas Grid is operated by Gas Transmission Company Limited (GTCL), a state owned company under Petrobangla. The transmission system is divided into two operational regions viz. Transmission East comprises Dhaka, except greater Faridpur district, Sylhet and Chittagong divisions and Transmission West comprises geographical area on the west side of the Corresponding Author: S.M Amir Hossain amir_gtcl@yahoo.com rivers Jamuna and lower Meghna which means Khulna, Rajshahi, Barisal divisions and greater Faridpur district of Bangladesh (National Energy Policy, 2004). By this study various scenario such as pressure drop along the pipeline, maximum gas flow rate at minimum required outlet/downstream pressure, the effect of compressors to the network established at Ashuganj and Elenga, how long the pipeline can

68 Gas Consumption, MMscf cope up with the forecasted demand or when boost up device would need to be installed have come out. Natural Gas Transmission and Distribution Scenario in West Zone Construction of Jamuna multipurpose bridge with built-in facilities of suspended pipeline river crossing (1999) paved the way for extending the transmission network to the West Zone (Paschimanclal Gas Company Limited, 1999). After that several gas transmission pipelines have been constructed in that region so far as shown in Table 1. Table 1: Major natural gas transmission pipeline. Segment Length (km) OD (inch) WT (inch) Elenga- Jamuna Bridge (JB), East JB Section JB, West-Nalka Nalka-Baghabari Nalka-Hatikumrul Bonpara-Bheramara Hatikumrul-Bogra Bonpara-Rajshahi Bheramara-Kushtia- Jessore-Khulna The schematic of West Zone natural gas transmission network is shown in Figure.1. Fig. 1: Schematic of West Zone gas transmission network. Since inception, Paschimanchal Gas Company Limited (PGCL) of Petrobangla has been distributing natural gas to the customers in West Zone. Recently, Sundarban Gas Company Limited (SGCL) is formed to distribute gas to South and South-West region viz. Khulna and Barisal divisions including greater Faridpur district. The distribution network under SGCL is now in design and implementation phase. The year-wise natural gas consumption history of West Zone (Gas Transmission Company Limited, 2014) is shown in Fig Financial year Fig. 2: Year-wise natural gas consumption in West Zone. Gas consumption varying year to year in West Zone has been depicted in Fig. 2. To get the steady growth rate, consumptions of West Zone for the years to are considered in calculation of compound gas consumption growth rate which is found around 8% per year. In future, potential gas demand may rise mainly for proposed power plants, fertilizer factories, Export Processing Zone (EPZ) and other industries. 2. NETWORK SIMULATION BY PIPESIM For transmission system analysis, it is necessary to configure the pipeline model with correct pipeline data. The transmission model was updated using all pipeline data for analysis of the main transmission grid along with interconnected transmission pipelines in the network. West Zone A virtual network model comprises two models viz. physical model and fluid model. Among others, pressure drop and volume of flow depend on pipeline length, diameter, wall thickness, efficiency factor etc. which are considered to build the physical model. Fluid Model 59

69 Pressure (psig) The fluid model is the main prerequisite that should be defined first while building a simulation network model. To create a fluid model, amount of water and liquefiable hydrocarbons are also defined along with gas composition as pressure drop in pipeline largely depends on these fluid properties. Black Oil Fluid Model is defined in this simulation network. The fluid composition used in the analysis is shown in Table 2. Table 2: Compositional fluid model (PMRE, 2010) Element % Mole Nitrogen CO Methane Ethane Propane i-butane n-butane i-pentane n-pentane Hexane Heptane Octane Total Specific Gravity: at base condition (60 F & psia) Effect of temperature gradient is not considered and 60ºF of gas temperature is considered all through the pipeline. The Watercut and Liquid Gas Ratio (LGR) are considered 0% and 0 STB/MMscf respectively to represent gas flow in the model. In these models Beggs and Brill Revised fluid flow correlation has been used for horizontal flow assuming there is no vertical flow in the network. 3. SIMULATION RESULTS AND ANALYSIS Simulation results mainly contain two parts: one is analytical data viz. pressure, temperature, mass/volume flow rate etc. and another is graphical representation of data containing pressure drop and temperature profiles along with the length of the pipeline. As temperature variation in Bangladesh is negligible, temperature profile is not one of the major factor for discussion. The pressure drop along the distance from source is the main concern for this study. To validate the network model, pressure drop calculations are performed analytically using modified Panhandle B equation (Crane, 1988, Kennedy, 1993) and then compare the results with both field data and simulated value as shown Fig Pressure at different load centers Sirajgonj Baghabari Bogra Rajshahi Load Centers Simulated Real Analytical Fig. 3: Simulated, real and analytical pressures at different load centers. Simulated value is quite equal to real value, though few variation (0.025%) is observed incase of analytical value. This variation may be occurred due to the variation of the value of the some factors viz. average temperature, specific gravity, compressibility factor etc. in consideration. 3.1 Present Situation: Volumetric Flow Rate and Pressure Drop Scenario of the Existing Network The existing network comprises of 246km gas transmission pipelines of various sizes from Elenga to Rajshahi via. Baghabari, Bogra and Iswardi. At present about 120 MMCFD gas is supplied in West Zone through the network with upstream pressure 390psig at Elenga. It is observed that total pressure drop (21psig) in the network at present flow situation is very low as gas flow is low compared to the network capacity. 3.2 Case-I: Maximum Possible Volumetric Flow Rate in the Network at Present Flow Conditions This case study is made for the network of 423km pipeline (existing along with extension) from Elenga to Khulna. The simulation result obtained from this case study shows that maximum 205MMCFD gas including 50MMCFD for Khulna would be possible to transmit through the network with present upstream pressure (400psig) at Elenga. So, additional 85MMCFD gas over present consumption can be supplied through the network at present upstream pressure. The pressure drop profile is shown in Fig. 4 60

70 Fig. 4: Pressures drop profile at maximum volumetric flow in the network at present upstream pressure. 3.3 Case-II: Effect of Compressor Established at Ashuganj. To boost up the national gas grid pressure, one compressor station by Chevron at Muchai and other two by GTCL at Ashuganj and Muchai have already been installed. The compressor of Ashuganj is designed in such a manner that it will maintain minimum 650psig pressure at Elenga. This case study shows that maximum 380MMCFD of gas would be possible to transmit through network maintaining downstream pressure not less than 350psig when network upstream pressure at Elenga rises to 650psig with the help of compressor, established at Ashuganj. The pressures drop profile in this case is shown in Fig. 5. Fig. 5: Pressures drop profile at maximum volumetric flow rate when network upstream pressure at Elenga rises to 650psig with help of compressor established at Ashuganj. 3.4 Case-III: Effect of Compressor Established at Elenga. This case study shows that maximum 620MMCFD gas would be possible to transmit through the network maintaining downstream pressure not less than 350psig when network upstream pressure at Elenga rises to 1000psig with the help of compressor established at Elenga. The study also shows that 85MMscfd gas would be possible to transmit to Khulna fulfilling the probable long term future demand of other demand centers in the network. The pressures drop profile in this case is shown in Fig

71 Fig. 6: Pressures drop profile at maximum volumetric flow rate when network upstream pressure at Elenga rises to 1000psig with help of compressor established at Elenga. 3.5 Summary of Cases Studies Maximum volumetric flow rate at different upstream pressure at Elenga in Cases studies are tabulated in Table 3. Table 3: Maximum volumetric flow rate at different upstream pressure. Cases Pressure (psig) Flow Upstream Downstream (MMCFD) Case-I Case-II Case-III The gas flow in the network will be almost two and three times maximum flow at present upstream pressure due to establishment of compressors at Ashuganj and Elenga respectively. 4. DISCUSSION The West Zone network can consume more gas than present supply at this moment, because gas based 150 MW power plant at Khulna and first phase of 360 MW power plant at Bheramara are ready to consume around 70 MMCFD gas. So, present demand can be considered 190MMCFD. Designing a simulation network, which is only the part of total transmission system, has some limitations. The temperature gradient could not be measured and hence, it is considered negligible. The pipeline network is considered horizontal and straight though there is some elevation and curvature. The effect of such elevation and curvature in flow parameters are not considered in this analysis. 5. CONCLUSION At present situation there is no pressure crisis in the network. Total pressure drop (21psig) is very low as gas flow is low. Maximum 205 MMCFD gas can be supplied through the network at present upstream pressure at Elenga. The study shows that around 380 MMCFD gas can be supplied through the network with the help of compressors established at Ashuganj and that can meet the demand for atleast 9 years. The existing compressor at Ashuganj is sufficient to meet the near future demand in West Zone maintaining downstream pressure not less than 350 psig at any demand center. Moreover, 620 MMCFD gas can be delivered to the West Zone with compressors established at Elenga which can meet the demand for next 15 years at an 8% growth rate. 6. REFERENCES 1. Analytical report of sales line gases of various gas fields, prepared by PMRE Department, BUET, Dhaka, September Crane Co Flow of Fluids through Valves, Fittings and Pipes. 3. Kennedy, J. L., Oil and Gas Pipeline Fundamentals, 2 nd Edition, PennWell Publishing Co., USA, Memorandum of Inauguration of Gas Supply to Western Zone, November 1999, Paschimanclal Gas Company Limited, Bangladesh. 5. Monthly Progress Repot, August 2014, Gas Transmission Company Limited, Bangladesh. 6. National Energy Policy, Ministry of Power, Energy and Mineral Resources, Government of the People s Republic of Bangladesh, Dhaka, May

72 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh STUDY OF PHOTO CATALYTIC AND ANTIBACTERIAL ACTIVITY OF Ag/B/N CO-DOPED TiO 2 / CNT COMPOSITE FILMS Md. M. R. Mazumder, Md. S. Islam, Md. A Hossain, Elias Mahmud, Dali Rani Sarker, ZidniaRahman and Md. NizamUddin* Department of Chemistry, Shahjalal University of Science and Technology, Sylhet-3114, Bangladesh Thin films of TiO 2 and silver/boron/nitrogen co-doped TiO 2 /carbon nanotube (CNTs) composite on glass substrates have been successfully prepared by a simple sol-gel drop coating route. Commercially available and relatively cheap precursors such as titanium (IV) isopropoxide (TIP), silver nitrate, boric acid, urea and functionalize Carbon nanotubes (CNTs) have been used as sources of titanium, silver, boron, nitrogen and CNTs, respectively. The films were characterized by X-ray diffraction and UV-Vis spectroscopy. XRD pattern of pure TiO 2 and co-doped TiO 2 composite films photocatalysts showed single phase of anatase. The UV-Vis absorption spectrum showed that absorption edge shifted to visible light region after doping in TiO 2. The photocatalytic properties of the prepared thin films were evaluated by degradation of methylene blue under visible light irradiation. It has been found that photocatalytic efficiency was significantly improved when TiO 2 is subjected to modify by using Ag, B, N and CNTs. Highest photocatalytic activity has been shown by 2%B 5%N CNT-TiO 2 with an efficiency of 58%, whereas with pure TiO 2 film the efficiency was only 17%. The antimicrobial activities of the prepared composite thin films were also tested using the bacteria Escherichia coli. The composite doped with silver, revealed higher antimicrobial activity than samples containing boron, nitrogen and CNTs. Highest antibacterial activity has been shown by 2%B 5%N 2%Ag CNT-TiO 2 composite. All of the thin films were used for second time degradation and antibacterial studies for catalytic stability measurement. These findings suggest that Ag, B, N and CNTs modified TiO 2 has potential application in the development of alternative for wastewater treatment and disinfectants for environmental protection as a stable photocatalyst. 1. INTRODUCTION Textile industries produce large volume of colored dye effluents that are toxic and non-biodegradable (Reife and Fremann, 1996). These dyes create severe environmental pollution problems by releasing toxic and potential carcinogenic substances into the aqueous phase. Various chemical and physical processes such as precipitation, adsorption, air stripping, flocculation, reverse osmosis and ultra filtration can be used for color removal from textile effluents. However these techniques are non-destructive since they only transfer the non-biodegradable matter into sludge, giving rise to a new form of pollution, which needs further treatment. Recently, there has been considerable interest in the utilization of advanced oxidation processes (AOPs) for the complete destruction of dyes. AOPs are based on generation of reactive species such as hydroxyl radicals that oxidize a broad range of organic pollutants, quickly and non-selectively (Das et. al., 1999).Titanium dioxide (TiO 2 ) is generally considered to be the best photocatalyst and has the ability to detoxify water from a number of organic pollutants (Khodja et. al., 2001). In addition, tiles, glass possess excellent decorative and chemical durability, and are widely used in various areas such as in hospitals and in every household. Unfortunately, tiles/glass itself does not have antibacterial activity and microorganisms easily breed on its surface, especially in moist environment. The existence and breeding of microorganisms on the surface of tiles/glass may harm people s health, therefore, preparation of the antibacterial film on the surface of tiles/glass as well as the investigation of its antibacterial activity is of practical significance (Matsubara et. al., 1995). Furthermore, there are still problems in the use of TiO 2 for practical and wide-spread photo-catalytic applications: such as i) Recycling ii) TiO 2 only absorb UV radiation iii) TiO 2 has low quantum yield rate. * Corresponding Author: Md. Nizam Uddin, nizam3472@yahoo.com

73 Bearing these questions in mind, an integrated study that is still lacking in this field was carried out in this work for the remediation of the issues listed above. Here, synthesis of Ag/B/N co-doped TiO 2 and CNT Composite thin films on glass substrates by a simple sol-gel drop coating route was focused. These films were employed as photocatalysts under visible light irradiation in the degradation of aqueous methylene blue (MB) and in the antibacterial study. 2. EXPERIMENTAL SECTION 2.1 Functionalization of MWCNTs 1.0 g multi wall carbon nano tubes (MWCNTs) were immersed in a 40 ml mixed solution of concentrated sulphuric acid and nitric acid with a volume ratio of 1:1. The mixture was then heated to C for 5 hours under refluxing to obtain a dark-brown suspension and cooled naturally to room temperature. The MWCNTs were filtered and washed with distilled water until the ph of the filtered solution was about 6-7. The product was then dried at 80 C in an oven and kept in a desicator. 2.2 Preparation of TiO2 Film A set of photocatalytic composite thin films were prepared namely (a) TiO 2, (b) CNT-TiO 2 (c) 2%Ag-TiO 2, (d) 2%B 5%N 2%Ag -CNT-TiO 2 and (e) 2%B 5%N-CNT-TiO 2. Titanium (IV) iso propoxide (TIP) (0.5 ml) was added to anhydrous (Anh.) ethanol (3.35ml) under vigorous stirring conditions and then triethyl ammine (TEA) (0.18 ml ) was added as a stabilizer of the solution and stirred at 200 rpm for 2 3 min under normal condition (solution-a). A second solution was prepared separately by mixing hydrochloric acid (0.30 ml), water (0.05 ml) and Anh. ethanol (3.35 ml) using a magnetic stirrer at 200 rpm (solution- B). The two solutions were then mixed drop wise and stirred vigorously for 60 min. The formed TiO 2 sol was transparent, quite stable and highly sensitive to the amount of TEA and water. The sol was aged for 24 h and served for film preparation. The transparent sol was stable for three weeks. TiO 2 thin films were prepared by a drop-coating method. Prior to the coating process, sodalime silica glass substrates (microscope slides) with dimension of 10 mm 60 mm 1.5 mm were grinded by a commercial bench grinder (model: ST- 150), then cleaned in potassium dichromate and dichloromethane solution. Finally the abrasive substrates were rinsed with alcohol and de-ionized water and then dried at 100 C in a microoven. The TiO 2 film was prepared by coating the precursor solution (0.4 ml) on the glass at room temperature and then annealed for 20 min using a micro oven at 200 C; finally the film was vapor treated in the vapor of boiling water for 30 sec to remove the loosely bonded particles. The coating process was repeated three times for thin film preparation and finally annealed at 500 C for 2 h using a muffle furnace (JSMF-30T, Korea). CNT-TiO 2 and Ag, B, N co-doped TiO 2 -CNT composite thin films were prepared by a similar method, where 0.5 mg/ml of MWCNT added with solution A and desired percentage of silver nitrate, boric acid and urea added in solution B as silver, boron and nitrogen precursors, respectively. The prepared thin films were then used for methylene blue degradation and antibacterial study. 2.3 Characterization Film XRD patterns were recorded by Rigaku (MiniFlesx) using Cu K α radiation (λ= A ). The Scherrer equation was applied to the anatase (101) diffraction peak to calculate the average crystalline sizes. The absorption spectra of the bandwidth of the co-doped and bare (un-doped) TiO 2 films ranging from nm were investigated by UV-Vis spectroscopy (Simadzu 1800). 2.4 Photocatalytic Process Photochemical degradation was carried out in a visible light chamber. An outer water pump was used to circulate water of constant temperature through the system continuously to maintain a constant temperature during the degradation study. The chamber consisted of two magnetic stirrers, two cooling fans and a 200 W tungsten lamp. Degradation was carried out under visible light. 150 ml M MB solution was taken and a catalyst film was used for degradation study. The surface area of each film was 6 cm 2. Change in the concentration of MB solution during photocatalytic degradation at different time intervals was monitored by UV-Vis spectroscopy (Simadzu 1800). The absorption spectra were recorded and rate of decolorization of MB was observed in terms of change in the intensity at λ max of the dye. The decolorization efficiency (%) has been calculated as: Efficiency (%) = (C 0 C t )/C (A o -A t )/A o 100 where A 0 is the light absorbance of MB before the treatment and A t is that of after treatment at time t. Before taking the samples under visible light irradiation, the solution of MB was treated with coated films for 30 min in the dark to achieve adsorption and desorption equilibrium. 2.5 Antibacterial Study Process The antibacterial activity of the Ag/B/N co-doped TiO 2 and CNT composite thin films against the 64

74 Absorbance (a.u) intensity/a.u (105) (211) (204) (101) (004) (200) pure E. coli bacteria (ATCC 25922, purchased from ATCC) have been investigated based on the socalled antibacterial drop-test (Akhavan et. al., 2010) in the laminar air flue chamber. Sizes of all the samples used in this experiment were 25 mm / 25 mm. Before the microbiological experiment, all glass wares and samples were sterilized by heat treating at 180 C for 60 min. The microorganisms were cultured on a nutrient agar plate at 37 C for 24 h. The cultured bacteria were added in 10 ml saline solution to reach the concentration of bacteria to colony forming units per milliliter (CFU ml -1 ) corresponding to McFarland scale. A portion of the saline solution containing the bacteria was diluted to 10 8 CFU ml -1. For the antibacterial drop-test, each film was placed on a sterilized Petri dish. Then 100 µl of the diluted saline solution containing E. coli were spread on the surface of the film. It was then irradiated by a tungsten lamp; a temperature of 25 C was maintained by the cooling system. After 60 min, the bacteria were washed from the surface of the film, using 10 ml saline solution (NaCl) in the sterilized conical flask. Then 25 µl of each bacteria containing suspension were spread on a nutrient agar plate and incubated at 37 C for 24 h in order to count the surviving bacterial colonies. The reported data were the average values of three separate similar runs. 3. RESULTS AND DISCUSSION 3.1 XRD of Thin Films XRD patterns of co-doped and bare-tio 2 /CNT composite thin films annealed at 500 C for 2 h are shown in Figure 1. It is identified that all the diffraction peaks can be indexed to the anatase phase of TiO 2 (1 0 1), (0 0 4), (2 0 0), (1 0 5), (2 1 1), (2 0 4), (1 1 6), (2 1 5) and (106) planes [JCPDS: ] and no other phase can be detected. No Ag, B and N derived peaks due to other oxides and nitrides were detected in all the patterns, indicating that Ag, B and N as dopants in TiO 2 exhibit no tendency to segregate and/or precipitate in different phases during the synthetic process. The Ag, B and N in the matrix are assumed to be either interstitial or systematically substitute Ti or O without changing the host TiO 2 matrix. It can be found that the XRD peak positions of doped samples are in good agreement with the reference anatase phase of TiO 2 (Gombac et. al., 2007). The diffractive band at 2θ of 26.0, attributed to the CNTs was also insignificant. The prepared CNT-TiO 2 films were black, indicative of the presence of CNTs in the samples. Therefore, it is suspected that the low crystalline of the CNTs or overlapping of the main XRD band of the CNTs with that of TiO 2 was the main reason for which the CNT band was not detectable. The crystal sizes of all the samples are estimated using the Scherer equation. Considering the peak of (101) planes in account, the average crystalline sizes of the sample a, b, c, d and e are 12.89, 12.27, 11.74, and nm, respectively. It suggests that the change in particle size with respect to Ag/B/N content is not significant Anatase theta/deg Fig. 1. XRD data of (a)tio 2, (b)cnt-tio 2 (c) 2%Ag-TiO 2, (d) 2%B 5%N 2%Ag -CNT-TiO 2 and (e) 2%B 5%N-CNT-TiO 2 composite thin films calcinated at 500 C Finally it has been found that there is no change in the d spacing value: 3.5A, which implies that Ag/B/N/CNT modification in co-doping samples do not change the average unit cell dimension. For our samples the average lattice parameters are as follows: a= 3.78A, c = 9.44 A and unit cell volume = A Wavelength/nm Fig. 2: UV-visible absorption data of (a)tio 2, (b)cnt-tio 2 (c) 2%Ag-TiO 2, (d) 2%B 5%N 2%Ag-CNT-TiO 2 and (e) 2%B 5%N -CNT-TiO 2 composite thin films calcinated at 500 C. 3.2 UV-Vis absorption Spectra of Thin Film e d c b a e d c b a 65

75 Figure 2 compares the UV-Vis absorption spectra of (a) TiO 2, (b) CNT-TiO 2 (c) 2%Ag-TiO 2, (d) 2%B 5%N 2%Ag-CNT-TiO 2 and (e) 2%B 5%N- CNT-TiO 2 composite thin films. After doping boron, nitrogen, silver and CNT to the TiO 2 the absorptions of catalysts increased significantly in the range of wavelengths from 350 to 800 nm. This clear red-shift in the absorption onset reveals the narrowing of the band gap with in TiO 2 by B/N/Agdoping. The red-shift within the absorption edges follows an increasing order as follows: (a)<(b)<(c)<(d)<(e). This is in good agreement with the result in reference (Arana et. al., 2001). Moreover the red shift observed in the composite cases is significantly higher compared to that of bare-tio 2 case. 3.3 Photocatalytic Activity of Photo Catalysts The photo-catalytic activity of bare and B/N/Ag codoped TiO 2 /CNT composite thin films was examined by photo catalytic degradation of MB. Figure 3 shows the percentage of degradation efficiency for the same films in (i) cycle number 1 (1 cycle) and (ii) cycle number 2 (2 cycle). Data clearly show that the degradation efficiency increases continuously during the process of degradation for both cycles. However the rate of degradation clearly differs from bare to co-doped TiO 2 /CNT composite films. The composite with atomic percentage: CNT-TiO 2, 2%Ag-TiO 2, 2%B 5%N 2%Ag -CNT-TiO 2 and 2%B 5%N-CNT- TiO 2 shows higher degradation performance, up to 58%, whereas bare-tio2 films show that of 17%. The photo-catalytic performance within the atomic percentage 2%B 5%N-CNT-TiO 2 composite film shows maximum efficiency to degrade MB dye solution under four hours visible light irradiation and it is 58%. However all co-doped composite films show significantly better activity under visible range light compared to bare-tio 2 films. One of the main problems in using TiO 2 -based photo-catalysts is the deactivation, which mostly attributes to blockage of the active sites on the surface, loss of coating material from the surface due to erosion, etc. To evaluate the possibility of catalyst recovery and re-use, successive photocatalytic MB degradation was performed for all of the composite and bare- films. After each cycle, films were annealed for 1 hr at 500 C and then reused. Figure 6 (ii) shows that successive utilization for 2 cycle induced even better performance for all the films (a), (b), (c), (d) and (e). For 2 cycle the efficiency has been found to be 35-64% for composite films, whereas it is 24 % for bare- film. The increase in efficiency for 2 cycle might be due to (i) the surface chemistry changing during each heat treatment after degradation study and/or (ii) the nitrogen concentration within the structure might be increased for the MB solution adsorption on the film. It is still in great debate of the synergy effects on photo activities and the importance of the relative ratios on photo activities. Further work is ongoing to understand this behavior. 3.4 Evaluation of antibacterial activity The bactericidal activities of the mesoporous composite films were evaluated by the inhibition of bacterial growth of E. coli, which is a gramnegative bacterium and is responsible for causing many infections in daily life. The bactericidal activities of the samples were investigated by the inactivation of E. coli under visible-light-irradiated. (i) (ii) Fig. 3: Percentage of degradation efficiency of (a)tio 2, (b)cnt-tio 2 (c) 2%Ag-TiO 2, (d) 2%B 5%N 2%Ag -CNT-TiO 2 and (e) 2%B 5%N-CNT- TiO 2 films (i) in cycle number 1 (1 cycle), (ii) in cycle number (2 cycle) Figure 4 demonstrates the photographs of disinfection of E. coli in the various systems. It is clearly seen that in Ag, B, N co-doped TiO2-CNT composite film, the E. coli was almost disinfected 66

76 compared with the pure TiO 2 ; the pure TiO 2 has the higher disinfection efficiency than that of control (blank) as a result of various reactive oxygen species (O 2-,OH -, H 2 O 2, etc.) generated on the visible light irradiated photocatalysts. These reactive species cause lipid per oxidation reaction that subsequently causes a breakdown of the cell membrane structure and therefore, its associated functions is the mechanism underlying cell death. In addition, the antimicrobial properties of silver compounds and silver ions have been historically recognized and applied in a wide range of applications from disinfecting medical devices and home appliances to water treatment. It is true that silver exerted antibacterial function itself (Bokare et. al., 2013). It is concluded that silver acted as a metal antibacterial agent as well as a kind of doping metal with boron, nitrogen in TiO 2 composite films. Although there have been few reports about using Ag-TiO 2 nanocomposites as antimicrobial materials, the higher silver content (often larger than 4 atom %) makes them expensive and probably their relatively high human toxicity, may inhibit their broad applications. The result indicates that the as-synthesized 2%B 5%N 2%Ag-CNT- TiO 2 composite films shows outstanding antimicrobial activity. Fig. 4: Colony forming unit (CFU) of E-coli after visible light irradiation for 60 min in presence of (a) TiO 2, (b) CNT-TiO 2 (c) 2%Ag-TiO 2, (d) 2%B 5%N 2%Ag -CNT-TiO 2 and (e) 2%B 5%N-CNT-TiO 2 and without film (control ) in 1 cycle and 2 cycle. 4. CONCLUSIONS An experimental study was performed to realize the synergistic effect of metal, non metal and CNT doping in TiO 2 for photo-catalytic degradation and antibacterial activity study. Co-doped TiO 2 and CNT composite thin films with silver, boron and nitrogen were successfully synthesized by simple sol-gel drop coating method. The 2%B5%N-CNT- TiO 2 composite film demonstrated 58% photocatalytic efficiency and 2%B 5%N 2%Ag -CNT- TiO 2 composite film showed 99% bacteria killing efficiency under visible light irradiation. The absorption edges for the doped films were found to be shifted toward the visible region, while the overall absorption remarkably increased and electron hole recombination rate remarkably decreased for 2%B5%N-CNT-TiO 2 composite films. The doped composite films retained their superior catalytic activity for extended periods. It may be concluded that silver acted as a metal antibacterial agent as well as a kind of doping metal with boron and nitrogen in the TiO 2 composite films. REFERENCES 1. Reife, A. and Fremann, H.S. (1996) Environmental Chemistry of Dyes and Pigments, Wiley, New York 2. Das, S., Kamat, P.V., Padmaja, S., Au, V., Madison, S.A., (1999), Free radical induced oxidation of the azo dye Acid Yellow 9, J. Chem. Society, Perkins Transactions, 2 pp Khodja, A. A., Sehili, T., Pilichowski, J. F. and Boule, P., (2001), Investigation of Photocatalytic Degradation of Methyl Orange by Using on ZnO as an Alternative Catalyst to TiO2, J. Photochem. Photobiol. A: Chem, 141 pp Matsubara, H., Takada, M., Koyama, S., Hashimoto, K. and Fujishima, A., (1995), photoactive tio2 containing paper... activity under weak uv-light illumination, Chem. Lett., 20, pp Akhavan O., Azimirad R., Safa S. and Larijani M. M., Visible light photo-induced antibacterial activity of CNT doped TiO 2 thin films with various CNT contents, J. Mater. Chem., 20, pp Gombac, V., Rogatis, L.D., Gasparotto, A., Vicario, G., Montini, T., Barreca, D., Balducci, G., Fornasiero, P., Tondello, E. and Graziani, M., (2007), TiO 2 with boron and nitrogen for photocatalytic applications, Chemical Physics, 339, pp Arana, J., Rendon, E. T., Rodriguez, J. M. D., Melian, J. A. H., Diaz, O. G. and Pena, J. P., (2001), Photocatalytic degradation of formic acid using Fe/TiO2 catalysts, Appl. Catalysis B:Environ, 30, pp Bokare A., Sanap A., Pai M., Sabharwal S., and Athawale A. A., Antibacterial activities of Nd doped and Ag coated TiO 2 nanoparticles under solar light irradiation, Colloids and Surf. B: Biointerfaces, 102, pp

77 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh ALARM ALLOCATION FOR AN EVENT-BASED ALARM SYSTEM Pradeep Dalpatadu, Salim Ahmed* and Faisal Khan Department of Process Engineering, Memorial University, St. John s, NL, A1B 3X5, Canada This article proposes an allocation methodology for an event-based alarm system. Currently in process plants, alarms are allocated to individual variables to indicate their unsafe deviations. In the proposed eventbased system, alarms will be allocated to events and an alarm will be a direct indicator of an undesired event. The event will be predicted using a model that uses real-time data from a process. Process measurements are also used to identify the variables associated with an event. This articles outlines a procedure to identify the events to allocate alarms. The hazards and operability study (HAZOP) is used to identify significant events which can take place in a plant or equipment. The methodology is demonstrated using an application example. 1. INTRODUCTION Predictive control has found widespread industrial applications. Predictive maintenance is also getting popular. However, the use of prediction for the purpose of warning system design has remained an unexplored area. The use of models for prediction of possible runaway conditions in a reactor has been reported (Bosch et. al., 2004). Models have also been used for disturbance management (Kim et. al., 1990), and predictive alarms have been discussed in the context of reactor safe-zones (Varga et. al., 2010). The idea of so-called grey forecasting for pre-alarm design has also been reported (Lu and Lu, 2012). Although the use of models for alarm design is relatively new, models have been used for fault detection for many years. The basic purpose of an alarm system is to alert, inform and guide (EEMUA, 2007). However, the current industrial alarm systems often fail due to the appearance of a large number of alarms (alarm flooding) during an abnormal event and repetitive appearance of alarms without any real abnormality (false alarms). One root cause for this situation has been identified as the single-variable nature of the alarms. When each variable is alarmed, their number becomes overwhelming. A malfunction may affect several variables and in the single variable setting it may cause a number of alarms to annunciate. Thus during an upset with multiple failures or malfunctions, a very large number of alarms are generated leading to alarm flooding which is considered one of the major problems with the current alarm system. Most past research efforts on this topic were focused on alarm management, with little having been done to improve the actual design of the alarm systems. Different alarm management techniques have been reported in the literature (Brooks et. al., 2004, Hollifield and Habibi, 2007, Izadi et. al., 2010, ISA, 2009). Data-based multivariable setting of alarms has been proposed (Chen, 2010), and false alarm reduction using multivariate statistics has been addressed (Kondaveeti et. al., 2009). The primary reason for alarms as the cause of an undesired event is the appearance of too many alarms when a process approaches an abnormal situation. This means that the alarm system is least effective when it is most needed (EEMUA, 2007). Typical alarm problems include the flooding of alarms in response to a major transient condition or a shift in operating mode, standing alarms, alarm inflation, nuisance alarms, and alarms used as indicators of equipment status. Many of the existing problems of the current alarm system stem from the allocation of alarms. Proposals for alarms come from a variety of sources. Among the in-plant sources are safety and risk analysis, custom and practice, simulation studies, task analysis and so on. External sources include requirements from regulatory authorities and insurers, equipment manufacturer s standard practice, alarm hardware requirement, software designer requirements and so on. Even sometimes alarms are used in the place of an automation component (EEMUA, 2007). There is a lack of structured procedure to allocate plant alarms and this often result in poor alarm allocation. * Corresponding Author: Salim Ahmed, sahmed@mun.ca

78 To overcome the limitations of the current variablebased alarm system, an event-based alarm system has been proposed in the literature (Dalpatadu, 2014). An event is the outcome of a disturbance or malfunction of an equipment or failure of a control system or a combination of two or more of these. In the current alarm system any change in plant or equipment condition is treated as an event. For example a deviation in the level of liquid in a tank is considered as an event in the current system and an alarm is allocated to monitor the level. The alarm annunciates when the level passes a certain value. Similarly the inlet and outlet flows of the tank are also assigned alarms. In the proposed event-based alarm system, overflow of the tank is considered as an event and an alarm is allocated to indicate overflow of the tank. The overflow alarm will annunciate based on the current state of the level as well as the inlet and outlet flow rate along with corresponding valve positions. The advantage is that the alarm will be clear indicator of a well defined situation. An operator readily realizes the consequences of an overflow. In the variable-based alarm system, each of the variables will be assigned an alarm while in the event-based system one overflow alarm may be enough to monitor overflow of the process. Thus the number of alarms in the event-based system will be significantly lower. Thus the proposed event-based alarm system will reduce the number of alarms in a plant, reduce the response time of the operators, provide information and guidance and prioritize the set of annunciated alarms in a structured way. However, there are numerous challenges associated with implementation of the proposed system. How to estimate the risk of an event from a set of process measurements is challenging as well as critical for event-based alarms. In general, the alarm system refers to the complete system for generating and handling alarms that includes all the hardware and the software elements. In the context of this article only the alarm annunciation procedure is considered. This article details the procedure for identification of the events for alarm allocation. The hazards and operability study is used to identify the events. The methodology for event identification is discussed in Section II. An application example is presented in Section III followed by concluding remarks in Section IV 2. METHODLOGY Fig. 1 presents the details about the event-based alarm system design methodology. Three main steps are involved in the proposed procedure. This article presents only the first step, namely the alarm allocation methodology. A. Alarm allocation procedure B. Alarm processing methodology C. Alarm annunciation philosophy In the proposed alarm system, alarms will be allocated to specific events. This will require identification of events that may take place during the operation of the process under consideration. Events, in the context of the proposed warning system, are defined as undesirable abnormal conditions such as runaway reaction in a reactor, flooding of a tank or operational problems e.g. plant shutdown or product degradation. One or several initial causes such as failures can cause deviation of the process variables away from their normal operation conditions. The process can further deviate from normal operation range due to failure of process safety barriers. Subsequently, an undesirable event can occur. The first step in the methodology is to identify the undesired events which can take place during the operation of the particular process. There are many risk assessment tools that can be used to identify events. In the proposed procedure, the Hazard and Operability Study (HAZOP) is used to identify the potential events. HAZOP study is a qualitative risk assessment method to identify process hazards that can occur due to deviations of process variables. Piping and instrumentation diagrams are used to identify the propagation of major process variable deviations. Hazard and Operability Study (HAZOP) is a stepwise procedure for hazard identification used to identify potential abnormal conditions and operational problems. The study simulates abnormal behavior by considering deviations and disturbances due to causes likely to impact immediate and surrounding plant resulting in consequences. It then decides whether the design has adequate features i.e. safeguards that can prevent occurrence or limit the consequential effects. If no such safeguard exists, then it considers what actions are required to remedy the situation or what event can take place in the absence of a safeguard. The main features of HAZOP are as follows (Crowl and Louvar, 2011). Concentrate on one location in a process at a time -Node. Consider each process variable individually - Parameter. Pose a series of standard questions about deviations from normal conditions - Guide Word. Guide Word + Parameter results in a scenario - Deviation. 69

79 Identify the source of the deviation - Causes. Fig. 1: Event-based early warning system design methodology Fig. 2: HAZOP procedure 70

80 Guide word NO, NOT, NONE MORE, HIGHER LESS, LOWER AS WELL AS PART OF REVERSE OTHER THAN SOONER THAN WHERE ELSE LATER THAN Table 1. HAZOP guideword list Meaning The complete negation of the intention Quantitative increase Quantitative decrease Quantitative increase Quantitative decrease The logical opposite of Complete substitution Too early or in the wrong order In additional location Too late or in the wrong order Table 2. Measured variables in the CSTR Variable T L To Fo TJo FJo F TJ TV LV. Description Temperature of the reactor content Level of liquid in the reactor Temperature of reactant inflow Flow rate of reactant inflow Temperature of coolant inflow Coolant flow rate Flow rate of reactant outflow Temperature of coolant outflow Temperature control valve position Level control valve position 1 FJ Table 3. HAZOP study results for the CSTR Variable Deviation Consequences Causes Runaway reaction Temperature controller malfunction No Off quality product Temperature sensor failure Plug pipe line Reverse Runaway reaction Backflow due to high back pressure Off quality product Coolant pump failure Off quality product Temperature controller malfunction More Coolant pump failure As well as None Contamination of water supply Low Runaway reaction Temperature controller malfunction Partially plug line Temperature sensor failure Cooling pump malfunction 2 TJo High Runaway reaction Cooling tower failure Runaway reaction Feeder mixture system failure High 3 Cao Off quality product Feed flow controller failure Low Off quality product Feeder mixture system failure 4 To High High reactor temperature Feed heater failure 5 T High Runaway reaction Temperature controller failure Low Off quality product Temperature sensor failure Overflow of reactor Feeding pump failure High Failure of the level control system Outlet valve blockage 6 L Level sensor failure 7 F 8 Fo Low High Low/No None identified None identified Overflow of reactor High outlet flow Failure of the level control system Tank leakage Level controller malfunction Level sensor failure Outlet valve blockage Level controller malfunction Level sensor failure Tank leakage High Overflow of reactor Feed flow controller failure Reserve None identified Pump mechanical problem Low/No None identified Pump failure 71

81 Identify the effects of the deviation - Consequences. Identify what is required to prevent/mitigate the deviation - Actions. Identify what abnormal situation can take place in the current setting - Event. Table 1 presents the list of HAZOP guidewords. It is argued that HAZOP, due to its qualitative nature, leads to the allocation of large number of alarms. This might be true for the variable-based alarm system where each variable whose deviation leads to a hazardous event is assigned an alarm. Due to the very large number of variables, the number of alarms becomes large. However, undesired event in a process may not be dependent on the number of variables measured. Moreover, deviation of a set of variables may lead to the same event. Thus, in the event-based alarm system, as alarms are allocated to events, the number of alarms will be significantly lower 3. CASE STUDY: CSTR A simulated jacketed continuous stirred tank reactor (CSTR) is considered for this study. The process diagram for the CSTR is presented in Fig 3. An irreversible exothermic reaction A! B with a first order kinetics is assumed to take place in the reactor. A temperature controller is used to control the reactor temperature by manipulating the coolant flow rate. The level of liquid in the reactor is also maintained by manipulating the reactor outlet flow. Heat losses are considered negligible and a perfect mixing condition is assumed. Ten variables that are listed in Table 2 are measured. Table 3 summarizes the result of the HAZOP study for the CSTR. The HAZOP study identifies the significant events that can take place in the reactor. In the conventional plant alarm system, there would be ten alarms. Also considering the high and low setting, there can be as many as twenty alarms. For example, the HAZOP Study shows that the coolant flow rate and the temperature of the coolant are related to the runaway event. Thus there is no need to allocate two alarms for these two variables. A runaway alarm will be sufficient to indicate any abnormal situation related to these two variables. Considering all possible deviation of the variables, the following three significant abnormal events are identified and three alarms are to be allocated for this system. Other aspects of the alarm system have been detailed in (Ahmed et. al., 2011, Chang et. al., 2011, Dalpatadu et. al., 2013). A. Runaway B. Flooding C. Low product quality 4. CONCLUDING REMARKS Reducing the number of alarms in the process plants is a grave concern. Operators are often overwhelmed by alarms and are unable to perform their main responsibilities. The proposed alarm system will significantly reduce the number of alarms. Also it will provide plant operators with direct indicators of events. The use of HAZOP ensures that the major safety aspects will be identified in the alarm allocation. The next step for this alarm design procedure is to develop a model for predicting events from a set of measurements of process variables and to develop an alarm annunciation and prioritization methodology. ACKNOWLEDGEMENT Authors gratefully acknowledge the financial support provided by Research and Development Corporation (RDC), Vale Research Chair Grant, and Natural Sciences and Engineering Research Council (NSERC) of Canada. REFERENCES 1. Bosch, J., Strozzi, F., Snee, T., Hare, J., and Zaldr, J. (2004), A comparative analysis between temperature and pressure measurements for early detection of runaway initiation, Journal of Loss Prevention in the Process Industries, 17(6), pp Kim, I. S., Modarres, M., and Hunt, R. N. M. (1990), A model-based approach to on-line process disturbance management: The application, Reliability Engineering and System Safety, 29, pp Varga, T., Szeifert, F., and Abonyi, J. (2010), Detection of safe operating regions: A novel dynamic process simulator based predictive alarm management approach, Industrial & Engineering Chemistry Research, 49, pp Lu, X., and Lu, W. (2012), Pre-alarm model of diesel vapour detection and alarm based on grey forecasting, Journal of Process Control, 45, pp EEMUA (2007), Alarm Systems: A Guide to Design, Management and Procurement, 2nd ed. EEMUA, no Brooks, R., Thorpe, R., and Wilson, J. (2004), A new method for defining and managing 72

82 process alarms and for correcting process operation when an alarm occurs, Journal of Hazardous Materials, 115, pp Hollifield, B., and Habibi, E. (2007), Alarm Management: Seven Effective Methods for Optimum Performance, International Society for Automation 8. Izadi, I., Shah, S.L., and Chen, T. (2010), Effective resource utilization for alarm management. Proc. 49th IEEE Conf. on Decision and Control, December , 2010, Atlanta, Georgia, USA 9. ISA (2009), Isa 18.02: Management of alarm systems for the process industries, International Society for Automation 10. Chen, T. (2010), On reducing false alarms in multivariate statistical process control, Chemical Engineering Research and Design, 88, pp Kondaveeti, S.R., Shah, S.L., and Izadi, I. (2009), Application of multivariate statistics for efficient alarm generation, Preprints of the 7th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, June 30 - July 3, 2009, Bacelona, Spain 12. Dalpatadu, P. (2014), Design of an event-based early warning system for process operations, Master s thesis, Memorial University, Crowl D., and Louvar, J. (2011), Chemical Process Safety, 3rd ed. Prentice Hall, Ahmed, S., Gabbar, H. A., Chang, Y., and Khan, F. I. (2011), Risk based alarm design: A systems approach, Proc. 4th ADCHEM, May 2011, pp , Hangzhou, P.R. China 15. Chang, Y. Khan, F., and Ahmed, S. (2011), A risk-based approach to design warning system for processing facilities, Process Safety and Environmental Protection, 89(5), pp Dalpatadu, P., Ahmed, S., and Khan, F. (2013), Alarm allocation for event based process alarm systems, Proc. 10th DYCOPS, December 2013, pp , Mumbai, India 73

83 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh CONTINUOUS-TIME IDENTIFICATION USING SINUSOIDAL RESPONSE: A COMPARATIVE STUDY Shaikh M. Fahim, Salim Ahmed and Syed A. Imtiaz Department of Process Engineering, Memorial University of Newfoundland, St. John s, Canada The main objective of this study is to evaluate the performance of a set of recently developed approaches for continuous-time identification. Three major approaches for identification using sinusoidal response are considered (i) direct identification using the integral equation approach (ii) by estimating the step response from the sinusoidal response and (iii) by linear approximation of the sinusoidal input. The effect of frequency of the input signal and that of the data length and the noise to signal ratio are studied in simulation. A first order plus time delay model is considered in the case study and the properties of the estimates of the gain, the time constant and the delay are studied. Monte Carlo simulations are performed to estimate the bias and variance of the estimated parameters. Based on an average error criterion defined based on the estimated bias and variance estimates of the parameters, the performance of the methods are compared. The performances of the three algorithms were found to be comparable at low to mid level frequencies of the input. However, at high frequencies of the input, the performance of the piece-wise linear approximation method deteriorated. 1. INTRODUCTION The integral equation approach (Diamessis, 1965) is a well-known technique for parameter estimation of continuous-time transfer function models. However, use of this technique has so far been limited to step and step-like input signals (Hwang and Lai, 2004, Lie et. al., 2007, Ahmed et. al., 2007). Ahmed (2014) recently proposed an integral equation approach for direct identification of the parameters and the delay using the integral equation approach. The sinusoid has a distinct advantage over some other signals due to its smooth nature which helps it to change variables gradually. Besides, use of the sinusoid as input gives the opportunity to excite process at the frequencies of interest and thus helps to obtain precise frequency response of the plant. In recent times using sinusoidal input for system identification has become popular (Kalafatis et. al., 2005, Zaremba and Pavlov, 2002, Hwang et. al., 2004). At the same time identification from step response has some distinct advantages (Ahmed et. al., 2007, Wang and Zhang, 2001, Wang et. al., 2001). To combine these two procedures, Ahmed et al. (2009) proposed a novel idea of transforming the sinusoidal response to step response by passing it through a linear filter and then estimating the process model parameters using the integral equation approach. Any signal can be expressed as an amalgamation of linear approximated signals for small sampling intervals. With this idea, a sinusoid was represented approximately with piece wise linear signals and subsequently model parameters were extracted (Ahmed, 2010) using the integral equation approach. This technique turned out to be computationally less complex than estimating model parameters directly from the sinusoidal or step response. In this article, using the above mentioned three methods, the parameters for a FOPD model were estimated to evaluate the performance of these algorithms with varying noise to signal ratio (NSR), input frequency and data length. The estimated model parameters were compared using an average error criterion (Ahmed, 2006). The following section briefly describes the above mentioned methodologies. 2. METHODOLOGY Let us consider a first order plus time delay (FOPD) system stated by the Equation 1 * Corresponding Author: Salim Ahmed, sahmed@mun.ca

84 where, G(S) is the transfer function between the input, U(S) and the output Y(S); [ ] are the model parameters. The concept is, using sinusoidal signal as an input and introducing measurement noise we will generate noisy response, with which following the later mentioned three methods, the model parameters i.e. time constant, gain and time delay of the system will be estimated; however the methods are applicable to higher order models as well. 2.1 The Direct Approach In the time domain, a sinusoidal input with amplitude, frequency, and phase is expressed as follows In the Laplace domain Equation 2 can be written as Considering, and, the above Equation 3 can be rewritten as following Considering the initial transient state of the process output, y(0), is zero, Equation 1 can be expressed in the following equation error format as Taking inverse Laplace transform of Equation 5, we end up with the time domain equation as where y [k] (t) denotes the k-th order integral of y(t). To estimate parameters, Equation 6 is written in the following suitable form to use the least-squares solution technique. Here, d is the time delay in terms of number of sampling intervals ( ), i.e. and N is the total no of samples available. When the time delay is not an integer multiple of sampling interval, d is chosen as the nearest integer in the positive direction. Finally, the least-squares (LS) solution of the estimation equations in Equation 9 gives us the estimated parameters of the system Due to integration operation, the LS solution may be biased even for a white measurement noise. To get an unbiased estimate, the instrumental variable (IV) method is implemented (Young, 1970). To generate the instruments, the LS solution of the parameters are used to get the predicted output. The instrument vector, is then derived by replacing the terms related to the output,, in the regressor by their predicted values,. Afterwards, is written for t = t d+1 ; t d+2 t N and combined to get the instrument matrix. The instrumental variable estimate of the parameters is given by From Equation 11, the parameters can be directly obtained and delta can be obtained as. Thus, we get the entire set of parameters [ ] for the FOPD model. 2.2 Identification by Estimating Step Response Equation 1 can be rewritten as If the input is a unit step, we have unit step response, can be obtained as and the Or equivalently, where, Comparing Equation 12 and 13, we get the relation to obtain the unit step response from output data due to other type of input signal, i.e. in this case the sinusoidal input. Here, Equation 8 can be written for t = t d+1 ; t d+2 t N and then combined together to give a set of estimation equations Here, Y(s) is the response due to the same sinusoidal input that was used in previous section and for a deterministic input, U(s), which is a sinusoid in this case, can be obtained mathematically. Now considering the term as a filter, F(s), which is known, from Equation 14, it can be said that the step response of the unknown process can be obtained from its output due to a 75

85 sinusoidal input and then by passing it through the filter. Using Equation 4, for a sinusoidal input with single frequency, the filter becomes Using Equation 14 and Equation 15, we get the relation to obtain the step response from sinusoidal response as where, k is the order of the integral. Using Equation 20 and 21, rearrangement leads to following leastsquare formulation Or equivalently, where, As can be seen from Equation 16, for F(s) to be stable, the phase ( ) of the sinusoid needs to be bounded by. But the issue arises when the phase ( ) of the input sinusoid becomes zero, making the filter F(s) unstable with lesser number of poles compared to zeros. Besides, with zero phase ( ), the filtering involves direct differentiation of the output signal which is not desired for the noisy outputs. To solve this problem, we used the linear filtering technique through defining an extra filter in Laplace domain as with a known value of. In this article, for simplicity, we have used the value of as 1 for parameter estimation purpose. Afterwards, the filtered unit step response of the system,, was obtained from Equation 16 as Equation 23 can be written for t = t d+1 ; t d+2 t N and then combined together to give a set of estimation equations to solve for the model parameters. 2.3 Identification by Piece-wise Linear Approximation Following integral equation approach, assuming zero initial condition the model equation can be written as If an input is piece wise linear, it can be mathematically expressed as As in this particular case, we obtain the step response of the augmented system, the parameters have to be estimated from the augmented system rather than the original process. Considering the same FOPD system used in the previous section, the relation between input and output of the augmented system in Laplace domain is as followed For unit step, using, Equation 18 becomes Here, i corresponds to the sampling instant, is the rate of change of slopes of the input signal at the i- th sample point, which can be obtained from Equation 27 and. where, are the slopes of the signals at the sampling instants, estimated through backward approximation i.e. and is the unit step signal defined as Taking inverse Laplace of Equation 19, assuming zero initial condition, and afterwards following integral equation approach, we get, For any, where tk is the k-th sampling time, in Equation 26, for all the terms with,. So, for, we have For a unit step input applied at time t = 0, the following integral holds for For such an input the delayed signal can be expressed as 76

86 Fig. 1. Estimated process parameters with different methodology for different values of NSR Fig. 2. Estimated process parameters with different methodology for different data length Fig. 3. Estimated process parameters with different methodology for various frequency factors Fig. 4. Comparison of different algorithms based on average error criterion changing one input variable at a time 77

87 For simplicity in the presentation we will use the notation. Using the notation, the integral of the delayed input signal can be expressed as Using Equation 25 and 32, the estimation equation then becomes Or equivalently, With component, we denote as the does not have a t Equation 34 can be written for t = t d+1 ; t d+2 t N and then combined together to give a set of estimation equations to solve for the model parameters. 3. OPTIONS FOR PREPARATION OF MANUSCRIPT For simulation purpose, we have considered the FOPD model to be. Simulations were carried out with a fixed value of amplitude and phase of the sinusoid which were in this case 20 and 0 rad respectively. In each case, the parameters were obtained for 50 Monte-Carlo simulations (MCS), and then based on the obtained parameters, the methods were compared based on the average error criterion defined as where, represents the true values of the i-th parameter, is the mean of the estimated values and is the set of estimated values. is the number of parameters. 3.1 Effect of NSR To check the robustness of the algorithms in the presence of noise, the noise to signal ratio was varied from 5% to 60% for a data length and frequency of 1500 and 0.05 rad/s, respectively. The results are shown in Fig. 1. This gives us the idea that with the increased NSR the parameter estimation deviates from the true value which is expected and in terms of performance the step response method has a slightly better estimation compared to the other two methods. 3.2 Effect of Data Length Data length, which actually corresponds to sampling time plays an important role in estimation of the parameters. It is obvious that with the increase in data length the estimation results will improve. For demonstration purpose the data length was varied from 500 to 1500 points and the obtained parameters are presented in Fig. 2. The simulation results suggests that both the direct and step response techniques have comparable performance which is slightly better than that of the piece-wise linear approximation method. 3.3 Effect of Frequency The third input variable, frequency, plays a vital role is parameter estimation. The FOPD system considered in this simulation has cut-off frequency of 0.05 rad/s. For simulation purpose, the parameters were obtained for a range of input frequencies starting from 0.5 times to 1.5 time of system cut-off frequency. Defining the ratio of the input signal frequency to the cut-off frequency as the frequency factor, Fig. 3 represents estimated parameters w.r.t different values of frequency factors. The simulation results suggest that while the input sinusoid has a frequency upto process cutoff frequency the parameters obtained with different techniques do not have that much of a significant difference but as the input frequency tends to increase more, the piece-wise linear approximation has a better performance. But for very high frequencies the piece-wise approximation procedure results in higher error. Fig. 4 represents the estimated average error for different conditions. Based on the average error criterion, it can be said that both direct and step response methods have slightly better estimation for a frequency factor less than CONCLUDING REMARKS There has been some new developments in the field of identification from sinusoidal response. However, the users need to know the applicability and performance of different methods. A comparative study is carried out in this study to 78

88 compare the performances of three recently developed methods for identification using sinusoidal response. The purpose of this study was to provide a guideline for the user with regards to the choice of identification method when a sinusoid is used as input. The comparable performance of the three methods indicate that the users have a wide range of choices to use the sinusoids. However, the performance varies with data length, and more importantly with the frequency of the input signal. Performance of the algorithms in identification of higher order models and the effects of frequency as well the phase will be studied in the future. ACKNOWLEDGMENTS Authors gratefully acknowledge the financial support provided by Research and Development Corporation (RDC), and Natural Sciences and Engineering Research Council (NSERC) of Canada. REFERENCES 1. Diamessis, J. (1965), A new method for determining the parameters of physical systems, Proceedings of the IEEE, 53(2), pp Hwang S.-H. and Lai, S.-T. (2004), Use of two-stage least-squares algorithms for identification of continuous systems with time delay based on pulse responses, Automatica, 40(9), pp Liu, M., Wang, Q.-G., Huang, B., and Hang, C. C. (2007), Improved identification of continuous-time delay processes from piecewise step tests, Journal of Process Control, 17(1), pp Ahmed, S., Huang, B., and Shah, S. L. (2007), Novel identification method from step response, Control Engineering Practice, 15(5), pp Ahmed, S. (2014), Continuous-time identification using sinusoidal inputs: An integral equation approach, Industrial & Engineering Chemistry Research, 53(33), pp Kalafatis, A. D., Wang, L. and Cluett, W. R. (2005), Identification of timevarying ph processes using sinusoidal signals, Automatica, 41(4), pp Zaremba, A., and Pavlov, A. (2002), Real-time identification of an induction motor using sinusoidal pwm voltage signals, American Control Conference, 4, pp Hwang, S.-H., Ling, H.-C. and Shiu, S.-J. (2004), Robust identification of continuous parametric models based on multiple sinusoidal testing under slow or periodic disturbances, Industrial & engineering chemistry research, 43(19), pp Wang, Q.-G., and Zhang, Y. (2001), Robust identification of continuous systems with deadtime from step responses, Automatica, 37(3), pp Wang, Q.-G., Guo, X., and Zhang, Y. (2001), Direct identification of continuous time delay systems from step responses, Journal of Process Control, 11(5), pp Ahmed, S., Huang, B., and Shah, S. (2009), Process identification from sinusoidal test data by estimating step response, System Identification, 15(1), pp Ahmed, S. (2010), Piecewise linear approximation of sinusoidal inputs for process identification, Control Automation Robotics Vision (ICARCV), pp Ahmed, S. (2006), Parameter and delay estimation of continuous-time models from uniformly and non-uniformly sampled data, Ph.D. dissertation, University of Alberta, Edmonton, Canada 14. P. Young (1970), An instrumental variable method for real-time identification of a noisy process, Automatica, 6(2), pp

89 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh REDUCTION OF MAGNETITE ORE FINES WITH HYDROGEN Saikat Kumar Kuila a, Shamik Chaudhuri a, Ritayan Chatterjee a,b * and Dinabandhu Ghosh a a Department of Metallurgical and Materials Engineering, Jadavpur University, Kolkata , India b Department of Applied Sciences, Haldia Institute of Technology, West Bengal , India Iron was produced by the hydrogen reduction of magnetite ore fines in a thermogravimetric analyzer. Experiments were carried out in the temperature range of K. The other variables studied were hydrogen flow rate ( cc/minute), sample bed height ( cm), hydrogen partial pressure (0.5-1 atm) and particle size ( micron). Phase identification, product morphology and elemental analysis were done by X-ray diffraction, scanning electron microscopy and energy dispersive X-ray spectroscopy, respectively. The results showed that the reduction of magnetite fines took place in two stages: Fe 3 O 4 FeO and FeO Fe, each of which was rate controlled by pore diffusion. The activation energy was found to be 33kJ/mol. The percentage removal of oxygen went up to above 60%. 1. INTRODUCTION In the Indian subcontinent, the steel industry mainly depends on the consumption of lumps and sinters of iron ores. Ore fines have not been used here due to technological inefficiency. During the year to , only 40-45% of the overall iron ore could be used inside the country and the rest was exported since those cannot be directly used for iron making without agglomeration. The pelletization, in particular, is the only means of utilization of fines in iron making in the near future. This process requires the much-needed attention as it would offset the demand for high grade iron ore in the country (Wang and Sohn, 2013). More than 90% of iron is currently produced by the blast furnace (BF) process, while the balance is produced by the direct reduction (DR). Despite the improvements in the modern BF processes such as increasing campaign life and productivity, decreasing coke consumption, developing better coke making processes, increasing coal injection and injecting natural gas and plastics, it still suffers from drawbacks. The process requires the iron ore to be fed in the form of sinters or pellets and coke produced from high-grade coking coal. Also, the BF process is highly capital and energy intensive, requiring large-scale infrastructure and operation. Those constraints limit the flexibility of the BF process in terms of operation and choice of materials (Carlson, 2010). Thus, BF iron production is projected to decrease significantly in the future (Chatterjee, 1993). Besides, the primary greenhouse gas emitted from iron and steel industry is CO 2 which is not desirable from environmental regulations (Fruehan, 1998). Accordingly, a number of new iron making technologies have been developed or are under development (Greene, 2005). Most of these processes, however, are not sufficiently intensive to replace the BF because they cannot be operated at high temperature due to the sticking and fusion of particles. Subsequently a new technology was developed to produce iron directly from fine particles by a gas-solid suspension process, which would be more energy efficient than BF and drastically lower environment pollution, especially CO 2 emission (Sohn, 2007). Even so, currently there is no commercial process that can utilize large reserves of magnetite ore in India and other countries. Nor is there much research work on reduction of magnetite to iron. In this context, as well as considering the fact that the reduction of a dense magnetite poses challenge, it is worthwhile to take up a systematic study of reduction of magnetite by hydrogen (Takeuchi, 2007). To make the study more practical and industrially important, the reduction of magnetite ore fines, instead of pure magnetite, was considered in the present study. It may be noted that the reduction of magnetite to wustite, and subsequently to iron, is not very difficult when magnetite is an intermediate product of hematite reduction. The hexagonal hematite undergoes volume expansion when it converts into the cubic magnetite and, * Corresponding Author: Ritayan Chatterjee ritayanchatterjee@gmail.com, ritayanc@research.jdvu.ac.in

90 consequently, develops cracks and pores which makes the reduction of the resulting magnetite kinetically favorable. The difficulty of the reduction of an original magnetite which is dense has made a large reserve of magnetite ore unused (Teplov, 2010). 2. EXPERIMENTAL The reduction of magnetite ore fines was carried out in a thermogravimetric apparatus (TGA) which comprised a furnace, a balance (accuracy 0.1 mg), and an alumina crucible for holding Fe 3 O 4 powder. The powder was placed in the TGA at room temperature and its initial mass was recorded by the in-built balance. Next, the temperature of the furnace was raised at the rate of 10 C/minute to the chosen reduction temperature in argon atmosphere. When the temperature was attained, hydrogen gas was passed from a gas cylinder at a chosen flow rate, recorded by a rotameter. This point of time was called the zero time (t = 0). Both gases were freed from moisture, carbon dioxide and oxygen by passing through the columns of silica gel and molecular sieve, and through an alkaline pyrogallate solution, respectively. The inbuilt software allowed the TGA to record the progress of the reduction by noting the change in weight of the powder as a function of time. When the 100% reduction, or the available maximum reduction was achieved, which corresponded to the complete removal of the initial mass of removable oxygen, there would be no more change in the weight. Then, the flow of hydrogen was closed and the argon was resumed. The reduced powder was cooled in argon atmosphere and removed from the system at about K. More details of the experimental set up can be found in the reference (Chatterjee et al, 2012). The instantaneous fractional reduction (F) was found using the relation, F = (mass of oxygen removed) / (initial mass of oxygen). The starting material and the reduction product have been characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM). XRD pattern of the powder sample was taken using a Rigaku Ultima-III diffractometer with Bragg- Brentano geometry and using Cu Kα radiation; the microscopic studies were done by a JEOL, JSM 8360 microscope. The elemental analysis of the starting material and reduced products was done by the energy dispersive X-ray spectroscopy (EDX) using an Oxford Instrument 7582 spectroscope with INCA software attached with the SEM set up. The oxygen weight percentage of the ore was crosschecked by a LECO, USA TC600 oxygen determinator (OD). 3. RESULT AND DISCUSSIONS 3.1 Characterization of magnetite ore fine Phase identification by XRD The XRD pattern of the starting magnetite ore is shown in Fig. 1. Peak a is identified as Fe 3 O 4 with Fe replaced by Mg at some sites and by Cr at some other sites. There is some presence of Fe 2 O 3 as revealed by peak b and cubic Fe 3 O 4 as peak c Elemental analysis by EDX and comparison with the oxygen analysis by OD The EDX analysis of the initial ore sample which is shown in Table 1, gave the weight % of Fe and O, together with those of other elements. The first two columns, A and B, represent the analysis obtained from the two different locations of the ore. The third and fourth columns give the corresponding values in atom %. The oxygen concentration varies from 31 to 32% at the two locations. Fig. 2 presents the oxygen analysis of the same sample by the oxygen determinator(od). In agreement with the EDX analysis, the latter method yields 28.8% oxygen. The average oxygen content of the starting sample was thus considered as 31%. This value will be used in the calculation of the fractional reduction of the ore (F). Fig.1. XRD pattern of the unreduced sample Fig.2. Oxygen analysis of the unreduced sample by oxygen determinator 81

91 Table 1. EDX analysis of the unreduced sample Element Weight % (A) Weight % (B) Atom % (A) Atom % (B) O Mg Al Si P Ca Cr Fe Ni Totals Morphology by SEM The SEM image of the starting magnetite ore fines is shown in Fig. 3. Fig.3. SEM image of the unreduced sample 3.2 Hydrogen reduction of magnetite ore Effect of Temperature Isothermal reduction experiments were performed at three temperatures, 973, 1073, 1173 K with a bed height of 0.5 cm, hydrogen flow rate of 400 cc/minute, and particle size of micron. The F vs t plots are shown in Fig. 4. It gives the extent of reduction, in a duration of 25 minutes, as 57.06%, 60.42%, 62%, respectively at the three temperatures. It was found from some additional experiments that the effect of temperature beyond 1173 K was not significant. Hence, this temperature (1173 K) was considered to be the optimum and the experiments for the purpose of studying the other variables were conducted at this temperature. On the basis of of the data shown in Fig. 4 it can be shown that F 2 has a linear relationship with t at each temperature, which supports the pore diffusion controlled kinetics for the experimental condition (flat plate geometry made by the powder bed). The linearity can be shown to occur with two different slopes. This means that the reduction (Fe 3 O 4 to Fe) does not occur in a single step. Instead, the course of the reduction can be divided in two segments. In the first 10 minute, the reduction of Fe 3 O 4 to FeO takes place and in the last minute, the reduction of FeO to Fe Effect of flow rate Reduction experiments were performed with four hydrogen flow rates, 100, 200, 300, 400 cc/minute, at 1173 K with a bed height of 0.5 cm. The resulting F vs t plots are shown in Fig. 5 which establishes that the extent of reduction, in a duration of 30 minutes, increases from 45% to 60% as the flow rate increases from 100 to 400 cc/minute. However, the effect of flow rate is not noticeable above 300 cc/minute. This means that the concentration gradient of hydrogen across the enclosed gas film became constant at the flow rates of 300 cc/minute and above Effect of bed height Reduction experiments were performed with three bed heights of 0.25 cm, 0.5 cm and 0.75 cm at 1173 K with the hydrogen flow rate of 400 cc/minute and particle size of micron. The masses of the starting samples corresponding to the bed heights were 115 mg, 417 mg and 610 mg. The resulting F vs t plots are shown in Fig. 6. The bed height of 0.5 cm was considered as the optimum Effect of partial pressure Reduction experiments were performed with three partial pressures of hydrogen, namely 1, 0.75 and 0.5 atm at a fixed temperature of 1173 K and with a fixed bed height of 0.5 cm. The resulting F vs t plots are shown in Fig. 7. The percentage reduction decreased from 60% to 50% as the p H2 decreased from 1 to 0.5 atm. Accordingly, a p H2 of 1 atm was maintained in the runs intended to study the effects of the other variables Effect of particle size Three different particle sizes, , , and micron, were employed to study the effect of magnetite ore particle size on hydrogen reduction at 1173 K and with a 0.5 cm bed height. The resulting F vs t plots are shown in Fig. 8. The particle size of micron resulted in the greatest degree of reduction and hence was considered as the optimum particle size Activation energy determination From the rate of reaction obtained from the isothermal reduction experiments at different temperatures, the activation energy for the reduction was calculated using the Arrhenius equation. This equation is expressed as: D pore = D o exp ( E D,pore /RT) where D o is a constant (pre-exponential), E D,pore stands for the activation energy for pore diffusion, 82

92 R is the gas constant, T is the temperature given in Kelvin and D pore is pore diffusivity. The equation yielded an activation energy of 33 kj/mol. Considering a porous bed, this value of the activation energy indicates that the rate was controlled by pore diffusion. Another experiment was performed at a heating rate of 10 C /min. The nonisothermal conversion is shown in Fig. 9. Initially, the rate of reduction slowly increased with increasing temperature up to 673 K. Subsequently, there was a rapid rise in the rate of reduction in the temperature range of K. Beyond 973 K and up to 1173 K, the rate of reduction drastically fell to zero. Fig. 7. Effect of partial pressure (F vs t) plot Fig. 4. Effect of temperature (F vs t) plot Fig.8. Effect of particle size (F vs t) plot Fig. 5. Effect of hydrogen flow rate (F vs t) plot Fig. 9. Non isothermal reduction plot Fig. 6. Effect of bed height (F vs t) plot 3.3 Characterization of reduction product at 1173 K Phase identification by XRD The XRD pattern of the post reduced magnetite reduced at 1173 K is shown in Fig. 10, which clearly establishes the presence of iron. As expected, the product was free from any unreduced magnetite or hematite SEM EDX studies 83

93 The SEM image of the product obtained from the hydrogen reduction of magnetite ore fines at 1173 K is shown in Fig. 11. No trace of melting or sintering is observed, which ensures that the reduction was purely gas solid type. In comparison to the unreduced grains, shown in Fig. 3 the reduced grains are nearly of same size, which means there was no change in overall grain size in the reduction process. The corresponding EDX results of reduced product are given in Table 2. In the reduced sample the oxygen concentration is reduced to 18% and Fe concentration is increased to 63%. Fig. 10. XRD pattern of the reduced sample Fig.11. SEM image of the reduced sample Table 2. EDX analysis of the reduced sample Element Weight% Atomic% O Mg Al Si P Ca Cr Fe Ni Total CONCLUSIONS A magnetite ore containing 31% O and 51% Fe was reduced by hydrogen. The parameters studied were temperature, hydrogen flow rate, sample bed height, hydrogen partial pressure and particle size. The degree of reduction went up to above 60%. The best result was obtained under the following experimental condition, temperature of 1173 K, 0.4 l/minute hydrogen flow rate, 0.5 cm bed height, 1 atm partial pressure of hydrogen and micron particle size. The reduction took place in two stages: Fe 3 O 4 FeO (during the first 10 minutes of the run) and FeO Fe (during the concluding stage, minute, of the run), each of which was controlled by pore diffusion kinetics. The activation energy was found to be 33 kj/mol (and 11 kj/mol in the second stage of the reduction). REFERENCES 1. Carlson B. (2010), The direct reduction of iron from its ore using traditional techniques, PhD thesis, South Dakota School of Mines and Technology, Rapid City 2. Chatterjee R., Banerjee S., Banerjee S. and Ghosh D. (2012), Reduction of nickel oxide powder and pellet by hydrogen, Transactions of the Indian Institute of Metals, 65 (3), pp Chatterjee A. (1993), Beyond the blast furnace., CRC Press, Boca Raton, USA 4. Fruehan R. J. (1998), Blast-furnace output will continue to fall, New Steel, 14 (5), pp Greene L. (2005), Ironmaking process alternative screening study, volume 1 (No. ORNL/TM-2005/7). ORNL 6. Sohn H. Y. (2007), Suspension ironmaking technology with greatly reduced energy requirement and CO 2 emission, Steel Times International, 31 (4), pp Takeuchi N., Nomura Y., Ohno K., Maeda T., Nishioka K., Shimizu M. (2007), Kinetic analysis of spherical wustite reduction transported with CH 4 gas, ISIJ International, 47 (3), pp Teplov A. O. (2010), Kinetics of the low temperature hydrogen reduction of single crystal Magnetite, Russian Metallurgy (Metally), 11, pp Wang H., Sohn H.Y. (2013), Hydrogen reduction kinetics of magnetite concentrate particles relevant to a novel flash ironmaking process, Metallurgical and Materials Transactions B, 44B, pp

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95 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh 3D FLEXIBLE SUPER-CAPACITOR ELECTRODES SYNTHESIZED VIA LAYER BY LAYER ASSEMBLY OF GRAPHENE- POLYANILINE NANOSTRUCTURES Mahbub Hassan and Vincent.G. Gomes* School of Chemical and Biomolecular Engineering, The University of Sydney, NSW 2006, Australia Stand-alone composite films were prepared via layer-by-layer (LBL) organization of polyaniline (PANI) nano-spheres coated with graphene oxide (GO) nano-blocks, followed by in-situ chemical reduction. Stable cationic polyaniline (PANI) nanospheres were first attached to the anionic GO sheets by electrostatic interaction and layer-by-layer deposition of GO/PANI nanostructures on a membrane filter via targeted selfassembly under vacuum. The reduction of GO on the assembled film using hydroiodic acid (HI) produced composites with its hierarchical organization intact. The interpenetrating network having a 3D open structure produced a flexible graphene/pani film using our scalable design method. The film was tested as a standalone supercapacitor electrode using voltammograms. The electro-capacitance of the film (448 F/g) was enhanced by 60% through the synergistic combination of graphene and PANI nanostructures. About 83% capacity retention was observed for the composite compared to 56% for PANI alone after subjecting the samples to 1000 operating cycles. 1. INTRODUCTION Supercapacitors are emerging key devices over today s batteries for electricity storage and supply because of their fast charge/discharge rates, excellent cycle stability and high power density. The main challenge in this field is the scalable fabrication of electrode with high electrochemical performance to meet the growing power supply requirements for a variety of applications, including portable electronics, implantable devices, electric vehicles and renewable energy storage (Armand and Tarascon, 2008, Goodenough and Kim, 2010). Based on the energy storage mechanism of the electrode materials, supercapacitors are categorized into two types, -: (a) the electrical double layer capacitor (EDLC), where the capacitance comes from the pure electrostatic charge accumulated at the electrode/electrolyte interface and, (b) the pseudo-capacitor (PC), in which fast and reversible faradic processes take place due to electro-active species. A conjugated polymer, polyaniline (PANI), is considered a promising pseudocapacitive electrode-material because of its high conductivity, thermal and environmental stability, and suitable redox behaviour. Nanostructured PANI in the form of dispersions, nanowires, nanotubes, nanofibres has shown significant property enhancement in different applications (Wang and Zhang, 2013). However, the electrode material made of pure PANI suffer from poor cycling performance and low rate capability due to the intrinsic capacitance decay upon repeated insertion and reinsertion of electrolyte ions. To address these issues the structurally robust and electrically conductive EDLC materials such as porous carbon, carbon spheres, cabon black nanoparticles, carbon nanotubes and graphene have been incorporated with polyaniline (Jiang et. al., 2013). Graphene, which has excellent electrical, mechanical, optical, chemical and surface properties, is widely utilized to prepare various hybrid materials (Bai et. al., 2011). The high surface areas of graphene accommodate the deposition of ionic charges upon electrostatic interactions and also act as nanocurrent collector on fast transport of electron from Faradic charge transfer reactions of the anchored pseudocapacitive polymer, and thus enhances the overall electrochemical performance of the hybrid composite (Rudge et. al., 1994). Composites of graphene/pani have been previously synthesized using various methods such as blending (Wu et. al., 2010), in-situ polymerization (Mao et. al., 2010) and electro polymerization (Wang et. al., 2009). However, the observed capacitance values are * Corresponding Author: Vincent G. Gomes, vincent.gomes@sydney.edu.au

96 mainly limited by the agglomeration of graphene sheets and do not reflect the intrinsic capacitance of an individual graphene sheet. In addition, the electrical conductivity and hierarchical organization of the original active material are affected when the working electrode is prepared by mixing with binder or additive (Stoller and Ruoff, 2010). But a free-standing and binder-free electrode with favourable flexibility and cycle stability are highly desirable to produce next generation flexible supercapacitors (Lin et. al., 2013). Free-standing graphene/pani paper were synthesized by polymerization on preformed graphene sheet (Wang et. al., 2009, Yan et. al., 2010)), but the noncovalently attached PANI on the graphene paper could easily be washed away upon repeated electrochemical cycling in a solution environment. Therefore, the design of mechanically stable and easy ions accessible 3D structure of nanoscale interpenetrating graphene/pani film is highly desirable. In this report, we represent a scalable and versatile strategy to fabricate three dimensional (3D) selfassembled hierarchical nanocomposite by the nanoscale interaction of polyaniline nanospheres (PNSs) and graphene nanosheets for supercapacitor electrode as schematically illustrated in Fig. 1. Fig. 1. A schematic diagram of process steps (a) Pre-mixing of PANI nanospheres and graphene sheets (b) PANI spheres attached to GO hybrid structure (c) Layer by layer (LBL) assembly of PANI/GO film (d) HI reduced porous LBL film of the scalable synthesis process of 3D hierarchical PANI/graphene composite The positively charged PNSs are attached on negatively charged graphene oxide (GO) sheets by strong electrostatic forces and further confined within layer by layer structures by vacuum assisted self assembly (VASA) process with in-situ chemical reduction by hydroiodic acid (HI). Such hierarchical PNSs/graphene composite induce synergism in capacitive performance by utilizing more exposed active surface areas of both materials. The graphene sheets are pillared by nanostructured PNSs and thus retard the restacking while the PNSs are sandwiched between graphene layers which improve the mechanical reinforcement of the electrode thereby realizing good cycling performance. The 3D open structure of PANI/graphene flexible composite deliver 60 % synergistic capacitive performance (448 F/g at 0.5 A/g) over PANI film (240 F/g at 0.5 A /g) on stainless steel electrode (SSE) with 82.8% capacity retention after 1000 cycles which is much higher than the 53.2 % of PANI. The result shows its potential application as electrode material in energy storage device and the proposed synthesis route can be extended to the synthesis of hierarchical nanocomposite using 0-D and 2-D nanocomponents for highly sophisticated applications as electronics and biomedical in the fields of electrochemical and biochemical engineering. 2. EXPERIMENTAL METHODS 2.1 Preparation of Polymer Nanospheres (PNSs) by Microemulsion Polymerization PNSs were prepared by microemulsion polymerization. Briefly, 3 g SDS was mixed in 30 ml deionized Milli-Q water in a beaker and magnetically stirred on an electrically controlled heater for 30 min. 1g aniline (Sigma-aldrich) was dissolved in 2.65 ml of 1 M HCl (32%) for 15 min and mixed with 10 ml Milli-Q water and pouring it in the SDS containing beaker. The mixture was kept stirring until the heater temperature reached to 60 0 C g Ammonium peroxydisulfate (Sigmaaldrich) was mixed in 7.35 ml water and the mixture was added drop by drop in the reactor. The reactor was kept stirring for 3 h to polymerize. Then the PANI was collected as a sphere suspension after being washed 8 times with 100 ml of deionized Milli-Q and two more washings with 50 ml acidic water (0.5 M HCl) through a 0.2 µm PTFE membrane filter. The wet sample was scraped off the membrane and the spheres were resuspended in water, precisely adjusted to different ph and concentrations. To determine the weight of sample, part of the sample was oven dried and weighted. 2.2 Preparation of PANI/GO Nanostructure GO was prepared by Hummer s method and purified by dialysis and the details are described somewhere (lei et. al., 2010). PNSs were diluted as 0.1 mg/ml and GO as 0.15 mg/ml with deionized water. Both suspensions were sonicated using a Branson 450 ultrasonic cleaner (40 khz) in Milli-Q water for 15 min and range of samples with different ph (2.5 to 11) were prepared for Zetapotential measurements. The final composition of the composite was set by controlling the volume ratio of GO and PANI suspensions. It was found during the study that 60 % graphene and 40% PNSs produced better morphology and electrochemical properties. Prior to mixing both 150 ml of GO (ph 3.5) and PNSs (ph 2.5) were kept under sonication for 15 min and then the PNSs dispersion 87

97 was added drop by drop into the as sonicated GO dispersion. The mixture was left in the sonication bath another 30 min for well coating of PNSs around GO sheets. 2.3 Preparation of PANI/Graphene Composite Film The dispersion of PNSs attached GO hybrid nanostructure was hierarchically assembled via vacuum assisted self assembly (VASA). An allglass vacuum filtration set up of Millipore was used with 0.2 µm PTFE membrane. Required amount of GO/PANI dispersion was poured in the system and vacuumed at low pressure. To improve the stability of the films, the vacuuming was continued even after all liquids were drained out. To keep the morphology unchanged the in-situ polymer reduction was adopted. The addition of 40 ml HI (55%) was carried out with several cycles such as the HI was uniformly dropped on the composite coated film and left for 5 min followed by slowly vacuumed at low pressure to ensure the inner penetration of HI into the composite matrix. At the half way of the last cycle the vacuuming was turned off and the specimen was left for 30 min in the system. The membrane was then transferred into an oven and remained at 90 0 C for 2 hr, rinsed with water and peeled off. For comparison GO was similarly reduced by HI. 2.4 Characterization The zeta potential of PNSs and GO as a function of ph was measured using Zetasizer-3000 (Malvern Instruments, UK) to determine the effect of surface charge on PNSs and GO dispersions. TEM was performed using JEM 1400 (JEOL, Japan) with an accelerating voltage till 120 kv with samples chosen randomly from the bulk vial with ten-fold dilution in ethanol. The drop casting method was employed to disperse graphene on a holey lacey 200 mesh carbon coated grid. SEM was carried out with a JEOL 6701 scanning electron microscope operated at 10 kv. UV vis absorption spectra (Varian Cary 50) were measured at wavelengths of nm. Raman spectra were recorded using an Invia Raman spectrometer (Renishaw plc, UK) with laser excitation source at 514 nm. XRD measurements were conducted by Siemens D-5000 using CuK α radiation. Electrochemical measurement of the cyclic voltammograms (CV), galvanostatic charge/discharge and electrochemical impedance spectroscopy (EIS) were conducted on an electrochemical analyzer (SP300, BioLogic Science Instruments, France) at room temperature within a voltage window from -0.2 to 0.8 V. Electrical impedance spectroscopy (EIS) measurements were recorded in the frequency range from 0.1 to 100 khz at a 10 mv amplitude referring to the open circuit potential. A conventional threeelectrode cell was used, including an Ag/AgCl (saturated KCl) electrode as the reference electrode, a platinum foil as the counter electrode. On the other hand the graphene and graphene/pani films directly as freestanding electrode while PANI film prepared by drop casting method on stainless steel electrode (SSE) were used as working electrodes in 0.5 M H 2 SO RESULTS AND DISCUSSION Electrostatic self-assembly is a suitable strategy to create well-defined nanocomposites. It is based on the electro-static attraction between consecutively adsorbed, oppositely charged species. PANI nanostructures were utilized (Lee et. al., 2009) as positively charged polyelectrolyte to build carbon based layer by layer composite. The GO with carboxylic acid (-COOH) and phenolic hydroxyl groups exist as anions (COO-) in aqueous solution (Li et. al., 2008), resulting in negatively charged GO. Polyaniline nanoparticles with nanosphere morphology were prepared by microemulsion polymerization. We found polyaniline nanospheres with diameters from 30~60 nm can easily accommodate on the microscale flat surfaces of GO sheets. To achieve a favorable nanoscale coassembly of polymer nanospheres and GO sheets it is necessary to determine the optimal surface charges of their stable colloidal dispersions. In this study, the cationic nature of partially doped PANI at ph~2.5 corresponding to + 42 mv was chosen to build hybrid nanostructure with the polyanion of GO at ph ~3.5 of zetapotential - 68 mv. These optimum surface charges along with dropwise addition of 0-D PANI on ultrasonically agitated 2- D GO dispersion formed a strongly interacting PANI coated GO hybrid nanostructure as shown in Fig. 3 (SEM) where the granular and agglomerated PANI nanosphers are tightly attached on the flexible and corrugated nature of GO sheets. To further elucidate the electrostatic adsorption between GO and PANI we investigated the Raman spectra of PANI and GO/PANI hybrid. Fig. 2. (a) Raman spectra of PANI, PANI/GO, PANI/graphene and graphene (b) SEM image of LBL morphology of PANI spheres coated with GO 88

