Molecular and Kinetic Characterization of Anammox Bacteria Enrichments and Determination of the Suitability of Anammox for Landfill Leachate Treatment

AN ABSTRACT OF THE THESIS OF

Sharmin Sultana for the degree of Master of Science in Environmental Engineering presented on December 1, 2016

Title: Molecular and Kinetic Characterization of Anammox Bacteria Enrichments and Determination of the Suitability of Anammox for Landfill Leachate Treatment

Abstract approved: ______Tyler S. Radniecki

Anaerobic ammonium oxidation (anammox) has recently appeared as a promising approach for removing nitrogen from landfill leachates because it requires less oxygen and no organic carbon compared to traditional nitrification-denitrification system, and it produces low sludge volumes, thereby reducing operating and biological sludge disposal costs by over 60%. Anammox bacteria anaerobically oxidize ammonia with nitrite to form dinitrogen gas, which is bubbled out of the system. When combined with partial nitrification (the aerobic oxidation of half the ammonia to nitrite), anammox bacteria can be an efficient and sustainable solution to treat landfill leachate. However, leachate loading rates to the anammox reactor are critical due to the high concentrations of potential anammox inhibitors, including heterogenous organic carbon, heavy metals, pesticides and nitrite.

In this study, anammox bacteria were enriched from two sources; sludge from the world’s first full-scale anammox plant (Dokhaven wastewater treatment plant) in Rotterdam, Netherlands and sludge from the Virginia Hampton Roads Sanitation

District (HRSD) wastewater treatment facility, the first full-scale anammox plant in the United States. The sludge was enriched over 14 months in two sequencing batch reactors (SBR) and about a year period in a novel carbon nanotube membrane upflow anaerobic sludge blanket (MUASB) reactor. Of the two systems, SBR and MUASB, the MUASB was much more effective at enriching anammox bacteria due to its ability to capture planktonic anammox cells and enhance the anammox granulation process. First-order, Grau second-order, Stover-Kincannon kinetic models were developed for both SBRs, with the second order Grau and Stover-Kincannon kinetic models describing the SBRs most accurately.

To determine the effect of landfill leachate loading rates on anammox activity, partially nitrified Coffin Butte landfill leachate (Benton County, OR) was fed to MUASB reactor over a variety of nitrogen loading and hydraulic retention times. A Stover- Kincannon model was developed for the MUASB reactor with and without leachate present in the anammox media. It was observed that the Stover-Kincannon model constants were affected and decreased in presence of leachate in the media. The maximum substrate utilization rate (Umax) decreased by the factor of 11 and saturation constant (KB) decreased by the factor of 29. Therefore, the inhibition observed here is most likely best described by mixed inhibition kinetics, and organic carbon present in the leachate was suspected to be a major cause of the observed anammox inhibition. The leachate was pretreated with a FeCl3. 6H2O coagulation process to help alleviate the observed anammox inhibition. This process removed 40% of the organic carbon from the leachate. However, the pretreated leachate still induced a 40% inhibition of the anammox processes. This suggests that the FeCl3. 6H2O pretreatment process did not remove enough of the organic carbon to prevent inhibition from occurring.

Molecular and Kinetic Characterization of Anammox Bacteria Enrichments and Determination of the Suitability of Anammox for Landfill Leachate Treatment

by Sharmin Sultana

A THESIS

submitted to

Oregon State University

in partial fulfillment of the requirements for the degree of

Master of Science

Presented December 1, 2016 Commencement June 2017

Master of Science thesis of Sharmin Sultana presented on December 1, 2016

APPROVED:

Major Professor, representing Environmental Engineering

Head of the School of Chemical, Biological and Environmental Engineering

Dean of the Graduate School

I understand that my thesis will become part of the permanent collection of Oregon State University libraries. My signature below authorizes release of my thesis to any reader upon request.

Sharmin Sultana, Author

ACKNOWLEDGEMENTS

I would like to express my sincere appreciation to my amazing supervisor Dr. Radniecki for showing me the biggest support and patience. Needless to say none of this study would have been possible without his help. I truly appreciate your effort, dedication and empathy that you showed in helping me throughout my graduate school life.

I would like to thank Dr. Semprini, Dr. Dolan and Ms. Berger for being my committee members and guiding me towards the MS degree. I would like to thank Mohammed Azizian for being there always in the lab with his helping attitude.

Additional thanks go to all of my awesome lab mates Bushee, Stein, Hillard, White, Tetzolf and Kannon for their enormous help in the lab. Thank you, Bushee and Stein for being there with me as my friends. I appreciate those times we spent together with laughter and joy.

I am also grateful to all CBEE graduate students, faculty and stuffs for their kindness and support towards completing my MS degree.

I am thankful to my mother and other family members for their support during my whole graduate school life. I am very lucky to have my husband, Wahid Hassan by my side when I needed him most. I would like to dedicate this work to my mother, Nilufar Yeasmin whose soul and blessing will be with me forever.

TABLE OF CONTENTS

Page

INTRODUCTION ...... 1

LITERATURE REVIEW ...... 4

2.1 Importance of Nitrogen Removal ...... 4

2.2 Biological Nitrogen Removal Processes ...... 5

2.2.1 Nitrification ...... 6

2.2.2 Denitrification ...... 7

2.2.3 Anammox ...... 8

2. 3 Discovery of Anammox ...... 9

2.3.1 Anammox Biochemical Properties and Metabolic Pathway ...... 11

2.3.2 Summary of Enrichment Techniques ...... 13

2.3.3 Factors Affecting Anammox Process ...... 15

2.3.3.1 Concentration of Substrates ...... 16

2.3.3.2 pH ...... 16

2.3.3.3 Temperature ...... 17

2.3.3.4 Bicarbonate Concentration ...... 17

2.3.3.5 Organic Carbon ...... 17

2.3.3.6 Sulfide ...... 18

2.3.3.7 Oxygen ...... 18

TABLE OF CONTENTS (Continued)

Page

2.3.3.8 Type of Inoculum ...... 19

2.3.3.9. Heavy Metals Inhibition ...... 19

2.4 Application of Anammox in WWTP ...... 21

2.4.1 SHARON-Anammox Treatment Process ...... 22

2.4.2 Demon Treatment Process ...... 23

2.5 Substrate Removal Kinetic Models ...... 25

2.5.1 Monod Model ...... 26

2.5.2 First-order Substrate Removal Model ...... 28

2.5.3 Grau Second- order Substrate Removal Model ...... 29

2.5.4 Modified Stover-Kincannon Model ...... 30

MATERIALS AND METHODS ...... 34

3.1 Sequencing Batch Reactor ...... 34

3.2 Membrane Upflow Anaerobic Sludge Blanket Reactor ...... 35

3.3 Water Quality Analysis ...... 37

3.3.1 pH ...... 37

3.3.2 Total Suspended and Volatile Suspended Solids ...... 38

3.3.3 Chemical Oxygen Demand (COD) ...... 38

3.3.4 Ammonium, Nitrite and Nitrate Test ...... 38

TABLE OF CONTENTS (Continued)

Page

3.4 Media Recipe ...... 39

3.5 Genomic Analyses ...... 40

3.5.1 DNA Extraction and PCR ...... 40

3.5.2 Real-time PCR ...... 42

3.5.3 Calculations for Standard Curve ...... 43

3.6 Sample collection and Storage ...... 44

3.7 Kinetic Experiments ...... 44

3.8 Leachate Experiment ...... 44

3.9 Leachate Pretreatment ...... 45

RESULT AND DISCUSSION ...... 46

4.1 Anammox Enrichment Study ...... 47

4.1.1 Performance and Efficiency of VA_SBR ...... 47

4.1.2 Performance and Efficiency of NL_SBR ...... 54

4.1.3 Comparison Stoichiometric Ratio of Substrates between VA_SBR and

NL_SBR ...... 61

4.1.4 Population of Total Bacteria, Planctomycetes and Anammox in SBRs

...... 64

4.1.5 MUASB Reactor ...... 68

TABLE OF CONTENTS (Continued)

Page

4.1.6 Summary of Anammox Enrichment ...... 77

4.2. Kinetic Study ...... 81

4.2.1 First-order Substrate Removal Model ...... 81

4.2.2 Grau Second-order Substrate Removal Model ...... 84

4.2.3 Modified Stover-Kincannon Model for SBRs ...... 86

4.2.4 Modified Stover-Kincannon Model for MUASB ...... 89

4.2.5 Summary of Kinetic Model Parameters ...... 91

4.3 Anammox Treatment of Landfill Leachate in the MUASB Reactor ...... 94

4.3.1 Effect of Leachate on Anammox Kinetics in MUASB Reactor ...... 94

4.3.2 Effect of Leachate on Anammox Activity in MUASB Reactor ...... 96

CONCLUSION ...... 101

BIBLIOGRAPHY ...... 103

APPENDIX ...... 116

LIST OF FIGURES Figure Page

Figure 2.1: New Nitrogen cycle including anammox……………..……………………………….……..…6

Figure 2.2: Phylogenetic tree based on 16S ribosomal RNA gene showing the relationship among Ca. Scalindua, Ca. Brocadia, Ca. Kuenenia, Ca. Anammoxoglobus, Ca. Jettenia to other Planctomycetes and other reference organisms..………………….…………………….………10

Figure 2.3: A. B. Probable biochemical pathway and reaction mechanism of anammox...12

Figure 2.3: C. Biochemical pathway and enzymatic machinery of anaerobic ammonium oxidation (K. stuttgartiensis)…………………………………………………………………………………...……………………………12

Figure 2.4: Number of articles published on anammox bacteria enrichment using different reactors from 1992 to 2012 …………………………………..……………………………………………..………14

Figure 2.5: First full-scale anammox based treatment plant, Rotterdam, Netherlands……23

Figure 2.6: A. HRSD York River centrate equalization tank (left) and DEMON tank (right)………………………………………………………………………………………………….……………………….24

Figure 2.6: B. Biomass separation device (BSD)……………………………………………………………..24

Figure 2.7: Two steps of the deammonication (DEMON) process (partial nitritation and anaerobic ammonia oxidation) …………………………………………………………………….……………...25

Figure 3.1: Schematic diagram of sequencing batch reactor …………………………….….………35

Figure 3.2: Schematic diagram of each cycle of sequencing batch reactor……………………..35

Figure 3.3: (A) Classical electrofiltration cell setup. (B) Electrofiltration with conducive membrane/thin film set up…………………………………………………………………………..……………...36

LIST OF FIGURES (Continued) Figure Page

Figure 3.4: Schematic diagram of membrane upflow anaerobic sludge blanket reactor………………………………………………………………………………………………………………………….37

+ - Figure 4.1: Substrate (total NH4 -N and NO2 -N) removal efficiency (%) vs age of VA_SBR reactor.……………………………………………………………………………………………………………….…….…48

+ - Figure 4.2: Substrate (total NH4 -N and NO2 -N) removal rate (mg N/L-day) vs age of VA_SBR reactor ………………………………………………………………………………………………….……..…48

+ Figure 4.3: Influent and effluent ammonium (NH4 ) concentration (mg N/L-day) changed over time in VA_SBR.……………………………………………………………….....………………………..……..50

Figure 4.4: Influent and effluent nitrite (NO2-) concentration changed over time in VA_SBR.………………………………………………………………………………………….…………………………...50

Figure 4.5: Nitrate produced or consumed vs age of the VA_SBR reactor (day)..……….…51

Figure 4.6: Ammonium removal efficiency (%)vs age of the VA_SBR reactor (day).……… 52

Figure 4.7: Nitrite removal efficiency (%) vs age of the VA_SBR reactor (day).……………….52

Figure 4.8 Substrate (total ammonium and nitrite nitrogen) removal efficiency (%) vs age of NL_SBR reactor.……………………………………………………………….....…………………………………..55

Figure 4.9: Substrate (total ammonium and nitrite nitrogen) removal rate (mg N/L- day) vs age of NL_SBR reactor……………………….…………………………………………………….……………...55

Figure 4.10: Influent and effluent concentration of ammonium (mg N/L) vs age of NL_SBR reactor (day).…………………………….……….………………………………………………………………………..57

LIST OF FIGURES (Continued) Figure Page

Figure 4.11: Influent and effluent concentration of nitrite (mg N/L) vs age of NL_SBR reactor (day).…………………………………………….………………………………………………….………………57

Figure 4.12: Nitrate production or consumption (mg N/L) vs age of reactor (day) in the NL_SBR reactor.……………………………………………………………………………………………..………..…..58

Figure 4.13: Ammonium removal efficiency (%) vs age of reactor (day) in the NL_SBR reactor……………………………………………………………………………………………………………….………..59

Figure 4.14: Nitrite removal efficiency (%) vs age of reactor (day) in the NL_SBR reactor.………………………………………………………………………………………………………....….…………59

Figure 4.15: Nitrite (NO2) consumption to ammonium (NH4) consumption ratio in VA_SBR (left) and NL_SBR (right) on daily basis. Arrows are used to show the probable upset periods……………………..………………………………………………………….………………………………………61

Figure 4.16: Nitrite (NO2) consumption to ammonium (NH4) consumption ratio in VA_SBR (left) and NL_SBR (right) on monthly basis. …………………………….…………….……………….……..63

Figure 4.17: : Population of total bacteria, Planctomycetes and anammox bacteria (Ca. Brocadia and Ca. Kuenenia) as log of copy number per ng of genomic DNA in VA_SBR with time.………………………………………………………………………..……..……………………………………..……65

Figure 4.18: Population of total bacteria, Planctomycetes and anammox bacteria (Ca. Brocadia and Ca. Kuenenia) as log of copy number per ng of genomic DNA in NL_SBR with time……………………………………………………………………………………………………………………..………65

+ - Figure 4.19: Substrate (total NH4 -N and NO2 -N) removal efficiency (%) vs the age of the MUASB reactor (day). ………………………..…………………………………………………………………………69

LIST OF FIGURES (Continued) Figure Page

+ - Figure 4.20: Substrate (total NH4 -N and NO2 -N) removal rate (mg N/ day) vs the age of MUASB reactor ………………………………………………………….………………………..…….………..………70

Figure 4.21: Ammonium removal efficiency (%) vs age of the MUASB reactor (day)…….…71

Figure 4.22: Nitrite removal efficiency (%) vs vs the age of the MUASB reactor (day)………71

Figure 4.23: Influent and effluent concentrations of ammonium (mg N/L) vs age of the MUASB reactor (day).……………………………………………………………………..…………………….……..72

Figure 4.24: Influent and effluent concentrations of nitrite (mg N/L) vs age of the MUASB reactor (day)…………………………………………………………………………….……………………….…..…….72

Figure 4.25: Nitrate production or consumption (mg N/L) vs age of reactor (day) in the NL_SBR reactor.…………………………………………………………………………..……………………….………73

Figure 4.26: Nitrite (NO2) consumption to ammonium (NH4) consumption ratio in MUASB reactor on daily bas………….……………………..……………………………………………………………………74

Figure 4.27: Nitrite (NO2-) consumption to ammonium (NH4+) consumption ratio in MUASB reactor on monthly basis.………………………………………………………………………………...74

Figure 4.28: Population of anammox, Planctomycetes and total bacteria as copy number per ng of genomic DNA in MUASB with time.……………………………………………………….……...76

Figure 4.29: The color of enriched anammox observed in the MUASB reactor (left), color of anammox granule reported in literature (right). ……………………………….…………….……...80

Figure 4.30: First-order kinetic model for VA_SBR (left) and NL_SBR (right).………….…....82

LIST OF FIGURES (Continued) Figure Page

Figure 4.31: First-order kinetic model validation for VA_SBR (left) and NL_SBR (right).…83

Figure 4.32: Grau second-order kinetic model for VA_SBR (left) and NL_SBR (right)…..…84

Figure 4.33: Grau second order kinetic model validation for VA_SBR (left) and NL_SBR (right).…………..……………………………………………………………………………………………………….….…85

Figure 4.34: Stover-Kincannon kinetic model for VA_SBR (left) and NL_SBR (right)……………………………………………………………………………………………………………………………87

Figure 4.35: Modified Stover-Kincannon kinetic model validation for VA_SBR (left) and NL_SBR (right).……………………………………………………………………………………………………………..88

Figure 4.36: Modified Stover-Kincannon kinetic model for total substrate in MUASB reactor……………………….…………………………………………………………………………………………………90

Figure 4.37: Stover-Kincannon kinetic model validation for total substrate in MUASB reactor ……………………………………………………………………………………………………………………..…90

Figure 4.38: Stover-Kincannon model with and without leachate for total nitrogen in the MUASB reactor……………….……………………………………………………………………………………………95

Figure 4.39: Effect of landfill leachate experiment (Stover-Kincannon model experiment) on the total nitrogen removal efficiency (%).…………………………………………………………………97

Figure 4.40: Landfill leachate pre-treatment experiment before (left) after (right)….……98

Figure 4.41: Effect of landfill leachate pretreatment on the total nitrogen removal efficiency (%) in the MUASB reactor…………………………………….……………………………….……..99

LIST OF TABLES

Table Page

Table 2.1: Forms of nitrogen in the environment……………………………………………….…….…… 6

Table 2.2: Biodiversity and presence of anammox bacteria……………………….……..…………..10

Table 2.3: Parameters of aerobic and anaerobic ammonia oxidation ………….…….…..……..27

Table 3.1: Recipe of media used for MUASB reactor………………………………………………………39

Table 3.2: Targets and primer used for endpoint PCR and qPCR primer optimization……..41

Table 3.3: Optimized primer concentration and volume for PCR and qPCR…………………..42

Table 4.1: Student t-tests were performed for each common months for both VA_SBR and NL_SBR…………………………………………………………………………………………………………………………64

Table 4.2: Summary of anammox enrichment in VA_SBR, NL_SBR and MUASB…….……….78

Table 4.3: Comparison among three kinetic models for SBRs and MUASB with correlation co-efficient and standard error of estimate…………………………………………………………………..91

Table 4.4: Summary of kinetic model constants for SBRs and MUASB ……………………..….92

Table 4.5: Summary of kinetic model constants of MUASB reactor with and without leachate………………………………………………………………………………………..………………….………….96

Table 4.6: 50% inhibitory concentration of heavy metals on anammox population……100

LIST OF APPENDIX FIGURES Figure Page

Figure A1: Ammonium standard curve for IC…………………………………………………..…………118

Figure A2: Nitrite standard curve for IC…………………………………………………………….……….118

Figure A3: Nitrate standard curve for IC …………………………………………………..………………..119

Figure A4: COD standard curve used for landfill leachate pretreatment with FeCl3. 6H2O………………………………………………………………………………………………………………………….119

Figure A5: Standard curve for total bacteria quantification ……………………………..………..120

Figure A6: Standard curve Planctomycetes quantification.………………………………….………120

Figure A7: Standard curve for anammox quantification ………………………………….....…….121

Figure A8: Map of metagenomics sequencing read for all identified and unidentified bacteria from VA_SBR and NL_SBR ………………………………………….………………………………..123

Figure A9: Total effluent substrate predicted from first- order model vs. total influent substrate in VA_SBR……………………………………………………………………………………………………126

Figure A10: Total effluent substrate predicted from Grau second-order model vs. total influent substrate in VA_SBR………………………………………………………………………………………126

Figure A11: Total effluent substrate predicted from Stover-Kincannon model vs. total influent substrate in VA_SBR………………..…………………………………………………………………….127

Figure A12: Total effluent substrate predicted from first- order model vs. total influent substrate in NL_SBR. ………………………………………………………………………………………………….127

LIST OF APPENDIX FIGURES (Continued) Figure Page

Figure A13: Total effluent substrate predicted from Grau second-order model vs. total influent substrate in NL_SBR………………………..………………………………………………………..…..128

Figure A14: Total effluent substrate predicted from Stover-Kincannon model vs. total influent substrate in NL_SBR……………………………………………………………………...………………128

Figure A15: Leachate experiment in MUASB before and after pretreatment………………130

LIST OF APPENDIX TABLES Table Page

Table A1: Media recipe for anammox enrichment in SBRs……………………………………………117

Table A2: Mean, standard deviation and p-value calculated for Nitrite consumption to ammonium consumption ratio in MUASB reactor ……………………….……………….…………….121

Table A3: Relative abundance of different types of bacteria from metagenomics sequencing result (samples taken from VA_SBR and NL_SBR)…………………………………….124

Table A4: Statistical parameters for nitrite consumption to ammonium consumption ratio of VA_SBR…………………………………………………………………………………………………………………..129

Table A5: Types of Inhibition……………………………………….……………………………………………..129

ACRONYMS AND SYMBOLS

AOB…………………….. Ammonium Oxidizing Bacteria

Anammox………..…… Anaerobic Ammonium OXidation

COD………………….….. Chemical Oxygen Demand

SHARON …………..…. Single Reactor for High Activity Ammonium Removal Over Nitrite

CANON ……………..….Completely Autotrophic Nitrogen Removal Over Nitrite

DEMON…………….…. DEamMONification

DENAMMOX………... DENitrification-anAMMOX

RBC………...... Rotating Biological Contactor

DO…………………….…. Dissolved Oxygen

MLSS …………….…..….Mixed Liquor Suspended Solids

MLVSS………………..... Mixed Liquor Volatile Suspended Solids

VSS ……………………..…Volatile Suspended Solids

RPM ……………….……..Revolution per minute

NOB………………..……. Nitrite Oxidizing Bacteria

SBR ………….……...... Sequencing Batch Reactor

WWTP ……..……….....Waste Water Treatment Plant

FA……………….….... ….Free Ammonia

FNA ……………...……...Free Nitrous Acid

ACRONYMS AND SYMBOLS (Continued)

Q…………………..... …..Flow rate (ml/min)

V…………………… Reactor volume (L)

Si……………..……. Influent substrate concentration

Se……………….…. Effluent substrate concentration

X………………..….. Total biomass concentration in reactor (mg VSS/L)

Xi……………….….. Influent biomass concentration m(g VSS/L)

µ………………..….. Specific growth rate (d‑1)

θH …………….…Hydraulic retention time (day)

HRT ………………..Hydraulic Retention Time (day)

SRT ………………..Solid Retention Time (day)

‑1 µmax………………… Maximum specific growth rate (day )

Ks…………………….Half‑saturation constant (mg substrate/L)

-1 K2………….…………………….Rate constant (day ), Grau second‑order model

KB…………………...Saturation constant (mg N/L-day), Stover-kincannon model

Umax………………...Maximum substrate utilization rate (mg N/L-day), Stover-kincannon model

CHAPTER 1

INTRODUCTION

The existence of anaerobic ammonium oxidation (anammox) bacteria was first predicted by Broda (1977) and almost two decades later, Mulder et al (1995) discovered anammox in a rotating biological reactor. Anammox makes a novel shortcut to nitrogen cycle as they use ammonium (NH4) and nitrite (NO2) as their main substrate and make dinitrogen (N2) gas directly (Mulder et al., 1995; Strous et al., 1999b; Sri Shalini and Joseph, 2012). Thus, the anammox process has become very popular over traditional biological nitrogen removal processes as it has many advantages, including the complete removal of nitrogen with a 65% reduction in energy, a 100% reduction in supplemental carbon and alkalinity requirement, and the production of less sludge (Graaf et al., 1995; Strous et al., 1999b).

