IMPACT OF SHORT SOLIDS RETENTION TIME ON TREATMENT PERFORMANCE AND FOULING BEHAVIOR IN MEMBRANE BIOREACTOR SYSTEM LIU AOYUN

Transcription

1 IMPACT OF SHORT SOLIDS RETENTION TIME ON TREATMENT PERFORMANCE AND FOULING BEHAVIOR IN MEMBRANE BIOREACTOR SYSTEM LIU AOYUN NATIONAL UNIVERSITY OF SINGAPORE 2017

2 IMPACT OF SHORT SOLIDS RETENTION TIME ON TREATMENT PERFORMANCE AND FOULING BEHAVIOR IN MEMBRANE BIOREACTOR SYSTEM LIU AOYUN (B.Eng. (Hons.), NUS) A THESIS SUBMITTED FOR THE DEGREE OF MASTER OF ENGINEERING DEPARTMENT OF CIVIL & ENVIRONMENTAL ENGINEERING NATIONAL UNIVERSITY OF SINGAPORE 2017 Supervisor: Professor Ng How Yong Examiners: Associate Professor Bai Renbi Dr Lefebvre Olivier Patrick

3 DECLARATION I hereby declare that the thesis is my original work and it has been written by me in its entirety. I have duly acknowledged all the sources of information which have been used in the thesis. This thesis has also not been submitted for any degree in any university previously. LIU AOYUN 7 JULY 2017

4 Acknowledgement Acknowledgement There will never be enough gratitude expressed to those who had helped me in the course of research studying and thesis writing. First of all, I would like to extend my greatest thanks to my supervisors, Professor Ng How Yong and Prof Ong Say Leong for their valuable insights, suggestions and support despite their busy schedules. Their inputs had been really beneficial in overcoming challenges during the course of research project. I would also like to thank Ms. Huang Shujuan, Dr. Low Siok Ling and Dr. Ng Kok Kwang, my colleagues in the research project. Thank you for your guidance and kind assistance in helping me with experimental design, sample analysis and data processing. Gratitude also goes to PUB personnel in charge: Dr. Winson Lay and Ms. Png Hui Yi, thank you for having taken time off your busy schedules to supervise and assist in the research project. To the WS2 Lab technicians: Mr. Chandra for his inputs during the reactor fabrication process; and Ms. Lee Leng Leng and Ms. Tan Xiaolan for their help in the routine maintenance of the laboratory equipment which ensures the validity of data obtained. To the students who have helped me in this project in one way or another: Ms. See Ying Ting, Ms. Gao Hong (FYP students) and Ms. Hang Shuhui (UROP students). I really appreciated their help in sample analysis during the course. Above all, I would like to thank all my friends and family members for their unconditional support. I felt heavily indebted for their love. i

5 Summary Summary Aeration for membrane fouling control remains the biggest challenge in energy optimization of Membrane Bioreactor (MBR) system. Among key operating parameters, MLSS concentration was reported as a vital factor in determining energy demand for aeration. Thus, this study aimed at operating MBR systems under short SRTs. Four identical lab-scale membrane bioreactors were set up to investigate the impact of short SRTs on treatment performance and membrane fouling behaviour in MBR system in treating domestic wastewater. Hollow fiber membrane and ceramic membrane were deployed in two phases of this study, respectively. All other operating parameters but SRT were kept constant. SRT varied as 3, 5, 7 and 10 d in four MBRs. Effluent water quality and membrane fouling factors were analysed twice a week to elucidate the impact of short SRTs. In the first phase where hollow fiber membrane was deployed, all MBRs achieved high carbonaceous removal (> 91.8% COD removal and > 96.6% BOD removal). In 5d-, 7d- and 10d-SRT MBRs, almost complete nitrification was observed (> 99% NH3-N removal); While, 3d-SRT MBR only achieved 71.5% removal. TN removal increased as SRTs were increased with 48.0%, 52.4%, 53.5% and 56.0% in the 3d-, 5d-, 7d- and 10d-SRT MBRs, respectively. TP removal efficiencies were 26.8%, 20.9%, 18.6% and 19.4% in the four MBRs. Observed from four fouling cycles in this study, membrane fouling rate decreased with increasing SRTs among the 3d-, 5d-, 7d- and 10d-SRT MBRs. Particle Size Distribution profile showed that Particle size increased among the 3d-, 5d- and 7d-SRT MBRs; while the 10d-SRT MBR showed comparable particle size as the 3d-SRT MBR. Thus, particle size alone is not a good ii

6 Summary indicator of fouling behavior. Specific concentration of TOC, proteins and carbohydrates in SMP increased with decreasing SRTs; while only specific protein concentration in the EPS observed similar trend. TOC rejection decreased with increasing SRTs, which confirmed that rejection of organic matters contributed to membrane fouling. LC-OCD results further showed that rejection of biopolymers decreased with the increase of SRTs. This indicated that mainly rejection of biopolymers contributed to membrane fouling. EEM spectra was plotted for permeate, SMP and EPS. It was found that microbial byproducts-like and humic acid-like substances in EPS contributed to membrane fouling under short SRTs. Therefore, it was found in this study that SRT of 5 d and above were capable of producing high quality effluent with moderate fouling rate. Membrane fouling was controlled by SMP concentration of mixed liquor. Rejection of biopolymers by membrane resulted in gel/cake layer formation, thus leading to membrane fouling. In the second phase with ceramic membrane, COD and BOD showed high removal in four MBRs, > 89.4% and > 93.7% respectively, regardless of the SRTs. 7d- and 10d-SRT MBRs achieved more than 98.6% NH3-N removal; while, 3d- and 5d-SRT MBRs only achieved 69.5% and 86.3% removal. Lower nitrification efficiency could be a combined effect of lower biomass concentration and lower carbon source in the influent of phase 2 than phase 1. TN removal efficiencies were 44.1%, 45.8%, 51.2% and 52.2% in the four MBRs, which increased with increasing SRTs. TP removal efficiencies were recorded 25.3%, 28.6%, 28.9% and 29.1%. Observed from all four fouling cycles in this study, fouling rate decreased with the increase in SRT, indicating that shorter SRT contributed to faster fouling rate. In Particle Size Distribution iii

7 Summary profile, increasing particle size was observed among the 3d-, 5d- and 7d-SRT MBRs; while the 10d-SRT MBR showed even smaller particle size as the 3d- SRT MBR. Thus, particle size alone could not explain fouling behavior fully. Specific concentration of TOC, proteins and carbohydrates in SMP increased with decreasing SRTs; while no trend was observed in the EPS. It also showed that TOC rejection decreased with increasing SRTs. LC-OCD result showed that concentration of DOC and biopolymers decreased with increasing SRTs. Furthermore, rejection of DOC and biopolymers showed a decreasing trend with the increase of SRT. Thus, SMP concentration, rather than EPS, contributed to membrane fouling in the studied MBR systems. Rejection of organic matters, especially biopolymers, contributed to membrane fouling. Keywords: MBR; SRT; treatment performance; membrane fouling; LC-OCD; EEM; SMP; EPS iv

8 List of Abbreviations List of Abbreviations MBR SRT COD BOD TN TP TOC SMP EPS Membrane Bioreactor Solids Retention Time Chemical Oxygen Demand Biological Oxygen Demand Total Nitrogen Total Phosphorous Total Organic Carbon Soluble Microbial Product Extracellular Polymeric Substances LC-OCD Liquid Chromatography Organic Carbon Detector EEM OLR Emission-Excitation Matrix Organic Loading Rate v

9 List of Tables Table of Contents DECLARATION... Acknowledgement... i Summary... ii List of Abbreviations... v Table of Contents...vi List of Tables... viii List of Figures...xi Chapter 1 Introduction... 1 MBR Application in Wastewater Treatment and Reclamation... 1 Ceramic Membrane vs Polymeric Membrane... 3 Energy Optimization Strategies in MBR Application... 4 Research Objectives... 5 Thesis Organization... 5 Chapter 2 Literature Review Biological Nutrient Removal Process Mechanism of Nitrification and Denitrification Process Nitrogen Removal and Microbial Community under Short SRTs Major Factors for Membrane Fouling Mixed Liquor Suspended Solids (MLSS) Concentration Particle Size Distribution of Mixed Liquor Soluble Microbial Products (SMP) Extracellular Polymeric Substances (EPS) Fouling Potential of Organic Components Membrane Fouling Mechanism and Control Problem Statement Energy Consumption in MBR system Effects of SRT on membrane fouling Chapter 3 Materials and Methods Membrane Bioreactor (MBR) Systems System Design and Configuration Membrane Properties and Operating Conditions for Hollow Fiber Membrane Membrane Properties and Operating Conditions for Ceramic Membrane Feed water Characteristics vi

10 List of Tables 3.3 Sampling and Extraction Methods Sampling Methods Soluble Microbial Product (SMP) Extraction Extracellular Polymeric Substances (EPS) Extraction Analytical Methods Water Quality Analysis Organic Matters Analysis Particles Analysis Membrane Cleaning Procedures Chapter 4 Results and Discussion MBR systems using Hollow Fiber Membrane Biomass Concentration and Characteristics Treatment Performance of MBR system under Four SRTs Fouling Behavior of Hollow Fibre MBR under short SRTs Fouling Mechanism in Hollow Fiber MBR Systems MBR systems using Ceramic Membrane Biomass Concentration and Characteristics Treatment Performance of MBR system under Four SRTs Fouling Behavior and Contributing Factors under Different SRTs Fouling Mechanism in Ceramic MBR system Chapter 5 Conclusions and Recommendations Conclusions Recommendations References Publications vii

11 List of Tables List of Tables Table 1 Summary of biochemistry involved in nitrification and denitrification process Table 2 Expressions for nitrification kinetics Table 3 Expressions for denitrification kinetics Table 4 Maximum growth rate for nitrifiers in various environment (USEPA, 1975) Table 5 Summary of fouling factors in literatures Table 6 Summary of operational parameters controlled in the experiment Table 7 Hollow Fiber membrane properties Table 8 Summary of operating parameters and conditions of four MBRs (phase one) Table 9 Ceramic membrane properties deployed in phase two Table 10 A summary of operating parameters and conditions in phase two Table 11 Influent characteristics for Ceramic MBR system in phase two Table 12 Biomass concentration and sludge characteristics in four Hollow Fiber MBRs Table 13 Influent characteristics in phase one Table 14 TOC COD and BOD removal in four MBRs of phase one Table 15 Ammonia, nitrate and nitrite concentration in effluent and its removal in phase two Table 16 TN removal in four MBRs of phase one Table 17 TN removal and its breakdown by removal mechanism (phase one) Table 18 Total Phosphate removal by four MBRs in phase one viii

12 List of Tables Table 19 A summary of fouling cycle duration for four MBRs in phase one. 56 Table 20 effects of biomass Concentration on fouling for four MBRs in phase one Table 21 Statistics of Particle Size Distribution profile for four MBRs in phase one Table 22 TOC, Protein and carbohydrate concentrations for the four MBRs in phase one Table 23 Specific concentrations of TOC, proteins and carbohydrates for the four MBRs in phase one Table 24 Organic rejections by the four MBRs in phase one Table 25 Organic contents profiles by LC-OCD analysis in phase one Table 26 Organic rejections by the four MBRs in phase one (LC-OCD analysis) Table 27 Summary of the peak data by the EEM analysis in phase one (effluent) Table 28 Summary of the peak data by EEM analysis in phase one (SMP) Table 29 Summary of the peak data by EEM analysis in phase one (EPS Table 30 Biomass concentration and sludge characteristics of the four ceramic MBRs Table 31 Influent characteristics in phase two Table 32 TOC COD and BOD removal in the four MBRs of phase two Table 33 Summary of Ammonia, nitrate and nitrite concentration in influent and four MBR effluent Table 34 TN removal in the four MBRs of phase two ix

13 List of Tables Table 35 TN removal and its breakdown by removal mechanism (phase two) Table 36 Total Phosphate removal by the four MBRs in phase two Table 37 Effects of biomass concentration on fouling of the four MBRs in phase two Table 38 Statistics of particle size distribution profiles for the four MBRs in phase two Table 39 TOC, Protein and carbohydrates concentrations for the four MBRs in phase two Table 40 Specific concentration of TOC, proteins and Carbohydrates for the four MBRs in phase two Table 41 TOC, protein and carbohydrate rejection by the four MBRs in phase two Table 42 Organic contents profiles by LC-OCD analysis in phase two Table 43 Organic rejections by the four MBRs in phase two (LC-OCD analysis) Table 44 Summary of peak data by EEM analysis in phase two (effluent) Table 45 Summary of peak data by EEM analysis in phase two (SMP) Table 46 Summary of peak data by EEM analysis in phase two (EPS) x