98 Fig. 2 (a) shows the characteristics bands of PANI, such as C-H bending of the quinoid ring at 1180 cm -1, C-H bending of the benzenoid ring at 1228 cm -1,C-C stretching of the quinoid ring at 1415 cm - 1, and C-C stretching of the benzene ring at 1617 cm -1 were observed, revealing the presence of doped PANI (ES) structures. Beside other characteristic peaks C=C stretching of quinoid at 1590, C=N stretching of quinoid at 1495 and C-N stretching of benzenoid at 1338 are also observed for the PANI. In comparing the spectrum derived from the GO-PANI hybrid to that of PANI, a clear trend in the spectral position of the peak assigned to the C-N stretching of the cation radical species (C- N+) (Yan et. al., 2007) can be noticed. In the spectrum of PANI, this peak is at 1338 cm -1, whereas in the spectrum of composite, this peak is seen to shift to the higher wavenumber of 1347 cm - 1. The observed upshift of C-N+ stretching in the Raman spectra can be explained by the interaction between the C-N+ species of PANI and the COO - species of the GO. The strong cation-anion attraction increases the energy necessary for C-N+ stretching vibrations in the PANI molecule to occur, which is reflected in the higher frequency of the Raman peaks. The electrostatically built GO/PANI structures were hierarchically organized by vacuum assisted self assembly (VASA) process on a membrane filter. Layer by layer type morphology of PANI nanospheres coated GO is observed through SEM in Fig. 2 (b). To obtain the full potential of graphene it is required to reduce the GO sheets to graphene but the mixing of reducing agent can dismantle the hierarchical morphology of the GO/PANI nanostructures directed self assembled composite. Currently, no method exists to reduce GO in polymer while keeping the hierarchical morphology unaltered. Therefore we adopted in situ reduction of GO in PANI while undertaking VASA. The chemical reduction of the GO/PANI composite by HI under VASA converted GO into RGO. This is evident by comparing the UV-Vis spectra of GO, graphene/pani composite and PANI (Fig.3). Fig. 3. (a) UV-vis spectra of PANI, PANI/graphene and GO (b) SEM images of Porous (arrow mark) LBL structure of PANI/graphene film and the in-set of high magnification of circle mark of Fig. 3 (b) captures agglomerated PANI spheres on graphene sheets For PANI, the two peaks at 830nm and 430 nm are attributed to quinoid excitation and another short peak at 343 is assigned to the - * transition of the benzenoid ring. These three peaks are characteristic of doped PANI (emeraldine salt) (Feng et. al., 2011). The spectra of GO prior to mixing with PANI is found at 241nm. The red shift of the peak of GO from 240 to 270 denotes the restoration of sp2 electronic structure of graphene from graphene oxide (Zhu et. al., 2010). The spectrum of graphene/pani composite film is similar to that of the doped PANI, except a new peak at 268 nm is appeared which corresponds to the presence of graphene and this result clearly indicates the successful in-situ reduction of GO in PANI composite. In addition, the absorption peaks of the composite are broader and lower and appeared at high wavelength. These phenomena can be attributed to the strong - *conjugation of PANI with graphene (Feng et. al., 2011). Beside UV-Vis analysis, Raman spectra is utilized on reduced composite Fig. 2 (a) shows Raman spectra of the self assembled composite to confirm the nanostructure of graphene/pani along with the PANI nanoparticles and reduced graphene. The HI reduced graphene show two characteristics band at 1588 cm -1 ( G mode) and at 1360 cm -1 (D mode) for the disorder induced peak due to the defects in graphene sheets and edges. The strength of this peak is related to the amount of disordered graphite and the degree of conjugation disruption in the graphene sheet, the peaks exhibit successful in-situ reduction of GO in polymer as compared with previous report (Pei et. al., 2010). The intensity of graphene/pani remarkably decreases as they grow on the surface of graphene sheets. On the other hand, the C C and C-N stretching band 1590 and 1337 cm 1 red shift to 1582 and 1328 cm 1. The results suggest that the benzenoid unit concentration is increased in graphene/pani, which gives evidence that a π π interaction between the quinoid ring of the PANI and the graphene occurs. This interaction is believed to facilitate charge transfer between graphene and PANI and thus influence the charge-carrier transport properties of the nano hybrids (Yu et. al., 2012). The morphology of the vacuum assisted reduction of PANI/graphene material was investigated by SEM. Fig 3 (b) shows the layer by layer morphology of 3D polyaniline nanosphere coated graphene sheets with porous channels (arrow 89

99 mark). A magnification of the circle mark of Fig 9.a is presented by a high contrast image (Inset), where the presence of nanospheres on graphene sheet is clearly visible. Moreover in comparison to Fig. 2 (b) and Fig. 3 (b), the LBL morphology is clearly attained and the porous channels with compact features (Fig 3.b) are attributed to our vacuum drawn in-situ reduction process. Thus such a unique geometric matrix can allow easy penetration of electrolyte ions and their nanoscale level storage by utilizing both double layer and pseudocapcitance platforms. To fully exploit the benefits of such 3D open structure, the as produced film was cut into pieces and directly tested as working electrode Fig. 4. (a) &. (b) show the film is highly flexible and can be suitable as an electrode for a flexible supercapacitor. graphene/pani composite showed small deviations from linearity, due to the pseudocapacitive nature of PANI compared to graphene. The specific capacitance calculated from the discharge curves of the graphene/pani composite film was 448 F/g, much higher than that of the graphene film (133 F/g) and the PANI film on SSE electrode (241 F/g). Both the graphene /PANI and PANI films exhibited larger specific capacitances over graphene film. The gravimetric capacitance of graphene/pani film was also found to be higher than the equivalent compositional value of PANI and graphene in the composite (133* *0.4= 176). The 60 % enhancement in capacitance of the composite film indicates the synergistic effect of the nanoscale interactions of both components. Fig. 4. Optical images of synthesized graphene/pani film, (a) Cut to use direct working electrode (b) Shows flexibility of the electrode 3.1 Electrochemcal performance of graphene/pani film electrodes To test the prepared hierarchically organized nanocomposite as a super capacitor electrode, the electrochemical properties such as cyclic voltammetry (CV), galvanostatic charge/discharge, rate capability, cyclic life measurements were characterized within the potential window of -0.2 to 0.8 V. The CV curves at a scan rate of 10 mv/s of graphene/pani, PANI on SSE and graphene films are shown in Fig. 5(a) Graphene film exhibited a smooth shape with no apparent peaks, characteristic of the electric double-layer capacitance, while redox peaks for PANI and graphene/pani were attributed a pseudo-capacitance derived from redox transition of PANI (i.e., the leucoemeraldineemeraldine transition and the emeraldinepernigraaniline transition). It is evident that the current density for the composite film was much higher than that of the other two samples, suggesting its higher specific capacitance. To determine the specific capacitance of those three electrode materials, galvanostatic charge discharge measurements were carried out at a current density of 0.5 A/g as shown in Fig. 5 (b). The charge curves were nearly symmetric with respect to their corresponding discharge curves for the potential range tested. This indicates a high degree of reversibility between the charge and discharge processes. The charge discharge curves of the PANI film on the SSE electrode and Fig. 5 (a) CV curves of as prepared films of PANI/graphene, PANI on SSE and graphene. (b) Galvanostatic charge/discharge curves of as prepared graphene/pani, PANI on SSE and graphene films at the current density of 0.5 A/g. (c) Cycling stability of graphene/pani and PANI measured at 2 A/g A long cycle life of a supercapacitor is important for its practical applications. Fig. 5(c) shows the variation of retention rate with cycle number for graphene/pani and PANI at a constant current density of 2 A/g. We observe that the specific capacitance of the PANI film on SSE decreased sharply within 500 cycles, subsequently the slope of the curve reached a plateau, with 56% of the specific capacitance maintained after 1000 cycles. However, for graphene/pani composite, a decrease in capacitance only occurred within 200 cycles, while retaining 88% of its initial value. After 1000 cycles, there was still 83% capacity retention. 4. CONCLUSIONS High quality free standing flexible 3D PANI/graphene composite was fabricated by 90

100 hierarchical assembly of hybrid nanostructure of graphene and polyaniline nanospheres through a bottom up facile method. The PANI/graphene composite shows remarkable electrochemical performance with high specific capacitance, good rate capability, and extended cycling performance due to a rationally designed synthesis route. Furthermore, the synthesis route demonstrated here is scalable and can be exploited to produce a range of 3D open structured hierarchical composites for electrode materials in the emerging field of nanotechnology. ACKNOWLEDGEMENT MH gratefully acknowledges a scholarship based on ARC linkage project. REFERENCES 1. Armand,M and Tarascon, J. M., (2008) Nature, 451, Goodenough, J. B and Kim, Y., (2010) Chem. Mater, 22, Wang, J and Zhang,D., Adv. Polym. Technol., 2013, 32, Jiang, H., Lee, P.S., Li, C., Energy Environ. Sci., 2013, 6, Bai,H., Li,C., Shi,G., Adv. Mater., 2011, 23, Rudge, A., Raistrick, I., Gottesfeld S and Ferraris, J. P., (1994) Electrochim. Acta, 39, Wu, Q., Xu, Y., Yao, Z., Liu, A and Shi, G., (2010) ACS Nano,4, Mao,L., Zhang,K., Chan, H.S.O. and Wu, J. S., J. Mater. Chem., 2012, 22, Wang, D.W., Li,F., Zhao, J.P., Ren, W.C., Chen, Z.G., Tan, J., Wu, Z.S., Gentle, L., Lu, G.Q., Cheng H.M., ACS Nano, 2009, 3, Stoller, M.D., Ruoff, R.S., Energy Environ. Sci., 2010, 3, Lin, H., Li, L., Ren,J.,Cai1,Z.,Qiu1,L.,Yang,Z. and Peng,H., 2013, Nature Scientific Reports 3, Yan, X. B., Chen, J.T., Yang, J., Xue,Q. J., Miele,P., ACS Appl. Mater. Interfaces, 2010, 2, Lei, Z. B., Chen, Z. W. and Zhao, X. S., J. Phys. Chem. C, 2010,114, Lee. S. W., Kim, B. S., Chen, S., Horn, Y.S., Hammond, P.T., J. Am. Chem. Soc., 2009, 131, Li,D., Müller, M. B.,Gilje, S., Kaner R. B.,Wallace, G. G., Nat. Nanotechnol., 2008, 3, Yan,X. B., Han, Z. J., Yang, Y. and Tay, B.K., J. Phys. Chem. C 2007, 111, Feng, X.M.,Li, R.M.,Ma, Y.W., Chen, R.F.,Shi, N.E., Fan,Q.L. and W. Huang., Adv. Funct. Mater., 2011, 21, Zhu,C., Guo,S., Fang, Y. and S. Dong., ACS Nano,2010, 4, Pei,S., Zhao,J., Du,J., Ren,W., Cheng, H.M., 2010, Carbon, 48, Yu,H.,Wang,T., Wen,B., Lu,M., Xu,Z., Zhu,C., Chen,Y., Xue,X., Sun.C and Cao,M., J. Mater. Chem., 2012, 22,

101 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh EFFECT OF EXTERNAL SHADING AND WINDOW GLAZING ON ENERGY CONSUMPTION OF BUILDINGS IN BANGLADESH Md. Jahangir Alam 1*, Biplob Kumar Biswas 1, Mohammad Ariful Islam 2 1 Department of Chemical Engineering, Jessore University of Science and Technology, Jessore- 7408, Bangladesh 2 Department of Mechanical Engineering, Khulna University of Engineering & Technology, Khulna-9203, Bangladesh Energy efficiency of buildings is attracting significant attention from the research community as the world is moving towards sustainable building design. Energy efficient approaches are measures or ways to improve the energy performance and energy efficiency of buildings. External shading and window glazing influence the solar energy on a window and the conveyed energy within the room through the window. In our present study, the effect of advanced glazing and overhangs on the solar energy transmitted into or lost from the room through the fenestration areas have been evaluated for typical residential buildings in Bangladesh using EnergyPlus software. It was found that appropriate overhangs or side fins in the south, west and east windows would lead to the optimal reduction of the annual energy transferred into the buildings and can have an energetic behavior equivalent to high performance glazing. The results have been summarized to easy selecting the best window with different glazing, overhangs and side fins based on energy evaluation. 1. INTRODUCTION Population growth and economic progress have led to an increase in the demand for energy. The worldwide increase in demand for energy has put rising pressure on identifying and implementing ways to save energy. In global context, buildings account for a surprisingly high 40% of worldwide energy consumption (Krarti, 2012). If the energy consumed in manufacturing steel, cement, aluminum and glass used in construction of buildings is being considered, this consumption would be more than 50% ( Energy efficient buildings is an important factor related to the energy issue; according to Omer (2008) a building has three parameters directly related to energy consumption: thermal comfort (thermal conditioning), visual comfort (lighting) and air quality (ventilation). Energy consumption analysis of buildings is a difficult task because it requires considering detailed interactions among the building, HVAC system, and surroundings (weather) as well as obtaining mathematical or physical models that are effective in characterizing each of those items. The dynamic behavior of the weather conditions and building operation, and the presence of multiple variables, require the use of computer aid in the design and operation of high energy performance buildings (Zhu, 2006, Catalina, et. al., 2008). Windows have long been used in buildings for daylighting and ventilation. Many studies have even shown that health, comfort, and productivity are improved due to well-ventilated indoor environments and access to natural light. However, windows also represent a major source of unwanted heat gain/loss, discomfort, and condensation problems. But in recent years, windows have undergone a technological revolution. Highperformance, energy-efficient window and glazing systems are now available that can dramatically cut energy consumption and pollution sources: they have lower heat gain/loss, less air leakage and warmer window surfaces that improve comfort and minimize condensation. These high-performance windows feature double or triple glazing specialized transparent coatings, insulating gas sandwiched between panes that reduce the energy lost through windows. In addition, well-designed shading devices features reduce heat transfer and cooling requirements of buildings. Shading devices can also improve user visual comfort by controlling glare and reducing contrast ratios. This often leads to increased satisfaction and productivity. Shading devices offer the opportunity of differentiating one building facade from another. This can provide * Corresponding Author: Md Jahangir Alam, jahangirche@gmail.com

102 interest and human scale to an otherwise undistinguished design ( Rahman and Satyamurty (1999) investigated the difference between the values of shading factors for windows with overhangs calculated under extraterrestrial and terrestrial conditions and showed that the shading factor values evaluated under terrestrial conditions can differ by 25% compared to the extraterrestrial values for nonsouth facing windows shaded by over hangs. Francis and Milorad (2006) evaluated the impact of using switchable glazing on energy use for space cooling. Using software EnergyPlus, he found that application of switchable glazing would lead to a reduction in annual cooling electricity consumption by up to 6.6% where the actual amount depends on existence of overhangs, orientation of building wings, types and locations of rooms. Milorad and Francis (2007) also evaluated the energy saving that can be achieved by applying advanced glazing to a typical high-rise residential building in Hong Kong using the simulation software EnergyPlus. It was found that the application of low-e glazing would lead to a reduction in cooling electricity use by up to 4.2%. The saving due to application of low-e reversible glazing would be up to 1.9%; double clear glazing up to 3.7%; and clear plus low-e glazing up to 6.6%. The achievable saving would depend on orientation of building wings, and type and location of rooms. Singh (2009) investigated the energy rating of different window glazing available in the Indian market. This rating is helpful in selecting the best window for a given building and a given climate. He developed energy rating equations for different glazing, buildings and climates by regression analysis. Weir (1998) suggested the embodied energy of the four main materials used in the construction of an inert gas filled, double-glazed window. In the above mentioned research papers, it can be concluded that the energy transferred through the window depends on many parameters such as type of the window, overhangs and side fines and selecting the optimum window is very difficult. However, there is no significant information were found in the literature about building performance in the weather condition of Bangladesh. In present study, in the first stage, the effects of applying overhangs and side fins have been investigated on the single clear glazing window, and then the optimal condition has been obtained for Bangladesh weather conditions. At the second stage, the effect of advanced glazing windows are optimized and in the final stage the results have been summarized to simple selecting the best window with different glazing, overhangs and side fins based on energy rating. 2. SIMULATION TECHNIQUE Various building energy simulation softwares are used now-a-days to simulate building energy consumption and to design energy efficient building such as EnergyPro, EnergyPlus, EAB, REScheck etc. Among them EnergyPlus is developed by US department of Energy and it is getting popular to simulate and design of energy efficient building. 2.1 Simulation software The building energy simulation program EnergyPlus was used in our present study to predict annual energy use in the residential buildings of Jessore district in Bangladesh. EnergyPlus (version ) is made available by the LBNL in USA. EnergyPlus calculates thermal loads of buildings by the heat balance method. This method takes into account all heat balances on outdoor and indoor surfaces and transient heat conduction through the building. The simulation results of EnergyPlus have been validated through numerous analytical, comparative and empirical tests. Although EnergyPlus is capable of simulating heating, ventilation, and air conditioning (HVAC) systems, the details of HVAC systems are not modeled since the primary objective of the study was to examine the influence of windows on thermal loads of buildings. In EnergyPlus, the heat transfer by radiation, convection and conduction is calculated at each time step. The U-values are not constant through the simulation because the radioactive and convective heat transfer is calculated by algorithms that take into account parameters such as temperature difference between the surface and the air [Energyplus engineering document, 2006]. 2.2 Description of the building: The thermal performance of a residential one storied building (Fig. 1) including 1 m 2 windows have been located at the center of the wall of zones 1, 2, 3, 4 (south, east, west, and, north zone respectively) that has been evaluated by computer simulation. All the zones have been assumed to be maintained at the same temperature in the second floor and the energy is transferred only with exterior walls and windows into the zones. The thermal properties of the wall, ceiling and floor materials have been considered as ideal. Effect of four types of windows has been studied as follow: Single clear glazing (S.Clear) Double low-e Opaque glazing (D.L.O) 93

103 Double low-e Clear (Argon) glazing (D.L.C) Double clear glazing (D.Clear) Heat Loss Energy, the absolute value of the total heat flow through an exterior window when the total heat flow is negative. Also, the cp (coefficient of performance) index has been used for evaluating the shading effect and using of advanced glazing window that it has been determined from the following equation. (ii) (a) Plan of the building In equation (ii) E a is the total energy that it is transferred into the building from the single clear pane glazing window without overhangs or side fins (reference model). Also E b is the total energy that it is transferred into the building from the window (new model). In this new model the type of window, overhang and side fin are different with the reference one. Results have been shown in Table 1 for all Models. Table 1: Overhang and side fin configurations in all direction (b) Isometric view of the building Fig. 1: Computational building In the present study, the effects of window shading have been investigated for three cases: (1) Windows without overhangs and side fins. (2) Windows with overhangs and without side fins. (3) Windows with overhangs and side fins. Simultaneously the depth, the width and the distance above the window of the overhangs and the depth of side fins have been changed. In present study, window energy transfer (E) has been used for the declaration of the results and has been determinate from the following equation (i). (i) Hourly windows annual heat gain (or loss) has been calculated by EnergyPlus program and they have been declared as follow: Window Heat Gain Energy, the total heat flow to the zone from the glazing, frame and divider of an exterior window when the total heat flow is positive. The total window heat flow is the sum of the solar and conductive gain from the window glazing. Window Case Overhangs (m) Width Depth Distance above the window (m) The overhangs and side fins have been applied only at single clear glazing windows. Also the cp index for heating, cooling periods or for the year has been calculated. Taking into consideration the formula of the cp, it can be concluded that, increasing the cp index, leads to a decrease of the total energy transferred into the building from window. An assumption was made that all zones were ideally controlled by thermostats such that the zone temperatures would be kept steadily at 23 0 C in the year. 3. RESULTS AND DISCUSSION Side fin with 1 m width Depth of the right side (m) Depth of the left side (m) In this section, the cp index has been calculated for the heating and cooling periods or for the whole year. The results have been shown in Figs. 2 5 for each direction of the windows. 94

104 For the south window (Fig. 2), the best performance application case of overhangs and side fins is the case 6 (overhang with 2 m width, 1 m depth without distance above the window and a side fin in the left side of the window and 1 m 2 area). With attention to cases 1 6, it can be concluded that using of overhangs increase the annual average cp index (from 19% up to 44%). Also with increasing the cp index the energy consumption would lead to a decrease. Fig. 4: Results east window Fig. 2: Results for south window For the north window (Fig. 3), the best performance is obtained in the case 5 (overhang with 2 m width, 1 m depth without distance above the window and with a side fin in the right side of the window and 1 m 2 area). Taking into consideration the cases 1 6, it can be concluded that using overhangs increase the annual average cp index (from 18% up to 38%). For the west window (Fig. 5), the best performance has been obtained in the case 4 (overhang with 2 m width, 1 m depth and 0.2 m distance above the window and without side fins of the window). And With attention to cases 1 6, it can be concluded that using of overhangs and side fins, the cp index has only 9-20 % change during the heating or cooling periods. Fig. 5: Results west window Fig. 3: Results north window For the east window (Fig. 4), the best performance application case of overhangs is the case 4 (overhang with 2 m width, 1 m depth and 0.2 m distance above the window and without side fins of the window). With attention to cases 1 6, it can be indicated that using of overhangs increase the annual average cp index (from 15% up to 30%). Using of advanced glazing systems i.e., Double low-e Opaque glazing (D.L.O), Double low-e Clear (Argon) glazing (D.L.C), Double clear glazing (D.Clear) window, the ef index increase for each direction of the windows but Double low-e Clear (Argon) glazing (D.L.C) give highest cp index for south facing window and also save more energy. 4. CONCLUSION The final results have been evaluated to simple selecting the best window with different glazing, overhangs and side fins based on energy rating of 95

105 building in Jessore, Bangladesh. With attention to these values, the following conclusion remarks can be made: 1. For the south, windows of a single clear glazing window with an overhang (with adding the width) and side fin window is the best solution for case 6. Also, it can be noticed that using of appropriate overhang and side fin will lead to similar performance to the advanced glazing windows and a reduction in the cost. 2. For the north windows, using of overhangs or side fins (the case 5 especially) useful for heating, cooling periods. Also, it can be concluded that using of appropriate overhang and side fin will lead to similar performance to the advanced glazing, but using of double low- E clear (argon) glazing window is more useful. 3. For the west windows, using of overhangs or side fins (the case 4 especially) useful for heating, cooling periods. Also, it can be seen that using of appropriate overhang and without side fin will lead to similar performance to the advanced glazing, but using of double low-e clear (argon) glazing window is more useful. 4. For the west windows, using of overhangs or side fins does not a significant change in the energy transferred through the window into the building for heating or cooling periods. Although, using of the double clear glazing, Double low-e Opaque glazing and double low- E clear (argon) glazing window can lead to a considerable energy transfer reduction. 5. Usage of the most appropriate overhang or side fin that has been established for the single clear pane glazing is more useful for any direction of window than the advanced glazing windows (double clear glazing, low-e glazing). 5. Rahman, A.N. M. Mizanur, and Satyamurty, V.V. (1999), Overhang shading factor values for windows of general azimuthal angle evaluated under extraterrestrial and terrestrial condition, International Journal of Energy Research. 23, pp Singh, M. C., and Garg, S. N. (2009), Energy rating of different glazings for Indian climates, Energy, 34, pp Weir, G., and Muneer, T. (1998), Energy and environmental impact analysis of doubleglazed windows, Energy Conversion and Management. 39, pp Yik, F., and Bojic, M. (2006), Application of switchable glazing to high-rise residential buildings in Hong Kong, Energy and Buildings. 38, pp Zhu, Y. (2006), Applying computer-based simulation to energy auditing: a case study. Energy and Buildings, 38, pp Energy Efficiency in Buildings, (2009). Retrieved from Energyplus engineering document, The US department of energy. (2006), Retrieved from: < plus/>. 12. 'Whole Building' Design Guide, A program of the national institute of building sciences. Retrieved from: REFERENCES 1. Bojic, M., and Yik, F. (2007), Application of advanced glazing to high-rise residential buildings in Hong Kong, Building and Environment. 42, pp Catalina, T., Virgone, J., and Blanco, E. (2008), Development and validation of regression models to predict monthly heating demand for residential buildings. Energy and Buildings, 40, pp Krarti, M. (2012), Weatherization and energy efficiency improvement for existing homes: An Engineering approach. Mechanical and Aerospace Engineering Series, pp Omer, A. M. (2008), Renewable building energy systems and passive human comfort solutions. Renewable & Sustainable Energy Reviews, 12, pp

106 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh EFFECT OF PHARMACEUTICAL INDUSTRY EFFLUENTS ON SEED GERMINATION AND SEEDLING GROWTH OF SOME CULTIVATED CROPS Shamim Ahmed Hira and Md. Mizanur Rahman Department of Chemistry, Shahjalal University of Science and Technology, Sylhet Investigation was carried out to analyze the effect of effluent on seed germination and seedling growth of some cultivated crops. Alongside, study about their physico-chemical parameters has also been conducted. The effluent was collected from SILCO pharmaceutical company limited which is situated at Khadimnagar in Sylhet. Concentrations used were 0%, 25%, 25%, 50%, 75%. On the other hand four different types of crops (e.g. Okra, Data Shak, Ridge Gourd, Black mustard) were allowed to grow in presence of this effluent. The minimum relative toxicity was found to be 25% and increased further with the increasing concentration of effluent. Higher total dissolved solid (TDS) resulted a decrease in optimal crop production. A favorable effect on seed germination, seedling growth, shoot length and root length was observed at lower concentrations. An extremely high concentration of effluent caused inhibitory effect on the crops. On the basis of the study conducted, it can be concluded that pharmaceutical effluent which is discharged as waste can be used for irrigation purpose, after having gone through proper dilution. 1. INTRODUCTION Bangladesh is an agro-based country. Okra, Amaranths, Ridge gourd, Black mustard etc. are the most important vegetables of Bangladesh. Now-adays, pharmaceutical effluents are being discharged to agricultural farmland without any treatment. Treating waste effluents is very essential for cultivation of crops and environment. Even though the economy of Bangladesh is predominantly based on agriculture, the contribution of industries to our national economy cannot be denied. The important industries of this country include chemical, pharmaceutical, leather tanning, textiles, oil refinery, paper, fertilizer, sugar and so on. Effluent generated by these industries is one of the major sources of pollution. Contamination of air, water and soil by these effluents discharged from the industries give leads to many diseases and pose a major threat to human health. (WHO, 2002) The shorter life expectancy prevailing in the developing countries can be attributed due to pollution (WHO, 2003). At present, less than 10% of the effluent generated is treated while the rest of the untreated waste water is discharged into the nearby water bodies. The use of industrial effluents for irrigation has emerged widely in the recent days. Due to the presence of considerable amount of N, P, K and Ca along with other essential nutrients (Niroula 2003) the effluent streams are used for cultivation. There are both useful and damaging effects of waste water irrigation on crops. (Raman et el. 2002, Saravanamoorthy and Ranjitha kumari, 2007). Therefore, it is necessary to study the impact of these effluents on crop system before they are recommended for irrigation (Thamizhiniya et el. 2009). The present investigation was carried out to study the impact of untreated effluents discharged from pharmaceutical industries. on seed germination and growth of the four selected plant crops. 2. EXPERIMENTAL 2.1 Collection of the Effluents The effluents used in this study were collected in a pre-cleaned plastic bottle from SILCO pharmaceutical company limited which is situated at Khadimnagar, Sylhet. The effluents were stored at 4 C temperature in order to avoid physicochemical changes of properties. Various physicochemical characteristics were analyzed at the organic chemistry research laboratory of Shahjalal University of Science and Technology (SUST), Sylhet, Bangladesh. 2.2 Characterization of the Effluent The physico-chemical properties of the effluent samples were analyzed according to standard procedures (APHA, 1989). The results are given in Table 1. * Corresponding Author: Md Mizanur Rahman, rmizanur@sust.edu

107 2.3 Collection of Seed Materials The seed materials were collected from Surma Beeze Bhandar which is situated at Bandar bazar in Sylhet. Seed materials that were collected belonged to Okra, Amaranths, Ridge gourd and Black mustard. Experimental setup was the same as described by Nawaz et al. (2006). The percentage of germination of different crops was effected by different concentrations of pharmaceutical effluent which are listed in table 2 The outcome Germination test is described below: 2.4 Germination Study The healthy and uniform seeds were selected and their surfaces were sterilized with 0.1 % HgCl 2 before thorough washing with distilled water.. The germination test was carried out using 4 sterile petri dishes of 9, 10, 11, 12 cm in size. A double ring filter paper was placed on each petri dish. Distilled water was used to make solutions of varying effluent concentrations (0%, 25%, 50%, 75% and 100%). Each of the waste water samples was added to each petri dish in such an amount that would allow the seeds to get favorable moisture for germination and growth. 20 seeds of each agricultural crop and 15 seeds in case of Ridge Gourd were placed in the petri dishes. The petri dishes were set in the organic chemistry research laboratory at room temperature (30±2) C. The experiment extended over a period of nine days in order to facilitate germination. The measurements of the root and shoot length were noted. The results were determined by counting the number of germinated seeds, and also by measuring the length of primary root and main shoot on the 9 th day of the experiment. The data were subjected to analysis of Duncan s Multiple Range Test (DMRT) (Duncun, 1957).The ratio of germination and elongation were calculated as suggested by Rao and Kumar (1953) and by Hoque et. al. (2003). 3. RESULTS The physico-chemical properties of the pharmaceutical effluent are provided in table1. The effluent was dark brown in color. It consisted of high amount of oxygen demanding waste, along with excessive dissolved and suspended solids. The growing image was shown in Fig Germination Percentage 98 Fig. 1: Scheme of germination Here, C 0 = Seeds of receptor plants grown in distilled water only (control) C 1 = Seeds of receptor plants grown in waste water of 25% concentration C 2 = Seeds of receptor plants grown in waste water of 50% concentration C 3 = Seeds of receptor plants grown in waste water of 75% concentration C 4 = Seeds of receptor plants grown in waste water of 100% concentration A= Number of seeds in each petri dish B= Number of seeds Germinated C= percent of germination A, B and C are same in case of table 2, 3 and 4 D= Percent of inhibitory effect. (-ve inhibitory effect and +ve indicates stimulatory effect) D can be calculated by using the following equation, D= [for the first value of D] and D= [for the second value of D] Where c1, c2 and c3 are the first, second and third value C [e.g germination percentage] Other values of D were calculated in the same manner. Table 1: Physico-chemical parameters of pharmaceutical effluent S. No. Parameters Values Standards 1 Color Dark brown Colorless 2 Odor Unpleasant Odorless 3 Temperature ( C) ph Electrical conductivity (ms) Total solids (mg/l) Total Suspended Solids (mg/l) Total Dissolved Solids (mg/l)

108 9 Dissolved oxygen (mg/l) Biochemical Oxygen Demand (mg/l) Chemical Oxygen Demand (mg/l) ppm Table 2: Percent of seed germination of some cultivated crops Treatment Okra Data Shak Ridge Gourd Black Mustard A B C D A B C D A B C D A B C D C C C C C Table 3: Effect of pharmaceutical effluent on shoot length Treatment Okra Data Shak Ridge Gourd Black Mustard A B C A B C A B C A B C C C C C C Table 4: Effect of pharmaceutical effluent on root length Treatment Okra Data Shak Ridge Gourd Black Mustard A B C A B C A B C A B C C C C C C Fig. 2: Percentage seed germination of Okra at different effluent concentrations. Fig. 3: Percentage seed germination of Data Shak at different effluent concentrations 99

109 and seedlings growth is affected. Other researchers also reported that waste water contain some essential organic compound which increase growth of crop (Pathak et al. 1999, Ramana et al. 2000, Lubello et al. 2004, Nath et al. 2009). In case of Black Mustard there is no inhibiting effect by effluent on seed germination. 5. CONCLUSION Fig. 4: Percentage seed germination of Ridge Gourd at different effluent concentrations. It can be concluded from the study that physicochemical parameters such as ph, electrical conductivity, COD, TS, TDS, and TSS are relatively high in pharmaceutical effluent and it severely affects seed germination. The untreated pharmaceutical effluent could possibly lead to soil deterioration and low productivity. The effects vary from crop to crop because each plant species has its own tolerance level. Since, the effluents are toxic, it is suggested that further experiments should be conducted to achieve more scientific results regarding the effect of wastewater on various crops and plants. REFERENCES Fig. 5: Percentage seed germination of Black mustard at different effluent concentrations. 4. DISCUSSION Pharmaceutical effluent was chosen for the experiment and its effect was investigated on seed germination, root length, shoot length. According to Rodosevich et al. (1997) seed germination controls plants population, ensures reproduction and crop productivity. From the experimental outcome it may be inferred that for okra and Ridge Gourd, the rates of germination decreased with increasing concentration of the effluent. It means that high concentration of the pharmaceutical effluent is not suitable for these two species. In case of Data Shak the rates of germination increased with increasing concentrations of the effluent. It can be assumed that there are some essential organic compounds present in waste waters which may prove to be beneficial for plant growth. According to Panasker and Pawar (2011a, b) polluted water at low concentration does not inhibit the seedling growth but at higher concentration germination of seeds 1. WHO (2002), Water Pollutants: Biological Agents, Dissolved Chemicals, Non-Dissolved Chemicals, Sediments, Heat, World Health Organization, CEHA, Amman, Jordan 2. WHO (2003), The World Health Report, Shaping the Future, World Health Organization, 1211, Geneva 27, Switzerland 3. Niroula, B. (2003), Comparative effects of industrial effluents and sub-metropolian sewage of biratnagar on germination and seedling growth of rice and blackgram, Our Nature, 1, pp Ramana, S. et. al., (2002), Effect of distillery effluent on seed germination in some vegetable crops, Biorecourse Technology, 82, pp Saravanmoorthy, M., and Ranjitha-Kumari, B., (2007), Effect of textile waste water on morpho-physiology and yield on two varieties of peanut (Arachis hypogea L.), Journal of Agricultural Technology, 3, pp Thamizhiniyan, P. (2009), Sugar mill effluent toxicity in crop plants. Journal of Phytology, 1, pp American Public Health Association (APHA) (1989): Standards methods for the examination of water and waste water. 17 th edn. Washington, DC 8. Nawaz, S. et. al., (2006), Effect of industrial effluents on seed germination and early growth 100

110 of Cicer arientum, Journal of Bioscience, 6, pp Duncun, D. B. (1957), A significance test for difference between rank treatments between rank treatments in an analysis of variance, Virgina Journal of science, 2, pp Rao G.M., and N.V. Kumar (1983), Impact of Tannery Effluents on Seed Germination in Cicer Arintum, Poll. Res. J, 5, pp Hoque, A. T. M. R et. al. (2003),Suppressive effects of aqueous extracts of Azadirachta Indica leaf on some initial growth parameters of six common crops, Asian Journal of Plant Sciences, 2(10), pp Rodosevich S. et. al., (1997), Weed Ecology, Implications for Management. Wiley Publishers, New York, USA 13. Panasker D. B., and Pawar R. S. (2011), Effect of textile mill effluent on growth of Vigna unguiculata and Pisum sativum seedlings, Indian Journal of Science and Technology, 4, pp Panasker D. B., and Pawar R. S. (2011), Effect of textile mill effluent on growth of Sorgham vulgare and Vigna aconitifolia seedlings, Indian Journal of Science and Technology, 4, pp Pathak, H., et. al (1999), Soil amendment with distillery effluent for wheat and rice cultivation, Water, Air and Soil Pollution, 113, pp Lubello, et. al., (2004), Municipal-treated waste water reuse for plant nurseries irrigation. Water Research, 38, pp Nath, K., et. al., (2009), Phytotoxic effects of chromium and tannery effluent on growth and metabolism of Phaseolus mungo Roxb, Journal of Environmental Biology, 30, pp

111 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh ANALYZING ANNULUS PRESSURE BUILD-UP TO ASSESS WELL INTEGRITY A. Rashid Hasan Petroleum Engineering, Texas A&M University, College Station, TX Many wellbore integrity issues manifest as pressure build up in the production annulus. Because of the safety concern, most annulus pressure buildup occurrences have various reporting requirements and often must be addressed in a timely manner. The magnitude of the integrity issue often requires time consuming and costly testing that may include acoustic well sounding (AWS) or pulling the gas-lift valves off to surface. This paper presents a unified approach to modeling annulus pressure transients that result in testing procedures that are quick, unobtrusive, and allow determining the presence and magnitude of the integrity problem in a very cost effective way. 1. INTRODUCTION Demand for energy has led to drilling and production from deep off-shore resources, making well integrity an important issue. Production annulus in a well is often filled with mud and completely encased. Long production periods, especially at rates in excess of originally planned, could heat the liquid in the enclosed annulus. The ensuing annulus pressure buildup (APB) could be extreme, leading to casing failure. On the other hand, decommissioned gas wells have shown worrisome sustained casing pressure (SCP) increase; presumably due to gas seeping through poor cement jobs. Gas-lift wells will generally have only gas in the annulus but a leaking gas-lift valve (GLV) could allow tubing liquid to flow into the annulus, raising annulus pressure and wellbore integrity concerns. These disparate wellbore integrity issues have one common item; they all manifest as annulus pressure build up. Because of the safety concern, most annulus pressure buildup occurrences have various reporting requirements and often must be addressed in a timely manner. The magnitude of the integrity issue often requires time consuming and costly testing that may include acoustic well sounding (AWS) or pulling the valves off to surface. A few models to predict the SCP patterns exist. These are generally based on gas migration through a poorly bonded cement sheath placed around the casing. Xu (2001) presents such a model and discusses other works on the topic. Rocha-Valadez (2014) offers a complete survey of literature related to gas lift valve integrity and approaches to testing faulty gas lift valves. In this paper, our objective is to develop models for transient pressure behavior of fluid in the tubing/casing annulus for the appropriate physical system. 2. MODELING ANNULUS PRESSURE BUILDUP 2.1 SCP. Fig. 1 shows a typical wellbore, with a cement sheath placed around a casing, bonding it with the surrounding formation. If the cement bonds poorly, gas may seep through it and accumulate at the casinghead. Even at very low rates, the accumulated gas over time can exert pressure. If the pressure keeps rebuilding after being bled off, the casing is said to exhibit Sustained Casing Pressure (SCP). SCP inflicts mechanical stresses that compromise the integrity of the tubular and cement; i.e., SCP is indicative of compromised well integrity, possibly subjecting the operator to regulatory compliances. To model gas seepage through a cement thickness of L c ft. into the annulus, we use Darcy equation (in oil-field units) with average values for gas properties, kAT q L Z P T c i i sc sc p 2 f p 2 c (1) where q is in scf/d, k is in md, μ is in cp and pressures are in psia. Increased gas in the gas cap at the top will mean both an increase in its pressure, p * Corresponding Author: A. Rashid Hasan, rashid.hasan@pe.tamu.edu

112 and height, L h, due to compression of the mud column (of height L f ). We relate the rate of pressure increase, dp/dt, to gas seepage rate, q, and gas cap volume change rate, dv/dt, using the gas law with negligible variation in Z-factor, as follows, approach can be applied to model annulus pressure rise due to a faulty gas-lift valve (GLV). qpsc 1 dp dv V p (2) ZRTwb ZRT dt dt Increased gas column pressure will result in an increase at the cement top pressure, p c, that would lead to lowering of gas seepage rate, q. The change in gas volume dv, is equal and opposite to the change in mud volume (V i + c m V m p), thus, dv dp dvm cm Vm p (3) dt dt dt Combining the equations, we obtain the following expression for rate of pressure change, dp dt kat 0 sc 2 2 p f ( p m L f ) Lc i Z itwb 1 Vi cmvm p 1 1 cm p Using the following groups of parameters, (4) b L m f ; 2 2 m kAT d L Z P T 2 m 2bc b c c p bc 1 (5) m 2 f c i i sc sc wb m ; Fig. 1. Schematic of a well with SCP due to gas seeping through a poor cement sheath we write the solution for Eq. 4, in terms of time, t, as a function of pressure, p as shown in Eq. 6. t 1 A B C D (6) d where, A c m V m 2 tanh p f 1 1 p b p f B c V C V bc V (1 ) ln p b i m m 2 p f 2 m m ln c m p (1 ) Vi V m ln p f ( p b) 2 2 p 1 D (7) f Before we present the results of the SCP model represented by Eq. 6, let s discuss how the same Fig. 2. Schematic of a leaking GLV causing liquid to flow into annulus, allowing pressure rise. 2.2 GLV A faulty gas-lift valve will allow liquid from the tubing to flow in to the annulus after gas injection has ceased. The figure below sketches the process 103

113 and shows our attempt to model resulting pressure increase due to liquid inflow to annulus. As in the case of SCP, the annulus gas gets compressed, although, now, due to liquid ingress through the faulty GLV. The same approach as in SCP modeling can be applied to the gas volume in the annulus. Material balance can be set up allowing rate of pressure change to mimic liquid ingress rate. The method relies on calculating the total amount of gas in the annulus at each time step. Knowing the liquid level in the annulus and the casinghead pressure, the total volume of gas and its density can be calculated, leading to the computation of the total mass of gas. An estimate of liquid ingress rate can quantize the damage to the faulty GLV. For a shut-in case when amount of gas in the annulus remains constant, stabilized maximum pressure can be estimated from a few days worth of data instead of running the test for weeks, or even months. Fig. 4 shows that the percent error in estimating the maximum pressure does not really improve with more data gathered. Thus a few days test data should be all that needs to be gathered. We should note that the model expression has at least two unknown parameters, seepage constant k, and casinghead gas cap height, h thus, a minimum of two data are needed for the model to work. Indeed, our estimates of these parameters can be made more accurate through minimizing the errors between estimated and actual values of pressure; more data is needed to reduce uncertainty. dn dt 0 1 dv p V ZRT dt dp dt (8) Note that, we have assumed negligible variation in Z and T with time and represented them by their average values in Eq. 8. With further assumptions that are quite robust, we can develop the following simple expression for liquid level variation with casinghead pressure, L L p p (9) o o / A significant difference between SCP and the present case is that the volume of gas in the annulus in this case is orders of magnitude larger. Thus, while the gas law can still be applied to the gas in the annulus, the large depth and hence pressure difference between the casinghead and the GLV may need to be accounted for. Because density varies nonlinearly with depth, the annulus was subdivided into a number of cells for numerical integration of Eq. 8. The average pressure and temperature of a cell is used to calculate the gas density, which is then used to evaluate the mass in that cell, as well as the pressure difference across the cell. 3. RESULTS AND DISCUSSION 3.1 SCP Our SCP model was used to predict data from a number of wells. Fig. 3 shows very good agreement of our model with the data which came from Xu (2001). The general tendency of the model to overestimate casinghead pressure noted in data from other wells as well is probably due to cooling of the wellhead with time, a fact that was not considered in the model. The good agreement of the model with the data implies that the Fig. 3. SCP Model agreement with data from Xu Fig. 4. Error in maximum pressure estimate from SCP model as a function of number of data points 3.2 GLV Because of relative ease of access to the wellhead, on-shore wells or wells in shallow water allow Gas lift valve integrity testing. However, these integrity testing are often done using acoustic sounding to determine liquid level change with time in the annulus. Acoustic well sounding requires the casing head to remain open during the test thus requiring estimating of annulus liquid level during shut-in. We had access to some acoustic liquid level data gathered by a vendor from a well in shallow water. Unfortunately, the proprietary nature of the data 104

114 does not allow us its publication. We were pleased to see though that our estimates of rate of increase in liquid level in the annulus of this well after the casinghead has been shut-off agreed with the results obtained by the vendor. 4. CONCLUSIONS This paper presents broad principles that can be applied to test the integrity of a well annulus. Application of material and momentum balances to the fluid(s) in the annulus, along with fluid P-V-T properties, allowed us to design tests and analyze test data that are useful in determining the integrity of the well. Data available in the literature were used to validate the model developed for Sustained casing pressure. The adequacy of the model for determining GLV integrity is indicated proprietary data. REFERENCES 1. Rocha-Valadez, T (2014), Well Integrity Diagnostics for Sustained Casing Pressure and Faulty Gas-lift Valves Based on Pressure Transient Modeling. Ph.D. thesis, Chemical Engineering Department, Texas A&M University, College Station, TX., USA 2. Xu, R (2001), Analysis of Diagnostic Testing of Sustained Casing Pressure in Wells. Ph. D. thesis, Louisiana State University, Baton Rouge, LA, USA 105

115 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh REMOVAL OF REACTIVE DYE FROM WASTE WATER BY BATCH AND COLUMN ADSORPTION: BATCH AND KINETIC MODELLING M. R. Khan, 1,2* T. K. Deb, 2 K. Islam, 2 and M. R. Karim 2 1 Faculty of Chemical and Natural Resources Engineering, University Malaysia Pahang, Gambang, Kuantan, Pahang, Malaysia 2 Department of Chemical Engineering and Polymer Science, Shahjalal University of Science and Technology (SUST), Sylhet-3114, Bangladesh Adsorption has been an effective process for treating waste water since the very beginning, but the cost effectiveness and the availability of cheap and recyclable resource for the preparation of the adsorbent at large scale is still a big concern. In this study, development of adsorbent from the waste burnt clay and effectiveness of it for the removal of reactive textile dye from waste water have carried out. Activated burnt clay adsorbent was developed by the activation of the locally collected burnt clay and been used for the removal of reactive-nova-r dye from aqueous solution. Monolayer adsorption was determined to be the driving phenomena by the better fitting of the experimental data with the Langmuir isotherm than that for the Freundlich isotherm. The rate constants for the mass transport phenomena were calculated by the analysis according to 1 st order, 2 nd order and unified approach phenomena. For the prediction of the applicability of activated burnt clay-nova-r dye on industrial scale, laboratory scale adsorption column of different size (10 to 20 cm) were fabricated equipped with feeding by dye solution of different concentrations (50 to 150 ppm) and at different flow rates (5.5 to 15 ml/min.); and column design parameters including length of mass transfer zone, adsorption capacity etc were calculated. Also, modelling of the experimental data of column study was done using the empirical relationship based on Bohart Adams model and good correlation was obtained. 1. INTRODUCTION Water is one of the most important enablers of life on earth and is the purest symbol of wealth, health, serenity, beauty and originality. Water which is free of toxic chemicals and pathogenic bacteria is of topmost importance for living beings (Pradeep, 2009). In recent decades, water and environment are alarmingly reported to be severely contaminated by organic matters, especially by dye contaminants of textile waste water (Kavitha et. al., 2014). This effect is dominant in developing nations, like Bangladesh. Untreated textile waste water consists of a large variety of dyes and chemicals that make a big environmental challenge for textile activity not only for the liquid waste generated but also for its chemical composition (Stathatos et. al., 2001). Main contributor of toxicity in textile waste water is the wide range of dyestuffs, which are generally organic compounds of complex structure; and is the first pollutant to be known in wastewater (Banat et. al. 1997). As all of these are not contained in the * Corresponding Author: M.R. Khan, mrkhancep@yahoo.com final product, major portion became waste and finds way in the waste stream (Kavitha et. al., 2014). Due to the lacking of effective and cheaper approach, these compounds get released in to the nearby aquatic system and consequently severe changes and disruptions of ecosystem services results from the negative impact of these invasive aquatic species (Yagub et. al., 2014). In addition to the high intensity of colours, even in very little concentration (Banat et. al. 1997, Yagub et. al., 2014, Chu and Chen, 2002), dyes are reported to be carcinogenic, mutagenic, or teratogenic to the aquatic lives (Mittal and Gupta, 1996) and causes the lowering of the photosynthesis rate (Gupta et. al., 1990) and destructs the ecological balance (Prasad and Shanthi, 2012). It has been reported to cause severe impact to human beings such as dysfunction of the kidney, reproductive system, liver, brain and central nervous system (Kadirvelu, 2003). Also, dyes have direct and indirect negative effects on humans for jaundice, tumors, skin irritation, allergies, heart

116 defects and mutations (Hariharasuthan, 2013). As a demonstration of the impact, 3.5 million people are reported to die each year for water related diseases which is almost the entire city of Los Angeles (Water Facts Water). Consequently, it is of high importance to select an appropriate treatment method for the removal of dye from wastewater and to improve the quality of treated wastewater discharged into the environment. Presently, several techniques are used for the removal of textile dyes from wastewater, including chemical oxidation (Osugi et. al., 2009), anaerobic treatment (Abe et. al., 2011), coagulation (Lau et. al., 2014), membrane filtration and photocatalysis (Kant et. al., 2014) and so on, but the cost associated with such process and required techniques makes it difficult to adapt at all the situations. In such cases, adsorption has several additional advantages such as high removal efficiency, simplicity and easy operation of textile dyes containing wastewater. Also, a number of researchers have investigated different low-cost adsorbents prepared from boron waste (Olgun and Atar, 2011), bagasse pith (Pehlivan et. al., 2013), fly ash (Kara et. al., 2007), bottom ash (Atar and Olgun, 2009), industrial waste (Jain et. al., 2003), blast furnaces lag (Murillo et. al., 2006), silkworm pupa ( Noroozi et. al., 2007), red mud (Knocke et. al., 1981), hen feathers and agricultural waste residues (Teng et. al., 1995), wood, pyrolised tyres (Williams et. al., 1990), coal and banana pith, rice husk, de-oiled soya (Gupta and Mittal, 2006), fly ash, blast furnace slag, red mud, bottom ash (Mittal and Gupta, 1996) and so on and reported to be efficient for respective removals of dye. In this present study, a low cost adsorbent was developed from the locally available burnt clay and suitability of it for removal of reactive novo R dye has been studied. Isotherm and batch kinetic experiments were conducted to determine the equilibrium and kinetic parameters describing dye adsorption on clay adsorbent. The kinetic data was modeled by unified modeling approach and the rate constants of adsorption have been determined. The efficiency of this adsorbent was assessed by laboratory scale adsorption columns and important design parameters such as depth of exchange zone, adsorption rate, and adsorption capacity of a fixedbed column for this system have been studied. Breakthrough curves for the adsorption of dye were also analyzed by using the Bohart Adams model and characteristic parameters were determined. 2. MATERIALS AND METHODS 2.1 Materials The textile dye Reactive Novo-R and its homologous are used for yarn dying and was collected from a yarn dyeing company of Chittagong, Bangladesh. For the preparation of working solution, at first a stock solution of 1000 ppm was prepared by dissolving 1gm of dye in 1L double distilled water which was further diluted to prepare the working solution of desired concentrations. All other chemicals used in this study were of analytical grade and were used without further purification. Hydrochloric acid, Sulphuric acid and sodium hydroxide were purchased from Merck, Germany. Burnt clay was collected from local peanut seller (locally used for making the raw peanuts to be crispy after collection from local hilly track). It was sieved of large particles followed by washing by distilled water with vigorous shaking for removal of the objectionable dirt and contaminants. Then, the washed burnt clay was treated in 0.2 M H 2 SO 4 for 60 minutes with shaking at 300 rpm in a flask shaker, and cleaned with distilled water until the rinsing water ph be reached at 7. Finally, it was dried in an oven at 105 C overnight and the dried activated burnt clay was sieved using sieve shaker (Model: HMK14-DZ, China) and fractioned particle range of mm was used as adsorbent for adsorption experiment. 2.2 Analysis and Procedures of column study Determination of residual dye concentration after adsorption was done by spectro-photometric method in a UV-Spectrophotometer (UVspectrophotometer, model: UV-1601, Shimadzu, Japan) with prior centrifugation of the sample solution for 10 minutes. Batch adsorption test and isotherm study was done in a flask shaker operated at 300 rpm at room temperature (25±2 o C) by taking 200mL of dye solution with desired doses of adsorbent. The data for the isotherm study was taken after the equilibrium been reached. For the kinetic study, same protocol was followed with taking the measurement of residual dye concentration continuously with certain intervals. Fixed bed column studies were conducted by laboratory scale adsorption column made of polyacrylic tube (inner diameter= 2 cm and length = 30 cm) filled with packed adsorbent bed up to desired lengths (Fig. 1). For restricting the removal of adsorbent from the bed with effluent water, glass wool layers of 1 cm were employed at the top and bottom of the adsorbent column. The flow of feed solution was in downward flow mode and desired experimental flow rates were maintained by a peristaltic pump (Model: KAMOER, China). 107

117 Experiments were done with bed depths of 10, 15 and 20 cm, and in each case new columns filled with fresh adsorbent were used. The spent adsorbent were later used for the regeneration study by charging the regenerating agent in the opposite direction of the feed flow been used for the adsorption study. The working temperature of the column study experiment was 25±2 C, and the ph was 6.0±0.2 for experimental runs. Fig. 1: Experimental set-up for fixed bed column study where, and are the adsorption density at equilibrium (kg kg 1 ) and corresponding equilibrium dye concentration of the solution respectively. and n represent Freundlich isotherm parameters; specifying the sorption coefficient representing the quantity of adsorbed species for a unit equilibrium concentration and measure of the sorption intensity and/or surface heterogeneity respectively Khezami and Capart, 2005). The sorption equilibrium data fitted better to Langmuir isotherm (Fig. 2) with correlation coefficient value of which is then that for the Freundlich isotherm (Fig. 3) having the correlation coefficient value of Respective isotherm parameters based on equation 1 and 2 are summarized in table 1. Also the dimensionless equilibrium parameter or the separation factor (R L ) (Weber & Chakravorti et al, 1974), which indicates the shape of isotherm, was found in the range of 0<R L <1 within the entire range of concentrations used in the experiment indicating the isotherm to be favorable. In addition, the observed value of [1/n] from Freundlich isotherm as (i.e. <1) demonstrates the L-normal Langmuir isotherm (Fytianos et. al., 2000, Reed and Matsumoto, 1993). 3. RESULT AND DISCUSSION 3.1 Adsorption Isotherm Interpretation of the isotherm data were done by models of Langmuir (Langmuir, 1916) and Freundlich (Khan et. al., 2012). The better fitting of the experimental data with Langmuir model indicated the significance of monolayer adsorption of the molecules onto a homogeneously distributed and finite number of identical sites over the adsorbent surface. The linearized form of Langmuir isotherm equation can be represented as: Fig. 2: Langmuir adsorption isotherm plot (temperature =25 o C, shaking speed = 250rpm). (1) Where, is the amount of dye adsorbed on per unit mass of adsorbent at equilibrium (kg kg -1 ); is the maximum Langmuir adsorption capacity (kg kg -1 ); is the residual dye concentration (kg m 3 ) at equilibrium, and K is the adsorption equilibrium constant. Again, Freundlich isotherm describes the adsorption of the molecule onto a heterogeneous surface. The linearized form of Freundlich isotherm can be represented as: (2) Fig. 3: Freundlich adsorption isotherm plot (temperature =25 o C, shaking speed = 250rpm). 108

118 3.2 Adsorption kinetics study Assessment of the time dependence of the Reactive Nova-R-Activated clay adsorption system; namely, evaluation of the kinetics data was done by pseudofirst-order, pseudo-second-order, and unified approach models. The experimental result of the kinetic test indicates a higher rate of adsorption and consequent dominant removal of the dye contaminants at prior stages of the reaction followed by the gradually lowered removal rate after 35 minutes. This decreasing removal rate towards the end suggests the formation of monolayer coverage of dye molecules on the outer surface of the adsorbent at beginning, followed by diffusion onto the inner surface of the adsorbent particles through the film because of continuous agitation Pseudo 1st and 2nd Order Model The Lagergren pseudo-first-order rate expression (Khare et. al., 1987) has been applied for the determination of specific rate constant of adsorption for this system: (3) where, and q are the amounts of dye adsorbed (kg kg 1 ) at equilibrium and at time t (min), respectively, and are the rate constant of adsorption. Also, pseudo-second order rate equation (equation 4) developed by Ho and McKay (Ho and McKay, 1998) was applied for kinetic data assessment. Assuming the adsorption capacity of dye on the adsorbent particles is proportional to the active sites present on the surface of the adsorbent, the modified Lagergren equation (Ho and Mckay, 1999) is given as in equation 5. (4) Here, and are the sorption capacity (kg kg 1 ) at equilibrium and at time t respectively, and k is the pseudo-second-order sorption rate constant (kg kg -1 min 1 ); and linearized form after integration within the experimental boundary is: (5) A better fitting linearized plot (Fig. 4) of equation 5 with the experimental data than that for equation 4 (Fig. 5) highlights the higher applicability of pseudo 2 nd order kinetics expression for the entire range of contact time. Also, adsorption rate constant for different initial dye concentrations is calculated and presented in Table 1. It is important to note that for a pseudo-second-order-model, the correlation coefficient (R 2 ) is higher than 0.97 for all dye concentrations used and also experimental values of are in higher agreement with the calculated theoretical values, and therefore, the pseudo-firstorder model is not suitable for this adsorption system. Moreover, the observed values of the rate constant decreased with increasing initial dye concentration and is may be due to the lower competition for the sorption surface sites at lower concentration. At higher concentrations, the competition for the surface active sites is high and consequently lower numbers of sorption rates are obtained. Similar phenomena have been reported by (Ho and McKay, 1999, Ahmad and Kumar, 2010, Baskaralingam et. al., 2006) and more authors for different adsorption system. Fig. 4: Pseudo 2 nd order kinetic study (temperature =25 o C, shaking speed = 250rpm) Fig. 5: Pseudo 1 st order kinetic study (temperature =25 o C, shaking speed = 250rpm) 3.3 Unified approach modelling Although the kinetic data fit well with pseudosecond-order kinetic models, the observed rate constants are dependent on initial concentrations which make them difficult for application in adsorption process modelling. Here, kinetics model named Unified Approach Model was used to characterize the adsorbent adsorbate system using both equilibrium and kinetic concepts (Islam et. al., 2004) for the better assessment of the kinetics. The model is reported to be valid for the systems when the adsorption is governed by the Langmuir isotherm. It is considered that the adsorption process could be described by a physicochemical interaction: 109

119 A ac k k1 1 aca, K k2 k2 (6.a) where, A, ac and aca are the indication for the adsorbate, the active sites on the adsorbents and the active complexes respectively while the rate constant for adsorption, and the rate constant for desorption and the constant for Langmuir adsorption model are represented by k 1, k 2 and K respectively. The model is given by the following equation: dq k1 ( q q)( C0 waq) k2q (6.b) dt where, the amount of dye adsorbed (kg/kg) at time t, the initial concentration of dye(kg/m 3 ) and adsorbent dosage (kg adsorbent/m 3 of solution) are indicated by q, C o and w a respectively. At equilibrium, dq dt 0 ( C0 C ) q q e e, wa where, C e is the bulk dye concentration at equilibrium, q is the amount adsorption density at e equilibrium. At equilibrium equation 6.b reduces to the Langmuir equation and by solving we obtain the relation for q versus t as: 1 ( q ) ln k1t Y a( ) ( q ) and, ak1t e q (6.c) ak1t e 1 where, For,,,, and,. The value of for a given initial concentration and adsorbent dosage is same as β as determined from above equation. is determined from the slope of the equation 6.b and k 2 is determined from the relation. The k 1 and k 2 values are found to be independent of different initial concentrations and adsorbent dosages. By using the values of experimental k 1, k 2 and ; the theoretical lines of q(t) for different adsorbent dose and initial concentration are developed from equation (6.c) and indicated by solid lines in the plots, where the symbols represents the corresponding experimental q(t) values. From this plots it is evident that the experimental data fits quite well with the theoretically developed model (Fig. 6) representing the usefulness of unified approach modelling for describing this adsorption system. The equilibrium and kinetics parameters altogether with the co-relation factors are presented in table: I. Fig. 6 unified approach modelling of adsorption kinetic study (temperature =25 o C, shaking speed = 250rpm). 3.4 Column adsorption study For the packed bed adsorption column, time for breakthrough appearance and the shape of the breakthrough curve are very important characteristics in order to determine the operational feasibility and dynamic response. It also quantifies the loading behaviour of dye to be removed from the solution by fixed-bed columns and is usually expressed in terms of adsorbed dye concentration (C ad ), inlet dye concentration (C o ), outlet dye concentration (C), or normalized concentration [ratio of effluent dye concentration to inlet dye concentration (C/C o )] as a function of time or volume of effluent for a given bed height. Effluent volume ( ) can be calculated as: (7) Here, t and Q are the total flow time (min) and the volumetric flow rate (m 3 min 1 ). The area above the breakthrough curve [outlet concentration (C, kg m 3 ) versus t (min) plot] can be used to find the total adsorbed dye quantity and the column capacity [ (kg/kg)]. [kg/kg] (8) Here, w is the amount of adsorbent in the column (kg). A number of mathematical models have been developed which predict the mass transfer zone and concentration profiles in the bed. 110

120 Table 1: pseudo-first-order, pseudo-second-order, and unified approach kinetic model parameters of the adsorption system. Langmuir parameter Pseudo second order Pseudo first order Unified approach q e q e (calculated) K ads R 2 (calculated) K ads R 2 q e (calculated) K 1 K 2 C o q e q α K (mg/ L) (gm/gm) (gm/kg) (L/mg) (mg/gm) (min -1 ) (mg/gm) (mg/min) (gm/gm) L/(mg. min) (min -1 ) Among various design approaches, bed depth service time (BDST) approach based on Bohart Adams equation (Bohart and Adams, 1920) and proposed by Hutchins (to minimize the number of experiment requirement for determination of the service times) (equation 9.a-9.c) is widely used for the prediction of mass transfer zone and concentration profiles in the bed. or, (9.a) (9.b) (9.c) Here, is the initial adsorbate concentration (kg m 3 ); C is the outlet effluent concentration of the adsorbate (kg m 3 ); is the adsorption rate constant (m 3 kg 1 min 1 ); is the adsorption capacity (kg m 3 ); X is the bed depth (m); V is the linear flow velocity through the bed (m min 1 ); and t is the service time of the column (min). After the values of,, and been determined for laboratory columns, by using these equations, service time of a bed can be predicted for a specified bed length. 1) Behaviour of adsorption column: The breakthrough times and the exhaust times were considered as time of obtain C/C o = 0.1 and 0.9 respectively. The observed volume of treated effluent and the requirement of bed height up to breakpoint have been shown in Table II and a positive correlation was observed. The effluent concentration as a function of time for different bed height under constant flow rate and dye concentration is shown in Fig. 7. The depth of adsorption zone or mass transfer zone (MTZ) was obtained as 0.08 m. From the slope and intercept of the 10% bed saturation line, design parameters like K and N o was determined. Also, the minimum column height (X o ) necessary to produce an effluent concentration C(t) (10 mg/l) was calculated. The values of K c, N o and X o were found to be L/mg min, mg/l and 0.08 m, respectively indicating the system to be efficient for removal of dye from water environment ) Effect of flow rate and initial concentration: Columns were run with flow rates of 5.5 to 15 ml/min, whereas original flow rate was 10 ml/min under same initial dye concentration at 100 mg/l. The breakthrough and exhaust times (corresponding to 0.1 mg/l effluent concentration) were found to decrease with increasing of the flow rates (Fig. 8) which are in agreement with the respective literatures. Also these values were found comparable with the theoretically calculated values. Higher flow rates result in low residence times in the column, and inhibit the local equilibrium and thus cause lower capacity of dye adsorption from the bulk solution (Inglezakis and Grigoropoulou, 2004). Also, channelling increases with flow rate and causes the decrease of bed performance. Under the identical conditions, increment of the feed concentration caused the lowering of the dominant decline of the break through time and thus lower treated water volume, but the total adsorption capacities were observed to be the same. Fig. 7: Effect of bed depth on the performance of adsorbent column (temperature =25 o C, dye concentration = 100 ppm).

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124 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh CHARACTERIZING DENTAL EROSION POTENTIAL OF BEVERAGES AND BOTTLED DRINKING WATER IN BANGLADESH Fatima Enam 1, Mehnaz Mursalat 1, Upoma Guha 2, Nirupam Aich 3, Muzahidul Islam Anik 1, Mohidus Samad Khan 1* 1 Department of Chemical Engineering, Bangladesh University of Engineering and Technology (BUET), Dhaka-1000, Bangladesh. 2 Department of Operative Dentistry, University of North Carolina, Chapel Hill, NC USA 3 Department of Civil, Architectural, and Environmental Engineering, University of Texas, Austin, TX USA. Dental erosion, caused by prolonged direct contact between tooth surfaces and acidic substances, is a predominant condition that occurs worldwide. Dental erosion is the dissolution of minerals from the tooth surface as a result of exposure to nonbacterial acids. Hydrogen ions (H + ) from acidic solutions can replace the calcium ions (Ca 2+ ) of the enamel, consequently breaking the crystal structure of the enamel and initiating dental erosion. Erosive tooth wear can lead to severe impairment of esthetics along with loss of hardness and functionality. Acidic challenges responsible for dissolution of dental enamel and root dentin can be intrinsic (i.e. gastroesophaegal reflux disease) and extrinsic (i.e. exposure from acidic foods and beverages). Beverages such as soft drinks, energy drinks and fruit juices, and also bottled drinking water have often been linked to dental erosion. ph, titratable acidity, ionic strength, and mineral contents (calcium and phosphate concentration), are considered as the critical parameters for estimating the dental erosion potential of beverages and drinking water. Especially, continuous intake of drinks or food with ph lower than the critical erosive ph of enamel (5.2~5.5) and root dentin (~6.7) are considered to be majorly responsible for dental erosion, however, other parameters will contribute too. In Bangladesh, there is limited scientific information available to assess the potential of dental erosion of the commercially available beverages and drinking water. This article aims to characterize the dental erosion potential of beverages and bottled drinking water available in Bangladesh market. The experimental results indicate that all soft drinks, energy drinks, and juices have high erosive potential, while bottled water samples are potentially nonerosive. These results will be helpful in determining oral health hazard associated with habits of dietary drinks among population of Bangladesh. This study results will be useful for the health professionals, regulatory authorities, and government policy makers for quality control of the available beverages and bottled drinking water available in the local market. Finally, creating awareness among mass population regarding such health hazard potential of common dietary drinks can help remediate a recurring public health issue. 1. INTRODUCTION Dental erosion, acidic dissolution of enamel and dentin major components of dental hard tissue, has progressively become a major concern for detrimental dental health (Lussi 2006, Lussi, Schaffner et al. 2007). Erosion refers to the dissolution of tooth structure under continuous exposure to low ph, while not being associated with bacterial infection (Imfeld 1996). Replacement of minerals, primarily calcium from enamel or hydroxyapatite Ca 5 (PO4) 3 (OH) (s), can induce degradation of teeth structure and upon long-term exposure can lead to severe deleterious impacts on dental aesthetics and functionality such as loss of strength (Lussi 2006). Etiological studies report two major classifications of the causes of the dental erosion intrinsically by the gastroesophaegal reflux disease and extrinsically due to the exposure towards the acidic food and beverages (Zero 1996, Jensdottir, Arnadottir et al. 2004, DDS 2011). Soft drinks, beverages, and juices commonly consumed by the people of Bangladesh have low ph, and might be related to dental erosion issues. Dental erosion potential from regular diet can be appreciated from the ph and titratable acidity (TA) * Corresponding Author: Mohidus Samad Khan, mohid@buet.ac.bd

125 values of the commonly available drinks and food (Brown, Smith et al. 2007, Kitchens and Owens 2007, Cochrane, Yuan et al. 2012). ph values when reach threshold values below 6.7 and can potentially cause erosive wear to root-dentin and enamel, respectively (Dawes 2003, Featherstone and Lussi 2006). Fruits, juices, soft drinks, sports and energy drinks, and some cases bottled water can have ph lower or closer to such values and their continuous consumption can lead to such erosive potential (Larsen and Nyvad 1999, Brown, Smith et al. 2007, Kitchens and Owens 2007, Cochrane, Yuan et al. 2012, Pinto, Bandeca et al. 2013). While ph=-log[h + ] provides the amount of H + ions that will be available to cause replacement of minerals (e.g. calcium) from tooth structure, titratable acidity (TA) provides the amount of alkali required to neutralize the acid or in other words measures the erosive capacity of the food or beverage. The concentrations of calcium (Ca 2+ ) and phosphate (PO 4 3- ) ions and total dissolved solids (TDS) in the exposure media (ingested drinks or food and saliva) provide with the solubility product (K sp ) which eventually dictates the degree of dissolution of enamel (Cochrane, Yuan et al. 2012). Besides, other factors such as frequency of consumption, buffering capacity of saliva, temperature of the drinks, oral hygiene etc., also have shown to impact the absolute erosion caused by the drinks (Amaechi, Higham et al. 1999, Amaechi and Higham 2005). Compromise of dental health through erosion has been increasingly prevalent among both young and adult population worldwide as evidenced from epidemiological studies (Tsinidou 2000, Lussi, Schaffner et al. 2007, Johansson, Omar et al. 2011). A recent study conducted with 147 pregnant women in Dhaka city has shown the prevalence of dental erosion among 52% of the studied population (Mahmud, Begum et al. 2014). This indicates towards high risk for such erosive complications for the entire population. We believe this erosion prevalence will be more due to increased consumption of low ph drinks (as predicted from market research data), poor oral hygiene practice, lack of dental education and affordable dental care among general population of Bangladesh (Sarwar, Kabir et al. 2012, Trefis 2012, Khan, Zaman et al. 2013, Silvi, Islam et al. 2014). Therefore, it becomes essential that systematic evaluation of the erosive potential of commonly consumed food and beverages in Bangladesh has become imperative. However, lack of such studies presents with a critical knowledge gap. The objective of this study is to experimentally analyze different dental erosion indicating parameters, such as ph, TA, TDS, PO 4 3, Ca 2+, of the soft drinks, energy drinks, fruit juices, and bottled drinking water available in the local market of Bangladesh, and evaluate the potential erosive hazard associated with these drinks. 2. MATERIALS AND METHODS 2.1 Sample collection Locally available and/or produced beverages and bottled drinking water samples were collected from different markets and super shops of Dhaka, Bangladesh. The collected samples were broadly classified into four categories: a) soft drinks (14 brands), b) energy drinks (4 brands), c) fruit juices (12 brands; all were mango juices), and d) bottled drinking water (8 brands). For each brand, three (3) samples of different production batches were collected. 2.2 Chemical analyses All the chemicals used were reagent grade. Each test was repeated three times (i.e., samples from three batches and three tests for each sample) and the average results were used for further analysis. All the tests were carried out at room temperature. The ph of each sample drink was measured immediately upon opening. A calibrated bench top ph meter (Hanna HI2211) was used to measure ph of the samples. A HACH Model Conductivity/TDS Meter was used to measure the TDS of the samples. The TDS of each sample drink was measured immediately upon opening. For carbonated samples, however, the samples were allowed to sit till some of the gas escaped. The titratable acidity (TA) of each sample was measured by titrating 25 ml of each sample with 0.1M NaOH, using phenolphthalein as the indicator. For the samples with an intense color (e.g. black cola), the samples were diluted for accuracy in determining the endpoint. The calcium (Ca 2+ ) concentrations in the samples were determined using complexometric titration method. Ethylenediaminetetraacetic acid (EDTA) solution was prepared by dissolving g of reagent grade EDTA (Sigma Aldrich) in 500ml of water to prepare a 0.01M solution. A ph 11 buffer solution was prepared to maintain an alkaline environment which would help any magnesium precipitate; else the EDTA would simultaneously complex with the magnesium ions. 25ml of the samples were titrated with the EDTA solution, using Calcon as the indicator. The phosphate content of the beverage samples were measured using spectrophotometer (Hach UV/vis spectro-photometer, DR4000). 10 ml samples of the beverages were taken into cuvettes, diluted appropriated so as to reduce color effect or reduce the phosphate (PO 4 3- ) concentration 116

126 below the maximum threshold of the equipment. Using the preset program for determining total phosphate as orthophosphate, the procedure was carried out. 3. RESULTS AND DISCUSSION The mean values of the experimental results of TDS, ph, TA, phosphate and calcium contents of soft drinks, energy drinks, fruit juices and bottled water are shown in Table 1. The ph, TDS, TA, phosphate and calcium contents of different beverages and bottled drinking water are graphically represented and compared in Fig. 1a-e respectively. 3.1 Soft Drinks Prolonged exposure of teeth to food or drinks with ph values below critical dental erosive ph values can lead to potential dental hard tissue removal by demineralization (Dawes 2003, Fraunhofer and Rogers 2004, Featherstone and Lussi 2006). The soft drink samples had the lowest ph values, with the black cola drinks having the minimum, all below ph 3 (Table 1, Fig. 1a). Low ph and presence of orthophosphoric acids can dissolve protective protein layers deposited on teeth by salivary fluid. Then the drinks can diffuse inside the enamel and can cause leaching of minerals. The black cola drinks had the highest levels of phosphate (PO 3 4 ) - compared to other samples (Fig. 1d). Amongst the black colas Mojo exhibited high 3- PO 4 content, while both Mojo and CocaCola contain relatively high calcium (Ca 2+ ) content compared to other soft drinks (Fig. 1d, e). Virgin Red had the highest TDS while Sprite had the lowest (Fig. 1c). The results for erosive potential for soft drinks are consistent with prior reports for other countries (Fraunhofer and Rogers 2004, Jensdottir, Arnadottir et al. 2004). 3.2 Energy Drinks The energy drinks category had slightly higher ph than the soft drinks (Fig. 1a) but TA values were much higher compared to the soft drinks (Fig. 1c). Studies carried out on sport and energy drinks show that they have a high erosion potential relative to other drinks, which is consistent with studies from other countries (Kitchens and Owens 2007, Pinto, Bandeca et al. 2013). The phosphate levels in energy drinks were found to be lower than that of the soft drinks, especially, black cola drinks (Fig. 1d). Amongst the samples, calcium, TDS and TA were found higher in Red bull compared to other energy drinks (Fig. 1e). The other energy drink Tiger was found to be rich in phosphate as compared to other samples. 3.3 Fruit Juices Fruit juices have a considerable higher ph (>3) but with similar titratable acidity as soft drinks (Fig. 1a, c). This indicates the high erosive potential of the juices which is consistent with literature findings (Larsen and Nyvad 1999). This was true for all the mango juices available in the local market. The concentrations of phosphate were low but calcium content was found higher as compared to other beverages (Table 1). Ceres Mango was found to be more acidic with higher TA (Fig. 1a-b) while Sundrop exhibited the highest calcium and phosphate content among all the juice samples (Table 1). 3.4 Bottled Water The experimental results show that locally available bottled drinking waters possess much lower erosive potential compared to the soft drinks, fruit juices, and energy drinks available in the local market. All the bottled water samples had a ph over 6.7, most of them having a ph over 7, and with almost negligible TA (Table 1; Fig. 1a, c). With the exception of spring water (Evian), other samples had negligible amounts of calcium and phosphate. Among the samples, Spa and Evian showed greater phosphate and calcium content respectively than any other sample (Table 1), while Efad and Aquafina were found to have higher TA (Table 1). All these results indicate towards significantly lower to almost no erosive potential of teeth upon exposure towards bottled drinking water. 3.5 General Comments The experimental results show that all the beverages locally available were acidic, with the soft drinks category having the lowest ph values, followed by the energy drinks, the fruit juices and finally the bottled water samples having a ph close to 7. It is noticeable that most of the samples had a ph below 4.5 which is way below the critical erosive ph values for enamel ( ) and dentin (6.5), indicating high erosive potential upon continuous or recurrent consumption with the exception of bottled water samples (Featherstone and Lussi, 2006). TA was the highest for the energy drinks, although the ph values were comparatively less acidic. Calcium was present in high levels in fruit juices compared to other beverages, with extremely low levels in most soft drinks. Phosphate levels, on the other hand, were high in black cola drinks and negligible in others. Presence of minerals (Ca 2+ ) and dissolved solids (TDS) can induce resistance to dissolution, which can somewhat alter the erosive potential (Featherstone and Lussi 2006, Cochrane, Yuan et al. 2012). 117

127 Bottled drinking water Fruit juices Energy drinks Soft drinks 4. CONCLUSION The present work has shown that beverages commonly available in Bangladesh have dental erosion potential based on the values of different physicochemical properties affecting enamel dissolution. Besides the low ph, indicative of high possibility for demineralization owing to acidity, the titratable acidity values of certain beverages, especially those of energy drinks, showed greater risks of erosion. However, high levels of calcium and phosphate ions present in soft drinks may also influence the potential for enamel dissolution. Although, the erosion potential of the beverages were estimated based on parameter values reported in established literature, future in vitro studies, planned and initiated, with teeth samples exposed to these samples will be able to determine the actual degree of dental erosion. However, evaluation of dental erosion potential, like this present chemical analyses and future in vitro studies, will serve as the basis for determining the potential erosion risk towards the population of Bangladesh. Finally, creating awareness among general public, health workers, and nutritionists about the dental health hazard attributable to regularly consumed food and beverages is critical to averse forthcoming high prevalence of erosion induced dental diseases and also to improve overall oral health of the population. ACKNOWLEDGEMENT This research was supported by BCEF Academic Research Fund. Table 1: TDS, ph, TA, phosphate and calcium contents of soft drinks, energy drinks, fruit juices and bottled drinking water Sample Total Dissolved Solids (TDS), ppm ph Titratable Acidity (TA), mg/l as CaCO 3 Phosphate (PO 3-4 ), ppm Calcium (Ca ++ ), ppm CocaCola Fanta Sprite Pepsi Mirinda Orange Up Mountain Dew RC Cola Uro Orange Virgin Red Mojo Clemon RC Club Soda Appy Fizz Red Bull Speed Tiger Power SunDrop Mango Ceres Mango Danish Mango Frooto Mango Fruitika Mango Mangolee mango Shezan Mango Pran Mango Aquafina Mum Ifad Acme Evian Spa Fresh Pran Jibon

128 (a) (b) (c) (d) (e) Fig. 1: Dental erosion indicating parameters of beverages and bottled drinking water. a) ph, b) TDS, c) TA, d) phosphate, e) calcium 119

129 REFERENCES 1. Amaechi, B., S. Higham and W. Edgar (1999). "Factors influencing the development of dental erosion in vitro: enamel type, temperature and exposure time." Journal of oral rehabilitation 26(8): Amaechi, B. T. and S. M. Higham (2005). "Dental erosion: possible approaches to prevention and control." Journal of Dentistry 33(3): Brown, C. J., G. A. Y. Smith, L. Shaw, J. Parry and A. J. Smith (2007). "The erosive potential of flavoured sparkling water drinks." International Journal of Paediatric Dentistry 17(2): Cochrane, N. J., Y. Yuan, G. D. Walker, P. Shen, C. H. Chang, C. Reynolds and E. C. Reynolds (2012). "Erosive potential of sports beverages." Australian Dental Journal 57(3): Dawes, C. (2003). "What is the critical ph and why does a tooth dissolve in acid?" Journal- Canadian Dental Association 69(11): DDS, Y.-F. R. (2011). "Dental Erosion: Etiology, Diagnosis and Prevention." The academy of Dental Therapuetics and Stomatology 31(8): Featherstone, J. and A. Lussi (2006). "Understanding the chemistry of dental erosion." 8. Fraunhofer, J. A. v. and M. M. Rogers (2004). "Dissolution of dental enamel in soft drinks." General Dentistry 52(4): Imfeld, T. (1996). "Dental erosion. Definition, classification and links." European journal of oral sciences 104(2): Jensdottir, T., B. Arnadottir, Thorsdottir and A. B. K (2004). "Relationship between dental erosion, soft drink consumption, and gastroesophageal reflux among Icelanders." Clinical oral investigastion 8: Johansson, A.-K., R. Omar, G. E. Carlsson and A. Johansson (2011). "Dental Erosion and Its Growing Importance in Clinical Practice: From Past to Present." International Journal of Dentistry. 12. Khan, M. H. A., K. Zaman, S. Islam, M. M. Islam, M. G. Sarwar and M. M. Rahman (2013). "Evaluation of school oral health education program- A review." Bangladesh Journal of Dental Research & Education 3(2): Kitchens, M. and B. Owens (2007). "Effect of Carbonated Beverages, Coffee, Sports and High Energy Drinks, and Bottled Water on the <i>in vitro Erosion Characteristics of Dental Enamel." Journal of Clinical Pediatric Dentistry 31(3): Larsen, M. and B. Nyvad (1999). "Enamel Erosion by Some Soft Drinks and Orange Juices Relative to Their ph, Buffering Effect and Contents of Calcium Phosphate." Caries Research 33(1): Lussi, A. (2006). Dental Erosion :From diagnosis to therapy. 16. Lussi, A., M. Schaffner and T. Jaeggi (2007). "Dental erosion - diagnosis and prevention in children and adults." International Dental Journal 57(6): Mahmud, S. Z., F. Begum and M. M. Uddin (2014). "Assessment of common oral and dental diseases among pregnant women at Dhaka city in Bangladesh." South American Journal of Medicine 2(2): Pinto, S. C., M. C. Bandeca, C. N. Silva, R. Cavassim, A. H. Borges and J. E. C. Sampaio (2013). "Erosive potential of energy drinks on the dentine surface." BMC Research Notes 6(67): Sarwar, A. F. M., M. H. Kabir, A. F. M. M. Rahman, N. A. Kasem, S. A. Ahmad, P. K. Debnath, P. C. Mallick, M. M. Hoque, K. A. Hossain, S. I. Khan, A. H. H. U. Ahmed and S. Parveen (2012). "Oral hygiene practice among the primary school children in selected rural areas of Bangladesh." J. Dhaka National Med. Coll. Hos. 18(1): Silvi, A. S., M. S. Islam, M. A. J. H. Chowdhury, M. Z. Hossain, M. M. Zannath, A. Akter, M. R. Amin and M. A. Hossain (2014). "Awareness among caregivers on oral health of children." American Research Thoughts 1(2): Trefis. (2012). "Coca Cola update: Bubbling abroad with Bangladesh expansion." Retrieved December 5, 2014, from oca-cola-update-bubbling-abroad-with-newbangladesh-bottler/ Tsinidou, K. (2000, 2009). "Prevalence of Dental Erosion in Children and Young Adults and the role of diet." Retrieved 16 October, 2014, 2014, from Zero, D. T. (1996). "Etiology of dental erosion - Extrinsic factors." European journal of oral sciences 104(2):