Wastewater sidestreams (e.g. anaerobic digester effluent) and landfill leachate contain high nitrogen concentrations (in the form of ammonium) are often costly to treat due to high energy and/or chemical demands. Biological treatment processes often provides a cheaper solution than other physico-chemical processes and the anammox process is amongst the cheapest of the biological processes for removing high concentrations of ammonia when the organic carbon concentrations are low (Wang et al., 2009; Abma et al., 2007). Since, anammox bacteria have very slow growth rate (doubling time 11 days), it is very important to enrich anammox in efficient way for full- scale treatment processes (Strous et al., 1999b).

Quantifying anammox kinetics is a useful tool to help determine who efficiently the anammox population is being enriched (Babaei et al., 2013). Several kinetic models can be used for this purpose, depending on type of inoculation, age of anammox sludge

2 and type of reactor (Anderson et al., 1996; Jin and Zheng, 2009a). First-order, Grau second-order, Stover-Kincannon models are very popular to predict effluent concentration of substrates (Babaei et al., 2013; Jin and Zheng, 2009a; Ni et al., 2010). First-order model assumed a first order reaction scenario inside the reactor and Grau second-order model is a combination of Monod model and second-order chemical reaction (Anderson et al., 1995; Babaei et al., 2013; Grau et al., 1975; Jin and Zheng, 2009a). Stover-Kincannon model is analogous to Monod model but the effluent substrate concentration is dependent on loading rate (influent substrate concentration and hydraulic retention time) (Anderson et al., 1996; Grady and Williams, 1975; Stover and Kincannon, 1982).

In this study, two sequencing batch reactors (SBR) and a membrane upflow sludge blanket reactor (MUASB) were developed to enrich anammox over a two year period. One of the SBRs (NL_SBR) was inoculated with anammox sludge from Dokhaven wastewater treatment plant (WWTP), Rotterdam, Netherlands and the other SBR (VA_SBR) was inoculated with anammox sludge was from Hampton Roads Sanitation District (HRSD) York River wastewater treatment, Virginia. The Dokhaven WWTP utilizes the SHARON- Anammox process, where the partial nitrification and anammox reactions occur in separate reactors, while the HRSD WWTP utilizes the DEMON process, in which the partial nitrification and anammox reaction occurs in the same reactor, to treat their wastewater influent (Kartal et al., 2004; Mulder et al., 2001). The MUASB reactor was inoculated with the anammox sludge from VA_SBR after 6 months of anammox enrichment in VA_SBR.

The main objectives of this study were to develop reactors (SBR and MUASB) to enrich anammox bacteria from anammox sludge; to compare performance among VA_SBR, NL_SBR and MUASB in terms of total nitrogen removal efficiency, ammonium and nitrite stoichiometric ratio and quantification of anammox bacteria by qPCR; to develop kinetic models (first-order, Grau second-order, Stover-Kincannon) for all three

3 reactors, and to treat synthetic wastewater and diluted landfill leachate using enriched anammox with and without pretreatment.

CHAPTER 2

LITERATURE REVIEW

2.1 Importance of Nitrogen Removal

Nitrogen is the most abundant element of our atmosphere comprising almost 79% of it, and is a nutrient on which all living creatures depend (Sultana, 2014). Nitrogen is an important building block for proteins and nucleic acids in both plants and animals (Bertino, 2010). Nonetheless, excessive amount of nitrogen in a water body can cause eutrophication that may lead to dense plant and algae growth. Once the plant and algae matter decays, a lack of oxygen can occur that may cause damage to fisheries, especially in coastal area (Sultana, 2014). The global increase in population has, through an increase in food and drinking water demand, increased the amount of nitrogen released into the environment (through wastewater discharges and fertilizer applications) which has resulted in increased pressure on the surrounding environmental system (Townstead et al., 2003).

A primary source of nitrogen released to water bodies is municipal wastewater, which typically contains about 80 mg/L of NH4-N (Metcalf and Eddy, 2003). Other sources of nitrogen discharge, including industrial waste, landfill leachate, and sludge liquor from anaerobic digestion, can contain significantly higher amounts of ammonia (NH4), ranging from 1400 to 2800 mg/L of NH4-N (Liang & Liu, 2008; Cema et al., 2009). To protect the environment, the nitrogen discharge limit is strictly regulated from the effluent of wastewater treatment plants (WWTP).

There are several processes to treat nitrogen from wastewater or landfill leachate; the physicochemical processes (ion exchange, precipitation, air stripping, activated carbon adsorption, filtration) and biological processes (aerobic/ anaerobic treatment) (Metcalf and Eddy, 2003). Biological treatment processes are relatively cheaper with

+ lower operation and maintenance cost especially when NH4 -N is in the range of 100- 5000 mg/L, and will be discussed in further detail below (Mulder et al., 1995).

2.2 Biological Nitrogen Removal Processes

In the environment, nitrogen compounds, both inorganic and organic, exist as gases in air and as soluble species in water and soils, in both oxidized and reduced forms (Table 2.1) (Tekin, 2013). The nitrogen cycle, which both oxidizes and reduces nitrogen species in the environment, is mediated by several types of microbes that catalyze corresponding nitrogen species. The aerobic ammonium oxidizers (AOB) oxidize ammonium to nitrite, nitrite oxidizing bacteria (NOB) further oxidize nitrite to nitrate in presence of oxygen (Metcalf and Eddy, 2003). Heterotrophic denitrifying bacteria reduce nitrate to dinitrogen gas utilizing organic carbon as the electron donor (Metcalf and Eddy, 2003). Anammox bacteria utilize ammonium and nitrite both as their substrate (ammonium as electron donor and nitrite as electron acceptor) and produce dinitrogen gas directly (Graaf et al., 1995; Mulder et al., 1995). Engineers have utilized the natural nitrogen cycling functions of these microbes to eliminate nitrogen from wastewater streams through conventional nitrification/denitrifications processes and more recently, through the anammox process (Kartal et al., 2004; Mulder et al., 2001).

Table 2.1: Forms of nitrogen in the environment (adopted and modified from Bertino, 2010)

Reduced form Oxidized form

- Nitrite (NO2 )

- Nitrogen Gas (N2) Nitrate (NO3 )

+ Ammonia (NH4 , NH3) Nitrous Oxide (N2O) Organic Nitrogen (urea, humic acid, fulvic acid, amino acids, Nitric Oxide (NO)

Peptides, proteins, amides , purins, pyridines etc.) Nitrogen Dioxide (NO2)

Figure 2.1: New Nitrogen cycle including anammox. Adopted from (Monballiu et al., 2013; Van Hulle et al., 2010).

2.2.1 Nitrification

Nitrifying bacteria are chemolithoautotrophs that oxidize reduced nitrogen compounds to produce both energy and electrons for biosynthesis, and fix CO2 as their carbon source, via Calvin cycle (Metcalf & Eddy, 2003). Because much less energy is accessible from oxidation of inorganic compounds compared to that from the complete

7 oxidation of organic compounds, a lower growth efficiency of autotrophs compared to heterotrophs is observed (Wang et al., 2009).

Nitrification occurs in two steps (Wang et al., 2009), first, ammonia oxidizing bacteria (AOB) oxidize ammonium to nitrite (Eq. (1)). The nitrite is further oxidized to nitrate by nitrite oxidizing bacteria (NOB) (Eq. (2)). The overall reaction for complete nitrification, based on experimental growth yield, can be written as shown in Eq. (3) (Ottengraf et al., 1991, Lin et al., 2009).

+ − + AOB: NH4 + 1.5 O2 → NO2 + 2H + H2O (1)

− − NOB: NO2 + 0.5 O2 → NO3 (2)

+ - - NH4 + 1.83O2 + 1.98HCO3 → 0.021 C5H7NO2 + 1.041H2O + 0.98NO3 + 1.88H2CO3 (3)

Eq. (3) indicates that complete nitrification needs 4.18 g oxygen to oxidize 1 g of

- NH4-N into NO3 -N and that this is an obligatorily aerobic process (Wang et al., 2009).

− + Additionally, approximately 8.62 g HCO3 is required per g of NH4 -N oxidized to buffer

+ + the system because 1 mole of NH4 -N produces 1 mole of H .

2.2.2 Denitrification

- - Denitrification is the reduction of nitrate (NO3 ) to nitrite (NO2 ) and ultimately to dinitrogen (N2) gas under anoxic condition (Eq. (4); Figure 2.2; Metcalf and Eddy, 2003). Denitrifying bacteria are ubiquitous in environmental systems because they are facultative in nature and are more diverse microbial group as they contain organotrophs, lithotrophs, phototrophs, and diazotrophs (Tekin, 2013; Wang et al., 2009).

The denitrification process involves the transfer of electrons from organic carbon to oxidized form of nitrogen in order to make dinitrogen gas and more cells (Eq. (4) and (5)). If there is no organic substrate present in the wastewater, external carbon sources

8 should be added as electron donor (Wang et al., 2009). The most commonly used external carbon source is methanol for denitrification (Metcalf and Eddy, 2003). Eq (4) shows that denitrification produces hydroxyl ion (OH-) that restores half of the alkalinity that was consumed by nitrification (Metcalf and Eddy, 2003). The functions of organic substrate are to reduce nitrate and to make more biomass (Eq (5)).

- − NO3 + 0.833 CH3OH → 0.8333CO2 + 0.5N2 + 1.167 H2O + OH (4)

− − NO3 + 1.08CH3OH + 0.24 H2CO3 → 0.056 C5H7NO2 + 0.47N2 + 1.68H2O + HCO3 (5)

The functions of organic substrate are to reduce nitrate and to make more biomass (Eq (5)). The overall denitrification steps can be simplified as follows (adopted from (Wang et al., 2009))

Nitrate reductase Nitrite reductase Nitric oxide reductase Nitrous oxide reductase - - 2NO3 2NO2 (2NO) N2O N2

2.2.3 Anammox

The anammox process has brought a revolutionary change in the realm of biological wastewater treatment system and has been successfully applied in full scale treatment plants that removed nitrogen biologically with lower cost than traditional nitrogen removal system (Kuenen, 2008; Mulder et al., 1995; Strous et al., 1998). Anammox bacteria use ammonium and nitrite as their primary substrate and produce harmless dinitrogen gas (N2) directly (Strous et al., 1998). Thus, the process does not require full nitrification and denitrification step, and reduces aeration requirements by 60% and eliminates the need to add organic carbon (Mulder et al., 1995). Because of its sustainability, low power consumption and reduced greenhouse gas emission, compared

9 to conventional nitirification/denitrification systems, the anammox system has increased in popularity at full-scale systems (van der Star et al., 2007).

2. 3 Discovery of Anammox

In 1977, Broda predicted the anammox process and observed that there were two types of lithotrophs missing in the nature who used ammonium as an electron donor (Broda, 1977). This missing lithotroph, anammox bacteria, were eventually identified in a pilot-scale fluidized bed denitrifying reactor in the mid 1990’s (Mulder et al., 1995). Since their initial discovery, anammox bacteria have been found to exist in various ecosystems (Gao and Tao, 2011), such as oceanic anoxic basins (Dalsgaard and Thamdrup, 2002; Kuypers et al., 2003), marine ecosystem (Lam et al., 2007; Mohamed et al., 2009), freshwater ecosystems (Schmid, 2000), terrestrial ecosystems (Humbert, 2011), river sediment (Zhang et al.,2007), estuaries (Dale et al.,2009), in sea ice (Rysgaard et al., 2008) and treatment plants (Wang et al., 2016).

The anammox process is mediated by a group of bacteria within the Planctomycetes phylum (Hu et al., 2010). Five genera (Candidatus Brocadia, Kuenenia,

Scalindua, Anammoxoglobus, Jettenia) with ten species of anammox have currently been described (Figure 2.2; Hu et al., 2010; Zhang and Liu, 2014). Among them, Candidatus Scalindua have been found in marine ecosystem (Table 2.2; Hu et al., 2010; Schmid et al., 2005), while Candidatus Brocadia, Candidatus Kuenenia have been found in wastewater systems (Table 2.2; Strous et al., 1999a).

Figure 2.2: Phylogenetic tree based on 16S ribosomal RNA gene showing the relationship among Ca. Scalindua, Ca. Brocadia, Ca. Kuenenia, Ca. Anammoxoglobus, Ca. Jettenia to other Planctomycetes and other reference organisms. Adopted from (Jetten et al., 2001; Kuenen, 2008). The scale bar represents 10% sequence divergence.

Table 2.2: Biodiversity and presence of anammox bacteria, adopted from (Woebken et al., 2008) Genus Species Source Reference

Brocadia Candidatus Brocadia anammoxidans Wastewater (Strous et al., 1999b)

Candidatus Brocadia fulgida Wastewater (Kartal et al., 2004)

Kuenenia Candidatus Kuenenia stuttgartiensis Wastewater (Schmid, 2000)

Scalindua Candidatus Scalindua brodae Wastewater (Schmid, 2000)

Candidatus Scalindua Wastewater (Kuypers et al., 2003) Wagneri

Candidatus Scalindua Seawater (Kuypers et al., 2003) Sorokinii

Candidatus Scalindua Arabica Seawater (Woebken et al., 2008)

Jettenia Candidatus Jettenia asiatica Not reported (Quan et al., 2008) Anammoxoglobus Candidatus Wastewater (Kartal et al., 2007) Anammoxoglobus propionicus

2.3.1 Anammox Biochemical Properties and Metabolic Pathway

Anammox bacteria use nitrite as an electron acceptor, ammonium as electron donor, nitric oxide, hydroxylamine and hydrazine are formed as intermediates (Figure 2.3). The formation of nitric oxide is key because of the difficulty of activating ammonium without oxygen present (Kartal et al., 2011a). A set of three reactions, Eqs. (6) to (8) are given below based on in silico analysis of genome assembly of anammox (Ca . K. stuttgartiensis) was proposed where nitric oxide (NO) and hydrazine (N2H4) were considered as intermediates (Kartal et al., 2011a).

- + - ' NO2 + 2H + e =NO + H2O (E0 = +0.38 V) (6)

+ + - ' NO + NH4 + 2H + 3e =N2H4 + H2O (E0 = +0.06 V) (7)

+ - ' N2H4 = N2 + 4H + 4e (E0 = -0.75 V) (8)

+ - ' NH4 + NO2 = N2 + 2H2O (ΔG0 = -357 kJ/mol) (9)

The role of hydrazine (N2H4) as an intermediate was proposed after observing the transient accumulation of the compound when anammox bacteria were incubated with hydroxylamine (Kartal et al., 2011a; van de Graaf et al., 1996). During reversible inhibition, hydoxylamine and hydrazine addition is helpful to recover the upset reactors (Dapena- Mora et al., 2007; Kimura and Isaka, 2014). Eq. (8) is the energy producing step and some

12 studies suggest that addition of hydrazine can boost the metabolism of anammox and further continue the reaction (Dapena-Mora et al., 2007; Jin et al., 2012).

Figure 2.3: A. Probable biochemical pathway and reaction mechanism of anammox (adopted from (Jetten et al., 1998) . “Ammonium and hydroxylamine are converted to hydrazine by a membrane-bound enzyme complex, hydrazine is oxidized in the periplasm to dinitrogen gas, nitrite is reduced to hydroxylamine at the cytoplasmic site of the same enzyme complex responsible for hydrazine oxidation with an internal electron transport”. B. “Ammonium and hydroxylamine are converted to hydrazine by a membrane-bound enzyme complex, hydrazine is oxidized in the periplasm to dinitrogen gas, the generated electrons are transferred via an electron transport chain to nitrite reducing enzyme in the cytoplasm”. C. Biochemical pathway and enzymatic machinery of anaerobic ammonium oxidation (K. stuttgartiensis). Adopted from (Kartal et al., 2011a).

2.3.2 Summary of Enrichment Techniques

The doubling time of anammox bacteria is very long (11 days to 20 days) compared to a model heterotrophic organism, Escherichia coli (0.35 h; Strous et al., 1998). Because of the slow growth rate, it is extremely difficult to enrich anammox. In early studies, the anammox process was implied within fixed bed reactor and fluidized bed reactor (Mulder et al., 1995; Strous et al., 1999b). Subsequently, Strous et al., (1999) had promoted the theoretical research obtaining high purity anammox (99.6%) bacteria using density- gradient centrifugation. Strous et al. then cultured anammox bacteria in a sequencing batch reactor in a mixed culture system and generated the following stoichiometric equation (Strous et al., 1998).

+ – – + – NH4 + 1.32NO2 + 0.066HCO3 + 0.13H = 1.02N2 + 0.26NO3 + 2.03H2O +

0.066CH2O0.5N0.15 (10)

The research with anammox bacteria enrichment and wastewater treatment were furthered by sequencing batch (SBR) reactor (Kartal et al., 2011; Strous et al., 1998), membrane bioreactor (MBR; van der Star et al., 2007), moving bed biofilm reactor (MBBR) non-woven membrane reactor (Ni et al., 2010), upflow anaerobic sludge blanket (UASB) reactor (Schmidt et al. 2004), rotating biological contactor (RBC; Pynaert et al., 2003) and many other reactors (Zhang and Liu, 2014). Zhang and Liu (2014) performed a bibliometric analysis about the number of articles published on anammox enrichment using different reactor types, from year 1995 to 2012 (Figure 2.4). SBR seems most popular for anammox processes from the graph.

Figure 2.4: Number of articles published on anammox bacteria enrichment using different reactors from 1992 to 2012 (adopted from (Zhang and Liu, 2014))

A Dapena- Mora et al (2004) performed enrichment of anammox bacteria using sequencing batch reactor. In that study, the reactor was inoculated with Rotterdam treatment plant sludge and after 2 months of culture some anammox activity was observed. FISH analysis of enriched anammox showed that the anammox were of Kuenenia stuttgartiensis type. Since anammox bacteria have very slow growth rate sequencing batch reactor was proved to be a good reactor system for anammox enrichment (Dapena-Mora et al., 2004). Sequencing batch reactor maximizes biomass concentration in the system.

