Applied Science, Faculty of
Engineering, School of (Okanagan)
DSpace
UBCO
Cimon, Caroline
Master of Applied Science - MASc
University of British Columbia
Methane production is limited during anaerobic digestion (AD) due to complex molecular structure of organic waste and inhibition of archaea by by-products generated from mineralization of organic matter. In British Columbia, biochar and wood ash are waste products of bioenergy produced from forestry residues. Recent studies have found that addition of biochar to AD increases methane production through direct interspecies electron transfer and biofilm formation, attenuation of inhibition and buffering effect. The objective of this study was to compare the effects of local biochar and wood ash in granular (0.85-4.75 mm) and powdered (< 0.075 mm) form on the biochemical methane production (BMP) of AD of municipal sludge from the Lulu Island wastewater treatment plant (WWTP) in Vancouver, British Columbia (Canada) in batch bioassays. Powdered biochar at dosage of 0.8-3.7 g/g-volatile solids (VS)-substrate achieved the highest improvement in rate of methane production with 192-461% increase from controls, in the first 16 days. This increase was followed by an early stationary methane production phase and a reduction of total methane yield ranging from 9 ± 4% at the lowest dosage to 25 ± 1% at the highest. Results indicated that the early plateau could be caused by adsorption of volatile fatty acids (VFAs) by the biochar. There was generally no significant difference in total methane yield from granular biochar at dosages up to 2.2 g/g-VS-substrate, however, at 3.7 g/g-VS-substrate there was a 16 ± 3% reduction. Methane production rates from wood ash (under the propriety name of ZMM® T-Carbon) amended assays were either not significantly different from controls except at a granular dosage of 2.2 g/g-VS-substrate, where production rates were better than controls. Thus, ZMM® T-Carbon may contribute essential nutrients and be beneficial only under high organic loading rate. Granular ZMM® T-Carbon was effective at reducing ammonia nitrogen by up to 14%. Evidence from BMP colonization test and scanning electron micrograph images demonstrated that syntrophic bacteria and methanogenic archaea colonized the surface of the granular char media. Future research should investigate the VFA adsorption capacity of various biochar types.
EFFECT OF BIOCHAR AND WOOD ASH AMENDMENT ON BIOCHEMICAL METHANE PRODUCTION OF WASTEWATER SLUDGE FROM A TEMPERATURE PHASE ANAEROBIC DIGESTION PROCESS by Caroline Cimon B.Eng., McGill University, 2013 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF APPLIED SCIENCE in THE COLLEGE OF GRADUATE STUDIES (Civil Engineering) THE UNIVERSITY OF BRITISH COLUMBIA (Okanagan) February 2020 © Caroline Cimon, 2020 ii The following individuals certify that they have read, and recommend to the College of Graduate Studies for acceptance, a thesis/dissertation entitled: Effect of biochar and wood ash amendment on biochemical methane production of wastewater sludge from a temperature phase anaerobic digestion process submitted by Ms. Caroline Cimon in partial fulfillment of the requirements of the degree of Master of Applied Science. Dr. Cigdem Eskicioglu Supervisor Dr. Sumi Siddiqua Supervisory Committee Member Dr. Nicolas Peleato Supervisory Committee Member Dr. Jian Liu University Examiner iii Abstract Methane production is limited during anaerobic digestion (AD) due to complex molecular structure of organic waste and inhibition of archaea by by-products generated from mineralization of organic matter. In British Columbia, biochar and wood ash are waste products of bioenergy produced from forestry residues. Recent studies have found that addition of biochar to AD increases methane production through direct interspecies electron transfer and biofilm formation, attenuation of inhibition and buffering effect. The objective of this study was to compare the effects of local biochar and wood ash in granular (0.85-4.75 mm) and powdered (< 0.075 mm) form on the biochemical methane production (BMP) of AD of municipal sludge from the Lulu Island wastewater treatment plant (WWTP) in Vancouver, British Columbia (Canada) in batch bioassays. Powdered biochar at dosage of 0.8-3.7 g/g-volatile solids (VS)substrate achieved the highest improvement in rate of methane production with 192-461% increase from controls, in the first 16 days. This increase was followed by an early stationary methane production phase and a reduction of total methane yield ranging from 9 ± 4% at the lowest dosage to 25 ± 1% at the highest. Results indicated that the early plateau could be caused by adsorption of volatile fatty acids (VFAs) by the biochar. There was generally no significant difference in total methane yield from granular biochar at dosages up to 2.2 g/g-VSsubstrate, however, at 3.7 g/g-VSsubstrate there was a 16 ± 3% reduction. Methane production rates from wood ash (under the propriety name of ZMM® T-Carbon) amended assays were either not significantly different from controls except at a granular dosage of 2.2 g/g-VSsubstrate, where production rates were better than controls. Thus, ZMM® T-Carbon may contribute essential nutrients and be beneficial only under high organic loading rate. Granular ZMM® T-Carbon was effective at reducing ammonia nitrogen by up to 14%. Evidence from BMP colonization test and scanning electron micrograph images demonstrated that syntrophic bacteria and methanogenic archaea colonized the surface of the granular char media. Future research should investigate the VFA adsorption capacity of various biochar types. iv Lay Summary In Canada, sludge processing accounts for 50% of the cost of operating wastewater treatment plants. Conventional anaerobic digestion (AD) is a biochemical process that reduces the volume of sludge and produces consumable energy in the form of methane. However, it requires a long time (> 20 days). Addition of biochar could increase diversity and retention of microorganisms in AD while increasing methane production rate and, therefore, reduce operation and capital costs. This study compares biochar with a lower priced similar material, wood ash, the findings show that both materials can have positive effects on AD efficacy. Adsorption of volatile fatty acids by biochar is a factor that was considered for the first time in this research. Studies on biochar and its potential adverse effects to AD are important to assist decision makers in choosing the right type of media to enrich microbial cultures and enhance methane production rate. v Preface Part of this work was presented at the Value of Biogas 2019 Conference in Vancouver (January 15-16, 2019). Chapters 3 and 4 (excluding section 4.3.4) of this thesis has been published. Cimon, C., Kadota, P. and Eskicioglu C. (2020) Effect of biochar and wood ash amendment on biochemical methane production of wastewater sludge from a temperature phase anaerobic digestion process. Bioresource Technology. 297:122440. An abstract was submitted to the 8th International Conference on Engineering for Waste and Biomass Valorisation, July 13-16, 2020 in Guelph, Ontario. The submitted abstract contains the information from Section 4.3.4 on biofilm formation and is entitled “A study of biochar and wood ash amendment for bioaugmentation of syntrophic bacteria and methanogenic archaea”. This research program was designed by Dr. Cigdem Eskicioglu in collaboration with Metro Vancouver. Mr. Paul Kadota with Metro Vancouver contributed to the work by providing feedback and recommendations as well as reviewing the manuscript and conference abstracts. Ms. Caroline Cimon designed the laboratory experiments, collected and analyzed data and performed the writing and preparation of the above-mentioned manuscript and conference abstracts and presentations. The supervisor of this research, Dr. Cigdem Eskicioglu, oversaw all aspects of the laboratory experiments, data analysis and presentation of the work. Mr. Ravichandra C. Patil (a visiting M.Sc. student from IIT Guwahati, India) and Ms. Shiva Khoei (Ph.D. student at Bioreactor Technology Group) contributed to part of the data collection. A portion of the experimental design was built upon the work of Ms. Bita Nazyab (a previous M.A.Sc. student at Bioreactor Technology Group). This work has been carried out under the sponsorships of the Natural Science and Engineering Council of Canada (NSERC) Collaborative Research and Development Grant (CRDP J 530065-18). vi Table of Contents Abstract .................................................................................................................................... iii Lay Summary ........................................................................................................................... iv Preface ....................................................................................................................................... v Table of Contents ..................................................................................................................... vi List of Tables ............................................................................................................................ x List of Figures ........................................................................................................................ xiii List of Abbreviations ............................................................................................................ xvii Acknowledgements ............................................................................................................... xix Dedication ............................................................................................................................... xx Chapter 1: Introduction ............................................................................................................1 Background ...............................................................................................................1 Motivation for Research .............................................................................................4 Lulu Island Wastewater Treatment Plant ...................................................................5 1.3.1 Upgrading AD with Enhancement Technologies ..................................................6 Objective ...................................................................................................................8 Chapter 2: Literature Review .................................................................................................10 2.1.1 Wastewater Treatment .......................................................................................10 2.1.1.1 Preliminary and Primary Treatment Process ..............................................11 2.1.1.2 Secondary Treatment Process ...................................................................12 2.1.1.2.1 Nitrogen Removal .................................................................................13 2.1.1.2.2 Phosphorus Removal ...........................................................................15 2.1.1.2.3 Suspended Growth Bioreactors ............................................................16 2.1.1.2.4 Attached Growth Bioreactors ................................................................17 2.1.1.2.5 Hybrid Bioreactors ................................................................................19 2.1.1.3 Tertiary Treatment Process ........................................................................21 vii 2.1.1.4 Sanitation Classification of Biosolids and Compost ....................................23 2.1.1.5 Composting ................................................................................................24 2.1.1.6 Incineration and Landfilling .........................................................................25 2.1.2 Digestion ............................................................................................................26 2.1.2.1 Microbiology and Biochemistry of Anaerobic Digestion ..............................28 2.1.2.2 Operational Parameters .............................................................................29 2.1.2.3 Biochemical Methane Potential Assay ........................................................34 2.1.2.4 Interspecies Electron Transfer ....................................................................35 2.1.2.5 Two-Phase Anaerobic Digestion ................................................................38 2.1.2.5.1 Temperature Phase Anaerobic Digestion .............................................40 2.1.3 Conductive Material ...........................................................................................43 2.1.3.1 Magnetite ...................................................................................................44 2.1.3.2 Graphite and Carbon Fiber Material ...........................................................45 2.1.3.3 Activated Carbon ........................................................................................47 2.1.3.4 Biochar .......................................................................................................51 2.1.3.4.1 Production of Biochar ...........................................................................51 2.1.3.4.2 Physicochemical Properties of Biochar .................................................53 2.1.3.4.3 Biochar as an Anaerobic Digestion Amendment ...................................55 2.1.3.4.4 Biochar as a Soil Amendment...............................................................56 2.1.3.4.5 Effect on Greenhouse Gas Emissions ..................................................57 2.1.4 Wood Ash ..........................................................................................................57 Chapter 3: Materials and Methods.........................................................................................60 Experimental Setup .................................................................................................60 3.1.1 Mixed Sludge .....................................................................................................62 3.1.2 Substrate ...........................................................................................................63 3.1.3 Inoculum ............................................................................................................64 viii Char Material ...........................................................................................................64 Biochemical Methane Potential Assays ...................................................................66 Analytical Testing.....................................................................................................68 3.4.1 Chemical Oxygen Demand ................................................................................68 3.4.2 Total Solids and Volatile Solids ..........................................................................68 3.4.3 Gas Volume and Composition............................................................................69 3.4.4 pH and Alkalinity ................................................................................................70 3.4.5 Volatile Fatty Acids ............................................................................................71 3.4.6 Zeta Potential and Electrical Conductivity ..........................................................72 3.4.7 Ammonia Nitrogen .............................................................................................72 3.4.8 Scanning Electron Microscope Imaging .............................................................73 3.4.9 Particle Size Analysis .........................................................................................74 Chapter 4: Results and Discussion........................................................................................75 Properties of Influent and Effluent from the TPAD System .......................................75 Char Characterization ..............................................................................................76 Performance of BMP Assays Amended with Biochar and ZMM® T-Carbon .............80 4.3.1 Phase 1 .............................................................................................................82 4.3.1.1 Size of Char ...............................................................................................82 4.3.1.2 Dosage of Char ..........................................................................................84 4.3.1.3 Zeta Potential and Electrical Conductivity ...................................................86 4.3.1.4 Effect of Sludge to Inoculum Ratio on Methane Production ........................87 4.3.1.5 Positive Controls ........................................................................................89 4.3.2 Phase 2 .............................................................................................................90 4.3.2.1 Buffering Capacity of Biochar and ZMM® T-Carbon....................................90 4.3.2.2 Ammonia Nitrogen......................................................................................94 ix 4.3.3 Phase 3 .............................................................................................................96 4.3.3.1 Methane Production from Char ..................................................................96 4.3.3.2 Salt Toxicity ................................................................................................97 4.3.3.3 Type of Inhibition ........................................................................................98 4.3.3.4 Adsorption of Volatile Fatty Acids ...............................................................99 4.3.4 Phase 4 ........................................................................................................... 100 4.3.4.1 Biofilm Formation ..................................................................................... 100 Chapter 5: Conclusion ......................................................................................................... 108 Summary of Findings ............................................................................................. 108 Strength and Limitations of Research .................................................................... 110 Potential Applications of Research Findings .......................................................... 111 Future Work Directions .......................................................................................... 112 References ............................................................................................................................ 113 APPENDICES......................................................................................................................... 124 Composition of BMP Assays ......................................................... 124 Statistical Analysis ........................................................................ 129 Calibration Curves for Laboratory Analyses .................................. 143 Cumulative Methane Production Graphs....................................... 145 Total Volatile Fatty Acid Graphs .................................................... 149 Summary of Results for Laboratory Analyses at the End of BMP Assays ............................................................................................................. 152 pH Variation Graphs for BMP Assays ........................................... 157 Characterisation of Inoculum and Substrate Sludge Added to BMP Assays ............................................................................................................. 161 x List of Tables Table 1.1: Effluent standards for hazardous waste facilities ........................................................3 Table 4.1: Properties of mixed sludge, substrate and inoculum sludge for BMP assays ............75 Table 4.2: Parameters of SoilMatrix biochar and ZMM® T-Carbon ............................................77 Table 4.3: Elemental composition of SoilMatrix biochar and ZMM® T-Carbon ...........................77 Table 4.4: Summary BMP results for SoilMatrix biochar amended assays ................................80 Table 4.5: Summary of BMP results for ZMM® T-Carbon amended assays ..............................81 Table 4.6: Results of analyses of the liquid phase of second-generation BMP assays ............ 107 Table A-1: BMP assay composition for each BMP assay treatmenta ....................................... 125 Table B-1: Example of statistical analysis using the two sample Student’s t-testa.................... 129 Table B-2: Statistical analysis of cumulative methane production assays with powdered biochar (μ2) and controls (μ1) using the two sample Student’s t-test for B1 at SIR = 2.2 g-VS/g-VS ............................................................................................. 130 Table B-3: Statistical analysis of cumulative methane production assays with powdered biochar (μ2) and controls (μ1) using the two sample Student’s t-test for B1 at SIR = 3.2 g-VS/g-VS ............................................................................................. 131 Table B-4: Statistical analysis comparing cumulative methane production assays with powdered biochar (μ2) and controls (μ1) using the two sample Student’s t-test for B1 at SIR = 4.4 g-VS/g-VS ............................................................................... 132 Table B-5: Statistical analysis comparing cumulative methane production assays with powdered ZMM® T-Carbon (μ2) and controls (μ1) using the two sample Student’s t-test for B2 at SIR = 2.2 g-VS/g-VS ...................................................... 133 Table B-6: Statistical analysis comparing cumulative methane production assays with powdered ZMM® T-Carbon (μ2) and controls (μ1) using the two sample Student’s t-test for B2 at SIR = 3.2 g-VS/g-VS ...................................................... 134 xi Table B-7: Statistical analysis comparing cumulative methane production assays with powdered ZMM® T-Carbon (μ2) and controls (μ1) using the two sample Student’s t-test for B2 at SIR = 4.4 g-VS/g-VS ...................................................... 135 Table B-8: Statistical analysis comparing cumulative methane production assays with granular biochar (μ2) and controls (μ1) using the two sample Student’s t-test for B3-A at SIR = 4.4 g-VS/g-VS ................................................................................ 136 Table B-9: Statistical analysis comparing cumulative methane production assays with granular char (μ2) and controls (μ1) with added buffer using the two sample Student’s t-test for B4 at SIR = 4.4 g-VS/g-VS ...................................................... 137 Table B-10: Statistical analysis comparing cumulative methane production assays with granular char (μ2) and controls (μ1) without added buffer using the two sample Student’s t-test for B4 at SIR = 4.4 g-VS/g-VS ...................................................... 138 Table B-11: Statistical analysis comparing cumulative methane production assays with char (μ2) and controls (μ1) using the two sample Student’s t-test for B5 at SIR = 4.4 g-VS/g-VS ............................................................................................................. 139 Table B-12: Statistical analysis comparing cumulative methane production assays using the two sample Student’s t-test for B5 ......................................................................... 140 Table B-13: Statistical analysis comparing cumulative methane production assays using the two sample Student’s t-test for B6 at SIR = 4.4 g-VS/g-VS ................................... 141 Table B-14: Statistical analysis comparing cumulative methane production assays with Granular ZMM® T-Carbon (μ2) and controls (μ1) using the two sample Student’s t-test for B7 at SIR = 4.4 g-VS/g-VS ...................................................................... 142 Table F-1: Properties of BMP assay digestate on final day of B1 ............................................ 152 Table F-2: Properties of BMP assays’ digestate on final day of B2 .......................................... 153 Table F-3: Properties of BMP assays’ digestate on final day of B4 .......................................... 154 xii Table F-4: Properties of BMP assays’ digestate on final day of B5 .......................................... 155 Table F-5: Properties of BMP assays’ digestate on final day of B6 .......................................... 156 Table H-1: Properties of inoculum and substrate sludge for each batch of assays .................. 