UBC Theses and Dissertations

UBC Theses Logo

UBC Theses and Dissertations

Comparison of nitrification activity in membrane and conventional enhanced biological phosphorus removal… Bahadoorsingh, Parmeshwaree 2010

Your browser doesn't seem to have a PDF viewer, please download the PDF to view this item.

Item Metadata

Download

Media
24-ubc_2010_fall_bahadoorsingh_parmeshwaree.pdf [ 4.62MB ]
Metadata
JSON: 24-1.0062797.json
JSON-LD: 24-1.0062797-ld.json
RDF/XML (Pretty): 24-1.0062797-rdf.xml
RDF/JSON: 24-1.0062797-rdf.json
Turtle: 24-1.0062797-turtle.txt
N-Triples: 24-1.0062797-rdf-ntriples.txt
Original Record: 24-1.0062797-source.json
Full Text
24-1.0062797-fulltext.txt
Citation
24-1.0062797.ris

Full Text

Comparison of Nitrification Activity in Membrane and Conventional Enhanced Biological Phosphorus Removal Processes  by  Parmeshwaree Bahadoorsingh  B.Sc. University of the West Indies, 1993 M.Phil. University of the West Indies, 1998  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  DOCTOR OF PHILOSOPHY in  The Faculty of Graduate Studies (Civil Engineering)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)  October 2010  © Parmeshwaree Bahadoorsingh, 2010  Abstract  Abstract While research is conclusive that the membrane bioreactor process performance in removing the carbonaceous and phosphorus constituents of wastewater is superior or equivalent to a conventional gravity separation process, there have been conflicting reports regarding its ability to achieve nitrification rates comparable to the conventional process. In this long-term study conducted at University of British Columbia‘s (UBC‘s) wastewater treatment pilot plant facility, the specific nitrification activity of a membrane enhanced biological phosphorus removal (EBPR) process was compared to that of a conventional EBPR process operating under identical conditions to identify factors that influence the relative nitrification rate of the processes. The specific nitrification rate measured from batch experiments showed a natural variation between the processes. There were periods where the specific nitrification rate of the membrane process was either consistently high or consistently low, relative to the conventional process. Average rates were nearly equal, however, the membrane process showed less variability in the individual rates. Nitrifier decay rates measured during the various performance periods conformed to the variation observed as rates for the membrane process were lower relative to the conventional process during periods where the specific nitrification rate for the membrane process was higher and vice versa. The presence of rotifers caused an increase in the decay rate of the conventional process. These organisms were absent in the membrane process. Vigorous coarse bubble aeration did not affect the decay rate. Terminal restriction fragment length polymorphisms (T-RFLP) analysis showed that ammonia-oxidizing (AOB) communities differed for the two processes, however the nitrite-oxidizing bacteria (NOB) communities as represented by the genus Nitrobacter and Nitrospira were similar for both processes. Temperature effects were significant for both AOB and NOB communities, but the effect was greater for the AOB community. Community shifts for the AOB were observed to occur during plant operation. Quantification of the nitrifiers by a real time polymerase chain reaction assay indicated similar quantities of AOB, Nitrobacter and Nitrospira in the two processes with  ii  Abstract  Nitrospira being the most abundant of the nitrifiers present in the systems. AOB and Nitrobacter quantities correlated with the relative nitrification rate of the processes.  iii  Table of Contents  Table of Contents ABSTRACT .................................................................................................................... ii TABLE OF CONTENTS ............................................................................................... iv LIST OF TABLES ...................................................................................................... viii LIST OF FIGURES....................................................................................................... x LIST OF ABBREVIATIONS ....................................................................................... xiv ACKNOWLEDGEMENTS ....................................................................................... xvii 1  INTRODUCTION...................................................................................................... 1  2  LITERATURE REVIEW ........................................................................................... 4 2.1  NITROGEN REMOVAL IN THE ACTIVATED SLUDGE PROCESS .................................... 4  2.1.1  Nitrification ................................................................................................. 4  2.1.2  Nitrifying organisms.................................................................................... 5  2.1.2.1  Aerobic autotrophic bacteria ................................................................................ 6  2.1.2.2  Heterotrophic nitrifiers .......................................................................................... 6  2.1.2.3  Anaerobic ammonia oxidizers ............................................................................. 7  2.1.3  Nitrification kinetics .................................................................................... 7  2.1.4  Factors affecting nitrification ....................................................................... 8  2.2  ENHANCED BIOLOGICAL PHOSPHORUS REMOVAL ................................................ 10  2.2.1  Process pathways .................................................................................... 11  2.2.2  Process configuration............................................................................... 12  2.3  MEMBRANE BIOREACTORS................................................................................. 13  2.3.1  MBR classification .................................................................................... 15  2.3.2  Nitrification in MBR................................................................................... 15  2.3.3  Membrane floc ......................................................................................... 17  2.3.4  Community composition ........................................................................... 19  2.3.5  Reaction kinetics ...................................................................................... 20  2.4  MEMBRANE ENHANCED BIOLOGICAL PHOSPHORUS REMOVAL ............................... 21  2.4.1  MEBPR research ..................................................................................... 22  2.4.2  Process performance: Comparison with EBPR ........................................ 25  iv  Table of Contents  2.5  ASSESSING MICROBIAL POPULATIONS ................................................................ 26  2.5.1  Culture-based techniques ........................................................................ 26  2.5.2  Molecular-based techniques .................................................................... 27  2.5.2.1  Community profiling ........................................................................................... 27  2.5.2.2  Bacterial quantification....................................................................................... 31  3  THE KNOWLEDGE GAP ....................................................................................... 33  4  PROJECT OBJECTIVE ......................................................................................... 35 4.1  5  RESEARCH QUESTIONS ..................................................................................... 35  MATERIALS AND METHODS ............................................................................... 37 5.1  TEST FACILITY .................................................................................................. 37  5.1.1 5.1.1.1  5.1.2  UBC pilot plant description ....................................................................... 37 Process flow ...................................................................................................... 38  Plant routine operations ........................................................................... 40  5.1.2.1  SRT control ........................................................................................................ 41  5.1.2.2  Sampling plan .................................................................................................... 43  5.1.2.3  Analytical methods ............................................................................................. 43  5.2  NITRIFICATION RATE MEASUREMENT .................................................................. 45  5.3  NITRIFIER DECAY RATE MEASUREMENT............................................................... 47  5.3.1  Comparison of bubble type ...................................................................... 47  5.3.2  Predator effects........................................................................................ 48  5.4  MOLECULAR METHODS ...................................................................................... 50  5.4.1  Sample collection ..................................................................................... 50  5.4.1.1  DNA extraction and quantification ..................................................................... 51  5.4.1.2  PCR primers ...................................................................................................... 51  5.4.2  Terminal restriction fragment length polymorphism fingerprinting ............. 52  5.4.2.1  PCR ................................................................................................................... 52  5.4.2.2  Restriction enzyme digestion ............................................................................. 53  5.4.2.3  T-RF length analysis .......................................................................................... 53  5.4.3  Quantitative PCR (qPCR)......................................................................... 55  5.4.3.1  qPCR assay ....................................................................................................... 55  5.4.3.2  Standard curve for real time PCR ...................................................................... 56  5.4.3.3  Cloning and sequencing .................................................................................... 59  v  Table of Contents  6  RESULTS AND DISCUSSION............................................................................... 60 6.1  PILOT PLANT PROCESS PERFORMANCE............................................................... 60  6.1.1  Reactor influent characteristics ................................................................ 60  6.1.2  Aerobic reactor characteristics ................................................................. 61  6.1.2.1  pH, temperature and dissolved oxygen ............................................................. 61  6.1.2.2  Floc structure and particle size .......................................................................... 64  6.1.2.3  Sludge microorganisms ..................................................................................... 68  6.1.3 6.1.3.1  Foam quantification ........................................................................................... 71  6.1.3.2  Suspended solids distribution ............................................................................ 73  6.1.3.3  Sludge yield ....................................................................................................... 79  6.1.3.4  Sludge volume index ......................................................................................... 81  6.1.4  Effluent characteristics ............................................................................. 83  6.1.4.1  Nitrogen removal performance and efficiency ................................................... 83  6.1.4.2  Phosphorus removal performance and efficiency ............................................. 87  6.1.4.3  COD removal ..................................................................................................... 89  6.1.5 6.2  Process suspended solids........................................................................ 70  Summary of pilot plant performance results ............................................. 91  SPECIFIC NITRIFICATION RATES .......................................................................... 92  6.2.1  Maximum specific nitrification rate ............................................................ 92  6.2.1.1  OUR results ....................................................................................................... 92  6.2.1.2  NOx production results ....................................................................................... 99  6.2.2  Sludge microorganisms and nitrification rates ........................................ 106  6.2.3  Process performance variability ............................................................. 107  6.2.4  Nitrification inhibition by toxic products ................................................... 111  6.2.5  Summary of specific nitrification rates results ......................................... 113  6.3  NITRIFIER DECAY AND GROWTH RATES ............................................................. 115  6.3.1  Effect of bubble type on nitrifier decay rate ............................................ 116  6.3.1.1  Nitrifier decay rates .......................................................................................... 117  6.3.1.2  Carbon dioxide stripping .................................................................................. 123  6.3.1.3  Assessment of decay rate measuring methods .............................................. 126  6.3.2  Effect of predators on decay rate ........................................................... 128  6.3.2.1  NaCl as a predator inhibitor ............................................................................. 128  6.3.2.2  Cycloheximide as a predator inhibitor ............................................................. 130  6.3.2.3  Specific nitrification rates ................................................................................. 131  vi  Table of Contents  6.3.2.4  6.3.3  Decay rates and relationship to process performance ............................ 138  6.3.4  Nitrifier growth rate (AUT) ....................................................................... 139  6.3.5  Summary of nitrifier decay rates results ................................................. 141  6.4  DYNAMICS OF NITRIFIER COMMUNITY STRUCTURE ............................................. 143  6.4.1  Method development.............................................................................. 143  6.4.2  T-RFLP analysis ................................................................................... 145  6.4.3  Nitrifier community structure................................................................... 151  6.4.4  Nitrifier dynamics and reactor conditions ................................................ 158  6.4.4.1  Effects of temperature on community structure ............................................... 162  6.4.4.2  Relationship of specific nitrification rate and community structure .................. 165  6.4.5 6.5  7  Decay rates ...................................................................................................... 136  Summary of community structure ........................................................... 167  QUANTITATIVE POPULATION DYNAMICS ............................................................. 169  6.5.1  Cloning and sequencing ......................................................................... 169  6.5.2  Specificity of PCR product...................................................................... 170  6.5.3  Standard curves ..................................................................................... 172  6.5.4  Ammonia- and nitrite-oxidizing bacteria distribution................................ 172  6.5.5  Reactor operation and nitrifier abundance.............................................. 178  6.5.6  Nitrifier abundance in relation to nitrification rate .................................... 181  6.5.7  Summary of nitrifier quantitative dynamics ............................................. 187  CONCLUSIONS AND RECOMMENDATIONS .................................................... 189 7.1  SUMMARY ...................................................................................................... 189  7.2  PROJECT CONCLUSIONS .................................................................................. 195  7.3  ENGINEERING SIGNIFICANCE ............................................................................ 196  7.4  RECOMMENDATIONS FOR FUTURE RESEARCH ................................................... 197  REFERENCES............................................................................................................ 199 APPENDIX I: UBC PILOT PLANT DRAWINGS ......................................................... 215 APPENDIX II: INSTRUMENTATION AND CONTROLS DIAGRAM ........................... 223 APPENDIX III: TEMPERATURE COEFFICIENT DETERMINATION .......................... 225 APPENDIX IV: PHOTOGRAPHS................................................................................ 227  vii  List of Tables  List of Tables Table 5-1  Methods for sample preservation and chemical analysis ........................ 44  Table 5-2  PCR Protocol.......................................................................................... 52  Table 5-3  Real Time qPCR Assay Details .............................................................. 56  Table 6-1  Reactor influent characteristics ............................................................... 61  Table 6-2  Change in mean particle size of conventional mixed liquor resulting from coarse bubble aeration ..................................................... 66  Table 6-3  Foam quantification in the membrane process reactors .......................... 72  Table 6-4  Operating SRTs for the individual processes in the membrane and conventional reactors....................................................................... 75  Table 6-5  Effluent quality from the membrane EBPR and conventional EBPR treatment processes .................................................................... 83  Table 6-6  Summary of % difference in specific nitrification rate between the membrane EBPR process and conventional EBPR process................................................................................................. 102  Table 6-7  Mean specific nitrification rates corrected for temperature at 20oC ..................................................................................................... 105  Table 6-8  Summary of plant operational and control parameters .......................... 109  Table 6-9  Wastewater composition....................................................................... 109  Table 6-10  Specific nitrification rates with exchanged solids and supernatant .......................................................................................... 112  Table 6-11  Decay rates measured under fine and coarse bubble aeration ............. 120  Table 6-12  Heterotrophic decay rates for membrane EBPR and conventional EBPR mixed liquor measured under coarse and fine bubble aeration .............................................................................. 121  Table 6-13  Reference values for autotrophic decay rates determined under aerobic conditions....................................................................... 123  Table 6-14  TIC removal rates derived for fine and coarse bubble aeration ............. 125  Table 6-15  Specific nitrification rate measurement method comparison ................. 127  Table 6-16  Summary of decay rates and prevailing conditions during the rate determination................................................................................. 139  Table 6-17  Sample set description by sample date, process temperature and relative specific nitrification rate ..................................................... 144  Table 6-18  Diversity measures for the nitrifier profiles ............................................ 152  Table 6-19  Summary statistics based on process groups ....................................... 155  viii  List of Tables  Table 6-20  Summary statistics for overall effects of specific nitrification rates for AOB and Nitrobacter .............................................................. 167  Table 6-21  Analysis of standard curves for individual real time assays ................... 172  Table 6-22  Correlation coefficients determined between reactor operational parameters and nitrifier abundance .................................... 179  Table A-1  Temperature coefficient for membrane and conventional process mixed liquor............................................................................. 224  ix  List of Figures  List of Figures Figure 2-1  Schematic of P and N removal process configurations ........................... 13  Figure 2-2  MBR biological nutrient removal unit ...................................................... 23  Figure 2-3  Configuration for bio-P and nitrogen removal.......................................... 24  Figure 2-4  Five stage membrane bioreactor for N and P removal ............................ 24  Figure 2-5  Configuration for nutrient removal with MBR process ............................. 25  Figure 2-6  DGGE gel of amplicons comparing amoA and 16S primers for different environmental samples ............................................................. 29  Figure 2-7  Illustration of the steps of the T-RFLP method ........................................ 30  Figure 5-1  UBC pilot plant process flow schematic .................................................. 39  Figure 5-2  Schematic of respirometers, controls and data acquisition system .................................................................................................... 45  Figure 5-3  Schematic of reactors arrangement for decay rate measurement ......................................................................................... 48  Figure 5-4  Real time PCR data for 16S rRNA Nitrospira plasmid DNA used for generating standard curve (Run 090826) .................................. 58  Figure 6-1  Time series plots of pH, temperature and DO in the aerobic zones...................................................................................................... 62  Figure 6-2  Correlation of the pH and DO for the membrane EBPR and conventional EBPR processes................................................................ 63  Figure 6-3  Comparison of particle size distribution for the membrane (M) process and conventional (C) process floc at the start (samples 07-10-26) and end (samples 08-12-08) of the investigation ........................................................................................... 64  Figure 6-4  Mean floc size in membrane and conventional processes ...................... 67  Figure 6-5  Structure of membrane process and conventional process floc (Day 326) ............................................................................................... 68  Figure 6-6  Sludge microorganisms observed in the membrane EBPR and conventional EBPR aerobic mixed liquors .............................................. 69  Figure 6-7  Changes in system biomass and anoxic reactor TSS concentration at hourly intervals after foam re-suspension ..................... 73  Figure 6-8  Distribution of total suspended solids in the membrane (M) and conventional (C) processes ............................................................. 74  Figure 6-9  Comparison of total suspended solids mass in membrane and conventional processes .......................................................................... 76  Figure 6-10  Oligochaetes observed in conventional mixed liquor (Day 165) .............. 78  x  List of Figures  Figure 6-11  Sludge yield determination from plant operational data (day 0 to 160) ................................................................................................. 80  Figure 6-12  Sludge volume index measured during the pilot plant operation ................................................................................................ 82  Figure 6-13  Nitrogen concentration in membrane EBPR and conventional EBPR process effluent ........................................................................... 84  Figure 6-14  Time series concentrations of ammonium, nitrite + nitrate and TKN in membrane (M) EBPR and conventional (C) EBPR effluent ................................................................................................... 86  Figure 6-15  Comparison of phosphorus concentrations in membrane EBPR and conventional EBPR process effluents ................................... 87  Figure 6-16  Time series plot of PO4-P concentrations in influent and membrane process (M) and conventional process (C) effluents.................................................................................................. 88  Figure 6-17  Comparison of soluble COD concentrations in membrane EBPR and conventional EBPR process effluents ................................... 90  Figure 6-18  Concentrations of influent total COD and effluent soluble COD concentration in the membrane and conventional processes.................. 90  Figure 6-19  Respirometry data for a typical batch test (day 23) ................................. 93  Figure 6-20  Effect of length of pre-aeration period on response time to maximum rate (day 55) ........................................................................... 95  Figure 6-21  Effect of NaNO2 addition on response time to maximum rate (day 38) .................................................................................................. 95  Figure 6-22  (a) Measured SOUR of the AOB for the membrane EBPR and conventional EBPR processes, and (b) differences in measured SOURs .................................................................................. 97  Figure 6-23  (a) Measured SOUR of the NOB for the membrane EBPR and conventional EBPR processes, and (b) differences in measured SOURs .................................................................................. 97  Figure 6-24  (a) Measured SOUR of the nitrifying bacteria (AOB and NOB) for the membrane EBPR and conventional EBPR processes, and (b) differences in measured SOURs ................................................ 98  Figure 6-25  Changing concentration of NH4-N and NOx-N with time during a batch test (Day 83) ............................................................................ 100  Figure 6-26  Comparison of specific nitrification rates for the membrane EBPR and conventional EBPR processes (rates at prevailing plant temp) ........................................................................................... 101  Figure 6-27  Comparison of specific nitrification rates for the membrane EBPR and conventional EBPR processes (rates at 20oC). ................... 104  xi  List of Figures  Figure 6-28  Comparison of mean specific nitrification rate for membrane and conventional processes at 20oC from present and previous (Monti, 2006) studies .............................................................. 108  Figure 6-29  Decreasing nitrification rate over the 10-day test period as measured by measurement of the NOx-N production rate for two replicate tests (a) test 2 and (b) test 3 ............................................ 118  Figure 6-30  Semi-log plot for decay rate calculation at measured temperature (Test 02) ........................................................................... 119  Figure 6-31  Total inorganic carbon (TIC) concentration in reactors over the 10-day test period ................................................................................. 124  Figure 6-32  Inorganic carbon sources and sinks for the wastewater system............ 125  Figure 6-33  Specific nitrification rate of control and NaCl treated mixed liquor .................................................................................................... 130  Figure 6-34  Specific nitrification rates for the control and mixed liquor treated with cycloheximide (Test 1) ...................................................... 132  Figure 6-35  NH4-N and NOx-N concentration in the unfed reactors during Test 1 ................................................................................................... 134  Figure 6-36  Specific nitrification rates for the control and mixed liquor treated with cycloheximide (Test 2) ...................................................... 135  Figure 6-37  Semi-log plots for decay rate determination for treated and control samples .................................................................................... 136  Figure 6-38  Averaged electropherograms for amoA genes for the membrane process and conventional process sample set .................... 146  Figure 6-39  Averaged electropherograms for 16S rRNA Nitrobacter genes for the membrane process and conventional process sample set ........................................................................................................ 147  Figure 6-40  Averaged electropherograms for 16S rRNA Nitrospira genes for the membrane process and conventional process sample set ........................................................................................................ 148  Figure 6-41  Frequency of occurrence of (a) amoA and (b) Nirobacter TRFs detected in the sample set ............................................................ 150  Figure 6-42  NMS ordination plot based on process grouping for (a) amoA and (b) Nitrobacter................................................................................ 153  Figure 6-43  T-RF identified by indicator analysis that were present in different relative abundance in the membrane and conventional processes ........................................................................ 157  Figure 6-44  Joint plot evaluating effect of reactor operational parameters on community change .......................................................................... 160  Figure 6-45  Ordination plots based on the defined temperature groups for the amoA and Nitrobacter ..................................................................... 163  xii  List of Figures  Figure 6-46  Ordination plots based on nitrification rate for the (a) amoA and (b) Nitrobacter................................................................................ 166  Figure 6-47  PCR product from amoA, 16S rRNA Nitrobacter and 16S rRNA Nitrospira assays ........................................................................ 170  Figure 6-48  Dissociation curves............................................................................... 171  Figure 6-49  Amplification Plots ................................................................................ 173  Figure 6-50  Abundance of ammonia and nitrite oxidizers in the membrane process and conventional process........................................................ 175  Figure 6-51  Relation of specific nitrification rate with C/N ratio and temperature .......................................................................................... 181  Figure 6-52  Comparison of specific nitrification rates between membrane and conventional processes ................................................................. 182  Figure 6-53  Comparison of nitrifier abundance in the membrane and conventional systems ........................................................................... 183  Figure 6-54  Correlation between abundance of nitrifiers and specific nitrification rate ..................................................................................... 185  Figure 6-55  Relation between influent NH4-N and specific nitrification rate .............. 186  Figure 6-56  Wasting rate for membrane and conventional processes...................... 187  Figure A-1  Schematic of reactor instrumentation and controls ............................... 222  Figure A-2  Plot for nitrification temperature coefficient determination ..................... 223  xiii  List of Abbreviations  List of Abbreviations Amo  Ammonia monooxygenase  ANOVA  Analysis of variance  AOA  Ammonia-oxidizing archea  AOB  Ammonia-oxidizing bacteria  AS  Activated sludge  b  Decay rate  BLAST  Basic logic alignment search tool  BNR  Biological nutrient removal  BOD  Biochemical oxygen demand  bp  Base pairs  CaCO3  Calcium carbonate  CAS  Conventional activated sludge  CEBPR  Conventional enhanced biological phosphorus removal  CSLM  Confocal scanning laser microscope  CO2  Carbon dioxide  COD  Chemical oxygen demand  d  Day  DGGE  Denaturing gradient gel electrophoresis  DO  Dissolved oxygen  DNA  Deoxyribonucleic acid  dsDNA  Double stranded deoxyribonucleic acid  EBPR  Enhanced biological phosphorus removal  EPS  Extracellular polymeric substances  F/M  Food to mass  g  Gram  h  Hour  HAO  Hydroxylamine oxidoreductase  HRT  Hydraulic retention time  kg  Kilogram  L  Liter  xiv  List of Abbreviations  m  Meter  MBR  Membrane bioreactor  MEBPR  Membrane enhanced biological phosphorus removal  MCRT  Mean cell residence time  mg  Milligram  mL  Milliliter  MLSS  Mixed liquor suspended solids  mm  Millimeter  MRPP  Multi-response permutation procedures  N  Nitrogen  NADH  Nicotinamide adenine dinucleotide  NAPS  Nucleic Acid Protein Service  NaNO2  Sodium nitrite  NaHCO3  Sodium bicarbonate  NaOH  Sodium hydroxide  NCBI  National Center for Biotechnology Information  NH4Cl  Ammonium chloride  NH4-N  Ammonium nitrogen  NMS  Nonmetric multidimensional scaling  NO2-N  Nitrite nitrogen  NO3-N  Nitrate nitrogen  NOB  Nitrite-oxidizing bacteria  ORP  Oxidation-reduction potential  OTU  Operational taxonomic unit  OUR  Oxygen uptake rate  P  Phosphorus  PAOs  Phosphate accumulating organisms  PCR  Polymerase chain reaction  PHA  Polyhydroxyalkanoates  PO4-P  Phosphate  poly-P  Polyphosphate  qPCR  Quantitative polymerase chain reaction  xv  List of Abbreviations  RAS  Return activated sludge  rcf  Relative centrifugal force  RDP  Ribosomal database project  RISA  Ribosomal intergenic spacer analysis  SBR  Sequencing batch reactors  SMP  Soluble microbial product  SND  Simultaneous nitrification-denitrification  SOUR  Specific oxygen uptake rate  SRT  Solids retention time  SSU  Small subunit  SVI  Sludge volume index  TIC  Total inorganic carbon  TCA  Tricarboxylic acid  TKN  Total Kjeldahl nitrogen  TMP  Trans-membrane pressure  TP  Total phosphorus  T-RF  Terminal restriction fragment  T-RFLP  Terminal restriction fragment length polymorphism  TSS  Total suspended solids  L  Microliter    Growth rate  UBC  University of British Columbia  UCT  University of Cape Town  VFA  Volatile fatty acid  VSS  Volatile suspended solids  WWTP  Wastewater treatment plant  xvi  Acknowledgements  Acknowledgements I would like to express my gratitude to my supervisor Dr. Eric Hall and cosupervisor Dr. William Mohn for their guidance and support throughout this project. I am very appreciative of their thoughtful advice and encouragement during the several very decisive times. I would also like to thank my committee members Dr. Don Mavinic and Dr. Allan Gibb for all their comments provided in the preparation of this dissertation. Special thanks to Fred Koch for his assistance at the pilot plant, sharing his enthusiasm for research and above all for his encouragement during my many difficult experiences. Thanks to Susan Harper and Paula Parkinson for their technical assistance in the Environmental Engineering Laboratory and for providing a safe and enjoyable work environment. I thank Scott Jackson and Bill Leung of the Civil Engineering workshop for their help with my experimental setup and Doug Hudniuk for his willingness to assist with works at the pilot plant. My colleagues in the Environmental Engineering programme, Soubhagya, Alireza, Zaki, Margaret, Parvez, Wayne, Hemanth and Thomas, I am thankful for the company you all provided, the discussions we had and for listening to my numerous complaints. I am indebted to the members of Mohn‘s Microbiology Lab especially Dr. Martin Hartmann, Dr. Vijayakumar Somalinga and Claire Stilwell. I thank you for all the assistance and for making the time in the lab a memorable experience. I would like also to acknowledge the Government of the Republic of Trinidad and Tobago and the Organization of American States for the financial support provided for this doctoral program. To my Mother (Satcour), sisters (Reetu and Vitra), niece (Jasminder), relatives and friends, I am grateful for all the support provided during my absence from home. Finally to my Daddy (Kenny Bahadoorsingh) who passed away before the end of my programme, thank you for leading me to another accomplishment.  xvii  1: Introduction  1  Introduction The discharge of wastewater containing nitrogen and phosphorus is of concern  because of the potential for these nutrients to adversely affect ecological systems. Removal of these nutrients is therefore necessary and can be achieved through biological or physical-chemical treatment processes. Biological methods, however, tend to be the preferred means, principally because they result in lower waste sludge production and are perceived as being somewhat of a more environmentally acceptable means by the public (Oldham and Rabinowitz, 2001). In Canada, wastewater treatment plant (WWTP) effluent is required to meet discharge limits according to legislation pertaining to municipal wastewater effluents for the various provinces. In British Columbia, The Municipal Sewage Regulation (B.C. Reg. 129/99) of the Environmental Management Act provides limits for effluent quality for discharge to the environment and according to the regulations, total phosphorus (TP) and total nitrogen (TN) limits as low as 0.25 mg/L and <6 mg/L respectively, are required for some receiving waters. Many existing WWTPs are either approaching or have reached their design capacities because of the continual population growth which Canada is experiencing and hence meeting stringent discharge standards is a potential issue for concern. Based on population numbers provided by Statistics Canada (2009), there was a 5.3% increase in British Columbia‘s population over the period 2004 to 2008. As a consequence of the continued population growth expected, together with the stringent regulatory demands regarding the discharge of nitrogen- and phosphoruscontaining wastewater into receiving water bodies, many of the existing treatment plants may require upgrading in order to satisfy the effluent limitations. Within the recent past, membrane bioreactor (MBR) technology has gained attention as an innovative means towards expanding treatment capacity of existing wastewater treatment plants, mainly because of the footprint requirements and the ability to operate MBRs at high hydraulic loadings. An MBR is essentially a modification of an activated sludge system in which the secondary clarifier is replaced by a filtration membrane for solids-liquid separation. In the MBR process, treatment of the waste is effected by biological processes as well as through physical separation. This technology has been successfully applied in full-scale for conventional activated sludge system 1  1: Introduction  rehabilitation to achieve high effluent quality. To achieve phosphorus removal, however, the current practice with MBRs involves the addition of chemical coagulants (Tchobanoglous et al., 2003). The addition of coagulants in the MBR process increases the sludge production and this negates the advantage associated with operation at high solids retention time (SRT) and mixed liquor suspended solids (MLSS) which tends to reduce sludge production. The enhanced biological phosphorus removal process (EBPR) allows removal of both phosphorus and nitrogen by biological processes. The principal mechanism of phosphorus removal is by ‗luxury uptake‘ where biological phosphate is stored in the biomass as polyphosphate (poly-P) and subsequently removed by sludge wasting. Attempts have been made at coupling EBPR with membrane processes and the effluent quality achieved from bench and pilot scale tests indicated stable nitrification and efficient phosphorus removal even though the systems were operated with reduced sludge withdrawal (Adam et al., 2002). For upgrade of biological nutrient removal (BNR) treatment plants, the membrane enhanced biological phosphorus removal therefore presents an attractive alternative where the plants are operating at, or near, their rated treatment capacities. This concept has recently been applied to retrofit a full-scale municipal wastewater treatment facility in Running Spring California, where a conventional activated sludge plant was upgraded to achieve biological nutrient removal and also to expand its hydraulic capacity within the existing footprint following a change in the plant‘s discharge permit (Judd, 2006). It was, however, implemented in combination with a proprietary simultaneous nitrification-denitrification (SND) system. Nitrification is the process used in wastewater treatment to reduce the ammonia content of wastewater. The conversion of ammonia to nitrate is a two-step process brought about by two highly specialized groups of aerobic autotrophic bacteria. In the first step, ammonia is oxidized to nitrite by a wide variety of beta proteobacterial ammonia-oxidizers and in the second step nitrite is oxidized to nitrate by nitrite-oxidizers. Though nitrification is stable in MBR processes, MBR nitrogen removal capability is questionable, as research has presented conflicting views in respect of its ability to achieve nitrification rates on par with its conventional counterpart. The membrane system possesses characteristics which could either enhance or negatively affect the nitrification process. In producing a suspended solids free effluent, it retains the  2  1: Introduction  suspended solids in the system and there is no washout of the slow-growing nitrifiers. The small floc size feature tends to enhance mass transfer conditions, though at the same time can expose the nitrifiers to predator grazing. MBR systems may also operate with higher MLSS which can impede the oxygen transfer. If the characteristics that negatively affect the process outweigh those that enhance the process, the consequence is a nitrification-specific loss in the membrane process and this could limit its application in a conventional plant upgrade. There have been reports of a reduced specific nitrification rate in the membrane EBPR process (Monti, 2006; Parco et al., 2006). Reduction in performance of the nitrification process is of significance in a biological system as recovery of the process is relatively long because the process is catalyzed by the slow-growing autotrophs. The reduction in performance of the nitrification process therefore needs to be addressed and fully understood in order to optimise the efficiency of the membrane EBPR process and to provide complete confidence in the membrane EBPR process.  3  2: Literature Review  2  Literature Review  2.1  Nitrogen removal in the activated sludge process The activated sludge process essentially involves aeration in the presence of a  microbial suspension, solids-liquid separation following aeration, wasting of excess biomass and the return of the remaining biomass to the aeration tank (Benefield and Randall, 1985). The success of the process in treating wastewater depends largely on the solids-liquid separation of the activated sludge floc from the treated wastewater before effluent discharge. Nitrogen removal is achieved by the nitrification-denitrification process. In the nitrification-denitrification process, ammonium ions produced in wastewater from the hydrolysis of urea and degradation of organic-nitrogen compounds are removed by conversion to nitrogen gas via either the nitrite pathway or the nitrate pathway. Biological systems for nitrogen removal all incorporate an aerobic zone for nitrification and an anoxic zone for denitrification. Pre-anoxic, post-anoxic and simultaneous nitrification /denitrification are the major process configurations provided for nitrogen removal.  2.1.1  Nitrification There are two biochemical reactions that occur in the nitrification process i.e. the  oxidation of ammonia to nitrite (nitritation) and the oxidation of nitrite ions to nitrates (nitratation). In the first reaction, ammonia is oxidized to nitrite with the formation of the hydroxylamine intermediate. The enzymes ammonia monooxygenase (AMO) and hydroxylamine oxidoreductase (HAO) catalyze the ammonia oxidation and nitrite production reactions respectively with molecular oxygen as the electron acceptor. The reactions are summarized in the following equations. NH3 + O2+ 2 H+ + 2e-  AMO  NH2OH + H2O  HAO  0.5 O2 + 2 H+ + 2e-  NH2OH + H2O +  Equation (2-1) -  HNO2 + 5 H + 4e  Equation (2-2)  H2O  Equation (2-3)  4  2: Literature Review  A combination of these reactions gives the overall nitritation reaction as presented in equation 2-4. NH3+ 1.5 O2  HNO2 + H+ + H2O  Equation (2-4)  The nitrite produced during the nitritation reaction is further oxidized to nitrate according to the following reactions. HNO2 + H2O  HNO3 + 2 H+ + 2e-  Equation (2-5)  0.5 O2 + 2 H+ + 2e-  H2O  Equation (2-6)  The nitrite oxidation is catalysed by the nitrite oxidoreductase enzyme with molecular O2 as the electron acceptor. The nitrate produced from the oxidation of ammonia and nitrite during the nitrification process is reduced to nitrogen gas during the denitrification process. In the denitrification process the electron donor is provided either by the influent wastewater or an external carbon source.  2.1.2  Nitrifying organisms The two steps of the nitrification process are catalyzed by chemolithotrophic  ammonia-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB). While there are some heterotrophic bacteria and anaerobic ammonia-oxidizing (anammox) bacteria that oxidize ammonia, AOB are thought to be largely responsible for the oxidation of ammonia. Recent evidence, however, has indicated that ammonia-oxidizing archaea (AOA) is another microbial group that is involved in ammonia oxidation (Konneke et al., 2005). These microorganisms were found to contain all three subunits (amoA, amoB, and amoC) of ammonia monooxygenase, the enzyme which catalyzes the oxidation of ammonia. They have been identified only in activated sludge systems operating at low dissolved oxygen (DO) concentration for simultaneous nitrification and denitrification (Park et al., 2006) and therefore they may not be major contributors to ammonia oxidation in activated sludge systems that are highly aerated (Wells et al., 2009).  5  2: Literature Review  2.1.2.1  Aerobic autotrophic bacteria The nitrifying bacteria belong to the Nitrobacteracae family. There are several  genera of nitrifying bacteria. The ammonia-oxidizing genera include Nitrosococcus, Nitrosocystis, Nitrosolobus, Nitrosomonas and Nitrosospira and the nitrite-oxidizing genera include Nitrobacter, Nitrococcus and Nitrospira. Nitrosomonas and Nitrobacter have previously been recognized as the nitrifiers largely responsible for nitrification in the activated sludge process. However, the dominance of Nitrospira-like microorganisms and the absence of Nitrobacter in wastewater systems have indicated that uncultured Nitrospira-like microorganisms are the dominating nitrite oxidizers (Juretschko et al., 1998; Schramm et al., 1999). Studies have shown that Nitrospira and Nitrobacter can both co-exist in activated sludge treatment systems (Coskuner and Curtis, 2002; Kelly et al., 2005; Simm et al., 2005). Nitrospira are known to be k-strategists with high substrate affinities and low maximum activity or growth rate whereas, Nitrobacter are r-strategists that can grow faster than N. europaea and Nitrospira (Schramm et al., 1999). K- and r-strategies are derived from the k/r selection theory that categorizes the selection pressures which determine a population‘s evolution broadly into growth rates and carrying capacity of the environment. In the activated sludge process, the aerobic nitrifying bacteria are found embedded within the floc of heterotrophs and the AOB and NOB are in close contact within the floc (Mobarry et al., 1996; Wagner et al., 1996).  2.1.2.2  Heterotrophic nitrifiers Heterotrophic nitrifiers include algae, fungi, and bacteria. The substrate and  products of heterotrophic nitrifiers are similar to those of autotrophic nitrifiers; however, nitrification rates of heterotrophic nitrifiers are lower compared to those of autotrophic nitrifiers and heterotrophic nitrification is thought to occur preferentially under conditions that are unfavorable for autotrophic nitrification, such as acidic environments (Schmidt et al., 2003).  6  2: Literature Review  2.1.2.3  Anaerobic ammonia oxidizers Anaerobic ammonia oxidizers oxidize ammonium to dinitrogen gas (N2) using  nitrite as the electron acceptor (Jetten et al., 1998; Schmidt et al., 2003) in the Anammox reaction. Anaerobic ammonia oxidizers belong to a group of planctomycete bacteria. The two bacteria which have been associated with the Anammox reaction are ‗Candidatus Brocadia anammoxidans‘ and ‗Candidatus Kuenenia stuttgartiensis‘ (Schmidt et al., 2003).  2.1.3  Nitrification kinetics Nitrifier growth rate is a critical factor in the design of wastewater plants because  of the relatively low autotrophic growth rate compared to the heterotrophic growth rate. The estimation of maximum specific growth rate (AUT) as described by Melcer and Dold (2004) in the Water Environment Research Foundation (2004) Report is given in the following Equation (2-7).  dS NO X   AUT  AUT dt YAUT Equation (2-7)  where dSNO/dt  = measured nitrification rate (mg N / L·d)  AUT  = maximum specific nitrifier growth rate (d-1)  XAUT  = initial concentration of autotrophs (mg COD /L)  YAUT  = autotrophs growth yield coefficient (mg COD / mg N)  The quotient (XAUT / YAUT) of the equation is given by the Equation 2-8.  X AUT (TKNinf  TKN eff  TKN sludge)    YAUT (1  bAUT   )  V Equation 2-8  where XAUT  = initial concentration of autotrophs (mg COD /L)  YAUT  = autotrophs growth yield coefficient (mg COD / mg N)  7  2: Literature Review  TKNinf  = influent TKN load (mg N /d)  TKNeff  = effluent TKN load (mg N /d)  TKNsludge = waste sludge TKN load (mg N /d)   = sludge retention time (d)  bAUT  = autotroph decay rate (d-1)  V  = system volume (L)  The assessment of nitrification behaviour has focused on measuring maximum specific growth rate because the significance of decay rate has traditionally been underestimated (Dold et al., 2005). Nitrifier decay rates are higher under aerobic conditions as compared to anoxic conditions and this has been attributed to predation on autotrophic bacteria under aerobic conditions (van Loosdrecht and Henze, 1999; Martinage and Paul, 2000). Lee and Oleszkiewicz (2003) observed that alternating oxidation-reduction potential (ORP) conditions lead to lower decay rates as compared to decay rates measured for aerobic and anoxic conditions and suggested that the adaptation during routine exposure to anoxic conditions may cause the bacteria to better cope with the stressful conditions. The difference in decay rates is of significance since it is recognized that autotrophs will decay under each ORP condition as they cycle through a nutrient removal plant.  2.1.4  Factors affecting nitrification Nitrification will not take place unless there are sufficient quantities of AOB and  NOB and concentrations will be sufficient only when environmental conditions allow the bacteria to proliferate (USEPA, 1993). The important process parameters recognized in bacterial nitrification kinetics are pH, dissolved oxygen (DO) and temperature. Nitrification rates are inhibited at low DO and a DO in excess of 2.0 mg/L is generally recommended for complete nitrification (Water Environment Federation, 2005). Nitrifiers are pH sensitive and an optimum pH range of 7.5 - 8 is required for the process. Substrate concentration, carbon to nitrogen ratio (C/N), sludge retention time (SRT), and alkalinity, have also been found to have considerable impacts on the nitrification process.  