Strous (Strous et al., 1998) performed fluidized-bed reactor to treat sludge digester effluent although the retention capacity was not good in that system. However, Schmidt et al (2004) showed that UASB reactor provides more advantages than SBRs, such as, more robust to shocks and toxins and lower foot-print resulting more anammox enrichment and activity (Schmidt et al., 2004). In this study, both SBRs and membrane UASB (MUASB) reactors were used to enrich anammox.

Anammox activity is often expressed as the consumption ratio of nitrite to ammonium (Ruscalleda et al., 2008; Strous et al., 1998). From stoichiometry of anammox reaction (Eq. 10) anammox bacteria consume 1.32 times more nitrite than ammonium (Strous et al., 1998). The stable stoichiometric ratio was usually observed after 60 to 90 days after operation if the lab-scale reactors was inoculated with sludge from any wastewater treatment plant that utilized anammox bacteria (Dapena-Mora et al., 2004). The start-up period of anammox reactor is long because of slow growth rate of anammox. For example, the first full-scale anammox plant in Netherlands needed more than 800 days to see anammox activity (van der Star et al., 2007) . To see a stable conversion, it this plant required more than 1200 days and the maximum removal rate was achieved as 9.5 kg-N/m3-day (van der Star et al., 2007).

To quantify the population and diversity of anammox in enriched sludge, qPCR has been used as a very popular method (Chen et al., 2013; Guo et al., 2016; Jetten et al., 2001; Strous, 2000). Additionally, qPCR has been used to quantify the presence and expression of anammox enzymes that initiate the corresponding chemical reactions (Tekin, 2013).

2.3.3 Factors Affecting Anammox Process

Studies have shown that anammox activity is inhibited by elevated substrate concentrations, heavy metals, antibiotics, some types of short-chain fatty acids or even limited dissolved oxygen (Chamchoi and Nitisoravut, 2007; Gao and Tao, 2011). Some inhibitory effects are reversible. For instance, nitrite inhibition caused by less than 140 mg N/L nitrite can be completely reversed by adding hydroxylamine or hydrazine (Kimura and Isaka, 2014). Likewise, dissolved oxygen (DO) inhibition is also reversible (Jetten et al., 2001). However, some inhibitory effects are irreversible, such as methanol (Guven et al., 2005).

The optimum pH and temperature for anammox bacteria are 7 to 8.5 and 20 to 43˚C respectively (Strous et al., 1998; Xu et al., 2010; Dijkman and Strous, 2002; Jin et al., 2012; Li et al., 2009; Strous et al., 1999b). However, most authors recommended the temperature to be within 30 to 37 ˚C (Sri Shalini and Joseph, 2012; Zhang et al., 2015). Carbon to nitrogen ratio (C/N) is also important for anammox process operation as at C/N ratios greater than 1, denitrifying bacteria will outcompete anammox bacteria for nitrite (Sri Shalini et al., 2015).

2.3.3.1 Concentration of Substrates

While the presence of substrates (ammonium and nitrite) is a requirement for the anammox process, it can be inhibited at elevated concentration of these substrates. Nitrite and ammonium concentration above 100 mg N/L (Ni et al., 2010; Strous et al., 1999b) and 700 mg N/L (Dapena-Mora et al., 2007), respectively, can inhibit the process to a significant extent. Several studies demonstrated that the inhibition can be completely recovered by adding hydrazine or hydroxylamine, even after a long term exposure as they are important intermediates in anammox reaction and initiate energy producing reactor (electron production) (Ni et al., 2010; Strous et al., 1999b).

2.3.3.2 pH

The optimum pH range for the anammox process, suggested from different studies, is from 6.7 to 8.5 (Li et al., 2009; Strous et al., 1999b; Strous, 2000; Van Dongen et al., 2001). This optimal pH range is driven, in large part, by the concentrations of free ammonia (FA) and free nitrous acid (FNA) present at pH values outside of this range. The amount of FA increases with increasing pH (pKa = 9.3) and FNA increases with decreasing pH (pKa = 3.4) (Van Hulle et al., 2010). FA (above 20 mg N/L) is the main inhibitor above pH 8 and FNA (above 1.5 μg N/L) is the main inhibitor below pH 7.5 (Fernández et al., 2012; Van Hulle et al., 2010).

2.3.3.3 Temperature

Studies have shown that temperature can affect anammox activity in many ways. Dosta et al (2008) and Duran et al (2014) observed that stoichiometry of anammox

- + reaction (NO2 : NH4 ) did not change with the temperature change from 15⁰C to 20 ⁰C. However, when temperature dropped from 30⁰C to 18⁰C, they observed a decrease in the nitrite to ammonium ratio because the activation energy increased (at maximum anammox activity and at 35–40 °C, activation energy of 63 kJ mol−1) and led to destabilization of biological system, thus accumulated nitrite in the reactor. They also observed that the temperature above 45 °C caused biomass lysis and reduced the anammox activity. Although, in our study, the temperature of the anammox reactors was not controlled, the ambient temperature never dropped below 20oC and it is a reasonable assumption that temperature has had very little effect on anammox reactors.

2.3.3.4 Bicarbonate Concentration

Since, anammox is autotrophic in nature, they need inorganic carbon (bicarbonate) as a carbon source instead of organic carbon. Low anammox activity was observed under bicarbonate to ammonium ratio of 2.3:1 (Liao et al., 2008) and above 4.7:1 causing inhibition (Van Hulle et al., 2010). The reason of inhibition above the ratio of 4.7:1, might be attributed to type production of FA (Van Hulle et al., 2010).

2.3.3.5 Organic Carbon

Landfill leachate usually contains high organic carbon depending on the age of the landfill as well as high ammonium nitrogen. Several studies showed that chemical oxygen demand (COD) can inhibit the anammox process irreversibly. Molinuevo et al (2009) showed that COD above 237 mg/L caused complete cease in anammox process as denitrifying bacteria outcompeted anammox bacteria for nitrite. Tang et al (2010)

- observed that denitrifying bacteria outcompete anammox when the COD:NO2 -N was

18 above 2.92:1 and longer exposure (more than 12 hrs) made the inhibition irreversible.

- + Chamchoi et al (2008) observed that the stoichiometric ratio (NO2 :NH4 ) was disturbed showing less anammox activity at COD range 100-400 mg/L (COD:N ratio 0.9 to 2) and COD above 300 mg/L caused inactivation or eradication of anammox bacteria.

2.3.3.6 Sulfide

The presence of sulfur bacteria is very common in a mixed community where they

2- reduce sulfate (SO4 ) to hydrogen sulfide (H2S) in anoxic condition using organic carbon as electron donor (Van Hulle et al., 2010). In this study, the SBRs were first fed with ammonium sulfate ((NH4)2SO4), but after observing sulfide smell, the substrate was reduced by ammonium chloride (NH4Cl). Dapena-Mora et al. (2007) observed 50% anammox inhibition at 9.6 mg S/L concertation. Nitrate can reduce sulfide inhibition since, sulfide can use nitrate as electron donor and reduce it to nitrite (van de Graaf et al., 1996).

2.3.3.7 Oxygen

Anammox bacteria are inhibited by dissolved oxygen (DO) since they are strictly anaerobic, although the inhibition was observed reversible (Egli et al., 2001). Because of this tolerance to DO, full-scale treatment plants with deammonification (DEMON), oxygen-limited autotrophic nitrification-denitrification (OLAND; Monballiu et al., 2013) and complete autotrophic nitrogen removal overnight (CANON; Third et al., 2005) processes were possible to implement. In all of these cases, the anammox bacteria are exposed to DO during the partial nitrification stage before regaining activity after the aeration ceases and the system turns anaerobic.

2.3.3.8 Type of Inoculum

Researchers obtained success in enriching anammox bacteria inoculating the reactors with fluvial sediments (e.g., river sediment), activated sludge (e.g., anaerobic digesting sludge) as inoculum and inorganic salt as medium (Dapena-Mora et al., 2004; Strous, 2000; Third et al., 2005). There is a difference in anammox activity in the reactors based on the type of anmmox (granular anammox or suspended anammox sludge) used (Chen et al., 2016; López et al., 2008; Quan et al., 2008). The start-up time of anammox reactor was several years when activated sludge was used as inoculum although it has been reduced to several months recently using those enriched anammox directly to inoculate new reactor (Abma et al., 2007; Chen et al., 2013; Joss et al., 2009; van der Star et al., 2007).

Studies have proved that anammox granule size affect the mass transfer from liquid media through the film of stagnant liquid to the granular surface and then to the core of the granule (Skiadas et al., 2003). Additionally, the anammox growth rate was observed to be higher in free cells (van der Star et al. 2008) than in the anammox granules (Strous et al., 1999), part in due to the mass transfer limitation of the granules, and in part because less energy needs to be invested to facilitate substrate transfer and to the biosynthesis of biofilm matrix component (Kartal et al. 2012).

2.3.3.9. Heavy Metals Inhibition

Efficiency of the anammox enrichment depends on nutrient balance of both macronutrients (C, N, P) and micronutrients (Fe, Ni, Co, Cu, Zn, Mn, Mo) (Sri Shalini et al., 2015; Sri Shalini and Joseph, 2012). Metals are important components of many enzymes, for instance Cu and Mo are important for nitrite reductase (NIR) and nitrite oxidoreductase (NOR). However, the concentration of heavy metals should be kept within appropriate ratio to remove any inhibition possibility. Lotti et al (2012) observed that the

20 inhibitory potential was higher for copper than, Cu shows 25% decrease in anammox activity where Zinc shows 15% for 24 hour exposure period. Studies showed that Cu can cause more harm than Zn at lower concentration to the anammox reactor, for instance 1.9 mg/L of Cu and 3.9 mg/L of Zn were observed to cause 50% inhibition after 24 hrs exposure (Daverey et al., 2014; Lotti et al., 2012). Lotti et al (2012) performed inhibition test with immobilized anammox cells in gel beads and found less inhibition. Immobilized anammox might be less sensitive to metals because of the diffusion gradient difference of the metal towards the anammox.

2.4 Application of Anammox in WWTP

After the discovery of anammox, several novel, advanced and sustainable methods of biological N-removal technologies have been developed and patented by the researchers from all over the world (Li et al., 2008) including: SHortcut nitrification- denitrification Ammonium Removal Over Nitrite (SHARON) (Van Dongen et al., 2001), Oxygen-Limited Autotrophic Nitrification-Denitrification (OLAND; Monballiu et al., 2013), Complete Autotrophic Nitrogen removal Over Nitrite (CANON; Third et al., 2005), Simultaneous Nitrification Anammox and Denitrification (SNAD; Chen et al. 2009) and ANaerobic AMMonium OXidation (ANAMMOX) (Yang et al., 2009). The equations involved in above mentioned processes are given below (Eqs. (11) to (14)). .

+ - + SHARON: NH4 +0.75 O2 + HCO3 → 0.5NO2 + 0.5NH4 + CO2 + 1.5H2O (11)

+ + + OLAND: 2NH4 + 1.5O2 → N2 + 2H + 3H2O (12)

+ + + CANON: NH4 + 0.85O2 → 0.11NO3+0.44N2 +1.14H +1.43H2O (13)

+ + SNAD: NH4 +2 O2 +0.83 CH3OH → 0.5N2 + 0.83CO2 + H + 3.17H2O (14)

Among the above mentioned processes, anammox is a novel process that removes ammonia using nitrite as an electron acceptor under anoxic condition and forms dinitrogen gas (Dong and Tollner, 2003; Mulder et al., 1995). Partial nitritation with anammox (PN/A) has become one of the most popular way to remove ammonium from wastewater (Lackner et al., 2014). PN/A technologies have been successfully implemented in 100 full-scale treatment plants until 2014 where high strength ammonium wastewater with low C:N ration and high temperature (Lackner et al., 2014) has been treated successfully.

Anammox process works best in low C/N ratio, and the value is close to 1 (Sri Shalini and Joseph, 2012). Among those treatment plant 75% of all PN/A installations are used for sidestream treatment of municipal wastewater, 50% installations are sequencing batch reactors, 88% of all plants are operated as single-stage systems (Lackner et al., 2014). Although the system is very efficient since it reduces the aeration cost for full nitrification, incoming solids, proper aeration control, nitrite or nitrate build up cause operational difficulties (Lackner et al., 2014).

PN/A takes place in OLAND, CANON and SHARON-Anammox processes. SHARON- Anammox has several advantages than CANON and SHARON since this process is better- understood, the nitrogen loading and conversion rate are higher as well (Van Dongen et al., 2001).

2.4.1 SHARON-Anammox Treatment Process

The large-scale process SHARON (single reactor system for high-rate ammonium removal over nitrite) was devised by Mark van Loosdrecht and colleagues to convert ammonium exclusively to nitrite through partial nitrification, rather than nitrate (Van Dongen et al., 2001). Since the process was accomplished in a single reactor, microbes formed the granules in a way that ammonium oxidizers were present on the outer side of the granule and anammox organisms were present in the inner side with substrate transport being governed by diffusion (Van Hulle et al., 2010). Temperature control is a crucial factor for SHARON type of reactor. Since NOB grows at a slower rate than AOB, temperature is maintained higher in this reactor to prevent nitrite oxidation (Van Dongen et al., 2001; Xu et al., 2010). Hydraulic retention time (HRT) is also adjusted to keep AOBs inside the reactor and to washout NOBs from the reactor (Xu et al., 2010).

In 2002, the first full-scale anammox based treatment plant was built in Waterboard Hollandse Delta (WSHD) STW Rotterdam, Netherlands (Dokhaven/

Sluisjesdijk), which was initially a SHARON plant treating ammonium rich digester effluent (Van Dongen et al., 2001). It was predicted that a full-scale anammox based treatment plant would take 2 year based on lab-scale experiment, but it actually took more than 3.5 years which was attributed to the slow growth rate of anammox. (Mulder et al., 2001). Abma et al (2007) stated that the delay might be caused by problems with operation, incidental loss of biomass and freezing problem, toxicity by nitrite accumulation, dead zone resulting from poor mixing, sulfide formation.

Figure 2.5: First full-scale anammox based treatment plant, Rotterdam, Netherlands (adopted from (PAQUE, 2011))

2.4.2 Demon Treatment Process

The first full-scale anammox based treatment plant (treating sidestream influent) was built in the US at the Hampton Roads Sanitation District (HRSD) York River treatment plant, Seaford, Virginia in October 2012 (Figure 2.6). They imported 5000 gallons of concentrated biomass of anammox to seed the reactor, which operates utilizing the DEMON process (“Demon of a Process in Seaford,” 2015).

A B

Figure 2.6: A. HRSD York River centrate equalization tank (left) and DEMON tank (right). B. Biomass separation device (BSD) , adopted from (“Demon of a Process in Seaford,” 2015)

The DEMON process takes place in a single reactor, like OLAND and CANON. In this plant, partial nitritation-anammox was designed for centrate treatment from anaerobically digested biosolids and operated as a sequencing batch reactor (SBR). The DEMON process occurs in two steps – 1) the partial nitritation of ammonia and 2) the subsequent anaerobic oxidation of the residual ammonia to dinitrogen gas by nitrite (Figure 2.7).

The HRSD York River plant obtained success in a 65% reduction in aeration energy, 100% reduction in supplemental carbon and approximately 50% reduction in alkalinity requirement in comparison with conventional biological nitrogen removal treatment system (“Demon of a Process in Seaford,” 2015). The DEMON process was able to achieve operating objectives with 70% to 90% total nitrogen removal within 3 months of installment (“Demon of A Process in Seaford,” 2015).

Figure 2.7: Two steps of the deammonication (DEMON) process (partial nitritation and anaerobic ammonia oxidation), adopted from (“Demon of a Process in Seaford,” 2015).

2.5 Substrate Removal Kinetic Models

Kinetic modelling is very important to describe, operate and predict the performance of the reactors (Amin et al., 2013). There are various popular models to perform kinetic studies for anaerobic treatment system including Monod (Monod 1949), first- order Substrate Removal Model, Grau second‑order (Grau et al., 1975), and Stover ‑Kincannon modified (Stover and Kincannon, 1982).

Each of these kinetic models were developed based on some specific assumptions. Following are the assumptions for anaerobic biofilm kinetic models, which are also applicable to anammox reactors (Saravanan and Sreekrishnan, 2006): The granules are spherical in size, there is negligible external mass transfer, the density of the biofilm is constant, the relative concentration of anammox bacteria remains constant throughout anaerobic granule and that these assumptions remain true irrespective of the location in the reactor from where the granule was taken. Additionally, it is assumed that substrate utilization rate can be described by the Monod model and that the input data was taken when the reactor was under steady-state conditions (Amin et al., 2013).

2.5.1 Monod Model

Monod kinetic model is very popular and useful for process kinetics of reactors in wastewater and anaerobic digester treatment plant. Monod (1949) established a differential equation relating utilization of a single rate-limiting substrate and corresponding microbial growth of microbes in a pure culture suspended in a liquid media and at a constant temperature (Bekins et al., 1998). Monod equation is given below.

dS µmax푋 Se KdX = − + (15) dt Y Ks+Se Y

µmaxSe µ= (16) Ks+Se Where, dS = substrate removal rate (mg N/L-day) dt t= time (day) µ=specific growth rate (day-1)

-1 µmax= maximum specific growth rate ( day )

Ks= half saturation constant (mg/L)

Se= effluent total nitrogen concentrations (mg N/L) X= biomass concentration (mg VSS/L) Y= biomass yield (mg VSS/mg of N)

In the Monod formula the rate of transformation increases with the increase of substrate concentration but after a certain concentration the transformation rate does

µmax푋 KdX not go further approaching maximum value given by with decay- assumed to Y Y be negligible. The asymptotic approach is controlled by Se and Ks, the half saturation

27 constant. The Monod model is applicable over a large variation of substrate concentration.

The Monod model is often used to study the kinetics of pure culture of bacteria consuming simple substrate to mixed culture of bacteria consuming complex organic substrates assuming the growth kinetics is similar for both culture systems (Chen et al., 2013). The Monod model parameters of aerobic and anaerobic ammonia oxidation are given in Table 2.3. There are some limitations of Monod kinetic equation as it does not consider influent substrate concentration as an input to determine effluent substrate concentration (Chen et al., 2013). In this study, the Monod model was not used as the parameters were difficult to estimate in our sludge system.

Table 2.3: Parameters of aerobic and anaerobic ammonia oxidation, adopted from (Jetten et al., 2001) Parameter Nitrification Anammox Unit

+ - + - NH4 +O2 → NO2 NH4 +NO2 → N2 Free energy -275 -357 kJ/mol Biomass yield 0.08 0.07 mol/mol C Aerobic rate 200-600 0 nmol/min/mg protein Anaerobic rate 2 60 nmol/min/mg protein Growth rate 0.04 0.003 per hr Doubling time 0.73 10.6 days

+ Ks NH4 5-2600 5 μM

- Ks NO2 N/A <5 μM

Ks O2 10-50 N/A μM

N/A not applicable; Ks affinity constant

2.5.2 First-order Substrate Removal Model

The first- order substrate removal model assumes that first order kinetics is prevailed in the reactor (Jin and Zheng, 2009b). Assuming the substrate concentration is completely mixed, the general first order reaction is given below:

dS QSi QSe − = − − K1S (17) dt V V Where, dS = substrate removal rate (mg N/L-day) dt

QSi = influent loading rate or rate of substrate entering into the reactor (mg N/L-day) V

QSe = rate of substrate leaving the reactor (mg N/L-day) V

K1S = rate of substrate conversion due to first order reaction (mg N/L-day)

Se= effluent substrate concentration (mg N/L)

Si = influent substrate concentration (mg N/L) V= volume of the reactor (L) Q= flow rate (L/day) 푉 θH = = hydraulic retention time (day) 푄

-1 K1= first- order substrate removal rate constant (day )

Under pseudo steady-state condition the rate of change of substrate dS concentration is negligible, = 0. Therefore, the above equation can be modified as dt

QSi QSe Se-Si - = K1Se or, =K1Se (18) V V θH

Se-Si The value of rate constant K1 can be determined by plotting vs. Se and slope θH of the line will give K1. Bekins et al (1998) proved that first order model is valid when the substrate concentration (S) is much less than half saturation constant (Ks). The half saturation constant for total substrates of anammox is less than 0.14 mg N/L (Table 2.3).