161 xiii List of Figures Figure 1.1: Diagram of anaerobic digestion system for sludge stream at Lulu Island WWTP ......6 Figure 1.2: Proposed temperature phase anaerobic digestion system with Archaea Incubator for bioaugmentation of methanogenic archaea ..........................................7 Figure 2.1: Biochemical pathways of anaerobic digestion .........................................................29 Figure 2.2: Diagram of the three types of interspecies electron transfer ....................................37 Figure 3.1: Lab-scale temperature phase anaerobic digester set-up .........................................63 Figure 3.2: SoilMatrix biochar ....................................................................................................65 Figure 3.3: ZMM® T-Carbon ......................................................................................................65 Figure 3.4: Temperature controlled shaker ................................................................................67 Figure 3.5: Biochemical methane potential assays ....................................................................67 Figure 4.1: SEM images of SoilMatrix biochar at a magnification of 500x (left) and 200x (right) ......................................................................................................................78 Figure 4.2: SEM images of ZMM® T-Carbon at a magnification of 500x (left) and 200x (right) ......................................................................................................................78 Figure 4.3: Particle size distribution of SoilMatrix biochar by wet analysis .................................79 Figure 4.4: Particle size distribution of ZMM® T-Carbon by wet analysis ...................................79 Figure 4.5: Graphs of cumulative methane yield of assays with two size ranges and three dosages of biochar and ZMM® T-Carbon ................................................................83 Figure 4.6: Comparison of methane yield for controls in all batches of assays, SIR 4.4 g-VS/g-VS ..................................................................................................................86 Figure 4.7: Graph of total volatile fatty acids variation during BMP assays for B1, SIR = 4.4 g-VS/g-VS with powdered biochar ..........................................................................88 Figure 4.8: Graph of total volatile fatty acids variation during BMP assay for B2 at SIR = 4.4 g-VS/g-VS with powdered ZMM® T-Carbon ............................................................89 xiv Figure 4.9: Graphs comparing the effects of granular char and buffer on methane yield ...........91 Figure 4.10: Graph of acetic acid variation during BMP assays for B1, SIR = 4.4 g-VS/g-VS with powdered biochar ............................................................................................93 Figure 4.11: Graph of propionic variation during BMP assays for B1, SIR = 4.4 g-VS/g-VS with powdered biochar ............................................................................................93 Figure 4.12: Graph comparing the effects of powdered biochar and buffer on methane yield....94 Figure 4.13: Graphs of cumulative methane and carbon dioxide production for inoculum activity test with acetic acid substrate......................................................................99 Figure 4.14: Graph of methane yield for first-generation BMP assays in B3-A ........................ 102 Figure 4.15: Graph of methane yield for second-generation BMP assays in B3-B ................... 102 Figure 4.16: Graph of methane yield for first-generation BMP assays in B4 ............................ 104 Figure 4.17: Graph of methane yield for second-generation BMP assays in B5 ...................... 104 Figure 4.18: SEM images of microorganisms growing inside the pores of the biochar at a magnification of 20,000x (left) and 5,000x (right) .................................................. 105 Figure 4.19: SEM images of microorganisms growing inside the pores of the ZMM® T-Carbon at a magnification of 5,000x (left) and 10,000x (right) ............................... 106 Figure C-1: Graph of calibration curve of the U-shape manometer.......................................... 143 Figure C-2: Graph of chemical oxygen demand calibration sample curve ............................... 143 Figure C-3: Graph of ammonia nitrogen calibration curve ....................................................... 144 Figure C-4: Graph of daily methane production of second-stage TPAD reactor (38°C, 28 d) .. 144 Figure D-1: Cumulative methane production graph for BMP assays for B1 with SIR 2.2 = g-VS/g-VS and powdered (< 0.075 mm) biochar ...................................................... 145 Figure D-2: Cumulative methane production graph for SIR = 3.2 g-VS/g-VS for B1 and powdered (< 0.075 mm) biochar ........................................................................... 145 Figure D-3: Cumulative methane production graph for BMP assays for B1 with SIR = 4.4 g-VS/g-VS and powdered (< 0.075 mm) biochar ...................................................... 146 xv Figure D-4: Cumulative methane production graph for BMP assays for B2 with SIR = 2.2 g-VS/g-VS and powdered (< 0.075 mm) ZMM® T-Carbon ........................................ 146 Figure D-5: Cumulative methane production graph for BMP assays for B2 with SIR = 3.2 g-VS/g-VS and powdered (< 0.075 mm) ZMM® T-Carbon ........................................ 147 Figure D-6: Cumulative methane production graph for BMP assays for B2 with SIR = 4.4 g-VS/g-VS and powdered (< 0.075 mm) ZMM® T-Carbon ........................................ 147 Figure D-7: Cumulative methane production graph for BMP assays for B7 with SIR = 4.4 g-VS/g-VS and granular (0.85 – 4.75 mm) ZMM® T-Carbon..................................... 148 Figure E-1: Graph of total volatile fatty acids variation during BMP assays for B1 at SIR = 2.2 g-VS/g-VS with powdered biochar................................................................... 149 Figure E-2: Graph of total volatile fatty acids variation during BMP assays for B1, SIR = 3.2 g-VS/g-VS with powdered biochar ........................................................................ 149 Figure E-3: Graph of total volatile fatty acids variation during BMP assays for B2 at SIR = 2.2 g-VS/g-VS with powdered ZMM® T-Carbon .................................................... 150 Figure E-4: Graph of total volatile fatty acids variation during BMP assay for B2 at SIR = 3.2 g-VS/g-VS with powdered ZMM® T-Carbon .......................................................... 150 Figure E-5: Graph of total VFA variation during the colonization test of biochar with BMP assays for Batch 3B .............................................................................................. 151 Figure E-6: Graph comparing the effects of buffer addition on total VFA variation during BMP assay for Batch 4 with biochar and ZMM® T-Carbon .................................... 151 Figure G-1: Graph of pH variation during BMP assays for B1 at SIR = 2.2 g-VS/g-VS with powdered biochar ................................................................................................. 157 Figure G-2: Graph of pH variation during BMP assays for B1 at SIR = 3.2 g-VS/g-VS with powdered biochar ................................................................................................. 157 xvi Figure G-3: Graphs of pH variation during BMP assays for B1 at SIR = 4.4 g-VS/g-VS with powdered biochar ................................................................................................. 158 Figure G-4: Graphs of pH variation during BMP assay for B2 at SIR = 2.2 g-VS/g-VS with powdered ZMM® T-Carbon .................................................................................. 158 Figure G-5: Graphs of pH variation during BMP assay for B2 at SIR = 3.2 g-VS/g-VS with powdered ZMM® T-Carbon .................................................................................. 159 Figure G-6: Graphs of pH variation during BMP assay for B2 at SIR = 4.4 g-VS/g-VS with powdered ZMM® T-Carbon .................................................................................. 159 Figure G-7: Graph of pH variation during the colonization test of biochar BMP assays for B3-B ..................................................................................................................... 160 Figure G-8: Graph comparing the effects of buffer addition on pH variation during BMP assays for B4 with granular char ........................................................................... 160 xvii List of Abbreviations AD Anaerobic digestion AOB Ammonia oxidizing bacteria ATAD Autothermal aerobic digestion ATO Advance thermal oxidation ATP Adenosine Triphosphate BMP Biochemical methane production BOD Biological oxygen demand CAS Conventional activated sludge CEC Cation exchange capacity COD Chemical oxygen demand CSTR Completely stirred tank reactor DIET Direct interspecies electron transfer DO Dissolved oxygen EBPR Enhanced biological phosphorus removal EC Electrical conductivity EPA United States of America’s Environmental Protection Agency EPS Extra-polymeric substances GAC Granular activated sludge HLR Hydraulic loading rate HRT Hydraulic retention time IFAS Integrated fixed-film activated sludge IPS intra-polymeric substances LCFA Long chain fatty acid MBR Membrane bioreactor MLSS Mixed liquor suspended sludge xviii MPN Most probable number MS Mixed sludge NADH Nicotinamide adenine dinucleotide PAC Powdered activated carbon PAO Phosphorus accumulating organisms PHB Poly-β-hydroxybutyrate RAS Return activated sludge RBC Rotating biological contactor rpm Revolution per minute SCOD Soluble COD SEM Scanning electron micrograph SIR Sludge to inoculum ratio SRT Sludge retention time TCOD Total COD TF/AS Trickling filter/activated sludge TPAD Temperature phase anaerobic digester TS Total solids TSPS Thickened screen primary sludge TSS Total suspended solids TWSS Thickened waste secondary activated sludge UASBR Up-flow anaerobic sludge blanket reactor VFA Volatile fatty acids VS Volatile solids VSS Volatile suspended solids WAS Waste activated sludge WWTP Wastewater treatment plant xix Acknowledgements I would like to thank my research supervisor Dr. Cigdem Eskicioglu for her dedicated guidance, support and for giving me the opportunity to work with the Bioreactor Technology Group. I would like to thank the committee members Dr. Sumi Siddiqua, Dr. Solomon Tesfamariam and Dr. Nicolas Peleato. I am grateful to ZMM® Mineral Corp. and Airterra for supplying material and technical information about their product, and my colleagues Shiva Khoei, Niloufar Shakourifar and Ravichandra C. Patil and undergraduate students Taylor Thurlin, Daniela Valladares and Sheereen Aminuddin for helping me with setting up my experiment and with data collection. This work would not have been possible without the help of Timothy Abbott and Bita Nazyab who trained me in the lab, answered my questions and provided helpful suggestions and recommendations. I wish to thank Timothy Abbott for his dedicated work managing the lab and providing helpful guidance for this work. I want to express my gratitude to Mr. Paul Kadota for his help with the manuscript and the team at Metro Vancouver, Ms. Marla Bondar and Mr. Paul Markin, for providing great advice and suggestions for this work. xx Dedication À Léa, Loïc, Thomas, Rosalie et Mathis 1 Chapter 1: Introduction Background Historically in North America, domestic, industrial and stormwater were combined in the same collection system and conveyed to the nearest water body. This was the most economical approach to drain stormwater and dispose of wastewater rapidly away from the city. Economic changes between 1851 and 1971 caused the Canadian population to shift from 87% living in rural areas to 25%. Ever since, the urban population has been continually increasing while the number of people living in rural areas has fallen. In 2011, 80% of Canadians were living in a population center (> 400 people/km2) (Statistics Canada, 2016). In the past in Canada as well as currently in other countries, population densification increases pressure on environmental systems and drinking water contaminated by sewage has led to epidemic waterborne disease outbreaks. Raw sewage contains communicable diseases in addition to being an attractant for disease vectors, usually insects (i.e. mosquitoes). Water and crops contaminated by fecal matter can transmit gastrointestinal diseases, for example enteric fevers (typhoid), dysenteries (cholera), Escherichia coli (E. coli) and salmonellosis diarrhea. Poor sanitation in urban areas, such as open septic tanks and soil contaminated with human feces, is responsible for transmission of parasitic worms and pathogens transmitted from insect and animal vectors (World Health Organization, 2018). In the last 150 years, notably in the Canadian province of Ontario from 1880 to 1913, waterborne diseases such as typhoid fever killed on average 20-30 per 100,000 people. The urban areas had over double the mortality rates of rural areas (with the exception of towns and cities with a sanitation system). In Cochrane (Ontario) in 1923, raw sewage contaminated the drinking water of the town causing one third of the population to suffer typhoid fever resulting in a mortality rate of 2,100 per 100,000 people. After water and wastewater treatment was 2 established, the mortality rates from gastrointestinal illnesses in Ontario declined steadily to approximately 2-3 per 100,000 people from 1920 to 1930 (Ross, 1935). Nowadays, as a result of continuous sanitation efforts, water is a source of gastrointestinal illness in only approximately 2 cases per 100,000 people (Vrbova et al., 2012). Sanitation is important for disease control but also for the health of ecosystems. Raw wastewater discharged into the environment causes adverse effects on the receiving water bodies as well as unsightly and odorous pollution. Microorganisms in the receiving water body consume oxygen to degrade organic matter. When concentrations of readily biodegradable materials are high, hypoxic conditions occur and cause undesirable effects such as fish kill. Moreover, turbid water blocks sunlight from the vegetation and prevents it from generating oxygen through photosynthesis. Nitrogen and phosphorus are essential nutrients for algae and a limiting factor in the environment that naturally restrains their growth. Urine and household products like soaps and detergents contain high concentrations of nitrogen and phosphorus that fertilize algae. The proliferation and death of algae can cause eutrophication of waterbodies and lead to fish kill and a long lasting deterioration of the water quality. Moreover, certain cyanobacteria release toxins that are extremely poisonous to some animals including humans (Chislock et al., 2013). Moreover, harmful compounds such as metals/metalloids contained in sewage can bioaccumulate in aquatic animals and cause deleterious health effect to populations consuming them (Ali and Khan, 2018; Deb and Santra, 1997). The extent of damage caused to the environment depends on the compounds discharged into the sanitation system by the users. Generally, the composition of the wastewater varies based on the types of industries present in the collection system and the measures in place to prevent hard to treat or ecologically toxic waste from entering the sewer. For instance, in British Columbia, it is illegal for anyone to discharge any liquid or solid except domestic wastewater to sanitary or storm sewers unless it conforms to the standards listed in Table 1.1 below. Storm sewers are intended for the drainage of rainwater and snowmelt and 3 usually flow directly to the receiving environment. Legally, domestic sewage is defined as “Human excreta and waterborne waste from preparation and consumption of food and drink, dishwashing, bathing, showering and general household cleaning and laundry” (Sewerage System Regulation, BC Reg. 326/2004). Source control programs are set in place by municipalities to assist businesses and residents in complying with the law. The program gives access to alternative disposal, recycling and provides information about safe disposal measures. Table 1.1: Effluent standards for hazardous waste facilities Reproduced from B.C. Reg. 132/92, s. 34; am. B.C. Reg. 319/2004, s. 2. Parameter Standarda for Discharges to the Environment or to Storm Sewers Standarda for Discharges Directed to Municipal or Industrial Effluent Treatment Works Physical pH Temperature Total suspended solids Toxicity (limit bioassay — 50% survival of Rainbow trout after 96 hours) 6.5 to 8.5b 32°C 20 100% effluent 5.0 to 11.0** — — 50% effluent Inorganics Aluminum, dissolved Ammonia, total (expressed as nitrogen) Antimony, dissolved Arsenic, dissolved Barium, dissolved Boron, dissolved Cadmium, dissolved Chromium, dissolved (hexavalent) Chromium, total Cobalt, dissolved Copper, dissolved Cyanide (weak acid dissociable) Fluoride, dissolved Lead, dissolved Manganese, dissolved Mercury, total Molybdenum, dissolved Nickel, dissolved Selenium, dissolved Tin, dissolved Zinc, dissolved 0.5 2.0 0.25 0.1 1.0 10.0 0.05 0.1 0.5 0.1 0.1 0.1 15 0.1 0.5 0.001 0.5 0.5 0.05 0.5 0.2 2.0 — 0.5 0.3 2.5 15.0 0.1 0.2 1.0 0.3 0.3 0.2 18 0.3 1.0 0.01 1.0 1.0 0.1 1.0 0.5 Organics 5 day Biochemical oxygen demand (BOD) Dioxin toxicity equivalence Oil Phenol Polychlorinated biphenyls, total Total chlorinated phenol Total organic halogens (as Cl) 20 15 pg/L 10 0.2 0.005 0.006 1.0 — 15 pg/L 60 0.5 0.005 0.05 1.0 a: Maximum concentration or range in (mg/L) unless otherwise specified. Pg/L is the abbreviation for picograms per litre b: pH units are the negative log of the hydrogen ion concentration. Note: Local municipal requirements may be more restrictive. 4 The Greater Vancouver area is located along the coastline of British Columbia. It is also the youngest major city in Canada. When the Canadian Pacific Railway reached the Pacific Coast, the population of Vancouver increased dramatically from 1,000 to 344,833 people from 1886 to 1951. Until the 1950’s, combined sewers were built to discharge untreated sewage directly into the Georgia Strait, Fraser River, False Creek, Burrard Inlet and English Bay. Extreme pollution in recreational sites such as beaches prompted the construction of Iona Island WWTP and Lions Gate WWTP, in 1961 and 1963 (Rawn et al., 1953). Additionally, sewers replaced cesspools and septic tanks. However, by 1967, only 3 out of 11 outfalls discharged treated sewage. In 1973, Lulu Island WWTP opened followed by Annacis Island WWTP in 1976. A fifth plant joined the Greater Vancouver Sewerage and Drainage District (GVS&DD) in 1987, the Northwest Langley WWTP from the Township of Langley. The five WWTPs provided primary treatment until Annacis Island WWTP and Lulu Island WWTP upgraded to secondary treatment in 1997 and 1998. At-present all the sewers in the Greater Vancouver area are connected to a WWTP. Federal regulation adopted in 2012 requires all WWTPs in Canada to provide at least secondary treatment (Wastewater Systems Effluent Regulations, SOR/2012-139). Upgrade from primary to secondary treatment of Iona Island WWTP is expected for 2030 and Lions Gate WWTP will be replaced with the North Shore WWTP in 2022. The Langley WWTP is currently under expansion, with a target commissioning date of 2026-2027. The GVS&DD is planning major upgrades of all its WWTPs in the next 15 years, which represent capital budgets of several billions of dollars. Motivation for Research The five WWTPs in Metro Vancouver produce annually 55,000 tons of residual solids, with the expansions of the WWTPs the amount could increase to 90,000 tons by 2021. Increasing the efficiency of anaerobic digestion (AD) reactors is imperative to diminish the volume of sludge transported, increase treatment capacity and allow for redundancy. Moreover, 5 increasing efficiency of AD would contribute to the collective efforts to generate more renewable energy and lower greenhouse gas emissions. Higher pathogen inactivation during stabilization would allow more alternatives for land application because the biosolids would fall under Class A in the regulation instead of the current Class B. This could also contribute to reduce biosolids transport costs. A preliminary study conducted by researchers at UBC Microbiology and Immunology on microbial community structure revealed that less than 1% of the microorganisms in the Lulu Island WWTP AD reactors were methane formers (archaea) (unpublished data). This research project is part of a broader NSERC project in partnership with Metro Vancouver that aims at increasing the relative abundance of methanogenic archaea within the AD reactors thus increasing the methane content of the biogas and volatile solids (VS) reduction and decreasing the sludge retention time (SRT). The Archaea Incubator is an innovative concept developed by UBC and Metro Vancouver to increase the resilience and efficiency of the AD process by enhancing the proportion of methane producing archaea The Archaea Incubator would contain electrically conductive media with a high surface area favorable to biofilm formation and direct interspecies electron transfer (DIET). A variety of media options are available on the market, the optimal carrier media would come from a renewable source, be inexpensive and would be either neutral or beneficial to the quality of the produced biosolids. Lulu Island Wastewater Treatment Plant Lulu Island WWTP is owned and operated by the GVS&DD, which is a local government board within the Metro Vancouver Regional District. The plant treats annually 26,000 ML of sewage collected from the municipality of Richmond (except East Richmond) which encompasses a population of approximately 172,000 residents. Lulu Island WWTP currently has trickling filters with contact stabilization as a secondary treatment process, effluent disinfection using sodium hypochlorite (only from April 1 to October 31) and two mesophilic 6 (38°C) AD reactors. The plant achieves a reduction of 98% biological oxygen demand (BOD) and 97% total suspended solids (TSS). The treated effluent discharges into the Fraser River. A dissolved air floatation thickener thickens the waste activated sludge (WAS) and the scum from the primary and secondary clarifiers. Thickened screened primary sludge (TSPS) and thickened waste secondary activated sludge (TWSS) are combined in a blending tank (mixed sludge) and fed to the digesters at an average daily rate of 0.22 mega liters per day (MLD) and 0.12 MLD, respectively. Each digester has a liquid volume capacity of 5,300 m3, the average SRT in 2017 was 29 days and the AD reactors achieved a VS reduction of 63% by weight (Figure 1.1). Two centrifuges dewater the digestate to 23.4% total solids (TS) and the Class B biosolids produced are reused for land rehabilitation and mine reclamation (Metro Vancouver, 2017). The liquid portion of the digestate (centrate) is recycled back to the dissolved air floatation thickener. Figure 1.1: Diagram of anaerobic digestion system for sludge stream at Lulu Island WWTP AD: Anaerobic digester, TSPS: Thickened screened primary sludge, TWSS: Thickened waste secondary sludge and MLD: Mega liters per day. 1.3.1 Upgrading AD with Enhancement Technologies The design proposed combines a temperature phase anaerobic digestion process (TPAD) with an Archaea Incubator. The TPAD system was aimed at improving overall methane production, pathogen inactivation, TS destruction and dewaterability from the AD of mixed sludge. The TPAD optimization from bench-scale reactors was performed in a previous AD 1 38°C AD 2 38°C TSPS 0.22 MLD 3.9% TS TWSS 0.12 MLD 5% TS Mixed Sludge 0.34 MLD 4.23% Digestate 0.34 MLD 1.6% TS Biogas 293 m³/d 7 research study led by Bita Nazyab in 2018. Amongst scenarios tested by Nazyab, the TPAD system operating with an acid-phase (55°C, 2 d) and methane-phase (38°C, 28 d) for a total SRT of 30 days achieved the highest specific methane production, pathogen inactivation and dewaterability. Therefore, this configuration was chosen as a source of hydrolyzed mixed sludge (HMS) substrate and inoculum for biochemical methane production (BMP) assays conducted in this research project. The Archaea Incubator would require a carrier media to support the growth of syntrophic bacteria and methanogenic archaea. Figure 1.2 illustrates the upgraded system proposed. Figure 1.2: Proposed temperature phase anaerobic digestion system with Archaea Incubator for bioaugmentation of methanogenic archaea AD: Anaerobic digester, TSPS: Thickened screened primary sludge, TWSS: Thickened waste secondary sludge and HMS: Hydrolyzed mixed sludge. Multiple carrier material have raised interest for the Bioreactor Technology Group to serve as media for the Archaea Incubator, it was decided that the most promising ones would undergo preliminary testing in BMP assays, which are easier to set-up/monitor compared to continuously-fed AD with higher liquid volume. Biochar was the first selected material for testing because it is relatively inexpensive, the raw material is abundantly available, and it can remain in the biosolids for land application. Wood ash is similar in nature to biochar except that it has AD 1 Methane Phase AD 2 Methane Phase Hydrolysis Temperature: 38oC Temperature: 38oC TSPS Mixed Sludge HMS Digestate Archaea Incubator HMS Biogas Temperature: 55oC TWSS Hydrolysis Phase Archaea 8 no market value. Wood ash is abundantly produced by the wood product industry when forestry residue is burnt for fuel to generate electricity and heat. In Kelowna, most of the daily produced wood ash from Tolko was landfilled and a small portion was used as amendment in the composted municipal wastewater biosolids (OgoGrow). Wood ash was tested in BMP assays alongside the biochar for comparison purposes. Objective The design of the Archaea Incubator prototype using char particles relies heavily on the physical characteristics of the media such as type of media, particle size range and dosage. For the design, the larger particles would be most suitable because they could be harvested using simple straining techniques. On the contrary, powdered media would require a more complicated separation system. The Bioreactor Technology Group found evidence from the reviewed literature that biochar or wood ash would be suitable media for colonization of syntrophic bacteria and methanogenic archaea and that methane production may be enhanced with acidified mixed sludge substrate from the Lulu Island WWTP. Biochar and wood ash appeared to be most beneficial when amended to AD processes undergoing acid stress such as high organic loading rates. However, the appropriate dosage of biochar varied broadly in studies depending on substrate type and biochar feedstock and no studies were found on wood ash amendment to AD of sewage sludge. In this study, the experiments were conducted in BMP assays with the following main objectives: 1. To evaluate the effect of size, amount and type of char particles on the methane production from municipal wastewater sludge. 