8  2: Literature Review  Of the many factors that affect nitrifiers, DO concentration has been cited as one of the most important. Reported values of the limiting DO for the process are variable and range from 0.5 - 4 mg/L (Stenstrom and Song, 1991). DO concentration and mass transport effects, mean cell residence times (MCRTs) and heterotrophic/autotrophic competition for DO can combine to give the apparent nitrification-limiting DO concentration. The kinetics of nitrification are also limited by carbon. In municipal wastewater treatment, the aerobic degradation of organic matter by heterotrophic biomass produces sufficient CO2 to be used as a carbon source by the autotrophs and it has been shown that nitrifying bacteria live in clusters with heterotrophic bacteria, thereby profiting from the short distance to the CO2 substrate generated by the heterotrophic bacteria (Schramm et al., 1999). Carbon dioxide is used by autotrophic bacteria in the form of bicarbonate alkalinity when the carbon dioxide dissolves in water. Hence, the nitrification process can be increased by addition of bicarbonate as liquid (e.g. NaCO3) or powdered buffers such as CaCO3 (Denecke and Liebig, 2003). Alternatively, the rate can be increased by CO2-enriched air sparging. Low CO2 concentrations affect growth rate and may reduce nitrification, although there is a tendency for inhibition of growth at concentrations greater than 5 mg/L (Denecke and Liebig, 2003). Nitrification can be affected by the presence of protozoa and studies have indicated both positive as well as negative effects. Protozoa exist within the microbial community and graze on free floating bacteria and suspended particles and tend to promote good floc formation and settling. Increases in nitrification rates can be caused by protozoa grazing on heterotrophic bacteria that normally compete with the nitrifying bacteria for ammonia (Petropoulos and Gilbride, 2005). The assimilation of ammonia by heterotrophic bacteria tends to occur in preference to nitrification under conditions of high ammonia and high heterotrophic population densities. The control of the heterotrophic bacteria by protozoan grazing therefore results in more ammonia being available for nitrifying bacteria and a more efficient nitrification process. Nitrifying bacteria in activated sludge are found within the floc particles and are less exposed to grazing by the protozoa under normal conditions. The activated sludge floc size can therefore influence the nitrification rate. There is an apparent increase in nitrification rate with smaller floc particles and nitrate production rates are lower in the 9  2: Literature Review  absence of protozoan grazing (Petropoulos and Gilbride, 2005). The location of the bacteria within the floc and the tendency of autotrophs to form large agglomerates of bacteria that make them more resistant to grazing by protozoa have also been used to explain the finding that there was not any effect of protozoa on nitrification rate (Lee and Oleszkiewicz, 2003). Heterotrophic activity could inhibit the nitrification process. The nitrifiers in activated sludge are found to be located mostly within the inner part of floc because they grow slowly and they tend to be overgrown by heterotrophic bacteria. Ammonia and oxygen concentrations decrease towards the center of the floc and in addition, the outer heterotrophic layer reduces the oxygen available for nitrification (Manser et al., 2005c). High concentrations of soluble microbial products have also been found to inhibit nitrifying bacteria from pure cultures (Chudoba, 1985) but the inhibitory effect is transient and not always observed (Ichihashi et al., 2006). Production of these products by activated sludge microorganisms is common and the concentration is proportional to the amount of substrate degraded (Chudoba, 1985). The inhibitory effects on nitrification were noted with accumulation of high molecular weight (MW) compounds with MW > 700 (Chudoba, 1985). The inhibitory microbial products were found to reside not in the supernatant but rather in the activated sludge flocs (Ichihashi et al., 2006).  2.2  Enhanced biological phosphorus removal Traditionally, phosphorus removal is achieved through chemical addition.  Chemical treatment involves adding either calcium or other metal salts to form insoluble phosphates which are then removed by sedimentation. The most commonly used precipitants are calcium in the form of lime, aluminum sulphate (alum), sodium aluminate, ferric chloride, ferrous chloride and ferrous sulphate (Bowker and Stensel, 1990). The use of chemicals increase the operational cost of wastewater treatment because of the costs associated with supply of chemicals and management of the large quantities of sludge generated principally by the production of precipitates. Another drawback to the use of chemicals is that the counter ions of the salts remain in the treated water, causing an increase in salinity. The success with the biological  10  2: Literature Review  phosphorus removal (BPR) process in achieving low effluent phosphorus concentration has reduced the practice of chemical addition for phosphorus removal, although there are BPR facilities designed to incorporate both chemical and biological processes (Tchobanoglous et al., 2003).  2.2.1  Process pathways In the enhanced biological phosphorus removal (EBPR) process, phosphorus  removal is achieved primarily by circulating activated sludge through anaerobic and aerobic phases together with the introduction of influent wastewater into the anaerobic phase (Barnard, 1975). The principal mechanism of phosphorus removal is by ‗luxury uptake‘ as defined by Levin and Shapiro (1965) where biological phosphate is stored in the biomass as polyphosphate (poly-P) and subsequently removed by sludge wasting. Through alternating anaerobic and aerobic environments, conditions for the growth of the phosphorus-accumulating organisms (PAOs) are achieved. In the anaerobic phase where the activated sludge is mixed with the influent wastewater, microorganisms that are able to take up carbon sources from the influent anaerobically are favoured. The PAOs are capable of hydrolysing stored poly-P for supplying energy for the anaerobic uptake of the carbon sources and hence they can thrive under such conditions. In the anaerobic phase, therefore, they take up carbon sources mainly in the form of short chain fatty acids and store them as reserves in the form of polyhydroxyalkanoates (PHA) and with the hydrolysis of poly-P, there is release of orthophosphate. In the aerobic phase that follows, the PAOs utilize the stored PHA as the carbon and energy source while taking up the orthophosphate which is intracellularly accumulated as poly-P. Acetate is the favored substrate for EBPR as PAOs are known to thrive on short chain fatty acids. For the conversion of acetate to PHA, reducing power is required since PHA is a more reduced compound than acetate. There are principally two pathways for generation of this reducing power which can be explained by the Comeau-Wentzel and the Mino models (Wentzel et al., 1991). The basis of the Comeau-Wentzel model was that the tricarboxylic acid (TCA) cycle functions under anaerobic conditions to oxidize a part of the acetate to CO 2 and to generate reducing power in the form of nicotinamide adenine dinucleotide (NADH). The  11  2: Literature Review  Mino model proposed that the anaerobic degradation of intracellularly stored glycogen to acetyl-CoA together with its partial oxidation to CO2 generates reducing power for PHA syntheses (Mino et al., 1998). Mino et al. (1998) reviewed the works of several others and concluded that while experimental evidence favours the Mino model there is also the possibility that partial functioning of the TCA cycle provides reducing power for PHA formation. Pereira et al. (1996) found from a redox balance that glycogen as a sole source was insufficient for providing the reducing power. They proposed a model combining both pathways and concluded that 70% of reducing power is provided by glycogen degradation and the remaining 30% through the TCA cycle for PHA formation under anaerobic conditions.  2.2.2  Process configuration Process configurations for BPR facilities all include an anaerobic zone followed  by an aerobic zone to promote favorable conditions for the growth of the PAOs. An anoxic zone is provided for denitrification when there is requirement for nitrogen removal. An alternative to separate zones/tanks is through control of phase length in which aerobic and anaerobic conditions are achieved by controlling the phases of the operational cycle and allowing the anoxic phase to extend into an anaerobic phase (Rosen et al., 2006). The configurations that are commonly used to achieve both phosphorus and nitrogen removal are the A2O, and University of Cape Town (UCT) processes (Tchobanoglous et al., 2003). Schematic representations of these process configurations are given in Figure 2-1. The UCT process considers the adverse effect of nitrate on phosphate release in the anaerobic phase and returns the nitrate-containing return activated sludge (RAS) to the anoxic zone. The nitrate-free mixed liquor from the anoxic zone is recycled to the anaerobic zone.  12  2: Literature Review  Anaerobic  Anoxic  Aerobic Effluent  Aerobic (nitrate) Recycle Sludge Recycle  A2O Process  (a) Anoxic Recycle  Anaerobic  Anoxic  Aerobic  Influent  Effluent Aerobic (nitrate) Recycle Sludge Recycle  (b) Figure 2-1  2.3  UCT Process  Schematic of P and N removal process configurations  Membrane bioreactors Membrane bioreactor (MBR) processes combine biological treatment with  membrane filtration. MBRs replace sedimentation and tertiary filtration in conventional wastewater treatment systems. In the carbon removal or nitrification MBR process, treatment of the waste is effected by biological oxidation processes as well as through physical separation. The influent is fed into an aerated bioreactor where the organic components are oxidised by the microbial population within the activated sludge. The bioreactor is usually aerated with coarse bubble aeration for providing oxygen for the oxidation process and for a means of membrane fouling control. The biomass is then filtered through the membrane filtration unit and there is separation of the liquid and the filterable solids. The MBR has been applied to the treatment of a wide variety of wastewaters including those of domestic and industrial origin and has potential in agricultural wastewater treatment (Cicek, 2003). Its ability to handle the many different waste types 13  2: Literature Review  and yet maintain a high quality effluent has demonstrated the flexibility and robustness of the process. Also, the modular nature of most commercial-ready membranes makes them readily applicable for retrofitting of existing wastewater treatment plants while minimizing plant footprint. One of the main advantages of the MBR process is that MBRs can produce a suspended solids-free effluent with little concern about biomass settleability. This is principally because the membranes are able to completely retain biomass. They can also be operated at elevated concentrations of biosolids to maintain high volumetric rates of biological activity. Operating at high mixed liquor suspended solids (MLSS) can, however, impede oxygen transfer and increase sludge viscosity (van Dijk and Roncken, 1997) resulting in higher energy requirements for aeration and pumping. Full scale plants are now being operated at moderate MLSS ranging from 8 - 18 g/L for economic reasons (Drews et al., 2005). The high biomass concentration and high specific activity results in high oxygen requirements for oxidation processes and maintenance energy for the MBR. The long SRT and low food to mass ratios (F/M), as well as the heat generated during the exothermic oxidation and nitrification reactions, result in minimal biomass production and consequently reduce waste solids management and disposal requirements. Heat generated is within a range of 6 - 8 Wh/m3 and is considered significant as compared to the conventional activated sludge (CAS) process because of the higher biomass concentration (van Dijk and Roncken, 1997). The MBR process also allows for the uncoupling of the hydraulic retention time (HRT) and SRT. This facilitates operation at higher hydraulic loading without compromise on the degradation of slowly biodegradable contaminants. Operations under high rate conditions of up to 5 hours HRT while maintaining 20-day SRT are possible with the exploitation of membrane technology (Monti, 2006). The limitations in MBR systems arise principally from the high initial and replacement costs of the membrane itself, although there have been recent developments of less expensive and more efficient membranes. There is potential difficulty with post-treatment of the sludge because of poor filterability as reflected by its  14  2: Literature Review  relatively high specific filtration resistance (Cicek et al., 1999). Also, there is a high energy demand for operation of MBR systems.  2.3.1  MBR classification Membranes can be classified based on their pore size, material, physical  configuration and on their mode of operation. MBRs are distinguished primarily by their use of either sidestream (external) or submerged membranes. In the sidestream configuration, the membranes are usually horizontal or vertical tubular membranes placed external to the bioreactor. The system operates in a crossflow mode and is designed to reduce deposition of suspended solids at the membrane surface. The high cross flow velocities are provided by recirculating pumps. While this configuration is simple and provides more direct hydrodynamic control of fouling, the energy demand for pumping is relatively high. In the submerged configuration, the membranes are either horizontally or vertically placed fibres, or vertically placed flat sheets submerged within the bioreactor. The systems are aerated at the bottom side, while permeate is withdrawn by means of suction at the permeate side. This configuration was first introduced by Yamamoto et al. (1989) with the intent to eliminate the need for recirculating pumps and consequently to reduce operational cost. The submerged configuration operates more cost effectively than the side-stream configuration. While aeration costs are higher and account for more than 90% of the energy consumption, the energy for pumping is significantly lower as compared to the sidestream configuration (Gander et al., 2000). In the submerged configuration, aeration is provided to scour the membrane, to set up a cross flow effect and suppress fouling and to provide oxygen to the biomass.  2.3.2  Nitrification in MBR MBRs can achieve stable nitrification. SRT and biomass retention are the  principal factors that influence nitrification in MBR as at high SRT, slow-growing nitrifiers tend to accumulate in an MBR. Grazing of protozoa and metazoa on nitrifying bacteria  15  2: Literature Review  can, however, result in a critical decrease of the nitrifying capacity of an MBR system (Ghyoot and Verstraete, 2000). The role of protozoa in MBR is in contrast to that reported for the conventional activated sludge process. MBR can achieve complete nitrification at SRT > 5 days (Fan et al., 2000; Rosenberger et al., 2000; Macomber et al., 2005; Ng and Hermanowicz, 2005). Complete nitrification has also been reported in a system operating with SRT as short as 3 days (Ng et al., 2006) and nitrification ceased at SRT < 2.5 days (Fan et al., 2000; Rosenberger et al., 2000; Macomber et al., 2005; Ng and Hermanowicz, 2005) because of washout of the nitrifying bacteria. The characteristics of the MBR biomass with regards nitrification can be determined by the influent quality, since the ratio of autotrophs to heterotrophs in the biomass of the MBR is mainly determined by the influent C/N ratio (Fan et al., 2000). The biomass retention is advantageous at low temperature operation when nitrification is inhibited. At low temperatures, there is an increase in biomass concentration as a result of a lower sludge decay rate. The complete retention of biomass together with the biomass concentration increase at low temperature can compensate for the loss of biomass activities (Chiemchaisri and Yamamoto, 2005). Nitrification has been shown to be greater in MBR when compared to a CAS process (Gao et al., 2004a; Gao et al., 2004b; Ng and Hermanowicz, 2005). This observation was based on effluent nitrate concentration. There also tended to be more stable nitrite oxidation in the MBR which was attributed to the further nitrification within the pores of the membrane, the increased air supply from the coarse bubble aeration and smaller floc size and reduced mass transfer effects within the floc size (Manser et al., 2005c). Biofilm growth on the surface of the membrane does not contribute significantly to the overall nitrification performance (Manser et al., 2005c). With respect to specific nitrification activity (g N/g VSS·d) in the MBR as compared to the CAS, there are limited reports and these are inconsistent. Investigations have indicated that it is greater in MBR compared to CAS (Zhang et al., 1997), whereas there are those that indicate otherwise (Liebig et al., 2001; Li et al., 2006b; Monti, 2006; Parco et al., 2006). Differing trends have also been observed between the two systems depending on the operating conditions, with the specific  16  2: Literature Review  nitrification rate being higher in MBR at low SRT and comparable for both systems at higher SRT of 6 - 7 days (Aguilera Soriano et al., 2003). The observations of higher specific nitrification rate in the MBR have been explained by the capability of the MBR to retain nitrifiers, the smaller floc size distribution and the less dense floc structure. Population differences between the two sludges could account for the differences in the specific nitrification rates as noted by Manser et al. (2005b) who compared the rates using MBR and sequencing batch reactors (SBR). They found that the SBR exhibited a higher rate and that the autotrophic biomass was dominated by Nitrosomonas eutropha/europaea which are known to exhibit high maximum growth rates and a low affinity to the substrate, while Nitrosomonas oligotropha dominated in the MBR, with a lower maximum growth rate combined with a high affinity to the substrate. Specific nitrification rate in MBR varies with SRT (Fan et al., 1996; Han et al., 2005) as well as operational time of the reactor (Gao et al., 2004b; Li et al., 2005). There is a decrease with increasing SRT and this decrease of the specific sludge nitrifying activity has been attributed to a change in nature of the activated sludge, accumulation of inert biomass from metabolic products of endogenous respiration, impeded oxygen transfer from the outside to the inside of activated sludge flocs owing to an increase of the sludge concentration at long SRT and competition of biomass derived from low F/M ratio (Fan et al., 1996; Huang et al., 2001; Han et al., 2005; Li et al., 2006b). The effect of operational time of the reactor depended on whether the numbers of ammoniaoxidizing bacteria and nitrite-oxidizing bacteria in the mixed liquor tended to increase (Gao et al., 2004b) or decrease (Li et al., 2005) as operational time increased. The rate increased as the numbers increased and decreased as they decreased and it is apparent, therefore, that the specific nitrification rate is dependent on the quantity of nitrifiers within the system.  2.3.3  Membrane floc The floc in MBR is notably different from CAS in morphology and size. The  membrane floc particle size is related to the separation technique and the different operating conditions of high sludge retention time, high sludge concentration and high  17  2: Literature Review  shear stress hydrodynamic conditions that are commonly used in membrane bioreactors. The floc in the MBR is an accumulation of small size floc and has a loose structure (Zhang et al., 1997). It has been reported that the MBR floc contains a considerable amount of branched (Holbrook et al., 2005), thin, long filamentous bacteria that produce high amounts of extracellular polymeric substances (EPS) as compared to the CAS floc (Witzig et al., 2002). The size of floc particles in MBR has been found to be dependent on the operating SRT. It decreases with increasing SRT as well as MLSS (Sperandio et al., 2005). Several studies have reported smaller floc particles, with average diameters ranging from 20 - 40 m in the MBR as compared to the CAS, which range from 20 to 120 m (Zhang et al., 1997; Cicek et al., 1999; Gao et al., 2004a; Manser et al., 2005a; Ng and Hermanowicz, 2005). This difference was attributed to shear stress in the MBR. In an MBR, the tangential flow along the membrane as well as the coarse aeration, creates significant shear stresses. Shear stress modifies the composition as well as the characteristics of the biological suspension as the break-up of the floc causes reduction in the floc size and the release of bacterial polymers. These bacterial polymers can reduce the settleability of the suspension (Wisniewski and Grasmick, 1998; Kim et al., 2001) and are also known to inhibit nitrification (Chudoba, 1985). Ghyoot et al. (1999) observed a sudden decrease in specific sludge nitrification activity in an MBR treating sludge reject wastewater related to the pump shearing action and break up of floc, but noted that it was probably due not only to shear stress from filtration, but to a combination with other, yet unidentified, factors. Also the intensive recirculation destructures the floc and modifies the size distribution of the particles present (Wisniewski and Grasmick, 1998). This results in a reduction in size of the particles which limits the importance of diffusional transfer within the floc and increases the apparent reaction rate (Wisniewski and Grasmick, 1998). Smaller floc size results in improved mass-transfer conditions in the MBR and consequently a more viable biomass as compared to the CAS (Cicek et al., 1999). The distribution of MBR floc particle size is bimodal, with a macro and micro floc population. The microfloc population (1 - 15 m) occurs from the retention of colloids,  18  2: Literature Review  small particles and free bacteria and leads to an increase in the non-settleable fraction of the suspension (Wisniewski and Grasmick, 1998; Sperandio et al., 2005). The consequences with regard its settling properties are not as significant, since separation of the biomass from final effluent in an MBR is achieved by barrier technology and therefore, the efficiency of the separation process is not dependent on floc-forming capability as is necessary in the CAS system. The non-settleable fraction, however, appears to be the main fraction responsible for membrane clogging (Wisniewski and Grasmick, 1998). The small floc size is noted as an advantage, as it may contribute to the growth of nitrifiers. Though nitrifiers prefer smaller flocs, they are found to be present in an aggregated form rather than dispersed (Luxmy et al., 2000a). The floc size therefore influences the presence of ammonia-oxidizers and consequently the specific nitrification rate. The percentage of ammonia-oxidizers increases with decreasing floc size (Luxmy et al., 2000a) and there is an increase in specific nitrification rate (Zhang et al., 1997). The smaller size of the flocs may improve nitrifier contact with the substrate and oxygen. However, they may also become more exposed to grazing. Luxmy et al. (2000b) reported heavier grazing of the smaller flocs which mostly consist of small (<1 μm) dispersed bacterial species, by the predator population in a membrane-separation activated sludge system.  2.3.4  Community composition The membrane itself in an MBR system does not influence the microbial  community (Manser et al., 2005c). However, the retention of biomass, higher MLSS concentrations, and higher sludge age with which the MBR operates tend to change the composition of the microbial community as compared to a CAS. While only minor differences in community structure were reported by Gao et al. (2004b), Cicek et al. (1999) observed substantial variations in the microbial populations in an MBR compared to a CAS. Compared to the CAS, the MBR sludge contained greater numbers of single cell free swimming bacteria, smaller numbers of filamentous organisms, almost no nematodes and fewer protozoa. Li et al. (2005) also found that the two systems harboured different bacteria based on comparison of denaturing gradient gel  19  2: Literature Review  electrophoresis (DGGE) bands and that the number of bands gradually increased with increasing operational time of the reactors. The increase was however, greater in a CAS system. There are conflicting reports on the nitrifying community composition of MBR biomass as compared to conventional systems. The population in an MBR with respect to nitrifying bacteria has been reported to be similar to that of a CAS (Li et al., 2005; Manser et al., 2005c) as well as different to that of a CAS (Liebig et al., 2001; Witzig et al., 2002). Witzig et al. (2002) found no Nitrosomonas nor Nitrosospira commonly found in CAS, but did detect Nitrospira, whereas Nitrosomonas were reported for an MBR (Li et al., 2005; Manser et al., 2005c). The study by Witzig et al. (2002), which was carried out without any sludge withdrawal and hence a long sludge age, also showed absence of grazing organisms such as protozoa and metazoa and that the microbial population was substrate-limited. The quantity of nitrifiers in an MBR varies with MLSS concentration, decreasing with increasing MLSS and SRT (Li et al., 2006b). This is contradictory to the assumption that the retention provided by the membrane is advantageous for keeping the slow growing nitrifiers in the system. The increase of MLSS was attributed to the accumulation of extracellular polymeric substances (EPS) and inert matter under long SRT of 135 - 415 days and the accumulation of EPS is believed to affect the metabolic behavior of ammonia-oxidizers. Li et al. (2006a) concluded that the inhibitory effect of EPS on nitrifiers is finite, as these micro-organisms could adapt to the bulk liquid EPS conditions after an extended operational period. However, a steady accumulation of soluble microbial products (SMP) followed by a decrease in concentration due to degradation as operational time increased, appeared to be the typical behavior in an MBR (Huang et al., 2000; Gao et al., 2004a).  2.3.5  Reaction kinetics Specific microbial activity can be influenced by the amount of oxygen and  substrate available. The half saturation constant for substrate is similar in an MBR and a CAS, whereas the half saturation constant for oxygen is significantly higher in a CAS compared to an MBR (Manser et al., 2005a). The differences were thought to have  20  2: Literature Review  resulted from mass transfer effects within the floc since diffusion limitation plays a significant role in activated sludge flocs, but is negligible for flocs with a diameter smaller than 100 m, as is the case for the MBR floc. Various estimates of nitrifier decay rate have been reported with regard to comparison between MBR and CAS systems. Nitrifier decay rates have been found to be either comparable in MBR and CAS systems (Manser et al., 2006), lower (Cicek et al., 1999) as well as higher for MBR as compared to CAS systems. Similarly, inconsistencies in yield coefficients between the two systems have been reported. Comparable yields were reported by Macomber et al. (2005). Higher yield coefficients in an MBR as compared to a CAS (Cicek et al., 1999; Holbrook et al., 2005) and lower yields in an MBR as compared to CAS (Rosenberger et al., 2002) have also been reported for various studies. Higher biomass yields in MBR have been attributed to a reduced protozoa presence as compared to the CAS system (Cicek et al., 1999). There are contrasting reports regarding biomass viability in the MBR. Cicek et al. (1999) observed that biomass in the MBR exhibited a higher viable fraction and this was attributed to improved mass-transfer conditions in the MBR associated with smaller flocs and more free swimming bacteria. Biomass viability in an MBR was, however, reported to decrease with increasing MLVSS and bioreactor operational time due to the retention of inert compounds (Hasar et al., 2002). A lower specific oxygen uptake rate (SOUR) in an MBR than in a CAS at similar MLSS concentration also indicated lower biomass viability because of the additional colloidal COD retained by the MBR (Holbrook et al., 2005) and the physiological state of the biomass. The bacteria are in a low metabolic activity stage and use energy for maintenance metabolism and not for growth (Witzig et al., 2002).  2.4  Membrane enhanced biological phosphorus removal The membrane enhanced biological phosphorus removal (MEBPR) process  combines the MBR concept with an enhanced biological phosphorus removal process (EBPR) for removal of BOD, nitrogen and phosphorus from wastewater. MEBPRs have been shown to produce treated effluent with lower phosphorus concentrations as compared to the effluent from conventional EBPR processes (Adam et al., 2002; Monti  21  2: Literature Review  et al., 2006). The MEBPR process is effective under sludge ages which are typical for conventional systems as well as with higher sludge ages that are more typical of MBR systems. One notable advantage of the introduction of biological phosphorus removal in an MBR operating mode comes from the reduced chemical and sludge disposal costs which could result in up to 27% reduction in total operation and maintenance costs (Annaka et al., 2006). Also, through variable recycle ratios among the reactors, there is the flexibility to operate under variable anaerobic, anoxic and aerobic biomass fractions to optimize nutrient removal according to influent wastewater characteristics and effluent concentration requirements (Ramphao et al., 2005).  2.4.1  MEBPR research The MEBPR bioreactor process is gaining attention in the research field because  of its potential for combining the advantages of biological phosphorus removal and membrane technology in wastewater applications. There have been various areas of investigation with the focus being on optimizing process operational parameters. The following section summarizes some of the recent works published in the field. Adam et al. (2002) were among the first to show that biological P removal could be attained using a membrane bioreactor. Using raw domestic sewage in a bench-scale plant with an anaerobic, anoxic, aerobic-membrane unit process as shown in Figure 2-2, effluent N and P concentrations were found to be lower when compared to a conventional wastewater treatment plant (WWTP).  22  2: Literature Review  effluent  influent  excess sludge Anaerobic  Figure 2-2  Anoxic  Aerobic + filter reactor  MBR biological nutrient removal unit Source: Adam et al., 2002  Two configurations of membrane bioreactors were assessed by Lesjean et al. (2002, 2003) to achieve enhanced biological phosphorus and nitrogen removal. The first configuration as illustrated in Figure 2-3 was adapted from the conventional EBPR activated sludge process, and was designed with a pre-denitrification zone whereas the second configuration featured post-denitrification without addition of external carbon for enhanced nitrogen removal. Both performed equally with respect to phosphorus removal, with most of the P-uptake occurring in the anoxic reactors. The performance was attributed to the MBR retaining all phosphate-accumulating microorganisms and providing aerobic conditions which fix the phosphate, when the effluent is separated from the sludge. The post-denitrification mode achieved consistently better N-removal efficiency than the pre-denitrification mode. Pharmaceuticals residues and steroids were also monitored in the two parallel MBR pilot plants and it was found that the MBR plants could remove most of the compounds.  23  2: Literature Review  Figure 2-3  Configuration for bio-P and nitrogen removal Source: Lesjean et al., 2005  A pilot scale five stage membrane system operating initially at a 30-day SRT was investigated by Fleischer et al. (2005) to determine the capability of the system to produce a low N and P effluent. A schematic of the system is shown in Figure 2-4. Chemical addition was required to consistently meet the desired effluent quality for P< 0.1 mg/L because of the unfavourable influent BOD/TKN ratio. P as low as 0.03 mg/L was achieved with the combination of biological and chemical addition.  Anoxic recycle  Influent  Cell 1  Cell 2  Cell 3  Cell 4  Cell 5  Anaerobic  Anoxic  Anoxic  Aerobic  Anoxic  Cell 6  Permeate  Membrane  Nitrified recycle  Figure 2-4  Aerobic  RAS  Five stage membrane bioreactor for N and P removal Source: Fleisher et al., 2003  Annaka et al. (2006) presented the process configuration illustrated in Figure 2-5 for investigating an alternative MBR process for reducing operational cost by reducing power, chemical consumption and sludge disposal costs.  24  2: Literature Review  Figure 2-5  Configuration for nutrient removal with MBR process Source: Annaka et al., 2006  The system incorporated an improved membrane with thinner fibers than conventional membranes which required less air for cleaning and cyclic aeration operation that omits backwashing. The tank configuration of anoxic first, followed by anaerobic and then aerobic, served to prevent DO from entering the anaerobic tank from the aerobic tank and provided favorable conditions for biological phosphorus removal. Additionally, the influent was fed into both the anoxic and anaerobic tanks in order to ensure that the organic substrates necessary for the release of the phosphorus were contained in the anaerobic tank sludge. Investigations of the kinetics of UCT-type nutrient MBRs using flat sheet membranes have also been reported (Ramphao et al., 2005; Parco et al., 2006; du Toit et al., 2007; Parco et al., 2007).  2.4.2  Process performance: Comparison with EBPR Comparative studies between the MEBPR process and the conventional  enhanced biological phosphorus removal process (CEBPR) have shown that the MEBPR process could produce an improved quality effluent (Adam et al., 2002; Lesjean et al., 2002; Monti et al., 2006; du Toit et al., 2007). With a sludge age of 15 days,  25  2: Literature Review  effluent total phosphate as low as 0.05 - 0.16 mg/L can be achieved (Adam et al., 2002). The MEBPR also has the capability to recover from bio-P process upsets at a noticeably faster rate than the CEBPR (Monti, 2006). MEBPR exhibits excellent nitrification (Adam et al., 2002; Lesjean et al., 2002; Monti et al., 2006). Monti (2006) and Parco et al. (2006), however, noted lower specific nitrification rates in the membrane train relative to the conventional train under similar operating conditions.  2.5  Assessing microbial populations An essential component of a biological wastewater treatment system is the  microbial community. Microorganisms, principally bacteria, are responsible for removal of the pollutants. The community tends to respond to changes in system operating conditions and environment by changes in composition and such population dynamics can impact the treatment process. Microbial methods have been applied to provide insight into the microbial community structure and abundance of bacteria in wastewater systems. These methods for assessing bacterial populations can be generally classified as culture-based or molecular-based techniques.  2.5.1  Culture-based techniques Culture-based techniques often involve enrichment, the process in which the  organism of interest would be taken out of the community, followed by isolating pure cultures of the organism (Madigan et al., 2000). Ammonia-oxidizing bacteria (AOB) pure cultures are typically obtained by picking colonies from a solid medium. The selective medium used is critical and must be free of organic carbon sources and must contain inhibitors of heterotrophic organisms, an ammonia source, and essential trace elements (Kowalchuk and Stephen, 2001). ―AOB are notorious for their slow growth and low maximum growth yield, making their isolation and maintenance in pure culture difficult and time-consuming. Also, the  26  2: Literature Review  culture media may select for particular strains that may not necessarily represent the most abundant populations present. Furthermore, as with other microorganisms, the fraction of viable cells in an environmental sample that is actually amenable to laboratory culture conditions may be quite small‖ (Kowalchuk and Stephen, 2001). These factors result in an underestimation of both numbers and diversity (Juretschko et al., 1998). Culture-based studies are important for understanding the physiology and function of microorganisms, but these approaches alone are insufficient for monitoring the abundance and diversity of organisms within an environmental system. These limitations of culture-dependent methods may be partially overcome by cultivation-independent techniques.  2.5.2  Molecular-based techniques Culture-independent molecular methods are preferred for investigating nitrifying  bacteria because of the problems associated with cultivation of the nitrifiers. These molecular-based techniques focus on the detection and analysis of nucleic acids and they include both sequencing and profiling methods. Sequencing methods determine the sequence of nucleotides of the deoxyribonucleic acid (DNA) usually from gene clone libraries. High cost is the main limitation of sequencing, however, this has been changing. Profiling methods are strategies that categorize organisms into groups based on similar and specific characteristics and have the advantage of being rapid, affordable, relatively easy to use and amendable to high sample throughput.  2.5.2.1  Community profiling Commonly  used  profiling  techniques  include  denaturing  gradient  gel  electrophoresis (Muyzer et al., 1993), terminal restriction fragment length polymorphism analysis (Liu et al., 1997) and automated ribosomal intergenic spacer analysis (Fisher and Triplett 1999). These profiling techniques require polymerase chain reaction (PCR) amplification of a specific genetic marker region, followed by resolution of the amplicons based on distinct characteristics.  27  2: Literature Review  The PCR amplification reaction requires two PCR primers, a heat stable polymerase enzyme and nucleotides. A primer is an oligonucleotide (small piece of DNA) that contains a specific sequence that when combined with single-stranded target DNA, will hybridize with the complementary sequence in the target DNA and form a double-stranded structure (Bitton, 2005). Nucleotides are molecules that make up the structural units of DNA and the polymerase serves to synthesize these into polymers. The PCR cycling involves first heating for denaturing of the double stranded DNA (dsDNA) and separation into two single strands. This is followed by a cooling cycle for annealing, in which the primers form hydrogen bonds with their complementary sequence. The temperature is then increased and the polymerase attaches to each end of the primer sites. During this extension cycle, the dsDNA is synthesized as the polymerase attaches nucleotides to extend the primers. As the cycling is repeated, the DNA is amplified.  i.  DGGE  The denaturing gradient gel electrophoresis (DGGE) technique allows PCR products of similar length but of different sequence composition to be separated in a linearly increasing gradient gel (Muyzer et al., 1993). The technique is based on the principle of the decreasing mobility of a partially melted DNA molecule in polyacrylamide gel so that separation is achieved by the resistance to migration with denaturing. This method has been applied to environmental samples, including activated sludge (Luxmy et al., 2000a; Li et al., 2005) using both 16S rRNA (Limpiyakorn et al., 2005; LaPara and Ghosh, 2006) and amoA functional (Nicolaisen and Ramsing, 2002; Hornek et al., 2006) genes for profiling nitrifying bacterial communities. It has also been used for comparing AOB and nitrite-oxidizing bacteria (NOB) communities in conventional activated sludge processes with membrane bioreactors (Luxmy et al., 2000a; Wittebolle et al., 2008). A typical DGGE gel is shown in the Figure 2-6. The analyses generate profiles, but sequence information can also be obtained as the individual bands could be recovered and analyzed.  28  2: Literature Review  S  Figure 2-6  K  T  R  S K T R  Wastewater treatment plant Estuary Tidal mudflat Rice paddy soil  DGGE gel of amplicons comparing amoA and 16S primers for different environmental samples Source: Nicolaisen et al., (2002)  ii.  T-RFLP  Terminal restriction fragment length polymorphism (T-RFLP) analysis is one of the most frequently used high throughput profiling methods. It allows for differentiation of sequences based on the location of specific enzymatic restriction sites. It detects the most abundant populations and is thus appropriate for comparing communities on the basis of those abundant populations. It is also appropriate for evaluating the diversity of particular groups such as nitrifiers. Although the technique is commonly applied to 16S rRNA genes, it was also successfully applied to amoA functional genes (Horz et al., 2000; Siripong and Rittmann, 2007a). The technique involves PCR amplification of the gene of interest from the DNA, using fluorescently labeled primers. The PCR product is digested with a restriction enzyme, resulting in the formation of a number of fragments of various lengths. After enzymatic digestion of PCR amplicons, each unique terminal restriction fragment (T-RF) may be inferred to represent a single population within a community and hence differences in the sizes of T-RFs reflect differences in the sequences of genes, allowing phylogenetically distinct populations of organisms to be distinguished. The T-RFs produced during the enzyme digestion are separated on a high-resolution sequencing device for detection of only the fluorescently-labeled end fragments. The steps of the T-RFLP method are illustrated in the Figure 2-7.  29  2: Literature Review  1. DNA EXTRACTION The dsDNA is extracted from the sample.  2. PCR AMPLIFICATION The extracted DNA is amplified using fluorescently labeled primers (♦). Either one or both primers can be labeled. 5‘ 3‘ 5‘ 3‘ 3‘  Sequence 1  5‘  3‘  Sequence 2  5‘  3. RESTRICTION ENZYME DIGESTION The restriction enzyme (▼) cleaves the DNA at the recognition site and produces a number of fragments of different lengths. Restriction enzyme with G_CG‘C recognition site AATTGGCCGCGCATATTG  AATTGGCCGCG  TTAACCGGCGCGTATAAC  TTAACCGGC GCGTATAAC  CATATTG  dsDNA with GCGC nucleotide sequence  Fragment lengths after digestion  Sequence 1  Sequence 2  4. CAPILLARY ELECTROPHORESIS  Fragment Frequency  The fragment lengths are resolved by electrophoresis. Only the fluorescently labeled end fragments are detected.  Fragment Length  Figure 2-7  Illustration of the steps of the T-RFLP method  30  2: Literature Review  iii.  RISA  Ribosomal intergenic spacer analysis (RISA) is similar to the T-RFLP methods but involves PCR amplification from total bacterial community DNA of the intergenic region between the small (16S) and large (23S) subunit rRNA genes. The basis of the method is that the 16S-23S intergenic region displays significant heterogeneity in both length and nucleotide sequence (Fisher and Triplett, 1999). The RISA method has been applied to an activated sludge process treating wastewater (Ciesielski et al., 2009) as well as a wastewater treatment process for pulp and paper mill effluent (Yu and Mohn, 2001) for profiling bacterial communities.  2.5.2.2  Bacterial quantification Culture-independent molecular methods that have been investigated for  quantification of nitrifying bacteria include quantitative dot-blot hybridization (Mobarry et al., 1996), fluorescent in-situ hybridization (FISH) using oligonucleotide probes (Okabe et al., 1999; Schramm et al., 1999) and PCR based methods (Dionisi et al., 2002; Harms et al., 2003). Konuma et al. (2001) compared methods for enumeration of AOB and concluded that dot-blot hybridization was superior to FISH for wastewater mixed liquor and effluent samples. FISH generally involves hybridization with fluorescently labeled oligonucleotide probes followed by visualization with a confocal scanning laser microscope (CSLM) and manual counting of cell numbers. Limitations to the FISH procedure for bacteria quantification include (i) the availability of an expensive microscope, (ii) the fact that the technique is time consuming (iii) problems with inhomogeneous signal intensities and (iv) limited accuracy for samples containing densely aggregated cells like activated sludge flocs or biofilms. Several researchers have attempted to overcome these limitations. Semi-automated digital image analysis tools were reported by Bloem et al. (1995) for cell counting. Daims et al. (2001a) presented a method for absolute quantification of cells in dense clusters and Manser et al. (2005b) proposed a rapid method to quantify nitrifying bacteria in activated sludge without the use of an expensive CSLM.  31  2: Literature Review  PCR methods have also been adapted to quantify bacteria. Quantitative real-time PCR (qPCR) is one such method that has been used for both AOB and NOB quantification. In real-time PCR, the progress of the amplification is monitored at each PCR cycle. Real time PCR is based on the detection of the fluorescence produced by a reporter molecule which increases, as the reaction proceeds. These fluorescent reporter molecules include dyes that bind to the dsDNA (SYBR® Green assay) or sequencespecific probes (TaqMan assay). Both amoA and 16S rRNA have been measured for real time quantification of nitrifiers in activated sludge systems. The quantification has traditionally used the Taqman probe (Harms et al., 2003; Robinson et al., 2003; Limpiyakorn et al., 2005; Kuo et al., 2006). More recently, however, there have been reports of SYBR® Green assay (Geets et al., 2007; Nakagawa et al., 2007; Wittebolle et al., 2008). The SYBR® Green assay tends to be more accurate as compared to the Taqman assay when used with degenerate targets such as amoA in a mixed community. This is principally because of the specificity of the Taqman probe.  32  3: The Knowledge Gap  3  The Knowledge Gap Based on the literature reviewed, it is apparent that the outcomes of the various  studies on the nitrification process in MBR are contradictory. There are a lot of inconsistent data and this may have been a consequence of the differences of investigating conditions, such as the type of wastewater, SRT, process configuration etc. Many of the studies on MBR were carried out for the purpose of optimizing the MBR process. With regard to comparative studies for MBR and CAS, the work of Manser et al. (2005a; 2005b; 2005c; 2006) provided a comprehensive study on the nitrification process in terms of the microbial populations, mass transfer and kinetics. This study, which included diurnal variation of the flow of domestic wastewater, was done in parallel, operating at an SRT of 20 days, but process conditions were not identical, as reactor volumetric capacity differed markedly for the two systems. The literature reports obtained with regard to EBPR processes combined with membrane separation were few in number and the focus was on confirming that bio-P removal does occur given the low sludge wasting, reducing operational cost, optimizing reactor configuration for nitrification and determining N and P removal kinetics. There have been limited studies comparing membrane and conventional EBPR processes (Monti, 2006; Parco et al., 2006; du Toit et al., 2007; Lee et al., 2009). The studies by Monti (2006), provided insight on the performance of both systems from comparative pilot scale testing and under near identical conditions, as compared to the other studies. Monti (2006) found that the MEBPR process could produce lower treated effluent phosphorus concentrations compared to the CEBPR process. Interestingly, there was a reduced specific nitrification rate in the MEBPR process, relative to a conventional BPR process. This is somewhat anomalous behavior when considering that the membrane system retained a larger fraction of biomass and the viability of biomass was comparable for both systems. The study by Parco et al. (2006) also reported reduced specific nitrification rate with the membrane process. In these studies the cause of the reduced specific nitrification rate was not confirmed.  33  3: The Knowledge Gap  The membrane possesses characteristics which could either enhance or negatively affect the nitrification process. If the characteristics that negatively affect the process outweigh those that enhance the process, the consequence is a nitrificationspecific loss in the membrane process. The several factors that could determine the specific nitrification rate have all been investigated under several different operating conditions. It is evident from the literature that the selected experimental conditions influence the outcome of the studies and thus the cause for differences in the nitrification activity for the membrane EBPR process cannot simply be inferred from the previous works on MBR.  34  4: Project Objective  4  Project Objective The characteristics of the membrane bioreactor process, combined with the  different experimental conditions in various investigations, may have led to contradicting conclusions in the literature regarding its performance relative to the conventional process. The reduced specific nitrification activity reported for the membrane process is of concern because it could limit MBR application in a conventional-type plant upgrade. The potential for application of MBR technology in the upgrading of conventional plants arises principally from the footprint requirements while achieving higher effluent quality. Reduction in nitrification activity could be critical if the reduced activity negatively impacts nitrification performance under dynamic operating conditions, or when high loading rates or short hydraulic retention times are applied to optimize the economic potential of MBR technology. To prevent ammonium nitrogen breakthrough to the effluent, it will be necessary to understand the influencing factors for the nitrification activity, such that the best course for ameliorating its impacts can be determined. The objective of this research was to compare the nitrification process in membrane EBPR and conventional EBPR processes and identify factors that play a crucial role in determining the nitrification activity of the membrane EBPR process, relative to a conventional EBPR process.  4.1  Research questions The following questions were to be addressed.  1.  Is there a difference in the specific nitrification rate for the membrane EBPR and conventional EBPR processes, under identical operating conditions?  2.  If the rate differs, is the difference due to varying biomass composition, kinetics, or nitrifier community composition? i.  Are there differences in the growth and decay rates between the two systems and what are the reasons for differences?  35  4: Project Objective  ii.  Is there a difference in predator presence in the systems? Does predator grazing influence the rates?  iii.  Does the coarse bubble aeration provided for membrane fouling control influence the nitrification rate? Is there a reduced carbon dioxide concentration in the membrane EBPR process from carbon dioxide stripping due to aeration? Is there any effect on the growth rate? Does the shear stress result in greater decay?  iv.  Is any difference due to a difference in the dominant AOB and NOB communities in the two systems?  v. 3.  Does the biomass in each system contain different quantities of nitrifiers?  If the rates do not differ, then what are the variables influencing this finding?  36  5: Materials and Method  5  Materials and Methods  5.1  Test facility The study was conducted at the Wastewater Treatment Pilot Plant at the  University of British Columbia (UBC) over the period November 2007 to February 2009. The pilot plant consisted of two identical reactor trains, both configured for the University of Cape Town (UCT) enhanced biological phosphorus removal process. For approximately six months prior to the start of this project the plant was being operated with membrane filtration modules in both trains. For the present study, one of the membrane modules was replaced with a conventional clarifier for solids-liquid separation. In preparation for the changeover of one train to a conventional process, the aerobic mixed liquors from both trains were intermixed. The intermixing was carried out for six weeks, following which the membrane module in one train was removed and a secondary clarifier was put into operation. The membrane module in the other train was then changed out for cleaning and both trains were set to operate under near identical conditions. The reactors were operated in parallel treating a common settled primary effluent from a domestic wastewater source.  5.1.1  UBC pilot plant description Each train of the plant consisted of a 2228 L compartmentalized reactor with  anaerobic, anoxic and aerated zones of liquid volumes approximating 240 L, 619 L and 1369 L respectively. Two ZeeWeed® custom-made hollow fiber membrane modules with nominal pore diameter of 0.04 m and with a combined surface area of approximately 24 m2 were used for solids-liquid separation in one train. The membrane modules were provided by Zenon Environmental Inc. (Oakville, Ontario, Canada), now GE Water and Process Technologies. The membranes were submerged in the aerated reactor and were operated under a constant flux of 12 L/m2·h and in the permeation mode for 9.5 minutes followed by a backflush with permeate for 30 seconds. Aeration for the treatment process, as well as for membrane fouling control, was provided by intermittent coarse bubble aeration using a 10 sec ON and 10 sec OFF cycle with air at a flow rate of  37  5: Materials and Method  0.34 m3/min (12 scfm). This air flow rate was specified in accordance manufacturer‘s recommendation for fouling control and was generally adequate for the process aeration. A medium-bubble air sparger was provided for additional aeration to meet process requirements when required. A conventional gravity secondary clarifier served for solids-liquid separation in the second train. The center-feed clarifier with approximate liquid volume of 457 L and surface area 0.5 m2 operated with a surface overflow rate of 10.6 m/d and HRT of 2 h. This surface overflow rate was lower than the typical design rate for secondary clarifier of 16-28 m/d as given by Tchobanoglous et al. (2003). Dissolved oxygen for the process was provided by aeration with a continuous fine bubble aeration system operating at a flow rate of 0.085 m3/min (3 scfm). This aeration system also provided the mixing to keep the solids suspended in the aeration tank. A single primary clarifier with similar dimensions to the secondary clarifier was installed upstream of both trains. The primary clarifier operated with a surface overflow rate of 34.6 m/d (typical design rate 40 m/d Tchobanoglous et al. (2003)) and HRT of 0.6 h and the effluent flowed to a 20 L holding tank with mixer. This holding tank provided the source of primary clarifier effluent to both the membrane and conventional trains. A complete description of the plant is provided in the layout drawings of Appendix I.  5.1.1.1  Process flow A process flow schematic of the facility is shown in Figure 5-1. A fraction of the  raw sewage flow from a housing development on the UBC campus was diverted and collected in a sump and was then pumped from the sump to a set of storage tanks. The sewage was pumped to fill the tanks daily at 3:00 am, 9:00 am, 3:00 pm and 9:00 pm. The sewage in the storage tanks was then pumped continuously to the primary clarifier at a rate of 12 L/min (17.28 m3/d). The settled primary clarifier effluent flowed by gravity to a holding tank from which it was pumped by two independent feed pumps to each anaerobic reactor, from which it flowed by gravity to the anoxic reactors and then to the aerated reactors. In the membrane EBPR train, the mixed liquor was filtered and permeate was withdrawn by pumping at 4.8 L/min (0.288 m3/h) to the permeate tank. 38  5: Materials and Method  Permeate was also returned to the aeration tank as required to maintain the liquid level in the process. The excess permeate was discharged as effluent to the sewer at a rate that was equal to the process influent flow rate. In the conventional EBPR train, the mixed liquor from the aeration tank flowed to the clarifier where the suspended solids settled out by gravity and the effluent flowed to a holding tank with an HRT of 5 minutes.  