EFFECTIVE SLUDGE DEWATERING USING Moringa oleifera SEEDS EXTRACT COMBINED WITH ALUMINUM SULPHATE

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1 EFFECTIVE SLUDGE DEWATERING USING Moringa oleifera SEEDS EXTRACT COMBINED WITH ALUMINUM SULPHATE Qabas Marwan Abdulazeez, Mohammed Saedi Jami and Md. Zahangir Alam Bioenvironmental Engineering Research Centre (BERC), Department of Biotechnology Engineering, Faculty of Engineering, International Islamic University Malaysia (IIUM), Kuala Lumpur, Malaysia ABSTRACT This research aims to find an optimum mixture dosage of natural and chemical coagulant for sludge dewatering. Moringa oleifera seeds extract by NaCl solution (1 M) was used as a natural coagulant due to its characteristics such as: availability, low cost, biodegradable, and environmentally friendly. This natural coagulant was combined with aluminum sulphate Al 2(SO 4) 3.18H 2O (Alum) as chemical coagulant. Sludge sample was prepared from kaolin suspension 5% (w/v). The purpose of combining the two is to produce mixture with low chemical concentration and to utilize the natural coagulant in sludge dewatering process, thus, less hazardous impact to human health and environment. Optimization was done for M. oleifera to determine the total dosage and optimum conditions for the mixture. The specific resistance to filtration (SRF) value for M. oleifera optimization is 1.058E+11 m/kg with R 2 = for the optimum process conditions: mg/l dosage, ph 6.6, and 21.2 minutes for mixing time. The optimum ratio for the mixture is 10:90 (w/w) for M. oleifera and alum with SRF = 0.77E+11 m/kg at R 2 = At mixture ratio of 50:50 (w/w), SRF value was 0.833E+11 m/kg, which is good enough to decrease the usage of alum up to 50% with efficiency decreased only by 9.24% compared with alum alone. Keywords: Moringa oleifera, alum, sludge dewatering, SRF, natural coagulant, environmentally friendly. 1. INTRODUCTION One of the most costly processes in wastewater treatment plants is sludge treatment; it represents approximately 50% of wastewater treatment system cost [1]. Dewatering process is the most effective and economic process to decrease sludge volume, this process can be done by adding conditioners to sludge to separate particles from water. These chemical coagulants such as aluminum sulphate (alum) and polyaluminium chloride (PAC) have negative impacts on the environment and also hazardous effects on human body [2]. One of the solutions is to use mechanical dewatering such as conventional belt press, this process can run without any chemicals, but this technique has some limitations especially in developing countries due to the high cost of equipment and energy consumption [3]. The other solution is to use natural coagulants, the most common plant used for that is Moringa oleifera. M. oleifera (also known as horseradish tree) is a non-toxic plant; it grows naturally in tropical areas in Asia, India, Africa and Latin America [4]. The seeds of this plant have the ability to flocculate any suspended particles with negative charge in water and wastewater. This seeds have cationic polyelectrolyte, which provides strong adsorption with negative particles, thus, the particle surface will be neutralized [5]. M. oleifera has the potential to be used side by side with chemical coagulants because of its availability, low cost, biodegradable, and environmentally friendly [6]. Currently, using a combination consisting of natural and chemical coagulants is not very widely used in water and wastewater treatment. A recent study [7] showed that more than 90% of concrete wastewater turbidity was removed by using a combination of M. oleifera with Alum at ratio 20:80 (w/w), respectively. Other study showed the significant effect of water turbidity removal by using a mixture consisting of M. oleifera with PAC as coagulant. The optimum dosage to remove 95.7% of turbidity was 30 mg/l with 300 mg/l for PAC and M. oleifera [8]. These combinations give chance to minimize the cost and usage of these chemical coagulants, which led to less hazardous effects on humans and environment. In this study, the use of M. oleifera combined with alum was investigated. Design of Experiment (DOE) was used to optimize the process conditions, such as the ratio of the two coagulants, dosage, ph and mixing time. 2. MATERIALS AND METHODS 2.1 Materials Sludge sample, chemicals and M. oleifera seeds Kaolin suspension (type: R&M Chemicals, 500 g - UK) was used as a model material of the sludge. Aluminum sulphate (HmbG) was used as chemical coagulant. Moringa oleifera seeds used in this research were collected from Serdang, Selangor, Malaysia and kept dry inside their pods for about 4 months. Hexane solvent (n-hexane 99%, SYSTEM, 2.5 L) was used for oil extraction, and sodium chloride NaCl (Bendosen, 1 Kg) was used as salt extraction. ph values were adjusted using sodium hydroxide (NaOH) and hydrochloric acid (HCl) 372