2. To determine if the benefits of char could be tied with high concentrations of inhibitory compounds such as ammonia and volatile fatty acids which occur when the organic loading to AD is high. 9 3. To assess the suitability of biochar and wood ash media to colonize syntrophic bacteria and methanogenic archaea for bioaugmentation purposes of an anaerobic digester. In order to achieve the objectives listed above, the following tasks were implemented: I. Set-up BMP assays with three (3) different substrate (wastewater sludge) to inoculum (anaerobic culture) ratios, three (3) dosages and two (2) particle size ranges of biochar and wood ash, in triplicates with controls (no char) and blanks (anaerobic culture only). Furthermore, analyze: a. The effect of acid stress on control BMP assays and the effect of each particle size range and char type on the rate of methane production, duration of the lag phase and total methane yield (supports Objectives 1 and 2). b. The BMP assays for ammonia nitrogen, volatile fatty acids, pH and alkalinity, in order to determine the effects of biochar and wood ash addition on the AD process. Verify if the char material affects AD ammonia concentrations (supports Objective 2). II. Set-up additional BMP assays inoculated with biochar and wood ash recovered from BMP assays (operated under Task I) and fresh substrate (sludge) without external inoculum addition. Analyze the rate of methane production to determine if methanogenic archaea and syntrophic bacteria inoculated the BMP assays with culture colonized on the char particles (supports Objective 3). a. Analyze the char with a scanning electron micrograph (SEM) for evidence of microorganisms colonized on the surface and take images (supports Objective 3). III. Obtain and prepare microbial consortia samples from the most promising BMP assays for genomics analysis (supports Objective 3). Genomics analysis (outside scope of this thesis) was conducted by an external research laboratory at UBC Microbiology and Immunology. 10 Chapter 2: Literature Review The following sections are intended to provide the reader with background information on wastewater treatment processes in order to better understand how biochar and wood ash could improve the outcomes of the system. First, the conventional wastewater process used in North America is described along with some variations in design. This will offer the reader an understanding of how the Lulu Island WWTP operates. Second, the most common solid stream processes are explained with a particular focus on AD and sludge pre-treatment. Third, recent advancements in the biochemistry of AD with an emphasis on DIET is discussed. Finally, the most recent literature on conductive carrier media capable of stimulating DIET in AD is reviewed. 2.1.1 Wastewater Treatment Municipalities in most of the developed world rely on WWTP to prevent propagation of diseases and to protect neighboring water bodies from eutrophication. The classification of a WWTP can range from level I to IV and each increase in level corresponds to an increase in level of complexity and operational expertise. The level is determined using a points system based on raw wastewater flows and toxicity, effluent discharges, number of treatment steps and complexity of in-house laboratory analysis (EOCP, 2018). The main treatment steps are preliminary, primary, secondary, tertiary and advanced wastewater treatment. Preliminary and primary treatment, consist of a coarse screen for debris and a settling tank to remove settleable solids. The screenings are landfilled or incinerated. Secondary treatment reactors include the conventional activated sludge (CAS) process, rotating biological contactor (RBC), trickling filter and hybrid systems such as the integrated fixed-film activated sludge (IFAS) and the trickling filter with a solids contact basin. The sludge from the bioreactor is separated from the water by flocculation and settling or with membrane filtration. Tertiary treatment implies a disinfection and polishing step to reduce the effluent TSS and BOD and may include nutrient removal (i.e. 11 phosphorus and nitrogen). Pathogens are inactivated chemically with a strong oxidizing agent, for instance with chlorine and ozone, or physically by ultraviolet radiation and pasteurization. The primary and secondary sludge produced during treatment can be further degraded in a digester, composted, incinerated or landfilled. The dewatered digested sludge, also called biosolids, may be recycled as a soil amendment while the liquid fraction is returned to the headworks of the WWTP (Metcalf & Eddy, 2014). The following sections elaborate on each step of the treatment process. 2.1.1.1 Preliminary and Primary Treatment Process Preliminary treatment removes non-degradable coarse material such as grit, sand, paper, rags, sticks, diapers, debris and large plastics material. The influent to the plant first passes through bars and screens and then through a grit chamber. Grit chambers are more common in WWTPs that are on a combined sewer system where the grit and sand from the roads enter the system through the storm drains. Particles greater than 0.225 mm tend to settle and remain in the collection system, while smaller particles will flow with the wastewater to the WWTP. The material is abrasive and can cause premature wear on plant equipment such as pumps and comminutors. Moreover, the material tends to settle quickly once it reaches the clarifier. If the primary sludge is subsequently digested, the grit and sand will not degrade so it will occupy unnecessary space in the tanks. The ideal equipment to perform the task of removing grit and sand would exclude any putrescible material (Droste, 1997). In a grit chamber, the particles are removed based on their density which roughly corresponds to particles greater than 0.15 – 0.200 mm in diameter. There are three main designs, horizontal flow grit chambers, aerated grit chambers and vortex type grit chambers. In the horizontal flow grit chamber, the flow is slowed to 0.3 m/s for a sufficient distance to allow the grit and sand to settle while the organic material flows through. In the aerated grit chamber, air is blown in a circular air current that keeps organic material in suspension and coarse heavy material settles 12 to the bottom. The benefit of this design is that airflow can be adjusted to control settling without affecting the detention time in the chamber. The vortex type grit chambers work in a similar way, the swirling motion separates the heavy grit from the lighter material. The grit swirls at the bottom and is captured in a trough while the rest of the suspended material flows out the top of the unit with the wastewater (Metcalf & Eddy, 2014). Primary treatment refers to the removal of suspended particles that settle by gravity or float to the surface. Sedimentation tanks are typically 3 – 4.0 m deep, either rectangular or circular, with a hydraulic detention time of 1.5 – 2.5 hours. The rectangular design is more space efficient and require less material since the walls can be shared with other tanks. The amount of biological degradation is negligible in this step of treatment. The efficiency of removal ranges from 50 – 70% TSS and 25 – 40% BOD (Metcalf & Eddy, 2014). The remaining TSS is non-settleable and requires biological degradation or chemical flocculation for removal. There is disparity between TSS and BOD removals from primary sedimentation because a fraction of the TSS is either inert or requires longer than 5 days to degrade. The primary sludge scraped from the bottom of the tank into the solids hopper and the scum skimmed from the surface are further processed as part of the solids stream (Droste, 1997). Effluent from the primary sedimentation tank then flows to the secondary treatment process for biological treatment. 2.1.1.2 Secondary Treatment Process Secondary treatment systems are diverse microbial ecosystems majorly composed of aerobic heterotrophic bacteria, and a minority of protist, fungi, plants and animals collectively called activated sludge or zoogleal film. The main bioreactor designs are described in the next sections. Following the bioreactor, the activated sludge or sloughed biofilm flows to a second sedimentation tank where the floc settles to the bottom and the clear water exits through the effluent trough. Membrane bioreactor (MBR) are similar to CAS systems except that instead of a secondary clarifier, the activated sludge flows to a tank with immersed membrane filters that 13 draw permeate using a vacuum pump. MBR technologies (microfiltration and ultrafiltration) are increasingly popular because they achieve lower effluent TS concentrations while reducing the footprint of the plant by up to 50%. However, MBRs consume near double the electrical energy and the expensive membranes need replacement every 5 to 10 years (Brepols, 2011; Metcalf & Eddy, 2014). Brepols (2011) did a life cycle cost analysis that compared a tertiary CAS with an equivalent MBR and obtained an initial investment cost 22% lower for the MBR. This result was explained by the cost savings realized on materials, size of equipment and labor during construction. The study did not consider cost-savings from land purchasing, which is a major factor in most cities in Canada, notably in the Greater Vancouver area. Nevertheless, the operational cost would be 14% higher for an MBR due to energetic requirements (the results from the study were recalculated to include disinfection) (Brepols, 2011). The CAS and MBR may also be designed to include nutrient removal such as nitrogen and phosphorus where required by the legislator. In the following sections, the principles of nitrogen and phosphorus removal is explained, followed by the three main secondary biological treatment reactor designs. 2.1.1.2.1 Nitrogen Removal Nitrogen is fundamental to the functioning of all organisms on Earth as it is contained in DNA and all amino acids. It is also often a limiting factor to the capacity of the environment to support life (Schlesinger and Bernhardt, 2013). For instance, mineralization of soil is associated with desertification, on the contrary, eutrophication of water bodies by nitrogen rich sources causes algae blooms. The most abundant source of nitrogen is the atmosphere in the form of nitrogen gas. All the nitrogen present in the form of organic compounds originate from either fixation by microbes or, to a minimal extend, lightning. Microorganisms with the capacity to fix nitrogen are present in water bodies, soil and wetlands and contribute to 15% of the nitrogen needed by plants. Photosynthetic organisms use sunlight to generate the energy necessary to 14 synthesize organic matter partly from the ammonium, nitrate and nitrite absorbed from the soil or from a symbiotic relationship with nitrogen fixing microbes (Schlesinger and Bernhardt, 2013). Heterotrophic organisms including humans perform the mineralization of protein and amino acids to obtain energy and generate urea as a by-product. Bacteria convert urea to ammonia or ammonium. Chemoautotrophic nitrifying organisms such as bacteria Nitrosomonas and Nitrobacter convert ammonia into nitrate and nitrite according to Reactions 1 and 2. 2 ∙ 𝑁𝐻4+ + 3 ∙ 𝑂2 → 2 ∙ 𝑁𝑂2− + 4 ∙ 𝐻+ + 2 ∙ 𝐻2𝑂 (1) 2 ∙ 𝑁𝑂2− + 𝑂2 → 2 ∙ 𝑁𝑂3− (2) Under anoxic conditions, nitrite and nitrate can undergo denitrification by heterotrophic bacteria by serving as electron acceptors for the oxidation of organic compounds. These bacteria will reduce nitrate, nitrite, nitric oxide and nitrous oxide to oxidize organic compounds. The final product of denitrification is N2 gas. Reaction 3 summarizes the biochemical process. C10H19O3N + 10∙NO3−→ 5N2+ 10CO2 + 2H2O +NH3 +10OH− (3) When partial nitrification or denitrification occurs, nitrous oxide is generated and released into the atmosphere. Nitrous oxide is a potent greenhouse gas emitted by WWTPs that contributes to global warming (Eskicioglu et al., 2018). In the absence of oxygen, ammonia can still be oxidized to nitrogen gas in a process called anaerobic ammonium oxidation (Anammox) by bacteria. Anammox bacteria use nitrite as an electron acceptor to oxidize ammonium in a ratio of 1:1 (Kuenen, 2008). Partial nitritation and Anammox biochemical reactions are demonstrated in Reactions 4 and 5 (van Dongen et al., 2001). NH4+ + HCO3- + 0.75O2 → 0.5NH4+ + 0.5NO2– + CO2 + 1.5H2O (4) 0.5NH4+ + 0.5NO2− → 0.5N2 + H2O (5) Anammox is gaining popularity in streams with a high concentration of total nitrogen (Eskicioglu et al., 2018). Nevertheless, most WWTP rely on conventional nitrification-denitrification for biological removal of nitrogen. Many reactor configurations are effective at 15 nitrogen removal. They typically consist of a CAS system with alternating anoxic and aerated zones and readily biodegradable chemical oxygen demand (rbCOD) provided in a strategic zone to optimize denitrification. The design of a reactor for nitrogen removal is discussed in the section on IFAS. 2.1.1.2.2 Phosphorus Removal Phosphorus is a key element for life since it is present in important components of cells such as phospholipids, DNA and adenosine triphosphate (ATP) and adenosine diphosphate (ADP). However, it is minimally present in gaseous form. The main source of phosphorus is from geological minerals and is considered a limiting factor for growth in aquatic environments (Schlesinger and Bernhardt, 2013). Heterotrophic phosphorus accumulating organisms (PAOs) are responsible for removing phosphorus from the process by storing it within their cells inside polyphosphate storage granules. The actual phosphorus removal from the wastewater stream is accomplished when the sludge containing PAOs is wasted. The treatment process is termed enhanced biological phosphorus removal (EBPR) and it can remove up to 80% of total phosphorus from municipal wastewater (Metcalf & Eddy, 2014). Some processes include a separate anaerobic reactor to ferment primary sludge to provide a source of volatile fatty acids (VFA) for the EBPR. In the EBPR process, the influent flows through an anaerobic zone and is mixed with the return activated sludge (RAS) from the secondary clarifier. The PAOs have the capacity to oxidize VFAs using their stored reserves of polyphosphate as electron acceptor in the absence of oxygen. This process implies that orthophosphate is released from the cells. Meanwhile, the acetate is absorbed by the PAO and stored as poly-β-hydroxybutyrate (PHB) for later use. In this treatment stage, the PAO have an advantage over other types of heterotrophic bacteria so they proliferate. The depletion of polyphosphate storage causes stress on the PAOs. The mixed liquor suspended solids (MLSS) from the anaerobic zone then flows to an aerobic zone where the PAOs, having access to oxygen metabolize the stored PHB. The energy from 16 the oxidation process is used by the cells to reabsorb orthophosphate and convert it back to polyphosphate. Because of the previous stress from starvation, the PAOs will uptake more orthophosphate than was released in the anaerobic zone, leading to a net phosphorus removal from the system after the sludge is wasted from the secondary clarifier (Grady et al., 2011). 2.1.1.2.3 Suspended Growth Bioreactors Suspended growth bioreactors are large tanks filled with MLSS that rely on oxygen transfer equipment (i.e. diffusers and blowers) to provide aerobic conditions and mixing throughout the tank. The activated sludge contains heterotrophic bacteria that oxidize organic carbon to fuel their growth and metabolism, and rotifers that graze on bacteria. Consequently, the process generates a large amount of biomass. In the secondary clarifier, part of the settled activated sludge is returned to the bioreactor and part of it is wasted. MLSS concentrations should remain within the operational range, usually 500 – 5,000 mg/L for systems with clarifiers and 1,000 - 10,000 mg/L for MBRs (Metcalf & Eddy, 2014). MLSS concentration and SRT control is done by adjusting the flow rate of the RAS. When RAS flow decreases, wasting of activated sludge increases, leading to a decrease in the MLSS concentration in the bioreactor. In the clarifier system, the floc quality determines foremost the SRT. A short SRT is associated with filamentous bacteria growth, which cause problematic filamentous bulking in the clarifier when they proliferate. Bulking refers to large buoyant flocs of filamentous bacteria that rise to the surface instead of settling and flow out of the clarifier with the treated effluent. This usually happens under high dissolved oxygen (DO) conditions and low SRT. On the other hand, long SRTs with low amounts of filamentous bacteria can favor the formation of pinpoint floc, which are light, compact, and thus do not settle well. In low proportions, filamentous bacteria may help floc formation and floc settling. Therefore, for optimal performance, DO concentration of 2 mg/L is recommended. For MBR systems, longer SRTs are associated with sludge that filters more efficiently (Grady et al., 2011). The configuration of suspended growth bioreactors can be a 17 complete mix or plug flow design. The CAS system is homogeneously mixed by the turbulent action of the rising bubbles and, less often, mechanically. A well designed bioreactor will prevent “dead zones”, which are areas that are not mixed and aerated, and short-circuiting. Both conditions would have detrimental effects on actual hydraulic retention time (HRT) and effluent quality. The plug-flow configuration reduces opportunities for short-circuiting and dead zones by having only vertical complete mixing. The organic matter is progressively degraded as the wastewater travels through a baffled channel (Droste, 1997). 2.1.1.2.4 Attached Growth Bioreactors Attached growth bioreactors types such as RBCs and trickling filters are designed to provide a maximum surface area in the reactor for biofilm attachment. The main limiting factor in attached growth processes is the low oxygen transfer rate through the biofilm. The complexity of the microbial ecosystem is higher in attached growth reactors because the SRT is not a control parameter. In such processes, it is common to find organisms that are higher on the phylogenic scale such as insects, worms, snails and nematodes. When the biofilm becomes too thick, it sloughs off and removed by gravity settling. One benefit of these systems is that the HRT is independent of the SRT so biomass washout is less concerning than for suspended growth systems. The slime may act as a protection layer for microorganisms and allow the process to recover quickly from toxic loads. In addition, the oxygen and nutrient transfer gradient within the biofilm is such that different groups of bacteria colonize the inner and surface layers of the biofilm. For instance, fixed-film bioreactors may provide nitrogen removal without being specifically designed for that purpose. This is because the nitrification of ammonia occurs on the surface biofilm layer while denitrification occurs in the deeper anoxic part of the biofilm (Metcalf & Eddy, 2014). The RBC consists of a shaft with tightly packed plastic disks of 2 – 3.2 m in diameter, usually 40% submerged and rotating at a speed of 1 – 2 revolutions per minute (rpm) (Droste, 18 1997). The rotation of the RBC exposes the biofilm to the organics and nutrients contained in the wastewater and to oxygen from the air. The system is inexpensive to operate since it does not require additional aeration nor recycling flow. Moreover, in small systems, the tank containing the RBC may also serve as a secondary settling tank, resulting in a compact and efficient WWTP. RBC reactors have been dropping in popularity because of unpredictable change in biomass composition resulting in lower treatment performance. In addition, the uneven repartition of the biofilm can cause strain on the motor and gear assembly (Metcalf & Eddy, 2014). Emergency maintenance is complicated by the size and heaviness of the contactors and the work often requires a crane. Trickling filters are nonsubmerged bioreactors common in areas with a yearlong climate above freezing conditions. The tank is filled with packing such as rocks or plastic media and two distributor arms spray the wastewater over the surface of the packing. The wastewater trickles down the tower where organic particles and nutrients attach onto the surface of the slime layer where bacteria hydrolyze and absorb them. The effluent then reaches the underdrain where a portion is recycled to the distributor arms and a portion flows to a secondary sedimentation tank. The wastewater is recycled to increase BOD removal and DO, and to keep the biofilm moist. The sloughed off biofilm flows directly to the secondary clarifier. The underdrain must be porous enough to allow the flow of water, sloughed off biofilm and air, yet strong enough to support the weight of the media, biofilm and water. For this reason, rocks have been replaced with plastic packing in recent years. The lighter media also allows for taller towers, more void space for airflow and higher specific surface area for biofilm attachment. Generally, the depth of the packing can only be a maximum of 2.5 m for rock media and 12 m for plastic media. The distributor arms could rotate by the action of hydraulic pressure from the nozzles alone but it is more common to connect it to a motor with a variable speed drive because it offers operational control over the hydraulic loading rate (HLR). Natural ventilation is when the air penetrates inside the filter through the underdrain and the filter surface. Natural ventilation is only possible 19 for trickling filters that require a low rate of BOD removal, which is associated with a HLR of 1 - 4 m3/m2 d and OLR of 0.08 – 0.3 kg BOD/m3 d. For higher HLR and OLR, forced draft aeration is necessary to achieve 70 – 90% BOD removal. Like RBCs, trickling filters require less energy, cost less and are simpler to operate than suspended growth processes. The main disadvantage of trickling filters is that the sloughed off biofilm collected in the secondary clarifier often does not settle well and results in higher TSS and BOD in the treated effluent than with CAS. The process is also limited by oxygen transfer rate when the BOD is higher than 400 - 500 mg/L (Metcalf & Eddy, 2014). 