2.5.3 Grau Second- order Substrate Removal Model

Grau second-order model was developed to determine multicomponent substrate removal by activated sludge (Grau et al., 1975). The model was developed on the linear removal concept basis which was a broader special case of Monod model. In this model, the order of reaction is analogous to chemical reaction order where the rate constant is not limited to integers only (Grau et al., 1975). The second-order chemical kinetics can be written as follows

dS Se 2 - = K2 X( ) (19) dt Si

Where,

Se-= effluent substrate concentration (mg N/L)

Si = influent substrate concentration (mg N/L)

-1 K2 =second order substrate removal constant (day ). X = biomass concentration (mg/L)

The Grau second-order model was derived from combining the Monod model (Eq (16)) and chemical reaction kinetics (Eq. (19)). The integrated and linearized from of Grau second-order model is given as follows,

SiθH Si = θH+ Si-Se K2Xi

Here,

θH = Hydraulic retention time (day) = V/Q V= volume of the reactor (L) Q= flow rate (L/day)

Si The second term of right hand ( ) side is often considered as a constant “a”. K2X So, the equation will be

SiθH =a + bθH (20) Si-Se

Si Where, “a” (day) = for substrate kinetics (Grau et al., 1975), “a” depends on the K2Xi

Si initial specific substrate concentration and, “b” is another constant (dimensionless) Xi which is close to 1 that reflects the impossibility of attaining zero value of substrate concentration (Grau et al., 1975) at any θH.

2.5.4 Modified Stover-Kincannon Model

Stover-Kincannon model (Stover and Kincannon, 1982) is one of the mostly used mathematical models to determine kinetic constants for UASB reactors. The model was first established for rotating biofilm contactor (RBC) reactor. Stover-Kincannon model provides some flexibility as it is capable of predicting the substrate removal rate independent of reaction kinetics (zero-order, first-order or second- order) at any loading condition (Yu et al., 1998). The model considers substrate removal rate as a function of dS substrate loading rate. The substrate removal rate ( ) in the original Stover- Kincannon dt model is given by,

dS Umax (Q Si/A) = (21) dt KB + (Q Si/A)

dS Q Where, = (Si-Se) and, dt V

Se = effluent substrate concentration (mg N/L)

Si = influent substrate concentration (mg N/L) V = volume of the reactor (L) Q = flow rate (L/day)

- KB = saturation value constant (mg N/L day)

- Umax = maximum substrate utilization rate, (mg N/L day) and A = disc surface area that affects the bacterial growth attached to the disk in an RBC.

The original model assume the suspended biomass is negligible compared to the attached biomass (Stover and Kincannon, 1982). However, in this study all anammox bacteria were in suspended state. Studies have shown that even in biofilm system, the suspended biomass within the interstitial void spaces of the media affect the substrate removal efficiency to a significant extent and can contribute to one-half of total substrate removal (Dahab, 1982; Song and Young, 1986; Tay et al., 1996). Therefore, to extend the scope of the model, the volume of the media (where most suspended biomass exist) was used as a modification of this model instead of using disc surface area (Yu et al., 1998) as given in the equation below,

dS Umax (Q Si/V) = Where, V= volume of media for all biomass dt KB + (Q Si/V)

Linearization of this equation gives the relationship as follows

dS V kB V 1 ( )-1 = = + (22) dt Q(SI-Se) Umax QSi Umax

The modified Stover-Kincannon model (Eq. (22)) can be rewritten as, dS Umax ( Si/θH) = (23) dt KB + (Si/θH)

Here, θH = hydraulic retention time (day) and Si = the loading rate (mg N/L- day). θH

The equation (Eq. (23)) resembles Monod equation (Eq. (16)) however, the

dS Si substrate removal rate ( ) is dependent on loading rate ( ) in Stover-Kincannon dt θH model unlike Monod model. Therefore, the combined effect of influent substrate concentration (Si) and hydraulic retention time (θH) actually affects the substrate removal rate.

The modified Stover-Kincannon model (Eq. (22)) can also be rewritten as,

dS Umax Si = (24) dt KB θH + Si

This equation also resembles Monod equation (Eq. (16)) where Ks in Monod is analogous to KB θH in Stover- Kincannon but as a function of θH . Therefore, hydraulic retention time (θH) affects the saturation constant in this model unlike Monod model.

From Eqs. (23) and (24), it can be concluded that Stover-Kincannon model emphasizes more on the loading rate for substrate removal but Monod model does not.

Kinetic models for bacterial growth depends on two factors, growth rate and substrate utilization rate (Bhunia and Ghangrekar, 2008). Monod (1949) model is very popular as a kinetic model to describe the process kinetics of anaerobic digester. In Monod model, the effluent concentration is independent of influent concentration of the targeted substrate (Chen and Hashimoto, 1980).

However, Grau et al (1975) and Grady and Williams (1975) showed that the effluent substrate concentration should not be considered independent of the influent substrate concentration, especially when mixed culture is used. Therefore, first order, Grau second-order and Stover- Kicannon kinetic models can be used to predict effluent substrate concentration.

CHAPTER 3

MATERIALS AND METHODS

3.1 Sequencing Batch Reactor

In this study, two identical sequencing batch reactors (SBR) were constructed and operated for almost two years to enrich anammox from the Hampton Roads Sanitation District (HRSD) York River treatment plant, Seaford, Virginia (VA_SBR) and the Dokhaven wastewater treatment plant (WWTP), Rotterdam, Netherlands (NL_SBR). The schematic diagram of the rector is shown in Figure 3.1.

Both SBRs have had identical working volume of 4L in 5L glass VWR bottles. The SBRs have been operated in 24 hour cycle consisting of 0.33 hr feeding, 22.67 hr reaction, 1 hr settling and 0.33 hr decanting time (Figure 3.2). Peristaltic pump flow rate was maintained 55ml/min during feeding and decanting. Influent was supplied from identical VWR bottle of 10L. Nitrogen gas bags were attached to the SBRs and media bottles during whole operation period to remove the possibility of oxygen entrance during feeding or decanting period inside the reactor.

Figure 3.1: Schematic diagram of sequencing batch reactor.

Figure 3.2: Schematic diagram of each cycle of sequencing batch reactor.

3.2 Membrane Upflow Anaerobic Sludge Blanket Reactor

A membrane upflow anaerobic sludge blanket (MUASB) reactor was developed and inoculated with anammox sludge from VA_SBR after a year of enrichment. A carbon nanotube (CNT) membrane filter, kindly provided by Dr. David Jassby (UC Riverside) was installed on top of the reactor and charged by DC power source with 2V to reduce biomass

36 loss. Combination of electrically conducting CNT with cross-linked polymer (PA or PVA) filters are better than traditional ultrafiltration (UF) membrane as they maintain their critical transport properties (salt rejection and water permeability) and also, reduce membrane fouling (Guillen and Hoek, 2010). The electrically conductive (2500 S/m) filters made of cross-linked polyvinyl alcohol and carboxylated multi-walled carbon nanotubes (PVA–CNT–COOH) can substantially increase the electrofiltration efficiency, producing charged membrane surface that can repulse bacteria, thus increase biomass retention (Dudchenko et al., 2014).

Figure 3.3: (A) Classical electrofiltration cell setup. (B) Electrofiltration with conducive membrane/thin film set up (adopted from Dudchenko et al., 2014).

Figure 3.3 shows the difference between traditional electrofiltration cell and new electrofiltration with conductive membrane (Dudchenko et al., 2014). The classical electrofiltration system was inefficient due to an insulator formation resulting from opposite electrode placed on the opposite sides of the membrane (Guillen and Hoek, 2010). Whereas in the conductive membrane, CNT itself acts as cathode, thus reduces the high energy demand for permeate flow (Dudchenko et al., 2014).

A steel mesh of #500 was placed on top and the CNT membrane was placed on the bottom of the of the plastic O-ring insulator. The steel mesh was connected with positive end of the power to make it anode and CNT membrane worked as cathode. Since CNT membrane was negatively charged, it would repulse the bacteria as bacteria surface carried negative charge. A Masterflex peristaltic pump (Cole-Parmer Instrument Company, IL, USA) was maintained at 0.67 ml/min throughout the operation period. The volume of the reactor was 400ml and hydraulic retention time (HRT) was 10 hrs. The anammox sludge volume was approximately 50ml.

Figure 3.4: Schematic diagram of membrane upflow anaerobic sludge blanket reactor.

3.3 Water Quality Analysis

3.3.1 pH

pH was measured by accumet (Fisher Scientific) pH meter and probe. The pH probe was calibrated each time with pH 4 and pH 7 buffer solution.

3.3.2 Total Suspended and Volatile Suspended Solids

10 ml of completely mixed sludge samples are collected from each reactor to determine TSS and MLVSS. Samples are filtered with Whatman 934AH fiberglass filters (GE Healthcare Life Sciences) and total suspended solids (TSS) and volatile suspended solids (VSS) were determined according to APHA Standard Methods (APHA, 2005).

3.3.3 Chemical Oxygen Demand (COD)

Chemical oxygen demand (COD) was determined using Thermo Scientific (Thermo Fisher Scientific, MA USA) Orion AQUAfast COD Low range (0-150 mg/L) cuvettes that has strong oxidizing agent, potassium dichromate (KCr2O7). The standard and samples are digested using the procedure of COD reactor digestion method 8000 (USEPA approved). Thermo Scientific Orion AQUAMATE 8000 UV-Vis Spectrophotometer has been used to measure absorbance after completing the digestion. A standard curve of COD vs absorbance was plotted (Appendix Figure A4) and used to determine the COD for samples.

3.3.4 Ammonium, Nitrite and Nitrate Test

Dionex ICS-5000 (Dionex, Sunnyvale, CA, USA) was used to measure ammonium, nitrite and nitrate concentration. Anions and cations pump pressure were maintained at 1600 and 2000 psi. Eluent gas cartridge (EGC) concentrations were maintained at 15 mM and 30 mM for anions (NaOH) and cations (Methanesulfonic Acid; MSA) respectively. Dionex IonPac™ CS16 column was used for cation and Dionex IonPac™ AS18 column was used for anion. Tests durations were 8 min for anions and 15 min for cations. Standard

+ - - curves were drawn from NH4Cl, NaNO2 and KNO3 solution for NH4 , NO2 and NO3 . 1 mM

+ - to 10mM concentration of NH4 and NO2 were used for standard curve (Appendix Figure

- A1-A2). 0.1 to 2mM concentration of NO3 were used for standard curve of nitrate (Appendix Figure A3).

3.4 Media Recipe

Media bottles were soap-washed and autoclaved before preparing media. Components of media were added to 10L of nanopure DI water, to the final concentrations listed in Table 3.1, and stirred. After mixing, the media bottle was purged with nitrogen gas for 30 minutes to remove oxygen.

Table 3.1: Recipe of media used for MUASB reactor Component Concentration in Media

(NH4)Cl 4 mM

NaHCO3 12 mM

NaNO2 4 mM

CaCl2 ∙ 2H2O 2 mM

KH2PO4 0.2 mM

MgSO4 ∙ 7H2O 1 mM

KNO3 1 mM

FeSO4 ∙ 7H2O 0.040 mM

EDTA 0.080 mM

Trace Metal Solution* 1ml/L of media

*Trace Metal Solution Recipe (for 1L volume)

ZnSO4 ∙ 7H2O 546mg

CoCl2 ∙ 6H2O 309 mg

MnSO4 ∙ H2O 1.065 g

CuCl2 ∙ 2H2O 222 mg

Na2MoO4 ∙ 2H2O 266 mg

NiSO4 ∙ 6H2O 368 mg

K2SeO4 155 mg

H3BO4 18 mg

EDTA 18.75 g

Media components used for making MUASB are given in Table 3.1 with ammonium and nitrite concentrations of 4mM, each. Media used for SBRs had higher concentrations of ammonium (up to 16mM) and nitrite (up to 16mM), since it would be diluted with remaining media inside the reactor. Media constituents for two SBRs are given in Appendix Table A1. The final concentration of mixture inside the SBRs was maintained from 2 to 4 mM for both substrates (ammonium and nitrite).

3.5 Genomic Analyses

3.5.1 DNA Extraction and PCR

Total DNA was extracted from sludge samples (approximately 3ml) collected from each anammox reactors at different time interval using PowerSoilTM DNA Isolation Kit (MO Bio Laboratories, Inc., CA, USA), as described in the manufacturer’s protocol. DNA concentration in each sample was quantified with a NanoDrop UV-Vis Spectrphotometer ND-1000, per manufacturer’s protocol.

16S rRNA gene fragments were amplified from the extracted DNA with total bacteria, Planctomycetes and anammox specific primers for Candidatus Brocadia and Candidatus Kuenenia species (Invitrogen) and AccuStart II PCR ToughMix (Quanta BioSciences, Inc.) using an Eppendorf thermocycler (Eppendorf Mastercycler gradient, Germany). Primers and the thermal cycling conditions used for PCR reaction are described in Table 3.2. Endpoint PCR was done for each primer set at different primer concentrations (Table 3.3) to obtain optimum primer concentration for each primer pair before performing any qPCR.

Table 3.2: Targets and primer used for endpoint PCR and qPCR primer optimization

* Target Primer Sequence (5’-3’) Size Td Ta Te

name (bp) (°C), (°C) (°C)

durati

Bacterial 16S 1369f CTTGTACACACCGCCCGTC 123 94, 56, 72, rRNA gene¥ 1492r GGWTACCTTGTTACGACTT 1min 1min 1.5min

Planctomycetes PLA 46F GGATTAGGCATGCAAGTC 472 94, 50, 72,

16S rRNA gene U 518R ATTACCGCGGCTGCTG 1min 1min 2min

¥¥

Amx694F GGGGAGAGTGGAACTTCGG 266 96, 64, 72,

Anammox¥¥¥ Amx960 GCTCGCACAAGCGGTGGA 1min 1min 1min

R GC

¥Reference: Li et al., 2009 ¥¥Reference: Yang et al., 2007 ¥¥¥Reference: Hu et al., 2010 * Td =denaturing temperature, Ta = annealing temperature, Te =elongation temperature

After amplification, the endpoint PCR product were run through a 1% (w/v) agarose gel (120 Volts) to check the correct size comparing with standardized molecular weight ladder and ensure that only one PCR product is being produced. The gels were visualized using a UV Transilluminator (UVP BioDoc-It™ System, CA, USA).

The optimized concentration and volume for 16S rRNA probes: total bacteria (1389f/ 1492r), Planctomycetes (Pla46f/ U518r) and anammox (Amx 694f/ 960r) are given in Table 3.3. For all PCR and qPCR studies, those concentrations were used for both forward and reverse primers.

Table 3.3: Optimized primer concentration and volume for PCR and qPCR

Target Concentration of Volume of each Cycle

primer (mM) primer (μl)

Total bacteria 1 3 30

Planctomycetes 10 4 30

Anammox 10 1 40

3.5.2 Real-time PCR

Endpoint PCR product are purified using QIAquick PCR Purification Kit (QIAGEN, Germany). DNA concentration was quantified with NanoDrop spectrophotometer (ND- 1000, CGRB Core facility, OSU). 16S rRNA gene is quantified with qPCR reaction is done with 1X iQ SYBR Green Supermix (Bio-Rad, Singapore) using ABI PRISM 7500 FAST Sequence Detection System. The quantification was based on the fluorescent dye SYBR Green, which binds to double stranded DNA during qPCR amplification. The data from qPCR are obtained and analyzed by 7500 FAST System v 2.0.6 software. Melting curve

43 analysis of the PCR products was conducted following each assay to ensure that the fluorescence signal originated from specific PCR products and not from primer–dimers or other artifacts.

3.5.3 Calculations for Standard Curve

Purified DNA are quantified by Nanodrop Spectrophotometer and diluted ranging from 1x to 10-8X with nano pure DI water. The 16S rRNA gene of total bacteria, Planctomycetes and anammox are then quantified after qPCR reaction with corresponding probes, using ABI PRISM 7500 FAST Sequence Detection System. The cycle times were obtained from 7500 FAST System v 2.0.6 software and used to calculate DNA copy number. Cycle time was selected from the constant fluorescence value 300,000 for all qPCR data analysis.

The DNA copy number calculation was based on the assumption that the average weight of a base pair (bp) is 650 Daltons. The inverse of the molecular weight is the number of moles of template present in one gram of material. Using Avogadro's number, 6.022x1023 molecules/mole, the number of molecules of the template per gram can be calculated. Finally, the number of molecules or number of copies of template in the sample can be estimated by multiplying by 1X109 to convert to ng and then multiplying by the amount of template (in ng).

DNA copy number per μl of extracted DNA = [concentration of extracted DNA (ng/ul)]* [6.022x1023 (molecules/mol)] *1/ [650 (g/ mol of bp)) * length of template (bp)] * [1X109 (ng/g)] (25)

Cycle time and log (copy number) are plotted for standard curve plot (Appendix Figure A5 to A8).

3.6 Sample collection and Storage

Water samples were collected from influent and effluent from each of three reactors in 1.5 ml micro-centrifuge tubes. Samples are stored in -80˚C refrigerator before chemical analysis if they needed to be analyzed later. For molecular analysis, suspended microbes with have been collected by syringe in a 15ml falcon tube, centrifuged, decanted and stored in -80˚C refrigerator before extracting DNA. After DNA extraction from microbe samples, templates were kept in -80˚C refrigerator in 2ml centrifuge tubes.

3.7 Kinetic Experiments

Several kinetic models first-order, Grau second-order and Stover-Kincannon model parameters were developed from two identical SBRs. For this purpose, the HRT was varied from 3 hr to 3 days and the concentration of substrates (ammonium and nitrite) were varied from 14 mg/L N to 56 mg/L N. The equations and models assumptions are described in section 2.6. Stover-Kincannon model was performed for kinetic study in MUASB.

3.8 Leachate Experiment

Landfill leachate collected from Coffin Butte landfill (Benton County, Oregon) was used for leachate experiment to determine Stover-Kincannon kinetic parameters. For this experiment, the ammonium salt (NH4Cl) of the anammox growth media was replaced with landfill leachate ammonium. Since, leachate had a higher concentration of

+ ammonium (NH4 ) it was diluted 10 times (DF=10) with nanopure DI water and all other constituents are added as mentioned in Table 3.1. The desired concentration of ammonium and nitrite was 84 mg N/L in the MUASB for the kinetic study. The concentration of COD was 185 mg/L after the dilution. Stover-Kincannon kinetic model experiment was performed for substrate concentration ranging from 14 to 84 mg N/L for

45 with leachate and without leachate, keeping the hydraulic retention time (HRT) same (10 hrs).

3.9 Leachate Pretreatment

FeCl3 was added to landfill leachate to a final concentration of 3 g/L of FeCl3. 6H2O. The landfill leachate pH was reduced to pH 4 with concentrated HCl. Following the pH reduction, the landfill leachate/FeCl3 mixture of 2L volume was mixed rapidly for 1 min at 80 RPM using flocculator (jar test apparatus) and mixed slowly at 100 RPM overnight on a rocker table (G10 Gyrotory Shaker, New Brunswick Scientific Co., Inc, NJ, USA). A beaker of 2L volume was used for the mixing purpose. After the overnight mixing, the pH was increased back to 7 by adding concentrated NaOH.

CHAPTER 4

RESULT AND DISCUSSION

In this study, anammox enrichment was performed in three different reactors- two sequencing batch reactors (VA_SBR and NL_SBR) and one carbon nanotube (CNT) membrane upflow anaerobic sludge blanket reactor (MUASB). Anammox bacteria were cultured in SBRs for more than 16 months and an MUASB reactor with carbon nanotube membrane filter for more than 10 months.

One of the SBRs (VA_SBR) and the MUASB were inoculated with anammox sludge from the Hampton Roads Sanitation District (HRSD) York River treatment plant in Seaford, Virginia. The HRSD treatment plant is the first full-scale anammox based treatment plant in the US (Wu et al., 2016). The anammox process has been used as a sidestream for deammonification (DEMON) treatment process. The other SBR, NL_SBR, was inoculated with anammox sludge from Dokhaven wastewater treatment plant (WWTP), Rotterdam, Netherlands, the first full-scale anammox treatment plant in the world (Mulder et al., 2001). The plant utilizes the SHARON- Anammox process.