14 List of Figures List of Figures Figure 1 Microbial Nitrogen Cycle... 9 Figure 2 MBR fouling mechanism map (Meng et al., 2009) Figure 3 Fouling factors and its implications on operating & design Figure 4 Schematic Flow of pre-denitrification MBR system Figure 5 Experimental setup in phase one (left) and phase two (right) Figure 6 hollow fiber membrane module: (a) hollow fiber arrangement; (b) module bottom; (c) inlet for air scoring; (d) outlet for permeate; (e) a closer look at permeate outlet Figure 7 Experimental setup of four MBRs using hollow fiber membrane (phase one) Figure 8 Experimental design of MBR in phase two: (a) air scoring design; (b) membrane tank design; (c) air inlet design; (d) cleaned membrane Figure 9 Display of four MBRs running Ceramic membrane in phase two Figure 10 ammonia, nitrate and nitrite profile of MBR effluent in phase one 48 Figure 11 Comparison of TN removed per day of four MBRs in phase one Figure 12 A graph shows the breakdown of TN removal (phase one) Figure 13 TMP Profile for four MBRs in phase one Figure 14 Individual TMP Profile for each MBR in phase one Figure 15 Particle size distribution profile of mixed liquor in four MBRs (phase one) Figure 16 Organic contents in the effluent from the four MBRs in phase one 61 Figure 17 TOC concentrations of the SMP and EPS for the four MBRs in phase one xi

15 List of Figures Figure 18 Specific TOC concentrations of the SMP and EPS for the four MBRs in phase one Figure 19 Protein concentrations in the SMP and EPS for the four MBRs in phase one Figure 20 Specific Protein concentrations in the SMP and EPS for the four MBRs in phase one Figure 21 Carbohydrate concentrations in the SMP and EPS for the four MBRs in phase one Figure 22 Specific carbohydrate concentrations in the SMP and EPS for the four MBRs in phase one Figure 23 Comparison of organic contents in the effluent for the four MBRs (phase one) Figure 24 Comparison of organic contents in the SMP for the four MBRs (phase one) Figure 25 DOC (dissolved organic carbon) rejection profiles for the four MBRs in phase one Figure 26 CDOC (hydrophilic DOC) rejection profiles for the four MBRs in phase one Figure 27 Biopolymers rejection profiles for the four MBRs in phase one Figure 28 Humics rejection profiles for the four MBRs in phase one Figure 29 EEM spectra of the 3d-SRT MBR effluent in phase one Figure 30 EEM spectra of the 5d-SRT MBR effluent in phase one Figure 31 EEM spectra of the 7d-SRT MBR effluent in phase one Figure 32 EEM spectra of the 10d-SRT MBR effluent in phase one Figure 33 EEM spectra of the 3d-SRT MBR SMP in phase one xii

16 List of Figures Figure 34 EEM spectra of the 5d-SRT MBR SMP in phase one Figure 35 EEM spectra of the 7d-SRT MBR SMP in phase one Figure 36 EEM spectra of the 10d-SRT MBR SMP in phase one Figure 37 EEM spectra of the 3d-SRT MBR EPS in phase one Figure 38 EEM spectra of the 5d-SRT MBR EPS in phase one Figure 39 EEM spectra of the 7d-SRT MBR EPS in phase one Figure 40 EEM spectra of the 10d-SRT MBR EPS in phase one Figure 41 Ammonia, nitrate and nitrite profiles of the MBR effluents in phase two Figure 42 A graph showing the breakdown of TN removal (phase two) Figure 43 TMP Profiles of the four MBRs in phase two Figure 44 Particle size distribution profiles of mixed liquor in the four MBRs (phase two) Figure 45 Display of organic contents in the effluents from the four MBRs in phase two Figure 46 TOC concentrations of the SMP and EPS for the four MBRs in phase two Figure 47 Specific TOC concentrations of the SMP and EPS for the four MBRs in phase two Figure 48 Protein concentrations of the SMP and EPS for the four MBRs in phase two Figure 49 Specific protein concentrations of the SMP and EPS for the four MBRs (phase two) Figure 50 Carbohydrate concentrations of the SMP and EPS for the four MBRs in phase two xiii

17 List of Figures Figure 51 Specific carbohydrate concentrations of the SMP and EPS for the four MBRs in phase two Figure 52 Comparison of organic contents in the effluent for the four MBRs (phase two) Figure 53 Comparison of organic contents in the SMP for the four MBRs (phase two) Figure 54 EEM spectra of the 3d-SRT MBR effluent in phase two Figure 55 EEM spectra of the 5d-SRT MBR effluent in phase two Figure 56 EEM spectra of the 7d-SRT MBR effluent in phase two Figure 57 EEM spectra of the 10d-SRT MBR effluent in phase two Figure 58 EEM spectra of the 3d-SRT MBR SMP in phase two Figure 59 EEM spectra of the 5d- SRT MBR SMP in phase two Figure 60 EEM spectra of the 7d-SRT MBR SMP in phase two Figure 61 EEM spectra of the 10d-SRT MBR SMP in phase two Figure 62 EEM spectra of the 3d-SRT MBR EPS in phase two Figure 63 EEM spectra of the 5d-SRT MBR EPS in phase two Figure 64 EEM spectra of the 7d-SRT MBR EPS in phase two Figure 65 EEM spectra of the 10d-SRT MBR EPS in phase two xiv

18 Chapter 1 Introduction Chapter 1 Introduction MBR Application in Wastewater Treatment and Reclamation Water is essential to life on this planet, yet it is a finite resource. Our supply of clean water has been strained in recent years as more water bodies become severely contaminated while the world is witnessing a rapid population growth. To tackle this, new water resources for drinking water are urgently researched. Currently, more and more focus has been put on domestic wastewater treatment and reclamation. Traditionally, water reclamation uses the secondary effluent of a typical domestic wastewater treatment plant. Secondary effluent goes through pre-treatment before RO filtration, followed by disinfection process. To take Singapore as an example, NEWater, a name for the reclaimed water from municipal wastewater, is a main water supply for semi-conductor industry and a small quantity of it has been fed into reservoirs for in-direct potable usage. NEWater is obtained from purifying secondary effluent by microfiltration/ultrafiltration followed by RO and disinfection units. However, in urban city setting, limitation of land is one of the key constraint for expansion of wastewater treatment plant due to population growth or new large wastewater treatment plant. In addition, the cost and quality of reclaimed water by such method is largely dependent on the characteristics of the secondary effluent such as turbidity, organic and inorganic contents. Conventional activated sludge (CAS) alone is inadequate to produce high quality effluent for reuse purposes. Thus novel technologies are urgently sought for compact, energy-efficient and cost-effective reclamation process. MBR system is one of them. 1

19 Chapter 1 Introduction MBR system is a combination of conventional activated sludge process and membrane separation process. Thus it is able to deliver a compact system with high water production per unit land usage, thus reducing the required footprint. MBR system incorporates MF or UF for solids-liquid separation. Unlike gravity settling in secondary clarifier, MBR removes most suspended solids and pathogens to achieve high-grade effluent quality and good disinfection effect. Apart from this, membrane separation enables biomass accumulation in the system, which in turn ensures higher nutrients removal under the same operating conditions as compared with conventional activated sludge process, making it possible to produce high quality effluent with consistency. In addition to high effluent quality, MBR allows more flexibility in operation as solids retention time (SRT) and hydraulic retention time (HRT) are decoupled. Therefore, MBR is gaining more and more popularity in both municipal and industrial wastewater treatment and water reclamation. In the last decade, with the advancement in membrane fabrication technology and system design, MBR has become more efficient and economical, especially for countries with limited land like Singapore. While MBR has some obvious advantages over CAS process, it also has its problems that hinder its widespread application. First of all, MBR requires higher capital cost than CAS process. Secondly, it has much higher operation and maintenance cost, arising from membrane fouling control and membrane replacement. Membrane fouling is a process of transporting and attachment of organic and inorganic substances onto membrane surface from mixed liquor that the membrane submerged in. With the development of membrane fouling, more chemical cost is incurred to recover and more energy consumption is expected 2

20 Chapter 1 Introduction to counter the increased trans-membrane pressure under constant-flux operation mode. Therefore, in order to promote the application of MBR system, effective controlling methods are urgently needed to prolong the inevitable fouling process. Recently, investigation, identification and modelling of membrane fouling behaviour is largely researched. However, no unified conclusion is concluded due to the complexity in mixed liquor characteristics and its interaction with membrane surface. Ceramic Membrane vs Polymeric Membrane Currently, polymeric and ceramic membrane are the two main type of membrane for water application. Due to their different characteristics, they are applied in different areas. Typically, polymeric membrane is applied in domestic wastewater treatment plant; while ceramic membrane is largely applied in industrial wastewater treatment. Both have their own merits. Polymeric membrane can be designed in a very compact way such that active surface is optimized. Besides, energy consumption for membrane scoring is generally lower than that in ceramic membrane. On the other hand, ceramic membrane possesses that merits of high thermal and chemical stability, making it resilient in various operational conditions. Although ceramic membrane bears higher manufacturing cost, it s gaining popularity in domestic wastewater treatment because of its resilience and ease of cleaning and backwashing. Thus, a long-term benefit is expected in an MBR system incorporated with ceramic membrane. 3

21 Chapter 1 Introduction Considering the benefits of ceramic membrane and hollow fiber membrane in treating domestic wastewater, it is advisable to have an in-depth study of fouling mechanism under short SRTs for both membranes. Energy Optimization Strategies in MBR Application Over the past five decades, MBR technology advancement has witnessed the demand for energy reduction from 5.0 kwh/m 3 required for side-stream MBRs, to 1.0 kwh/m 3, then to about 0.5 kwh/m 3 very recently (Buer & Cumin, 2010). The first milestone is the concept shift from side-stream MBRs to submerged MBRs, resulting in significantly energy reduction. Subsequently, specific energy consumption was reduced to below 1.0 kwh/m 3, mainly due to membrane module development and process optimization. On the contrary, the specific energy consumption for CAS process was reported as low as 0.3 kwh/m 3 (Fenu et al., 2010). Therefore, to promote MBR application, the requirement for specific energy consumption has targeted to be reduced to below 0.5 kwh/m 3 recently. In Singapore, step-wise strategies have been proposed and implemented to reach the targeted specific energy consumption. Started from the lowest pilot baseline of 1.3 kwh/m 3 in 2003, Singapore has implemented the following strategies sequentially: flux increment; aeration reduction; process design optimization; SRT/MLSS optimization; MLSS recirculation optimization; process aeration optimization and membrane scoring optimization. Energy demand arising from aeration has been identified as the major challenges in energy reduction in MBR applications. Operating at lower Mixed Liquor 4

22 Chapter 1 Introduction Suspended Solids (MLSS) concentration was proposed to ensure better oxygen transfer efficiency thus reduced energy consumption. Solids Retention Time (SRT) is one of the key parameters that controls MLSS. Research Objectives In view of research needs identified above, the goal of this study is to investigate the effects of short SRTs on treatment performance and fouling propensity in MBR systems, such that the feasibility of energy optimization by reducing SRTs could be verified. Both hollow fiber and ceramic membrane was adopted for better verification. To investigate the treatment performance of hollow fiber and ceramic MBRs under short SRTs, namely 3, 5, 7 and 10 d. To investigate fouling propensity under SRT of 3, 5, 7 and 10 d. Particle Size Distribution, TOC, Protein/Carbohydrates, LC-OCD and EEM spectra were used to identify the contributing factors to membrane fouling. To elucidate fouling mechanism under short SRTs. Thesis Organization The rest of this thesis is divided into following chapters: Chapter 2 Literature Review This chapter included a comprehensive review of the books and published literatures, which are relevant to this study. The various topics include nitrification and denitrification process in biological treatment 5

23 Chapter 1 Introduction and its implications in MBR systems operating under short SRT condition. It also discussed major factors contributing to membrane fouling, including MLSS concentration, particle size distribution, organic matters concentration and fouling mechanism elucidation. It present key findings and research gaps and needs. Chapter 3 Material and Methodologies This chapter described lab-scale experimental set-up and operating parameters in this study of both phases. The characteristics of membrane deployed in two phases were also explained. The detailed sampling, extraction and analytical methods were described in this chapter. Chapter 4 Results and Discussion This chapter presented the experimental findings and discussed its implications and comparison with related studies and literature reviews. Two sections focused on treatment performance and fouling behaviour in phase one and two, respectively. In each section, a fouling mechanism was proposed to explain membrane fouling under short SRTs. Chapter 5 Conclusion and Recommendations This chapter summarized the main conclusion obtained. Based on experimental constrains, recommendations for future studies were also suggested. 6