2.1.1.2.5 Hybrid Bioreactors Hybrid bioreactors combine the benefits of both suspended and attached growth systems. The trickling filter and activated sludge system is designed to increase BOD removal and flocculate the sloughed off biofilm to increase its settleability in the secondary clarifier. This combination is efficient because it requires an aeration tank 80 to 95% smaller than a CAS system. Moreover, the trickling filter and activated sludge system can achieve TSS below 10 mg/L in the treated effluent with OLRs of 0.4 – 1.8 kg/m3 d. The design includes a recycle of the activated sludge from the secondary clarifier to the aeration tank. The solids contact mode refers to the same configuration but it is operated with an HRT and SRT averaging 45 – 60 min and 1 – 2 days, respectively, such that most of the BOD is removed in the trickling filter and the aeration tank’s primary function is bioflocculation (Metcalf & Eddy, 2014). The IFAS reactor was first studied by Randall and Sen in 1996 as a full-scale retrofit of a CAS process for biological nitrogen removal. The reactor is filled with roughly 40% plastic media for biofilm growth. Biofilm can hold a larger proportion of nitrifying bacteria compared to CAS, at a lower SRT, and can increase the nitrogen removal of an existing plant without having to increase the size of the reactor. The reactor is separated into a preanoxic zone, an IFAS zone and ideally, two other aeration zones. There is a recycle of activated sludge from the secondary 20 clarifier to the reactor influent. The moving bed biofilm reactor (MBBR) is almost identical to the IFAS with the exception that the tank is filled with more media (70%) and there is usually no sludge recycle (Metcalf & Eddy, 2014). Since the primary purpose of upgrading a CAS system to an IFAS system is to provide nitrogen removal, the basic design for a nitrification-denitrification bioreactor is also explained in this section. Aeration has a dual purpose in IFAS bioreactor applications. The first is to homogenize the substrate, carrier media distribution and suspended microorganisms throughout the reactor. The second is to ensure the bioreactor is operating aerobically. In other words, the substrate (ammonia) should be oxidized by microorganisms using oxygen as an electron acceptor. As with other attached growth reactors, the biofilm growing on submerged carrier media has a lower oxygen transfer efficiency than suspended sludge (Rosso et al., 2011). So too low aeration would prevent desirable aerobic bacteria from forming on the media. In a full-scale study, the minimum DO that allowed nitrification on the surface of the biofilm was found to be 4 mg/L, as measured in the bulk liquid (Li et al., 2016). Manufacturers recommend coarse-bubbles (50 mm) to agitate the media, but larger bubbles are less efficient at transferring oxygen into the water. Blowers used for aeration are the most energy demanding equipment in a typical WWTP with an activated sludge process. The higher DO concentration and larger diffuser hole sizes for IFAS reactor make it more expensive than CAS (Rosso et al., 2011). Like for other attached biomass systems, the biofilm growing on the plastic packing allows the dissociation of the HRT from the SRT. The benefit is larger for autotrophic nitrifying bacteria than for heterotrophic bacteria because their growth rate is slower. Generally, nitrification is regarded as the limiting factor in the rate of nitrogen removal because ammonia oxidizing bacteria (AOB) need more time to multiply than the SRT of most CAS systems, which causes AOB to wash out of the reactor. Under ideal operating conditions, the biofilm layer would be composed of a surface layer of AOB. However, heterotrophic bacteria can outcompete AOB 21 on the media if rbCOD is present. For this reason, the IFAS reactor is located at the end in a zone separated by baffles where heterotrophic bacteria have already oxidized the rbCOD. When there are enough AOB in the biofilm for complete nitrification, the reactor can be operated at a reduced SRT for the suspended growth than nitrification processes with only biomass in suspension. A study on a full-scale IFAS reported that the amount of biomass measured in carrier biofilm could be up to twice the amount of biomass in suspension (Singh and Kazmi, 2016). Sloughing of AOB biomass from the media supplements the suspended biomass’ AOB population, which increases overall nitrification efficiency. Biofilm attachment and detachment is a function of film thickness, film density and rate of gas produced in the deeper layers (Takacs et al., 2007). Denitrification can also take place in the deeper layer of the biofilm if the aeration is too low or if the biofilm is thick enough to become impermeable to oxygen diffusion (Li et al., 2016). Heterotrophic bacteria accomplish denitrification under anoxic conditions by oxidizing rbCOD using the nitrate and nitrite produced by the AOB. The IFAS should be optimized for nitrification with denitrification taking place in a separate, unaerated zone with no media, in order to reduce costs. In summary, an efficient nitrogen removal IFAS process has an anoxic zone where denitrification and oxidation of rbCOD occurs, followed by an IFAS reactor for nitrification and a recycle flow that provides nitrate and nitrite to the anoxic zone. An intermediate zone may be beneficial to increase DO with fine bubble diffusers and to remove any excess rbCOD before the IFAS reactor (Metcalf & Eddy, 2014). 2.1.1.3 Tertiary Treatment Process Disinfection is usually included in tertiary treatment to protect the public and downstream population from pathogens responsible for severely infectious diseases such as cholera, diarrhea, typhoid fever and dysentery. Pathogen reduction relies on a multi-barrier approach and is calculated by number of log10 removal of total virus. The World Health Organization recommends 6-7 log10 removals for irrigation of crops meant for human consumption. For 22 instance, primary and secondary treatment would be considered 1 and 2 log10 removals, respectively, while disinfection would be 3 log10 removals, for a total of 6 log10 removals (Sano et al., 2016). Disinfection refers to the chemical or physical inactivation of pathogens. Chlorination and UV irradiation are the most widely used disinfecting agents. The main compounds used for chlorination are sodium hypochlorite (12% solution), calcium hypochlorite (powdered) and chlorine gas (100%). Before discharging effluent to a water body, the residual chlorine should be neutralized to prevent fish kill, usually with either sodium sulfite, sodium bisulfite, sodium metabisulfite or sodium thiosulfate (Metcalf & Eddy, 2014). Chlorination is an effective disinfectant but concerns have been raised about its use because a number of chlorination by-products are considered carcinogenic by Health Canada. Ozone, chlorine and other halogens such as fluorine, bromine and iodine react with organic matter present in the water to produce a wide array of disinfection by-products, most of which are not yet identified. Their fate in the environment and potential effects on drinking water sources and ecosystems are an active area of research (Li et al., 2019). In recent years, an increasing number of WWTPs have replaced chlorination with ultraviolet (UV) reactors. UV light disinfects water by damaging the DNA of pathogens thus preventing them from replicating. Pathogens may shelter in particle matter and avoid UV irradiation, so the disinfection effectiveness depends on the particulate matter present. Since no residual remains after UV irradiation, its effectiveness cannot be directly measured. Instead, it is verified based on the proportion of UV light that can transmit through a sample of water. The transmittance is measured as a percentage (Metcalf & Eddy, 2014). Tertiary treatment is also a polishing step designed to improve the quality of the secondary effluent for reclamation purposes or before discharge to a sensitive environment. The technology installed depends on the requirements for the specific application and the regulatory limits. Sensitive water bodies are those characterized by naturally low total organic carbon and nutrient levels, for example the Okanagan Lake (British Columbia, Canada). The treated effluent 23 from the Kelowna WWTP must comply with strict limits for maximum daily discharge of 10 mg TSS/L, 10 mg BOD5/L, 10 mg total nitrogen/L and 2.0 mg total phosphorus/L (Gosselin, 2018). Colloidal and suspended particles from the secondary effluent can be reduced to meet stringent regulatory limits by filtration, chemical precipitation, flotation, adsorption and chemical oxidation. A variety of filtration systems are available on the market, some systems are combined in series with other technologies such as chemical coagulation and depth filtration or ultrafiltration followed by ozonation and UV disinfection. For advanced TSS reduction, filtration technologies are commonly used. Microfiltration, ultrafiltration, depth filters and cloth filters act as a physical strainer for the particles. Ultrafiltration has the smallest pore size ranging from 0.005 – 0.1 μm and can remove pathogenic organisms such as viruses. Nanofiltration and reverse osmosis have the added benefit of rejecting dissolved solids like salts. However, these filters are expensive to operate because they require high pressure to draw permeate through the membrane and only a fraction of the water is recovered. The reject stream is concentrated with dissolved and particulate matter, which may restrict disposal options. A dissolved air flotation unit is a reactor with a pressurized water tank and a surface skimmer. Air is pumped into the water tank and the air saturated water flows into the reactor where air bubbles will form onto the particles and reduce their buoyancy. The particles rise to the surface of the water where they are skimmed into a trough (Metcalf & Eddy, 2014). 2.1.1.4 Sanitation Classification of Biosolids and Compost Sewage sludge may be applied as land amendment under certain treatment conditions and application restrictions to prevent propagation of disease. Measuring individual pathogens in a sample is unfeasible. Instead, laboratories rely on estimation techniques such as coliforms which are a group of bacteria that are easy to culture and generally harmless. Fecal coliforms are from the family Enterobacteriaceae and are found in the feces of warm-blooded animals. They are used as surrogates to indicate the probability of a sample to contain human pathogens 24 and is measured in most probable number (MPN). Untreated sewage sludge contains organic matter that may attract rodents, pets, birds and insects seeking food. The pathogens contained in the sewage may propagate via the animals (vectors) and contaminate humans. Therefore, the regulation includes a management practice to reduce the availability of the food source called the vector attraction reduction criteria. Biosolids are categorized into Class A and Class B. Class A biosolids has low probability of containing pathogens and can be applied to most land as opposed to Class B biosolids which may still contain pathogens and are heavily regulated to protect the public (EPA, 2003). As per the Organic Matter Recycling Regulation (BC Reg. 18/2002), Class A biosolids originating from the composting or digestion of sewage sludge must have a fecal coliform count of less than 1000 MPN/g-TS and a 38% minimum VS reduction to satisfy the vector attraction criteria. There are also strict limits on trace metals arsenic, cadmium, chromium, cobalt, copper, lead, mercury, molybdenum, nickel, selenium and zinc. For Class B, the fecal coliform count must be less than 2 x 106 MPN/g-TS and must satisfy the 38% VS reduction for vector attractant and minimum limits on trace metals. Nazyab (2018) analyzed the anaerobically digested wastewater sludge of the Lulu Island WWTP in Vancouver for trace metals and found that the concentrations were well below the minimum limits set for Class A and B biosolids. In order to satisfy Class A or B biosolids, sludge treatment is required, the most common are composting and digestion. However, the municipality may opt for incineration or landfilling if neither are feasible. 2.1.1.5 Composting Composting is an effective method of stabilizing wastewater sludge and generates a safe and nutrient-rich soil amendment. It is suitable for both unstabilized sludge (primary and secondary sludge) and biosolids from the AD process. The sludge is first mixed with a bulking agent that favors airflow such as wood chips and then piled into mounds known as windrows. The windrows are turned periodically to allow aerobic conditions and to homogenize the 25 compost. Moisture is also added periodically to prevent drying of the compost piles. Microorganisms, through mainly bacteria and fungi, degrade the carbonaceous material and produce carbon dioxide, water and heat. The temperature of the compost pile can reach 50 - 70°C, which enable pathogen inactivation. Composted biosolids can be classified as Class A soil amendments if the windrows are insulated and mixed at least 5 times and temperatures are above 55°C for 15 days (BC Reg. 18/2002). However, composting is a slow process (> 60 days) and requires a large land area away from the community because of objectionable odors and health risks related to bioaerosols released during the composting process (Metcalf & Eddy, 2014). 2.1.1.6 Incineration and Landfilling Screenings and grit from preliminary treatment are mostly non-readily biodegradable material that must be removed to prevent blockage and to protect equipment downstream such as pumps and membranes. The material is heavily contaminated by pathogens and contains undesirable material that prevents resource recovery, therefore, it is usually disposed into a sanitary landfill or incinerated. The choice of disposal for dewatered primary and secondary sludge depends on regulations, cost and end use availability. Landfills are generally frowned upon by local communities so finding suitable land area to build them can be challenging. Incineration, or advanced thermal oxidation (ATO), is used throughout North America and the EU as a low footprint alternative to landfilling. The biosolids have to be dewatered to 30-35% and high VS content to allow combustion without needing an additional fuel source. The heat can be recovered to heat buildings, tanks or generate electricity. However, ATO releases carbon dioxide and other combustion emissions resulting in air pollution that cause adverse health and environmental effects. In Canada, strict legislation regarding air emissions have forced industry to adapt by installing air pollution control equipment such as wet scrubbers and 26 by controlling the combustion process. Offensive odors may be generated from auxiliary processes but can be reduced with proper odor elimination systems (Metcalf & Eddy, 2014). 2.1.2 Digestion Transportation and processing of dewatered sludge accounts for 25-65% of the budget of WWTPs (Pérez-Elvira et al., 2006). Digestion is an effective process to stabilize sludge and reduce TS and VS content. If the digester is operated at an SRT of at least 40 days at 20°C or 60 days at 15°C, the resulting digested sludge, once dewatered, can be reused as Class B soil amendment. The digested sludge can meet Class A criteria if digested at a minimum temperature of 50°C and meets the pathogen and vector attractant reduction processes and quality criteria (BC Reg. 18/2002). Digestion can be performed aerobically or anaerobically. Aerobic digestion is similar to a CAS reactor except no soluble, readily biodegradable substrate is supplied. Therefore, microorganisms contained in the WAS undergo endogenous respiration where cellular material is consumed by microorganisms. If the aerobic digester receives primary sludge, it will act as a substrate source and delay endogenic respiration resulting in a longer SRT. Conventional aerobic reactors are simple to operate and can achieve 38-50% VS reduction. However, they cost more to operate because of aeration and alkalinity requirements. Moreover, aerobic sludge has low dewaterability and the reactor does not produce methane (Metcalf & Eddy, 2014). The autothermal aerobic digestion (ATAD) process relies on the exothermal energy released from microorganisms oxidizing waste and cellular material to heat the digester. By properly insulating the digester, temperatures above 55°C can be reached without an external source of energy. Class A biosolids may be achieved if the temperature is maintained above 55°C for at least 30 min. The organic degradation rate is limited by the oxygen transfer rate, as a consequence, the DO in the reactor is persistently low. The negative oxygen balance leads to fermentation and production of VFAs. The main advantages of ATAD are the production of 27 Class A biosolids, auto-sufficient alkalinity and a shorter SRT resulting in smaller reactor volume requirements. Disadvantages include low dewaterability, strong odors, foam production and the release of nutrients in the liquid stream because of hydrolysis (S. Liu et al., 2012; Metcalf & Eddy, 2014). ATAD reactors can be used as first stage pretreatment for anaerobic digesters. Indeed, the production of VFA and rapid hydrolysis of complex organics (protein, fats and carbohydrates) benefits the anaerobic digestion process rendering it more efficient (lower SRT, higher methane yield) and results in Class A biosolids (Metcalf & Eddy, 2014). Anaerobic digestion produces methane, which is a valuable energy source. AD reactor designs are either biofilm growth or suspended growth. Suspended growth reactors are mainly complete stirred tank reactors (CSTR). CSTR are insulated tanks made of a corrosion resistant material such as stainless steel and are heated. For mixing, the digester may be configured to recycle the gas produced, recirculate the digestate or has an impeller. To accommodate any change in volume and to provide pressure in the system, most reactors have a floating lid. Biofilm growth in the form of granules are typically found in the upflow anaerobic sludge blanket reactors (UASBR). Reactors with granules have several advantages over the CSTR such as providing a stable digester biomass retention, an increase resistance to toxic flows, 70% COD reduction and an OLR of 50 kg-COD/m3 d. However, the mechanism of granulation formation is poorly understood which makes the design of a UASBR difficult (Amani et al., 2010). Reactors are under positive pressure to prevent oxygen contamination and to harvest the biogas. The biogas is composed of 70 - 75% methane and 30 - 35% carbon dioxide. AD process is endothermic but most systems reuse the biogas as fuel to heat the digester. The process may generate enough energy to heat buildings in the winter, and if unneeded, it is flared. Some large facilities use boilers with turbine generators to produce electricity that can be sold to the grid. Alternatively, the value of the biogas can be improved by removing CO2, H2S, ammonia, siloxanes and moisture and injected into the natural gas network (Metcalf & Eddy, 2014). Anaerobic digesters represent a higher risk for health and safety than aerobic systems. Biogas 28 leakage or introduction of air in the system could lead to explosive conditions. Consequently, plant owners and engineers allocate a significant capital and resources to the design, construction and commissioning of anaerobic reactor systems to comply with standards and regulations. Moreover, AD increases the cost of operation of a WWTP because of the higher skill level required from the operators (Canadian Biogas Association, 2019). AD is more common in large municipalities, whereas aerobic digestion is frequent in small WWTPs. 2.1.2.1 Microbiology and Biochemistry of Anaerobic Digestion Anaerobic digestion depends on syntrophic activity between groups of bacteria and archaea. Bacterial enzymes hydrolyze organic particles outside of the cell membrane such as proteins, lipids and polysaccharides into simple sugars, amino acids and long chain fatty acids (LCFA) to facilitate transport across the cell (Figure 2.1). The same group of bacteria ferment the products to butyrate, propionate, acetate and H2 during acidogenesis. During anaerobic oxidation process, acidogenic bacteria convert the LCFA and VFA to acetate and H2. Finally, aceticlastic and hydrogenotrophic methanogens convert acetate and hydrogen to carbon dioxide and methane. Obligate syntrophic metabolism occurs when groups of organisms rely on each other to uptake inhibitory metabolites in order to continue consuming substrate. VFAs and hydrogen are both substrate and inhibitory compounds to methanogenic archaea, therefore the rate of production must balance with the rate of consumption. High H2 partial pressure (> 104 atm) prevents H2 from accepting electron from the conversion of VFAs and LCFA to acetic acid, so the production stops. H2 being the electron source for methane production, the uptake of H2 by methanogens allows the production to continue. Methanogens also rely on the fermentative bacteria to supply carbon in the form of acetate or CO2 (Grady et al., 2011). 