130 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh TOXICITY OF TEXTILE MILL EFFLUENTS Afrina Samain, AKM Ahsanul Islam, Akber Hakim, Khaliqur Rahman* Engineering Resources International House: 60, Road: 18, Block-J, Banani, Dhaka 1213, Bangladesh Toxicity of Textile Mill Effluents (TMEs) is estimated based on literature data on Lethal Concentration 50 percent (LC50) of eight chemical groups: Salts, Nonylphenol Ethoxylates (NPEs), non-npes, Phosphates, Dyes, Dye carriers, Solvents and Chelates present in different effluent discharges. While many chemicals are present in TMEs, these groups are considered to be most significant, either because a group is more potent, or because the group is present in high concentrations. Steam and water balances of a typical textile mill are obtained based on Time-Temperature diagram of dyeing operations of a 15 tons per day (t/d) textile mill and toxicities of different effluent streams are estimated from a combination of factory data, industry practice and literature data. The toxicities of different discharge streams vary widely and based on their values it is possible to segregate the streams into three categories as Heavy, Medium and Light with relative toxicities 57.7, 2.2 and 0.5 and flows 525, 1380 and 556 m 3 /d respectively. For the combined stream of all effluents, these values are 13.7 and 2461 m 3 /d respectively. TMEs may be treated with or without segregation of streams, but consideration of toxicity clearly brings out the advantage of flow segregation. The bulk of the effluent, characterized as Medium may be treated using conventional techniques, while the highly toxic portion of considerably smaller volume may be treated to recover both chemicals and water. The Light effluent may be recycled with little treatment. Design considerations of treatment facilities for TMEs are generally based on BOD and COD loadings, but consideration of toxicity strengthens the rational for a comprehensive design. A more definitive estimate of toxicities of TMEs require further in-depth study. 1. INTRODUCTION Toxicity of an effluent is a measure of its poisonous characteristic. In the literature, TMEs are often referred to as toxic, but most do not go beyond this statement. In some cases, toxicity due to metals from dyeing sources is mentioned at best. TMEs are generally described by ph, Temperature, BOD, COD and other variables. While the technical options of an effluent treatment plant (ETP) design on effluent composition may be reasonably understood, toxicity per se is not considered a design variable. This paper makes an attempt to determine the toxicity of effluent streams based on available literature and outlines a strategy for design of effluent treatment facilities. One of the very few works that are available on toxicity of TMEs is the Marbek Report (2001) on Textile Mill Effluents Study: Identification and Evaluation of Best Available Technologies Economically Achievable (BATEA) for Textile Mill Effluents submitted to Environment Canada and the present paper is based on the findings of this report. 2. BACKGROUND toxicity of an effluent is determined from the toxicity and concentrations of these chemicals. The lethal toxicity of a substance is measured by determining the concentration at which an effluent has an effect on survival, growth, and reproduction of test organisms. An effluent is not acutely toxic if less than 50% test species die in 100% effluent (i.e. without having any dilution). The Marbek model is based on subchronic and acute tests to determine this lethal concentration. A subchronic test is a 4-8 day test and an acute test is a short-term, typically 48 to 96 hours, survival determination test. On the other hand, a full chronic test lasts one or more life cycles and may range from a month to more than a year. Because most TMEs are discharged to a freshwater environment, Marbek study uses data for freshwater organisms with priority for fish species. Lethal concentration 50% (LC50) is used to measure the aquatic toxicity of a chemical compound in an aqueous solution and is normally expressed in mg/l or ppm. The relative toxicity, may be defined in terms of - the concentration of chemical i and - the LC50 value of chemical i as: The toxicity of TMEs is due to the combined effects of many different chemicals and the level of * Corresponding Author:Khaliqur Rahman, khaliqur@gmail.com

131 Table 1. LC50 Toxicity Data of Textile Mill Effluent Chemical Group Process Source LC50 (ppm) Salts Salts use is large and quantity factor may contribute to toxicity; also a source of toxic metals; originate mainly from dyeing NPE surfactants Surfactants are highly toxic; used in desizing, scouring, mercerizing, 4.6 Non-NPE surfactants bleaching, finishing, and dyeing in appreciable amounts. Surfactants are divided into two groups, nonylphenol ethoxylates (NPEs) and 4.7 others (non-npes). Phosphates Phosphates (salts or esters of phosphoric acid) are toxic at high concentration; used as bleaching and buffering agents, surfactants, 73 flame retardant finishes and water conditioners. Dyes Many dyes have low toxicity (LC50>180), but some are highly toxic (LC50<10); metalised mordent dyes could be a source of toxic metals. 6.2 Dye carriers Dye carriers are highly toxic; used to accelerate dyeing and are relatively insoluble in water. 2.5 Solvents Toxic chlorinated compounds; used in scouring. 4.5 Chelating agents Chelates also contribute to toxicity; used as major additives in bleaching. 207 Table 2. Operating Variables of a typical textile mill Operating Variables Value Unit Remark Capacity 15 t/d Design Liquor Ratio 8 Operational Wash Water Ratio 5 min-7 10 min-12 Operational 15 min-15 Unfixed Dye Fract. 0.3 Best guess Ambient Temp. 30 C Measured Steam Pressure 700 kpa Measured Flue Gas Temp. 220 C Measured Excess Air Fract Calculated Flue Gas Mol. Wt. 27 Calculated Approach Temp 5 C Best guess Insulation Heat Loss Factor 1.2 Best guess Blow down Frac Best guess Condensate Temp. 60 C Measured Boiler Make-up Water Temp. 30 C Measured Condensate Recovery Frac. 0.5 Best guess Cooling Water Recovery Frac. 0.1 Best guess NG (Steam & Process) m3/d Measured NG (Stenter) 3600 m3/d Best guess NG (Steam) m3/d Calculated An effluent is a mixture of chemical compounds and in this case it is necessary to consider whether the toxicity of the stream is greater (synergistic) or less (antagonistic) than the sum of the toxicity of individual chemicals. For most effluents the toxicity would be equal to the sum of the toxicity of individual chemicals (additive) and Marbek model adopted the synergistic hypothesis. Since a large number of chemicals are found in TMEs, it is impractical to take the toxicity of each chemical into account. A pragmatic compromise is to classify chemicals into several groups and each group treated as a pseudo chemical compound. Eight chemical groups are selected for the Marbek model either because the chemical group is highly 122

132 toxic, or because the group is present in high concentrations. The eight chemical groups and the corresponding LC50 values are presented in Table 1 based on the information available in the Marbek Report (2001). In the literature on textile mill effluents, metals may be specifically mentioned as a source of toxicity of TMEs, but metals are not included as a separate group in this study. Metals are essentially covered in Salts and Dyes groups 3. METHODOLOGY FOR TOXICITY DETERMINATION The determination of toxicity of an effluent from a mill requires data on concentrations of the chemical groups present in the effluent streams and also water balance of the mill. But relevant data are rarely available in Bangladesh and also feasibility of carrying out experiments to get the info is remote at the present time. However, an attempt is made here to make an estimate of the toxicity of an effluent from a typical textile mill in the country based on industry practice in the Canadian textile sector and some limited data in Bangladesh. First, the water balance of a mill is established from Time-Temperature diagram of the dyeing process and in the second step the concentration of the chemical groups of the Marbek model are estimated from industry practice and further plausible considerations. A typical textile mill in Bangladesh has been chosen for this study. Raw material for the industry is knitted greige fabric of different varieties comprising of 100% cotton, Viscose, PC, CVC, Melange etc. Cotton processing forms about 75-80% of the total production, whereas the contribution of other fabric is about 25-20%. Bulk production is carried out on pressurized jets and atmospheric dyeing machines. The basic operating data of the chosen textile mill are shown in Table 2. The operating variables of the mill would be easily identifiable from their names in the table and the quality of the data is indicated in the Remark column of the table. The table has been prepared based on an IFC ( ) Project report. IFC has been carrying out different projects on Cleaner Production in the Textile Washing/Dyeing/Finishing Sector in Bangladesh and the authors have been actively involved in some of the IFC s works. There are three broad stages in a dyeing process: Pre-Treatment, Dyeing and After-Treatment. Each stage, in turn will have a number of steps and these depend on the type of textile, dyes and the art of the process. For the present study these are: Pre- Treatment 9 steps, Dyeing 1 step and After- Treatment 6 steps. The different steps are represented in the usual Time-Temperature diagram of the dyeing process as shown in Figure 1 and identified with numbers in the shaded box below the discharge arrows. At the end of each step occurs a discharge and estimates of flow and quantity of chemicals in the discharge would enable the determination of effluent toxicity. The discharges have been identified as Heavy, Medium and Light and have been shaded accordingly (shown as shaded boxes) based on intuitive considerations and plant operation experience. Based on the operating conditions indicated in the Time-Temperature diagram, Figure 1, and the data given in Table 1, the demand side need of water and steam for the mill may be estimated. This is shown in Table 3. Note that water is needed for filling the dyeing vessel, for washing and for cooling. The data from Table 3 are presented in a simplified process flow diagram (PFD) of the mill in Figure 2 and the cumulative estimates of the three categories are shown as a bar chart in Figure 3. The cooling water usually flows through a coil, as is the case with steam also, and these streams do not generally mix with the liquor in the vessel. A common coil may be used for both cooling and heating although it is shown separately in the diagram for clarity. The total effluent discharge, 2461 t/d from the mill is equal to the net water demand for dyeing. This corresponds to a specific consumption of 164 lite water per kg fabric (l/kg). For the study on Cleaner Production (CP) conducted by the same authors for IFC, the specific consumption was estimated to be 153 l/kg and this agrees reasonably with our current estimate. The demand of steam is 98 t/d corresponding to 6.6 kg steam per kg fabric (kg/kg), whereas in the CP study the specific consumption of steam was estimated as 11.7 kg/kg. It should be noted here that in the present study steam demand is estimated for dyeing operations only and does not take into considerations other uses that exits in the mill. However, there appears to be significant difference between the two values. In the CP study, estimates were made based on supply side considerations as against demand side estimate in the present case. A relevant point to note is that the CP study suggests that optimum consumption of steam should lie in the range 5 7 kg/kg fabric and thus a supply side estimate of 11.7 kg/kg appears out of the norm whereas the present demand side value of 6.6 kg/kg appears more reasonable. 123

133 Operation PerOxide Caustic Wash Wash Wash PerOxide Killer Wash AceticAcid Enzyme Wash Lavelling Dyes Salt Soda Wash Acetic Acid Dekol RSA Wash Fixing Agent Wash Softener Total Fig. 1. Dyeing Process: Time-Temperature Diagram Table 3. Water and Steam Flows (t/d ) Pre-Treatment Dyeing After Treatment FillWater WashWater Effluent CoolingWater Steam Table 4. Effluent Toxicity Effluent Category Heavy Medium Light Total Flow, t/d = m3/d Toxic Fraction Toxic chemicals Actual amount used in dyeing (this study) kg/d Estimates in effluent streams (Marbek) kg/d Estimates in effluent streams (this study) kg/d LC50 mg/l Relative Toxicity, T i Salts NPEs nonnpes

134 Phosphates Dyes Dye carriers Solvents Chelates Total GREIGE FABRIC Mill Capacity = 15 t/d BATCHING & INSPECTION Light Effluent (0.7) PRE-TREATMENT Fill & Wash Water 2325 Medium Effluent (2) 2461 (13.7) Heavy Effluent (57.7) DYEING Cooling Water Steam 98 AFTER-TREATMENT Recovered Cooling Water Recovered Condensate SLITTING & DEWATERING 5 5 DRYING & COMPACTION BATCHING & INSPECTION FINISHED FABRIC Fig. 2. Water & Steam Balance (Flow, t/d and Relative Toxicity within brackets, dimensionless) Next, an estimate of the amount of each chemical group (identified in Table 1) in an effluent stream is needed to determine the toxicity due to the chemical group. As mentioned earlier, very little data are available regarding this matter and drastic guesses have been made to make any progress. Out of the eight chemical groups, only the amounts of salts and dyes that have been used are available without much ambiguity. Many of the chemicals that are used in the mill are only identified with their descriptive names, such as dyes or at best with trade names and the entire dyeing process is administered using recipes that are usually provided by the dye suppliers. Further, a customer is reluctant to divulge much information about their dyeing operations. Even, if the relevant data about quantities consumed were available, their concentrations in the effluent streams would be hard to estimate without resort to experimental work. Thus, the missing data have been filled based on data available in the Marbek study and rationalizing the data for a 15 t/d mill capacity. These are shown below in Table 4. The relative toxicity, T i, calculations may now be followed from Table 4. In the present study, the amount of dye consumed is kg/d and assuming unfixed dye fraction as o.3, the amount discharged to the effluent is taken as kg/d as against Marbek estimate of 46.6 kg/d. This 125

135 difference between the two values suggests Canadian practice to be more efficient and better controlled. However, industries in Bangladesh would consider a value of 0.3 for the unfixed dye fraction as reasonable. The salt discharge fraction is taken arbitrarily as 0.95 and a value of 0.88 for the discharge fraction would make the salt discharge equal to the Canadian practice. For the remaining chemical groups, except for solvents, their amounts are taken from Marbek estimates as shown in Table 4. The contribution from solvents has been ignored as the authors could not find any solvents in the list of chemicals for the dyeing process for this particular mill. Next the amount of chemicals in the three effluent categories are calculated assuming that of the total amount discharged, 90% is discarded to successive categories. This is again an arbitrary choice, but is based on the consideration that repeated wash and discharge operations will lower the concentration of a chemical very rapidly. less toxic). Thus a relative toxicity of 13.7 (TME LC50 = 7.3%) would indicate that the effluent is highly toxic. The major contribution of toxicity arises from dyes as may be seen from the T i values in Table 4. The contribution of the dye carriers adds up the effect. The amount of dye used in the present mill is 22.8 g per kg fabric (342.5/15 = 22.8) whereas the average value for the Canadian industry is about 14 g/kg. In fact, there are industries in Bangladesh that have consumption values closer to Canadian practice. Thus it is likely that dye used in this particular mill is much in excess of the required amount and that in reality larger amount of unfixed dye is discharged to the effluent. A value of 0.3 for unfixed dye fraction is conservative in the present contest and the contribution of toxicity from dyeing sources could be significantly more than estimated. Clearly, there is a need to look into the dyeing practice and also the technology used by the industry. Next in importance are nonnpe surfactants. In the Canadian and other western countries NPEs as surfactants are being actively replaced by nonnpes. NPEs are highly toxic and in the environment degrade to more environmentally persistent NP. It is unlikely that Bangladesh textile sector has adopted this philosophy with the same vigor and it is more likely that toxicity due to NPEs is more than the estimated value shown in Table 4. A more in-depth study would be required to establish the actual situation. Fig. 3.Effluent Flow and Toxicity 4. DISCUSSION The relative toxicity of the combined effluent is estimated as An alternative way to express the same result is to assign a TME LC50 value of 7.3% (100%/13.7 = 7.3%) to the effluent. In other words, to reduce the relative toxicity to unity the effluent is to be diluted where the dilution water will be 92.7%. Note the inverse relationship between relative toxicity, T i and TME LC50 value expressed as %. The lower the %TME LC50 value of an effluent, the more potent it is (needs more dilution to make it Salts, although being used in large quantities have less effect because of their low LC50 value. It should be noted here that no particular considerations have been made to isolate the toxicity due to the presence of metals. Also as mentioned above contribution from solvents has been ignored as the authors could not find any solvents in the list of chemicals for the dyeing process. In addition to the combined effluent, relative toxicities have also been estimated for the three different categories of effluent discharge streams, namely Heavy, Medium and Light. The values of relative toxicity and flow of the effluent streams vary significantly and has important implications from design perspective of effluent treatment plants. The standard approach to ETP design for TMEs in Bangladesh is a combination of physico-chemical and biological treatment. In a few cases some tertiary treatment also exist. Whether or not these plant would operate in a satisfactory manner is not considered seriously at the design 126

136 stage. Let us briefly outline some of the difficulties of ETP design for TMEs. Organic pollutants from dyes, acids, tallow, etc resulting in BOD load may be controlled by biological treatment. But TMEs also contain nonbiodegradable (or hard to degrade) material termed as refractory material, e.g., detergents. The presence of these chemicals is indicated in the COD demand. In many TMEs BOD/COD ratio is low and in this case biological treatment may not be a suitable option. High TDS value due to the presence of salts can also be difficult to deal with in a conventional system. Color in TMEs is a significant esthetic issue and cannot be easily treated because the chemical are not easily degradable. The physico-chemical treatment steps help reduction of color and suspended solids and significant reduction of BOD and COD loads. But many biological treatment facilities have not operated successfully. These plants generally operate under aerobic conditions. Naresh et al (2013) in a recent review paper stated that various researchers showed that dyestuff do not degrade appreciably under aerobic condition. The common observation is that both aerobic and non-aerobic condition would be necessary for successful operation of biological treatment facilities. Highly toxic effluents are not easily degradable and this clearly brings out an option for segregation of effluent streams and design effluent treatment systems based on toxicity of the streams. The idea of stream segregation is not new. Khan et al (2006), Mithun (2012) and Shaid et al (2013) have also discussed this in the context of Bangladesh Industry. The low toxic Light streams may be recycled after possible ph and other minor adjustments. The Medium category may be treated in a conventional manner using a combination of phisco-chemical and biological treatment. Alternatively RO system may be also considered allowing recovery of water. The Heavy category may be treated for recovery of salts using a combination of preliminary treatment followed by evaporation and crystallization operations. Because of its high toxicity, biological treatment will not be an option for the Heavy category. The strategy to treat the different categories of effluent streams separately and recycling the treated water would be a way to move towards the concept of zero discharge. 5. CONCLUSIONS an attempt to make quantitative estimates of effluent toxicities of different streams from a typical textile mill in Bangladesh. However, firmer estimates of effluent toxicities are necessary and more in-depth studies are required in this area. The work is not going to be easy, both in terms of expertise and investment. The importance of proper treatment of TMEs cannot be overstated and commitment is required from the stake holders in the textile industry to make progress in this area. REFERENCES 1. Khan M, Knapp J, Clemett A and Chadwick M (2006), Managing Pollution from Small Industries in Bangladesh, Technical report, Research for Development, Department for International Development (DFID) 2. International Finance Corporation (IFC) Project: Cleaner Production in the Textile Washing/Dyeing/Finishing Sector in Bangladesh, Phase II, Marbek Report (2001), Textile Mill Effluents Study: Identification and Evaluation of Best Available Technologies Economically Achievable (BATEA) for Textile Mill Effluents, 2001, Submitted to Environmental Protection Branch, Environment Canada by Marbek Resource Consultants 4. Mithun, M. R. (2012), Biological Treatment of Textile Effluents: Best adoptable option results in cost & environment savings with outstanding treatment efficiency, Bangladesh Textile Today 5. Shaid, A., Osman, M. S., Hannan, M. A. and Bhuiyan, M. A. (2013), Direct Reusing of Textile Wastewater in Scouring-Bleaching of Cotton Goods Devoid of Any Treatment, International Journal of Research and Development, 5(8), pp Naresh, B., Jaydip, J., Prabhat, B. and Rajkumar, P. (2013), Recent Biological Technologies for Textile Effluent Treatment, International Research Journal of Biological Science, 2(6), pp

137 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh SYNTHESIS, DEVELOPMENT & CHARACTERIZATION OF COBALT MODIFIED ORDERED MESOPOROUS CARBON FOR PEM FUEL CELL Khondker N. Sultana, Ahmed L. Fadhel, Vishwanath Deshmane, Debasish Kuila and Shamsuddin Ilias* North Carolina A&T State University, Greensboro, NC This particular research is aimed at developing an ordered mesoporous carbon (OMC) with large surface area as Pt support to address the issues of high cost and durability in commercializing PEMFC. OMC was synthesized using an SBA-15 silica template and sucrose as a carbon source. The catalysts were characterized using BET, TEM, XRD and TGA techniques. BET surface area of the OMC was found to be 1006 m 2 /g. XRD and TEM image confirmed the ordered arrangements of the hexagonal pores. Fuel cell polarization tests were conducted using this OMC based catalyst with 20 wt% Pt loading. Preliminary results of modified-omc synthesis using Co-SBA-15 as a template and performance tests of 20wt%Pt on modified- OMC electrocatalyst are also discussed briefly. The polarization test was conducted to observe the comparative performance of 20 wt% Pt/OMC, 20 wt% Pt/Co modified-omc and 20 wt% Pt/Vulcan XC-72 catalysts in PEMFC. Electrochemical surface area (ECSA) of the synthesized catalyst, measured by cyclic voltammetry, was found to be 54.3 m 2 Pt/gPt for 20 wt% Pt/Co modified OMC and 34.7 m 2 Pt/gPt for 20 wt% Pt/OMC. 1. INTRODUCTION High power density, high efficiency and low emissions to the environment have made the polymer electrode membrane fuel cells (PEMFC) one of the potential sources of power. A major challenge in commercialization of PEMFC is the high cost of platinum (Pt), which is a main component of fuel cell electrocatalysts. The supply of high purity hydrogen needed for PEMFC is an additional cost, since very low concentrations of CO (> 10 ppm) can poison the Pt catalyst (Escudero et. al., 2002). In order to get better fuel cell performance, it is necessary to develop effective catalysts that have lower platinum loadings and resistance to CO poisoning. One of these objectives can be achieved by utilizing higher surface area carbon support where Pt can be well dispersed in the form of nanoparticles (Wallace et. al., 2009). In recent times, ordered nanostructured carbons are of great interest because of their better textural, electrical and mechanical properties. They have unique features, which include: a) enhanced mass transfer due to the presence of ordered structure; b) distinctive electrical properties that limit the charge of the supported metal particle; and c) the possibility of novel metal/carbon combinations to develop catalysts which have reduced sensitivity of the CO poisoning (Perathoner et. al., 2007). Ordered mesoporous carbon (OMC) has been considered as the prospective catalyst support in this regard because of its high specific surface area, as well as larger pore volume and pore sizes compared to the commercially used Vulcan XC-72 carbon. The primary objective of using OMC as a catalyst support is to enhance transport of reactant gases by providing uniform interconnected pores on uniformly dispersed metal particles minimizing the requirement of high Pt loading. This will allow high electrochemical activity since the catalytic reduction of oxygen and catalytic oxidation of hydrogen are surface processes (Wallace et. al., 2009). 2. OMC AS CATALYST SUPPORT For realizing high electrocatalytic performance, catalyst supports should have high surface area to provide high dispersion and narrow distribution of the platinum nanoparticles. Catalyst supports interact with metals and influence the catalytic activity as well as the stability of the electrocatalyst. High electrical conductivity of carbon has made it a potential support material for electrocatalyst. Traditionally activated carbon with * Corresponding Author: Shamsuddin Ilias, ilias@ncat.edu

138 significantly lower surface area has been used in PEMFC. However, ordered mesoporous carbon (OMC), due to its highly ordered mesoporous structure and large surface area, has been considered as potential alternative to conventional carbon black. OMC has a hexagonal mesoporous structure, which is mainly synthesized by a hard templating mechanism such as SBA-15. (a) (b) Fig. 1: (a) Cross-sectional view and (b) three dimensional view OMC This OMC has primary mesopores but it also has some secondary pores, which are micropores. The hexagonal mesopores are interconnected with channels. The reason behind the formation of micropores was slit-like pores between two adjacent carbon nanorods (Du et. al., 2012). OMC has been used by researchers as the support material for both anode and cathode catalyst in PEMFC. PtRu catalyst supported on mesoporous carbon has been used in anode by Bruno et. al. (2013). Using the polarization curve, it was shown that mesoporous carbon performed better in the mass transfer controlled region compared to commercial activated carbon. This was attributed to the high surface area of the mesoporous carbon that allows enhanced diffusion of reactant gases (Bruno et. al., 2013). Enhancement of the electrical conductivity is also essential for higher performance. Graphitization by metal, known as catalytic graphitization, has been considered as one of the most efficient methods to improve electrical conductivity. In this research, cobalt has been used as the graphitizing metal, which facilitated the formation of graphitic sites on the amorphous carbon resulting in much higher electrical conductivity of the synthesized OMC. 3. METHODOLOGY 3.1 SBA-15 Synthesis SBA-15 was synthesized according to the method optimized in-house by adopting the procedure described by Zhao et. al. (1998). The molar ratios of different components used in the synthesis of SBA-15 material were 1 TEOS: CTAB: P123: 31 H 2 O: 2.68 HCl. During the synthesis of SBA-15, two different solutions were prepared: 1) Pluronic P123 dissolved in 2M HCl solution; and 2) CTAB dissolved in DI water to get a clear solution. After the preparation of these solutions, CTAB solution was added to the P123 solution and stirred for 30 minutes. To the formed mixture a measured quantity of TEOS was added and stirred for 20 h at 35 C. The final material was aged at 98 C for 24 h. After aging, the material was washed with DI water, then washed with ethanol and acetone to remove CTAB and P123 and subsequently filtered. The filtrate was air dried for ~24 h followed by drying at 110 C for 24 h. Finally, the dried material was calcined at 550 C with the heating and cooling rate of 1.8 C/min to remove the remaining traces of CTAB and P123. Co-SBA-15 was synthesized using the same procedure as SBA- 15 synthesis except CoCl 2. 6H 2 O was used as the precursor for cobalt and was dissolved in ethanol to be mixed with the mixture of P123 and CTAB solution. After the addition of TEOS, NH 4 OH was added for CoCl 2 precipitation. 3.2 OMC Synthesis OMC and the Co modified OMC were synthesized using SBA-15 and Co-SBA-15 mesoporous silica as a hard template and sucrose as the carbon source (Almeida et. al., 2013). In a typical synthesis 1.25 g of sucrose was dissolved in 5 ml of DI water and 0.14 g of H 2 SO 4 was added it. 1 g of SBA-15 was dispersed in this solution and was stirred well for 15 minutes. The mixture was placed in the furnace for 6 h at 100 C, and then at 160 C for an additional 6 h. Another solution was prepared adding 0.09 g sulfuric acid to a solution obtained by dissolving 0.80 g of sucrose into 5 ml of DI water. The silica-sugar mixture formed in the first stage was then dispersed into this solution. The heating cycle with 6 h at 100 C and further 6 h at 160 C was repeated. The obtained sample was carbonized for 6 h in the tubular furnace at 900 C with a heating ramping rate of 5 C/min under N 2 environment. The carbon silica composite obtained after carbonization was treated with 5% w/w aqueous hydrofluoric acid (HF) solution at room temperature for 5 h, to remove the silica template. The HF treated sample was then washed with water and ethanol followed by centrifugal separation. The template-free carbon products thus obtained was dried at room temperature overnight and then at 120 C for 8 h. 3.3 Preparation of Electrocatalyst Electrocatalysts were synthesized based on 20 wt% metal (Pt) loading supported on OMC. At first; H 2 PtCl 6.6H 2 O was dissolved into acetone and then mixed with OMC. Then the mixture was stirred for 30 min followed by sonication for 2 h. The mixture was further stirred at 60 C overnight. The dried sample was reduced using 5%H 2 /Ar flow at 350 C for 2 h after which it was cooled down under N 2 flow to obtain the electrocatalyst. 129

139 3.4 Preparation of Catalyst Ink About 50 mg of synthesized electrocatalyst was used for preparing one batch of catalyst ink. The electrocatalyst was dissolved in 10 ml of isopropanol. Then, the mixture was stirred for 15 minutes, followed by sonication for 30 minutes. To this mixture, a 5 wt% Nafion ionomer (33% Nafion loading) was added. The mixture was sonicated again for 60 minutes followed by stirring for 15 minutes. 3.5 Preparation of Membrane Electrode Assembly (MEA) To prepare the MEA, catalyst ink was directly sprayed on the Nafion membrane of 5 cm 2 and the amount of catalyst ink sprayed was monitored so that the Pt loading would be 0.4 mg/cm 2 for each of the electrodes. Then the MEA was treated with 0.5 M H 2 SO 4 by boiling at 80 C for 1 h. After that, the membrane was boiled in DI water at 80 C for 1 h to remove the sulfuric acid from the membrane and then dried at room temperature. 4. RESULTS 4.1 Characterization of SBA-15 and OMC Surface area analysis of synthesized SBA-15 and OMC was carried out using N 2 physisorption technique. The OMC was also characterized using XRD analysis and TEM study of the mesoporous structure. Fig. 2 represents the N 2 adsorption desorption isotherm for OMC. Volume of N 2 (cc/gm) Relative pressure (p/p o ) Adsorption Desorption Fig. 2:N 2 adsorption desorption isotherm of ordered mesoporous carbon From the above figure, it is evident that the isotherm of OMC exhibited type IV mesoporous structure as classified by IUPAC (Donohue and Aronovich, 1998). However, the nitrogen adsorption desorption isotherm for the synthesized OMC was found to be slightly different from that of the synthesized SBA-15. The difference is mainly due to the wide pore size distribution in the OMC. The initial portion of the adsorption isotherm was due to the monolayer-multilayer adsorption on the walls of the pores as described by Zhao et. al. (1998). Capillary condensation phenomenon started at approximately p/p o = 0.4 in the N 2 adsorption desorption isotherms, which takes place only in mesoporous materials (Donohue and Aronovich, 1998). The slightly sharp increase of around 0.96 p/p o partial pressure indicates nitrogen uptake, which is presumed to be due to the macropores that form between two adjacent carbon rods as a slit pores. Pore size distribution of OMC was determined by applying the BJH method on desorption branch. A wide pore size distribution was observed due to the presence of micropores and mesoporous structure. The presence of mesopores in size range of 2-4 nm was observed from the BJH pore size distribution. Specific surface area and pore size of the synthesized SBA- 15, OMC and Co modified OMC are summarized in Table 1. Material Table 1. Surface area analysis Sp. surface area (m 2 /g) Average pore diameter (nm) SBA OMC wt% Co-SBA Co modified OMC Interestingly, the BET surface area of modified- OMC was found to be significantly higher compared to that of OMC only. Fig. 3 depicts the N 2 adsorption desorption isotherms of Co modified OMC sample. The presence of mesopores was confirmed from the type IV isotherms. Pore size distribution also was observed from BJH desorption branch to confirm the pore size. Most of the pores were found in the range of 3-4 nm with a narrow pore size distribution. Volume (cc/g) Adsorption Desorption Relative pressure (p/p o ) Fig. 3:N 2 adsorption desorption isotherm of Co modified OMC Small angle x-ray diffraction (SAXRD) analysis was performed to establish the ordered nature of the 130

140 mesopores in OMC. Fig. 4 represents the SAXRD pattern of OMC. A sharp peak observed at around 1.5 scattering angle (2 theta angle) is attributed to (100) plane. This indicates that synthesized carbon has a well-ordered mesoporous structure. However, for Co modified OMC, no SAXRD scattering peak was seen indicating a lack of ordered structure. graphitized structure. In Raman spectra of OMC, no characteristic peaks for graphitic structure were seen. A slight peak of around 1100 cm -1 has been observed, which represents the amorphous structure in the OMC sample. Therefore, graphitization was attained due to the nucleation by the cobalt particles during the synthesis of Co modified OMC. Fig. 5 shows the TEM image of OMC revealing an ordered arrangement of pores with dimensions of approximately 2 nm found between enclosures formed by carbon nanorods Co modified OMC OMC Intensity Intensity degree Fig. 4: Small angle XRD pattern of synthesized OMC Raman shift (cm -1 ) Fig. 6: Raman spectra of OMC and Co modified OMC. 4.2 MEA Evaluation Synthesized MEAs were evaluated using the Fuel Cell Test Station by performing the polarization test and ECSA evaluation. The polarization curves generated for the electrocatalysts supported on OMC, Co modified OMC, and commercial Vulcan XC-72 are shown in Fig. 7. OMC showed poor performance compared to both commercial carbon and the Co modified mesoporous carbon wt% Pt/OMC 20 wt% Pt/Vulcan XC wt% Pt/Co modified OMC Fig. 5: Transmission electron microscopy of ordered mesoporous carbon Potential, E (V) Synthesized OMC and Co modified OMC were also characterized by Raman Spectroscopy to confirm graphitization of carbon walls. Fig. 5 shows the Raman spectra for both OMC and Co modified OMC. The characteristic peak for graphitic structure was found at 1583 cm -1 for Co modified OMC. A second peak observed around 1328 cm -1 in the Raman spectra of Co modified OMC indicates the defects and disorders with respect to ideal graphitic materials. The peak at 1163 cm -1 depicts that the synthesized Co modified OMC sample has slight amorphous structure. Hence, the Co modified OMC sample is a partially Current density, I (ma/cm 2 ) Fig. 7: Polarization curves for synthesized electrocatalysts at 70 C and 1 atm (stoichiometric ratio of O 2 and H 2 ) The electrocatalyst based on OMC could not withstand a load higher than 250 ma/cm 2. This drop in voltage in ohmic polarization region was very large compared to that of the commercial carbon. The difference in voltage could be due to the amorphous nature of OMC walls resulting in lower electron conductivity than commercial carbon black. Therefore, catalyst support with a 131

141 higher graphitization degree, as well as high specific surface area and pore volume, was essential. In this regard, cobalt was incorporated into the silica framework to induce carbon crystallization in OMC which was further used to prepare 20 wt% Pt/Co modified OMC electrocatalyst. The performance of the fuel cell was considerably improved with 20 wt% Pt/Co modified OMC catalyst compared to that of 20 wt% Pt/OMC. The ohmic resistance was overcome by increasing the graphitization degree of the OMC using Co-SBA-15. This resulted in the operation of the fuel cell at a higher load. The higher current density is indicative of the role of Co particle in generating the heterogeneous nucleation sites that leads to the graphitization of amorphous carbon in Co-modified OMC (Dignard-Baileya et. al., 1994). Current density, I (ma/cm 2 ) Fig. 8: Cyclic voltammetry for electrocatalysts using 0.2 l/min H 2 at anode and 0.05 l/min N 2 at cathode Cyclic voltammetry test was performed for the synthesized electrocatalysts. It is evident from the CV voltammogram that the area attributed to the capacitive current due to the charging/discharging of the electric double layer for 20 wt% Pt/OMC was higher than that associated with 20 wt% Pt/Vulcan carbon XC-72. The ECSA of 20 wt% Pt/Co modified OMC was found to be 54.3 m 2 Pt/gPt, which is significantly higher than the ECSA of 20 wt% Pt/OMC electrocatalyst and comparative to the ECSA of 20 wt% Pt/Vulcan XC-72. This improved electrochemical surface area was due to the graphitization of the walls of mesoporous carbon. 5. CONCLUSIONS Potential, E (V) 20 wt% Pt/Vucan XC wt% Pt/OMC 20 wt% Pt/Co modified OMC Co modified OMC played a significant role towards the enhancement of the fuel cell performance by means of partial graphitization of mesoporous carbon. High specific surface area of ordered mesoporous carbon contributed to the better dispersion of Pt on the catalyst support, which allows high electrochemical activity since the catalytic reduction of oxygen and catalytic oxidation of hydrogen are surface processes. Moreover, Co contributed to the enhancement of electrical conductivity by partially graphitizing the structure of the carbon. Future studies will be focused on the enhancement of the structure and morphology of the carbon to achieve even higher performance than commercial carbon. ACKNOWLEDGMENTS Funding from National Science Foundation through NSF CREST Bioenergy Center, Award No. HRD is gratefully acknowledged. REFERENCES 1. Escudero, M.J., Hontañón, E., Schwartz, S., Boutonnet, M., and Daza, L. (2002), Development and performance characterisation of new electrocatalysts for PEMFC, Journal of Power Sources, 106(1 2), pp Wallace, G.G., Chen, J., Mozer, A. J., Forsyth, M., McFarlane, D. and Wang, C. (2009), Nanoelectrodes: energy conversion and storage, Materials Today, 12(6), pp Perathoner, S., Gangeri, M., Lanzafame, P., and Centi, G. (2007), Nanostructured electrocatalytic Pt-carbon materials for fuel cells and CO 2 conversion, Kinetics and Catalysis, 48(6), pp Du, H.-Y., Wang, C.H., Hsu, H.C., Chang, S.T., Huang, H.C., Chen, L.C., and Chen, K.H. (2012), Graphene nanosheet CNT hybrid nanostructure electrode for a proton exchange membrane fuel cell, International Journal of Hydrogen Energy, 37(24), pp Bruno, M.M., Petruccelli, M.A., Viva, F.A., and Corti, H.R. (2013), Mesoporous carbon supported PtRu as anode catalyst for direct methanol fuel cell: Polarization measurements and electrochemical impedance analysis of mass transport, International Journal of Hydrogen Energy, 38(10), pp Zhao, D., Feng J.L., Huo, Q.S., Melosh, N., Fredrickson, G.H., Chmelka, B.F., and Stucky, G.D. (1998), Triblock copolymer syntheses of mesoporous silica with periodic 50 to 300 angstrom pores, Science, 279, pp Almeida, R.K.S., Melo, J.C.P., and Airoldi, C. (2013), A new approach for mesoporous carbon organofunctionalization with maleic anhydride, Microporous and Mesoporous Materials, 165, pp Donohue, M.D. and Aranovich, G.L. (1998), Adsorption Hysteresis in Porous Solids, Journal of Colloid and Interface Science, 205(1), pp

142 9. Dignard-Baileya, L., Trudeau, M.L., Jolya, A., Schulza, R., Lalandea, G., Guaya, D. and Dodeleta, J.P. (1994), Graphitization and particle size analysis of pyrolyzed cobalt phthalocyanine/carbon catalysts for oxygen reduction in fuel cells, Journal of Materials Research, 9(12), pp

143 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh STUDY OF TEXTILE SLUDGE TREATMENT USING INCINERATION TECHNIQUES Salma A. Iqbal Department of Chemical Engineering & Polymer Science, Shahjalal University of Science & Technology, Sylhet-3114, Bangladesh A.K.M. Abdul Quader and Iqbal Mahmud Department of Chemical Engineering, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh The sludge from the wastewater treatment plant in textile units is considered hazardous as it is often contaminated with heavy metals of dyestuffs and chemicals. Currently, land filling is the most common practice for textile sludge disposal. Leaching of heavy metals from textile sludge is a growing concern in Bangladesh. The present study focuses on the characterization, thermal treatment of textile sludge and the possibility of making value added products from the ash obtained from the incinerated sludge. Sludge samples were analyzed for various physical properties including ph, acidity, alkalinity, sulfate, nitrate, chlorides etc and heavy metals like Chromium, Cadmium, Lead, Mercury, Arsenic, Nickel, and Zinc. Characteristics of the textile sludge vary from industry to industry due to the involvement of different processes. Sludge samples were incinerated at 500 C, 700 C and finally at 800 C for different time intervals. The ph of the raw sludge varied from 6.1 to 8.3, chloride concentrations mg/kg, sulfate concentration 3276 to 6218 mg/kg and nitrate mg/kg. The Toxicity Characteristics Leaching Procedure (TCLP) leachate from the raw sludge showed significant concentrations of Cr, Pb, Cd, Ni, Zn- Chromium mg/l, Lead mg/l, Cadmium mg/l, Nickel mg/l and Zinc mg/l. The concentrations of heavy metal in leachate from the stabilized sludge samples were very low. The compressive strength, bulk density, water absorption of the stabilized sludge and ash samples were examined and the results showed that up to 10% of the raw sludge and 10-20% ash samples could be used for stabilization and/or solidification and additionally, 80% volume reduction of the raw sludge could be obtained. This study attempts to find out an environment-friendly solution for the management of the textile sludge. 1. INTRODUCTION The rapid growth of textile industry in Bangladesh plays an important role in economic development as well as employment generation. Currently, the textile industry sector accounts for 45% of all industrial employment in the country and contributes 5% of the total national income. The number of textile industrial units in 1954 was only 53 but now there are more than 5000 units (Rahman, 2003). A large number of textile dyeing, printing and finishing industries have been built as cluster at Narayanganj, Savar, Demra, Tongi, Joydevpur, Gazipur, Hazaribagh and Tejgaon industrial area of greater Dhaka district. In dyeing process, the dyes are grouped as Acid, Direct, Disperse, Food, Mordant, Natural, Pigment, Reactive, Sulphur and Vat dyes. Dyes in each group are subdivided as yellow, orange, red, violet, blue, green, and black dyes comprising of complex organic and inorganic chemicals. (Salma, 2012). A significant amount of liquid dye waste is generated in the dyeing process. Textile sludge is an unwanted residual solid generated in the textile wastewater treatment plant and its management is a critical environmental issue. In wastewater treatment process, different chemicals are added and most of the chemicals get settled out during the process. Finally, they end up in the sludge and the sludge produced contains hazardous materials like Chromium, Cadmium, Beryllium, Lead, Mercury, Nickel, Aluminum and toxic organic chemicals having high BOD and COD loads. They are toxic to both human health and environment (Monahan et al, 1990, Islam et al, 1994, Meyer et al, 1997). The environmental impacts of landfill are the polluting air, water and soil. The uncontrolled * Corresponding Author: Salma A. Iqbal, salmacep@gmail.com

144 production of landfill gases such as methane, carbon dioxide, traces of non-methane and volatile organic carbons leads to global warming. The most serious environmental impact of sludge disposal to landfill is contamination of local groundwater by the generated leachate. The leaching potential of the raw sludge from the effluent treatment plant is very high (Hossain,2006). Disposal of solid wastes generated in textile dyeing industries located at Savar, Gazipur and Narsingdi areas has led to serious toxicity problems. The contamination of groundwater aquifer by the leachates is of great environmental concern. The use of sludge as ceramic and building material converts waste into useful products. It eliminates disposal problems. Benefits of using sludge and sludge ash as an additive to bricks and blocks includes immobilizing heavy metals in the fired matrix, oxidizing organic matter. 2. MATERIALS AND METHODS Textile wastewater sludge samples were collected from greater Dhaka district. Normally each sample weighing 20 kg was collected at a time. Locations from where wastewater sludge samples were collected are shown on the map. The Grab sampling methods were used for the sampling purpose. Sampling was carried out at locations where sludge was routinely removed from the wastewater treatment for subsequent disposal and in some cases the sludge samples were not routinely removed, occasionally this was used by the ETP. Immediately after the collection of sludge, its moisture content was determined. For this, 20 gm of sludge for each sample collected was taken and kept in an electric oven for 24 hours at a temperature of 105 C for the moisture removal and the percent moisture was calculated. Then all the collected samples were bone dried and kept in air tight plastic container for further analysis. The sludge samples were digested (EPA3050B method) and the digested samples were preserved in small disposable plastic bottles and kept in a cool dry place before analysis. The TCLP tests of leachate were performed using the method US EPA 1311.The performance of the incinerator was investigated and the temperature was increased slowly with time. Initially the temperature was set at 200 C for 20 minutes; in the next 20 minutes the temperature reached 500 C and within 1 hour it reached 800 C. The maximum reachable temperature of the electric incinerator was 1000 C. The operating temperature for the incineration process was kept at 800 C for 2 hours, 3 hours, 4 hours and 6 hours for the same sample. Sludge treatment of incineration by a gas fired incinerator and an electric incinerator was performed. The incineration process was continued up to 800 C and 4 hours. During the incineration process the sludge sample reduces its volume as well as mass. Incinerated ash samples contain heavy metal; heavy metal analysis was performed by the AAS. The waste water treatment sludge was added to clay in proportions of 5wt%, 10wt%, 20wt%, 30wt%. One batch of 100% clay was prepared for reference purpose. The moisture content of the mixture must be above 2% so that the samples are not brittle when formed. Samples were produced by using manual press operated at 90psi. The samples were dried in an oven at 80 C for 18 hours. The samples were then fired at 1200 C by natural gas. Blocks of size 5.08cm x 5.08cm x 5.08cm (2 x 2 x 2 ) were cast to find out the compressive strength of cement with various percentages of sludge/ash, 5% sludge/ash, 10% sludge/ash, 20% sludge/ash and 30% sludge/ash in partial replacement of cement and the water to cement ratio was 0.4 and some stone chips were mixed with cement, sand, sludge/ash and water. The cement, sand and stone chips ratio was kept at 1:1.5:2 (weight basis) and the 7 days, 14 days and 28 days compressive strength were determined. Without addition of sludge/ ash three blocks were made and also three cement-sludge/ash block samples were prepared for one set of experiment. Fig. 1. Sampling location of Sludge Samples 3. RESULTS AND DISCUSSIONS The sludge samples were analyzed for selected industrial units for determining sludge characteristics in terms of their physical and chemical constituents. The parameters analyzed included: ph, alkalinity, percent organic, sulfate, nitrate, chloride, silica and the heavy metals. The sludge samples were incinerated and stabilized with clay or cement. Table 1 shows the preliminary analysis of Textile Sludge sample. 135

145 Sample No. ph Alkalinity (ascaco 3 ) mg/kg Table 1. Results of Preliminary Analysis of Textile Sludge Chloride,mg /kg Sulphate, mg/kg Nitrate, mg/kg Moisture Content % Organic Content % Ash Content % S S S S S S S S S S Fig. 2. Chromium concentration of collected 36 textile sludge samples from different industries Fig. 3. Lead concentration of collected 36 textile sludge samples from different industries Fig. 3 shows the variations of chromium concentrations in 36 samples and it shows that the highest concentration in sample 35, which is in Narayanganj and the value of chromium concentration is nearly 550 mg/kg. Compared to maximum pollutant concentrations for surface disposal, the sludge sample is polluted. The minimum concentration of chromium is shown for the sample no. 22 and its location is in Savar. From Fig. 3 it is seen that the Lead concentration in some samples is very high, but in some samples it is low. The concentrations vary between 1.2 mg/kg to mg/kg. The variation is due to the different types of dyes and the different techniques used to meet the demand of clients.. The powder sludge sample was kept in the incinerator and the temperature was increased for the following time periods: 2 hours, 4 hours and 6 hours. Fig. 4 shows that the weight loss is high for the 6 hour time period, at 800 C. The leachate of sludge in Fig. 5 shows significant concentrations of Pb, Cr and Cd while the ash sample shows low concentrations of Pb, Cr and Cd. S1, S2, S3 represent the sludge sample 1,2,3 and A1, A2, A3 represent the incinerated ash sample of 136

146 sludge sample 1,2,3. During the incineration process the leaching potential of the metal becomes low because the metal forms oxide. Fig. 7 shows the results of compressive strengths of blocks made from ash+cement and sludge+cement. The compressive strengths of the blocks made from sludge is lower because the sludge samples contain a lot of organic compounds. So the bonding is not strong. Fig. 4. Temperature vs. weight loss of textile Sludge at different time periods Fig.7: Comparison of compressive strength made blocks 4. CONCLUSIONS Fig. 5. Results of average concentrations of Cr, Pb and Cd in Standard TCLP leaching test of leachates from raw sludge and incinerated Ash From Fig. 6, it is observed that with the addition of ash, the compressive strength increases but at the 30% ash addition the compressive strength decreases. Ash has cementing property for bonding. Up to 20% ash addition, the ash sample shows its cementing property and the chemical bonding is strong; but when more ash is added it does not show better bonding property and so the compressive strength decreases. Fig. 6: Comparison of compressive strength of blocks from mixing of cement and incinerated Ash Incineration is an important disposal method for the large volume of sludge produced by industrial and municipal wastewater treatment. The Toxicity Characteristics Leaching Procedures (TCLP) test results of leachate and heavy metal concentration of sludge leachate are higher than the US EPA LDR limit. The compressive strength test results of the blocks show that use of sludge and ash is possible for its preparation within certain limits. Ten percent sludge and 10-20% ash can be used as a cement replacement for block preparation. REFERENCES 1. Hossain, M.A. (2004), Stabilization of Heavy Metals in Industrial Sludge with Concrete Mix, M.Sc. Engg. Thesis, Civil Engineering Department, Bangladesh University of Engineering And Technology, Dhaka. 2. Islam M.M., Halim M.A., Safiullah S., Waliul Hoque S.A.M., and Islam, S. (2009), Heavy metal (Pb,Cd,Zn,Cu,Cr,Fe and Mn) content in Textile Sludge in Gazipur, Bangladesh, Science Alert. 3. Manahan, S.E. (1990), Hazardous Waste Chemistry, Toxicology and Treatment, Lewis Publishers, Michigan, USA 4. Meyer, E. (1997),Chemistry of Hazardous Materials, Prentice Hall, Englewood Cliffs, NJ, USA 5. Petel H., Pandey S. (2009), Exploring the reuse potential of chemical sludge from textile waste water treatment plants in India-a hazardous waste, American Journal of Environmental Sciences, 5(1), pp

147 6. Rahman, M.M. (2003), Study of Liquid Effluents from the Textile Dyeing Plant, B.Sc. Engineering Thesis, Chemical Engineering Department, Bangladesh University of Engineering And Technology, Dhaka. 7. Akhter, S. (2012).Textile Sludge Disposal Using Inceration Techniques, PhD Thesis, Chemical Engineering Department, Bangladesh University of Engineering And Technology, Dhaka. 8. Iqbal, S.A., Kabir F., Quader A.K.M.A., Mahmud I (2008), Thermal treatment of textile sludge, 12 th Annual paper Meet (APM) organized by Mechanical Engineering Division and IEB held at IEB, Dhaka Centre, Dhaka, Bangladesh. 9. USEPA (1997), 40 Code for Regulations, part , US Environmental Protection Agency, USA 138

148 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh RESOURCE RECOVERY FROM SPENT ZINC CARBON DRY CELL USING HYDROMETALLURGICAL TECHNIQUE Md. Hasib Al Mahbub, Nandini Deb, Shamsul Abedin, Muhammad Raisul Abedin, Mohidus Samad Khan* Department of Chemical Engineering, Bangladesh University of Engineering and Technology (BUET). Dhaka-1000, Bangladesh. The global consumption of zinc-carbon (Zn-C) dry cell batteries is significant. Zn-C batteries are also produced and widely used in Bangladesh. However, almost 95% of the spent dry cell batteries are disposed into the environment. The metal contents of Zn-C dry cells are not vastly hazardous to the environment; however, higher concentration of zinc (Zn) and manganese (Mn) present in Zn-C dry cells shows an industrial interest in recycling and recovering of Zn and Mn. The main challenge is to find an economically feasible recycling process. This research aims Zn and Mn recovery from spent Zn-C dry cells using hydrometallurgical technique. In this study dry cells were manually dismantled to collect the paste and neutral leaching was carried out to remove potassium and some non-metal content which reduce the acid consumption in leaching; sulphuric acid of different concentrations (1.5 M, 1.8 M, and 2.0 M) was used for acidic leaching with different citric acid concentrations: 20, 40 and 60 g/l. Highest recovery of Mn and Zn were found 91.85% and 39.23% respectively for 2.0 M H 2 SO 4 and 60 g/l citric acid concentration. Finally the process was followed by chemical precipitation using 2M sodium hydroxide solution, which recovered 93% of Zn and 90% of Mn from the leached solution as hydroxide. 1. INTRODUCTION The consumption of different types of zinc-carbon (Zn-C), alkaline, nickel-cadmium (Ni-Cd), nickelmetal hydride (NiMH) batteries are increasing in recent years. Resource recovery from waste dry cell batteries, offers a greater economic value. In 2012, the 17 members of the European Battery Recycling Association s (EBRA) recycled about 26,660 tons of portable batteries and accumulators (EBRA 2013). Worldwide Zn-C dry cell consumption is very high because of their favorable electrical properties and price ratio. Zn-C batteries are generally used in radios, recorders, remote controls, calculators, toys and many other objects where small quantities of power is required. Due to short lifespan, Zn-C dry cells run out rapidly and are thrown away. These large amounts of batteries, which are simply disposed to the environment, have high contents of zinc (Zn) and manganese (Mn). Therefore, an economically feasible recycling program is necessary for the resource recovery from Zn-C dry cells. In different developed countries several waste battery collection and recycle programs, such as EBRA, EMRC and SMRC, are in practice (EMRC 2013, EBRA 2014, SMRC 2014). In the last 30 years, several processes have been studied and developed to recover Zn and Mn from Zn-C dry cell (Espinosa, Bernardes et al. 2004, Sayilgan, Kukrer et al. 2009, Sayilgan, Kukrer et al. 2009, Shin, Senanayake et al. 2009, Senanayake, Shin et al. 2010, Khan and Kurny 2012). Batteries are generally recycled in pyrometallurgical or hydrometallurgical process (Bernardes, Espinosa et al. 2004). Pyrometallurgical process requires selective volatilization of metal at an elevated temperature (De Michelis, Ferella et al. 2007, Sayilgan, Kukrer et al. 2009). But Hydrometallurgical processes have several advantages over Pyrometallurgical processes like metal recovery at lower cost, and less air emission (Sayilgan, Kukrer et al. 2009). In hydrometallurgy metals can be leached from metal oxides present in the battery by reactions with acid or alkali solutions only or in presence of any reductive reagent. (Salgado, Veloso et al. 2003, Avraamides, Senanayake et al. 2006, F., D. et al. 2006, Mantuano, Dorella et al. 2006, GĘGA and WALKOWIAK 2011) Several methods have been introduced to recover metals from leach solutions * Corresponding Author: Mohidus Samad Khan, mohid@buet.ac.bd

149 after leaching like precipitation, liquid-liquid extraction, electro-winning. (de Souza and Tenório 2004, F., D. et al. 2006, Mantuano, Dorella et al. 2006, Ferella, De Michelis et al. 2010, KURSUNOGLU and KAYA 2014) Several research projects have been carried out to find an efficient hydrometallurgical recovery of metal by different leaching system like acidic leaching, alkaline leaching, and reductive acidic leaching (F., D. et al. 2006, Shin, Kang et al. 2008, Sayilgan, Kukrer et al. 2009, Shin, Senanayake et al. 2009, Ferella, De Michelis et al. 2010). Few well-known hydrometallurgical processes are RECYTEC, REVABAT, RECUPYL, BATENUS(RECYPYL, REVATECH, Nguyen 1991, Fröhlich and Sewing 1995). For a higher Mn recovery, many studies have focused on reductive acid leaching with different reductants like glucose, sucrose, lactose, oxalic acid, hydrogen peroxide (Veglio and Toro 1994, Ismail, Ali et al. 2004, F., D. et al. 2006, De Michelis, Ferella et al. 2007). This paper aims at the comparative studies of the effectiveness of the acidic leaching (sulfuric acid) to recover Zn and Mn from spent battery in presence of a reductive reagent citric acid. At first the black battery paste was separated from other component parts of the battery. It was then introduced through several treatments followed by reductive acidic leaching and chemical precipitation. Citric acid was chosen since it is cost effective and non-hazardous (Sayilgan, Kukrer et al. 2009). 2. METHODOLOGY 2.1 Battery Dismantling and Powder Pre- Treatment Spent zinc carbon batteries of different types and sizes were collected from Olympic Industries Limited Bangladesh. The batteries were manually dismantled. The black battery paste was separated from other component parts of the battery like plastic films, zinc casing, paper pieces etc. The battery paste was ground to fine particle size. Wet battery powder was heated in laboratory oven at 110 º C to remove moisture content until a constant weight was attained. The moisture content was found to be about 8% of the total wet battery paste. 2.2 Neutral Leaching The battery powder was washed with distilled water maintaining a solid/liquid ratio of 1:10 for 3 hours under continuous moderate stirring and heating. The average temperature during neutral leaching was 80 º C. After neutral leaching and consecutive filtering, Zn and Mn content in filtrate sample was determined by Atomic Absorption Spectrophotometry (AA-6800 Atomic Absorption Spectrophotometer by Shimadzu). It was found to be very negligible and ensured minimum loss of Zinc and Manganese with the filtrate. 2.3 Acid Leaching Acid leaching tests were done with sulphuric acid (H 2 SO 4 ) with citric acid as reducing agent. In acidic leaching, oxides of Zn and Mn were dissolved by H 2 SO 4 to form zinc sulphate (ZnSO 4 ) and manganese (II) sulphate (MnSO 4 ) according to the following reaction (De Michelis, Ferella et al. 2007): ZnO + H 2 SO 4 ZnSO 4 +H 2 O MnO + H 2 SO 4 MnSO 4 +H 2 O But other oxides of Manganese like Mn 2 O 3, Mn 3 O 4 dissolve partially as the MnO 2 produced in the reaction is insoluble (F., D. et al. 2006). The following reactions explain the formation of MnO 2 : Mn 2 O 3 + H 2 SO 4 MnO 2 + MnSO 4 + H 2 O Mn 3 O 4 + 2H 2 SO 4 MnO 2 + 2MnSO 4 + 2H 2 O Therefore, a reducing agent is required to dissolve all the Mn as MnSO 4 (Salgado, Veloso et al. 2003, Veloso, Rodrigues et al. 2005, De Michelis, Ferella et al. 2007). The reduction of MnO 2 to MnSO 4 with citric acid occurs as follows (Ferella, De Michelis et al. 2010): 9MnO 2 +9H 2 SO 4 +C 6 H 8 O 7 9MnSO 4 +6CO 2 +13H 2 O The leaching test was performed in a closed erlenmeyer flask set on an electric heater equipped with a magnetic stirrer (JSR hotplate and stirrer). A condenser was used to ensure that the heating did not affect the molarity of the solution. 2.4 Leaching Tests with Sulphuric Acid- Citric Acid Leaching test with sulphuric acid citric acid was performed in a 250 ml closed Erlenmeyer flask set on an electric heater equipped with a magnetic stirrer. The solution mixture was prepared by dissolving neutral leached battery powder and citric acid (Merck) (varying concentrations of citric acid: 20, 40 and 60 gm/l) in 100 ml sulphuric acid (varying concentrations of sulphuric acid: 1.5 M, 1.8 M and 2.0 M) maintaining 20% pulp density. The mixture was continuously stirred for 3 hours at moderate speed with the hot plate magnetic stirrer and the temperature was kept at 80ºC. The final solution was filtered with filter paper (Whatman No.42).The amount of Zn and Mn dissolved in the filtered solution was measured by Atomic 140

150 Absorption Spectrophotometer using AA- 6800(Shimadzu). 2.5 Chemical Precipitation Chemical precipitation tests have been performed on filtered leach solution from the reductive-acid leaching step. ph of the solution was increased slowly with 2N NaOH (Merck) solution. Complete precipitation of zinc and manganese occurred at ph value of 8 and 12 respectively. 3. RESULTS AND DISCUSSIONS The battery paste separated from a single D type battery was about 57% of the total battery weight. Weight of the different components of battery were measured with laboratory weighing machine (Shimadzu libror EB330H). The XRF analysis of the dry and washed electrolyte paste was done by XRF-1800 by SHIMADZU. According to XRF analysis of dry battery paste, Zn and Mn constituted almost 65% of the electrolyte paste (Table 2). Table 1. Percentage of Different Components in a D-Type Zinc-Carbon Dry Cell Component Weight(gm) Percentage (%) Zinc Casing(Anode) Upper and Lower Steel Paper Plastic Scrap Battery Paste Carbon Rod Moisture Content Total Table 2. XRF analysis of the dry battery paste (D type) Metal Weight Percentage (%) Mn Zn C Fe 6.13 Si 1.76 Al 1.47 K 0.52 Ru 0.30 Ca 0.16 Co 0.10 Ni 0.08 S 0.08 Ti 0.08 Table 3. XRF analysis of the neutral leached battery paste (D type) Metal Weight Percentage (%) Mn Zn C Fe 2.57 Si 2.10 Al 1.74 K 0.71 Ru 0.18 Ba 0.13 Co 0.12 Ca 0.11 Ti 0.10 Ni 0.08 S 0.07 Cu 0.05 Cr 0.04 After neutral leaching, the washed powder contained 75% of Zn and Mn together in the electrolyte paste (Table 3). The amount increased as the moisture content was removed from original battery powder by heating and the water soluble ions were removed through neutral leach process. Table 4. Recovery of Zinc and Manganese by Reductive Acidic Leaching Constant parameters H 2 SO 4 :1.5M Leaching time:3 hrs Pulp density:20% Temperature: 80 o C H 2 SO 4 :1.8M Leaching time:3 hrs Pulp density:20% Temperature: 80 o C H 2 SO 4 :2.0M Leaching time:3 hrs Pulp density:20% Temperature: 80 o C Citric acid concentrations (g/l) Zinc Recover y (%) Manganese Recovery (%)

151 Highest dissolution of Mn and Zn by reductive-acid leaching were found to be 91.85% and 39.23% respectively for 2M sulphuric acid and 60g/l of citric acid concentration at 80 o C and 20% pulp density (Table 4). 93% Manganese and 90% Zinc have been recovered from this leached liquor using chemical precipitation. The dissolution of Mn seemed to increase with the molarity of sulphuric acid solution at constant 60g/l citric acid concentration. Chemical precipitation tests have been performed on filtered leach solution. Complete precipitation of Zn and Mn occurred at ph value of 8 and 12 respectively. 93% Mn and 90% Zn were recovered from the leached solution as hydroxides. 4. CONCLUSIONS With increasing consumption of zinc-carbon dry cell batteries, their disposal and management have become an issue of great concern. Different countries have imposed strict regulation on their disposal due to growing environmental concern. With the idea to reuse valuable metals contained in spent dry cells, a hydrometallurgical process has been proposed in this study. Highest simultaneous recovery of both Manganese and Zinc was found to be 2.0M H 2 SO 4, 60g/l citric acid, 20% pulp density, 80 o C temperature with moderate stirring speed % of Manganese and 39.23% of Zinc have been recovered through the reductive-acid leaching process. Precipitation tests on obtained liquors have also been performed showing 93% Manganese and 90% Zinc recovery from the leached liquor. The results verify that citric acid can be successfully used to extract manganese and zinc from spent dry cells. Analytical study of the results shows that recovery of manganese is positively influenced by increase in sulphuric acid concentration and citric acid dosage. Further study will be continued on higher recovery of Zn with a suitable reducing agent. The main attraction in this hydrometallurgical approach is that the reagents and extracted metals can be reused and recycled, which makes the process cost effective and environmentally friendly. This research will also be continued to introduce a feasible industrial process to recover the resources in spent zinc carbon batteries. ACKNOWLEDGEMENT The authors acknowledge Mr. Nazrul Islam of Olympic Battery Ltd. Bangladesh for providing spent Zn-C batteries, Dr. Rowshan Mamtaz of the Department of Civil Engineering, BUET for helping with AAS experiment and Department of Glass and Ceramics Engineering, BUET for XRF analysis. REFERENCES 1. Avraamides, J., G. Senanayake and R. Clegg (2006). "Sulfur dioxide leaching of spent zinc carbon-battery scrap." Journal of Power Sources 159(2): Bernardes, A. M., D. C. R. Espinosa and J. A. S. Tenório (2004). "Recycling of batteries: a review of current processes and technologies." Journal of Power Sources 130(1 2): De Michelis, I., F. Ferella, E. Karakaya, F. Beolchini and F. Vegliò (2007). "Recovery of zinc and manganese from alkaline and zinccarbon spent batteries." Journal of Power Sources 172(2): de Souza, C. C. B. M. and J. A. S. Tenório (2004). "Simultaneous recovery of zinc and manganese dioxide from household alkaline batteries through hydrometallurgical processing." Journal of Power Sources 136(1): EBRA (2013). 2012: Noticeable growth of the quantity of batteries recycled by EBRA members, European Battery Recycling Association. 6. EBRA. (2014). "European Battery Recycling Association." Retrieved 9/14, 2014, from 7. EMRC. (2013). "Battery recycling: overview." Retrieved 9/18, 2014, from 8. Espinosa, D. C. R., A. M. Bernardes and J. A. S. Tenório (2004). "An overview on the current processes for the recycling of batteries." Journal of Power Sources 135(1 2): F., F., M. I. D., P. F., B. F., F. G., N. M., V. F. and T. L. (2006). "Recovery of zinc and manganese from spent batteries by different leaching systems." Acta Metallurgica Slovaca 12: Ferella, F., I. De Michelis, F. Beolchini, V. Innocenzi and F. Vegli (2010). "Extraction of Zinc and Manganese from Alkaline and Zinc- Carbon Spent Batteries by Citric-Sulphuric Acid Solution." International Journal of Chemical Engineering Fröhlich, S. and D. Sewing (1995). "The BATENUS process for recycling mixed battery waste." Journal of Power Sources 57(1 2): GĘGA, J. and W. WALKOWIAK (2011). "Leaching of Zinc and Manganese from Used Up Zinc-Carbon Batteries Using Aqueous 142

152 Sulfuric Acid Solutions." Physicochemical Problems of Mineral Processing 46: Ismail, A. A., E. A. Ali, I. A. Ibrahim and M. S. Ahmed (2004). "A comparative study on acid leaching of low grade manganese ore using some industrial wastes as reductants." The Canadian journal of chemical engineering 82(6): Khan, M. H. and A. S. W. Kurny (2012). "Characterization of Spent Household Zinc- Carbon Dry Cell Batteries in the Process of Recovery of Value Metals." Journal of Minerals & Materials Characterization & Engineering 11(6): KURSUNOGLU, S. and M. KAYA (2014). "DISSOLUTION AND PRECIPITATION OF ZINC AND MANGANESE OBTAINED FROM SPENT ZINC-CARBON AND ALKALINE BATTERY POWDER." Physicochemical Problems of Mineral Processing 50(1): Mantuano, D. P., G. Dorella, R. C. A. Elias and M. B. Mansur (2006). "Analysis of a hydrometallurgical route to recover base metals from spent rechargeable batteries by liquid liquid extraction with Cyanex 272." Journal of Power Sources 159(2): Nguyen, T. T. (1991). Process for the simultaneous recovery of manganese dioxide and zinc, Google Patents. 18. RECYPYL. Retrieved 9/21, 2014, from hydrometallurgy.html. 19. REVATECH. "RECYCLING OF ALKALINE AND ZINC-CARBON BATTERIES." Retrieved 9/21, 2014, from ml. 20. Salgado, A. L., A. M. O. Veloso, D. D. Pereira, G. S. Gontijo, A. Salum and M. B. Mansur (2003). "Recovery of zinc and manganese from spent alkaline batteries by liquid liquid extraction with Cyanex 272." Journal of Power Sources 115(2): Sayilgan, E., T. Kukrer, G. Civelekoglu, F. Ferella, A. Akcil, F. Veglio and M. Kitis (2009). "A review of technologies for the recovery of metals from spent alkaline and zinc carbon batteries." Hydrometallurgy 97(3 4): Sayilgan, E., T. Kukrer, F. Ferella, A. Akcil, F. Veglio and M. Kitis (2009). "Reductive leaching of manganese and zinc from spent alkaline and zinc carbon batteries in acidic media." Hydrometallurgy 97(1 2): Senanayake, G., S. M. Shin, A. Senaputra, A. Winn, D. Pugaev, J. Avraamides, J. S. Sohn and D. J. Kim (2010). "Comparative leaching of spent zinc-manganese-carbon batteries using sulfur dioxide in ammoniacal and sulfuric acid solutions." Hydrometallurgy 105(1 2): Shin, S. M., J. G. Kang, D. H. Yang, J. S. Sohn and T. H. Kim (2008). "Selective Leaching of Zinc from Spent Zinc-Carbon Battery with Ammoniacal Ammonium Carbonate." MATERIALS TRANSACTIONS 49(9): Shin, S. M., G. Senanayake, J.-s. Sohn, J.-g. Kang, D.-h. Yang and T.-h. Kim (2009). "Separation of zinc from spent zinc-carbon batteries by selective leaching with sodium hydroxide." Hydrometallurgy 96(4): SMRC. (2014). "Southern Metropolitan Regional Council " Retrieved 9/14, 2014, from s/grants/strategic-waste-initiativesscheme/dry-cell-battery-waste-collection-andrecycling-program. 27. Veglio, F. and L. Toro (1994). "Reductive leaching of a concentrate manganese dioxide ore in acid solution: stoichiometry and preliminary kinetic analysis." International Journal of Mineral Processing 40(3 4): Veloso, L. R. S., L. E. O. C. Rodrigues, D. A. Ferreira, F. S. Magalhães and M. B. Mansur (2005). "Development of a hydrometallurgical route for the recovery of zinc and manganese from spent alkaline batteries." Journal of Power Sources 152(0):

153 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh PIPELINE LEAK DETECTION USING PARTICLE FILTERS B. M. S. Arifin*, Zukui Li and Sirish L. Shah Department of Chemical and Materials Engineering, University of Alberta, Edmonton, Canada T6G 2V4 While most of the available Leak Detection Systems (LDS) can detect pipeline leak efficiently, pin pointing the leak location is still an unresolved problem. The main reason for this problem is limited number of sensors installed on long pipelines. Because of lack of measurements, precise leak location cannot be often determined. This study is an attempt to remedy this problem by using a particle filter as a soft-sensor to estimate the measurements at some intermediate locations with the help of available end-point measurements. Simulations are performed to check the efficacy of the proposed method. 1. INTRODUCTION Pipelines are now commonly used to transport hydrocarbon fluids over long distances from the production site to the end-user (Chis, 2007 and Sivathanu, 2003). The fluids are often flammable, toxic, corrosive and hazardous to the environment. Early detection and localization of leaks is therefore of utmost importance (Chis, 2007, Sivathanu, 2003). Existing pipeline leak detection techniques can be classified as internal and external methods (Williams, 1996 and Zhang et. al., 2013). Internal methods monitor internal pipeline parameters by using already installed sensors; on the other hand external methods work on the principle of physical detection of escaping fluid (Zhang et. al., 2013). External methods can usually detect the leak location more precisely but they are more costly and cannot be retrofitted on old pipelines in most cases. Hence, external methods are not used for continuous monitoring. On the other hand, internal methods can be used for continuous monitoring with less cost. But most of the existing internal methods cannot detect the leak location precisely. In particular, small leaks are difficult to detect. If the leak detection methods are sensitized to detect small leaks, there is always the risk of many false alarms with the result that the operators are often overwhelmed by too many false alarms (Rafai and Barnes, 1999). Internal methods can be broadly divided in two groups as model based and data driven (Zhang et. al., 2013). For the model based methods, a dynamic pipeline flow model is required (Geiger, 2006). The disadvantages of model based methods are that the models are composed of nonlinear partial differential equations and hence a closed form solution is not available. Furthermore, a lot of uncertainties are involved due to changes or imprecise information of fluid properties (e.g. fluid density and viscosity), fluctuation in ambient and process conditions, changes in pipeline properties such as scaling and roughness. On the other hand data driven methods (Zhang et. al., 2013) do not require any model but they rely on the statistical analysis of the steady state archived data of the pipeline system. So, the disadvantages are that this method cannot detect leak under transient conditions and a lot of a-priori information plus process data is required which may not always be available. Data driven methods also fail to localize the leak position when the leak size is small (less than 5% of nominal flow rate). Since data driven (statistical analysis) methods suffer from poor performance during transient conditions and are unable to detect small leaks and localize the leak location, the model based method (based on real time transient model) is considered in this study. To handle the uncertainties involved with the model, Monte Carlo simulation based particle filter algorithm (Arulampalam et. al., 2002) is used to estimate the unmeasured states and filter the measured values using available measurements in hand. The residual errors are used for leak detection. In a previous study, a particle filter algorithm was used to detect leaks in gas pipelines in a simulation environment (Liu et. al., 2005). This study focuses on liquid pipelines. The deviation between the estimated states of the model and actual measurements (where there are * Corresponding Author: B. M. S. Arifin, arifin@ualberta.ca

154 real sensors in the pipeline) will give the indication of leak and also be used to pin-point leak location. In this article, some simulation results of softsensing with the particle filter are included. Work will be focused on validating the proposed system on real pipeline data and subsequent implementation of the methodology on a real system. 2. METHODOLOGY AND PROBLEM DESCRIPTION Let us first discuss how the soft-sensing approach will be incorporated in this case. Fig. 1: Soft-Sensing approach in pipe-line leak detection Figure 1 gives a rough idea about applying the softsensing approach in pipeline leak detection. For simplicity we are assuming that the pipeline operates in an isothermal mode. So, the energy equation and temperature measurements are neglected in the current study. In most of the cases, we have measurements available at the ends of the pipeline. In the case of Fig 1, pressure, mass flow rate and density of both node 1 (,, ) and node 7 (,, ) are available. We need at least 4 among these 6 inletoutlet measurements, 2 will be used as the boundary conditions of the continuity and momentum equations and 2 will be used as the measurement with which the estimates of the particle filter will be compared to update the estimated states. and node 5), the accuracy of the estimated states will increase and often data of some intermediate nodes are measured in real life, especially at the intermediate pump and valve stations. Generally the intermediate pump stations are located at 50 mile intervals. Using these data and the power of a particle filter we can have estimated data even at 5 mile intervals. Once the data for the no-leak (normal) condition have been estimated at 5 mile intervals, these will be then used as reference data. Now, if there is a leak, both the true end data (node 1 and node 7) and true intermediate data (node 3 and 5) will show some discrepancy from their standard behavior. By capturing these discrepancies, a leak will be detected. For the leak localization, these data will be used to estimate the unknown states at smaller grid points say at 5 mile intervals. They will also deviate from the previously estimated data under no leak condition. The section (each section has length of 5 mile), which shows the maximum amount of discrepancy, will be the detected as the section with the leak. Hence, this method will pin-point the leak location within a 5 mile distance which is a great improvement over the current leak detection methods, which can localize leak within a 50 mile distance. In this study, the simulated pipeline is 37 km in length with 16 inch inlet diameter. The continuity and momentum balance equations are discretized by the method of characteristic (Thomas, 1999). The equations are given below: Continuity equation: Momentum equation: = 0.(1) Our goal is to use a particle filter to estimate the pressure, mass flow rate and densities (states) of the intermediate nodes (denoted by in Fig. 1). For example, let and be the boundary conditions and and are two available measurements. Now, the particle filter will estimate the rest of the 17 unknown states. Discretized equations: (2) The power of the particle filter is that it can estimate the unknown states quite accurately even if the model is highly non-linear and the noise is non- Gaussian. So, we can take these estimated states as our true measurements. Of course if we had some more true measurements in hand (suppose node 3 (3) 145

155 3. SIMULATION PREPARATION AND SIMULATION RESULTS 3.1 Preparation for Simulation.(4) Where, pressure (Pa) = velocity of sound in the pipe fluid (m/s) cross-sectional area of the pipe (m 2 ) mass flow rate (kg/s) pipeline friction factor (Fanning friction factor) pipeline diameter (m) sample time (s) specific volume (m 3 /kg) fluid density (kg/m 3 ) gravitational acceleration (m/s 2 ) angle of elevation from the flat land (degree) number of space nodes number of time nodes For the simulation purpose, the 37 km pipeline was divided into 19 equal divisions (20 nodes). Fig. 2 is a schematic of the nodes. We have a total of 60 variables which include pressure, mass and density at each of these nodes. For simplicity, the pipeline was assumed to be horizontal throughout its length i.e., is assumed to be zero in equations 3 and 4. The boundary conditions were a) mass flow rate at node 1 ( ) and b) pressure at node 20 ( )). We also had two measurements as a) pressure at node 1 ( ) and b) density at node 1 ( ). There were two significant mismatches between the model for simulation and the model used in Particle Filter (PF) estimation. One of them was the change in density ( ). While simulating the pipeline, fluid compressibility was considered constant whereas during the estimation stage, fluid density was considered to be constant. Unequal initial condition was the other mismatch. Process uncertainty was simulated by adding Gaussian white noise with the simulated state variables. Fluid compressibility was simulated by using the following equation (Hayward, 1967): (5) where, bulk modulus of the fluid =, volume of liquid at zero pressure, volume of liquid at pressure. Fig. 2: Schematic diagram of the process to be used in the simulation In this study, the pipeline was simulated with the combination of equations 3, 4 and 5. Kerosene was chosen as the working fluid for these simulations. So, properties of kerosene were used in equations 3 and 4. We equally divided the 37 km long pipeline in 19 sections (20 nodes) for computational simplicity. Although in an actual system, neither are these nodes equidistant nor are the number of nodes 20. Though in the real case, the mass flow rate is not constant at the leak free condition, for simplicity we assumed it as constant with some noise. Similar simplifications were made for pressure and density. We also avoided unpredictable or sudden changes in our simulated model. In this study it was found that friction factor ( ) and sonic velocity ( ) were two crucial tuning parameters for the simulated model to converge with the theoretical nature. Since the pipelines were old, roughness of the pipelines were much bigger from the literature value. After fixing all these issues, we could finally simulate our pipeline model. The next step was to add noise to the simulated data, to be subsequently used as measurement and boundary values for the particle filter part. The particle filter part was used to estimate the unknown states. For brevity, in this study we included the result for node 7 and node 15 to check the efficiency of the particle filter. Pressure and mass flow rates of these two nodes were investigated. In all these simulations, a total of 500 samples were simulated and the sample time was 5s. So the total simulation length was 2500s. 3.2 Simulation Results 146

156 Mass Flow Rate (kg/s) Pressure (Pa) Pressure (Pa) Pressure (Pa) Pressure (Pa) The simulation results are shown in Fig 3 through Fig 11. One crucial issue with particle filter is to select the optimal number of particles. Generally, the more the number of particles used, the more the accuracy of estimation observed with the cost of more computational effort (Modisette, 2013). All the simulations in this study were done with several particle numbers. For simplicity, the results included here contain only the lowest and highest number of particles that were used during the simulations. From industrial practice, if the leak cannot be properly detected and located within 10 minutes of first leak detection alarm, the pipeline is completely shutdown to avoid any unpleasant circumstances. So, there is a tradeoff between accuracy and computational effort. Figures 3 to 6 compare the estimated pressure with the simulated pressure at node 7 and node 15. It is to be noted in Fig. 3 to 5 that though there was huge differences in initial states between simulation model and estimation model, the particle filter was able to track the simulated pressure. It is realizable that due to model uncertainty or noise in the original (simulated states) states, exact estimation of the states is not possible. Fig. 4 and Fig. 6 are the zoomed in versions of Fig. 3 and Fig. 5 respectively. From Fig. 4, it is clear that although with particle number 10 the estimated pressure of node 7 converged 12 samples earlier than particle number 100, in terms of error accumulation, estimation with particle number 100 is more accurate. Fig. 6, shows similar result for pressure at node 15, though in this case both the estimated pressure converged with the simulated pressure at the same time. Simulated and Estimatied Pressures (Pa) at node 7 x Simualated 6 Estimated with 10 Particles Estimated with 100 Particles Number of Samples Fig. 3: Comparison of pressures at node 7 Fig. 7 and Fig. 9 show the comparison of simulated and estimated mass flow rates at node 7 and node 15 with different number of particles. It is again clear that although there were differences in initial conditions, the particle filter was able to track the true mass profile. The zoomed in versions of Fig. 7 (Fig. 8) and Fig. 9 (Fig. 10) show that in case of mass flow rate, the number of particles has negligible effect on the convergence rate and estimation with number of particles 10 and 100 are quite similar. Simulated and Estimatied Pressures (Pa) at node 7 x Simualated Estimated with 10 Particles 2.7 Estimated with 100 Particles Number of Samples 3 2 Fig. 4: Zoomed in version of Fig. 3 Simulated and Estimatied Pressures (Pa) at node 15 x Simualated 4.5 Estimated with 10 Particles Estimated with 100 Particles Number of Samples Fig. 5: Comparison of pressures at node 15 Simulated and Estimatied Pressures (Pa) at node 15 x Simualated Estimated with 10 Particles 1.45 Estimated with 100 Particles Number of Samples Fig. 6: Zoomed in version of Fig. 5 Simulated and Estimatied Mass Flow Rate (kg/s) at node 7 Simualated Estimated with 10 Particles Estimated with 100 Particles Number of Samples Fig. 7: Comparison of mass flow rates at node 7 Fig. 11 gives a comparative idea of computational cost with the increase of particle numbers. Considering the industrial practice of allocating