24 Chapter 2 Literature Review Chapter 2 Literature Review 2.1 Biological Nutrient Removal Process Wastewater treatment system is an engineering system to speed up the natural process of purifying contaminated water by itself (USEPA, 2004). Traditionally, wastewater treatment, before discharge to natural water bodies, effectively protects nature from anthropogenic contamination. While, in a more modern view, effective wastewater treatment is the prerequisite for water reuse. In a typical wastewater treatment plant, physical, biological and chemical processes are integrated to reduce or completely remove pollutant contents from the wastewater stream, such that it is safe to discharge or to recycle. According to USEPA guideline, pollutants of concern for municipal wastewater includes oxygen-demanding substances, nutrients (nitrogen (N) and phosphorus (P)), pathogens, inorganics and synthetic organic chemicals, thermal, emerging pollutants and etc. Nutrients removal (N and P) is the primary goal of wastewater treatment plants. Ammonia and phosphorus (as phosphate), as essential nutrients for aquatic plants, can boost growth of algae and even cause eutrophication (Tchobanoglous, 2003). Ammonia, in the molecular form of NH3, exposes toxicity to fish in receiving waters (USEPA, 1975). Chloramines, a reactant of hypochlorite and ammonium, makes disinfection less effective in water and wastewater treatment. Ammonia, which could be oxidized to nitrite and nitrate biologically, exerts nature s stress for oxygen depletion. Nitrate in drinking water is hazardous to public health because of its conversion to nitrite which changes hemoglobin to methemoglobin. The transformation makes red blood cells incapable of carrying oxygen around body. It is reported that high level of 7

25 Chapter 2 Literature Review nitrate in drinking water can lead to blood disorder in infants, commonly known as blue baby syndrome. In water reuse, ammonia causes biofilm development in distributing pipeline for industrial use (USEPA, 1975). Therefore, due to the concerns of protecting receiving waters, public health and downstream water reuse, nutrients have to be removed according to requirements. In a municipal wastewater treatment plant, N and P are mainly removed by biological process, called biological nutrients removal (BNR) process. Phosphorus (P), as a cellular component in biomass (1-2%), is essentially up taken for cell synthesis and subsequently separated from treatment stream by sludge wasting. To improve P removal, enhanced biological phosphorus removal (EBPR) can be done by selectively enriching polyphosphateaccumulating organisms (PAOs) in activated sludge. It is a common process that integrates anaerobic tank before aerobic tank. The phosphorus fraction for PAOs is 5-7%, contrary to 1-2% for normal biomass. Thus P removal is largely improved. Apart from removal by biomass assimilation, nitrogen is mainly removed biologically through a combination of nitrification and denitrification. During nitrification step, influent ammonia is oxidized to nitrate via nitrite, which is followed by denitrification process where nitrate is reduced to dinitrogen gas escaping from wastewater treatment system. Pre-denitrification configuration is commonly adopted in conventional wastewater treatment plant (Khin, 2004; USEPA, 1975; Zhu, 2008). It has the advantages of avoiding addition of external carbon source and moderate nitrate in effluent stream. This study has incorporated such configuration with 8

26 Chapter 2 Literature Review membrane filtration process to examine the feasibility of operating MBR system under short SRTs, namely 3, 5, 7 and 10 d with nitrogen removal Mechanism of Nitrification and Denitrification Process Figure 1 Microbial Nitrogen Cycle As depicted in Figure 1, ammonia entering biological treatment train can be removed by assimilation and oxidization. Assimilation by cell synthesis accounts for a small amount of ammonia removal in wastewater treatment plant. In the adopted pre-denitrification configuration, major mechanism for ammonia removal is through oxidization, which has two pathways: aerobic conversion from ammonia to nitrate (nitrification) followed by anoxic conversion from nitrate to dinitrogen gas (denitrification). A summary of functional microbial, enzyme, carbon source and oxygen requirements for nitrification and denitrification process is illustrated in Table 1. Table 1 Summary of biochemistry involved in nitrification and denitrification process. Reaction Enzyme Bacteria Nitrification NH 3 + O 2 + 2H NH 2OH + H 2O AMO 9 AOB (nitrosomonas) Carbon Source Inorganic carbon Oxygen Demand Aerobic

27 Chapter 2 Literature Review NH 2OH O 2 NHO 2 + 2H + + 2e - HAO NO O 2 NO 3 - Denitrification 2NO H e - N 2 + 2OH - + 4H 2O 2NO H + + 6e - N 2 + 2OH - + 2H 2O NOR Nitrate reductase Nitrite reductase NOB (nitrobacter) Pseudomonas Methylomonas Organic carbon Anoxic Nitrification Biochemistry and Kinetics Nitrification biochemistry and implication on process design Two major chemolithotrophic bacteria are found in nitrification process: Ammonia-Oxidizing Bacteria (AOB) and Nitrite-Oxidizing Bacteria (NOB). AOB converts ammonia to nitrite via hydroxylamine with the catalytic effect of ammonia monooxygenase (AMO) and hydroxylamine oxidoreductase (HAO). Subsequently, NOB converts nitrite to nitrate with nitrite oxidoreductase (NOR) involved. The overall expression for denitrification is displayed as below, when biomass composites is taken as C5H7NO2: From the above equations, the following conclusions could be drawn: a) Nitrifiers yield can be calculated empirically. The yield is 0.15 mg cells/mg NH4 + -N for nitrosomonas and 0.02 mg cells/mg NO2 - -N, which implies that nitrifiers are slow-growing organisms. Thus it is important to create adequate time for nitrifiers to grow when designing a nitrification-denitrification system. b) The theoretical oxygen consumption ratio is 4.57 mg O2 per mg NH4 + -N oxidized for energy production. Taking synthesis effect into account, 4.19 mg O2/mg NH4 + -N is required for nitrifying organism. Considering that there are many other oxygen-consuming material inside wastewater stream, the total oxygen demand of a treatment plant is highly elevated. 10

28 Chapter 2 Literature Review c) Alkalinity is consumed in nitrification process. Although the situation is alleviated by stripping carbon dioxide from the liquid, it is often that nitrification process gets depressed rapidly when ph gets below 7 (USEPA, 1975). Nitrification kinetics and implications on process design Nitrifying organism growth rate, thus nitrification rate, is dependent on environmental factors and operating conditions largely. Table 2 below summarizes the relationship of ammonia concentration, oxygen, ph, temperature and solids retention time (SRT) to nitrification kinetics. Table 2 Expressions for nitrification kinetics. Description Relationship of ammonia-n concentration to growth rate Relationship of ammonia oxidation rate to growth rate Relationship of temperature to growth rate Relationship of dissolved oxygen to growth rate Relationship of ph to growth rate Equation = + = = + =.. ( ) μ = + μ = ( (7.2 )) Therefore, the combined kinetics expression is below: =.. ( ) (. (. ))... (2-1) From the above equations, the following conclusions could be drawn: 11

29 Chapter 2 Literature Review a) Ammonia concentration affects nitrifier s growth rate significantly. Thus, under short SRT operation, HRT has to be small to ensure the supply of ammonia nitrogen to nitrifying microorganisms. b) Tropical climate in Singapore (24 ~ 35 o C year round) promotes microorganism growth rate, making it very suitable for short SRT operation. c) Consistent with findings above, ph is better to be controlled around 7.2 mg/l in oxic tank. d) DO level is proportional to growth rate. But it cannot be too high, which may bring up difficulties to maintain anoxic environment in anoxic tank. Therefore, in this study, the HRT was controlled at 5.5 h, DO of oxic tank was mainatined at 1~2 mg/l and ph was controlled at 7.0 ± 0.2 mg/l to optimize environmental condition for nitrifiers growth. In other words, the environmental conditions were maintained similar for a fair comparison of nitrification efficiency under different SRTs Denitrification Biochemistry and Kinetics Denitrification Biochemistry In oxygen-depleting condition, denitrification process takes place, which transforms nitrate or nitrite to gaseous nitrogen. The process is essentially dissimilatory reduction of nitrate and nitrite to dinitrogen gas by nitrate reductase and nitrite reductase with nitric oxide and nitrous oxide as intermediate products (Zhu, 2008). The biological process of denitrification, called nitrate dissmilation, involves the conversion of nitrate to dinitrogen gas under anoxic condition. Organisms involved are facultative heterotrophic bacteria like pseudomonas, micrococcus, 12

30 Chapter 2 Literature Review anchromobacter and bacillus. The denitrifying bacteria utilizes organic carbon source such as methanol as electron donor and nitrate as electron acceptor. Denitrifiers are also capable of assimilating nitrate by converting it to ammonia for the nitrogen requirement of cell growth. In the context that ammonia is already present, nitrate assimilation can be ignored. Effects of DO on denitrification The biochemical pathway for denitrifiers are similar despite several enzymes involved while utilizing oxygen or nitrate as terminal electron acceptor. Moreover, using oxygen is more thermodynamically favored. Thus many denitrifiers can shift between oxygen and nitrate rapidly. Dissolved oxygen suppresses denitrification. When oxygen is present, dissimilatory nitrate reduction process is slower than aerobic respiration. Thus facultative microorganisms will prefer oxygen to nitrate utilization. However, denitrification can happen in low level of DO, which is due to oxygen gradient in the system whereby denitrification happens at zero dissolved oxygen. Internal Recirculation (IR) is performed appropriately to enhance the removal of nitrogen and phosphorous. But it also imposes the problem of introducing oxygen residuals to anoxic tank. Effects of alkalinity on denitrification Denitrification process produces alkalinity with a stoichiometric ratio of 3.57 mg alkalinity as CaCO3 per mg nitrate or nitrite reduced to nitrogen gas. This increment of alkalinity can partially offset the effect of nitrification process where alkalinity is reduced. However, the ratio ranges from 2.89 to 2.95 in real wastewater treatment system (USEPA, 1975). 13

31 Chapter 2 Literature Review Denitrification Kinetic Denitrification process converts nitrate to nitrogen gas in an anoxic environment. Although there are a few intermediate products involved, generally there is no accumulation like nitrite. Thus it is valid to assume that denitrification is a one step process. Table 3 Expressions for denitrification kinetics Description Equation Relationship of nitrate-n to growth rate = + Effect of carbon concentration to growth rate = + Effect of ph on kinetics Depressed when ph gets below 6.0 and above 8.0 with optimal range of 7.0 to 7.5. Same as nitrification process, a combined effects of environmental factors on denitrification rate (and denitrifier growth) has the combined kinetic expression as follows: = ( )( ) (2-2) From the above equations, the following valuable conclusions can be drawn: a) Generally, is very small. So when nitrate is above 1-2 mg/l, there is no effect of nitrate concentration on denitrification rate. b) Denitrification rate can be related to denitrifier growth rate as follows: = (2-3) Reports have shown that when aerobic process follows the anoxic denitrification, net yield,, can be reduced by almost one order of magnitude (USEPA, 1975) because endogenous metabolism is enhanced when oxygen is served as electron donor. Therefore, in a pre-denitrification configuration, denitrification rate reduces significantly due to low growth rate of the nitrifiers. 14

32 Chapter 2 Literature Review Nitrogen Removal and Microbial Community under Short SRTs Nitrogen removal is highly dependent on the species and concentration of nitrifiers and denitrifiers in MBR system. The yield of heterotrophic bacteria is greater than that of nitrifying bacteria. In a combined carbon oxidationnitrification system, there is a danger that slow growing nitrifiers may be washed out if the heterotrophic bacterial established a growth rate exceeding the maximum growth rate of nitrifying bacteria. To reduce the net growth rate of heterotrophic bacteria, one could reduce substrate concentration S or increase activated solids X in the system. Information on the effect of short SRT on nutrients removal in a predenitrification submerged MBR system are limited. Tan et al. (2008) has conducted experiments on four MBR systems with SRTs of 5, 8.3, 16.7 and 33.3 d, concluding that high COD and ammonia removal was achieved and not dependent on SRTs; while TN removal increases with increasing SRTs. However, most reports on biological nutrient removal performance in MBR systems were with longer SRT of more than 20 d (Rosenberger et al., 2002; Yoon et al., 2004; Patel et al., 2005) and some studies were based on synthetic wastewater (Han et al., 2005; Patel et al., 2005; Ng and Hermanowicz, 2005). Traditionally, in a conventional activated sludge process, SRT has to be carefully designed and prolonged necessarily to avoid washing out of slowgrowing microorganisms. Table 4 below illustrates the maximum growth rate in various environment. Tan et al. (year) found that, although nitrification performance was comparable under the four different SRTs, genetic analysis on microbial communities did not reveal any obvious trend but complex and different communities in each system were observed. 15

33 Chapter 2 Literature Review Table 4 Maximum growth rate for nitrifiers in various environment (USEPA, 1975) 2.2 Major Factors for Membrane Fouling Mixed Liquor Suspended Solids (MLSS) Concentration Particles have been reported to affect membrane fouling in MBR systems due to size screening effect and its interaction with membrane surface. Most particles are able to be retained by microfiltration/ultrafiltration membrane (nominal pore size ~ 0.1 micron). Particles move to membrane surface by permeate drag force; and the retained particles could form a loose layer on membrane surface due to weak interactions like electrostatic double layer. This fouling layer was reversible by re-suspension to mixed liquor solution due to air scoring effect. However, the effects of particles concentration (characterized as MLSS concentration) on membrane fouling was contradictorily concluded in many reports. On one hand, it was found that particles in mixed liquor contributes to membrane fouling by large mass deposition on membrane surface with the effect of permeate drag force. It was reported that membrane fouling increased as particles more severely deposited on membrane surface (Han, Bae, Jang, & 16