29 Figure 2.1: Biochemical pathways of anaerobic digestion Copyright Taylor and Francis Group, LLC © 2011 from Biological Wastewater Treatment by C. P. Leslie Grady, Jr., Glen T. Daigger, Nancy G. Love and Carlos D. M. Filip. Reproduced by permission of Taylor and Francis Group, LLC, a division of Informa plc. 2.1.2.2 Operational Parameters Volatile fatty acids belong to the carboxylic (COOH) acid group. The main VFA produced in AD are acetic acid (CH3COOH), propionic acid (CH3CH2COOH) and butyric acid (CH3CH2CH2COOH). Other less significant organic acids produced are valeric acid (CH3(CH2)3COOH), lactic acid (CH3CHOHCOOH), formic acid (HCOOH), and caproic acid (CH3(CH2)4COOH) (Gerardi, 2003). These compounds originate from the partial oxidation of substrate during cell respiration because of fermentation. Fermentation is a biochemical process that occurs in many organisms such as yeast, bacteria and animal cells. During fermentation, the conversion of organic carbon to energy can be sustained even in the absence of more energetically favorable electron acceptors such as oxygen, nitrate and sulfate (Willey et al., 2011). Complex biodegradable particulates Proteins and carbohydrates Lipids Amino acids and simple sugars Long chain fatty acids Volatile acids Acetic acid Hydrogen Methane Fermentation Anaerobic oxidation Hydrolysis Acidogenesis Methanogenesis 30 The first step of fermentation is hydrolysis. Proteins, lipids and polysaccharides are hydrolyzed by enzymes and converted to smaller molecules to facilitate transport across cell membranes. Once inside the cytoplasm, long carbon chains in fatty acids and lipids are converted to acetyl-CoA, a precursor metabolite, by the β-oxidation pathway. Bacteria ferment amino acids using many different mechanisms. The Stickland Reaction can oxidize amino acids, such as leucine, alanine, isoleucine, phenylalanine, histidine and tryptophan. First, the amino group is removed from the amino acid by deamination and produces pyruvate which is then converted to acetyl-CoA. Two molecules of nicotinamide adenine dinucleotide (NADH) are generated as a result. NADH are oxidized to NAD+ by two other amino acids that act as electron acceptors and are converted to organic acid in the process (i.e. acetate) (Junghoon et al., 2014; Willey et al., 2011). Polysaccharides are hydrolyzed and phosphorolyzed by enzymes into monosaccharides and are converted to a form that is compatible with their usual metabolic or catabolic pathway. One of the most important pathways for cellular respiration is the Embden-Mayerhof pathway, also called the glycolysis cycle, and it takes place in the cytoplasm of eukaryotes and prokaryotes. The pathway is reversible as well. Glycolysis of 1 glucose molecule generates a net 2 adenosine triphosphates (ATPs), 2 molecules of water, 2 molecules of pyruvate and 2 molecules of NADH. However, in the absence of oxygen, NADH cannot be converted back to NAD+ and the cycle is disrupted. During fermentation, some of the pyruvate or a derivative of pyruvate is used as an electron acceptor for the oxidation of NADH to NAD+ and generates organic acids as by-product. The type of organic acid produced depends on the microbial species present and the substrate (Willey et al., 2011). In AD, VFAs are in turn consumed by methanogenic archaea to fuel their metabolism and replicate. An accumulation of VFA in the digestate is an indicator of process imbalance. The instability may be caused by inhibition of the methanogenic archaea by environmental stress (i.e. abrupt temperature or pH change), a sudden increase in OLR or the presence of cytotoxic compounds. It is important to monitor VFA 31 concentrations with regular analyses of the AD reactor because the relative change in VFA concentrations is a reliable indicator of process stability (Ahring et al., 1995). Total alkalinity is the measure of the pH neutralizing capacity of the digester content (digestate). It depends on the presence of carbonate, bicarbonate, hydroxide, ammonia, ammonium, phosphate and silicate content in addition to earth metals (Gerardi, 2003). It is measured as calcium carbonate equivalent (mg as CaCO3/L). As fermentative bacteria produce VFAs, the alkalinity present reacts with the acids and generates salts. Once methanogens convert the VFA ions to methane and carbon dioxide, alkalinity is released. Degradation of amino acids produces NH3/NH4+ which also increases the total alkalinity in the liquid. For this reason, additional alkalinity to the AD reactor is usually not necessary but is sometimes employed to prevent pH drop when the OLR is higher than normal and to neutralize the rapidly forming VFAs. However, the addition of buffering agents may cause salt toxicity in the reactor and lead to complete inhibition of the AD (McCarty and McKinney, 1961). pH is a measure of concentration of hydrogen ions in power of hydrogen. Fluctuations in pH are an indicator of process instability, such as an accumulation of VFA and insufficient alkalinity, indicating that methane formers are stressed. Generally, the pH should be near neutral (pH 7.5) but AD was found to occur at pH 6 – 8.3 (Angelidaki and Sanders, 2004). By itself, pH is a poor indicator of process stability because the pH response to the stress is too slow and generally, once the pH starts to vary, the process is already failing (Ahring et al., 1995). Total solids (TS) and volatile solids (VS) measured are estimates of the biodegradation potential of sludge. Although they do not identify the specific contents of the sludge, they are rapid and inexpensive measures to assess the operation of the digestion process. For instance, the degree of sludge mineralization in an AD can be estimated using percent difference in VS of 32 the substrate sludge (influent) and digestate (effluent). VS concentration is often used as an estimate of the degradable organic fraction in the sludge although it encompasses recalcitrant organics as well. Therefore, volatile suspended solids (VSS) is often used to estimate the microbial fraction of the sludge. TS/VS are most useful when comparing time trends of sludge from similar processes. Percent TS is an accurate measure of the water content of the wastewater sludge, which informs on the performance of the process, for instance the clarifier, dissolved air flotation system and dewatering equipment. Moreover, TS/VS is a standard method used around the world and the majority of peer-reviewed research articles standardize results by weight or percent of TS and VS. For example, specific methane production (mL-CH4/g-VS), biomass yield (g-VSS/g-COD), sludge to inoculum ratio (g-VS/g-VS) and solids removal (%TS, %VS, VS/TS or VSS/TSS) (Metcalf & Eddy, 2014). Chemical oxygen demand is an indicative measurement of sludge strength. In the laboratory, the sample is mixed with a strong oxidizing agent, which destroys carbon bonds in organic matter and generates carbon dioxide. However, COD overestimates the degradable material in an anaerobic digester since it also measures recalcitrant organic material that may require more than one SRT to biodegrade. It is important to mention that COD measured could include any carbonaceous media added to a digester such as plastic, graphite, carbon fiber, activated carbon, wood ash and biochar. COD is particularly useful to characterize the strength of dilute samples with soluble compounds like volatile acids and alcohols because they are inaccurately measured using the TS/VS analysis. Samples are filtered with 0.45 μm membrane filter to measure the soluble COD fraction (SCOD) which gives an estimate of hydrolysis performance. COD or total COD (TCOD) is standardly used in the field when expressing OLR (kg-COD/m3d), degradation extent (% COD) and solubilized fraction (SCOD/TCOD) (Amani et al., 2010; Droste, 1997; Metcalf & Eddy, 2014). 33 Ammonia is generated by amino acid degradation and its concentration varies depending on the sludge source. For anaerobic digesters fed with municipal sewage sludge, ammonia toxicity is a limiting factor for more efficient methane production, especially at thermophilic temperatures. Mineralization of organic matter generates free ammonia (NH3) and its ionized form ammonium (NH4+). They are the main inorganic nitrogen species present in wastewater sludge and their respective concentrations will depend on solution pH and temperature. The NH4+/NH3 equilibrium shifts towards NH3 as pH and temperature increases, which is more cytotoxic than NH4+. Sprott & Patel in 1986 suggested the reason for inhibition was from free ammonia diffusing into the methanogen’s cell membrane and causing imbalances in cation concentrations thus impeding metabolism (as cited by Chen et al., 2008). For this reason, thermophilic AD are more prone to ammonia toxicity (Sung and Liu, 2003). High concentrations of ammonium (> 7 g NH4+-N/L) was found to favor hydrogenotrophic metanogenesis over acetoclastic methanogenesis which explained the observed accumulation of acetate in the digesters as a result of ammonia toxicity. Synergistic and antagonistic inhibitory interactions inside reactors can have strong effects on microbial activity and related methane production (Chen et al., 2008). The most important being the synergy between sulphide and ammonium, removing sulphide decreases the potency of ammonium. The same happens between calcium and ammonium ions and sodium ions. In addition to monitoring inhibitory conditions in the AD reactor, measuring concentrations of ammonia in the digester supernatant may be required to control the nitrogen loading rate that is recycled back to the start of the treatment process. Indeed, the sludge supernatant, very high in nitrogen, can overload the biological nutrient removal process and cause plant upsets. This is a major problem in areas with sensitive ecosystems and strict regulations for effluent nitrogen concentrations (Eskicioglu et al., 2018). 34 2.1.2.3 Biochemical Methane Potential Assay Biochemical methane potential (BMP) is a laboratory test procedure meant to evaluate the biodegradability of a substrate. It is analogous to the better-known biological oxygen demand test performed to evaluate the strength of a substrate in an aerobic system. Owen and colleagues (1979) first developed the BMP technique as a rapid and inexpensive method of determining the effects of a substrate and inhibitors on AD. Other researchers have modified the method over the years and have been attempting to standardize the procedure (Filer et al., 2019; Holliger et al., 2016). The general procedure is summarized in this section. The inoculum sludge and substrate are added to serum bottles at a pre-determined ratio based on VS content, preferably in triplicates. The pH and alkalinity are adjusted to obtain a neutral pH and an alkalinity greater than 4 g/L as CaCO3. Nutrients may be supplemented to support microbial growth if pure carbonaceous substrate is used as opposed to primary or secondary sludge. The bottles should be purged with gas (usually N2) to remove oxygen, and then capped and incubated at the same temperature as the digester that supplied the inoculum. It is recommended to acclimatize the inoculum sludge to the substrate type and to withhold substrate feeding to the inoculum reactor for 3 – 7 days prior to conducting the BMP experiment. The biogas should be measured frequently using a manometer or by volume displacement. A gas chromatograph measures the composition of gas. Each experiment should include a positive control with inoculum and pure substrate (i.e. acetic acid, cellulose, glucose) to evaluate the performance of the inoculum sludge. In addition, a negative control with only inoculum sludge should be conducted to evaluate biogas production resulting from degradation of inoculum (Angelidaki and Sanders, 2004; Filer et al., 2019; Holliger et al., 2016; Raposo et al., 2011). Disparities exist in the published research in the methods used to measure biogas volume, frequency of biogas composition measurement, type of pH adjustment and setup of positive and negative controls. It would be difficult for laboratories to use a single method for BMP tests so it is important to understand which factors influences the outcome of the tests and 35 which are insignificant. The results of an inter-laboratory study involving 19 participating laboratories clarified the importance of each factor (Raposo et al., 2011). The factors that had no significant influence on the BMP test were inoculum source and concentration, working volume, stirring and headspace gas used for initial purging. The results from BMPs with and without pH and alkalinity adjustment and mineral medium (nutrients) addition were comparable. These elements were probably not significant in this study because the sludge to inoculum ratio (SIR) was low (0.3, 0.5 and 1.0 g-VS/g-VS) and the inoculum sludge provided enough nutrients and alkalinity. SIR was a significant factor influencing the rate of methane production and to a lesser extent total yield. The authors recommended choosing a low SIR for experimental reproducibility. Similarly, temperature of incubation (thermophilic versus mesophilic) had no influence on total methane yield but affected the rate of methane production. Finally, the main factor to influence the BMP yield was the quantification of gas and measurement system. Nevertheless, the results compounded from all 19 laboratories achieved a 10% precision (Raposo et al., 2011). Therefore, it is important when reporting BMP experiments to provide a detailed description of the methods used and results from positive and negative controls to ensure reproducibility and to help the audience comprehend the results. 2.1.2.4 Interspecies Electron Transfer In recent years, with the advancement of DNA sequencing technology, the microflora involved in the digestion of organic material has gained interest and led to fascinating discoveries and new opportunities of improving the digestion process. Fermentation of VFAs and alcohols by syntrophic organisms releasing electrons which are used to reduce H+ to H2. Hydrogenotrophic methanogens oxidize the hydrogen gas to reduce carbon dioxide to methane gas. The hydrogen acts as an electron carrier that is transferred from one species to another by diffusion. The transfer of electrons by hydrogen or formate is considered rate-limiting factors in methane production because it requires multiple enzymes and several steps. Direct interspecies 36 electron transfer (DIET) is an alternative to using the diffusive electron carriers (i.e. formate or hydrogen) and occurs via three mechanisms as illustrated in Figure 2.2 using conductive pili and electron transport proteins and conductive material (Park et al., 2018b; Zhao et al., 2017). Cytochromes are proteins that can transfer electrons by oxidation-reduction in an electron transport chain. For example, hemeproteins are cytochromes that transfer electrons by the oxidation-reduction of iron. C-type cytochromes, OmcS, are abundantly distributed on pili of Geobacter sufurreducens (G. sulfurreducens) (Cheng and Call, 2016). Conductive pili are proteins with metal-like conductivity features. Conductive pili were found to allow electron transfer between syntrophic organisms in a co-culture of G. metallireducens and G. sulfurreducens where the electron acceptor had an altered gene that prevented any hydrogen consumption. Moreover, G. sulfurreducens was naturally unable to use formate as a source of electrons. Transmission electron micrograph images showed the two species of bacteria formed aggregates with conductive pili and cytochrome networks (Summers et al., 2010). The same research group later provided evidence that electrons could also flow from one species to another through conductive material when the genes responsible for pili and cytochromes proteins were deleted. SEM images showed the syntrophic bacteria in the co-culture were scattered on the surface of the conductive media and formed electrical connections with it. In addition, the addition of conductive media, granular activated carbon (GAC) in that case, to cultures with aggregates performing electron transfer through pili increased the methane production rate by 250% compared to controls without GAC (F. Liu et al., 2012). Similar studies, with co-cultures of genetically engineered Geobacter, suggest that electron transfer without conductive pili or cytochromes can occur with biochar, carbon cloth and graphene (Chen et al., 2014b, 2014a). Other studies have shown DIET could increase AD efficiency by reducing the lag time, increasing the methane production rate, total methane yield and resistance to inhibitory compounds in co-culture AD using pure substrate (Park et al., 2018a). However, direct evidence of DIET in mixed cultures from environmental samples is challenging because of the complexity 37 and diversity of biochemical pathways occurring within the digester, many of which have yet to be studied (Park et al., 2018b). Nonetheless, the same benefits attributed to DIET were observed in experiments on AD using pure substrates inoculated with a mixed culture supplemented with biochar and magnetite (Baek et al., 2016; Luo et al., 2015). In the study with biochar, none of the species associated with performing DIET were found in the genomic analysis. The authors suggested other species may be capable of DIET or different metabolic pathways that coincidentally lead to similar results (Luo et al., 2015). In other words, researchers studying mixed cultures should remain cautious in attributing to DIET outcomes that are similar to those reported in DIET studies using co-cultures. Figure 2.2: Diagram of the three types of interspecies electron transfer Mechanisms of (A) indirect interspecies electron transfer (IIET) via hydrogen, (B) biological direct interspecies electron transfer (DIET), and (C) conductive material-mediated DIET. Reproduced from Baek et al. (2018) under Creative Commons CC BY 4.0 license. For AD applications, Zhao et al. (2017) suggested using simple substrates to promote DIET for AD by adding a hydrolysis and fermentation phase to generate high concentrations of acetate and other VFAs because Geobacter cannot degrade complex organic molecules. The 38 most abundant genus of methane formers, Methanosaeta and Methanosarcina, have the capacity of exchanging electrons via pili and conductive material (F. Liu et al., 2012). 2.1.2.5 Two-Phase Anaerobic Digestion Decomposition of waste activated sludge is slow because of complex macromolecules, mainly intra-polymeric substances (IPS) contained within tough cell walls and extra-polymeric substances (EPS) in the floc structure. Hydrolysis is considered the rate-limiting step in the decomposition of macromolecules to biogas. Extended hydrolysis periods increases the SRT requirement in the digester resulting in large and inefficient reactors (Neumann et al., 2016). Pre-treatment increases the rate of hydrolysis by breaking apart cells mechanically and chemically, by oxidizing complex molecules to simpler ones and by increasing the rate of enzymatic activity. Examples of pre-treatment processes are grinding, centrifugation, ultrasound, microwave, thermal, high pressure thermal, alkaline treatment and oxidation (hydrogen peroxide, acids, alkali, ozone) (Carlsson et al., 2012; Carrère et al., 2010; Eskicioglu et al., 2008; Neumann et al., 2016). Physical methods require sophisticated equipment and electrical energy. Chemical treatment implies constant costs for transport of the products or for the energy needed to generate the chemical on-site (i.e. ozone). There are also health and environmental risks associated with the handling and storage of chemicals at WWTPs. Thermal pre-treatment is popular because the energy necessary for heating may be supplied by the biogas generated from the methane phase reactor. The boiler system used for pre-treatment is the same used to heat the methane-phase reactor. Therefore, capital costs of upgrades can be minimized by retrofitting existing digesters. The heat from the pre-treatment vessel can heat the subsequent conventional mesophilic (30 - 38°C) digester directly or with a heat transfer system. Thermally pre-treated AD systems have the capacity to produce more energy than required for the process, which was confirmed in full-scale WWTPs (Neyens and Baeyens, 2003). In some cases, the gain in biogas production from thermal pre-treatment is less than the extra energy 39 required to heat the system. On the other hand, an efficient use of low quality energy remains unnecessary as long as WWTPs waste (flare off) the excess biogas they produce (Carrère et al., 2010). Although the main objective of pre-treatment is to decrease SRT and increase methane production without compromising the digester’s stability, increased pathogen inactivation, dewaterability and COD degradation are also sought after benefits (Pilli et al., 2014). Most single-stage mesophilic (35 - 38°C) AD reactors cannot achieve the level of pathogen inactivation required to classify as Class A biosolids (Han and Dague, 1997). As was discussed in section 2.1.1.4, at temperatures above 50°C, the required HRT for heat treatment decreases exponentially with increasing temperature such that a pre-treatment HRT of only 30 minutes would be required at 70°C or higher to achieve fecal coliform concentrations less than 1000 MPN/g-TS (Organic Matter Recycling Regulation, BC Reg. 18/2002). Dewaterability is measured by capillary suction time and directly relates to the volume of biosolids that will need to be transported off-site. A digestate with a high capillary suction time will take more time and energy to dewater and result in biosolids with lower solids content (more water). EPS is a slime surrounding cells composed of polysaccharides, proteins, glycoproteins, humic substances and lipids that entraps water. IPS have similar composition and are released during cell lysis. IPS and EPS are responsible for the poor dewaterability of sludge (Neyens and Baeyens, 2003). High temperature increases solubilization of organic matter that forms the EPS and IPS and improves dewaterability. For WAS, there is a linear increase in solubilization as temperature rises from 90 - 190°C but duration of treatment has low impact. Also, the solubilization by heat treatment is higher for less biodegradable WAS than for readily biodegradable WAS (Carrère et al., 2008). At temperatures of 165 - 180°C, dewaterability, methane production and odor reduction of WAS are the highest according to the literature reviewed by Neyens and Baeyens (2003). The aqueous phase of the sludge exist in bond water and free water. The bond water is held inside the cells and onto the surface of cells by adsorption with polysaccharides, nucleic acids, proteins and functional groups of the EPS. Polar groups bind particularly strongly with 40 water. The particles form an electrically charged double layer and bonds to water molecules (Katsiris and Kouzeli-katsiri, 1987). Heat pre-treatment (60 - 180°C) disrupts the double layer by degrading the lipids, polysaccharides and proteins from the cell surface, which destroys the cell wall releasing the bond water and increases dewaterability of the sludge. Therefore, the higher the temperature above 150°C, the better the removal of the free and bond water from the EPS, which enhances dewaterability. Solubilization of WAS increased by 40 – 60% at pre-treatment temperature of 170°C and methane production increased by 60 – 70% at 175°C. However, above 175°C, refractory compounds tend to form and can have inhibitory effects on methane production in the AD reactor (Neyens and Baeyens, 2003). Thermal pre-treatment, can be a biological process at temperatures around 70°C and below. 2.1.2.5.1 Temperature Phase Anaerobic Digestion Temperature phase anaerobic digestion (TPAD) is a biological thermal pre-treatment process. The fermentative acid generating phase occurs in a separate tank at a short SRT (1-3 days) heated at thermophilic (50 - 70°C) conditions. In the first stage of the TPAD system, organic molecules such as proteins, lipids and polysaccharides are first hydrolyzed and then rapidly converted to fatty acids, amino acids and simple sugars by acidogenic bacteria. The production of VFA consumes the alkalinity present in the reactor and causes the pH to decrease to approximately pH 5.5 – 6.8. The alkalinity is restored once the VFAs are converted to methane (Gerardi, 2003). Ge et al. (2010b) noticed in their experiment that an increase in temperature of 50°C to 60°C led to an increase in acetic acid production but higher temperatures did not result in any further increase in VFAs. Interestingly, propionic acid production and total VFA was inhibited by 50% by low pH (4.5) when HCl was added to the acid-phase (65°C, 2 d). Solubilization of organics increased with every increase in temperature tested. Temperatures above 50°C in the first stage improves the rate of hydrolysis by increasing enzymatic activity (Carrère et al., 2010). For the methane forming stage, mesophilic (35 - 38°C) 41 conditions are generally chosen to reduce energy input requirement and higher process stability. The hydrolysis improvement in pre-treatment varies with the type of substrate sludge. Ge and colleagues (2010a, 2010b) found an optimal rate of hydrolysis for primary sludge at 50°C, but minimal further increase above that temperature. For WAS, there was a significant increase in the rate of hydrolysis with each increase in temperature at 60, 65 and 70°C but no increase at 50°C compared to the control operated at 37°C. These results translated to improved VS removal (improvement of 20 – 25% for primary sludge and 11 – 30% for WAS) compared to mesophilic control (VS destruction 40 - 45%), and were consistent with previous work on a thermophilic (55°C) - mesophilic (35°C) TPAD reactor with SRTs of 10 - 15 days by Han and Dague (1997). They measured an 18% increase in VS destruction and 16% increase in methane production compared to the single stage mesophilic control (VS reduction of 32.5 – 46.8%) operating at the same SRT range. The two stage system process does not affect the pH, VFA and alkalinity of the methane phase digester significantly when compared to single stage process (Han and Dague, 1997; Nazyab, 2018). Nazyab (2018) reported no improvement in methane production from mixed sludge in thermophilic (70°C, 2 d) – mesophilic (38°C, 30 – 15 d) TPAD and only a marginal improvement in VS reduction (2.9%). Nonetheless, at all SRT tested (15, 20, 30 days), the VS reduction achieved was 61 – 64% in both TPAD configurations and in the single-stage mesophilic control. Therefore, there was less possible gain in VS destruction than in other studies. The thermophilic (55°C, 2 d) – mesophilic (38°C, 28 – 13 d) TPAD resulted in an increase in methane production of 5.6 – 14.7% compared to the single-stage mesophilic control reactor. Both the thermophilic (55°C, 2 d) and the thermophilic (70°C, 2 d) acid-phase reactors resulted in an increase in SCOD/TCOD of roughly 50%. The 55°C acid-phase generated 55% more total VFA than the mixed sludge, whereas the 70°C acid-phase had merely 8% more total VFA than the mixed sludge. Dewaterability and pathogen inactivation was also higher in the thermophilic (55°C, 2 d) – mesophilic (38°C, 28 d) configuration, which was attributed to the higher acidification state of the sludge (Nazyab, 2018). As observed by 42 Bolzonella et al. (2012) acidification level is highly variable and depends to a large extent on the operating parameters and type of sludge. TPAD reactors have been operated successfully at full-scale in industrial and municipal WWTP applications since many years, although it is difficult to determine how many are currently in function. In 2006, the United States of America’s Environmental Protection Agency (EPA) listed nine in their publication ‘Biosolids Technology Fact Sheet, Multi-Stage Anaerobic Digestion’ and six WWTPs located in the USA were described in a case study. The main reasons stated for upgrading existing systems were control of excessive foaming, odor control, production of Class A fertilizer and increase sludge loading capacity (decrease SRT) and VS reduction. All TPAD systems were retrofits of old single-stage digesters. The upgrade to TPAD allowed all systems to achieve EPA Class A biosolids and, of the four that reported a VS reduction, all were around 65%. In addition, upgrade to TPAD solved odor and foaming issues. TPAD configuration can help control foaming because the filamentous bacteria that traps the gas bubbles are intolerant to the low pH present in the acid phase. The study reports a price of US$9.39 – US$51.50 per dry ton based on maintenance and operations costs for TPAD systems. Two facilities, Ontario (California, USA) and Tacoma (Washington, USA), reported the cost of the retrofitting old digesters were US$2.5 million and “very low”, respectively (Wilson et al., 2006). In summary, TPAD systems can improve solubilization of organic matter by increasing the rate of hydrolysis and VFA production, which result in higher VS destruction, methane production, Class A biosolids and lower detention times in the reactors. The TPAD system may be easily retrofitted from existing digesters and offer better operational control than single-stage reactors for each step involved in the biochemical process of anaerobic digestion. Disadvantages of TPAD systems include higher energetic demand and more piping and pumps. 