157 Mass Flow Rate (kg/s) Mass Flow Rate (kg/s) Mass Flow Rate (kg/s) Time required (s) to Simulate 500 samples or 2500s minutes time to locate the leak position and accuracy, 50 particles is the best choice for the pipeline system. These findings will be helpful while applying the particle filter in a real pipeline. 4. CONCLUSION AND FUTURE WORK The simulation results show that if the prediction model is good, then the particle filter works very well to capture the dynamics of the real system and it can serve the purpose of a leak detection softsensor. But the reality is, no model can imitate a real system accurately and the real system can have variability which cannot always be predictable by soft-sensors Number of Samples Simulated and Estimatied Mass Flow Rate (kg/s) at node 7 Fig. 8: Zoomed in version of Fig. 7 Simualated Estimated with 10 Particles Estimated with 100 Particles Number of Samples Fig. 9: Comparison of mass flow rates at node Simulated and Estimatied Mass Flow Rate (kg/s) at node 15 Simualated Estimated with 10 Particles Estimated with 100 Particles Simulated and Estimatied Mass Flow Rate (kg/s) at node 15 Simualated Estimated with 10 Particles Estimated with 100 Particles Number of Samples Fig. 10: Zoomed in version of Fig. 9 The future aim of this study is to make this approach applicable to real pipeline systems. The energy conservation equation will be also employed to better estimate the dynamics of the real pipeline. Since pipelines are not always horizontal, incorporating the elevation change in our prediction model will be another future improvement Number of Particles Fig. 11: Computational cost with Particle number REFERENCES Choice of Optimal number of Particles 1. Al-Rafai, W., & Barnes, R. J. (1999), Underlying the performance of real-time software-based pipeline leak-detection systems. Pipes and Pipelines International, 44(6), Arulampalam, M. S., Maskell, S., Gordon, N., & Clapp, T. (2002), A tutorial on particle filters for online nonlinear/non-gaussian Bayesian tracking. Signal Processing, IEEE Transactions on, 50(2), Chis, T. (2009), Pipeline leak detection techniques. arxiv- preprint arxiv : Geiger, G. (2006), State-of-the-art in leak detection and localization. Oil Gas European Magazine, 32(4), Hayward, A. T. J. (1967), Compressibility equations for liquids: a comparative study. British Journal of Applied Physics, 18(7), Liu, M., Zang, S., and Zhou, D. (2005), Fast leak detection and location of gas pipelines based on an adaptive particle filter. International Journal of Applied Mathematics and Computer Science, 15(4), Modisette, J. P. (2013), State Estimation of Pipeline Models using the Ensemble Kalman Filter. In PSIG Annual Meeting. Pipeline Simulation Interest Group. 8. Sivathanu, Y. (2003), Natural gas leak detection in pipelines, Technology Status Report, En Urga Inc., West Lafayette, IN. 9. Stafford, M., & Williams, N. (1996), Pipeline leak detection study. HSE Books. 10. Thomas, P. J. (1999), Simulation of industrial processes for control engineers. Butterworth- Heinemann. 148

158 11. Zhang, J., Hoffman, A., Murphy, K., Lewis, J., and Twomey, M. (2013), Review of Pipeline Leak Detection Technologies. In PSIG Annual Meeting. Pipeline Simulation Interest Group. 149

159 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh A STUDY ON CHITOSAN AND ITS DERIVATIVE AS ECO-FRIEND NATURAL FIBRE MODIFIER OBTAINED FROM PRAWN SHELL WASTE Md. Mofakkharul Islam 1, Md. Waliul Islam 1, Md. Asadul Hoque 2 and Md. Ibrahim H. Mondal 1 * 1 Polymer and Textile Research Lab, Department of Applied Chemistry and Chemical Engineering, Rajshahi University, Rajshahi 6205, Bangladesh 2 Department of Materials Science and Engineering, Rajshahi University, Rajshahi 6205, Bangladesh Natural fibre (Jute, Cotton) is agricultural renewable cellulosic raw material that have high stiffness, very low elasticity, susceptibility toward sunlight and microbial attacks etc, which cause hindrances on its use. Chitin is the second most abundant biopolymer after cellulose, distributed in the crustaceans (shirmps, crabs) shell waste. Chitosan is a deacetylated product of chitin. Chitosan and its derivative are safe and friendly substance for human usage. The present study reports synthesis, characterization and application of chitosan and its derivative on cotton fibre to minimize hindrance and enhance the effectiveness for intensified textile and other uses through the eco-friend modification and avoiding chemical modifier. The molecular weight, degree of deacetylation and ash content of prepared chitosan were 1,39,958 Da, 85% and 2.33% respectively. The moisture content, water holding capacity and total nitrogen content were above 10%, 450% and 6.5% respectively. FTIR spectra showed characteristic peaks of OH at 3415 cm -1, NH 2 at 1600 cm -1 and carbonyl at 1659 cm -1. The thermal behavior of chitin, chitosan, N-octyl chitosan, cotton, chitosan treated cotton and N-octyl chitosan treated cotton were investigated by Thermogravimetric analysis (TG), Differential thermal analysis (DTA) and Derivative thermogravimetric analysis (DTG). These analyses showed comparatively higher thermal stability of treated fibre than untreated fibre. N-octyl chitosan was identified by FTIR and the spectra showed that the peak at 1600 cm -1 of chitosan decreased due to the appearance of a new peak at 1520 cm -1 in N-octyl chitosan. Chitosan and its derivative were applied on cotton fibre and characterized. 1. INTRODUCTION Natural fibres, especially jute and cotton, are the agricultural renewable raw materials used for textiles as well as other products. Although these fibres possess high dimensional stability, there are some problems in the direct use of fibres in textiles due to some unfavorable properties such as, high stiffness, low elasticity, susceptibility towards sunlight (UV) etc. With a view to minimize the undesirable properties and to enhance their effectiveness for intensified textiles and other uses, the present study is of prime importance. Chitin is the major component in the outer shell of shrimps (prawn) and crabs, and the outer covers of insects. Chitin, poly (β-(1-4)-n-acetyl-dglucosamine), is a natural polysaccharide of major importance, first identified in 1884 (Rinaudo, 2006). Among the noble families of biological macromolecules, the relevance of chitin and its main derivative chitosan and others is becoming increasingly evident. Potential and usual applications of chitin and chitosan and their derivatives are estimated to be more than two hundred (Aranaz et. al., 2009). The duo are the second most abundant higher molecular weight biopolymers and are recognized as versatile environment friendly raw materials. Chitosan is a deacetylated product of chitin which is obtained from alkaline hydrolysis, in presence of ethanol with reflux at ambient temperature. Chemically, chitosan is a linear (1-4) linked 2- amino-2-deoxy-β-d-glucan (i.e. β-d-glucosamine) having the structure that is very much close to cellulose except the hydroxyl group in C(2) of cellulose is replaced by amino group in chitosan. Indeed, it is a copolymer of N-acetyl-glucosamine and glucosamine units (Muzzarelli, 1996, Hirano, 2003 and Oktem, 2003). Due to the limited solubility of chitosan, some researchers have attempted to prepare water soluble derivatives of chitosan which are safe and friendly substances for human usage (Chattopadhyay and Inamdar, 2013). * Corresponding Author: Md. Ibrahim H. Mondal, mihmondal@yahoo.com

160 Many chemicals that are used as modifiers from early for natural fibres are toxic to humans and do not easily degrade in the environment. The textile industry continues to look for eco-friendly processes that act as substitutes for toxic textile chemicals. From this point of view, chitosan and its derivatives are excellent candidates as eco-friendly textile chemical. Nowadays, the surface modification of textile fibres is considered as the best route to obtain modern textile treatments (Jocic et. al., 2002). It enables level of beneficial effect by the modification of fibre surface only, thus enhancing expected promising properties such as dyeability, elasticity, water repellency, smoothness, softness and minimizing whole fibre attack and hence avoiding the deterioration in fibre quality (Erra et. al., 1999). Among the various available biopolymers, polysaccharide chitosan (CS) is highly recommendable, since it shows unique chemical and biological properties and solubility in acidic solutions and many of its water soluble derivatives that are suitable for bond formation with cellulose makes them easily available for industrial purposes as fibre modifiers. The present investigation was undertaken for synthesis of chitosan and N-octyl chitosan derivative from prawn shell wastes as natural fibre modifier to develop high quality textile fibres using these synthesised eco-friendly bio-polymers. 2. EXPERIMENTAL 2.1 Materials Cotton fibres were collected from Keya Spinning Mill Ltd., Dhaka, Bangladesh. Prawn shells were collected from Mongla (near Sundarban forest) in Bangladesh that are wastes from prawn processing area. Sodium hydroxide, ethanoic acid, ethanol, sodium chlorite, hydrochloric acid, acetone, octanal, sodium borohydride etc. were purchased from Merck (Germany). All the reagents used were of analytical grade. 2.2 Methods Fibre preparation: Cotton fibres were treated with 0.2% Na 2 CO 3 solution at 75 o C for 30 min in the ratio of 1:50 (Singha and Thakur, 2009, Farouqui and Mondal, 1989, Mondal et. al., 2002). The fibre was then thoroughly washed with distilled water, dried at 105 o C and then stored in a desiccator : Preparation of chitin and chitosan from prawn shell: The collected prawn shells were first washed with hot water and dried at 105 o C for 72 h in an oven; the dried shells were then ground to different meshes using a blender. The deproteinnization and demineralization of raw chitin was carried out using 1M NaOH and 1M HCl by maintaining a solid:liquor ratio of 1:16 at 100 o C for 4h respectively (Alam et. al., 2008). Chitosan was obtained through deacetylation of chitin using NaOH in presence of ethanol (chitin:naoh = 1:30, w/w) at 80 o C for 4h. The resultant solid, known as chitosan, was washed to neutral and dried in a vacuum oven at 50 o C for 20 h Preparation of N-octyl chitosan: N-octyl chitosan (NOCS) was prepared by introducing an octyl group to NH 2 on C 2 of glucosamine unit. To prepare NOCS, 1gm of chitosan was suspended in 50 ml of methanol, and then 1g of octanal was added in the suspension while stirring at room temperature. After 24 h of reaction time, the ph of the reaction mixture was adjusted to 8-10 by NaOH solution and then NaBH 4 solution (0.5g in 5 ml of water) was slowly added to the reaction mixture. The reacting mixture was stirred with a magnetic stirrer at ambient temperature for another 24 h, followed by neutralization using 2M HCl. The prepared NOCS was collected by precipitation using methanol into the neutralized solution and then filtered, repeatedly washed with methanol and water, and dried at 60 o C for 12 h under reduced pressure (Zhang et. al.,2003, Vinsova and Vavrikova, 2008, Bobu et. al., 2011) Treatment of cotton fibre with chitosan and N-octyl chitosan: The washed fibres were dipped in chitosan and chitosan derivative containing solution of different concentrations at 60 o C for 1h. The ph of the solution was maintained at by using 0.2M acetic acid (Gerald and Witucki, 1993 ). The treated fibres were washed with distilled water and subsequently dried in hot air at 60 C to be at a constant weight. 2.3 Characterization of chitosan and its derivative, raw and modified fibre Moleculer weight of chitosan: Four different concentrations 0.2%, 0.4%, 0.6% and 0.8% solution of chitosan in 0.1M acetic acid and 0.2M NaCl (1:1, v/v) were prepared and the molecular weight was determined by Ostwald viscometer. From the intrinsic viscosity, the molecular weight (Mw) of chitosan was calculated, using Mark- Houwink equation (No. et. al., 2003, George and Julian, 1982): [η]=k(mw) a Where K and a are constants for given solutesolvent system and temperature. The Values of K and a are and 0.93 respectively Degree of deacetylation of chitosan: Elemental analysis is a simple, suitable and rapid method to determine the degree of deacetylation 151

161 (DDA) value of chitin. The degree of deacetylation was calculated from the carbon/ nitrogen ratio (C/N). It varies from in completely N- deacetylated chitosan (C 6 H 11 O 4 N per unit) to in chitin, the fully N-acetylated polymer (C 8 H 13 O 5 N repeat unit). The degree of deacetylation was therefore calculated according to the following equation (Kasaai et. al., 2000 ) DDA = {1-(C/N-5.145)/( )} Infrared spectroscopy: FTIR spectra of chitin, chitosan, N-octyl chitosan, cotton, chitosan treated cotton and N-octyl chitosan treated cotton were recorded with KBr pellets on Shimadzu IR spectrophotometer (Shimadzu, Kyoto, Japan). Briefly, a disk was made from 2 mg of chitin or chitosan powder and 200 mg of KBr Thermal analysis: The experiments were performed using a Seiko-Exstar-6000, TG/DTA (Seiko Instruments Inc. Japan). The tests were conducted between C under an inert atmosphere (Argon). The heating rate and the air flow rate were 10 C/min and 200 ml/min respectively Scanning electron microscopy: Scanning electron microscopy (SEM) was performed using a scanning electron microscope (FEI Quanta Inspect, Model: S50) to observe the micro structure and the surface morphology of the treated as well as untreated fibres. The fibres surfaces were coated with a thin film of carbon to render them conductive (Hunt et. al., 1997). 3. RESULTS AND DISCUSSION determined by viscometric method and the value was 1,39,958 Da Degree of deacetylation: Degree of deacetylation indicates the removal of acetyl groups from the molecular chain of chitin, leaving behind a complete amino group (-NH 2 ); chitosan versatility depends mainly on these high degree chemical reactive amino groups. The degree of deacelylation mainly depends on the method of purification, reaction conditions such as temperature, alkaline concentration and reaction time (Oktem, 2003). Estimated degree of deacetylation was around 85% Infrared spectroscopy: Fig. 1(a-f) show the characteristic FTIR spectra of chitin, chitosan, N- octyl chitosan, cotton, chitosan treated cotton fibre and N-octyl chitosan treated cotton fibre respectively. The peak intensity or band at 1659 cm -1 gradually decreased while that at 1600 cm -1 increased, indicating the prevalence of NH 2 groups; the peak at 1600 cm -1 displayed a grater intensity than the one at 1659 cm -1, demonstrating effective deacetylation of chitin. The spectral evidence of chitosan through chemical modification, namely, the disappearance of the peak at 1600 cm -1 due to the conversion of NH 2 into N-octyl substituents, and the occurrence of new bands at 1520 cm -1 corresponding to C-H stretching into methyl groups. From the curves in Fig. 1(d-f), it is clearly seen that cotton, chitosan treated cotton and N-octyl chitosan treated cotton are more or less near about same except at the band of 1317 cm -1 and 1340 cm -1 due to incorporation of chitosan and N-octyl chitosan respectively on the cotton fibre. Chitin in crustacean waste (Prawn shell) is tightly associated with protein, lipid, pigment and calcium deposits. Preparation of chitosan using prawn shell waste involved three main steps: deproteinization to remove proteins, demineralization to remove calcium carbonate and calcium phosphate and deacetylation to remove acetyl groups. During the demineralization process, excessive undesirable foams were produced due to generation of CO 2 gas Molecular weight: The physicochemical, biological and rheological properties of chitosan vary significantly as function of its molecular weight and molecular weight distribution (Rodriguez et. al., 2004). Moreover molecular weight of chitosan depends largely on the raw materials and reaction variables. It is therefore important and in some cases critical to know precise and accurate values of the molecular weight of the chitosan. The molecular weight was Fig. 1: FTIR spectra of (a) Chitin, (b) Chitosan, (c) N-octyl chitosan, (d) Cotton, (e) Chitosan treated cotton and (f) N-octyl chitosan treated cotton Thermal analysis: Thermal behavior of chitin, chitosan, cotton, chitosan treated cotton fibre and N- 152

162 octyl chitosan treated cotton fibre were examined by performing TG, DTG and DTA thermogram studies. From the experiment it was seen that the weight loss at C is 65.3% for chitin, at o C it is 70.9% for chitosan and at o C it is 69.3% for cotton respectively. The weight loss of chitosan and N-octyl chitosan treated cotton fibres are 54% at 350 o C and 29.7% at 306 o C respectively. From this analysis it is clear that the thermal stability of treated cotton fibres is much higher than that of the untreated cotton fibres. The DTA curve indicates two endothermic peaks at different temperatures due to moisture and thermal degradation of chitin, chitosan, cotton and, chitosan and N-octyl chitosan treated cotton fibres respectively. The DTG curve represents the decomposition rate at which the thermal decompositions occurred at different temperature ranges. Consequently, it can be said that the thermal stability of chitosan and N-octyl chitosan treated fibres are increased, compared to the unmodified fibres. This may have resulted due to the incorporation of chitosan and its derivative with the cotton fibres Surface morphology: The surface morphology of the treated and untreated cotton was studied under scanning electron microscope. Fig. 2(a-c) show the scanning electron micrograph of cotton, chitosan treated cotton and N-octyl chitosan treated cotton fibres respectively. The SEM micrograph represents the microporous surface of the untreated cotton fibre. But, the chitosan and N- octyl chitosan treated cotton fibres exhibit smoother surface due to the absorption of chitosan and N- octyl chitosan on the fibre. The surface of the chitosan treated fibre seems smoother than that of the N-octyl chitosan treated fibre. This is because of the film forming tendency of chitosan, which is more than N-octyl chitosan. Chitosan exhibits an inherent property of film formation, which is clearly seen as gloss on fibre surface. According to the photograph, chitosan is spread on the fibre in a homogeneous manner without agglomerating on the fibre surface. Fig. 2(b): SEM of chitosan treated cotton fibre Fig. 2(c): SEM of N-octyl chitosan treated cotton fibre 4. CONCLUSION Chitin, chitosan and its derivative were prepared successfully from prawn shell waste. The incorporation of chitosan and N-octyl chitosan on the cotton backbone were confirmed by FTIR analysis and thermogravemetric nature, and morphological study indicates the suitability of chitosan and N-octyl chitosan as modifier. These modified fibres will be used as key components for textile and many other uses. ACKNOWLEDGEMENTS The authors would like to acknowledge the Ministry of Education in Bangladesh for funding the project as Higher Education Research Grant in 2014 (Project Ref. No.: (38)/6-35). Fig. 2(a): SEM of raw cotton fibre REFERENCES 1. Alam, R., Khan, M. A., Khan, R. A., Ghoshal, S. and Mondal, M. I. H. (2008), Study on the physico-mechanical properties of photo-cured chitosan films with oligomer and acrylate monomer, Journal of Polymers and the Environment, 16, pp

163 2. Aranaz, I., Mengibar, M., Harris, R., Panos, I., Miralles, B., Acosta, N., Galed, G. and Heras, A. (2009), Functional characterization of chitin and chitosan, Current Chemical Biology, 3, pp Bobu, E., Nicu, R., Lupei, M., Ciolacu F. L. and Desbrieres, (2011), Synthesis and characterization of N-alkyl chitosan for paper making applications, Cellulose Chemistry and Technology, 45(9-10), pp Chattopadhyay, D. and Inamdar, M. S. (2013), Improvement in properties of cotton fabric through synthesis nono-chitosan application, Indian Journal of Fibre and Textile, 38, Erra, P., Molina, R., Jocic, D., Julia, M. R., Cuesta, A. and Tascon, J. M. D. (1999), Shrinkage Properties of Wool Treated with Low Temperature Plasma and Chitosan Biopolymer,Textile Research Journal, 69, pp Farouqui, F. I. and Mondal, M. I. H. (1989), Scouring and bleaching of jute fibre in relation to its strength, Rajshahi University Studies, Part-B, XVII, 1 7. George A. F. R. and Julian, G. D. (1982), Determination of the viscometric constants for chitosan, Journal of Biological Macromolecules, 186, pp Gerald L. and Witucki, A. (1993), Silane Primer: Chemistry and application of alkoxy silanes, Journal of Coatings Technology, 65, pp Hunt, B.J. and James, M. I. (1997), Polymer Characterization (1 st edition), Blackie Academic and Professional, London. 10. Jocic, D., Jovancic, P., Petrovic, Z., Bertan, E., Navarro, A., Julia, M. R. and Erra, P. (2002), The Textile Conference 2 nd Autex Conference, Textile Engineering at the dawn of a new millennium: An exciting challenge, Bruges, Belgium 1-3 July, pp Kasaai, M.R., Arul J. and Charlet, G (2000), Intrinsic Viscosity Molecular Weight Relationship for Chitosan, Journal of Polymer Science Part B Polymer Physics 38, Mondal, Md. I. H., Farouqui, F. I. and Enamul Kabir, F. M. (2002), Graft copolymerization of cellulose fibre using potassium persulphate as initiator, Cellulose Chemistry and Technology, 36, pp Muzzarelli, R. A. A. (1996), in the polymeric materials encyclopedia edited by Salamone J. C. (CRC press Inc. Boca Raton Fl, USA), pp No., H. K., Lee, S. H., Park, N. Y. and Meyers, S. P. (2003), Comparison of physicochemical, binding and antibacterial properties of chitosan prepared without and with deproteinization process, Journal of Agricultural and Food Chemistry, 51, pp Oktem T. (2003), Surface treatment of cotton fabric with chitosan, Coloration Technology, 119, pp Rinaudo, M. (2006), Chitin and chitosan: Properties and applications, Progress in Polymer Science, 31(7), pp Rodriguez,B. B., Bolbot, J. A. and Tothill, I. E. (2004), Urease-glutamic dehydrogenase biosensor for screening heavy metals in water and soil samples, Analytical and Bioanalytical. Chem., 380, pp Singha, A. S. and Thakur, V. K., (2009), Synthesis and characterization of silane treated grewia optiva fibres, International Journal of Polymer Analysis and Characterization, 14, pp Vinsova, J. and Vavrikova, E. (2008), Recent advances in drugs and prodrugs design of chitosan, Current Pharmaceutical Design, 14, pp Zhang, C., Ping, Q., Zhang, H., Shen, J. (2003), Preparation of N-alkyl-O-sulfate chitosan derivatives and micellar solution of taxol, Carbohydrate Polymer, 54, pp

164 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh MODIFICATION OF COTTON FIBRE WITH FUNCTIONALIZED SILANE COUPLING AGENTS Md. Khademul Islam, Md. Raihan Sharif and Md. Ibrahim H. Mondal* Polymer and Textile Research Lab, Department of Applied Chemistry and Chemical Engineering, Rajshahi University, Rajshahi 6205, Bangladesh Modification of cotton fibre was studied by condensation polymerization with functionalized silane coupling agents like vinyltrimethoxysilane (VTMS) and vinyltriethoxysilane (VTES) in ethanol/water medium. The modification of cotton fibre enhanced the tensile, water repellency and wrinkle recovery properties due to higher flexibility of Si-O bond and fibre matrix interfacial strength properties. The hydrophilicity of modified cotton fibre was decreased in aqueous solution which affects the overall chemical phenomenon of the fibre. The optimized condition of modification for VTMS and VTES was 600% and 500% on the weight of fibre in ethanol/water mixture (60:40) containing surfactant by maintaining a ph of 3.5 at 40 C in the fibre-liquor ratio of 1:40. It was observed that swelling behaviour and moisture absorption of modified cotton fibres decreased in polar solvents, whereas they increased in nonpolar solvents. The inclusion of silicon containing species and the quantities of atomic silicon were identified by Fourier transform infrared spectroscopy (FTIR) and Energy Disperse X-ray analysis (EDAX) respectively. The surface morphology and thermal behavior of the modified fibre was investigated by Scanning electron microscopy (SEM) and Thermo gravimetric analysis (TGA) respectively. 1. INTRODUCTION Cotton fibre is one of the most important natural fibres that has a wide range of applications in textile materials because of its availability, low density, light weight, low cost, and above all environment friendly characteristics (Mohanty et al., 2003, Van voorn et al., 2001). It can easily be transformed into multifarious products affecting every phases of our daily life because of its wide spread application. But the major problem of cotton products is hydrophilicity and moisture sensitivity in nature which limit an extended use of cotton as well as other fibres (Rachini et al., 2012). These properties affect the stability of cotton goods of its environments. Many physicochemical modification steps have already been done to overcome these properties such as alkaline treatment, acetylation, benzoylation, acrylation, oxidation and isocynation of the natural fibre (Singha and Rana, 2012). The modification of cotton fibre by silane coupling agent has been receiving considerable attention, recently. The modified cotton fibre exihibits versatile physico-chemical properties including improved tensile strength, elasticity, swelling properties, wrinkle recovery properties, fastness and thermal stability properties, etc. In this study, we present the chemical modification of cotton fibres treated with two organosilane coupling agents, such as vinyltrimethoxysilane (VTMS) and vinyltriethoxysilane (VTES), in an ethanol/water system. The effect of various grafting parameters and chemical structure of organosilane on the grafting quantity and treated fibres were characterized using various experimental techniques including Scanning electron microscopy (SEM), Thermogravimetric analysis (TGA) and Fourier transform infrared spectroscopy (FTIR) and Energy disperse X-ray analysis (EDX). The moisture absorption & swelling behavior and tensile strength were also studied for physical characteristics of modified cotton fibre. 2. EXPERIMENTAL 2.1 Materials Cotton fibres were collected from Keya spinning mills Ltd., Bangladesh. Ethanol, sodium carbonate and acetic acid were purchased from Merck Germany. The silane coupling agents, vinyltrimethoxysilane (VTMS) and vinyltriethoxysilane (VTES) were collected from Aldrich, USA. All other reagents and solvents were commercial products of high purity. 2.2 Methods Washing of Cotton Fibre: The fibres were first washed thoroughly with 0.2% Na 2 CO 3 solution at 75 C for 30min in the ratio of 1: 50 (Singha et al., 2009a). * Corresponding Author: Md. Ibrahim H. Mondal, mihmondal@yahoo.com

165 2.2.2 Silane Treatment: The pretreated fibres (washed) were dipped in alcohol-water mixture (60:40 v/v) containing VTMS and VTES for 1h. The ph of the solution was maintained at 3.5 to 4 by using 0.2M acetic acid (Gerald et al., 1993). The treated fibres were washed with distilled water and subsequently dried in hot air at 60 C. The swelling behavior, moisture sorption, thermal properties and chemical resistance behavior of the silane treated fibres were studied. 2.3 Evaluation of Physical and Chemical properties Chemical Resistant: The chemical resistance of the silane treated fibre was studied as a function of percent weight loss of fibre when treated with different chemicals. A known amount of raw and silane treated fibre was dipped in a definite volume of hydrochloric acid and sodium hydroxide of definite strength for a time interval (12-48 h) and percent chemical resistance was calculated using the following formula (Singha et al., 2009a). Chemical resistant, % = Wi Wf 100 Wi Where W i and W f indicate the initial and final weights of the fibres respectively Wrinkle Recovery Angle : Wrinkle recovery of a fabric is defined as the ability of the fabric to resist the formation of wrinkles when subjected to a folding deformation. The wrinkle recovery measurement was performed by Wrinkle recovery tester (Daiei Kagaku Seiki Ltd. Kyoto, Japan) in Apparel Manufacturing Department, University of Textile Engineering, Dhaka. The test was performed by cutting the treated sample into cm size patches. The patches were then folded and kept under the weight of 500 gm for 5 min. Finally the folded samples were inserted inside a template, which was later placed in the testing machine Moisture Absorption: The moisture absorption of the VTMS and VTES treated fibres as well as raw fibres were performed at a constant humidity level. The treated and raw samples of cotton fibres were dried at 60 C in an oven until a constant weight was obtained. The percent moisture absorption was studied as a function of weight gain and was calculated using the following formula (Singha et al., 2009a). Moisture absorption, % = Wf Wi 100 Wi Where W i and W f are the weight of the dried samples and the final weight of the sample taken out from the humidity chamber Swelling Behavior: Swelling behavior of the modified and raw cotton fibres was determined by treating with water, methanol, and carbon tetrachloride. Known initial weights W i of the VTMS and VTES treated and raw samples were immersed in 100 ml of solvent at room temperature for 72 h. The samples were filtered and the excess solvent was removed with the help of filter paper, then the final weight W f was measured. The percent swelling was calculated (Singha et al., 2009a) as: Swelling, % = Wf Wi 100 Wi Where W i and W f indicate the initial and final weight of the fibres respectively. 2.4 Characterization of Raw and Surface Modified Cotton Fibre Infrared Spectroscopy: FTIR spectra of the silane treated and raw fibres were recorded with KBr pellets on Shimadzu IR-8900 spectrophotometer (Shimadzu Kyoto Japan) Thermal Analysis: The experiments were performed using a Seiko-Extar-TG/DTA-6300 (Seiko- Japan). The tests were conducted between C under an inert atmosphere (argon). The heating rate and the air flow rate were 10 C/min and 200mL/min Scanning Electron Microscopy and Energy Disperse X-ray Analysis: Scanning electron microscopy (SEM) and Energy disperse x-ray analysis (EDX) were performed using a scanning electron microscope (FEI Quanta Inspect, Model: S50, Kyoto Japan) to observe the micro structure, the surface morphology and elemental analysis of the treated as well as untreated fibres. The fibre surface was coated with thin film of carbon to render it conductive (Hunt and James, 1997). 3. RESULTS AND DISCUSSION The percent graft yield was increased with an increase of silane concentration upto 600% for VTMS and 500% for VTES on the basis of fibre. This happened due to the higher cross-linking reaction between the cellulosic OH group and OH group of the silanol at higher concentration. The rate of conversion of VTMS and VTES containing methoxy and ethoxy group into reactive hydroxyl group by hydrolysis of silane is directly 156

166 related to the ethanol/water ratio, ph value and reaction temperature. At 60:40 ratio of ethanol/water, the maximum amount of silane coupling agents is hydrolyzed because silane is insoluble in water. The formation of silanol was enhanced by the protonation of alkoxy ( OCH 3 and OCH 2 CH 3 ) groups in acidic ph value, which was 3.5 and 4 for VTMS and VTES respectively. At ph value lower than 3.5, the formation of silanol group was insufficient (Brinker, 1988). Temperature is an important parameter for this reaction mechanism because it decreased the activation energy of the reactant and molecular collision between the reactant molecules. The graft yield increased with the increase of reaction temperature upto 35 o C and 40 C for VTMS and VTES respectively (Mondal, 2013). 3.1 FTIR Studies for the Confirmation of Modified Fibre The FTIR spectra of raw, VTMS and VTES modified cotton fibres are shown in Fig. 1(a-c) respectively. The spectra of the modified cotton fibre are more or less similar to the raw cotton fibre, except the peaks at 761 cm -1 and 1280 cm -1 for Si-O-Si symmetry stretch and Si-O-C bond for VTMS modified cotton fibres and at 899 cm -1 and 1280 cm -1 for Si-CH 2 (Rangel-Vazquez and Leal- Garcia, 2010) and at 761 cm -1 for Si-C-H bond for VTES modified fibres, confirming the presence of silicon containing species on the modified cellulosic fibre. Fig. 2: SEM of raw cotton fibre. Fig. 3: SEM of VTMS modified cotton fibre. Fig. 2, 3 and 4 show the SEM micrograph of unmodified, VTMS modified and VTES modified cotton fibres respectively. The untreated cotton fibre shows the presence of the large amount of micro pores on its surface. After VTMS and VTES treatment, the cotton fibre surfaces are coated with an outer layer of silane monomer (Rashidi et al, 2004) which is represented in Fig. 3 and Fig. 4. The rupture surface of the modified fibre indicates the excess deposition of the silane layer on the fibre hair present in the cotton fibre. Fig. 1: FT-IR spectra of (a) raw cotton, (b) VTMS treated and (c) VTES treated cotton fibres. 3.2 Surface Morphology 157 Fig. 4: SEM of VTES modified cotton fibre 3.3 Elementary Analysis

167 Fig. 5, 6 and 7 represent the EDX analysis of raw cotton, VTMS treated cotton and VTES treated cotton fibres. From EDX analysis, it can be observed that the raw cotton fibre has no silicon atom but after modification with VTMS and VTES, the presence of Si atom has been observed. This result confirms the incorporation of silane monomer on the surface of modified cotton fibre. Fig. 6: EDX of VTMS modified cotton fibre. Fig. 7: EDX of VTES modified cotton fibre. Fig. 5: EDX of washed cotton fibre. 3.4 Thermal Analysis Thermal behaviour of raw, VTMS and VTES modified cotton fibres was examined by a study of TGA thermogram. Each of the figures represents two thermogram curves namely TGA and DTG. From Fig. 8, 9 and 10, it can be seen that the loss in weight is around 69.3% at C for raw cotton, and 39.5% at 386 o C for VTMS modified cotton and 55.7% at 384 o C for VTES modified cotton, respectively. From the DTG curve, it is found that the rate of decomposition of raw cotton fibre is higher than that of VTMS and VTES modified cotton fibres. Thus, the thermal stability of VTMS and VTES modified fibres is higher than that of unmodified fibres, which may have happened due to the incorporation of silane coupling agents with the cellulosic fibres. Fig. 8: TGA and DTG of raw cotton fibre Fig. 9: TGA and DTG of VTMS modified cotton fibre 158

168 4. CONCLUSION Fig. 10: TGA and DTG of VTES modified cotton fibre Physical Properties of Raw and Silane Modified Cotton Fibres Table 1 shows the swelling behaviour of raw cotton as well as VTMS and VTES modified cotton fibres both for polar and nonpolar solvents. Swelling ability reflects the relationship between void structures in backbone polymer and size of solvents molecule (Singha et al., 2008 and Singha and Thakur, 2009). The raw cotton fibres exhibit maximum swelling with polar solvents like water and methanol and least swelling with nonpolar solvents like CCI 4. After treating with silane coupling agents, there is a decrease in the swelling in the polar solvents whereas it increases in the nonpolar solvent because of decreasing the hydrophilic character of raw cotton fibre. The tensile strength of modified cotton fibre was higher than that of raw cotton fibre and these are due to the modification of cotton fibre with VTMS and VTES (ISO (E)). The wrinkle recovery angle of modified cotton fabric was higher than that of unmodified cotton fabric for warp and weft direction respectively. Because, the presence of Si- O bond in the functionalized fabric shows high flexibility that recover the winkle which exerted on the fabric surface by loading (Abidi et al., 2007). The moisture absorption sites are blocked after incorporation of silane chain through surface modification by showing less affinity for moisture than the original fibre. Table 1. Swelling behaviuor, tensile strength, wrinkle recovery angle and moisture absorption properties of raw and modified cotton fibres Fibre type Swelling behaviour % H2O CH3OH CCl4 Breaking load, Kg/yarn Tensile strength Tenacity, Elongation g/count % Wrinkle recovery angle, degree For warp for weft Moisture absorption % Raw cotton VTMS modified cotton VTES modifed cotton In this work, we have presented the chemical modification of cotton fibres with silane coupling agents. Maximum weight gain percent is obtained at optimum value of the reaction parameters such as silane concentration, ph, ethanol-water ratio and temperature. The chemical attachment between silanol and hydroxyl group of cotton fibres was evaluated by FTIR and EDAX analyses. The modified fibres showed improved physicochemical properties such as tensile properties, moisture absorption, elongation, wrinkle recovery and thermal stability properties compared to the unmodified cotton fibres. This new type of cotton was obtained through modification with silane coupling agents which enhance the application of garment products, textiles etc. REFERENCES 1. Mohanty, A. K., Wibowo, A., Misra, M. A. and Drzal, L. T. (2004), Effect of process engineering on the performance of natural fiber reinforced cellulose acetate biocomposites. Composites Part A, 35, pp Van voorn, B., smit H. H. G., Sinke, R. J. and de klerk B. (2001), Natural fibre reinforced sheet moulding compound, Composites Part A: Applied Science and Manufacturing, 32, pp Rachini, A., Troedec, M. L., Peyratout, C. and Smith, A. (2012), Chemical modification of Hemp Fibres by silane coupling Agents. Journal of Applied polymer science, 123, pp Singha, A. S. and Rana, A. K. (2012), Effect of Silane Treatment on Physicochemical properties of Lignocellulosic C. indica Fibre, Journal of Applied Polymer science. 124, pp Singha, A. S. and Thakur, V. K. (2009a), Synthesis and characterization of silane treated grewiaoptiva fibres, International Journal of Polymer Analysis and Characterization, 14, pp Gerald L. and Witucki, A. (1993), Silane Primer: Chemistry and application of alkoxysilanes, Journal of Coatings Technology, 65, pp Hunt, B.J. and James, M. I. (1997), Polymer Characterization (1 st edition), Blackie Academic and Professional, London 8. Brinker, C. J. (1988), Hydrolysis and condensa-tion of silicates: Effects on structure, Journal of Non- Crystalline Solids, 100, pp Mondal, I. H. (2013), Grafting of Methyl Acrylate and Methyl methacrylate onto jute fibre: physicchemical characteristics of the grafted jute, Journal of Engineered Fibres and Fabrics, 8(3), pp Rangel-Vazquez N. A. and Leal-Garcia, T. (2010), Spectroscopy Analysis of Chemical Modification 159

169 of Cellulose Febres, Journal of Mexican Chemical Society, 54(4), pp Rashidi, A., Moussavipourgharbi H. and Mirjalili, M. (2004), Effect of low-temperature plasma treatment modification of cotton and polyester fabrics, Indian Journal of Fibre & Textile Research, 29, pp Singha, A. S., Shama, A. and Thakur, V. K. (2008), Pressure Induced Graft Co-polymerization of Acrylonitrile onto Saccharumcilliare Fibre and Evaluation of some Properties of Grafted Fibres, Journal Bulletin of Material Science,31(1), pp Singha, A. S., and Thakur, V. K. (2009b), Morphological, Thermal and Physico-chemical Characterizations of Surface Modified Pinus Fibres, International Journal of Polymer and Analysis and Characterization, 14(3), pp International Standard ISO (E). Textilewoven fabrics. Determination of breaking strength and elongation (Strip Method). International Organization for Standardization, Switzerland, Abidi, N., Hequet E., and Tarimala, S. (2007), Functionalization of cotton fabric with vinyltrimethoxysilane, Textile Research Journal, 77, pp

170 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh LOW COST CARBOXYMETHYL CELLULOSE PREPARATION FROM AGRO WASTE ON THE BASIS OF PARTICLE SIZE Md. Saifur Rahman, Md. Abu Sayeed and Md. Ibrahim H. Mondal* Polymer and Textile Research Lab, Department of Applied Chemistry and Chemical Engineering, Rajshahi University, Rajshahi 6205, Bangladesh This study explores the feasibility of higher degree of substitution (DS) via one step carboxymethylation in lieu of multisteps carboxymethylation of -cellulose employing size reduction method. The extracted α- cellulose from corn leaves of different particle sizes were converted to carboxymethyl cellulose (CMC) by etherification process using sodium hydroxide and monochloroacetic acid (MCA) with alcohol as medium under heterogeneous condition. The DS of synthesized CMC was increased with decrease of α-cellulose particle size and the maximum DS obtained was 2.39 in case of α-cellulose particle size of 74 µm while the minimum DS obtained was 0.21 from particle size of 1071 µm. Yield, molecular weight and solubility of the obtained product increased with the decrease of particle size. The synthesized CMC was identified by FTIR and the surface morphology were analyzed by SEM. The best result of etherification was obtained at reduced α-cellulose particle size of 74 µm and the obtained product yield was %. Overall, this process may help to manage the huge amount of agro waste as well as mitigate environmental woes. 1. INTRODUCTION Corn is one of the most important and abundant cereal crops that are grown widely throughout the world and recently in Bangladesh. Approximately 1,850,656 MTPY corn is grown in Bangladesh (Uddin et. al., 2013). For every 1 kg of dry corn produce, about 0.15 kg of cobs, 0.22 kg of leaves and 0.50 kg of stalks are obtained (Sokhansanj, et. al., 2010). Most of these agricultural wastes are composed of cellulose in the plant cell walls. Cellulose is a linear and high molecular weight polymer that neither melts nor dissolves readily in water and most common organic solvents, making it less useful in most industrial purposes. As cellulose is susceptible to chemical derivatization reactions, it can be converted to useful chemical feedstock (Barkalow and Young, 1985). Cellulose carboxymethylation is a versatile transformation which gives us a versatile water swellable or water soluble polymers and intermediates with various valuable features (Klemm et. al., 2005, Heinze and Koschella, 2005, Feddersen and Thorp, 1993, Sandford and Baird, 1983). CMC is produced by aqueous alkali swollen cellulose reaction with monochloroacetic acid in surplus of alcohol (Alam and Mondal, 2013). * Corresponding Author: Md. Ibrahim H. Mondal, mihmondal@yahoo.com CMC garnered ample scientific attention, especially due to its polyelectrolyte character and it is the most widely used cellulose ether today with applications in the detergent, food exploration, paper, textile, pharmaceutical and paint industries (Methacanon et. al., 2003). Many researchers have investigated the synthesis of CMC from different cellulosic sources, such as paper sludge (He et. al., 2009), hyacinth (Barai et. al., 1997), wood residue (Egbuchunam and Okicimen, 2003), cotton linters (Nagieb et. al., 2001), bagasse (Rose et. al., 2007) etc. Heinze and Pfeiffer (Heinze and Pfeiffer, 1999) reported that Common CMC with DS in the range of 0.5 to 1.5 has been the subject of several review papers. The properties of cellulose derivatives are mainly signified by the DS and the maximum DS is 3 (Salmi, et. al., 1994). To gain higher DS through carboxymethylation process, researchers have implemented solvent system, concentration of alkali, MCA, temperature, duration of reaction and the steps of carboxymethylation (Khullar et. al., 2005). However, literature confirmed the absence of published reports on higher DS that is achieved via single step carboxymethylation rather than multistep carboxymethylation. Herein, this study was attempted to explore the accomplishment of higher DS via single step carboxymethylation instead of multistep carboxymethylation by applying size reduction technique of starting material. Furthermore, the

171 conversion of corn waste will not only produce useful value added products, but will also minimize environmental pollution. 2. METHODOLOGY Fresh and mature corn leaves, a cellulosic waste of corn plants were collected from Regional Wheat Research Institute (RWRI), Rajshahi, Bangladesh. Monochloroacetic acid (BDH, England), sodium hydroxide (BDH, England), hydrochloric acid (BDH, England), glacial acetic acid (BDH, England), ammonium oxalate (Merck, Germany), sulfuric acid (Merck, Germany) etc. with corresponding purity. The others chemicals, such as solvents and inorganic salts were reagent grade and used without further purification. 2.1 Preparation of sample The collected corn waste i.e. leaves were sorted manually to remove defective leaves and foreign materials and then cut into small pieces, dried in sunlight for several consecutive days to reduce moisture. To sum up, leaves were dried at 105ºC for 6h by Forced Convection Oven (FC-610, Toyo Seisakusho Co., Ltd.) and pulverized into powder using a disk mill (FFC-15). Afterwards, the powdered sample was separated into different particle sizes (i.e. 74, 100, 149, 340 and 1071 µm, respectively) by using a USDA Standard Testing Sieve (The W.S Tyler Company Mentor, Ohio 44060, USA) and stored in desiccator for later use. 2.2 Isolation of α-cellulose A suitable amount of powdered husk sample was treated with 18% NaOH solution for 2 h with occasional stirring in a solid to liquor ratio of 1:100 at room temperature. After filtration, the cellulose residue was washed thoroughly with 2% acetic acid and then with hot distilled water. The cellulose was stirred with n-hexane for 1 h at room temperature followed by washing with 95% ethanol. The cellulose thus obtained was heated with 0.7% NaClO 2 solution in the solid to liquor ratio of 1:50 at ph 4, and at 90-95ºC for 90 min. It was then treated with 0.2% sodium meta bisulphite solution for 15 min, filtered, washed thoroughly with distilled water, and finally dried at 60ºC (Mondal and Haque, 2007). 2.3 Carboxymethylation of α-cellulose In alkalization pretreatment, α-cellulose was suspended in alcohol and 30% NaOH (w/v) was added over a period a time 30 min under vigorous stirring at room temperature, and continued for another 60 min. Following this, 120% MCA was added slowly to the slurry for 30 min with stirring, and placed in a water bath at 55ºC for 3.5 h. The product thus obtained was then filtered and washed several times with alcohol/h 2 O (70/30 w/v) to remove undesired by-products and then dried at 60 C. General mechanism comes by production of CMC from α-cellulose of corn leaves which required two consecutive steps of reactions (Xiaojia et. al., 2003, Bono et. al., 2009). The summarized basification (a) and etherification (b) reactions are given below: [C 6 H 7 O 2 (OH) 3 ]n + nnaoh [C 6 H 7 O 2 (OH) 2 ONa]n + nh 2 O (a) [C 6 H 7 O 2 (OH) 2 ONa]n + nclch 2 COONa [C 6 H 7 O 2 (OH) 2 OCH 2 COONa]n + nnacl (b) 2.4 Determination of yield of CMC Yield of CMC was measured based on dry weight basis. The dry weight of the obtained CMC was divided by the weight of α-cellulose to get the yield value [Bono et, al., 2009]. W CMC yield, 100, W 0 where, W and W 0 is weight of oven dried CMC (g) and oven dried α-cellulose (g), respectively 2.5 Determination of degree of substitution To determine the degree of substitution (DS), a suitable amount of dried CMC was ashed gently between 450 and 550 C for 24 h, and then dissolved in 100 ml of distilled water. 20 ml of this solution were titrated with 0.1 N sulphuric acid using methyl red as indicator. The DS was calculated (Veronica et. al., 2006) as,. 2 Degree of Substitution (DS),. b where, ; b is the volume (in ml) of 0.1 N sulphuric acid and G is the mass of pure CMC in grams. 2.6 Determination of molecular weight CMC was dissolved in 0.78M NaOH solution and the molecular weight was determined by using Ostwald viscometer. From the intrinsic viscosity, the molecular weight of the CMC was calculated by the Mark-Houwink -Sakurada equation (Brandrup et. al., 1998) as, [ ] = K M a, Where, K, a, [ ] and M are constant for solvent, polymer shape factor, intrinsic viscosity and molecular weight of CMC, respectively. 2.7 Structural and morphological analysis FTIR spectra of cellulose from corn leaves and synthesized CMC were recorded in solid state by using KBr pellet method using a FTIR spectrophotometer (Model: FTIR-8900, Shimadju, Japan) between 400 and 4000 cm -1. The dried

172 samples were examined using a Scanning Electron Microscope (SEM) (Model-S 3400 N, VP SEM, Hitachi, Japan) using 20 (kv) accelerating voltage. The surfaces of the samples were sputter coated with gold for 3 min. 3. RESULTS AND DISCUSSION CMC was synthesized using the described method from the extracted α-cellulose at different particle size and the correlation among α-cellulose, DS, % yield and also the solubility of the obtained product is listed in Table 1. It can be seen from Table 1 that the DS and yield of the prepared CMC enhance gradually with the reduced particle of α-cellulose and the highest yield obtained was % with DS 2.39 in case of α-cellulose particle size, 74 µm. Reduced α-cellulose particle provides a greater surface area which increases the chance of collisions between reactant and α-cellulose, so the reaction rate increases as well increasing the yield and DS of CMC. Increasing DS means that each anhydroglucose unit constituent react with carboxymethyl, the weight of the produced carboxymethyl cellulose also increased. In addition, solubility of the prepared CMCs was tested in water (polar solvent) and it was found that CMC with DS 0.21 and 0.38 were insoluble in water. On the other hand, CMC having DS 1.52, 2.21 and 2.39, respectively exhibited high solubility in water. CMC with DS below 0.40 is insoluble whereas above this value CMC is completely soluble, as its hydro affinity increases with the increase of DS (Varshney et. al., 2006). The present study represents the similar results. Table 1. Determination of DS in CMC synthesized from corn leaves α-cellulose at different particle size Particle size, µm DS Yield of CMC, % Solubility Insoluble in water Insoluble in water Highly soluble in water Highly soluble in water Highly soluble in water From Table 2 it can be observed that the DS, intrinsic viscosity and molecular weight of the prepared CMCs increase gradually with the decrease of α-cellulose particle size. The etherification mainly depends upon the accessibility of reactants and the availability of the activated hydroxyl groups (Alam and Mondal, 2013). When particle size decreases, surface area as well as number of available free OH groups for substitution reaction increases, thus DS increases. Reduction in particle size of α-cellulose could enhance the affinity between cellulose particles and reactants and thus increases the etherification rate as well as the carboxymethyl substitution rate (Yeh et. al., 2010). As the DS increased, the numbers of OH groups were replaced by carboxymethyl groups. As the carboxymethyl group is heavier than OH group, the molecular weight of the final product CMC increases (Alam and Mondal, 2013). Thus there is a significant correlation between intrinsic viscosity and DS, intrinsic viscosity increased gradually with the increase of DS. The effect of DS on viscosity was due to the more carboxymethyl groups substituted by the hydroxyl groups of the α-cellulose molecules. Table 2. Determination of molecular weight of the synthesized CMC calculated by the Mark- Houwink-Sakurada equation as a function of particle size (Value of k = dl/g and a = 0.61 at 35ºC) Particle size, µm DS Intrinsic viscosity, [η] Molecular weight Structural characterization Characterization of the extracted α-cellulose and synthesized CMCs were performed by FTIR spectroscopy. There is a significant difference in the FTIR spectra of virgin corn leaves and extracted α-cellulose from corn leaves are depicted in Fig. 1 (A) and (B), respectively. The peaks in wave number at 1740, 1638, 1605 and 1514 cm -1 were not observed in the extracted α-cellulose of corn leaves. In addition, the peak at 1514 cm -1 is not present, and on the other hand, the absorption peak at 1249 cm -1 is drastically reduced as seen on the spectra of the extracted α-cellulose. These two absorption peaks were important since their absence in the α-cellulose spectra strongly indicates that most of the lignin was removed (Kondo, 1997, Ivanova et. al., 1989). From the spectra of all CMCs with various DS, the strongest absorbances were observed at 1620, 1423 and 1061 cm -1 (arrow) which indicated the presence of carboxymethyl substituent at COO -, -CH 2 and - O- groups of synthesized CMC respectively. The IR spectra of the standard CMC procured from the 163

173 % T % T market are also recorded in Fig. 2 (A). The spectra of A 4. CONCLUSION α-cellulose at different particle size were converted to CMCs successfully and the higher DS was obtained B Wavelength (cm -1 ) Fig. 1: FTIR spectra of A) virgin corn leaves and B) extracted α-cellulose Fig. 3: The surface morphology of α-cellulose F E D C B Fig. 4: The surface morphology of CMC Wavelength (cm -1 ) Fig. 2: FTIR spectra of Standard and prepared CMC with different DS, (A) Standard CMC (DS=0.8), (B) CMC with DS 2.39, (C) CMC with DS 2.21, (D) CMC with DS 1.52, (E) CMC with DS 0.38, and (F) CMC with DS the synthesized CMC with higher DS shows distinctly higher intensity than in the spectra of the CMC with comparatively lower DS including commercial CMC in Fig. 2 (Helene et. al., 2013). Morphological analysis The surface morphologies of extracted α-cellulose and synthesized CMC with DS 2.39 are shown in Fig. 3 and 4, respectively. Fig. 4 illustrates that the obtained products are rod like (or ribbon shaped) which is similar to other reported images for a typical CMC molecule (Ahemen et. al., 2013). The surfaces of α-cellulose are smoother with very minimal damage whereas the prepared CMC surface is more intended, rough and collapsed (Rachtanapun et. al., 2012). This is because alkali treated α-cellulose was further treated with strong alkali during carboxymethylation results the ruptured surface of obtained CMC (Donald et. al., 2001). A 400 in case of reduced α-cellulose particle size. Production of CMC by size reduction technique of α-cellulose has a significant impact on gaining higher DS via single step carboxymethylation rather than multistep carboxymethylation. So this study as well as this size reduction method may be considered as new dimension in preparing good quality CMC with distinct DS which will be economically feasible. In situ, the conversion of agro waste will not only produce value added product but also play a vital role to manage agro waste as well environmental pollution. REFERENCES 1. Ahemen, I., Meludu, O. and Odoh, E. (2013), Effect of Sodium Carboxymethyl Cellulose Concentration on the Photophysical Properties of Zinc Sulfide Nanoparticles British Journal of Applied Science & Technology, 3, pp Alam, A. B. M. F. and Mondal, M. I. H. (2013), Utilization of cellulosic wastes in textile and garment industries. i. synthesis and grafting characterization of carboxymethyl cellulose from knitted rag, Journal of Applied Polymer Science, 128, pp Barai, B. K., Singhal, R. S. and Kulkarni, P. R. (1997), Optimization of a process for preparing carboxymethyl cellulose from water hyacinth (Eichornia crassipes) Carbohydrate Polymers, 32, pp Barba, C., Montane, D., Rinaudo, M. and Farriol, X. (2002), Synthesis and characterization of carboxymethyl cellulose (CMC) from non-wood 164

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176 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh A SYSTEMS ENGINEERING APPROACH FOR AUTOMATED IRRIGATION Jannatun Nahar*, Jinfeng Liu and Sirish L. Shah Department of Chemical and Materials Engineering, University of Alberta, Edmonton, Alberta, Canada T6G 2V4 Irrigation system can be automated from two perspectives; one is the automation of water distribution system in irrigation and second one is the automation of a decision support system that can optimize the amount of water required for irrigation. The ultimate goal of this study is to develop a decision support system for irrigation. However in this work the objective is to use a model replicating water movement through the agricultural land to develop a state estimator using an extended Kalman filter (EKF). The state of this system is the pressure head of water in the soil at different depths and at different times so that the determination of these unknown states would enable us to calculate the soil moisture present in the soil as a function of time and space. Since the soil matrix is highly heterogeneous, therefore it limits the use of literature values for soil parameters. This requires the use of parameter and initial state estimation algorithm before starting the state estimation which is then performed using prediction error method. The results of parameter estimation indicate that the soil parameters are time varying and therefore require frequent updates. The use of bias update or feed-back information with the extended Kalman filter enabled a better estimation of the states although some errors were noted in the bottom soil layers. 1. INTRODUCTION Most agricultural practitioners refer to automated irrigation as a system with open loop configuration, where the water distribution is done with automated equipment comprising timer and volume controlling metering valves which are set according to the decision of the operator or the farmer. Therefore, the conventional concept of automated irrigation dwells on automation of irrigation water distribution (Mareels et. al., 2005), rather than emphasising on the concept of feedback and distributing only a required amount of water as needed for irrigation. This may reduce the distributional water loss but due to lack of feedback information from the soil conditions the amount of water allocated and used for irrigation remains far away from the optimum values. On the other hand, closed-loop automated irrigation includes decision support system within the irrigation controller to determine the amount and timing rather than the operator or the farmer; decisions are made on the basis of data acquired by sensors and control algorithms that may take crop characteristics into account. This study considers a feedback option which will take into account measured data such as soil water content, precipitation, temperature and combine this with an agro-hydrological model to estimate other unknown states of the agricultural system. The unknown states of this agro-hydrological system are the water pressure heads at different depths, which in terms gives us the knowledge of moisture content at different depths inside soil matrix. Due to the high heterogeneity of the soil matrix, various parameters of the soil are required to be estimated as a part of model development. An ensemble Kalman filter based soil moisture estimation approach was proposed by De Lannoy et. al., 2007, where the ensemble Kalman filter is being applied using CLM2.0 model (Community Land Model). In their study the parameters of the model were obtained from a multi-objective calibration technique including an optimal initial state estimation. The effects of assimilation depth and frequency on the soil moisture measurements were studied and it was concluded that the optimal assimilation frequency was 1-2 weeks. The bias estimation was only performed in the measurement nodes which improved the overall results. In another study by Bouletet. al., 2002 an extended Kalman filter was used along with cost function minimization to perform soil parameter estimation. This method considers the uncertainties associated with catchment hydrological behavior; however it was found that the results do not differ much from the case where the minimization routine was performed with no moisture correction. Therefore a * Corresponding Author: J. Nahar, jnahar@ualberta.ca

177 progressive parameter technique or adaptive filtering was suggested. The ensemble Kalman filter is associated with higher amount of computational complexity but its advantage is that it can deal with systems that have numerous states, whereas the extended Kalman filter has lesser complexity but fails in systems with large number of variables. Since irrigation application mainly involves soil in the top surface horizons, the number of states under consideration is not large. Therefore an extended Kalman filter with lesser computational complexity is explored in this study where the parameters of the system are determined using a prediction error method (pem), a nonlinear parameter estimation technique. The parameter estimation technique was performed in open-loop configuration and the errors were analyzed in section 3. The design and performance of extended Kalman filter is discussed in section 4 followed by concluding remarks. (2.2) where, hydraulic capacity, and subscript stands for depth inside soil or different nodes and superscript stands for time or each simulation step. Superscript κ stands for denoting implicit or explicit case. For explicit case it can be taken as zero. Considering the matric potentials ( ) as the states of this system and denoting them with from here onwards equation (2.3) can be developed. ; 2. SYSTEM MODELING The system for this study is mainly comprised of the soil-water matrix at the earth s surface. The inputs and outputs considered in this system are the water flow by the means of rain, drainage and root water extraction by plants. Since our primary focus is determining precise irrigation not only by using an agro-hydrological model but also by means of feedback control, so consideration of other hydrological phenomena such as macroscopic flow of water inside soil, effects of nutrients on long term water flow are not considered thereby keeping the system in a simple form. The governing equation that defines this system is Richard s equation which is developed from the basics of Darcy s law and equation of continuity and is shown in equation (2.1). Details on the development of Richard s equation can be found in (Richards, 2004) (2.1) Here in equation (2.1), θ is the soil moisture content (cm/cm), is the hydraulic conductivity (cm/s), is the vertical distance inside soil matrix (cm), S a is soil water extraction rate by plant roots (cm 3 cm -3 d - 1 ), is the extraction rate by drain discharge in the saturated zone (d -1 ), is the exchange rate with macro pores (d -1 ) and is the matric potential (cm) also known as soil suction. Saturated soil has matric potential of 0 cm and unsaturated soil has matric potential of negative values. (2.3) In the above equation one has to determine states at j+1 instant (, and ) using values from j time steps. Here, and are calculated from previous steps at nodes, and. Thus the system equation is comprised of equations (2.3) and (2.4). (2.4) where, forms a sparse matrix. (2.5) Moisture content, θ is the output and is denoted by. Equations (2.3) and (2.4) can be rewritten in following form to give the nonlinear state space of the system. (2.6) (2.7) A is a N N matrix, X is a N 1 matrix, E is a N 1 matrix, Y is M 1 output matrix, D is a M N matrix and G is a N 1 matrix where, N is the number of states and M is the number of outputs and M<N. The discretized version of Richard s equation is developed by implicit backward, finite difference scheme with explicit linearization of hydraulic conductivities (Van Dam, 2008). 168

178 ; ; ; (2.8) The elemental values of D matrix depend on the relation of measurements depths and the depths of each state. Suppose if there are 4 measurements and 8 states or nodes from which nodes 1,3,5 and 8 correspond to the four measurement positions then D, a 4 8 matrix will have non-zero values only at positions D(1,1), D(2,3), D(3,5) and D(4,8), such that it picks the values from states that are associated only with corresponding measurement depths. 3. PARAMETER ESTIMATION AND MODEL VALIDATION 3.1 Soil parameters The parameters of this system include both soil and crop parameters, but initially for simplicity since we assumed bare soil fields the parameters under consideration are residual moisture content (θ res ), saturated moisture content (θ sat ), saturated hydraulic conductivity (K sat ), Mualem-vanGeuchten parameters of soil which include air entry pressure (h e), the measure of the pore-size distribution (η), shape parameter (l exp ) and the inverse of air entry suction,(α). All of these parameters are defined by soil class and since there is heterogeneity inside the soil matrix with respect to depth at a specific location so the value of these parameters varies for the same location at different depths. So knowing the type of soil may give us an idea of the values of these parameters from literature, but those are not adequate enough to be used in the model to get reliable results. Therefore a parameter estimation algorithm must be included as a part of the model development. 3.2 Parameter Estimation In section 3.1 it is already mentioned that at least 7 parameters are required to define the characteristics of soil matrix. So if there are L numbers of layers in the soil then 7 L parameters have to be estimated. The numerous parameters make parameter estimation a very complex issue. So instead of estimating all these parameters the emphasis is given to the most sensitive parameters. The study by (Mertens et. al., 2005) performed a detailed sensitivity analysis experimentally and concluded that saturated hydraulic conductivity (K sat ), saturated moisture content (θ sat ) and residual moisture content (θres) are the most sensitive parameters of the top soil. Therefore in our study parameter estimation was performed for these three parameters at different nodes. Equations (2.6) and (2.7) were used to develop a nonlinear grey box model, which was then used to develop a prediction error method to determine the unknown parameters. In the prediction error algorithm, once the model structure is chosen then an optimal predictor is constructed. This optimal predictor uses past input and output data to obtain predictions as a function of parameters. The difference between the actual and predicted data generates the prediction error, from which an objective function is formed. The parametric value for which this objective function is minimized will give the best estimation of model parameters (Huang and Kadali, 2008). Based on this principal, there exists a MATLAB built-in function pem that was used to estimate the parameters as well as initial states of the system. 3.3 Error analysis In this study the data used are daily soil moisture at depths 5, 20, 50 and 100 cm along with weather data at the St.Albert Weather Station (Alberta Agriculture and Rural Development, 2014) located north of Edmonton, Alberta, Canada. The soil moisture data from 16July, 2014 till 15August, 2014 were used for performing prediction error method to get the values of model parameters and initial states. Based on the model shown in equations (2.3) - (2.7) the estimated parameters and initial conditions were used to generate the outputs which are the soil moisture contents. Then the generated soil moisture data were compared with the actual data that were collected from the weather station and the errors were determined. The values of the estimated parameters and initial states are shown in Table 1 and the error calculated by comparing the simulation results with the actual data is shown in Fig. 1. Table 1. Estimated parameters and initial states Initial,,, states, cm/cm cm/cm cm/hr cm Node no e

179 Moisture content, cm/cm Moisture content, cm/cm Moisture content, cm/cm Moisture content, cm/cm error Fig. 1: Time trend of error between model output with estimated parameter and real data. The parameter estimation algorithm was run with 6 nodes but the error is interpreted only for the 4 nodes where the measurements are available. It was observed that the error is usually higher at the surface node, so increasing nodes at the top may help to get better estimation. But on the other hand this increases the number of parameter to be estimated thereby increasing the complexity of the problem. So it was suggested that the minimum number of nodes must be at least greater than the number of soil layer present in the location under study whereas the maximum number of nodes must be less than the minimum number plus a few more nodes. Fig. 1 also shows that the prediction error increases as time increases. This is expected because of the existence of model mismatch. So a frequent update of parameters is necessary. 4. STATE ESTIMATION 10 time,day percentage error nodes Design of the extended Kalman filter The state estimation was performed using an extended Kalman filter algorithm. The algorithm consists of two steps, one is the prediction step and the second is the update step. The basic idea of extended Kalman filter is to use the model to generate the outputs and then the predicted output is compared with the measurements and accordingly the estimates are updated. The main difference between the extended Kalman filter and the Kalman filter is that the extended Kalman filter can deal with nonlinear systems such as the one under study whereas the ordinary Kalman filter fails for these cases. Prediction step State estimate Covariance estimate Update step Measurement residual Residual covariance Kalman gain Update state Covariance estimate Where, State transition and observation matrices are defined to be the following Jacobians. 4.2 Simulation results Measurement node 1 ( -5cm depth) actual data estimated data Measurement node 2 ( -20cm depth) actual data estimated data Time steps, hour Time steps, hour 0.5 Measurement node 3 ( -50cm depth) 0.5 Measurement node 4 ( -100cm depth) actual data estimated data Time steps, hour Fig. 2: Simulation results for state estimation without bias correction actual data estimated data Time steps, hour

180 Moisture content, cm/cm Moisture content, cm/cm Moisture content, cm/cm Moisture content, cm/cm Measurement node 1 ( -5cm depth) actual data estimated data Time steps, hour Measurement node 2 ( -20cm depth) actual data estimated data Time steps, hour 0.5 Measurement node 3 ( -50cm depth) 0.5 Measurement node 4 ( -100cm depth) actual data estimated data Time steps, hour 0.3 actual data 0.25 estimated data Time steps, hour Fig. 3: Simulation results for state estimation with bias correction 0.35 The four subplots in Fig. 2 show the results for four measurement nodes. The x-axis of the figures shows the time steps where each time step represents one hour in real life. The dotted lines represent the hourly data collected from the St. Albert weather station starting from April 1, It is found that the data simulated by the extended Kalman filter tracks the actual change in the soil moisture for the first measurement node (-5cm) but some bias is observed on the rest of the measurement nodes. Considering the mean error between the actual and simulated data as the bias, another plot was generated which is shown in Fig. 3. After the bias corrections were being applied the performance of the extended Kalman filter was considered satisfactory. 5. CONCLUSIONS The use of extended Kalman filter for state estimation of soil matrix enables us to have the knowledge of moisture content at unknown depths, which may help us to accurately calculate the required amount of irrigation water. Although bias at measurement nodes can be easily considered in this estimation, establishing a bias estimating method at all depths is the challenge ahead. On the other hand, fusing feed-back information in the parameter estimation algorithm may help us to develop a regular parameter updating method which can capture the time varying nature of parameters. REFERENCES 1. AgroClimatic Information Service, Alberta Agriculture and Rural Development, Canada (accessed August 20, 2014) 2. Boulet, G., Kerr, Y., Chehbouni, A., &Kalma, J. D. (2002). Deriving catchment-scale water and energy balance parameters using data assimilation based on extended Kalman filtering. Hydrological sciences journal, 47(3), De Lannoy, G. J., Houser, P. R., Pauwels, V., &Verhoest, N. E. (2007). State and bias estimation for soil moisture profiles by an ensemble Kalman filter: Effect of assimilation depth and frequency. Water resources research, 43(6). 4. Huang, B., &Kadali, R. (2008). Dynamic modeling, predictive control and performance monitoring. Berlin: Springer. 5. Mareels, I., Weyer, E., Ooi, S. K., Cantoni, M., Li, Y., & Nair, G. (2005). Systems engineering for irrigation systems: Successes and challenges. Annual Reviews in Control, 29(2), Mertens, J., Madsen, H., Kristensen, M., Jacques, D., &Feyen, J. (2005). Sensitivity of soil parameters in unsaturated zone modelling and the relation between effective, laboratory and in situ estimates. Hydrological processes,19(8), Richards, L. A. (2004). Capillary conduction of liquids through porous mediums.journal of Applied Physics, 1(5), Van Dam, J. C., Groenendijk, P., Hendriks, R. F. A., & Jacobs, C. M. J. (2008). SWAP version 3.2: Theory description and user manual. Wageningen, The Netherlands: Alterra.. 9. Chui, C. K., & Chen, G. (1999). Kalman filtering. With real time applications. 171

181 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh NUTRITION VALUE ANALYSIS OF ARTIFICIALLY RIPENED BANANA (BARI-1 HYBRID BANANA, MUSA SPP.) A. H. M. Sazedur Rahman, Md. Nazibul Islam, Mollik Yousuf Imtiaz, Abdullah Faisal Pasha, Mehnaz Mursalat, Sabrina Shawreen Alam, Mohidus Samad Khan * Department of Chemical Engineering, Bangladesh University of Engineering and Technology (BUET). Dhaka-1000, Bangladesh. Fruit ripening is a natural process in which the fruit goes through various chemical changes and gradually becomes sweet, colored, soft and palatable. The fruit ripening process can be stimulated using various chemicals on fruits. A wide number of artificial fruit ripening agents are applied on fruits in order to accelerate the process of ripening. The available scientific information often reports the health and safety issues of direct or indirect consumption of the ripening agents. However, the effects of artificial ripening agents on the nutrition value of artificially ripened fruits, and their consequent effect on human health are less understood. The purpose of this study is to measure, analyze and compare the nutritional value of naturally and artificially ripened fruits. Bari-1 hybrid banana (Musa Spp.; local name: Sagar Kola) was chosen to carry out the experimental study. Natural and artificially ripened banana samples were collected from banana orchard and local market. Unripe green banana samples were also artificially ripened in the laboratory using artificial ripening agents, ethephon and kerosene. Different nutrition parameters, such as moisture content, total energy, vitamin C, vitamin B1 and vitamin B12 complex were assessed for the four kinds of banana samples. The assessed parameters of natural and chemically ripened fruits were compared and analyzed to identify any change in nutrition value and to determine the potential health hazards associated with them. 1. INTRODUCTION The natural process of fruit ripening can be viewed as a combination of physiological, biochemical and molecular processes (Bouzayen, Latche et al. 2010). It involves co-ordination of different metabolism with activation and deactivation of various genes leading to change in tissue (Singal, Kumud et al. 2012). The metabolism of fatty acids and branched amino acids serves as precursor of aroma volatile during fruit ripening process and induces olfactory stimulation (Bangerth, Song et al. 2012). Ethylene is the ripening agent that is naturally found within fruits. It induces ripening and is considered a growth regulating plant hormone (Theologis 1992, Chaves and Mello-Farias 2004, Cornelius S. Barry and Giovannoni 2007). It is reported that a wide number of artificial fruit ripening agents are applied on fruits in order to stimulate the process of ripening. Most of these chemicals go through processes that produce either ethylene or acetylene (Mursalat, Rony et al. 2013). In Bangladesh, ethephon is widely used to ripen fruits like banana, pineapple, etc (Hakim, Huq et al. 2012). To stimulate the ripening process, ethephon is sprayed on fruits. Other methods involve dipping fruits in the ethylene glycol solution (Mohamed- Nour and Abu-Goukh 2010), or using fume generated from calcium carbide. In recent days, fume from kerosene stove or lantern has been used to initiate ripening of different fruits artificially. Scientists have reported that it is the combustion product of kerosene that induces ripening (House, Nelson et al. 1929). The effect of these artificial ripening agents on the food nutritional value and human health has drawn national and global attention. However, limited scientific information is available on the nutrition value of artificially ripened fruits, and their consequent effect on human health. The methods applied on fruits in order to pace up the ripening process artificially, changes with time and demand. Therefore, it is important to conduct systematic scientific research to identify and analyze a) whether the artificial ripening agents change the nutritional values of the fruit, b) whether these artificial ripened fruits pose any threat to human health or to the surroundings, and c) if the answer of question b is yes, then the following question * Corresponding Author: Mohidus Samad Khan, mohid@buet.ac.bd

182 arises; to what extent the artificial ripened fruits are hazardous to human health. This article reports the first part a systematic study which aims to develop scientific understanding on the above issues. Alongside, it contains the change of nutrition values for naturally and artificially ripened fruits. In this study, Bari-1 hybrid banana samples were used. Natural and artificially ripened banana samples were collected from banana orchard and local market. Green banana samples were artificially ripened in the laboratory by ethephon and by using open lid kerosene lantern. Moisture content, total titratable acidity, vitamin C (ascorbic acid), vitamin B1 (thiamine), vitamin B6 (pyridoxine) and vitamin B12 (cobalamin) complex of the four types of banana samples were assessed and analyzed. This systematic approach of investigating artificial ripened fruits can also be used to analyze other fruit items. 2. MATERIALS AND METHODS The fruit samples used in the experiments were Musa Spp. (locally known as Sagor kola), a hybrid developed by BARI (Azam, Islam et al. 2010). Both green and ripe banana samples were collected from local wholesale market Sadarghat. Ripe banana samples were also collected from banana orchard. For experimentation, reagent grade hydrochloric acid and sulfuric acid from MERCK KGaA, Germany were used. To develop the calibration curves for vitamins B and C, standard reagents were collected from the Quality Control Laboratory, Renata Pharmaceutical Ltd. The ethephon used in the experiments was obtained from a local fertilizer shop from Bheramara, Kushtia district. Each test was repeated thrice (n=3) and the average results were used for further analysis. All tests were carried out at room temperature. 2.1 Ethephon treatment of Green Banana A dozen (n=12) of unripe green banana samples were treated with 50ml ethephon solution having a concentration of 300mg/liter. The treated banana samples were kept in a confined space for 24 hours. Later, they were exposed to open air (Fig. 1) Kerosene treatment Banana samples (n=8) were placed into an airtight container (50 liters). An open lid kerosene lantern was placed at the center of the container and was allowed to light until the oxygen inside was exhausted. The banana samples were kept in the container for 24 hours and then exposed to open air. 2.3 Determination of Moisture Content The moisture content was determined by oven dry method (E and K. 2011). Freshly cut banana samples were allowed to dry at 110 º C until a constant weight was observed. It took about four and a half hours for the samples to reach the constant weight. Weight readings of the banana samples were taken before and after drying; the weight difference denotes the amount of moisture in the samples. The moisture content is expressed in gram of moisture available per 100gram of fruit sample (g of moisture/100g of fruit sample) (Muhammad Shahnawaz, Sheikh et al.). 2.4 Determination of Total Titratable Acidity (TTA) Titrable acidity was measured by titrating the sample using standardized NaOH solution (Ho, Aziah et al. 2012). The banana sample was blended with water and boiled for 20 minutes. The boiled solution was centrifuged at 60 rpm for 5 minutes, and was titrated with standardized 0.1M NaOH solution using Phenolphthalein indicator. The result is expressed in g Acetic acid/100g of fruit stem (Ozgur and Koyuncu 2002). 2.6 Determination of Vitamins B Vitamin B contents were determined by spectrophotometric method (Ozgur and Koyuncu 2002). A Shimadzu UVVIS 2600 spectrophotometer was used in this experiment. Calibration curves (Fig. 2-4) were generated for each of the vitamins using standard reagents collected from the Quality Control Laboratory, Renata Pharmaceutical Ltd. The results are expressed in ppm. 2.7 Vitamin C Vitamin C (ascorbic acid) concentration was determined by redox titration using standardized Iodine solution (MUNIR, BALOCH et al. 2013). Vit-C standard reagents collected from the Quality Control Laboratory, Renanta pharmaceutical Ltd, was used to cross-check the strength of the iodine solution. In this experiment, starch solution was used as an indicator. The results obtained are expressed in ppm. (Control) fresh green banana after 48 hours Ethephon treated banana after 48 hours. Fig. 1: Ethepon treated artificially ripened banana 173

183 Absorbance Moisture Content (%) Absorbance Absorbance Fig. 2: Calibration curve for vitamin B1 at wave Length nm upto 100ppm Fig. 3: Calibration carve for vitamin B6 at wave length nm upto 100 ppm. 3 R² = Concentration (ppm) R² = Concentration (ppm) Table 1. Nutrition value of naturally and artificially ripened banana (Bari-1 hybrid banana; Musa Spp.). Naturally ripened banana Ripe banana collected from local market Artificially ripen banana: Ethephon treated Artificially ripen banana: Kerosene treated Parameters Moisture content (%) Total Titrable Acidity (g citric acid/ Fresh Weight) Vitamin C (ppm) Vitamin B1 (ppm) Vitamin B6 (ppm) Vitamin B12 (ppm) Fig.5 shows a comparison of the moisture contents of naturally and artificially ripened banana samples. The Moisture contents of the four kinds of banana samples ranged from 73% to 85%. The kerosene treated samples exhibited the lowest moisture content values; heat evolved while burning the kerosene and increased temperature may have contributed to the low moisture content (Shiva Kumar Modi, Prasad et al. 2013) y = x R² = Naturally ripened Banana Banana from local market Ethephon treated Banana Kerosene treated banana Concentration (ppm) Fig. 4: Calibration curve for vitamin B12 at wave length nm upto 100 ppm. 3. RESULTS AND DISCUSSION The moisture content, total titratble acidity, vitamin C, vitamin B1, vitamin B6 and vitamin B12 contents of naturally and artificially ripened banana samples are enlisted in Table 1. Fig. 5: Moisture contents of the naturally and artificially ripen banana samples. The comparison of the vitamin contents of different banana samples is presented in Fig.6. The vitamin contents (C, B1, B6, B12) of the artificially ripened banana samples were found lower than those of fresh banana samples; vitamins B6 and B12 were found higher for fresh banana samples (Fig. 6). The Recommended Dietary Allowance (RDA) of vitamin B1 is 1.2mg/day and 1.1mg/day for male and female respectively (Dickinson 2002). The vitamin B1 content exhibited by the banana samples ranged from 176.5mg/100g to 236.6mg/100g, which are well above the RDA 174

184 TTA (g citric acid/100 Fresh Weight) Vitamin Contents (ppm) values. The RDA for vitamin B6 and B12 are 25mg per day and 2.4µg respectively (2006). The vitamins B6 and B12 contents for all banana samples were found to be above the RDA values. There is no established report regarding the adverse effect of consuming excessive vitamin B1, B6 and B12 (Dickinson 2002) Fig. 6: Vitamin contents of the naturally and artificially ripen banana samples. Vitamin C is one of the vital nutritional contents of banana and the recommended dietary allowance (RDA) of vitamin C for an adult is mg of vitamin C per day (Dickinson 2002). The upper tolerance limit of vitamin C in human body is 2g per day (Dickinson 2002). The vitamin C content of the banana samples during the experiment was found to be higher than RDA value. However, among the samples, the kerosene treated ones contained lowest amount of vitamin C (17.5mg/100g). This can be attributed due to the heat evolved and lack of oxygen. According to ripening chemistry, vitamin C decreases with the increase of temperature(adeyemi and Oladiji 2009); vitamin C is also sensitive to oxygen present in the system (Hakim, Huq et al. 2012) Vit B1 (ppm) 0 Vit B6 (ppm) Vit B12 (ppm) Naturally ripened banana Banana from local market Ethephon treated Banana Kerosene treated banana Naturally ripened banana Banana from local market Ethephon treated Banana Vit C (ppm) Kerosene treated banana Fig. 7: Total titrable acids of the naturally and artificially ripen banana samples. Fig.7 graphically represents the experimental results of total titrable acidity (TTA) of naturally and artificially ripened banana samples. The total titratable acid level was found to be highest in the kerosene treated samples, while the level was lowest in the fresh samples. This implies that the fresh banana samples were less acidic. Researchers have reported that high TTA can cause dental erosion, especially among kids (Featherstone and Lussi 2006). Therefore, regular consumption of artificially ripened banana can be hazardous for dental health General Observation This experimental study did not come across the presence of any chemical contamination in banana samples introduced by artificial ripening agents. The experiments were carried out to analyze if there was any change of nutrition values in the artificially ripened banana samples. From the experimental results, it was found that the fresh banana samples contained relatively higher nutrition values and less acidity comparing to those of the artificially ripened banana samples. However, no significant pattern of change in vitamins and moisture contents value was found. In contrast, TTA value exhibited a trend, which is lower acidic value for the naturally ripened banana samples and higher acidic value for the artificially ripened banana samples. TTA was significantly low for naturally ripened banana samples collected from orchard, which could be used as marker to identify artificial ripened banana samples. 4. CONCLUSION The analysis of nutritional value and health effects of chemically adulterated foods is a dynamic process and in recent times the use of artificial agents for fruit ripening has become widespread, globally. However, the effects of artificial ripening on the fruit nutrition values have been less explored. This study assessed and compared different nutritional values and parameters of both naturally and artificially ripened banana samples. It cannot be deduced from the study that artificial fruit ripening agents lead to contamination of fruits. However, the possible health hazard associated with relentless and indiscriminate use of such agents cannot be ignored. The current study was an initiation to observe the changes in the basic nutritional parameters upon hindering the natural process of ripening by applying artificial agents. The parameters of the artificially ripened samples did vary from those of the naturally ripened ones. The change of vitamins and moisture contents did not show any substantial trend, however, the total titrable acidity values were found much lower for the naturally ripened bananas, which indicate rather 175