The Results and Discussion chapter is divided into three sections. The first section deals with comparison of influent and effluent concentrations, nitrogen removal rates and efficiencies, and bacterial population dynamics in each of three reactors. The second section covers kinetic studies of the three reactors in which first order, Grau second order and Stover-Kincannon models were used to characterize the SBRs and MUASB. The third section discusses the removal of nitrogen from landfill leachate, both pretreated and not, using anammox cultured in a MUASB.

4.1 Anammox Enrichment Study

Anammox enrichments were first started with two SBRs. Subsequently an MUASB was developed after observing some operating difficulties in SBRs and to ensure more biomass retention for efficient enrichment. In this section, the results from anammox reactors regarding enrichment will be discussed and compared. Total nitrogen removal,

- nitrogen removal efficiency, nitrite consumption to ammonium consumption ratio (NO2 :

+ NH4 ) and qPCR results are used to quantify the anammox enrichment in the different reactors. Some physical parameters can also be used as a proof of successful anammox enrichment, such as pH increase after substrate consumption, N2 bubble production and appearance of reddish color of anammox granule after few months of enrichment.

4.1.1 Performance and Efficiency of VA_SBR

The VA_SBR inoculated with HRSD York River WWTP anammox sludge, was operated for more than 16 months. The WWTP has been using the DEMON process which contains both AOBs and anammox in a single treatment tank. The VA_SBR was first fed

+ - with 14 mg N/L of substrates (NH4 and NO2 ) and the loading rate was increased gradually to 56 mg N/L up to day 50 (Figure 4.1). Although the percentage removal of total substrate dropped in that period, the total nitrogen removal rate increased (Figure 4.1 and 4.2).

Figure 4.1 and 4.2 illustrate the combination of substrate (ammonium and nitrite) removal efficiency (%) and substrate removal rate in mg N/ L-day respectively and in VA_SBR reactor. The reactor was unstable for first few months showing higher and sometimes lower substrate removal efficiency.

+ - Figure 4.1: Substrate (total NH4 -N and NO2 -N) removal efficiency (%) vs age of VA_SBR reactor. Arrows are used to show the reactor upset caused from high concentration of - NO2 shock.

+ - Figure 4.2: Substrate (total NH4 -N and NO2 -N) removal rate (mg N/L-day) vs age of VA_SBR reactor. Arrows are used to show the reactor upset caused from high - concentration of NO2 shock.

Some technical issues arose during operation, such as, timer malfunctions, which resulted in an influent overflow in the rector that caused nitrite build-up. The effect of

49 those incidents on the performance of the anammox were observed on day 50, 210, 356 and 380 during this study period (showed with arrows in Figure 4.1 and 4.2). On average, it took around a week to recover completely from the shock. The recovery period depends on the concentration of nitrite and the duration of high nitrite concentration in the reactor. If the concentration was too high (more than 90 mg N/L) in VA_SBR, it took more than two weeks to regain the previous performance (Figure 4.2 and 4.4).

+ On day 50, NH4 -N removal went below 18% when the reactor received more than

+ - 60 mg N/L of NH4 . NO2 -N removal efficiency went below 30% when it received more

- than 40 mg N/L of NO2 (Figure 4.3, 4.4, 4.6 and 4.7). On day 350, the efficiency went down to 10% from 99% due to the nitrite concentration reaching 90 mg N/L as a result of a technical error (longer feeding time and reactor overflow) during feeding cycle of the VA_SBR. Nitrite above 70 mg N/L for a longer period (more than 12 hrs) is extremely harmful for anammox and can lead to irreversible inhibition (Jetten et al., 2001; Kartal et al., 2011).

The maximum nitrogen removal capacity of this reactor was 0.092 g N/L-day or

3 0.092 kg/m reactor-day (Figure 4.2) on day 138. This is much lower than the first literature value reported by anammox enrichments operated by Strous et al (1997), which achieved maximum nitrogen removal of 1.5 kg N/m3-day in a fluidized-bed anammox reactor fed with sludge digestion effluent from a domestic WWTP. Strous developed fluidized bed reactor and subsequently, fixed bed reactor to enrich anammox with Syrian glass beads having high surface area were used as carrier material and recycle was applied to reduce the potential toxicity from high nitrite concentration. The above mentioned steps taken by Strous, in developing those reactors may have made a difference between their study and our study.

100

0 21 36 56 97 122 202 217 238 260 313 354 374 411

Ammonium Ammonium Concentration (mg N/L) Age of Reactor (day)

Influent NH4 Effluent NH4

+ Figure 4.3: Influent and effluent ammonium (NH4 ) concentration (mg N/L) changed over time in VA_SBR. Arrows are used to show the reactor upset caused from high - concentration of NO2 shock.

100

NitriteConcentration (mg N/L) 0 21 36 56 97 122 202 217 238 260 313 354 374 411 Age of Reactor (day) Influent NO2 Effluent NO2

- Figure 4.4: Influent and effluent nitrite (NO2 ) concentration (mg N/L) changed over time in VA_SBR. Arrows are used to show the reactor upset caused from high concentration - of NO2 shock.

Figures 4.1 to 4.4 illustrate that the nitrogen removal efficiency of the VA_SBR reactor depends on the substrate loading rate. Anammox bacteria can adjust with the sudden shock of highly concentrated ammonium and nitrite but it requires some time to

51 recover or to adopt. For instance, anammox started to utilize more substrates (both ammonium and nitrite) gradually when both substrate concentrations were increased to 50 mg N/L (Figure 4.2, 4.3 and 4.4) from day 21 to day 138, showing the maximum total nitrogen removal rate of 0.092 g N/L on day 138. Although, during that time period (day 21 to day 138), the efficiency of total nitrogen removal varied between as low as 30% to as high as 90%. The increase in total nitrogen removal rate can be attributed to higher anammox activity due to the higher anammox population in the reactor than before.

NO Produced 40 3

0 110 138 210 222 250 271 331 360 389 417 -20

NO3 Consumed Nitrate Production (mg Nitrate(mg Production N/L)

-40 Age of Reactor (day)

Figure 4.5: Nitrate produced or consumed (mg N/L) vs age of the VA_SBR reactor (day). - Arrows are used to show the reactor upset caused from high concentration of NO2 shock.

Figure 4.5 illustrate the nitrate production or consumption throughout the operation period of VA_SBR although the data for first 110 days were not shown. The graph shows that there are several days where nitrate was consumed by denitrifying bacteria instead of being produced by anammox bacteria. Around day 210 and day 356, when the upset occurred due to high nitrite concentration, the denitrification activity was also observed. Anammox bacteria and denitrifying bacteria co-exist in the single reactor especially in mixed culture system (Abbassi et al., 2014; Dong and Tollner, 2003). High

52 concentration of nitrite is favorable for the growth of denitrifying bacteria and anammox bacteria are outcompeted, thus decrease the anammox activity.

Figure 4.6: Ammonium removal efficiency (%)vs age of the VA_SBR reactor (day). Arrows - are used to show the reactor upset caused from high concentration of NO2 shock.

Figure 4.7: Nitrite removal efficiency (%) vs age of the VA_SBR reactor (day). Arrows are - used to show the reactor upset caused from high concentration of NO2 shock.

Figure 4.6 and 4.7 show the individual efficiency for each substrate, ammonium

+ - + (NH4 ) and nitrite (NO2 ) removal from VA_SBR. NH4 -N removal efficiency was lower than

- NO2 -N removal most of the time during the operation period. During the period of day

+ 80 to day 160 and substrate concentration range from 42-70 mg N/L, NH4 -N removal

- was more severely affected than NO2 -N removal, suggesting that anammox activity was also accompanied by denitrifying bacteria. For instance, from day 80 to day 160, the

- substrate concentration varied from 40 to 70 mg N/L (Figure 4.3 and 4.4) where NO2 -N

+ removal efficiency was observed almost stable (50% to 100%) but NH4 -N removal

+ efficiency was not (15% to 90%) (Figure 4.6 and 4.7). NH4 -N removal efficiency was

- inconsistent and showed no pattern during the study period whereas NO2 -N removal efficiency stayed within 50% to 100% most of the time, except for the substrate overflow incidents. The higher nitrite removal percentage than ammonium removal percentage was most likely because of denitrification activity if there was any organic matter present.

HRSD York River WWTP has been operating DEMON process in two steps- partial nitrification with AOBs and anaerobic oxidation of ammonium with anammox bacteria. Since, we collected the anammox sludge from that treatment plant, there is a high possibility of having other bacteria present in the VA_SBR. The discrepancy between ammonium consumption and nitrite consumption might suggest some other bacteria activity (i.e. denitrification).

Another important parameter of anammox enrichment, the nitrite consumption to ammonium consumption ratio for both SBRs used in this study, will be discussed in section 4.1.3.

4.1.2 Performance and Efficiency of NL_SBR

The NL_SBR inoculated with Dokhaven WWTP was operated for more than 14 months. The treatment plant has been function with SHARON-Anammox process where the partial nitrification and anammox process were taken place in separate reactors (two- reactor system) unlike the DEMON process (single- reactor system) (Lackner et al., 2014; Mulder et al., 2001). In this study, the NL_SBR reactor was first started with fed-batch

+ - system where the substrates, NH4 and NO2 , were fed by a set of syringes from a syringe pump and continued for 3 months. The system ended up being not very effective and had nitrite often accumulated in the SBR (data not shown).

While SBRs can tolerate hydraulic shocks, they cannot handle substrate concentration shock (Jin et al., 2008). Since, the fed-batch system was used over a very short cycle time, it was more susceptible to substrate concentration shocks (higher nitrite concentration), and that could not provide the promising solution for anammox enrichment. After the failure of 3 months’ trial period with fed-batch system, the reactor was transformed to an SBR from day 160 (data shown here from day 194) with 24 hr cycle time, same as the VA_SBR.

The NL_SBR reactor showed very poor performance in terms of total substrate

+ - (NH4 -N and NO2 -N) removal efficiency for first few months (Figure 4.8) which could be attributed to the recovery period after fed-batch system failure. For instance, from Figure 4.9, from day 194 to 300, the total nitrogen removal rate was observed to be as low as 5 mg N/L to as high as 70 mg N/L (ignoring the negative values) and was inconsistent in comparison with the activity occurred in later time period (day 300 to day 360).

Figure 4.8: Substrate (total ammonium and nitrite nitrogen) removal efficiency (%) vs age of NL_SBR reactor.

Figure 4.9: Substrate (total ammonium and nitrite nitrogen) removal rate (mg N/L- day) vs age of NL_SBR reactor.

Since, both SBRs (VA_SBR and NL_SBR) were connected with same pump and timer system, both reactors were subjected to substrate shock at the same time period. The incident of substrate shock (140 mg N/L) on day 377 in NL_SBR reactor took more than 40 days to recover (Figure 4.8 and 4.9). The shock happened due to substrate overflow and the reactor had not yet fully recovered. Some negative nitrogen removal

- rates were also observed in this reactor suggesting NO2 -N production instead of

- consumption on day 225 (-5 mg N/L), 262 (-2 mg N/L), 377 (-21 mg N/L). NO2 was observed being produced by denitrifying bacteria in anoxic condition in NL_SBR reactor (Figure 4.12), instead of being consumed by anammox bacteria. Although purging with nitrogen gas to remove air from the reactor and the attached N2 gas bag were always maintained for this reactor like VA_SBR reactor. Figure 4.8 also shows that, from day 190 to day 241, the nitrogen removal efficiency was unstable and the efficiency was as low as -5%. The reason might be that

- the concentration of nitrite was too high (122 mg NO2 -N /L) at that time period (Figure 4.11). It was observed that nitrite concentration above 70 mg N/L for a longer period (more than 12 h is extremely harmful for anammox and can lead to irreversible inhibition (Jetten et al., 2001; Kartal et al., 2011). Figure 4.10 and 4.11 showed a gradual decrease

+ in substrate concentration, from day 190 to 210, starting from 101 mg NH4 - N/L and 116

- + - mg NO2 - N/L to 50 mg NH4 - N/L and 30 mg NO2 - N/L respectively. The NL_SBR performed best (up to 97% total nitrogen removal efficiency) when the ammonium and nitrite were

+ - maintained 35-80 mg NH4 - N/L and 34-50 mg NO2 - N/L concentration range respectively. The anammox activity was drastically reduced (-21% nitrogen removal efficiency) when

+ the concentration for ammonium and nitrite were above 80 mg NH4 - N/L and 90 mg NO2 -N/L, and when they stayed inside the reactor for longer period without any dilution (Figure 4.10 and 4.11).

120

100

Concentration (mg N/L) 20

0 193 209 224 246 267 328 350 390 Age of Reactor (day) Influent NH4 Effluent NH4

Figure 4.10: Influent and effluent concentration of ammonium (mg N/L) vs age of NL_SBR reactor (day).

160 140 120 100 80 60 40

Concentration (mg N/L) 20 0 193 209 224 246 267 328 350 390 Age of Reactor (day) Influent NO2 Effluent NO2

Figure 4.11 Influent and effluent concentration of nitrite (mg N/L) vs age of NL_SBR reactor (day).

Figure 4.10 and 4.11 show that from day 290 to day 350, both ammonium and nitrite removal were at some of their highest levels (Figure 4.8 and 4.9). The performance

58 of the NL_SBR reactor was better in that period than any other time period as there was not any upset from substrate overflow during that time.

20 NO3 produced

0 194 210 225 247 268 329 356 391 -10

-20 NO3 consumed NitrateProduction (mg N/L)

-30 Age of Reactor (day)

Figure 4.12: Nitrate production or consumption (mg N/L) vs age of reactor (day) in the NL_SBR reactor.

Figure 4.12 shows the nitrate production and consumption throughout the age of NL_SBR reactor. NL_SBR also suffered from denitrification activity similar to VA_SBR (Figure 4.5 vs. 4.12). The denitrification activities in both reactors may have been caused by the death of the unwanted bacteria that eventually introduced the organic carbon (electron donor), necessary for the survival of denitrifying bacteria. In some days, it was observed that the denitrifying bacteria outcompeted anammox bacteria in both SBRs.

Figure 4.13 and 4.14 depict the individual efficiency for each substrate,

+ - ammonium (NH4 ) and nitrite (NO2 ) removal from NL_SBR. Similar pattern was observed

- in NL_SBR as VA_SBR in that NO2 -N removal was less affected with the change in

+ substrate concentration than NH4 -N (Figure 4.6 vs. 4.13 for ammonium and Figure 4.7

- vs. 4.14 for nitrite). There were some negative values observed in both NO2 -N removal rate and efficiency resulting from denitrification and thus, nitrite production from nitrate

(Figure 4.12). Since, the reactor was maintained anaerobic during the operation period, the nitrite production can be attributed to the activity of denitrifying bacteria. The

+ - maximum NH4 -N removal efficiency and NO2 -N removal were obtained 94% and 100% respectively in the NL_SBR.

Figure 4.13: Ammonium removal efficiency (%) vs age of reactor (day) in the NL_SBR reactor.

Figure 4.14: Nitrite removal efficiency (%) vs age of reactor (day) in the NL_SBR reactor.

To summarize, the ammonium consumption and nitrite consumption was not consistent throughout the operation period of NL_SBR. Since, the anammox sludge was collected from SHARON-Anammox type of treatment plant, there is a high possibility of having other bacteria (i.e. denitrifying bacteria) present in the NL_SBR. The activity of denitrifying bacteria might be reflected on the data (Figure 4.12). Nitrite removal efficiency was observed noticeably higher than ammonium in all reactors (Figure 4.6, 4.7, 4.13 and 4.14). Both SBRs were upset several times during the operation as mentioned earlier due to higher substrate concentration.

Anammox bacteria are inhibited by their own substrates, ammonium and nitrite, and nitrite was observed being more inhibitory than ammonium (Dapena-Mora et al., 2007; Isaka et al., 2007). In this study, even at lower concentration of nitrite of 35 mg NO2—N/L, inhibition of anammox process was observed for the reactor (Figure 4.4) whereas in literature, nitrite concentration above 140 mg N/L was considered as suboptimal for anammox process and 280 mg/L was considered as complete inhibitor (Jetten et al., 1998). Reactor upsets affected ammonium removal more than nitrite removal. Ni et al (2011) has also seen similar results when their reactor got upsets.

Since, anammox bacteria coexisted with all other bacteria in all of our mixed anammox culture systems that might be the reason of seeing the discrepancy in ammonium and nitrite consumption from day to day. The total amount of anammox population in the reactors were low resulting lower nitrogen removal efficiency in comparison with literature value. For instance, López et al (2008) performed a study where he enriched 85% anammox and showed 1.6 g N/L-day nitrogen removal after a year of start-up the reactor from activated sludge in an SBR. Studies have shown that the reactors inoculated with mature and highly enriched anammox granules performed better than reactors inoculated with sludge and are more robust to sudden shocks of higher substrate concentration (Jin et al., 2008; Strous et al., 1998).

4.1.3 Comparison Stoichiometric Ratio of Substrates between VA_SBR and NL_SBR

The stoichiometric ratio of ammonium and nitrite from Eq. (10) is very crucial to determine if the substrate concentration is changing due to only anammox bacteria in a mixed bacteria population (Jin et al., 2013; Ruscalleda et al., 2008). Strous et al (1999)

- + obtained a NO2 : NH4 consumption ratio of 1.32 from a highly purified anammox reactor. This ratio has been widely used to determine the performance and efficiency of anammox reactor and anammox activity (Eq. (10); López et al., 2008). In this section, the

+ - stoichiometric ratio of NH4 consumption and NO2 consumption will be discussed and compared between VA_SBR and NL_SBR reactors.

VA_SBR NL_SBR 5 5 4.5 4.5 4 4 3.5 3.5 3 3

2.5 2.5 NO2:NH4 2 NO2:NH4 2 1.5 1.5 1 1 0.5 0.5 0 0 20 80 140 200 260 320 380 190 250 310 370 430 Age of Reactor (day) Age of Reactor (day) - + Figure 4.15: Nitrite (NO2 ) consumption to ammonium (NH4 ) consumption ratio in VA_SBR (left) and NL_SBR (right) on daily basis. Arrows are used to show the probable upset periods.

Figure 4.15 illustrates that nitrate consumption to ammonium consumption ratio was highly variable in both the VA_SBR (1.48 ± 1.04) and the NL_SBR (1.00 ± 0.67), which

62 could be attributed to the presence of mixed bacteria in both reactors. Metagenomic sequencing results also indicate a highly diverse microbial population in both SBRs (Appendix Figure A8, Table A3).

The higher stoichiometric ratio might be caused by denitrifying bacteria in both reactors indicating more nitrite being consumed than ammonium. Denitrifying bacteria use nitrite in anoxic condition with organic carbon as electron donor to reduce nitrite and can outcompete anammox. There could be some organic matter present in the reactor during start-up, that could result denitrification although the measurement of organic matter was not performed in this study.

Figure 4.16 (left and right) illustrate the stoichiometric ratio of nitrite consumption to ammonium consumption in VA_SBR (left) and NL_SBR (right) on a monthly basis. From month 7 on, both VA_SBR and NL_SBR were operated simultaneously with same SBR setup and cycle time.

There are some months when VA_SBR maintained good reactor performance indicated by the nitrite to ammonium consumption ratio close to 1.32. For instance, in all almost months (month 1 to 4, 6, 7, 8, 9, 12, 13 and 14), there was no evidence that the mean stoichiometric ratio was not equal to 1.32 (p-value > 0.1; Table 4.1), although month 1 showed a very high level of variability. In the months 10, 11 and 13, there is a significant difference in the ratio between experimental mean and 1.32 (p-value < 0.05) in VA_SBR.

NL_SBR showed slightly different pattern in those month than VA_SBR. In months 7, 8, 10, 11, 12 and 14, there was no evidence that the stoichiometric ratio was not 1.32 (p-value > 0.05; Table 4.1) in NL_SBR. Therefore, with 95% confidence, in those months the ratio was observed 1.32.

VA_SBR NL_SBR 5 5 4.5 4.5 4 4 3.5 3.5 3 3 2.5 2.5

NO2:NH4 2

NO2:NH4 2 1.5 1.5 1 1.32 1 0.5 0.5 0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 7 8 9 10 11 12 13 14 Age of reactor (month) Age of reactor (month)

Figure 4.16: Nitrite (NO2) consumption to ammonium (NH4) consumption ratio in VA_SBR (left) and NL_SBR (right) on monthly basis. Error bars represent 95% confidence intervals for monthly data. represents the month when the mean stoichiometric ratio is significantly different from 1.32 (p-value < 0.05). Arrows are used to show the probable upset periods.