43 2.1.3 Conductive Material Evidence from genetically engineered organisms in co-cultures suggested DIET and syntrophic metabolism occur more efficiently with the addition of conductive material, although the electron transfer mechanisms between cells are poorly understood (Zhao et al., 2015). Carbonaceous material such as GAC, powdered activated carbon (PAC), carbon cloth, carbon felt, carbon brush, and graphite are good candidates for electron flow because they are electrically conductive, have a high surface area, are non-biodegradable and durable (Mumme et al., 2014; Park et al., 2018a; Zhao et al., 2015). Bioelectrodes for bioelectrochemical systems are part of another active area of research that investigates the electrical conductivity of material but with the goal of harvesting electricity. To measure the efficacy of the electrode material, microorganisms and substrate are placed in a compartment with an anode under anaerobic conditions and the oxidizing agent is located in a separated compartment with a cathode. The compartments are divided by a cation exchange membrane (Eskicioglu et al., 2018). Volumetric current density is defined by the amount of current generated by volume of material and it increases as the specific surface area of the material increases. The volumetric current density generated by the microorganisms attached to the anode is a direct measurement of the biological electron transfer performance of the electrode material (Xie et al., 2015). According to the literature reviewed by Xie and coworkers (2015), carbon felt electrodes could achieve a maximum current density of 6 kA/m3, carbon nanotube textile 7.2 kA/m3, activated carbon fiber network 2.7 kA/m3, activated carbon nanofibers 2.7 kA/m3, graphite brush 1 kA/m3 and graphite granules 250 A/m3. In a study comparing pine wood biochar, graphite granules and GAC electrodes, the power output for each was 457 ± 20 mW/m2, 566 ± 5 mW/m2 and 674 ± 10 mW/m2, respectively (Huggins et al., 2014). In the following sections, the most promising conductive materials are compared based on cost, environmental sustainability, availability and the advantages and inconveniences of 44 adding each material to an AD reactor. Their efficacy in enabling DIET will be reviewed from the latest literature. Nanomaterials such as carbon nanotubes may enhance DIET but were excluded from this review because of the concern for possible impacts on receiving ecosystems and human health because of land application of biosolids (Li et al., 2014). 2.1.3.1 Magnetite Magnetite (Fe3O4) is frequently found in soil and in sediments and is abundantly found as rock mineral. It is naturally produced by Fe(III)-reducing microorganisms in the environment from the oxidation of organic compounds using Fe(III) as the final electron acceptor. Magnetite nanoparticles were found to facilitate electron transfer between Geobacter sulfurreducens and Thiobacillus denitrificans (Kato et al., 2012). The electron transfer process was identified by deleting the genes for pili and OmcS in two syntrophic strains of Geobacter and incubating them in a co-culture. Strains with deleted genes for pili were unable to transfer electrons between organisms even in the presence of magnetite. When G. sulfurreducens with deleted gene for OmcS was incubated with electron acceptor Fe(III) oxide, only the cultures supplemented with magnetite were able to reduce Fe(III) oxide. The magnetite replaced cytochromes OmcS in short range electron transfer between pili and the electron acceptor. When magnetite was added to wild type cultures (non-genetically modified), the cells decreased expression for the OmcS gene, probably using magnetite as an electron mediator instead of cytochromes to save on the energy needed to synthesize OmcS cytochromes (Liu et al., 2015). Results from research on the AD of cheese whey substrate using mixed cultures from a sewage AD reactor supplemented with 100 – 700 nm magnetite resulted in 107% improvement in methane production and 20% increase in biogas methane content (Baek et al., 2016). In another study, the presence of granular (8 – 12 mm) magnetite significantly increased the abundance of dissimilatory iron reducing bacteria and the rate of hydrolysis in a lab scale AD treating WAS. These results were attributed to the degradation of complex organics and cell walls by iron 45 reducing bacteria that may have been using magnetite as electron acceptor for the reduction of dissimilatory Fe(III) (Peng et al., 2018). So far, there is limited evidence of long range electron transfer between syntrophic bacteria and methanogenic archaea using magnetite. Magnetite is an inexpensive product (approximately 1$/kg on the market) and is widely available. In an AD reactor, its magnetic properties could be exploited to harvest microorganisms by removing magnetically the magnetite particles from the liquid. However, all magnetite available commercially is mined. Therefore, the resource is considered non-renewable and would have a net positive carbon footprint because of emissions from processing and transportation. 2.1.3.2 Graphite and Carbon Fiber Material Graphite is a carbon crystal composed of flat sheets of six carbon rings and each carbon has a covalent bond with three other atoms of carbons. The fourth electron on the outer shell of the carbon molecule is delocalized and free to carry current. Graphite is very stable at atmospheric conditions and can be manufactured from carbonaceous material at relatively low pressure and temperature. Graphite is also found in rock minerals throughout the world (Shabalin, 2014). Carbon fiber materials, which include graphite, come in a multitude of designs such as fabrics, granules, plates and rods. To make fibers, a precursor polymer is spun into a filamentous yarn. The yarn is then carbonized at high temperature (1500 - 3000°C) leaving a carbon filament with molecules arranged in a hexagonal graphite plane. The heat treatment under inert gas volatilizes the non-carbonaceous elements from the polymer. Graphite contains carbon arranged in a plate of six carbon rings that becomes shaped in a column when fibers are formed (Park and Heo, 2015). Most polymers used for fabrication are derived from petroleum sources, mainly polyacrylonitrile and pitch, and are non-renewable. However, recycled polymers can also be used but the process is more expansive (Leitten et al., 2002). Electrical resistance of graphene, nanofibers and quasi-single crystalline graphite is 1 x 10-8, 0.6 – 1.4 x 10-6 and 5.2 46 × 10−5 Ω m, respectively (Shabalin, 2014). For efficient interspecies electron transfer, surface area and conductivity are the most important factors when considering the shape of the carbon material. Carbon cloth, felt and foams are made from the same material and have high surface area, which is favorable for biofilm attachment. The first study that found carbon cloth could promote DIET was conducted on a co-culture of G. metallireducens and G. sulfurreducens with ethanol and fumarate. The mechanism for electron transfer was identified by deleting the gene for pili expression in both species. Ethanol was metabolized to succinate in the co-culture with carbon cloth but not with cotton cloth. Moreover, the co-culture of mutant strains with carbon cloth performed nearly as well as the wild strains (Chen et al., 2014b). A study by Dang and coworkers (2016) compared the effects of amending carbon cloth, carbon felt, GAC (0.841 – 2.38 mm), graphite rods (13 mm x 12 mm) and polyester cloth in lab-scale anaerobic reactors based on their resilience to increased OLR and time required to recover from sour conditions (VFA > 100 mM, pH < 6, CH4 production < 43%). Reactors were inoculated with sludge from a WWTP and fed with substrate prepared using commercial dog food. Overall, there was only a slight difference between the volumes of methane produced from each reactor. The reactor amended with GAC was the most resilient to high OLR and recovery took the shortest time, followed by carbon cloth, carbon felt, polyester cloth, graphite rods and control (no amendment). The control reactor and the reactor with graphite rods poorly recovered from the sour conditions. DNA extraction and sequencing was conducted on the carbon cloth biofilm and suspended sludge as well as on the polyester cloth biofilm and sludge in suspension. The genera Sporanaerobacter, Enterococcus and Methanosarcina were particularly enriched on the carbon cloth (Dang et al., 2016). As previously discussed, studies involving wild mixed cultures of inoculum can only rely on indirect evidence that DIET is the leading biochemical mechanism occurring. In addition, the species present only offer clues as to which may be participating in DIET. Future research with cultures of Sporanaerobacter and Enterococcus species may determine if they have the capacity to transfer electrons to Methanosarcina through DIET. 47 Nevertheless, carbon materials, with the exception of graphite rods, were beneficial for the degradation of complex organic matter under high OLR and provided a suitable surface area for syntrophic microorganism growth (Dang et al., 2016). In a similar study, Barua et al. (2018) also measured a 46% increase in methane production in the AD reactor amended with carbon fiber compared to the control reactor fed with butyric and propionic acid substrates. Carbon fiber materials are a promising technology for improvement of methane yield in digesters because of their stimulatory effects on microorganisms. The main advantages of carbon materials are their design versatility and physicochemical properties. Moreover, carbon fibers are non-biodegradable and have low contents of contaminants. Carbon materials are expensive because of the high-energy requirements for their fabrication so they would be best suited for reactors designed with media retention. Activated carbon is another type of carbon based material that has performed very well in DIET experiments, but it is produced differently from carbon fibers and has different properties. 2.1.3.3 Activated Carbon Activated carbon (AC) plays an important role in water and wastewater treatment because of its adsorptive properties. It can be produced from any biomass but the most common materials are wood and bituminous or lignite coal. The material is first pyrolyzed to temperatures of 500 - 800°C and then activated with steam or CO2 at temperatures of 850 - 1000°C. The lack of oxygen prevents the organic molecules from oxidizing, instead, the heat breaks apart chemical bonds resulting in the production of volatile organic compounds, tar liquid and carbon rich solid particles. During the process, the carbon molecules in the particles form crystalline structures of aromatic sheets stacked in random patterns with free space in between called free interstices. This matrix is very porous and stable (Chowdhury et al., 2013). The activation step further increases the porosity of the material, enlarges the pores and removes the material that may have accumulated inside the pores such as tar, which results in a high 48 surface area to volume ratio. Typically AC is composed of 88% carbon, 6% oxygen, 1.0% sulfur, 0.5% hydrogen, 0.5% nitrogen and 4% minerals (Bansal and Goyal, 2005). The adsorption properties of the AC is due to those disordered flat aromatic ring structures forming pores and to the presence of surface functional groups composed of hydrogen, oxygen, nitrogen and phosphorus. Examples of functional groups are lactones, ketones, carboxyls, amines, phosphates, phenols and ethers (Gun’ko and Bandosz, 2003). The type of functional groups affect the characteristics of the AC, such as acidity, polarity and wettability. Functional groups with oxygen and hydrogen are the most important influencers of the physio-chemical characteristics of the AC. For instance, carboxyls, lactones and phenols are associated with acidic surface groups that are also polar and hydrophilic. Characterization and identification of surface functional groups are difficult because the behaviors of the compounds are different when associated with the AC matrix. The shape of the pores can vary tremendously even on a single particle (Bansal and Goyal, 2005). Pores are categorized into three diameter sizes, micropores (< 2 nm), mesopores (2 – 50 nm) and macropores (> 50 nm). The AC is commercially available in two particle sizes, powdered (0.01 – 0.03 mm) and granular (0.6 – 3.0 mm). In general, AC has a porosity of 0.5 – 0.8 (volume/volume) and a surface area of 500 – 1,200 m2/g (Chowdhury et al., 2013). The majority (roughly 95%) of the surface area is attributed to micropores, whereas the rest is in the mesopores (5%) and macropores (0.04%) (Bansal and Goyal, 2005). Bacteria and archaea are greater than 1000 nm in size so AC with large macropores is most suitable for cell attachment. PAC is more advantageous for CSTR while GAC is more effective in fixed film and fluidized bed reactors because they are designed for media retention. Biological treatment of organic material using AC combines both the adsorptive capacity of GAC with biological degradation by the biofilm forming onto its surface. However, if the biofilm becomes too thick it can block the pores of the AC and considerably slow down diffusion of adsorbates. Early research on biological treatment using GAC by Voice and colleagues (1992) found that the removal of hydrocarbons from water in an aerobic fluidized bed 49 reactor using GAC colonized by biofilm was more effective than on a similar material with biofilm or on sterile GAC performing only adsorption. Moreover, the biofilm formation was much faster on the GAC than on the control material. The difference was attributed to the higher availability of nutrients to the biofilm within the pores of the GAC particles because of adsorption. Interestingly, the study found by tracking oxygen balance that the higher rate of degradation of hydrocarbons and the resilience to increases in OLR in the GAC reactor compared to control was a result of the adsorption of hydrocarbons by GAC and that biological activity was similar for both GAC and the control material (Voice et al., 1992). GAC may regenerate biologically and function like a buffer when OLR varies. Under high OLR, the GAC adsorbs organic compounds and under low OLR, the compounds desorb and diffuse into the biofilm where it is degraded (Aktaş and Çeçen, 2007; Voice et al., 1992). Two theories dominate on the mechanisms of bioregeneration, first the change in concentration gradient between the AC surface and the liquid phase because of biodegradation would cause the compounds to desorb and become available to microorganisms. However, desorption depends on the strength of the chemisorptive bonds and some compounds may show irreversible adsorption, notably if there is covalent bonding. Second, exo-enzymes released from the biofilm would degrade the adsorbates contained in the pores. Although enzymes would have limited access to micropores and mesopores because of their larger size (Aktaş and Çeçen, 2007). In the last decade, DIET between syntrophic bacteria and methanogenic archaea has been shown to occur in co-cultures of Geobacter metallireducens and Methanosarcina barkeri amended with AC. The bacteria and archaea could exchange electrons through GAC to reduce CO2 to CH4 (F. Liu et al., 2012; Rotaru et al., 2014). Indirect evidence for DIET with AC was also found in mixed cultures producing methane. The majority reported a methane production increase, reduced lag time and higher tolerance to increase in OLR (Dang et al., 2016; Lee et al., 2016; Park et al., 2018a, 2018b; Xu et al., 2015). GAC addition was particularly effective when added as carrier media in a UASBR treating landfill leachate rich in VFAs. The reactor amended with GAC media 50 achieved 70 – 90% COD removal while OLRs were gradually increased from 5.9 to 36.7 kg-COD/m3 d in a period of 130 days. On the other hand, the control reactor inoculated with UASBR granules had excessive VFA (9.5 g/L) accumulation and failed after 17 days at the lowest OLR (Lei et al., 2019). It is unclear which size ranges of particles are most favorable for AD enrichment besides PAC having a higher specific surface area and GAC being easier to retain in a reactor. Xu and coworkers (2015) found coal-based PAC (0.075 – 0.177 mm) to be more performant than GAC (0.84 – 2.00 mm) in UASBRs at producing methane under high loading rate of brewery wastewater, whereas Park and coworkers (2018b) found the opposite to be true. In batch bioassays, GAC (1.1 – 1.7 mm) performed better than PAC (< 0.1 mm). A higher specific surface area is associated with more sites for both adsorption and attachment of microorganisms. Since AC is a non-selective adsorbent, there is a possibility for it to adsorb substrates. In a mixture, which molecule will adsorb on the surface of the AC will depend on molecular sizes, physicochemical properties ( i.e. moiety, polarity and hydrophobicity) and on the surface chemistry and porosity of AC (Gun’ko and Bandosz, 2003). Amongst the literature reviewed, only Liu and coworkers (2012) reported a significant adsorption of the substrate (ethanol) by AC, although the adsorption of AD substrates such as methanol, ethanol, acetic acid, butyric acid and propionic acid have been documented for a while (Freitas et al., 2007; Gun’ko and Bandosz, 2003; Hajilari et al., 2019). AC benefits the degradation of organic waste in both aerobic and anaerobic reactors. In aerobic reactors, oxygen is the final electron acceptor so DIET contribution is probably insignificant. The mechanisms for methane production enhancement with AC are likely to involve complex dynamics between adsorption, bioregeneration, biofilm growth, microbial community structure and DIET. AC is expensive to purchase because the pyrolytic process and activation step are endothermic so they require a significant energy input. For this reason, when used for adsorption, the AC media in the filter bed is reactivated after it becomes spent to save on costs. AC could be an economically feasible media option for an AD application with a focus 51 on DIET, if a media retention or recycling step was added. The pyrolytic process has the benefit of generating bio-oil and syngas, which have high energetic value and allow some cost recovery. When biomass is pyrolyzed without an activation step, it generates a product called biochar which shares many properties with AC but is less expensive to produce and potentially more cost-effective for DIET applications. 2.1.3.4 Biochar Biochar, like activated carbon, is a product of pyrolysis. However, biochar is made exclusively from biomass unlike activated carbon, which can be made from biomass or coal, and biochar is not activated. The activation process increases the porosity by burning the tar and residues that accumulated in the pores during pyrolysis (Bansal and Goyal, 2005). Therefore, both products share similar characteristics, although biochar is generally less performant. For instance, they are both electrically conductive; have a high surface area and porosity; have complex surface functional groups; and a capacity to adsorb non-specific compounds. Despite being 1000 times less conductive than activated carbon, biochar was also found to facilitate DIET (Chen et al., 2014a). Biochar is of particular interest because it is a by-product from the pyrolysis of biomass such as agricultural waste and forestry residue. Moreover, the biochar produced is resistant to biodegradation. When produced from renewable biomass, biochar is an effective method to sequester carbon and mitigate greenhouse gas emissions. 2.1.3.4.1 Production of Biochar In Canada and in the USA, pulp and paper industries pyrolyse woody residues to produce bio-oil, gas and biochar. Pyrolysis is an endothermic reaction where biomass is heated above 400°C by an exogenous energy source without oxygen (Woolf et al., 2014). The bio-oil and volatile compounds produced during the reaction are broken down by tar cracking to produce syngas and is constituted of carbon monoxide, carbon dioxide, water vapor, methane and hydrogen gases. A part of the generated syngas can be combusted to provide heat for 52 pyrolysis and the remaining can be used as a fuel source (Jeffery et al., 2015). The structure of the carbonized wood is influenced by the pyrolytic process mainly, the heating rate, heating temperature and composition of the gas in the process (Nishimiya et al., 1998). Fast pyrolysis occurs at heating a rate greater than 10°C/s, while any lower rate is qualified at slow pyrolysis. However, a compromise must be made between the amount of energy recovered and the quality of the residual biochar in terms of specific surface area and porosity. Generally, fast pyrolysis at high temperatures produces more bioenergy, while slow pyrolysis at low temperatures produces better biochar (Jeffery et al., 2015). The phases of carbonization are important to understand how organic matter such as wood becomes electrically conductive. According to Nishimiya and colleagues (1998) the successive stages occur as follows: 1. At about 300°C, there is destruction of the crystalline structure of cellulose and generation of carbonyl groups (C=O). 2. Between 400°C and 700°C carbonyl groups are replaced by C=C and form aromatic rings that resemble graphite layers. 3. At 600°C and more, dehydration occurs where compounds containing O and H volatilize and the C/H and C/O ratios increase. 4. At approximately 800°C, there is a sharp increase in condensation of aromatic rings, which form disordered graphite layers. In this phase, there is breakage of single and double bonds between O and C and between C and C and a major increase in electrical conductivity occurs. 5. At 1,800°C and above, condensed aromatic rings form graphite structures. The loss of volatile matter is responsible for the high porosity of carbonized wood. The aromatic rings are strongly bonded by ether linkage (Pastor-Villegas et al., 1998). The delocalized electrons that characterize the aromatic rings cause the electrical conductive nature of the carbonized wood (International Union of Pure and Applied Chemistry, 1994). 53 Woolf and colleagues (2014) compared different pyrolysis configurations and found that in an optimal combination (slow pyrolysis, tar cracking and catalytic methanol synthesis) there was a minimum penalty of 21 kJ of bioenergy per gram of carbon in the biochar. According to the same authors, producing good quality biochar fertilizer leads to a loss in energy yield, which affects the market price of biochar. Promotion of biochar is necessary because pyrolytic processes are economically favorable over combustion systems only if biochar is marketable. In western Canada, Alberta Biochar Initiative (ABI) regroups governments, academics and industry working together to promote the use of biochar as an initiative to offset greenhouse gas emissions, increase agricultural sustainability and enhance soil fertility. ABI is part of the broader International Biochar Initiative (IBI) and shares the same agenda in addition to publishing standards for biochar characterization and uses as soil amendment (International Biochar Initiative, 2015). 