185 healthy conditions, especially for the kids. Nonetheless, this systematic approach of investigating artificial ripened fruits can be used to analyze other chemically adulterated food items as well. This calls for further research and study, which may involve varying the amount of artificial fruit ripening agents on fruits. The future work is likely to address the presence of any chemical contamination in the fruit samples introduced during the artificial ripening process. ACKNOWLEDGEMENT This research was supported by BCEF Academic Research Fund. The authors acknowledge Mr. R. Hasan and Mr. M.L.A. Mainuddin of Renata Pharmaceutical for the standard reagents for vitamins B1, B6, B12 and C. REFERENCES 1. (2006). Tolerable Upper intake levels for Vitamin and Minerals, European Food Safety Authority: Adeyemi and Oladiji (2009). "Compositional changes in banana (Musa ssp.) fruits during ripening." African Journal of Biotechnology 8(5): Azam, F. M. S., S. Islam, M. Rahmatullah and A. Zaman (2010). Clonal propagation of Banana (Musa spp.) 'Cultivar Bari-1' (AAA genome, Sapentium subgroup). International Conference on Banana and Plantain in Africa: Harnessing International Partnerships to Increase Research Impact. Mombasa, Kenya 4. Bangerth, F. K., J. Song and J. Streif (2012). "Physiological Impacts of Fruit Ripening and Storage Conditions on Aroma Volatile Formation in Apple and Strawberry Fruit: A Review." HortScience 47(1): Bouzayen, M., A. Latche, P. Nath and J. C. Pech (2010). Developmental Biology - Biotechnological Perspectives, Springer. 6. Chaves, A. L. S. and P. C. d. Mello-Farias (2004). "Ethylene and fruit ripening: From illumination gas to the control of gene expression, more than a century of discoveries." Genetics and Molecular Biology 29(3). 7. Cornelius S. Barry and J. J. Giovannoni (2007). "Ethylene and Fruit Ripening." Journal of Plant Growth Regulation 26: Dickinson, A. (2002). Recommended Intakes of Vitamins and Essential Minerals C. f. R. Nutrition. 9. E, A. and S.-A. L. K. (2011). ARPN Journal of Engineering and Applied Sciences 6(2): Featherstone, J. D. B. and A. Lussi (2006). Understanding the Chemistry of Dental Erosion. Dental erosion from diagnosis to thheory, Monographs in oral science. 20: Hakim, M. A., A. K. O. Huq, M. A. Alam, A. Khatib, B. K. Saha, K. M. F. Haque and I. S. M. Zaidul (2012). "Role of Health Hazardous Ethephone in Nutritive Values of Selected Pineapple, Banana and Tomato " Journal of Food, Agriculture & Environment 10(2): Ho, L. H., N. Aziah, A. A and R. Bhat (2012). "Mineral composition and pasting properties of banana pseudo-stem flour from Musa acuminata X balbisiana cv. Awak grown locally in Perak, Malaysia." International Food Research Journal 19(4): House, M. C., P. M. Nelson and E. S. Haber (1929). "NATURALLY RIPENED TOMATOES OF ARTIFICIALLY VERSUS THE VITAMIN A, B, AND C CONTENT." The Journal of Biological Chemistry 44(3): Mohamed-Nour, I. A. and A.-B. A. Abu-Goukh (2010). "Effect of ethrel in aqueous solution and ethylene released from ethrel on guava fruit ripening." Agriculture and Biology Journal of North America 1(3): Muhammad Shahnawaz, S. A. Sheikh and S. M. Nizamani "Determination of Nutritive Values of Jamun Fruit (Eugenia jambolana) Products." Pakistan Journal of Nutrition 8(8): MUNIR, M., A. K. BALOCH, W. A. KHAN, F. AHMAD and M. JAMIL (2013). "Development of Iodimetric Redox Method for Routine Estimation of Ascorbic Acid from Fresh Fruit and Vegetables " Journal of Chemical Society of Pakistan 35(3): Mursalat, M., A. H. Rony, A. H. M. S. Rahman, M. N. Islam and M. S. Khan (2013). "A Critical Analysis of Artificial Fruit Ripening: Scientific, Legislative and Socio-Economic Aspects." ChE Thoughts 3(1). 18. Ozgur, M. U. and I. Koyuncu (2002). "Determination of Ternary Mixtures of Vitamins (B1; B6, B12) by Zero-Crossing Derivative Spectrophotometry." Turkish Journal of Chemistry 26: Shiva Kumar Modi, B. D. Prasad and M. Basavaraj (2013). "The Influence of Moisture Content and Density on Thermal Conductivity of Ficus Carica Linnaus (Fig Fruit) by Transient Line Heat Source Method." International Journal of Engineering and Innovative Technology 3(6): Singal, S., M. Kumud and S. Thakral (2012). "Application of apple as ripening agent for banana " Indian Journal of Natural Products and Resources 3(1): Theologis, A. (1992). "One Rotten Apple Spoils the Whole Bushel: The Role of Ethylene in Fruit Ripening." Cell Press 70(2):

186 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh MATERIAL AND LEACHING CHARACTERIZATION OF MUNICIPAL SOLID WASTE INCINERATION (MSWI) ASHES: AN APPROACH TOWARD SUSTAINABLE WASTE MANAGEMENT Kazi Tasneem *, Boo Hyun Nam University of Central Florida, 4000 Central Florida Blvd, Orlando, FL 32816, U.S. Jongwan Eun University of Wisconsin-Madison, 1415 Engineering Dr., Madison, WI 53706, U.S. Incineration of municipal solid waste (MSW), as a means of volume reduction and energy recovery, and management of municipal solid waste incineration (MSWI) ashes have received a growing attention over the world. In the U.S., production of MSW has increased up to 65% since 1980, to the current level of 251 million tons per year with 53.8% landfilled, 34.5% recycled and composted, and 11.7% incinerated with energy recovery. In the process of incineration, MSWI ash is produced as byproduct; about 80 to 90% of the MSWI ash is bottom ash (BA) and 10 to 20% is fly ash (FA) by weight. Many European and Asian countries have utilized MSWI BA as beneficial construction materials in the areas of roadbed, asphalt paving, and concrete, by separating it from FA. The FA is mostly limited to landfill disposal as hazardous material due to its high content of toxic elements and salts. On the contrary, the current practice of the U.S. is to combine both BA and FA, and the combined ashes are disposed in landfills. This research work entails chemical and microstructural characterization of MSWI BA and FA produced from an incineration facility in Florida, U.S. The material characterization method includes Scanning Electron Microscopy (SEM), Energy Dispersive X- ray Spectroscopy (EDS), and X-ray Diffraction (XRD) techniques. In addition, leaching tests have been conducted on BA-mixed hot mix asphalt (HMA) and Portland cement concrete (PCC) to investigate the environmental properties (e.g. leachate concentration). The leaching results reveal the reduced leaching potential of toxic materials from MSWI ashes while being incorporated into HMA and PCC. Lastly, a preliminary experimental approach has been devised for the vitrification of FA which is a promising thermal process of transferring material into glassy state with higher physical and chemical integrity to reduce toxicity so that utilization of FA can also be possible. 1. INTRODUCTION As the volume of waste production in the U.S. has continued to raise, the management of municipal solid waste (MSW) adopts incineration technology that converts MSW into ash with 75% volume reduction and recovers energy. In the process of incineration, about 80 to 90% of the MSW by weight are bottom ash (BA) and 10 to 20% are fly ash (FA) (Chandler et al., 1997, Wiles and Shepherd, 1999, Lam et al., 2010). The total MSW generation in the U.S. has increased up to 65% since 1980, to the current level of 251 million tons per year with 53.8% landfilled, 34.5% recycled and composted, and 11.7% incinerated with energy recovery (U.S.EPA, 2012). The current practice of the U.S. is to combine municipal solid waste incineration (MSWI) BA and FA, and the combined ash is disposed in landfills. The zero recycling of MSWI ash may be due to the statewide inconsistency in ash management, regulations, and standard leaching test procedures (Wiles and Shepherd, 1999). In addition, concerns associated with highly soluble salt content and heavy metal concentration in MSWI ashes may further discourage its beneficial utilization (Hasselriis, 2012). On the contrary, many of the European and Asian countries have successfully implemented systematic approach towards the management and utilization of MSWI ashes with environmental criteria set by their strategic regulations (ISWA, 2006, ISWA, 2008, Vehlow, 2012). In European countries, by separating FA from MSWI ashes, BA has been actively recycled in the areas of roadbed, asphalt paving, and concrete products (ISWA, * Corresponding Author: Kazi Tasneem, ktasneem@knights.ucf.edu

187 2006). FA is mostly limited to landfill disposal as hazardous material due to its high content of toxic elements and salts (ISWA, 2008, Hasselriis, 2012). Leaching test procedures implemented by different counties have shown significant reduction of leachability of MSWI ashes when used in asphalt and cement mixtures. Stabilization by physical and chemical encapsulation can be the mechanism to explain the reduction of leachability (Chandler et al., 1997, Wiles and Shepherd, 1999, Lam et al., 2010). On the other hand, FA can be treated by vitrification technology which is a thermal process of transferring material into glassy state with higher physical and chemical integrity to reduce toxicity (Bernardo et al., 2012). In spite of successful recycling of BA with minimum environmental consequences, which have been shown by many studies in European and Asian countries, disposal of MSWI ashes has remained a common practice in the U.S. Therefore, efforts are required to identify the potential areas of MSWI ashes to be utilized; particularly replacement of cement and fine aggregate by BA in hot-mix asphalt (HMA) and Portland cement concrete (PCC). Evaluation of physical, mechanical and leaching properties associated with those applications is also essential to promote sustainable management of MSWI ashes. The objectives of this research are to: 1) provide a detailed chemical and microstructural characterization of MSWI BA and FA produced in Florida by using Scanning Electron Microscopy (SEM), Energy Dispersive X-ray Spectroscopy (EDS), X-ray Diffraction (XRD) analysis, and laboratory chemistry experiment; 2) to investigate the leachate concentration of BA and BA-mixed HMA and PCC by using Synthetic Precipitation Leaching Procedure (SPLP) batch tests; and 3) to conduct a preliminary study of the vitrification of FA for its feasible utilization and management with least possible environmental impact. 2. MATERIALS AND METHODS 2.1 Material and Chemical Characterization of BA and FA MSWI BA and FA, obtained from an incineration plant in Florida, U.S., were oven dried at 110 C for 2 h. The maximum particle sizes of the ashes were 50 mm and 0.1 mm for the BA and FA, respectively SEM, EDS, and XRD: The microstructure, morphology, and chemical composition of BA and FA specimens were characterized by using Zeiss Ultra-55 SEM Spectrometer with acceleration voltage of 5 to 20 kv, equipped with Ultra-Dry silicon drift EDS detector. Thin sections of sample were coated with Gold-Palladium using a sputter coater. For the mineralogical analysis, powdered BA and FA samples (90 μm) were subjected to XRD analysis using Rigaku X-ray diffractometer with CuKα radiation, 2θ scanning from 5 to 80º with 0.02º step size and dwell time of 1 second per step Chemistry Experimentation: A laboratory experiment was conducted to measure the hydrogen (H 2 ) gas evolution from BA and FA and to backcalculate the amount of metallic Al in BA and FA by using varied amount of BA and FA samples (with same particle size of 90 μm) in NaOH aqueous solution at different volume and concentration. 2.2 Leaching Characterization of BA BA-mixed HMA: BA with particle size smaller than 4.45 mm was used as 0, 10, 20, 30, and 40% of the fine aggregate replacement in 0.1-m diameter HMA specimen with 5.7% binder content based on Marshall Mix Design. Compacted BAmixed HMA specimens were then crushed to obtain sample size greater than 9.5 mm for SPLP tests BA-mixed PCC: 28 days air-cured concrete specimens ( mm 2 ) with water to cement ratio of 0.5, were casted with 10, 20, 30, and 50% of the fine aggregate replacement of BA with particle size passing 4.75 mm. Hardened concrete specimens were crushed to obtain particle sizes ranging from 20 to 40 mm which were subjected to SPLP test SPLP Test: SPLP batch tests were conducted to assess the leaching behavior of the BA in HMA and PCC when exposed to stormwater infiltration. Extraction fluid was prepared by mixing sulfuric and nitric acid to obtain solution with a ph of 4.2. Leaching solution and samples at solid-to-liquid ratio of 1:20 were agitated in a rotary tumbler at 30 rpm for 24 hours. All SPLP extracts were then filtered and leaching tests were conducted in triplicate. Major alkaline elements and trace heavy metal concentrations in the eluates were determined with inductively coupled plasma optical emission spectrometry (ICP-OES). A total of ten elements, Al, Ca, Na, Si, and K (major alkaline elements) and Cu, Fe, Mg, Ti, and Zn (minor trace metals) were chosen to be evaluated in this study. 3. RESULTS AND DISCUSSIONS 3.1 Microstructure Analysis by SEM BA particles are mostly rounded, with no distinguishable crystal structures due to having 178

188 amorphous phase (Fig. 1); while FA exhibits planar, cylindrical, and spherical particles on sintered clusters with highly crystalline phase that is attributable to a lower workability of FA while mixing with cement. Compared to BA, higher porous structure in FA exhibits crystallinity and angularity with vesicles connecting to the exterior of the particles. Such vesicle porosity is believed to provide large surface area for chemical interaction which is attributed to the leaching characteristics of MSWI ashes (Chandler et al., 1997). a) bottom ash b) fly ash Fig. 1: SEM images of BA and FA at 2000x magnification. 3.2 Compositional Analysis by EDS Average chemical compositions of BA and FA are listed in Table 1. The EDS analysis shows that the major elements of BA are Ca, Si, Al, and Na and the minor elements are Mg, Fe, and Ti with small amount of K, Cl, and Zn. On the other hand, higher amount of Cl and Hg (highly volatile element) are observed in FA. Major elements of the FA are Cl, Ca, K, Na, and Hg and minor elements are Si, Al, Cu, and Co. FA appears to contain higher amount of soluble salts and toxic heavy metals compared to BA. 3.3 Mineralogy Analysis by XRD The X-ray diffraction patterns for BA and FA are presented in Fig. 2 and 3, respectively. The major minerals of BA are portlandite (Ca(OH) 2 ), silica (SiO 2 ), and calcite (CaCO 3 ), while the major phases in FA are halite (NaCl), sylvite (KCl) and calcium chloride hydroxide hydrate (CaCl 2.Ca(OH) 2.2H 2 O). Many other minor minerals were detected with low amounts due to the intrinsic heterogeneous characteristics of the MSWI ashes. The analysis of the XRD data shows good agreement with the findings from the EDS results. BA appears to have relatively stable chemical forms and strength building component (silica), whereas FA contains mostly highly soluble phases which are responsible for potential leaching. Table 1. Elemental composition of BA and FA (weight %) Element BA FA O Na Mg Al Si P S Cl K Ca Ti Cr Mn Fe Co Ni Cu Zn Hg Total Theta (degree) Fig. 2: X-ray diffraction pattern for MSWI BA CAH: [Ca 2 Al(OH) 7.5H 2 O] Ca(OH) 2 2. Ca(OH) 2 3. Quartz: SiO 2 4. CaCO 3 5. Jaffeite 6. C3A: Ca 3 Al 2 O Theta (degree) Fig. 3: X-ray diffraction pattern for MSWI FA CaCl 2.Ca(OH) 2.2H 2 O 2. CaSO 4 3. KCl 4. CaCO 3 5. NaCl 6. Al 2 O

189 Release Concentration (µg/l) Release Concentration (µg/l) 3.4 Hydrogen Gas Evolution Test H 2 gas generation is associated with the reuse of BA and FA in construction materials (Chandler et al., 1997, Vehlow, 2012), especially in cement paste and concrete due to the hydrolysis of metallic Al present in BA and FA (as confirmed by EDS), according to the following reaction (Hill et al., 2005): 2Al + 4OH - + 2H 2 O 2Al(OH) 3 + H 2. In order to back-calculate the relative amount of metallic Al in total Al content within MSWI ashes by measuring H 2 gas evolution, both BA and FA were treated with an excess amount of 1, 2 and 3 M NaOH solutions and reaction product of H 2 gas was collected in an inverted cylinder over water. The calculated Al contents in both ashes are found to be approximately 0.03% by weight, which is considerably small to appear in the XRD analyses (Fig. 2 and 3). This experiment shows evolution of H 2 gas even from significantly small amount of metallic Al which appears to present in MSWI BA and FA that eventually may lead to inferior mechanical performance of the ash-mixed concrete. 3.5 Leaching Behavior of BA and BA-mixed HMA and PCC During acidic leaching, release concentration of major elements (Ca, Al, Si, Na, and K) of BAmixed HMA increases with increasing BA content (Fig. 4). However, minor elements (Cu, Fe, Mg, Ti, and Zn) show different leaching behavior. Generally, minor elements are slightly reduced in lower contents of BA (e.g., 10 and 20% of BA) and then increase again in higher contents of BA (e.g., 30 and 40%). Significantly reduced leaching of heavy metals (except Zn) is observed for BA-mixed HMA as compared to BA alone (100% BA). Similar to HMA, leaching of most of the major elements (Al, Si, Na, and K) increases with increasing BA contents (Fig. 5). Significant reduction of the leaching of Al, Si, Na, and K are observed due to the incorporation of BA in PCC as compared to the BA alone. Generally, minor elements increase with increasing amount of BA. Unlike the case of the HMA, the PCC impede releasing the element from the BA in lesser extent. PCC itself contains Ca and Fe as integrated component in the strength building cement matrix (Hewlett, 1998); thus higher leaching of Ca and Fe from BA-mixed PCC has been observed as compared to the BA alone. 3.6 Comparison of Leaching with Standards Due to the lack of appropriate leaching criteria for the investigation of environmental risk of using BA in milled-hma and crushed-pcc applications, leaching concentration of priority elements were compared with the U.S. Drinking Water Standard, the Secondary Maximum Contamination Level (SMCLs) (U.S.EPA, 2009) and Multi-Sector General Permit (MSGP) for Stormwater Discharges (MSGP, 2008) (Table 2). In BA-mixed HMA and PCC, release of most of the toxic elements of interest (except Al) appears to meet the SMCLs for Drinking Water Standards. However, leaching of all of the priority elements (including Al) is observed to be well below the Stormwater Runoff Discharge Limit Fig. 4: Effect of BA contents for releasing major and minor elements from BA mixed HMA Bottom Ash Contents (%) Bottom Ash Contents (%) Fig. 5: Effect of BA contents for releasing major and minor elements from BA mixed PCC. Table 2. Leaching comparison with regulatory standards (µg/l) Element SMCL MSGP BA-mixed HMA BA-mixed PCC Cu Fe < Zn Al K Al Si Ca Na Cu Ti Zn Fe Mg K Al Si Ca Na Cu Ti Zn Fe Mg 180

190 3.7 Vitrification of FA Preliminary vitrification of FA has been conducted by adding silica with FA and melting at 1200 C and 1 hour holding time. Thus the produced apparent vitrified FA was analyzed using X-ray diffraction which shows mostly stable oxide forms, sodium oxide (Na 2 O), silica (SiO 2 ) and calcium oxide (CaO) (Fig. 6). It appears to be promising by the evidence of the formation of more stable chemical phases of FA after vitrification which may reduce the leaching potential. Vitrified FA with Silica_1200 C Fig. 6: X-ray diffraction pattern for vitrified FA. 4. CONCLUSIONS Theta (Degree) Characterization of MSWI BA and FA has been performed. Microstructural analysis by SEM reveals that FA possess more internal porosity and angular morphology compared to BA, which is attributed to the reduced workability of FA-mixed concrete and increased leaching susceptibility. Based on the compositional and mineralogical analysis by EDS and XRD, respectively, BA contain higher amount of silica (strength-building component in cement hydration) than FA. FA contains highly soluble salts, Cl, and heavy metals, which may require pretreatment before using it in concrete. Both BA and FA exhibit to contain approximately 0.03% of metallic Al by weight, which may lead to hydrogen gas evolution and ultimately inferior performance of concrete. Standard leaching tests show significant reduction in leaching of alkaline elements (Ca, Al, Si, Na, and K) and heavy metals (Cu, Fe, Mg, Ti, and Zn) from BA when they are mixed in HMA and PCC. This leaching reduction is likely due to the physical and chemical encapsulation in asphalt and cement mixture. Release of most priority elements (except Al) meets the Secondary U.S. Drinking Water Standards. In addition, leaching of all those elements (including Al) is well below the U.S. Stormwater Runoff Discharge Limit. The reuse of BA in HMA and PCC, therefore, appears to be an encouraging and sustainable alternative from environmental perspective. Based on the SiO 2 2. Na 2 O 3. CaO 3 preliminary study, vitrification appears as a promising means to stabilize toxics in FA. REFERENCES 1. Bernardo, E., Scarinci, G. and Colombo, P. (2012), Vitrification of Waste and Reuse of Waste-Derived Glass. In: MEYERS, R. (ed.) Encyclopedia of Sustainability Science and Technology. Springer New York. pp Chandler, A. J., Eighmy, T. T., Hartlén, J., Helmar, O., Kosson, D. S., Sawell, S. E., Van Der Sloot, H. A. and Vehlow, J. (1997), Municipal Solid Waste Incinerator Residues, Amsterdam, the Netherlands, Elsevier. 3. Hasselriis, F. (2012), Waste-to-Energy Ash Management in the United States. Encyclopedia of Sustainability Science and Technology. New York: Springer. pp Hewlett, P. C. (1998), NY, John Wiley & Sons. 5. Hill, J. W., Petrucci, R. H., Mccreary, T. W. and Perry, S. S General Chemistry, New Jersey, USA, Pearson Prentice Hall. 6. ISWA (2006), Management of Bottom Ash from WTE Plant. The International Solid Waste Association (ISWA). 7. ISWA (2008), Management of APC residues from W-t-E Plants. International Solid Waste Association (ISWA). 8. Lam, G. H. K., Ip, A. W. M., Barford, J. P. and Mckay, G. (2010), Use of Incineration MSW Ash: A Review. Sustainability, 2, pp MSGP (2008), Multi-Sector General Permit for Stormwater Discharges Associated with Industrial Activity (MSGP), U.S. Environmental Protection Agency (U.S. EPA), Washington DC. 10. U.S.EPA (2009), Drinking Water Contaminants. EPA 816-F U.S. Environmental Protection Agency (U.S. EPA), Washington DC. 11. U.S.EPA (2012), Municipal Solid Waste Generation, Recycling, and Disposal in the United States: Facts and Figures for U.S. Environmental Protection Agency (U.S. EPA), Washington DC. 12. Vehlow, J. (2012), Waste-to-Energy Ash Management in Europe. Encyclopedia of Sustainability Science and Technology. New York: Springer. pp Wiles, C. and Shepherd, P. (1999), Beneficial Use and Recycling of Municipal Waste Combustion Residues -A Comprehensive Resource Document. Boulder, CO: National Renewable Energy Laboratory (NREL). 181

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192 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh FEASIBILITY OF REMOVAL OF HEXAVALENT CHROMIUM USING A MIX OF FISH SCALES Fatima Enam, Syeda Tajin Ahmed and Md. Mominur Rahman* Bangladesh University of Engineering and Technology, Department of Chemical Engineering, Dhaka-1000 Solid wastes and liquid effluents from leather industries contain chromium. Compounds of chromium are toxic and cause severe health effects in humans. The objective of this research was to explore the effectiveness of adsorption of heavy metal using an inexpensive and readily available biosorbent, preferably made from waste materials. An investigation was carried out in order to determine the performance of a natural biosorbent, derived from fish scales of three species, Tilapia (Oreochromis mossambicus), Ruhu (Labeo rohita ) and Catla ( Catla catla), in the removal of hexavalent chromium in a laboratory scale packed bed column. By involving both mixed scales in the raw form and scales ground to a specified mesh size, the adsorption was modeled using isotherms and breakthrough curves were plotted. The extents of adsorption were compared and regeneration of the beds carried out. The maximum adsorption capacity of ground and unground fish scales were found to be mg/g and mg/g respectively. 1. INTRODUCTION Chromium (VI) has long been a major pollutant of surface water in Bangladesh, owing to the numerous leather processing industries (LPI) using chrome liqueur or chrome powder for tanning of leather. Residual chromium after leather processing is discharged in solid or liquid effluents. This causes chromium contamination not only of water but also of aquatic lives, land, vegetables farming and crops, thus posing a serious health hazard.the Cr(VI) concentration in industrial effluentcan be in the range of 0.5 to 27,000 mg/l (Patterson, 1985).The tolerance limit for the discharge of Cr(VI) into inland surface water is 0.1 mg/l and in potable water 0.05 mg/l (EPA, Environment Pollution Control Alternatives, 1990).Soluble Cr(VI) is extremely toxic and shows mutagenic and carcinogenic effects on biological systems due to its strong oxidizing nature (McLean, 2001). Metal coagulants, such as alum, can be used to partially remove heavy metals from wastewater (Eilbeck and Mattock, 1987), but, the use of metal coagulants is not 100% effective for removing metal cations from water at ph 7 (Bell and Saunders, 2005). Moreover, the high cost of adsorbents such as activated carbon and some ionexchange resins used for the treatment of water and wastewater has led to intensive research on the development of more effective and cheaper adsorbents. Bailey et al. (1999) mentioned that natural materials that are available in large quantities or industrial waste products can also be used as adsorbents. Recent biosorption experiments have focused attention on waste materials, which are by-products or the waste materials from largescale industrial operations. For e.g. Catla fish scales (Prabuet al, 2012), the waste myceliaavailable from fermentation processes, olive mill solid residues (Pagnanelli et al, 2002), activated sludge from sewage treatment plants, biosolids (Norton et al, 2003), aquatic macrophytes (Keskinkan et al, 2004), etc. Fish scales have the ability to remove a great variety of heavy metals. Rice isthe staple food of Bangladesh, and usually accompanied by fish dishes. High demand for fish in the municipal areas resultsin a steady build-up of fish scales in the market places, which eventuallyend up in the municipal waste. In this study, biosorbents have been produced in the laboratoryfrom the waste fish scales collected from local markets.the adsorption experiments of Cr(VI) were carried out in a packed bed column. In addition, desorption studies have been carried out to determine if the adsorbent can be regenerated. 2. METHODOLOGY 2.1. Preparation of fish scales Fish scales of Ruhu, Catla and Tilapia were collected from local market in Town Hall, * Corresponding Author: Md. Mominur Rahman mrrahman.rahman@gmail.com

193 Mohammadpur, Dhaka. The raw fish scales were washed repeatedly to remove any dirt, sand or mud. The fish scales were then washed with demineralized water and dried in the sun until the samples were visibly free from moisture. In order to remove the retained moisture from the fish scales, the samples were dried in an oven at a temperature of 70 deg C for 4 hours (Kondapalli et al., 2009).After drying, the three types of fish scales were mixed thoroughly and the resulting mixture contained fish scales of Ruhu, Catla and Tilapia in the ratio of 1:1:1 by weight. From this mixture, one part was cleaned, separated and ground by using a pestle and mortar. They were then sieved for homogeneity by using Tyler mesh. These ground samples were again dried inside an oven at 70 deg C to obtain samples that are moisture free. These fish scales were used to make an adsorption bed of ground scales. Cr(VI) concentrations, using a UV spectrophotometer (Model: HACH DR/4000 UV Spectrophotometer). 3. RESULTS AND DISCUSSION 3.1 Adsorption Isotherms To describe the equilibrium relationship between adsorbed Cr(VI) ions onto the fish scales, qe (mg adsorbed/g adsorbent) and Cr(VI) ions in solution, C e (mg/l) adsorption isotherm models namely Langmuir and Freundlich, were plotted which are shown in Fig 1 and 2, respectively. The remaining portion of the mixed raw scales, was cut into small pieces having an average diameter of 1 cm. The scales were then oven dried again at 70 deg C. These were used to make an adsorption bed of unground scales Preparation of Solution Stock solution of Cr(VI) was prepared by dissolving 4.74 g of reagent grade Potassium Dichromate(K 2 Cr 2 O 7 ) in 30 L solution. The resulting K 2 Cr 2 O 7 solution had a concentration of 50 ppm (w/v). The ph of the prepared solution was 5. Fig. 1: Langmuir Isotherm 2.3. Regeneration The regeneration of the ground bed was carried out by flushing the bed with 1M NaOH solution repeatedly to remove the adsorbed species, until the exiting solution was free from any chromium Experimental Design Two packed beds of fish scales were made by taking two glass columns (length mm; diameter 25.4mm), one of which contained the ground scales and the other, the unground scales. The stock solution of 50 ppm Cr(VI) was supplied from an overhead tank (20 L capacity)through the ground and unground beds. The solution flow rate was maintained at 5 ml/min by controlling the regulating valve at the exit of each column. The exiting solution from the bottom was collected in test tubes at an interval of 10 minutes. The collection of samples was carried out until the exiting solution appeared to have the same color as the stock solution, implying that the adsorption capacity of the beds has reached their saturation. The collected samples were then analyzed for Fig. 2: Freundlich Isotherm The figures show that both Langmuir and Freundlich models fitted the experimental data well, as shown by the values of the correlation coefficient. Although the constants are specific to test conditions and adsorption type, the results indicate comparable assessment of the two isotherms prepared and investigated. The Langmuir and Freundlich constants determined from the slopes and intercepts of the respective plot are summarized in Table 1. The constant q max (maximum adsorption capacity, (mg/g) in the Langmuir isotherm is useful when comparing adsorption performance of adsorbents. 184

194 Table 1. Langmuir and Freundlich Parameters for adsorption of Cr (VI) onto fish scales Isotherm type Langmuir Isotherm Freundlich Isotherm Parameters q max B R 2 K f 1/n R 2 (mg/g) Ground Scales Unground Scales A confirmation of the fitness of experiment data into the Langmuir isotherm model indicates the homogenous nature of the adsorbent surface (Hammaini, 2002). In the Freundlich isotherm model, K f and n are the Freundlich constants; n gives an indication of how favorable the adsorption is, and K f (mg/g (L/mg) 1/n ) is the adsorption capacity of the adsorbent(foo and Hameed, 2010). With a higher R 2 value, which represents the fitting of the line, adsorption onto the unground scales was better modeled using the Langmuir isotherm and the biosorption of ground scales by the Freundlich isotherm Breakthrough Curves Individual breakthrough curves were used to compare the adsorption capacities of the packed columns with different mix of fish scales which are shown in Fig 3 and 4. The ratio of the equilibrium Cr(VI) concentration, C e (mg/l), and initial solution concentration, C 0 (mg/l), which was used to show the longer break-through times indicate higher efficiency of the adsorbent inside the column in removing the desired adsorbate and it will function for a longer time without regeneration/replacement of the column material. column where the adsorption of the species takes place and descends down the column with time, has disappeared. Once saturation had been reached, the beds were flushed, using 1 M NaOH solution. The regenerated bed efficiency dropped significantly, indicated by a shorter operating time, as shown in Fig 5. The bed gets exhausted in approximately 80 minutes, implying the saturation of the bed. Consequent regenerations resulted in even shorter operation times. Hence, the regeneration capability of fish scales is low. Fig. 4: Breakthrough Curve for ground fish scales Fig. 3: Breakthrough curve for unground fish scales Both columns operated over a considerable amount of time before reaching saturation. The time of exhaustion of both beds (when 95% of the bed is saturated) appear at about 170 minutes. Beyond this point, the task of removing the Cr (VI) ions can no longer be accomplished. This point indicates that the mass transfer zone, the moving fraction of the Fig 5: Breakthrough Curve for ground fish scales after regeneration Removal Rates The rates of removal during the courseof the experiments are represented in Fig 6 and 7. The removal rate drops rapidly within the 1 st hour of continuous operation(from 4.39 mg/l.min to mg/l.min). The adsorption of Cr(VI) on unground fish scales were continued upto 140 minutes of operation, after which the rate becomes less than 185

195 Removal Rate (mg/l.min) Removal Rate (mg/l.min) Extent of Adsorption % 0.05 mg/l.min, signifying a negligible adsorption on fish scales. Reduction in the removal rate of Cr(VI) on ground scales is less than that on unground scales (from 4.24 to 0.5 mg/l.min) in the 1st hour. The rate of adsorption reaches 0.05 mg/l.min in approximately 125 minutes of continuous operation, showing that unground scales remove Cr(VI) for a longer time with a comparable removal rate Time (mins) Fig. 6: Removal Rate of Cr(VI) by unground fish scales with time Time (min) Fig. 7: Removal Rate of Cr(VI) by ground fish scales with time Extent of Adsorption The extent of adsorptionefficiency is given as, The unground scales start off with a higher efficiency than the ground scales. At the end of 140 minutes of operation, the efficiency of adsorption of unground scales was higher than that of the ground scales. This graph also indicates that the drop in efficiencywith time is more rapid for ground scales after 90 minutes Fig.8: Extent of Adsorption of ground and unground fish scales. 4. CONCLUSION This paper proposed the use of fish scales of Ruhu, Catla and Tilapia as biosorbents for effective removal of the heavy metals from the synthetic aqueous solution of hexavalent chromium in a fixed bed.equilibrium data werepresented in the form of isotherms. Based on the Langmuir coefficients, the maximum adsorption capacity of Cr(VI) was mg/g for ground scales and mg/g for unground scales. The breakthrough curves have a typical S shape, and the calculated percentage of total removal of chromium (VI) is satisfactory, with 87.8% for unground scales and 84.8% for ground scales. REFERENCES ground scales unground scales Time (mins) 1. Bailey S. E.,.Olin T. J, Bricka R. M., and Adrian D. D. (1999), A Review of Potentially Low-Cost Sorbents for Heavy Metals.Water Research, 33(11): Bell R.R. and Saunders G.C. (2005), Cadmium Adsorption on Hydrous Aluminium (III) Oxide: Effect of Adsorbent Polyelectrolyte, Applied Geochemistry Eilbeck W.J. and Mattock G. (1987),Chemical Processes in Wastewater Treatment, Ellis Horwood Limited, John Wiley and Sons, New York, U.S.A. 4. EPA (1990), Environmental Pollution Control Alternatives, EPA/625/5-90/25, EPA/625/4-89/023. Environmental Protection Agency, Cincinaati, OH, USA. 5. Foo, K.Y., Hameed, B.H. (2010), Insights into the modeling of adsorption isotherm systems, Chemical Engineering Journal, 156:

196 6. Hammaini, A., Ballester, A., Blázquez, M.L., González, F., Muñoz, J.A. (2002),Effect of the presence of lead on the biosorption of copper, cadmium and zinc byactivated sludge, Hydrometallurgy 67 (1), Keskinkan, O., Goksu, M.Z.L., Forster, C.F. (2004), Heavy metal adsorption properties of a submerged aquatic plant, Biosource Technology, 92: Kondapalli S. and Mohanty K (2009). Biosorption of Hexavalent Chromium from Aqueous Solution by Catlacatlascales, Equilibrium and kinetics studies, Chemical Engg Journal,155, McLean J., Beveridge T.J. (2001),Chromate reduction in Pseudomonad isolated from a site contaminated with chromate copper arsenate, Appl Environ Microbiol, 67(3): Norton, E.J.(2003),Evaluation of Multiple-Rate Biosolid Applications on SudangrassYield.Forage and Grain Report 11. Pagnanelli, F.Ferella, F.DeMichelis, I.Vegliò, F. (2011),Adsorption onto activated carbon for molybdenum recovery from leach liquors of exhausted hydrotreating catalysts. Hydrometallurgy 12. O. Keskinkan, M.Z.L. Gosku, M. Basibuyuk, C.F. Forster. (2004), Heavy metal adsorption properties of a submerged aquatic plant (Ceratophyllumdemersum),Biosource Technology 92, Patterson, J.W. (1985),International Wastewater Treatment Technology, 2 nd Edition, Butterworth-Heinemann, London. 14. Prabu K., Shankarlal S. and Natarajan E. (2012),A Biosorption of Heavy Metal Ions from aqueous Solutions Using Fish Scale (Catlacatla), International Journal of Bioprocess Technology, 1(1):

197 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh Effect of mesoporous support on H 2 production via methanol steam reforming in the presence of Cu and Zn Catalysts Richard Y. Abrokwah 1, Vishwanath G. Deshmane 2, 3, Sri Lanka Owen 3, William Dade 3, Sara. Al-Salihi 2 and Debasish Kuila 3* 1 Department of Energy and Environmental Systems, North Carolina Agricultural and Technical State University (NCAT) Greensboro, NC USA 2 Department of Chemical, Biological and Bioengineering (NCAT) Greensboro, NC USA 3 Department of Chemistry (NCAT) Greensboro, NC USA *dkuila@ncat.edu We have synthesized mesoporous SiO 2 (MCM-41& SBA-15), TiO 2 and CeO 2 encapsulated Cu and Zn nanocatalysts using an optimized one-pot hydrothermal procedure. Both silica and TiO 2 catalysts possess a high surface area in excess of 800m 2 /g and 250m 2 /g, respectively. XRD studies confirmed a long range ordered structure in Cu-MCM/41 and Zn-MCM/41 catalysts and the presence of catalytically active anatase phase in the crystalline Cu and Zn/TiO 2 catalysts. The effect of interactions between the metal (Cu and Zn) and the support (SiO 2, TiO 2 and CeO 2 ) on steam reforming of methanol (SRM) to produce hydrogen has been investigated. Results from SRM studies indicate that TiO 2 is a better support for Zn and SiO 2 based supports interact better with Cu catalysts. 10%Cu-CeO 2 produced the lowest (1.84%) CO selectivity followed by 2.96% and 5.58% CO selectivity for 10%Zn-TiO 2 and 10%Cu-MCM-41, respectively. 1. INTRODUCTION A need for clean and sustainable energy combined with the urgency to reduce emissions has come together to form a global imperative, one that demands new technologies and new approaches for the way we produce and use energy. Hydrogen as fuel for proton exchange membrane fuel cells (PEMFC) is believed to be crucial for the energy and environmental sustainability. To accrue the full environmental benefits of hydrogen as an energy carrier, low-carbon intensive and low polluting fuels, lower cost processes for producing hydrogen from renewable energy sources need to be developed. Our research group at NSF CREST Bioenergy Center of North Carolina A&T State University has been working on the fundamental aspects of novel mesoporous support encapsulated nanocatalysts for hydrogen production via steam reforming reactions (SRRs) of biofuels. On-board reforming of energy dense alcohols like methanol is envisaged as a practical route to address the flammability and storage challenges associated with compressed hydrogen and to produce clean hydrogen to power fuel cell electric vehicles. However, steam reforming of methanol (SRM) produces CO as a byproduct which rapidly poisons the anode electrode catalyst of the PEMFC (Baird, and Cann, 2012). It is therefore crucial to design and explore robust catalysts that have impressive methanol conversion, high selectivity for hydrogen and insignificant selectivity (less than 20ppm) for carbon monoxide during SRM. Copper and zinc based catalysts have been used in SRM due to their high reactivity (Bobadilla et. al., 2013, Bard and Pettersson, 2001, Pinzari et. al., 2006). The use of high surface area mesoporous supports, which have large pore sizes, are expected to provide pathways for rapid methanol diffusion and avail a large active surface area for kinetically efficient catalysis. In this study, we report the comparative catalytic performance of Cu and Zn supported on SiO 2, TiO 2 and CeO 2 for steam reforming of methanol (SRM) in a packed bed reactor. 2. EXPERIMENTAL 2.1 Materials and Methods All the analytical grade reagents were used without purification. Tetramethylorthosilicate, 99% (TMOS) and ammonium hydroxide, reagent ACS were procured from Acros Organics, New Jersey, USA. Cetyltrimethylammonium bromide (CTAB), pluronic P123, Cu(NO 3 ) 2.2.5H 2 O, Ce(NO 3 ) 4 and * Corresponding Author: Debasish Kuila, dkuila@ncat.edu

198 Intensity Zn(NO 3 ) 2.6H 2 O were procured from Sigma- Aldrich, Missouri, USA. Ethanol anhydrous and acetone, ACS reagents were purchased from Fischer Scientific, New Jersey, USA. The Deionized water was purified using a Mill-Q Advantage A10 Elix 5 system obtained from Millipore Corporation (Bedford, MA, USA). 2.2 Experimental Procedure For synthesis of MCM-41, SBA-15 and CeO 2 molar ratios used (1 TMOS: 0.13 CTAB: H 2 O: 20 Ethanol) were based on our previous study (Balaji et. al., 2011, Kosaraju et. al., 2014). In a typical synthesis of Zn/MCM-41, CTAB was dissolved in de-ionized water at 30 C to get a colorless solution-1. Another solution designated as 2 was prepared by dissolving required quantities of zinc nitrate in ethanol. Solution 2 was gently poured into 1 and stirred for 30 minutes. To this solution, TMOS was added drop-wise and the solution was stirred for another 30 minutes. Ammonium hydroxide was then added to this solution drop-wise until the ph of the solution was 10 and stirred for another 3 h. The resulting material was aged in an oven at 65 C for 18 h. The solid material was then water washed, filtered and then washed with ethanol. The filtrate was first air dried for ~24 h and then dried in an oven at 110 C for 24 h. Finally, the material was calcined at 550 C for 16 h with a heating and cooling rate of 2 C/min to remove CTAB completely. In SBA-15 synthesis P123 was additionally used as a template directing agent. For the synthesis of Zn/TiO 2 catalyst, TIPR was the limiting reagent and a molar ratio of (1 TIPR: 0.2 CTAB: H 2 O: Ethanol) was used. Precipitation with ammonium hydroxide was followed with aging for 24 h at room temperature. The TiO 2 and CeO 2 catalysts were calcined at 450 C (at 5 C min -1 ) for 6 h in static air to remove the organic template. 2.3 Catalyst Characterization and Testing The textural properties (surface area, pore volume and pore size) of the catalysts were determined by BET analysis using a Quantachrome NOVA 2200e instrument. Small and wide angle XRD diffractions were recorded using a D8 Discover X-ray diffractometer from Bruker (Bruker Optics, Inc., Billerica, MA). The morphological properties of the catalysts were analyzed using Zeiss Libra 120 transmission electron microscope operated at an accelerating voltage of 120 kv. The SiO 2 catalyst were pre-reduced in a tubular furnace using 4% hydrogen in argon at 550 ºC for 5 h. CeO 2 and TiO 2 catalysts were pre-reduced under similar conditions at 350 ºC for 3 h. The activity tests for all catalysts were performed at atmospheric pressure in a continuous down flow stainless steel fixed bed reactor (Tube ID: 6.22 mm). The activated catalyst was mixed with white quartz sand in a volume ratio of catalyst/sand 2:1. The mixture was then loaded into the reactor sealed with quartz wool at both ends and activated in-situ at 350 C for 1 h under 4% H 2 in argon environment just before the steam reforming reactions. A methanol/water feed molar ratio of 1:3 and flow rate of 2838 h -1 GHSV at STP was maintained for all experiments. Temperature of all reactions was 250 ºC. The composition of the reaction products and collected condensate was analyzed using an Agilent 7890B GC equipped with TCD and FID detectors. 3. RESULTS AND DISCUSSIONS 3.1 XRD Studies Fig. 1 shows the small angle x-ray diffraction peaks of MCM-41 supported catalysts MCM-41 10Zn-MCM-41 10Cu-MCM theta (deg) Fig.1: Small angle XRD patterns of calcined MCM- 41catalysts Based on the Bragg scattering (nλ = 2dsinө), pure MCM-41 possessed the highest long range ordered mesoporosity. This observation concurs with TEM micrograph in Fig. 2 which depicts the ordered cylindrical mesopores of the MCM-41 matrix. However, the peak intensity decreased upon incorporation of the metals in the support indicating the loss of some degree of the ordered structure. 3.2 BET Analysis Table 1 summarizes the results of N 2- physiosorption studies of the various catalysts used in this study. 10%CuTiO 2 and 10%ZnTiO 2 catalysts showed a notable surface area of 285.6m 2 /g and 250.2m 2 /g, respectively. The amorphous MCM-41 matrix showed a large surface area (1039 m 2 /g) which decreased by ~23% when the Cu and Zn metals were added. This trend could be due to the blocking of the smaller mesopores by the metal particles and decrease in long range order of mesoporous structure leading to an increase in the 189

199 Weight (%) Heat Flow (W/g) average pore size and a concomitant decline in the catalytic surface area. Table 1: Textural Properties of Catalysts Catalyst SA (m 2 /g) Pore Size Pore Volume (cm 3 /g) (nm) MCM Cu-MCM Zn-MCM Cu-SBA Zn-TiO Cu-TiO Cu-CeO catalysts was significantly higher than the Zn catalysts. 10%ZnTiO 2 showed 22.35% methanol conversion and 2.96% CO selectivity compared to 10%CuTiO 2 that showed 14.48% conversion and a very high CO selectivity of ~56%. This behavior was in sharp contrast to the silica supported catalysts wherein 10CuSBA-15 (99.8% H 2, ~7%CO selectivity) and 10%Cu-MCM41 (100% H 2 and ~5% CO selectivity) displayed catalytic dominance over 10%ZnMCM Temperature ( C) Fig. 3: TGA-DSC profile of mesoporous-tio 2 These results clearly suggest that interactions of Zn with TiO 2 and Cu with SiO 2 are more helpful in promoting a better SRM catalytic performance compared to Zn with SiO 2 and Cu-TiO 2. Fig. 2: TEM micrograph of MCM Thermal Analysis Fig. 3 shows the TGA-DSC profile of mesoporous- TiO 2. The endothermic weight loss around 85 C is attributed to the removal of adsorbed water molecules on the TiO 2 surface. The strong exothermic peak between C is ascribed to the removal of the surfactant (CTAB). The exothermic peak at ~450 C represents the TiO 2 crystallization temperature. No significant weight loss was observed between 500 C to 900 C signifying the thermal stability of the mesoporoustio 2 support. 3.4 Catalyst Testing for SRM Table 2 shows methanol conversion and selectivity towards H 2, CO, CO 2 and CH 4 measured over the supported 10wt% metal on SiO 2 /TiO 2 /CeO 2 supports at 250 o C. Our results revealed that the performance of the catalysts changed drastically when the support was changed. All the catalysts showed impressive (>94%) hydrogen selectivity; the reforming reactivity of the Cu supported Table 2: Methanol steam reforming on mesoporous SiO 2, TiO 2 and CeO 2 supported catalysts Catalyst MeOH Conver sion (%) Selectivity (%) H 2 CO CO 2 CH 4 10CuMCM ZnMCM CuSBA Cu TiO ZnTiO CuCeO Furthermore, 10%Cu-CeO 2 yielded an appreciable ~45% conversion, and lowest CO selectivity of 1.84% with H 2 selectivity of ~100%. The observed higher CO 2 selectivity with Cu-SiO 2, Zn-TiO 2 and Cu-CeO 2 can be attributed to their higher activity for water gas shift reaction. Our studies reveal that the support of active metal components plays a crucial role in dictating activity and selectivity of SRM. The significantly higher CO 2 selectivity observed for CeO 2 catalyst concurs with previous studies (Deeprasertkul et. al., 2014) which claimed 190

200 that it is due to the great oxygen retention capability of CeO 2 which probably facilitated the oxidation of CO to CO 2 during the reforming reaction (Udani et. al., 2009). 7. CONCLUSIONS We have successfully synthesized high surface area Cu and Zn/MCM-41, Cu and Zn/TiO 2 and Cu/CeO 2 catalysts by an optimized one-pot hydrothermal procedure. All the catalysts are mesoporous in nature. Small angle XRD analyses showed that both Cu and Zn/MCM-41 catalysts possessed a long range ordered structure at 10 wt% metal loading. All the catalyst displayed an impressive >94% hydrogen selectivity. 10%Cu-MCM41 showed the highest SRM activity with ~68% methanol conversion and ~6% CO selectivity while 10%CuCeO 2 yielded ~45% methanol conversion with the lowest ~1.84%CO selectivity. Our studies clearly demonstrate the unique interactions between specific metal and support that plays a crucial role in deciding the catalyst s activity and selectivity. ACKNOWLEDGEMENTS The authors acknowledge the funding received from National Science Foundation (NSF) for the NSF-CREST Bioenergy Center (Grant No. HRD ). The authors also thank Dr. Sankar and Dr. Yarmolenko (Center for Advanced Materials and Smart Structures-CAMSS) at NCAT for the use of the XRD for material characterization. Finally, we acknowledge the Joint School of Nanoscience and Nanoengineering (JSNN) for using the TEM and SEM-EDX instruments. REFERENCES 1. Baird, C., Cann, M., Environmental Chemistry (2012), 5th ed., W. H. Freeman and Company: New York, pp Bobadilla, L. F.; Palma, S., Ivanova, S., Dominguez, M. I., Romero-Sarria, F., (2013), Steam Reforming of methanol over supported Ni and Ni-Sn nanoparticles International Journal of Hydrogen Energy, 38(16), Lindström, Bard, and Lars J. Pettersson. Hydrogen generation by steam reforming of methanol over copper-based catalysts for fuel cell applications. International Journal of Hydrogen Energy 26.9 (2001): F. Pinzari, P. Patrono, U. Costantino. Methanol reforming reactions over Zn/TiO 2 catalysts. Catalysis Communications 7 (2006) Balaji, T., B. Yulia, R. Atikur, I. Saiful, R. Mizanur, I. Azharul, P. Joslyn, K. James, T. Jasmine, K. Dhananjay, I. Shamsuddin, and K. Debasish, Development of Mesoporous Silica Encapsulated Pd-Ni Nanocatalyst for Hydrogen Production, in Production and Purification of Ultraclean Transportation Fuels. 2011, American Chemical Society. p Kosaraju, K., A. Rahman, M. Duncan, B. Tatineni, Y. Basova, V. Deshmane, R. Abrokwah et al. Bimetallic nanocatalysts in mesoporous silica for steam reforming reactions to produce H 2 for fuel cells. Future Energy, Environment, and Materials 88 (2014): Deeprasertkul, C., Longloilert, R., Chaisuwan, T., Wongkasemjit, S.(2014) Impressive low reduction temperature of synthesized mesoporous ceria via nanocasting, Materials Letters 130,pp Udani, P. P. C., P. V. D. S. Gunawardana, H. C. Lee, and D. H. Kim. Steam reforming and oxidative steam reforming of methanol over CuO CeO 2 catalysts. International journal of hydrogen energy 34, no. 18 (2009):

201 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh COMPARATIVE ANALYSIS OF CHITOSAN PRODUCTION METHODS AND ITS OPTIMIZATION S.M.Z. Islam, Sheikh M. E. Babar * Biotechnology and Genetic Engineering Discipline, Khulna University, Khulna-9208, Bangladesh A comparative study of chitosan production with respect to chemical consumption and time consumption between two different protocols has been performed. Identifying the better process, an optimization was done using Box Behnken experimental design. Hydrochloric acid (HCl) concentration for demineralization, sodium hydroxide (NaOH) concentration for deproteinization and sodium hypochlorite (NaOCl) concentration for decoloration are the three process parameters that have been used to optimize the effect on yield, water binding capacity (WBC) and fat binding capacity (FBC). The level of acid, alkali and bleach concentrations were chosen as 1±0.5N, 3.5±0.5% (w/v), and 3.25±0.25% (w/v), respectively. Statistical regression analysis, 3D surface plots and contour plot were used to determine optimum chitosan production condition. 1N HCl, 3% NaOH and 3.25% NaOCl were found to be the optimum condition. This condition showed 28% yield with 349% WBC and 540% FBC. 1. INTRODUCTION Chitosan, a polymer rarely found in nature, is a non-toxic, biodegradable, biocompatible and highly polycationic biopolymer comprising of (1, 4)- linked aminodeoxy-β-d-glucan. It is derived by deacetylation of chitin, which is a major component of the shells of crustaceans such as crab, shrimp and lobster. Insects such as butterflies and ladybugs also have chitin in their wings and the cell walls of yeast, mushrooms and other fungi contain this substance too (Shahidi et al., 2005; Tharanathan et al., 2003). After cellulose, chitin is the second most abundant natural biopolymer found in nature and its annual production in aquatic systems alone is estimated to be tons (No and Meyers, 1989 and Cauchi, 2002). Due to its diversified chemical, biochemical and microbial properties e.g., immobilization properties, anti-microbial, anti-fungal and antitumor activities, chitosan has been extensively using in food, medical and other biochemical purposes since several years. It is also known that chitosan is helpful in lowering blood cholesterol and accelerating skin regeneration processes, and it is used as binding, gelling, thickening and stabilizing agent in food industries (Knorr, 1984, Muzzarelli et al., 1996). It has been shown that several million tons of shrimp shell waste possesses a significant and renewable major resource for the biopolymer chitin and chitosan (No and Meyers, 1989, 1992). Shrimp shell as well as other crustacean shell waste mainly consists of protein (30-40%), calciumcarbonate (30-50%), and chitin (20-30%) on a dry basis (Johnson and Peniston, 1982). They vary with species and seasons (Green and Kramer, 1984). Chitin represents one third of the shell composition and is highly hydrophobic, insoluble in water but soluble in most organic solvents. Chitosan, the deacetylated product of chitin, is soluble in very dilute acids such as acetic acid or formic acid. Isolation of chitin from crustacean shell waste consists of three basic steps: demineralization (DM), deproteinization (DP), and decoloration (DC). These three steps are the standard procedure for chitin production (No and Meyers, 1989). The subsequent conversion of chitin to chitosan is known as deacetylation (DA), which is generally done by treatment with concentrated sodium hydroxide solution (40-50%) at 100ºC or higher to remove some or all of acetyl group from the chitin (No and Meyers, 1995). Several research dissertations were carried out in Khulna University (Naznin, 2005 and unpublished thesis) in recent past to produce chitosan by different modified process protocol where three basic steps (DM, DP and DA) with their variations were used. The processes that were previously used were costly because of more chemical and time consumption. This study is aimed at developing a cost effective process between the two protocols and optimization of the better one. * Corresponding Author: Sheikh M. E. Babar, babarku@gmail.com

202 2. MATERIALS AND METHOD 2.1 Materials Shrimp shells were collected from local markets (Rupsha sea food, Rupsha approach road, Rupsha, Khulna, Bangladesh). The species was Penaeus monodon commonly called Black tiger (Bagda in Bangla). Hydrochloric acid, sodium chloride, sodium hypochlorite and acetic acid were purchased from Sigma Aldrich. Distilled water was used throughout this research. 2.2 Methodology of Chitosan Production Sample collection and preparation: To prepare the sample for the production of chitosan and its proximate analysis, the shrimp shells were washed thoroughly with fresh tap water and kept in a slanting position in a tray to remove the water and dried under the sun. Ten grams (10 g) of dry shrimp shells were used for chitosan preparation Demineralization: The dried shell chips were immersed in different HCl solutions (0.5N, 1N and 1.5N) keeping solid to liquid in the ratio 1:15. The mixture was kept for 0.30 h at room temperature with constant stirring using a glass rod. In the initial stage of the reaction, frequent stirring is required to prevent the floating of the shell chips caused by the generation of CO 2 gas. After 0.30 h of immersing, demineralized shell chips were collected and washed with distilled water Deproteinization: The demineralized shell chips were added to various aqueous NaOH solutions (3%, 3.5% and 4%) keeping solid to liquid in the ratio 1:10. The mixture was kept for 2 h at room temperature with continuous stirring using a locally made agitator. In this stage, continuous stirring is required for increasing the rate of deproteinization of the shell chips. After 2 hours of immersing deproteinized shell chips were collected and washed with distilled water Decoloration: After deproteinization, shrimp shells (also referred to as demineralized, deproteinized or shrimp shell chitin) were decolorized with acetone for 10 min and dried for 2 hr at ambient temperature, followed by bleaching with (3%, 3.25%, 3.50%) (v/v) sodium hypochlorite (NaOCl) solution (containing 5.25% available chlorine) for 5 min at ambient temperature with a solid to solvent ratio of 1:10 (w/v), based on dry shell. Samples were then washed with tap water and dried for 2-3 hrs until the powder was crispy Deacetylation: Roberts (1997) concluded that there is no standard deacetylation process but most work has been carried out using concentrated NaOH solution (35-50% w/w) at temperature of C for reaction times of hours keeping solid to liquid in the ratio of approximately 1:10. The decolorized shell chips produced by decoloration step were added to 50% (w/v) NaOH. The mixture was boiled at 90 o C in a water bath for one hour with occasional stirring using a glass rod. At the end of this stage chitosan was obtained which did not float on the 50% (w/v) NaOH solution. 2.3 Physicochemical and Functional Properties Analysis Moisture Content: Moisture content of the chitosan was determined by the gravimetric method (Black, 1965) by complete drying of the sample. A beaker was cleaned, dried and then the constant weight of the beaker was taken. Total sample was placed in the beaker and weight was taken. Difference between these two weights gave the weight of the sample. Now, the beaker with the sample was placed in a controlled oven and was dried at 105ºC for 24 hours. The percentage of the moisture content was calculated by the following equation: Moisture content (%) = [(W 2 -W 3 )/ (W 2 -W 1 )] x 100 Where, W 1 =Weight of aluminum dish, W 2 =Weight of sample with aluminum dish, W 3 =Weight of glass beaker with sample after drying at 105 C for 24 hours Water Binding Capacity (WBC): WBC of chitosan was measured using a modified method of Wang and Kinsella (1976). WBC was initially carried out by weighing a centrifuge tube containing 0.05g of sample, adding 1 ml of water, and mixing on a vortex mixer for 1 min to disperse the sample. The contents were left at ambient temperature for 30 min with intermittent shaking for 5s in every 10 min and centrifuged at 3,500 rpm (6,000 x g) for 25 min. After the supernatant was decanted, the tube was weighed again. WBC was calculated as follows: WBC (%) = [water bound (g)/ initial sample weight (g)] x Fat Binding Capacity (FBC): FBC of chitosan was measured using a modified method of Wang and Kinsella (1976). FBC was initially carried out by weighing a centrifuge tube containing 0.05 g of sample, adding 1 ml soybean oil. The contents were left at ambient temperature for 30 min with shaking for 5 s in every 10 min and centrifuged at 3500 rpm (6,000 x g) for 25 minutes. 193

203 After the supernatant was decanted, the tube was weighed again. FBC was calculated as follows: FBC (%) = [fat bound (g)/ initial sample weight (g)] x 100. All experiments were carried out in triplicates. 2.4 Box-Behnken design Box Behnken design (Box, 1960) helps in investigating linear, quadratic, and crossproduct effects of three factors, each varied at three levels, and also includes three center points for replication. HCl concentration in normal (X 1 ), percent (w/v) NaOH concentration (X 2 ), and percent (w/v) NaOCl concentration (X 3,) were chosen as three factors and the three levels as high, middle, and low which are designated with +1, 0, and 1, respectively. The factors (variables) and their levels are presented in Table 1. Table 1. Levels of variables chosen for Box- Behnken study Process variables Levels HCl concentration (N) X NaOH concentration (%) X NaOCl concentration (%) X Chitosan yield (y), percent WBC (w) and percent FBC (f) were set as responses. The general quadratic response equation for this design is given below: Y( f ) A A X A X A X A X X A5 X 1X 2 A X. 3 1 A 6 X 1 2 X A 7 X ( 1) 3 A Where, Y is the response [(y), (w) and (f)], X 1 represents the HCl concentration in normal, X 2 is the percent NaOH concentration, X 3 is the percent NaOCl concentration, A 0 represents the regression coefficient, A 1 -A 3 are the linear coefficients, A 4 -A 6 the crossproduct coefficients, and A 7 -A 9 are the quadratic coefficients. Microsoft Excel software (Microsoft, Redmond, WA) was used for the analysis of regression, statistical significance and ANOVA. In addition to Excel, Sigmaplot 12 was used for drawing surface plots and contour plots. 3. RESULTS AND DISCUSSION 3.1 Comparison between Two Protocols We started working on producing chitosan from shrimp shell since several years in our laboratory. The previous researchers conducted research (unpublished thesis) in developing a commercially feasible protocol for chitosan production by optimizing the chemical concentrations and other operating variables. Present study was aimed to 8 X 1 2 reduce chemical concentration by maintaining the quality of chitosan, hence making the production process more feasible in terms of commercial aspects. The comparative values of process parameters between the two protocols were compared and it is seen that protocol proposed by No et. al., 2000 (Protocol B) is more efficient than the protocol proposed by No and Meyers, 1995 (Protocol A ) for commercial chitosan production. Protocol B took h less than protocol A and less money (about Tk. 900 per kg of shell). Considering the benefits of Protocol B, this method was chosen for chitosan production in this study and later, optimization of yield, water and fat binding capacities were performed using Box- Behnken experimental design. 3.2 Regression analysis After several trial runs process parameters with their levels have been chosen and were provided in table 1. Upon selection of the input conditions (chemical concentrations), chitosan was produced according to the experimental design conditions and the output responses (y, w, f) were calculated and tabled as presented in Table 2. Table 2. Input parameters (HCl, NaOH, and NaOCl concentration) and output responses (percent yield, WBC, and FBC) for Box Behnken design (HCl concentration (X 1 ; N) (NaOCl concentration, (X 3 ; %) (NaOH concenntration (X 2 ; %) Chitosan yield (%) WBC (%) FBC (%) These values were used for regression analysis using regression analysis function in the data analysis of Excel. The confidence level was kept at 95%. To find the coefficients (A 0 - A 9 of Eq. (1)) and the significant interactions among the parameters of the experimental response regression analysis was used. Different sets of these values 194

204 were obtained for each response analysis. The ANOVA analysis of the design variables was also calculated (Table 3) where values of coefficients and p-values three responses were obtained. A p- value less than 0.05 indicate that the factor interacted significantly with the response. From this table it is seen that four of the factors were significantly related (p <0.05) for yield, which indicates that one linear factor (Concentration of HCl for deproteinization) as well as one crossproduct and one quadratic factor were found interactive in separation efficiency (Table 3). HCl concentration was significant than the other two parameters. However, for WBC and FBC less significant factors were seen (data not shown). WBC was found more significant with sodium hypochlorite concentration meaningthat decoloration has an affect on water binding capacity. FBC was seen affected significantly on quadratic factor with NaOCl concentration. A few reports [Ragonese et. al., 2002] have considered only the coefficients of significantly related factors to generate the quadratic equation, but in our analysis, all nine coefficients [Babar et. al., 2007] were used in making the response equation, though not all factors were significant (p < 0.05). Table 3. Coefficient and corresponding probability values (p-value) for specific responses (y) (linear factors, crossproducts, and quadratic factors) Parameter (Coefficients) Yield Coefficient p-value Constant (A 0 ) a X 1 (A 1 ) a X 2 (A 2 ) X 3 (A 3 ) X 1 X 2 (A 4 ) a X 1 X 3 (A 5 ) X 2 X 3 (A 6 ) X 1 X 1 (A 7 ) a X 2 X 2 (A 8 ) X 3 X 3 (A 9 ) Using the regression analysis and from their coefficients value the second- order polynomial equations for the three responses were formed below: Y( y) X X X X 1X X 1X X 2 X X 4.19X 36.92X......( 2) 1 2 Y( w) X X X 3 74X 1X 2 166X 1X 3 114X 2 X X 6.38X 538.5X......( 3) Y( f ) X X X 3 17X 1X X 1X 3 136X 2 X X 62.53X 613.9X (4) 1 2 The R 2 values of the regression analyses of the three responses were found over The linearity of the analyses illustrates that all factors were well related to the response. From the ANOVA analysis, we found the predicted values of the response based on Eqs. (2)- (4). From this, we plotted the predicted versus experimental response (data not shown). Both the linearity and the slopes were found to be over 0.90, which indicates that the quadratic equation can predict the response well from these three factors. If the experimental and predicted values were not closely related the slope and R 2 values would have been far distant from Response surface plot analysis For observing the effect on the response, one factor was held constant while the other two factors were varied. To predict the values of chitosan yield, water binding capacity and fat binding capacity, equations (2) - (4) were used and all the three dimensional (3-D) response surface plots are shown in Fig. 1. For each response three combinations were possible, so a total of nine 3-D plots were created Yield: Fig. 1 (A-C; i) represents the effect of HCl, NaOH and NaOCl concentration on yield. When HCl concentrations were kept constant at 0.5N (data not shown), maximum yield of chitosan were observed 45.08% where both NaOH and NaOCl concentration were 3%. Minimum yield (21.96%) was observed at 4% NaOH and 3.25% NaOCl. When HCl concentration was kept constant at 1.5N (data not shown) maximum yield was found % observed at 4% NaOH and 3.5% NaOCl Minimum yield (22.655%) was found at 3% NaOH and 3.25% NaOCl. When these plots had drawn with keeping HCl concentration constant at 1N, it is seen that yield was higher at lower NaOH and lower at medium zone of NaOCl concentration. So, it can be observed that yield of chitosan varied with NaOH concentration as well as NaOCl concentration. It was also observed that when concentration of HCl and NaOH was reduced, yield increased. Higher NaOH concentration causes extensive deproteinization which lead to loss of yield and higher NaOCl concentration reduces viscosity that also has an effect on yield. When NaOH concentration was kept constant at 3.5%, yield was found at lower HCl concentrations and at somewhat higher NaOCl concentrations (Fig. 1). At constant NaOH concentration of 3.5%, highest yields 36.9% % were observed at the concentraons of 0.5N HCl and 3% NaOCl

205 FBC (%) FBC (%) FBC (%) WBC (%) WBC (%) WBC (%) Yield (%) Yield (%) Yield (%) A B C NaOH (%) NaOCl (%) HCl (N) NaOCl (%) HCl (N) (i) 4 NaOH (%) (ii) NaOH (%) NaOCl (%) HCl (N) NaOCl (%) HCl (N) NaOH (%) (iii) NaOH (%) NaOCl (%) HCl (N) NaOCl (%) HCl (N) NaOH (%) Fig. 1: 3-D response surface plots for all design conditions. (A) The effect of NaOH (%) and NaOCl (%) on predicted responses (yield (i), WBC (ii), and FBC (iii)) at constant HCl concentration of 1 N, (B) the effect of HCl (N) and NaOCl (%) on predicted responses at NaOH concentration of 3.5%, and (C) the effect of HCl (N) and NaOH (%) on predicted responses at a constant NaOCl concentration of 3.25%. In case of lowest yield, extensive demineralization at 1.25N HCl caused reduction of chitosan yield. Shrimp shell treated with 0.5N HCl and 3% NaOH showed maximum yield ( %) when NaOCl concentration was kept constant at 3 percent. From these 3-D surface plots of yields, it is clear that concentration of HCl is more effective on yield. However, NaOH also has an impact on yield WBC and FBC: Fig. 1(A-C; ii) represents effects of NaOCl, HCl and NaOH concentrations on water binding capacity. Opposite to yield, WBC was seen higher at higher HCl concentration. NaOH concentrations were not seen much effective when HCl concentrations were kept constant at 1N. However, at 3% NaOH with 1.5N HCl and 3.25% NaOCl, the predicted value of WBC was found maximum (349.34%). Minimum WBC (178.15%) was observed at 0.5N HCl and 3% NaOCl. It wasseen that in all three cases the lowest WBC (178.15) was obtained at 0.5N HCl and 3% NaOCl at constant 3% NaOH. Keeping NaOH concentration constant at 3 percent, highest WBC (349.34%) was observed when deproteinization was done with 1.5N HCl and decoloration with 3.25% NaOCl. These values were slightly contrasting with those reported by Rout (2001), where WBC for chitosan samples was found in the range from 581% to 1,150% with an average of 702%. The inclusion of decoloration step during the production of chitosan was found to decrease the water binding capacity of chitosan produced from shrimp (Moorjani, 1975). From the 3-D surface plots for FBC [Fig. 1(A-C (iii)), it was found that fat binding capacity increased with increased HCl concentration and NaOCl. Higher acid concentration had a positive effect on FBC. Positive effect of HCl concentration and NaOCl on FBC was due to more 196

206 deproteinization and decoloration of chitosan respectively. Maximum FBC (560.78%) was found at 1.25N HCl, 3% NaOH and constant 3.25% NaOCl. For the vegetable oil (Soybean), the shrimp shell chitosan samples showed desirable FBC range from 445.3% to % which is in agreement with the values reported by No et al. (1998). 3.4 Overall optimization To observe the optimum conditions three contour plots for yield, WBC and FBC were drawn and only one plot (for yield) is shown in this article (Fig. 2). From the 3-D and contour plots it was found that maximum value of WBC and FBC were obtained at 1.5N HCl, 3% NaOH and 3.25% NaOCl. In contrast, maximum yield was found at lower HCl concentration (0.5N HCl, 3% NaOH and 3.25% NaOCl). However, at lower HCl color of the product was not commercially suitable (yellowish). Uses of 1.5N HCl slightly reduced chitosan production due to excessive deproteinization but produced white colored chitosan. Considering all the factors, 1N HCl for demineralization, 3% NaOH for deproteinization and 3.25% NaOCl was chosen as the optimum condition for better quality of chitosan where yield was much higher and chitosan color was commercially suitable. It was also observed that proper mixing helps in complete removal of minerals and protein from shrimp shell. Both mineral and protein content have significant effect on chitosan yield, quality and purity. NaOH concentration HCl concentration Fig. 2: Contour plot showing the values of yield at various operating conditions at a constant NaOCl concentration of 3.25 % (w/v) 4. CONCLUSIONS It was found that, between the two processes, process developed by No et. al 2000, showed better process parameters (reduced time and costs) and yield. The highest yield of chitosan was obtained at 1N, 3% and 3.25% acid, alkali and bleach, respectively. It was also found that both high concentration of acid and alkali reduced the yield of chitosan due to excessive demineralization and deproteinization. Agitation also plays an important role on yield. Continuous mechanical agitation in contrast with hand starring is also responsible for high deproteinization. On the other hand higher fat and water binding capacity was found at high alkali concentration and bleach. But the higher concentration of acid had negative effect on yield of chitosan. For this reason, the concluded optimum condition would be suggested as 1N HCl, 3% NaOH and 3.25% NaOCl. However, optimization should be done based on the end use of chitosan. 5. REFERENCES 1. Black, C.A. (1965), Methods of Soil Analysis: Part I physical and mineralogical properties. American Society of Agronomy. Madison, Wisconsin. 2. Box, G.E.P. and Behnken, D.W. (1960), Some new three level designs for the study of quantitative variables Technometrics. 2, pp Cauchi, H.M. (2002), Chitin Production by Arthropods in Hydosphere, Hydobiologia, 470(1-3), pp Green, J.H. and Kramer, A. (1984), Food Processing Waste Management, AVI publishing Co., Westport, CT, Johnson, E.L., and Peniston, Q.P. (1982), Utilization of shellfish waste for chitin and chitosan production. In: Martin, RE., Flick, G.J., Hebard, C.E. and Ward, D.R., eds. Chemistry and Biochemistry of marine food products. AVI Pub. Co., Westport, CT, pp Knorr, D. (1984), Use of chitinous polymers in food- A challenge for food research and development. Food Technol. 38(1), pp Moorjani, M.N., Achutha, V. and Khasim, D.I. (1975), Parameters affecting the viscosity of chitosan from prawn waste. J. Food Sci. Technol., 12, pp Muzzarelli, R.A.A. (1996), Chitosan-based dietary foods. Carbohyr. Polym., 29, pp Naznin, R. (2005), Extraction of Chitin and Chitosan from Shrimp (Metapenaeus monoceros) Shell by Chemical Method. Pakistan Journal of Biological Sciences. 8 (7), pp No, H.K. and Meyers, S.P. (1989), Recovery of amino acids from seafood processing Waste water with a dual chitosan-based ligand- 197

207 exchange system. J. Food Sci., 54(1), pp No, H.K., Meyers, S.P. (1992), Utilization of Crawfish Processing Wastes as Carotenoids, Chitin, and Chitosan Sources. Journal Korean Soc. Food Nutrition, 21(3), pp No, H.K., Lee, K.S., Meyers, S.P. (2000), Correlation Between Physicochemical Characteristics and Binding Capacities of Chitosan Products. Journal of Food Science. 65(7). pp Ragonese, R., Macka, M., Hughes, J., Petocz, P. (2002), The use of the Box-Behnken experimental design in the optimisation and robustness testing of a capillary electrophoresis method for the analysis of ethambutol hydrochloride in a pharmaceutical formulation, J Pharm. Biomed. Anal., 27, pp Roberts, G. A. F. (1997), Chitosan production routes and their role in determining the structure and properties of the product. In : Domard, et al. (eds.) Advance in Chitin Sci. Vol. 2 Taiwan, National Taiwan Ocean University, pp Shahidi, F.; Abuzaytoun, R. (2005), Chitin, chitosan, and co-products: chemistry, production, application, and health effects. Adv. Food Nutr. Res., 49, pp Sheikh M. E. Babar, Song E.J and Hasan M.N., and YOO Y.S. (2007), Experimental design optimization of the capillary electrophoresis separation of leucine enkephalin and its immune complex, J. Sep. Sci., 30, pp Tharanathan, R.N.; Kittur, F.S. (2003), Chitin - the undisputed biomolecule of great potential. Crit. Rev. Food. Sci. Nutr., 43, pp Wang J. C, and Kinsella J. E. (1976), Functional properties of novel proteins: alfalfa leaf proteins. J Food Sci., 41, pp

208 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh MOLECULAR SIMULATION OF ANTIBODY-ANTIGEN INTERACTIONS USING 3D HOMOLOGY MODELLING AND DOCKING Mohidus Samad Khan 1*, M.A. Whitehead, and Theo G.M. van de Ven Department of Chemistry, McGill University University Street, Montreal, Quebec, H3A 2A7. Canada 1 Current Address: Department of Chemical Engineering, Bangladesh University of Engineering and Technology (BUET). Dhaka-1000, Bangladesh. Antibody-antigen interactions play a major role in many biological systems and can be used in sensors to capture target molecules. However, the antibody-antigen interactions especially on cellulosic materials are poorly understood. Computational methods offer access to molecular details that are inaccessible by experiment and predict chemical properties cheaply and quickly in silico, unlike expensive, difficult and time-consuming experiments. Antibody 3D homology modelling and antigen-antibody docking calculation followed by Quantum Mechanical calculation can be highly useful to understand antibody structure and binding mechanism. Picloram (4-Amino-4 3,5,6-trichloropyridine-2-carboxylic Acid) and anti-picloram binding fragments (Fab) were studied in this way. The 3D Molecular Modelling of Picloram and anti- Picloram Fab interactions allowed the structural, electronic properties and energies of Picloram interaction with possible binding sites at different ph to be calculated. The electronic properties and energies show that strong interaction occurs at ph 7 and not when acidic. Understanding the interaction mechanism can be useful in developing and regenerating antibody based sensors and filtration systems. Besides antibody based filtration technique, molecular study of antibody-antigen interactions at different ph can be useful in detoxification of drug or toxic chemicals from the human body. 1. INTRODUCTION Antibodies have a wide range of applications that include immunochemistry, medical diagnostics, antibody based therapeutics, antibody based electrochemical sensors, paper filters and sensors to detect and deactivate pathogens and unwanted chemicals in water and bio-fluids (Pelton 2009, Venkataprasad 2009, Khan, Thouas et al. 2010). However, the biotechnology industry has a limited understanding of the antibody-antigen interactions at different ph conditions on cellulosic materials which are important in medicine and pharmaceutical industries (Venkataprasad 2009, Khan, Thouas et al. 2010). (Young 1984, Mikkelsen and Corton 2004). Antibody contains two heavy chains and two light chains of amino acids and has antigen binding fragments (Fab) that contain six specific zones, complementary determining regions (CDR): CDR L1-L3, and CDR H1-H3 (Elgert 2009). These CDRs are antigen binding sites. Computational chemistry is used to understand antibody structure and antibody-antigen binding in-vivo and in-vitro (Sivasubramanian, Sircar et al. 2009, Kuroda, Shirai et al. 2012). X-ray crystallography and nuclear magnetic resonance are robust experimental techniques to determine Antibody structures, but are laborious, expensive and time consuming (Sircar, Kim et al. 2009, Almagro, Beavers et al. 2011). The 3D structure data of proteins, antibodies and nucleic acids are stored in Protein Data Bank (PDB) ( (2012), available as PDB file format. Currently about 85,600 PDB files are available with an approximate increasing rate of 8,000 per year (2012), which is less than % of the billions of different antibodies human body can possibly generate (Fanning, Connor et al. 1996). Consequently, 3D homology modelling is the state of the art in structure-based protein engineering applications (Sivasubramanian, Sircar et al. 2009, Almagro, Beavers et al. 2011). Homology based protein simulation programmes can predict 3D antibody structures (Almagro, Beavers et al. 2011). These homology models search different identical fragments of the 3D antibody structures from the PDB database and join them to create the primary antibody structure. The primary model is optimized 199

209 using different Molecular Mechanical Force Fields (Sircar, Kim et al. 2009, Almagro, Beavers et al. 2011); a few programmes provide the option to use Quantum Mechanics theories to optimize the very long chains of CDR H3 (Almagro, Beavers et al. 2011, 2012, Kuroda, Shirai et al. 2012). Possible antigen binding sites are identified from the optimized antibody structure, and antibody-antigen interactions are analyzed from antibody-antigen docking (Sivasubramanian, Sircar et al. 2009, Almagro, Beavers et al. 2011, Kuroda, Shirai et al. 2012). We calculated antibody-antigen interactions using molecular mechanics (MM) followed by quantum mechanics (QM). MM predicts large molecular structures, possible molecular interactions at a specific region and initial starting point geometries for QM calculations. MM calculation requires a significant lower computation time. However, MM theories do not consider electrons in modelling calculation, which actually hold all molecules together. QM calculates the energy of state and electronic properties of the interacting molecules. The major limitation of QM methods is that they require longer computing time (Lewars 2011). Molecular simulation combining MM and QM can be highly useful to accurately understand antibody structure and mechanism efficiently. This theoretical study will guide experimental studies to develop and regenerate an antibody based filtration technique (Deschamps, Hall et al. 1990, Tang, Zeng et al. 2008, Venkataprasad 2009, Chen, Zeng et al. 2010), and to detoxify drugs and other toxic chemicals from the human body (Benet, Spahn- Langguth et al. 1993, Zhang, Mack et al. 1998, Strazielle, Khuth et al. 2004). Chen, Zeng et al. 2010). Hall et al identified the amino acid sequence of the anti-picloram Fab (Tang, Zeng et al. 2008, Chen, Zeng et al. 2010) (Figure S1; supplementary information). The Molecular Operating Environment 2011 (MOE ) programme developed by Chemical Computing Group (2011) was used to model the 3D structure of Picloram antibody, to identify possible binding sites, to analyze antibody-antigen interactions using antibody-antigen docking, and to predict the best antibody-antigen interaction. The MOE Antibody Moduler provides a flexible and automated graphical interface for antibody homology modelling. From MOE calculation the interacting antigen (Picloram) and antibody receptor atoms were extracted to run the Semi-Empirical Quantum calculation PM6, which takes less computational time than ab initio (Lewars 2011). GaussView and Gaussian 09W programmes were used to run PM6 calculations. The interaction energies and electronic properties like delocalized molecular orbitals (DLMO) and electrostatic potentials (ESP) of PM6 calculated molecules were analyzed to identify the favourable and unfavourable interaction conditions. (a) A separate blind test was performed using Picloram and three other Picloram-like molecules: Fluroxypyr, Aminopyralid and Clopyralid, to validate the calculation methodology. The theoretical results were found to be consistent with the experimental results. The blind test results to validate the MOE calculation methodology are not shown in this study and will be discussed in a separate article. 2. METHOD The antibody-antigen interactions at the molecular level are applied to Picloram (4-Amino-3,5,6- trichloropyridine-2-carboxylic Acid) and Picloram antibody. Picloram, a long lived herbicide can enter the fresh water supply and may cause health and environmental problems. Antibody based electrochemical sensors and paper filters can detect and remove Picloram (Tang, Zeng et al. 2008, (b) Fig. 1: (a) Used PDB templates for different antibody fragments: frames (FR) and complementary determining regions (CDR); structure scores based on sequence similarity are given in parenthesis. (b) Protonate 3D model of anti-picloram 200

210 3. RESULTS AND DISCUSSION To model the 3D anti-picloram Fab structure, a knowledge-based approach was employed by using the built-in PDB database of MOE (2011, Almagro, Beavers et al. 2011). The known amino acid sequence of anti-picloram Fab was used to search homologous templates from the PDB database. The template search uses a sequence-toprofile alignment algorithm which ranks the templates by a structural score on the basis of the sequence similarity and identity. The structure scores range from 0 (not suitable for homology modelling purpose) to 100 (ideal protein structure) (2011). To build up 3D anti-picloram Fab, top scoring PDB templates for individual frames (FR) and CDR loops were chosen for light and heavy chains. The structure scores for top scoring variable heavy chain (VH) varied from 87.9% to 99.4%; and for the light chain (LH) templates the top score varied from 85.4 % to 98.9% (Fig. 1a). Structure scores higher than 85% ensure the selection of antibody templates with physically realistic backbone structures. Once the top scoring homologous FR and CDR templates were found, the respective loop templates were joined accordingly (Fig. 1b), followed by optimization using Merck Molecular Force Field theory (MMFF94x) (Halgren 1996, 2011, Almagro, Beavers et al. 2011). The energy of MMFF94x optimized structure for ph 7 was found kcal/mol. The solvation effect on the optimized structure at ph 7 was considered, and the ionizaiton states and hydrogen positions in the optimized 3D structure were assigned using the Protonate 3D option (2011). After using this option, the energy of the modelled antibody at ph 7 was kcal/mol. The MM calculation does not necessarily give accurate energies, however, the energy difference ( kcal/mol) qualifies more stable antibody structure considering the solvation effect. Fig. 2: (a) φ-ψ Plot of modelled anti-picloram Fab: green points indicate core regions and yellow points indicate allowed regions; (b) CDRs positioned in Fab backbone. (c) Possible binding sites coloured in electrostatic surfaces: red colour is indicating negative regions and blue is positive. (d) Picloram interaction at binding site 7. (e) Picloram interaction in receptor atoms pocket. (f-g) Picloram interaction with receptor atoms of CDR H2 (Asn 61, Lys 63), CDR L3 (Trp 115) and VH FR (Trp 47). (h) Electrostatic Potential (ESP) surfaces of the Picloram-receptor atoms complex showing Picloram is held inside the pocket using electrostatic interactions; red colour is indicating negative regions and blue is positive. 201

211 The structural stability of the modelled Fab was also verified from the Phi(φ)- Psi(ψ) Plot, Ramachandran Plot (Ramachandran, Ramakrishnan et al. 1963) (Fig. 2a), which checks the stereochemical quality of a protein structure. The data points of the backbone torsion angles φ and ψ tend to cluster in favourable core regions (inside green lines) and allowed regions (inside yellow lines); the white areas are unfavourable regions because of steric hindrance. Fig. 2b shows the CDRs in the backbone structure of the modelled antibody Fab. The binding sites available in the 3D Fab structure were identified using MOE , which uses geometric methods to locate "Pockets" without the use of energy models (2011). Fig. 2c shows the van der Waals surfaces of the binding sites mapped with positive and negative regions, which are coloured in red and blue. The geometric positions and CDR receptor atoms of all possible binding sites were analyzed. Binding site 1, 2, 3, 7, 8 were adjacent to or surrounded by CDR receptor atoms. Other possible binding sites, such as 4, 5, 6, 9, 10, 11were not related to CDR receptor atoms; therefore, these sites were excluded for further calculations. After the preliminary sorting out possible binding sites, the Picloram interactions were investigated at different binding sites using the Docking technique. For each binding site, a number of possible orientations of Picloram, generated by MOE , were manually placed inside the pocket to allow them to interact with the binding site receptor atoms. To calculate the optimal interactions from docking, the van der Waals interactions, electrostatic interactions, hydrophobichydrophilic interactions, hydrogen bonding, and interaction energies were considered. From the analysis of 120 Picloram-receptor atom interactions the best fit interaction was found, which was at binding site 7 surrounded by CDR H2 and L3 (Fig. 2d). The Picloram fits properly inside the van der Waals surface of the binding site (Fig. 3). Fig. 2e shows that the Picloram is positioned inside the binding pocket with compatible electrostatic interactions (i.e. Picloram s positive ends interact to receptor atoms negative ends and vice versa), hydrophobic-hydrophobic interactions and polarpolar interactions. Fig. 2f shows the ligand interactions with different residues of the receptor atoms: Asparagine (Asn 61) and Lysine (Lys 63) of CDR H2, Tryptophan (Trp 115) of CDR L3 and Tryptophan (Trp 47) of VH FR. To validate the above mentioned methodology to predict antigen-antibody interaction, a separate blind test was performed. In the blind test, Picloram and three other Picloram like molecules: Fluroxypyr, Aminopyralid and Clopyralid, were allowed to interact with the binding sites of anti- Picloram Fab, and the interaction results were analysed using the MOE programme without knowing the experimental results beforehand. From the MOE modelling results, Picloram and Picloram like molecules were ranked on the basis of the probability to interact with anti-picloram Fab, where Picloram and Clopyralid were more likely to interact with anti-picloram Fab, and Aminopyralid was most unlikely to interact with anti-picloram Fab followed by Flurozypyr; i.e. the rank would be: Picloram, Clopyralid, Fluroxypyr and Aminopyralid. The proposed rank from theoretical calculation was verified against the experimental results supplied by the partner research group (Chris Hall Lab, Guelph University) (Hall, Deschamps et al. 1989, Almquist, Niu et al. 2004). The theoretical results were found to be consistent with the experimental results. The blind test to validate the MOE calculation methodology will be discussed in a separate article. (a) (c) (b) (d) Fig. 3: Picloram docking inside receptor atoms. (a) Picloram position inside receptor atoms van der Waals surface; (b) Picloram position inside receptor atoms electrostatic surface; (c) Picloram s electrostatic surface interaction with receptor s electrostatic surface; (d) Picloram s hydrophobichydrophilic surface interaction with receptor atom s hydrophobic-hydrophilic surface.