Anaerobic Primary Clarifier  Mixer  Holding Tank  Anoxic  Aerobic  Permeate Tank  Mixer  Clarifier Anaerobic Reactor Storage Tank  Tank Overflow  Storage Storage Tank Tank  Anoxic Reactor  Effluent Tank  Aerobic Reactor  Overflow to sewer  Sludge to sewer  Sewer  Sump  Figure 5-1  UBC pilot plant process flow schematic  In the membrane EBPR train there was an anoxic recycle line from the anoxic zone to the anaerobic zone in order to return biomass to stimulate growth of PAOs. There was also an aerobic recycle line from the aerobic zone to the anoxic zone to return nitrate for denitrification. Similarly, in the conventional EBPR train there was an anoxic recycle line and an aerobic recycle line. There was also a return activated sludge (RAS) line which returned the settled solids from the secondary clarifier to the aeration tank. The return of RAS directly to the aeration tank was not consistent with full-scale practice, but was utilized here in an attempt to achieve similar distribution of suspended  39  5: Materials and Method  solids within both process trains for the comparative study. In full-scale practice, the RAS is returned to the anoxic zone for a UCT-type process. During the study, the operational parameters maintained for both the membrane EBPR and conventional EBPR processes were as follows:Reactor Feed Rate  3.7 L/min (5.328 m3/d)  HRT  10 h  Nominal SRT  12 d  Nominal DO  2.5 – 3.0 mg/L  Anoxic Recycle Ratio  1:1  Aerobic Recycle Ratio  1:1  Acetate Feed Rate  7 g/L @ 22 mL/min (0.25 kg/d)  The acetate was added to the anaerobic reactor to maintain favorable VFA to TP ratio in the reactor influent for the P removal process. These operational parameters provided for optimum performance of the plant with respect to N and P removal at the selected HRT and SRT. These operating conditions were selected in accordance with the findings of Monti (2006), who investigated the performance of the UBC Pilot Plant EBPR process under various conditions. The SRT at which the plant was operated was lower than typical values, but represented the current design practice for conventional BPR processes in Western Canada (Oldham and Rabinowitz, 2001).  5.1.2  Plant routine operations  The daily operations of the plant included the following. i.  Monitoring pH of the primary effluent and the mixed liquor in the anaerobic, anoxic and aerobic reactors with a portable VWR probe.  ii.  Monitoring of dissolved oxygen concentration (DO) and temperature in the aerobic reactors with a portable YSI probe.  iii.  Monitoring of membrane trans-membrane pressure (TMP) to track filter performance in order to determine need for chemical cleaning.  iv.  Wasting of biomass solids for SRT control.  v.  Hosing the clarifiers and reactors and re-suspending the foam in the anoxic tank of the membrane train.  40  5: Materials and Method  vi.  Adding approximately 1.2 kg sodium bicarbonate to each of the two mixed raw sewage storage tanks in order to compensate for alkalinity consumption and H+ production during the nitrification process and to maintain a suitable aerobic zone pH.  vii.  Measuring the conventional EBPR composite effluent total suspended solids (TSS) concentration for use in calculating the daily sludge wasting volume to account for the solids mass loss with the effluent. A pump on a timer cycle served as a composite sampler for collecting samples from the secondary effluent holding tank. This composite sample was used only for TSS determination. All other secondary effluent samples were obtained as grab samples from the effluent holding tank.  The plant routine operations also included collecting samples of influent, effluent and reactor mixed liquor as detailed in the section 5.1.2.2 for chemical analysis to monitor the plant process performance. Flow rates were measured at least twice per month to maintain the desired influent feed, acetate feed, anoxic recycle, aerobic recycle and RAS recycle. The rates were determined from the time taken to collect a fixed volume of the flow. Membrane cleaning was undertaken when the TMP approached the operational limit of 65 kPa. The typical operating TMP as specified by the manufacturer was 10 - 65 kPa. Membrane cleaning involved removal of the membrane module from the aerated reactor and soaking it in a dilute sodium hypochlorite solution (200 mg OCl-/L) for 24 hours, followed by an additional soak in concentrated citric acid solution (2000 mg/L) for 48 hours.  5.1.2.1  SRT control SRT was maintained by daily wasting of sludge from the aerobic reactor. The  volume of sludge to be wasted was determined from Equation (5-1) using the total solids mass in each system.  41  5: Materials and Method  Sludge Wasting Rate (w)  w =  Total sludge mass SRT  - Mass loss from effluent  Waste sludge concentration  4   =  i 1  Vi  Si  c   QSe  Sw Equation 5-1  where w V  = =  c Q Si Se Sw  = = = = =  sludge wasting rate (L/d) reactor volume (L) V1 (anaerobic) = 240.5 L V2 (anoxic) = 618.5 L V3 (aerobic) = 1368.7 L V4 (clarifier) = 456.7 L SRT (d) flow rate (L/d) reactor volume suspended solids (mg/L) effluent suspended solids (mg/L) waste sludge suspend solids concentration (mg/L)  For the membrane process, total sludge mass was calculated from TSS concentration measurements in the anaerobic, anoxic and aerobic reactors and excluded the foam, i.e. the foam was not mixed into the anoxic reactor before sampling. For the conventional process, total sludge mass was calculated from TSS concentration measurements in the anaerobic, anoxic and aerobic reactors as well as the clarifier and a composite clarifier effluent sample. Samples for TSS concentration measurements were taken from within the reactors and/or sample taps and before the daily sludge wasting process at least twice per week. Also, daily composite clarifier effluent samples were taken for calculating the daily wasting rate. Initially the clarifier sample was collected as a column sample by inserting a hollow pipe and collecting an undisturbed column of the clarifier contents. This was subsequently changed from operation day 75 to a stirred sample in which the clarifier contents were manually mixed, to be consistent with the previous operational practice of Monti (2006). The stirred sample was taken during the wasting process when the clarifier level dropped and stirring was possible without causing overflow of solids.  42  5: Materials and Method  5.1.2.2  Sampling plan Grab samples of the reactor influent (primary effluent), membrane EBPR effluent  (permeate) and the conventional EBPR secondary effluent were taken on alternate days from the respective holding tanks for analysis of ammonium-nitrogen (NH4-N), nitratenitrogen (NO3-N), nitrite-nitrogen (NO2-N) and orthophosphate (PO4-P), total and soluble chemical oxygen demand (COD) and volatile fatty acids (VFA). The VFA was measured in influent samples only. All samples for soluble parameter determination, except for the membrane EBPR effluent, were filtered with a 0.45 m syringe filter. Samples were preserved and stored at 4oC until the analyses were performed at the Environmental Engineering Laboratory according to the methods described in subsection 5.1.2.3. At least once per week, mixed liquor samples were collected from each of the reactors. The samples were centrifuged, the supernatant was filtered with a 0.45 m syringe filter and preserved (Table 5-1) for analysis of NH4-N, NO3-N, NO2-N, PO4-P, TKN and TP. VFA was also measured for the anaerobic mixed liquor filtered supernatant. Mixed liquor samples from all reactors and the clarifier were also taken at least twice per week for total and volatile suspended solids (TSS and VSS) determination. Aerobic mixed liquor samples were also collected at random for particle size measurement. All samples were collected before wasting of suspended solids from the reactors for SRT control.  5.1.2.3  Analytical methods The analytical methods used during the study together with instrument details  and sample preservation where required, are summarized in Table 5-1 for the various parameters measured. The methods used, except for VFA determinations are in accordance with Standard Methods (Eaton et al., 2005). Also, particle size measurement followed the Malvern Mastersizer 2000 instrument standard operating procedure. The mixed liquor was placed into the instrument‘s sample cell and was pumped through the instrument for analysis. The procedure was fully automated and measurement was based on laser diffraction technique.  43  5: Materials and Method  Table 5-1  Methods for sample preservation and chemical analysis  Parameter  Preservation Method  Analytical Method  Instrument  Ammonium-nitrogen (NH4-N)  1 drop of 5% H2SO4 added to 5 mL of centrifuged and filtered sample  4500-NH3 H Flow injection analysis  Quikchem 8000, Lachat  Chemical oxygen demand (COD)  -  5220 D Closed reflux, calorimetric method  HACH spectrophotometer  Nitrate-nitrogen (NO3-N)  1 drop of phenol mercuric acetate to 5 mL of centrifuged and filtered sample  4500-NO3 I Cadmium reduction Flow injection analysis  Quikchem 8000, Lachat  Nitrite-nitrogen (NO2-N)  1 drop of phenol mercuric acetate to 5 mL of centrifuged and filtered sample  As for nitrate minus the Cu-Cd reduction step  Quikchem 8000, Lachat  Ortho-P (PO4-P)  1 drop of phenol mercuric acetate to 5 mL of centrifuged and filtered sample  4500-P-G Flow injection analysis  Quikchem 8000, Lachat  Total inorganic carbon (TIC)  1 drop of phenol mercuric acetate to 5 mL of centrifuged and filtered sample  Acidified infrared as described in 5310B for high temperature combustion method  IL-550 TOC-TN, Lachat  Total Kjeldahl nitrogen (TKN)  4 drops of 5% H2SO4 added to 40 mL of sample  4500-Norg D Block digestion and Flow injection analysis  Quikchem 8000, Lachat  Total phosphate (TP)  4 drops of 5% H2SO4 added to 40 mL of sample  Digestion as for TKN with 4500-P-G Flow injection analysis  Quikchem 8000, Lachat  Volatile fatty acids (VFA)  1 drop 2% H2PO4 added to 1 mL of sample  Application note 228-398 using HP-FFAP (1998)  HP 5890 Gas Chromatogram  Particle Size  -  Laser diffraction technique  Malvern Mastersizer 2000  -  44  5: Materials and Method  5.2  Nitrification rate measurement The mixed liquor nitrification rate was measured using oxygen uptake rate (OUR)  and NOx-N production rate (NPR) methods during a single batch test. Reactors with DO, pH and temperature controls and a data acquisition and storage system were used for the batch tests. A schematic of the set-up is shown in Figure 5-2. Details of control equipment and instrumentation arrangement are given in Appendix II.  Substrate and sample port  Temp probe  DO probe  DO probe  pH probe  pH probe  pH controller  Air diffuser  To air supply  Temp probe  Substrate and sample port  pH controller  Water jacket  Air diffuse r  Water jacket  Magnetic Stirrer  Magnetic Stirrer  To air supply  System control & Data acquisition  Figure 5-2  Schematic of respirometers, controls and data acquisition system  The system was programmed with Labview Signal Express® software to control the DO between a set maximum of 4 mg/L and a minimum of 2 mg/L. A pH controller maintained pH at 7.0 ± 0.2 by dosing with either 0.05 N NaOH or 0.25 M NaHCO3. A temperature control bath recirculated water through the reactor jacket to maintain the mixed liquor at pilot plant temperature ± 1oC for the duration of the test. DO, pH and temperature data were logged every 10 seconds during the test.  45  5: Materials and Method  Each reactor was filled with 8.3 L of mixed liquor taken from one of the aerobic tanks of the pilot plant trains. The pH was adjusted to 7.0 and the mixed liquor was aerated for 2 hours until the endogenous respiration rate was attained. A 630 mg amount of ammonium chloride (NH4Cl) was then added to each reactor to reach a final concentration of approximately 20 mg N/L. This concentration was established to ensure zero-order nitrification kinetics without causing substrate inhibition effects. After 2 minutes from substrate addition, a sample was taken from each reactor, centrifuged for 3 - 4 minutes at 1660 rcf and the supernatant was filtered through a 0.45 m filter. Samples of 10 mL volume of the filtrate were used for measurement of NH4-N and NOx-N. Samples were taken subsequently at 10-15 minute intervals for up to 2 hours thereafter. These samples were required for determining the change in both substrate and product concentration with time, for measurement of the nitrification rate by the substrate depletion method. One drop of 5% H2SO4 and one drop of 0.1% phenol mercuric acetate was used for preservation of samples collected for determination of NH4-N concentration and NOx-N concentration respectively. These concentrations were measured by the analyses described previously in Table 5-1. Duplicate samples for TSS and VSS were also collected at the start of the test, before the addition of substrate and at the end of the batch test. The average of these VSS values was used for normalizing the measured nitrification rate to give the rate per g VSS. The nitrification rate was also measured as a two-step reaction in some of the batch tests to determine the activity of both the ammonia-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB). This was done by addition of 7-10 mg N /L NaNO2 as substrate prior to the NH4Cl substrate addition. During such tests, the NH4Cl was added after complete utilization of the NaNO2 substrate. This point of complete utilization was identified by a decrease in OUR to the initial base rate that was attained before addition of substrate. Measurement of the nitrification rate as a two-step reaction followed the method described by Moussa et al. (2003).  46  5: Materials and Method  5.3  Nitrifier decay rate measurement The nitrifier biomass decay rate for both the membrane EBPR and conventional  EBPR processes was measured under conditions for determining (i) effect of shear arising from bubble size and (ii) effect of predators on the decay rate. In each investigation, four 12-L reactors, two containing membrane process mixed liquor and two with conventional process mixed liquor were set up in the laboratory. The mixed liquor samples were taken from the aerated zones of the pilot plant trains. The reactors were maintained in the laboratory temperature control room set to the temperature of the pilot plant mixed liquor at the time of sample collection. The reactors were mixed and aerated and the DO was maintained at 5 mg/L through the use of DO controllers. The pH in each reactor was manually adjusted and maintained at 7.0 ± 0.5 with either 1M NaHCO 3 or 0.05N NaOH base addition. The reactors were left aerated and unfed for 10 days.  5.3.1  Comparison of bubble type The 12-L decay reactors were set up using both fine and coarse bubble aeration  systems. Fine bubbles were provided with a commercially available fine bubble air diffuser stone. The course bubble aeration was achieved by using a diffuser constructed from tubing with 5 mm  holes. Two of the four reactors were fitted with fine bubble diffusers and two with coarse bubble aeration devices, so that each mixed liquor was aerated using both bubble sizes. A schematic of the reactor arrangement is presented in Figure 5-3. Every two days over a 10-day period, 2-L samples were withdrawn from each of the four reactors for nitrification rate measurements. Rates were determined from OUR and NOx-N production methods as described previously. All tests were performed at the decay reactor temperature ± 1oC. Samples of 30 mL volume were also taken daily from each of the 12-L decay reactors for measurement of NH4-N, NOx-N and TIC concentrations. The samples were centrifuged for 3 - 4 minutes at 2000 rcf and filtered through a 0.45 m filter and 10 mL aliquots of the filtrate were preserved with 5% H2SO4 and phenol mercuric acetate for NH4-N and NOx-N and total inorganic carbon (TIC) determination respectively.  47  5: Materials and Method  Mixer  Two reactors containing membrane process mixed liquor  Two reactors containing conventional process mixed liquor DO probe to controller  DO Controller  power supply From air supply  Solenoid valve Reactor with fine bubble diffuser stone  Figure 5-3  Reactor with coarse bubble diffuser tube  Reactor with fine bubble diffuser stone  Reactor with coarse bubble diffuser tube  Schematic of reactors arrangement for decay rate measurement The reactors were kept in a temperature-controlled environment. pH was monitored with a portable pH probe and alkali was added manually to maintain a pH of 7.  During the decay rate experiment, pH was controlled by addition of 0.05 N NaOH rather than NaHCO3. This was to avoid the addition of an external source of the bicarbonate ion, since TIC (total inorganic carbon) was being monitored within the reactors. At the start of the test, however, bicarbonate was added. The decay test was carried out on three aerobic mixed liquor samples taken from the pilot plant on Day 273, Day 296 and Day 328, at which times the pilot plant temperature was 20oC, 23oC and 20oC respectively and when the specific nitrification rate was consistently higher in the membrane process than in the conventional process.  5.3.2  Predator effects The experiments were designed to compare the biomass decay rate with and  without active predators. A suitable means for inactivation of the predators was to be determined prior to performing the decay rate test. Two methods were investigated for predator inhibition. These included inactivation by using NaCl (Moussa et al., 2005) and cycloheximide (Lee and Welander, 1994; Petropoulos and Gilbride, 2005; Chabaud et al., 2006). Preliminary investigations of these two inhibitors were carried out to  48  5: Materials and Method  determine the effect on the predators as well as any effects on the nitrifiers. These preliminary experiments are described in the following.  Inhibition with NaCl This experiment was carried out using a control and treated sample for both the membrane process and conventional process mixed liquors. Four batch reactors, each containing 2 L of mixed liquor from the membrane or conventional process were set up. Sodium chloride was added to one of the reactors with membrane process mixed liquor and to another with conventional process mixed liquor. The NaCl was added in an amount to achieve a final concentration of 5 g/L. All four reactors (treated and control) were left to stand for two hours, during which time samples of the mixed liquor from each reactor were taken for microscopic examination under a light microscope. During this time, the reactors were mixed and the DO was maintained between 2 - 4 mg/L. This procedure was repeated with NaCl concentrations of 8 g/L, 10 g/L and 12 g/L for selection of an appropriate concentration. After the two hour period, nitrification rate measurement was carried out on all four mixed liquors using the NOx-N production rate method as previously described. In order to remove the excess salt before measurement of the nitrification rate and provide similar conditions for comparison with the control, each of the four mixed liquors was centrifuged at 1400 rcf for approximately 30 minutes, the supernatant was discarded and the biomass was re-suspended in effluent from the corresponding pilot train. The effluent from the conventional process was filtered to remove all suspended solids before use.  Inhibition with cycloheximide A similar set-up as described for NaCl inhibition, but using 250 mL conical flasks containing 100 mL of mixed liquor, was used to determine the effectiveness of cycloheximide for inhibiting the predators. Cycloheximide was added to two of the mixed liquors to reach final concentrations of either 100 mg/L or 200 mg/L and the movement of the sludge microorganisms was examined daily under a light microscope for 10 days. The reactors were kept aerated over the period that the mixed liquors were examined for inactivation of the organisms. This experiment was carried out over a similar period to  49  5: Materials and Method  that of the decay test in order to confirm that the organisms which were inactivated remained inactive over the complete test period.  Decay Rate Determination Decay rate determination followed the procedure described in subsection 5.3.1 with the reactors containing either mixed liquor that had been treated with cycloheximide for inactivation of the predators, or a control mixed liquor that had not been treated. Every day over the 10-day period, 1-L samples were withdrawn from each of the four 12-L reactors for nitrification rate measurements. Rates were determined from the NOx-N production method after addition of NH4Cl, as described previously. Samples of 30 mL volume were also taken daily from each of the 12-L reactors for measurement of NH4-N, and NOx-N concentrations. The samples were centrifuged for 3 - 4 minutes at 2000 rcf and the supernatant was filtered through a 0.45 m filter after which10 mL aliquots of the filtrate were preserved with 5% H2SO4 and 0.1% phenol mercuric acetate for NH4-N, and NOx-N determination respectively. This decay test was carried out on samples taken on Day 349 and Day 459, during which time the plant mixed liquor temperature averaged 18oC and 14oC respectively.  5.4  Molecular methods  5.4.1  Sample collection Approximately 50 ml of aerobic mixed liquor was collected from each train of the  pilot plant and transported to the laboratory on ice. Sample of 1.8 mL of volume was transferred to a 2-mL screw top tube and centrifuged at 16000 x g for 5 minutes. The supernatant was discarded and the solids were stored at -20oC until DNA extraction. Replicate samples were not collected since Monti (2006) showed that the pilot plant reactors behaved as completely mixed tanks and in addition gel images presented in Monti (2006) for three replicate samples showed identical bands in all replicate samples.  50  5: Materials and Method  It was therefore concluded that a single sample from the aeration tank would be representative of the reactor contents.  5.4.1.1  DNA extraction and quantification DNA extraction was carried out using the FastDNA® Spin Kit for soil (QBiogene  Mississauga, Ont. Canada). The extraction followed the manufacturer‘s protocol with deviations as noted: (i) the processing time in the FastPrep® instrument was increased from 30 seconds to 45 seconds, (ii) the mixing time for binding DNA to the matrix was increased from 2 minutes to 5 minutes and (iii) the settling time was increased from 3 minutes to 5 minutes. The DNA extracted from the process was examined by agarose gel electrophoresis under conditions of 80 V for 45 minutes and staining with ethidium bromide for visualization. The DNA extract was stored at -20oC until processing. A fluorometry method using Quant-iT™ PicoGreen® dsDNA Kit (Invitrogen) was used for quantification of the DNA extracted from the wastewater samples. The procedure used involved construction of a standard curve. Standards ranging from 10 to 1000 ng/mL DNA were prepared by serial dilution of lambda DNA provided with the kit. The picogreen fluorescent nucleic acid stain was diluted 1 in 200 with a 1X TE buffer and 50 L of the diluted picogreen solution were loaded onto a 96-well plate. 50 L of the standards and DNA samples diluted 1 in 500 were mixed into the picogreen solution and fluorescence of both standards and samples was measured using a Wallac VICTOR2 1420 Multilabeled Counter (Perkin Elmer) at 485 nm excitation and 535 nm emission.  5.4.1.2  PCR primers The primer set amo-1F (GGG GTT TCT ACT GGT GGT) and amo-2R (CCC CTC  KGS AAA GCC TTC TTC), specific to AOB belonging to the ß subclass of Proteobacteria, was used for PCR amplification of a fragment of the amoA functional gene (Rotthauwe et al., 1997). For amplification of the small subunit (SSU) fragment of the Nitrobacter 16S rRNA gene, the FGP872 (CTA AAA CTC AAA GGA ATT GA)  51  5: Materials and Method  forward primer plus the nitrifier-specific reverse primer FGPS1269‘ (TTT TTT GAG ATT TGC TAG) were used (Degrange and Bardin, 1995). For amplification of the Nitrospira 16S rRNA gene, the forward and reverse primers Eub338f (ACT CCT ACG GGA GGC AGC) and Ntspa685r (CGG GAA TTC CGC GCT C), respectively, were used (Amann et al., 1990; Regan et al., 2002).  5.4.2  Terminal restriction fragment length polymorphism fingerprinting  5.4.2.1  PCR The above PCR primers were labeled at the 5‘ end with fluorescent dyes for  terminal restriction fragment length polymorphism (T-RFLP) analysis. The forward primers were labeled with 6-FAM and the reverse primers, with HEX fluorescent dyes. The PCR reaction mix and thermal cycling conditions for amplification of the DNA were modified from those described by Siripong and Rittmann (2007b) and Degrange and Bardin (1995) and are summarized in Table 5-2.  Table 5-2  PCR Protocol  amoA  Target gene 16S rRNA Nitrobacter  16S rRNA Nitrospira  0.4 0.4 1x 200 2.5 2 1 50  0.2 0.2 1x 200 2.5 1 1 50  0.4 0.4 1x 200 2.5 1 1 50  PCR Mix FAM - Forward primer (M) HEX - Reverse primer (M) 10 x QIAGEN PCR buffer dNTPs (M) MgCl2 (mM) Qiagen Taq polymerase (U) DNA template diluted 10-fold (L) Total reaction volume (L)  Thermal profile Initial denaturing No of Cycles Denaturing Annealing Elongation Final elongation PCR amplicon length (bp)  o  5 min @ 95 C 30 o 40 sec @ 95 C o 90 sec @ 60 C o 90 sec @ 72 C o 10 min @ 72 C 491  o  5 min @ 95 C 35 o 60 sec @ 95 C o 60 sec @ 50 C o 60 sec @ 72 C o 10 min @ 72 C 389  o  5 min @ 95 C 35 o 90 sec @ 95 C o 30 sec @ 60 C o 90 sec @ 72 C o 10 min @ 72 C 343  52  5: Materials and Method  The PCR reaction was carried out using a PTC-200 Peltier thermal cycler (MJ Research). After the final elongation cycle, the reaction was cooled to 4oC and stored at -20oC. The product obtained was confirmed by electrophoresis on a 2% agarose gel under conditions of 80 V for 45 minutes and staining with ethidium bromide for visualization. A second conditioning PCR was carried out by using 5 L of product from the first PCR as template and using the same conditions, except a reduced primer concentration of 0.1 M and only 10 cycles.  5.4.2.2  Restriction enzyme digestion For the restriction enzyme digestion, 5 uL of the conditioning PCR product was  digested with 1 L (10 U) of HhaI (New England Biolabs) in the manufacturer‘s recommended buffer. The digestion reaction was done in a final volume of 20 L at 37oC for 5 h. Following the incubation, the enzyme was inactivated at 65oC for 20 minutes. The terminal restriction fragments (T-RFs) were then analyzed using capillary electrophoresis on an automated sequencer with the ROX500 internal size standard. The capillary electrophoresis was performed by the Nucleic Acid Protein Service Unit (NAPS) at UBC using Applied Biosystems instrumentation.  5.4.2.3  T-RF length analysis The DNA profiles from capillary electrophoresis were analyzed using  GeneMarker Version 1.70 software. T-RFs were manually binned according to size, defining operational taxonomic units (OTUs). A minimum peak intensity of 300 fluorescent units distinguished peak signal from noise and a cut off fragment size of 60 bp distinguished between T-RFs and primer dimers. The minimum peak intensity corresponds to 1% of the maximum detectable peak intensity and the minimum cut off for fragment size was selected based on the minimum size of the ROX500 internal standard used for sizing fragment lengths during the capillary electrophoresis analysis. A data matrix was prepared based on T-RF length and corresponding peak height. The peak height data were normalized with the total peak height for each sample. This was done in order to account for variability in intensity that could result from starting DNA  53  5: Materials and Method  template concentration, PCR amplification efficiency as well as variations in conditions during the capillary analysis for the individual samples. A multivariate analysis was performed with the normalized peak height data using PC-ORD software. The main matrix was constructed with rows (samples) and columns (OTUs) and the second matrix with sample rows and columns comprising both categorical and quantitative variables which included the process type, operating temperature, nitrification rate and sludge volume index. For DNA profiles, Richness, Eveness and Shanon Diversity Indices were calculated. Richness is equivalent to the total number of T-RFs per sample. Evenness (E) represents the proportional distribution of peak height and was calculated according to the equation E = H' / ln(richness). Shannon‘s index (H‘) gives information on the peak diversity per sample unit and was calculated from the equation s  H '   pi log pi i  where pi is the peak height and S is the number of non-zero elements per sample. These computations were executed using the PCORD 5 software. The non-metric multidimensional scaling (NMS) technique was used for ordination. Each NMS run was performed in the ‗Slow and Thorough‘ mode of PCORD with a Sorenson‘s (Bray–Curtis) dissimilarity distance matrix. One-way analysis of variance (ANOVA), multi-response permutation procedures (MRPP) and simple regression techniques were used to test the significance level between groups. ANOVA and MRPP were applied to the categorical variables whereas, simple regression was applied to the continuous variables. ANOVA and regression were done using Statistica 8.0, and MRPP, using PCORD 5. Indicator species analysis was used to compare the abundance of the OTUs present in the groups in order to assess which of the OTUs contribute to the observed differences.  54  5: Materials and Method  5.4.3  Quantitative PCR (qPCR) Real-time qPCR was done for an assessment of the AOB and NOB in the  membrane and conventional processes. qPCR is based on the detection of the fluorescence produced by a reporter molecule which increases, as the PCR reaction proceeds. qPCR therefore monitors the fluorescence emitted during the reaction as an indicator of amplicon production at each PCR cycle. For this study, the SYBR® Green dye was used for fluorescence. This dye has negligible fluorescence in the absence of double stranded DNA (dsDNA) but fluorescence is increased upon binding to dsDNA. As more PCR product is formed, more SYBR® Green binds to the PCR product, resulting in an increased fluorescence. Consequently, during each subsequent PCR cycle more fluorescence signal is detected. One of the disadvantages of SYBR® Green is that it binds to all dsDNA and thus any non-specific products formed in the PCR reaction would contribute to the fluorescent signal.  5.4.3.1  qPCR assay The PCR assays (Table 5-3) were performed on a Stratagene Mx3000P thermal  cycler. DNA extracts were diluted 10-fold, and 1 L of the diluted DNA was used as template in all reactions. In all experiment sets, negative controls containing distilled deionized water with no template DNA were subjected to the same procedure to detect any possible contamination. Melting curve analysis was performed to verify that the fluorescent signal obtained in the qPCR assay originated from specific PCR products and not from nonspecific reaction products or artifacts such as primer dimers. The melt curve cycle followed the final PCR amplification cycle with continuous monitoring of fluorescence during the temperature transition.  55  5: Materials and Method  Table 5-3  Real Time qPCR Assay Details amoA  Nitrobacter  Nitrospira  1x 0.5 0.5 1 20  1x 0.5 0.5 1 20  1x 0.5 0.5 1 20  PCR Mix iQSYBRGreen supermix (mM) Forward primer (M) Reverse primer (M) DNA template (L) ddH2O for total reaction volume (L)  Thermal profile Initial denaturing No of Cycles Denaturing Annealing Elongation  5.4.3.2  o  5 mins @ 95 C 30 o 40 sec @ 95 C o 30 sec @ 60 C o  90 sec @ 72 C  o  5 mins @ 95 C 35 o 60 sec @ 95 C o 60 sec @ 50 C o  60 sec @ 72 C  o  5 mins @ 95 C 35 o 40 sec @ 95 C o 30 sec @ 60 C o  90 sec @ 72 C  Standard curve for real time PCR Plasmid DNA containing cloned PCR products were used as standards for  quantification of the bacteria. The cloning procedure is described in subsection 5.4.3.3. Ten-fold serial dilutions of the plasmid DNA, ranging from 102 to 1010 were used as template in the PCR reactions. These serial dilutions of the plasmid were run in triplicates together with the samples and a data set obtained for the standard templates is shown in the Figure 5-4. The data is presented for the 16S rRNA Nitrospira only as a typical data set. Similar plots were obtained for the amoA and 16S rRNA Nitrobacter. Figure (a) shows the amplification plots for each of the serial dilutions which ranged from 102 to 109. The amplification plot gives the relation of fluorescence intensity with PCR cycle and is usually defined by a baseline, exponential phase and a plateau. Figure (b) shows the log transformation of the amplification plot from which the threshold cycle (Ct) was obtained as the point of intersection between the amplification plot and the threshold fluorescence value. The threshold fluorescence is above the baseline, in the exponential phase and usually falls within the linear portion of the log transformed amplified curve. The standard curve generated is shown in figure (c) as a plot of Ct vs. log of copy number. The copy number for the templates was calculated from the  56  5: Materials and Method  concentration of the extracted plasmid DNA determined from spectrophotometer measurement at 260 and the following equation for copy number:  Copy number = =  (g/mol) / Avogadro‘s Number (bp size of plasmid + insert) (330Da x 2 nucleotide/bp) 6.022 x 1023  The construction of the standard curves from the amplification data, as well as linear regression analysis was performed with MxPro Version 3.2 software.  57  5: Materials and Method  45000  (a)  40000  35000  Fluorescence (dR) Fluorescence (dR)  30000 25000 20000 102 103 104  15000  10000  105  106  107  108  109  Threshold  5000 0 -5000 0  5  10  15  20  25  30  35  40  35  40  Cycles 100000  (b) Threshold  Fluorescence (dR) Fluorescence (dR)  10000  1000  102 103  100  104  105  106 107  108  109  10  1 0  5  10  15  20  25  30  Cycles 40 Slope = -3.4926 R2 = 0.9933  (c) 35 30  Ct  Ct  25 20 15 10 5 0 0  1  2  3  4  5  6  7  8  9  Log copy number  Figure 5-4  Real time PCR data for 16S rRNA Nitrospira plasmid DNA used for generating standard curve (Run 090826)  58  5: Materials and Method  5.4.3.3  Cloning and sequencing Amplified amoA genes from the wastewater sample were ligated into the  ®  pCR 2.1-TOPO® plasmid vector and cloned in Escherichia coli TOP10 cells, using the TOPO-TA cloning vector kit (Invitrogen) according to manufacturer‘s instructions. White colonies picked at random were screened for inserts of the proper size by PCR amplification of the inserts with amoA primers. The inserts were cultured and the plasmid was purified with Quantum Prep® Plasmid Miniprep (BIORAD) kit according to manufacturer‘s  instructions.  The  purified  plasmid  DNA  was  quantified  with  spectrophotometry at 260  using a NanoDrop® ND-1000 spectrophotometer (Nanodrop Technologies). This cloning procedure was repeated for the 16S rRNA genes of Nitrospira and Nitrobacter. Each of the cloned genes was sequenced at Nucleic Acid Protein Service (NAPS). The obtained sequences for amoA and the 16S rRNA genes were subjected to Basic Local Alignment Search Tool (BLAST) search in the National Centre for Biotechnology  Information  (http://www.ncbi.nlm.nih.gov/)  (NCBI) and  the  GenBank Ribosomal  nucleotide Database  Project  database (RDP)  (http://rdp.cme.msu.edu/), respectively, to confirm that all sequenced clones represented the targeted sequences.  59  6: Results and Discussion  6  Results and Discussion  6.1  Pilot plant process performance Over the period of the investigation, a daily routine for pilot plant operation and a  reactor sampling plan were established. This allowed for monitoring the pilot plant processes, in order to determine the performance of the plant in treating the wastewater and also to ensure that conditions which could limit the nitrification process were avoided. The plant was operated at a nominal SRT of 12 days, HRT of 10 hours and with anoxic, aerobic and RAS recycle ratios to flow of 100%, over the entire duration of the investigation. The operating conditions and process performance of the UBC pilot plant membrane and conventional trains were compared with focus on those parameters which are known to influence the nitrification process. The results presented in this subsection are based on monitoring data collected over a plant operation period of 472 days.  6.1.1  Reactor influent characteristics The pilot plant received its wastewater from two residential developments on the  UBC campus. The characteristics of the wastewater were typical of a medium strength domestic wastewater with respect to the nutrient concentration (Tchobanoglous et al., 2003). The characteristics of the primary effluent / bioreactor influent are shown in Table 6-1. The wastewater characteristics were monitored on both weekdays and weekends and no significant variations with day of the week were evident. Time series plots of the influent parameters are presented together with final effluent concentrations in the figures included in subsection 6.1.4.  60  6: Results and Discussion  Table 6-1  Reactor influent characteristics  Parameter  Units  CODtotal CODfiltered TKN NH4-N NOx-N TP PO4-P pH  mg/L mg/L mg N/L mg N/L mg N/L mg P/L mg P/L -  Average  Min  Max  314 188 47.0 36.4 0.03 6.0 2.5 7.3  146 69 31.3 18.6 * 3.3 0.3 6.6  663 303 82.4 50.9 0.34 10.3 6.8 7.8  * Below detection limit  6.1.2  6.1.2.1  Aerobic reactor characteristics  pH, temperature and dissolved oxygen The pH, temperature and dissolved oxygen (DO) concentrations in the aerobic  reactors were monitored daily. The time series plots of these parameters are shown in Figure 6-1. To maintain a stable aerobic zone pH near 7.0, sodium bicarbonate was added once per day to the raw sewage storage tanks which provided influent feed to the primary clarifier and which also served as equalization basins for the incoming raw wastewater. The process temperature was not controlled and the variation observed was reflective of the changing seasons. The temperature ranged between a minimum and maximum of 13oC and 24oC respectively. DO was manually controlled and was targeted for operation between 2.5 – 3.0 mg/L. There were a few instances, particularly for the membrane reactor, where DO concentration was significantly higher or lower than the targeted concentration. This was a consequence of the manual method for controlling the reactor DO and a few aeration system mechanical failures.  61  6: Results and Discussion  9.0 Influent  8.5  Membrane  Conventional  8.0  pH  pH  7.5 7.0 6.5 6.0 5.5 5.0 0  50  100  150  200  250  300  350  400  450  500  350  400  450  500  Days in Days inOperation Operation 25 Membrane  Conventional  o  Temperature C) Temperature((oC)  23 20 18 15 13 10 0  50  100  150  200  250  300  Days in Operation  Days in Operation  10.0 Membrane  Conventional  (mg/L) (mg/L) DODO  8.0  6.0  4.0  2.0  0.0 0  50  100  150  200  250  300  350  400  450  500  Days in in Operation Operation Days  Figure 6-1  Time series plots of pH, temperature and DO in the aerobic zones  62  6: Results and Discussion  Correlations between the membrane EBPR and conventional EBPR processes are given in the Figure 6-2 for pH and DO. Each data point shown on the graph represents the pH or DO taken at the same time for the two processes. The pH or DO for the membrane process is given along the x-axis and the corresponding value for the conventional process is given along the y-axis. As seen from the figure for the pH data, almost all of the points lie along the diagonal line and hence for most instances during the plant operation, the pH values of the two aerobic reactors were comparable. Operational values ranged between 6.6 and 7.8 and averaged 7.3 and therefore, the pHs maintained in the aerobic reactors were generally suitable for nitrification to occur. Literature indicates an optimal pH of between 7.2 and 8.0 for nitrification and that pH  8.5  6.0  8.0  5.0  Conventional DO (mg/L)  Conventional pH  values below 6.5 and above 10 limit nitrification activity (Gerardi, 2002).  7.5 7.0 6.5 6.0 5.5  4.0 3.0 2.0 1.0 0.0  5.5  6.0  6.5  7.0  7.5  8.0  8.5  0.0  1.0  Membrane pH  (a) pH  Figure 6-2  2.0 3.0 4.0 Membrane DO (mg/L)  5.0  6.0  (b) DO  Correlation of the pH and DO for the membrane EBPR and conventional EBPR processes  For the dissolved oxygen concentration, there was some discrepancy between the two reactors. The DO was manually controlled by increasing or decreasing air flow in response to the DO level reading from a portable DO meter. DO was monitored once per day and overcompensating for changes would have resulted in fluctuations. Except for a few instances, particularly in the membrane reactor where DO concentration fell below 2.0 mg/L, the DO concentrations in each aerobic reactor were well above the concentration at which nitrification is inhibited. Reported values for the limiting DO for the 63  6: Results and Discussion  process are variable and have been indicated in literature to range from 0.5 - 4.0 mg/L (Stenstrom and Song, 1991). It is generally accepted, however, that nitrification is not limited at DO greater than 2.0 mg/L (Water Environment Federation, 2005).  6.1.2.2  Floc structure and particle size It is well documented that there are differences in membrane and conventional  processes floc particle size (Cicek et al., 1999; Luxmy et al., 2000b; Gao et al., 2004a; Holbrook et al., 2005; Sperandio et al., 2005; Geng and Hall, 2007). Particle size measurements made during the present investigation concur with those literature reports which indicate that the membrane floc is smaller than the conventional floc. The typical floc size distribution for the two processes is given in Figure 6-3. 12 C_07-10-26  M_07-10-26  C_08-12-08  M_08-12-08  10  (%) Volume(%) Volume  8  6  4  2  0 0.01  0.1  1  10  100  1000  10000  Particle size Particle size(m) (m)  Figure 6-3  Comparison of particle size distribution for the membrane (M) process and conventional (C) process floc at the start (samples 07-10-26) and end (samples 08-12-08) of the investigation  The figure compares the particle size distribution for each mixed liquor type at the start of the investigation (samples 07-10-26) and towards the end (samples 64  6: Results and Discussion  08-12-08). Floc sizes were identical at the start because the mixed liquors in both trains had been cross-mixed. Floc size measurements showed a difference between the two floc sizes occurring within just a few days after changeover from a membrane process to a conventional process, indicating a short transition period, less than one SRT, from membrane process floc size to a conventional process floc size. The smaller floc size for the membrane mixed liquor has been attributed to floc breakup resulting from the shearing action associated with the vigorous coarse bubble aeration of the process. A measure of turbulence in an aerated tank is given by the root mean square velocity gradient (Das et al., 1993) and is defined as follows:  G  Qair H w V  where G  = root mean square velocity (s-1),  Qair  = air flow rate (m3/s),  H  = depth of water column (m)  w  = specific weight of sludge (N/m3)  V  = reactor volume (m3)    = viscosity of sludge (Pa·s)  Das et al. (1993) found that floc breakup was related to the degree of turbulence in an aeration basin with greater floc breakup occurring with increasing G values. Assuming similar properties for viscosity and specific weight of sludge for both processes, the G value then becomes proportional to the square root of the air flow rate. The air flow rates applied to the membrane and conventional trains were approximately 0.34 m3/min (12 scfm) and 0.085 m3/min (3 scfm) respectively. Since the oxygen transfer efficiency of a fine-bubble system (conventional train) is greater than that for a coarse-bubble system (membrane train), the airflow rate required for the coarse-bubble aeration system was greater than that required for the fine-bubble system to achieve the same oxygen transfer rate. Hence, the turbulence in the membrane EBPR process was two times (√12 / √3) greater than for the conventional EBPR process. The greater turbulence in the membrane process would therefore cause more floc break up resulting in smaller particles. Particle size measurements of samples of the conventional mixed liquor that 65  6: Results and Discussion  were subjected to coarse bubble aeration showed a smaller floc size compared to the mixed liquor under fine bubble aeration, thus validating the relation between the vigorous aeration and particle size. These measurements were carried out together with the decay rate measurements as described in section 5.3.1. Samples of the conventional mixed liquor were taken from the 12-L laboratory decay reactors after the first day of aerating with fine and coarse bubble aeration and particle size was measured. The results of these measurements are given in Table 6-2. Similar results have been reported by others (Merlo et al., 2007; Menniti and Morgenroth, 2010) who also concluded that coarse bubble aeration was a dominant factor affecting the particle size in a membrane bioreactor.  Table 6-2  Change in mean particle size of conventional mixed liquor resulting from coarse bubble aeration Conventional mixed liquor mean particle size (m) Coarse bubble aeration Fine bubble aeration Experiment 1  118  177  Experiment 2  117  146  117.5 (0.5)  161.5 (15.5)  Average  Number in parenthesis represents the standard deviation  At the pilot plant, there were no significant changes in the floc size with operational time of the reactors following the transition from a membrane mixed liquor to a conventional mixed liquor. The membrane process floc remained constantly smaller than conventional process floc as shown in Figure 6-4. The membrane EBPR process and conventional EBPR process floc diameters averaged 63 m (Std dev 18, n=9) and 128 m (Std dev 40, n=9) respectively based on the volume weighted mean diameter (D4,3) and were statistically different (p < 0.01) based on a paired t-test. These values are similar to those reported for a previous study at the UBC pilot plant (Geng and Hall, 2007). Average diameters ranging from 20 – 40 m for the MBR and 20 – 120 m for the CAS have been reported (Zhang et al., 1997; Cicek et al., 1999; Gao et al., 2004a; Manser et al., 2005a; Ng et al., 2006).  66  6: Results and Discussion  180 Membrane  Mean floc size (m)  Mean floc size (m)  160  Conventional  140 120 100 80  60 40 20 0  3  10  13  16  21  23  28  29 406 412 419 441 443 479  Time (day) Time (day)  Figure 6-4  Mean floc size in membrane and conventional processes  In addition to the floc size, there were observable differences between the two flocs with respect to floc structure. As seen from the images in Figure 6-5, the conventional process floc appeared large and compact compared to that in the membrane process, which showed a dispersed microfloc. There was also a notable difference in the number of filaments present. The filamentous organisms were visibly more abundant within the membrane process floc as compared to the conventional process floc. Similar observations regarding abundance of filamentous organisms have been reported by others (Cicek et al., 1999; Witzig et al., 2002). The abundance of filaments in the conventional process mixed liquor tended to vary, despite maintaining constant SRT and other operating conditions. From routine microscopic examination, filament abundance could be correlated to the presence of nematodes. A notable reduction in the amount of filamentous bacteria was observed during periods when worm infestations occurred and this was thought to be caused by grazing of the worms on the filamentous bacteria. The presence of filaments is usually associated with poor settling sludge and in the present study, the appearance and disappearance of worms and consequent changes in abundance of filaments resulted in variation of sludge volume index (SVI). This is discussed further in subsection 6.1.3.4.  67  6: Results and Discussion  (a) Membrane Floc  Figure 6-5  6.1.2.3  (b) Conventional Floc  Structure of membrane process and conventional process floc (Day 326)  Sludge microorganisms Microscopic examination of the aerobic mixed liquor from both processes  revealed that each process was supporting different microorganisms. In addition, it was observed that, for the conventional process, there were changes in the microorganisms present over the duration of the investigation. Some of the microorganisms observed at different periods of the study are shown in Figure 6-6. Noticeable differences between the two processes were (i) that stalked ciliates were more abundant in the conventional mixed liquor as compared to the membrane mixed liquor in which free swimming ciliates and filamentous bacteria were dominant and (ii) the absence of rotifers and nematodes in the membrane mixed liquor. The rotifers and nematodes were, however, observed periodically in the conventional mixed liquor. The observations on the abundance of free swimming ciliates and filamentous bacteria in the membrane process mixed liquor relative to the conventional process mixed liquor are in agreement with previous reports (Cicek et al., 1999; Luxmy et al., 2000b). These have been attributed to the readily available particulate food source (prey) for the free swimming organisms and the selection of microorganisms which are not essential for good sludge settleability. An abundance of filamentous bacteria usually  68  6: Results and Discussion  100 m Vorticella Stalked ciliate found in both mixed liquors Magnification x 20  Carchesium Stalked ciliate observed in conventional mixed liquor only Magnification x 20  Rotifer seen in conventional mixed liquor only Magnification x 20  Filamentous bacteria more abundant in membrane process Magnification x 20  100 m  Aspidisca Crawling ciliate seen in both mixed liquors Magnification x 20  Figure 6-6  500 m  Oligocheate Nematode noted in conventional mixed liquor only Magnification x 40  Sludge microorganisms observed in the membrane EBPR and conventional EBPR aerobic mixed liquors 69  6: Results and Discussion  results in a mixed liquor with poor settleabilty. The nature of the membrane process is such that it does not necessitate a mixed liquor with good settling properties since solidsliquid separation is achieved by filtration. The SVI measured for the processes correlated with the observation of the filamentous bacteria. SVI data are presented and discussed further in subsection 6.1.3.4. The absence of the higher organisms in the membrane mixed liquor noted here, is in contrast to studies by Luxmy et al. (2000b) and Ghyoot and Verstraete (2000) in which rotifers and nematodes were observed, but is in agreement with studies by others (Cicek et al., 1999; Witzig et al., 2002; Wei et al., 2003). The absence of the higher organisms in the membrane mixed liquor was possibly due to the turbulent conditions that existed in the membrane system. The turbulent conditions, which are caused by the vigorous course bubble aeration, probably results in an unsuitable environment for these organisms. There has been report of a relationship between MBRs shear conditions and the presence of predators, whereby worms proliferate in low shear environment but were absent under high shear conditions in MBRs (Menniti and Morgenroth, 2010). In the present study, although nematodes were absent from the suspended solids portion of the membrane process, they were observed at times when the membranes were removed for cleaning, attached to the lower portion of the membrane fibers. The lower portions of the membrane fiber are known to be less disturbed by rising air bubbles (Bérubé et al., 2006). The membrane fibers probably provided a suitable niche for the attachment and growth of the worms. The red worms are a common phenomenon of fixed film systems and carriers have been introduced into continuous suspended growth activated sludge processes as a means to support worm populations (Hendrickx et al., 2009b).  