2.1.3.4.2 Physicochemical Properties of Biochar Electrical conductivity (EC) refers to the ability of a solution to transfer electrical current. It is proportional to the amount of ions in the digestate (salinity). Inorganic compounds such as alkalis, carbonates, sulfides, chlorides and cations may originate from the wastewater sludge, added buffer, biochar material and the mineralization of organic waste. EC offers insight into possible inhibitory conditions to microorganisms such as salt stress. Cells are sensitive to changes in environmental salinity because it can cause osmotic imbalances. However, EC is indiscriminate of the types of ions whereas salt toxicity depends on the elements present and their concentrations. Testing various dosages of biochar in an AD reactor and its effect on EC is important because its mineral content will increase the concentration of dissolved solids in the liquid phase such as cation ions and may cause inhibition of organisms. Cation exchange capacity (CEC) is the measure of the affinity for a material to exchange cation and depends on the electrical charge of the material surface (Luz et al., 2018). In the 54 case of biochar, ammonium sorption relates to cation exchange with surface functional groups, which depend on the pyrolysis conditions and raw material. Competition with stronger ions present in the wastewater can decrease ammonium sorption. Porosity relates to the size and amount of pores in the biochar. Larger pores will allow faster diffusion rate and adsorption (Luz et al., 2018). The microorganisms populating the biochar will vary depending on pore size that best suits their habitat preference. Pore size is classified the same way as AC. Smaller deeper pores favor anaerobic conditions and shelter microorganisms from inhibitory compounds in the liquid phase. However, their access to nutrients and substrate is limited by the diffusion rate through the surface biofilm and the pores. The specific surface area corresponds to the available surface area per weight of material. The pyrolysis process involves volatilization of nitrogen and hydrogen compounds and creates a porous honeycomb looking structure (Luz et al., 2018). The Brunauer Emmett-Teller gas sorption theory is typically used to measure the specific surface area of biochar. Although the adsorption capacity of biochar is related to its specific surface area, it appears that surface complexity and the variety of surface functional group play a greater role (Kizito et al., 2015). Surface area increases with increasing pyrolysis temperature, notably between 450 and 1000°C. For pine biochar, the optimal final temperature range that produced the highest surface area (400 ± 1 m2/g – 420 ± 6 m2/g) was 750 - 850°C. The ramp rate and final temperature that yield the biochar with the highest surface (420 ± 6 m2/g) area was 650°C/h and 750°C, respectively (Brown et al., 2006). Zeta-potential offers insight into surface charge of the biochar particles. The zeta potential depends on the characteristics of the biochar surface functional groups and varies with pH and temperature. Biochar particles with negative zeta potential will have higher electronegativity and will adsorb positive ions. As temperature of pyrolysis increases, the 55 functional groups containing H and O decrease and zeta potential becomes less negative (closer to neutral). Therefore, the adsorptive properties of the biochar can be tied to the zeta potential with generally higher adsorption with higher absolute values of zeta potential (Hong et al., 2019). On the other hand, more negative zeta potential values are associated with colloidal particles that tend to stay in suspension because they repel each other, which decreases the settleability of the sludge. To improve dewatering, positively charged polymer can be added to neutralize surface charges and improve the release of bound water from the EPS contained in the sludge (Sun et al., 2015). Electronegative biochar may cause the polymer dosage to increase during sludge dewatering. 2.1.3.4.3 Biochar as an Anaerobic Digestion Amendment In the past decade, an increasing number of studies have reported benefits associated with the addition of biochar to AD. Improvements in methane production are associated with its high surface area for biofilm formation, adsorption capacity for ammonium, pH buffering capacity and electrical conductivity (Fagbohungbe et al., 2017). Experiments with pure substrates and co-cultures of Geobacter metallireducens and Methanosarcina Barkeri have shown that biochar was a good electron acceptor and could promote DIET between syntrophic bacteria and methanogenic archaea (Chen et al., 2014a). In studies involving wild mixed cultures, biochar improved methane production during the AD of chicken and cattle manure, sewage sludge and food waste (Cai et al., 2016; Inthapanya et al., 2012; Pan et al., 2019; Shen et al., 2016; Zhao et al., 2015). Wang, Li, Gao and Wang (2018) investigated the effect of biochar when added to AD of an activated sludge and food waste at 1:4 mixture based on wet weight with a high SIR of 1.5 g-VS/g-VS. Typically, the higher the SIR and the higher the chances of digester failure caused by accumulation of VFAs, mainly butyrate and propionate. The researchers’ hypothesis was that biochar could promote degradation of VFA through DIET. The results showed that biochar amendment decreased the duration of the lag phase, increased 56 methane production and reduced VFA accumulation compared to controls. Very few studies have been conducted on biochar addition to the methane phase of a TPAD utilizing wastewater sludge (Shen et al., 2016). High amounts of functional groups on the surface of the biochar could increase CEC and decrease likelihood of ammonia inhibition in AD. The key parameters that can improve biochar efficacy for adsorbing total ammonia nitrogen and improve methane production when added to AD are dependent on biochar pyrolysis conditions, wastewater composition and concentration of inhibitory compounds, presence of competing ions and physicochemical properties of biochar (Fagbohungbe et al., 2017). Pyrolysis and combustion of wood generate hazardous compounds that remain in the charred material, notably polycyclic aromatic hydrocarbons (PAH), dioxins, furans and trace metals. These can cause inhibition of biological treatment processes at high dosages (Hale et al., 2012; Lo et al., 2010). PAH are degradable by microorganisms in both aerobic and anaerobic conditions (Haritash and Kaushik, 2009). On the contrary, dioxins and furans are much more persistent and may also be formed and concentrated during the digestion process (Muñoz et al., 2018). The IBI biochar standard has set the maximum allowable concentration of PAH at 6 mg/kg for safe use for soil amendment and other environmental applications (International Biochar Initiative, 2015). In a study, biochar from pine wood was measured to contain 0.07 mg/kg of total PAH which tended to decrease at longer time and higher temperature of pyrolysis (Hale et al., 2012). 2.1.3.4.4 Biochar as a Soil Amendment Researchers have found evidence that residues of combustion and pyrolysis play a major role in forest eco-systems. Forests of interior Western Canada and Northwestern United States populated by ponderosa pine and Douglas fir are well adapted to cyclical fires (Deluca and Sala, 2006). DeLuca & Sala (2006) found that nitrification increased in ponderosa pine 57 forests where frequent fires occurred compared to forest that had not recently burned. In the boreal forest, the regrowth of successional tree species is stimulated by the char left from wildfires (Pluchon et al., 2014). Char may contribute to forest soil fertility by buffering the pH, increasing the water holding capacity and nutrient retention (Glaser et al., 2002). Researchers in the field of agriculture tested char as a soil amendment and found it could provide similar benefits to farmland (Ding et al., 2016). The mechanisms leading to better crop yield after application of biochar to soil can be explained by nutrient adsorption-desorption, high CEC, increased water holding capacity and soil aeration, decreased bulk density and the promotion of microorganisms growth onto the porous surface of the biochar (Jeffery et al., 2015). 2.1.3.4.5 Effect on Greenhouse Gas Emissions Applying biochar to farmland mitigates potent greenhouse gas emissions such as methane, nitrous oxide and carbon dioxide generated in soils. Metabolism of organic matter produces carbon dioxide, but the organic carbon contained in biochar derived from biomass can remain undecomposed in soil for over a hundred years (Jeffery et al., 2015). In addition to carbon sequestration, soils amended with biochar generate less nitrous oxide than soils amended with its parent biomass material (Schouten et al., 2012). Nitrous oxide is a by-product of denitrification and a potent greenhouse gas. Some studies have found adding biochar to soils amended with digestate could reduce emissions, although the mechanisms involved require more research (Jeffery et al., 2015; Martin et al., 2014). Agricultural field studies showed that methane flux is lower in soils amended with biochar possibly because its porous structure increases air content which inhibits methanogens (Karhu et al., 2011). 2.1.4 Wood Ash In the wood industry, wood ash is a waste by-product of heat and electricity production that needs to be transported offsite to be landfilled. This represents additional costs for the wood industry and there is an increasing interest in finding cost-effective and environmentally 58 sound alternatives to landfilling. Wood ash is employed in Scandinavian countries as a mean of returning nutrients to the forest soils following tree harvests and preventing soil acidification (Aronsson and Ekelund, 2004). In Canada, this practice is less common for forest soils but wood ash is used as a liming agent on farmland in certain provinces such as British Columbia. Indeed, wood ash has the benefit of containing carbonates and oxides which increase alkalinity and pH of the soil and CEC. Wood ash provides a source of nutrients for plants, notably K, Ca, Mg, Al, Fe and P. However, it may increase soil salinity levels and contaminate water bodies with toxic compounds. The application of wood ash to soil is regulated in British Columbia by the Environmental Management Act and falls under the Soil Amendment Code of Practice and the Organic Matter Recycling Regulation. The wood ash must meet criteria for heavy metal content, dioxins, furans and PAH. Moreover, there are restrictions on slope, aspect and topography of sites wood ash may be applied to (Sylvis Environmental, 2008). Biotoxic effects of wood ash on growth of phytoplankton and bacteria were reported at concentrations of 5-50 mg/L in an aquarium experiment and were attributed primarily to the liming effect. Wood ash may also contain metals with various toxicity effects in the ecosystem such as Zn, Co, Fe, As, Cr, Cd and Hg. Organic pollutants such as dioxins, furans and PAH are also found in high concentrations in wood ash. The mobility of these compounds and metals through the soil and into the water bodies are a great concern for scientists studying this topic (Aronsson and Ekelund, 2004). As mentioned previously, PAH are effectively degraded biologically, unlike dioxins and furans that do not get degraded during digestion and can bioaccumulate in the food chain (Haritash and Kaushik, 2009; Muñoz et al., 2018). Some stimulating effects of wood ash amendment on biogas production when added to AD of solid fraction of municipal solid waste and cattle slurry were documented in the literature and mainly attributed to the promotion of bacterial growth from the supply of nutrients such as Mg, P, Ca, and trace metals (Lo et al., 2010; Podmirseg et al., 2013). Yin and coworkers (2018) 59 amended bottom ash derived from incineration of WAS to lab-scale batch reactors anaerobically digesting municipal WAS. They found that a dosage of 0.9 g/g-TS increased the rate of hydrolysis of WAS and VFA degradation by 140% and 87%, respectively. They also measured a 36% increase in methane production and 32% shorter lag phase compared to controls without wood ash. Beneficial effects on VFA production and degradation were explained by the alkaline conditions stimulating hydrolytic bacteria and nutrient supplementation. At a concentration of 1.5 g/g-TS, the AD was inhibited, probably because of toxic concentrations of cations (high salinity) (Yin et al., 2018). Wood ash is a porous material and may be suitable for biofilm growth. However, wood ash is not expected to be electrically conductive because incineration is not conducive to the generation of graphite layers, which requires the surrounding gas to be oxygen free. Therefore, it is unlikely to stimulate DIET in AD. To the best of the author’s knowledge, no studies exist on AD of municipal sewage sludge amended with wood ash. 60 Chapter 3: Materials and Methods This research studied the potential for char (biochar and wood ash with commercial name of ZMM® T-Carbon) to improve the digestion of sewage sludge from a WWTP by conducting BMP assays. The specific objective of this study was to determine the effects of granular (0.850 - 4.75 mm) and powdered biochar (<0.075 mm) and ZMM® T-Carbon on the daily and ultimate cumulative methane production with an emphasis on decreased lag phase and increased methane production rate. In this chapter, the experimental setup as well as the methods and materials used to conduct and analyze the BMP assays are described. Experimental Setup The BMP experiments were conducted in seven batches (B1, B2, .., B7) over the course of one year. In phase 1, in B1 and B2, three SIRs (2.2, 3.2, 4.4 g-VS/g-VS) were tested, each at three different dosages of powdered biochar and ZMM® T-Carbon as reported in Chapter 4, Tables 4.4 and 4.5. Biochar and ZMM® T-Carbon were initially dosed according to inoculum TS based on previous research (Cai et al., 2016; Podmirseg et al., 2013). However, in this study, as SIR increased, the effect of the biochar decreased, and since the inoculum amount was the same in all assays, this demonstrated that the dosage of biochar was primarily dependent on substrate amount rather than inoculum. For clarity purposes, dosages were reported in Tables 4.4 and 4.5 in both g/g-TSinoculum and g/g-VSsubstrate. The experiments included a group of assays (blanks) containing exclusively char and inoculum to determine the BMP contribution of ZMM® T-Carbon and biochar. Inoculum activity tests, or positive controls, were performed using glucose and acetic acid substrates at an SIR of 0.5 g CODsubstrate/g VSinoculum, with nutrient and buffer solution. The setup of activity tests and composition of the nutrient solution was based on experiments from Eskicioglu and coworkers (2017). In phase 2, an SIR of 4.4 g-VS/g-VS was selected based on phase 1 results to emulate a digester operating under high OLR. A dosage of 0.9 g/g-VSsubstrate of powdered biochar (< 0.075 mm) (SIR = 4.4 g-VS/g-VS) revealed to be too 61 low to measure statistically significant effects on methane production, therefore, the dosage of powdered (< 0.075 mm) and granular (0.850 - 4.75 mm) biochar and ZMM® T-Carbon was subsequently increased, until an inhibition became evident, to 1.8, 2.2 and 3.7 g/g-VSsubstrate. Granular media was also tested at lower dosages (B3, B5, B6 & B7) between 0.2 and 0.9 g/g-VSsubstrate but only at an SIR of 4.4 g-VS/g-VS. To investigate the buffering capacity of biochar and ZMM® T-Carbon, BMP assays with granular char at 2.2 g/g-VSsubstrate (B4) and powdered biochar at 3 g/g-VSsubstrate (B6) were prepared with and without added buffer (20 mmol/L of Na2CO3 and KHCO3). In phase 3, to compare inoculum activity with and without biochar, additional BMP bottles (B6) were setup with acetic acid and nutrient (positive control at an SIR of 0.5 g-COD/g-VS) and mixed sludge (control at an SIR of 4.4 g-VS/g-VS) along with inoculum and buffer solutions. Half the assays were amended with 2.5 g of powdered biochar. Moreover, in order to assess potential inhibition of methanogens compared to controls, assays with powdered biochar and controls were injected with 2 mL of 68 g/L of acetic acid at day 30. Performance in methane production was compared. In phase 4, the colonization of methanogenic archaea and syntrophic bacteria was tested in a series of BMP assays that are identified as first-generation and second-generation. The experiment was repeated twice. In the first experiment (B3-A), granular biochar was amended to BMP assays at a dosage of 0.16, 0.24 and 0.30 g/g-VSsubstrate containing inoculum, substrate sludge and buffer. The BMP assays were incubated for 19 days. On the final day, the bottles were opened and the sludge was strained with a coarse strainer with opning size of 0.9 mm to recuperate the biochar granules. The granules from each bottle were immediately transferred to a new bottle containing substrate sludge and buffer (generation 2, B-3B). As controls, new granular biochar was amended at the same dosages of 0.16, 0.24 and 0.30 g/g-VSsubstrate to BMP assays containing substrate sludge and buffer. The experiment lacked a 62 control with substrate and inoculum sludge, therefore, the experiment was repeated with controls and granular ZMM® T-Carbon was included in the test. For the second experiment (B4), first-generation assays consisted of inoculum and substrate sludge with buffer amended with granular biochar and ZMM® T-Carbon at 2.2 g/g-VSsubstrate, incubated for 59 days. On the final day, the sludge was strained using a coarse strainer of 0.9 mm opening and 1 g (wet weight) of char granules was transferred into new bottles with fresh substrate and buffer. Triplicate controls were setup with inoculum and substrate sludge and buffer. The second-generation assays (B5) were incubated for 49 days. At the end of the second-generation experiments, the bottles were opened and tested for pH, alkalinity, ammonia and VFA. Samples of granular biochar and ZMM® T-Carbon were prepared for SEM imaging. Samples were also preserved at -80°C for future microbial fingerprinting analysis conducted by an external laboratory. 3.1.1 Mixed Sludge The feed (mixed sludge) was a mixture of 65 ± 5% primary and 35 ± 5% secondary clarifier sludge, based on volume, shipped every 14 days from Lulu Island WWTP in Vancouver (British Columbia, Canada). At the plant’s headworks, the influent wastewater was screened with a 13 mm screen opening before flowing into an aeration tank to remove grit. The wastewater then flowed to a sedimentation tank where the settleable solids and scum (thickened primary sludge) were removed and screened with a screen opening of 5 mm. The waste secondary sludge was thickened using a dissolved air flotation thickener and then blended with the TSPS. In the laboratory, the mixed sludge was kept in a refrigerator at 4°C and fed to the digester in 24 h intervals. The properties of the mixed sludge were analyzed for every new batch. 63 3.1.2 Substrate The substrate used was from the first stage (acid-phase) of a bench scale TPAD process in operation since one year from the start of this research. The TPAD setup is illustrated Figure 3.1 below. The acid-phase vessel had a SRT of 2 days in a 2 L Erlenmeyer flask with a working volume of 1 L, operated at a temperature of 55°C, in an automated shaker (Innova 44R, New Brunswick Scientific) rotating at 90 rpm. The properties of the substrate sludge was analyzed weekly for TS, VS, COD, pH, alkalinity, VFAs (acetic, propionic and butyric acids), ammonia nitrogen and gas composition (N2, O2, CH4 and CO2). Figure 3.1: Lab-scale temperature phase anaerobic digester set-up Mixed sludge was fed to the acid-phase digester (a) with a sludge retention time of 2 days at 55°C. The effluent acidified sludge was immediately injected into the methane-phase digester (b) for a sludge retention time of 28 days at 38°C. a Acid phase 55°C b Methane phase 38° 64 3.1.3 Inoculum The inoculum was from the second stage (methane-phase) of the TPAD process, operated at an SRT of 28 days, a temperature of 38°C in a 4 L Erlenmeyer flask with a working volume of 2.5 L in an automated shaker rotating at 90 rpm. The digester was fed daily with the effluent from the acid-phase digester. The biogas volume produced was measured from the Tedlar® bag daily using a U-tube manometer built in-house. Periodically, 25% of the sludge was withdrawn for inoculation of BMP assays. In order to compensate, daily withdrawal of effluent sludge was withheld until the level in the reactor was restored. Char Material Biochar (Figure 3.2) was purchased from a commercial supplier within the ABI (SoilMatrix Biochar, Airterra, www.airterra.ca). The biochar was sourced from waste forest industry wood consisting of a mix of pine, spruce and cedar. The pyrolytic process was controlled to temperatures between 450-550°C. T-Carbon was used to compare the effects of biochar. The ZMM® T-Carbon (Figure 3.3) was produced from a local sawmill in the Okanagan Valley (British Columbia, Canada) using a conventional fixed grate biomass combustion system fueled by pine, spruce and fir bark and some dry wood shavings. The system is consisted of three furnaces with steam boilers. The steam was used for drying lumber and producing power in a steam turbine. The ZMM® T-Carbon was donated by ZMM Mineral Corp. (ZMM® T-Carbon., www.zmmcanadamineralscorp.com). Biochar and ZMM® T-Carbon were dried overnight at 80°C and sieved with #4, #20 and #200 USA standard testing sieves (VWR, USA). Powdered media was less than 0.075 mm and granular media was smaller than 4.75 mm but larger than 0.850 mm. The pH and EC were analyzed by mixing 1 g of biochar to 25 mL of ultra purified water (16.8 ± 0.1 μS/cm). 65 Figure 3.2: SoilMatrix biochar Figure 3.3: ZMM® T-Carbon 66 Biochemical Methane Potential Assays The procedure for batch BMP assays was adapted from previous work (Angelidaki et al., 2009; Holliger et al., 2016). The required amount of inoculum sludge for BMP experiments was transferred into a 2 L glass bottle and incubated in the same shaker (Figure 3.4). Substrate feeding was withheld for 7 days to allow the sludge to degas and reduce its methane contribution during BMP assays (Angelidaki et al., 2009). Batch digestion assays were conducted in 160 mL serum bottles (Figure 3.5). The volume of inoculum and total liquid amount was the same for all BMP assays from the same batch and the substrate amount was calculated based on the SIR. Water treated by reverse osmosis was added to obtain a maximum total liquid volume of 70 - 80 mL. For instance, for an SIR of 4.4 g-VS/g-VS and dosage of 0.9 g/g-VSsubstrate, 38 mL of substrate (3.35% VS by weight), 20 mL of inoculum (1.45% VS by weight), 22 mL of water and 1.12 g of dry powdered biochar were added to each bottle. A list of the bottle composition for all batches of assays is available in Appendix A. Buffer (20 mmol/L of Na2CO3 and KHCO3) was added to all the assays except for blanks since the inoculum already contained sufficient alkalinity. It was determined by experience that serum bottles should contain no more than 1.28 g-VS of substrate with a minimum headspace of 80 mL when performing experiments with biochar to prevent pressures exceeding 200 kPa in the bottle, if the gas was to be released in more than 12-hour intervals. The inoculum sludge was withdrawn from the methane-phase digester using a large syringe and added immediately to each bottle to minimize oxygen exposure. Each bottle was purged with N2 gas for 5 minutes before being sealed with a butyl rubber and aluminum cap. Bottles were incubated at 38°C at 90 rpm while resting horizontally for better mixing, in the same incubating shaker containing the source inoculum. For every batch of BMP assays and SIR tested, there were triplicate controls containing no biochar or ZMM® T-Carbon, and blanks containing exclusively 20 mL of inoculum sludge. The data was analyzed statistically with the Student’s t-test method using Microsoft Excel. An example of statistical analysis is provided in Appendix B. Data measured the same 67 day from the same experiment were compared by calculating the percent difference of the average of triplicate assays. The standard deviations were combined using propagation of uncertainty. Figure 3.4: Temperature controlled shaker Figure 3.5: Biochemical methane potential assays 68 Analytical Testing 3.4.1 Chemical Oxygen Demand COD is an experimental method used to measure rapidly the strength or organic content of wastewater sludge. The organics are oxidized by dichromate ions, which changes their state from Cr6+ to Cr3+. Chromic ions (Cr3+) absorb light in the 600 nm range. The absorbance is proportional to the COD concentration in the range of 100-700 mg-COD/L. The method used for COD determination was the Closed Reflux Colorimetric Method from the Standard Methods for the Examination of Water and Wastewater procedure 5220D (APHA-AWWA-WEF, 2005). Each sample was diluted using water treated by reverse osmosis to target an absorption in the middle of the calibration curve (350 mg-COD/L) and homogenized using a kitchen blender for 3 min. Using a pipette, 2.5 mL of diluted sample was added to a 12 mL vial with 1.5 mL of digestion solution and 3.5 mL of catalyst solution. The digestion solution contained water, sulfuric acid, mercuric sulfate and potassium dichromate and the catalyst solution contained pure sulfuric acid and silver sulfate. The samples were heated at 150°C for 3 hours in a Thermotron S-1.5C Benchtop Environmental Chamber (Thermotron Industries, Holland, Michigan) and then their absorption was measured with a Thermo Scientific™ GENESYS™ 10S UV-Vis Spectrophotometer (Thermo Fisher Scientific, Inc., Ottawa) at a wavelength of 600 nm. The concentration of COD in the samples was determined using a calibration curve prepared by measuring the adsorption of a set of standards. An example of calibration curve is available in Appendix C. 3.4.2 Total Solids and Volatile Solids The procedure for TS and VS determination followed the Standard Methods 2540 B and 2540 E, respectively (APHA-AWWA-WEF, 2005). TS content was determined by measuring approximately 10 g of sludge sample in porcelain dishes, in triplicates. The precise weight of the 69 empty dishes and dishes with samples were measured using an analytical balance (Mettler-Toledo Excellence XA-105, Thermo Fisher Scientific, Inc., Ottawa). The samples were placed in an oven to dry overnight at 90 - 95°C. The samples were heated for 3 hours at a temperature of 103 - 105°C before being transferred in a desiccator to cool to ambient temperature. The weight was measured and the samples were placed in a furnace at 550°C for 30 minutes to burn volatile solids. The samples were cooled, by placing them in the oven and then in the desiccator, to ambient temperature. The final weight was recorded from the analytical balance. All porcelain dishes were cleaned using a 20% sulfuric acid solution and burned at 550°C to remove trace VS contaminants for next set of samples tested. 