34 Chapter 2 Literature Review Tak, 2005). It was also reported that an increase of solids concentration (and its correlating characteristics such as viscosity and dewaterability) contributed to membrane fouling significantly (Germain et al., 2007). Some reported in one experiment that the contribution of suspended solids (SS), colloids and dissolved molecules (OM) on membrane fouling was 65%, 30% and 5%, respectively. Thus effects of SS on membrane fouling by forming cake layer was far more significant than colloids and OM by causing pore blockage and narrowing (Defrance, Jaffrin, Gupta, Paullier, & Geaugey, 2000). On the other hand, some reported that colloids contributed more significantly to membrane fouling although solids concentration increased as SRT was increased from 20 to 100 d (Ahmed, Cho, Lim, Song, & Ahn, 2007). Moreover, it was found that fouling in submerged MBR system was not controlled by mixed liquor suspended solids concentration (Ng, Tan, Ong, Toh, & Loo, 2006). Thus MLSS concentration alone is a poor indicator of membrane fouling behavior Particle Size Distribution of Mixed Liquor Particle size distribution of particles is critical in controlling membrane fouling rate. Fine particles were more likely to deposit on membrane surface or inside pores (Z. Wang, Wu, Yin, & Tian, 2008). Particles of sizes close to membrane pore size or smaller would cause pore closure and even complete blockage (Bai & Leow, 2002; Lim & Bai, 2003). Pore blocking was observed and the pores were more easily blocked by fine particles by numerous researches under SRT of 10, 20, 30, 40, 60 and 100 d (Ahmed et al., 2007; Zhang, Chua, Zhou, & Fane, 2006). In addition, gel/cake layer formed by smaller particles created larger filtration resistance than large particles (Chang, Le Clech, Jefferson, & Judd, 2002; Kuberkar & Davis, 2000). Larger particles are less likely to be affected 17

35 Chapter 2 Literature Review by permeate drag force; but its random attachment to membrane surface would cause dense cake layer formation because of stronger electrostatic interaction with gel layer. Some researcher reported otherwise that cake layer formed by large particles acted as a secondary filter to prevent small particles from further fouling the primary membrane, thus inversely correlated to membrane fouling (Meng et al., 2006). Particle size (as well as floc size) distribution is a combined effect of operational parameters, such as SRT, HRT, OLR and DO (Zhang et al., 2006). SRT affects microbial communities, microbial physiology, MLSS/MLVSS ratio and inorganics, thus affecting the structure and size of flocs formation. Ahmed et al. reported that fine particles in the order of 1 micron was more populated at shorter SRTs (Ahmed et al., 2007) Soluble Microbial Products (SMP) Soluble Microbial Products (SMP), firstly defined by Nankung and Rittmann (year), is originated from various microbial activities such as substrate metabolism, biomass growth and decay (Barker & Stuckey, 1999; Laspidou & Rittmann, 2002). Thus, SMP can be divided into two categories: Substrate- Utilization-Associated Products (UAP) and Biomass-Associated Products (BAP). UAPs are usually small carbonaceous compounds from substrate metabolism; BAP are usually larger cellular macromolecules from cell lysis and biomass decay (Jarusutthirak & Amy, 2006). Based on current analytical methods, SMP mainly contains polysaccharides and proteins in either soluble or colloidal forms. SMP is ubiquitously present in biological process systems 18

36 Chapter 2 Literature Review and considered as one of the major factors affecting membrane fouling in MBR systems (Drews, Lee, & Kraume, 2006; Jarusutthirak & Amy, 2006; Liang, Liu, & Song, 2007; Meng et al., 2006; Z. Wang et al., 2008). SMP composites are usually smaller or close to membrane pore sizes, thus SMP is often correlated with internal pore narrowing. SMP was also reported to be associated with gel layer formation due to size exclusion of macromolecules (Drews et al., 2006; Jarusutthirak & Amy, 2006). Such gel layer formation altered membrane surface properties which encouraged attachment of flocs and debris, thus the formation of cake layer. Furthermore, SMP, because of its small sizes, tightens cake formation by filling up spaces between cake layers (Bae & Tak, 2005). Liang et al. (2007) further concluded it is the proteins and carbohydrates in SMP that worsened membrane fouling. However, other researchers argued that EPS, not SMP, that was correlated with membrane fouling (B. Cho & Fane, 2002; Lee, Kang, & Shin, 2003). SRT affects the characteristics and amount of SMP. SMP increases with increasing SRTs, thus leading to more severe fouling under shorter SRTs (Ahmed et al., 2007; Liang et al., 2007). On the contrary, Jarusutthirak and Amy (2006) reported that production of hydrophilic colloids and macromolecules was lower at shorter SRT, which led to less flux decline Extracellular Polymeric Substances (EPS) Extracellular Polymeric Substances (EPS) was produced by most bacterial in different processes like secretion, cell lysis, nutrients transport between cells 19

37 Chapter 2 Literature Review and the environment. EPS provides matrix for bio-floc formation and allows communication among cells in such flocs (Laspidou & Rittmann, 2002). Based on the way EPS is bounded to cells, EPS can be subdivide into loose-bound EPS (LB-EPS) and tight-bound EPS (TB-EPS), which can be extracted separately in a laboratory. Mainly, fractions of EPS is polysaccharides (PS), protein, lipids, nucleic acids and humic sunstances; but its composition and concentration are highly dependent on the operating conditions (Drews et al., 2006; Meng et al., 2006; Z. Wang et al., 2008). Often EPS was reported as the main factor contributing to membrane fouling in MBRs. Furthermore, there is another school of researchers believe that SMP is the soluble portion of EPS, arguing that EPS is predominantly affects membrane fouling and it could influence SMP concentration significantly (Meng et al., 2006). Since EPS plays an important role in forming microbial aggregates, its presence in mixed liquor and membrane surface is heterogeneous and dynamic. Thus, EPS fouling happens in a complex mechanism as its characteristics and spatial distribution on membrane surface would affect permeate flux significantly (Drews et al., 2006). Nagaoka et al. (1996) reported that accumulation of EPS affects filterability and viscosity of activated sludge significantly, which in turn contributes to membrane fouling. By examining the foulants on membrane surface, Cho and Fane (2002) concluded that attachment of EPS in the initial stage led to slow and steady rise in the TMP, which further promoted the rapid rise of TMP in the later stage when biomass and cell debris deposited on membrane surface readily. However, there is a contradictory reports on the role of protein and polysaccharides in EPS on membrane fouling. 20

38 Chapter 2 Literature Review Since EPS is the product associated with microbial activities, EPS amount is a factor of both biomass concentration and microbial growth rate. Some has reported that higher concentration of floc-bound EPS at lower SRTs, which can be explained by higher growth rate and more active microbial activities (Al- Halbouni et al., 2008). While, some reported likewise but also concluded that in the condition of high MLSS concentration, bound EPS was not sensitive to SRT (J. Cho et al., 2005). Since bound EPS concentration cannot always explain the fouling behavior observed, specific EPS concentration and specific cake resistance were adopted to relate EPS with fouling rate (J. Cho et al., 2005; Ng et al., 2006). Specific EPS concentration is the EPS amount normalized by MLVSS concentration, which shows the EPS quantity experienced by each cell. Ng et al. (2006) concluded that fouling rate was slower when specific EPS concentration was decreased. Specific cake resistance, a function of EPS, MLVSS, TMP and permeate viscosity, explains the extent of influence imposed by EPS on hydraulic resistance of sludge flocs. However, these two concepts converge when a non-dimensional analysis was performed to induce the mathematic expression of specific cake resistance. It was found that specific cake resistance can also be expressed by a function of bound EPS per unit mass of MLVSS. Cho et al. (2005) also concluded that specific cake resistance had no impact on TMP rise at the value below 20 mgeps/gmlvss and above 80 mgeps/gmlvss; but positive impact on TMP rise in between Fouling Potential of Organic Components Based on current extraction and analytical methods, proteins, carbohydrates and humic substances are major components in SMP and EPS. However, their role 21

39 Chapter 2 Literature Review and dominance in controlling fouling are still open to debate. The table below summarizes findings from various papers. Table 5 Summary of fouling factors in literatures Major Component in Mixed Liquor Extraction Methods references Carbohydrates (SMP) Centrifuge and Zhang et al., 2006 filtration Protein (EPS) Ion exchange Meng et al., 2006 Carbohydrates (SMP) Centrifuge and filtration Le-Clech et al., 2006 Carbohydrates (SMP) Centrifuge and filtration (0.45 µm) Ng et al., 2006 Carbohydrates (EPS) Ion exchange Halbouni et al., Membrane Fouling Mechanism and Control Membrane fouling mechanism in MBR system has been widely researched. It has been observed and experimentally proved that a clean membrane experiences three stage before it reaches unacceptably high TMP, in a constantflux operation mode (B. Cho & Fane, 2002; Meng et al., 2006; Zhang et al., 2006). In the first stage, membrane surface is conditioned by light particles that are more influenced by permeation drag force, leading to pore blockage and closure. Thus an abrupt TMP rise has been observed in a few hours. The experimental results revealed that pores were easily blocked by particles of the same or larger particles. The second stage involves a prolonged period of slow TMP rise due to accumulation of soluble microbial products (SMP), extracellular polymeric substances (EPS), colloids and other products of bioactivity on membrane surface. Some are of mixed liquor origin; while some are produced by biofilms 22

40 Chapter 2 Literature Review developed on the membrane surface. The last stage shows a sudden rise in TMP driven by the self-accelerating nature of fouling under constant flux operation. For sustainable long-term operation, stage 1 needs to be limited; stage 2 needs to be extended and stage 3 needs to be avoided. Deposition of large particle in first stage such as bio-flocs and cell debris, is reversible by providing unstable environment such as membrane scoring and backwashing (Zhang et al., 2006). Accumulation of binomial products on membrane surface in the second stage can be controlled by deploying bio-carriers, chemical-enhanced backwashing and cleaning in place. 2.4 Problem Statement Figure 2 MBR fouling mechanism map (Meng et al., 2009) MBR system had been implemented in large application at full scale on industrial wastewater treatment and domestic wastewater treatment and 23

41 Chapter 2 Literature Review reclamation. It is capable of producing high quality effluent and achieving excellent pathogens removal with consistent performance. However, the disadvantages of MBR, especially high-energy consumption and membrane fouling, are hindering its widespread application Energy Consumption in MBR system Starting from the first tabular side-steam MBR whose specific energy demand was reported as 6 8 kwh/m 3, energy demand reduction in MBR has improved significantly to only about 0.5 kwh/m 3 for Zenon submerged MBRs very recently (Buer & Cumin, 2010). Although a wide variation was reported in literature, full-scale MBR system was reported as kwh/m 3 (Palmowski, Veltmann, & Pinnekamp, 2010) and kwh/m 3 (Lazarova, Martin, Bonroy, & Dauthuille, 2010) typically. While the specific energy demand for CAS was reported only 0.3 kwh/m 3 for domestic applications (Fenu et al., 2010) and kwh/m 3 for industrial applications (Cummings & Frenkel, 2008). Higher cost incurred by MBR than CAS process is a result of both higher capital cost (capex) and higher operational cost (opex). The main components of opex are membrane fouling control and membrane replacement (Judd & Judd, 2008). Membrane fouling is a complex interaction between membrane surface and mixed liquor that can be alleviated by operating in low pressure, in constantflux mode, subcritical flux, intermittent relaxation, backwashing and scoring (Xiang & Bo, 2001). It can also be controlled by modifying membrane surface properties and mixed liquor characteristics to discourage deposition of organics and inorganics on membrane surface and pores. Among all control methods, aeration is commonly considered as the most energy-intensive (Judd & Judd, 2008). Based on the aeration model suggested by Verrecht et al. (2008), a 24

42 Chapter 2 Literature Review significant energy reduction could be achieved by retaining lower MLSS concentration. Other researchers have also reported that higher MLSS concentration implied significantly more mixing energy cost and reduced oxygen transfer efficiency in the MBR system (Fenu et al., 2010; Krzeminski et al., 2012). Lower MLSS concentration can be achieved by optimizing operating parameters like dissolved oxygen (DO), organic loading rate (OLR), solids retention time (SRT) and hydraulic retention time (HRT). However, these parameters definitely affect mixed liquor characteristics, which may result in different fouling behavior in turn. Based on pilot-scale MBR studies in Singapore, optimization of HRT/flux, recirculation ratio, SRT/MLSS, etc. were conducted, resulting in a specific energy demand below 0.5 kwh/m 3. However, there are questions remained unanswered: Are the optimized parameters applicable to other membrane brands? Is there a unified fouling mechanism? Is it possible to predict fouling behavior to enable fast adjustment in operations? Effects of SRT on membrane fouling Three fouling factors have been often discussed: nature of feed; membrane properties and hydrodynamic environment (Zhang et al., 2006). Characteristics of the feed, namely, mixed liquor where membrane is submerged in a municipal MBR system, is controlled by many factors such as HRT, SRT, DO and Organic Loading. In this study, the effects of short SRTs on the nature of mixed liquor was the focus. 25