6.1.3  Process suspended solids The conventional train of the pilot plant was operated with the RAS from the  secondary clarifier returning to the aerobic zone in an attempt to maintain a similar biomass distribution to that of the membrane process. In the membrane process all of the suspended solids are retained in the aerobic zone by solids-liquid separation using the membrane module. Despite the similarity of operation, the membrane process 70  6: Results and Discussion  operated with a higher overall system biomass concentration compared to the conventional process biomass concentration (i.e. anaerobic, anoxic and aerobic biomass). This resulted from the concentration of solids in the aerobic zone as a result of the filtration process and the recycling of the concentrated stream throughout the reactors (Ramphao et al., 2005). The difference in biomass concentration was also a consequence of the suspended solids contained in the clarifier. These are discussed further in subsection 6.1.3.2. Another difference observed between both membrane EBPR and conventional EBPR processes was the presence of foam in the membrane EBPR process. A thick blanket of foam was always present in the anoxic reactor of the membrane process, covering the entire surface area of the reactor. The foam was observed in the anaerobic and aerobic reactors at some times, but in notably lower amounts. In the case of the aerobic reactor it occupied approximately 50% of the reactor surface area. The foam appeared thickened and dark brown in color in the anoxic and anaerobic zones, but was light brown and less concentrated in the aerobic zone. The foam was not removed from the system, but was re-suspended by a combination of stirring with a mechanical mixer and hosing with water during the routine plant housekeeping. This folding in of the foam was done after the daily sludge wasting was complete, since the foam was not included in SRT calculations.  6.1.3.1  Foam quantification Quantification of the foam in the anoxic zone was undertaken during the winter  (Day 161) and the summer (Day 308). During these two seasons, there was a noticeable difference in the amount of foaming in the membrane train anoxic reactor. For quantification, the foam was removed from the reactors, weighed and thoroughly mixed to obtain a representative sample for analysis of total solids. After mixing, three samples of the foam were taken and a total solids determination was done in duplicate on each of the samples. The results were averaged and are presented in the Table 6-3.  71  6: Results and Discussion  Table 6-3  Foam quantification in the membrane process reactors  Reactor  Dry Mass (kg)*  Anaerobic Anoxic Aerobic Total  Winter 0.03 0.83 0.07 0.93  Summer 0.06 1.72 0.07 1.86  % TS by weight ** Winter 3.5 (0.02) 4.4 (0.02) 2.1 (0.04)  % TVS by weight **  Summer 3.7 (0.09) 4.3 (0.09) 2.5 (0.02)  Winter 84.5 (0.06) 84.1 (0.17) 83.7 (0.64)  Number in parentheses represents standard deviation *n=1  ** n = 2  TS = Total solids  TVS = Total volatile solids  The measured masses of the foam solids were in agreement with the visual observation that the amount of foam appeared to be greater during the summer than in the winter. There was a greater mass of foam during the warmer summer period and the anoxic foam was thickened to a 4% solids concentration. This value is in close agreement with the findings of the study by Monti (2006) who reported 4 - 6% solids content for the anoxic foam. The contribution of the foam to the system TSS inventory was also determined. This was done by measurement of TSS before and after mixing of the foam into the respective reactors. A comparison of the TSS including and excluding the foam solids showed that there was negligible increase in the aerobic and anaerobic zone solids but a 35% increase in the anoxic zone suspended solids. The total solids mass increased by approximately 6% when the foam was considered. Monti (2006) indicated that foam contributed approximately 8% to the solids inventory for a membrane EBPR system. The effect of the foam management on SRT from an operational perspective showed that there was an SRT difference of 1 day when the foam solids were included. The SRT in the membrane EBPR process was calculated at 12 days without mixing in foam and 13 days with foam re-suspended. Throughout the study, the daily wasting rate was determined from TSS measurements before mixing in the foam. Consistency in plant routine operations was therefore ensured to eliminate differences that could arise from foam management. Elimination of foam in the calculation of sludge wasting rate can be justified as most of the foam did not remain suspended in the bulk liquid for any extended period. The time that the foam remained in the system was determined by measuring the TSS 72  6: Results and Discussion  before mixing in the foam and then at hourly intervals after foam re-suspension. The results, as shown in Figure 6-7, indicated that approximately 50% of the foam solids in the anoxic reactor resurfaced within 1 hour after being mixed into the reactor. 12  6000 Membrane system 5000 Membrane anoxic reactor  8 6  4000 3000  Conventional system  4  2000  2  1000 Membrane  Conventional  Anoxic- Membrane  0  0 -2  Figure 6-7  6.1.3.2  Anoxic Reactor TSS (mg/L)  System Solids (kg)  10  -1  Before mixing  0  Just after mixing  1  2 3 Time (h)  4  5  6  7  Changes in system biomass and anoxic reactor TSS concentration at hourly intervals after foam re-suspension  Suspended solids distribution A comparison of the suspended solids concentrations in the three reactor zones  (Ana = anaerobic; Ano = anoxic; Aer = aerobic) for each of the processes as well as the clarifier (Cla) is shown in Figure 6-8 (a), (b) and (c). The data presented for the clarifier represent the TSS concentrations after mixing the clarifier. The box plot of Figure 6-8 (a) presents the statistical evaluation of the TSS data collected over the 472 days in operation for each reactor. Figure 6-8 (b) shows the correlation of the reactor suspended solids between both processes. Figure 6-8 (c) gives the contribution of suspended solids from each reactor to the total system suspended solids mass expressed as a percentage of total solids (TSS). From Figure 6-8 (a) and Figure 6-8 (b) it is evident that for the two processes, the highest concentration of suspended solids was in the aerobic zone and the lowest in the  73  6: Results and Discussion  8000  (a)  max  TSS (mg/L) Conventional TSS (mg/L) TSS (mg/L)  7000 6000 5000 4000 3000  3rd quartile median 1st quartile min  2000 1000 0 Ana-M  Ano-M  Aer-M  Ana-C  Ano-C  Aer-C  Clar  Eff-C  6000  (b) Conventional TSS (mg/L)  5000  4000  3000  2000  Anaerobic Anoxic Aerobic  1000  0  0  1000  2000  3000  4000  5000  6000  Membrane TSS (mg/L) Membrane TSS (mg/L) 80%  70%  72%  (c)  69%  % TSS % TSS  60% 50% 40%  30%  23%  20%  16% 11%  10%  5%  3%  0% Ana-M  Figure 6-8  Ano-M  Aer-M  Ana-C  Ano-C  Aer-C  Cla  Distribution of total suspended solids in the membrane (M) and conventional (C) processes 74  6: Results and Discussion  anaerobic zone. In addition, the membrane EBPR process generally carried higher TSS concentrations than the conventional EBPR process. The higher TSS in the membrane process could be attributed to the concentration of solids in the aerobic zone as a result of the filtration process and the recycling of the concentrated stream throughout the reactors (Ramphao et al., 2005). From Figure 6-8(c), it can be seen that there was a difference in the suspended solids fractions distribution in the two processes. The difference in suspended solids distribution observed for the two processes arises from the suspended solids contained in the clarifier. In the conventional EBPR process, 89% of the suspended solids were held in the three bioreactors and the remaining 11% in the clarifier, whereas for the membrane EBPR process, all of the suspended solids were contained within the three bioreactors. The difference was greatest for the anoxic zones for which the suspended solids fractions averaged 23% and 16% for the membrane process and conventional process respectively. The solids fraction was calculated using TSS concentration from the reactors before the anoxic foam was re-suspended into the tank and therefore the difference cannot be attributed solely to the foam fraction. As a consequence of the suspended solids distribution in the three reactors (i.e. anaerobic, anoxic and aerobic only), there were small differences in the SRT with the conventional EBPR process operating at 10.6 d compared to the membrane EBPR process at 12 d. If the retention time of the solids in the clarifier is included, however, overall SRT would be 12 d. Individual SRTs for the membrane EBPR and conventional EBPR process reactors were as indicated in Table 6-4.  Table 6-4  Operating SRTs for the individual processes in the membrane and conventional reactors Membrane Reactor  Conventional Reactor  Anaerobic SRT:  0.60 d  0.36 d  Anoxic SRT:  2.76 d  1.92 d  Aerobic SRT:  8.64 d  8.28 d  12 d  10.56 d  Note: SRTs shown for conventional reactor does not include clarifier SS  75  6: Results and Discussion  Aerobic SRTs for the nitrification process were similar for both processes. The differences observed in anaerobic and anoxic SRTs could have affected the biological phosphorus removal and denitrification performances of the processes. For an effective EBPR process, a minimum anaerobic SRT of 0.5 d at 20oC is recommended if the influent concentrations of VFA and readily available organic matter are sufficiently high (Grady et al., 1999). Also, a combined anaerobic and anoxic SRT of 2 - 3 d is a desired minimum for the denitrification process (Grady et al., 1999). The anaerobic SRT for the conventional process was below the recommended value for EBPR and was just within the minimum SRT for denitrification. Notwithstanding the fact that both processes were being operated under similar conditions and treating the same influent, there were periods during the study in which there was a notable difference in TSS between the two processes. This is illustrated in Figure 6-9 which shows the time series plot of TSS mass for the membrane process and conventional process as well as the % difference between the two processes. The total suspended solids inventory shown for the conventional process includes the suspended solids in the clarifier. 10  100% Conventional  8  80%  6  60%  4  40%  2  20%  0  0%  0  50  100  150  200  250  300  350  400  450  % Difference %Difference  (kg) TSS(kg) TSS  Membrane  500  Day in Operation  Figure 6-9  Comparison of total suspended solids mass in membrane and conventional processes The vertical bars represent the % difference relative to the membrane process % = (M-C)/M  76  6: Results and Discussion  During the investigation, differences in TSS between the two processes ranged from 0.4% to 46%. The relatively low TSS in the conventional system, observed between days 100 - 250 and days 300 - 400, could not be attributed to overestimation of sludge wasting or unintentional wasting from solids lost in the effluent, as the process suspended solids inventory was carefully estimated when the occurrence was first observed. Suspended solids loss per day was estimated at 0.16 kg/d based on an average effluent TSS of 30 mg/L and a flow rate of 3.7 L/min and this was not sufficient to account for the difference, which reached a maximum value of 3.7 kg TSS at day 240. The TSS reduction could, however, have been a consequence of a worm infestation. Small red worms, identified as belonging to the oligochaete group were visible in abundance in the clarifier and aerobic reactors of the conventional process, whereas they were absent in the mixed liquor of the membrane process. The absence of worms in the membrane process is in accordance with the findings of Cicek et al. (1999) who also observed high concentrations of nematodes in activated sludge and almost none in a membrane system. It also agrees with the conclusions by Wei et al. (2003) that a CAS system tended to support worm growth better than an MBR, since an MBR system was not able to sustain the growth of worms that were deliberately introduced into the system. The worms that were present in the conventional system of the present study are shown in Figure 6-10. The worm infestation was first observed around day 150 by the reddened appearance of the mixed liquor when left in the batch reactor. This first observation was made towards the start of the spring season when temperatures were averaging 15oC (Std dev = 1). Hendrickx et al. (2009a) investigated effects of operational parameters on worms for sludge reduction and reported that the highest sludge consumption rates were measured at a temperature around 15°C and at higher temperatures of 25oC, worm survival decreased. Following this initial observation, there was a series of plant upsets whereby the DO level in the process was reduced to and remained at 0 mg/L throughout overnight periods. The exact length of the non-aerated period during each upset was uncertain, as plant DO data were not continuously logged. The worms were, however, still present in the process after these periods of anoxia, but did not appear in the abundance to cause the red coloration previously observed in the reactor. Unfortunately, the worms were not quantified at the time the infestation was first observed. Quantification was, however, 77  6: Results and Discussion  undertaken at a later time by dispersing 1 mL of the mixed liquor in distilled water, vacuum filtering onto a gridded filter and counting the red bodies under a stereo microscope. This count was done on triplicate filters and the average of the counts was determined. By day 225 the worm density was 25 worms/ mL mixed liquor.  Magnification x 40  Figure 6-10  Magnification x 100  Oligochaetes observed in conventional mixed liquor (Day 165)  An aeration compressor failure on Day 252 again caused the systems to be without oxygen for an estimated 24 hours. A temporary aeration system was unable to supply all of the required oxygen and as a consequence, both pilot trains were operated at reduced oxygen concentrations. The worms subsequently disappeared from the process, but were noted to reappear on Day 297. During the period in which the worms were absent from the system, it was observed that there was a smaller difference in biomass concentration between the membrane EBPR and the conventional EBPR processes. The disappearance of the worms from the process was attributed to the low oxygen concentration, however, the sudden appearance and disappearance of worms is a phenomenon that has been frequently observed, but for which there is no known explanation (Wei et al., 2003). Food quality, temperature and oxygen concentration tend to determine the ultimate presence of the organisms in an activated sludge plant (Ratsak et al., 1993). It has been reported that at oxygen concentrations of 1 mg/L, worm counts decrease (Hendrickx et al., 2009a) and thus low oxygen is used as a means for control  78  6: Results and Discussion  of worm growth in fixed film systems. There is also tendency for the worms to proliferate in systems with high protein content and smaller floc particles (Liang et al., 2006).  6.1.3.3  Sludge yield The sludge yield was subsequently determined for both the membrane and the  conventional system in light of the differences in biomass inventory observed. The yield was calculated for the period up to Day 145 from the total mass of suspended solids removed via wasting and the total mass of influent total COD removed. The mass of suspended solids wasted for the processes were determined from the following equations. For the membrane process, Mass of SS wasted (kg) =  Wasting Rate (L/d) x Aerobic TSS (mg/L) / 1 000 000  For the conventional process, Mass of SS wasted (kg) =  Wasting Rate (L/d) x Aerobic TSS (mg/L) / 1 000 000 + Effluent SS (mg/L) x Influent Flow (L/d)  The plots of the daily mass of influent COD removed and the daily mass of the suspended solids wasted together with the respective cumulative mass are shown in Figure 6-11. The yields were determined as the slope of the plot of cumulative mass of SS wasted against cumulative mass of COD removed. For the period considered, the yields for the membrane EBPR and conventional EBPR process were 0.43 kg TSS / kg COD removed and 0.38 kg TSS / kg COD removed, respectively. The lower yield for the conventional EBPR process is possibly the result of the grazing of the worms. The presence of worms has been correlated to lower sludge yields in a study by Wei et al. (2003) who compared the yields in CAS and MBR systems. This reduced sludge yield associated with the activity of worms is being investigated as a biological approach to sludge processing (Ghyoot and Verstraete, 2000; Elissen et al., 2006).  79  6: Results and Discussion  300 Daily mass Daily mass-- M M  Daily C Dailymass mass -- C  Cummulative mass Cumulative mass - M- M  Cummulative mass Cumulative mass - C- C  250  4  M C  200  3 150 2 100 1  50  0  removed of COD Cumulative mass massCOD removed Cummulative  (kg/d) removed(kg/d) CODremoved massofofCOD Dailymass Daily  5  0  0  20  40  60  80  100  120  140  160  Day in Operation 125  2.5  Daily -M Dailymas mass -M  Dailymass mass -- CC Daily  Cummulative mass Cumulative mass - M- M  Cummulative mass Cumulative mass -C-C 100  M 2.0 75  C 1.5  50 1.0 25  0.5  0.0  wasted Cumulative wasted SSSS massof Cummulativemass  ofwasted massSS Daily SS wasted (kg/d)(kg/d) Daily mass  3.0  0  0  20  40  60  80  100  120  140  160  (kg TSS) ofwasted Cumulative mass massSS SS wasted (kg/TSS) Cummulative  Day in Operation 125.0 Cummulative -M-M Cumulative mass  Cumulative mass Cummulative -C -C y = 0.4263x - 5.6009 R2 = 0.9985  100.0  M 75.0  C  50.0  y = 0.3826x - 5.837 R2 = 0.9972  25.0  0.0  0  50  100  150  200  250  Cummulative mass COD removed removed(kg (kgCOD) COD) Cumulative mass of COD  Figure 6-11  Sludge yield determination from plant operational data (day 0 to 160)  80  6: Results and Discussion  The reduced yield for the conventional EBPR process, relative to the membrane EBPR process, is contradictory to the findings of the previous study by Monti (2006) who reported that the yield for the membrane EBPR ranged from 0.23 – 0.28 g VSS / g COD and was 15% lower compared to the conventional EBPR yield which ranged from 0.25 – 0.31 g VSS / g COD. This difference in yields between the two studies may, therefore, be indicative of differences in mixed liquor microorganisms, particularly worms, for the two studies. There were no reports of worms in the previous study. There are inconsistent results from studies comparing yield coefficients for membrane bioreactor processes and conventional processes. Yield coefficients estimated for membrane processes have been reported to correlate well with conventional activated sludge data (Macomber et al., 2005; Masse et al., 2006; Lee et al., 2009). Ghyooot and Verstraete (2000) reported 20-30% lower yields in an MBR as compared to a CAS and attributed the lower yield in the MBR to the presence of greater quantities of protozoa. Higher yield coefficients in MBR as compared to CAS systems have also been reported (Cicek et al., 1999; Holbrook et al., 2005; Ramphao et al., 2005; du Toit et al., 2007). The higher biomass yield in an MBR compared to a conventional system was attributed to the lower protozoa presence in the membrane system (Cicek et al., 1999). In the study by Cicek et al. (1999), nematodes were also observed in the conventional process, but were absent in the membrane process. It is noted that although the literature indicates conflicting observations with regards the yields for the two systems, the reason provided for the lower yield in either system has been related to predation effects by higher microorganisms.  6.1.3.4  Sludge volume index The sludge volume index (SVI) was calculated from settleability tests and TSS  measurements (mg/L) of the aerobic mixed liquors. The settleability test recorded the volume of mixed liquor (mL/L) that settled over a 30-minute period. Initially sludge bulking as indicated by the high SVI (250 - 350 g/L) occurred in both processes. Sludge bulking persisted in the membrane EBPR process, but decreased markedly in the conventional EBPR process at day 128. The SVIs measured over the study period are shown in Figure 6-12. 81  6: Results and Discussion  450 Membrane  Conventional  300  400  400 350  (mL/g) SVI (mL/g) SVI  300 250 200 150 100 50 0 0  50  100  150  200  250  350  450  500  Days inOperation Operation Day in  Figure 6-12  Sludge volume index measured during the pilot plant operation  For the membrane process, SVI varied between 202 – 399 g/L and for the conventional process SVI ranged between 28 – 356 g/L. This is in contrast to the previous study by Monti (2006) which reported SVIs of greater than 250 g/L for both membrane EBPR and conventional EBPR processes throughout the study at the UBC pilot plant, thus indicating that there was a significant change in the settleability properties of the conventional EBPR mixed liquor in the present study. The periods of reduced SVI also coincided with periods in which worm infestations occurred in the conventional EBPR process and when there was a reduced presence of filamentous bacteria. The presence of worms has previously been shown to eliminate a filamentous population in an MBR reactor operating under low shear conditions (Menniti and Morgenroth, 2010). The changes in SVI that were observed in the present study and that coincided with the presence of the worms were in accordance with studies by Wei et al. (2003), which confirmed that reduced sludge yield and SVI were consequences of the presence of worms in conventional activated sludge systems. The impact on SVI has been attributed to the formation of larger flocs by the bacterial population in order to withstand grazing pressure and the presence of excretion products (faeces) of the worms (Ratsak et al., 1996; Ratsak, 2001). It was apparent from the present study that the reduced SVI was a consequence of reduction in filamentous 82  6: Results and Discussion  bacteria as observed from the changes in abundance of filamentous bacteria in the conventional mixed liquor.  6.1.4  Effluent characteristics The effluent quality obtained from each of the treatment processes is presented  in Table 6-5. Both processes performed satisfactorily to produce a low nutrient concentration effluent. Based on the average concentrations, the membrane EBPR process produced a higher quality effluent with respect to TSS and COD. Nitrogen and phosphorus effluent concentrations were not statistically different (p > 0.05) based on paired t-tests. The average values calculated for N and P excluded the data from periods of breakthrough in the effluent. There was one occurrence of N breakthrough in the conventional process only. P breakthrough occurred on two occasions for the conventional process and once for the membrane process. These periods of breakthrough are discussed in the subsections following.  Table 6-5  Effluent quality from the membrane EBPR and conventional EBPR treatment processes  Parameter Units TSS COD NH4-N NOx-N TKN PO4-P TP  mg/L mg/L mg N/L mg N/L mg N/L mg P/L mg P/L  Average * 37 0.1 12.3 1.1 0.2 0.3  Membrane EBPR Minimum Maximum * 2 * 7.0 0.3 0.02 0.1  * 127 0.7 18.9 3.5 0.8 1.6  Conventional EBPR Average Minimum Maximum 25 52 0.2 12.6 2.4 0.5 0.6  1 2 * 6.2 0.4 0.04 0.1  150 242 1.1 22.0 4.2 1.6 1.7  * Below detection limit  6.1.4.1  Nitrogen removal performance and efficiency The Figure 6-13 compares the effluent quality for the membrane EBPR and  conventional EBPR processes with respect to nitrogen concentrations. The data  83  6: Results and Discussion  Conventional NH4-N (mg/L)  0.5  (a) NH4-N 0.4 0.3 0.2 0.1 0.0 0.0  0.1  0.2 0.3 0.4 Membrane NH4-N (mg/L)  0.5  25  Conventional NOx (mg/L)  (b) NOx-N 20 15 10 5 0 0  5  10  15  20  25  4.0  5.0  Membrane NOx (mg/L) 5.0  Conventional TKN (mg/L)  (c) TKN 4.0 3.0 2.0 1.0 0.0 0.0  1.0  2.0  3.0  Membrane TKN (mg/L)  Figure 6-13  Nitrogen concentration in membrane EBPR and conventional EBPR process effluent  84  6: Results and Discussion  presented in the figure represent the typical effluent quality achieved from each process after the elimination of outliers associated with periods of breakthrough. These nontypical data sets are discussed later in the sub-section. From Figure 6-13, it can be seen that the NH4-N concentration was similar for both membrane EBPR and conventional EBPR process effluents, however, the membrane EBPR process had generally lower TKN concentrations than the conventional EBPR counterpart. A paired t-test indicated that the effluent NH4-N concentration was not statistically different (p=0.38). A paired t-test for the effluent TKN, however, showed that the difference was significant (p<0.01). The NOx-N concentrations were similar for both processes and the marginal difference observed was not significant (p=0.13). This is contradictory to literature studies which reported lower nitrate in the conventional process caused by additional denitrification from the anoxic clarifier sludge blanket (Siegrist and Gujer, 1994; Monti et al., 2006). This effect of additional denitrification was not evident in the present investigation, possibly because of the small clarifier sludge blanket that was present in the clarifier. In the present study, the sludge blanket occupied only a small volume of the clarifier, with the fraction of total system biomass in the clarifier averaging 11%. For significant denitrification to occur in clarifiers a substantial sludge blanket is required and for clarifiers for which considerable denitrification has been reported, the clarifier suspended solids approximated to 20%25% of the total biomass (Siegrist et al., 1995; Monti et al., 2006). The similar concentration of NOx-N observed in both processes, was, however, in agreement with the findings of du Toit et al. (2007). At the target SRT of 12 d, both membrane and conventional processes achieved complete nitrification as illustrated by the low NH4-N concentrations in the effluent. Effluent concentrations averaged 0.13 mg N/L (Std dev = 0.10) and 0.18 mg N/L (Std dev = 0.73) for the membrane and conventional processes respectively, with resulting removal efficiencies of above 99%. Complete nitrification for both CAS and MBR processes has been reported previously (Manser et al., 2005c; Lee et al., 2009). There was one instance of ammonium breakthrough in the effluent of the conventional process as shown in Figure 6-14. The major upset was observed during the operation period from day 350 to day 400 when effluent concentrations exceeded  85  6: Results and Discussion  10  Influent NH4-N (mg N/L)  Influent  Effluent-M  Effluent-C  50  9 8 7  40  6 30  5 4  20  3 2  10  Effluent NH4-N (mg N/L)  60  1 0 50  100  150  200  300  350  400  450  Day in Operation  0.50 Influent  Influent NOx (mg/L)  250  Effluent-M  0 500 25  Effluent-C  0.40  20  0.30  15  0.20  10  0.10  5  0.00 0  50  100  150  200  250  300  350  400  450  Effluent NOx (mg/L)  0  0 500  Days in Operation 90  14 Influent  Effluent-M  Effluent-C  12  70 10  60 50  8  40  6  30  4  20  Effluent TKN (mg N/L)  Influent TKN (mg N/L)  80  2  10 0 0  50  100  150  200  250  300  350  400  450  0 500  Day in Operation  Figure 6-14  Time series concentrations of ammonium, nitrite + nitrate and TKN in membrane (M) EBPR and conventional (C) EBPR effluent  86  6: Results and Discussion  1.0 mg N/L. This isolated period of low quality effluent was subsequently related to a mechanical failure rather than a process upset. The scraper arm for the clarifier bottom had not been restarted after clarifier stirring for sample collection, causing overflow of the solids blanket. In addition the mixer in the secondary effluent holding tank was not functional, resulting in settlement of solids in the tank and eventual carryover to the composite sample. Anaerobic decomposition of the settled solids in the effluent holding tank resulted in release of NH4-N in the effluent. The performance of the processes confirmed the nitrification process at an operational SRT of 12 days and minimum temperature of 13oC. At the selected operational conditions, both membrane and conventional processes provided nitrogen removal of > 95%. The failure that occurred was primarily a result of carryover of solids in the clarifier effluent and this highlights the advantage of complete retention of suspended solids that is afforded by the membrane.  6.1.4.2  Phosphorus removal performance and efficiency The Figure 6-15 shows the phosphorus concentrations of the effluent for the  membrane EBPR and conventional EBPR processes. It can be seen that both systems produced effluent with similar P concentrations and there was P breakthrough occurring  5.0  4.0 Conventional TP (mg P/L)  Conventional PO4-P (mg P/L)  for both processes, but at different time points.  3.0 2.0 1.0  4.0 3.0 2.0 1.0 0.0  0.0 0.0  1.0  2.0  3.0  Membrane PO4-P (mg P/L)  Figure 6-15  4.0  0.0  1.0  2.0  3.0  4.0  5.0  Membrane TP (mg P/L)  Comparison of phosphorus concentrations in membrane EBPR and conventional EBPR process effluents 87  6: Results and Discussion  Performance of the systems with respect to P removal over the duration of the study is illustrated in Figure 6-16. The figure also shows the process operational temperature.  10  30 Influent  Effluent-M  Effluent-C  Temperature  PO4-P (mg/L)  20 6 15 4 10 2  Temperature (oC)  25  8  5  0  0 0  50  100  150  200  250  300  350  400  450  500  Day in Operation  Figure 6-16  Time series plot of PO4-P concentrations in influent and membrane process (M) and conventional process (C) effluents  Effluent concentrations averaged 0.2 mg P/L (Std dev = 0.3) and 0.5 mg P/L (Std dev = 0.7) for the membrane EBPR and conventional EBPR processes respectively, with resulting removal efficiencies of above 80%. There were two periods of instability of the P removal process, however, the failures did not occur simultaneously for both membrane and conventional systems and therefore, were likely process-related. P breakthrough for the membrane process occurred over day 110 to 120. This period coincided with a period of low temperature operation. P breakthrough in the conventional system occurred intermittently from day 80 to 120 and during days 140 to 170. The first upset for the conventional process coincided with the period during which sludge bulking in the clarifier resulted in clarifier blanket spills and carryover of suspended solids in the effluent, so that the P removal decrease was primarily due to the 88  6: Results and Discussion  release of PO4-P from particulate material in the secondary clarifier effluent. Although this period included the period of low temperature operation during which there was breakthrough in the membrane EBPR process, the conventional process effluent quality did not deteriorate at the same time as the membrane process, indicating that it was less affected by the low temperature. The last incidence of carryover was observed at day 113, after which the biomass was noted to have improved settling properties. At the second effluent P breakthrough in the conventional system, it was noted that the effluent P concentration was significantly higher than that of the influent. During this period, influent and effluent PO4-P concentrations averaged 1.0 mg/L and 2.7 mg/L respectively, and from this increase it was inferred that there was not simply a loss of the P removal mechanism in the process, but that there might be factors contributing to increase the P concentration across the system. This period corresponded to the period in which a worm infestation occurred in the conventional process. The presence of these worms has been shown to cause an increase in phosphate and nitrate concentration (Rensink and Rulkens, 1997; Wei and Liu, 2005; Huang et al., 2007) due to mineralization activities associated with the worms. No increase in nitrate concentration was observed in this study, during the worm infestation period.  6.1.4.3  COD removal Comparison of soluble COD concentrations of the membrane EBPR and  conventional EBPR effluent are shown in Figure 6-17. Effluent concentrations averaged 37 mg/L (Std dev = 34) and 52 mg/L (Std dev = 47) for the membrane EBPR and conventional processes respectively. A paired t-test indicated a significant difference (p < 0.01) between the two effluent concentrations. COD removal efficiency averaged 89% and 85% for the membrane EBPR and conventional processes respectively. The lower concentration of soluble COD in the membrane process effluent has been well documented in the literature (Aguilera Soriano et al., 2003; du Toit et al., 2007; Lee et al., 2009) and has been attributed to the retention properties of the membrane. Time series plots of the total influent COD and effluent soluble COD concentrations for both processes are shown in Figure 6-18. . 89  COD (mg/L) Soluble COD Conventional Soluble Conventional  6: Results and Discussion  200 175 150 125 100 75 50 25 0 0  25  50  75  100  125  150  175  200  Membrane Soluble Soluble COD COD (mg/L) (mg/L) Membrane  Figure 6-17  Comparison of soluble COD concentrations in membrane EBPR and conventional EBPR process effluents  500 Influent  450  Membrane  Conventional  400  (mg/L) COD mg/L COD  350 300 250 200  150 100 50  0 0  Figure 6-18  50  100  150  200 250 300 DayDay in in Operation Operation  350  400  450  Concentrations of influent total COD and effluent soluble COD concentration in the membrane and conventional processes  90  6: Results and Discussion  6.1.5  Summary of pilot plant performance results Both trains of the pilot plant were operated at a target SRT of 12 d and an HRT of  10 h for a period of 472 days. The pilot plant process monitoring data collected over the period of the study indicated that comparable operational conditions were maintained for both process trains. The pilot plant EBPR processes treated a real wastewater influent with characteristics that were typical of a medium strength domestic wastewater with respect to nutrient concentration. There were variations in concentrations of the constituents which were reflective of fluctuations that are usually associated with the variability of a real wastewater. The EBPR processes generally performed satisfactorily to remove the N and P constituents from the wastewater, with the membrane process achieving marginally higher quality effluent. The differences between the NH4-N and PO4-P concentrations in the effluents of the two processes were not statistically significant (p=0.38 and p=0.39 for NH4-N and PO4-P concentrations respectively). The membrane process appeared to be more stable with respect to N removal as compared to P removal, based on the occurrence of P breakthrough in the effluent. P removal deteriorated during low temperature operation for the membrane process, but N removal was unaffected. This could be a consequence of the high fraction of aerobic biomass solids in the system available for the nitrification process. The aerobic and anaerobic biomass accounted for 72% and 5% of the total biomass of the system respectively. A decrease in P removal in the conventional process occurred due to particulate carryover in the secondary clarifier effluent. The process seemed to be less affected by the low operational temperature as compared to the membrane process. The presence of nematodes in the conventional process appeared to reduce the biomass with the result that sludge yields for the conventional EBPR process were lower than for the membrane process. Nematodes were absent from the mixed liquor of the membrane process.  91  6: Results and Discussion  The presence of nematodes in the conventional process also influenced the mixed liquor settling properties, presumably as a result of nematode grazing on the filamentous bacteria. The reduction of the filamentous bacteria resulted in improved settling which was indicated by lower SVI values. The results confirmed the ability of the membrane process to perform biological P and N removal at relatively shorter SRT of 12 d compared to the 15-20 d long SRT that is typical of a biological nutrient removal process. The results also show the membrane bioreactor‘s capability for the removal of carbonaceous constituents of wastewater to achieve effluent quality which surpasses that of a conventional process.  6.2  Specific nitrification rates The specific nitrification rate was determined from laboratory batch tests to  evaluate the nitrification activity of both the membrane process and conventional process mixed liquors. The rates were measured using aerobic mixed liquor samples taken from the UBC pilot plant membrane and conventional trains.  6.2.1  Maximum specific nitrification rate Nitrification rates were measured from laboratory batch tests by the oxygen  uptake rate (OUR) and NOx production rate (NPR) methods.  6.2.1.1  OUR results A typical dataset acquired during a batch test is shown in Figure 6-19. The batch  test was carried out under controlled conditions of DO, pH and temperature. The aeration system was set to turn ON when DO reached a minimum set point value of 2 mg/L and turn OFF when a maximum DO of 4 mg/L was attained. The oxygen uptake rates were then calculated from the decreasing DO concentration by linear regression. The pH was adjusted to 7.0 at the start of the batch test and was maintained by a pH controller through alkali dosing. The mixed liquor was kept at the pilot plant operating temperature by a temperature-control recirculating water bath. 92  6: Results and Discussion  30  60 Temp M  pH C  pH M  DO - C  DO - M  OUR - C  OUR - M  50 NH4Cl addition  NaNO2 addition  OUR  20  40  Temperature  15  10  30  20  pH  5  OUR (mg O2 / L·h)  DO (mg/L); pH; Temperature (oC)  Temp C  25  10  DO  0 0  0 1  2  3  4  5  6  7  Time (h) M = Membrane  Figure 6-19  C = Conventional  Respirometry data for a typical batch test (day 23)  Over the first two hours, the OUR decreased to a constant minimum rate which was taken to be the endogenous oxygen uptake rate. This base rate represented the oxygen uptake after utilization of available carbon substrate and was also taken as a measure of the background heterotrophic bacteria activity occurring in the reactor during the nitrification rate measurement. Upon addition of the NaNO2 substrate, the OUR increased to a maximum value which subsequently decreased to the initial base rate once the substrate had been utilized. NaNO2 provided substrate for the nitrite-oxidizing bacteria (NOB) and therefore, the increase in OUR upon addition of the NaNO2 indicated the maximum respiration rate of the NOB. Similarly, NH4Cl served as substrate for the ammonia-oxidizing bacteria (AOB) and the maximum rate was indicative of the activity of both the AOB and NOB. The maximum nitrification rate was not immediately achieved upon addition of NH4Cl, taking from 15 – 45 minutes to reach the maximum. This phenomenon has been observed by several authors during ammonia uptake and OUR tests (Katehis, 2005; Guisasola et al., 2006; Manser et al., 2006). Guisasola et al. (2006) hypothesized that the most probable cause was the limitation of reducing equivalents required for maximal ammonia monooxygenase activity at the time of substrate addition. 93  6: Results and Discussion  The enzymes involved in the overall reaction of ammonia to nitrite are ammonia monooxygenase (AMO) for ammonia oxidation and hydroxylamine oxidoreductase (HAO) to produce nitrite. NH3 + O2 + 2H+ + 2e-  ---(AMO)---> NH2OH + H2O  NH2OH + H2O ---(HOA)---> NO2- + 5H+ + 4eAMO requires molecular oxygen and reducing equivalents to catalyze NH3 oxidation. The electrons released in the hydroxylamine oxidation are channeled back to AMO. The lag described above could be related to the need for oxidation of sufficient NH2OH and in turn NH3, before maximal AMO activity is attained. Katehis (2005) also attributed the slow response to oxygen-limiting conditions. Oxygen limitation was less likely to have occurred in the present tests, since the mixed liquor was aerated for up to 2 h prior to addition of substrate and oxygen concentrations were controlled between 4 - 2 mg/L throughout the test. In addition, further tests were carried out in which the length of the initial aeration period, prior to addition of NH4Cl substrate, was varied to determine whether there was any effect on the time required to reach the maximum specific rate. The results of these tests are shown in Figure 6-20. For both aeration time periods (1 h and 2 h), the response time to attain the maximum rate was similar. Therefore, the extended aeration period provided to ensure a wellaerated mixed liquor did not appear to influence the response time to attain the maximum rate. Also, two consecutive OUR batch tests were completed on a single mixed liquor sample. It can be seen that under the same test conditions, on the second spiking with substrate, the response time to the maximum rate remained almost unchanged. The phenomenon was, therefore, still observed after the biomass had been acclimatized to excess quantities of ammonia. Any effect related to the addition of nitrite, prior to the addition of ammonia, was also assessed by OUR nitritation batch tests with and without the prior addition of NaNO2. As Figure 6-21 shows, the same response time to reach the maximum nitratation rate was observed under both conditions. Hence, NaNO2 addition did not contribute to the initial period of low NOx production rate.  94  6: Results and Discussion  70 OUR-2h  OUR-1h  60  OUR (mg O2 /L /h)  50  40  30  20  10 First addition of substrate after 1-h initial aeration period  First addition of substrate after 2-h initial aeration period  Second addition of substrate  Second addition of substrate  0 0  1  2  3  4  5  6  Time (h)  Figure 6-20  Effect of length of pre-aeration period on response time to maximum rate (day 55)  50  Nitritation Rate (no NaNO2 addition)  45  Nitritation Rate (with NaNO2 addition)  40  OUR (mg O2 / L/ h)  35 30 25 NH4Cl  20 15  Endogenous Rate  addition of NH4Cl substrate  NaNO2  10 addition of NH4Cl or NaNO2 substrate  5 0 0  1  2  3  4  5  6  7  8  9  Time (h)  Figure 6-21  Effect of NaNO2 addition on response time to maximum rate (day 38) 95  6: Results and Discussion  The OUR rates for the NOB and AOB which catalyze the nitrification process were calculated from the maximum mean OUR according to the following equations:  OURNOB =  OURAOB =    n  OURnob n    n  OURaob n  - OURHET  - OURNOB – OURHET  where OURHET = endogenous respiration rate =    n  OURhet n  and n  = number of OURs calculated during a single batch test  An autotrophic rate (OURAUT) was also determined as follows, OURAUT =    n  OURaob n  – OURHET  The OUR data were normalized with the VSS measured in the reactors to give specific oxygen uptake rate (SOUR) expressed as mg O2 / g VSS·h. Comparisons of the SOUR of the ammonia-oxidizing bacteria and nitrite-oxidizing bacteria measured for the membrane EBPR and conventional EBPR processes are presented in Figure 6-22 and Figure 6-23 respectively. The SOUR-based specific nitrification rates for the autotrophs are also shown in Figure 6-24 for comparison with the NOx-N production method. The data set for the specific nitrification rates measured by the OUR method is concentrated towards the beginning of the study (day 10 to day 29) and with few exceptions, this data set showed that the specific nitrification rate in the membrane EBPR process was similar to that of the conventional EBPR process at startup. This was expected because at the start of the study, the mixed liquors in both processes were intermixed prior to replacement of one of the membrane modules with a clarifier. It was 96  6: Results and Discussion  also expected, however, that within about 14 days of operation, there should have been an observable and consistent difference in specific nitrification rates between the two processes. This expectation was based on the results of the previous study at the pilot plant (Monti, 2006).  70%  328  296  267  29  28  23  21  14  13  10  0  10% 328  296  0% -10%  267  2  20%  29  4  30%  28  6  40%  23  8  50%  21  10  60%  14  12  13  (mg O2 h-1 /g VSS )  14  Conventional  10  Membrane  % Difference of specific rates % Difference of specific rates =(M-C)/M =(M-C)/M  Specific Nitrification Rate Rate Nitrification Specific (mg O 2/g VSS·h)  16  -20% -30%  Day in Operation  Day in Operation  Day in Operation  Day in Operation  (a)  (b)  Figure 6-22  (a) Measured SOUR of the AOB for the membrane EBPR and conventional EBPR processes, and (b) differences in measured SOURs  30%  2.0 1.5 1.0 0.5 328  296  267  29  28  23  21  14  13  10  0.0  328  296  29  -30% -40% -50% -60% -70%  Day in Operation  Figure 6-23  28  -20%  Day in Operation  Day in Operation  (a)  267  2.5  0% -10%  23  3.0  10% 21  3.5  20%  14  4.0  13  Conventional  10  Membrane  4.5  % Difference of specific rates % Difference of specific rates =(M-C)/M = (M-C)/M  (mg O2 h /g VSS )  Specific Nitrification Rate Specific nitrification rate (mg O2-1/g VSS·h)  5.0  (b)  Day in Operation  (a) Measured SOUR of the NOB for the membrane EBPR and conventional EBPR processes, and (b) differences in measured SOURs  97  6: Results and Discussion  20 Membrane  Specific Nitrification Rate Rate Nitrification Specific (mg O 2/g VSS·h) (mg O2 h-1 /g VSS )  18  Conventional  16 14 12 10 8 6 4 2  328  296  267  29  28  23  21  14  13  10  0 Day in in Operation Operation Day  (a)  40%  20%  328  296  267  29  28  23  21  14  13  0%  10  specific %%Difference raterates Difference ofofspecific =(M-C)/M = (M-C)/M  60%  -20%  -40% Day in Operation  Day in Operation  (b) Figure 6-24  (a) Measured SOUR of the nitrifying bacteria (AOB and NOB) for the membrane EBPR and conventional EBPR processes, and (b) differences in measured SOURs  As can be seen from Figure 6-22, Figure 6-23 and Figure 6-24, there was only a marginal difference in measured rates between the two processes up to day 29. In order to confirm that this observation was not related to the selected method for measuring the nitrification rate, the specific rates were also measured using the NOx-N production method. Nitrification rate measurements were continued with the NOx-N production measurement to be consistent with the procedure for reproducing the findings of the previous study. It is noted, however, that nitrification rate measurements performed with the OUR method towards the end of the study, indicated differences in rates which 98  6: Results and Discussion  concurred with those measured by the NOx-N production method. Thus, the method for determining rates did not affect the results.  6.2.1.2  NOx production results The tests were carried out using the same equipment setup as described for the  OUR test. Mixed liquor samples were withdrawn from the batch reactors at intervals after addition of NH4Cl substrate for measuring both the NH4-N and NOx-N concentrations. Typical results used for calculating the nitrification rates are shown in Figure 6-25. The overall nitrification rate was determined from the change in concentration of both NH 4-N and NOx-N with time, as estimated by linear regression. The maximum rate measured was then normalized with the VSS from the mixed liquor in the batch reactor to give a specific rate expressed as mg N / g VSS·h. The nitrification reaction followed zero order kinetics, however, as observed with the OUR method, the maximum nitrification rate was not immediately achieved upon addition of NH4Cl, taking from 5 – 45 minutes to reach the maximum. Consequently, the NH4-N consumption and the NOx-N production were not represented by a single linear fit and the maximum rate was preceded by a period with an initial low rate which lasted between 5 and 45 minutes in some batch tests.  99  6: Results and Discussion  25  N/L) (mgN/L) NO4-N NH x-N(mg  Membrane  20  Conventional  yC = -4.792x + 17.179 R2 = 0.9928  15  10  yM = -6.0733x + 17.412 R2 = 0.998  yC = -7.4078x + 18.104 R2 = 0.9984  5 yM = -8.8005x + 18.522 R2 = 0.9978  0 0.00  0.25  0.50  0.75  1.00  1.25  1.50  1.75  2.00  Time (h) Time (h) Time (h) 30 yM = 10.518x + 7.031 R2 = 0.9984  25 20 yM = 4.1096x + 9.4386 R2 = 0.9409  15  yC = 7.2822x + 8.5487 R2 = 0.9962  10 5  yC = 2.8985x + 9.9639 R2 = 0.9774 Membrane  0 0.00  0.25  0.50  0.75  1.00  1.25  Conventional  1.50  1.75  2.00  Time (h)  Figure 6-25  Changing concentration of NH4-N and NOx-N with time during a batch test (Day 83)  Comparisons of the specific rates measured by the substrate depletion method for the membrane EBPR and conventional EBPR processes together with the % differences between the two processes are presented in Figure 6-26. The specific nitrification rates are reported based on rate of change in NOx-N concentration rather than NH4-N concentration because the latter is also taken up by heterotrophs for growth and is produced by endogenous decay. 100  6: Results and Discussion  7.0  Specific Nitrification Rate (mg N/g VSS·h) Specific Nitrification Rate (mg N h-1 /g VSS )  Membrane  Conventional  6.0 1  3  2  4  5.0  4.0  3.0  2.0  1.0  10 13 14 21 23 28 29 31 42 48 80 83 84 86 87 91 125 126 155 223 225 226 227 238 244 258 260 267 271 273 296 328 329 349 367 398 406 412 419 454 459 472  0.0  Day in Operation Day in Operation  100%  1  2  3  4  60%  40%  20%  0%  10 13 14 21 23 28 29 31 42 48 80 83 84 86 87 91 125 126 155 223 225 226 227 238 244 258 260 267 271 273 296 328 329 349 367 398 406 412 419 454 459 472  % Difference of specific rates specific rates of (M-C)/M % Difference =% =%(M-C)/M  80%  -20%  -40%  -60%  Day Dayin inOperation Operation  Figure 6-26  Comparison of specific nitrification rates for the membrane EBPR and conventional EBPR processes (rates at prevailing plant temp) The top graph shows measured nitrification rate for each of the process. The bottom graph illustrates the difference between the two processes expressed as a percentage relative to the membrane process %(M-C)/M.  101  6: Results and Discussion  The entire program of experimentation was divided into four periods as illustrated in Figure 6-26. During the initial period of operation (period 1), the rates for the membrane and conventional processes were almost equal. This was followed by a period in which the membrane process rate was first higher than the conventional process rate and then the relationship was reversed (period 2). From day 244 onwards, the membrane process consistently achieved a higher specific nitrification rate than the conventional process (period 3). From day 407, the membrane process rate was again lower relative to the conventional process (period 4). Possibilities for these changes that were observed over the period of the investigation are discussed in later sections. The % differences in rates between the processes during the periods are summarized in Table 6-6. Statistical evaluation using the paired t-test indicated that, during the periods in which there was a relative difference in the rates, the difference was significant (p< 0.05).  Table 6-6  Summary of % difference in specific nitrification rate between the membrane EBPR process and conventional EBPR process  Process specific nitrification rate performance  Period of operation  Membrane process rate greater than conventional process rate Membrane process rate less than conventional process rate  % Difference measured Maximum  Minimum  Day 244 – day 398  62%  2%  Day 406 – end of study at day 472  42%  7%  The relationship between the nitrification rates for the processes observed over the duration of the study was different than those reported in the literature. Other studies have reported equal rates for both membrane and conventional processes (Manser et al., 2005c), higher rates for the membrane process (Aguilera Soriano et al., 2003) or consistently lower rates for the membrane process (Monti, 2006; Parco et al., 2006) relative to a conventional process. Given the relationships reported in the literature and those observed in the present study, it would seem that the processes cannot be assumed to have either a higher or lower inherent specific nitrification rate. Neither is a consistent characteristic of the individual process and there appears to be a natural variation in the specific nitrification rate in both process configurations. 102  6: Results and Discussion  The data presented in Figure 6-26 show the specific nitrification rates measured at the prevailing pilot plant temperatures to minimize any effects that would be associated with a temperature shock. Subsequently, the nitrification rates were mathematically converted to rates at 20oC and a mean specific nitrification rate for each of the processes was determined for a comparison over the entire study. Each measured specific nitrification rate was corrected to 20oC using Equation 6-1 which follows the Arrhenius relation. bT = b20()T-20 Equation 6-1  where T = temperature  = temperature correction coefficient = 1.055 for membrane mixed liquor = 1.064 for conventional mixed liquor The temperature correction coefficients applied were measured for both the membrane process and the conventional process mixed liquors. Details for the  measurement are given in Appendix III. The rates corrected to 20oC are shown in Figure 6-27. A similar relation was observed between the two processes as for the uncorrected rates and thus, it could be inferred that there was no impact of adjusting rate data to 20oC using the θbased Arrhenius relationship.  103  6: Results and Discussion  7.0  Specific Nitrification Rate (mg N/g VSS·h) Specific Nitrification Rate (mg N h-1 /g VSS )  Membrane  Conventional  6.0 1  2  3  4  5.0  4.0  3.0  2.0  1.0  10 13 14 21 23 28 29 31 42 48 80 83 84 86 87 91 125 126 155 223 225 226 227 238 244 258 260 267 271 273 296 328 329 349 367 398 406 412 419 454 459 472  0.0  Day in Operation  Day in Operation  100%  1  2  3  4  60%  40%  20%  0%  10 13 14 21 23 28 29 31 42 48 80 83 84 86 87 91 125 126 155 223 225 226 227 238 244 258 260 267 271 273 296 328 329 349 367 398 406 412 419 454 459 472  % Difference of specific rates % Difference of specific rates = % (M-C)/M =%(M-C)/M  80%  -20%  -40%  -60%  Day DayininOperation Operation  Figure 6-27  Comparison of specific nitrification rates for the membrane EBPR and conventional EBPR processes (rates at 20oC). The top graph shows measured nitrification rate for each of the process. The bottom graph illustrates the difference between the two processes expressed as a percentage relative to the membrane process %(M-C)/M.  104  6: Results and Discussion  The mean specific nitrification rates were therefore calculated for the membrane and conventional processes and are presented in Table 6-7 together with statistical data.  