In general, there was less variability in the NL_SBR than the VA_SBR because NL_SBR had higher Planctomycetes (suggesting higher anammox population; Figure 4.17 and 4.18). However, in the months 9 and 13, there was a significant difference observed in the stoichiometric ratio (p-value < 0.05). The large error bars and significant difference in the stoichiometric ratio from 1.32 were observed mostly in the months when the upsets occurred due to nitrite overflow (month 13 in NL_SBR) or due to denitrification activity (month 9 in NL_SBR).

Table 4.1: Student t-tests were performed for each common months for both VA_SBR and NL_SBR

Month VA_SBR NL_SBR mean SD p-value mean SD p-value 7 1.33 0.79 0.98 1.83 0.81 0.39 8 1.36 0.56 0.78 0.96 0.69 0.10 9 1.25 0.81 0.75 0.73 0.38 0.004 10 0.67 0.005 3.84e-14 1.39 1.34 0.94 11 2.38 1.31 0.05 1.49 0.87 0.62 12 1.28 0.81 0.89 0.97 0.55 0.06 13 0.94 0.45 0.07 0.75 0.38 0.01 14 1.29 0.76 0.90 0.73 0.67 0.08

4.1.4 Population of Total Bacteria, Planctomycetes and Anammox in SBRs

In this study, molecular analysis with real-time quantitative PCR (qPCR) was performed to observe and quantify anammox population in different time periods in all reactors. The qPCR was performed using specific primers targeting 16S rRNA to determine diversity and abundance of anammox species (Candidatus Brocadia and Candidatus Kuenenia). Ca. Brocadia and Ca. Kuenenia are very commonly found in activated sludge in wastewater treatment plant (Schmid et al., 2005, 2005; Strous et al., 1999b). qPCR was performed targeting 16S rRNA to measure total bacteria, planctomycetes and anammox population (only Ca. Brocadia and Ca. Kuenenia genera).

Planctomycetes Total Bacteria Anammox 1.E+08

1.E+06

1.E+04 DNA

1.E+02

1.E+00

CopyNumber per nggenomic of

361 100 222 277 311 441 Age of Reactor (day)

Figure 4.17: Population of total bacteria, Planctomycetes and anammox bacteria (Ca. Brocadia and Ca. Kuenenia) as log of copy number per ng of genomic DNA in VA_SBR with time. Error bars represent 95% confidence interval plotted based on the cycle time corresponding to 300,000 fluorescence value. The triplicates for that sample did not show same cycle time for the corresponding fluorescence that was responsible for the large error bar at that data point. All other triplicate for the same sample showed same cycle time at the corresponding fluorescence value and all three cycle curves fell on top each other for all samples. Error bars for all others samples are zero.

Planctomycetes Total Bacteria Anammox

1.E+06

1.E+04 DNA

1.E+02

1.E+00

CopyNumber per ngGenomic of

100 212 350 451 Age of Reactor (day) Figure 4.18: Population of total bacteria, Planctomycetes and anammox bacteria (Ca. Brocadia and Ca. Kuenenia) as log of copy number per ng of genomic DNA in NL_SBR with time.

Figure 4.17 and 4.18 illustrate the bacteria populations in VA_SBR and NL_SBR. These figures show that in the beginning of reactor operation (around day 30~50) NL_SBR

5 6 had almost 5 times more total bacteria as VA_SBR (7.4 X10 vs. 3.5X10 copies/ng of genomic DNA). During those time periods, Planctomycetes bacteria in NL_SBR was observed almost 25 times higher than in VA_SBR (1.24X106 vs. 4.9X104 copies/ng of genomic DNA).

From the metagenomics sequencing results, it was observed that Planctomycetes population was 1% and 4.6% of total bacteria population in VA_SBR and NL_SBR, respectively (Appendix Figure A8, Table A3). The samples for genome sequencing were taken around day 350 from both SBRs. From Figure 4.17 and 4.18, similar results were observed around that time, Planctomycetes population was 3 times higher in NL_SBR than in VA_SBR (3.16 X 106 vs. 1.06 X 106 copies/ng of genomic DNA). Since, anammox bacteria belong to Planctomycetes phylum, the ratio of anammox population in VA_SBR to NL_SBR might be assumed as 1:3 around that time period (day 150).

From qPCR results, doubling times for Planctomycetes and anammox bacteria (Ca. Brocadia and Ca. Kuenenia) in VA_SBR and NL_SBR were calculated during the operation time of 222 to 361 for VA_SBR were 39 days and 37 days. Doubling times for Planctomycetes and anammox bacteria in NL_SBR were calculated from day 212 to 350 and were found to be 28.5 days and 26.6 days. The doubling time obtained for Planctomycetes and anammox bacteria are almost same in both reactors suggesting that the growth in Planctomycetes population is similar to the growth rate of all anammox bacteria.

Doubling time of anammox was observed lower in NL_SBR. Under optimal condition, the anammox growth rate was obtained in the range from 3.6 to 11 days (Strous et al., 1998; Tsushima et al., 2007; van der Star et al., 2007). However, longer doubling time (around 30 days) was also reported in the literature, especially in the

67 reactor systems where biomass washout was observed (Fux and Siegrist, 2004). Hence, those study suggested that biomass retention time is important for anammox enrichment.

qPCR results also confirmed that the anammox bacteria (Ca. Brocadia and Ca. Kuenenia) were present in two SBR reactors but higher in NL_SBR than VA_SBR (Figures 4.17 and 4.18). The maximum nitrogen removal obtained from NL_SBR reactor was 0.5 g N/L of sludge -day that was almost two times higher than VA_SBR (0.25 g N/L of sludge - day) (Figure 4.2 and 4.9) during the time period when Planctomycetes population was observed higher in NL_SBR. Since, the qPCR results show that NL_SBR had more Planctomycetes population from the very beginning, the better performance might be attributed to the higher Planctomycetes population thus overall anammox population. When the maximum nitrogen removal was observed in both reactors, the Planctomycetes population was 15 times higher in NL_SBR (on day 138) than VA_SBR (on day 328).

Anammox population was observed to increase from day 0 to day 350 in both SBRs. However, the amount of copy number in each reactor was much less than expected. The reason might be attributed to the targeted anammox species. The qPCR result proved that, there were anammox bacteria in each of the reactors but the quantification was misleading since, all anammox species were not targeted in this study. A decrease (from 1X 102 to 4X101) in targeted anammox population was observed from day 361 to day 441 in VA_SBR. From day 350 to 451, a decrease in targeted anammox population was observed NL_SBR from 6X 103 to 4 X101. This might be attributed to the reactor upset because of substrate shock from high nitrite concentration that was also shown in Figure 4.1 and 4.6.

4.1.5 MUASB Reactor

The VA_SBR and NL_SBR were both suffering from high substrate concentration shock and nitrite accumulation in the reactors. The frequency and extent of nitrite accumulation in VA_SBR was one of the motivations to develop another reactor, MUASB which would be less susceptible to high substrate concentration. Jin et al (2008) observed that SBRs are more vulnerable to substrate shock than the upflow anaerobic sludge blanket reactor (UASB) because of the difference between the operational principle; SBR is a continuously mixed reactor while the UASB is a plug flow type reactor.

After having operational difficulties with SBRs an upflow reactor (MUASB) with carbon nanotube (CNT) membrane filter, kindly provided by Dr. Jassby (UC Riverside) was developed (Figure 3.3 and 3.4; Dudchenko et al., 2014). The CNT membrane was charged and placed in the reactor in such a way so that anammox bacteria could not escape the reactor. During decanting period in SBR, there might be a good amount of anammox biomass loss from the reactor as poor settling condition was sometimes observed. For anammox enrichment, it was observed from SBRs that biomass retention in the reactor is very important leading to the development of MUASB (Dapena-Mora et al., 2004; Ganigué et al., 2008).

Figure 4.19 illustrates that the nitrogen removal efficiency (%) from MUASB gradually increased from 30% to 80% within 80 days from the reactor starting date while the influent substrate (ammonium and nitrite) concentration was gradually increased from 7 mg N/L to 56 mg N/L. After day 80, the substrate concentration was kept around 42 mg N/L with the exception of from day 187 to 203, right after the leachate experiment (section 4.3), during which time the substrate concentration was accidentally increased

- to 150 mg NO2 - N/L (Figure 4.24). During this period of high substrate loading, the total nitrogen removal efficiency was observed to decrease from 86% to 13% (Figure 4.19).

+ - Figure 4.19: Substrate (total NH4 -N and NO2 -N) removal efficiency (%) vs the age of the MUASB reactor (day). Arrows indicate the reactor upsets causing from higher nitrite concentration (above 77 mg N/L), CNT membrane clog on day 169; Inhibition caused by leachate experiment before day 230 (data are not shown here).

From Figure 4.20, it was observed that the maximum nitrogen removal obtained was 1.5 g N/ L of sludge-day, which is almost 5 times higher than VA_SBR (0.25 g N/ L of sludge-day) and 3 times higher than NL_SBR (0.5 g N/ L of sludge-day). The MUASB was inoculated with the anammox sludge from VA_SBR. The results suggest that MUASB provides a better environment for anammox enrichment than the SBRs.

The MUASB also showed faster anammox enrichment compared to the two SBRs used in this study. For instance, it took only 60 days to remove 60% total nitrogen where the VA_SBR took more than 100 days and NL_SBR took more than 230 days to achieve 60% total nitrogen removal (Figure 4.1, 4.7 and 4.19). Although, the MUASB reactor was inoculated with the anammox sludge from VA_SBR, a substantial improvement was observed in anammox activity within a short period of time as mentioned above. The difference in performances was due to the difference in biomass retention times. In MUASB, all anammox biomass was kept inside the MUASB with CNT filter on top of the reactor where the anammox biomass could not be captured in SBR reactors.

+ - Figure 4.20: Substrate (total NH4 -N and NO2 -N) removal rate (mg N/ day) vs the age of MUASB reactor. Arrows indicate the reactor upsets causing from higher nitrite concentration (above 77 mg N/L), CNT membrane clog on day 169; Inhibition caused by leachate experiment before day 230 (data are not shown here).

It should be noted that there were two incidents that caused the MUASB reactor upset. On day 167, the CNT membrane filter was clogged and it was replaced with another new CNT membrane filter. After 10 days, the MUASB recovered partially achieving around 50% total nitrogen removal efficiency. Another reactor upset happened during leachate experiment (from day 210 to day 230). The consequences of leachate experiment will be discussed further in section 4.3.

Figure 4.21: Ammonium removal efficiency (%) vs age of the MUASB reactor (day). Arrows indicate the reactor upsets causing from higher nitrite concentration (above 77 mg N/L), CNT membrane clog on day 169; Inhibition caused by leachate experiment before day 230 (data are not shown here).

Figure 4.22: Nitrite removal efficiency (%) vs vs the age of the MUASB reactor (day). Arrows indicate the reactor upsets causing from higher nitrite concentration (above 77 mg N/L), CNT membrane clog on day 168; Inhibition caused by leachate experiment before day 230 (data are not shown here).

160 140 Influent NH4 Effluent NH4 120 100 80

(mg (mg N/L) 60 40

20 Concentration of Ammonium Ammonium Concentrationof 0 49 61 84 104 120 169 198 256 275 Age of reactor (day) Figure 4.23: Influent and effluent concentrations of ammonium (mg N/L) vs age of the MUASB reactor (day).

180 160 Influent NO2 Effluent NO2 140 120 100 80 60 40 20

Concentration Nitrite of (mg N/L) 0 49 61 84 104 120 169 198 256 275 Age of Reactor (day)

Figure 4.24: Influent and effluent concentrations of nitrite (mg N/L) vs age of the MUASB reactor (day).

Figure 4.23 and 4.24 illustrate the concentrations of substrates ammonium (mg N/L) and nitrite (mg N/L) with the age of MUASB reactor. The maximum ammonium and nitrite concentration was observed to be 141 mg N/L and 160 mg N/L, respectively on day 188 and very less nitrogen removal (less than 20%) was observed at those high

73 concentration level. Although VA_SBR and MUASB were inoculated with same sludge, VA_SBR shower poor performance compared to MUASB when the substrate concentration was observed higher than the usual concentration. VA_SBR showed less than 6% total nitrogen removal efficiency above 40 mg N/L of substrate concentration (Figure 4.1). Those results suggest that MUASB was more robust to substrate shock than VA_SBR as stated by Jin et al (2008).

25 NO3 Production 20 15 10 5 0 -5 49 61 84 104 120 169 198 256 275

-10 NitrateProduction (mg N/L) -15 NO3 Consumption -20 Age of reactor (day)

Figure 4.25: Nitrate production or consumption (mg N/L) vs age of reactor (day) in the NL_SBR reactor.

Figure 4.25 illustrates the nitrate production and consumption with the age of the reactor in the MUASB reactor. Some denitrification activities were observed in the MUASB in different time periods, however the total duration of denitrification period is relatively lower in the MUASB reactor than the SBRs (Figure 4.5, 4.12 and 4.25).

NO2:NH4 2

0 49 61 84 104 120 169 198 256 275 Age of Reactor (day)

Figure 4.26: Nitrite (NO2) consumption to ammonium (NH4) consumption ratio in MUASB reactor on daily basis.

- + Figure 4.27: Nitrite (NO2 ) consumption to ammonium (NH4 ) consumption ratio in MUASB reactor on monthly basis. Represent the months when the mean nitrite to ammonium consumption ratio were significantly different form 1.32 (p-value < 0.05). p- values for all other months are given in Appendix Table A3 for MUASB reactor.

Figures 4.21-4.24 show the ammonia and nitrite consumption patterns that were

- + used to calculate the daily and monthly NO2 :NH4 stoichiometric ratio in the MUASB reactor (Figures 4.26 and 4.27, respectively). The reactor showed that the mean ratio was 2.5, then with time it gradually decreased to 1.5 suggesting a decrease in heterotrophic denitrifying activity and an increase in anammox activity (Figure 4.26 and 4.27). Only in months 2, 7 and 9, the mean ratio was significantly different from 1.32. The average stoichiometric ratio was observed 1.67 ± 0.35 over throughout the operation period of MUASB reactor. The error bars from Figure 4.27 were smaller than the error bars of Figure 4.16, suggesting the ratio was closer to 1.32 in the MUASB than the SBRs. MUASB provides more biomass retention and thus enrich anammox better, eventually it increases anammox activity.

During the upset of MUASB reactor, in month 7, the mean stoichiometric ratio increased to 1.93 from 1.29 with large error bars indicating the effect of reactor upset from CNT clog. Another upset occurred during month 9 when the landfill leachate experiments were conducted and are likely responsible for the inhibition of anammox activity (or the increase of heterotrophic denitrifying activity) suggested by the increase of the ratio. The landfill leachate experiments in MUASB contained relatively high COD and could provide sufficient food for the enrichment of denitrifying bacteria, which results in anammox being outcompeted (Ruscalleda et al., 2008).

MUASB Planctomycetes Total Bacteria Anammox

1.E+06

1.E+04

1.E+02

1.E+00

Copy Number per ng of genomic Copyng per Number DNA genomic of

185 306 Age of Reactor (day)

Figure 4.28 Population of anammox, Planctomycetes and total bacteria as copy number per ng of genomic DNA in MUASB with time. Error bars represent 95% confidence interval plotted based on the cycle time corresponding to 300,000 fluorescence value. The triplicates for that sample did not show same cycle time for the corresponding fluorescence that was responsible for the large error bar in that data point. All other triplicate for the same sample showed same cycle time at the corresponding fluorescence value and all three cycle curves fell on top each other for all samples. Error bars for all others samples are zero.

Figure 4.28 illustrates the total bacteria, Planctomycetes and anammox population in MUASB reactor. The total bacteria population stayed almost same throughout the operation period. However, Planctomycetes population increased over time indicating an increase in anammox population. In this study, only Ca. Brocadia and Kuenenia species of anammox were targeted in the anammox-specific qPCR analyses and they seem to be missing in our DNA templates (Figure 4.28). Since, all anammox genera belong to Planctomyctes phylum, and an increase in Planctomycetes mean the increase in overall anammox population.

From day 49 to day 160, the total nitrogen removal efficiency (33% to 88%) and total nitrogen removal rate (17mg N/L-day to 187mg N/L-day) both showed an increasing trend until the membrane clog incident occurred (Figures 4.21 and 4.22). From day 185 to day 306, although the Planctomycetes population increased, the % of nitrogen removal efficiency and the total nitrogen removal rate, both decreased because of the membrane clog and landfill leachate inhibition incidents. However, it might suggest that, the poor performance was temporary and the leachate inhibition was irreversible because the overall Planctomycetes population did not decrease in those accidents.

The doubling time of Planctomycetes obtained from the MUASB reactor from Figure 4.28 was almost 80 days which was higher than the SBRs. However, the anammox activity was higher in MUASB resulting higher total nitrogen removal (almost 5 times higher than VA_SBR). The reason might be because of the amount of overall bacteria population in the MUASB reactor was less than the two SBRs and during the qPCR experiments the DNA copy number was not normalized with the collected sample volume. The maximum nitrogen removal rates were obtained at different time periods. During those time periods, the Planctomycetes: total bacteria ratio was observed to be 3.5% in VA_SBR, 46% in NL_SBR and 10% in MUASB reactor (Table 4.2).

4.1.6 Summary of Anammox Enrichment

According to the results, MUASB showed better performance than SBRs that might be because of the better biomass retention in the MUASB reactor. The MUASB reactor, containing a CNT membrane filter, provided better biomass retention time than SBRs. For anammox enrichment, biomass retention is very important (Dapena-Mora et al., 2004). Total N-removal rate in MUASB was also observed almost 5 times higher than in VA_SBR, suggesting anammox bacteria were enriched more in the MUASB than in VA_SBR (Table 4.2). Anammox bacteria consume 1.32 times more nitrite than ammonium as their substrates.

Table 4.2: Summary of anammox enrichment in VA_SBR, NL_SBR and MUASB

Reactor VA_SBR NL_SBR MUASB Maximum nitrogen removal (g N/L of sludge - 0.25 0.50 1.5 day) Days needed to achieve 138 310 178 maximum N-removal rate - + NO2 : NH4 0.20 to 4.5 0.05 to 0.27 to 4.33 2.92 Total bacteria (copy number per ng of genomic 6X 106 7X 10 6 2.7X 10 6 DNA) (day 100) (day 300) (day 185) Planctomycetes (copy number per ng of genomic 2.1X 105 3.2X 106 2.7X 105 DNA) (day 100) (day 300) (day 185) Planctomycetes : Total bacteria 3.5% 46% 10%

The anammox process is inhibited by relatively higher concentrations of ammonium and nitrite. Nitrite and ammonium concentration above 100 mg N/L and 700 mg N/L can inhibit the process to a significant extent (Ni et al., 2010; Strous et al., 1999b; Dapena-Mora et al., 2007), respectively. In this study, inhibition was observed several times in different reactors due to nitrite or denitrification activity. The death of other bacteria might increase the organic carbon and create a favorable environment for denitrifying bacteria but hostile environment for anammox (Figure 4.8 and 4.12). In this study, it took 7 to 20 days to recover from the upset conditions. To avoid substrate inhibition (especially nitrite inhibition), the loading rate and concentration of substrate should be kept low but that might result long start-up time.

The doubling time for Planctomycetes and anammox bacteria in the SBRs are higher (around 40 days, Figure 4.17 and 4.18) than literature reported value (11 days; Strous et al., 1998). The ratio of Planctomycetes to total bacteria was higher in NL_SBR

79 than VA_SBR and the activity of anammox was also higher as well (Table 4.2). The maximum nitrogen removed from NL_SBR was almost double than VA_SBR (0.25 g N/L of sludge -day vs. 0.5 g N/L of sludge -day), moreover the Planctomycetes population observed 15 times higher in NL_SBR than VA_SBR during corresponding periods (Figure 4.17 and 4.18).

In addition to the quantification analysis, the macroscopic property of anammox bacteria was also observed during the operation period of anammox reactors. The black- colored sludge, eventually turned into light brown-colored anammox over the course of time, in all three reactors, however, the color was darker than the literature reported color (light reddish orange color). For instance, the diffrence between the color of enriched anammox bacteria in MUASB and the anammox granule from litrearture is given below in Figure 4.29.

Figure 4.29: The color of enriched anammox observed in the MUASB reactor (left), color of anammox granule reported in literature (right; adopted from (Ali et al., 2013)).