2 with three values of molarity: 3 M, 1 M and 0.3 M to get the exact ph values Equipment Vacuum filtration apparatus, type (GAST, MODEL DDA-V111-ED, USA) with 90 mm funnel diameter, filter papers (Whatman, Qualitative 1, 90 mm Diameter), soxhlet extraction apparatus for oil extraction, cylinder beakers (HmbG, 1 L), laboratory weighing balance (METTLER TOLEDO, B204-S), viscometer (BROOKFIELD), laboratory oven, stopwatch, ph meter (SARTORIUS), magnetic stirrer, jar test apparatus (Stuart flocculator sw6, UK) and sieve 212 µm (type: Retsch). 2.2 Methods Preparation of sludge sample Kaolin suspension was used as sludge sample by adding 5 g of kaolin powder to 1 L distilled water (5% w/v) and mixed at 200 rpm for 10 minutes using jar test device [9] Preparation of M. oleifera seeds extract Good seeds of Moringa oleifera were selected, pods were removed, and seeds were grinded and sieved with 212 µm. Then, 10 g of M. oleifera powder was defatted by 170 ml of hexane solvent for about 90 minutes using soxhlet extraction apparatus [10]. After drying the defatted seeds powder in oven, 5 g of this powder was mixed with 1 L of NaCl (1 Molar) using magnetic stirrer for about 60 minutes [11]. Finally, the solution was filtered by filtration paper using vacuum filtration apparatus Preparation of alum solution 1 g of Alum powder was dissolved in 100 ml distilled water. The dosage will be 10 mg of alum for each ml stock solution [8]. 2.3 Design of experiment and statistical analysis One-Factor-At-a-Time (OFAT) OFAT was used to determine the possible optimum dosage for the three factors: concentration of seeds extract, ph and mixing time, each factor was investigated at different levels of values. The suitable range of these factors was set depend on SRF values. For mixing speed, it was fixed at two values: rapid mixing at 125 rpm for the first minute, followed by slow mixing at 40 rpm [10] Design of Experiment M. oleifera optimization Depending on OFAT values for SRF, the range of the three factors: concentration of seeds extract, ph and mixing time were determined, as shown in Table-1. The experiment was designed using Design-Expert software v9 (Stat-Ease Inc). Table-1. Range of levels for parameters used in jar test. Parameters Range of levels Conc. of seeds extract (mg/l) ph Mixing time (min)

3 Table-2. Three factors design. Std Run Block Factor 1 A:conc. of seeds extract (mg/l) Factor 2 B: ph Factor 3 C: mixing time (min) 14 1 Block Block Block Block Block Block Block Block Block Block Block Block Block Block Block Block Block Block Block Block Response 1 SRF (m/kg) Moringa oleifera and alum mixture optimization From M. oleifera optimization, the best dosage was mg/l at ph = and mixing time = 21.2 min. This dosage is suitable for alum because it works properly in acidic medium with ph close to 6.5 [7]. The total dosage of the mixture was determined to be mg/l. The minimum and maximum ratio for each component in the mixture was 10% (23.56 mg/l) and 90% ( mg/l), respectively. Optimization was done by using Design-Expert software v9 (Stat-Ease Inc). Table-3. Range of levels for mixture parameters. Parameters Conc. of M.O seeds extract (mg/l) Concentration of alum (mg/l) Range of levels ph Mixing time (min) Mixing speed (rpm)

4 Std. Run Component 1 A: M. oleifera (mg/l) Table-4. Mixture model design. Component 2 B: Alum (mg/l) Response 1 SRF (m/kg) ? ? ? ? ? ? ? ? Analytical methods SRF measurement SRF measurements for sludge samples were done after two hours of settling time for complete sedimentation [12]. Pressure of 300 mmhg was applied using vacuum filtration with 90 mm funnel diameter. From Darcy s law for liquid flow through porous media, an equation to calculate SRF can be obtained: (1) Where: α: specific resistance to filtration (SRF) (m/kg). a: slope (s/m 6 ). P: pressure (N/m 2 ). A: area of filter medium (m 2 ). µ: viscosity of the filtrate (N.s/m 2 ). P c: the mass of dry cake per filtrate volume (kg/m 3 ). The viscosity for each sample was measured by viscometer. Slop was determined by plotting filtration time per filtrate volume (t/v) versus filtrate volume (V). The plot should give a straight line [9], as shown in Figure-1: Figure-1. Plot of time/volume vs volume ph Measurement ph values were measured using ph meter (SARTORIUS, PB-10) Data analysis The significance of coefficients was analyzed using ANOVA test and P-value (Probability > F). If P- value for a model was less than 0.05, that model is considered significant. For optimization, the optimum values were obtained by regression model equation and analyzing the 3D response plot for M. oleifera and 2D response plot for mixture. 3. RESULTS AND DISCUSSIONS 3.1 Factors influence M. oleifera dewatering Three factors were used in M. oleifera optimization: M. oleifera dosage, ph, and mixing time, each factor has different effect on response value. The effects of different dosages of M. oleifera on dewatering process were studied by using different range of dosages: mg/l, this range of values was obtained by OFAT preliminary optimization. The best dosage which resulted in the lowest SRF value was 288 mg/l with SRF 375