Table 6-7  Mean specific nitrification rates corrected for temperature at 20oC Process  Mean specific nitrification rate (mg N/g VSS·h) Minimum specific nitrification rate (mg N/g VSS·h) Maximum specific nitrification rate (mg N/g VSS·h) Std deviation Population (n)  Membrane  Conventional  3.40 1.81 4.98 0.90 42  3.31 1.22 5.47 1.06 42  The specific nitrification rates at 20oC averaged 3.40 mg N/g VSS·h and 3.31 mg N/g VSS·h for the membrane and conventional processes respectively and were not statistically different (p=0.39) based on a paired t-test. These mean rates are within the 3 – 5 mg N/g VSS·h range reported for the previous pilot plant study by Monti (2006). They are, however, higher than those reported in the literature, which range from 0.02 to 2.28 mg N/g VSS·h (Zhang et al., 1997; Fan et al., 2000; Liebig et al., 2001; Gao et al., 2004a; Manser et al., 2005c) under various conditions of wastewater type and sludge wasting rates. The high measured nitrification rate from the present study could be reflective of a nitrifier population which adapts to the prevailing environment in the systems. The ability of the nitrifiers to perform under adverse conditions was observed during one nitrification rate batch test in which there was an accidental overdose of NH4Cl substrate resulting in an initial NH4-N concentration of approximately 250 mg N/L. This is in excess of the concentration at which the nitrification process is known to be inhibited. A concentration of 50 mg N/L was observed to have inhibition effects on an enriched Nitrobacter culture (Blackburne et al., 2007a). The nitrification reaction proceeded, although at a lower rate of 1.0 mg N/g VSS·h and 2.0 mg N/g VSS·h for the membrane and conventional processes respectively. This batch test was carried out on day 394 and the result from this test was not included in the specific nitrification rate data set presented earlier.  105  6: Results and Discussion  It can be inferred from the statistical data presented in Table 6-7 that there was more variation in the conventional EBPR process rates compared to the membrane EBPR process rates. Conversely, there was more consistency in the nitrification rate of the membrane system and it may be that the variability in the nitrification rate of the conventional system could have given rise to the reversing comparative relations. Initially, the incidence of higher organisms in the conventional process was the only factor to which the variability in specific nitrification rate could be attributed, as the presence of higher organisms in the conventional mixed liquor was observed to vary. It was hypothesized that predator grazing could have resulted in a decrease of nitrifiers in the system, leading to a reduction in the nitrification rate in the conventional process. This hypothesis was tested by measuring decay rates, details of which are presented in section 6.3.  6.2.2  Sludge microorganisms and nitrification rates The impact of the worms was more apparent on the mixed liquor settling  properties than on the specific nitrification rates. The fact that the presence of the worms did not correlate with the changes in nitrification rate throughout the entire duration of the project indicated that they may not have significantly affected the nitrification rate. There were periods towards the end of the study in which the worms were present at relatively high density, but at this time, the conventional train specific nitrification rate was higher than the membrane specific nitrification rate. Reports on the influence of worms on the nitrification process are inconsistent. Lee and Welander (1994) found that the presence of worms disturbed nitrification, whereas Wei and Liu (2005) stated that worms had no effect on nitrification. Setter (1995) related a reduction in nitrification rate to interference from the worms. Rensink and Rulkins (1997) reported that worms caused an increase in nitrate and phosphate in the water phase from mineralization, but otherwise had no effect on the nitrification process. For the present study, the mixed liquors from both processes were routinely examined under a microscope and the organisms present were noted. It was observed that, for the conventional train mixed liquor, the microorganism population did not remain constant and there were changes occurring over the period during which it was 106  6: Results and Discussion  monitored. The major change was related to the presence of rotifers. Rotifers were notably absent in the conventional mixed liquor after day 412. It was interesting that the period in which the rotifers were not found in the sludge, also coincided with the change in specific nitrification rate from a higher rate in the membrane process to a lower rate compared to the conventional process. Thus, the change from a higher rate to a lower rate in the membrane process relative to the conventional process appeared to be more related to the presence of rotifers, than to the presence of nematodes. Literature reports on the effects of rotifers are also inconsistent. Lee and Welander (1994) established that the presence of rotifers in activated sludge negatively affects the nitrification process and reported up to 75% increase in nitrification rates with inactivation of rotifers, while Lee and Oleszkiewicz (2002) showed no effect of protozoa on nitrification rates. Given the contradictions in the literature, decay rate measurements were carried out on the membrane process and conventional process mixed liquors during each of the periods with and without the rotifers, to determine the effect on the nitrification process. Details are provided in section 6.3.  6.2.3  Process performance variability The results obtained for the difference in specific nitrification rates between the  membrane EBPR and conventional EBPR processes were not as expected. A relationship similar to that reported by Monti (2006) was expected, given that both these investigations were carried on the same system using similar operating conditions. Throughout the previous study by Monti (2006), the specific nitrification rate was consistently lower in the membrane EBPR process relative to the conventional EBPR process. In the present study, differences were observed, but the differences between the membrane and conventional trains were not consistent. In addition, during the period in which the membrane process specific nitrification rate was consistently lower, there was a considerable difference in the magnitude of the measured rates between the two studies. The % difference between rates was greater in the previous study, ranging from 15% - 75% compared to 7% - 42% for the present study at times when the membrane rate was lower. This difference between the two studies was apparently resulting from variation in specific nitrification rate in the conventional process. In both studies, membrane process rates were similar, however, in the present study, the conventional 107  6: Results and Discussion  process rate was more variable. This variation in the conventional process rate resulted in variation in the difference between the membrane and conventional processes rates and consequently there were differences in outcomes of the studies. A comparison of the rates from both studies is shown in Figure 6-28.  6.00  Mean Rate NitrificationRate SpecificNitrification MeanSpecific (mg VSS·h) N/ggVSS·h) (mgN/  Present Study  Monti (2006)  5.00 4.2 4.00 3.40 3.00  3.31 2.8  2.00 1.00 0.00 Membrane  Figure 6-28  Conventional  Comparison of mean specific nitrification rate for membrane and conventional processes at 20oC from present and previous (Monti, 2006) studies Error bars represent standard deviation  There were two questions arising out of the results of measurements of specific nitrification rates. The first was regarding the cause for the conflicting results in both studies carried out under similar test conditions. The second relates to the reasons for the variation in nitrification rates observed. Based on the review of literature studies comparing specific nitrification rates of membrane and conventional processes, it was assumed that inconsistent comparative rates among the studies were a consequence of the different conditions for the various investigations. The finding of the present study questions this assumption. Table 6-8 summarizes the plant operating conditions during the present study and gives a comparison with the previous study by Monti (2006), carried out at the same  108  6: Results and Discussion  test facility and treating wastewater from the same domestic source. The composition of the wastewater source from both studies is given in the Table 6-9.  Table 6-8  Summary of plant operational and control parameters Present study  o  Temperature ( C)  Membrane  Conventional  Membrane  Conventional  11.2 – 23.8 (16.9)  11.1 – 24.2 (17.2)  14.0 – 23.6  14.0 – 23.6  (3.0)  (3.0)  2.5 – 3.5  2.5 – 3.5  6.0 – 7.6 (6.9)  6.7 – 7.84 (7.3)  6.6 – 7.9  6.6 – 7.9  UCT  UCT: one clarifier  UCT  UCT: two clarifiers  0.67-0.84 (0.79)  0.66-0.85 (0.79)  0.83  0.83  -  reactors = 89% clarifiers = 11%  -  12  10.6  12  80% of 12 = 9.5  Higher in MBR  -  Higher in MBR  -  0.43  0.38  0.23 – 0.28  201 – 399 (246)  28 – 355 (223)  250  Similar in both  Similar in both  -  DO (mg/L) Aerobic zone pH Process configuration Aerobic VSS/TSS Suspended Solids distribution SRT (d) TSS Sludge yield (g VSS/g COD) SVI N-removal  Monti (2006)  reactors = 80% clarifiers = 20%  15% higher membrane  than  250 Higher in CAS  Number in parentheses represents average value  Table 6-9  Wastewater composition Mean Values Present Study Monti (2006)  Parameter  Units  CODtotal CODfiltered TKN NH4-N NOx-N TP PO4-P pH  mg/L mg/L mg N/L mg N/L mg N/L mg P/L mg P/L -  314 188 47.0 36.4 0.03 6.0 2.5 7.3  307.3 96.5 33.6 25.6 not det 4.2 2.4 7.2  109  6: Results and Discussion  From the comparison, it can be seen that the domestic wastewater was of a higher strength in the present study. There were modifications to the sewerage system which feeds the pilot plant, from the time when the study by Monti (2006) was completed. Thus, the catchment areas would have differed slightly. Also, sections of sewers were replaced with new sewers. This would have resulted in reduction in infiltration and an increase in the strength of the wastewater. It is also seen that although operating conditions of DO, pH and SRT were comparable to those of the previous study, there were differences with regard to the distribution of suspended solids, the sludge yield and the SVI. The difference in suspended solids distribution could have been a consequence of having different numbers of clarifiers in the two studies, as the previous study utilized two clarifiers because of the bulking sludge. A single clarifier was adequate for the present study because the sludge exhibited good settling properties as evident from the SVI data. The difference in suspended solids distribution could have lead to some differences in the average redox conditions, as one study would have had a larger anoxic fraction. Decay rates are influenced by redox conditions and it has been shown that decay rate decreases under anoxic conditions (van Loosdrecht and Henze, 1999; Martinage and Paul, 2000). This, however, may not be an influential factor for this comparison, given that there was a reversing relationship whereby the nitrification rates in the systems were both higher and lower at a various times. It is apparent that the performance of the membrane EBPR and conventional EBPR processes, with regards to specific nitrification rates, may not be dependent only upon the traditional process control and operational parameters such as SRT, DO, nitrogen loading, pH and temperature. These parameters were reasonably similar for both studies and the major difference was derived from the mixed liquor properties that were being influenced by the sludge microorganisms. Thus, while the abiotic factors influence the nitrification rates, biological factors may also be of significance as there were differences observed in performance and trends, which were not attributable to plant operations and test conditions. The differences observed in sludge yield and SVI between studies, are indications that during each study, there were differences in the sludge microorganisms present in the processes.  110  6: Results and Discussion  6.2.4  Nitrification inhibition by toxic products Toxic conditions can develop in a biological treatment process by the production  of soluble microbial products (SMPs) during the removal of organic pollutants by the microorganisms present in activated sludge (Barker and Stuckey, 1999). SMPs have been defined as soluble cellular components that are either released during cell lysis, diffuse through the cell membrane, are lost during synthesis, or are excreted for some purpose (Laspidou and Rittmann, 2002). SMP production has been shown to be closely linked to the quantity of biomass present and the presence of SMP can inhibit the nitrification process (Chudoba, 1985; Ichihashi et al., 2006). To investigate the extent to which microbial products may have affected the nitrification process in each of the EBPR trains, nitrification rates were measured after centrifuging and interchanging the particulates and supernatants of each mixed liquor. Approximately 0.8 L each of membrane and conventional mixed liquor taken from the pilot plant was centrifuged for 55 minutes at 1400 rcf until the supernatant and suspended solids were separated. The supernatant from the membrane sample was interchanged with the supernatant from the conventional sample and then the particulates were re-suspended by stirring with a magnetic stirrer. Experimental controls were also prepared by centrifuging a membrane process and a conventional process sample and then re-suspending the separated particulates in the same supernatant. The treatment of the control was to account for changes in the floc that could arise from the centrifuging process. Nitrification rate measurements were made using batch reactor tests by the NOx production method. The experiment was carried out on day 367, day 420 and day 454. Pilot plant specific nitrification rates on each of these days were either higher for the membrane process (day 367) or lower for the membrane process (days 420 and 454). The results are shown in Table 6-10. The rates for the ―membrane treated‖ are for the sample with the membrane process suspended solids and the conventional process supernatant. Similarly, rates for the ―conventional treated‖ are for the sample with the conventional process suspended solids and the membrane process supernatant. The results showed that specific nitrification rate increased, relative to the control, when membrane process floc was re-suspended in the conventional process  111  6: Results and Discussion  supernatant and it decreased for the conventional floc that was re-suspended in the membrane process supernatant.  Table 6-10  Specific nitrification rates with exchanged solids and supernatant Specific Nitrification Rate (mg N/g VSS·h) Membrane EBPR Conventional EBPR Test 1 Test 2 Test 3 Test 1 Test 2 Test 3  Treated Control % Change  Day 367  Day 420  Day 454  Day 367  Day 367  Day 367  4.33 3.62  2.05 1.75  2.33 1.82  2.75 3.18  2.03 2.35  1.97 2.18  + (20%)  + (17%)  + (28%)  - (14%)  - (14%)  - (10%)  Treated refers to the condition with process supernatant interchanged after centrifuging. The control rate is similar to the pilot plant rate. % change calculated relative to the control.  The increase in membrane process nitrification rates and the decrease in conventional process nitrification rates when the supernatants were interchanged, suggested that the membrane process supernatant contained inhibitory substances that impacted the nitrification activity. The three tests carried out were completed during periods in which relative specific nitrification rates differed, as indicated by the rates measured for the controls. The results obtained were consistent regardless of the relative performance of the processes with respect to the specific nitrification rates. It was hypothesized that the concentration of SMP present in the membrane mixed liquor was a likely cause for the inhibition observed when the supernatant was exchanged. A relationship between nitrification activity and SMP concentration was previously reported by Li et al. (2006a) and they concluded that the SMP inhibited the activity of the nitrifiers. SMP was expected to be higher in the membrane process compared to the conventional process because of the retention properties of the membrane and the high shear conditions. A previous investigation carried out at the UBC pilot plant comparing soluble EPS in the membrane and conventional EBPR processes showed that the membrane process supernatant contained consistently higher concentrations of soluble carbohydrates, protein, and humic substances (Geng  112  6: Results and Discussion  and Hall, 2007). Also, Merlo et al. (2007) compared the SMP of two process types and reported higher SMP in the membrane process. A review of SMP and extracellular polymeric substances (EPS) by Laspidou and Rittmann (2002) showed that soluble EPS were the same as SMP. There are several factors that are known to influence the concentration of soluble EPS. These include type of wastewater, sludge loading rate, sludge age, MLSS concentration and mechanical stress. Gao et al. (2004a) reported that EPS covered the microbes in an MBR but not in the CAS system. In the membrane train, the highly turbulent conditions that arise from the vigorous course bubble aeration can result in the release of EPS to the mixed liquor during floc breakup, since the cells are encased in an EPS matrix. Increases in shear have been shown to increase the release of soluble EPS by eroding EPS into solution (Wisniewski and Grasmick, 1998; Kim et al., 2001). EPS production is also associated with the presence of filamentous bacteria (Witzig et al., 2002). Filamentous bacteria were observed to dominate the membrane mixed liquor as compared to the conventional mixed liquor and therefore, their presence in abundance in the membrane mixed liquor could contribute to higher EPS. The inhibition effect observed with the membrane supernatant was possibly caused by higher EPS and SMP concentration in the membrane process relative to the conventional process. Higher concentrations of soluble EPS and SMP in a membrane process relative to a conventional process have been confirmed by others (Geng and Hall, 2007; Merlo et al., 2007). Despite the presence of inhibiting compounds in the membrane mixed liquor supernatant, specific nitrification rates measured for the membrane process were at times higher compared to the conventional process.  6.2.5  Summary of specific nitrification rates results The contrasting outcomes of the various literature studies comparing specific  nitrification rates of the membrane and conventional processes have been attributed to the different mixed liquor test conditions of SRT, hydraulic retention time (HRT), experimental scale i.e. bench vs. pilot, etc. In the present study, differences in operational and experimental conditions were minimized by investigating membrane and  113  6: Results and Discussion  conventional biomass from processes which were subject to near identical operational conditions. Both processes were operated in parallel, at a target 12 day SRT and 10 h HRT and treating a similar influent domestic wastewater source. The process operating conditions were set primarily to reproduce those of a previous study (Monti, 2006) undertaken at the same pilot plant facility, during which specific nitrification rates in the membrane process were observed to be consistently lower than those in the conventional process. Despite the similarity of process configuration, biomass source and operational conditions, the outcome of the two studies differed in respect to the observed specific nitrification rates. Hence, the attribution of these contradictory results to differences in operating and experimental conditions may not be valid. The results of the nitrification rate measurements presented here, show that the membrane and the conventional system did not exhibit consistent differences in specific nitrification rates. There were periods where both processes exhibited either equal rates, higher rates in the membrane train or lower rates in the membrane train. This was primarily a consequence of the variation in rates of the conventional process. Although there was variation in nitrification rate for the membrane process, the conventional rate was more variable. This, therefore, resulted in variation in the difference in rates between the two processes. The processes cannot be categorized on the basis of a consistent higher or lower specific nitrification rate because neither was a consistent characteristic of the individual processes and there appeared to be a natural variation in the rates. It should be noted however, that the specific rate takes into account the difference in biomass content of the two processes. If volumetric nitrification rate is compared for the two trains, the membrane process consistently demonstrated higher nitrification capacity. This is of significance from an operations perspective since both pilot plant trains were operated under identical conditions, but the membrane process operated with more biomass. The average specific nitrification rate for the two processes was calculated using all measurements made over the different experimental periods. Specific rates averaged 3.4 mg N/g VSS·d and 3.3 mg N/g VSS·d at 20oC for the membrane and conventional processes respectively. The correction to 20oC was based on measured temperature coefficients of 1.055 and 1.064 for the membrane and conventional mixed liquors respectively. Although the average specific nitrification rates were nearly equal for both 114  6: Results and Discussion  processes, the membrane process exhibited less variability in the individual rates compared to the conventional process. The membrane process also showed more stability in relation to the biomass content and composition compared to the conventional process. The biomass of the conventional process was observed to periodically support the presence of higher organisms, in particular, nematodes and rotifers. While there was correlation between the appearance of rotifers and the nitrification rates, there was no correlation between the presence of the nematodes and the specific nitrification rate. The absence of a correlation between the specific nitrification rates and nematodes could be due to a simultaneous reduction of both nitrification rate and VSS content caused by nematodes. The presence of the nematodes resulted in a decrease in the system biomass. The supernatant of the membrane process appeared to contain inhibitors, likely SMPs, which reduced specific nitrification rates. Although the inhibition caused a reduced nitrification rate in the membrane process, there were periods during which the membrane process specific nitrification rate was higher than that of the conventional process.  6.3  Nitrifier decay and growth rates It has been documented that a reduction in bacterial numbers and consequently,  activity, is caused by such mechanisms as predation, cell lysis from adverse environmental conditions and other external decay processes (van Loosdrecht and Henze, 1999). The concept of decay incorporates maintenance, endogenous respiration, degradation of enzymes or cell lysis (van Loosdrecht and Henze, 1999) and in wastewater treatment systems, loss of activity from decay is likely due to a combination of several of these mechanisms. In each of the pilot plant trains of the present study, candidate promoters for bacterial decay were identified for investigation. These included predation by the higher organisms present in the conventional mixed liquor and the shearing action of the vigorous coarse bubble aeration used for fouling control in the membrane process. Decay rate measurement for the membrane and conventional mixed liquors was 115  6: Results and Discussion  undertaken towards determining the extent to which these two factors influenced nitrifier decay and whether any difference arising in nitrifier decay rates was a cause for the difference in specific nitrification activity observed between the two processes. It was hypothesized that a relatively higher decay rate in one process would result in the presence of fewer nitrifiers with the consequence of a lower specific nitrification rate.  6.3.1  Effect of bubble type on nitrifier decay rate The decay rate was measured on aerobic mixed liquor samples taken from the  pilot plant trains on day 273, day 296 and day 328, at which times the pilot plant temperature was 20oC, 23oC and 20oC respectively and when the specific nitrification rate was consistently higher in the membrane process than in the conventional process. The mixed liquors were held in batch reactors under laboratory conditions in which they were unfed and aerated with either fine bubble or coarse bubble aeration. The different bubble sizes were used to simulate conditions that resulted from the different aeration systems in the two processes at the pilot plant. In the pilot plant, there was continuous fine bubble aeration for the conventional EBPR process, whereas for the membrane EBPR process, aeration was provided by intermittent vigorous coarse bubble aeration. It was hypothesized that the shearing action of the coarse bubbles could induce decay from cell lysis and thereby impact the nitrifier decay rate. CO 2 reductions have been reported to occur in systems when rising air bubbles strip more CO 2 than is transferred to the water (Wett, 1998) and therefore another possible effect associated with the coarse bubble aeration is CO2 stripping. It was hypothesized that if the stripping was sufficient to impact on the CO2 equilibrium, it could effect a reduction in HCO-3 which is the carbon source for autotrophs and thereby increase the decay rate. In the laboratory reactors, the fine and coarse bubble aeration conditions were achieved by using different diffuser types. For fine bubbles, a commercially available fine-bubble diffuser stone connected to the air supply was used to supply air to the reactors. For coarse bubble aeration, a diffuser constructed from plastic tubing with 5 mm diameter holes was used. The air flow rates in the two aeration systems were adjusted to achieve gentle, fine, bubbles or vigorous, coarse, bubbles. The difference in 116  6: Results and Discussion  air flow rates was consistent with the operation of the pilot plant. At the pilot plant, the air flow rates applied to the membrane and conventional pilot plant trains were approximately 0.34 m3/min (12 scfm) and 0.085 m3/min (3 scfm) respectively. The aeration systems provided in the laboratory reactors were reasonably comparable to the pilot plant with respect to the conditions of operations. It is recognized, however, that despite the similarity in conditions, the laboratory reactors represent a small system with minimum liquid depth and therefore, differences in shear conditions are expected between the laboratory reactor system and the pilot plant system. Photographs are included in Appendix IV to illustrate the different aeration systems and bubble sizes achieved in the two laboratory reactors. They also show, for comparison, the aeration diffuser mechanisms used at the pilot plant.  6.3.1.1  Nitrifier decay rates The nitrifier decay rate was determined from monitoring the reduction in the  nitrification rate of the biomass during exposure to starvation conditions. The nitrification rates were measured as both single-step and two-step nitrification reactions as described previously. The single step autotrophic decay rate (bAUT) was determined from nitrification rate batch tests based on measurement of the NOx-N production rate. The decay rates for nitrite- (bNOB) and ammonia- (bAOB) oxidizing bacteria were obtained from nitrification rate batch tests using OUR measurements. The bAUT was also derived from the OUR measurements for a comparison of the two measurement methods. The nitrification batch tests were carried out using 1 L samples withdrawn from the laboratory 12-L aerobic mixed liquor reactors which were kept aerated and unfed over the 10-day period of the nitrification rate tests. The method followed that adopted by several other researchers (Siegrist et al., 1999; Vanrolleghem et al., 1999; Lee and Oleszkiewicz, 2003; Manser et al., 2006). Figure 6-29 shows the change in specific nitrification rate measured over the 10-day period for the membrane process and the conventional process mixed liquors, aerated with fine and coarse bubble aeration systems. The rates presented in Figure 6-29 are for two replicate tests and are those calculated based on the NOx-N production.  117  6: Results and Discussion  (a) Test 02 70 M Fine  M Coarse  C Fine  C Coarse  60  mg N/g VSS·d  50  40  30  20  10  0 0  2  4  6  8  10  12  Time (d) M = membrane process C = conventional process  (b) Test 03 60 M Fine  M Coarse  C Fine  C Coarse  50  mg N/g VSS·d  40  30  20  10  0 0  2  4  6  8  10  12  Time (d) M = membrane process C = conventional process  Figure 6-29  Decreasing nitrification rate over the 10-day test period as measured by measurement of the NOx-N production rate for two replicate tests (a) test 2 and (b) test 3  118  6: Results and Discussion  There was an initial sharp decrease in nitrifier activity over the first two days followed by a more gradual decrease for the duration of the test. The rates decreased exponentially by up to 60% from the initial rate. The decay rates were calculated as the slope of the semi-log plot of specific nitrification rate vs. time as shown in Figure 6-30 and are summarized for the different aeration types in Table 6-11. The table also gives the bAUT values calculated using the different methods of respirometry and product concentration measurements. Also presented in the table are bNOB and bAOB values. These rates were determined from similar plots as shown in Figure 6-30 using nitrification rates that were measured as a two-step reaction.  7 M Fine  M Coarse  C Fine  C Coarse  Ln (specific nitrification rate)  6 5 4  3 2 1 0 0  2  4  6  8  10  12  Time (d) M = Membrane process C = Conventional process  M-Fine (□) M-Coarse (■)  Figure 6-30  Linear Equation Y = -0.1623x + 5.0029 Y = -0.1335x + 5.083  R2 0.8997 0.8584  C-Fine (o) C-Coarse (●)  Linear Equation Y = -0.2197x + 4.8566 Y = -0.2457x + 4.5944  R2 0.9943 0.8240  Semi-log plot for decay rate calculation at measured temperature (Test 02)  119  6: Results and Discussion  Table 6-11  Decay rates measured under fine and coarse bubble aeration -1  o  Decay Rate (d ) at T = 20 C  bNOB  Membrane Process OUR NPR bAOB bAUT bAUT  bNOB  Conventional Process OUR NPR bAOB bAUT bAUT  Fine Bubble  0.04*  0.06 (0.01)  0.08 (0.01)  0.11 (0.02)  0.14 (0.01)  0.14 (0.01)  0.12 (0.03)  0.19 (0.02)  Coarse Bubble  0.08 (0.01)  0.07 (0.01)  0.08 (0.01)  0.12 (0.01)  0.11 (0.01)  0.10 (0.01)  0.11 (0.01)  0.20 (0.02)  OUR – Oxygen uptake rate; NPR – NOx-N production rate Numbers in parenthesis represent the standard deviation for three measurements * Based on one measurement only  The values shown in the Table 6-11 represent the average of the three tests which were conducted at the prevailing pilot plant temperatures of 20oC, 23 oC and 20oC. The process temperature was not controlled and the variation is representative of daily temperature fluctuations.  Therefore, using the measured temperature coefficient for  each of the mixed liquors (membrane = 1.055 and conventional = 1.064) and the relationship given previously in Equation 6-1, the nitrifier decay rate calculated at 23oC was first corrected to 20oC and a mean rate for each of the processes was determined for a comparison. As applied here, the shearing action of the coarse bubble aeration system would appear to have had little or no effect on the decay of the nitrifiers, as rates measured under both fine and coarse bubble aeration were similar. For the membrane process, nitrifier decay rates were 0.11 d-1 and 0.12 d-1 for fine and coarse bubble and for the conventional process, nitrifier decay rates were 0.19 d-1 and 0.20 d-1 for fine and coarse bubble respectively. It may be that because the nitrifiers are generally embedded within the floc of heterotrophs (Mobarry et al., 1996; Wagner et al., 1996), there was minimal direct contact between the air bubbles and the nitrifying bacteria to effect die-off from shear. Also, the time period for contact between air bubbles and floc may have been lower for the coarse bubble reactor in these experiments. The time taken to reach the set point DO in the coarse bubble reactor was less than for the fine bubble reactor because substantially higher air flow rates were used for the coarse bubble to obtain a vigorous 120  6: Results and Discussion  bubbling effect as well as higher shear conditions. At the start of the decay test and over a 1-hour period, the coarse bubble aeration was ON for an average of 7 minutes whereas the fine bubble was ON for 15 minutes. Since the reactors were not fed, the required aeration times decreased over the duration of the test and by day 10, aeration systems were ON for an average of only 2 minutes per hour. This uneven time of contact between bubble and floc for the two reactors was also the scenario at the pilot plant, where the fine bubble aeration system was operated continuously, whereas the coarse bubble aeration was intermittent. To evaluate the rationale of minimal contact arising from the location of nitrifiers within the floc, heterotrophic decay rates (bh) under the different aeration conditions were also calculated and the values are presented in the Table 6-12. The heterotroph decay rate was derived using the base oxygen utilization rate from the respirometry data before the addition of substrate. Table 6-12  Heterotrophic decay rates for membrane EBPR and conventional EBPR mixed liquor measured under coarse and fine bubble aeration Aeration Type  -1  o  Heterotroph Decay Rate bH (d ) at 20 C Membrane Conventional  Fine bubble Coarse bubble  0.10 (0.01) 0.10 (0.01)  0.11 (0.02) 0.12 (0.02)  Standard deviation shown in parenthesis Rates based on OUR method  Heterotroph decay rates were equal for the fine and coarse bubble aeration tests and also for the membrane and conventional processes. The heterotrophs were expected to be located on the outer layer of the floc and there was no effect on heterotroph decay rate with the different bubble types. Thus the consequence of minimal bubble contact arising from location of the autotrophs within the floc is not considered to have impacted decay rates. The results presented in Table 6-11 also show that decay rates were almost equal for ammonia- and nitrite-oxidizing bacteria. Under coarse bubble aeration, bNOB and bAOB were 0.08 d-1 and 0.07 d-1 for the membrane process and 0.10 d-1 and 0.11 d-1 for the conventional process, respectively. The comparable decay rates for AOB and  121  6: Results and Discussion  NOB are in agreement with the findings of other studies (Manser et al., 2006; Salem et al., 2006). The autotrophic decay rate for the conventional EBPR process was also observed to be higher than for the membrane EBPR process. The value of bAUT differed depending on the nitrification rate measurement method. Rates derived from respirometry measurements were lower than those obtained from NOx-N concentration measurements. However, there is agreement regarding the general trend based on the two measurement methods, that the autotrophic decay rate for the conventional EBPR process was higher than that for the membrane EBPR process. The nitrifier decay rates measured for the membrane and conventional processes are compared to literature values in Table 6-13 for decay rates measured under aerobic conditions. The literature values of bAUT are widely variable and the techniques used for the determination of decay rates as well as the experimental conditions have significant impacts on their values (Martinage and Paul, 2000). The values obtained for bAUT in the present study are generally within the range reported in the literature. The most relevant, prior study is that by Manser (2006), which also investigated membrane and conventional processes. Manser (2006) reported similar values for both membrane and conventional processes, whereas the present study showed that the values differed. The specific nitrification rates also differed for both studies with Manser (2006) reporting similar nitrification rates for both membrane and conventional processes. In the present study, the higher decay rate observed for the conventional process substantiates the lower specific nitrification rate measured at the same time for the pilot scale conventional EBPR process. The higher nitrifier decay rate measured for the conventional mixed liquor, was attributed to the presence of higher organisms which were not observed in the membrane mixed liquor. It was hypothesized that the grazing pressure associated with the predators could result in an increased nitrifier decay rate. This hypothesis was tested by measuring the decay rates with and without active predators and is discussed later in sub-section 6.3.2.  122  6: Results and Discussion  Table 6-13  Reference values for autotrophic decay rates determined under aerobic conditions -1  Reference  Nitrifier Decay Rate (d )  Sludge Source  Rate Determination Method  MBR & CAS pilot – domestic waste  OUR  bNOB  bAOB  bAUT  Manser (2006)  0.15 - 0.14  0.15 - 0.14  -  Katehis (2005)  -  -  0.09 - 0.11  Dold et al. (2005)  -  -  0.14  0.21  0.20  -  Lee & Oleszkiewicz (2003)  -  -  0.153  Nowak et al.(1994)  -  -  0.2  Pilot AS – combined municipal and steel industry  OUR  Siegrist (1999)  -  -  0.21  Municipal wastewater  OUR  Present study  0.06 - 0.14  0.06 - 0.14  0.08 - 0.12  MEBPR & CEBPR pilot – domestic waste  OUR  Present study  -  -  0.11 - 0.20  MEBPR & CEBPR pilot – domestic waste  SR  Salem (2006)  WWTP – combined sewer  SR  AS WWTP  SR  SBR treating synthetic waste  SR  SR – Substrate removal or NOX-N production rate; OUR – Oxygen uptake rate; AS – Activated sludge; WWTP – Wastewater treatment plant; CAS – Conventional activated sludge; MBR – Membrane bioreactor; MEBPR – Membrane enhanced biological phosphorus removal; CEBPR – Conventional enhanced biological phosphorus removal  6.3.1.2  Carbon dioxide stripping Carbon dioxide dissolves in water to form carbonic acid, which then ionizes into  hydrogen and bicarbonate ions. The series of equilibrium reactions occurring is as follows; CO2 (g) + H2O ↔ CO2 (aq) CO2 (aq) + H2O ↔ H2CO3 (aq) H2CO3 (aq) ↔ H+ (aq) + HCO3- (aq) HCO3- (aq) ↔ H+ (aq) + CO32- (aq) 123  6: Results and Discussion  In order to maintain the equilibrium, when CO2 is removed from the system, H2CO3 dissociates to form CO2 (Cohen and Kirchmann, 2004). Thus, removal of CO2 will impact on the concentration of HCO3-, which is the inorganic carbon source for autotrophs. The total inorganic carbon (TIC) concentration, which is a measure of the sum of dissolved carbon dioxide (CO2), carbonate (CO32-), bicarbonate (HCO3-) and carbonic acid (H2CO3) species, was measured daily in the four 12-L laboratory reactors over the 10-day decay test period. The TIC concentrations in the reactors with both fine and coarse bubble aeration showed similar changes. The TIC decreased sharply over the first two days and then decreased more gradually for the remaining period. This change in the inorganic carbon concentration as shown in Figure 6-31 was similar to that of the nitrification rates which were measured for the decay rate determination. Carbon limitation was not concluded to be a cause for the decrease in nitrification activity with time as a similar decrease in activity was observed in the predator decay tests in which bicarbonate was added throughout the experiment to compensate for alkalinity loss.  40 M Fine  M Coarse  C Fine  C Coarse  35  30  TIC mg/L  25 20 15 10 5 0 0  Figure 6-31  2  4  6 Time (d)  8  10  12  Total inorganic carbon (TIC) concentration in reactors over the 10-day test period  The rate at which the TIC was depleted was calculated over the first two days and it was found that the rates were higher in the coarse bubble reactors relative to the fine bubble reactors. The rates are presented in the Table 6-14. 124  6: Results and Discussion  Table 6-14  TIC removal rates derived for fine and coarse bubble aeration TIC Removal Rate (mg / L·d) Coarse Bubble (c‘) 9.7 (0.8) 8.9 (0.0)  Fine Bubble (F) 7.0 (1.2) 7.2 (1.5)  Membrane (M) Conventional (C)  Based on two replicate tests; Standard deviation shown in parentheses  This difference in TIC depletion rate could be attributed to CO2 loss via stripping. If the inorganic carbon was being utilized at a higher rate in the nitrification process for the reactor aerated with coarse bubbles, then it should be reflected by a higher nitrification rate for the mixed liquor. Comparing the nitrification rates for the coarse bubble and fine bubble systems for both mixed liquor types (see Figure 6-29), no such difference in rates could be detected. Over the first two days, no consistent change in nitrification rate could be determined from all the tests. Despite the more extensive TIC depletion for the coarse bubble aeration, there was no corresponding increase in decay rate. The loss of CO2 resulting from stripping was probably compensated for by the rate of production of carbon dioxide by oxidation of heterotrophic biomass. The carbon dioxide equilibrium was thus maintained without reaction of HCO3-. The sources and sinks for the inorganic carbon are identified in Figure 6-32. Autotrophic biomass Inorganic carbon source  Aeration CO2 stripping  SINK CO2  +  H2O  ↔  HCO3-  +  H+  SOURCE  CxHyOz + O2  CO2 + H2O  Aerobic degradation by heterotrophic biomass  Figure 6-32  NH4  NO2  NO3  Nitrification  Inorganic carbon sources and sinks for the wastewater system  125  6: Results and Discussion  Carbon dioxide stripping results in an increase in pH. The increase of pH results from either depletion of H+ or generation of OH- when the reaction proceeds at low pH or high pH respectively. This pH increase was not observed either at the pilot plant or in the laboratory reactors, indicating that while CO2 stripping might have occurred, it may not have been significant. On the contrary, pH in the batch reactors decreased and was adjusted by addition of NaOH. The decrease in pH could be attributed to the nitrification process which produces H+ ions. The pH values in the laboratory reactors as well as in the pilot plant were maintained at near-neutral to ensure favorable conditions for the nitrification process. Over the 10-day decay test period, pH in the laboratory reactors averaged 7.2. The inorganic carbon species dominating at this operating pH would be the HCO3- ion. The CO2 was therefore present largely in an ionized form, which is not removed by stripping and which is also the form utilized by the autotrophs, so that CO 2 stripping caused by aeration may not have greatly influenced the nitrification rate in the process.  6.3.1.3  Assessment of decay rate measuring methods The decay rates were calculated from nitrification rates which were measured  using two methods that are based on different principles for determining the nitrification activity. The NOx production rate method measured the nitrifier activity from the rate of increase of NOx-N concentration after the addition of ammonium chloride as substrate. The NOx-N is produced from the oxidation of ammonia by the action of the nitrifiers. The respirometric method measures the increase in the rate of oxygen consumption after the addition of ammonium chloride and is based on the assumption that the increase is due to the activity of the autotrophs. The respirometric method is known to have several advantages over the NOx-N production method. One advantage that is often highlighted is the elimination of error resulting from the sampling procedure that is necessary with the NOx-N production method. In the present study, the reactors and associated equipment were tested to determine the difference arising from the individual reactor and equipment setup. Tests in which both batch test reactor 1 and reactor 2 were filled with mixed liquor from a single source showed that there was better reproducibility in measured nitrification rates 126  6: Results and Discussion  with the NOx production method compared to the respirometric method as seen from Table 6-15. This test was completed using both conventional EBPR process mixed liquor and membrane EBPR process mixed liquor and with both mixed liquors, a similar result was obtained. Error arising from DO probe response was discounted, since the same probe provided reasonably close values for the endogenous and NOB rates. Also, the possibility of errors from a slow probe response could be dismissed because in both cases of a high membrane rate and a low conventional rate for the AOB, there were notable differences between the AOB rate values determined in the two reactors.  Table 6-15  Specific nitrification rate measurement method comparison  Process Conventional (Day 271) Membrane (Day 268)  Endo 1.64  1.20  Specific Nitrification Rate OUR Method (mg N / gVSS·h) Reactor 1 Reactor 2 NOB AOB Endo NOB AOB 1.08 0.98 1.81 1.04 1.4  0.64  2.85  1.3  0.61  3.5  Substrate Method * (mg N / gVSS·h) Reactor 1 Reactor 2 1.74  1.86  3.77  3.76  * Rates based on formation of NOx-N For conversion of mg N to mg O2 multiply by 4.33  Despite all efforts with DO probe maintenance and calibration, there was always some difference between OUR results for batch test reactor 1 and reactor 2. It can be appreciated that such is the case with most instruments and no two individual reactor systems, regardless of their similarity, would give identical output. It was interesting though, that the discrepancy was always greatest for the ammonia-oxidizing rates. Since the present study required a comparison of data from two different mixed liquor sources, it was important to minimize systematic errors. Therefore, the reactor system used was interchanged randomly such that a single reactor was not assigned to any one mixed liquor type. Based on this assessment, however, it was decided that further decay testing would utilize only the substrate depletion method.  127  6: Results and Discussion  6.3.2  Effect of predators on decay rate Predation is recognized as a mechanism that plays a major role in bacterial  decay (van Loosdrecht and Henze, 1999; Martinage and Paul, 2000). The membrane EBPR and conventional EBPR process mixed liquors exhibited differences in communities and in the case of the conventional EBPR process, there were observable changes in the community occurring under constant plant operational conditions. As discussed previously, protozoa were present in both process mixed liquors, while rotifers and nematodes were present only in the conventional mixed liquor. In order to test the hypothesis that the presence of higher organisms was contributing to increased grazing and loss of nitrification activity, nitrifier decay rates were measured under conditions with and without predator inactivation. Grazing on the nitrifiers by the higher organisms was expected to increase the effective decay rate which would produce a lower nitrification rate. It was hypothesised that, inactivation of the predators would remove the grazing pressure and decay rates would decrease, with the effect of an eventual increase in nitrification activity. The increase in nitrification rate was, however, not anticipated as an immediate response because of the slow growth rate of the nitrifiers. Hence, an increase was not expected over the relatively short duration of the decay test. Notwithstanding this, the experiment was conducted but with expectations of a smaller decrease in nitrification rate over the decay test period, rather than an increase in rate. For this experiment, a suitable means for predator inactivation was required. NaCl and cycloheximide were selected for this purpose based on literature reports of their effect on activity of predators (Lee and Welander, 1994; Moussa et al., 2005; Chabaud et al., 2006). Both were investigated during preliminary experiments and the more appropriate of the two was applied for the decay rate determination experiment. The results of the preliminary trials for the NaCl and cycloheximide are also presented together with the decay rate measurement in the following subsections.  6.3.2.1  NaCl as a predator inhibitor Appropriate conditions for predator inactivation with NaCl were first determined  by observation of organism movement under different salt concentrations and contact times. NaCl concentrations of 5 g/L, 8 g/L, 10 g/L and 12 g/L were established in 128  6: Results and Discussion  reactors with mixed liquor and samples were taken at intervals for microscopic examination. The higher concentrations of 10 g/L and 12 g/L caused the nematodes to begin to burst and shrivel within 5 minutes and after 60 minutes, there was a complete kill. At the 8 g/L concentration, the nematodes were killed after 120 minutes of contact time and at the 5 g/L concentration, the nematodes remained active even after 120 minutes of contact time. The NaCl was effective on the nematodes as well as lower organisms such as protozoa, as observed from microscopic examination. Based on the observations, 8 g/L was selected for further testing. Further preliminary tests were completed to determine the effect of the NaCl treatment on the nitrifier activity, since it has been reported that increasing Clconcentrations decrease nitrification activity (Moussa et al., 2005). This was done by treating 1 L of mixed liquor with 8 g/L NaCl for a contact time of 120 minutes, centrifuging the mixed liquor after the contact period and replacing the supernatant with the respective process final treated effluent. A control mixed liquor was also prepared by centrifuging and replacing the supernatant with the process treated effluent. Replacing the supernatant with the process final effluent allowed for removal of the excess salt added and provided comparable conditions to those of the control. Nitrification rate batch tests were then carried out on the treated and control samples by the NOx production measurement method. This was done for both membrane process and conventional process mixed liquors. There was an immediate reduction in activity of the nitrifiers as seen from the specific nitrification rate measurements which are shown in Figure 6-33. The change in nitrification rates observed is contradictory to the findings of Salem et al. (2006) who stated that concentrations of NaCl of up to 10 g/L had no effect on nitrifier activity. Moussa et al. (2005) indicated that 5 g/L had no effect on the nitrifiers. The results of Figure 6-33 indicate that NaCl was not a suitable inhibitor. Ideally the inhibitor should target the predators without affecting the nitrifiers.  129  6: Results and Discussion  Specific Nitrification Rate (mg N/gVSS.h)  3.5 M-c' 3  C-c'  2.5  M-t  2 1.5 C-t  1 0.5 0  Mixed liquor treatment  M - membrane mixed liquor  Figure 6-33  6.3.2.2  C – conventional  c’ - control (untreated)  t - treated  Specific nitrification rate of control and NaCl treated mixed liquor  Cycloheximide as a predator inhibitor The time required for inactivation of predators with cycloheximide was in the  order of days as compared to hours for the NaCl. Inactivation is achieved through a biochemical mechanism whereby cycloheximide inhibits protein synthesis. The preliminary trials were set up using 250 mL conical flasks containing mixed liquor to which cycloheximide was added at concentrations of 100 mg/L and 200 mg/L. These concentrations were selected based on literature reports (Petropoulos and Gilbride, 2005; Chabaud et al., 2006). The flasks were aerated and left unfed over a 10-day period. At concentrations of 100 mg/L and 200 mg/L, the nematodes became inactive after 72 hrs and the rotifers after 5 days. Unlike the NaCl, there was no noticeable effect on the free swimming and stalked ciliates. The cycloheximide therefore required a minimum time of 3 days for inactivation of the nematodes. These observations agree with those from previous investigations regarding the effectiveness of cycloheximide (Lee and Welander, 1994; Moussa et al., 2005; Chabaud et al., 2006). These literature reports indicated that the addition of cycloheximide caused a dramatic decrease in the numbers of rotifers and nematodes but that the numbers of attached ciliates and flagellates remained unchanged.  130  6: Results and Discussion  Based on the inactivation properties of the cycloheximide as compared to the NaCl on the mixed liquor organisms, the former was selected for use as the inhibitor in the following experiments. The major drawbacks regarding the cycloheximide, however, were the time required for inactivation and the fact that it was effective only on certain types of predators. The selectivity of inactivation was overcome by the fact that there were differences in the types of organisms present in the two mixed liquors to which the cycloheximide was being applied, with only one mixed liquor supporting nematodes and rotifers. Thus, the cycloheximide could facilitate a comparison of predator effect with nematodes and rotifers as the indicator organisms. For the decay rate test, the cycloheximide was added to the 12-L laboratory reactors on day 0 and the experiment was carried out as previously described for the decay rate determination with different aeration systems.  