43 Chapter 2 Literature Review Fouling Factors Operating & Design Nature of Feed Flocs SMP & EPS Colloids Reactor Parameters SRT & HRT Organic Load DO Membrane Properties Pore size (distribution) Hydrophilic/hobic Surface charge Hydrodynamic Environment Flux critical or sustainable Flow and shear - magnitude & distribution Membrane Selection MF/UF Material of Fabrication Module Characteristics Submerged hollow fiber Submerged flat sheet Operating mode Bubbling two phase Intermittent flux Intermittent bubbling Backwash Figure 3 Fouling factors and its implications on operating & design However, there were conflicting findings on this. Some argued that fouling rate declined with increasing SRTs (Ahmed et al., 2007; Liang et al., 2007). While some claimed otherwise (Lee et al., 2003). Some argued that more fine particles under short SRTs led to faster fouling rate (Ahmed et al., 2007); some discovered that EPS is the predominant factor on membrane fouling (B. Cho & Fane, 2002); while some argued that it is more SMP produced under shorter SRT that contributed to faster fouling (Liang et al., 2007). However, these conclusions were based on long SRT of more than 10 d. Ng et al. (2005) conducted experiments for short SRTs (oxic SRTs of 3, 5, 10 and 20 d) and found that both EPS and SMP contributed to fouling. They also found the 26

44 Chapter 2 Literature Review common foulant for all four SRTs, namely carbohydrates. Nevertheless, this research failed to conclude a fouling mechanism under short SRTs. Therefore, this study has investigated the effects of SRT on characteristics of mixed liquor (MLSS concentration, SMP and EPS, floc size distribution) and subsequently, key potential foulants were concluded in hollow fiber and flat sheet modules. 27

45 Chapter 3 Materials and Methods Chapter 3 Materials and Methods 3.1 Membrane Bioreactor (MBR) Systems System Design and Configuration Figure 4 Schematic Flow of pre-denitrification MBR system. A pre-denitrification MBR system was proposed to investigate the effects of solids retention time (SRTs). Such design had the benefit of no additional external carbon source for denitrification is required, thus saving chemical cost. Table 6 Summary of operational parameters controlled in the experiment. Parameters SRT-3d SRT-5d SRT-7d SRT-10d HRT (h) 5.5 SRT (d) Flux (LMH) >25 As shown in Table 6, HRT and Flux were controlled parameters at 5.5 hours and not less than 25 LMH, respectively. However, the four MBRs were maintained with different SRT of 3, 5, 7 and 10 d. The SRT and HRT were 28

46 Chapter 3 Materials and Methods calculated based on the volume where biological process dominantly took place, namely, anoxic and oxic tank only, as shown in Equation (3-1) and (3-2). Flux was calculated as Equation (3-3). Sludge wasting volume is different for four reactors, thus flux varied slightly as a result. = (3-1) = (3-2) = ( ) (3-3) Where HRT = hydraulic retention time (h); SRT = solids retention time (day); = influent flow rate (L/day); = volume of anoxic tank; = volume of oxic tank; = biomass concentration of anoxic tank; = biomass concentration of oxic tank; = biomass concentration of membrane tank; = flow rate of sludge wasting; = active membrane surface (m 2 ); and = suction time in a day (24 hour *0.9). Systems were designed according to specification described hereafter for phase 1 (hollow fiber membrane) and phase 2 (ceramic membrane). Influent wastewater, from the primary sedimentation tank (PST) of a water reclamation plant in Singapore, was first introduced to the anoxic tank where a stirrer was installed to promote mixing. Mixed liquor would then overflow to the oxic tank, at the bottom of which an aeration system was situated to provide oxygen for microbial activity as well as to promote mixing. Oxic tank mixed liquor flowed to membrane tank by gravity. Air scoring was installed right beneath the membrane module for maximal scoring effect. Sludge wasting line was located at the membrane tank. There were two internal recirculation line each with a flow rate of 2Q. One line circulated mixed liquor from the 29

47 Chapter 3 Materials and Methods membrane tank to the oxic tank; and the other line circulated mixed liquor from the oxic tank to the anoxic tank. Compared to having only one recirculation line from membrane tank to anoxic tank straight, it reduced the effect of residual dissolved oxygen brought over from the membrane tank to the anoxic tank. High residual oxygen in recirculated mixed liquor could adverse the formation of anoxic environment for denitrification performance. Figure 5 Experimental setup in phase one (left) and phase two (right). Membrane operation interval was set at 9-min suction and 1-min relaxation. Suction and feed pumps were controlled by level sensor located at the side wall of membrane tank to maintain a targeted water level. To monitor membrane fouling extent, a pressure gauge (SMC) was installed between the membrane outlet and suction pump. The pressure was taken as trans-membrane pressure (TMP) required to maintain constant flux. TMP data was recorded every 15 min. 30

48 Chapter 3 Materials and Methods Membrane Properties and Operating Conditions for Hollow Fiber Membrane Table 7 Hollow Fiber membrane properties. PTFE Hollow Fiber Membrane Module Dimension (mm 3 ) 400 (L) x 58 (D-E) x 50 (D-M) Active Membrane Area (m 2 ) 0.1 Nominal pore size (µm) 0.1 The hollow fiber membrane, made of Polytetrafluotoethylene (PTFE), used in this research project was provided by a Japanese membrane manufacturer. The module (as shown in Figure 6a) has an active surface area of 0.1 m 2 and a nominal pore size of 0.1 µm. The hollow fibers are arranged in a U-shape with permeate outlets fixed at the top as shown in Figures 6(b) and (e). Figure 6 hollow fiber membrane module: (a) hollow fiber arrangement; (b) module bottom; (c) inlet for air scoring; (d) outlet for permeate; (e) a closer look at permeate outlet 31

49 Chapter 3 Materials and Methods Figure 7 Experimental setup of four MBRs using hollow fiber membrane (phase one). As shown in Figure 7, four parallel MBRs were set up to investigate the effects of short SRTs on the performance of MBR system. Except for SRTs, all other parameters were controlled constant as shown in the Table 7. The total HRT was calculated as 6.07 h; while biological HRT as 5.5 h as required. The total SRT was calculated as 3.41, 5.79, 8.06 and d for the four MBRs. Flux varied slightly in the four MBRs to compensate different sludge wasting volume, namely 25.7, 26.3, 26.5 and 26.7 LMH, respectively. With an aeration rate at 0.5 L/min, the DO in the anoxic tank was around 0.2~0.3 mg/l in the four MBRs; and the DO of the oxic tank was around 1.5~1.8mg/L. 32

50 Chapter 3 Materials and Methods Table 8 Summary of operating parameters and conditions of four MBRs (phase one) Phase 1 (Four Bioreactors in parallel using Hollow Fiber Membrane) Parameters SRT-3d SRT-5d SRT-7d SRT-10d HRT (h) 5.5 a (6.07) b SRT (d) 3 a (3.41) b 5 a (5.79) b 7 a (8.06) b 10 a (11.24) b Working volume (L) 14.8 (7.3L:6.1L:1.4L) Flux (LMH) Aeration rate (L air/min) 0.5 c Scoring rate (L air/min) 4 d ph 7.0 ±0.2 Anoxic DO (mg/l) 0.3 ± ± ± ± 0.1 Oxic DO (mg/l) 1.8 ± ± ± ± 0.7 SADm (m 3 air/m 2 membrane/h) 2.4 SADp (m 3 air/m 3 permeate) a biological HRT and SRT; b total HRT and SRT; c at hydrostatic pressure of 0.67 psi; d at hydrostatic pressure of 0.68 psi. Specific aeration demand based on membrane area (SADm) was 2.4 m 3 air/m 2 membrane/h. While, specific aeration demand based on permeate volume (SADp) was 134.3, 131.6, and m 3 air/m 3 permeate for the 3d-, 5d-, 7d- and 10d-SRT MBRs. However, in industrial practice, much lower SADm (0.18~0.6) and SADp (7~24 or higher) can be achieved by implementing intermittent aeration or stacked membrane modules. Caustic buffer was added to the oxic tank to maintain the ph at 7.0 ± 0.2 for optimal nitrification rate. Aeration rate was controlled at as low as 0.5 L/min to reduce the effect of dissolved oxygen brought over to the anoxic tank through recirculation line. Scoring rate was kept at 4L/min for all bioreactors. 33

51 Chapter 3 Materials and Methods Membrane Properties and Operating Conditions for Ceramic Membrane Table 9 Ceramic membrane properties deployed in phase two Ceramic Flat Sheet Membrane Module Dimension (mm 3 ) 245 x 88 x 5 Active Membrane Area (m 2 ) Nominal pore size (µm) 0.1 The flat sheet membrane was made of ceramic, provided by a Japanese membrane manufacturer in Singapore. It has the same nominal pore size of 0.1 µm, which is same as that of the Hollow Fiber. However, it has a smaller active membrane surface area compared to the HF membrane. Thus, in order to reuse the anoxic and oxic tank, two pieces of flat sheet membrane were installed in the membrane tank (with a total active membrane area = 0.09 m 2 ). The air scoring equipment was designed as shown in Figure 8. Figure 8 Experimental design of MBR in phase two: (a) air scoring design; (b) membrane tank design; (c) air inlet design; (d) cleaned membrane 34

52 Chapter 3 Materials and Methods Figure 9 Display of four MBRs running Ceramic membrane in phase two As shown in Figure 9, four parallel MBRs were set up and operated simultaneously to investigate the effects of short SRTs on the performance of MBR system. Table 9 summarizes its operating conditions in phase 2. The total HRT in the ceramic MBR system was The total SRT was maintained at 3.69, 5.69, 8.13 and for the 3d-, 5d-, 7d- and 10d-SRT MBRs, respectively. The total HRT and SRT was slightly higher than those of the hollow fiber MBRs due to slightly larger working volume. Other parameters such as ph, aeration rate and scoring rate, were kept the same as the hollow fiber MBRs. The DO for the anoxic tank was around 0.3 mg/l for the four MBRs; while the DO for the oxic tank was 2.0~2.5 mg/l. SADm was calculated as 2.7 m 3 air/m 2 membrane/h and SADp was 115.9, 111.0, and m 3 air/m 3 permeate for the 3d-, 5d-, 7d- and 10d-SRT MBRs, respectively. 35

53 Chapter 3 Materials and Methods Table 10 A summary of operating parameters and conditions in phase two Phase 2 (Four Bioreactors in parallel using Ceramic Membrane) Parameters SRT-3d SRT-5d SRT-7d SRT-10d HRT (h) 5.5 a (6.33) b SRT (d) 3 a (3.69) b 5 a (5.69) b 7 a (8.13) b 10 a (12.07) b Working volume (L) 15.2 (7.3L:5.4L:2.5L) Flux (LMH) Aeration rate (L air/min) 0.5 c Scoring rate (L air/min) 4 d ph 7.0 ±0.2 Anoxic DO (mg/l) 0.3 ± ± ± ± 0.03 Oxic DO (mg/l) 2.0 ± ± ± ± 0.9 SADm (m 3 air/m 2 membrane/h) 2.7 SADp (m 3 air/m 3 permeate) a biological HRT and SRT; b total HRT and SRT; c at hydrostatic pressure of 0.61 psi; d at hydrostatic pressure of 0.41 psi. 3.2 Feed water Characteristics Table 11 Influent characteristics for Ceramic MBR system in phase two mg/l Influent (total) Influent (soluble) TOC 54.5 ± ± 6.9 COD ± ± 22.1 BOD 82.5 ± 6.5 TN 49.8 ± ± 8.0 NH3-N 33.3 ± 3.4 TP (as PO4 - ) 29.3 ± ± Sampling and Extraction Methods Sampling Methods Membrane permeate, mixed liquor (anoxic, oxic and membrane tank) and influent was sampled three times a week. Mixed liquor was taken from the sampling point located at mid-height. 36