212 After identifying the favourable Picloram-receptor atoms interaction, the receptor atoms and Picloram structures were extracted from MOE to run a semi-empirical PM6 calculation. PM6 calculated energies for receptor atoms, Picloram, and Picloram interacting with receptor atoms at ph 7 were , , and kcal/mol, respectively. To understand the Picloram-receptor atom interaction, electronic properties such as DLMOs and ESPs were analysed. Fig. 2g shows the electrostatic potential (ESP) surfaces of the Picloram-receptor atoms interactions. The Picloram molecule was found well surrounded by the receptor atoms and held by electrostatic interactions. ESP surfaces of the Picloram and receptor atoms before and after interactions are shown in Fig. 3. DLMOs of Picloram-receptor atoms interactions were analysed, and no strong electron overlap was found, either in the lowest unoccupied molecular orbital (LUMO) or the highest occupied molecular orbital (HOMO). However, a slight overlap of DLMO wave functions was found at different energy levels (not shown here). Table 1: Semi-Empirical PM6 calculated Picloram and anti-picloram Fab interaction energy (kcal/mol) under different ph conditions Energies (kcal/mol) Picloram interacting with receptor atoms (E ligand+receptor atoms) Receptor Atoms (E receptor atoms) Interaction Energy, E (E ligand+receptor atoms (E ligand + E receptor atoms)) ph Picloram Condition (E ligand) Neutral Alkaline Acidic The PM6 calculation was also conducted on the MOE extracted molecules for alkaline (high ph) and acidic (low ph) conditions and the interaction energies were calculated (Table I). The side chains of the residue molecules were protonated and deprotonated to match with changed ph. Table I shows that the Picloram and anti-picloram Fab interaction is more stable at ph 7 (E ph 7 = kcal/mol) and highly unstable at acidic condition (E Acidic = kcal/mol). Consequently, these calculations can be useful in developing antibody based filtration systems to filter Picloram and Picloram like chemicals. At neutral ph, the antibody based filter will capture Picloram. Once the filter is saturated, a back wash with acidic solution will release Picloram and regenerate the filtration system for reuse. These calculations confirm the experimental results from a separate study (Venkataprasad 2009). Besides the antibody based filtration technique, molecular studies of antibody-antigen interactions at different ph can be useful in detoxification of drug or toxic chemicals from the human body. 4. CONCLUSIONS Molecular modelling of Picloram and anti-picloram Fab interactions at different phs were calculated using 3D homology modelling, force field theory and quantum mechanical calculation. This method allowed understanding the structural and electronic properties of antibody-antigen interactions at possible binding sites, and to calculating the antibody-antigen interaction energies at different ph conditions. The electronic properties and energies show that a strong interaction of Picloram and anti-picloram Fab occurs at ph 7 but not when acidic. This information can be useful in developing and regenerating antibody based sensors and filtration systems. ACKNOWLEDGEMENT This research was supported by SENTINEL Bioactive Paper Network funded by the NSERC- CRSNG, and an NSERC Discovery Grant. Authors acknowledge SENTINEL Bioactive Paper Network for funding, and Drs. Chris Hall and Chris Williams for useful discussion. REFERENCES 1. (2011). Molecular Operating Environment (MOE), Montreal, QC, Canada, H3A 2R7, Chemical Computing Group Inc. 2. (2012). "RCSB PDB Protein Data Bank: An Information Portal to Biological Macromolecular Structures." Retrieved Nov 05, 2012, from 3. Almagro, J. C., M. P. Beavers, F. Hernandez- Guzman, J. Maier, J. Shaulsky, K. Butenhof, P. Labute, N. Thorsteinson, K. Kelly, A. Teplyakov, J. Luo, R. Sweet and G. L. Gilliland (2011). "Antibody Modeling Assessment." PROTEINS: Structure, Function, and Bioinformatics 79(11): Almquist, K. C., Y. Niu, M. D. McLean, F. L. Mena, K. Y. F. Yau, K. Brown, J. E. Brandle and J. C. Hall (2004). "Immunomodulation confers herbicide resistance in plants." Plant Biotechnology Journal 2(3): Benet, L. Z., H. Spahn-Langguth, S. Iwakawa, C. Volland, T. Mizuma, S. Mayer, E. Mutschler and E. T. Lin (1993). "Predictability of the covalent binding of acidic drugs in man." Life Sciences 53(8): PL141-PL

213 6. Chen, L., G. Zeng, Y. Zhang, L. Tang, D. Huang, C. Liu, Y. Pang and J. Luo (2010). "Trace Detection of Picloram Using an Electrochemical Immunosensor Based on Three-Dimensional Gold Nanoclusters." Analytical Biochemistry 407(2): Deschamps, R. J. A., J. C. Hall and M. R. McDermottg (1990). "Polyclonal and Monoclonal Enzyme Immunoassays for Picloram Detection in Water, Soil, Plants, and Urine." Journal of Agriculture and Food Chemistry 38(9): Elgert, K. D. (2009). Immunology: Understanding The Immune System, Wiley- Blackwell. 9. Fanning, L. J., A. M. Connor and G. E. Wu (1996). "Short Analytical Review: Development of the Immunoglobulin Repertoire." Clinical Immunology and Immunopathology 79(1): Halgren, T. A. (1996). "Merck Molecular Force Field. I. Basis, Form, Scope, Parameterization, and Performance of MMFF94*." Journal of Computational Chemistry 17(5&6): Hall, J. C., R. J. Deschamps and K. K. Krieg (1989). "Immunoassays for the detection of 2, 4-D and picloram in river water and urine." Journal of agricultural and food chemistry 37(4): Khan, M. S., G. Thouas, W. Shen, G. Whyte and G. Garnier (2010). "Paper Diagnostic for Instantaneous Blood Typing." Analytical Chemistry 82(10): Kuroda, D., H. Shirai, M. P.Jacobson and H. Nakamura (2012). "Computer-aided antibody design." Protein Engineering, Design & Selection 25(10): Lewars, E. G. (2011). Computational Chemistry: Introduction to the Theory and Applications of Molecular and Quantum Mechanics. New York, Springer. 15. Mikkelsen, S. R. and E. Corton (2004). Bioanalytical Chemistry. New Jersey, John Wiley & Sons, Inc., Publication. 16. Pelton, R. (2009). "Bioactive Paper Provides a Low-Cost Platform for Diagnostics." Trends in Analytical Chemistry 28(8): Ramachandran, G. N., C. Ramakrishnan and V. Sasisekharan (1963). "Stereochemistry of polypeptide chain configurations." Journal of Molecular Biology 7(1): Sircar, A., E. T. Kim and J. J. Gray (2009). "RosettaAntibody: Antibody Variable Region Homology Modeling Server." Nucleic Acids Research 37(Web Server issue): W474-W Sivasubramanian, A., A. Sircar, S. Chaudhury and J. J. Gray (2009). "Toward High-Resolution Homology Modeling of Antibody Fv Regions and Application to Antibody-Antigen Docking." PROTEINS: Structure, Function, and Bioinformatics 74(2): Strazielle, N., S. T. Khuth and J.-F. o. Ghersi- Egea (2004). "Detoxification systems, passive and specific transport for drugs at the blood- CSF barrier in normal and pathological situations." Advanced Drug Delivery Reviews 56(12): Tang, L., G.-M. Zeng, G.-L. Shen, Y.-P. Li, Y. Zhang and D.-L. Huang (2008). "Rapid Detection of Picloram in Agricultural Field Samples Using a Disposable Immunomembrane-Based Electrochemical Sensor." Environmental Science & Technology 42(4): Venkataprasad, C. (2009). Adsorption of Herbicides and Bacteria Using Pulp Fibers. Master of Applied Science, Master of Applied Science Thesis, Concordia University. 23. Young, C. R. (1984). Structural Requirements for Immunogenicity and Antigenicity. Molecular Immunology. M. Z. Atassi, C. J. V. Oss and D. R. Absolom. New York, Marcel Dekker, Inc.: Zhang, K., P. Mack and K. P. Wong (1998). "Glutathione-related mechanisms in cellular resistance to anticancer drugs." International journal of oncology 12(4):

214 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh DETECTION OF CAUSALITY BETWEEN INDUSTRIAL ALARM DATA BASED ON TRANSFER ENTROPY Weijun Yu and Fan Yang* Tsinghua National Laboratory for Information Science and Technology Department of Automation, Tsinghua University, Beijing , P.R.China In modern industrial processes, more and more alarm variables are configured, and there may exist interactions, in particular causal relationships amongst them, and thus it is difficult for operators to identify the root cause immediately once an abnormal situation occurs. Therefore, causality detection based on alarm series becomes a very important problem. Transfer entropy is an effective way to detect causality between different continuous variables. However, this method is computationally costly. Alternatively, alarm data can be used directly for computation of transfer entropy to identify the causality between variables because alarm data analysis is straightforward for alarm management with less computational cost in practice. This proposed method is suitable for the industrial situations contaminated by noise. 1. INTRODUCTION In modern industrial processes, more and more physical quantities become measureable and monitored by DCS or other monitoring systems. Thus almost every variable can be configured to have at least one alarm. As a result the number of alarm variables is often quite large and hence a large number of alarms are raised in a disorderly manner during an abnormal situation. Moreover, there are complex interactions between these alarm variables due to the process dynamics and the design of the associated monitoring systems. In addition, once an abnormal situation occurs at some place in the process, the fault will spread quickly to other units of the process because of the internal interactions. This will eventually lead to the so-called alarm flooding phenomenon. In such a situation, operators cannot identify the type of the fault or find the root cause of it. This may lead to serious and catastrophic events. For example, in 1994, before an explosion accident happened in a fluid catalytic cracking unit of a refinery of British Texaco Company, there were 1775 alarms occurred in a short time period, which operators failing to take effective actions and led to a major accident (Yang and Xiao, 2011). There are different ways to reduce the number of alarms. Yang et al. (2012, 2013) used signed direct graphs to identify the process topology and connectivity and help us in fault diagnosis and process hazard assessment. Noda et al. (2011) and Yang et al. (2012) used event correlation analysis to design a policy to reduce alarms and operations. Another more common way is using causality information between alarm variables. In this way, we can find the propagation path of the fault and help operators identify the root cause (Hollender and Beuthel, 2007). This enables operators to take effective preventative actions immediately. Thus the detection of the causality between variables becomes very important. Schreiber (2000) defined Transfer Entropy (TE) to describe the causality between variables. Transfer Entropy has since been successfully used on industrial data to identify causal relationships between process variables (Bauer et al., 2007). Recently, Duan et al. (2013, 2014) extended the traditional concept of TE and make it more useful, especially for multivariate cases. Yang et al. (2014) and Duan et al. (2014) also summarized these methods for capturing causality in industrial processes. However, TE has primarily been used on continuous time series, which can describe the whole characteristic of the process but is computationally quite expensive. In the context of alarm management, we are more concerned about causality under abnormal situations rather than the exact dynamic relationships under normal situations. Therefore, it is unnecessary to take all cases (all the situations and all the process data) into account and * Corresponding Author: Fan Yang, yangfan@tsinghua.edu.cn

215 alarm data process data focus on processing of data in abnormal situations (typically processing alarm data). In addition, because some alarm variables themselves are not generated by continuous variables, such as switch variables (e.g., ON/OFF) and state variables, a discrete version of TE can be applied. Considering the computational cost and the above issues, we can detect the causality between variables using alarm data directly. 2. TRADITIONAL CONCEPT OF TRANSFER ENTROPY The basic definition of TE raised by Schreiber to detect the causality from I to J is as follows: ( k) ( l) ( k) ( l) p( it 1 it, jt ) TEJ I p( it 1, it, jt )log 2 ( k ) p( it 1 it ) where p() represents the probability density function, p( ) represents the conditional probability density function, i t represents the value of I at time t, k or l in the super script represent taking k or l historical variable values in the series before time t. Here the numerator of the logarithm part represents the prediction result of the value of I when we know historical data of I and J; the denominator of the logarithm part represents the prediction result of the value of I when we only know the historical data of I itself. The thought of TE is that if there exist causality from J to I, it will be helpful to predict the value of I using the historical data of J, then the value of the numerator should be larger than the value of the denominator and the value of the whole calculation equation should be larger than zero; if there don t exist causality from J to I, the value of the whole equation should be close to zero. remove the causality between series, we can use the result as the corresponding threshold. In the experiment, we can repeat the procedure several times and use the average μ λ as the threshold. When the calculation result is greater than the threshold by some σ λ, we can conclude that there exists significant causality from J to I. 3. TRANSFER ENTROPY BASED ON ALARM DATA 3.1 Alarm Series and Data Preprocessing We suggest using alarm series or event series. Each digit in the series is 0 or 1, where 0 represents that there is no alarm at present and 1 represents that there is an alarm at present. In the neuroscience area, Ito et al. (2011) also used binary electrical signal series to detect causality. But there are different characteristics of binary series in different areas. Firstly, electrical signals in the neuroscience area always exist in a very short time, so the series is very sparse and people put more emphasis on the beginning time of signals; while alarms in the industrial process often last for a period of time and once an abnormal situation occurs, the alarms will probably be intensive. On the other hand, electrical signals in the neuroscience area are usually clean, while there are often some false alarms and missed alarms in industrial processes because of noise (Noda et al., 2011), just as shown in Fig. 1. Thus we need some data preprocessing before using industrial data for analysis. When we use TE, two conditions should be maintained: (1) there should be enough relevant data points to predict the probability density function of data and (2) the time series used should be stable, which means the mean and the covariance of the series will not change with time (Girod et al., 1990, Li, 1999). sample time Generally speaking, the value of TE will not be exact zero because of noise, so we need a threshold to identify when we can conclude there is causality from J to I. In order to obtain such threshold, Kantz and Schreiber (1997) suggested using Monte Carlo method with surrogate data. When using this method, we keep the number of alarms in series J but change the sequence and occurrence times of these alarms randomly, which can generate a surrogate series J. We then calculate TE using I and J and get a result. Since the locations of alarms in J are randomly generated, which can theoretically sample time Fig. 1: False alarms and missed alarms generated by noise (false alarm at t=7, missed alarm at t=62) The preprocessing we use here mainly includes: (1) Remove those alarms with no other alarms before or after them over a long period of time 206

216 processed signal original signal (2) Put some more signals around those alarms which last for a long time before recovering (Kondaveeti et al., 2013). With such data preprocessing, we can reduce the number of false alarms and missed alarms, as shown in Fig. 2. appropriate thresholds, as shown in Fig. 3. X Y Z sample time Fig. 3: Measured values of X, Y, Z and the corresponding alarm series We can know from (1) that there exists direct causality from X to Y and Y to Z, and indirect causality from X to Z. But there is no causality from Y to X, Z to Y or Z to X. Fig. 2: False and missed alarms removed by pre-processing 3.2 Procedure of Proposed Method The procedure of the method to detect causality between industrial alarm series based on TE is shown as follows: a. Obtain the original series; b. Preprocess data and obtain series I, J; c. Calculate the TE from J to I; d. Calculate the corresponding threshold: d1. Based on J, obtain a surrogate series J ; d2. Calculate the TE from J to I; d3. Repeat d1, d2 and use the average result as the threshold; e. Compare the result in c with the threshold in d. If the result is larger than the threshold, there exists causality from J to I; if the result is smaller than the threshold, there does not exist causality from J to I. 4. CASE STUDY sample time 4.1 Numerical case The first case is described by a numeral equation as follows: Yk 1 0.8X k 0.5Y k v1 k (1) Zk 1 0.6Y k v2k where X, Y and Z are three continuous random variables, Xk ~ N (0,1), v1 k, v2k ~ N (0, 0.1), X is abnormal in two periods of time, and Y and Z can be calculated. Convert these variables into binary alarm series with If we calculate the TE result using original alarm series, we can get the result in Table 1. Here the numbers in brackets are the corresponding thresholds, and the numbers with underlines mean that the result is greater than the corresponding threshold and we can conclude that there exists significant causality. col Table 1. Directly calculated TE results and the corresponding thresholds TE X Y Z row X N/A (0.0005) (0.0009) Y (0.0009) N/A (0.0004) Z (0.0005) (0.0011) N/A We can see that the results in Table 1 do not fit (1) very well. If we do the preprocessing first, the result is shown in Table 2. We can see that the result indicates the causality from X to Y, Y to Z and X to Z, which fits (1) well. Table 2. Calculated TE results after pre-processing and the corresponding thresholds TE X Y Z col row X N/A (0.0007) (0.0011) Y (0.0010) N/A (0.0010) Z 0 0 N/A 4.2 Simulated case We have also used the Tennessee-Eastman Process (TEP) (Lawrence et al, 1996) to test the effectiveness of the method. The typical flow chart of TEP can be seen in Fig. 4. Because the whole TEP is too large, we choose some typical input-output variables. A portion of TEP flowsheet with control loops is shown in Fig

217 The chosen input-output variables are: (1) Feed A valve input and feed A output; (2) Feed A valve input and feed D output; (3) Reactor cooling water flow valve input and reactor temperature output. We can see from Figs. 4 and 5 that these inputs are shown with blue circles and theses outputs are shown with red circles. Fig. 5: Portion of TEP flowsheet with control loops 5. CONCLUSIONS We have applied the TE method to detect causality using industrial alarm data and make some improvements according to the industrial characteristic. From the results of the case study, the proposed method is shown to be effective. This study is preliminary. However, because the method is computational-friendly and alarm series face alarm management applications, the study has a wide perspective. Fig. 4: Flow chart of TEP We can see from Fig. 5 that among these input-outputs, there is a feedback loop between feed A valve and feed A, so there exists causality between them on both directions; there does not exist causality between feed A valve and feed D; there exists causality from reactor cooling water flow valve to reactor temperature output, because the former one controls the latter one. The calculated results are shown in Table 3: Table 3 Calculated results of TEP Groups TEI O TEO I (0.0002) (0.0003) (0.0000) (0.0001) (0.0003) We can see that the results are consistent with our expectation, which means the method is effective. ACKNOWLEDGMENTS We would like to express our acknowledgments to the National High-tech R&D Program of China (2013AA040702) and ABB Technology Ltd. for the financial support. REFERENCES 1. Yang, F. and Xiao, D. (2011), Research topics of intelligent alarm management, Computers and Applied Chemistry, 28(12), pp Yang, F., Shah, S.L., and Xiao, D. (2012), Signed directed graph modeling and validation of industrial processes by process knowledge and process data, International Journal of Applied Mathematics and Computer Science, 22(1), pp Yang, F., Xiao, D., and Shah, S.L. (2013), Signed directed graph-based hierarchical modelling and fault propagation analysis for large-scale systems, IET Control Theory and Applications, 7(4), pp Noda, M., Higuchi, F., Takai, T., and Nishitani, H. (2011), Event correlation analysis for alarm system 208

218 rationalization, Asia-Pacific Journal of Chemical Engineering, 6, pp Yang, F., Shah, S.L., Xiao, D., and Chen, T. (2012), Improved correlation analysis and visualization of industrial alarm data, ISA Transactions, 51(4), pp Hollender, M. and Beuthel, C. (2007), Intelligent alarming: Effective alarm management improves safety, fault diagnosis and quality control, ABB Review, 1, pp Schreiber, T. (2000), Measuring information transfer, Physical Review Letters, 85(2), Bauer, M., Cox, J.W., Caveness, M.H., and Downs, J.J. (2007), Finding the direction of disturbance propagation in a chemical process using transfer entropy, IEEE Transactions on Control Systems Technology, 15(1), pp Duan, P., Yang F., Chen, T., and Shah, S.L. (2013), Direct causality detection via the transfer entropy approach, IEEE Transactions on Control Systems Technology, 21(6), pp Duan, P., Yang, F., Shah, S.L., and Chen, T. (2014), Transfer zero-entropy and its application for capturing cause and effect relationship between variables, IEEE Transactions on Control Systems Technology, DOI: /TCST Yang, F., Duan, P., Shah, S.L., and Chen, T. (2014), Capturing Connectivity and Causality in Complex Industrial Processes, Springer. 12. Duan, P., Chen, T., Shah, S.L., and Yang, F. (2014), Methods for root cause diagnosis of plant-wide oscillations, AIChE Journal, 60(6), pp Girod, B., Rabenstein, R., and Stenger, A. (1990), Signals & Systems, Wiley, New York. 14. Li, X-R. (1999), Probability, random signals and statistics: A textgraph with integrated, Software for Electrical and Computer Engineers, CRC, Boca Raton, FL. 15. Kantz, H. and Schreiber, T. (1997), Nonlinear Time Series Analysis, Cambridge University Press, Cambridge, UK. 16. Ito, S., Hansen, M.E., Heiland, R., Lumsdaine, A., Litke, A.M., and Beggs, J.M. (2011) Extending transfer entropy improves identification of effective connectivity in a spiking cortical network model, PLoS One, 6(11), e Noda, M., Higuchi, F., Takai, T., and Nishitani, H. (2011), Event correlation analysis for alarm system rationalization, Asia-Pacific Journal of Chemical Engineering, 6, pp Kondaveeti, S.R., Izadi, I., Shah, S.L., Shook, D.S, Kadali, R, and Chen, T. (2013), Quantification of alarm chatter based on run length distributions, Chemical Engineering Research and Design, 91(12), pp Lawrence, R.N. (1996), Decentralized control of the Tennessee Eastman challenge process, Journal of Process Control, 6(4), pp

219 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh SIMULATION OF EASTERN REFINERY PROCESS Mohammad Hasibul Hasan, Tania Hossain, Quazi Azizul Hassan, Sabrina Khan and M. T. Sowgath* Bangladesh University of Engineering and Technology, Bangladesh Eastern Refinery Limited plays an important role in producing petroleum products in Bangladesh, producing almost 16 different petroleum products. Crude Distillation Unit is the energy intensive unit. Simulation of Crude Distillation Unit of Eastern Refinery Limited Company was carried out using Aspen Plus Process Simulator. Various design data have been taken from Eastern Refinery Limited. Aspen Plus model is developed and simulation data is validated. Different distillation curves obtained from the simulator are similar to the expected. 1. INTRODUCTION Petroleum plays an important role in meeting energy demand in different sectors in Bangladesh such as power generation sector, industrial sector, commercial sector (Haq et al., 2003). Eastern Refinery Limited, a subsidiary of Bangladesh Petroleum Corporation (BPC) went into operation in Arabian Light Crude (ALC) oil and Murban Crude (MC) oil are the main raw materials that are imported from KSA and Abu Dhabi. ERL produces 16 products from these crude oils. ERL produces mainly fuel products (ERL, 2014). Modeling and Simulation of Atmospheric distillation unit (ADU) play an important role in facing the challenges in plant operation and business challenge. Operability point of view such as higher feed rate, increased yield of high value product, return product quality giveaway and increased energy efficiencies subject to constant fluctuations in the raw material quality and other disturbances of the process units are studied by optimization. Imported raw crude properties are continually changing and the complexities of petroleum mixture process model needs to work for wide variety of mixture in a Crude Distillation Unit. Besides, Crude Distillation Unit is the energy intensive unit. Eastern Refinery faces challenges for the decade due to changes in market demand and supply of raw crude. Simulation of ERL model can play a role in facing those challenges. In this work, study of ERL is carried out using Aspen Plus simulator to maintain the product quality for ALC and MC blend. Aspen Plus model is developed and simulation data are validated. Different distillation curves obtained from the simulator are similar to the expected. Preliminary result shows that the model prediction of the columns in the Crude Distillation is close to that of plant operation. 2. PROCESS DESCRIPTION 2.1 Process Description The ERL refinery unit includes the major process units: Crude distillation unit, Catalytic reforming unit, Asphaltic bitumen plant, Long Residue Visbreaking unit and Mild hydrocracking unit. ADU is equipped with 33 trays and feed enters at 4th equivalent tray. Crude oil is preheated in a series of 9 heat exchangers passing through desalter unit and fed into furnace where it is heated to 366 o C to vaporize the feed partially. The partially vaporized feed is sent to the distillation column. From the top column TG is withdrawn and condensed and sent to reflux drum and from where off gas is flared. In reflux drum gasoline is refluxed to top column and part of it sent to stabilization column. Kerosene-I and Kerosene II are withdrawn from the 26th and 20th trays respectively and flown to the stripper column. LGO and HGO is withdrawn from tray no. 12 and 9 respectively and sent to the storage tank after treating. The atmospheric residue is stripped at the bottom of the distillation column. * Corresponding Author: M. Tanvir Sowgath, mstanvir@che.buet.ac.bd

220 Fig. 1: Eastern Refiner PFD in Aspen Plus 2.1 Aspen Plus Model All simulations were conducted using steady-state model developed under Aspen plus environment. BK-10 property package was selected as the thermodynamic fluid package. The simulation ERL model (Fig. 1) consists of pre-fractionation train used to heat the crude liquids, and an ADU to fractionate the crude into its straight run products. The liquids are heated to 350 o F in the crude furnace. ADU is the separation of hydrocarbons in crude oil into fractions based on their boiling points which lie within a specified range. The simulations have been performed using specifications such as product flow rate constraints and duties of condensers, pump-arounds and reboilers. True boiling point (TBP) curve was used to determine the behavior of the crude distilled product. Small variations in the true boiling point curve may have a significant impact on process control and overall profitability. The temperature at any point on the temperature-volumetric yield curve represents the true boiling point of the hydrocarbon material present at the given volume percent point distilled. 3. RESULT AND DISCUSIION In this work, the Atmospheric distillation unit (ADU) process ALC and MC (Table 1) and produces different products (Table 1). ALC possesses the specific gravity ranged from 0.84 to 0.86, whereas Murban has the specific gravity ranged 0.82 to % ALC and 20% MC blend is used. Table 1. Crude Feed Input Parameters Temperature ( o F) 460 Pressure (psia) 45 Flowrate (bbl/day) 100,000 Table 2. Different Products Gas Total Gasoline(TG) Light gasoline (LG) Heavy gasoline (HG) Kerosene-I Kerosene-II Light gas Oil (LGO) Heavy gas oil (HGO) Reduced crude oil From Fig. 2 to Fig. 6, the TBP curves were shown for crude feed, light product, naptha, kerosene, diesel and AGO respectively, where experimental means prediction by simulator and standard means standard value of the feed and product in literature. In each case, distilled volumetric rates with respect to temperature are increasing. These phenomena are consistent with standard phenomena. From these graphs, it can be seen that true boiling point of experimental value is slightly different from standard value. That is why the remaining curves were slightly different from the standard one. Curve of kerosene and diesel could be examples of this phenomenon. However, the main objective was fulfilled and experimental values were quite similar 211

221 to theoretical ones. The TBP of different products of our simulation was similar to the original higher grade products, whereas our simulated unit was simpler than the original ERL plant. The model does not contain the intermediate unit operation of ERL so our results for Kerosene and naphtha are not similar to experimental values. Fig. 5: True boiling point curve of Kerosene. Fig. 2: True boiling point curve of crude feed Prediction Fig. 6: true boiling point curve of Diesel. 4. CONCLUSIONS Fig. 3: True boiling point curve of light product. Aspen Plus model is developed and simulation data is validated. Different distillation curves (TBP) obtained from the simulator is similar to the expected. Preliminary result shows that prediction by Aspen plus of the product quality is close to literature value. However, Kerosene and naphtha related unit operation needs to be added to get similar trends. REFERENCES 1. Haq M.B., Gomes E. and Tamim M. (2003), Proceedings of the International Conference on Mechanical Engineering,(ICME2003), December 2003, Dhaka, Bangladesh 2. ERL (2014),Eastern Refinery Limited, viewed 30 November, 2014, < Fig. 4: True boiling point curve of Naptha. 212

222 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh DISPERSION MODELING OF ACCIDENTAL RELEASE OF CHLORINE GAS Rajesh Paul 1 *, Animesh Mondal 2, M.A.A. Shoukat Choudhury 1 Bangladesh University of Engineering and Technology (BUET), Dhaka, Bangladesh. 2 Auburn University, Alabama, United States This study investigates the impact of accidental release of Chlorine gas in surrounding areas. The impact is studied using standard dispersion modeling techniques considering various locations with different surface conditions (urban or rural) in different seasons and meteorological conditions. The affected areas which are harmful to human exposures at different levels are detected using Areal Locations of Hazardous Atmospheres (ALOHA) Software. The affected areas are divided into three level of concerns namely red zone, orange zone, yellow zone. Red zone is the affected area in which there is severe concentration of toxic gas and exposure to which may cause life threatening health effects or even death. Exposure to Orange Zone may cause long lasting adverse health effects and in Yellow zone average individual may feel notable discomfort, irritation but reversible upon cessation of exposure. The modeling was performed for an accidental release of 1.6 tons chlorine gas from a horizontal cylindrical tank lasting for one hour. For a typical summer atmospheric condition of Bangladesh, this accidental chlorine release would cause a red zone of 1.1 kilometers, orange zone of 3.6 kilometers and yellow zone stretching to 7.0 kilometers to downwind from the source. Variation in the different threat zones are observed in the article due to change in temperature, wind velocity and surface roughness (ground condition). 1. INTRODUCTION The airborne transport of toxic material away from the accident site is described by dispersion modeling. So, public safety responders and emergency management personnel use toxic gas dispersion models for emergency planning of accidental chemical releases. Bosanquet and Pearson (1936) derived the early air pollutant plume dispersion equations. However, they did not assume Gaussian distribution for pollutants dispersion. Sutton (1947) derived plume dispersion equation for pollutants by including the assumption of Gaussian distribution for the vertical and crosswind dispersion of the pollutant. Afterwards, Gaussian dispersion model has been modified by many researchers and computer programs have been developed using this model for calculating the dispersions of the pollutants. Eidsvik (1980) proposed heavy gas dispersion model for released gases that are heavier than air. Initial behavior of a heavy gas will be different from a neutrally buoyant gas. Initially a heavy gas will sink because it is heavier than the surrounding air. As the gas cloud moves downwind, it becomes diluted and its density reduces and it begins to behave like a neutrally buoyant gas. The results of dispersion modeling are used to determine the consequences of accidental releases of hazardous or toxic materials e.g. location of impacted areas, ambient concentrations. Labovský and Jelemenský (2010) presented CFD simulation by Fluent 6.3 for dispersion modeling of released ammonia from a pressurized storage tank. Labovský and Jelemenský (2011) also compared simulation results with the results obtained by Fladis field experiments (1997). Fladis field experiments were carried out by the Risø National Laboratory for liquefied ammonia leakage. Shuxia et al. (2012) analyzed the consequence of liquefied ammonia leakage on environment using software ALOHA (Areal Locations of Hazardous Atmospheres). In this study, chlorine (Cl 2 ) is considered a pollutant gas for dispersion modeling since it is one of the most commonly produced and used industrial chemicals in the world. It is a greenish yellow gas and heavier than air. Usually, it is pressurized and cooled for storage and shipment as liquid. In this study, Software ALOHA is used for dispersion modeling of released chlorine gas. It displays the estimation as three threat zones (red zone, orange zone and yellow zone), where toxicity of chlorine exceeded user-specified level of concern. In this study, Acute Exposure Guideline Levels (AEGLs) are used to define the toxicity level of concerns for three threat * Corresponding Author: Rajesh Paul, rajesh07@che.buet.ac.bd

223 zones with an exposure time of 60 minutes. ALOHA uses the heavy gas dispersion model to calculate the concentration of released chlorine. Chlorine gas is heavier than air and its initial behavior will be different from a neutrally buoyant gas. In this paper, section 2 describes dispersion techniques of the pollutants; software selection is discussed in section 3 and section 4 presents modeling of released chlorine in the surrounding areas for a hypothetical accident. The effects of wind velocity, temperature and surface roughness on dispersion is also observed in section DISPERSION TECHNIQUES The airborne transport of toxic material away from the accident site is carried away by the wind as a Plume or puff. The continuous release of a toxic material forms plume. In hydrodynamics, a plume is a column of one fluid moving through another. When a plume moves away from its source, it usually widens due to entrainment of the surrounding fluid at its edges. The motion of the fluid is controlled by wind velocity, buoyancy and momentum of the released material, ground condition, atmospheric conditions, and release height above the ground., The released material is carried downwind faster and a plume becomes larger and narrower whenever there exists higher wind velocity. On the other hand, puff model describes the temporal concentration of a material from the sudden release of a fixed amount of the material. A large vapour cloud moves downwind from the release point and dissipates by mixing with fresh air. For instantaneous release of a material of fixed mass into air, Equation 1, together with appropriate boundary and initial conditions, forms the fundamental basis for dispersion modeling (Crowl and Louvar, 2002). It is assumed that no reaction or molecular diffusion occurs. Where, c is the concentration of the material due to release, K j is the eddy diffusivity, u j is the air velocity and the subscript j represents the summation over all coordinate directions x, y and z. The x-axis is the centerline directly downwind from the release point and is rotated for different wind directions. The y-axis is the distance off of the centerline and the z-axis is the elevation above the release point. So, the point (x, y, z) = (0, 0, 0) is at the release point. 3. SOFTWARE SELECTION Among the wide varieties of available software the ALOHA has been used to calculate the concentration of the released chlorine. It is a program designed to model chemical releases for emergency responders and planners. ALOHA allows modeling of many release scenarios: toxic gas clouds, Boiling Liquid Expanding Vapor Explosions (BLEVE), jet fires, vapor cloud explosions and pool fires. Depending on the release scenario, ALOHA evaluates the corresponding type of hazard. ALOHA displays its estimate as a threat zone, which is an area where hazards (such as toxicity, flammability, thermal radiation or damaging overpressure) exceed a user-specified level of concern. It is possible to generate a variety of scenario-specific outputs, including threat zone plots, threats at specific locations and source strength graphs. ALOHA also defines its limitation clearly and state the reason behind. For example it cannot make predictions further than 10 kilometers downwind from a release point. There are several reasons that imposed this limitation on ALOHA. The primary reason for this cutoff is related to the equations ALOHA uses to predict threat zone length. 4. DISPERSION MODELING OF CHLORINE GAS Chlorine is used in different purposes such as bleaching agent, in the preparation of chlorides, chlorinated solvents, pesticides, polymers, synthetic rubbers and refrigerants. It is a greenish yellow gas and heavier than air. Chlorine is a respiratory irritant. The severity of health effects depend upon the route of exposure, the dose and the duration of exposure to Chlorine. Following chlorine exposure, the most common symptoms are: airway irritation, wheezing, breathing difficulty, sore throat, cough, chest tightness, eye irritation, skin irritation etc. 4.1 Toxic Levels of Concern (LOCs) Selection Toxic Levels of Concern (LOCs) is used to assess the toxicity threat of a chemical release. A toxic LOC indicates threshold concentration of exposure to a chemical that could hurt people if they breathe it in for a defined length of time. Generally, the lower the toxic LOC value for a substance, the more toxic the substance is by inhalation. The most common public exposure guidelines are Acute Exposure Guideline Levels (AEGLs), Emergency Response Planning Guidelines (ERPGs) and Temporary Emergency Exposure Limits (TEELs). In this study, Acute Exposure Guideline Levels (AEGLs) concentrations are used to define the toxic zones. AEGLs are the best public exposure LOCs 214

224 available to date and all three tiers (AEGL-1, AEGL-2, and AEGL-3) are developed for five exposure periods: 10 minutes, 30 minutes, 60 minutes, 4 hours and 8 hours. Table 1: AEGLs for Chlorine exposure in ppm. Exposure Time Toxic level AEGL-3 AEGL-2 AEGL-1 10 minutes minutes minutes hours hours AEGL-3 is the airborne concentration (expressed as ppm or mg/m 3 ) of a substance above which it is predicted that the general population could experience life-threatening health effects or death. AEGL-2 is the airborne concentration (expressed as ppm or mg/m 3 ) of a substance above which it is predicted that the general population could experience irreversible or other serious, longlasting adverse health effects. AEGL-1 is the airborne concentration (expressed as ppm or mg/m 3 ) of a substance above which it is predicted that the general population could experience notable discomfort and irritation. However, the effects are not disabling and are transient and reversible upon cessation of exposure. 4.2 Dispersion Modeling of Chlorine Release Release Description: This describes a hypothetical case of chlorine release from Global Heavy Chemicals Limited, a Chlor-alkali plant situated at keranigonj in Dhaka. Let s assume that due to leakage in a storage tank, approximately 1.6 tons of chlorine was directly released into the atmosphere from the storage through a circular hole with a diameter of 1 inch. The diameter of the cylindrical storage tank is 6 feet and the length is 15 feet. The temperature is 31 o C, in presence of the wind travelling from the southeast direction at 7.5 miles per hour. The sky is assumed to be more than half covered by clouds and the humidity is 75 percent Results: Figure 1 shows the ALOHA's threat zone plot for one hour accidental release of 1.6 tons of chlorine from a horizontal cylindrical tank. The area is considered an open country. On the plot the red, orange and yellow regions represent the areas where chlorine concentrations are predicted to exceed the corresponding LOC values (the AEGL values for 60 minutes exposure time) at some time after the release begins. The red (AEGL-3) threat zone which is the area with the greatest exposure level is predicted to extend more than 1 km downwind the source. The orange (AEGL-2) threat zone is predicted to extend more than 3.5 km downwind of the source. The yellow (AEGL-1) threat zone is predicted to extend 7 km Effect of Wind Velocity: The dispersion of a fluid in air depends on wind velocity. In presence of higher wind velocity, the released material is carried downwind faster and a plume becomes larger and narrower. For the described hypothetical chlorine release, results of the variation of wind speed on the dispersion of toxic chlorine gas in air are presented in Table 2. Table 2: Variation of different threat zones with wind velocities Wind velocity (mph) Red Zone (Km) Orange Zone (Km) Yellow Zone (Km) From Table 2, it is observed that the length of red zone (average chlorine concentration in 60 minutes is more than 20 ppm), orange zone (average chlorine concentration in 60 minutes is more than 2 ppm) and yellow zone (average chlorine concentration in 60 minutes is more than 0.5 ppm) decrease with increasing wind velocity due to higher washout of plume by higher wind velocity. With the help of higher wind velocity, the released gas is dispersed in the larger area within a short span of time reducing the area of higher concentration Effect of Surface Roughness: Surface roughness is the roughness of the ground over which a pollutant cloud moves. Degree of ground roughness depends on the size and number of roughness elements, which can range in size starting from blades of grass to buildings. Ground conditions affect mechanical mixing at the surface and the wind profile with height (Crowl and Louvar, 2002). Trees and buildings increase mixing while lakes and open areas decrease it. For the described hypothetical chlorine release case, results of the variation of surface roughness on the dispersion of toxic chlorine gas in air are presented in Table 3. Ground roughness increases mechanical mixing, roughness elements for example buildings, 215

225 trees increase mixing of air and the pollutant cloud and dilute the pollutant gas. So, from Table 3, it is observed that threat zones become smaller with increasing surface roughness Effect of Temperature: Atmospheric stability depends on air temperature (Turner, 1973). Atmospheric stability relates to vertical mixing during the day when air temperature decreases rapidly with height and encouraging vertical motion. The atmosphere may be more or less turbulent at any given time, depending on the amount of incoming solar radiation. For the described hypothetical chlorine release case, results of the variation of temperature on the dispersion of toxic chlorine gas in air are presented in Table 4. Moderate to strong incoming solar radiation heats air near the ground causing it to rise and generates large eddies. Therefore, from Table 4 it is observed that chlorine gas is dispersed more at higher temperature. Thereby threat zones increase with air temperature. On the other hand, for relatively weak solar radiation, air near the surface has a reduced tendency to rise and less turbulence develops. Figure 1: Different threat zones (red, orange and yellow zone) for Chlorine release. Table 3: Variation of different threat zones with surface roughness. Surface roughness, Z 0 (cm) Red Zone (Km) Yellow Zone (Km) 3 (Open country) Table 4: Variation of different threat zones with Temperatures. Temperature ( 0 C) Red Zone (Km) Orange Zone (Km) Yellow Zone (Km)

226 5. CONCLUSIONS Dispersion modeling of released chlorine gas from a horizontal cylindrical storage tank is carried out using software ALOHA. For accidental release of 1.6 tons chlorine gas from a horizontal cylindrical tank through a hole of diameter 1 inch, affected area is divided into red zone, orange zone and yellow zone. The length of red zone (average chlorine concentration in 60 minutes is more than 20 ppm) has been estimated to be 1.1 kilometers, orange zone (average chlorine concentration in 60 minutes is more than 2 ppm) 3.6 kilometers and yellow zone (average chlorine concentration in 60 minutes is more than 0.5 ppm) 7 kilometers, respectively downwind from the source. With all other conditions constant, a threat zone is likely to be smaller with increasing ground roughness and wind velocity. The length of a threat zone is likely to rise with increasing temperature as temperature affects atmospheric stability. Though average atmospheric conditions of Bangladesh have been taken into account for the formulation of this modeling, the real situation may differ from the average value leading to a considerable change in the results. So care must be taken in the interpretation of the results. REFERENCES 1. Acute Exposure Guideline Levels (AEGLs), viewed on January < index.htm> 2. Bosanquet, C. H., & Pearson, J. L. (1936). The spread of smoke and gases from chimneys. Trans. Faraday Soc., 32, Crowl, D. A., & Louvar, J. F. (2002). Chemical process safety: fundamentals with applications. Pearson Education, Eidsvik, K. J. (1980). A model for heavy gas dispersion in the atmosphere. Atmospheric Environment (1967), 14(7), Labovský, J., & Jelemenský, L. (2010). CFD simulations of ammonia dispersion using dynamic boundary conditions. Process Safety and Environmental Protection, 88(4), Labovský, J., & Jelemenský, L. (2011). Verification of CFD pollution dispersion modelling based on experimental data. Journal of Loss Prevention in the Process Industries, 24(2), Li, S., Sun, X., & Liu, L. (2012) The ALOHA-based Consequence Analysis of Liquefied Ammonia Leakage Accident. 8. Mondal, A. and Paul, R. (2013), Dispersion Modelling of Accidental Release of Toxic Gases, B. Sc. Engg. thesis, Bangladesh University of Engineering & Technology, Dhaka 9. Nielsen, M., Ott, S., Jørgensen, H. E., Bengtsson, R., Nyrén, K., Winter, S.,... & Jones, C. (1997). Field experiments with dispersion of pressure liquefied ammonia. Journal of hazardous materials, 56(1), Sutton, O. G. The theoretical distribution of airborne pollution from factory chimneys. Quarterly Journal of the Royal Meteorological Society (1947): Turner, D. B. (1973). Workbook of atmospheric dispersion estimates. US Government Printing Office. 217

227 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh MINIMISATION OF WATER USAGE IN INDUSTRY USING WATER CASCADE ANALYSIS: A WINERY CASE STUDY Nicholas Nyamayedenga, Iqbal M. Mujtaba School of Engineering, University of Bradford, West Yorkshire BD7 1DP, UK This work applies Water Cascade Analysis (WCA) developed by Manan et al. (2006) as a tool to minimise overall freshwater usage in Karimba Winery in Zimbabwe. For this purpose, a similar numerical analysis performed on the mosque by Manan et al. (2006) is applied on the data supplied for Karimba Winery (KW) to determine and set water minimisation targets and pinch location of the water distribution network. The winery study realised 27% and 68.8% reduction in freshwater flow and wastewater generation respectively. Using excel spreadsheets, system models were developed and sensitivity analyses were carried out to investigate system response with increase or decrease in contaminant levels at pinch determining levels. The winery models showed an increase in freshwater demand as contaminant concentration went up. 1. INTRODUCTION There is very little fresh water in the world that is pitied against an ever growing population, water pollution, increasing living standards and the increase in water demand (Mujtaba, 2012). Buros (2000) states that the shortage of freshwater is not a temporary one, but a long term and substantial problem. Most of the accessible water around us is held by the seas. 97% of the world s water is saline leaving only 3% as freshwater of which about 97% is held in glaciers (Mujtaba, 2012). These statistics call for a properly managed and integrated approach to the usage of freshwater in both industry and urban sectors. Among different processes, water cascade analysis is a process integration tool that can be used to study the operations of a water using network in order to minimise the usage of freshwater in industry. Flow of freshwater and wastewater determine the operational costs of water usage in industry. The issue of water minimisation in industry can be solved by reducing both freshwater flow and generation of wastewater. Three possibilities for reducing flow of fresh and waste water exist as follows: (1) Re-use; wastewater can be re-used in another operation unit where its level of contamination does not affect or interfere with the operation of that unit. (2) Regeneration re-use; a partial treatment of the wastewater is carried out to remove contaminants which would prevent its reuse and then this treated water becomes a source to another unit and (3) Regeneration recycling; contaminants that have accumulated are removed by regeneration and then the water recycled. This water can be used in the unit it previously left (Doyle and Smith, 1997; Iancu, 2007; Khor et al., 2012). 2. WATER CASCADE ANALYSIS Generally the WCA involves first analysing the existing water-using structure to determine the flow regime of both freshwater and wastewater. Next, based on the biological oxygen demand (BOD) the concentration of the wastewater from each waterusing unit is determined and these are ranked in ascending order. Concentration intervals are determined between one concentration level and the next. These concentration intervals are also called purity levels with the highest purity level being that of fresh water at a BOD of zero (Manan et al., 2006). The purpose of purity intervals is to examine the feasibility of the water at that interval if it can be cascaded to the next unit without affecting the operations thereof. So, a water cascade diagram is drawn using the purity levels and the corresponding flowrates. Interval fresh water demands are determined to obtain the amount of fresh water required at each purity level. The principle of water cascading can be summarised in the example presented in figs. 1 and 2. The negative values in figs. 1 and 2 above only show that there is water demand. * Corresponding Author: Iqbal M. Mujtaba, I.M.Mujtaba@bradford.ac.uk

228 In Fig. 1, freshwater is supplied at each purity level. Fig. 1 above shows a unit that produces 200kg/s water at a purity level of at 50 ppm concentration while 2 more units require 100kg/s and 50kg/s at purity levels of at 100 ppm concentration and at 150 ppm concentration respectively. The 50 ppm unit becomes a source while the 100 ppm and 150 ppm units become demands. Here the 200 kg/s at 50 ppm wastewater produced by the first unit can satisfy the requirements of the second and third units without affecting their operations because its purity at is higher than that of the second and third units at and so the water from the first unit can safely be cascaded down as shown in fig. 2 above. What we are saying here is that the second and third units do not require freshwater at all. There is a potential saving in freshwater consumption of 150 kg/s and reduction in wastewater flow of the same magnitude. Using the following set of equations an interval water balance table was drawn to determine the net water source or water demand at each purity level (Manan et al., 2006). Equations 1 to 3 can also be applied to conditions in figure 2. (1) Assuming the highest possible pure water contaminant concentration of 1,000,000 ppm (Manan et al., 2006; Iancu, 2007) the purity (P) of a stream thus, is described by equation 1 where C is the concentration of water at that purity level (P k ). (2) n is the number of purity levels in a unit where in equation 2, N D and N S are number of pure water demands and sources respectively. In fig. 2 there are two pure water demands and 1 pure water source. This gives 3 purity levels. N DP is the number of duplicate concentration levels of which 219

229 there is none in fig. 2 (see Manan et al., 2006 for further details). P = P n P n + 1 (3) P becomes the difference in purity levels. Equation 4 applies to the water cascade model for Karimba Winery (Table 3) to determine the flow of freshwater (F FW ) for a network. 3. WCA ON KARIMBA WINERY (4) Tables 1 and 2 show a systematic and detailed analysis of water demands and possible water sources for KW. Following the same procedure outlined in Manan et al. (2006) to determine the net water demand or source for the factory, an interval water balance table for Karimba Winery (KW) was obtained table 3. An assumed freshwater flow of 0 t/d was supplied to the network which resulted in an infeasible pure water cascade diagram. 0 t/d freshwater flow is assumed and injected into the system to check the feasibility of the water cascade. The negative water flow values in the water cascade diagram mean the water cascade analysis is infeasible table 3 (b). This is so because of the assumption of 0 t/d freshwater flow. However, on supplying the system with the absolute value of the least negative interval, freshwater demand for the system (53.35 t/d) yielded a feasible pure water cascade diagram table 3 (c) with a reduction in freshwater flow and wastewater generation of 27% and 68.87% respectively. Table 3 is an excel model of the KW that was done by an excel spreadsheet by combining the interval water balance table 3 (a), pure water cascade diagram table 3 (b) and the feasible pure water cascade diagram table 3 (c). Table 1. Summary of water demands for KW Stream Demands Description Flowrate (t/d) BOD (ppm) D1 WB D2 WP D3 CDP D4 BW D5 De-alkaliser 2 10 D6 Boiler D7 Toilets A water cascade diagram shows the cumulative water source/demand, pure water surplus/deficit and interval freshwater demand. Table 3 (b) becomes very important as it shows the amount of freshwater required to satisfy the operations of the water-using network (the absolute value of the least negative interval freshwater demand). Here, the absolute value of the lowest negative interval freshwater demand is taken to be the minimum freshwater flowrate. Table 2. Summary of water sources for KW Stream Source Description Flowrate (t/d) BOD (ppm) S1 WB S2 Rainwater S3 CDP S4 Boiler S5 BW & De-alkaliser S6 WP SENSITIVITY TEST OF WCA The pinch point of the WCA for KW occurred at purity interval P 4 (P k = ; 15 ppm) table 3. This consequently yielded freshwater demand and wastewater generation for KW system of t/day and 9.75t/day respectively. Now the freshwater supply determined by the WCA holds if the BOD values of table 2 remain constant (a fixed outlet concentration), but in real life they do vary. Contaminant concentration varies if the water quantity is fixed (Majozi, 2005). It is not possible to have the same contaminant mass load entering the water-using units. This then calls for a sensitivity test to determine how the system responds with varying BOD and maybe predict when this might occur, which really is beyond the scope of this work. Using an excel spreadsheet table 3 for the KW water network, the contaminant concentration at the pinch location was altered to examine system response to this disturbance. Reduction in the freshwater contaminant concentration results in decreasing freshwater demand while raising the contaminant concentration to above the pinch determining concentration results in increasing freshwater demand for the KW case Fig. 3. As expected, freshwater demands increased with increase in contaminant concentration. It is important to note that the lowest negative value in requirement means that there is insufficient freshwater at that level; therefore pure water of the highest purity level must be supplied in order to satisfy the requirements of the system or network. This then enables the designer to have a clear picture of their predictions for the retrofit design. Injecting the KW system with 55t/day freshwater, more than was determined by the model at pinch level supplied the network with adequate freshwater but however, this is a waste of the resource since an optimum supply value was obtained. 220

230 Table 3. Water Cascade model for Karimba Winery This also increased the flow of wastewater above the 9.75t/d while the negative value of t/d wastewater improved to t/d indicating that there was abundantly surplus freshwater in the system. Injecting the system with less than required (as calculated) amount of freshwater further rendered the model infeasible by lowering the least negative value of 53.35t/d to t/d and the pinch location disappeared from the model. This then validates the model that it can be employed to determine the optimum freshwater supply of any water using system. Fig. 4 is a retrofitted design of KW using the data from tables 1 and 2. The waste from the toilet is not utilised as it is contaminated with faecal matter. 221

231 water network, the WCA can and is a strong tool for minimising water usage in any water using process. Nomenclature Fig. 3. Freshwater demand at purity level (Karimba Winery) P = Purity level n = Number of purity levels N D = Number of pure water demands N S = Number of pure water sources N DP = Number of duplicate concentrations C = Concentration of pure water Pn = Purity level n F FW = Flow of freshwater F WW = Flow of wastewater P FW = Purity of freshwater FWC = Freshwater concentration S = Sum of sources flowrate D = Sum of demands flowrate P = Difference in purity level AC & UV= Activated carbon and Ultraviolet REFERENCES Fig. 4. A retrofitted design of KW 5. CONCLUSIONS Although the WCA was implemented on the activities of a mosque (Mannan et al., 2006) and recommended to most buildings, offices and institutions it has been successfully adapted to an industrial process and shown that there can be substantial amounts of savings in water usage and thereby minimise water usage in industry. WCA successfully shows that for a process to minimise its water usage, proper process integration must be done so as to determine the best solution to high freshwater and wastewater flow. By studying the existing water distribution network, setting the minimum water targets and calculating the new 1. Buros, O. K. (2000) Desalination Association. Riyadh: Saudi Arabia. 2. Doyle, S.J. and Smith, R. (1997) Targeting Water Reuse with Multiple Contaminants. Process Saf. Environ. Prot. 75, Iancu, P. (2007) Process Integration For Water Minimisation In Oil Processing And Petrochemistry. University Politechnica of Bucharest: Bucharest. 4. Khor, C.S., Shah, N., Mahadzir, S. and Elkamel, A. (2012) Optimisation of petroleum refinery water network systems retrofit incorporating reuse, regeneration and recycle strategies. Can. J. Chem. Eng. 90, Majozi, T. (2005) Wastewater minimisation using central reusable water storage in batch plants. Comput. Chem. Eng. 29, Manan, Z.A., Wan Alwi, S.R. and Ujang, Z. (2006) Water pinch analysis for an urban system: a case study on the Sultan Ismail Mosque at the Universiti Teknologi Malaysia (UTM). Desalination 194, Mujtaba, I.M. (2012) The Role of PSE Community in Meeting Sustainable Freshwater Demand of Tomorrow s World via Desalination, Computer Aided Chemical Engineering- 31, 30,

232 Proceedings of the International Conference on Chemical Engineering 2014 ICChE 2014, Dhaka, Bangladesh POTENTIAL BENEFITS, HAZARDS AND PREVENTION OF GAS HYDRATE Ogunlana, A.O., Azanor, H.K., Rahman, Imtiaz, S., M. A., Ahmed S.* Faculty of Engineering and Applied Science, Memorial University of Newfoundland Memorial University of Newfoundland, St. John s, NL, Canada, A1b 3X5 In this study, the physical and chemical properties of hydrates, mechanism of hydrate formation in pipeline, prevention and control techniques during operations and pipeline design considerations to prevent the accumulation of hydrate are reviewed. The benefit associated with the newly developed kinetic inhibitors (KHIs) and Anti-Agglomerants (AAs) as a potentail enviroment friendly hydrate removal agent is also dicussed. This study can be used to identify the types of hydrate, the problem that it can cause and select the appropriate technology to deal with the problem associated with hydrate in pipeline. This study also discusses the potential benefits of gas hydrate as an alternative green energy resource. The knowledge from this study will be of economic benefit to the oil and gas industry as it will help in improving pipeline operating envelope for a wide range of conditions. 1. INTRODUCTION Problems with gas hydrate during the production of oil and gas has led to appreciable production losses and potentially dangerous situations. Some of these losses and safety hazards could have been avoided if operators and field developers were more aware of the properties and the behaviour of gas hydrates in production facilities. This study presents some general information regarding such properties and behaviour. Gas hydrates were first obtained by Joseph Priestley (Makogon, 1978) in 1778 under laboratory conditions by bubbling SO 2 through 0 C water at atmospheric pressure and low room temperature. When describing the crystals he obtained, he did not name them hydrates. The second period of gas hydrates study began in 1934, when Hammerschmidt (Sloan and Koh, 2007) published the results of the inspection of the U.S. gas pipelines. It was noted that the inspection was complicated by the formation of solid plugs in the winter time. It was assumed that they encountered ice plugs freezing from hydrotest and condensed water. Hammerschmidt (Sloan and Koh, 2007) relying on his laboratory investigations, showed that the solid plugs consisted not of ice, but of hydrate of the transported gas. It was necessary to investigate in detail the conditions of the formation of gas hydrates and to find an effective means of preventing solid hydrate plugs from forming in pipelines. In the mid-thirties of the last century * Corresponding Author: M.A., Ahmed S., sahmed@mun.ca Nikitin hypothesized that gas hydrates were clathrate compounds. A few years later Stackelberg (Sloan and Koh, 2007) confirmed this claim by experimental investigation. International projects in recent years, including countries such as Japan, India, Canada, and US, have been implemented to explore the viability of gas hydrates, both on land and at sea, as a future source of methane. Experimental gas production tests of permafrost hydrates have been conducted in Canada in 2002 and 2008 (Giavarini and Hester, 2011) with Japan planning for a marine test in the upcoming years. The detailed composition of gas hydrates is determined by how the guest molecules are distributed over the two types of cavities that are present in the lattice. The distribution depends on a) the temperature; b) the pressure and c) the composition of the system in which the gas hydrates are formed. Water molecules take up approximately 90% of the weight of natural gas hydrates whereas the remaining 10% can be attributed to the gas molecules that are trapped in the hydrate lattice. A reliable experimental work is limited for the validation of a hydrate management strategy for industrial transport applications. This study will provide an overview of the benefits and the limitations of techniques that are available to control hydrates in the field. This study also contains recommendations regarding actions that can be taken when hydrate problems occur in the field.

233 2. PROPERTIES OF HYDRATES Gas hydrate is a crystalline ice-like solid formed at locations where water is in contact with smaller scape from these cages. Therefore a hydrate crystal is formed when these cages stack together to create a space-filling lattice. The small and middle-sized cages can combine to form a type I hydrate crystal lattice, whereas the small and large cage form a type II hydrate crystal lattice. The stability of the hydrate formed depends on the composition of the gas, although type II hydrates are expected to form in the vast majority of production facilities. During their formation the appearance and behaviour of gas hydrate crystals is similar to that of wet snow. When formed in gas/condensate systems these crystals first tend to form multiple slushy accumulations ( hydrate slugs ) that are very hygroscopic in that they take up large volume fractions of liquid water (much like a sponge). When hydrate formation continues these accumulations become increasingly firmer until they assume the appearance of dry snowballs which could rapidly block the pipeline. Fig. 1: Curve for typical hydrate system Natural gas hydrates form at low temperatures and high pressures. A typical hydrate system is shown in Fig. 1, the hydrate curve marks the boundary between the regions within which hydrates can, or cannot, exist. In general, the higher the pressure, the higher the temperature at which stable hydrates can exist. The hydrate dissociation temperature is thermodynamically well defined. The hydrate curve in Fig. 3 is merely a plot of the hydrate dissociation temperature versus the pressure. After all the water is converted into hydrates, dry hydrate crystals that are present in the bulk flow will no longer adhere to the pipe surface. However, this does not necessarily mean that large amounts of dry hydrates can be continuously transported through pipelines. For continuous transportation it is required that these crystals remain homogeneously dispersed in the fluid or condensate stream, whereas the viscosity of such guest molecules amongst which the C1-C4 hydrocarbons, H 2 S and CO 2 are the most relevant for the oil and gas industry. The water molecules form cages around the guest molecules hence cannot e hydrate slurries increases rapidly with increasing hydrate loading. If fluid (gas) is continuously transported through the pipeline and gradually cooled in due to hydrate formation, the likelihood of wet hydrate formation further downstream of the pipeline in increased. 3. THE CAUSE OF THE PROBLEM Most hydrate plugs are caused by operational mishaps or equipment failures rather than by a wrong design of the production facilities. Common causes of hydrate plug formation are mentioned below. 3.1 Loss of Inhibitor Insufficient amounts of inhibitor were injected, possibly because: The inhibitor injection pumps failed or were switched off Inhibitor was lost through external leaks in the injection system Part of the production system was starved of inhibitor because of internal leaks or the inhibitor was not properly distributed due to transient or varying wellhead pressures The inhibitor regeneration system failed The injected inhibitor was of poor quality The water production rate increased 3.2 Unexpected Ingress of Water The inadvertent ingress of excess water in dry gas lines is a common cause of hydrate formation. The following events would have happened: The disposal of a batch of water in a dry gas line An unnoticed failure of the gas dehydration system The ingress of seawater during a vacuum purge of a (leaking) dry gas line Poor separation of the water from condensate that is co-transported with dry gas Starting the production without prior removal of the water that was used for hydro testing 3.3 Under-Inhibited Cold Restart Hydrate plugs must have formed during a start of the production systems that do not normally operate inside the hydrate region. Several causes are: No start-up methanol or glycol was injected; No inhibitor injected prior to a planned shut-in that lasted longer than the cool down time; Liquids were not inhibited/removed/heated 224

234 before the production restart stripping of methanol from the water phase 3.4 Restarting the Production from an Initially Blocked Well The production can only be restarted if there is no danger for renewed hydrate formation in the well. After the hydrates have been removed, the situation is comparable to that during a normal shut-in of the well. However, before restarting the production it may be prudent to first take the preventive measures that are normally in place to prevent hydrate formation during shut-in such as the flushing of the wellhead with inhibitor and dumping of inhibitor in the well. 4. HYDRATE PREVENTION METHODS Many techniques are currently used to prevent the formation of hydrates, or hydrate plugs, during normal production. This section presents an overview of these methods Dehydration Water vapour can cause hydrate formation at low temperatures and high pressures. It may also create corrosion when it is in contact with hydrogen sulphide (H 2 S) or carbon dioxide (CO 2 ). These impurities are regularly present in the gas stream (Giavarini and Hester, 2011) Dehydration with glycol One common method to remove water from natural gas is glycol dehydration (Shell Exploration and Production,, 2012). In this process, tri-ethylene glycol (TEG) or di-ethylene glycol (DEG) is used to remove the presence of water in the gas stream The Low Temperature Separation (LTS) Process In LTS type dehydration process, the pressure of incoming gas is reduced by using choke or expander in order to reduce temperature. This temperature drop makes the water in the gas condense and come out in liquid form from gas The Low Temperature Exchange (LTX) Process This process is similar to the LTS process, except that methanol or glycol is not injected upstream of the Joule-Thompson (J-T) choke, and hydrates are allowed to form in the low-temperature separator. These hydrates form a layer between the condensate and the water phases where they are continuously melted by heating the water near the bottom of the separator. In addition, the low-temperature separation that occurs in an LTX unit results in stabilizing the liquids. This result in an increase in liquids recovered and a corresponding decrease in the heating value of the gas over what would be the case with separation at normal temperatures The IFPexol process This process was developed by Institut Francais du Petrole (IFP) (Morgan, 1976). It is also similar to the LTS process. In the IFPEXOL process, the prevention of hydrates in the heat exchanger and chiller is achieved by the addition of methanol to the natural gas stream being cooled (Dyck and Henderson, 1978). Methanol is normally recovered by a distillation process. However, the separation of methanol from water is somewhat difficult. In the IFPEXOL process, an innovative step is used that recovers most of the methanol for hydrate suppression without regeneration Twister This is a relatively new technology that is similar to the LTX process except for a more fancy choking process. Vanes are used to induce a swirl in the incoming gas before this gas supersonically expands through a Twister tube. After supersonic expansion the temperature of the gas is much lower than the temperature that would have been obtained after isenthalpic expansion. Moreover, the swirl forced the condensed liquids to move towards the wall of the tube near the end of which these liquids are (together with slip gas ) skimmed from the main (primary) stream. The liquids and the slip gas (the secondary stream) are then produced into an LTX unit that separates the liquids from the secondary gas. The secondary gas exiting the LTX unit is then merged with the primary gas. Field trials have shown that in practice the water dew point of the gas exiting a Twister unit (Twister tube plus LTX unit) can be a few degrees lower than the gas exiting a conventional LTX unit Maintaining High Temperatures Keeping the temperature of the system above the hydrate dissociation temperature, either by retaining the heat that is already present in the system (thermal insulation, pipeline burial) or by supplying additional heat to the system (direct electrical heating or heat tracing) can prevent hydrate formation. These are discussed below. Thermal insulation Pipeline burial Electrically heated pipelines Trenching of pipelines next to hot water injection lines Bundles 4.3. Maintaining Low Pressure Keeping the pipeline pressure below the hydrate dissociation pressure can also prevent hydrate formation. (Mokhatab and Poe, 2012). Production 225

235 at low pressure is sometime maintained until the pipeline outlet temperature has increased to above the hydrate dissociation temperature. Thereafter the normal pipeline pressure is restored. This hydrate prevention method can only be used if: The pipeline is short The process/flaring facilities can handle the produced low-pressure gas 4.4. Chemical Hydrate Prevention There are three different types of anti-hydrate chemicals. These are the thermodynamic hydrate inhibitors that shift the hydrate curve towards lower temperatures. The most commonly known examples are methanol, MEG (mono-ethylene glycol) and salt. The second and third types of anti-hydrate chemicals are the kinetic hydrate inhibitors and hydrate anti-agglomerants. Kinetic hydrate inhibitors temporarily prevent the crystallization of hydrates, whereas anti-agglomerants prevent hydrate crystals from forming hydrate plugs. 5. FORMATION PROCESS OF HYDRATE IN A PIPELINE The formation and build-up of natural gas hydrates in deep subsea pipelines are one of the most challenging flow assurance problems hence recent research trends has majorly focused on artic regions, subsea pipelines, oil and gas production and how it is affected by flow patterns, shut-down periods. Deep-water field activities has been on the increase over the past few years and it is projected that these fields would supply most of the world s oil & gas needs, however these fields are perfect environment to encounter hydrate forming conditions (Zerpa et. al., 2013). In this study a current conceptual picture for hydrate particle formation in water-dominated systems is presented as shown in Fig. 2. The whole process is divided into four steps: gas bubble entrainment in water; hydrate film grow the around the interface; particle packing, bedding, or agglomeration; and deposition or plugging (Turner, 2005). In most modeling efforts, hydrate is not considered as a separate phase, such modelling approaches treat the condensed phase (including water and oil) as a homogeneous mixture, with hydrate formation simply augmenting the bulk phase properties (Boxall, 2009, Boxall et. al., 2009, Davies et. al., 2009). Hence, in the previous modelling work (Zerpa et. al., 2013), the researchers used a simple multiphase flow model, which is capable of predicting stable hydrodynamic gas liquid slug flow (Danielson, 2011). The enhanced gas water contact around the interface provides a favourable environment for hydrate nucleation, leading to an initial hydrate film of up to 50 micro-meter in thickness (Taylor et. al., 2007); this corresponds to the thin hydrate shell represented during the growth stage of Fig. 4. It was mentioned that hydrate shells are transferred to the condensed water phase, allowing additional hydrate to form along the interface (Davies et. al., 2009b). Moreover, the interface itself will allow super-saturation of hydrocarbon gas in water (and, likewise, water in gas) within a few molecular diameters on each side of the dividing surface (Aman et. al., 2011, Dzyaloshinskii et. al., 1961, Neumann et. al., 2010). Fig. 2: Conceptual picture for hydrate blockage formation in water-dominated system (Turner, 2005) 6. POSSIBLE BENEFITS OF GAS HYDRATE Today the world is mainly moved by fossil fuels that depend of the oil reservoir that have been explored since the beginning of the 20th century. Table 1: World fossil fuel sources (Taylor et. al., 2007) Carbon Sources Mass of Carbon Estimated ( 10 9 Ton carbon) Gas Hydrate Fossil Fuels (oil, coal, gas) Dissolved Organic matter in water Peat 500 Other 67 Source: Beauchamp, 2004 However, many studies have shown that the gas hydrate is a possibility to complement the oil and other fossil fuels and it can be a cleaner way of energy and with mass carbon estimation two times bigger than the all fossil fuels together (Beauchamp, 2004) as shown in Table 1. The appropriate technology to determine the amount of natural gas hydrate deposits and the size of the gas hydrate deposits is still unknown. However, few technologies are in place for identifying the true 226

236 L/D (-) L/D (-) reserve of gas hydrate deposit. One of them is nuclear magnetic resonance well log, which has been used to provide substantial data regarding the hydrate deposits, such as the saturation of the gas hydrate (Collett, 2013, Riedel et. a., 2013) Worldwide Reserves Since natural gas hydrate has attracted the world s attention as an alternative potential energy, developing feasible methods for commercial production of natural gas hydrate depositions are essential. Until now three common methods for gas hydrate production have been proposed: depressurization, thermal stimulation, and inhibitor injection CO 2 Reduction One of the most important benefits that hydrate can offer is the CO 2 reduction. The use of gas hydrate to replace the CO 2 burning fossil fuels can be strong incentive for the exploration of gas hydrate in the coming years (Tezuka, 2002, Komatsu et. al., 2013, Yuan et. al., 2012, Zhou et. al., 2008). It has been demonstrated experimentally that a CO 2 emulsion has advantages when replacing CH 4 from a hydrate compared with high-pressure liquid CO 2. Moreover, a molecular dynamics simulation performed by Qi et al. (Ota and Zhang, 2011) also resulted in a similar conclusion that it is difficult for a CO 2 molecule to penetrate into the interior cages of the CH 4 hydrate via dissociation. Thus, a new technology is required for efficiently breaking the clathrate hydrate in environmental benign manner. 7. HYDRATE DEVELOPMENT LENGTH Re SL (-) Fig. 3: Hydrate development length It is also important to find the development length for oil dominated well for hydrate formation. From Fig. 3 it is observed that if the Reynolds number for slurry flow increases the development length increases. If the Reynolds number increases the flow inertia increases and this increment causes the increase in the flow development length. As presented in Fig. 4, the multiphase hydrate flow development length increases as the slurry 227 Reynolds number increases. It is also noted that the development length also increases as the volume fraction of gas phase (α) increases from 0.1 to 0.9. The increased volume fraction provides more inertia forces compared to the stratified force on the gas-liquid-solid flow of a pipeline. Thus, the hydrate flow development length and hydrate induction time will also be increased Re (Slurry) α = 0.1 α = 0.6 α = 0.7 α = 0.8 Fig. 4: Hydrate development length due to varying volume factions (α) 8. CONCLUSIONS This paper described the properties, causes and prevention of hydrates in pipelines. Based on the existing literature it is evident that the huge amount of hydrate exists in the vast ocean floor can be used as an alternative energy source for future global energy needs if this energy source is dealt with right technology. 9. ACKNOWLEDGEMENTS Authors would like to acknowledge Konstantinos, Dinesh Herath and Rafael for their contributions to this paper. REFERENCES 1. Y. F. Makogon, Hydrates of natural gas, Tulsa: PennWell Books, E. D. Sloan Jr and C. Koh, Clathrate hydrates of natural gases., CRC press, C. Giavarini and K. Hester, Gas Hydrates, Springer, "Shell Exploration and Production, "Overview Of Ormen Lange Project"," 14 November [Online].