6.3.2.3  Specific nitrification rates The specific nitrification rates measured over the 8-day period for the decay test  on pilot plant mixed liquor samples taken on Day 349 (referred to as Test 1 from here on) are shown for the membrane and conventional mixed liquors in Figure 6-34. In this test, both rotifers and nematodes were present in the conventional process mixed liquor, but were absent from the membrane process mixed liquor. The specific nitrification rate for the membrane untreated (□ control) is shown on the figure for day 0 only because an aeration problem developed in the reactor on day 1 causing DO concentrations to remain at approximately 0.5 mg/L throughout the test. The specific nitrification rates for the cycloheximide-treated samples showed an initial increase in the specific rates from day 0 to day 1 followed by a general decrease over the remaining portion of the test.  131  6: Results and Discussion  100  Specific Nitrification Rate (mg N /g VSS·d)  90  Rotifers inactive  Nematodes inactive  80 70 60 50 40 30 20 10  M-c'  M-t  C-c'  C-t  0 0  1  2  3  4  5  6  7  8  9  Time (d)  M - membrane  Figure 6-34  C – conventional  c - control (untreated)  t – treated  Specific nitrification rates for the control and mixed liquor treated with cycloheximide (Test 1)  Comparing the rates for the conventional treated and untreated (control) mixed liquors shows that the treated mixed liquors generally exhibited higher specific nitrification rates. There was an immediate increase in the activity of the nitrifiers with the addition of the cycloheximide. This effect may be an indirect effect of the cycloheximide and not necessarily related to the action of predators on nitrifiers. Addition of 100 mg/L of cycloheximide to the reactors caused instant foaming and a layer of suspended solids was observed on the surface of the reactors. This foaming effect was not observed during the preliminary trials with the cycloheximide, possibly because the effect was not as obvious in the smaller volume of 250 mL that was used, compared to the 12-L reactor. Continuous mechanical mixing, as well as intermittent manual mixing for resuspension of the floating solids was ineffective, with the result that there was a reduction in suspended solids concentration in the bulk liquid. The foaming was more intense in the membrane mixed liquor and during aeration of the reactor, the foaming increased, causing overflow and a loss of some biomass from the reactor. The layer of suspended solids remained on the surface of the reactors up to day 04, after which time the thickness of the floating layer was reduced. This reduction occurred possibly from 132  6: Results and Discussion  decomposition of the foam-causing material, or this material was extracted in the sample withdrawal process. In the test on the sample taken on day 459 (referred to as Test 2 from here on), the cycloheximide concentration was reduced to 50 mg/L and the foaming was controlled (Figure 6-36). A reduction in the cycloheximide concentration did not affect the inhibitory effect on the organisms. The immediate increase in nitrification rate was, however, still observed at the reduced concentration. A difference in nitrification rates during Test 1 was noted between the membrane and conventional treated mixed liquors, as seen from Figure 6-34. For the membrane mixed liquor, there was a decreasing specific nitrification rate over the 8-day test period. For the conventional mixed liquor, the rate decreased up to day 04 and then fluctuated thereafter. This increase coincided with the observation at day 05 that the rotifers had become inactive. Apparently the nitrification rate was more impacted by the rotifers than by the nematodes, as no observable change in rate was noted with the inactivation of the nematodes which occurred at day 03. It is possible that there was some regrowth of the nitrifiers as the grazing pressure associated with the rotifers was removed. The source of ammonium required for growth could have come from the hydrolysis of decayed bacteria and sludge organisms. It was noted that the ammonium concentration in the reactors containing the treated mixed liquor, although low, was higher than for the control as shown in Figure 6-35 (a). Evidence of growth in the reactors also comes from the increase in NOx concentration with time that was measured in the reactors as seen from Figure 6-35 (b). It is noted that there was a difference in re-growth rates between the membrane and conventional treated mixed liquor despite the similarity in NH4-N concentrations. At the start of the test on day 0, both membrane treated (M-t) and convention treated (C-t) had similar NOx-N concentration and a difference in re-growth rate was inferred from the difference in NOx-N concentration that was observed over the test period between the two samples. This disparity may have been a consequence of the experiment upset on day 0 when the foaming caused an overflow and loss of biomass from the membrane reactor. This loss of biomass may have reduced the initial concentration of the nitrifiers in the membrane batch reactor.  133  6: Results and Discussion (a) NH4-N  (b) NOx-N  0.5  70  M-c'  M-t  C-c'  C-t  M-c' NOx-N (mg N/L)  NH4-N (mg N/L)  M-t  C-c'  C-t  60  0.4  0.3 0.2 0.1  50 40 30  20 10  0.0  0  0  1  2  3  4 5 Time (d)  M - membrane  Figure 6-35  6  7  8  9  C – conventional  0  1  2  3  4 5 Time (d)  c’ - control (untreated)  6  7  8  9  t – treated  NH4-N and NOx-N concentration in the unfed reactors during Test 1 The results for the M-c‘ (□) reactor are under oxygen limiting conditions due to aeration system problems that developed at the start of the test.  An increase in nitrification rate with inactivation of rotifers in a continuous flow test has been observed by Lee and Welander (1994). Rotifers have also been reported to exert no effect on nitrification rates (Lee and Oleszkiewicz, 2003). A decrease in nitrification rates with protozoa inactivation has also been documented (Petropoulos and Gilbride, 2005). This decreased rate effect was explained by the increased competition between the heterotrophic bacteria and nitrifiers for substrate, as an increase in heterotrophic bacteria occurs from the removal of the grazing pressure by the protozoa. For the study by Petropoulos and Gilbride (2005), however, the protozoa were inhibited by 100 mg/L cycloheximide and higher organisms such as rotifers were absent and the community was dominated by ciliates. In the present study, it was found that under similar conditions for inhibition, there was no noticeable effect on the free swimming and stalked ciliates, an observation which agreed with those from previous investigations regarding the effectiveness of the cycloheximide (Lee and Welander, 1994; Moussa et al., 2005; Chabaud et al., 2006). Figure 6-36 shows the specific nitrification rate data for the pilot plant mixed liquor samples taken for Test 2. In Test 2, nematodes were present in the conventional mixed liquor, but rotifers were absent. Hence, characteristics of the mixed liquor under 134  6: Results and Discussion  test were not the same as for the previous Test 1 and the results are presented as independent tests. For the specific nitrification rate, a similar trend was noted as for Test 1, whereby there was an initial increase in the rate from day 0 followed by a general decreasing rate over the remaining period. The rates were comparable for both the treated and control membrane mixed liquors over the duration of the test. The initial increase on day 1 is probably the growth response of the bacteria to the excess bicarbonate that was added on day 0, in both tests, to compensate for alkalinity loss over the duration of the experiment.  90  Nematodes inactive  Specific nitrification rate (mg N/g VSS·d)  80 70 60 50 40 30 20 10  M-c  M-t  C-c  C-t  0 0  M - membrane  Figure 6-36  1  2  3  C – conventional  4  5 Time (d)  6  7  8  c - control (untreated)  9  10  t – treated  Specific nitrification rates for the control and mixed liquor treated with cycloheximide (Test 2)  For the conventional process the specific nitrification rates response with time were similar for the control and treated mixed liquor after nematode inactivation, thus suggesting that the nematodes were not impacting the nitrification rate. A similar finding (Rensink and Rulkens, 1997) was reported where addition of the oligochaete worm Tubificidae to activated sludge had no effect on the nitrification rate.  135  6: Results and Discussion  6.3.2.4  Decay rates The decay rate was calculated from the specific nitrification rate measurements  over an 8- to 9- day period. The calculated decay rates for both Test 1 and Test 2 are shown in Figure 6-37 (a) and (b) respectively, from the slope of the semi-log plots.  (a) Test 1  (b) Test 2 5.0  Ln (Specific Nitrification Rate)  Ln (Specific Nitrification Rate)  5.0 4.5 4.0 3.5 3.0 2.5  M-t Linear (M-t)  C-c Linear (C-c )  C-t Linear (C-t)  2.0 0  1  2  3  4  5  6  7  8  Time (d)  9  4.5 4.0 3.5 3.0 2.5 M-c Linear (M-c)  M-t Linear (M-t)  C-c Linear (C-c)  C-t Linear (C-t)  2.0  0  1  2  3  4  5  Time (d)  6  7  8  9  R2 -  Test (2)  Linear Equation  R2  M-C (□)  Linear Equation -  M-C (□)  M-t (■)  Y = -0.1035x + 4.4562  0.8376  M-t (■)  Y = -0.1453x + 4.4306 Y = -0.1245x + 4.3885  0.8568 0.9807  C-c (o)  Y = -0.0888x + 4.0745  0.7484  C-c (o)  Y = -0.0903x + 4.3924  0.6150  C-t (●)  Y = -0.0568x + 4.2883  0.2761  C-t (●)  Y = -0.1053x + 4.434  0.9155  Test (1)  Figure 6-37  10  Semi-log plots for decay rate determination for treated and control samples Decay rates for test 1 are at 18oC and for test 2 are at 14oC. Test 1 mixed liquor contained rotifers and nematodes. Only nematodes were present in test 2.  Test 1 The decay rates were 0.057 d-1 and 0.089 d-1 for the conventional treated (C-t) mixed liquor in which the rotifers and nematodes were inactivated and the conventional control (C-c) respectively. These rates were calculated at the mixed liquor temperature of 18oC. The decay rate for the control i.e. in the presence of rotifers and nematodes, was approximately 1.5 times that of the treated mixed liquor in which the organisms had been inactivated. This provides some evidence that predation on the nitrifiers contributed to nitrifier decay.  136  6: Results and Discussion  A meaningful comparison between decay rates for the membrane and conventional process mixed liquors was not possible in this experiment because of the missing data for the membrane control. The results, however, are able to show the effect on nitrifiers of the higher organisms which were present in the conventional mixed liquor, but absent from the membrane mixed liquor. It could be inferred that the presence of these organisms lowered the nitrification activity in the conventional mixed liquor and lead to the observed difference in measured specific nitrification rates. This increased decay rate from predation by rotifers, agrees with the findings of Martinage and Paul (2000) who reported values of 0.32 d-1 and 0.11 d-1 for autotroph decay rates measured with and without predators respectively at 24oC. The result, however, contrasts with that of Lee and Oleszkiewicz (2003) who reported that no significant difference was observed for decay rates in tests in which predators were inhibited. A poor R2 value was obtained for C-t (●). This was a consequence of a definite change in specific nitrification rate occurring at day 5 which coincided with the time at which the rotifers were inactivated. A more accurate decay measurement for C-t could have probably been derived from a test which was continued for a longer period after the inactivation of the rotifers. However, additional testing beyond the 8-day duration was limited by the volume of the decay reactors used in the experiment and hence, sample available for performing the specific nitrification rate tests.  Test 2 In this test, rotifers were absent from both mixed liquors and hence the test allowed for determination of the effects of nematodes only on nitrifier decay rates. The nematodes were present only in the conventional process mixed liquor. Decay rates measured for the conventional control and treated mixed liquor were 0.09 d-1 and 0.11 d-1 respectively at 14oC. The marginal difference in rates could imply that the nematodes were not impacting the decay rate and were also less influential on nitrifier grazing compared to the rotifers. This lack of grazing by the nematodes could be attributed to the fact that nitrifiers grow within large flocs, which are more difficult to ingest. Floc particle size can affect the ability of worms to feed because of the relatively small size of the mouth and pharynx (Ratsak, 2001). Lee and Welander (1994), found  137  6: Results and Discussion  that rotifers, in contrast to nematodes were able to grasp on and attack dense clusters of nitrifiers. Selective feeding might also be a possibility for the lack of grazing on the nitrifiers. Ratsak and Verkuijlen (2006) cited the work of other authors who reported that there was selective feeding by tubificids on different bacteria species. Selective feeding by oligocheates was also demonstrated in the investigation by Bowker et al. (1983) in which it was reported that the oligocheates showed preference to unicellular algae as opposed to colonial algae based on ingestion rates. Decay rates for the membrane control and treated mixed liquors were 0.15 d -1 and 0.12 d-1 respectively. The similarity of the decay rates for both membrane EBPR (0.12 d-1) and conventional EBPR (0.11 d-1) process mixed liquors when treated for inactivation of predators was an interesting result which suggest an impact of the different sludge organisms. It was expected that following treatment of the mixed liquor with cycloheximide, both mixed liquors would be similar with respect to active organisms and this was reflected by the similar decay rates observed.  6.3.3  Decay rates and relationship to process performance In the decay tests performed as described in the preceding sections, the mixed  liquor properties differed during the tests as evident from the relative performance of the two processes with respect to the specific nitrification rate and the organisms present. The Table 6-16 summarizes the prevailing conditions under which decay rates were measured. For a reasonable comparison, the decay rates shown were converted to standard temperature of 20oC using the measured temperature coefficients and method outlined in subsection 6.2.1.2. The decay rate measurements in Tests 1 and 2 were both carried out using a similar aeration system as for the fine bubble test and therefore, the control conditions of these tests were comparable to those of the fine bubble test. Missing data for the membrane process control experiment in Test 1 limited the comparisons with Test 2 to determine relationship of decay rate and specific nitrification rate. During Test 2 and the fine bubble test, however, the relative nitrification rate of the two pilot plant processes was reversed and hence a comparison of the tests was  138  6: Results and Discussion  Table 6-16  Summary of decay rates and prevailing conditions during the rate determination  Test Description  Test 1  Test 2  Fine Bubble  Mrate > Crate  Mrate < Crate  Mrate > Crate  Free swimming ciliates Rotifers and nematodes  Free swimming ciliates Nematodes only  -  --1 0.12 d  0.21 d -1 0.16 d  -1  0.11 d --  -1  0.13 d -1 0.16 d  -1  0.19 d --  Relative pilot plant nitrification rate Microorganisms present Membrane Conventional Decay Rate (bAUT)* Membrane Control Treated Conventional Control Treated  0.10 d -1 0.06 d  -1  -1  * Decay rate at 20oC  possible for determining relationship of decay rate and specific nitrification rate. As noted above, the conditions of the control experiment in Test 2 and the fine bubble test were similar. Comparisons made were, therefore, based only on control experiment results. When the specific nitrification rate was greater for the membrane process relative to the conventional process (Fine bubble test), the membrane process decay rate was lower (0.11 d-1) compared to the conventional process decay rate (0.19 d-1). When the specific nitrification rate was lower for the membrane process relative to that of the conventional process, the membrane decay rate was higher (0.21 d-1) compared to the conventional decay rate (0.13 d-1). There was a correlation between decay rates and relative specific nitrification rate which supports the hypothesis that the process with higher decay rates would have the lower specific nitrification rate.  6.3.4  Nitrifier growth rate (AUT) The measured decay rate together with the NOx concentration data obtained  during the nitrification batch test on day 0 of the decay tests for the bubble type investigation were used in estimating the growth rate for the respective processes. The estimation from the NOx response followed the method described by Melcer and Dold  139  6: Results and Discussion  (2004) in the WERF 2004 Report in which the maximum specific growth rate was determined following Equation 6-2.  dS NO X   AUT  AUT dt YAUT Equation 6-2  where dSNO/dt  = measured nitrification rate (mg N /L·d)  AUT  = maximum specific nitrifier growth rate (d-1)  YAUT  = autotrophs growth yield coefficient (mg COD / mg N)  XAUT  = initial concentration of autotrophs (mg COD / L)  The quotient (XAUT / YAUT) of the equation was calculated using the Equation 6-3.  X AUT (TKNinf  TKN eff  TKN sludge)    YAUT (1  bAUT   )  V Equation 6-3  where XAUT  = initial concentration of autotrophs (mg COD /L)  YAUT  = autotrophs growth yield coefficient (mg COD / mg N)  TKNinf  = influent TKN load (mg N/d)  TKNeff  = effluent TKN load (mg N/d)  TKNsludge  = waste sludge TKN load (mg N/d)    = sludge retention time (d)  bAUT  = autotroph decay rate (d-1)  V  = system volume (L)  The estimation for AUT was completed using the individually calculated bAUT at the temperature of the nitrification rate test. The estimates of AUT were then corrected for temperature using the measured temperature coefficients of 1.055 and 1.064 for the membrane process and conventional process mixed liquors respectively and then the average values were determined. The estimates of AUT at 20oC were 0.40 d-1 and 0.41 d-1 for the membrane and conventional processes respectively. The literature presents a wide range of nitrifier growth rates that are dependent upon operational parameters such as temperature, pH, SRT (Antoniou et al., 1990; Nowak et al., 1994; 140  6: Results and Discussion  Katehis et al., 2002). Literature values of AUT at 20oC were found to vary in the following ranges: 0.25 to 1.23 d-1 (Copp and Murphy, 1995) and 0.88 to 0.99 d-1 (Su et al., 2008). Since the estimated growth rates from the present study were similar for the two processes, then the decay rates would have the greater influence on number of nitrifiers and the nitrification activity for the two processes, so that the higher decay rate would result in a higher net loss of nitrifiers. 6.3.5  Summary of nitrifier decay rates results Decay rates were investigated and these provided further evidence of the natural  variation in performance of the systems. During periods in which the specific nitrification rate was greater for the membrane pilot scale EBPR process relative to that of the conventional process, the membrane process decay rate measured 0.11 d-1 compared to the conventional process decay rate of 0.19 d-1. During periods in which the specific nitrification rate was lower for the membrane process relative to the conventional process, the measured membrane process decay rate was 0.21 d-1 compared to the conventional process decay rate of 0.13 d-1. The decay rates for the two systems ranged from a low of 0.11 d-1 to a high of 0.21 d-1 and rate values were similar in both processes at either the high or low decay rate period. This amount of variability in decay rates for the processes might be linked to the interplay of the different mechanisms which account for bacterial decay. There were two mechanisms identified within the processes that could impact on the decay rates for the processes. These included decay from shear induced by the vigorous coarse bubble aeration used in the membrane process and predation by the higher organisms in the conventional process. Decay rates measured under different aeration types of fine and coarse bubble, showed that the effect of shear arising from aeration was not significant. Hao et al. (2010) reported on a mechanical shearing procedure for damaging cells of organisms and noted that vigorous shearing had no influence on bacteria. For the membrane process, decay rates were 0.11 d-1 and 0.12 d-1 and for the conventional process 0.19 d-1 and 0.20 d-1 when determined using fine and coarse bubble respectively. The fact that nitrifiers are usually embedded in the floc of heterotrophs (Mobarry et al., 1996; Wagner and Loy, 2002) and the assumption that this  141  6: Results and Discussion  results in minimal contact with air bubbles, was eliminated as an explanation for the results obtained, since the heterotrophic decay rates also showed a similar relationship. The heterotrophs, being located on the outer surface of the floc, would be more exposed to the shearing effects caused by vigorous aeration. Decay rates measured provided substantiation for the predation effect of rotifers on the nitrifiers. Rotifers were observed only in the conventional process. The decay rate was measured with and without inhibition of the rotifers in the mixed liquor using cycloheximide. In the conventional mixed liquor with active predators, the decay rate was 0.10 d-1, whereas in the mixed liquor with inactivated rotifers, the decay rate was 0.06 d-1. It was thought that, with inactivation of the rotifers, the grazing pressure on the bacteria was removed and decay associated with the predator mechanism was reduced. This was reflected by a 40% decrease in the decay rate. Similar decay tests showed that the nematodes found only in the conventional sludge had no negative impact on the nitrifier decay rate. Decay rates in the conventional sludge were 0.13 d-1 and 0.16 d-1 for the sludge with active and inactive nematodes respectively. While the predation effect of the nematodes did not affect the nitrifiers, there was a significant effect on the sludge settleability properties, evident from the low SVI values and reduced filamentous bacteria. It is well documented that predators feed on small flocs and dispersed bacteria, however, there has been report of filamentous bacteria being grazed by worms (Menniti and Morgenroth, 2010). The estimated value of bAUT impacts on the AUT estimate, which is a significant parameter with regard to wastewater treatment plant design. The assessment of the decay rates in the present study established that a similar decay rate could be applied to both the membrane and conventional processes. Despite there being variability in the measured rates for the two processes, it was observed that the rates remained within the same range for both processes. It is recognized that the decay rates covered a moderately wide range which correlated with the changes in specific nitrification rate. While the predation mechanism and the changes in sludge microorganisms could account for the variability in decay rates for the conventional process, it cannot explain that of the membrane process. There are several mechanisms for decay and neither of the two investigated seemed to relate to the variability observed.  142  6: Results and Discussion  6.4  Dynamics of nitrifier community structure It was hypothesized that differences in the nitrification performance observed for  the membrane and conventional processes were linked to differences in characteristics among the ammonia-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB) and therefore an assessment of the community structure and diversity of the nitrifiers was undertaken, using the terminal restriction fragment length polymorphism (T-RFLP) fingerprinting method. The T-RFLP method was first reported by Liu et al. (1997) as being applicable for assessing the diversity of complex bacterial communities and it has been applied to environmental samples including activated sludge. It, however, detects the most abundant populations and is thus appropriate for comparing communities on the basis of those abundant populations. It is also appropriate for evaluating the diversity of particular groups such as nitrifiers. The technique is commonly applied to rRNA genes but it has also been successfully applied to amoA functional genes (Horz et al., 2000; Siripong and Rittmann, 2007a). For this study, the amoA functional gene and 16S rRNA were used as the genetic markers for the AOB and NOB, respectively. The use of the amoA functional gene encoding the ammonia monooxygenase for the AOB allowed for targeting the complete range of all known ammonia oxidizers. An assay using equivalent nxr functional gene encoding the nitrite oxidoreductase for the NOB was only recently investigated (Poly et al., 2008) for soil samples and therefore has not been as rigorously tested as the amoA functional gene for wastewater samples. Therefore, the genera Nitrobacter and Nitrospira were chosen as representatives of the nitrite-oxidizing population for the two wastewater systems and their 16S rRNA genes were targeted.  6.4.1  Method development The T-RFLP technique involved PCR amplification of the amoA and 16S rRNA  genes from the extracted DNA, using fluorescently labeled forward and reverse primers. The PCR product was digested with a restriction enzyme which resulted in the formation of a number of fragments of various lengths. These fragments were then separated on a high-resolution capillary sequencing device for detection of the fluorescently labeled end fragments. The differences in the sizes of T-RFs reflected differences in the sequences  143  6: Results and Discussion  of amoA and 16S rRNA Nitrobacter and Nitrospira genes and hence phylogenetically distinct populations were distinguished. T-RFLP was performed on a total of 46 wastewater samples collected from both membrane EBPR and conventional EBPR processes over the period of investigation. Table 6-17 gives a description of the samples and process operating conditions. For each process, the sample set consisted of samples which represented the following conditions:- (i) the beginning of the study in November 2007, when there was a changeover from a membrane process to a conventional clarifier process, (ii) low temperature operation during the winter (iii) higher temperature operation during the summer (iv) periods in which both processes exhibited near equal specific nitrification rates and (v) periods in which there was a relative difference in specific nitrification rates between the processes.  Table 6-17  Sample set description by sample date, process temperature and relative specific nitrification rate o  Sample Date  Day in Operation  Temperature ( C)  Relative Nitrification Rate  02-Nov-07 05-Nov-07 08-Nov-07 13-Nov-07 15-Nov-07 21-Nov-07 17-June-08 07-July-08 10-July-08 17-July-08 21-July-08 23-July-08 15-Aug-08 15-Sep-08 24-Oct-08 20-Nov-08 24-Nov-08 02-Dec-08 08-Dec-08 15-Dec-08 19-Jan-09 24-Jan-09 06-Feb-09  10 13 16 21 23 29 232 258 260 267 271 273 296 328 367 394 398 406 412 419 454 459 472  13 14 15 15 14 13 19 21 22 22 21 21 24 20 17 18 17 18 17 13 15 16 16  M=C M=C M<C M=C M>C M>C M<C M>C M>C M>C M>C M>C M>C M>C M>C M>C M<C M<C M<C M<C M<C M<C  M = membrane EBPR process  C = conventional EBPR process  144  6: Results and Discussion  An ideal protocol for T-RFLP analysis provides for the purification of the PCR reaction before digestion. However, attempts to purify the PCR product by plate filtration and ethanol precipitation prior to restriction digestion were unsuccessful. Comparison of product intensity when visualized on ethidium stained agarose gels before and after purification revealed inconsistencies, indicating significant loss of product from some samples. In order to eliminate differences in T-RFLP results arising from sample processing, it was decided to omit the purification process. The consequences of this are the retention of a high concentration of the primer and polymerase in the reaction. The high concentrations of primers retained in the reaction produce a high intensity peak, which could mask the peaks from the lower concentration fragments. The residual polymerase has potential to cause A-tailing, giving rise to T-RF artifacts observed as small consecutive peaks. The effect of the high concentration of primer was overcome by performing a conditioning PCR procedure to increase the concentration of PCR amplicons. The conditioning PCR was carried out using the first PCR product with a reduced primer concentration. The effect of the residual polymerase was eliminated by selecting restriction enzymes which would produce a 3‘ overhang (Hartmann et al., 2007) since the polymerase attaches from the 5‘ end. Based on the sequence of clones for amoA and 16S rRNA genes of Nitrobacter and Nitrospira, the 4-bp cutting enzyme HhaI, with recognition site G_CG‘C, produced maximum polymorphism and was therefore used for T-RFLP.  6.4.2  T-RFLP analysis The electropherogram output from the restriction fragment length analysis of the  samples are given in Figure 6-38, Figure 6-39 and Figure 6-40 for the amoA, 16S rRNA Nitrobacter and 16S rRNA Nitrospira genes, respectively. The electropherograms show the fluorescence intensity of the various sized terminal fragments that were produced during the restriction enzyme digestion reaction, and it is assumed that each terminal fragment length corresponds to a certain phylotype. The electropherograms presented are based on the average fluorescence intensity of each sample set and show the T-RFs from both the FAM labeled forward primer and HEX labeled reverse primer. Average fluorescence  intensity  was  calculated  using  all  of  the  samples  shown  in  Table 6-17. 145  6: Results and Discussion  5000  (a) Membrane Process  4500  487 0  Fluorescence units  4000 3500 85 424  3000 2500 190 0  2000  491 0  1500 61 63 64  1000 500  213 239 0 0  131 0  0 0  50  100  150  200  250  278 0  355 0  300  350  400  450  500  TF length (bp) 5000  (b) Conventional Process  4500  213  Fluorescence units  4000 3500 3000  487  85 278  2500 2000  64 190  1500  491 424  1000 500  239  355  0 0  50  100  150  200  250  300  350  400  450  500  TF length (bp)  Figure 6-38  Averaged electropherograms for amoA genes for the membrane process and conventional process sample set 146  6: Results and Discussion  7000  (a) Membrane Process 6000  Fluorescence  5000  63  4000  181  3000  2000  1000  205 - 208  387  97  0 0  50  100  150  200  250  300  350  400  TF length (bp)  7000  (b) Conventional Process 63  6000  Fluorescence  5000  4000 181  3000  2000  1000  389 205  363  97  0 0  50  100  150  200  250  300  350  400  TF length (bp)  Figure 6-39  Averaged electropherograms for 16S rRNA Nitrobacter genes for the membrane process and conventional process sample set  147  6: Results and Discussion  1000 90  900  (a) Membrane Process  Fluorescence units  800 700 600 500 400 300 200 100 0 0  50  100  150  200  250  300  350  400  250  300  350  400  TF length (bp) 1000  (b) Conventional Process  900 800  Fluorescence units  90  700 600 500 400 300 200 100 0 0  50  100  150  200  TF length (bp)  Figure 6-40  Averaged electropherograms for 16S rRNA Nitrospira genes for the membrane process and conventional process sample set 148  6: Results and Discussion  For the amoA gene (Figure 6-38), comparing the T-RFLP fingerprint for the membrane process and conventional process samples, it was found that, while there were generally similar T-RF sizes present in both processes, the communities of the two processes were dominated by different phylotypes. This is evident from the difference in intensity of peaks such as at the 213, 278, 424 and 487 bp positions. There was also a significant peak occurring at the 491 bp length which is equivalent to the size of the uncut PCR amplicon. This is likely from the absence of the enzyme recognition site rather than incomplete digestion, since the 10 U quantity of enzyme added was in excess of the amount required for digestion of the quantity of DNA present in the samples. The maximum DNA concentration in any of the samples was estimated at 150 ng and by definition, 1 U of enzyme is the amount of enzyme required to digest 1 µg of DNA in 1 hour at 37°C in a total reaction volume of 50 µl. Similarly for the Nitrobacter 16S rRNA gene (Figure 6-39), the peak positions for the membrane process and conventional process samples indicated similar fragment sizes present in both systems. In both processes, however, the community appeared to be dominated by similar phylotypes. For the Nitrospira 16S rRNA gene (Figure 6-40), the majority of fragments were below the cut off size of 60 bp and this resulted in only one peak being recognized at the 90 bp position. Hence, no comparison of communities was possible for the Nitrospira data set, except to note that there was a single dominant phylotype in both the membrane and conventional processes. The fact that there was no peak observed at the full PCR amplicon length of 343 bp is evidence that the digestion was complete and repeating the digestion with another enzyme was not considered a feasible option to obtain improved results. As discussed previously, it was necessary to select an enzyme which would produce a 3‘ overhang so as to eliminate the A-tailing effect that could arise from using a PCR reaction that was not purified for polymerase removal or inactivation. This limited the availability of enzymes and the HhaI enzyme was the only appropriate enzyme, based on the polymorphism for the sequence data of the Nitrospira clones. The frequencies of occurrence of the various size fragments for amoA and Nitrobacter 16S rRNA genes (based on the presence or absence in each of the sample listed in Table 6-17) are shown in Figure 6-41 (a) and (b) respectively. It can be seen  149  Figure 6-41  B = FAM labeled T-RF  G392  G390  G389  Membrane  G388  Membrane  G387  G386  G363  G362  G236  (b) Nitrobacter  G208  B61 B63 B64 B66 B67 B69 B70 B88 B96 B131 B214 B223 B278 B492 G60 G61 G62 G63 G64 G66 G67 G68 G70 G74 G78 G81 G85 G91 G98 G100 G108 G111 G155 G170 G179 G181 G188 G189 G190 G192 G212 G213 G214 G221 G240 G274 G278 G353 G355 G357 G421 G423 G424 G486 G487  Frequency of occurrence in sample Frequency of occurence in samples  (a) amoA  G207  G206  G205  B = FAM labeled T-RF  G181  G93  G73  G70  G64  G63  G60  B391  B385  B373  B184  B181  B175  B159  B97  B63  Frequency of occurrence in sample Frequency of occurence in samples  6: Results and Discussion  250%  Conventional  200%  150%  100%  50%  0%  Terminal Fragment length Fragment Length (bp)(bp) G = HEX labeled T-RF  250%  Conventional  200%  150%  100%  50%  0%  TerminalFragment FragmentLength length(bp) (bp) Terminal  G = HEX labeled T-RF  Frequency of occurrence of (a) amoA and (b) Nitrobacter T-RFs detected in the sample set  150  6: Results and Discussion  that for the amoA gene there were fragments that were present in some of the membrane process samples but not in the conventional process samples and vice versa. There was only one characteristic peak at 85 bp that was present in all the samples, thus indicating presence of a stable population. There were a total of 14 FAM labeled and 41 HEX labeled terminal fragment lengths from the sample set and several of the T-RF sizes differed by only 1 bp, particularly at the smaller size fragments. These are considered as true peaks and are not an overestimation of T-RF sizes. Although they occur as consecutive peaks, they could not be attributed to T-RF artifacts because an enzyme which produced a 3‘ overhang was used to eliminate the ‗fill in‘ which usually give rise to this effect. In the binning process, only one peak can be assigned to a ‗bin‘ and resolution to the 1 bp was therefore required. For the 16S rRNA Nitrobacter gene, there were a total of 9 FAM labeled and 20 HEX labeled terminal fragment lengths from the sample set. As with the amoA gene, there was a significant difference between the T-RFs from the two dyes, indicating the difference in polymorphism from the forward and reverse primer ends.  6.4.3  Nitrifier community structure The peak height data from the T-RFLP profiles were normalized for use in the  multivariate statistical analyses to evaluate the nitrifier community. The analyses included non-metric multidimensional scaling (NMS), multi-response permutation procedures (MRPP) and diversity indices determination. One-way ANOVA and simple regression were also used for correlation of the peaks with the processes and operational factors. For a preliminary assessment of the diversity of the profiles for the ammoniaoxidizers and Nitrobacter, the species richness (S), evenness (E) and Shannon diversity index (H) were determined. The values are summarized in Table 6-18. Based on the Shannon index, there is similar diversity for the nitrifier profile in both the membrane and conventional processes. The diversity of the nitrifier profile between the membrane and conventional process contrasts that of the bacterial profile for the two processes. Previous study comparing the bacterial diversity in membrane and conventional EBPR  151  6: Results and Discussion  processes reported that the processes developed distinct bacterial communities (Hall et al., 2010).  Table 6-18  Diversity measures for the nitrifier profiles Membrane  Richness (S) Evenness (E) Shannon Index (H)  Conventional  amoA  Nitrobacter  amoA  Nitrobacter  11.1 0.867 2.034  5.1 0.746 1.143  11.0 0.819 1.907  5.9 0.711 1.180  The non-metric multidimensional scaling (NMS) technique was used for ordination; i.e., ordering of the samples along axes based on their similarity. NMS was selected since it does not make any of the assumptions commonly associated with other ordination techniques in respect of the distribution pattern (e.g. linear distribution) and is consequently more suited for environmental data (McCune and Grace, 2002). The ordination plot obtained for the sample set is shown in Figure 6-42 (a) and (b) for the AOB and Nitrobacter respectively. In the ordination plot, the proximity between samples corresponds to their similarity so that samples that are closer together are more similar than those that are further apart. The NMS ordination resulted in 3-dimensional solutions. The plots presented are based on the two axes with the highest total variance. The total percent of variation (r2) represented by each axis of plot (a) is 0.862 (axis 2 = 0.431 and axis 3 = 0.228) and 0.953 (axis 1 = 0.448 and axis 3 = 0.354) for plot (b). It can be seen from the plot (Figure 6-42a) that for the AOB, there was similarity between the communities of the membrane and conventional processes during the initial period of operation. This is indicated by the single cluster (I) on the plot with both membrane process and conventional process samples. As the reactor operation progressed, there were distinct clusters of membrane process and conventional process samples, indicating increasing dissimilarity between ammonia-oxidizing communities of the two processes. It can be seen also from the separate clusters among both the  152  6: Results and Discussion  (a) amoA  (b) Nitrobacter  (V) (I)  (IV)  (II)  (III)  Figure 6-42  NMS ordination plot based on process grouping for (a) amoA and (b) Nitrobacter The plot labels incorporate the wastewater process whereby membrane process samples are represented by M (●) and conventional process samples are represented by C (○) and the number represents the day in operation. The dashed (--) circles indicate the clusters formed by similar samples.  membrane process and conventional process samples, that there were changes in communities within each of the processes during the period of operation. Separation within the membrane process (clusters II and III) occurred principally along axis 3, whereas for conventional process (clusters IV and IV) samples, there was separation along axis 2. From visualization of the ordination plots, it appeared that initially the membrane and conventional processes harbored similar ammonia-oxidizers but there were shifts in community composition with time. At the start of the operations, both mixed liquors were derived from a common membrane process source and this accounts for the similarity during the early days in operation. As the operational time increased, the community of the conventional process changed to reflect selective pressures within the conventional process. The membrane process also reflected  153  6: Results and Discussion  changes in the AOB community but these were not a result of change in process configuration. Similar AOB community dynamics were observed by Wittebolle (2008) for both SBR and MBR processes. In their study, both systems were inoculated with a similar mixed liquor. Their denaturing-gradient gel electrophoresis analysis showed that the community changes which occurred over time in the SBR system were more gradual compared to those in the MBR system. Miura et al., (2007) using PCR-DGGE analysis observed similar changes in the bacterial community structure after changeover of an activated sludge system to a membrane system and attributed the changes to adaptation. Kaewpipat and Grady (2002) also reported from DGGE analysis that a highly dynamic community developed in two reactors containing sludge that was intermixed and the bacterial communities in the identically operated activated sludge reactors became significantly different over time, even though they started from a common community. Falk et al. (2009), however, reported, based on T-RFLP analysis, that an AOB community in an MBR showed no discernable shifts in composition. No such temporal changes could be detected in Nitrobacter populations. The Nitrobacter community was, therefore, similar for both processes and remained stable with time. The multi-response permutation procedures (MRPP) technique was used to test whether differences between membrane process and conventional process clusters were significant. In addition to determining the significance (p), the MRPP also gives the test statistic (T) which describes the separation between the clusters and the effect size which is provided by the chance-corrected within group agreement (A) that describes the within-group homogeneity. A-values less than 0 represent less agreement within groups than expected by chance and A=1 occurs when all items within the cluster are similar. The summary statistics for MRPP are based on the Sorensen (Bray-Curtis) distance measure. A one-way ANOVA test was also carried out for the process variables to determine the overall effect on the changes. For amoA, the high negative T value of -8.889 was an indication of strong separation between the two process groups (Table 6-19). This strong separation is consistent with the ordination plot. The low A value indicated that there was low withingroup homogeneity. A-values less than 0.1 are typical for environmental communities (McCune and Grace, 2002). Sorensen (Bray-Curtis) distance measure for the membrane 154  6: Results and Discussion  and conventional processes of 0.501 and 0.589 respectively showed that there was relatively high heterogeneity within the two systems with regards the ammonia oxidizers. The results indicate that the differences in clusters between the membrane and conventional processes are significant (p < 0.05) for the ammonia oxidizers.  Table 6-19  Summary statistics based on process groups  MRPP amoA Nitrobacter  ANOVA  T  A  F  p  -8.889 -2.56  0.07 0.03  13.124 2.076  0.028 0.062  For Nitrobacter, the difference in membrane and conventional processes clusters was not statistically significant. There was no strong separation between membrane and conventional process clusters and the clusters were placed in close proximity in ordination space. Sorensen (Bray-Curtis) distance measures for the membrane and conventional processes of 0.160 and 0.163 respectively, also show that there was low heterogeneity within the two systems. These results are consistent with the observations from the ordination plots. The nitrifier communities in the membrane and conventional processes were, therefore, similar for the Nitrobacter NOB but different for the AOB. Differences in bacterial communities between the membrane and conventional processes have been reported previously with the DGGE method (Luxmy et al., 2000a). Indicator analysis was used to compare the abundance of the phylotypes present in the membrane and conventional processes in order to assess which of the phylotypes contributes to the differences between the two process groups. The indicator values were calculated in PCORD which uses the method of Dufrene and Legendre (1997) and were tested for statistical significance using a Monte Carlo technique. Of the 55 T-RF lengths for the amoA gene, eight were found to be significantly correlated (p < 0.05). These peaks were present in different relative abundance in both processes and distinguished the membrane process community from the conventional 155  6: Results and Discussion  process community. Of the 29 T-RF lengths for the16S rRNA Nitrobacter gene, three were found to be significantly correlated (p < 0.05). The peak at 363 bp was found to be a characteristic peak for the membrane process. Figure 6-43 illustrates and also lists the relative abundance of these T-RFs in the membrane and conventional processes for amoA and Nitrobacter.  156  6: Results and Discussion  T-RF length  5000  C  4500  M  213 487  Fluorescence units  4000 3500  64 213 214 278 421 424 487 491  424  3000 278 2500 64  2000  491  Relative abundance in group (%) M C 5 4 5 5 18 76 63 66  95 96 95 95 82 24 37 34  1500 421  1000  M = Membrane C = Conventional  500 0 0  50  100  150  200  250  300  350  400  450  500  Figure shows average for membrane and conventional samples.  TF length (bp)  (a) amoA  T-RF length  7000  C  M  6000  205 363 389  Fluorescence  5000  Relative abundance in group (%) M C 13 100 95  87 0 5  4000  M = Membrane C = Conventional  3000  2000 389  205  1000  Figure shows average for membrane and conventional samples.  363 0 0  50  100  150  200  250  300  350  400  TF length (bp)  (b) Nitrobacter  Figure 6-43  T-RF identified by indicator analysis that were present in different relative abundance in the membrane and conventional processes 157  6: Results and Discussion  6.4.4  Nitrifier dynamics and reactor conditions The ordination plot of the amoA shown in Figure 6-42 indicated an apparent  change in community structure over time. This was evident from the separation within each process group. It was observed that, generally, the samples were clustered according to day 10 – 29, day 238 – 328 and day 406 – 472 for each process. The initial change in structure occurring was related to the initial common origin of both communities in membrane processes. This, however, does not explain the changes occurring within communities which gave rise to the clusters II - V identified. There has been previous report of shifts in AOB communities in both MBR and SBR systems over periods as short as 4 weeks (Wittebolle et al., 2008) The correlation of individual T-RFs with time for the membrane process and conventional process was tested by a simple regression method using the Statistica 8.0 (StatSoft Inc., Tulsa OK) software package, with the time as the independent variable and all peaks as dependent variables. There were T-RFs that significantly correlated (p < 0.05) with time and these are listed below for each process with common T-RFs in the two processes underlined: amoA Membrane 63, 64, 88, 96, 190, 221, 423, 487, 491, Conventional 63, 131, 189, 190, 212, 213, 214, 221, 278, 423 Nitrobacter Membrane 63, 386, 387 Conventional 363, 373, 386 These populations which changed with time may have been responsible for the clustering effect observed. These populations are most likely responding to reactor conditions and are possibly responsible for long-term differences in performance. Reactor operating and environmental conditions have been found to affect the diversity and dynamics of microbial populations. Terahara (2004) related shifts in nitrifier 158  6: Results and Discussion  population to changes in nitrification performance and influent characteristics from monitoring a lab-scale bioreactor from the start-up phase. Correlations between the operational parameters and the T-RFs in the present study, were evaluated for both amoA and Nitrobacter from the joint plots shown in Figure 6-44. The arrows represent the various pilot plant aerobic reactor operational parameters. The length of the arrow indicates the strength of the correlation between the parameter and the community. The parameters evaluated were temperature, pH, DO, MLSS, SVI, influent NH4-N, effluent NH4-N, influent NOx-N, effluent NOx-N and specific nitrification rate. It can be inferred from the plot that for both membrane and conventional processes, the AOB and Nitrobacter community changes strongly correlated with the temperature. This strong correlation of temperature is in agreement with previous study (Wells et al., 2009). The process temperature was not controlled and the variations in reactor temperature followed the changes in season. The effect of temperature is evaluated further in subsection 6.4.4.1. The pH and DO also showed correlation with the amoA community for both membrane and conventional processes. The pilot plant was operated at near neutral pH and at a target DO of 2.5 – 3.0 mg/L. There were, however, fluctuations in values during the operation as discussed in subsection 6.1.2.1. Despite operating within a relatively narrow range, it is apparent that these parameters correlated with community structure and may have caused changes in the structure. Egli et al. (2003) investigated effects of pH on community changes and reported differences in amoA RFLP patterns from reactors operating within a range of 7.0 and 7.5. A study by Wells et al. (2009) showed correlation with DO and the AOB community composition in a full-scale activated sludge bioreactor.  159  6: Results and Discussion  (a) amoA (ii) Conventional Process: amoA  (i) Membrane Process: amoA  C13  M273  M238 M398 M260  M267  M394  Temp  M328  M296  MLSS  C16 C10  DO  pH  SVI  C419  M367  N-Rate  Inf-NOx Ef-NH4  C328  Axis 3  Axis 3  Inf-NH4  M459  C29 C398  M406  Ef-NOx  C21  C23 M258  M412  M419  N-Rate  M271  SVI  Inf-NH4 Ef-NH4 Inf-NOx Ef-NOx  C459  MLSS C258 C296 M21  pH  C412 C406 C394  M472  M16  C472  Temp  C273  M23  DO  C271  C267  C238  M10  C260  M13  C367  M29  Axis 1  Axis 1  (b) Nitrobacter (ii) Conventional Process: Nitrobacter  (i) Membrane Process: Nitrobacter  C23  M23 M238 M29 M21  C21 C29 C10  M10  M16  M258  N-Rate  C459 C406  M459 M472  Inf-NOx Ef-NOx Ef-NH4  SVI Ef-NOx DO Inf-NOx  Temp  M367  C412  Axis 3  MLSS  C13  C472  Ef-NH4 Inf-NH4  Axis 2  M13 M398  C367 C238  SVI C398  N-Rate Inf-NH4 C16  DO C419  MLSS C258  M406  Temp  M271 M419 M267  C271  C267  M412  Axis 1  Figure 6-44  Axis 2  Joint plot evaluating effect of reactor operational parameters on community change 160  6: Results and Discussion  For both amoA and Nitrobacter in the conventional process, there was a strong correlation between the MLSS, the SVI and the community composition. The SVI was calculated from the mixed liquor suspended solids concentration and settleability. The changes in SVI and MLSS with time were presented in sub-section 6.1.3.4. It was concluded that predator grazing on filamentous bacteria was largely responsible for the variations in SVI and MLSS observed during the reactor operation and that the correlations observed were, therefore, a consequence of predator grazing. A similar inference that predator grazing significantly alters the structure of a bacterial community was made by Gude (1979). Also, Eschenhagen et al. (2003) compared the microbial population in an EBPR reactor under different operational modes (A/O and Phoredox) and observed from T-RFLP analysis that there were temporal variations in the community structure which were related to the appearance of filamentous bacteria. The influent NH4-N and effluent NH4-N concentrations, indicated on the plot as Inf-NH4 and Ef-NH4 respectively, showed no correlation with community structure. The pilot plant treated real domestic wastewater and as shown previously in Figure 6-14, the influent NH4-N concentrations varied within a range of 18 – 50 mg/L, which is typical of a domestic source. In agreement with most studies, this fluctuation in concentration had little effect on the community dynamics observed. Similar observation of no change in community structure in an MBR was reported by Chen and La Para (2008) when ammonia influent concentration was doubled. Zhang et al. (2010) also found that there was no effect of influent NH4-N concentration within a range of 7 – 50 mg/L, on the AOB communities in MBR reactors treating wastewater with various influents. Lydmark et al., (2007), however, reported that ammonium concentration was important in structuring communities. Although there was efficient nitrification in both processes in the present study, the specific nitrification rate was variable for the processes. As seen from Figure 6-44 (a) for amoA, for both the membrane process and the conventional process there was correlation between the specific nitrification rate (shown as the magnitude of the N-Rate arrow on the plot) and the community structure. This is evaluated further in subsection 6.4.4.2.  