54 Chapter 3 Materials and Methods Soluble Microbial Product (SMP) Extraction Mixed liquor supernatant (also treated as SMP in this study) was obtained by centrifuging the samples at 9,000 rpm for 10 min at 4 C before filtering by a 0.45-μm membrane filter (PALL, USA) Extracellular Polymeric Substances (EPS) Extraction The extraction of EPS was carried out by the heating method. The mixed liquor precipitated after centrifuging by 9,000 rpm for 10 min was re-suspended to original volume by using ultra-pure water. After completely mixing the biomass, the sample was incubated in an 80 C water bath for 15 min. The warm sample was taken out of water bath and centrifuged by 9,000 rpm for 10 min at 4 C, and the supernatant of the centrifuged sample was collected after filtration by a 0.45-μm membrane filter for subsequent analysis. 3.4 Analytical Methods Water Quality Analysis Total Organic Carbon (TOC) TOC was determined using a TOC-TN analyzer (TOC-VCSH Shimadzu, Japan). Biological Oxygen Demand (BOD) Seeding biomass was prepared as 1 ml/l. Nutrient solution was a mixture of ferric chloride, calcium chloride, MgSO4 7H2O and phosphate buffer with concentration of 1 mg/l. The mixture of seeding biomass and nutrient solution was then aerated under room temperature for 4 h to achieve saturated dissolved oxygen. Then sample and the mixture was mixed in BOD bottles. After 37

55 Chapter 3 Materials and Methods measuring DO (taken as initial DO), BOD bottles was incubated at 20 o C for 5 days. Final DO was measured after 5 d of incubation. Sample volume and BOD5 was calculated as follows: = ( ) (3-4) = ( ) (3-5) Where = samples volume; ; = initial and final DO for sample;, = initial and final DO for blank; and = volumetric fraction of sample =. Chemical Oxygen Demand (COD) COD was measured by the HACH METHOD Membrane permeate COD was measured by the COD LR (0-150mg/L); and influent COD was measured by the COD HR ( mg/l). Total Nitrogen (TN), Ammonia Nitrogen (NH3-N), Nitrate Nitrogen (NO3 - -N), Nitrite Nitrogen (NO2 - -N) Nitrite was measured by the LR TNT testing kits (HACH METHOD 10019). Nitrate was measured by the HR TNT testing kits (HACH METHOD 10020). Ammonia was measured by the HR TNT testing kits (HACH METHOD 10031). Total Nitrogen was measured by the HR TNT testing kits (HACH METHOD 10072). 38

56 Chapter 3 Materials and Methods Total Phosphorus (TP) TP was measured by the TNT testing kits (Hach Method 8190) Organic Matters Analysis Proteins Protein content was measured using the Lowry method with bovine serum albumin (BSA) as the standard (Lowry et al., 1951). Briefly, 1 ml of sample was added into two tubes and mixed with 5 ml of assay mix and vortexed thoroughly. After incubation of the sample in room temperature for 10 min, 0.5 ml diluted Folin Ciotalteu reagent was added into each tube and mixed by a vortex. The solution was incubated under room temperature for another 30 min before measuring by the spectrophotometer at a wavelength of 650 nm (HACH, DR6000). The Assay Mix was composed of 25 ml of alkaline reagent (0.1-M NaOH, 2% Na2CO3, 0.02% sodium potassium tartrate and 1% Na Dodecylsulfate) and 1 ml of copper reagent (0.5 % CuSO4 5H2O). Carbohydrates The phenol-sulfuric acid was used to measure the carbohydrate using glucose as the standard (Dubois et al., 1956). 2 ml of sample was added into a test tube, and then 1 ml of 5% (W/V) phenol solution was added into each tube. A rapid dispenser was used to add 5 ml of concentrated sulfuric acid. The solution was mixed immediately followed by a 30-min incubation period under room temperature. Absorbance measurements were taken at a wavelength of 490 nm using a spectrophotometer (HACH, DR 6000). 39

57 Chapter 3 Materials and Methods Excitation emission matrix (EEM) The three-dimension EEM fluorescence spectra were measured for dissolved organic matters in the membrane permeates, SMP and EPS by a luminescence spectrophotometer (LS-55, Perkin Elmer Co., USA). Profile obtained could be used to characterize humic-, fulvic-, protein- and microbial byproduct-like compounds. The emission spectra between the wavelength of 230 and 550 nm were collected at 0.5-nm increment by varying the excitation wavelength from 230 to 550 nm at 5-nm intervals. Excitation and emission slits were set at 10 nm with a scanning speed of 1000 nm/min. Chen et al. (2003) divided EEM spectra into five regions related to five types of organics. In general, Region I and II with shorter excitation wavelengths (< 250 nm) and shorter emission wavelengths (< 350 nm) are related to simple aromatic proteins. Region III with shorter excitation wavelengths (< 250 nm) and longer emission wavelengths (> 350 nm) is related to fulvic acid-like materials. Region IV with intermediate excitation wavelengths ( nm) and shorter emission wavelengths (< 380 nm) is related to soluble microbial byproduct-like material. Region V with longer excitation wavelengths (> 280 nm) and longer emission wavelengths (> 380 nm) is related to humic-acid like organic. LC-OCD LC-OCD (DOC-LABOR Dr. Huber, Germany) was used to fractionize and quantify dissolved organic matters. According to different MW and physiochemical characteristics of organic fractions, size exclusion column firstly separated the organic matters into four fractions, namely, biopolymer, humic substance, building blocks and low molecular weight neutrals. 40

58 Chapter 3 Materials and Methods Particles Analysis Mixed Liquor Suspended Solids (MLSS) and Volatile Suspended Solids (MLVSS) Biomass concentration was measured as MLSS and MLVSS according to the Standard Methods (APHA et al., 2005). Mixed liquor samples was filtered by a pre-treated glass fiber (GF/F, Whatman) and dried in the oven (MEMMERT ULM 6, Schmidt Scientific) at 105 o C for 1 h, followed by ignition in a furnance (Thermolyne 48000, Omega Medical Scientific) at 550 o C for 30 min. The glass fiber was pre-treated by filtering De-Ionized water and dried at 105 o C for 1 h and then 550 o C for 30 min. All weight was taken after room temperature was reached. MLSS and MLVSS was calculated as below: = (3-6) = (3-7) Where W0 = weight of pre-treated fiber glass; W1 = weight of fiber glass + sample after drying at 105 o C for 1 h; and W2 = weight of fiber glass + sample after drying at 550 o C for 30 min. Particle Size Distribution (PSD) Particle size distribution of mixed liquor were analyzed by a laser diffraction particle analyzer (LS230 Coulter, Beckman, Germany). 41

59 Chapter 3 Materials and Methods 3.5 Membrane Cleaning Procedures Membrane was cleaned only when the TMP reached 30 kpa. Sodium Hypochlorite with concentration of 3,000 ppm was used to soak the membrane module overnight. The cleaned membrane was then being used for the next fouling cycle. 42

60 Chapter 4 Results and Discussion 4.1 MBR systems using Hollow Fiber Membrane Biomass Concentration and Characteristics Four MBR systems received an average organic loading rate (OLR) of 0.02 kgcod/d during its operation. Under such loading rate, the anoxic tank MLVSS concentration was 886.7, , and mg/l for the -3d-, 5d-, 7dand 10d-SRT MBRs, respectively. The oxic tank had MLVSS concentrations of , , and mg/l, while the membrane tank MLVSS concentrations were , , and mg/l, respectively. Thus, biomass concentration for all four bioreactors showed an increasing trend from the anoxic to the oxic tanks, and then to the membrane tank. Increment from the anoxic tank to the oxic tank was attributed to faster microbial growth inside aerobic environment than anoxic environment, while the membrane tank accumulated higher biomass than oxic tank by solid-liquid separation of membrane. Although there were internal circulation with a flow rate of two times of influent flow, the above two factors could not be completely offset. It is also noticed that all four reactors maintained a high MLVSS/MLSS ratio of more than 0.8. The high ratio can be explained by short solids retention time inside the reactor. However, MBR system could still produce high quality effluent despite of poor biomass settlability. It could be concluded that increasing SRT maintained higher biomass concentration in the MBR system. 43

61 Anoxic Tank Oxic Tank Membrane Tank Table 12 Biomass concentration and sludge characteristics in four Hollow Fiber MBRs SRT-3d SRT-5d SRT-7d SRT-10d MLSS (mg/l) ± ± ± ± MLVSS (mg/l) 886.7± ± ± ± MLVSS/MLSS 0.83 ± ± ± ± 0.05 MLSS (mg/l) ± ± ± ± MLVSS (mg/l) ± ± ± ± MLVSS/MLSS 0.82 ± ± ± ± 0.05 MLSS (mg/l) ± ± ± ± MLVSS (mg/l) ± ± ± ± MLVSS/MLSS 0.80 ± ± ± ± 0.02 Daily sludge production (kgvss/m 3 treated) Organic Loading Rate (kgcod/day) ± ± ± ± ± F/M ratio (kgcod/day/kgvss) Biomass Observed Yield, Y obs (kgvss/kgcod) 1.15 ± ± ± ± ± ± ± ± 0.02 As summarized in Table 11, the daily sludge production was 0.095, 0.077, and kgvss/m 3 treated; the F/M ratios in the four MBRs were 1.15, 0.89, 0.83 and 0.80; the biomass observed yields were 0.33, 0.25, 0.19 and 0.14 for the 3d-, 5d-, 7d- and 10d-SRT MBRs, respectively. Therefore, they all decreased with increasing SRTs; indicating higher growth rate and microbial activity under shorter SRTs. 44

62 4.1.2 Treatment Performance of MBR system under Four SRTs Feed Wastewater Characteristics Table 13 Influent characteristics in phase one mg/l Influent (total) Influent (soluble) TOC 63.8 ± ± 11.0 COD ± ± 37.9 BOD ± 12.7 TN 43.8 ± ± 3.2 NH 3-N 33.3 ± 3.9 TP (as PO - 4 ) 25.2 ± ± 4.8 Four parallel MBRs received wastewater from the PST of a local water reclamation plant, with a total COD of mg/l, soluble COD of mg/l and BOD5 of mg/l. The TN of the influent was 43.8 mg/l and ammonia was 33.3 mg/l. Although influent characteristics fluctuated daily, the MBR systems were capable to produce effluent with consistent quality as discussed below. TOC, COD and BOD Removal Performance Table 14 TOC COD and BOD removal in four MBRs of phase one mg/l Influent SRT-3d SRT-5d SRT-7d SRT-10d TOC 63.8 ± ± ± ± ± ± 11.0* (85.9%) (87.4%) (87.1%) (86.1%) COD ± ± ± ± ± ± 37.9* (91.8%) (93.0%) (92.8%) (93.0%) BOD ± 12.7 * TOC, COD in soluble form 7.7 ± ± ± ± 0.2 (96.6%) (98.6%) (99.8%) (99.9%) Table 13 shows the total COD concentration in the influent wastewater and effluent from each MBR after Day 77. It is noticed that despite the variation in influent quality, the four lab-scale MBRs were able to produce effluents of 45

63 consistently high quality. The average effluent COD concentrations of the MBRs with SRT of 3, 5, 7 and 10 d were 27.7, 23.1, 23.8 and 23.4 mg/l, respectively. The COD removal rates were 91.8%, 93.0%, 92.8% and 93.0% accordingly, which is consistent with Tan et al. s (2008) finding that MBR were able to achieve high COD removal rate regardless of SRTs. In this study, high COD removal efficiencies were observed in all MBRs, even when the SRT was as low as 3 d. Furthermore, the data showed that as the SRT was increased, there was a marginal increase in COD removal rate. As shown in Table 11, the F/M ratios for the 3d-, 5d-, 7d- and 10d-SRT MBRs had a decreasing trend as 1.15, 0.89, 0.83 and Lower F/M ratio makes organic matters more readily consumed for biomass. The same trend was also observed in BOD removal as displayed in Table 11. Four MBRs could achieve high BOD removal efficiencies of more than 96.6% with marginally increase as the SRT was prolonged. High average TOC removal rates of 85.9%, 87.4%, 87.1% and 86.1% were observed in the four MBRs, producing effluent TOC average concentrations of 8.8, 7.8, 8.0 and 8.6 mg/l, respectively. This study showed that the four MBRs, regardless of SRTs, could achieve high COD, BOD and TOC removal efficiencies. Ammonia Removal Performance Table 15 Ammonia, nitrate and nitrite concentration in effluent and its removal in phase two mg/l Influent SRT-3d SRT-5d SRT-7d SRT-10d NH 3-N 33.3 ± ± ± ± ± 0.2 (71.5%) (99.0%) (99.0%) (99.2%) NO - 2 -N ± ± ± ± 0.3 NO - 3 -N ± ± ± ±

64 Ammonia is converted to nitrate via nitrite by nitrifying microorganisms in the oxic tank. With an average influent NH3-N concentration of 33.3 ± 3.9 mg/l, almost complete nitrification (~99% removal) was achieved by the 5d-, 7d- and 10d-SRT MBRs, while only 71.5% NH3-N removal efficiency was achieved in the 3d-SRT MBR. Figure 10 displays the distribution of ammonia-n, nitrate-n and nitrite-n in the MBR effluent. The 3d-SRT MBR produced effluents with 9.6 mg/l ammonia while there was almost no ammonia for the other MBRs. Nitrate concentrations were 10, 19.4, 18.5 and 18.2 mg/l for the 3d-, 5d-, 7dand 10d-SRT MBRs. Nitrite accumulation was only observed in the 3d-SRT MBR (2.1, 0.4, 0.7 and 0.4 mg/l for the four MBRs, respectively), indicating that nitrification and denitrification pathway were affected under short SRTs. Similar findings were also reported: more than 97% ammonia removal efficiency was observed in the 5d-SRT MBR (Tan et al., 2008); nitrification was badly deteriorated when the SRT was less than 2.5 d (Ng and Hermanowicz, 2005). 47