5 = 1.045E+11 m/kg, ph = 7.43, and mixing time = min. The curve of SRF value increased in both sides until it reached SRF = 2.076E+11 m/kg at 100 mg/l dosage, and SRF = 2.241E+11 m/kg at 500 mg/l dosage, as shown in Figure-2. The effect of ph was not significant in the range of ph from The optimum ph was 6.25 with SRF = 1.023E+11 m/kg, curve of SRF value increased slightly in both sides of ph range, as shown in Figure-3. For ph 3, acids for ph adjustment will release cations [13], which interfere with M. oleifera coagulation; this will make some changes on real M. oleifera efficiency. Therefore, the acidic medium was excluded. For mixing time, range was set from 5-30 min, SRF = 1.043E+11 m/kg at min optimum mixing time, as shown in Figure-4. At 5 and 30 min mixing, SRF values are 1.83E+11 and 1.123E+11 m/kg, respectively. As reported in [11], the dewatering ability of M. oleifera was studied on real sludge samples, these samples were collected from sewerage treatment plant, Kuala Lumpur. Optimum conditions were: mixing speed of 100 rpm, mixing time of 1 min, and M. oleifera dosage of 4695 mg/l. The response (SRF) was 1.22E+11 m/kg which is near from SRF value obtained from the current study (SRF = 1.058E+11 m/kg) as shown in Table-7. The difference of M. oleifera dosage between the previous study and the current study (235.5 mg/l) is refer to the extraction method and sludge sample. The previous study used M. oleifera in distilled water extracted form applied on real sludge sample, while the current study used M. oleifera in salt extracted form applied on synthetic sludge sample (kaolin suspension). Figure-3. SRF vs ph. Figure-4. SRF vs mixing time. 3.2 M. oleifera optimization The responses were analyzed using the analysis of variance (ANOVA), details are shown in Table-5. According to the results, the factors A, B, C, AB, AC, BC, A 2, C 2 were significant because P-values were less than 0.05 (Prob > F). The high value of R 2 which is showed that the quadratic model was also significant. The Predicted R 2 which is is in reasonable agreement with adjusted R 2 which is The lack of fit (F-value) of implies the lack of fit is significant, there is only a 0.05% chance that a Lack of fit F-value this large could occur due to noise. The final equation in terms of coded factors is: Figure-2. SRF vs dosage. SRF = *A *B *C *AB *AC *BC *A *B *C 2 (2) Where: A is dosage, B is ph, and C is mixing time. 376

6 Source Table-5. ANOVA for response surface quadratic model. ANOVA for Response Surface Quadratic model Analysis of variance Table [Partial sum of squares - Type III] Sum of squares df Mean square F Value p-value Prob > F Model < significant A-conc B-pH C-mix time AB AC BC A^ < B^ C^ Residual Lack of Fit significant Pure Error E-003 Cor Total Std Run Block Table-6. Experimental design for process optimization of M. oleifera. Factor 1 A: conc. of seeds extract (mg/l) Factor 2 B: ph Factor 3 C: mixing time (min) Response 1 SRF (m/kg) 14 1 Block E Block E Block E Block E Block E Block E Block E Block E Block E Block E Block E Block E Block E Block E Block E Block E Block E Block E Block E Block E

7 SRF values for M. oleifera optimization was obtained as shown in Table-6. Optimization results showed 10 solutions with desirability = 1, as shown in Table-7. To check the efficiency of optimization, five solutions were tested. The results of these solutions were similar to the predicted SRF values. Name Goal Table-7. Optimization results. Lower limit Constraints Upper limit Lower weight Upper weight Importance A:conc is in range B:pH is in range C:mix time is in range SRF minimize Number Conc. ph Solutions mixing time SRF Desirability E Selected E E E E E E E E E For interactions between M. oleifera dosage and ph, Figure-5 and Figure-6 show the contour plot of M. oleifera optimization with SRF as response and fix mixing time 17.5 min. Figure-5. Contour plot of the interaction of conc. with ph. 378