161  6: Results and Discussion  6.4.4.1  Effects of temperature on community structure The analysis of the membrane process and conventional process T-RFLP  sample set data showed that the AOB community in each of the systems was dynamic and thus, changed over the duration of the study. An evaluation of the reactor operational parameters showed a strong correlation between temperature and the community composition. The operational temperature was not controlled and there was variation in reactor temperature which was reflective of the changing seasons, as is typical of full-scale systems. To evaluate the relationship of temperature to the nitrifier community, the sample set was divided into two groups for analysis, based on the report that the nitrification rate drops sharply below 15oC (Halling-Sorensen and Jorgensen, 1993). Operational temperature of the pilot plant varied between 13oC to 24oC during the period of investigation, and the group variable was defined by temperatures 13oC<T<15oC and 15oC<T<24oC. The NMS ordination resulted in 3-dimensional solutions and the plots presented in Figure 6-45 (a) and (b) for amoA and Nitrobacter, respectively, are based on the two axes with the highest total variance. The cumulative r2 value represented by each axis of plot (a) is 0.862 (axis 1 = 0.405 and axis 3 = 0.247) and 0.953 (axis 1 = 0.448 and axis 3 = 0.354) for plot (b). From the ordination plot for the AOB, it is observed that the low temperature samples from both processes formed a distinct cluster, which separated from the higher temperature samples. There was an apparent change in AOB community structure with temperature. There was also more variation occurring in AOB composition at the higher temperatures, as inferred from the clusterings within the high temperature sample set, with membrane process and conventional process samples each forming two distinct clusters. From the ordination plot for Nitrobacter it is seen that there were clusters formed by a few of the membrane process and conventional process samples at higher temperatures. No distinct separation between either process was obvious for the low temperature samples, as both membrane and conventional process samples clustered together.  162  6: Results and Discussion  (a) amoA  (b) Nitrobacter  13oC<T<15oC Membrane (M) Conventional (C)  Figure 6-45  15oC<T<24oC  ▲  ○ ●  Ordination plots based on the defined temperature groups for the amoA and Nitrobacter The dashed (--) circles indicate the clusters formed by similar samples.  The correlation of the TFs with temperature was tested by a simple regression method using the Statistica 8.0 (StatSoft Inc., Tulsa OK) software package and with the temperature as the independent variable and all peaks as dependent variables. The overall effect with the Wilks Test is given by the p level of significance and the F value which is an indication of the effect size. The T-RFs that significantly correlated (p < 0.05) with temperature are listed as follows: amoA 61, 63, 78, 91, 189, 190, 421, 423, 424, 486 Nitrobacter 63,73, 159,181, 208, 236, 388, 389, 390, 392  163  6: Results and Discussion  For the AOB, there was stronger effect of temperature (F = 31.5) than for the Nitrobacter (F = 3.27) and the overall temperature effect was significant for both the AOB (p = 0.007) and NOB (p = 0.007). Based on the statistical analysis, it can be inferred, therefore, that the nitrifier community composition was affected by temperature. The greater effect of temperature on the AOB, compared to NOB, suggests that the AOB are more sensitive to temperature than the NOB and that the range of operational temperatures was not extreme enough to cause a similar effect on the Nitrobacter community. Also, differences in growth rates of the various AOB with temperature could influence the structure of the AOB communities. Growth rates were reported to have differed for the different genera of AOB (Belser and Schmidt, 1980). From a time series analysis of temperature at the pilot plant where samples were obtained for the present study, the average rate of change of temperature was estimated to be 0.05 oC/d, in both the positive and negative directions. This very gradual change probably allowed for acclimatization of the NOBs and minimized possible effects of temperature shock. Despite the changes in nitrifier community that occurred with changing temperature, the stability of the nitrification process was maintained as the nitrification performance of the pilot plant remained unaffected by the changing temperature. This possibly reflected the nitrifier communities‘ ability to adapt to temperature change. Temperature has been cited as an environmental factor that influences the activity of nitrifiers. Also, different AOB have different sensitivities to temperature. The findings of the present study show that temperature influences the nitrifier community structure. This is in agreement with the studies by others. Siripong and Rittmann (2007) and Wells et al. (2009) both demonstrated shifts in AOB in conventional-type activated sludge systems by using T-RFLP. This, however, is in contrast to the study by Limpiyakorn (2005), in which it was observed that there was little change in AOB communities occurring over a temperature range of 14 - 31oC. The study by Limpiyakorn et al., (2005) examined AOB communities in different wastewater treatment processes in which there was no marked variation of influent characteristics or operational parameters among the treatment systems.  164  6: Results and Discussion  6.4.4.2  Relationship of specific nitrification rate and community structure The number of TF peaks identified is an indirect indication of diversity within the  nitrifier community. The high diversity observed is consistent with the performance of the pilot plant with respect to nitrogen removal, since nitrification was always complete despite changes in the nitrifier community. The presence of functionally redundant bacterial populations provides for stable process performance. Functional redundancy refers to the presence of several different species with similar biochemical functions, so that the system is not dependent on the success of a single species (Rittmann and McCarty, 2001). This was identified as one of the key factors in the stable operation of biological wastewater treatment plants. The diversity observed for the nitrifiers in the present study is in contrast to the findings of Curtis and Sloan (2006) and Falk et al. (2009), but in agreement with those of Siripong and Rittmann (2007). Daims et al., (2001b) reported that FISH analysis of nitrifying bacteria in an SBR revealed a notably high diversity of ammonia-oxidizers, whereas there was a lack of diversity among analyzed 16S rRNA sequences. Relative nitrification rates measured during the present investigation, as discussed earlier in section 6.2, showed variation when both systems are compared. The rates were initially equal at the start of the investigation when the mixed liquor had been intermixed from both pilot plant trains. This was followed by a period where the nitrification rate in the membrane process was higher than for the conventional process, and then a period towards the end of the investigation where this was reversed. The sample set was, therefore, divided into three groups for analysis based on the relative nitrification rates of the two wastewater systems, to determine the relationship with the nitrifier community composition. Group (1) was defined for conditions of equal rates in both membrane and conventional processes, group (2) for membrane process rates higher than conventional process rate and group (3) where membrane process rate was less than conventional process rate. The NMS ordination plots presented in Figure 6-46 (a) and (b) for the AOB and Nitrobacter genes respectively, resulted in 3-dimentional solutions and the plots presented are based on the two axes with the highest total variance. Cumulative r2 value represented by each axis of plot (a) is 0.890 (axis 1 = 0.275 and axis 3 = 0.377) and 0.908 (axis 1 = 0.302 and axis 3 = 0.320) for plot (b). 165  6: Results and Discussion  (a) amoA  (b) Nitrobacter  (1) M rate = C rate Membrane (M) Conventional (C)  Figure 6-46  □ ■  (2) M rate > C rate  (3) M rate < C rate  ○ ●  ∆ ▲  Ordination plots based on nitrification rate for the (a) amoA and (b) Nitrobacter  Visual examination of the Figure 6-46 (a) for amoA gene indicated that the AOB community composition closely reflected nitrification rates. With few exceptions, the samples from periods when the membrane process rate was less than the conventional process rate (∆,▲), clustered together and were separate from the cluster of samples taken when the membrane process rate was greater than the conventional process rate (○,●). As observed in all previous ordination plots, there was also separation between the membrane process and conventional process samples within these two groups. The data for samples taken when rates were equal (□,■) were in close proximity and there was no separation between the membrane process and conventional process samples within this group. Thus, changes in relative performance of the two processes were 166  6: Results and Discussion  accompanied by changes in community structure, and it appears that the nitrification rate was influenced by changes in AOB community composition. For Nitrobacter, no distinct clustering according to nitrification rates was obvious, and the NOB community structure appeared to vary independently of the nitrification rate. The results of the regression with the specific nitrification rate as the independent variable and all peaks as dependent variable are summarized in Table 6-20 for amoA and Nitrobacter, and are generally in line with the observations from the ordination plot. For the amoA gene, the difference between the clusters was statistically significant (p < 0.05) and there was a relatively strong effect for the specific nitrification rate. For the 16S rRNA Nitrobacter gene, the differences between the clusters were not significant. Certain AOB populations correlated with nitrification rate, and despite there being no overall correlation of the NOB community with nitrification rate, one NOB population did correlate. The T-RFs that significantly correlated (p < 0.05) with specific nitrification rates are listed as follows: amoA  190, 213  Nitrobacter  63  Table 6-20  Summary statistics for overall effects of specific nitrification rates for AOB and Nitrobacter  F p  6.4.5  amoA  Nitrobacter  47.5 0.0042  2.03 0.069  Summary of community structure The T-RFLP results demonstrated that the nitrification process of both membrane  and conventional processes was mediated by a diverse group of AOB. With respect to the NOB, both Nitrobacter and Nitrospira were present in the processes, but, the Nitrospira community was dominated by a single phylotype.  167  6: Results and Discussion  There were clear differences in AOB community structure in the two processes, however, the NOB community was similar for both the membrane and conventional processes. In each of the processes, both the AOB and Nitrobacter communities were dynamic, changing over time with distinguishable shifts in populations. It could not be concluded whether the single Nitrospira population detected was variable because of limitations with the analysis. Changes in AOB community composition occurred with operational time of the reactors for the two processes, despite maintaining relatively constant operational parameters of SRT and HRT throughout the period of the investigation. Process operational temperature was not controlled, and the T-RFLP analysis showed that in each of the processes, changes in community structure corresponded to changes in temperature. Statistical evaluation showed that there was a significant effect of temperature on the AOB and NOB communities. The DO and pH were also found to have likely effects on community structure in both processes, although their values varied within a narrow range. For the conventional process, MLSS and SVI correlated strongly with community structure. The effects of predator grazing were reflected by the changes in the MLSS and SVI and, consequently, overall bacterial community structure. Despite the changes in community structure that occurred, the nitrification process remained stable and the plant consistently produced effluent low in NH4-N. Thus, the stability of the nitrification process did not depend on the presence of a stable community composition. The relative specific nitrification rates in both the membrane and conventional processes were observed to relate to changes in AOB community composition of each process. The community dynamics, therefore, corresponded to reactor operational environment, in particular, the operational time, temperature and specific nitrification rate of the processes. Particular populations were identified that were associated with these community changes, while others changed in relative abundance with no clear pattern. There was a small number of populations that remained stable.  168  6: Results and Discussion  6.5  Quantitative population dynamics  6.5.1  Cloning and sequencing Real-time quantitative PCR (qPCR) quantification was applied for an assessment  of the AOB and NOB in the membrane and conventional processes. This required preparation of standard curves using plasmid DNA that was obtained through cloning of PCR products. Clones were acquired for amoA, as well as 16S rRNA genes of Nitrobacter and Nitrospira from PCR amplicons obtained by PCR amplification of DNA template from the conventional process. The clones were sequenced and BLAST searches of the GenBank and RDP databases confirmed that (i) the sequence of the amoA clones was affiliated with an uncultured ammonia oxidizer bacterium (ii) the sequence of the 16S rRNA Nitrospira PCR amplicons corresponded to the genus Nitrospira and (iii) the sequence for the 16S rRNA Nitrobacter PCR amplicons belonged to the Class: Alphaproteobacteria Order: Rhizobiales Family: Bradyrhizobiaceae, which includes the genus Nitrobacter. Based on the sequences of phylotypes that were cloned, the expected T-RF sizes for the three undigested genes were predicted. The expected fragment sizes (bp) were determined as follows: Forward / Reverse amoA gene  278 / 213  16S rRNA Nitrobacter gene  27 / 71 and 185 / 71  16S rRNA Nitrospira gene  36 / 14  These expected peaks were identified on the respective electropherograms shown previously in Figure 6-38 to Figure 6-40, thus validating the appropriateness of the clones used for the calibration curve. The peak observed at 63 bp was concluded to correspond to the expected peak at 71 bp for the 16S rRNA Nitrobacter gene, since for fragment sizes less than 100 bp, there can be discrepancy between observed and expected fragment size of up to 11 bp (Hahn et al., 2001). The discrepancy between observed and expected fragment size can result from differences in electrophoretic mobility of fragments (Schutte et al., 2008). Also, fragments labeled with FAM and HEX, have been found to migrate faster than fragments labeled with ROX. As a result, the 169  6: Results and Discussion  sizes of fragments labeled with HEX or FAM can be underestimated (Schutte et al., 2008). The internal size standards used in this study were labeled with ROX. Peaks less than 60 bp were not included for analysis and hence, the peaks for Nitrospira are not visible on the figures shown.  6.5.2  Specificity of PCR product In addition to the above sequence analysis of the clones, the specificity of the  primer sets used in the qPCR reaction was also determined from PCR amplification of DNA template and visualization of the resulting product after electrophoresis on an ethidium stained agarose gel. For the primer sets for amoA, Nitrobacter and Nitrospira described previously, PCR with the DNA template resulted in a PCR specific product at the expected size. The gel image in Figure 6-47 shows the single band obtained for each of the three genes.  1  500 bp  Figure 6-47  2  3  4  5  6 7  1 = 1kb plus ladder 2 = amoA membrane process sample 3 = amoA conventional process sample 4 = Nitrobacter membrane process sample 5 = Nitrobacter conventional process sample 6 = Nitrospira membrane process sample 7 = Nitrospira conventional process sample  PCR product from amoA, 16S rRNA Nitrobacter and 16S rRNA Nitrospira assays  Melt curve analysis was also performed for each qPCR assay to verify the specificity of PCR products formed during the qPCR reaction. A single peak at the melting temperature (Tm) is indicative of a specific product and it is evident from the dissociation curves of Figure 6-48 (b) and (c), that there were no non-specific PCR products for the  170  6: Results and Discussion  12000  (a) amoA  Fluorescence (dR)  Fluorescence (dR)  10000  8000  6000  4000  2000  0 50  55  60  65  70  75  80  85  90  95  70  80  100  Temperature (ooC)  Temperature ( C) 12000 (b) Nitrobacter  (b) Nitrobacter  Fluorescence (dR)  Fluorescence (dR)  10000  8000  6000  4000  2000  0 0  10  20  30  40  50  60  90  o  Temperature((oC) Temperature C)  12000 (c) Nitrospira  (c) Nitrospira  Fluorescence (dR)  Fluorescence (dR)  10000  8000  6000  4000  2000  0 50  60  70  80  90  100  o  Temperature (oC) Temperature ( C)  Figure 6-48  Dissociation curves 171  6: Results and Discussion  16S rRNA Nitrobacter and 16S rRNA Nitrospira assays. A single peak was obtained at melt temperatures of 69oC and 89oC for the 16S rRNA Nitrobacter and 16S rRNA Nitrospira assays, respectively. For the amoA assay, however, a low intensity peak was observed in addition to the high intensity peak at the melt temperature of 86oC. This peak occurred for some of the samples and also in combination with the high peak at the Tm. The presence of this peak could not be attributed to non-specific PCR product, since only a single band at the target size of 491 bp was observed when the corresponding PCR product was visualized on an agarose gel. This peak is possibly from background fluorescence.  6.5.3  Standard curves Linear regression analysis for the standard curve data for the amoA and  16S rRNA genes of Nitrobacter and Nitrospira qPCR assays are summarized in Table 6-21. The amplification efficiency (E) range of 85 – 96% and correlation coefficients (R2) of 0.98 – 0.99 indicate satisfactory data quality since a reliable standard curve should have a R2 value of more than 0.95 and a slope between −3.0 and −3.9 corresponding to PCR efficiencies of 80 – 115%. Table 6-21  Analysis of standard curves for individual real time assays  Target gene  amoA  16S rRNA Nitrobacter  16S rRNA Nitrospira  Slope  -3.430  -3.714  -3.493  0.998  0.975  0.993  96% 2 7 10 - 10  85% 2 8 10 - 10  93% 2 9 10 - 10  2  R  Amplification Efficiency * Linearity Range  *The amplification efficiency (%E) = (10-1/slope – 1)% Amplification efficiency indicates the increase in PCR product per cycle i.e. 2E .  6.5.4  Ammonia- and nitrite-oxidizing bacteria distribution Typical amplification plots for the sample sets are shown in Figure 6-49 (a), (b)  and (c) for the amoA, 16S rRNA Nitrobacter and 16S rRNA Nitrospira genes respectively. 172  6: Results and Discussion  35000  (a) amoA  Fluorescence  30000 25000 20000  15000 10000 Threshold  5000 0  0  5  10  15  20  25  30  35  Cycles 45000  (b) Nitrobacter  40000  Fluorescence  35000 30000 25000  20000 15000 10000 5000  Threshold  0 0  5  10  15  20  25  30  35  40  25  30  35  40  Cycles 40000  (c) Nitrospira 35000  Fluorescence  30000 25000 20000 15000 10000  Threshold  5000 0  0  5  10  15  20  Cycles  Figure 6-49  Amplification Plots 173  6: Results and Discussion  The Ct value for each of the samples was determined from the amplification plots. The copy number derived from this Ct value and the corresponding standard curve was normalized with the sample DNA concentration, and nitrifier population size was, therefore, expressed as copy number per ng DNA. Thus, populations are essentially measured as a relative proportion of the total community, rather than absolute numbers per volume. Normalizing with DNA concentration controlled for any differences in extraction efficiency within the sample set, as well as the difference in biomass concentration between the membrane process and conventional process samples. DNA was extracted from a fixed volume of mixed liquor sample. The values presented for the quantification represent the average of three replicates of the qPCR assays. For each of the replicates, the sample set was run together with triplicates of the standards. A comparison of the abundance of the nitrifiers for the two wastewater processes is illustrated in Figure 6-50. Each data point shown on the graph represents the copy number /ng DNA of the bacteria at the same time point for the two processes. The copy number /ng DNA for the membrane process is given along the x-axis and the corresponding value for the conventional process is given along the y-axis. It is recognized from the figure that while there was similarity in order of magnitude, there was substantial scatter of points along the diagonal line, indicating poor correlation between the two processes for abundances of AOBs, Nitrobacter and Nitrospira. This is substantiated by the low correlation coefficient values (r) of ramoA = -0.194, rnitrobacter = 0.05 and rnitrospira = -0.018. For both the membrane and conventional processes, the AOB were generally in the order of 102 –103 copies /ng DNA, whereas for nitrite oxidizers Nitrobacter and Nitrospira, the abundances were 103–104 copies /ng DNA and 104–105 copies /ng DNA respectively. A one-tailed distribution paired t-test at the 95% confidence interval indicated that differences in mean quantities between the membrane and conventional processes for the AOB were not significant. Similarly for the NOBs, there was no significant difference between bacteria quantities for the membrane and conventional processes. Comparable quantities of AOB as well as NOB, have also been reported previously in an SBR and MBR (Wittebolle et al., 2008).  174  6: Results and Discussion  1.E+06 Conventional (Copy number / ng DNA)  ramoA = -0.194  rnitobacter = 0.050  rnitrospira = -0.018  1.E+05  1.E+04  1.E+03  1.E+02  1.E+01  1.E+00 1.E+00  1.E+01  1.E+02  amoA  Nitrobacter  1.E+03  1.E+04  Nitrospira  1.E+05  1.E+06  Membrane (Copy number / ng DNA)  Figure 6-50  Abundance of ammonia and nitrite oxidizers in the membrane process and conventional process  The relative difference in abundance of the AOB and NOB obtained was the converse of what was anticipated. A greater quantity of AOB was expected since the NOB depends on the product generated by the AOB during the first step of the nitrification reaction and the energy produced from oxidation of ammonia is greater than for oxidation of nitrite. Such a relationship, where the AOB abundance exceeds the NOB abundances, has been reported by several others (Harms et al., 2003; Geets et al., 2007). However, the oxidation of ammonia is known to be the rate-limiting step, as it is appreciably slower than the oxidation of nitrite. Additionally, the reaction rate is considered to be a function of the amount of viable bacteria and the measured nitritation rates were found to be approximately ten times greater than the nitratation rates. These rates were presented earlier in sub-section 6.2.1.1. Lower quantities of AOB compared to NOB tend to be associated with partial nitrifying systems, but have also been reported for MBR (Urbain et al., 1998) activated sludge (Gieseke et al., 2001) as well as SBR wastewater systems and for systems in which there is complete nitrification (Gieseke et al., 2001; Dionisi et al., 2002; Robinson 175  6: Results and Discussion  et al., 2003; Wittebolle et al., 2008). Situations where the growth of AOB and NOB cannot be coupled have been explained by the availability of nitrite from the reduction of nitrate to nitrite in anaerobic microenvironments (Belser, 1979). The nitrite produced in these anaerobic microenvironments diffuses into aerobic microenvironments where it becomes available to nitrite oxidizers. Such anaerobic microenvironments can occur within the floc where the nitrifiers are found. The relative abundance of the populations may also result from the differences in growth rates of the bacteria. Studies measuring specific growth rates in both pure cultures and wastewater systems have demonstrated lower growth rates for AOB compared to NOB. Growth rates of 0.54 d-1 and 0.67 d-1 for Nitrosomonas and Nitrobacter were reported for enriched cultures (Blackburne et al., 2007b). Schramm (1999) reported approximate mean cell diameters of 1.5 and 0.7 m for Nitrosospira and Nitrospira, respectively. Thus, the difference in biomass may be less than the difference in cell numbers. Although the energy produced from ammonia oxidation is larger than for nitrite oxidation per molecule of substrate, a larger cell size of AOB than NOB could result in a lower growth rate of the former. Decay rates measured in the present study for the AOB and NOB were similar. Decay rates for both AOB and NOB averaged 0.07 d-1 for the membrane process and 0.14 d-1 for the conventional process during the period in which specific nitrification rates were greater in the membrane process relative to the conventional process. This similarity in decay rates for AOB and NOB as discussed previously, is in agreement with findings by others (Manser et al., 2006; Salem et al., 2006). It would be possible, therefore, that there would be a net loss of AOB as a result of a lower growth rate for the AOB compared to the NOB and consequently there would be a larger quantity of NOB in the system. The difference between nitritation and nitratation rates and abundance of bacteria could also be attributed to ammonia oxidization by organisms other than autotrophic ammonia-oxidizing bacteria. Some heterotrophic bacteria and recently, ammonia-oxidizing archaea (AOA), have been recognized to oxidize ammonia to produce similar end products as the AOB. There have been reports of AOA occurring in activated sludge bioreactors (Park et al., 2006). Like AOB, the AOA were found to contain all three subunits (amoA, amoB, and amoC) of ammonia monooxygenase, the enzyme responsible for ammonia oxidation. The primers used in the qPCR were, 176  6: Results and Discussion  however, specific for the amoA gene of betaproteobacteria and did not target the archeal amoA gene. The protozoa Vorticella was also observed in large numbers in both the membrane process and conventional process mixed liquors. They too have been recognized as organisms that are capable of oxidizing ammonia (Gerardi, 2002) and could have contributed to the ammonia oxidization. The disparity between nitritation and nitratation rates and expected nitrifier abundance could also be the due to the presence of inhibitors in the sample DNA template which affected amplification of AOB. However, it is probable that any inhibitors affected all assays equally. It is also possible that the DNA extraction method did not recover DNA with equal efficiency from all bacteria from the mixed liquor solids. Another possibility for the result is with regards to the primer set used for amplification of the amoA functional gene. The primer set amoA-1F and amoA-2R used, targets a stretch corresponding to positions 332 to 349 and 802 to 822 respectively for the amoA gene sequence of Nitrosomonas europea (Rotthauwe et al., 1997) and may not have targeted all of the AOB present in the wastewater systems, thus underestimating the total quantity of AOB. The fact that one of the samples (sample taken on day 412) did not amplify also presents evidence for this, since nitrification rate batch tests carried out on this day did indicate oxidation of ammonia. This primer set was selected since it was used successfully for activated sludge samples (Dionisi et al., 2002; LaPara and Ghosh, 2006; Siripong and Rittmann, 2007b; Falk et al., 2009). The standard curve correlation as well as amplification efficiency obtained using the primer set were indicative of an optimized assay. However, designing a single assay to detect all AOB is not possible, because of the high sequence variability among ammonia-oxidizing bacteria (Dionisi et al., 2002; Harms et al., 2003). Robinson et al. (2003) used primers targeting amoA functional gene and real-time PCR assay to determine AOB quantities in municipal and industrial wastewater samples. They noted that amoA genes from the organisms in both samples were sufficiently different that the real-time PCR assay developed for the municipal samples did not detect AOB in the industrial plant and concluded that quantification of AOB will require multiple assays to include the diverse populations that could exist within the activated sludge system. With respect to the NOB, Nitrobacter was present in lower abundance than Nitrospira. The two genera of NOB do not exclude each other, as both were detected in 177  6: Results and Discussion  all samples. Nitrobacter are r-strategists that thrive under high nitrite concentrations whereas Nitrospira are K-strategists that thrive under low nitrite concentrations (Schramm et al., 1999). Also, the growth rate for Nitrobacter is higher relative to that of Nitrospira (Wagner et al., 2002). The nitrite concentration in the aerobic zone of the pilot plant, where samples were taken, ranged between 0.01 and 0.9 mg N/L and hence, this relatively low nitrite concentration, which is typical of an activated sludge system, provided conditions which favored Nitrospira. Despite the low nitrite concentration, Nitrobacter was stably maintained in the reactor. The coexistence of both Nitrobacter and Nitrospira is not an unusual phenomenon, as both bacteria have been observed to coexist in wastewater systems (Coskuner and Curtis, 2002; Simm et al., 2005; Siripong and Rittmann, 2007a; Siripong and Rittmann, 2007b). This phenomenon is possibly an indication of a fluctuating operating nitrite concentration occurring in the wastewater treatment systems. The ability of Nitrobacter to grow heterotrophically may also account for its survival in an environment that is rich in organic matter. This coexistence of various nitrifiers, with different  characteristics,  demonstrates functional redundancy which has been  recognized as important for maintaining stable performance of reactors (Rittmann and McCarty, 2001).  6.5.5  Reactor operation and nitrifier abundance The relationships between the amoA, 16S rRNA Nitrobacter and 16S rRNA  Nitrospira gene abundance and measured operational data were examined via correlation coefficients. It can be seen from the data presented in Table 6-22 that there was generally no correlation between reactor operational parameters and abundance, and there were no correlations that were significant (p > 0.01), except for Nitrospira abundance and SVI. The lack of correlations observed could have been a consequence of the relatively stable operating conditions of the reactor. As discussed previously in section 6.1, except for temperature, plant operational parameters such as SRT, HRT, pH, and DO were kept reasonably constant.  178  6: Results and Discussion  Table 6-22  Correlation coefficients determined between reactor operational parameters and nitrifier abundance  Parameter pH DO MLSS SVI Influent NH4-N Effluent NH4-N Influent NOx-N Effluent NOx-N C/N Ratio Temp  Correlation Coefficient (r) Membrane Conventional -0.0187 p=0.949 0.2085 p=0.456 -0.4325 p=0.122 0.0396 p=0.889 0.0894 p=0.761 -0.2995 p=0.278 -0.1155 p=0.694 -0.0189 p=0.947 0.1421 p=0.628 -0.3098 p=0.261 -0.0266 p=0.928 -0.3640 p=0.182 0.2163 p=0.458 0.5887 p=0.021 -0.1677 p=0.567 0.1359 p=0.629 0.0279 p=0.925 -0.0227 p=0.936 0.0835 p=0.776 -0.3248 p=0.238  pH DO MLSS SVI Influent NH4-N Effluent NH4-N Influent NOx-N Effluent NOx-N C/N Ratio Temp  Membrane 0.1458 p=0.619 -0.0783 p=0.790 0.0860 p=0.770 -0.0760 p=0.796 0.2099 p=0.471 0.3763 p=0.185 0.1267 p=0.666 -0.5121 p=0.061 0.4474 p=0.109 -0.0670 p=0.820  Conventional 0.1836 p=0.530 -0.5684 p=0.034 -0.0851 p=0.772 0.5350 p=0.049 -0.0698 p=0.813 -0.3562 p=0.211 0.5738 p=0.032 -0.3282 p=0.252 0.3939 p=0.163 -0.0632 p=0.830  pH DO MLSS SVI Influent NH4-N Effluent NH4-N Influent NOx-N Effluent NOx-N C/N Ratio Temp  Membrane 0.1106 p=0.695 0.0844 p=0.765 -0.1030 p=0.715 0.0572 p=0.840 0.2638 p=0.342 -0.0490 p=0.862 -0.2018 p=0.471 0.3976 p=0.142 -0.0752 p=0.790 -0.2176 p=0.436  Conventional 0.3135 p=0.255 -0.5125 p=0.051 0.0586 p=0.836 0.6698 p=0.006 0.2910 p=0.293 -0.4633 p=0.082 0.2108 p=0.451 -0.2019 p=0.470 0.5417 p=0.037 -0.1302 p=0.644  amoA  16S rRNA Nitrobacter  16S rRNA Nitrospira  Although the temperature varied between 13 – 24oC, there was no correlation between the abundance and temperature, thus suggesting that the abundance of nitrifiers was not impacted by temperature. The study by Dionisi et al. (2002) which 179  6: Results and Discussion  quantified AOB abundance by a cPCR assay, also indicated no seasonal differences in abundance for both municipal and industrial mixed liquors. Similarly, Mertoglu (2008) reported no seasonal variation in AOB abundance as determined by qPCR assay. Limpiyakorn et al. (2005), however, noted that total numbers of AOB varied with season and reported the largest population during the winter. Temperature is known to affect the metabolic activity of the bacteria and is reflected by the nitrification rate. In the present study, no definitive relationship between nitrification rates and temperature was observed (Figure 6-51). The influent C/N ratio varied between 4 - 10 and there was no correlation between the nitrification rate and C/N ratio as illustrated in Figure 6-51. Reduction in nitrification rates has been previously associated with an increased proportion of carbon. Ballinger et al. (2002) reported from FISH quantification of AOB that changes in abundance of nitrifiers corresponded to changes in C/N ratio of a synthetic wastewater. In the study by Ballinger et al. (2002) an increase in C/N ratio from 2 to 5 resulted in a decrease in abundance of AOB. For both processes in the present study, there was no correlation between AOB abundance and C/N ratio. The NOB, however, showed higher correlation. The lack of correlation observed between nitrification rates and operational parameters that are known to affect the nitrification rate probably resulted from the influence of other parameters on the rate. It is recognized that the investigation was not carried out under intensely controlled conditions to determine effect of the parameters independently. As such, the parameters discussed were not varying in isolation and the effects on rates were probably masked by a more influential condition, for instance predator grazing. On the other hand, the conditions more accurately reflect real treatment systems.  180  6: Results and Discussion  Specific Nitrification Rate (mg N / gVSS·h)  (a) Membrane  o  C/N Ratio; Temperature ( C)  Specific Nitrification Rate (mg N / gVSS·h)  (b) Conventional  o  C/N Ratio; Temperature ( C)  Figure 6-51  6.5.6  Relation of specific nitrification rate with C/N ratio and temperature  Nitrifier abundance in relation to nitrification rate The performance of the membrane and conventional processes with respect to  specific nitrification rates was discussed previously in section 6.2. A comparison of the rates is presented in the Figure 6-52. As illustrated in the figure, the specific nitrification 181  6: Results and Discussion  rate was characterized by periods where rates for both processes were equal, greater for the membrane process, as well as lower for the membrane process, at times over the  (mgN/gVSS/d)  Conventional process specific nitrification nitrification rate process Conventional gVSS·d) N /specific rate (mg  period of the investigation.  5.0  r = 0.567 4.0  3.0  2.0  1.0  0.0 0.0  1.0  2.0  3.0  4.0  5.0  Membrane process specific nitrification rate (mgN/gVSS/d)  Membrane process specific nitrification rate (mg N/gVSS·d)  Figure 6-52  Comparison of specific nitrification rates between membrane and conventional processes  It has been established from the qPCR data presented that the membrane and conventional wastewater systems exhibited similar relative abundance of nitrifiers, however, there was variation in relative nitrifier quantity over the period of investigation. A plot comparing the abundance of nitrifiers in the two systems with operation time is presented in the bar charts of Figure 6-53. For statistical comparison, the operational period was divided into the following groups according to the relative nitrification performance of the two processes: Equal rates for both processes (day 10 to day 21, plus additional days 29, 232) Membrane rate consistently higher than conventional (day 258 to day 394) Membrane rate consistently lower than conventional rate (day 406 to day 472).  182  6: Results and Discussion  C=M  M>C  M<C  2500  (a) amoA  Copy DNADNA number / ng/ ng Copy number  2000 1500 1000 500 0  10  13  16  21  23  29  232 258 261 268 272 274 297 328 367 394 398 406 412 419 454 459 472  -500 -1000 -1500 -2000  Membrane Conventional  -2500  Day in Operation  Time (d)  20000  (b) Nitrobacter number Copy DNADNA / ng/ ng Copy number  15000  10000  5000  0 10  13  16  21  23  29  232 258 261 268 272 274 297 328 367 394 398 406 412 419 454 459 472  -5000  -10000  -15000 Membrane Conventional -20000  Day in Operation  Time (d)  200000  (c) Nitrospira DNA Copy number / /ngngDNA Copynumber  150000  100000  50000  0 10  13  16  21  23  29 232 258 261 268 272 274 297 328 367 394 398 406 412 419 454 459 472  -50000  -100000 Membrane Conventional -150000  DayTime in Operation (d)  Figure 6-53  Comparison of nitrifier abundance in the membrane and conventional systems Vertical bars represent difference between two processes (M-C)  183  6: Results and Discussion  For the AOB, it can be seen from the comparative Figure 6-53(a) that there was a notable difference between the two processes when the rate for the membrane was lower relative to the conventional rate, with the ammonia oxidizer abundance being lower in the membrane system. During the period where the rate was higher in the membrane, 63% of the samples showed higher quantities of AOB in the membrane system. Similarly for the Nitrobacter, the Figure 6-53(b) showed that except one sample, the quantity of NOB was greater in whichever of the two systems had the greater nitrification rate. With regards the Nitrospira, however, no relationship between abundance and relative nitrification rate was obvious. It would appear, therefore, that the relative performance of the systems in respect of specific nitrification rates is related to the relative quantity of the AOB and Nitrobacter present. Nitrospira, although present in greater relative abundance than the Nitrobacter showed no relationship to the process performance. A paired t-test was used to test the level of significance for the difference in abundance of nitrifiers between the two processes. The null hypothesis that there is a significant difference between the quantities was accepted for p < 0.01. This level of significance reflected correction with the Bonferoni method to account for testing subsets of the data set. It was found, however, that the statistical test did not show a particular relationship. It was anticipated that an increase in nitrifying bacteria would be accompanied by a corresponding increase in metabolic activity. The relationship of the copy number expressed per ng DNA to the specific reaction rate (mg O2/ g VSS·h) was determined by linear regression analysis and the plots for the AOB, Nitrobacter and Nitrospira are shown in the Figure 6-54 (a), (b) and (c) respectively. The rates plotted were measured by an OUR method where the nitrification reaction was measured as a two-step reaction, so that the rate of the AOB was distinguished from that of the NOB. There appeared to be no significant correlation between the rates and abundance in each of the processes, based on the R2 value. A similar observation was made by Mertoglu (2008) based on measurement of autotrophic/heterotrophic bacterial ratio using real-time PCR amoA/16S rRNA gene copy ratios. The study showed that while the amoA/16S rRNA ratio varied from 3.6% to 8.3%, there was no direct correlation between the amoA/16S rRNA ratio and the nitrification activity of the WWTP.  184  6: Results and Discussion  (a) amoA  (b) Nitrobacter  (c) Nitrospira  Figure 6-54  Correlation between abundance of nitrifiers and specific nitrification rate  185  6: Results and Discussion  This lack of correlation could be a consequence of the PCR-based assay in which DNA of both active and inactive bacteria are amplified and detected or an inhibition of the activity of the bacteria. Also, the total population as reflected by the total DNA may have varied independently of the nitrification rate. The lack of correlation between the nitrifier abundance and nitrification rate could be due to the fact that the metabolic rates may also depend on responses to nutrient status. The relationship between influent NH4-N and specific nitrification rate is presented in Figure 6-55. There was a natural variation in the influent NH4-N concentration that was typical of a domestic wastewater and this resulted in there being no correlation between the concentration and nitrification rate. As noted previously, the effect of a single parameter may be obscured because of the continuing interactions of several factors which may have influence on the nitrification rate. Lydmark et al. (2007) compared specific nitrification rates in systems with varying ammonia concentrations. They observed the lowest rate in the system with the highest ammonia and attributed their observation to limiting oxygen conditions in the system.  Specific Nitrification Rate (mg N/gVSS·h)  5.0  4.0  3.0  2.0  1.0 R² = 0.0067  R² = 0.0263 Conventional  Membrane  0.0 25  30  35  40  45  Influent NH4-N (mg/L)  Figure 6-55  Relation between influent NH4-N and specific nitrification rate  Another possibility for the absence of correlation between nitrifier abundance and nitrification rate could relate to the stability of the population arising from the retention within the systems. The wasting rates for the membrane process as shown in Figure 6-56 remained relatively constant throughout the reactor operation whereas there  186  6: Results and Discussion  was some fluctuation in the conventional process with wasting rates ranging between 50-158 L/d. It is seen, however, that under conditions of both constant and variable wasting rates that the populations were maintained.  250 Membrane  Conventional  Wasting Rate (L/d)  200  150  100  50 0  100  200  300  400  500  Reactor Operation Time (d)  Figure 6-56  6.5.7  Wasting rate for membrane and conventional processes  Summary of nitrifier quantitative dynamics Real time quantification of the nitrifiers indicated that the membrane and  conventional processes contained nitrifiers in similar abundance. Nitrospira was most abundant followed by Nitrobacter and then the AOB. The difference in abundance between each of the nitrifers was at least one order of magnitude. The relative difference in the AOB and Nitrobacter populations of the two processes correlated with the relative specific nitrification rate performance. The AOB population was for most instances (13 of 16 measurements), generally greater in the process with the higher specific nitrification rate. For Nitrobacter, the population was almost always greater (14 of 16 measurements) in the processes with the higher specific nitrification rate. No definitive relationship was observed for Nitrospira. 187  6: Results and Discussion  Decay rates measured during the various performance periods with respect to the specific nitrification rates correlated with the qPCR results, as the period with the higher decay rate exhibited a lower abundance of nitrifiers. For Nitrospira, however, no relationship could be established between relative abundance and relative specific rate performance. The abundance of nitrifiers did not correlate with the nitrification rate and the reactor operational conditions for both the membrane and conventional processes. The lack of correlation was attributed to the stability of the reactor conditions together with the influence of various parameters to which nitrifiers respond. The relative abundances of AOB and NOB were not coupled to the nitritation and nitratation reaction rates respectively. Lower growth rates for the AOB, together with similar decay rates for AOB and NOB, smaller cell size of the NOB, ammonia oxidation by heterotrophic bacteria and AOA and methodology factors such as DNA extraction efficiency and primer amplification of the target organism, may have contributed to this observation.  188  7: Conclusions and Recommendations  7  Conclusions and Recommendations  7.1  Summary The uncertainty surrounding the membrane process nitrification performance was  the engineering problem on which this research project was structured. The study was conducted as a comparison between the membrane EBPR process and the conventional EBPR process. The overall objective of the study was to identify factors that play a crucial role in determining the specific nitrification activity of the membrane EBPR process, relative to a conventional EBPR process. To address the overall objective, research questions focused on (i) specific nitrification rates under identical operating conditions, (ii) bacterial decay rates of the processes (iii) mechanisms affecting decay rates (i.e. aeration and predation), (iv) the nitrifying communities and (v) the abundance of nitrifiers. The following summarizes the findings of the study.  i.  Membrane and Conventional EBPR Processes The study confirmed the feasibility of application of membranes to the EBPR  process. The data confirmed the ability of the membrane bioreactor process in performing biological P and N removal at relatively short SRT of 12 d. The results also confirmed membrane bioreactor capability of removing the carbonaceous constituents of wastewater to achieve effluent quality which surpasses that of a clarifier-based process. The membrane process appeared to be more stable with respect to N removal as compared to P removal, based on the occurrence of P breakthrough in the effluent. P removal deteriorated during the low temperature operation for the membrane process, but N removal was unaffected. This could be a consequence of the relatively high fraction of aerobic biomass solids in the system. P removal in the conventional process was less affected by the low operational temperature as compared to the membrane process. The presence of nematodes in the conventional process appeared to reduce the biomass with the result that sludge yields for the conventional EBPR process were lower than for the membrane process. Nematodes were absent from the mixed liquor of the  189  7: Conclusions and Recommendations  membrane process. The presence of nematodes in the conventional process influenced the mixed liquor settling properties, presumably as a result of nematode grazing on the filamentous bacteria. The reduction of the filamentous bacteria resulted in improved settling which was indicated by lower SVI values. The membrane process showed more stability in relation to the biomass content and composition compared to the conventional process. The biomass of the conventional process was observed to periodically support the presence of higher organisms, in particular, nematodes and rotifers. While there was correlation between the appearance of rotifers and the nitrification rates, there was no correlation between the presence of the nematodes and the specific nitrification rate. The absence of a correlation between the specific nitrification rates and nematodes could be due to a simultaneous reduction of both nitrification rate and VSS content caused by nematodes. The presence of the nematodes resulted in a decrease in the system biomass.  ii.  Specific Nitrification Rates The results of the nitrification rate measurements, showed that the membrane  and the conventional system did not exhibit consistent differences in specific nitrification rates. There were periods where both processes exhibited equal rates, higher rates in the membrane train or lower rates in the membrane train. The processes cannot be categorized on the basis of a higher or lower specific nitrification rate because neither was a consistent characteristic of the individual processes and there appeared to be variation in the difference in rates. This variation in rates between the two processes, was primarily, a consequence of the variation in rates of the conventional process. Specific nitrification rate over the different periods averaged 3.4 mg N/g VSS·d and 3.3 mg N/g VSS·d at 20oC for the membrane and conventional processes respectively. The correction to 20oC was based on measured temperature coefficients of 1.055 and 1.064 for the membrane and conventional mixed liquors respectively. Although the average specific nitrification rates were nearly equal for both processes, the membrane process exhibited less variability in the individual rates compared to the conventional process. It is concluded therefore from specific nitrification rate  190  7: Conclusions and Recommendations  measurements that neither the membrane nor the conventional system outperformed the other with regard to specific nitrification rates. The supernatant of the membrane process appeared to contain inhibitors, likely soluble microbial products, which reduced specific nitrification rates. Although the inhibition caused a reduced nitrification rate in the membrane process, there were periods during which the membrane process nitrification rate was higher than that of the conventional process.  iii.  Decay rates During periods in which the specific nitrification rate was greater for the  membrane pilot scale EBPR process relative to that of the conventional process, the membrane process decay rate measured 0.11 d-1 compared to the conventional process decay rate of 0.19 d-1. During periods in which the specific nitrification rate was lower for the membrane process relative to the conventional process, the measured membrane process decay rate was 0.21 d-1 compared to the conventional process decay rate of 0.13 d-1. The decay rates for the two systems ranged from a low of 0.11 d -1 to a high of 0.21 d-1 and rate values were similar in both processes at either the high or low decay rate period. This amount of variability in decay rates for the processes might be linked to the interplay of the different mechanisms which account for bacterial decay. There were two mechanisms identified within the processes that could impact the decay rates for the processes. These included decay from shear induced by the vigorous coarse bubble aeration used in the membrane process and predation by the higher organisms in the conventional process.  iv.  Influence of Aeration Decay rates measured under different aeration types of fine and coarse bubble,  showed that the effect of shear arising from aeration was not significant. For the membrane process, decay rates were 0.11 d-1 and 0.12 d-1 and for the conventional process 0.19 d-1 and 0.20 d-1 when determined using fine and coarse bubble  191  7: Conclusions and Recommendations  respectively. It is to be considered, however, that these were small systems with minimal liquid depth and therefore, the effect may not be a general observation.  v.  Influence of Predation Rotifers were observed only in the conventional process. The decay rate was  measured with and without inhibition of the rotifers in the mixed liquor using cycloheximide. In the conventional mixed liquor with active predators, the decay rate was 0.10 d-1, whereas in the mixed liquor with inactivated rotifers, the decay rate was 0.06 d-1. It was thought that, with inactivation of the rotifers, the grazing pressure on the bacteria was removed and decay associated with the predator mechanism was reduced. This was reflected by a 40% decrease in the decay rate. Similar decay tests showed that the nematodes found only in the conventional sludge had no negative impact on the nitrifier decay rate. Decay rates in the conventional sludge were 0.13 d-1 and 0.16 d-1 for the sludge with active and inactive nematodes respectively. While the predation effect of the nematodes did not affect the nitrifiers, there was a significant effect on the sludge settleability properties, evident from the low SVI values and reduced filamentous bacteria.  vi.  Growth Rate The estimated value of autotrophic decay rate (bAUT) impacts on the autotrophic  growth rate (AUT) estimate, which is a significant parameter with regard to wastewater plant design. The assessment of the decay rates in this study established that a similar decay rate could be applied to both the membrane and conventional processes. Despite there being variability in the measured rates for the two processes, it was observed that the rates remained within the same range for both processes. It is recognized that the decay rates covered a moderately wide range which correlated with the changes in specific nitrification rate. While the predation mechanism and the changes in sludge microorganisms could account for the variability in decay rates for the conventional process, it cannot explain that of the membrane process. There are several mechanisms for decay and neither of the two mechanisms investigated (i.e. aeration and predation) seemed to relate to the changes in rates that were observed.  192  7: Conclusions and Recommendations  vii.  