65 25 20 Nitrogen composites in MBR effluent ammonia-n nitrate-n nitrite-n concentration, mg/l SRT-3d SRT-5d SRT-7d SRT-10d Figure 10 ammonia, nitrate and nitrite profile of MBR effluent in phase one Total Nitrogen Removal Performance Table 16 TN removal in four MBRs of phase one mg/l Influent SRT-3d SRT-5d SRT-7d SRT-10d TN 43.8 ± ± 2.2 (48.0%) 20.6 ± 3.6 (52.4%) 20.4 ± 4.2 (53.5%) 19.7 ± 2.3 (56.0%) The four MBRs showed TN removal efficiencies of 48%, 52.4%, 53.5% and 56% for the 3d-, 5d-, 7d- and 10d-SRT MBRs, respectively. An increasing trend was observed as the SRT was increased. Tan et al. (2008) also reported 54% TN removal efficiency for SRT of 8.3 d and TN removal efficiency increased with increasing SRTs. TN removal can be achieved by wasting the biomass that accumulated N by cell assimilation and nitrification-denitrification process. N content in the MLVSS was found to fluctuate between 6.6 and 8.2% with an average of 7.2% by weight 48

66 of the MLVSS concentration. The total nitrogen removal and its breakdown by cell assimilation and nitrification-denitrification can be estimated by equations below. = ( ) (4-1) = ( )0.072 (4-2) = (4-3) Table 17 TN removal and its breakdown by removal mechanism (phase one) Total nitrogen removed (g/day) N removal by cell assimilation (g/day) (%) N removal by denitrification (g/day) (%) SRT-3d SRT-5d SRT-7d SRT-10d 1.25 ± ± ± ± ± 0.06 (33.4±9.4) 0.85 ± 0.32 (66.6±9.4) 0.32 ± 0.05 (28.2±9.5) 0.91 ± 0.37 (71.8±9.5) 0.24 ± 0.03 (17.3±2.8) 1.10 ± 0.17 (82.7±2.8) 0.18 ± 0.02 (14.9±3.6) 1.08 ± 0.3 (85.1±3.6) Calculated results are displayed in Table 17. Average N removed from four MBRs were 1.25, 1.23, 1.33 and 1.26 g/day, which showed a comparable total nitrogen removal in the four MBRs as shown in Figure 11. It was also observed that N removal by cell assimilation decreased as SRT was increased, with percentage of 33.4%, 28.2%, 17.3% and 14.9%, respectively, because shorter SRT showed higher sludge yield. Similarly, nitrogen removal by denitrification increased with increasing SRTs, with the percentage being 66.6%, 71.8%, 82.6% and 85.1%, respectively. It showed that nitrogen removal denitrification became more pronounced under longer SRTs as shown in Figure 12. Longer SRTs maintained higher biomass concentration which could be readily utilized by 49

67 endogenous respiration during denitrification process. It was measured that DO in the anoxic tank was around 0.2 mg/l, while denitrification performance could be considerably deteriorated with DO concentration as low as 0.1 mg/l. Under such circumstances, denitrification process is only effective in the zones where there existed favorable anoxic condition. Higher biomass concentration under longer SRTs hindered oxygen transfer, thus creating DO gradient inside anoxic tank. These two factors explained why denitrification was better for longer SRTs. Total nitrogen removed per day TN removed, g-n/day SRT-3d SRT-5d SRT-7d SRT-10d Figure 11 Comparison of TN removed per day of four MBRs in phase one 50

68 1.6 TN removal by cell assimilation TN removal by denitrification 1.4 TN Removed, g-n/day SRT-3d SRT-5d SRT-7d SRT-10d Figure 12 A graph shows the breakdown of TN removal (phase one) However, TN removal was less satisfactory since theoretical TN removal could be as high as 66.7% for pre-denitrification MBRs with 2Q recirculation. Having noticed that nitrate concentration was 10, 19.5, 18.5 and 18.2 mg/l for the four MBRs, respectively, there is nitrate accumulation in the system, which was a cause of incomplete denitrification. Factors that inhibit denitrification could be carbon source, denitrifier activity and DO. Pre-denitrification configuration with an influent average COD of mg/l and an influent average N of 43.8 mg/l, C/N ratio is sufficient for denitrification. Denitrifier concentration could be a problem when SRT was shortened as denitrifier was slow-growing bacterial. DO was another inhibiting factor because DO brought over into the anoxic tank through recirculation line competed carbon source with denitrifiers. From Table 7, DO in anoxic tank was still measurable, which indicated that there was still a substantial amount of DO left after oxidizing oxygen- 51

69 demanding matters. In this case, denitrification only happened where there was anoxic environment formed by DO gradient. Total Phosphorus Removal Performance Table 18 Total Phosphate removal by four MBRs in phase one mg/l Influent SRT-3d SRT-5d SRT-7d SRT-10d 26.2 ± ± ± ± 3.0 TP 25.2 ± 3.9 (26.8%) (20.9%) (18.6%) (19.4%) Low TP removal efficiencies (18.6~26.8%) were observed in this study. The results were expected because TP removal is only enhanced when there is an anaerobic-aerobic environment. In the case where there was an absence of anaerobic environment, phosphorus removal was only by cell assimilation which incorporated P as cell constituents. In this study, 3d-SRT MBR showed the highest TP removal because of its high sludge yield; while the rest had lower and comparable removal rates. 52

70 4.1.3 Fouling Behavior of Hollow Fibre MBR under short SRTs Fouling Cycles Profile 35 Trans-Membrane Pressure, kpa SRT-3d SRT-5d SRT-7d SRT-10d Cycle Running Days, d Figure 13 TMP Profile for four MBRs in phase one Membrane fouling cycle started at D77 (named as D0 in fouling cycle) when steady state was reached. In this study, four consecutive fouling cycles were conducted to investigate the fouling behavior and its contributing factors. From Figure 13, it was noticed that 3d-SRT MBR was the first to reach 30 kpa, followed by 5d-, 7d- and then 10d-SRT MBRs. It is concluded that, as the SRT was increased from 3 to 10 d, membrane became less prone to fouling. The TMP profiles also showed that the 5d-, 7d- and 10d-SRT MBRs shared the similar fouling behavior, which was observed in all 4 fouling cycles. 53

71 TMP Profile for SRT-3d MBR Trans-Membrane Pressure, kpa Cycle Running Days, d TMP Profile for SRT-5d MBR Trans-Membrane Pressure, kpa Cycle Running Days, d 54

72 TMP Profile for SRT-7d MBR Trans-Membrane Pressure, kpa Cycle Running Days, d TMP Profile for SRT-10d MBR Trans-Membrane Pressure, kpa Cycle Running Days, d Figure 14 Individual TMP Profile for each MBR in phase one 55

73 Table 19 A summary of fouling cycle duration for four MBRs in phase one days SRT-3d SRT-5d SRT-7d SRT-10d Cycle Cycle Cycle Cycle According to Table 19, on average, fouling cycle for the 3d-SRT MBR was around 7-11 d; while 9-15 d, d, d for the 5d-, 7d- and 10d-SRT MBRs, respectively. In order to analyze the pattern more clearly, the TMP profiles were organized separately for the four MBRs and the results are shown in Figure 14. It was observed that each cycle experienced two stage where fouling rate was slow and steady followed by a rapid and exponential increase. As the SRT was increased, the period for the steady stage prolonged. In the first stage, mainly macromolecules, colloids and SMP deposited on the membrane surface to form a gel-like layer (Z. W. Wang, Z., 2009). Fouling caused in this process is slow but irreversible. As filtration period is prolonged, sludge particles containing microorganisms readily attached to the gel layer to form a microenvironment for bacterial growth. In this process, a cake layer was formed on membrane surface. Such cake formation is reversible and could be destroyed by physical shear force like air scouring. 56

74 Membrane Tank Effects of Biomass Concentration on Membrane Fouling Table 20 effects of biomass Concentration on fouling for four MBRs in phase one SRT-3d SRT-5d SRT-7d SRT-10d MLSS (mg/l) ± ± ± ± MLVSS (mg/l) ± ± ± ± MLVSS/MLSS 0.80 ± ± ± ± 0.02 To investigate the effects of MLSS concentration on membrane fouling, measurements on MLSS and MLVSS was conducted for mixed liquor in the membrane tanks for the four MBRs. It was found that MLSS and MLVSS increased with increasing SRTs. However, the relationship between biomass concentration and fouling behavior is not conclusive (Ng et al., 2006). Rather, it is characteristics such as viscosity, dewateribility together with biomass concentration that contributed to membrane fouling (Germain et al., 2005) Effects of Mixed Liquor Particle Size on Membrane Fouling Particle size distribution profile has a direct impact on membrane fouling (Wang et al, 2008; Lim et al, 2003; Zhang et al, 2006). Particles that are smaller or comparable to membrane pore size could cause pore blockage or narrowing (Bai et al, 2002). Both fine and large particles could attach to membrane surface, which would develop into a thick and dense layer when TMP develops (Chang et al, 2002). Either of two circumstances leads to membrane fouling. To investigate particle size distribution of mixed liquor under different SRTs, experiments were conducted at steady state and results were as below. 57

75 Table 21 Statistics of Particle Size Distribution profile for four MBRs in phase one (um) Peak Mean (um) <10% <25% <50% <75% <100% SRT-3d SRT-3d SRT-5d SRT-5d SRT-7d SRT-7d SRT-10d SRT-10d Particle Size Distribution Profile 5 SRT-3d Mixed Liquor SRT-5d Mixed Liquor SRT-7d Mixed Liquor SRT-10d Mixed Liquor 4 Volume, % particle size, um Figure 15 Particle size distribution profile of mixed liquor in four MBRs (phase one) Particle size analyser was able to plot a size distribution profile ranging from 0.04 to 2000 micron. Peak volumes were at 92.1, 133.8, and µm for the 3d-, 5d-, 7d- and 10d-SRT MBRs. Mean values were 113.1, 135.8, and µm, respectively. Thus, it was found that particle size increased with increasing SRTs for the 3d-, 5d- and 7d-SRT MBRs. Smaller particle size was 58

76 observed in the 10d-SRT MBR might be a combined result of the attachment of large particles on membrane surface and re-suspension of loosely bound macromolecules in cake layer from the membrane surface. Initially, in all four MBRs, fouling was caused by attachment of particulates of smaller size to membrane surface, which caused pore blockage/narrowing and gel-layer formation. As filtration cycle prolonged, fouling by attachment of bigger sized particulates (cake-layer formation) became dominant. In the 3d-, 5d- and 7d-SRT MBRs, rejection of fine particles led to severe pore blocking, thus faster membrane fouling. Whereas in the 10d-SRT MBR, cake layer formed by large particles on membrane surface initially acted as secondary layer to prevent fouling by smaller sized particles (Kuberkar et al, 2000; Meng et al, 2006). Its fouling was ultimately caused by dense cake layer formation as the trans-membrane pressure was increased Effects of Mixed Liquor Organic Contents on Membrane Fouling TOC, Proteins and Carbohydrates Analysis Table 22 and 23 summarized organic content concentrations of Effluent, SMP and EPS in the four MBRs. To elucidate the correlation of organic contents in mixed liquor and fouling behavior, both TOC, protein and carbohydrate concentrations and their specific concentrations in the SMP and EPS were calculated. 59

77 Table 22 TOC, Protein and carbohydrate concentrations for the four MBRs in phase one TOC (mg C/L) Proteins (mg BSA/L) Carbohydrates (mg Glucose/L) SRT-3d SRT-5d SRT-7d SRT-10d Effluent 9.1 ± ± ± 1.2 SMP 14.8 ± ± ± 2.1 EPS 62.0 ± ± ± 10.8 Effluent 7.9 ± ± ± 0.7 SMP 12.1 ± ± ± 2.1 EPS 94.1 ± ± ± 7.4 Effluent 8.1 ± ± ± 1.6 SMP 12.1 ± ± ± 2.8 EPS 93.8 ± ± ± 13.2 Effluent 9.5 ± ± ± 1.9 SMP 15.4 ± ± ± 3.4 EPS ± ± ± 14.2 Table 23 Specific concentrations of TOC, proteins and carbohydrates for the four MBRs in phase one SRT-3d SRT-5d SRT-7d SRT-10d Specific TOC (mg C/g VSS) Specific Protein (mg BSA/g VSS) Specific Carbohydrates (mg Glucose/g VSS) SMP 8.6 ± ± ± 2.3 EPS 39.2 ± ± ± 7.4 SMP 6.1 ± ± ± 1.4 EPS 47.2 ± ± ± 2.4 SMP 5.0 ± ± ± 1.7 EPS 41.9 ± ± ± 4.8 SMP 5.1 ± ± ± 1.0 EPS 41.8 ± ± ±