4.2. Kinetic Study

Kinetic models for nitrogen removal kinetics for anammox sludge based reactors are an important and popular tool for design, analysis, operation and maintenance of anammox reactors (Ni et al., 2012). Some of the most widely used kinetic models for biological reactors include Monod, first- order substrate removal, Grau-second order and Stover-Kincannon model (Monod, 1949; Bekins et al., 1998; Chen et al., 2013; Grady and Williams, 1975; Grau et al., 1975; Stover and Kincannon, 1982). In this study, first- order substrate removal, Grau-second order and Stover-Kincannon model were used to predict effluent total substrate concentration from influent total substrate concentration. These models have been previously used to predict the performance of anammox-based reactors (Işik and Sponza, 2005; Ni et al., 2012).

For the kinetic experiment, the HRT was varied from 3 hr to 3 days and the concentration of substrates (ammonium and nitrite) were varied from 14 mg/L N to 56 mg/L N. All three models were validated via assessing the linearity between the actual effluent substrate concentration and models’ predicted effluent substrate concentration. The actual data were selected randomly when no anomalies were observed, from day 211 to 370 for VA_SBR and 222 to 370 for NL_SBR.

4.2.1 First-order Substrate Removal Model

The first- order substrate removal model assumes that the substrate is uniformly mixed and the kinetic rate of substrate is first-order inside the reactor. This condition is met if the substrate concentrations are below the half-saturation constant (Ks) value. The value of first order rate constant (K1) was obtained by plotting (Si-Se)/HRT versus Si, as shown in Eq. (18).

Figure 4.30 shows that the rate constants are 0.59 per day and 1.24 per day for VA_SBR and NL_SBR respectively. NL_SBR shows almost twice as much anammox activity as VA_SBR from this model. This statement can be validated with Planctomycetes qPCR results (Figure 4.17 and 4.18) where the Planctomycetes population was observed much higher in NL_SBR (3.16 X 106) than in VA_SBR (1.06 X 106). The Planctomycetes population can be used as a rough estimate of all anammox bacteria since all anammox bacteria belong to Planctomycetes phylum. The rate constants for both reactors fall in the lower end of the literature value (0.44 to 11.64; Table 4.4).

VA_SBR NL_SBR

0.08 0.08 day

- y = 1.237x - 0.0361 y = 0.5947x + 0.0118 day - R² = 0.8316 0.06 R² = 0.7958 0.06

0.04

Se)/HRT Se)/HRT in g N/L -

0.02 Se)/HRT in g N/L

(Si (Si 0 0.02 0.03 0.05 0.07 0.09 0.03 0.05 0.07 0.09 Se in g N/L Se in g N/L Figure 4.30: First-order kinetic model for VA_SBR (left) and NL_SBR (right).

Using Figure 4.30 and Eq. (18), the equations for predicting effluent total nitrogen concentrations of VA_SBR and NL_SBR can be derived and are given in Eq. (26) and (27) respectively.

Si Se = (26) 0.595θH+ 1 Si Se = (27) 1.237θH+ 1

Here, using influent substrate concentration (Si in mg N/L) and hydraulic retention time (θH in days ) the effluent substrate concentration, in mg N/L, can be determined using Eq. (26) and (27). The predicted value of effluent total substrate (ammonia and nitrogen) using these equations will be compared with the actual experimental effluent total substrate value in Figure 4.31.

VA_SBR NL_SBR 180 180 First- order Actual First -order Actual 140 P > 0.05 140 P >0.05

100 100

60 Predicted (mg/L) Se Predicted (mg Se N/L) 20 20 20 40 60 80 100 120 50 70 90 110 130 150 170 Experimental Se (mg N/L) Experimental Se (mg N/L) Figure 4.31: First-order kinetic model validation for VA_SBR (left) and NL_SBR (right).

Figure 4.31 illustrates how the first-order kinetic model prediction fits the actual total effluent nitrogen concentration for both SBRs. The model fits the actual effluent concentration better for VA_SBR than the NL_SBR, although overall the first order model is not a good fit for both SBRs. There is a significant difference observed between the actual effluent concentration and model predicted effluent concentration (p-value > 0.05) for both SBRs.

Bekins et al (1998) stated that first order model is valid when the substrate concentration (S) is much less than half saturation constant (Ks). The half saturation constant for total substrates of anammox is less than 0.14 mg N/L (Table 2.3). But in this study, substrate concentration was above 0.14 mg N/L for both substrates, that has

84 violated first-order model assumption. Therefore, first-order model is not appropriate to use for both VA_SBR and NL_SBR. However, at lower concentration (less than 50 mg N/L), first-order model fits surprisingly better for effluent substrate concentration for both SBRs

4.2.2 Grau Second-order Substrate Removal Model

Grau et al. (1975) developed a linear multicomponent substrate model to predict substrate concentration incorporating second order chemical reaction kinetics and the Monod model. In the Monod model, the effluent substrate concentration is independent of influent substrate concentration.

Using the linearized equation of Grau second- order model, Eq. (20), the second

Si order multicomponent substrate removal constant ((day)= ) for each SBR was found K2X by plotting θH/E vs. θH (Figure 4.32), where HRT (day) = θH and E = substrate removal

Si-Se efficiency (%) = . In this study K2 could not be calculated since the anammox biomass Si concentration was not measured.

VA_SBR NL_SBR 2.5 2.5 2 2

1.5 1.5 HRT/E HRT/E 1 1 0.5 y = 3.507x + 0.1205 0.5 y = 3.1917x + 0.6035 R² = 0.8802 R² = 0.9218 0 0 0.1 0.3 0.5 0.7 0.1 0.3 0.5 0.7 HRT HRT Figure 4.32: Grau second-order kinetic model for VA_SBR (left) and NL_SBR (right).

From Figure 4.32, the Grau second-order (Grau et al., 1975) kinetic constants “a” and “b” were found to be 0.12 day (intercept) and 3.51 (slope), respectively, for the

VA_SBR and 0.60 day and 3.19, respectively, for the NL_SBR. Correlation co-efficients were obtained 0.88 and 0.92 for VA_SBR and NL_SBR, respectively. Using the calculated values for “a” and “b”, the formulas for predicting effluent substrate concentration for VA_SBR and NL_SBR are given in Eqs. (28) and (29), respectively.

θH Se= Si (1- ) (28) 0.12+ 3.51θH

θH Se= Si (1- ) (29) 0.60+ 3.19θH

VA_SBR NL_SBR 180 180 Grau Second order Actual Grau Second order Actual

140 140 P > 0.05 P > 0.05

100 100 Predicted (mg/L) Se 60 60

20 20

Predicted Value, Se (mg/L) 20 40 60 80 100 120 50 70 90 110 130 150 170 Experimental value, Se (mg/L) Experimental Se (mg/L) Figure 4.33: Grau second order kinetic model validation for VA_SBR (left) and NL_SBR (right).

Figure 4.33 illustrates the comparison of actual effluent data with model predicted effluent data. The second-order model (Figure 4.31) shows better fit for the actual data for both VA_SBR and NL_SBR than the first-order model (Figure 4.29). The reason might be attributed to the order of reaction associated with anammox process. The validation results suggest that the reaction inside the SBRs are of second-order not of first-order.

From chemical kinetics viewpoint, both ammonium and nitrite concentrations are crucial and of equal importance for predicting effluent total substrate. Since, the model was originally derived from both Monod model and chemical reaction kinetic model for multicomponent substrate removal, that make the model unique and better than first- order model for our study purpose.

4.2.3 Modified Stover-Kincannon Model for SBRs

Modified Stover-Kincannon (1982) model is very popular for determining the kinetic constant for both SBRs and UASB type reactors and predicting the effluent substrate (total nitrogen) concentration (Amin et al., 2013; Işik and Sponza, 2005; Karapinar Kapdan and Aslan, 2008; Ni et al., 2010). The substrate utilization rate is a function of loading rate for rotating biological contactor (RBC) reactor by monomolecular kinetics in the original Stover-Kincannon model (Yu et al., 1998). The model was later modified to use for other types of reactor as discussed in Section 2.6.4.

In this study, the modified version was used to determine kinetic constants for all reactors. Figure 4.34 shows the graph plotted between the reciprocal of total substrate removal rate (V/Q(Si-Se)) against the reciprocal of nitrogen loading rate (V/(QSi)) where

KB/Umax is the slope and 1/Umax is the intercept using Eq. (22).

From Figure 4.34 and Eq. (22), the saturation constant (KB) and maximum total substrate utilization rate (Umax) were calculated to be 0.80 g N/L-day and 0.27 g N/L-day, respectively, for VA_SBR and 0.18 g N/L-day and 0.087 g N/L-day, respectively, for NL_SBR

(Figure 4.34). Ni et al. (2012) observed much higher KB and Umax for UASB reactor with granular anammox, of 12.1 and 11.4 g N/L-day, respectively (Table 4.4). However, Ni et al. (2012) used highly enriched (93.7%) anammox granules for that study. This might be the cause of the substantial differences in kinetic parameter values between that study

87 and our study as the modified Stover-Kincannon model does not take into account biomass concentrations.

VA_SBR NL_SBR 35 35 y = 2.9906x + 3.7414 y = 2.0272x + 11.509 R² = 0.8799 R² = 0.8931

25 25

Se)

day/g of N of day/g

- V/Q(Si

V/Q(Si 15 15

in in L in in L

5 5 0 2 4 6 8 10 0 2 4 6 8 10 V/QS in L-day/g of Ni V/QS in L-day/g of Ni Figure 4.34: Modified Stover-Kincannon kinetic model for VA_SBR (left) and NL_SBR (right).

KB and Umax were both observed to be higher for the VA_SBR than the NL_SBR. dS ( Higher KB values result in lower substrate removal rates dt), however, higher Umax values result higher substrate removal rate (Eqs. (22) to (24)). Figure 4.35 illustrate that the model provided higher output (effluent total substrate concentration) for NL_SBR than VA_SBR, for the same input (influent total substrate concentration). The results from anammox enrichment also suggest that the nitrogen removal per day was higher in NL_SBR than VA_SBR and maximum nitrogen removal achieved by NL_SBR was higher as well (Figure 4.2 and 4.8).

Introducing the kinetic parameter values into Eq. (22) the effluent total nitrogen (ammonium plus nitrite) concentration can be predicted for VA_SBR and NL_SBR by Eq. (30) and (31) respectively,

0.27Si Se= Si (1- ) (30) 0.80 + (Si/ θH)

0.087Si Se= Si (1- ) (31) 0.18 + (Si/θH)

NL_SBR VA_SBR 180 180 Stover-Kincannon Actual Stover-Kincannon 140 140 P > 0.05 100 100

60 Predicted (mg/L) Se 60 Predicted (mg/L) Predicted Se P > 0.05

20 20 20 40 60 80 100 120 50 70 90 110 130 150 170 Experimental Se (mg/L) Experimental Se (mg/L) Figure 4.35: Modified Stover-Kincannon kinetic model validation for VA_SBR (left) and NL_SBR (right).

Figure 4.35 illustrates the comparison between actual total nitrogen effluent and the model predicted total nitrogen. The model fits relatively better for both SBRs than first-order model (Figure 4.31). Grau second-order model and Stover-Kincannon model predicted almost similar effluent substrate concentration (Figure 4.30 (left) and Figure 4.35 (left)). Işik and Sponza, (2005)performed a simulation between Grau second-order model and Stover-Kincannon model and obtained that if Umax= KB, Grau second-order model can be transferred to Stover-Kincannon model.

4.2.4 Modified Stover-Kincannon Model for MUASB

The Stover-Kincannon model was also applied for the prediction of effluent concentration in MUASB reactor. This kinetic model method is very popular model for UASB, especially for anammox (Işik and Sponza, 2005; Ni et al., 2012). Stover-Kincannon kinetic model was developed for biofilm type of reactors. The UASB reactor type provides closer match to the model assumptions in comparison with other types of reactors. Since, a concentration gradient is observed throughout the UASB and as it works as a plug flow reactor, the diffusion gradient in the biofilm is analogous to the diffusion gradient observed in the UASB.

Figure 4.36 shows the graph plotted between the reciprocal of total substrate removal rate (V/Q(Si-Se)) against the reciprocal of nitrogen loading rate (V/(QSi)) where

KB/Umax is the slope and 1/Umax is the intercept. From Figure 4.36 and Eq. (22) the saturation constant (KB) and maximum total substrate utilization rate (Umax) were obtained 15.86 74 g N/L-day and 9.74 g N/L-day respectively, they both lie well within the literature value range (KB = 8.97 to 27.8 g N/L-day and Umax = 7.89 to 27.4 g N/L-day; Table 4.4) with a correlation coefficient of 0.94. Thus, the Stover-Kincannon fits relatively better for MUASB reactor than SBRs since MUASB provides a diffusion gradient working as plug flow reactor.

The effluent total nitrogen (ammonium and nitrite) concentration can be predicted for MUASB by the following equation, Eq. (32) 9.74Si Se= Si (1- ) (32) 15.86 + (Si/θH)

Using Eq. (32), the effluent substrate (Se) was predicted from actual Se and plotted in Figure 4.37. The model fit is excellent (SEE = 2.08) and there is no statistically significant

90 difference between the actual Se and the predicted Se using the Stove-Kincannon model (p- value= 0.997 > 0.05).

5 y = 1.6284x + 0.1026 4 R² = 0.9444

day/g of N) day/g -

Se) L Se) in -

1 V/Q(Si

0 0 0.5 1 1.5 2 2.5 3 V/Qsi

Figure 4.36: Modified Stover-Kincannon kinetic model for total substrate in MUASB reactor.

Figure 4.37: Stover-Kincannon kinetic model validation for total substrate in MUASB reactor (SEE= 2.08 and p- value >0.05).

Figure 4.37 also shows that Stover-Kincannon model fits better for MUASB than two SBRs (Figure 4.35), it might be because of the tendency of anammox to form attached biomass in the MUASB than in SBR that actually matches with the basic assumption for this model. Although the VA_SBR and MUASB were inoculated with same sludge, MUASB was fit better with this model than VA_SBR. Since, enriched anammox sludge was used to inoculate the MUASB from VA_SBR, that might explain the difference.

4.2.5 Summary of Kinetic Model Parameters

NL_SBR showed better correlation co-efficient for all kinetic models than VA_SBR (Table 4.3). The reason might be because the sludge was more enriched (higher Planctomycetes population) in the NL_SBR compared to the VA_SBR (Figure 4.17 and 4.18). The overall reason behind getting poor correlation co-efficient and model constants for SBRs in comparison with literature value, might be attributed to the mixed community of bacteria population in these reactors where anammox biomass was very low compared to the more enriched anammox biomass present in the literature studies. From metagenomic sequencing results, the percentage of Planctomycetes were obtained only 1% in VA_SBR and 4.6% in Nl_SBR (Appendix Figure A8, Table A3) after almost a year of enrichment in this study whereas in literature, the kinetic study was performed in 97% enriched anammox reactors (Ni et al., 2010).

Table 4.3: Comparison among three kinetic models for two SBRs with correlation co- efficient and standard error of estimate (SEE calculated from Appendix Figure A9-A14)

Model VA_SBR NL_SBR

Correlation SEE* p-value Correlation SEE* p-value

coefficient coefficient

First- Order 0.80 7.60 0.68 0.83 18.72 0.006

Grau second- 0.88 6.72 0.91 0.92 8.33 0.04 order

Stover- 0.88 6.72 0.87 0.89 8.41 0.28 Kincannon

*SEE= standard error of estimate

The correlation co-efficient was obtained relatively lower and the standard error of estimate was obtained relatively higher (Table 4.3) for the first-order substrate removal model of both SBRs suggesting first-order model is not predicting the effluent substrate concentration well. The first order model predicted significantly different effluent substrate concentration than actual (p-value <0.05). However, Grau second-order model and Stover-Kincannon model fit the actual data better.

Table 4.4: Summary of kinetic model constants for SBRs and MUASB

Model Kinetic Units VA_SBR NL_SBR MUASB Literature Constants

-1 ¶ First- Order k1 day 0.59 1.23 N/A 0.44 - 11.64

Grau second- a day 0.12 0.60 N/A 0.094-1.397¶ -- order b 3.51 3.19 0.964- 1.11¶

¶¶ Stover- KB g N/L-day 0.80 0.18 15.86 8.97-27.8 Kincannon

¶¶ Umax g N/L-day 0.27 0.09 9.74 7.89-27.4

¶Reference: Jin and Zheng, 2009a; Ni et al., 2010) ¶¶Reference: (Ni et al., 2012)

Table: 4.4 shows that the kinetic model parameters have a wide range of values depending on type of kinetic model, type of reactor and type of initial seeds used. The table shows that first order constant for the SBRs used in this study is within the range of literature value although the correlation coefficient and the Figure 4.31 suggest that first- order model is not a good fit for the SBRs. Literature showed much higher correlation co- efficient for first- order kinetic model of anammox reactors since they used highly enriched (93.7%) anammox granules (Ni et al., 2012) whereas in this study anammox sludge was used for kinetics. The percentage of anammox cells in comparison with total bacteria cells in a mixed culture system affect the kinetic rate constants.

Model validation results from this study suggest that Grau second- order and Stover- Kincannon, both are better fit for total nitrogen removal from VA_SBR and NL_SBR (Figure 4.41 and 4.42). Ni et al (2012) observed similar trend of kinetic model for anammox UASB rector where they got Stover-Kincannon and Grau second order models were better fit than other kinetic models.

MUASB showed better correlation co-efficient and kinetic parameters of Stover- Kincannon model than two SBRs (Figure 4.38 and 4.39). The reason might be attributed to the model assumption. Stover-Kincannon model was built for bacteria biofilm and MUASB reactor acts more as a biofilm type of reactor than as does the SBR reactor. Moreover, MUASB reactor showed more nitrogen removal efficiency indicating more anammox activity although at the starting time MUASB had same anammox biomass as VA_SBR. Over time MUASB was able to enrich more anammox than SBRs because SBRs were subjected to more substrate shocks than MUASB and in addition, MUASB provided more biomass retention time.

4.3 Anammox Treatment of Landfill Leachate in the MUASB Reactor

4.3.1 Effect of Leachate on Anammox Kinetics in MUASB Reactor

Landfill leachate contains very high ammonium concentrations that can be

- removed efficiently with the anammox process if COD/NO2 -N ratio is maintained close to 1 (Chamchoi et al., 2008; Tang et al., 2010). However, other constituents of the leachate can also affect the anammox activity, in particular, COD and heavy metals (Cecen et al., 2009; Lotti et al., 2012). Thus, before performing any treatment process, it is crucial to see if the reactor is inhibited by the leachate and if so, how dilution is required to eliminate the observed inhibition.

Kinetic models can play an important role to predict the behavior of the reactor with leachate before performing any treatment. To date, there is limited research that has been done to show to model anammox processes in the presence of landfill leachate.

In this study, the Stover-Kincannon model was used to determine the effect of landfill leachate on kinetic model parameters of the MUASB. The leachate was added to

+ the anammox growth media at a 1:10 dilution to lower the NH4 concentration to 53 mg N/L. However, the COD levels still remained relatively high at 130 + 5 mg/L. The Stover- Kincannon model was chosen for kinetic modeling for these sets of experiments due to its excellent performance in previous test with just anammox growth media (section 4.2.4).

Figure 4.38: Stover-Kincannon model with and without leachate for total nitrogen in the MUASB reactor (p-value = 0.01 <0.05).

Figure 4.38 depicts the Stover-Kincannon model for total (ammonium and nitrite) nitrogen for both with and without leachate. Influent ranging from 14 to 84 mg N/L (both ammonium and nitrite) was used for the influent substrate concentration and HRT was maintain constant at 10 hrs. Actual data used for without leachate experiment was taken from day 50 to 250.

A substantial decrease in both kinetic constants was observed from that experiment. KB and Umax were decreased. The maximum substrate utilization rate (Umax) was an order of magnitude lower in presence of leachate (0.88 g N/L-day) than in absence of leachate (9.74 g N/L-day), demonstrating that landfill leachate had a large negative effect on the anammox process (Table 4.5).

Table 4.5: Summary of kinetic model constants of MUASB reactor with and without leachate

Media used Kinetic parameter g N/L-day

+ With Leachate NH4 KB 0.54

Umax 0.88

+ W/O Leachate NH4 KB 15.86

Umax 9.74

There are four types of inhibition models discussed in literature; competitive, noncompetitive (does not exist in real-field), uncompetitive and mixed inhibition (Appendix

Table A6; (Cornish-Bowden, 2013). In the uncompetitive inhibition scenario, both Umax and KB decrease by the same factor and in the mixed inhibition scenario, a combination of competitive and uncompetitive inhibition, Umax and KB both decrease but by different factors. However, in this study Umax decreased by the factor of 11 and KB decreased by the factor of 29 (Table 4.5). Therefore, the inhibition observed here is most likely best described by mixed inhibition kinetics, but it requires further study to draw any definitive conclusions.