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238 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh AN APPROACH FOR QUANTITATIVE ESTIMATION OF LONG RANGE TRANSPORT OF FINE PARTICULATE MATTER ENTERING BANGLADESH 1 Bilkis A. Begum *, 2 Md. Nasiruddin 1 Chemistry Division, Atomic Energy Centre, Dhaka, G.P.O. Box Clean Air and Sustainable Environment Project, Department of Environment (DOE), Agargaon, Dhaka 3 Philip K. Hopke and 4 Andreas Markwitz 3 Center for Air Resource Engineering and Science, Clarkson University, NY, USA 4 Institute of Geological and Nuclear Sciences Limited, National Isotope Centre, Lower Hutt, New Zealand Particulate air pollution is a major environmental concern in Bangladesh during winter season. In this view fine particulate matter (PM 2.5 ) sampling was done in consecutive three winter seasons, December 2010 to February 2011, December 2011 to February 2012 and December 2012 to February The sampling stations were Continuous Air Monitoring Stations (CAMS) located at Farm Gate in Dhaka, Sapura in Rajshahi, Baira in Khulna and Male Declaration Station Shamnagar, Khulna. PM sampling was performed using dichotomous samplers, which collect samples in two sizes: PM 2.5 and PM during the first two years and the stations are Farm Gate in Dhaka, Sapura in Rajshahi, and Baira in Khulna. During third year, PM sampling was performed using an Air Metrics sampler that collects one fraction, either PM 2.5 or PM 10 at a time from Farm Gate in Dhaka, Sapura in Rajshahi, and Male Declaration Station Shamnagar, Khulna. All of the samples were analyzed for fine mass and black carbon (BC). It was found that the mean PM 2.5 value in Rajshahi was higher than for the Dhaka and Khulna sites although anthropogenic activities were higher in Dhaka than the other two cities. It was also observed that during the monsoon season, the daily average of PM 2.5 comply with the national ambient air quality standard (NAAQS) in Dhaka and Khulna sites, but in Rajshahi, PM 2.5 values exceed the NAAQS. A source for these higher values may be long range transport of PM from agricultural burning in upwind regions and/or from natural dust storms that occur around the mid/end of February in the Arabian Peninsula almost every year. A threshold value (2*STD+MEAN) was set for three sites in order to reduce the influence of local pollutants. It was found that threshold value for Rajshahi was 385μg/m 3 and for other two sites, it was 208μg/m 3 (Average value). Hence, it may conclude that a potential 177μg/m 3 comes from long range transport during the winter season. 1. INTRODUCTION Transboundary air pollution is a particular problem for pollutants that do not readily react in the atmosphere or wet or dry deposit. These cross boundary pollutants can be generated in one country and produce impacts in others. Control of these pollutants requires international action and collaboration to control their formation and effects. Transboundary air pollutants can survive for periods of days to weeks and can be transported thousands of kilometers and affect the air quality, soils, rivers, lakes and/or our food. Transboundary air pollutants can include particles and ground level ozone. Particulate matter pollution is a major concern in Bangladesh (Gurjar et. al. 2008). Prior studies (Begum et. al., 2010) found that during monsoon or post monsoon season when the wind comes from south or south-eastern directions, the concentration of fine PM complies with the Bangladesh National Ambient Air Quality Standard (BNAAQS). During the winter season, wind comes from north or north-west direction and concentration of fine PM goes up to 3 to 4 times higher compare to monsoon season. From source apportionment studies, Begum et al (2013, 2014) found that the sources of pollutants are motor * Corresponding Author: Bilkis A. Begum, bilkisab@dhaka.net

239 vehicles, diesel generators, biomass and wood burning, brick kilns, Zn from galvanizing factory and fugitive Pb from battery industries and Pb recycling. Bangladesh is a flat land having no desert areas. In Dhaka, there is no large industry except brick making industry. There are many small industries like garment industry and brick production sector. The garment industry accounts for 76% of the country's export earnings and 10% of its GDP By 2013, about 4 million people, mostly women, worked in Bangladesh's $19 billion-a-year industry, export-oriented ready-made garment (RMG) industry. These industries use diesel generators for power production. Bangladesh is second only to China, the world's second-largest apparel exporter of western brands. Although brick manufacturing is not formally recognized as an industry, its manufacturing capacity is 12 billion bricks per year from 5,200 kilns and surrounds the major cities of Dhaka, Khulna, Rajshahi, and Chittagong. This sector has major national economic significance. It contributes to 1.0% of the gross domestic product and employs directly and indirectly over 1,000,000 people. The main fuels in this industry are coal and wood and kilns operate only from early November to early March. Given its geographical location, there are four seasons in Bangladesh; winter (December to February), pre-monsoon (March-May), monsoon (June-September), and post-monsoon (October November). During winter, cold winds blow from the north-west. This cold air carries continental fine air masses (Begum et. al., 2011). As a result, local pollutants mix with transported material that was hanged along the lower levels of the Himalayas. The visible impact of air pollution is the haze, a layer of pollutants and particles from biomass burning and industrial emissions. This polluted Atmospheric Brown Cloud has a brownish color and this brown cloud phenomenon is a common feature of industrial and rural regions around the world (Ramanathan, 2008). Because of long range transport of air pollutants, the mostly urban emissions (fossil fuel related) and/or rural emissions (biomass burning and brick kiln related) are transformed into a regional haze (or cloud) that can span large areas. It is now becoming clear that the brown cloud may have huge impacts on agriculture, health, climate and the water budget of the planet (Ramanathan, 2008, Ramanathan and Carmichael, 2008). This haze is the result of forest fires, the burning of agricultural wastes, dramatic increases in the burning of fossil fuels in vehicles, industries and power stations and emissions from millions of inefficient cookers burning wood, cow dung and other biofuels. In order to estimate the long range transport of fine air pollutants, airborne particulate matter (APM) sampling has conducted in three cities, Rajshahi, Dhaka, and Khulna during the winter seasons. The objective of this work is to estimate the transported of fine air pollutants that increase the local airborne pollutant concentrations during the winter season. 2. MATERIALS AND METHOD 2.1 Sampling Samples were collected on 37 mm diameter Teflon filters using Thermo Andersen dichotomous samplers, which were programmed to sample at 16.7 lpm for proper size fractionation. The samplers at each station (Fig. 1) were positioned with the intake upward and located in an unobstructed area at least 1m from any obstacle to air flow and the sampler inlet was placed at a height of 10 m above ground level. Appropriate QA/QC protocols were followed during the sampling and mass measurements. Quality of the sampling was ensured by using appropriate laboratory and field blanks. The sampling protocol was every third day starting from September 2010 and continuing to July 28, 2012 at essentially all sites. After sampling, the filters were brought to the conditioned weighing room of DOE directly from the sampling site for equilibration and PM mass measurement. Care was taken in transporting the exposed filters to minimize any PM loss (in box tight with chips). Fig. 1: Locations of sampling sites in Bangladesh Subsequently, PM 2.5 samples were collected using Air Metrics sampler at three sites, Rajshahi CAMS, Dhaka CAMS and Male Declaration air quality monitoring station at Shyamnagar in the Shatkhira district of Khulna from 01 December, 2012 to 07 March, The sampler was setup on the flat roof of the building at a height of 8 m upper from 230

240 ground. The air flow of the sampler was maintained at 5 l/m. Twenty four hours (8 am to 8 am to the next day) representative samples were collected for fine PM (<2.5 µm aerodynamic diameter) using Teflon filters. After sampling, the filters were brought to the AECD Laboratory directly from the sampling site for equilibration and PM mass measurement. Care was taken in transporting the exposed filters to minimize PM loss (in box tight with chips). 2.2 Site Description and Measurement Period Dhaka is the capital city and is congested with a large number of motor vehicles, both public and private. Many small factories are also located in and around the city. The CAMS-2 site is at Farm Gate in Dhaka (latitude: N; longitude: E). Farm Gate is characterized as a hot spot site due to the proximity of several major roadways, intersections and large numbers of vehicles plying through the area (Begum et. al., 2005). The site is surrounded by commercial and semi industrial area. It was found from the source apportionment study that the main pollutant sources are road dust, soil dust, sea salt, Zn source, motor vehicle, and brick kiln in this site (Begum et. al., 2013). Rajshahi is situated in the northern region of Bangladesh (latitude N, longitude E) and near the border with India. The location of the CAMS-4 is in Sapura at the Divisional Forest Office. There are a few small industries surrounding the sampling site. The climatic conditions are very similar to Dhaka. As there is a low number of industries, apart from brick kilns in Rajshahi city, it has been found that the contribution of biomass burning is highest contributor to the measured PM mass concentrations (Begum et. Al., 2004). This biomass burning contribution may originate from the brick industry, domestic burning/residential combustion (cooking with low grade fuels) or from transboundary transport. Khulna, the third largest city of the country, is situated in the southern region of Bangladesh (latitude N, longitude E) near the Bay of Bengal. Being located in a large river delta, it is the second largest port of Bangladesh. The CAM station, CAMS-5, is located at Samagic Bonayan Nursery and Training Center in Baira about 3 km north of main art of Khulna. There are many small factories near the sampling site (both west and south sides), which are producing Touchwood, a special type of fuel, which is made from rice husk and used as fuel for cooking. A Male Declaration air quality monitoring station is situated at Shyamnagar (Shatkhira) in Khulna. The site (rural area) was 12 km away from main road and situated near Indian border. 2.3 PM mass and BC analysis PM mass was measured in the laboratory of the Department of Environment for the samples from September, 2010 to July, 2012) and at the AECD for the December, 2012 to March, 2013 samples. The PM 2.5 masses were determined by weighing the filters before and after exposure using a microbalance (Begum et. Al., 2006). The filters were equilibrated for 24 h at a constant humidity of 50% and a constant temperature (22 C) in the balance room before every weighing. A Po-210 (alpha emitter) electrostatic charge eliminator was used to eliminate the static charge accumulated on the filters before each weighing. The difference in weights for each filter was calculated and the mass concentrations for each PM 2.5 samples were determined. Black carbon (BC) measurement was made with a two-wavelength transmissometer (model OT-21, Magee Scientific, Berkeley, CA). The twowavelength transmissometer measures the optical absorption of the ambient PM sample at 880 nm (BC) and 370 nm (UVBC) (Hansen et. al., 1984). Certain organic aerosol components of wood combustion particles have enhanced optical absorption at 370nm relative to 880 nm. A calculated variable, Delta-C signal (UVBC(370nm) BC(880nm)), has been suggested as an indicator of wood combustion particles, but is not a direct quantitative measurement of their mass concentrations (Wang et. al., 2010, Wang et. al., 2011). 2.4 Meteorological Conditions In Bangladesh, the climate is characterized by high temperatures and high humidity for most of the year, with distinctly marked seasonal variations in precipitation. According to meteorological conditions, the year can be divided into four seasons, pre-monsoon (March-May), monsoon (June-September), post-monsoon (October- November) and winter (December-February) (Salam et. al., 2003). The winter season is characterized by dry soil conditions, low relative humidity, scanty rainfall, and low northwesterly prevailing winds. The rainfall and wind speeds become moderately strong and relative humidity increases in the pre-monsoon season when the prevailing direction changes to southwesterly (marine). During the monsoon season, the wind speed further increases and the air mass becomes purely marine. In the post-monsoon season, the rainfall and relative humidity decrease as does the wind speed. The wind direction starts shifting back 231

241 to northeasterly (Begum et. al., 2011). The meteorological data used in this study were obtained from a local meteorological station, located about 2 kilometers north of the CAMS in Dhaka. 2.5 Back Trajectory Calculation Using models of atmospheric transport, a trajectory model calculates the position of the air being sampled backward in time from the receptor site from various starting times throughout the sampling interval. The trajectories are presented as a sequence of latitude and longitude values for the endpoints of each segment representing each specific time interval being modeled. The vertical motion of air parcels is considered during this model. The NOAA Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT-4) (Draxler et. al., 2003) model was used to calculate the air mass backward trajectories for those days when fine particles were sampled. Archived REANALYSIS meteorological data were used as input. The latitude/longitude was used depending on the site of location of four countries and trajectories were computed backward in time up to 120 hours (5 days). Tick marks on the trajectory plots indicate 6-hour movement locations. on fossil fuels and unsustainable development patterns which is a common issue among international communities and there is no instant solution. Transboundary air pollutants can survive for periods of days or even years and can be transported thousands of miles. Thus, an approach of quantitative estimation of transported fine PM is discussed. 3.1 Estimation of Transported Fine PM To exclude low local source contributions, the daily events with concentrations that are two standard deviations above the mean value for a measured species were considered. Table 1 shows the mean, standard deviation, and the threshold values (2*STD+Mean) for fine PM and BC concentrations in three sites. The meteorological conditions during winter lead to prevailing northerly and northwesterly winds. There are then possible transboundary events (Adhikary, 2007) affecting local air quality. Fig. 2 shows the plot of the average fine PM concentrations for all three sites during winter month. The fine PM concentrations are always high at Rajshahi site and the distribution pattern of PM concentrations is similar at all of the sites. 3. RESULTS AND DISCUSSION It is a well-recognized scientific fact that air pollutants spread easily across borders. In the 1970s, a transboundary air pollution event promoted severe acidification in ecosystems in Europe. Northeast Asian regions including Japan, China, and Korea have also observed air pollutants crossing over borders from time to time. Japan and Korea, the countries most likely to be affected by air pollution because of their downwind locations. The targeted substances for restriction have changed over time, first with sulfur oxide (SOx) in the 1990s, yellow dust in the early 2000s, ozone (O3), a cause of photochemical smog, in the late 2000s, and the most recently recognized problem of PM 2.5 pollution. Although airborne particles are generally associated with global cooling effects, recent studies have shown that they can actually have a positive radiative forcing effect (Bond et. al., 2011) particularly in certain regions such as the Himalayas (Ramanathan, 2007). In South Asia, many countries recognize air pollution as a major public health concern and have undertaken steps to control air pollution, but data provided by some of these countries indicate that in many cities, air quality still falls below world standards for acceptable air quality (Hopke et. al., 2008). The fundamental cause embedded in the air pollution problem is that the current energy mix is dependent Fig. 2: Average concentration of fine PM at three sites from , and during winter month It can be seen that about 60% of PM 10 is PM 2.5. The percentage of BC in PM 2.5 (Table 3) has been increasing every year. From source apportionment study (Begum et. al., 2014), it has found that the BC contribution from motor vehicle is minimum but main contribution comes from coal and wood/biomass (signature is S, K and Cl). During monsoon season, the daily fine PM concentrations at the Dhaka and Khulna sites are lower than Rajshahi site (Table 3). Hence, it may conclude that there is influence of long range transport during winter and the pathway is through northwest direction (Rajshahi). Industries (garments and brick manufacturing) and vehicle numbers are higher in Dhaka rather than Rajshahi. During the December 2012 to February 2013 sampling period, 232

242 the start time and ending time for all sampling stations was held quite constant. Hence, the days with the peak PM and BC concentrations in Dhaka and Rajshahi are the same. It was not possible to operate the Shamnagar site with the sampling protocol as Dhaka and Rashahi. We had only few samples and also show the same pattern (Fig. 4). The backwards trajectories during the days which have concentrations above the threshold values at Rajshahi are shown in Fig. 3, 4 and 5. The average of threshold value at Rajshahi was 385μg/m 3 and average of threshold values of other two sites is 208 and by subtracting second value from first, it would be 177μg/m 3. It means that the long range transport is about 177μg/m 3 during winter season. Similarly for BC, threshold value for Rajshahi in 34.9μg/m 3 and the other two sites was 22.2μg/m 3 (Begum, 2011). Hence from long range transport it would be 12.7μg/m 3. From source apportionment study and NASA satellite image ( ew.php?id=47742), it was found that from November to January, anthropogenic activities is responsible for high fine PM mass but in February and March, the high fine PM is for natural dust storm. Table 1: Basic statistics of fine PM and BC concentrations (μg/m3) during winter season Parameter Rajshahi (24.38oN, 88.61oE) Dhaka (23.76oN, 90.39oE) Fine BC Khulna (22.48oN, 89.53oE) Fine BC Fine BC PM PM PM Min Max Mean STD Median Threshold Min Max Mean STD Median Threshold Min Max Mean STD Median Threshold Table 2: Basic statistics of fine PM and BC concentrations (μg/m3) during monsoon season Year Rajshahi Dhaka Khulna Mean STD Mean STD Mean STD BNAAQS (24h) 65 Fig. 3: Backwards trajectories of air parcel movement and arriving at Rajshahi in 2010 to 2011 Fig. 4: Backwards trajectories of air parcel movement and arriving at Rajshahi in Fig. 5: Backwards trajectories of air parcel movement and arriving at Rajshahi in CONCLUSIONS The Government took different step to reduce the air pollution such as banning of leaded gasoline and two stroke engine. Introduction of compressed 233

243 natural gas into engine is one of the good steps. Now, government is trying to introduce energy efficient and environment friendly brick burning technology. In order to reduce the long range transport of air pollution, regional initiatives also essential. ACKNOWLEDGEMENT We thankfully acknowledge the Department of Environment to give us permission for PM sampling during December 2012 to February 2013 period using their CAMS sites (Dhaka and Rajshahi city). REFERENCES 1. Gurjar, B. R., Butler, T. M., Lawrence, M. G., and Lelieveld, J. (2008), Evaluation of emissions and air quality in megacities, Atmospheric Environment, 42, pp Begum, B. A., Biswas, S. K., Markwitz, A., and Hopke, P. K. (2010), Identification of sources of fine and coarse particulate matter in Dhaka, Bangladesh, Aerosol and Air Quality Research, 10, pp Begum, B. A., Nasiruddin, M., Randal, S., Sivertsen, B., and Hopke, P. K. (2014), Identification and apportionment of sources from air particulate matter at Unban Environments in Bangladesh, British J of Applied Science and Technology, 4, pp Begum, B. A., and Hopke, P. K. (2013), Identification of haze creating sources from fine particulate matter in Dhaka aerosol using carbon fractions, J Air & Waste Management Association, 63(9), pp Begum, B. A., Biswas, S. K., Pandit, G. G., Saradhi, I. V., Waheed, S., Siddique, N., Seneviratne, M. C. S., Cohen, D. D., Markwitz, A., and Hopke, P. K. (2011), Long range transport of soil dust and smoke pollution in the south Asian region 6. Ramanathan, V. (2008), Asian Brown Cloud, ctures/ramanathan/ Ramanathan, V., and Carmichael, G. (2008), Global and regional climate changes due to black carbon, Nature Geoscience, 1, pp Begum, B. A., Biswas, S. K.,Kim, E., Hopke, P. K., and Khaliquzzaman, M. (2005), Investigation of sources of atmospheric aerosol at a hot spot area in Dhaka, Bangladesh. J. Air and Waste Management Association, 55, pp Begum, B. A., Kim, E., Biswas, S. K., and Hopke, P. K. (2004), Investigation of sources of atmospheric aerosol at urban and semi-urban areas in Bangladesh. Atmos. Environ., 38, pp Begum, B. A., Akhter, S., Sarker, L., and Biswas, S. K. (2006), Gravimetric analysis of Air Filters and Quality Assurance in Weighing, Nuclear Science and Applications, 15, pp Hansen, A. D., Rosen, H., and Novakov, T. (1984), The Aethalometer-An Instrument for the Real Time Measurements of Optical Absorption by. Science of the Total Environment, 36, pp Wang, Y., Huang, J., Zananski, T. J., Hopke, P. K., and Holsen, T. M. (2010), Impacts of the Canadian Forest Fires on Atmospheric Mercury and Carbonaceous Particles in Northern New York, Environmental Science & Technology, 44, pp Wang, Y., Hopke, P. K., Rattigan, O. V., and Zhu, Y. (2011), Characterization of Ambient Black Carbon and Wood Burning Particles in Two Urban Areas. J Environmental Monitoring, 13, pp Salam, A., Bauer, H., Kassin, K., Ullah, S. M., and Puxbaum, H. (2003), Aerosol chemical characteristics of a mega-city in Southeast Asia (Dhaka, Bangladesh). Atmos. Environ., 37, pp Begum, B. A., Hopke, P. K., and Markwitz, A., (2011), Status of air quality: Experience in Bangladesh. Submitted 16. Draxler, R. R., and Rolph, G. D. (2003), HYSPLIT 4(Hybrid Single-Particle Lagrangian Integrated Trajectory) Model access via NOAA ARL READY Website ( NOAA Air Resources Laboratory, Silver Spring, MD 17. Bond, T. C., Zarzycki, C., Flanner, M. G., and Koch, D. M. (2011), Quantifying immediate radiative forcing by black carbon and organic matter with the Specific Forcing Pulse, Atmos. Chem. Phys., 11, pp Ramanathan, V. (2007), Warming trends in Asia amplified by brown cloud solar absorption. Nature, 448, pp Hopke, P. K., Cohen, D. D., Begum, B. A., Biswas, S. K., Ni, B., Pandit, G. G., Santoso, M., Chung, Y.-S., Davy, P., Markwitz, A., Waheed, S., Siddique, N., Santos, F. L., Pabroa, P. C. B., Seneviratne, M. C. S., Wimolwattanapun, W., Bunprapob, S., Vuong, T. B., and Markowicz, A. (2008), Urban Air Quality in the Asian region. Science of the Total Environment, 404, pp Adhikary, B., Carmichael, G. R., Tang, Y., Leung, L. R., Qian, Y., Schauer, J. J., Stone, E. A., Ramanathan, V., and Ramana, M. V. (2007), Characterization of the seasonal cycle 234

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245 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh ASSESSMENT OF WATER QUALITY OF BHAIRAB RIVER IN BANGLADESH Z. H. Khan, U. K. Navera, R. Rahman Department of Water Resources Engineering, Bangladesh University of Engineering and Technology (BUET), Dhaka-1000, Bangladesh Surface water has played a valuable role in the development of human civilization. The concern over water quality to the danger of diffusion of toxic substances into other ecosystems has only grown. These changes occurred on a major or minor scale on physical, chemical and biological parameters of water resulting in serious impacts on agriculture, aquaculture, fisheries and industrial use purposes. One of the major causes of degradation of inland water quality can be attributed to land based activities while adequate regulatory measures are not incorporated and proper concerns can't be found from the side of the stakeholders. All major rivers running through cities or urban areas are subjected to some degree of pollution to some extent. This paper represents the analyzed results of physical and chemical parameters of the River Bhairab for the year 2007 which is located in the South Western part of Bangladesh. The significance of selecting this river as a study case is because it involves discharge from industries along with municipal waste as well as vehicular traffic movement and is subjected to pollution. It will highlight the state of other rivers in Bangladesh. Among all physical properties temperature, turbidity, conductivity or electric conductivity, suspended solid, total dissolved solids and total solids are represented in this paper. For chemical properties ph, chloride, alkalinity or T-alkalinity, DO, BOD, COD are shown. After analyzing the mentioned parameters it has been found that Bhairab River water is suitable for irrigation, fish culture, recreational activities, drinking purpose (after disinfection) and cooling purpose in industries during the monsoon period. 1. INTRODUCTION Bangladesh is ariparian country with three major river systems namely the Ganges, the Brahmaputra and the Meghna and are named as the GBM basin which constitutes about 8 per cent of the combined catchment area within this country. River basin is one of the major sources of water supply for different purposes which include irrigation for agriculture, uses are for domestic and municipal water supply, industry, fishery, forestry and navigation and this water also provides fertile lands (Mouri et al., 2011) by flooding. More than 92 per cent of the annual runoff generated within the GBM catchment areas flows through Bangladesh (Coleman, 1969). The combined flow of the Ganges and the Jamuna River typically vary between less than 5000 m 3 /s in the driest period (March-April) to 80, ,000 m 3 /s in late August to early September (WARPO, 2000b). Surface water quality, especially the river water resources depend largely on a number of physical, chemical and biological parameters (Tareq et al., 2013). Water quality is very important for survival of the human beings as well as the food chain and the surrounding environment and ecosystem (EPA, 2001). High population density and increase in various demands constantly pressure on surface water as well as ground water. Water is of fundamental importance for ecology and the wider environment. The change in the physical, chemical and biological characteristics of water have serious implications on agriculture, aquaculture, fisheries and industrial use purposes (Singh et al., 2002). The magnitude and source of any pollutant, to assess its impact, to overcome the pollution stage and to monitor these parameters is essential for sustainable river water resources development (Reddi et al., 1993). Water stress occurs when the demand for water exceeds the amount available water during a certain period of time or when poor quality of water restricts the use of this water. This phenomenon frequently occurs in areas with low rainfall and high population density or in areas where agricultural land or industrial activities are intense. Even where sufficient long-term fresh water resources do exist, seasonal or annual variations in the availability of * Corresponding Author: U. K. Navera uknavera@gmail.com

246 freshwater may at times cause water quality degradation (EEA, 1999). The major causes of degradation of inland water quality are related to land based activities, when adequate regulatory measures are not incorporated and the stakeholders do not show proper concern. In Bangladesh, industrial units are mostly located along the banks of the rivers. As a consequence, industrial units drain effluents directly into the rivers without any consideration of the environmental degradation. The main suspected sources of agricultural runoff pollution are from the use of fertilizers and agrochemicals, including herbicides and pesticides. Urea, Triple Super Phosphate (TSP), Muriate of Potash (MP) and gypsum are the major chemical fertilizers used in Bangladesh. The total amount of fertilizers used annually is about 2 million tons (BBS, 1998). Significant water pollution also results from lack of sanitation facilities in the rural areas of Bangladesh. Also an inadequate facility for urban wastewater treatment is another source of pollution. Chittagong and Mongla are the two seaports of the country and on an average they deal with 1500 to 1600 vessels and 12,000 to 13,000 cargos annually. These ports, however, do not have facilities to receive and treat bilge and ballast water and thus ships throw wastewater into the territorial waters of Bangladesh (BBS, 1998). All major rivers running through cities or urban areas are subjected to some degree of pollution to some extent. This paper represents the analyzed results of physical and chemical parameters (not biological) of the river Bhairab for the year 2007 which is located in the South Western part of Bangladesh. The significance of selecting this river as a study case is because it involves discharge from industry along with municipal waste as well as vehicular traffic movement and is subjected to pollution though it is not a main river. It will highlight the state of other rivers in Bangladesh. An attempt has been made to study the existing pollution status of the river Bhairab as well as to compare the existing values of the physical and chemical parameters with national and international standards. This type of study seems necessary to predict the pollution status based on the available data from Department of Environment (DoE). All data which are used in this paper were tested in laboratories conducted by the DoE. 2. WATER QUALITY IN BANGLADESH Water quality of the Ganges, Brahmaputra and their distributaries in Bangladesh are polluted to some extent. Analytical results of the physicochemical analysis indicated that the ph, DO, EC, TDS, Rh are within the permissible limits specified by National Guidelines and Standards for Water Qualities while BOD, COD, turbidity and total coliform exceeded the specified permissible limits; DoE standard of Bangladesh (ECR, 1997) and WHO guidelines (2004) (Tareq et al., 2013). A study conducted in Naryanganj, an industrial area in Bangladesh recommended that regular practice of wastewater treatment before discharging it to the receiving water bodies is obligatory. They also suggested that in a selected industrial zone where a large number of textile industries are situated, a combined wastewater treatment plant can be developed to minimize the treatment cost. The treated wastewater should be disposed off to the water bodies (rivers) away from the estuaries and the places where different kinds of human activities prevail. Low cost treatment alternatives like aerated lagoons and oxidization ponds should be encouraged to enlarge the cost benefit margin of the textile industries. There should be continuous monitoring at strategic points and at regular intervals to quantitatively determine the pollution load. Alam et al., 2007 predicted the risk and conducted water quality assessment of River Sitalakhya in Bangladesh. The recommendation of his research work was to make relevant estimation of the total pollution loads to water by all the industrial sectors of Bangladesh using the Industrial Pollution Protocol System (IPPS) method developed by the World Bank. In terms of pollution, one of the polluting sectors is the food industry, where the sugar mills and oil/fat factories cause most of the pollution. Pulp and paper industry is another water polluter. Metal industries (ferrous and nonferrous) rank first in terms of toxic metals emission. The largest amounts of toxic chemicals are released by the tanneries and leather industries (raw and processed). In terms of the total emission to air, water, and land, the top three most polluting industries are pulp and paper, food industry and tanneries/leather. These industries were large in size or located in large clusters (tanneries), which can be identified and managed as point sources of pollution. The other significant polluters include the metal and textile industries. These are dispersed all over the country and will be more difficult to manage from a pollution control point of view. Due to lack of resources, modern technology and awareness not much was being done to trap the harmful pollutants and reuse/recycle these chemicals. Recycling is practied only when it is part of the production process, and not as a part of pollution mitigation activity. If strict environmental monitoring is enforced as per the Environmental 237

247 Conservation Rules of 1997 and other relevant environmental laws, many of the industries of Bangladesh will be found in violation of the emission limits which directly affects the surface water quality. Both Directives and Regulations are aimed primarily at the safeguarding of human health by protecting both waters and fish (as part of the food chain), as well as the aquatic environment at large (EPA, 2001). 3. WATER QUALITY PARAMETERS There are three systems used for assessing the quality of river water (i) physical assessment that involves measure the changes of physical properties in water, (ii) chemical analysis, where samples of the water are tested in a laboratory for a range of parameters and (iii) biological assessment showing the effects of pollutants on the aquatic organisms at the time of sampling and it also reveals the longerterm effects of changing water quality (Metcalf and Eddy, 2003). Physical parameters: The most important physical properties of water are color, odor, temperature, turbidity, conductivity or electric conductivity, suspended solid, total dissolved solid, total solid. Among all physical properties DoE measure temperature, turbidity, conductivity or electric conductivity, suspended solid, total dissolved solid, total solid. Chemical parameters: Generally chemical properties of water involve ph, chloride, alkalinity or T-alkalinity, hardness, N-nitrogen, phosphorus, sulfur, gases, ammonia, nitrate and nitrite, DO, BOD, COD, metallic constituents (Metcalf and Eddy, 2003). Among all chemical properties, DoE measures ph, chloride, alkalinity or T-alkalinity, hardness, DO, BOD, COD. Biological parameters: Biological properties of water involve all types micro organisms including bacteria, fungi, algae, protozoa, plants, animals, fungi, algae (Metcalf and Eddy, 2003). This study does not include any biological properties. Table1: Bangladesh standards for surface water quality (Source: ECR, 1997) Water quality parameter Unit Disinfections only Conventional treatment P H BOD mg/l <2 <3 DO mg/l >6 >6 Total coliform No./100ml <50 <5000 The drinking water quality has been also determined by ECR, STUDY AREA Bangladesh has a tropical monsoon climate characterized by heavy seasonal rainfall, high temperatures, and high humidity. About 80 percent of rain falls during the monsoon season (June to August). The selected river Bhairab for this study enters into Bangladesh from Meherpur district and merges with Rupsha River in Khulna district (Fig. 1). It passes over Chuadanga, Jassore and Khulna districts. Its catchment area is 905 sq. meter. The sampling locations were selected based on DoE s criterion for monitoring of water quality and seasonal variation in selected physical and chemical characteristics of the Bhairab River. 5. SAMPLING Water samples were collected from twelve stations namely Noapara Ghat, Jassore (Side Point, Middle Point, Opposite Point); Charerhat Ghat, Khulna (Side Point, Middle Point, Opposite Point); Phultala Ghat, Khulna (Side Point, Middle Point, Opposite Point) and Labanchara Ghat, Khulna (Side Point, Middle Point, Opposite Point). Samples were collected by DoE according to standard sampling procedure. Grab samples procedure was applied in the sampling from the said rivers by DoE. (i) Volume of samples: 2 liters of each sample from each location. (ii) Point of sampling: A number of points at the surface across the entire width and at a number of depths at each point were selected to collect the sample. Surface water samples were collected from cm below the river water surface and at distances of cm from the bank of the river in labeled sample bottles. (iii) Preparation of sample containers: Plastic containers of capacity greater than 2 liters were used and the bottles were washed with conc. HNO 3 and rinsed repeatedly with distilled water, before the samples were collected. (iv) Sample collection: sample bottles were rinsed three times also with the river water. The measured and analyzed water quality parameters involved both the physical and chemical parameters including temperature, electric conductivity, P H, chloride content, T- alkalinity, turbidity, total solid, total dissolved solid, suspended solid, dissolved oxygen, BOD and COD. 238

248 6. PARAMETERIZATION OF PHYSICAL WATER QUALITY PARAMETERS OF BHAIRAB RIVER This study is focused on physical parameters such as temperature, turbidity, conductivity or electric conductivity, suspended solid, total dissolved solid, total solid for Bhairab River. The temperature of Bhairab River water showed that it might be tolerable for aquaculture like Carp fish, Diatoms, Green algae and Blue-green algae. Turbidity of Bhairab River water was found to be NTU (Pre Monsoon) and NTU (Monsoon), SS were mg/l (Pre Monsoon) and mg/l (Monsoon) and TDS was mg/l (Pre Monsoon) and mg/l (Monsoon) respectively. The results of the present study clearly indicate that the water of Bhairab River was carrying higher value of EC in pre monsoon period and is not suitable for maintaining the normal functioning of aquatic organisms. But in monsoon period its water can be used for irrigation due to lower value of EC. The standard values of SS and TDS were seen to be 10 mg/l and 1000 mg/l for the inland surface water of Bangladesh (Alam et al., 2007). After analysis the mean values of SS were found to be mg/l (Pre Monsoon) and mg/l (Monsoon) and TDS values were mg/l (Pre Monsoon) and mg/l (Monsoon). The amount of SS and TDS were also considerably high in pre monsoon. So in monsoon period Bhairab River water is favorable for any purpose. 7. PARAMETERIZATION OF CHEMICAL WATER QUALITY PARAMETERS OF BHAIRAB RIVER The chemical parameters like P H, chloride, alkalinity or T-alkalinity, DO, BOD, COD for Bhairab River were considered for this study. The P H value of Bhairab River water is suitable for fish culture and algae growth as well as industrial and manufacturing processes like food canning, freezing, rayon manufacturing and tanning leather. But this water needs to be pretreated in case of washing clothes. While considering chloride content river water is very much unsuitable for fish culture as well as surface irrigation though in case of T-alkalinity it is within the allowable limit for fish culture. Sampling result at the pre monsoon and monsoon period revealed that the values of DO were slightly low. In case of DO value river water is fit for irrigation, fish culture, recreational activity and cooling industries. But this water needs to be pretreated in case of use it for drinking purpose after disinfection. The mean value of biochemical oxygen demand (BOD) is 1.76mg/l (Pre Monsoon) and 0.98 mg/l (Monsoon) and chemical oxygen demand (COD) at different sampling stations were mg/l (Pre Monsoon) and mg/l (Monsoon) respectively. BOD and COD levels were observed higher at the Pre monsoon and Monsoon period. A standard value of COD for drinking purposes is 4 mg/l and for bathing is mg/l while in the case of biochemical oxygen demand (BOD), standard for drinking purpose is 0.2mg/l and for sewage effluent is 20 mg/l (Wintgens et. al, 2005; Jalil and Njiru, 2010). Fig.1: Location of River Bhairab in South Western Region (Source: WARPO, 2004) 239

249 Table 2: Temperature at different stations of Bhairab River (Source: (i) CWQB 1963,(ii) EPA 1976) Statistical Parameters Pre- Monsoon Monsoon Remark Mean ( 0 C) Optimum Temp for Carp fish is 32 0 C Minimum ( 0 C) Diatoms grow best at o C, Maximum ( 0 C) Green algae grow best at o C, Blue-green algae at o C. Table 3: Turbidity at Different Stations of Bhairab River (Source: CWQB, 1963) Statistical Parameters Pre- Monsoon Monsoon Mean (NTU) Minimum (NTU) Maximum (NTU) Remark Amount of fish 162 lb/ acre for 25 NTU, 94 lb/ acre for NTU, 29 lb/ acre for over 100 NTU. Usable for Beverages if turbidity is 1-2 NTU Food products for 10 NTU Water used in boilers for 1-20 NTU (varies with type of boiler) High grade paper for 5-25 NTU Water used for cooling for 50 NTU. Tanning leather for 20 NTU Table 4: Electrical Conductivity (EC) at Different Stations of Bhairab River (Source: Ayres and Westcot, 1985) Statistical Pre-Monsoon Monsoon Remark Parameters Mean (ds/m) Three categories of EC is specified by FAO Minimum for irrigation: (ds/m) (i) None (<0.7 ds/m) Maximum (ds/m) (ii) Slight to Moderate (0.7 to 3.0 ds/m) (iii) Severe (> 3.0 ds/m) Table 5: Total Solid (TS) at Different Stations of Bhairab River Statistical Parameters Pre-Monsoon Monsoon Remark Mean (mg/l) Compared with the standards of Minimum (mg/l) suspended and dissolved solids. Maximum (mg/l) Table 6: Total Dissolved Solid (TDS) at Different Stations of Bhairab River (Source: Ayres and Westcot, 1985) Statistical Parameters Pre-Monsoon Monsoon Mean (mg/l) Minimum (mg/l) Maximum (mg/l) Remark Three categories of TDS is specified by FAO for irrigation. (i) None ( < 450 mg/l), (ii) Slight to moderate ( mg/l), (iii) Severe ( > 2000 mg/l). Table 7: Suspended Solid (SS) at Different Stations of Bhairab River (Source : ECR, 1997) Statistical Parameters Pre-Monsoon Monsoon Remark Mean (mg/l) SS for fish culture is <1500 ppm. For drinking water allowable Minimum (mg/l) concentration ( maximum): Maximum (mg/l) Bangladesh standard 10 mg/l WHO standard is 10 mg/l. 240

250 TDS ( mg/l) SS ( mg/l) EC ( ds/m ) TS ( mg/l) Temperature (0 C) Turbidity ( NTU ) Temperature variation of Bhairab River in Pre-monsoon & Monsoon period Stations Pre Monsoon Monsoon Turbidity of Bhairab River in Pre-monsoon & Monsoon period Pre Monsoon Stations Monsoon Fig. 2: Temperature at different stations of Bhairab EC of Bhairab River River Pre-monsoon & Monsoon period Stations Pre Monsoon Monsoon Fig. 4: Electrical Conductivity (EC) at Different Stations of Bhairab River TDS of Bhairab River in Pre-monsoon & Monsoon period Stations Pre Monsoon Monsoon Fig. 3: Turbidity at Different Stations of Bhairab River TS of Bhairab River in Pre-monsoon & Monsoon period Stations Pre Monsoon Monsoon Fig. 5: Total Solid (TS) at Different Stations of Bhairab River 50 0 SS of Bhairab River in Pre-monsoon & Monsoon period Stations Pre Monsoon Monsoon Fig. 6: Total Dissolved Solid (TDS) at Different Stations of Bhairab River Fig. 7: Suspended Solid (SS) at Different Stations of Bhairab River 241

251 Table 8: P H at Different Stations of Bhairab River (Source: CWQB, 1963.) Statistical Parameters Pre-Monsoon Monsoon Remark Mean Minimum Maximum Optimum P H for aquaculture Fish eggs could be hatched, but deformed young were often produced between P H Limit of P H for resistant fish species is Range tolerated by trout is P H Best range for the growth of algae is P H Food canning when minimum P H 7.5 freezing when minimum P H 7.5 Washing clothes when P H Rayon manufacturing when P H Tanning leather when P H 6-8 Table 9: Chloride at Different Stations of Bhairab River (Source: EPA,1976.) Statistical Parameters Pre-Monsoon Monsoon Remark Mean (mg/l) Minimum (mg/l) Maximum (mg/l) Recommended for aquaculture Fish and aquatic life is 0.01 mg/l. Max fish can tolerate 0.37 mg/l. Minimum requirement for High-grade paper is 0.3 mg/l. For surface irrigation 4-10 mg/l ( Slight to moderate), > 10 mg/l (Severe). Table 10: T-Alkalinity at Different Stations of Bhairab River (Source: (i) CWQB, (ii) EPA, 1976.) Statistical Parameters Pre-Monsoon Monsoon Remark Mean (mg/l) Minimum (mg/l) Maximum (mg/l) Recommended max alkalinity for, Carbonated beverages 85 mg/l Food products (canning) 300 mg/l Fruit juice 100 mg/l Pulp and paper making 50 mg/l Textile mill products mg/l Rayon manufacture 50 mg/l Limit for fish culture is mg/l Table 11: Dissolved Oxygen (DO) at Different Stations of Bhairab River (Source: ECR 1997.) Statistical Parameters Pre-Monsoon Monsoon Remark Mean (mg/l) Usable for Irrigation when DO 5 g/l. Minimum (mg/l) Fisheries when DO 5 mg/l. Recreational act. DO 5 mg/l Maximum (mg/l) Drinking purpose at DO 6 mg/l after disinfection. Cooling industries at DO 5 mg/l. Table 12: BOD at Different Stations of Bhairab River (Source : ECR 1997) Statistical Parameters Pre-Monsoon Monsoon Remark Mean(mg/l) Minimum(mg/l) Maximum(mg/l) Usable for Irrigation when Fisheries when Recreational activity Drinking purpose Cooling industries BOD 2mg/l. BOD 6mg/l BOD 3mg/l BOD 2mg/l after disinfection. BOD 10mg/l 242

252 Alkalinity DO ( mg/l) Ph Chlorides (mg/l) Ph Varietion of Bhairab River in Pre-monsoon & Monsoon period Stations Pre Monsoon Monsoon 8000 Chloride of Bhairab River in Pre-monsoon & Monsoon period Stations Pre Monsoon Monsoon Fig. 8: P H at Different Stations of Bhairab River Fig. 9: Chloride at Different Stations of Bhairab T-Alkalinity of Bhairab River in Pre-monsoon & Monsoon River period Stations DO of Bhairab River in Pre-monsoon & Monsoon period Stations Pre Monsoon Monsoon Pre Monsoon Monsoon Fig. 10: T-Alkalinity at Different Stations of Bhairab River. Fig. 11: Dissolved Oxygen (DO) at Different Stations of Bhairab River Fig. 12: BOD at Different Stations of Bhairab River Fig. 13: Graphical representation of COD of Bhairab River at different sampling station 8. CONCLUSION Because of high turbidity in both pre-monsoon and monsoon period, water may need a certain degree of treatment before its usage in food products, boiler, pulp paper industries, tanning leather and beverage industries. For the reasons of high turbidity of Bhairab River, water may be used for fish culture 94 lb/acre in the above mentioned period. Based on EC, according to the restriction category for using water in agricultural purpose suggested by FAO the water of Bhairab (Premonsoon) falls in the Severe category. Similarly, based on TDS, according to the restriction category for using water for agricultural purposes the water of Bhairab (Pre-monsoon) falls in the Severe category. The analysis shows that Bhairab River water is suitable for irrigation, fish culture, recreational activities, drinking purpose (after 243

253 disinfection) and cooling purpose in industries during the monsoon period. Public awareness concerning natural water management, water quality preservation, re-use of waste water in sustainable development is recommended for every river in Bangladesh. REFERENCES 1. Alam, M. J. B., Muyen, Z., Islam, M. R., Islam, S. and Mamun, M., 2007, Water quality parameters along rivers. International Journal of Environmental Science and Technology, Vol. 4. Issue 1. p Ayres, R. S. and D. W. Westcot., 1985, Water Quality for Agriculture. FAO Irrigation and Drainage Paper 29 Rev 1. Rome, Italy: FAO. 3. BBS, 1998, Statistical Year Book of Bangladesh, Bangladesh Bureau of Statistic, Ministry of Planning, Dhaka, Bangladesh. 4. Coleman, J. M., 1969, Brahmaputra River: Channel Processes and Sedimentation. Sedimentary Geology, 3,. 5. CWQB, 1963, Water Quality Criteria, California Water Quality Resources Board, Publication No. 3-A. 6. EEA, 1999, Environment in the European Union at the turn of the Century, European Environment Agency, Copenhagen, Denmark. 7. ECR, 1997, Environment Conservation Rules, E.C.R, 1997 for GoB (Government of Bangladesh),. Shedule 3, Standards for Water. 8. EPA, 1976, Quality Criteria for Water, U.S. Environmental Protection Agency, Washington, DC. 9. Jalil, M. A. and Njiru, C., 2010, Water demand management at household level: problems and prospects. Proceedings of the International Symposium on Environmental Degradation and Sustainable Development (ISEDSD 2010). 12'h April, Dhaka 31-37pp. 10. Mouri, G., Takizawa, S., Oki, T., 2011, Spatial and temporal variation in nutrient parameters in stream water in a rural urban catchment, Shikoku, Japan: effects of land cover and human impact. J. Environ Manage., 92(7), Metcalf and Eddy, 2003, Waste Water Engineering, Third Edition Tata McGraw-Hill. 12. Reddi, K.R., Jayaraju, N., Suriyakumar, I., and Sreenivas, K., 1993, Tidal flunctuation in relation to certain physico-chemical parameters in Swarnamukkhi river estuary, East Coast of India. Ind. J. Mar. Sci., 22, Singh, K P, Malik, A., Mohan, D., and Sinha, S., 2004, Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of Gomti River (India): A case study; Water Res Tareq, S. M., Rahaman, M. S., Rikta, S. Y., Islam, S. M. N. and Sultana, M. S., 2013,Seasonal Variation in Water Quality in Jamuna and Brahmaputra River in Bangladesh, Jahangirnagar University Environmental Bulletin, Vol. 2, pp Wintgens, T., Melin, T., Schiller, A., Khan, S., Muston, M., Bixio, D. and Thoeye, C., 2005, The role of membrane process in municipal waste water reclamation and reuse. Desalination, 178: WARPO, 2000b, Main Report, Volume No. 2, National Water Management Plan Project, Ministry of Water Resource, Government of Bangladesh. 244

254 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh COMPARATIVE STUDY OF NONLINEARITY MEASURES USING ROUTINE OPERATING DATA Malik M Tahiyat and M A A Shoukat Choudhury* Bangladesh University of Engineering and Technology, Dhaka Bangladesh Nonlinearity has a very significant effect on the closed loop performance of a controller/process as it can render controller tuning ineffective. Nonlinearities can initiate oscillations in process variables that may cause plant-wide oscillations, which in turn results in loss of plant profitability and rapid wearing and tearing of plant machinery. Thus, quantification of nonlinearity is important for designing appropriate controllers, troubleshooting process faults and ensuring smooth operation of a process plant. In this paper, two databased nonlinearity measures namely, bi-coherence and surrogate-data based measures are used on the physical model of a spherical tank and the nonlinearity measures are compared both for open-loop and closed-loop cases. 1. INTRODUCTION Study of Nonlinear systems have been of foremost interest to researchers because most physical systems in reality are nonlinear. Nonlinear systems are defined by those, which do not follow the principle of superposition. Nonlinearities in process variables can arise for various reasons for example valve stiction and which, in turn, sets up oscillations that may propagate throughout the whole plant. Quantification of nonlinearity is also important for judging the adequacy of linear controllers. Two broad approaches exist for measuring nonlinearity of a process: Model based measures and Data-based based measures. The preference of the Data-based approaches over the Model-based resides on the fact that Model-based approaches, like Best Linear Approximation and Curvature-Based methods, require a process model, which is often unavailable or difficult to obtain (Choudhury et al. (2008)). Therefore, in recent times, data based methods are gaining popularity because they require time series data of the process which are readily available from the DCS or data historian. The data-based approaches include bi-coherence based approach, surrogate data-based approach, Lyapunov exponents and Correlation Dimension. Most notable data based methods include Bicoherence-Based Measures, proposed by Emara Shabaik et al. (1996) and Choudhury et al. (2004); surrogate Data-based measures by Kantz and Schreiber (1997) and Theiler et al. (1992) and Harmonic Analysis by Paulonis and Cox (2003), Ruel and Gerry (1998), and Thornhill and Hagglund (1997). Correlation dimension and maximal Lyapunov exponent have been examined for the diagnosis of nonlinearity in chemical processes by Zang and Howell (2005a,b). In this paper, an overview of nonlinearity is given in section 1. Two data based methods are briefly reviewed in section 2. A `Spherical Tank' process used for simulation study is described in section 3. The nonlinearities of the aforementioned system are quantified using data-based measures of nonlinearity in section NONLINEARITY MEASURES 2.1 Bi-coherence-based Method The bi-spectrum is the simplest of the various frequency domain HOS (Higher Order Statistics) techniques. It is the frequency domain counterpart of the third-order moments. The bi-spectrum is normalized in the following way to give a measure called bi-coherence whose magnitude is bounded between 0 and 1: Where, X(f) is the Fourier transform of the data series x(t). Significance of bi-coherence magnitude at each individual bi-frequency is given by: * Corresponding Author: M A A Shoukat Choudhury shoukat@che.buet.ac.bd.com

255 Where, K is the number of data segments used in bi-coherence estimation and is the critical value calculated from the central distribution table for a significance level of α with two degrees of freedom. Those bicoherence values which satisfy the above condition are termed as. Choudhury et al. (2008) the quantified the total nonlinearity present in the time series using the following index: 3. PROCESS FOR SIMULATION STUDY: SPHERICAL TANK The level of a spherical tank is used as a nonlinear process for simulation study as shown in Fig Surrogate-data based Method The purpose of surrogate data methods is to create synthetic data sets called surrogate time series, having the same power spectrum, but with the phase coupling removed by randomization. A key property of the test time series is then compared to that of its surrogates, and nonlinearity is diagnosed if the property is significantly different in the test time series (Theiler et al. (1992); Kantz and Schreiber (1997)). For a time-series, the surrogate data is calculated by: z = FFT(test time series) (4) Where, FFT=Forward Discrete Fourier Transform. Then, Fig 1: A Spherical Tank System The model equation is given by: Where the outlet flow rate at time t, h is the height of the water level from the bottom of the tank, R the radius of the spherical tank and d corresponds to the delay in the input flow rate. The outlet flow rate, can be expressed as Where, N = number of samples in the time-series. The quantity is a random phase in the range 0-2π. Then, Surrogate data = IFFT (6) Where IFFT=Inverse Discrete Fourier Transform. An embedded matrix of both tests and surrogate data has been created. Squared Prediction errors of both test data, and surrogate data, are calculated as described in Choudhury et al. (2008). Surrogate Nonlinearity Index, is then calculated from: Where and are the mean and variances of M sets of, respectively. Where, g is the gravitational constant and the height of the outlet pipe from the base of the vessel. For the open-loop simulation of the system, R=0.5m, and =0.01m have been used. The details of the parameters of the aforementioned model equation can be found in Agrawal and Lakshminarayanan (2003). The control of water level in the tank is accomplished by manipulating the inlet volumetric flow rate. 4. SIMULATION RESULTS Linear systems are said to exhibit `Sinusoidal fidelity i.e. a sinusoidal input will produce a sinusoidal output of the same frequency; nonlinear systems, however, produce additional frequencies as well. Thus, to study oscillatory behavior of a process, sinusoidal signals of varying frequencies and amplitudes are added to the systems. Then the measures of nonlinearity are estimated using the output level data. 246

256 4.1 Results for Open-loop Case Results using Bi-coherence based Method: Figure 2 shows that for small magnitudes of input signals, the values of TNLI are almost zero. Thus, the spherical tank system can be assumed locally linear as portrayed by the flat regions on the left portion of the plot. As the amplitude of excitation signal increases beyond a certain value, nonlinearity jumps as visualized from the several peaks at the right portion of the plot. The reason for this can be attributed to the fact that nonlinearity increases at a point where the total surge volume of the tank drops below a certain level. With the decrease in liquid volume, the tank loses its ability to attenuate disturbances, and thus it contributes to an increase in TNLI. Another fact is that the curvature of the spherical tank increases as we move away from the centre along the top or bottom direction of the tank. Thus the height of the same volume of water will behave in a more nonlinear fashion when operating closer to the top or bottom portion of the tank than it would while operating near the centre. Another finding is that the nonlinearity of this particular system is not very sensitive to changes in frequency. Therefore, it can be concluded that nonlinearity of the process depends on the size of the excitation signal. to changes in amplitude. While the TNLI varied from 0 to 0.6 in its plot,, varied from negative to slightly above 1. Fig. 3: Trend of in open loop 4.2 Results for Closed-loop Case A PI Controller is implemented to control the water-level of the spherical tank by manipulating the input flow-rate Results using Bicoherence based Method: The nonlinearity test results are shown in Fig. 4. As depicted from the absence of peaks in the right portion of the plot, the figure clearly shows that for the same amplitude and frequency, the TNLI is smaller in the closed-loop feedback configuration than in open loop. Also, at high frequency, the nonlinearity does not rise with the increase of amplitude because the tank essentially operates as a low-pass filter. Thus, it can be stated that the PI controller has contributed towards the decrease in nonlinearity of the process. Fig. 2: Trend of TNLI in open loop Results using Surrogate-data based method: The Surrogate-data based measure is applied to the same data-set. Figure 3 shows that nonlinearity is increasing with both frequency and amplitude. However, the rise in is neither uniform nor monotonic. The dependency of on amplitude can be attributed to the fact as discussed previously. However, Surrogate-data based method showed a higher sensitivity than Bi-coherence-based measure Fig. 4: Trend of TNLI in closed loop 247

257 4.2.2 Results using Surrogate-data based method: Surrogate data-based method gives the same message as portrayed by the Bi-coherence-based measure. This is shown in Figure 5. Comparison between Figures 3 and 5 shows that in case of the latter, values are lower than those in the former plot. In case of open loop, values of increased from negative to slightly above 1. In case of closed loop scenario, no such trend in was present in the plot and most of the values of were less than 1. Both the measures were able to show a decrease in nonlinearity in closed-loop condition as opposed to open-loop condition. Surrogate-data based measures showed a higher sensitivity to changes in amplitude and frequency of input excitation signals than the Bi-coherencebased method. The decrease in nonlinearity is more visible in case of Bi-coherence-based method as several peaks in the plot for open-loop cases were dropped for the closed loop cases. REFERENCES Fig. 5: Trend of 5. PRACTICAL ISSUES in closed loop The most notable difference between the two methods is the time taken for the execution of each algorithm. Using 2048 data points, bi-coherencebased measure required approximately 2-3 minutes of computational time while Surrogate-data based measure required around 22 minutes for execution for a core i-5 Intel processor and 4 GB RAM computer. The simulations were executed in in MATLAB & SIMULINK 2013a. Another difference lay in the number of data points required by each method to deduce a suitable pattern. Surrogate-data based measure produced a more perceptible pattern while working with 512 data points than with On the other hand, TNLI requires 2048 data points for getting reliable estimates. 6. CONCLUSIONS The study compares two data-based approaches for measuring nonlinearity: Bi-coherence-based measure and Surrogate-data based measure through application to a spherical tank model. The experiments were performed both for open-loop and closed-loop cases. The following conclusions can be made from this study: 1. Agrawal, P., Lakshminarayanan, S., Tuning proportional-integral-derivative controllers using achievable performance indices. Industrial & engineering chemistry research 42 (22), Choudhury, A. A. S., Shah, S. L., Thornhill, N. F., Diagnosis of process nonlinearities and valve stiction: data-driven approaches. Springer. 3. Emara-Shabaik, H. E., Bomberger, J., Seborg, D. E., Cumulant/bispectrum model structure identification applied to a ph neutralization process. 4. Kantz, H., Schreiber, T., Nonlinear time series analysis, vol. 7 of cambridge nonlinear science series. 5. Luyben, W. L., Process modeling, simulation and control for chemical engineers. McGraw-Hill Higher Education. 6. Paulonis, M. A., Cox, J. W., A practical approach for large-scale controller performance assessment, diagnosis, and improvement. Journal of Process Control 13 (2), Pottman, M., Seborg, D. E., Identification of non-linear processes using reciprocal multiquadric functions. Journal of Process Control 2 (4), Ruel, M., Gerry, J., Quebec quandary solved by fourier transform. PULP AND PAPER 9. Shoukat Choudhury, M., Shah, S. L., Thornhill, N. F., Diagnosis of poor control-loop performance using higherorder statistics. Automatica 40 (10), Theiler, J., Eubank, S., Longtin, A., Galdrikian, B., Doyne Farmer, J., Testing for nonlinearity in time series: the 11. method of surrogate data. Physica D: Nonlinear Phenomena 58 (1), Thornhill, N., H agglund, T., Detection and diagnosis of oscillation in control loops. 248

258 Control Engineering Practice 5 (10), Zang, X., Howell, J., 2005a. Correlation dimension and lyapunov exponent based isolation of plant-wide oscillations. 14. Dynamics and Control of Process Systems 2004, Zang, X., Howell, J., 2005b. Isolating the root cause of propagated oscillations in process plants. International Journal of Adaptive Control and Signal Processing 19 (4),

259 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh PERMIT-TO-WORK (PTW) SYSTEM: A CASE STUDY OF BANGORA GAS PLANT Chowdhury Mohammad Touhid Amin 1 *, Sultana R Syeda 2 1 EHS Manager-Designate, KrisEnergy Bangladesh Limited, Dhaka 1212, Bangladesh 2 Department of Chemical Engineering, Bangladesh University of Engineering and Technology, Dhaka 1000, Bangladesh With the maturity of the chemical process and allied industries in Bangladesh, health and safety is receiving increasing attention from all parties concerned. One of the critical areas of health and safety in complex process plants is the permit-to-work (PTW) system designed to control non-routine work processes, such as maintenance, start-up, and trial runs. In Bangladesh only a few privately owned organizations have PTW system in place to carry non-routine works safely. The present paper is a study of the application of PTW to Bangora Gas Plant of KrisEnergy Bangladesh Limited during planned shutdown from October, The paper elaborates the PTW system in place and demonstrates how it is helpful in carrying out maintenance work safely as well as in identifying potential hazards. 1. INTRODUCTION In process plants, reliable and productive plant operations are as important as occupational safety that requires employees be safeguarded from accidents in the work site. Ambiguous work plans weaken the quality of work management and give rise to misunderstandings between workers, which may lead to an incident. According to the Health and Safety Executive (HSE) (Health and Safety Executive, 1987), 30% of the accidents which occur in the chemical industries are maintenance related. The Accident Database of Institution of Chemical Engineers shows that over 700 accidents of the 5000 listed were maintenance-related, which are typically controlled by permits-to-work (PTW). Permitsto-work (PTW) is essentially a management tool for coordinating and controlling non-routine work processes, such as maintenance, start-up, and trial runs etc. in a potentially hazardous environment [Health and Safety Executive, 1996]. The accident database also reveals that the PTW systems in place were either poor or not followed when the incidents took place. Petroleum and allied industries store and process large quantities of hazardous substances including flammable and toxic materials, therefore, prone to serious incidents. One such major incident occurred on July 6, 1988 at the North Sea oil installation of Piper Alpha, which was destroyed following a series of explosions and a major fire. One hundred and sixty-five men lost their lives. One of the outstanding causes of the tragedy of Piper Alpha was reported to be the breakdown in coordination of hazardous activities (Cullen, 1990). To prevent such incidents it is vital that there is effective management of hazards, including the use of safe systems of work. The failure in coordination of hazardous activities in Piper Alpha led many operators of offshore oil installations to review their own safety systems (Iliffe et al. 1999; Matsuka and Muraki, 2002). Suggestions were made for further improvements in the existing system and computerizations of it (Lee and McMillan, 1992; Booth and Butler, 1992). In Bangladesh the major chemical, oil and gas processing industries belong to a few government owned umbrella organizations, namely, BCIC, Petrobangla, Bangladesh Petroleum Corporation etc. Most of the plants under these organizations do not have established safety work system for their maintenance works. Any accident related to occupational safety generally remain unreported unless fatal. A number of the multinational organizations in the country, although in limited form, follow safe work practices in their work premises. KrisEnergy Bangladesh Limited is one of them. KrisEnergy is an independent upstream company ** Corresponding Author: Chowdhury Mohammad Touhid Amin, touhid.amin@krisenergy.com

260 focused on the exploration, development and production of oil and gas in the basins of Southeast Asia. The company portfolio contains three offshore producing assets, the B8/32 and B9A oil and gas producing complex in the Gulf of Thailand and the onshore Bangora gas field in Block 9 in Bangladesh (Company Profile, KrisEnergy, 2014). Permit-to-work systems are part of the task risk assessment process of its Bangora Gas Plant (Permit-to-work Procedure KrisEnergy Bangladesh Ltd, 2014). In this paper different types of permits to work issued during the planned shutdown from October, 2014 of this gas plant are elaborated. The positive outcomes of the issued permits as well as presence of hazards during the work were identified. Suggestions for further improvement were also made. 2. PERMIT TO WORK (PTW) SYSTEM AT A GLANCE The PTW is defined by the E.E.T.P.U. [E.E.T.P.U., 1979.] as "a laid out and considered method of working that takes proper account of the potential 'hazards to employees and others in vulnerable situations, and provides a formal framework to ensure that all of the steps; necessary for safe working have been anticipated and implemented." The overall objectives of the PTW systems may be summarized as follows (Lee and McMillan, 1992): o Ensuring proper authorization for the work. o Stating explicitly the exact identity and nature of the work, and associated hazards. o Ensuring the necessary precautionary measures are taken. o Providing a record of the work and the safety measures taken. o Providing a formal procedure to ensure that the work has been done in a safe manner, and that the plant affected is in safe condition. The isolation of equipment from hazardous energy sources to protect workers is the first step of any maintenance work. Hazardous energy sources include electrical, hydraulic, pneumatic, mechanical, chemical, and thermal sources. The isolation of equipment is accomplished by using devices such as disconnecting switches or isolation valves along with posted tags and signs to prevent unintentional contact. Isolation of all hazardous energy sources in the workplace is essential in PTW systems. Under the PTW, the responsibilities fall on three kinds of people (Guidelines on permit-towork,1993): 1. The Approval Authority: Identifies the equipment to be worked on, and the specific work to be carried out (e.g. Offshore Installation Manager /Head of Plant Maintenance). 2. The Designating Authority: Specifies the safety precautions to be taken, such as gas testing, protective clothing and mechanical/ electrical isolations, before the permit is issued; and he must check that the work has been completed satisfactorily and the isolations removed before the equipment is returned to service (e.g. the 'Responsible Person Head Production/ Operations Supervisor). 3. The Performing Authority: Carries out the work according to the permit, adhering to the safety precautions and returns the permit to the DA upon completion or suspension (e.g. work party foreman). It is to be noted that although there are industry guide-lines for PTW (Oil Industry Advisory Committee, 1988), there is no 'standard' permitto-work system. Consequently, the actual permitto-work system varies from operator to operator and plant to plant. In permit-to-work (PTW) System when a task is identified an appraisal is carried out to identify the nature of the task and its associated hazards. Next, the risks associated with the task are identified together with the necessary controls and precautions to mitigate the risks. PTW form is the core of the permit-to-work procedure, all other documents, certificates, forms, are not stand-alone documents. The work permit is the master written statement signed by the appropriate, authorised persons, allowing work to be performed on under a stated set of preparations and controls. Permit-to-work can be of two types, namely, cold work and hot work. Cold work is defined as a task which does not under normal circumstances, produce a source of ignition. Hot Work is defined as tasks using a heat generating, open-flame or spark producing apparatus. Hot work includes, but is not limited to, welding, cutting, burning, grinding, and any related heat-producing jobs that could ignite combustible materials or flammable atmospheres (Permit-to-work Procedure KrisEnergy Bangladesh Ltd, 2014). 251

261 Number of Jobs Days 3. CASE STUDY 3.1 Scope Shut Down About 65 permits in total were issued during the planned shutdown from October, 2014 in Electrical, Instrument and Mechanical jobs. Examples of electrical jobs are yearly PMR of motor, switch boards, distribution boards, commissioning and function testing of new UPS system etc. Instrumentation jobs include installation of surge protector, rectification of valve leakage and valve passing, automation of N 2 snuffing system etc. Examples of mechanical jobs are replacement of Pressure Safety Valves (PSV) with certified PSVs, installation of isolation valve at the D/S wellhead Choke valve, internal cleaning and inspection of vessel, installation of corrosion coupon, modification of fuel gas line to the Regen Gas Heater, internal inspection of X-mass Tree valves, replacement of Actuator, replacement of choke valve etc. Figure 1 summarizes the percentage of different types of job carried out during the shutdown Electrical Instruments Mechanical There were four Work Permits applied during the shutdown, namely, o Hot Work A (open flame) Valid one shift o Hot Work B (spark potential)valid up to 3 days/shifts o Hot Work C (workshop) Valid up to 7 days/shifts O Cold work Valid up to 7 days/shifts Figure 3 shows the types and validity of the permits. All of these permits are supported by certificates and forms which can be attached to any of the four permits e.g. Confined Space/Vessel Entry, Safety System Isolations etc Hot A Hot B Hot C Cold Hot A Hot B Hot C Cold Fig. 3: Types of permits and their validity in days Fig. 1: The percentage of different types of job (%) during shutdown Figure 2 shows top 5 high risk activities carried out during this period, which include heavy lifting and work at heights during installation, change of process equipment, work on different electrical structure, entries to confined space for internal vessel inspection, welding jobs (hot work) etc. Mainly three types of certificates were used during the shutdown period. Figure 4 shows the percent of different certificates used during the planned shutdown period Isolation SSIC (Safety System Isolation) Heavy Lifting Work At Height Electrical Confined Space Entry Job Category Fig. 2: Categories of high risk jobs Hot Work (Open Flame) Fig. 4: Types of certificates (%) Confined Space Entry (CSE) 252

262 3.2 System Administrations To facilitate System Administration, Auditing, and good System Management, the following elements, controlled by the Area Authority were in place: o o o o o Permit Register Certificate Register Authorized (work in progress) on Permit Display Board Extended Period Isolation on Permit Display Board Completed Work Permit and attachments Archive File The original (top) copy of the Active PTW with its attachments, including the toolbox talk form and associated certificate was prominently displayed in a plastic folder at the work site. The 2 nd copy of the Active PTW with its attachments was displayed on the Permit to Work board in the Control room. The 3 rd copy of the Active PTW with its attachments was displayed in the Permit Control Board. Field Manger performed the role of the Permit Controller and carried out the following steps o o o o o o Identify the location of active permits. Identify areas of potential conflict. Locate personnel/work teams in the event of an Emergency. Locate Major isolations. Identify safe access and egress and maintain safe escape routes. Display an area plot plan that accurately reflects as-built status of the facility. 3.3 Observations PTW Audits were conducted by all departments, and assisted by the EHS Department as required. Additionally, Hazard Observation Cards were submitted during the shutdown period by the workforce. The positive outcomes, areas for improvement and recommendations based on the audit reports, hazard observation cards and feedback from EHS team in the field are listed below Positive outcomes: o For all high risk activities, additional Risk Assessments were completed. o General gas test conducted for the whole facility before start of every shift. o General toolbox talk conducted with all contractor personnel before every shift. o 100% compliance maintained in all Confined Space Entry jobs. o o o Emergency Mustering Exercise conducted with all personnel to test the overall response. Site Doctor verified Medical Certificates of the contractor personnel to ensure they are fit for work. Overall PPE compliance was maintained satisfactorily Hazards reported in heavy lifting jobs: o A crane was being driven by a helper with front wheel locked at the lay down area. o Many of the contractor personnel respected and obeyed the boundaries erected for different jobs of shutdown. But a few of them failed to maintain the boundaries and crossed them without taking permission from the Performing Authority Hazards Reported in Work at Height: o o o o Two contractor personnel were climbing the ladder at the same time While lifting and welding job was ongoing, there was no barrier in place to stop unauthorized entry. During scaffolding construction, scaffolders stood on the scaffolding tube and gas line. A worker was walking on the framework for cellar plates when the plates were not in place Hazards reported in electrical jobs: o Due to shortage of welding cable, working groups used two welding rod holders with a joint to extend the cable. Also the connection of the joint was naked could lead to electrocution. o Battery was removed from portable generator without using gloves and insulated tools. o Worker (grinder) placed the grinding machine beside his foot with power on. There was no switch guard on the grinding m/c and it could start incidentally Hazards Reported in Hot Work o Grinding spark was directly falling on Oxygen, acetylene and LPG cylinder which were placed just 5 feet away o Two helpers were standing on the line of grinding spark. o Welding job was ongoing during rain. o During hot work on one jobsite, no fire extinguisher was available nearby. o Air hose connected with pneumatic torque found cracked. o Degreaser mixed water was found in the drain line 253

263 o Operator manually topped up diesel to generators without hand pump and proper PPE Recommendations: o According to the current PTW procedure, 10% of total permits issued in the facility are being audited. Considering the number of hazard observations, permit audit (%) need to be increased. o o Use of permit control board can be utilized by the Area Authority beyond Shutdown time for routine activities. Electronic PTW system can be considered to reduce human error on PTW administration and better record keeping. o PTW Audits are predominantly being conducted by the EHS department. Personnel from other departments need to engage themselves more actively in the process. 4. CONCLUSIONS The issued permits-to-work, although had specific purposes, helped improving the safety scenario of the working environment as a whole. It was also found that the hazards could not be eliminated completely. Most of these hazards were related to safety culture of workers and contractors. Thus, creation of safety awareness through advocacy and trainings need to be integrated with safe working systems to get the maximum benefits. The concept of Permit-to-work system in chemical industries is not a new one. However, it has not yet been seriously considered in local industries. This paper presents a real case of PTW application in a local plant that demonstrates the effectiveness of such system and encourages introduction of safe work practice at large in our country. REFERENCES 1. Health and Safety Executive, 1987, Dangerous Maintenance, 2 (HMSO, London, UK). 2. Health and Safety Executive, 1996, Setting Up and Running a Permitto- Work System: How to do it, 1 (HMSO, London, UK). 3. Cullen, W.D., 1990, The Public Inquiry into the Piper Alpha Disaster (HMSO, London, UK). 4. Iliffe, R. E., Chung, P. W. H. and Kletz, T. A., 1999, More effective permit-to-work systems, Trans IChemE, Part B, Proc Safe Env Prof, 77: Matsuka, S. and Muraki, M., 2002, Implementation of transaction processing technology in permit-to-work systems, Trans IChemE, Part B, 80: Lee, B. S. and McMillan, W.S. A Knowledge Based System For Offshore Permit-To-Work Management Proceedings of the Second (1992) International Offshore and Polar Engineering Conference, San Francisco, USA, June 1992, Safety Science, 15 (1992) , Elsevier 7. Booth, M. and Butler, J.F., A new approach to permit to work systems offshore. Safety Science, 15: Company Profile, KRIS ENERGY - KrisEnergy2014, 26 December 2014, 9. KrisEnergy Bangladesh Ltd (T-BD-OPS- PRO Permit-to-work Procedure) 10. E.E.T.P.U., Safety, Health and Welfare Code of Practice - Television and Audio Servicing Industry, Electrical, Electronic, Telecommunications and Plumbing Union, London. 11. Oil Industry Advisory Committee, A Guide to the Principles and Operation of the Permit-to-work Procedures as Applied to the UK Petroleum Industry, Health and Safety Executive. 12. Guidance on permit-to-work systems HSG250 ISBN ) 13. Guidelines on permit-to-work (P.T.W.) systems OGP Report No.6.29/189 January 1993) 254

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266 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh UTILIZATION OF BANANA PSEUDO-STEM IN PRODUCTION OF MINERAL SAP DRINKS, FLOUR AND LIQUID DETERGENT Seefat Farzin, Fouzia Hasan Nowrin and Md. Mominur Rahman* Department of Chemical Engineering Bangladesh University of Engineering and Technology, Dhaka-1000, Bangladesh Banana pseudo-stem has an immense potential in food industry, mostly due to its high mineral content, availability, easy processability and medicinal value. This paper contains a proposal to use banana pseudostem from Musa sp. to produce mineral sap drinks, bakery ingredient and liquid laundry detergent. Physiochemical compositions and properties of extracted liquid, flour and ash from banana pseudo-stem were determined and the performances of finished products were evaluated. Parameters measured include minerals content (sodium, potassium, iron, calcium, magnesium, manganese, zinc, phosphorous), total solid, total dissolved solid, ph, starch, sugar, fat, carbohydrate, protein etc. Due to the presence of high amount of sodium, potassium and magnesium in the extracted liquid, it has comparable properties to be used as a sports drink. The flour from stem is a nutritious mixing ingredient with wheat flour in baking due to high dietary fiber content. Production of liquid detergent is profitable and less complicated than traditional processes due to easy processing of an alkaline solution. This study has shown significant progress towards the use of banana pseudo-stem in food and detergent industry and paves a way to rethink other possibilities that can support a sustainable environmental alternative of commercial products. 1. INTRODUCTION Banana is a tropical herbaceous plant composed of concentric layers of peels in the stem. The peel, trunk, and fruits of banana are rich in essential minerals (Twyford and Walmsley, 1974; Selema and Farago, 1996; Cordeiro et al., 2004; Oliveira et al., 2007; Haslinda et al., 2009). These stems also contain high quantity of starch, reducing starch and resistant starch; which are vastly important for proper metabolic and immunological function of the human body (Haslinda et al., 2009). Potassium (K) content is beneficial for people suffering from hypertension and excessive excretion of K through bodily fluids (Siddhuraju et al., 2001). Food enriched with iron can stimulate the production of hemoglobin in the blood and so helps in cases of anemia (Mohapatra et al., 2010). Also iron is an essential mineral in both human and animal body. Pseudo-stem sap can be used as mineral drinks and its flour could be used as bakery ingredients. This helps to reduce malnutrition (Marin et al., 2009). Furthermore, ash of these stems can be used to prepare liquid detergent due to presence of Na + and K + ions. There are also some suggestions to use pseudostem s fiber as making handicrafts or pulp and paper (Chertman, M. & Simões-Moreira, 2008) due to good morphological properties of these fibers, favoring production of cellulose with good mechanical strength (Haslinda et. al., 2009). After harvesting, banana plant is cut down and damped in fields. In these damping plants, a fungal attack called Sigatoka (Chillet, M., et al. 2009) creates an environmental nuisance. By effective using of fresh banana pseudo-stem (false stem composed of concentric roll blades and sheaths surrounding a growing point), this problem can be solved while adding value in the food industry. According to the FAO (2006), 72.5 million tones of bananas are being produced per year worldwide. According to the survey of Bangladesh Bureau of Statistics ( ), the production of banana decreased from 1 million ton in to 0.8 million ton in However, Bangladesh is the 18th country with abundant banana cultivation (NationMaster.com, 2013). The scope of the presented work is to check the physical and chemical composition of pseudo-stem sap, its core and ensure whether these could be used or not for human consumption and then finally assess the performance of the liquid detergent made from ash materials. * Corresponding Author: Md. Mominur Rahman, mrrahman@che.buet.ac.bd

267 2. EXPERIMENTAL METHOD 2.1 Banana Pseudo-Stem Mineral Sap Drink Extraction: Banana stems were collected from two species, i.e., Musa sp. cv. Bichi and Musa sp. cv. Kacha. Approximately 6 feet long pseudostems were extracted from the banana trunks. After washing thoroughly with distilled water, each part was cut into four parts to discard the core. Extraction of sap was performed using a sugarcane juice extractor. The sap was filtered with double rings filter paper and stored at 4 C Proximate composition: Total solids (TS), total dissolved solids (TDS), total suspended solids (TSS) and ash content were determined by gravimetric analysis. ph was measured using a ph meter (Denver instrument, model-215). Protein, total carbohydrate and fat content were measured by Kjeldahl method, difference method (FAO, 1988) and cold extraction method, respectively Mineral analysis: Fe, Mn, PO 4 and Zn concentrations were determined using UV Spectrophotometer (DR/4000) and Na, K concentrations were measured using Atomic Absorption Spectrophotometer (AAS-6800). Hardness (Ca, Mg) of both samples was measured by titration-based method (Kindstedt, P. S. & Kosikowski, F. V. 1985) Microbiological analysis: Necessary dilutions were made according to the Official Methods of Analyses of AOAC International (1995). For total count of mesophilic aerobic bacteria, incubation of 1.0 ml of the diluted solutions was prepared in ml of Count Agar Standard from Oxoid in Petri dishes. After solidification, inversion of dishes and incubation at 35 C was done for 48 hours. For determining of total yeast and mold in liquid sample, incubation followed by plate count was done with ml of Potato Dextrose Agar from Merck acidified with aqueous solution of 10% tartaric acid (ph 3.5). Petri plates were inverted and incubated at 25 C for 5 days (Speck, M. L., 1984). 2.2 Banana Pseudo-Stem Flour (BPF) Preparation: Banana pseudo-stem cores were collected and cut into small pieces. The pieces were boiled for approximately 15 min for softening the texture and then dried. The dried stems were blended (Jaipan IS-4250). Powdered stems were sieved allowing passing through 0.5 mm size sifter (mesh no ). The dried blended stems were then stored in an airtight plastic bottle in the refrigerator Proximate composition: Ash content was determined by gravimetric analysis. Total titratable acidity was measured by titrating a solution of BPF in water-ethanol mixture with dilute NaOH solution (Adelekan and Oyewole, 2010). Adelekan and Oyewole (2010) method was used for the determination of ph, with slight modification to accommodate laboratory resources. The ph value was determined by a ph meter (Denver instrument, model 215). Total soluble solid was determined with the help of a refractometer. For determining calorific value, ASTM D method was followed. Total starch content was determined according to the modified method of AOAC (Goni et al., 1997). Protein and total carbohydrate were measured through Kjeldhal method and difference method (FAO, 1988), respectively Mineral analysis: Fe, Mn, PO 4 and Zn concentrations were determined using UV Spectrophotometer (DR/4000) and Na, K concentrations were measured using Atomic Absorption Spectrophotometer (AAS-6800). Ca and Mg of BPF were measured by titrimetric method (Kindstedt, P. S. & Kosikowski, F. V. 1985). 2.3 Banana Pseudo-Stem Liquid Detergent The waste barks from the same samples were used in liquid detergent production. The residues of banana pseudo-stem were sun-dried and burnt. The ash was mixed with tap water up to its highest ph Then this raw mixture was filtered with double rings filter paper to obtain a liquid detergent solution. 3. RESULTS AND DISCUSSIONS 3.1 Banana Pseudo-Stem Sap Chemical compositions of pseudo-stem sap are shown in Table 1. Results show that extracted sap contained only a small amount of solids and low amount of sugar compared to 8% sugar content in sports drinks (D. G. Feriotti & A. M. Iguti, 2011). Table 1: Pseudo-stem sap proximate composition Parameters Musa sp. Musa sp. cv. Bichi cv. Kacha TS (mg/l) TDS (mg/l) TSS (mg/l) Total ash (%) ph Total sugar (%) Fat (%) Protein (%)

268 The main compositions of banana pseudo-stem are fiber and minerals, particularly potassium, calcium and magnesium (Emag, T. H. et al., 2007). This information reveals that pseudo-stem sap is also rich in these minerals. The mineral content of pseudo-stem sap are shown in Table 2. Analysis shows similar results i.e., highest amount of minerals that is present is potassium, with small amount of magnesium. Table 2: Pseudo-stem sap minerals Parameters (mg/l) Musa sp. cv. Bichi Musa sp. cv. Kacha Sodium Potassium Iron Manganese Calcium Magnesium Phosphorous Zink Table 3: Pseudo-stems sap microbiological activity Parameters (CFU/ml) Musa sp. cv. Bichi Musa sp. cv. Kacha Mesophilic ,000 aerobic bacteria Yeast and mold Table 4: Nutritional values of Banana pseudo-stem sap and commercial sports drink (Rovel, D., 2006) Parameters Musa sp. cv. Bichi Musa sp. cv. Kacha Commercial Sports drinks Sugar (%) Potassium (mg/l) Sodium (mg/l) Microbial analyses of sap are shown in Table 3. Here, mesophilic aerobic bacteria were present more than yeast and mold. The growth rate of mesophilic aerobic bacteria is greater than yeast and mold (Abadias. M., et al., 2007) under atmospheric conditions. Microbial growth depends on ph, moisture content, oxidation-reduction potential, nutrient content, antimicrobial constituents, and biological structures. This microbiological activity can be removed through ultraviolet action. Nutritional property of banana pseudo-stem sap compared to commercial sport drinks is almost similar with respect to sodium, whereas very high in potassium content and very low in sugar content (Table 4). However, better dilution and addition of nutrients can make the sap comparable to the sport drink. 3.2 Banana Pseudo-Stem Flour (BPF) Proximate compositions of BPF (Table 5) show slightly higher TTA and lower TSS values compared to the findings by Uma et al. (2005). According to Uma et al. (2005), ph of BPF ranged between This work showed more acidic values, which might be attributed to geological factors like soil and weather and plant genetics. BPFs showed gross calorific values of 3638 Kcal/Kg and Kcal/kg for Bichi and Kacha varieties, respectively. These values are comparable to that of wheat flour (calorielab, 2014), which ranges from 3620 to 3627 Kcal/kg. Total starch contents of BPFs were found to be lower than 25.50% (Shantha and Siddappa, 1970), due to the selection of tender banana stems. Table 5: Proximate compositions of BPF Parameters Musa sp. Musa sp. cv. cv. Bichi Kacha TTA (%) TSS (Brix ) ph Ash (%) Total starch (%) Protein Carbohydrate (%) Table 6: Banana pseudo-stem flour mineral content Parameters Musa sp. cv. Bichi (mg/100 g) Musa sp. cv. Kacha (mg/100 g) Sodium Potassium Iron Manganese Calcium - - Magnesium Phosphorous Zinc Mineral analyses of banana pseudo-stem flour (Table 6) showed that potassium is the most abundant mineral followed by magnesium and sodium. These results are similar to the reported values by Selema and Farago (1996). According to Montagut et al. (1965), Ca decreases with the growth of pseudo-stem and potassium ion replaces it, which justifies the experimental results. During the fruiting phase, K content decreases in pseudo- 257

269 stem and increases in fruits (Twyford and Walmsley, 1974). According to the Selema and Farago (1996), trace elements are present in a higher amount in the stem rather than in the fruit peel. Fe content was similar to the reports by Happi Emaga et al. (2007) Qualitative test of BPF: Since BPFs are rich in mineral, they were mixed with wheat flour in different proportions to verify the acceptability of the mixed flour as human food. To determine the quality of the product, BPF at different ratios (10%, 30% and 50%) was mixed with wheat flour and breads were prepared for taste test. Taste results among ten individuals (age between 24 to 50 years) manifested that taste of bread increases with the increasing proportion of BPF. 3.2 Banana Pseudo-Stem liquid Detergent Liquid detergent prepared from ash after burning the dried pseudo-stem was evaluated to check its performance in hand washing. Liquid solution was divided in three portions were then heated at three different temperatures, i.e., 40 C, 60 C and 80 C. A dirty cloth used for laboratory cleaning was divided into three portions and they were immersed into the different solutions. After washing, the dirty cloth becomes apparently clean and the resulting solution showed extracted stains and dirt in it. Comparison with the piece of cloth cleaned with normal water (without detergent solution) showed excellent performance of the detergent solution. Visual observations of the cloths washed with detergent and normal water (without detergent) were made (Fig. 1), which indicate that the optimum temperature is around 40 C. This makes it suitable for use in households. Alkali detergents are watersoluble alkalis in which ph range is usually (Edwards, J. K. P., 1969), while the maximum ph of liquid detergent prepared from ash was (a) (b) (c) (d) (e) Fig 1: Washing of dirty cloth at different conditions. (a) Dirty cloth (b) Cloth washing in normal water (c) Washing at 40 C with detergent (d) Washing at 60 C with detergent (e) Washing at 80 C with detergent. 3.3 Scope in Bangladesh According to Bangladesh Bureau of Statistics ( ) approximately 52 million banana plants grow in Bangladesh annually, which in turn has a great potential to produce approximately m 3 of sap enriched with minerals, tones of flour and m 3 of liquid detergent. 4. CONCLUSIONS The presence of essential minerals and medicinal properties in banana pseudo-stem sap has been shown with the possibility of its use as mineral drinks with some addition of sugar and sodium. Combination of wheat flour with BPF can meet dietary requirements, due to the substantial content of essential minerals. The detergent by-product has potential in removing emulsion wax, scuff marks, and heavy accumulations of dirt. The economical viability and low-foam properties are advantageous when compared to other commercial detergents. Banana pseudo-stem has proven itself to be an ideal example of utilization of waste agricultural resource to produce useful and valuable consumer products. The scope of this study was limited to three of them; however, there are tremendous possibilities of making other products that can substitute mineral and PVC products currently available in the market. The study on banana 258

270 pseudo-stem should be extended further to reach out these numerous possibilities. ACKNOWLEDGEMENTS This study was conducted in the laboratories of Civil Engineering Department of Bangladesh University of Engineering and Technology. The experimental facilities of Bangladesh Council for Scientific and Industrial Research (BCSIR) was also utilized for microbiological activity, fat, protein, sugar, total starch, and carbohydrate studies. REFERENCES 1. Accessed on May 27, 2014 at PM 2. Abadias, M., Usall, J., Anguera, M., Solsona, C., Vinas, I., 2007, Microbiological quality of fresh, minimally-processed fruit and vegetables and sprouts from retail establishments. 3. Adelekan, A. O. and Oyewole, O. B., 2010, Production of Ogi from germinated sorghum supplemented with soybeans, African Journal of Biotechnology 9(42): Association of Official Analytical Chemists. 1995, Cunniff, Patricia. Official Methods of Analysis of AOAC International. 16. ed. Arlington: AOAC. 5. Bangladesh Bureau of Statistics (BBS, ). 6. Bhat, R., Kiran, K., Arun, A. B. and Karim, A. A., 2010, Determination of mineral composition and heavy metal content of some nutraceutically valued plant products. Food Analytical Methods 3: Chaturvedi, U. C., Shrivastava, R. and Upreti, R. K., 2004, Viral infections and trace elements: A complex interaction. A review article, Current Science, 87(11): Chillet, M. et al., Sigatoka Disease Reduces The Greenlife On Bananas. Crop Protection, 28(1): Cordeiro, N., Belgacem, M. N., Torres, I. C. and Moura, J. C. V. P., Chemical composition and pulping of banana pseudo-stems. Journal of Industrial Crops and Products 19: Edwards, J. K. P., 1969, Floor Maintenance Materials: Their Choice and Uses, Transatlantic Arts Inc Feriotti, D. G., and Iguti, A. M., 2011, Proposal for Use of Pseudo-stem from Banana Tree, Maua Institute of Technology, Sao Caetano do Sul, Brazil. 12. Goni, I., Garcia-Alonso, A. and Saura-Calixto, F., 1997, A starch hydrolysis procedure to estimate glycemic index, Nutr. 17, Happi Emaga, T., Herinavalona Andrianaivo, R., Wathelet, B., Tchango Tchango, J. and Paquot, M., 2007, Effects of the stage of maturation and varieties on the chemical composition of banana and plantain peels. Journal of Food Chemistry in the Tropics 103: Haslinda, W. H., Cheng, L. H., Chong, L. C. and Noor Aziah, A. A., 2009, Chemical composition and physicochemical properties of green banana (Musa acuminata X balbisiana Colla cv. Awak) flour. International Journal of Food Sciences and Nutrition 60(S4): Kindstedt, P. S. and Kosikowski, F. V., 1985, Improved Complexometric Determination of Calcium in Cheese. Journalof Dairy Science, 68(4), Mohapatra, D., Mishra, S. and Sutar, N., 2010, Banana and its by-product utilisation: an overview. Scientific and Industrial Research 69: Montagut, G., Martin-Prével, P. and Lacoeuilhe, J. J., 1965, Nutrition minerale compare dans six essains. Fruits 20: NationMaster.com; o-agriculture-banana production; Accessed on June 14, 2013 at AM. 19. Oliveira, C., 2004, Equipamento Para Processo E Obtenção De Manta, A Partir De Fibra De Caule De Bananeira, Patent n#: PI Rovel, D., 2006, First in Thirst: How Gatorade Turned the Science of Sweat Into a Cultural Phenomenon, AMACOM Div American Mgmt Assn. 21. Selema, M. D. and Farago, M. E., 1996, Trace element concentrations in the fruit peels and trunks of Musa paradisiaca. Phytochemistry 42(6): Shantha, H. S. and Siddappa, G. S., 1970, Accumulation of starch in banana pseudo-stem and fruit, Journal of Food Science 35: Siddhuraju, P., Becker, K. and Makkar, H. P. S., 2001, Chemical composition, protein fractionation, essential amino acid potential and anti-metabolic constituents of an unconventional legume, Gila bean (Entada Phaseoloides Merrill) seed kernel. Journal of the Science of Food and Agriculture 82: Speck, M. L., 1984, Compendium of Methods for the Microbiological Examination of Foods. 2. ed. Washington, DC: Apha, Twyford, I. T. and Walmsley, D., 1974, The mineral composition of the robusta banana plant II. The concentration of mineral constituents. Plant and Soil 41:

271 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh BIOGAS PRODUCTION FROM ANAEROBIC CO-DIGESTION OF COW MANURE WITH KITCHEN WASTE AND WATER HYACINTH Salma A. Iqbal*, Farzana Tasnim, Aminur Rashid Chowdhury Department of Chemical Engineering and Polymer Science, Shahjalal University of Science and Technology, Sylhet-3114, Bangladesh Energy crisis and environmental pollution is the most concerned of today s world. In order to secure the future for ourselves and generations to follow, it is widely accepted that we must act now to reduce energy consumption and keep balance from deforestation in managing atmospheric emission of greenhouse effect. Hence, research in renewable energy for a green environment is a task of all countries. Renewable energy is often thought of as the next great technology that will one day replace mankind s dependency on fossil fuels. Other sources of energy are finite and will someday be depleted. Development of renewable energy is one of the important strategies adopted as part of Fuel Diversification Program in Bangladesh. The Renewable Energy Policy envisions that 5% of total energy production will have to be achieved by 2015 and 10% by 2020[1]. To achieve this target, the Government of Bangladesh is looking for various options preferably renewable energy resources. Biogas is one form of renewable energy. The prime objective of this paper is to compare biogas production and ultimate protection of environment from the harmful effects that would have been done by uncontrolled anaerobic digestion and to find an alternative source of energy. 1. INTRODUCTION Bangladesh is one of the most densely populated countries in the world, a total population of 120 million with a density 755 per sq. km, 81 percent of them living in the rural and the remaining 19 percent in the urban areas. As an agriculture country, Bangladesh is embedded with plenty of biomass which has been used for extracting energy burning directly or making biogas. Almost 80% people of our country directly or indirectly depend on agriculture. During winter seasons, huge amounts of vegetables are cultivated in our country which will be a potential source of kitchen waste. Due to lack of efficient transportation and preservation, huge amounts of vegetables are wasted, which may also be a source of biogas. As a riverine country Bangladesh is blessed with lots plants and trees which may be used for biogas production. Due to urbanization, many solid wastes are generated and the disposal of municipal solid waste is of great concern now a days. Solid waste contains lot of organic composition which is one of the sources of biogas. 2. AIM OF THE STUDY The principal goal of this present research work is given below: Biogas production from anaerobic co-digestion of Kitchen Waste & Cow Manure and Water Hyacinth, Cow manure & Sewage Sludge Comparison of biogas production of Kitchen Waste & Cow Manure and Water Hyacinth, Cow manure & Sewage Sludge To increase the biogas production rate To increase employment facility and enrich national economy. 3. MATERIALS AND METHODS The research work was conducted to investigate the production ability of biogas as an alternative energy from sewage sludge (SS), cow manure (CM), Water Hyacinth (WH) and kitchen waste (KW) through anaerobic digestion (AD). CM & KW and Water Hyacinth, CM & Sewage Sludge were digested by bacteria to produce biogas by biodegradation of organic materials. As reaction proceeds, the acidity increases, 1.5% NaOH on wet matter basis of loaded organic materials was also used to boost up digestion reaction by suppressing acidity. This whole process was conducted at 37 C. * * Corresponding Author: Salma A. Iqbal salmacep@gmail.com

272 3.1. Sources of Raw Materials The research work was conducted to investigate the production ability of biogas as an alternative energy from sewage sludge (SS), cow manure (CM), Rice Straw (RS), Jatropha (JT) & Water Hyacinth (WH) and kitchen waste (KW) through anaerobic digestion (AD). Sources of raw materials are given below: Cow Manure (CM), collected from a nearby village nearby. Sewage Sludge (SS), collected from the drain of SUST. Water Hyacinth (WH), collected from university Masjid Pond. Only the stem of WH was used. Kitchen waste (KW), collected from different halls of SUST and Surma residential area, Sylhet. to that of expelled water in the water collector. Each digester was connected to water chamber (plastic bottles) by a plastic pipe (gas pipe) which was used to pass the produced gas into water chamber. Another plastic pipe (water pipe) was used to take the displaced water from the water chamber to the water collector which was fitted air sealed by M-seal. Both the ends of the gas pipe were inserted at the top of the digester and the water chamber. The water pipe was inserted at the bottom of the water chamber and top of water collector. Fig.2: Hopper for mashing Fig. 1: Raw materials (i) cow manure (ii) Sewage sludge (iii) Kitchen waste (iv) Water Hyacinth 3.2. Waste Processing After removing the bones, plastic bags, metals and inorganic residues wastes were cut into small size in order to reduce size to get efficient biogas production [2]. Then these wastes were mashed by using hopper Experimental Setup A simple lab-scale apparatus was fabricated using digesters. Each digester was made of glass. The volume of digester was 1L each. CM with KW & CM with Water Hyacinth were fed to 1litre batch reactor. Both of them were loaded as 1:1 ratio & with a loading rate of 100 gm/l. Sewage Sludge was added with Water Hyacinth instead of normal water. Sewage Sludge was acted as seed of bacteria. 1.5% NaOH was added in both digesters. In this study the volume of produced gas was measured by water displacement method considering the volume of the generated gas equal Fig.3: Schematic diagram of the lab-scale experimental set-up 3.4. Lab-Scale Experiment Water Hyacinth was loaded with SS and CM. CM was charged as 50gm and SS with 500ml with other materials 50gm.NaOH were loaded with 1.5% of total solid contents in digesters. Again, 50gm KW was charged with 50gm of CM. These experiments were repeated several times Pilot Scale After performing multiple lab-scale experiments, we constructed two portable biogas reactors for pilot-scale experiment. 30 liters of water, 3 kg rice straw and 3 kg CM were putted into the reactor. 30 liters of the sewage sludge was loaded. The volume of each reactor was about 60 liter. A metal agitator shift was placed from the top surface of the reactor. The agitator was agitated manually. To maintain optimum temperature (37 C) for mesophilic digestion, a heating spiral coil was placed inside the 261

273 Volume Difference(mL) Volume difference(ml) reactor and hot water from water bath was passed through the digester by a pump. The reactor was operated in batch mode. Figure 5 illustrates the schematic diagram of the set up. Fig. 4: Lab Scale Setup 4.2. Biogas Production from KW & CM Gas Production from KW & CM Time (hours) Fig. 8: Gas Production from KW+CM [5] 4.3. Biogas Production from WH, CM & SS Gas Production from WH +CM + SS Time (Hours) Fig. 5 A portable biogas digester set up Fig. 9 Gas Production from WH+CM+SS[2] 4. RESULTS AND DISCUSSION 4.1 Composition of Kitchen Waste 5% 3% 4% 2% 7% 9% 14% 1% 55% (A) Rotten vegetables, (B) Rotten rice, (C) Cooked meat, (D) Fruits, (E)Cooked fish, (F) Rotten potato, (G) Bread, (H) Eggs shell, (I) Onion shell, 1% A B C D E F G H I 4.4. Comparison of Biogas production from KW+CM & WH+CM+SS for 254 hours Comparison shows that WH with CM produces much more gas than KW with CM. It can be said that WH with CM produces more than double the gas in comparison with CM at the same time. The gas from WH+CM was producing even after 374 hours. But the gas production from KW with CM stops after 240 hours. This huge difference is due to addition of sewage sludge & NaOH with WH & CM. Sewage sludge contains a lot of bio-digestible material in it. It also contains bacteria seed. But pure water doesn t contain any of that. Moreover NaOH was used to maintain ph and initiate bacterial action. These things help to increase the production of biogas. [4] So the degradation rate of Water Hyacinth, Cow Manure & Sewage Sludge is also higher than the degradation rate of Kitchen Waste & Cow Manure. Fig.7: Average physical composition of KW 262

274 Volume Difference(mL) 5. RECOMMENDATION Mesophilic condition can be implemented by putting reactor in glass house.[3] Lime/ Limestone can be used for better biogas production in rural or urban areas instead of NaOH. A government Policy on Biogas technology is urgently needed. Co-operation between govt. NGO & other stakeholder should be strengthened for the dissemination of the technologies. For treatment of H 2 S and CO 2 ; NaOH, Organic Amine and Benfield solution can be used. [6] Awareness should be raised to increase use of biogas and sustainable improvement. Biogas can also be used as industrial sector not only as household fuel. Support should be provided for more research on biogas. 6. CONCLUSIONS In a world where we feel the need of energy security more acutely with every moment, there is little space for ignoring the essence of development of the renewable energy sector. The search for alternative source of energy such as biogas should be intensified so that ecological disasters like deforestation, desertification, and erosion can be arrested. From the above discussion it can be said that co-digestion of water hyacinth with cow manure& sewage sludge can be another source of biogas production. With Mesophilic condition bacterial action and co digestion of cow manure and water hyacinth with sewage sludge will be a potential source of biogas for household as well as industrial energy source. Kitchen with CM can also be a reasonable substitute of natural gas. ACKNOWLEDGMENT The research work was conducted in the Water Analysis Laboratory of the Chemical Engineering & Polymer Science (CEP) Department, Shahjalal University of Science & Technology (SUST), Sylhet-3114, Bangladesh. The authors are grateful for the financial support of this research from Research Center, SUST and University Grants Commission (UGC), Bangladesh WH+CM +SS KW+CM Time (Hours) Fig.10: Biogas production(ml) vs. Time(hour) curve for KW+CM & WH+CM+SS 263

275 Total Gas Volume(ml) Gas Volume after 254 hours KW+CM WH+CM Fig.11: Comparison of biogas production of KW & CM and WH, CM & Sewage Sludge Table 1: Data table for biogas production per gm of biomass (degradation rate) after 254 hour Digester Loading Rate(gm/L) Biogas Production(ml) Degradation Rate(ml/gm) WH+CM+SS KW+CM REFERENCES [1] p?option=com_content&view=article& id=26&itemid=24 [2] Akhter Salma, Chowdhury Aminur Rashid, Tasnim Farzana; Study onanaerobic Co- Digestion of Cow Manure & Sewage Sludge with Rice straw, Jatropha, Water Hyacinth and Kitchen Waste to produce Biogas (unreleased) [3] García K, Pérez M. Anaerobic Co-digestion of Cattle Manure and Sewage Sludge: Influence of Composition and Temperature, Rafaela, Ruta 34, km 227 (2300), Santa Fe, Argentina. [4] Gregor D. Zupančič and Viktor Grilc, Anaerobic Treatment and Biogas Production from Organic Waste, Institute for Environmental Protection and Sensors, Slovenia, Volume 124, November 2012, Pages [5] Iqbal Salma A., Rahman Shahinur, Mizanur Rahaman, Abu Yousuf (ICME 2013), Anaerobic digestion of kitchen waste to produce biogas, Paper ID: 101 [6] J.I. Huertas, N. Giraldo and S. Izquierdo, Automotive Engineering Research Center- CIMA of Tecnologico de Monterrey, Removal of H 2 S and CO 2 frombiogas by Amine Absorption, ISBN:

276 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh PRODUCTION OF BIOFUEL FROM AGRICULTURAL WASTE Raka Islam and Rayhana N. Sohel Texas A & M University, College Station, Texas, USA M. A. A. Shoukat Choudhury* Bangladesh University of Engineering and Technology, Dhaka, Bangladesh The fact that fossil fuels will eventually run out has fomented the search for alternative energies. Biofuel is a popular form of alternative energy and from Bangladesh perspective, agricultural wastes like rice husk, wheat straw, corn cob, coconut shell and sugarcane bagasse are very promising raw materials. Pyrolysis is a major thermochemical process for producing biofuel and in this study a laboratory-scale batch reactor was assembled. The raw and crushed residues were pyrolized using three 2000 Watt heaters. The temperature was varied between C for a short reaction time and a mixture of oil, char and gas was produced. The oil was condensed by passing the heated stream through a 5 feet long U-tube condenser. The temperature profiles with time were determined for each sample. Percentage yield of oil and char were calculated and compared which showed maximum oil yield for saw dust and maximum char yield for corncob. The gross calorific values of the oil and char were compared for samples of corn cob, wheat straw, and rice husk and saw dust and they were in accordance with literature values. The calorific values of bio-oil ranged from 21.87MJ/Kg to 32.96MJ/Kg and that of char ranged from 22.37MJ/Kg to 29.17MJ/Kg. The energy obtained from the product samples were compared with the input energy from the heater. The results showed that agricultural wastes have vast potential as alternative fuels. 1. INTRODUCTION Biomass is an interesting answer to the growing demand for renewable energy. They are usually the by-products in various industries, i.e. agricultural, food, wood processing and paper industry or they can be purposely grown for energy utilization. Agricultural waste like rice husk, corn cob, wheat straw, coconut shell etc has great potential to be used as biofuels. Biofuel can be produced in biochemical or thermochemical method. Today only an estimated 46.5 % (World Bank, 2013) of the Bangladesh population is connected to the electricity grid. 29% of the energy comes from solid biofuels; they include rice straw, wood, cow dung etc. In global context, annual rice husk production is 137 million tonnes whereas, in Bangladesh, about 9.0 million tonnes of rice husk is produced reported in At present, about 67-70% of rice husk is consumed for steam producing in rice mills (Ahiduzzaman, et al., 2009). With a few exceptions, presently most of the boilers, used in these rice mills of Bangladesh are very inefficient. This results in a huge wastage of rice husk, which is an important source of biomass. Preliminary estimates are indicative that at least 50% of the rice husk produced could be saved and made surplus for its better use as input for small power generation. Similarly, corn cobs and wheat straws are mostly going in to waste. It is estimated that the total annual amount of recoverable agricultural-crop residues in Bangladesh is about 42 million tonnes and their proper utilization may go a long way in helping our energy crisis. The aim of this work was to produce biofuel from different agricultural wastes that are abundant in our country and compare these biofuels with conventional fuels in order to determine their potentials. 2. EQUIPMENT AND EXPERIMENTAL PROCEDURE A thermal reactor was constructed using mild steel pipe and plate. The reactor was insulated using 100% glass fiber yarn. A Teflon plate was placed between the cylindrical pipe and the plate for insulating purpose. A high temperature of about C was achieved by three 2000W heaters. Necessary provisions were made in the reactor for mounting the instruments for measuring pressure, temperature and a collection of fuel from the reactor. * Corresponding Author: M.A.A. Shoukat Choudhury, shoukat@che.buet.ac.bd

277 The gaseous products from the reactor were passed through a U-tube condenser with inlets and outlets for cooling water. The gaseous biofuel was cooled from C to room temperature. % Oil yield The feed was charged from the top of the reactor (Fig.: 1) and it was tightly sealed afterwards. In order to create an inert condition a nitrogen cylinder was used to circulate nitrogen through the reactor and the condenser. A thermocouple and pressure gauge were used to monitor the reaction parameters throughout the experiment. The valve was partially opened when pressure built up inside the reactor and the temperature was within the desirable range. A U-tube condenser was used to condense the product. The fuel was collected in a container. 3.2 Comparison of % yield of oil and char The oil and char obtained from rice husk, saw dust, corn cob and wheat straw was calculated and the yield was determined. From the figures (Figs. 2 and 3), it can be seen that the percentage yield of oil was the highest for saw dust and the percentage yield of char was the highest for corn cob % Char yield Rice husk Wheat straw Corncob Saw dust Types of agricultural wastes Fig. 2: Comparison of % char yield Fig. 1: Schematic diagram of experimental setup 3. RESULTS In this experiment, each of the test samples: rice husk, saw dust, corn cob and wheat straw were pyrolized in the batch reactor. Each time the calorific values were determined. The calorific value is the heat produced by combustion of a unit quantity of a substance under specified conditions. Here calorific value is expressed in calories per gram. For each sample, the experiment was run three times in order to check the repeatability. The chars of each sample were similarly tested. 3.1 Temperature profile during pyrolysis The rise in temperature with time has been compared for the pyrolysis of different raw materials. Based on the literature, the optimum temperature for pyrolysis of agricultural wastes is between 350 to C, the temperatures of the experiments were also maintained in this range. The highest temperature to reach was controlled depending on the yield and the duration of operation. When the oil collection rate appeared to considerably decrease, the heaters were turned off Rice husk 15 Wheat straw Corncob Saw dust Fig. 3: Comparison of % oil yield 3.3 Determination of calorific values The heat produced by combustion of a unit quantity of substance under specified conditions is called calorific value. Gross calorific value = (Temperature rise heat capacity of the calorimeter thermochemical corrections) /mass of sample = where, heat capacity of the calorimeter is 2425 cal/ 0 C & thermochemical correction = 30 calorie. 18 Types of agricultural wastes

278 Calorific value (Cal/gm) Types of agricultural wastes Mass of sample (kg) % yield of oil Average orcalific value (MJ/kg) % yield of char Average calorific value (MJ/kg) Output energy (KJ) Calorific value (cal/gm) 3.4 Property comparison of fuel and char The chart in Fig.4 shows the average values of the pyrolysis oil. For rice husk the average value from the three test runs was 7319 cal/gram and for wheat straw oil it was 5882 cal/gm. The values for saw dust and corn cob were close to 5300 cal/gm. The result implies that the biofuel from rice husk has the most energy content. The chars were tested similarly and Fig.5 shows that the highest calorific value was obtained for saw dust which was 6959 cal/gm. The values decreased from wheat straw to rice husk. The result indicates that the char from saw dust has the highest energy content among the other chars ricehusk wheat straw corncob sawdust heaters and the output energy was determined from the calorific values. Determination of input energy =Number of heater Power of heater duration of heater operation Number of heater used=3 Power of each heater=2000 watts=2kw Table 1: Input energy for each types of sample Types of agricultural wastes Duration of heater operation (min) Input energy(kj) = 3 2 duration of heater operation in sec Rice husk Wheat straw Corncob Sawdust Determination of output energy = Here, mass of oil=%yield of oil total mass of sample Mass of char= % yield of char total mass of sample Table 2: Output energy for each type of samples Types of agricultural waste Fig 4: Comparison of calorific values of oil Rice husk Wheat straw Corncob Sawdust sawdust wheat straw corncob ricehusk Types of agricultural wastes Fig. 5: Comparison of calorific values of oil 3.5 Comparison of input and output energy The energy input and the energy obtained from the agricultural wastes were calculated and compared. The input energy was the energy from the electrical The calorific values of fossil fuel oils are around cal/gm whereas the oils from the agricultural wastes are in the range of 5000 to 7500 cal/gm. Biofuel from rice husk appears to be the best biofuel produced compared to the other three sources. Also, after comparing the values, it appears that that the sample which gives fuel with higher calorific value produces char with lower calorific values and vice versa. 267

279 4. RECOMMENDATION AND FUTURE WORKS In Bangladesh, renewable energy in the form of biofuel from the abundant agricultural wastes could help meet our energy demand & at the same time create a sustainable future. Although this experiment cannot yet be implemented in a commercial scale, this experiment proved the potential of agricultural wastes chiefly rice husk as a potential energy source. This experiment had certain flaws such as: the setup was not completely leak proof and the temperature measurement was to a small extent faulty as the thermocouple measured the temperature at a single point in the reactor. A better setup or a different reactor (such as fluidized bed, ablative reactor, circulating cone reactor etc.) would provide better bio-oil yield. Thermochemical techniques for pyrolysis consume energy in the process. Biochemical conversions could therefore prove to be more economical and have potential for commercial application. 5. CONCLUSION Pyrolysis of several agricultural wastes (rice husk, corncob, wheat straw and saw dust) were carried out in a batch reactor by thermochemical techniques to produce biofuel. The temperature profile with time was shown. Percentage yield of oil and char were determined and compared. The percentage yield of oil was highest for sawdust and the corncob gave the maximum yield for char. Calorific values of the biofuel and char produced from each sample were determined and compared with those of fossil fuels and different types of coals respectively. Among the four samples of biooil, fuel obtained from pyrolysis of rice husk showed highest calorific values, an average of 7320 cal/gm. This fuel had a flash point of 87 0 C and a fire point of 90 0 C. On the contrary the char obtained from rice husk had the lowest calorific values whereas the char from saw dust had the highest. The average calorific value of saw dust was about 7000 cal/gm which falls between those of bituminous and anthracite coal. The result of this experiment conforms to the potential of biofuel produced from the agricultural wastes. REFERENCES 1. Ahiduzzaman, M., Rice Husk Energy Technologies in Bangladesh. Agricultural Engineering International, Volume Demiral, _., Eryazıcı, A. & enso z, S. S., Bio-oil production from pyrolysis of corncob (Zea mays L.). Biomass and Bioenergy, Issue 36, pp Goyal, H., Seal, D. & Saxena, R., Biofuels from thermochemical conversion of renewable resources: A review. Renewable and Sustainable Energy Reviews, Issue 12, pp Ibrahim, N. B., Bio-oil from Flash Pyrolysis of Agricultural Residues, Denmark: s.n. 5. Jahirul, M. I., Rasul, M. G., Chowdhury, A. A. & Ashwath, N., Biofuels Production through Biomass Pyrolysis- A Technological Review. Energies, Volume 5, pp Ji-lu, Z., Bio-oil from fast pyrolysis of rice husk: Yields and related properties and improvement of the pyrolysis system. Journal of analytical and applied pyrolysis, Volume 80, pp Marshall, A., Commercial Application of Pyrolysis Technology in Agriculture, s.l.: s.n. 8. Mullen, C. A. et al., Bio-oil and bio-char production from corn cobs and stover by fast pyrolysis. Biomass and Bioenergy, Issue 34, pp PJ, D. W. & Huijgen WJJ, H. H., Pyrolysis of Wheat Straw Derived Organosolv Lignin. Journal of Analytical and Applied Pyrolysis, pp

280 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh ADSORPTIVE REMOVAL OF METHYLENE BLUE BY RUBBER LEAF POWDER Md. Akhtarul Islam, Md. Tamez Uddin*, Sourav Chowdhury* and Md. Yasin Department of Chemical Engineering and Polymer Science, Shahjalal University of Science and Technology, Sylhet-3114, Bangladesh Batch experiments were conducted to investigate the potentiality of rubber leaf powder (RLP) as a low cost adsorbent for the removal of methylene blue (MB) from an aqueous solution. Batch mode experiments were carried out by varying operational parameters such as initial concentration of MB, ph and temperature of the solution. The adsorbent was characterized by Fourier Transform-Infrared Spectroscopy (FTIR). The extent of MB removal was found to increase with increasing ph and decreasing temperature. The equilibrium data were well fitted by Langmuir isothermal model with monolayer adsorption capacity of 111mg/g and the sorption kinetics was found to follow a pseudo-second-order kinetic model. From thermodynamic study, the adsorption process was found to be spontaneous and exothermic in nature. It was concluded that RLP was a prospective adsorbent for the removal of methylene blue from an aqueous solution. 1. INTRODUCTION One of the major problems of industrialization is water pollution. Waste color effluents from industries like textile, paper, plastics, leather and food cause serious environmental problems. These color effluents are the result of the production of dye and as an outcome of its use in the textile and other industries. More than 100,000 commercially available dyes with over 7*10 5 tons of dyes are produced annually (Pearce et. al., 2003). In this study methylene blue (MB), a basic dye, which is used extensively in dying industry, is used to investigate the potentiality of adsorbent for the removal of MB from aqueous solution. Basically biological, chemical and physical treatment processes are the conventional methods for the removal of dyes from waste water but they have disposal problems as large amounts of sludge is generated at the end of the process (Lee et. al., 2006). Among all the physical treatment processes, adsorption with activated carbon has been reported to be the most effective method due to the ease of operation and comparable low cost of application process (Crini, 2006). However, regeneration problem, high operating cost and difficulty in separation from wastewater are major drawbacks of using activated carbon (Gupta and Suhas, 2009). This has prompted the search for alternative low cost adsorbent. Therefore attempts have been made to remove dyes from waste water using law cost adsorbent such as modified sawdust (Zou and Bai, 2013), raw and modified pine cone (Yagub et. al., 2013), coffee residues (Kyzas et. al., 2012), Pineapple leaf powder (Weng et. al., 2009), Hazelnut Husks (Ozer et. al., 2012), Red Mud (Ratnamala and Shetty, 2012), Pine Cone (Deniz et. al., 2011) and Peanut Hull (Tanyildizi, 2010). In this study, rubber leaf powder [Hevea brasiliensisl L.] was used as an adsorbent to remove MB from aqueous solution. Rubber is a tropical plant and has high economic value but rubber leaves are solid waste and left unutilized in the field. Rubber leaf powder (RLP) has been used for the removal of Cu (II) (Ngah and M.A.K.M., 2008) and Pb (II) (M.A.K.M. and Ngah, 2006). But no evidence of using RLP as adsorbent for the removal of MB from aqueous solution has been found in the literature. The main objective of this study is to evaluate the potentiality of RLP for removal of MB in batch mode. Factors affecting adsorption process such as ph, initial MB concentration, temperature were studied in batch operation. Langmuir, Freundlich isotherm models and pseudo-first-order, Pseudosecond-order kinetic models were used to determine equilibrium and kinetic parameters describing MB adsorption on RLP. Thermodynamics of the MB adsorption on RLP was also studied. * Corresponding Authors: Sourav Chowdhury, souravcep17@gmail.com;

281 2. MATERIALS AND METHODS 2.1 Adsorbent Preparation and chemicals Rubber leaves were dried in an oven at 105 C for about 16 hours then crushed and boiled to remove colored components. After boiling the powder was dried at 105 C for about 20 h and stored in glass bottle. A stock solution of methylene blue (MB) was prepared by dissolving 1.0 g of MB of analytical reagent grade (Merck, Germany) in distilled water to produce 1L solution. The test solutions were prepared by diluting stock solution to the desired concentrations. Before mixing the adsorbent the ph of each solution was adjusted to the required value with HCl and NaOH solution. Potassium nitrate (Merck, Germany) was used as electrolyte during the determination of point of zero charge. 2.2 FT-IR characterization The infrared spectra of the biomass samples before and after MB uptake were recorded using a Fourier Transform Infrared Spectrometer (SHIMAZDU) operating in the range cm -1. FTIR characterization was performed in order to identify chemical functional groups present on the RLP that might be involved in the methylene blue uptake procedure. Here, IR spectra of adsorbent was analyzed before and after adsorption. 2.3 Batch adsorption procedure The batch adsorption experiments were conducted in 250 ml Erlenmeyer flasks containing MB solution of varying concentration, ph and adsorbent dosages. Equilibrium isotherms were evaluated by shaking.2g of RLP in 200ml of MB solution with varying initial concentration (50, 75, 100, 150 and 200 mg/l) at three different temperatures (293K, 303K and 323 K) and ph = 6.4. The influence of ph (3.55 to 10) was investigated at room temperature (30±2ᵒC) by shaking a fixed amount of RLP with 200ml of 100 ppm MB solution for 5 hours. The adsorbed quantity of MB at equilibrium, qe (mg/g), was computed by the following equation, q e ( C0 C W e ) V Where C 0 and C e (mg/l) are the liquid-phase concentrations of dye at initial and at equilibrium respectively. V is the volume of the solution (L) and W is the mass of dry adsorbent used (g). The MB adsorbed at any time, q t (mg/g), was calculated by the following expression, q t ( C0 Ct ) V W Where C t (mg/l) is the liquid-phase concentrations of dye at any time t. 2.4 Kinetic studies The pseudo-first-order and pseudo-second-order kinetic models were tested to ascertain the rate of adsorption process and potential rate controlling step. The linear form of pseudo-first-order equation is generally expressed as follows (Lagergren, 1998), ln( qe q) ln qe k1t The pseudo-second-order equation is expressed as follows (Ho and Mckay, 1999), t 1 q k q 2 2 e 1 q Where q e and q are the amounts of methylene blue adsorbed (mg/g) at equilibrium and at time t (min), respectively. k1 and k 2 are the rate constant of pseudo-first-order and pseudo-second-order sorption (min-1), respectively. 2.5 Adsorption isotherms The equilibrium adsorption isotherm is of importance in the design of adsorption systems (Wang et. al., 2005). In general, the adsorption isotherm describes how adsorbates interact with adsorbents. In this work, Langmuir and Freundlich models were used to describe the relationship between the amount of methylene blue adsorbed and its equilibrium concentration in solutions. Linear form of Langmuir equation, which is valid for monolayer sorption onto a surface, is given by following equation (Langmuir, 1916) 1 q e 1 q L 0 1 q K 0 L e t 1. C Where q 0 and K are Langmuir parameters The Freundlich model is an empirical equation based on sorption on heterogeneous surface. It is given as, Where ln q e ln K f e 1 ln C n K and n are the Freundlich constants. f 3. RESULTS AND DISCUSSION 3.1 Characterization of adsorbent Point of zero charge of adsorbent: The surface charge (Q) and ph at the point of zero charge (phzpc) of the adsorbent in aqueous phase was analyzed using the titration method (Kiefer et. al., 1997), and it was found to be 6.00 ± 0.2. e 270

282 Adsorption Density (1/Ce) q(mg/g) FTIR spectroscopy: The FTIR spectrum for methylene blue loaded adsorbent shows that the peaks were shifted slightly compared to that in the raw sample, suggesting the participation of functional groups such as OH, COOH, NH and CO that could be potential adsorption sites for interaction with the cationic methylene blue dye. Fig. 1: FTIR spectra of RLP (before adsorption) 3.2 Effect of ph, initial concentration and contact time From Fig. 2 it can be seen that as the ph increased the adsorption density also increased. The phpzc at the point of zero charge of Rubber leaf is 6.0 ±0.2 (Fig. 3.1). At ph< phpzc, Rubber leaf surface may get positively charged due to the adsorption of H +. Thus a force of repulsion occurs between the dye cations and the adsorbent surface resulting in low adsorption. The reverse situation occurs at ph> ph P zc. At ph > ph P zc, the Rubber leaf surface may get negatively charged due to adsorption of OH -, which increases the removal of positively charged dye cations through electrostatic forces of attraction. From Fig. 3 it can be seen that the actual amount of methylene blue adsorbed per unit mass RLP increased with increase in methylene blue concentration. This also provides information on the minimum time required for considerable adsorption to take place ph Fig. 2: Effect of ph on the Adsorption density of RLP for the removal of methylene blue ppm 75ppm 100ppm 150ppm 200ppm Time(minute) Fig. 3: Effect of initial concentration 3.3 Adsorption isotherms From Fig. 4 it can be concluded that experimental data fitted well with the Langmuir isotherm model indicating monolayer adsorption on RLP with adsorption capacity of 111 mg/g Intercept Slope Statistics Value Value Adj. R-Sq /qe Fig. 4: Langmuir isotherms for methylene blue adsorption onto RLP 3.4 Adsorption kinetics The prediction of batch sorption kinetics is necessary for the design of industrial sorption columns. The nature of the sorption process will depend on physical or chemical characteristics of the adsorbent system and also on the system conditions. In the present study, the applicability of the pseudo-first-order and pseudo-second-order model has been tested for the sorption of methylene blue onto rubber leaf. According to Fig. 5, it can be said that the pseudo-second -order kinetic model provided a good correlation for the adsorption of methylene blue onto Rubber because of high correlation coefficient than that of pseudo-firstorder as shown in table 1. Calculated value of adsorption density with pseudo-second-order kinetic model onto RLP is also in good agreement with the experimental values. 271

283 t/q ppm 75 ppm 100ppm 150ppm 200ppm Time(minute) Fig.5: Pseudo-second order kinetics for adsorption of Methylene Blue onto rubber leaf Table 1. Pseudo-first-order and Pseudo-secondorder kinetic constants for the adsorption of methylene blue onto Rubber leaf (for 50ppm methylene blue solution) Parameter C 0 (mg /L) q e,exp (mg /g) First-order kinetic model k qe,cal r Second-order kinetic model k qe,cal r Thermodynamic study In engineering practice, thermodynamic study of an adsorption process is necessary to determine whether the process is spontaneous or not. For a spontaneous process the value of G must be negative. In this experiment the removal of methylene blue onto rubber leaf powder was studied at 293, 303, and 323K to determine the thermodynamic parameters such as G, enthalpy change H and entropy change S for the characterization of temperature effect. The negative value of H confirms that the adsorption process was exothermic. Value of G, H and S are listed in table 2. Table 2. Thermodynamic parameters for the adsorption of methylene blue onto RLP H S - G (KJ/mole) (KJ/mole) (J/mole) 293K 303K 323K CONCLUSIONS The present study illustrated that RLP could be a prospective adsorbent for the removal of methylene blue from its aqueous solution. Batch experiments described the dependency of adsorption process on ph, initial MB concentration and temperature. The adsorption process demonstrated good agreement with Langmuir isotherm indicating monolayer adsorption. From kinetic studies, it was revealed that the adsorption process followed pseudosecond-order kinetic model. Thermodynamic study showed that the adsorption process was exothermic and spontaneous. Attempts such as treating RLP with others chemicals can be done to make it more efficient. Fixed bed column study should be conducted to evaluate the industrial applicability of RLP. REFERENCES 1. Weng, Lin, and Tzeng, (2009), Removal of methylene blue from aqueous solution by adsorption onto pineapple leaf powder, J. Hazard. Mater. 170(1), pp Pearce, Lloyd, and Guthrie, (2003), The removal of colour from textile wastewater using whole bacterial cells: a review Dyes Pigm. 58 (3), pp Ozer, Imamoglu, Turhan, and F., (2012), Removal of methylene blue from aqueous solutions using phosphoric acid activated carbon produced from hazelnut husks Boysan, Toxicological & Environmental Chemistry 94(7), pp Kiefer, Sigg, and Schosseler, (1997), Chemical and Spectroscopic Characterization of Algae Surfaces, Environ. Sci. Technol. 31(3), pp Deniz, Karaman, and Saygideger, (2011), Biosorption of a model basic dye onto Pinus brutia Ten.: Evaluating of equilibrium, kinetic and thermodynamic data, Desalination 270, pp Crini, (2006), Non-conventional low-cost adsorbents for dye removal: A review, Bioresour. Technol. 97(9), Ratnamala, Shetty, (2012), Removal of Remazol Brilliant Blue Dye from Dye- Contaminated Water by Adsorption Using Red Mud: Equilibrium, Kinetic, and Thermodynamic Studies, Water Air Soil Pollut. 223(9), pp Kyzas, Lazaridis, AC., (2012), Removal of dyes from aqueous solutions with untreated coffee residues as potential low-cost adsorbents: Equilibrium, reuse and 272

284 thermodynamic approachmitropoulos, Chem. Eng. J , Lee, Choi, Thiruvenkatachari and Shim, (2006), Evaluation of the performance of adsorption and coagulation processes for the maximum removal of reactive dyes Dyes Pigm. 69(3), Langmuir, (1916), The constitution and fundamental properties of solids and liquids. Part i. solids, J. Am. Chem. Soc. 38, pp M.A.K.M., Ngah (2006), Kinetic and thermodynamic study of Cd(II) (Hevea brasiliensis) leaf powder, J. Appl. Sci. 6, pp Tanyildizi, (2010), Modeling of adsorption isotherms and kinetics of reactive dye from aqueous solution by peanut hull Chem. Eng. J. 168(3), pp Lagergren, (1998), Zur theorie der sogenannten adsorption geloster stoffe, Kungliga Svenska Vetenkapsakademiens, handlingar, Kungliga Svenska Vetenkapsakademiens 24, pp Wang, Boyjoo and Choueib, (2005), A comparative study of dye removal using fly ash treated by different methods, Chemosphere 60, pp Gupta and Suhas, (2009), Application of lowcost adsorbents for dye removal A review J. Environ. Manage. 90(8), Ngah, M.A.K.M., (2008), Adsorption of copper on rubber (Hevea brasiliensis) leaf powder: Kinetic, equilibrium and thermodynamic studies Biochem. Eng. J. 39(3), PP Zhou and Bai, (2013), Characterization of modified sawdust, kinetic and equilibrium study about methylene blue adsorption in batch mode Korean J. Chem. Eng. 30(1), pp Yagub, M.T., Sen, and Ang, (2013), Removal of cationic dye methylene blue (MB) from aqueous solution by ground raw and base modified pine cone powder Environmental Earth Sciences 13(4), pp Ho, Mckay, (1999), Pseudo-second order model for sorption processes Process Biochem. 34(5), pp

285 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh DEVELOPMENT OF AN ALGORITHM TO CALCULATE HEART RATE FROM THE BLOOD PRESSURE DATA OBTAINED USING OSCILLOMETRIC ALGORITHM Noor Mohammed 1, Sumon Saha 1 *, Mohammad Z. Hossain 2 1 Bangladesh University of Engineering and Technology, Dhaka 1000, Bangladesh 2 University of Western Ontario, Ontario, N6A 5B9, Canada Human body is prone to various cardiovascular diseases. These cardiovascular anomalies can be diagnosed by studying various physiological parameters. Heart rate is one of these vital parameters. It represents the pumping action of heart in course of time. Any abnormality in the heart rate can subtly lead to prolonged cardiovascular illness. In this paper, an algorithm is developed to calculate heart rate from a large number of data. These data are obtained from the AC signals produced by the pressure sensor during blood pressure measurement using oscillometric method. Most of the automatic blood pressure monitors can measure blood pressure along with the heart rate. However, the measurement algorithm behind the heart rate calculation in these types of machine is yet to be classified. This research work demonstrates a method to calculate average instantaneous heart rate from a large number of discrete data and later, the results are validated using FFT (Fast Fourier Transform) model. 1. INTRODUCTION Heart rate is one of the vital and commonly measured physiological parameters in clinical practice. It is typically expressed as bpm (beats per minute). It can vary according to the body s physical needs, including the need to absorb oxygen and excrete carbon dioxide (O Rouke and Fuster, 2001). Every time the heart contracts, it forces a pulse wave through the arteries, which can be felt in any of the peripheral arteries, e.g., carotid, radial, femoral, pedal, brachial, etc. Though heart rate is an indicator of cardiovascular activity and oxygen consumption, it is not a substitute for measuring blood pressure. The normal heart rate ranges from 60 to 100 bpm. When the heart is not beating in a regular pattern, it is referred to as arrhythmia. An abnormal heart rate sometimes, but not always, indicates disease (O Rouke and Fuster, 2001). Heart rate can be measured manually by counting the radial palpations. However, this method requires a trained user and thus inherits some measurement errors. In developed countries, there are plenty of advanced electronic devices to measure heart rate. These types of devices use high level microchips or microcontrollers to compute heart rate. The existing computational algorithms to calculate heart rate in these chips are quite classified and confidential. Therefore, in this paper, an idea of a new computational algorithm is developed to calculate heart rate for the low level microcontrollers which use the blood pressure data obtained from oscillometric method. 2. PROPOSED ALGORITHM Prior to this part of research, a device had already been developed to measure human blood pressure using air pressure sensor with the help of oscillometric algorithm. This part of research is an auxiliary aid to this device to calculate heart rate from the AC signals of the pressure sensor. In our device, we have implemented an algorithm to calculate heart rate during the period of MAP (mean arterial pressure) detection. Fig. 1 shows the waveforms of the pressure inside the deflating arm cuff (red curve) with the corresponding amplitude of the amplified AC signal oscillations. A sample calculation for heart rate is presented in Table 1 which corresponds to Fig. 1. The algorithm detects the consecutive time interval when the amplitude of the oscillation is greater than 400 (1.96 V for a 10- bit ADC) up to ten samples and records the time intervals and the pressure values in two separate arrays. Then it separates the time intervals (the bold * Corresponding Author: Sumon Saha sumonsaha@me.buet.ac.bd

286 ones in Table 1) having the pressure differential greater than 3 mm HgP. These separated time intervals correspond to the time needed by the heart to complete a single beat. Then the average heart rate is calculated using the following formula: 60 HR avg, (1) t where t is the time interval for single heart beat. A suitable code is written using the above constraints in the main program block for the microcontroller to enable the feature of heart measurement in the device. domain. However, sometimes experiments call for the harmonic content of a reproduced waveform. The harmonic content is a display of the magnitude of the waveform versus frequency. This data analysis is simply known as data in frequency domain or frequency spectrum. The frequency spectrum allows anyone to visualize a waveform according to its frequency content (Klingenberg, 2005). Fourier analysis is an important tool to convert the time domain into frequency domain and vice versa. There are various algorithms to carry out this Discrete Fourier transform (DFT). Fast Fourier Transform is such an algorithm to compute the DFT. It rapidly computes by factorizing the DFT matrix into a product of sparse (mostly zero) factors (Van Loan, 1992). The entire FFT calculation is done using Microsoft Excel. 4. VALIDATION OF HEART RATE CALCULATION Fig. 1: Waveforms of the pressure inside the deflating arm cuff (red curve) with the corresponding amplified AC signal oscillations. Table 1. Calculation of heart rate using proposed algorithm. P (mm Hg) Amplitude t (s) t (s) HR avg (bpm) In order to validate the present algorithm for heart rate calculation, we obtained the heart rate from the frequency spectrum generated via FFT of the oscillation waveforms (see Fig. 1). In Fig. 2, the frequency spectrum corresponds to the waveform of Fig. 1. The frequency component with highest amplitude corresponds to the instantaneous heart rate in beats per second (Arteta et al., 2012). Then the average heart rate (bpm) is computed using the following formula: HR 60 f, (2) avg where f s is the frequency corresponding to the highest amplitude. s 3. FAST FOURIER TRANSFORM In engineering application, waveforms are generally presented to show the magnitude as a function of time. Thus, by knowing the period of the waveform, the frequency can be calculated. This kind of graphical analysis is known as data in time Fig. 2: Frequency spectrum of Fig. 1 obtained from FFT analysis (total number of samples, n = 1024) 275

287 In Fig. 2, the value of the frequency with the highest magnitude is f s = Therefore, from (2), the calculated heart rate is HR avg = 58 bpm. 5. COMPARISON OF RESULTS Table 2 shows the calculated results of heart rate obtained from both the proposed algorithm and FFT analysis. The computed results show negligible variation with respect to the results obtained from FFT model. Hence, this comparison reinforces our proposed new algorithm to calculate heart rate using the low-level microcontroller implementing oscillometric algorithm. Table 2. Comparison of calculated heart rate by the proposed algorithm with those obtained from FFT analysis. Subject No. Age (years) HR avg (bpm) Device HR avg (bpm) FFT analysis 6. LIMITATIONS OF THE ANALYSIS During the data logging process, it is not possible to be precisely aware of the subject s psychological and physiological state. The data recording process should pertain at least a period of 5 minutes. The measurement should be carried out under steadystate physiological condition and should be properly standardized to comparable data (see more information on heart rate variability website athttp:// Due to the limitations in the lab facility, no standard devices were attached to the subjects during the data logging process to have real-time data of the actual heart rate. As a result, our analysis does not reveal the heart rate variability with the standard readings of any commercial device. 7. CONCLUSIONS The entire research adopts the application of embedded microcontroller technology in the field of biomedical engineering. The present work focuses on the development of an algorithm that can calculate average heart rate of any human being. Our goal is to present a computational technique for the low-level microcontroller to calculate heart rate from the large number of data. This analysis does not require looking on all data sets below the threshold value. Hence, we can write an efficient code within the limited memory of the low-level microcontroller and thus, eliminates the need of additional external memory module for the microcontroller. 8. ACKNOWLEDGEMENT The authors gratefully acknowledge the financial support of the Department of Mechanical Engineering of Bangladesh University of Engineering and Technology, Bangladesh during this project. REFERENCES 1. O Rouke, R. A. and Fuster, V. (2001), Hurst's The Heart, 10 th ed., McGraw-Hill. 2. Klingenberg, L. (2005), Frequency Domain Using Excel, San Francisco State University School of Engineering. 3. Van Loan, C. (1992), Computational Frameworks for the Fast Fourier Transform, SIAM, Arteta, C., Domingos, J. S., Pimentel, M. A. F., Santos, M. D., Chiffot, C., Springer, D., Raghu, A. and Clifford, G. D. (2012), Low- Cost Blood Pressure Monitor Device for Developing Countries, Wireless Mobile Communication and Healthcare, 83, pp Heart Rate Variability, Biocom Technologies, Poulsbo, WA 98370, viewed 30 November, 2014, < 276

288 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh Analyzing Time Dynamic Concentration of Formaldehyde in Fresh and Formalin Treated Fish Labeo rohita Md. Mezbah Uddin, Sadat Kamal Amit, SM Rezwanul Islam, Rizwanur Rahman, Shawly Sameera, Mohidus Samad Khan Department of Chemical engineering, Bangladesh of Engineering and Technology (BUET), Dhaka-1000, Bangladesh Food is a naturally perishable substance that undergoes degradation because of the spoilage actions of chemical, microorganisms or enzymatic reactions. To retain the freshness of food items different physical and chemical preservative techniques are used. In Bangladesh, it is reported that formalin, a 37-40% solution of formaldehyde, is widely used as a chemical preservative to increase the shelf-life of food items, especially fishes. The effect of formalin on the nutrition value of fish and other food products is less understood. Formaldehyde detection in food items can be conducted by the presence of other aldehyde, ketone or alcohol groups in foods. Moreover, formaldehyde can be naturally formed in fish and other food items during their ageing and deterioration. This study aims to detect and quantify formaldehyde in fresh and formaldehyde treated fish samples. Rohu fish (Labeo rohuta) was used to conduct the experimental study. Formaldehyde solutions of different concentrations were applied on the fish samples. The residue formaldehyde in formaldehyde treated fish samples were quantified with time. Naturally produced formaldehyde in the untreated fish samples was quantified at different time intervals. The shelf lives of the fish samples, with or without formaldehyde treatment, were also investigated in this study. This systematic approach of investigating the effect of formaldehyde on fish samples can also be applied to analyze other food items and chemical preservatives. 1. INTRODUCTION Fish and fishery products have been recognized as a potential source of nutrition due to their high protein and unsaturated fatty acid content (Masniyom 2013). Fish contains fat, free amino acids and water which is susceptible to spoilage by microorganism and biochemical reactions (Gabriel Fernandes 1993). Fish and seafood are perishable and can only be kept fresh using different preservation techniques. During storage, many fish species exhibit changes in textural properties, long before they are spoilt (Bremner 1992). In order to keep the freshness of fish and seafood intact, fishermen and fish vendors tend to use different physical and chemical preservative techniques (Noordiana 2011). Bangladesh has a vast fishery resource comprising of fresh, brackish and marine water bodies inhabited by 296 fresh and brackish water and 511 marine species of fishes, 14 exotic species of fish and 24 species of prawn (T Yeasmin April 2010). Existing endemic specieses include 13 species of carps (both major and minor) and 4 species of catfishes including Indian major carp: Catla (Catla catla); Rohu (Labeo rohuta); Mrigal (Cirrhinus mrigala) and the River shad (Tenualosa ilisha) (M. M. Rahman 2012). In Bangladesh, it is reported that formalin is widely used as a chemical preservative to increase the shelf-life of food items, especially fishes. Moreover, formaldehyde is also used as an antibacterial and antifungal agent in fish culture for therapeutic and prophylactic treatment of fungal infection and external parasites of fish egg (M. M. Rahman 2012). Formalin is a generic term which describes a solution of 37-40% formaldehyde gas dissolved in water. Formaldehyde is listed as a probable human carcinogen (T Yeasmin April 2010). Formaldehyde is highly soluble in water. Detection of artificially added formaldehyde in food items is not straightforward, as formaldehyde detection techniques can be interfered by the presence of other aldehyde, ketone or alcohol groups in foods. Moreover, formaldehyde may also be naturally formed in foods during the ageing and deterioration of food items.

289 Absorbance Though formalin (i.e. formaldehyde) is widely used as a chemical preservative and antibacterialantifungal agent in Bangladesh, the effect of formalin on the nutrition value of fish and other food products is less understood. It is, therefore, important to conduct a systematic analysis to understand: a) effect of formalin on the shelf-life of fishes, b) naturally occurring formaldehyde in fresh fishes, c) residual formaldehyde present in formalin treated fishes, and d) change of food values of formalin treated fish with respect to fresh fish. This article depicts the first part of a systematic research which aims at detecting and quantifying formaldehyde in fresh and formalin treated fish samples. Alongside, it also reports the time dynamic concentration behavior of formaldehyde and its effect on shelf life in the samples. The selected fish was Rohu (Labeo rohuta). Separate fish samples were sprayed with and dipped into 400, 600 and 800 ppm formaldehyde solution. The samples were then analyzed to obtain the formaldehyde quantity at certain time intervals. The future work of this study will quantify the change of food values of formalin treated fishes with respect to fresh fishes. This systematic approach of investigating formalin treated fish can also be used to analyze other food items and chemical preservatives. 2. MATERIALS AND METHODS 2.1 Chemicals Reagent grade (40% w/w formaldehyde) formalin was diluted to prepare 400ppm, 600ppm and 800ppm formaldehyde solutions, and to develop calibration curves. Nash reagent was used as an indicator for formaldehyde detection. 150g of ammonium acetate (reagent grade) with 2ml of acetyl acetone (reagent grade) and 3ml of acetic acid (reagent grade) was taken into a beaker. Volume was adjusted to 500ml to prepare concentrated Nash reagent, which was kept in dark air tight bottle at room temperature. Trichloroacetic acid (10 w/w %) (reagent grade) was prepared which was used to extract formalin from fish fillet. NaOH (5N, 1N), sulfuric acid (1N), and hydrochloric acid (1N) were used to maintain filtrate ph in a range of (Smith 1973). 2.2 Sample Preparation Fish samples (Labeo rohuta) were collected from formalin free fish truck from Ministry of Fisheries and Livestock, BD, and from Shawpno Super Shop, Dhanmondi, Dhaka. Each fish sample was cut into 4 pieces. One of the pieces from each fish was kept untreated. Of the other three pieces, some were carefully sprayed with the prepared formaldehyde solution in a weight ratio of 8:1 (sample weight: HCHO weight) while some were dipped into a formalin solution of 2 liter for 15 minutes. Concentrations of formalin solutions were 400ppm, 600ppm and 800ppm respectively. Samples were kept in plastic boxes and stored at a temperature of 10 C for further analysis R² = Formaldehyde Concenration (ppm) Fig. 1: Calibration curve for formaldehyde detection in fresh and formaldehyde treated (dipping) samples. 2.3 Formaldehyde Detection Bones of the fishes were removed. Portions of the fishes taken for the experiment were blended with equal weight of water for approximately 1 min. Equal weight of Trichloroacetic acid (10 w/w %) was added with the blend and was mixed properly with the help of glass rod. The fish blend was filtered by Whatman 42 filter paper. 5ml of filtrate was taken and 10ml of distilled water was added with it. ph was adjusted between 6 to 6.5. Volume of the extract was diluted to 25ml by adding water. 5ml of this extract was taken and 5ml of Nash was added. Mixture was kept at 60 C water bath for 5min. Then mixture was cooled to room temperature and optical density (absorbance) was measured at 415nm by using UV mini-1240 spectrophotometer (Smith 1973). Calibration curves (Fig. 1 and 2) for formaldehyde solutions were prepared to quantify formaldehyde in fresh and treated fish samples. 3. RESULTS AND DISCUSSION 3.1 Naturally occurring formaldehyde in fresh fish sample Small amount of naturally occurring formaldehyde was detected and quantified in fresh fish samples. Fig. 3 shows that the concentration of naturally occurring formaldehyde increased slowly in fresh fish sample with respect to time. The results show 278

290 Concentration (ppm) Concentration (ppm) Absorbance the initial existence of formaldehyde in fresh fish, which increases with time Fig. 2: Calibration curve for formaldehyde detection in fresh and formaldehyde treated (dipping) samples R² = Formaldehyde concentration (ppm) R² = Time (Hour) Fig. 3: Change in naturally occurring formaldehyde content with time for fresh fish 3.2 Time dynamic behavior of formaldehyde in formalin treated fish: fish sample dipped in formalin solution Table 1 shows the residual amount of formaldehyde in the fish samples dipped in formaldehyde solutions of 400, 600 and 800 ppm. The results show that the residual formaldehyde concentration in treated fish fillets were much lower than that of treating solutions. The concentration of formaldehyde for 400 ppm dosed samples ranged from 1.1 to 0.35 ppm in a 53 hour period (Fig. 4). This ranges were 2.14 to 0.22 ppm and 2.66 to 0.47 ppm for 600 ppm and 800 ppm dosed samples respectively (Fig. 4). formaldehyde for 400 ppm dosed sample ranged from 2.54 to 0.96 ppm in 31 hour period whereas this range was 3.47 to 0.88 ppm and 3.95 to 2.06 ppm for 600 ppm and 800 ppm dosed sample respectively (Fig. 5). Fig. 5 shows the same decreasing trend of of residual formaldehyde content in treated fish samples with respect to time. The results of Table 1 and 2 show that the concentration of residual formaldehyde in treated fish samples were much lower than the concentration of treating solutions. This implies that only a small fraction the applied formaldehyde solutions (spry or dipping) penetrated into fish fillets. The residual formaldehyde concentration reduced with time, and the rate of reduction became slower with time. Therefore, the residual formaldehyde concentration of the treated fish samples may reach to a saturated level with time, and this saturated concentration could vary with the concentration of treating solution and amount of naturally occurring formaldehyde with time. Table 1. Residual formaldehyde in formalin treated fish sample (dipped in formaldehyde solution) Cumulative Time interval (hour) Residual formaldehyde of formalin treated fish (fish samples were dipped in formaldehyde solution) Mean Value (± SD) Fish treated with 400 ppm formaldehyde Fish treated with 600 ppm formaldehyde Fish treated with 800 ppm formaldehyde (±0.03) 2.14 (±0.02) 2.66 (±0.03) (±0.01) 1.50 (±0.01) 2.56 (±0.02) (±0.01) 1.00 (±0.02) 1.66 (±0.03) (±0.05) 0.56 (±0.05) 1.17 (±0.03) (±0.01) 0.71 (±0.02) 0.72 (±0.02) (±0.07) 0.35 (±0.04) 1.03 (±0.03) (±0.02) 0.55 (±0.01) 1.24 (±0.02) (±0.04) 0.28 (±0.02) 0.57 (±0.06) (±0.02) 0.22 (±0.03) 0.47 (±0.07) R² = Time Dynamic Behavior of Formaldehyde in Formalin Treated Fish: Formalin Sprayed on Fish Sample Figure 5 was generated for the fish samples sprayed with 400, 600 and 800 ppm solution of formaldehyde respectively. The concentration of time(hour) (a)

291 concentration (ppm) Concentration (ppm) concentration (ppm) Concentration (ppm) concentration (ppm) R² = Time(hour) (b) R² = Time(hour) (c) 3.5 R² = time (hour) (a) R² = time (hour) Fig. 4: Residual formaldehyde concentration in fish fillets dipped in (a) 400ppm, (b) 600ppm and (c) 800ppm formaldehyde solutions Table 2. Formaldehyde concentration change with time in treated (sprayed with formaldehyde solution) fish sample Cumulative Time interval (hour) Residual formaldehyde of formalin treated fish (formaldehyde solution sprayed on fish sample) Mean Value (± SD) Fish treated with 400 ppm formaldehyde Fish treated with 600 ppm formaldehyde Fish treated with 800 ppm formaldehyde (±0.20) 3.46 (±0.15) 3.95 (±0.13) (±0.20) 2.67 (±0.07) 1.27 (±0.67) (±1.07) 2.06 (±0.75) 2.06 (±0.84) (±0.66) 0.79 (±0.13) 1.49 (±0.07) (±0.13) 1.45 (±0.13) 1.40 (±0.15) (±0.95) 1.01 (±0.53) 1.36 (±0.59) (±0.20) 0.88 (±0.20) 2.06 (±0.62) (b) (c) R² = time (hour) Fig. 5: Residual formaldehyde concentration in fish fillets sprayed with (a) 400ppm, (b) 600ppm and (c) 800ppm formaldehyde solutions 280

292 3.4 General Observation: A saturated water solution, of about 40% formaldehyde by volume or 37% by mass, is called "100% formalin". Formalin is used as preservative and fixative agent for organic materials. It is usually diluted with water or buffer to produce 10% formalin solution (4% formaldehyde; appx. 40,000ppm) which is an optimal concentration for fixation (2009). Fixation helps to preserve cellular morphology. Moreover, it can preserve protein, lipids and other biomolecules (Rooban Thavarajah 2012). The fixation process takes place by reaction of formaldehyde with protein. It reacts with the side-chains of proteins to form reactive hydroxymethyl groups. It can penetrate nuclear proteins and nucleic acids stabilizing the nucleic acid-protein shell and modifying the nucleotides by reacting with free amino groups. Formaldehyde can react with some groups in unsaturated lipids particularly if calcium ions are present, but tends to be unreactive with carbohydrates. Formaldehyde can react with groups on lysine, arginine, cysteine, tyrosine, threonine, serine and glutamine forming reactive complexes which may combine with each other and form methylene bridges (cross-links) or with hydrogen groups(eltoum IF 2001). In this study, the concentrations of formaldehyde solutions (400, 600, 800 ppm respectively) used to treat fish samples were much lower than the formaldehyde concentration considered optimal for protein fixation. The experimental results showed that only a fraction of the applied formaldehyde was adsorbed by fish protein. However, the residual formaldehyde concentration in fish fillet reduced with time. Formaldehyde penetrates cells quickly but its reaction with protein starts slowly (Rooban Thavarajah 2012). This may be the reason of gradual decrease of formaldehyde content in fish samples. Besides, the residual formaldehyde may hinder the growth of microorganisms on the fish samples. It was observed that at 10ºC, fish fillets that were not treated with formalin solutions (i.e. fresh) had a shelf life of around 24 hours. On the other hand, at the same temperature, the shelf life of fish samples dipped in different formaldehyde solutions of various concentrations extended to 192 hour (appx). The shelf life extended to 30 to 35 hour for the fish samples treated with formaldehyde spray. This can be explained by the concentration of residual formaldehyde existing in formaldehyde treated fish flesh, which may contribute to protein fixation. Moreover, formaldehyde acts as an antibacterial and antifungal agent; therefore, treating fish samples with formaldehyde solutions may denature the microorganism on the fish skin or in fish fillet, and delay the spoilage of formalin treated fish samples Normal fish Formaldehyde treated fish (sprayed) Fig. 9: Shelf life of normal and formaldehyde solution treated fish sample 4. CONCLUSION This study reports the time dynamic concentration of naturally producing formaldehyde in fresh fish samples and residual formaldehyde in formalin treated fish samples; Rohu fish (Labeo rohuta) was used in this study. In this study, small amount of naturally occurring formaldehyde was detected and quantified in fresh fish samples, the concentration of naturally occurring formaldehyde increased slowly in fresh fish sample with respect to time. The concentrations of residual formaldehyde in formaldehyde treated fish samples were found to be very low (< 4 ppm) compared to that of the treating solutions concentrations ( ppm). The results indicate that only a fraction of the applied formaldehyde was adsorbed by fish protein. However, the formalin treated fish samples demonstrated longer shelf life compared to that of the non-adulterated fish samples. The antibacterial/antifungal nature of the formaldehyde solution and the existing residual formaldehyde in the formaldehyde treated fish samples may cause the longer shelf life. 5. ACKNOWLEDGEMENT Formaldehyde treated fish (dipped) This research was supported by BCEF Academic Research Fund. REFERENCES 1. (2009). Handbook of Autopsy Practice. New York, Humana Press. 2. Bremner, H. A. (1992). Fish flesh structure and the role of collagen - its post-mortem aspects and implications for fish processing International Conference on Quality 281

293 Assurance in the Fish Industry. Copenhagen, Denmark, Elsevier Science and Technology Books. 3. Eltoum IF, J. M., R. B. and Grizzle, W. E. (2001). "Introduction to the Theory and Practice of Fixation of Tissues." JOURNAL OF HISTOTECHNOLOGY 24(2): Gabriel Fernandes, J. T. V. (1993). "Role of omega-3 fatty acids in health and disease." Nutrition Research 13(1): S19-S M. M. Rahman, S. A., M. M. Hosen and A. K. Talukder (2012). "Detection of formalin and quality characteristics detection from wet markets ar Sylhet city in Bangladesh." Bangladesh Research Publications Journal 7(2): Masniyom, P., Benjama, O., Maneesri, J. (2013). "Effect of modified atmosphere and vacuum packaging on quality changes of refrigerated tilapia (Oreochromis niloticus) fillets." International Food Research Journal 20(3): Noordiana, N., Fatimah, A. B. and Farhana, Y. C. B (2011). "Formaldehyde content and quality characteristics of selected fish and seafood from wet markets." International Food Research Journal 18: Rooban Thavarajah, V. K. M., Joshua Elizabeth, Umadevi Krishnamohan Rao and Kannan Ranganathan (2012). "Chemical and physical basics of routine formaldehyde fixation." Journal of Oral and Maxillofacial Pathology 16(3): Smith, C. H. C. a. B. (1973). "Measurement of formaldehyde in fish muscle using TCA extraction and Nash reagent." Journal Fisheries Research Board of Canada 30: T Yeasmin, M. S. R., M N A Khan, F H Shikha and M Kamal (April 2010). "Present status of marketing of formalin treated fishes in domestic markets at Mymensingh sistrict in Bangladesh.." International journal of Bio Research 1(4):

294 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh COMPARING PERFORMANCE OF PROGRAMMABLE LOGICAL CONTROLLER (PLC) AND MICROCONTROLLER IN A SIMPLE TANK SYSTEM Sheikh Waheed Baksh*, Sayed Abu Sufyan, M. A. A. Shoukat Choudhury Department of Chemical Engineering Bangladesh University of Engineering and Technology, Dhaka Programmable logic controllers have been used for industrial control systems for many years. PLCs can be combined with most other technologies to provide a sophisticated control and monitoring system. They contain multiple inputs and outputs, which use transistors, and other circuitry to simulate switches and relays to control equipment. On the other hand, a microcontroller is only a small computer in an IC (integrated circuit) with inputs and outputs of low level. Thus to control something with a microcontroller one may need to do a lot of work to interface it with the system to control and perform a lot of low level programming and know the hardware and software of the specific microcontroller very well. In this work, a simple tank system has been used to evaluate the performance of both PLC and Microcontroller in controlling the level of the tank. In the PLC, the Ladder+ BASIC hybrid programming language has been used which is very popular and is the main feature of Programmable Logical Controller (PLC). In case of microcontroller, ATmega8 has been employed to control the level of the simple tank system. 1. INTRODUCTION Programmable Logic controllers (PLC s) are widely used in motion control, positioning control and torque control. The purpose of a PLC was to directly replace electromechanical relays as logic elements, substituting instead a solid-state digital computer with a stored program, able to emulate the interconnection of many relays to perform certain logical tasks. A Programmable Logic Controller, PLC or Programmable Controller is a digital computer used for automation of electromechanical processes. PLCs are used in many industries and machines. Unlike general-purpose computers, the PLC is designed for multiple inputs and multiple output arrangements, extended temperature ranges, immunity to electrical noise, and resistance to vibration and impact. A PLC has many "input" terminals, through which it interprets "high" and "low" logical states from sensors and switches. In an effort to make PLCs easy to program, their programming language was designed to resemble ladder logic diagrams. Thus, an industrial electrician or electrical engineer accustomed to reading ladder logic schematics would feel comfortable in programming a PLC to perform the same control functions. On the other hand, another control system to the process named microcontroller has been also used in a wide range of applications. Microcontrollers are used in automatic controlled products and devices, such as automobile engine control systems, implantable medical devices, remote controls, office machines, appliances, power tools, toys and other embedded systems. By reducing the size and cost compared to a design that uses a separate microprocessor, memory, and input/output devices, microcontrollers make it economical to digitally control devices and processes. Mixed signal microcontrollers are common, integrating analog components needed to control non-digital electronic systems. 2. BASIC CONCEPTS OF PLC AND MICROCONTROLLER This section describes the basics of Programmable Logical Controller (PLC) and Microcontroller. The description, basic features, functional procedure, relative advantages of the implemented PLC (T100MD888+PLC) and Microcontroller (ATmega8) will be provided in the following section. 2.1 Introduction to T100MD888+ PLC T100MD888+ is a new member in the highly popular T100MD+ PLC family. The basic unit comprises 8 analog I/Os, 8 digital Inputs and 8 * Corresponding Author: Sheikh Waheed Baksh, sheikhwaheedbaksh@yahoo.com

295 digital outputs. Two of the digital outputs which can be defined as PWM output scan each deliver up to 10A Peak and 2A continuous, 24VDC current to the load. The 8 analog I/Os are configurable as 8 AI, no AO or 6 AI and 2 AO. All analog inputs are 10-bit resolution and all analog outputs are 8-bit resolution. T100MD888+ is expandable up to a total of 88 digital inputs and 88 digital outputs with the optional expansion module. It has an RS232 and an RS485 port, both of them are conversant in MODBUS protocol. Fig. 1: Sketch of T100MD+ PLC 2.2 Introduction to ATmega8 microcontroller The Atmel AVR ATmega8 is a low-power CMOS 8-bit microcontroller based on the AVR RISC architecture (Subrata. 2010). By executing powerful instructions in a single clock cycle, the ATmega8 achieves throughputs approaching 1MIPS per MHz, allowing the system to optimize power consumption versus processing speed. 3. PROCESS DESCRIPTION The performance of both PLC and microcontroller was evaluated on a simple tank system. The water inlet line was controlled by a manually operated gate valve. When performing the applications, the gate valve was maintained at full open condition. The water inlet pipeline continued towards a control valve (Fig. 3(b)) which was controlled using the modified PLC and microcontroller. The control valve was operated using a 4 ma (milliampere) to 20 ma indicating 0 to 100% open condition. The valve was operated by receiving signal from the signal board. A compressor delivered the instrument air required to run the control system. The inlet water pipeline discharged into an open tank (Fig. 3(a)). The tank level is determined using a level transducer, which sent the tank level signal to the signal board. The highest level of the tank was marked by 20 ma and the lowest level marked by 4 ma current signal. From the signal board, the control system i.e. PLC and microcontrollers, received the values of the 284

296 signal as a current unit which was sent by the level transducer. The output signal from the control systems gave corresponding values to the signal board for valve action. The whole control loop was oriented using feedback control pattern. Fig. 2: Block diagram of ATmega8 285

297 (a) (b) Fig. 3: (a) The tank system along with the Level Transducer, (b) Control Valve 4. IMPLEMENTATION OF PLC & MICROCONTROLLER IN THE SIMPLE TANK SYSTEM As the PLC T100MD receives only voltage unit values from control equipment, the incoming signal from the level transducer is then converted from Fig. 4: Process diagram of the simple tank system 286 current unit to voltage unit using resistors parallel with the circuit. The voltage value is then received at the Analog to Digital Converter port (ADC port) of the PLC. The value is continuously checked every 0.5 seconds using manual function. The digital signal of the tank level is then run by a ladder logic which

298 responds to predetermined action stated by the logic and the custom function. Using two relays from the PLC, the ladder logic was built in a way that while the level transducer gives a low level signal, which is around 4 ma/ 1 V, the ladder logic automatically allows the opening of the valve at 100% capacity at the inlet. At every 0.5 seconds delay, the tank level transducer signal is checked using the timer loop, and the valve action is continued until the level transducer gives high level signal, which is around 20 ma / 5 V. At the high level signal, the relays converts the valve action from 100% capacity to 0% capacity and stops the water inlet flow of the pipeline. The water drained from the tank eventually as the outlet valve was fixed at 50% open capacity. The ladder logic program again sends signal to the valve for an action to open it to 100% capacity when the level transducer sends a low level signal to the PLC. The output signal from the PLC is sent in voltage form which is not adaptable to the signal board of the tank system. To amend, the voltage signal was converted to current signal using an operational amplifier after the PLC. The Digital to Analog Converter port sends the output signal from the PLC which is then again passed through the opamp comparator to convert the voltage signal to current signal. In the microcontroller process, the logic of the tank system level control has been written in C language using microcontroller operation manual procedure. The signals sent from the level transducer is received by the current to voltage converter and then received by port C of the ATMEGA8 microcontroller. The output signal of the microcontroller is sent by port B to the Opamp comparator to deliver the final voltage signal for the valve. 5. RESULTS Both control systems gave successful simulation as well as practical demonstration in a simple tank system. TRiLOGI simulator and ISIS Proteus Circuit Simulator was used for PLC and Microcontroller accordingly. Fig. 5 displays the implemented PLC simulation on the simple tank system. The TRiLOGI simulator uses 2 relays and 5 input signals for this simple tank system simulation. Fig. 6 shows the microcontroller implementation on the simple tank system in ISIS Proteus Circuit Simulator. Fig. 5: TRiLOGI input of implementing PLC in the simple tank system 287

299 Fig. 6: Circuit diagram of the implementing microcontroller 6. DISCUSSION Although both PLCs and Microcontroller have been widely used in industrial application, they both have several advantages and relative disadvantages. a) Costs: Generally, PLCs are custom programmed for custom-built machines. Complicated manufacturing robotics designed for incredibly specific tasks can be extremely expensive. Since microcontrollers are fully integrated onto a chip, they are cheap to manufacture. b) Rigidity: Once a microcontroller or PLC has been programmed, typically they cannot be reprogrammed. c) Operation and maintenance: The programmable nature of these chips also allows manufacturing robots to reproduce these motions very quickly and consistently, thus increasing productivity. d) Current driving capacity: PLCs have large current driving capacity while microcontroller has small current driving capacity. In this case, PLC is more preferable than that of microcontroller. e) Voltage requirement: Normally, most of the Microcontroller use 5VDC supply. On the other hand, most PLCs work with 24VDC or 230V AC. f) Programming language: PLC can be programmed using ladder diagrams. So it is more reliable and usable for anyone than microcontroller which requires programming languages such as assembly, C, and Basic. 7. CONCLUSION In this study, a PLC and microcontroller based control system was developed for a simple tank system, which is capable of controlling the liquid level of a tank. PLC obtains liquid height through sensing circuit and determines the PID parameters through automatic adjustment mode. Then the PLC controls the liquid level through a control valve. The performance of PLC in the simple tank system was very stable over a wide range of temperatures and voltage disturbances. Although occupying a smaller space, the microcontroller showed some unstable behavior due to long hours of continuous operation. The response time of the PLC and microcontroller is almost identical. 288

300 REFERENCES 1. Advanced Micro Controls, Inc, (1999) What is a programmable logic controller (plc)? [ [Accessed 16 June 2014]. 2. Bolton, W. (2011) Programmable Logic Controllers. 4th ed. : Elsevier. 3. Dunning, G. (2008) 'Programming the Controllogix Programmable Automation Controller Using Rslogix 5000 Software. : Cengage Learning. 4. Gilliland, M. (2002) The Microcontroller Application Cookbook 2: Featuring the Basic Stamp Ii. illustrated ed. : Woodglen Press. 5. Kamal, R. (2009) Microcontrollers: Architecture, Programming, Interfacing and System Design. illustrated ed. : Pearson Education India. l 6. Liptak, B. (2005) Instrument Engineers' Handbook, Fourth Edition, Volume Two: Process Control and Optimization. 4, illustrated, revised ed. :Crc Press. 7. Petruzella, F. (2005) Programmable Logic Controllers. : Tata McGraw-hill Education. 8. Rohner, P. (1996) Automation with Programmable Logic Controllers. : Unsw Press. 9. Scott, A. (2013) Instant Plc Programming with Rslogix : Packt Publishing Ltd. 10. Singh, A. and Kumar, S. (2008) Microcontroller and Embedded System. : New Age International. 11. Triangle Research International, (2001) Trilogi. [ [Accessed 13 June 2014]. 12. Yadav, D. and Singh, A. (2004) Microcontroller: Features and Applications. : New Age Internationa 289

301 Proceedings of the International Conference on Chemical Engineering 2014 ICChE2014, December, Dhaka, Bangladesh HVAC SYSTEM: AN INDISPENSABLE RUDIMENT FOR QUALITATIVE MEDICINE PRODUCTION 1 Khalida Binte Harun*, 1 Razib Hasan and 2 Arif Morshed Azad 1 Renata Ltd, Mirpur, Dhaka 2 Ispahani Alliance Pharmaceuticals Limited HVAC system is an integral system of heating, air conditioning and ventilation component of a facility s functionality that maintains air circulation, temperature and humidity. By air circulation it continuously maintains air particles and obviates bacterial growth to ensure the safety of scientists and technicians working in a lab or production facility, the integrity of processes, and the environment outside. HVAC system is one of the core concepts that is always considered the fundamental stage of pharmaceutical plant design as HVAC system design influences architectural layouts with regard to items such as airlock positions, doorways and lobbies. The architectural components have an effect on room pressure differential cascades and cross-contamination control. The prevention of contamination and cross-contamination is an essential design consideration of the HVAC system. This system can be designed in different ways according to class or ISO requirements so that upon completion, the clean facility meets with the specifications and requirements of the end-user and regulatory authorities. 1. INTRODUCTION Air happens to be the most communal fundamental in surroundings that sometimes human forgets its existence. At the same time air regardless of different environments, acts as a vehicle for bacterial and gaseous adulterates brought in by the movement of people, material, etc. Since many of these air borne adulterates are harmful either to products or people working in such environments. Therefore, their removal is necessary considering medical, legal, social or financial grounds. Pharmaceutical rules and specifications often contain very precise requirements of air conditioning technology, such as temperature, humidity and ventilation of premises.. This generally formulated requirements are partially mentioned in the supplementary guidelines of EU GMP (Good Manufacturing Process) Guide for pharmaceutical manufacturing facility as per the FDA GMP regulation. According to The Federal Standard 209 E of USA, clean room is defined as, A room in which the concentration of airborne particles is controlled to specified limits. (Pradeep, 2010) Therefore, while designing the HVAC system for different areas in pharmaceutical plants it is very necessary to study the application, identify various factors affecting the particulate count and decide the level of contamination that can be permitted. 2. HVAC SYSTEM DESIGN CRITERIA 2.1 External condition To design any HVAC system, external condition of design site play a key role. External conditions are given in Table Clean Room Criteria Temperature and humidity are the main criteria for clean room. But this two are maintained keeping raw materials and products specifications into account. Clean rooms have been classified into various levels of cleanliness based on the particulate count by different standards. Table 1. External conditions of the site (Anita et al. 2010) External Temperature Maximum and minimum external temperature Air humidity Maximum and minimum values Sound Limits Day and night limit Emission of harmful Air limit technical * Corresponding Author: Khalida Binte Harun, khalidabinte@gmail.com

302 substances instruction Cardinal points Orientation of the buildings Wind Direction Main wind direction and speeds elimination of the impurities is achieved by cleaning or filtering system. Direct heat recovery without additional heat exchanger (low investment). Table 2: Clean Room Classification (FDA, 2006) Air borne Particulate Cleanliness Class International Standard ISO USA Federal Standard E Description Max no Description Max no particles 0.5 and particles 0.5 and larger per larger per m 3 m 3 ISO Class Class ISO Class Class ISO Class Class ISO Class Class ISO Class Fig.1: Diagram of pure external air plant (Anita et al. 2010) 3. DIFFERENT TYPE HVAC SYSTEM 3.1 Pure (100%) External Air Conditioning System The inlet air to the rooms always consists of 100% external air or fresh air. Fresh air is continuously prepared in the HVAC system as per the defined conditions (temperature, humidity, purity). Pure external air conditioning system is used with the following conditions: Supply of following production areas through a joint ventilation system The exhaust air from the rooms is so highly contaminated with impurities that the safe elimination of impurities cannot be assured by the cleaning /filtering system. Vapor emission control to reduce fire and explosion hazards Central Recirculating Air/Mixed Air Conditioning System The inlet air to the room consists of some fresh air and some recirculating air. The share of fresh air and recirculating air can be fixed or can be varied in accordance with the external temperature. It is important that the amount of external air be properly adjusted to accommodate the number of people working in the room. Central recirculating air/ mixed air conditioning systems are used with the following features: Dedicated equipment. Concentration of impurities in the exhaust air from the rooms is low enough that the safe Fig.2: Diagram of central recirculating air or mixed air plant (Anita et al. 2010) 3.3. Decentralized recirculating air/mixed air conditioning system with central external air preparation system The air supply and exhaust air of room or a zone is conveyed via recirculating air facility. Conveying centrally-prepared external air guarantees the required external air share for the personnel in the room. The recirculating air facility is usually fitted with a condenser and a filter stage. Decentralized recirculating air/mixed air facilities with central external air preparation are used with the following features: Supply of different production areas through a joint external air preparation system. The concentration of impurities in the exhaust air from the rooms is so low that safe elimination of the impurities is achieved by the filtering system. 291

303 for different section can be easily regulated in this system. Fig. 3: Decentralized recirculating air/mixed air conditioning system with central external air preparation. (Anita et al. 2010) 3.4. Pure Recirculating Air Conditioning System The air supply and exhaust air of a room or zone is conveyed via a recirculating air facility. No prepared external air is supplied. Pure recirculating air conditioning system is used with the following conditions: Areas which are not permanently staffed. The inlet of external air could influence the air quality. For high-quality clean room zones in a clean room mainly cleanliness class A in a sterile room, LF (Laminar Flow) work benches. 4. SYSTEM FOR TEMPERING AND VOLUME FLOW REGULATION 4.1. Single Duct System Temperature regulation takes place either by room or by zone through heater or cooler in Air handling Unit (AHU). The air currents are regulated by volume current regulators or damper. Normally heater or cooler in AHU are regulated by Building Management System (BMS) getting signal from room temperature or zone temperature sensors Dual Duct System After the air preparation in AHU, the inlet air splits into two different sections. One section is heated to high temperature and other section is cooled down to a lower temperature. These two sections of air are mixed in a blending box before entering the room or zones. Whole process is controlled by BMS getting signal from temperature sensors. This system is used for flexibility. Variable air currents Fig.4: Pure recirculating air conditioning system (Anita et al. 2010) Fig. 5: Room Supply with a single duct system (Anita et al. 2010) Fig.6: Room Supply with Dual Duct System (Anita et al. 2010) 5. PREVENTING CONTAMINATIONS AND CROSS CONTAMINATIONS Contaminations and cross contaminations are prevented by creating pressure difference from room to room. Normally solid dose facility follows 292

304 clean corridor concepts. Corridor is supposed to be be clean all the time. Corridor is maintained at higher pressure, then air locks the room at lower pressure. Hence, no particulate can enter the corridor from room, while air always passes from corridor to room. Whenever a room is needed to separate from its adjacent room, an air gap is created to ensure separation. This air gap is called air lock. There are three different types air lock Bubble If a low humidity and high humidity zone or any dusty zone are to be seperated, an air gap is created which is in higher pressure from its adjacent rooms. So that no air can come into it. Air always passes to adjacent rooms. Fig. 8: Cascade (Singh et al, 2014) Fig. 9: Sink Airlock (Singh et al, 2014) Fig. 7: Bubble (Singh et al, 2014) 5.2 Cascade When any airlock from its high pressure region moves to one adjacent room in lower pressure it is called cascade. Air passes from high pressure room to airlock, then airlock to low pressure room, but there remains no direct contact between high pressure and low pressure rooms Sink When any airlock is in lower pressure region from its adjacent room then it s called sink. Normally in order to separate any room filled with dirt from a cleaner onethis type airlock is used. Moreover, sometimes the dirt filled room is turned into sink in order to avoid extra room consumption Air Flow Pattern Air Flow Pattern is another important factor to maintain cleanliness in room. For this, position of supply air grill and return air grill is maintained in a way so that air from supply grill can shower the production machine and goes back to lower return air grill. So position of diffuser grill is important to ensure no dead spot in room Pressure Differential from Room to Room For same class, pressure differential from room to room is 15Pa and for different class is 30Pa. But these values are variable according to design criteria. There are alert, action and absolute limits to maintain pressure difference. These three limits are decided by the top management according to ISO regulation. In alert limit, workers need to be alert and inform engineering department. Whenever pressure differential value reaches the action value, all of the production work is immediately shut down. Finally, absolute limit is maximum limits. 293

305 Fig. 10: Air flow pattern in room (Pradeep, 2010) 6. FILTERS Air filters are used to attain the desired air quality and conditions in the premises of pharmaceutical manufacturing sites. The following are two valid European standards for air filters: DIN EN 779 Particle air filter for general ventilation DIN EN Suspended matter filter (HEPA and ULPA) Fig. 12: Filter Models (Anita et al. 2010) Separation in the air filters is based on different physical effects; those are given below (Anita et al. 2010): Diffusion Effect: Diffusion effect is only effective for very small particles and consequence of Brownian molecular movement which causes a diffuse movement of the particle along a virtual streamline. It is separated at the fiber if it remains sufficiently close to the fiber for a long enough time. Inertness Effect: The inertness effect causes separation among the fibers, if the particle of a particular size cannot follow the course of the streamline. Blocking Effect: The blocking effect occurs, if a particle is on a streamline whose distance from the fiber during circulation is less than half the particle diameter. Sieve Effect: The sieve effect only occurs for a particle whose diameter is greater than the free cross-section between the fibers. Fig. 11: Structure of air filter (Anita et al. 2010) The filter media used in air filter generally consist of fiber glass or synthetic-organic fibers, binding agents are thermally or chemically connected with them. The following models are generally used: Filter mats- Filter classes G1 to F6 Conveyor belt filter- Filter classes G1 to F5 Pocket filter- Filter classes G1 to F9 Cassette filter- Filter classes F5 to F9 Fig. 13: Separation technic in filter (Anita et al. 2010) 294