78 Effluent TOC concentrations were 9.1, 7.9, 8.1 and 9.5 mg/l for the 3d-, 5d-, 7d- and 10d-SRT MBRs; Protein contents of effluent were 7.2, 7.6, 5.6 and 6.5 mg/l, respectively; and Carbohydrate contents were 6.9, 3.5, 3.6 and 3.5 mg/l, respectively. As shown in Figure 16, TOC and Protein concentrations of effluents in the four MBRs were of great variation and did not show any trend; while carbohydrate concentration was the highest in the 3d-SRT MBR and comparable among the rest MBRs TOC concentration proteins concentration carbohydrates concentration Concentrations SRT-3d SRT-5d SRT-7d SRT-10d Figure 16 Organic contents in the effluent from the four MBRs in phase one TOC concentrations in the SMP were 14.8, 12.1, 12.1 and 15.4 mg/l in the four MBRs, respectively; EPS TOC concentrations were 62.0, 94.1, 93.8 and mg/l, respectively. Thus, both SMP and EPS TOC did not show any trend correlated to fouling trend. Specific TOC concentrations in the SMP were 8.6, 6.1, 5.0 and 5.1 mg/l for the 3d-, 5d-, 7d- and 10d-SRT MBRs, respectively; specific TOC concentrations in the EPS were 39.2, 47.2, 41.9 and 41.8 mg/l, 61

79 respectively. Thus, specific TOC concentrations in the SMP decreased with increasing SRTs as shown in the black dots of Figure 18, which followed the fouling trends; while specific TOC concentrations in the EPS did not follow any trend. Therefore, specific TOC concentrations in the SMP contributed to membrane fouling under short SRTs. TOC Comcemtration SMP EPS 140 concnetration, mg/l-c SRT-3d SRT-5d SRT-7d SRT-10d Figure 17 TOC concentrations of the SMP and EPS for the four MBRs in phase one 62

80 specific TOC concentration 80 specific concentration, mgc/gvss SMP EPS SRT-3d SRT-5d SRT-7d SRT-10d Figure 18 Specific TOC concentrations of the SMP and EPS for the four MBRs in phase one Protein Concnetration SMP EPS concentration, mgbsa/l SRT-3d SRT-5d SRT-7d SRT-10d Figure 19 Protein concentrations in the SMP and EPS for the four MBRs in phase one 63

81 Specific Protein Concentration 100 concentration, mgbsa/gvss SMP EPS 0 SRT-3d SRT-5d SRT-7d SRT-10d Figure 20 Specific Protein concentrations in the SMP and EPS for the four MBRs in phase one Protein concentrations in the SMP were 8.9, 6.0, 6.8 and 7.8 mg/l in four MBRs, respectively; Protein concentrations in the EPS were 91.2, 119.4, and mg/l, respectively. Thus, the SMP protein concentrations did not show any trend; while the EPS protein concentrations increased with increasing SRTs, which might be a result of increased biomass concentrations under longer SRTs. Specific protein concentrations in the SMP were 5.2, 3.2, 2.7 and 2.6 mg/l for the 3d-, 5d-, 7d- and 10d-SRT MBRs, respectively; specific protein concentrations in the EPS were 57.6, 56.8, 52.1 and 51.9 mg/l, respectively. Thus specific protein concentrations in both the SMP and EPS decreased with increasing SRTs, which were consistent with the fouling trend. Therefore, specific proteins in the SMP and EPS, not total concentration, contributed to fouling trend. 64

82 Carbohydrates Concentration 50 concentration, mgglucose/l SMP EPS 0 SRT-3d SRT-5d SRT-7d SRT-10d Figure 21 Carbohydrate concentrations in the SMP and EPS for the four MBRs in phase one Specific Carbohydrates Concnetration concentration, mgglucose/gvss SMP EPS 0 SRT-3d SRT-5d SRT-7d SRT-10d Figure 22 Specific carbohydrate concentrations in the SMP and EPS for the four MBRs in phase one 65

83 Carbohydrate concentrations in the SMP were 5.7, 5.3, 5.0 and 5.7 mg/l in the four MBRs, which did not follow the fouling trends. Carbohydrates in EPS were 17.9, 26.1, 29.1 and 31.9 mg/l, respectively. Thus EPS carbohydrates increased with increasing SRTs, which might be a result of higher biomass concentration in longer SRTs; while SMP carbohydrates did not show any trend. Specific carbohydrate concentrations in the SMP were 3.8, 2.8, 2.3 and 1.9 mg/l for the 3d-, 5d-, 7d- and 10d-SRT MBRs, respectively, which followed the fouling trends; specific carbohydrate concentrations in the EPS were 11.4, 12.9, 11.9 and 10.8 mg/l, respectively, which did not show any trend. Thus specific carbohydrates in the SMP, not EPS, contributed to membrane fouling. To conclude, specific TOC, protein and carbohydrate concentrations in the SMP contributed to membrane fouling in the 3d-, 5d-, 7d- and 10d-SRT MBRs. SMP composites are usually smaller or close to membrane pore sizes, thus SMP is often correlated with internal pore narrowing. SMP was also reported to be associated with gel layer formation due to size exclusion of macromolecules (Jarusutthirak et al., 2006; Drews et al., 2010). It was also found in this study that specific protein contents in the EPS, not other compounds, contributed to membrane fouling. Table 24 Organic rejections by the four MBRs in phase one TOC rejection (%) SRT-3d 38.8 ± 8.1 SRT-5d 33.5 ± 6.1 SRT-7d 32.0 ± 7.2 SRT-10d 30.4 ±

84 Table 24 summarizes an analysis on TOC rejections by the four MBRs. TOC showed rejection rates of 38.8, 33.5, 32.0 and 30.4% for the 3d-, 5d-, 7d- and 10d-SRT MBRs, respectively. Thus average TOC rejection increased with decreasing SRTs. It was also noticed that the 5d-, 7d- and 10d-SRT MBRs showed comparable TOC rejections, which explained the similar fouling behavior among the three MBRs. Therefore, rejection of organic matters by membrane contributed to membrane fouling. LC-OCD Analysis LC-OCD was deployed to analyze organic matters distribution profile according to molecular weights in the effluent and the SMP in the four MBRs. The results are summarized in Table 25. As shown in Figure 23, concentrations of organic matters in the effluents of all the four MBRs were consistent and comparable over the whole spectrum of sizes. Similar trends were also observed in the SMP as shown in Figure

85 Table 25 Organic contents profiles by LC-OCD analysis in phase one DOC Hydrophobic Hydrophillic (HOC) (CDOC) mg/l Biopolymers Humics Building Blocks LMW neutrals SRT-3d SRT-5d SRT-7d SRT-10d Effluent 7.4 ± ± ± ± ± ± ± 0.8 SMP 10.4 ± ± ± ± ± ± ± 0.6 Effluent 6.9 ± ± ± ± ± ± ± 0.8 SMP 9.5 ± ± ± ± ± ± ± 1.3 Effluent 6.9 ± ± ± ± ± ± ± 0.8 SMP 9.2 ± ± ± ± ± ± ± 0.3 Effluent 6.9 ± ± ± ± ± ± ± 0.6 SMP 10.1 ± ± ± ± ± ± ±

86 10 8 SRT-3d SRT-5d SRT-7d SRT-10d concentration, mg/l DOC Hydrophobic Hydrophillic Biopolymers Humics Buidling Blocks LMW neutrals Figure 23 Comparison of organic contents in the effluent for the four MBRs (phase one) SRT-3d SRT-5d SRT-7d SRT-10d concentration, mg/l DOC Hydrophobic Hydrophillic Biopolymers Humics Buidling Blocks LMW neutrals Figure 24 Comparison of organic contents in the SMP for the four MBRs (phase one) 69

87 Table 26 Organic rejections by the four MBRs in phase one (LC-OCD analysis) % DOC Hydrophillic (CDOC) Biopolymers Humics SRT-3d 28.5 ± ± ± ± 4.4 SRT-5d 27.2 ± ± ± ± 8.9 SRT-7d 24.1 ± ± ± ± 7.3 SRT-10d 31.0 ± ± ± ± DOC Rejection Profile 30 DOC rejection, % SRT-3d SRT-5d SRT-7d SRT-10d Figure 25 DOC (dissolved organic carbon) rejection profiles for the four MBRs in phase one 70

88 60 CDOC Rejection Profile 50 CDOC rejection, % SRT-3d SRT-5d SRT-7d SRT-10d Figure 26 CDOC (hydrophilic DOC) rejection profiles for the four MBRs in phase one 100 Biopolymers Rejection Profile 80 Biopolymers rejection, % SRT-3d SRT-5d SRT-7d SRT-10d Figure 27 Biopolymers rejection profiles for the four MBRs in phase one 71

89 50 Humics Rejection Profile 40 Humics rejection, % SRT-3d SRT-5d SRT-7d SRT-10d Figure 28 Humics rejection profiles for the four MBRs in phase one Rejection rate by membrane for various organic contents was calculated to further elucidate their correlation with fouling behavior. A summary is shown in Figure 23; and a comparison among the four MBRs was shown from Figure 25 to 28. No trend was observed in the DOC, CDOC and humics rejection rates for the 3d-, 5d-, 7d- and 10d-SRT MBRs. However, biopolymers rejection decreased slightly with increasing SRTs, although the variances were small. Thus it was concluded that rejection of biopolymers mainly contributed to membrane fouling - the more it rejected, the more prone to membrane fouling. It was also found that, as the operation time was prolonged, the dense cake layer formed on the membrane surface of the 10d-SRT MBR led to much higher rejection of DOC and CDOC, which was a result of secondary filtration by cake layer formed on membrane surface. 72

90 EEM Analysis Figure 29 EEM spectra of the 3d-SRT MBR effluent in phase one Figure 30 EEM spectra of the 5d-SRT MBR effluent in phase one 73

91 Figure 31 EEM spectra of the 7d-SRT MBR effluent in phase one Figure 32 EEM spectra of the 10d-SRT MBR effluent in phase one 74

92 Table 27 Summary of the peak data by the EEM analysis in phase one (effluent) SRT-3d SRT-5d SRT-7d SRT-10d Aromatic protein-like Fulvic Acid-like Humic Acid-like Figure 29 to 32 showed composites of the effluents of the four MBRs under EEM analysis. It was noticed that three peaks appeared in all the MBRs, regardless of intensity. According to the five-region method, the three peaks belong to aromatic protein, fulvic acid-like and humic acid-like substances. Peak intensities are summarized in Table 27. It was found that effluents from the four MBRs contained comparable amount of organic substances, namely, aromatic proteins, fulvic acid-like and humic acid-like substances. 75

93 Figure 33 EEM spectra of the 3d-SRT MBR SMP in phase one Figure 34 EEM spectra of the 5d-SRT MBR SMP in phase one 76

94 Figure 35 EEM spectra of the 7d-SRT MBR SMP in phase one Figure 36 EEM spectra of the 10d-SRT MBR SMP in phase one Table 28 Summary of the peak data by EEM analysis in phase one (SMP) SRT-3d SRT-5d SRT-7d SRT-10d Aromatic protein Humic Acid-like

95 Figure 33 to 36 showed composites of the SMP under the EEM analysis. It was noticed that only two obvious peaks appeared in all the MBRs, regardless of the intensity. According to the five-region method, the two peaks belong to aromatic protein and humic acid-like substances. Peak intensities are summarized in Table 28. It was found that the SMP from the four MBRs contained comparable amounts of aromatic proteins and humic acid-like substances. By comparing the peak values in the effluent and SMP, it was found that aromatic proteins reduced significantly from the SMP of the mixed liquor to the effluent, suggesting that membrane rejected significant amount of aromatic proteins; while humic acid-like substances did not show much difference. Therefore, EEM analysis suggested that rejection of aromatic proteins in SMP contributed to membrane fouling. 78

96 Figure 37 EEM spectra of the 3d-SRT MBR EPS in phase one Figure 38 EEM spectra of the 5d-SRT MBR EPS in phase one 79

97 Figure 39 EEM spectra of the 7d-SRT MBR EPS in phase one Figure 40 EEM spectra of the 10d-SRT MBR EPS in phase one Table 29 Summary of the peak data by EEM analysis in phase one (EPS SRT-3d SRT-5d SRT-7d SRT-10d Aromatic protein Microbial byproduct-like Humic Acid-like Figure 37 to 40 showed composites of the EPS for the four MBRs under the EEM analysis. Different from the effluent and SMP samples, it was noticed that 80