4.3.2 Effect of Leachate on Anammox Activity in MUASB Reactor

The Stover-Kincannon study with leachate caused an upset in the MUASB reactor on day 210 (Figure 4.19). The total nitrogen efficiency went down from 40% to 20% during the leachate experiment (Figure 4.39). The reason behind the decrease in anammox performance might be attributed to the potential inhibitory constituents of the leachate.

During the kinetic experiment with leachate, maximum influent COD

- concentration was 185 mg/L and NO2 -N was 84 mg/L. Since, anammox and denitrifying bacteria coexist in the reactor and high COD content and high nitrite concentration is favorable for denitrifying bacteria, they can outcompete anammox for nitrite. Thus, both

97 the COD concentration and the COD to total nitrogen (TN) ratio are important to maintain the reactor safe for anammox enrichment (Sri Shalini and Joseph, 2012). COD concentrations above 300 mg/L and COD:TN ratios above 0.6:1 can inactivate anammox activity (Chamchoi et al., 2008).

Figure 4.39: Effect of landfill leachate experiment (Stover-Kincannon model experiment) - + on the total nitrogen removal efficiency (%). NO2 consumption to NH4 consumption ratio = 1.69± 0.82.

During the leachate kinetic experiments presented here, the maximum COD:TN was 1.45:1, which was much higher the recommended ratio value of 0.6:1. The average nitrite to ammonium consumption ratio was found to be 1.69± 0.82 (Appendix Figure A14), which is higher than the expected stoichiometric ratio of 1.32. This higher stoichiometric ratio might be attributed to some denitrification activity that is fueled by the COD in the leachate.

A leachate pretreatment protocol was performed to remove the contaminant, COD that could potentially inhibit the anammox activity. Miller (2016) performed study on leachate pre-treatment where she showed FeCl3. 6H2O removed up to 45% COD at pH

4 with 3 g/L dosage. After performing leachate pre-treatment (Figure 4.45), the

- concentration of NO2 was 91 mg N/L, COD was 132 mg/L and the COD:TN was 0.8. The nitrite and COD concentrations were favoring denitrifying bacteria but the COD:TN was lower than before but higher than recommended literature values.

Figure 4.40: Landfill leachate pre-treatment experiment before (left) after (right).

While pretreatment removed 40% of COD from landfill leachate, it was not enough to prevent anammox bacteria inhibition, as nitrogen removal rates dropped from

- + 60% down to 20% (Figure 4.41). NO2 consumption to NH4 consumption ratio was observed to be 1.80 ± 0.80, suggesting denitrification activity that might be caused from excess organic carbon available from leachate. The key mechanism of COD in anammox activity is not yet well understood. Guven et al ( 2005) found that anammox can oxidize organic matter to carbon dioxide using nitrite as an electron acceptor. Therefore, high nitrite consumption to ammonium consumption ratio is also possible without denitrifying activity.

Figure 4.41: Effect of landfill leachate pretreatment on the total nitrogen removal - + efficiency (%) in the MUASB reactor. NO2 consumption to NH4 consumption ratio = 1.80 ± 0.80.

In addition to COD, there might be some other inhibitory constituents present in the leachate that caused lower nitrogen removal efficiency. Divalent metals (Zn, Cu, Co, Mo, Ni, Mn), as micronutrients, are very important for anammox metabolism and growth (Hira et al., 2012; Kartal et al., 2011b; Nies, 1999) since they are contained in many enzymes or co-enzymes (Table 3.1). However, studies have shown that higher metal concentrations and longer exposure times can inhibit anammox activity (Table 4.6).

The metals concentration in this study was not determined. However, Bushee, 2016 performed a study on metals in the landfill leachate used in this study. Thus, the 1:10 diluted metal concentrations were able to be estimated. Table 4.6 shows that metals concentrations were of much lower than the reported inhibitory concentrations (Cecen et al., 2009; Kimura and Isaka, 2014; Lotti et al., 2012). Therefore, metals (Cu, Zn, Ni) were not responsible for anammox inhibition.

100

Table 4.6: 50% inhibitory concentration of heavy metals on anammox population

Metals 50% inhibitory Estimated metal Estimated metal

concentration concentration before concentration after

pretreatment pretreatment with (mg/L)

FeCl3. 6H2O (mg/L) §§

(mg/L) §§§

Cu2+ 1.9 - 14.5§ 0.003 ± .001 0.0009 ± .0003 (max 70%

removal)

Zn2+ 3.9 - 7.6§ 0.012 ± .002 0.0012 ± 0.002 (max 90%

removal)

Ni2+ 48.6 § 0.016 ± .001 0.0064 ± 0.0004 (max 60%

removal)

§ Cecen et al., 2009; Kimura and Isaka, 2014; Lotti et al., 2012 §§ Bushee., 2016 §§§ Miller., 2016

101

CHAPTER 5

CONCLUSION

Anammox biomass was enriched from HRSD York River Treatment plant anammox sludge and Dokhaven Treatment plant anammox sludge in two SBRs (VA_SBR and NL_SBR) and an MUASB. The existence of Planctomycetes and anammox were confirmed by qPCR analysis. The maximum total nitrogen removal was obtained 0.25 g/L of sludge- day (VA_SBR), 0.5 g/L of sludge-day (NL_SBR), and 1.5 g/L of sludge-day (MUASB) per settled sludge volume basis after the start-up of 138 days, 310 days and 178 days,

- + respectively. The stoichiometric ratio of NO2 consumption:NH4 consumption was observed to be in a larger range in all reactors during the whole operation period; 0.2 to 4.5 for VA_SBR, 0.05 to 2.92 for NL_SBR and 0.27 to 4.33 for MUASB.

MUASB showed much more nitrogen removal efficiency and anammox activity than the two SBRs. Interestingly, the qPCR results did not indicate high levels of anammox bacteria in those reactors. It might be because the primers used for qPCR targetted only Candidatus Kuenenia and Brocadia species and, those species might be absent in the reactors. However, qPCR quanitified Planctomycetes very well, that grew over time, suggesting that other anammox species might be present and, also were enriched over time. MUASB showed more anammox activity than SBRs providing more biomass retention time suggesting MUASB is a better method for anammox enrichemnt from anammox sludge.

From kinetic model studies, it can be concluded that, the Stover-Kincannon model and Grau second-order model both fit the experimental data (effluent substrate concentration) relatively better compared to the first- order model. Based on the fit to

102 experimental data, the performance level of the models can be compared as Stover- Kincannon= Grau scond-order > first-order model.

Stover-Kincannon model paremeters were also determined for MUASB reactor with and without landfill leachate in the influent. That study suggested that both Umax and KB were decresed due to the inhibition from leachate. The inhibition type might be uncompetitive or mixed inhibition with COD being the most likely inhibitor. Flocculation with FeCl3. 6H2O to remove COD from leacahte did not resolve the inhibition problem since it removed only 40% of COD. Further pretreatment is required to remove a greater percentage of COD and, thus to find the actual inhibitor in the leachate.

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APPENDIX

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Table A1: Media recipe for anammox enrichment in SBRs

Component Concentration in Media

(NH4)Cl 16 mM

NaHCO3 12 mM

NaNO2 16 mM

CaCl2 ∙ 2H2O 4 mM

KH2PO4 0.4 mM

MgSO4 ∙ 7H2O 2 mM

KNO3 2 mM

FeSO4 ∙ 7H2O 0.080 mM

EDTA 0.160 mM

Trace Metal Solution* 2ml/L of media

*Trace Metal Solution Recipe (for 1L volume)

ZnSO4 ∙ 7H2O 546mg

CoCl2 ∙ 6H2O 309 mg

MnSO4 ∙ H2O 1.065 g

CuCl2 ∙ 2H2O 222 mg

Na2MoO4 ∙ 2H2O 266 mg

NiSO4 ∙ 6H2O 368 mg

K2SeO4 155 mg

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H3BO4 18 mg

EDTA 18.76 g

Ion Chromatography Standard Curves

4 y = 0.3669x

Concentration(mM) 2

0 0.000 5.000 10.000 15.000 20.000 25.000 Peak Height

Figure A1: Ammonium standard curve. Error bars represent 95% confidence interval.

9 8 7 6 5 4 y = 4E-05x2 + 0.0119x 3 R² = 0.9973

Concentration(mM) 2 1 0 0 50 100 150 200 250 300 350 Peak Height

Figure A2: Nitrite standard curve. Error bars represent 95% confidence interval.

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2.5

1.5

1 y = 0.0127x

Concentration(mM) 0.5 R² = 0.9898

0 0 20 40 60 80 100 120 140 160 180 Peak Height

Figure A3: Nitrate standard curve for IC. Error bars represent 95% confidence interval.

COD Standard Curve Used for Landfill Leachate Treatment

120

100

60 COD COD (mg/L) 40 y = 267.89x + 2.1611 R² = 0.9851 20

0 -0.05 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 Absorbance

Figure A4: COD standard curve used for landfill leachate pretreatment with FeCl3. 6H2O

120 qPCR Study: DNA Quantification

Standard for Total Bacteria 30 y = -3.123x + 39.021 R² = 0.9953 25 20 15

Cycle Time Cycle Time 10 5 0 0 1 2 3 4 5 6 7 8 9 10 log (Copy Number)

Figure A5: Standard curve for total bacteria quantification. Error bars represent 95% confidence interval plotted based on the cycle time corresponding to 300,000 fluorescence value. The triplicates for that sample did not show same cycle time for the corresponding fluorescence that was responsible for the large error bar at that data point. All other triplicate for the same sample showed same cycle time at the corresponding fluorescence value and all three cycle curves fell on top each other for all samples. Error bars for all others samples are zero.

Standard for Planctomycetes 25

15 y = -3.3x + 39.935

10 R² = 0.9945 Cycle Cycle Time 5

0 0 1 2 3 4 5 6 7 8 9 10 log (Copy Number)

Figure A6: Standard curve Planctomycetes quantification. All triplicates for the same standard sample showed same cycle time at the corresponding fluorescence value and all

121 three cycle curves fell on top each other for all samples. Thus, the error bars for all samples are zero. Standard for Anammox 25 y = -3.1429x + 39.434 R² = 0.9821 20

10 Cycle Cycle Time 5

0 0 2 4 6 8 10 12 log (Copy number)

Figure A7: Standard curve for anammox quantification. All triplicates for the same standard sample showed same cycle time at the corresponding fluorescence value and all three cycle curves fell on top each other for all samples. Thus, the error bars for all samples are zero.

Table A2: Mean, standard deviation and p-value calculated for Nitrite consumption to ammonium consumption ratio in MUASB reactor

Month Mean SD Error Bar P value (95% CI)

2 2.20 0.93 0.68 0.04

3 2.00 1.04 0.51 0.17

4 1.78 0.78 0.38 0.09

5 1.16 0.18 0.18 0.07

6 1.33 0.56 0.36 0.96

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7 1.93 1.02 0.67 0.04

8 0.17 0.11 1.08 0.16 9 1.21 0.03 2.16 1.64 10 0.48 0.64 1.43 0.62

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Classifed Reads - VA_SBR inside / ND_SBR outside Acidobacteria Acidobacteriia Actinobacteria Actinobacteria Corynebacteriales Mycobacteriaceae Mycobacterium Mycobacterium sp Chlorobi Chloroflexi Anaerolineae Anaerolineales Chloroflexi Caldilineae Caldilineales Caldilineaceae Caldilinea Caldilinea sp Chloroflexi Caldilineae Caldilineales Chloroflexi Firmicutes Clostridia Clostridiales Clostridiaceae Clostridium Clostridium sp Nitrospirae Nitrospira Nitrospirales Nitrospiraceae Nitrospira Nitrospira sp Planctomycetes Planctomycetia Planctomycetales Proteobacteria Alphaproteobacteria Caulobacterales Caulobacteraceae Brevundimonas Brevundimonas sp Proteobacteria Alphaproteobacteria Rhizobiales Hyphomicrobiaceae Hyphomicrobium Hyphomicrobium sp Proteobacteria Alphaproteobacteria Rhizobiales Hyphomicrobiaceae Rhodoplanes Rhodoplanes sp Proteobacteria Alphaproteobacteria Rhizobiales Methylocystaceae Methylosinus Methylosinus sp Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Rhodobacter Rhodobacter sp Proteobacteria Alphaproteobacteria Sphingomonadales Sphingomonadaceae Sphingomonas Sphingomonas sp Proteobacteria Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia Burkholderia sp Proteobacteria Betaproteobacteria Burkholderiales Comamonadaceae Diaphorobacter Diaphorobacter nitroreducens Proteobacteria Betaproteobacteria Burkholderiales Comamonadaceae Hydrogenophaga Hydrogenophaga sp Proteobacteria Betaproteobacteria Burkholderiales Proteobacteria Betaproteobacteria Hydrogenophilales Hydrogenophilaceae Thiobacillus Thiobacillus sp Proteobacteria Betaproteobacteria Nitrosomonadales Nitrosomonadaceae Nitrosomonas Nitrosomonas sp Proteobacteria Betaproteobacteria Nitrosomonadales Proteobacteria Betaproteobacteria Rhodocyclales Rhodocyclaceae Denitratisoma Denitratisoma oestradiolicum Proteobacteria Betaproteobacteria Rhodocyclales Proteobacteria Betaproteobacteria Proteobacteria Deltaproteobacteria Desulfuromonadales Geobacteraceae Proteobacteria Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas Pseudomonas sp Proteobacteria Gammaproteobacteria Xanthomonadales Xanthomonadaceae Pseudoxanthomonas Pseudoxanthomonas sp Proteobacteria Spirochaetes Spirochaetia Leptospiraceae Leptonema Leptonema illini Spirochaetes Spirochaetia Leptospiraceae Leptonema Leptonema sp

Figure A8: Map of metagenomics sequencing read for all identified and unidentified bacteria from VA_SBR and NL_SBR (Courtesy: Rich Hillard)

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Table A3: Relative abundance of different types of bacteria from metagenomics sequencing result (samples taken from VA_SBR and NL_SBR) (Courtesy: Rich Hillard).

VA_SBR- NL_SBR- Phylum Class Order Family Genus MS28F MS28F Acidobacteria Acidobacteriia 4 0 Actinobacteria Actinobacteria Corynebacteriales Mycobacteriaceae Mycobacterium 5 4 Chlorobi 258 110 Chloroflexi Anaerolineae Anaerolineales 27 74 Chloroflexi Caldilineae Caldilineales Caldilineaceae Caldilinea 51 55 Chloroflexi Caldilineae Caldilineales 371 78 Chloroflexi 6 4 Firmicutes Clostridia Clostridiales Clostridiaceae Clostridium 4 3 Nitrospirae Nitrospira Nitrospirales Nitrospiraceae Nitrospira 82 51 Planctomycetes Planctomycetia Planctomycetales 133 572 Proteobacteria Alphaproteobacteria Caulobacterales Caulobacteraceae Brevundimonas 43 0 Proteobacteria Alphaproteobacteria Rhizobiales Hyphomicrobiaceae Hyphomicrobium 7 2 Proteobacteria Alphaproteobacteria Rhizobiales Hyphomicrobiaceae Rhodoplanes 0 2 Proteobacteria Alphaproteobacteria Rhizobiales Methylocystaceae Methylosinus 11 2 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Rhodobacter 4 3 Proteobacteria Alphaproteobacteria Sphingomonadales Sphingomonadaceae Sphingomonas 2 0 Proteobacteria Betaproteobacteria Burkholderiales Burkholderiaceae Burkholderia 34 36 Proteobacteria Betaproteobacteria Burkholderiales Comamonadaceae Diaphorobacter 16 19 Proteobacteria Betaproteobacteria Burkholderiales Comamonadaceae Hydrogenophaga 7 4 Proteobacteria Betaproteobacteria Burkholderiales 53 73

125

Proteobacteria Betaproteobacteria Hydrogenophilales Hydrogenophilaceae Thiobacillus 22 21 Proteobacteria Betaproteobacteria Nitrosomonadales Nitrosomonadaceae Nitrosomonas 46 177 Proteobacteria Betaproteobacteria Nitrosomonadales 2 0 Proteobacteria Betaproteobacteria Rhodocyclales Rhodocyclaceae Denitratisoma 213 297 Proteobacteria Betaproteobacteria Rhodocyclales 29 10 Proteobacteria Betaproteobacteria 52 11 Proteobacteria Deltaproteobacteria Desulfuromonadales Geobacteraceae 15 10 Proteobacteria Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas 25 100 Proteobacteria Gammaproteobacteria Xanthomonadales Xanthomonadaceae Pseudoxanthomonas 13 13 Proteobacteria 5 0 Spirochaetes Spirochaetia Leptospiraceae Leptonema 7 19 Spirochaetes Spirochaetia Leptospiraceae Leptonema 4 1 Unclassified 11250 10437 No Hit 282 296

126

Kinetic Study: Standard Error of Estimate Calculation

170 VA_SBR

First- order Actual Linear (Actual) 120

N/L) 70

20 TotalEffluent Substrate, Se (mg 20 40 60 80 100 120 140 160 Total Influent Substrate, Se (mg N/L)

Figure A9: Total effluent substrate predicted from first- order model vs. total influent substrate in VA_SBR.

140 VA_SBR 120 Grau Second order Actual 100

N/L) 60

TotalEffluent Substrate, Se (mg 20 30 40 50 60 70 80 90 100 110 120 Total Influent Substrate, Se (mg N/L)

Figure A10: Total effluent substrate predicted from Grau second-order model vs. total influent substrate in VA_SBR.

127

VA_SBR 140 Stover-Kincannon Actual 120

100

20 30 40 50 60 70 80 90 100 110 120 Total Effluent Effluent Total N/L) Se Substrate, (mg Total Influent Substrate, Se (mg N/L)

Figure A11: Total effluent substrate predicted from Stover-Kincannon model vs. total influent substrate in VA_SBR. NL_SBR 170 First -order Actual 150

130

110

TotalEffluent Substrate, Se N/L) (mg 50 70 90 110 130 150 170 190 Total Influent Substrate, Se (mg N/L)

Figure A12: Total effluent substrate predicted from first- order model vs. total influent substrate in NL_SBR.

128

NL_SBR 170 Grau Second order Actual 150

130

110

TotalEffluent Substrate, Se N/L) (mg 50 70 90 110 130 150 170 190 Total Influent Substrate, Se (mg N/L)

Figure A13: Total effluent substrate predicted from Grau second-order model vs. total influent substrate in NL_SBR. NL_SBR 170

150 Stover -Kincannon Actual

130

110

30 TotalEffluent Substrate, Se N/L) (mg 50 70 90 110 130 150 170 190 Total Influent Substrate, Se (mg N/L)

Figure A14: Total effluent substrate predicted from Stover-Kincannon model vs. total influent substrate in NL_SBR.

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Table A4: Statistical parameters for nitrite consumption to ammonium consumption ratio of VA_SBR

Month VA_SBR NL_SBR

mean SD p-value mean SD p-value

1 2.64 1.65 0.15 - - -

2 1.31 0.44 0.94 - - -

3 1.52 0.56 0.60 - - -

4 2.17 1.37 0.12 - - -

5 3.03 1.20 0.02 - - -

6 0.77 0.38 0.06 - - -

Table A5: Types of Inhibition, adopted from (Cornish-Bowden, 2013)

app app / app app Type of Inhibition V V Km Km

Competitive V V/ Km Km(1+ i/Kic)

1+i/Kic

Mixed V V/ Km Km(1+ i/Kic)

1+i/Kiu 1+i/Kic 1+i/Kiu

Noncompetitive V V/ Km Km

1+i/Kiu 1+i/Kic uncompetitive V 푉 Km

1+i/Kiu Km 1+i/Kiu

Here, V= substrate utitization rate, K = half saturation constant.

130

Leachate Experiment in MUASB Before and After Pretreatment

Leachate Experiment : MUASB 3.5 3 W/O pretreatment 2.5 2

1.5 NO2:NH4 1 0.5 0 200 210 220 230 240 250 260 270 280 290 Age of reactor (day)

Figure A15: Leachate experiment in MUASB before and after pretreatment.