8 implies the model is significant because P-values were less than 0.05 (Prob > F). There is only a 0.03% chance that an F-value this large could occur due to noise. The factors A, B, and AB were also significant. Although the R 2 is high , nevertheless the predicted R 2 of is not close enough to the adjusted R 2 which is It is very difficult to get close values of SRF, especially when the difference between these values is small. The final equation in terms of L-Pseudo components is: SRF = 1.01 * A * B * AB (3) Where: A is alum and B is M. oleifera. The final equation in terms of real components: SRF = * Alum * M.O * Alum * M.O (4) Figure-6. 3D contour plot of the interaction of concentration and ph with SRF as response. 3.3 Mixing ratio optimization The responses were analyzed using ANOVA, details are shown in Table-8. The model F-value of The final equation in terms of actual components: SRF = E-003 * Alum E-003 * M.O E-006 * Alum * M.O (5) Source Table-8. ANOVA for Quadratic Mixture model. Mixture component coding is L_Pseudo Analysis of variance Table [Partial sum of squares - Type III] Sum of squares df Mean square F Value p-value Prob > F Model significant Linear Mixture AB 5.603E E Residual 2.493E E-004 Lack of Fit Pure Error 6.362E E E E-004 Cor Total not significant Results of SRF for the mixture are shown in Table-9. Comparing dewatering efficiency of combination of M. oleifera and alum, the alum alone is more effective. From the result obtained, alum has the ability to dewater sludge sample with SRF = 0.756E+11 m/kg compared with 1.058E+11 m/kg for M. oleifera, thus, alum is 28.54% more efficient than M. oleifera. For the mixture of M. oleifera with alum, sludge dewaterability increased side by side with alum composition in the mixture, starting from SRF = 1.005E+11 m/kg for 10% alum content, to SRF = 0.77E+11 m/kg for 90% alum content in the mixture, as shown in Figure-7. From the results obtained, it can be concluded that dewatering efficiency will be increased with the increasing of alum content in the mixture. As for M. oleifera alone, the best value of SRF which is 1.058E+11 m/kg is good enough to depend totally on natural coagulant. 379

9 Std. Table-9. Process design optimization of the mixture. Run Component 1 A: M.O (mg/l) Component 2 B: Alum (mg/l) Response 1 SRF (m/kg) E E E E E E E E+11 the use of combined M. oleifera and alum in the ratio of 10:90 would give good dewaterability with reduces the dependency of the dewatering process on chemical coagulants. REFERENCES [1] T. Tebbutt Principles of Water Quality Control, 3 rd edition ed., UK: Elsevier. [2] I M. Aho and J. E. Lagasi "A new water treatment system using Moringa oleifera seed," American Journal of Scientific and Industrial Research, vol. 3, no. 6, pp , [3] P. Day and P. Giles "Innovative belt filter press takes the hard work out of sludge dewatering," Filtration & Separation, vol. 39, no. 8, pp Figure-7. Optimization for different ratios of the two component mixture. 4. CONCLUSIONS The results showed that the optimum ratio of the mixture coagulant was 10:90 (w/w) for M. oleifera and alum at mg/l dosage, ph 6.56, and 21.2 min for mixing time. Although this ratio has recorded good value of response (SRF = 0.77E+11 m/kg), it was not good as the value obtained from using alum alone which is SRF = 0.756E+11 m/kg. The SRF recorded using M. oleifera alone was 1.058E+11 m/kg, which is good enough to eliminate the use of alum as chemical coagulant. To decrease the use of alum to half, a mixture ratio of 50:50 (w/w) for alum and M. oleifera has recorded SRF = 0.833E+11 m/kg. At this ratio, the efficiency of dewatering was decreased by 9.24% compared with alum alone, with 50% alum avoided. It can be concluded that [4] C.-Y. Yin "Emerging usage of plant-based coagulants for water and wastewater treatment," Process Biochemistry, vol. 45, no. 9, pp [5] V. Nand, M. Maata, K. Koshy and S. Sotheeswaran "Water Purification using Moringa oleifera and Other Locally Available Seeds in Fiji for Heavy Metal Removal," International Journal of Applied Science and Technology, vol. 2, no. 5, pp [6] T. A. Mohammad, E. H. Mohamed, M. J. M. Mohd Noor and A. H. Ghazali "Dual polyelectrolytes incorporating Moringa oleifera in the dewatering of sewage sludge," Desalination and Water Treatment, pp [7] H. M. d. Paula, M. S. d. O. Ilha and L. S. Andrade "Concrete plant wastewater treatment process by coagulation combining aluminum sulfate and 380

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