Nitrifier Community The T-RFLP results demonstrated that the nitrification process of both membrane  and conventional processes was mediated by a diverse group of AOB. With respect to the NOB, both Nitrobacter and Nitrospira were present in the processes but, the Nitrospira community was dominated by a single phylotype. There were clear differences in AOB community structure in the two processes, however, the NOB community was similar for both the membrane and conventional processes. In each of the processes, both the AOB and Nitrobacter communities were dynamic, changing over time with distinguishable shifts in populations. It could not be concluded whether the single Nitrospira population detected was variable in absolute abundance, because of limitations with the analysis. Changes in AOB composition occurred with operational time of the reactors for the two processes, despite maintaining relatively constant operational parameters of SRT and HRT throughout the period of the investigation. Process operational temperature was not controlled, and the T-RFLP analysis showed that in each of the processes, changes in community structure corresponded to changes in temperature. Statistical evaluation showed that there was a significant effect of temperature on the AOB and NOB communities. The DO and pH were also found to have likely effects on community structure in both processes, although the DO and pH values varied within a narrow range. For the conventional process, MLSS and SVI correlated strongly with community changes. The effects of predator grazing were reflected by the changes in the MLSS and SVI and, consequently, bacterial community structure. Despite the changes in community structure that occurred, the nitrification process remained stable and the plant consistently produced effluent low in NH4-N. Thus, stability of the nitrification process did not depend on the maintenance of a stable community composition. The relative specific nitrification rates in both the membrane and conventional processes were observed to relate to changes in AOB community composition of each process. The community dynamics, therefore, corresponded to reactor operational environment, in particular, the operational time, temperature and specific nitrification rate 193  7: Conclusions and Recommendations  of the processes. Particular populations were identified that were associated with these changes, while others changed in relative abundance with no clear pattern. There were a small number of populations that remained stable.  viii.  Nitrifier Abundance The membrane and conventional processes contained nitrifiers in similar  abundance. Nitrospira was most abundant followed by Nitrobacter and then the AOB. The difference in abundance between each of the nitrifier species was at least one order of magnitude. The relative difference in the AOB and Nitrobacter populations of the two processes correlated with the relative specific nitrification rate performance. The AOB population was almost always greater in the processes with the higher specific nitrification rate. Similarly for Nitrobacter, the population was almost always greater in the processes with the higher specific nitrification rate. No definitive relationship was observed for Nitrospira. Decay rates measured during the various performance periods with respect to the specific nitrification rates correlated with the qPCR results, as the period with the higher decay rate had a lower abundance of nitrifiers. For Nitrospira, however, no relationship could be established between relative abundance and relative specific rate performance. The abundance of nitrifiers did not correlate with the nitrification rate and the reactor operational conditions for both the membrane and conventional processes. The lack of correlations were attributed to the stability of the reactor conditions together with the influence of various parameters to which nitrifiers respond. The relative abundances of AOB and NOB were not coupled to the nitritation and nitratation reaction rates. Lower growth rates for the AOB together with similar decay rates for AOB and NOB, smaller cell size of the NOB, ammonia oxidation by heterotrophic bacteria and AOA and methodology factors such as DNA extraction efficiency and primer amplification of the target organism may contribute to this disparity.  194  7: Conclusions and Recommendations  7.2  Project conclusions From the comparative study of the membrane EBPR and conventional EBPR  processes, the following overall conclusions were derived with regard to the specific nitrification rates of the two processes: 1.  There is no characteristic difference in the specific nitrification rates between the two processes.  2.  There are differences in the two processes with respect to characteristics that could influence the rates such as nitrifying bacteria communities and nitrifier decay mechanisms; however, these may account for the variability in the specific nitrification rates but do not define the actual process.  Other conclusions include the following: 1.  The membrane process showed more stability in relation to the biomass content and composition compared to the conventional process.  2.  There was correlation between the appearance of rotifers and the nitrification rates, but there was no correlation between the presence of the nematodes and the specific nitrification rate in the conventional process. The nematodes were found to enhance the settleability properties of the conventional process mixed liquor and also to reduce the biomass content.  3.  The liquid phase of the membrane process contained inhibitors, likely SMPs, which impacted negatively on specific nitrification rates.  4.  Similar nitrifier decay rate can apply to both the membrane and conventional EBPR processes.  5.  The effect of shear arising from vigorous coarse bubble aeration was not significant on nitrifier decay rates.  6.  There were differences in AOB community structure in the two processes, however, the NOB community was similar for both the membrane and conventional processes.  195  7: Conclusions and Recommendations  7.  The AOB and Nitrobacter communities were dynamic, changing over time with distinguishable shifts in populations  8.  The community dynamics corresponded to reactor operational environment, in particular, the operational time, temperature and specific nitrification rate of the processes.  9.  The membrane and conventional processes contained nitrifiers in similar abundance.  10.  The abundance of nitrifiers correlated poorly with the nitrification rate and the reactor operational conditions for both the membrane and conventional processes.  7.3  Engineering significance The engineering problem which this research attempted to address, concerned  the potential limitation for the application of membranes in upgrading conventional BNR plants. This developed from the contradictory reports on membrane bioreactor nitrogen removal capability as research has presented conflicting views in respect of its ability to achieve nitrification rates on par with its conventional counterpart. This research was undertaken as a comparative study that allowed near identical conditions in both a membrane EBPR and conventional EBPR processes with respect to reactor volume, configuration, operating conditions, and wastewater source. The experimental design thus eliminated external factors contributing to the specific nitrification performance of the individual processes. The assessment of the nitrifier kinetics in this study established that similar nitrification kinetics apply to both the membrane EBPR and conventional EBPR processes. Both processes performed similarly with respect to nitrification rates. The bAUT which impacts on the AUT estimate is a significant parameter with regard to wastewater treatment plant process design. The nitrifier growth rate is used in determining SRT which is applied in the sizing of reactors for the nitrification process. Appropriate rates would therefore provide for an optimized design which could minimize  196  7: Conclusions and Recommendations  capital expenditure. Despite there being variability in the measured rates for the processes, the study showed that the rates remained within the same range for both processes. It is recognized, however, that the decay rates covered a moderately wide range which correlated with the variability in specific nitrification rate performance. The findings of this study, therefore, provide an improvement in the understanding of the membrane EBPR process and support the contention that the membrane EBPR process can be implemented for upgrade of conventional EBPR plants, without reservations regarding its capability to nitrify.  7.4  Recommendations for future research There were questions arising from the experiments completed and the data  obtained which were not addressed in this study, because of the project time constraint. These are recommended for further investigation and are outlined in the following. The test carried out, where the liquid phase and particulates of both processes were interchanged, suggested the presence of inhibitors in the membrane process which impacted nitrification performance. It appeared that the presence of inhibitors could limit the full nitrification potential of the membrane EBPR process. It was assumed that extracellular polymeric substance (EPS) was the probable cause of the inhibition. The source of the inhibitors should be confirmed and also quantified by analysis of the supernatant. This study was carried out under a fixed set of operating conditions and process operation conditions should be investigated which would minimize this source of inhibition. A limited number of clones were sequenced in this study and the data obtained were not sufficient to identify the nitrifiers to the species level. Identification of the nitrifiers to the species level should be undertaken by an extensive sequencing exercise, since changes in populations were noted under the different performance regimes. The role of organisms other than aerobic autotrophic bacteria that could contribute to ammonia oxidation in the processes should be investigated. This is recommended based on the higher quantity of NOB in the processes compared to AOB  197  7: Conclusions and Recommendations  that was observed and the recent findings of the presence of AOA in wastewater systems. A similar study to the present study comparing the membrane and conventional systems, is also recommended using a mixed wastewater source containing domestic, light industrial as well as stormwater, to represent a real-world scenario.  198  References  References Adam, C., Gnirss, R., Lesjean, B., Buisson, H., & Kraume, M. (2002) Enhanced biological phosphorus removal in membrane bioreactors. Water Science & Technology 46: 281–286. Aguilera Soriano, G., Erb, M., Garel, C., & Audic, J. M. (2003) A comparative pilot-scale study of the performance of conventional activated sludge and membrane bioreactors under limiting operating conditions. Water Environ Res 75: 225-231. Amann, R. I., Binder, B. J., Olson, R. J., Chisholm, S. W., Devereux, R., & Stahl, D. A. (1990) Combination of 16S rRNA-targeted oligonucleotide probes with flow cytometry for analyzing mixed microbial populations. Appl Environ Microbiol 56: 1919-1925. Annaka, Y., Hamamoto, Y., Akatsu, M., Maruyama, K., Oota, S., & Murakami, T. (2006) Development of MBR with reduced operational and maintenance costs. Water Science & Technology 53: 53-60. Antoniou, P., Hamilton, J., & Koopman, B. (1990) Effect of temperature and pH on the effective maximum specific growth rate of nitrifying bacteria. Water Research 24: 97101. Ballinger, S. J., Head, I. M., Curtis, T. P., & Godley, A. R. (2002) The effect of C/N ratio on ammonia oxidising bacteria community structure in a laboratory nitrificationdenitrification reactor. Water Science and Technology 46: 543-550. Barker, D. J., & Stuckey, D. C. (1999) A review of soluble microbial products (SMP) in wastewater treatment systems. Water Research 33: 3063–3082. Barnard, J. L. (1975) Biological nutrient removal without the addition of chemicals. Water Research 9: 485-490. Belser, L. W. (1979) Population ecology of nitrifying bacteria. Annual Review of Microbiology 33: 309-333. Belser, L. W., & Schmidt, E. L. (1980) Growth and oxidation kinetics of 3 genera of ammonia oxidizing nitrifiers. FEMS Microbiology Letters 7: 213-216. Benefield, L. D., & Randall, C. W. (1985) Biological process design for wastewater treatment. Charlottesville, Va., Inprint, 526 pp. Bérubé, P. R., Afonso, G., Taghipour, F., & Chan, C. C. V. (2006) Quantifying the shear at the surface of submerged hollow fiber membranes. J Membr Sci 279: 495-505. Bitton, G. (2005) Wastewater Microbiology. 3rd edn. John Wiley and Sons Inc,  199  References  Blackburne, R., Vadivelu, V. M., Yuan, Z., & Keller, J. (2007a) Kinetic characterization of an enriched Nitrospira culture with comparison to Nitrobacter. Water Research 41: 3033-3042. Blackburne, R., Vadivelu, V. M., Yuan, Z., & Keller, J. (2007b) Determination of Growth Rate and Yield of Nitrifying Bacteria by Measuring Carbon Dioxide Uptake Rate. Water Environ Res 79: 2437-2445(9). Bloem, J., Veninga, M., & Shepherd, J. (1995) Fully Automatic Determination of Soil Bacterium Numbers, Cell Volumes, and Frequencies of Dividing Cells by Confocal Laser Scanning Microscopy and Image Analysis. Appl Environ Microbiol 61: 926-936. Bowker, P. G., & Stensel, D. H. (1990) Phosphorus Removal from Wastewater. Pollution Technology Review No. 198. Bowker, D., Wareham, M., & Learner, M. (1983) The selection and ingestion of epilithic algae by Nais elinguis (Oligochaeta: Naididae). Hydrobiologia 98: 171-178. Chabaud, S., Andres, Y., Lakel, A., & Le Cloirec, P. (2006) Bacteria removal in septic effluent: Influence of biofilm and protozoa. Water Research 40: 3109-3114. Chen, R. D., & LaPara, T. M. (2008) Enrichment of dense nitrifying bacterial communities in membrane-coupled bioreactors. Process Biochemistry 43: 33-41. Chiemchaisri, C., & Yamamoto, K. (2005) Enhancement of oxygen transfer and nitrogen removal in a membrane separation bioreactor for domestic wastewater treatment. Water Science & Technology 51: 85-92. Chudoba, J. (1985) Inhibitory effect of refractory organic compounds produced by activated sludge micro-organisms on microbial activity and flocculation. Water Research 19: 197-200. Cicek, N. (2003) A review of membrane bioreactors and their potential application in the treatment of agricultural wastewater. Canadian Biosystems Engineering 45: Cicek, N., Franco, J., Suidan, M. T., Urbain, V., & Manem, J. (1999) Characterization and comparison of a membrane bioreactor and a conventional activated system in the treatment of wastewater containing high molecular weight compounds. Water Environment Research 71: 64-70. Ciesielski, S., Elimiuk, E., Mozejko, J., Nowakowska, E., & Pokoj, T. (2009) Changes in microbial community structure during adaptation towards polyhydroxyalkanoates production. Polish Journal of Biochemistry 58: 131-139. Cohen, Y., & Kirchmann, H. (2004) Increasing the pH of Wastewater to High Levels with Different Gases—CO2 Stripping. Water, Air, & Soil Pollution 159: 275.  200  References  Copp, J. B., & Murphy, K. L. (1995) Estimation of the Active Nitrifying Biomass in Activated Sludge. Water Research 29: 1855-1862. Coskuner, G., & Curtis, T. P. (2002) In situ characterization of nitrifiers in an activated sludge plant: detection of Nitrobacter spp. Journal Applied Microbiology 93: 431-437. Curtis, T. P., & Sloan, W. T. (2006) Towards the design of diversity: stochastic models for community assembly in wastewater treatment plants. Water Science and Technology 54: 227-236. Daims, H., Ramsing, N. B., Schleifer, K. H., & Wagner, M. (2001a) Cultivationindependent, semiautomatic determination of absolute bacterial cell numbers in environmental samples by fluorescence in situ hybridization. Appl Environ Microbiol 67: 5810-5818. Daims, H., Purkhold, U., Bjerrum, L., Arnold, E., Wilderer, P. A., & Wagner, M. (2001b) Nitrification in sequencing biofilm batch reactors: lessons from molecular approaches. Water Sci Technol 43: 9-18. Das, D., Keinath, T. M., Parker, D. S., & Wahlberg, E. J. (1993) Floc Breakup in Activated Sludge Plants. Water Environment Research 65: 145. Degrange, V., & Bardin, R. (1995) Detection and Counting of Nitrobacter Populations in Soil by PCR. Applied and Environmental Microbiology 61: 2093-2098. Denecke, M., & Liebig, T. (2003) Effect of carbon dioxide on nitrification rates. Bioprocess and Biosystems Engineering 25: 249-253. Dionisi, H. M., Layton, A. C., Harms, G., Gregory, I. R., Robinson, K. G., & Sayler, G. S. (2002) Quantification of Nitrosomonas oligotropha-Like Ammonia-Oxidizing Bacteria and Nitrospira spp. from Full-Scale Wastewater Treatment Plants by Competitive PCR. Appl Environ Microbiol 68: 245-253. Dold, P. L., Jones, R. M., & Bye, C. M. (2005) Importance and measurement of decay rate when assessing nitrification kinetics. Water Science & Technology 52: 469-477. Drews, A., Evenblij, H., & Rosenberger, S. (2005) Potential and Drawbacks of Microbiology–Membrane Interaction in Membrane Bioreactors. Environmental Progress 24: 426-433. du Toit, G. J., Ramphao, M. C., Parco, V., Wentzel, M. C., & Ekama, G. A. (2007) Design and performance of BNR activated sludge systems with flat sheet membranes for solid-liquid separation. Water Sci Technol 56: 105-113. Dufrene, M., & Legendre, P. (1997) Species assemblages and indicator species: the need for a flexible asymmetrical approach. Ecological Monographs 345-366.  201  References  Eaton, A. D., Clesceri, L. S., Rice, E. W., & Greenberg, A. E. (2005) Standard methods for the examination of water and wastewater. 21st edn. Egli, K., Langer, C., Siegrist, H. R., Zehnder, A. J. B., Wagner, M., & van der Meer, J. R. (2003) Community analysis of ammonia and nitrite oxidizers during start-up of nitritation reactors. Appl Environ Microbiol 69: 3213-3222. Elissen, H. J. H., Hendrickx, T. L. G., Temmink, H., & Buisman, C. J. N. (2006) A new reactor concept for sludge reduction using aquatic worms. Water Res 40: 3713-3718. Falk, M. W., Song, K., Matiasek, M. G., & Wuertz, S. (2009) Microbial community dynamics in replicate membrane bioreactors – Natural reproducible fluctuations. Water Res 43: 842-852. Fan, X. J., Urbain, V., Qian, Y., & Manem, J. (1996) Nitrification and mass balance with a membrane bioreactor for municipal wastewater treatment. Water Science & Technology 34: 129-136. Fan, X. J., Urbain, V., Qian, Y., Manem, J., Ng, W. J., & Ong, S. L. (2000) Nitrification in a membrane bioreactor (MBR) for wastewater treatment. Water Science & Technology 42: 289-294. Fisher, M. M., & Triplett, E. W. (1999) Automated Approach for Ribosomal Intergenic Spacer Analysis of Microbial Diversity and Its Application to Freshwater Bacterial Communities. Appl Environ Microbiol 65: 4630-4636. Gander, M., Jefferson, B., & Judd, S. (2000) Aerobic MBRs for domestic wastewater treatment: A review with cost considerations. Sep Purif Technol 18: 119-130. Gao, M., Yang, M., Li, H., Yang, Q., & Zhang, Y. (2004a) Comparison between a submerged membrane bioreactor and a conventional activated sludge system on treating ammonia-bearing inorganic wastewater. Journal of Biotechnology 108: 265269. Gao, M. C., Yang, M., Li, H. Y., Wang, Y. M., & Pan, F. (2004b) Nitrification and sludge characteristics in a submerged membrane bioreaction on synthetic inorganic wastewater. Desalination 170: 177-185. Geets, J., de Cooman, M., Wittebolle, L., Heylen, K., Vanparys, B., De Vos, P. et al. (2007) Real-time PCR assay for the simultaneous quantification of nitrifying and denitrifying bacteria in activated sludge. Applied Microbiology and Biotechnology 75: 211-221. Geng, Z., & Hall, E. R. (2007) A comparative study of fouling-related properties of sludge from conventional and membrane enhanced biological phosphorus removal processes. Water Res 41: 4329-4338.  202  References  Gerardi, M. H. (2002) Nitrification and denitrification in the activated sludge process. John Wiley and Sons Inc, Ghyoot, W., & Verstraete, W. (2000) Reduced sludge production in a two-stage membrane-assisted bioreactor. Water Research 34: 205-215. Ghyoot, W., Vandaele, S., & Verstrate, W. (1999) Nitrogen removal from sludge reject water with a membrane assisted bioreactor. Water Research 33: 23-32. Gieseke, A., Purkhold, U., Wagner, M., Amann, R., & Schramm, A. (2001) Community structure and activity dynamics of nitrifying bacteria in a phosphate-removing biofilm. Applied and Environmental Microbiology 67: 1351-1362. Grady, L. C. P. J., Daigger, G. T., & Lim, H. C. (1999) Biological wastewater treatment. 2nd edn. Marcel Dekker, Inc, Gude, H. (1979) Grazing by Protozoa as Selection Factor for Activated Sludge Bacteria. Microbial Ecology 5: 225-237. Guisasola, A., K. Chandran, K., Smets, B. F., Baeza, J. A., Carrera, J., & Lafuente, J. (2006) Observation and mathematical description of the acceleration phenomenon in batch respirograms associated with ammonium oxidation. Water Science and Technology 54: 181-188. Hahn, M., Wilhelm, J., & Pingoud, A. (2001) Influence of fluorophor dye labels on the migration behavior of polymerase chain reaction - amplified short tandem repeats during denaturing capillary electrophoresis. Electrophoresis 22: 2691-2700. Hall, E. R., Monti, A., & Mohn, W. W. (2010) A comparison of bacterial populations in enhanced biological phosphorus removal processes using membrane filtration or gravity sedimentation for solids–liquid separation. Water Res 44: 2703-2714. Halling-Sorensen, B., & Jorgensen, S. E. (1993) The removal of nitrogen compounds from wastewater. Amsterdam, The Netherlands, Elsevier Science Publishers, Han, S., Bae, T., Jang, G., & Tak, T. (2005) Influence of sludge retention time on membrane fouling and bioactivities in membrane bioreactor system. Process Biochemistry 40: 2393-2400. Hao, X., Wang, Q., Cao, Y., & van Loosdrecht, M. C. M. (2010) Measuring the activities of higher organisms in activated sludge by means of mechanical shearing pretreatment and oxygen uptake rate. Water Res 44: 3993-4001. Harms, G., Layton, A. C., Dionisi, H. M., Gregory, I. R., Garrett, V. M., Hawkins, S. A. et al. (2003) Real-Time PCR Quanitfication of Nitrifying Bacteria in a Municipal Water Treatment Plant. Environmental Science and Technology 37: 343-351.  203  References  Hartmann, M., Enkerli, J., & Widmer, F. (2007) Residual polymerase activity-induced bias in terminal restriction fragment length polymorphism analysis. Environ Microbiol 9: 555-559. Hasar, H., Kinaci, C., & Unl¨u, A. (2002) Viability of microbial mass in a submerged membrane bioreactor. Desalination 150: 263-268. Hendrickx, T. L. G., Temmink, H., Elissen, H. J. H., & Buisman, C. J. N. (2009a) The effect of operating conditions on aquatic worms eating waste sludge. Water Research 43: 943-950. Hendrickx, T. L. G., Temmink, H., Elissen, H. J. H., & Buisman, C. J. N. (2009b) Aquatic worms eating waste sludge in a continuous system. Bioresour Technol 100: 46424648. Holbrook, R. D., Massie, K. A., & Novak, J. T. (2005) A Comparison of Membrane Bioreactor and Conventional-Activated-Sludge Mixed Liquor and Biosolids Characteristics. Water Environment Research 77: 323-330. Hornek, R., Pommerening-Roser, A., Koops, H., Farnleitner, A. H., Kreuzinger, N., Kirschner, A., & Mach, R. L. (2006) Primers containing universal bases reduce multiple amoA gene specific DGGE band patterns when analysing the diversity of beta-ammonia oxidizers in the environment. Journal of Microbiological Methods 66: 147-155. Horz, H., Rotthauwe, J., Lukow, T., & Liesack, W. (2000) Identification of major subgroups of ammonia-oxidizing bacteria in environmental samples by T-RFLP analysis of amoA PCR products. Journal of Microbiological Methods 39: 197-204. Huang, X., Gui, P., & Qian, Y. (2001) Effect of sludge retention time on microbial behaviour in a submerged membrane bioreactor. Process Biochemistry 36: 10011006. Huang, X., Liu, R., & Gian, Y. (2000) Behaviour of soluble microbial products in a membrane bioreactor. Process Biochem 36: 401-406. Huang, X., Liang, P., & Qian, Y. (2007) Excess sludge reduction induced by Tubifex tubifex in a recycled sludge reactor. J Biotechnol 127: 443-451. Hwang, J. H., & Oleszkiewicz, J. A. (2007) Effect of Cold-Temperature Shock on Nitrification. Water Environment Research 79: 964-968; 964. Ichihashi, O., Satoh, H., & Mino, T. (2006) Effect of soluble microbial products on microbial metabolisms related to nutrient removal Water Research 40: 1627-1633.  204  References  Jetten, M. S. M., Strous, M., van de Pas-Schoonen, K. T., Schalk, J., van Dongen, U. G. J. M., van de Graaf, A. A. et al. (1998) The anaerobic oxidation of ammonium. FEMS Microbiol Rev 22: 421-437. Judd, S. (2006) The MBR Book. Principles and applications of membrane bioreactors in water and wastewater treatment. Elservier Ltd, Juretschko, S., Timmermann, G., Schmid, M., Schleifer, K. H., Pommerening-Roser, A., Koops, H. P., & Wagner, M. (1998) Combined molecular and conventional analyses of nitrifying bacterium diversity in activated sludge: Nitrosococcus mobilis and Nitrospiralike bacteria as dominant populations. Appl Environ Microbiol 64: 3042-3051. Kaewpipat, K., & Grady, C. P. L. J. (2002) Microbial population dynamics in laboratoryscale activated sludge reactors. Water Science and Technology 46: 19-27. Katehis, D. (2005) Measurement of maximum nitrifier specific growth rate for use in activated sludge modeling. Katehis, D., Fillos, J., & Carrio, L. A. (2002) Comparison of bench scale testing methods for nitrifier growth rate measurement. Water Sci Technol 46: 289-295. Kelly, J. J., Siripong, S., McCormack, J., Janus, L. R., Urakawa, H., Fantroussi, S. E. et al. (2005) DNA microarray detection of nitrifying bacterial 16S rRNA in wastewater treatment plant samples. Water Research 39: 3229–3238. Kim, J. S., Lee, C. H., & Chang, I. S. (2001) Effect of pump shear on the performance of a crossflow membrane bioreactor. Water Research 35: 2137-2144. Konneke, M., Bernhard, A. E., de la Torre, J. R., Walker, C. B., Waterbury, J. B., & Stahl, D. A. (2005) Isolation of an autotrophic ammonia-oxidizing marine archaeon. Nature 437: 543-546. Konuma, S., Satoh, H., Mino, T., & Matsuo, T. (2001) Comparison of enumeration methods for ammonia-oxidizing bacteria. Water Science and Technology 43: 107-114. Kowalchuk, G. A., & Stephen, J. R. (2001) Ammonia Oxidizing Bacteria: A Model for Molecular Microbial Ecology. Annual Review of Microbiology 55: 485-529. Kuo, D. H. W., Robinson, K. G., Layton, A. C., Meyers, A. J., & Sayler, G. S. (2006) Real-time PCR quantification of ammonia-oxidizing bacteria (AOB): Solids retention time (SRT) impacts during activated sludge treatment of industrial wastewater. Environmental Engineering Science 23: 507-520. LaPara, T. M., & Ghosh, S. (2006) Population dynamics of the ammonia-oxidizing bacteria in a full-scale municipal wastewater treatment facility. Environ Eng Sci 23: 309-319.  205  References  Laspidou, C. S., & Rittmann, B. E. (2002) A unified theory for extracellular polymeric substances, soluble microbial products, and active and inert biomass. Water Res 36: 2711-2720. Lee, N. M., & Welander, T. (1994) Influence of predators on nitrification in aerobic biofilm. Water Science & Technology 29: 9-355. Lee, Y., & Oleszkiewicz, J. A. (2003) Effects of predation and ORP conditions on the performance of nitrifiers in activated sludge systems. Water Research 37: 4202-4210. Lee, Y., and Oleszkiewicz, J. A. Evaluation of maximum growth and decay rates of autotrophs under different physical and environmental conditions. 2954-2969. Lee, H., Han, J., & Yun, Z. (2009) Biological nitrogen and phosphorus removal in UCTtype MBR process. Water Sci Technol 59: 2093-2099. Lee, Y., and Oleszkiewicz, J. A. (2002) Evaluation of maximum growth and decay rates of autotrophs under different physical and environmental conditions. Chicago, IL, United States: 2954-2969. Lesjean, B., Gnirss, R., & Adam, C. (2002) Process configurations adapted to membrane bioreactors for enhanced biological phosphorous and nitrogen removal. Desalination 149: 217-224. Levin, G., & Shapiro, J. (1965) Metabolic uptake of phosphorus by wastewater organisms. Journal Water Pollution Control Federation 37: 800-821. Li, F., Chen, J., & Deng, C. (2006a) The kinetics of crossflow dynamic membrane bioreactor Water SA 32: 199-204. Li, H., Yang, M., Zhang, Y., Yu, T., & Kamagata, Y. (2006b) Nitrification performance and microbial community dynamics in a submerged membrane bioreactor with complete sludge retention. Journal of Biotechnology 123: 60-70. Li, H. Y., Yang, M., Zhang, Y., Liu, X. C., Gao, M. C., & Kamagata, Y. (2005) Comparison of nitrification performance and microbial community between submerged membrane bioreactor and conventional activated sludge system. Water Science and Technology 51: 193. Liang, P., Huang, X., & Qian, Y. (2006) Excess sludge reduction in activated sludge process through predation of Aeolosoma hemprichi. Biochem Eng J 28: 117-122. Liebig, T., Wagner, M., Bjerrum, L., & Denecke, M. (2001) Nitrification performance and nitrifier community composition of a chemostat and a membrane-assisted bioreactor for the nitrification of sludge reject water. Bioprocess and Biosystems Engineering 24: 203-210.  206  References  Limpiyakorn, T., Shinohara, Y., & Yagi, O. (2005) Communities of ammonia-oxidizing bacteria in activated sludge of various sewage treatment plants in Tokyo. Microbial Ecology 54: 205-217. Liu, W. T., Marsh, T. L., Cheng, H., & Forney, L. J. (1997) Characterization of microbial diversity by determining terminal restriction fragment length polymorphisms of genes encoding 16S rRNA. Appl Environ Microbiol 63: 4516-4522. Luxmy, B. S., Nakajima, F., & Yamamoto, K. (2000a) Analysis of bacterial community in membrane-separation bioreactors by fluorescent in situ hybridization (FISH) and denaturing gradient gel electrophoresis (DGGE) techniques. Water Science and Technology 41: 259–268. Luxmy, B. S., Nakajima, F., & Yamamoto, K. (2000b) Predator grazing effect on bacterial size distribution and floc size variation in membrane-separation activated sludge. Water Science and Technology 42: 211-217. Lydmark, P., Almstrand, R., Samuelsson, K., Mattsson, A., Sörensson, F., Lindgren, P., & Hermansson, M. (2007) Effects of environmental conditions on the nitrifying population dynamics in a pilot wastewater treatment plant. Environ Microbiol 9: 22202233. Macomber, J., Cicek, N., Suidan, M. T., Jan, D., Ginestet, P., & Audic, J. M. (2005) Biological kinetic data evaluation of an activated sludge system coupled with an ultrafiltration membrane. ASCE Journal of Environmental Engineering 131-134: 579586. Madigan, M. T., Martinko, J. M., & Parker, J. (2000) Brock biology of microorganisms. 10th edn. Prentice Hall. Manser, R., Gujer, W., & Siegrist, H. (2006) Decay processes of nitrifying bacteria in biological wastewater treatment systems. Water Research 40: 2416-2426. Manser, R., Gujer, W., & Siegrist, H. (2005a) Consequences of mass transfer effects on the kinetics of nitrifiers. Water Research 39: 4633-4642. Manser, R., Gujer, W., & Siegrist, H. (2005b) A rapid method for quantification of nitrifiers in activated sludge. Water Research 39: 1585-1593. Manser, R., Gujer, W., & Siegrist, H. (2005c) Membrane bioreactor versus conventional activated sludge system: population dynamics of nitrifiers. Water Sci Technol 52: 417425. Martinage, V., & Paul, E. (2000) Effect of environmental parameters on autotrophic decay rate (b(A)). Environ Technol 21: 31–41.  207  References  Masse, A., Sperandio, M., & Cabassud, C. (2006) Comparison of sludge characteristics and performance of a submerged membrane bioreactor and an activated sludge process at high solids retention time. Water Research 40: 2405-2415. McCune, B., & Grace, J. (2002) Analysis of Ecological Communities. Gleneden Beach, Oregon, USA, MjM Software Design. Melcer, H., & Dold, P. (2004) Methods for Wastewater Characterization in Activated Sludge Modeling: WERF Report. IWA Publishing, Menniti, A., & Morgenroth, E. (2010) The influence of aeration intensity on predation and EPS production in membrane bioreactors. Water Res 44: 2541-2553. Merlo, R. P., Trussell, R. S., Hermanowicz, S. W., & Jenkins, D. (2007) A Comparison of the Physical, Chemical, and Biological Properties of Sludges from a Complete-Mix Activated Sludge Reactor and a Submerged Membrane Bioreactor. Water Environment Research 79: 328. Mertoglu, B. (2008) Long-term assessment of nitrification in a full-scale wastewater treatment plant. Journal of Environmental Science and Health, Part A: Toxic/Hazardous Substances and Environmental Engineering 43: 538. Mino, T., van Loosdrecht, M. C. M., & Heijnen, J. J. (1998) Microbiology and biochemistry of the enhanced biological phosphate removal process. Water Research 32: 3193-3207. Miura, Y., Hiraiwa, M. N., Ito, T., Itonaga, T., Watanabe, Y., & Okabe, S. (2007) Bacterial community structures in MBRs treating municipal wastewater: Relationship between community stability and reactor performance. Water Research 41: 627-637. Mobarry, B. K., Wagner, M., Urbain, V., Rittmann, B. E., & Stahl, D. A. (1996) Phylogenetic probes for analyzing abundance and spatial organization of nitrifying bacteria. Applied Environmental Microbiology 62: 2156-2162. Monti, A. (2006) Impact and potential of membrane solids-liquid separation in biological nutrient removal processes. Ph.D. Thesis. Department of Civil Engineering, University of British Columbia, Vancouver, Canada. Monti, A., Hall, E. R., Dawson, R. N., Husain, H., & Kelly, H. G. (2006) Comparative study of biological nutrient removal (BNR) processes with sedimentation and membrane-based separation. Biotechnol Bioeng 94: 740-752. Moussa, M. S., Lubberding, H. J., Hooijmans, C. M., van Loosdrecht, ,M.C.M., & Gijzen, H. J. (2003) Improved method for determination of ammonia and nitrite oxidation activities in mixed bacterial cultures. Appl Microbiol Biotechnol 63: 217-221.  208  References  Moussa, M. S., Hooijmans, C. M., Lubberding, H. J., Gijzen, H. J., & van Loosdrecht, M. C. M. (2005) Modelling nitrification, heterotrophic growth and predation in activated sludge. Water Research 39: 5080-5098. Muyzer, G., De Waal, E. C., & Uitierlinden, A. G. (1993) Profiling of Complex Microbial Populations by Denaturing Gradient Gel Electrophoresis Analysis of Polymerase Chain Reaction-Amplified Genes Coding for 16S rRNA. Applied and Environmental Microbiology 59: 695-700. Nakagawa, G., Ebie, Y., Tsuneda, S., Matsumura, M., & Inamori, Y. (2007) Use of realtime PCR to examine the relationship between ammonia oxidizing bacterial populations and nitrogen removal efficiency in a small decentralized treatment system Johkasou. Water Science and Technology 55: 203-210. Ng, H. Y., & Hermanowicz, S. W. (2005) Membrane bioreactor operation at short solids retention times: performance and biomass characteristics. Water Res 39: 981-992. Ng, H. Y., Tan, T. W., Ong, S. L., Toh, C. A., & Loo, Z. P. (2006) Effects of solid retention time on the performance of submerged anoxic/oxic membrane bioreactor. Water Sci Technol 53: 7-13. Nicolaisen, M. H., & Ramsing, N. B. (2002) Denaturing gradient gel electrophoresis (DGGE) approaches to study the diversity of ammonia-oxidizing bacteria. Journal of Microbiological Methods 50: 189-203. Nowak, O., Schwighofer, P., & Svardal, K. (1994) Nitrification inhibition – a method for the estimation of actual maximum autotrophic growth rates in activated sludge systems. Water Environment Researchter Science and Technology 30: 9-19. Oldham, W. K., & Rabinowitz, B. (2001) Development of biological nutrient removal technology in Western Canada. Canadian Journal of Civil Engineering 28: 92-101. Parco, V., du Toit, G., Wentzel, M., & Ekama, G. (2007) Biological nutrient removal in membrane bioreactors: denitrification and phosphorus removal kinetics. Water Sci Technol 56: 125-134. Parco, V., Wentzel, M., & Ekama, G. (2006) Kinetics of nitrogen removal in a MBR nutrient removal activated sludge system. Desalination 199: 89-91. Park, H. D., Wells, G. F., Bae, H., Criddle, C. S., & Francis, C. A. (2006) Occurrence of ammonia-oxidizing archaea in wastewater treatment plant bioreactors. Appl Environ Microbiol 72: 5643-5647. Pereira, H., Lemos, P. C., Reis, M. A. M., Crespo, J. P. S., Carrondo, M. J. T., & Santos, H. (1996) Model for carbon metabolism in biological phosphorus removal processes based on in vivo 13C-NMR labelling experiments Water Research 30: 2128-2138.  209  References  Petropoulos, P., & Gilbride, K. A. (2005) Nitrification in activated sludge batch reactors is linked to protozoan grazing of the bacterial population. Can J Microbiol 51: 791-799. Poly, F., Wertz, S., Brothier, E., & Degrange, V. (2008) First exploration of Nitrobacter diversity in soils by a PCR cloning-sequencing approach targeting functional gene nxrA. FEMS Microbiol Ecol 63: 132-140. Ramphao, M., Wentzel, M. C., Merritt, R., Ekama, G. A., Young, T., & Buckley, C. A. (2005) Impact of Membrane Solid–Liquid Separation on Design of Biological Nutrient Removal Activated Sludge Systems. Biotecnology and Bioengineering 89: 630-646. Ratsak, C.,H, & Verkuijlen, J. (2006) Sludge reduction by predatory activity of aquatic oligochaetes in wastewater treatment plants: Science or fiction? A review. Hydrobiologia 564: 197-211. Ratsak, C. H., Maarsen, K. A., & Kooijman, S. A. L. M. (1996) Effects of protozoa on carbon mineralization in activated sludge. Water Res 30: 1-12. Ratsak, C. H., Koouman, S. A. L. M., & Kooi, B. W. (1993) Modelling the growth of an oligochaete on activated sludge. Water Res 27: 739-747. Ratsak, C. H. (2001) Effects of Nais elinguis on the performance of an activated sludge plant. Hydrobiologia 463: 222. Regan, J. M., Harrington, G. W., & Noguera, D. R. (2002) Ammonia- and nitrite-oxidizing bacterial communities in a pilot-scale chloraminated drinking water distribution system. Appl Environ Microbiol 68: 73-81. Rensink, J. H., & Rulkens, W. H. (1997) Using metazoa to reduce sludge production. Water Science and Technology 36: 171-179. Rittmann, B. E., & McCarty, P. L. (2001) Environmental Biotechnology: Principles and Applications. Boston, McGraw-Hill, 754 pp. Robinson, K. G., Dionisi, H. M., Harms, G., Layton, A. C., Gregory, I. R., & Sayler, G. S. (2003) Molecular assessment of ammonia- and nitrite-oxidizing bacteria in full-scale activated sludge wastewater treatment plants. Water Science and Technology 48: 119–126. Rosen, C., Ingildsen, P., Guildal, T., Nielsen, T. M., Nielsen, M. K., Jacobsen, B. N., & Thomsen, H. A. (2006) Introducing biological phosphorus removal in an alternating plant by means of control: a full scale study. Water Science and Technology 53: 133– 141. Rosenberger, S., Witzig, R., Manz, W., Kraume, M., & Szewszyk, U. (2000) Operation of different membrane bioreactors: experimental results and physiological state of the microorganisms. Water Science and Technology 41: 269–277.  210  References  Rosenberger, S., Krüger, U., Witzig, R., Manz, W., Szewzyk, U., & Kraume, M. (2002) Performance of a bioreactor with submerged membranes for aerobic treatment of municipal wastewater. Water Research 36: 413–420. Rotthauwe, J., Witzel, K., & Liesack, W. (1997) The ammonia monooxygenase structural gene amoA as a functional marker: molecular fine-scale analysis of natural ammoniaoxidizing populations. Applied and Environmental Microbiology 63: 4704-4712. Salem, S., Moussa, M. S., & van Loosdrecht, M. C. M. (2006) Determination of the decay rate of nitrifying bacteria. Biotechnology and Bioengineering 94: 252-262. Schmidt, I., Sliekers, O., Schmid, M., Bock, E., Fuerst, J., Kuenen, J. G. et al. (2003) New concepts of microbial treatment processes for the nitrogen removal in wastewater. FEMS Microbiol Rev 27: 481-492. Schramm, A., de Beer, D., van den Heuvel, J. C., Ottengraf, S., & Amann, R. (1999) Microscale distribution of populations and activities of Nitrosospira and Nitrospira spp. along a macroscale gradient in a nitrifying bioreactor: quantification by in situ hybridisation and the use of microsensors. Applied and Environmental Microbiology 65: 3690–3696. Schutte, U., Abdo, Z., Bent, S., Shyu, C., Williams, C., Pierson, J., & Forney, L. (2008) Advances in the use of terminal restriction fragment length polymorphism (T-RFLP) analysis of 16S rRNA genes to characterize microbial communities. Appl Microbiol Biotechnol 80: 365-380. Setter, K. J. (1995) Attached growth nitrification using Ringlace media. M.Sc. Thesis. Department of Civil Engineering, University of British Columbia, Vancouver, Canada. Siegrist, H., Brunner, I., Koch, G., Phan, L. C., & Le, V. C. (1999) Reduction of biomass decay rate under anoxic and anaerobic conditions. Water Science and Technology 39: 129–137. Siegrist, H., and Gujer, W. (1994) Nitrogen Removal in Activated-Sludge Systems Including Denitrification in Secondary Clarifiers. Water Sci Technol 30: 101-111. Siegrist, H., Krebs, P., Buhler, R., Purtschert, I., Rock, C., & Rufer, R. (1995) Denitrification In, Secondary Clarifiers. Water Sci Technol 31: 205-214. Simm, R. A., Ramey, W. D., & Mavinic, D. S. (2005) Nitrifier population dynamics in a bench-scale conventional activated sludge reactor following an induced perturbation. Journal of Environmental Engineering & Science 4: 385-397. Siripong, S., & Rittmann, B. E. (2007a) Diversity study of nitrifying bacteria in full-scale municipal wastewater treatment plants. Water Research 41: 1110-1120.  211  References  Siripong, S., & Rittmann, B. E. (2007b) Diversity study of nitrifying bacteria in full-scale municipal wastewater treatment plants. Water Research 41: 1110-1120. Sperandio, M., Masse, A., Espinosa-Bouchot, M. C., & Cabassud, C. (2005) Characterization of sludge structure and activity in submerged membrane bioreactor. Water Sci Technol 52: 401-408. Statistics Canada. (2009) Population by year, by province and territory. http://www40.ststcan.gc.ca/101/cst01/demo02a-eng.htm. Accessed 07 August 2009. Stenstrom, M. K., & Song, S. S. (1991) Effects of oxygen transport limitation on nitrification in the activated sludge process. Research Journal Water Pollution Control Federation 63: 208-219. Su, Y., Makinia, J., & Pagilla, K. R. (2008) Estimation of Autotrophic Maximum Specific Growth Rate Constant: Experience from the Long-Term Operation of a LaboratoryScale Sequencing Batch Reactor System. Water Environ Res 80: 355-366(12). Tchobanoglous, G., Burton, F. L., Stensel, H. D., & Metcalf & Eddy. (2003) Wastewater engineering : treatment and reuse. 4th edn. Boston, McGraw-Hill, 1819 pp. Terahara, T., Hoshino, T., Tsuneda, S., Hirata, A., & Inamori, Y. (2004) Monitoring the microbial population dynamics at the start-up stage of wastewater treatment reactor by terminal restriction fragment length polymorphism analysis based on 16S rDNA and rRNA gene sequences. Journal of Bioscience and Bioengineering 98: 425-428. Urbain, V., Mobarry, B., de Silva, V., Stahl, D. A., Rittmann, B. E., & Manem, J. (1998) Integration of performance, molecular biology and modeling to describe the activated sludge process. Water Science and Technology 37: 223-229. USEPA. (1993) Manual: Nitrogen Control. EPA 625/R-93/0010. U.S. Environmental Protection Agency, Office of Research and Development, Washington, DC. van Dijk, L., & Roncken, G. C. G. (1997) Membrane bioreactors for wastewater treatment: The state of the art and new developments. Water Science & Technology 35: 35-41. van Loosdrecht, M. C. M., & Henze, M. (1999) Maintenance, endogenous respiration, lysis, decay and predation. Water Science and Technology 39: 107–117. Vanrolleghem, P., Spanjers, H., Petersen, B., Ginestet, P., & Takacs, I. (1999) Estimating (Combinations of) Activated Sludge Model No.1 parameters and components by respirometry. Water Science & Technology 39: 195-214. Wagner, M., & Loy, A. (2002) Bacterial community composition and function in sewage treatment systems. Curr. Opin. Biotechnol 33: 218–227.  212  References  Wagner, M., Rath, G., Koops, H., Flood, J., & Amann, R. (1996) In situ analysis of nitrifying bacteria in sewage treatment plants. Water Science and Technology 34: 237244. Wagner, M., Loy, A., Nogueira, R., Purkhold, U., Lee, N., & Daims, H. (2002) Microbial community composition and function in wastewater treatment plants. Antonie Van Leeuwenhoek 81: 665-680. Water Environment Federation. (2005) Biological nutrient removal (BNR) operation in wastewater treatment plants. WEF Manual of Practice No. 29. ASCE/EWRI Manuals and Reports on Engineering Practice No.109. McGraw-Hill, Wei, Y., & Liu, J. (2005) The discharged excess sludge treated by Oligochaeta. Water Science & Technology 52: 265-272. Wei, Y., vanHouten, R. T., Borger, A. R., Eikelboom, D. H., & Fan, Y. (2003) Comparison Performances of Membrane Bioreactor and Conventional Activated Sludge Processes on Sludge Reduction Induced by Oligochaete. Environ Sci Technol 37: 3171-3180. Wells, G. F., Park, H., Yeung, C., Eggleston, B., Francis, C. A., & Criddle, C. S. (2009) Ammonia-oxidizing communities in a highly aerated full-scale activated sludge bioreactor: betaproteobacterial dynamics and low relative abundance of Crenarchaea. Environ Microbiol 11: 2310-2328. Wentzel, M. C., Lotter, L. H., Ekama, G. A., Loewenthal, R. E., & Marais, G. v. R. (1991) Evaluation of biochemical models for biological excess phosphorus removal. Water Science and Technology 23: 567-576. Wett, B., Rosteck, R., Rauch, W., Ingerle, K. (1998) pH-controlled reject water treatment. Water Science and Technology 37: 165-172. Wisniewski, C., & Grasmick, A. (1998) Floc size distribution in a membrane bioreactor and consequences for membrane fouling. Colloids and Surfaces A: Physicochemical and Engineering Aspects 138: 403-411. Wittebolle, L., Vervaeren, H., Verstraete, W., & Boon, N. (2008) Quantifying community dynamics of nitrifiers in functionally stable reactors. Appl Environ Microbiol 74: 286293. Witzig, R., Manz, W., Rosenberger, S., Krüger, U., Kraume, M., & Szewzyk, U. (2002) Microbiological aspects of a bioreactor with submerged membranes for aerobic treatment of municipal wastewater. Water Research 36: 394-402. Yamamoto, K., Hiasa, M., Mahmood, T., & Matsuo, T. (1989) Direct solid-liquid separation using hollow fiber membrane in an activated sludge aeration tank. Water Science and Technology 21: 43-54.  213  References  Yu, Z., & Mohn, W. W. (2001) Bacterial Diversity and Community Structure in an Aerated Lagoon Revealed by Ribosomal Intergenic Spacer Analyses and 16S Ribosomal DNA Sequencing. Appl Environ Microbiol 64: 1565-1574. Zhang, B., Yamamoto, K., Ohgaki, S., & Kamiko, N. (1997) Floc size distribution and bacterial activities in membrane separation activated sludge processes for small-scale wastewater treatment/reclamation. Water Science and Technology 35: 37–44. Zhang, B., Sun, B., Ji, M., Liu, H., & Liu, X. (2010) Quantification and comparison of ammonia-oxidizing bacterial communities in MBRs treating various types of wastewater. Bioresour Technol 101: 3054-3059.  214  Appendix I: UBC Pilot Plant Drawings  Appendix I UBC PILOT PLANT DRAWINGS  215  UNIVERSITY OF BRITISH COLUMBIA DEPARTMENT OF CIVIL ENGINEERING  UBC WASTEWATER PILOT PLANT DRAWINGS  Drawing List Drawing No. 1 2 3 4 5 6 7  Title Cover Sheet Pilot Plant Location Pilot Plant Layout Reactor Layout Reactor Plan Reactor Section Pump & Piping Arrangement  UBC Wastewater Pilot Plant Project Title: Nitrification activity in membrane and conventional EBPR processes Drawing Title: Cover Sheet Drawing No.: 1 of 7 Scale: Not to scale  216  UBC Farm  Pilot Plant  TRIUMF  UBC Wastewater Pilot Plant Project Title: Nitrification activity in membrane and conventional EBPR processes Drawing Title: Pilot Plant Location Drawing No.: 2 of 7 Scale: Not to scale  217  To office trailer  Anaerobic Aerobic  Anoxic  Anaerobic  Feed storage tanks with mixers  Anoxic  Aerobic  Parking lot  Trailer containing reactors  Feed storage tank Influent sump with pump UBC Wastewater Pilot Plant Project Title: Nitrification activity in membrane and conventional EBPR processes Drawing Title: Plant Layout Drawing No.: 3 of 7 Scale: Not to scale  218  Permeate pump & holding tank  Acetate feed tanks  Primary clarifier  Primary effluent holding tank  Anaerobic  Anoxic  Aerobic  Clarifier influent pumps  Underflow pump  Membrane reactor  Aerobic  Anoxic  Anaerobic  Conventional reactor  Influent feed pumps Wash area  Sample refrigeration Final effluent holding tank  Secondary clarifier  Sludge wasting tank  UBC Wastewater Pilot Plant Project Title: Nitrification activity in membrane and conventional EBPR processes Drawing Title: Reactor Layout Drawing No.: 4 of 7 Scale: Not to scale  219  MLSS baffled overflow to clarifier  1‖ dia. Air drop pipe with air diffuser  Mixer  800  Anoxic 2730  Anaerobic  A Aerobic  A 600  Reactor access ladder  Plan All dimensions in mm  UBC Wastewater Pilot Plant Project Title: Nitrification activity in membrane and conventional EBPR processes Drawing Title: Reactor Plan Drawing No.: 5 of 7 Scale: Not to scale  220  Secondary clarifier (for conventional train only)  Compartment not in use  Effluent v-notch overflow weir  120  480  1250 1640  1600 1360  160  1675  6 mm thick compartmentalized steel tank  760  295  475  Section AA All dimensions in mm  UBC Wastewater Pilot Plant Project Title: Nitrification activity in membrane and conventional EBPR processes Drawing Title: Reactor Section Drawing No.: 6 of 7 Scale: Not to scale  221  From influent feed pump  From acetate feed pump  From clarifier underflow  RAS pump (for conventional train only)  Gravity flow to sludge wasting tank  Aerobic recycle pump  Anoxic recycle pump  REACTOR FRONT ELEVATION All pipes are 50 mm dia flexible hose  UBC Wastewater Pilot Plant Project Title: Nitrification activity in membrane and conventional EBPR processes Drawing Title: Reactor Pump and Piping Arrangement Drawing No.: 7 of 7 Scale: Not to scale  222  Appendix II: Instrumentation and Controls Diagram  Appendix II INSTRUMENTATION AND CONTROLS DIAGRAM  223  Figure A-1  Schematic of reactor instrumentation and controls Shown for one reactor only  224  Appendix III: Temperature Coefficient Determination  Appendix III TEMPERATURE COEFFICIENT DETERMINATION  The nitrification temperature coefficients were obtained from nitrification rates measured at three different temperatures. The nitrification rate measurements were carried out on mixed liquor samples collected over three consecutive days. Rates were measured on samples for which temperatures were adjusted by either rapidly increasing or rapidly decreasing the mixed liquor temperature. For the case of increasing temperature, mixed liquor samples were taken at a pilot plant temperature averaging 15oC and increased to 16oC, 20oC and 24oC. The temperature was increased at an average rate of 1.5oC / h by recirculating water from a temperature control bath. For the decreasing temperature determination, the mixed liquor at the plant averaged 20oC and the rate measurements were carried out at 20oC and on the mixed cooled to 16oC by recirculating cooling water (a plant upset on the third consecutive day prevented another measurement at a lower temperature). The nitrification temperature coefficients were calculated assuming that the effect of temperature on the nitrification rate is in accordance with the Arrhenius relationship. The coefficient () was derived from the slope (ln ) of the plot of ln (k/k20) vs. T-20. A typical plot is shown in Figure A-2.  Figure A-2  Plot for nitrification temperature coefficient determination  225  Appendix III: Temperature Coefficient Determination  Temperature coefficients determined for the membrane process and conventional process mixed liquor are summarized in Table A-1. The method for attaining the mixed liquor final temperature did not appear to affect the value of the coefficient calculated. Coefficients were comparable whether temperature was achieved by increasing or decreasing the initial mixed liquor temperature to reach the desired temperature.  Table A-1  Temperature coefficients for membrane process and conventional process mixed liquors Temperature Coefficient Increasing Temp Decreasing Temp Membrane Conventional Membrane Conventional * 1.059 1.059 1.059 1.169 1.058 1.067 1.054 1.079 1.048 1.061 1.062 1.175 1.053 1.069 1.057 1.084  Data type used for coefficient determination NH4-N uptake rate NOx-N production rate Specific NH4-N uptake rate Specific NOx-N production rate Average Std Dev *  1.055 0.004  1.064 0.004  1.058 0.003  1.127 0.045  Rates shown were based on plots constructed from two data points only  The nitrification temperature coefficients calculated were lower than the generally accepted value of 1.072 (Melcer and Dold, 2004). The nitrification temperature coefficient was also lower than the values reported in literature that were measured under conditions of a sudden temperature change. These values ranged between 1.088 and 1.116 (Hwang and Oleszkiewicz, 2007).  226  Appendix IV: Photographs  Appendix IV PHOTOGRAPHS  227  Appendix IV: Photographs  Fine Bubble Aeration  Top Fine bubble diffuser stone used in decay rate experiments Left Aerating with low air flow rate to minimize turbulent conditions in reactor used for fine air bubble condition  Coarse Bubble Aeration  Top Coarse bubble diffuser constructed from 12 mm diameter tubing Left Aerating with high air flow rate to obtain turbulent conditions in the reactor for the coarse bubble condition  228  Appendix IV: Photographs  Pilot Plant Aeration Diffusers  Left Air diffuser used for fine bubble aeration in the conventional process train  Left Air diffuser with equally spaced openings attached to the membrane module  229  

Cite

Citation Scheme:

        

Citations by CSL (citeproc-js)

Usage Statistics

Share

Embed

Customize your widget with the following options, then copy and paste the code below into the HTML of your page to embed this item in your website.
                        
                            <div id="ubcOpenCollectionsWidgetDisplay">
                            <script id="ubcOpenCollectionsWidget"
                            src="{[{embed.src}]}"
                            data-item="{[{embed.item}]}"
                            data-collection="{[{embed.collection}]}"
                            data-metadata="{[{embed.showMetadata}]}"
                            data-width="{[{embed.width}]}"
                            async >
                            </script>
                            </div>
                        
                    
IIIF logo Our image viewer uses the IIIF 2.0 standard. To load this item in other compatible viewers, use this url:
http://iiif.library.ubc.ca/presentation/dsp.24.1-0062797/manifest

Comment

Related Items