3.4.3 Gas Volume and Composition Biogas generated by each reactor was collected in a Tedlar™ bag. Every day or when the bag was full, the gas was emptied by a peristaltic pump into a U-shape water displacement column built in-house to measure the volume of biogas. The displacement of the water in the column had to be regularly calibrated by injecting a known volume of gas using a 100 mL syringe. An example of calibration curve is available in Appendix C. Biogas pressure in BMP bottles was measured with a hand held digital manometer (LEO 2, Keller, Winterthur, Switzerland) with an accuracy full scale of < 0.1 % at room temperature. The manometer was factory calibrated. The manometer came with a ¼” NPT adaptor to which was added a brass ¼” NPT female-female fitting and a polypropylene male luer lock with ¼” NPT (Cole-Parmer, Canada) adaptor for surgical needle attachment. The gas composition in terms of CH4, H2, N2 and O2 was measured by withdrawing a 1 mL sample using an Agilent syringe, then purging to 0.6 mL and injecting into a gas chromatograph (Agilent 7820A GC) with a packed column (Agilent G3591- 8003/80002) and a thermal conductivity detector. Helium was used as the carrier gas at a flow rate of 25 mL/min. The oven, column and detector temperature 70 were 70, 100 and 150°C, respectively. The volume was standardized at 101.326 kPa and 0°C. The volume of methane produced was calculated using Equations 6, 7 and 8. P(d) = ∆P(d) + Patm(d) (6) ∆N(d) = [y(d) ∗ P(d) ∗VhR∗T] − [y(d − 1) ∗ Patm(d − 1) ∗VhR∗T] (7) ∆V(d) = ∆N(d) ∗R∗T0P0= ∆N(d) ∗8.314 J ∗273.15 °K101326 Pa °K mol∗ 106 (8) Where, P(d): Pressure in the bottle at the current time of measurement (Pa) P(d-1): Pressure in the bottle taken at the previous time of measurement (Pa) Patm (d): Atmospheric pressure at the time of the measurement (Pa) Patm (d - 1): Atmospheric pressure at the time of the previous measurement (Pa) ∆P(d): Differential pressure read on the manometer (Pa) P0: Standard pressure (101326 Pa) ∆N(d): Moles of methane gas in the headspace since the previous measurement (mol) y(d): Concentration of methane in the bottle at the current measurement (%) y(d−1): Concentration of methane in the bottle at the previous measurement (%) R: Gas constant (8.314 J °K-1 mol-1) T: Temperature of the gas in the bottle (°K) T0: Standard temperature (273.15 °K) Vh: Headspace volume (m3) ∆V(d): Volume of methane at standard temperature and pressure produced since the previous measurement (m3) 3.4.4 pH and Alkalinity pH was analyzed immediately after sampling using an Accumet™ Excel XL25 pH/mV/Temperature/ISE meter (Thermo Fisher Scientific, Inc., Ottawa). The probe was immersed in a sample of 50 mL or more contained in a beaker until the reading was stable. Alkalinity was measured according to the Standard Method 2320B (APHA-AWWA-WEF, 2005). The sample was first centrifuged at 18,720 x g for 30 min. The centrate was transferred to a clean glassware. Approximately 10 mL of sample was transferred to a beaker and the weight of 71 the sample was recorded using a balance. The pH probe was immersed in the sample and a 0.1 N sulfuric acid solution was titrated using a 50 mL burette until the sample reached a pH of 4.60. The volume of sulfuric acid titrated was recorded and used to calculate the alkalinity in mg/L as CaCO3 equivalent according to Equation 9 below: 𝐴𝑙𝑘𝑎𝑙𝑖𝑛𝑖𝑡𝑦 =𝐴 ∙𝑁 ∙ 50,000𝑉 (9) Where, A: Volume of titrated sulfuric acid (mL) N: Molarity of the sulfuric acid (mol/L) V: Volume of sample (mL) 3.4.5 Volatile Fatty Acids For VFA determination, a fresh sample was centrifuged at 18,720 x g for 30 min. The supernatant was filtered using a filtering apparatus connected to a vacuum pump and a 0.22 μm filter paper. Samples from BMP assays were filtered using Nanosep® centrifugal tubes (Pall Corporation, New York, USA), which include a 0.20 μm membrane. 0.5 mL of filtrate was pipetted into 2 mL glass vials. Before analysis, 0.5 mL of internal standard solution was added. The internal standard was composed of iso-butyric acid (2%), formic acid, sulfuric acid and sodium hydroxide. Iso-butyric acid is not produced by AD. Therefore, the analyzing software calculates the relative concentration of acetic, propionic and butyric acids contained in the sample from the iso-butyric acid peak. Before each analysis, quality control was performed using a standard solution of acetic (2 g/L), propionic (2 g/L) and butyric (2 g/L) acids. The VFA content was analyzed using an Agilent 7890A GC equipped with a 25-meter Agilent 19091F-112 column (0.32 mm ID, nitroterephthalic acid modified polyethylene glycol stationary phase), a flame ionization detector and an auto-sampler (Agilent Technologies, Santa Clara, CA). Helium was used as the carrier gas at a flow rate of 40 mL/min. The initial temperature for the oven, column and detector were 70, 220 and 300°C and final temperature were 200, 220 and 300°C, respectively. 72 3.4.6 Zeta Potential and Electrical Conductivity Zeta potential and EC were measured for powdered and granular biochar and ZMM® T-Carbon at a dosage of 3.7 g/g-VSsubstrate. Immediately after opening each bottle, a 1 mL sample was diluted at 1:50 with ultra purified water and analyzed for both parameters using a Zetasizer Nano ZS (Malvern Instruments Ltd., Westborough, MA) at an absorption setting of 1.0 and refraction index of 1.65. The instrument measures the zeta potential using a Laser Doppler Micro-electrophoresis. An electric field is applied to the sample contained in a measuring cell. The particles contained in the solution move with a velocity that is dependent on the charge of the particle and is measured using a laser interferometric technique. The EC is obtained simultaneously and calculated by the software by measuring the electrical resistance of the solution between the two electrodes on the measuring cell (Malvern Instruments Ltd., 2019). 3.4.7 Ammonia Nitrogen Ammonia nitrogen was analyzed by colorimetry according to the Environmental Protection Agency method 350.1. In this method, hypochlorite, phenols, nitroferricyanide and ammonia react together to form indophenol blue, which absorbs light at a wavelength of 660 nm, and is proportional to the ammonia concentration. In wastewater, ammonia originates primarily from the breakdown of protein, urine and from household products. In the biological treatment process, microorganisms absorb ammonia and ammonium to synthesize proteins such as enzymes. In AD, proteins and amino acids are degraded which results in the release of NH4+ and NH3 to the liquid phase. For the analysis of ammonia nitrogen, digestate was centrifuged at 18,720 x g for 30 min. The supernatant from each sample was diluted with ultra-purified water in a volumetric flask and 0.61 mL was pipetted 10 mL glass culture tubes in triplicates. Six calibration standards between 0.1 – 7.5 mg/L were prepared by diluting ammonium chloride with ultra-purified water. Each tube was added with 2.0 mL of complexing solution composed of 33 g/L of potassium sodium tartrate and 24 g/L of sodium citrate; 0.86 mL 73 of alkaline phenol solution composed of 34 g/L of sodium hydroxide and 10.56 g/L of phenol; 0.01 mL of 12% sodium hypochlorite solution; and 0.39 mL of a 500 mg/L nitroferricyanide solution. The samples were stored in the dark for 1 h and then absorbance was measured with the spectrophotometer at a wavelength of 660 nm. An example of standard curve is available in Appendix C. 3.4.8 Scanning Electron Microscope Imaging The microbial fixation of colonized granular char samples for SEM imaging followed the method tested by Araujo et al. (2003) on granular biofilm samples from a fluidized bed reactor. At the end of the BMP assay, the bottles were uncapped and the sludge from each bottle was strained using a coarse strainer with 0.9 mm openings to recuperate the char granules. Then the granules were immersed in a 0.1 M phosphorus buffer solution with 1% glutaraldehyde and stored in the refrigerator at 4°C for 12 hours. The char was strained and immersed for 10 minutes in a beaker of fresh 0.1 M phosphate buffer solution. This was repeated three times. The samples of char granules were dehydrated by performing a series of 10 min immersions and straining in 50%, 70%, 80%, 90% and 95% of water diluted denatured ethanol (95%). Lastly, the samples were immersed in hexamethyldisilazane (HDMS) twice for 30 sec and allowed to dry in aluminum dishes under the fumehood for the night. The next morning, each sample was mounted on a stub with carbon tape as a conductive adhesive. The SEM images and elemental compositions were obtained using a TESCAN Mira3 XMU Scanning Electron Microscope (TESCAN, Czech Republic) equipped with an Oxford Instruments X-Max energy dispersive spectrometer detector (Oxford Instruments, UK) from the Fipke Laboratory for Trace Element Research at the UBC Okanagan Campus. Samples were first coated with platinum using a Cressington Sputter Coater (Cressington Scientific Instruments, UK). 74 3.4.9 Particle Size Analysis The particle size density was measured using a Malven Mastersizer 3000 equipped with a Hydro LV wet dispersion module (Malvern Instruments Ltd., Westborough, MA.). The instrument measures the light intensity of a laser beam diffusing through a sample of suspended particles. Detectors measure the intensity of the dispersed laser beam and the Mastersizer 3000 software analyses the size distribution. The wet dispersion module ensures the particles are in a stable suspension and dispersed enough to obtain accurate readings. For the analysis of char, the optical bench, the wet dispersion unit and the tubing were cleaned and flushed three times with water treated by reverse osmosis. Approximately 1 table spoon of char was added to the water and mixed by the stirrer in the unit. Duplicate samples of char were analyzed ten times each. The samples were analyzed at a particle refractive index of 1.650, absorption index of 1.000 and dispersant refractive index of 1.330. 75 Chapter 4: Results and Discussion The results of this study are divided into four phases. Phase 1 assessed the effect of various SIRs (2.2, 3.2 and 4.4 g-VS/g-VS) and char dosages on rate and extent of methane production from acidified mixed sludge. Phase 2 further explored these effects under the high SIR selected from phase 1 and studied the interaction between alkalinity of char and methane production. Phase 3 investigated if the methane production was inhibited by char addition. Finally, phase 4 tested the suitability of the granular char media for bioaugmentation. Properties of Influent and Effluent from the TPAD System The results of the weekly analyses performed on the influent and effluent of the TPAD digesters are summarized in Table 4.1. When compared to results obtained by Nazyab (2018), the mixed sludge (digester feed) during the course of this research was on average more acidic, had higher total COD, TS and VS, and less total VFA, alkalinity and ammonia. The same trend was noticeable for the acid-phase reactor, however, the methane-phase reactor had comparable values. Table 4.1: Properties of mixed sludge, substrate and inoculum sludge for BMP assays Parameters Mixed sludge (n = 16) Acidified sludge (substrate) (n = 42) Methane phase anaerobic digester (inoculum) (n = 33) pH 5.40 (0.27)1 5.54 (0.34) 7.55 (0.29) Alkalinity (mg as CaCO3/L) 1331 (420) 2262 (859) 5511 (631) Total solids (g/kg) 46.3 (5.0) 42.2 (6.3) 17.5 (2.1) Volatile solids (g/kg) 40.0 (3.5) 36.2 (4.6) 12.7 (1.3) Total ammonia nitrogen (mg/L) 492 (114) 1022 (305) 1440 (173) Chemical oxygen demand (g/L) 65.9 (10.0) 66.6 (8.1) 20.9 (5.4) Acetic acid (mg/L) 1096 (305) 2005 (390) 23 (22) Propionic acid (mg/L) 1134 (554) 1643 (438) 13 (9) Butyric acid (mg/L) 482 (143) 734 (148) 9 (7) 1Arithmetic average and, in parenthesis, standard deviation of the replicates (n). 76 Char Characterization The results of the characterization of ZMM® T-Carbon and biochar are listed in Table 4.2. Graphitization and ash content increases the density of the char. Graphite has a density of 2.25 g/ml. The density of the SoilMatrix biochar was within the typical range of 1.5-1.7 g/mL (Brewer et al., 2009). The density of ZMM® T-Carbon was high compared to wood ash from other studies (0.27-0.51 g/mL), possibly because the biomass was not completely combusted or because of higher mineral content. The high pH in water of ZMM® T-Carbon was also within the range for boiler-ashes between pH 9 and 13.5 (Demeyer et al., 2001; Etitgni and Campbell, 1991). The ash content of the SoilMatrix biochar was low compared to slow pyrolysis biochar (13.9% by weight) studied by Brewer et al. (2009). The pH of water with biochar is expected to increase with increased temperature of pyrolysis. SoilMatrix biochar had a pH in water above 8, which is typical (Domingues et al., 2017). The EC measured for biochar was similar to that measured for wheat straw biochar (210 μS/cm) (Pan et al., 2019). Table 4.3 show the elemental composition of biochar and ZMM® T-Carbon, analyzed using the energy dispersive spectrometer from the Fipke Laboratory for Trace Element Research at UBC Okanagan. The elemental composition was analyzed on the bulk product and may vary for different particle sizes. The biochar had relatively more carbon because of the pyrolysis process and a lower concentration of trace elements than ZMM® T-Carbon. Both materials had similar surface characteristics when analyzed with the SEM (Figures 4.1 and 4.2). SoilMatrix biochar had particle sizes ranging from 0.00213 mm and 3.08 mm with the most abundant size being 0.756-0.976 mm (Figure 4.3), while ZMM® T-Carbon had particle sizes ranging from 0.00188 and 2.710 mm, with the most abundant size range being 0.0864-0.516 mm (Figure 4.4). This is in agreement with the observation made while sieving that almost no granules were retained by the largest mesh (#4). Both char types were very brittle and had to be manipulated minimally to avoid crushing. 77 Table 4.2: Parameters of SoilMatrix biochar and ZMM® T-Carbon Parameter SoilMatrix Biochar ZMM® T-Carbon Density at 23°C (g/mL) 1.6 (0.1)1 1.3 (0.1) Ash (%) 11.4 (0.2) 62.4 (0.3) pH (1 g in 25 mL water) 8.1 (0.1) 9.7 (0.2) Zeta Potential (mV) -27 (1) -29 (2) Conductivity (Powdered) (μS/cm) 274 (1) 1900 (2) Conductivity (Granular) (μS/cm) 133 (0) 1474 (2) 1Arithmetic average and, in parenthesis, standard deviation of triplicate samples. Table 4.3: Elemental composition of SoilMatrix biochar and ZMM® T-Carbon Element Average Weight and Standard Deviation (%) SoilMatrix Biochar (n = 6) ZMM® T-Carbon (n = 6) C 88.03 (0.93)1 57.34 (18.72)1 O 11.00 (0.77) 20.89 (9.94) Mg 0.12 (0.12) 0.64 (0.24) Na - 0.24 (0.13) Al 0.06 (0.04) 0.37 (0.30) Si 0.03 (0.03) 1.32 (1.50) P 0.01 (0.01) 0.26 (0.11) S 0.04 (0.03) 0.86 (0.90) Cl 0.04 (0.02) 0.49 (0.48) K 0.28 (0.05) 5.40 (6.93) Ca 0.34 (0.17) 11.18 (13.26) Br 0.06 (0.14) 0.12 (0.3) Mn - 0.48 (0.53) Fe - 0.41 (0.41) 1Arithmetic average and, in parenthesis, standard deviation of n samples. 78 Figure 4.1: SEM images of SoilMatrix biochar at a magnification of 500x (left) and 200x (right) Figure 4.2: SEM images of ZMM® T-Carbon at a magnification of 500x (left) and 200x (right) 79 Figure 4.3: Particle size distribution of SoilMatrix biochar by wet analysis Figure 4.4: Particle size distribution of ZMM® T-Carbon by wet analysis 02460,01 0,1 1 10 100 1000 10000Volume Density (%)Size Class (μm)Trial 1 Trial 2 Trial 3 Trial 4 Trial 5 Trial 6 Trial 7 Trial 8 Trial 9 Trial 1002460,01 0,1 1 10 100 1000 10000Volume Density (%)Size Class (μm)Trial 1 Trial 2 Trial 3 Trial 4 Trial 5 Trial 6 Trial 7 Trial 8 Trial 9 Trial 10 80 Performance of BMP Assays Amended with Biochar and ZMM® T-Carbon The difference in methane production and maximum improvement for BMP assays amended with biochar and ZMM® T-Carbon relative to controls are summarized in Tables 4.4 and 4.5. The results are discussed in the following sections. Table 4.4: Summary BMP results for SoilMatrix biochar amended assays Dosage (g/g-TSinoculum) Dosage (g/g-VSsubstrate) Size SIR (g-VS/g-VS) Total CH4 yield (mL/g-VSsubstrate) Duration (days) Maximum improvement in CH4 rate (%) Difference in ultimate CH4 yield (%) Batch number (B) 0.50 0.16 G1 4.4 354 (11)3 19 25 (26) Day 3 -2 (5) 3 0.75 0.24 G 4.4 359 (25) 19 19 (16) Day 2 -1 (8) 3 1.00 0.6 P2 2.2 552 (11) 49 86 (66) Day 3 -6 (5) 1 0.4 3.2 545 (33) 49 77 (50) Day 3 -5 (7) 1 0.3 4.4 527 (8) 49 18 (6) Day 16 3 (3) 1 0.3 G 4.4 346 (8) 19 19 (7) Day 3 -4 (4) 3 2.00 1.2 P 2.2 539 (6) 49 211 (84) Day 5 -8 (5) 1 0.8 3.2 522 (14) 49 192 (65) Day 3 -9 (4) 1 0.6 4.4 512 (19) 49 97 (63) Day 3 0 (4) 1 3.00 1.8 P 2.2 490 (37) 49 461 (195) Day 4 -16 (8) 1 1.2 3.2 503 (21) 49 365 (144) Day 4 -12 (5) 1 0.9 4.4 504 (19) 49 17 (41) Day 4 -2 (4) 1 0.9 G 4.4 474 (14) 49 23 (20) Day 2 -1 (3) 5 6.00 2.2 G 4.4 590 (12) 59 24 (51) Day 4 0 (4) 4 1.8 P 4.4 423 (5) 49 336 (17) Day 6 -12 (2) 5 9.00 3.0 P 4.4 323 (7) 30 272 (43) Day 5 -19 (2) 6 12.00 3.7 G 4.4 403 (13) 49 -7 (7) Day 3 -16 (3) 5 3.7 P 4.4 359 (2) 49 282 (20) Day 2 -25 (1) 5 1G: granular (0.850 - 4.75 mm); 2P: powdered (< 0.075 mm); 3Arithmetic average and, in parenthesis, standard deviation of triplicates. 81 Table 4.5: Summary of BMP results for ZMM® T-Carbon amended assays Dosage (g/g-TSinoculum) Dosage (g/g-VSsubstrate) Size SIR (g-VS/g-VS) Total CH4 yield (mL/g-VSsubstrate) Duration (days) Maximum improvement in CH4 rate (%) Difference in ultimate CH4 yield (%) Batch number (B) 1.00 0.6 P1 2.2 514 (10)3 49 14 (25) Day 9 2 (4) 2 0.4 3.2 481 (20) 49 31 (29) Day 8 2 (5) 2 0.3 4.4 487 (10) 49 10 (6) Day 10 2 (2) 2 0.3 G2 4.4 524 (2) 48 9 (3) Day 17 -1 (1) 7 2.00 1.2 P 2.2 488 (7) 49 -2 (3) Day 18 -3 (3) 2 0.8 3.2 489 (19) 49 47 (28) Day 8 4 (5) 2 0.6 4.4 470 (7) 49 15 (14) Day 8 -2 (2) 2 0.6 G 4.4 511 (6) 48 9 (2) Day 17 -3 (2) 7 3.00 1.9 P 2.2 485 (7) 49 -4 (3) Day 49 -4 (3) 2 1.3 3.2 476 (3) 49 12 (25) Day 8 1 (2) 2 0.9 4.4 481 (10) 49 14 (9) Day 7 0 (2) 2 0.9 G 4.4 470 (3) 49 -2 (2) Day 49 -2 (2) 5 6.00 2.2 G 4.4 588 (19) 59 80 (30) Day 4 -1 (5) 4 1.8 P 4.4 453 (3) 49 37 (9) Day 9 -6 (1) 5 12.00 3.7 G 4.4 420 (10) 49 -13 (2) Day 49 -13 (2) 5 3.7 P 4.4 425 (7) 49 -2 (2) Day 17 -11 (2) 5 1P: powdered (< 0.075 mm); 2G: granular (0.850 - 4.75 mm); 3Arithmetic average and, in parenthesis, standard deviation of triplicates. 82 4.3.1 Phase 1 4.3.1.1 Size of Char The graphs of cumulative methane production for 35 triplicated assays, not shown in this chapter, are available in Appendix D. The results for the statistical analysis comparing the methane production for all the assays and the controls using the Student’s t-test are reported in Appendix B. Powdered biochar (< 0.075 mm) resulted in shorter lag phases and higher rate of methane production than controls noticeably at dosages above 0.8 g/g-VSsubstrate. Improvements from controls increased with dosage and peaked at 1.8 g/g-VSsubstrate with 336 ± 17% on day 6 at an SIR of 4.4 g-VS/g-VS and 461 ± 195% on day 4 at an SIR of 2.2 g-VS/g-VS. The lag phase reduction was 4 and 3 days respectively. Dosage of biochar was increased until no further decrease in lag phase was observed which occurred at a dosage of 3.7 g/g-VSsubstrate (Figure 4.5). In comparison, granular biochar (0.850-4.75 mm) did not improve the total methane yield at dosages of 2.2 g/g-VSsubstrate and below, as shown from the results in Table 4.4. However, at 3.7 g/g-VSsubstrate, there was a 16 ± 3% decrease in BMP and 8 ± 4% increase in CO2 production compared to controls. Unlike with powdered biochar, the decrease in total CH4 was not associated with a reduced lag phase. Rather, there was an increase in the lag phase at all dosages of granular biochar tested (0.2–3.7 g/g-VSsubstrate) relative to controls. Luo et al. (2015) also measured shorter lag phases and higher maximum methane production rate with smaller particles (75-150 μm) of biochar than larger ones (0.5-1.0 mm and 2-5 mm), possibly because of the higher specific surface area. Another reason could be that powdered particles have a shorter diffusion path than granular media so adsorbates can penetrate faster in the particle pores. These results show that powdered biochar could be amended to a full-scale complete stirred tank reactor to reduce the SRT and increase efficiency of AD. Future research should investigate the possibility of using powdered biochar to reduce VFA 83 accumulation in failing reactors or reactors undergoing acid stress (low pH, low alkalinity, high total VFA concentration). Figure 4.5: Graphs of cumulative methane yield of assays with two size ranges and three dosages of biochar and ZMM® T-Carbon BMP assays amended with biochar (a) and ZMM® T-Carbon (b). The largest improvement in lag phase reduction and rate of methane production was obtained with BMP amended with powdered (< 0.075 mm) biochar at a dosage of 1.8 g/g-VSsubstrate (△) followed by powdered biochar at 3.7 g/g-VSsubstrate (◇). All BMP assays had an SIR = 4.4 g-VS/g-VS. Points represent arithmetic average and error bars are standard deviations of triplicates. 01002003004005006000 10 20 30 40 50Cumulative methane yield (mL/g-VS)Time (days)ControlBiochar granular 0.9 g/g-VS substrateBiochar granular 3.7 g/g-VS substrateBiochar powdered 1.8 g/g-VS substrateBiochar powdered 3.7 g/g-VS substrate(a)01002003004005006000 5 10 15 20 25 30 35 40 45 50Cumulative methane yield (mL/g-VS)Time (days)ControlT-Carbon granular 0.9 g/g-VS substrateT-Carbon granular 3.7 g/g-VS substrateT-Carbon powdered 1.8 g/g-VS substrateT-Carbon powdered 3.7 g/g-VS substrate(b) 84 When granular and powdered ZMM® T-Carbon were studied simultaneously at the same dosage (3.7 g/g-VSsubstrate), both showed a detrimental effect during the first days of the exponential methane production phase, but granular to a higher extent than powdered ZMM® T-Carbon (Figure 4.5). After 49 days, assays amended with both sizes produced the same total methane (420 ± 10 and 425 ± 7 mL/g-VSsubstrate) and nearly 12% less than controls. At lower dosages, the difference in the effects of granular and powdered ZMM® T-Carbon were marginal (Appendix B), except for granular size and dosage of 2.2 g/g-VSsubstrate, which is discussed in the following section. The powdered fraction was associated with a higher mineral content, which was measured by EC in water (1900 ± 2 μS/cm for 40 g/Lwater) that may supply nutrients. Granules originate from larger wood shavings that had not entirely combusted to ash (EC 1474 ± 2 μS/cm for 40 g/Lwater). The reason why granules were more detrimental to BMP compared to control than powdered ZMM® T-Carbon is unclear. It could be caused by higher shearing stress while mixing and/or more toxic organic compounds contained in the granular fraction as a result of incomplete combustion. 4.3.1.2 Dosage of Char Dosages of biochar between 0.2 and 3.7 g/g-VSsubstrate were tested. Generally, the difference in BMP compared to controls was not significant below 0.8 g/g-VSsubstrate. At a dosage of 1.8 g/g-VSsubstrate, after 49 days, powdered biochar assays produced 12 ± 2% less total methane and the same volume of CO2 than controls. Inhibition occurred at lower dosages than reported in other research. Shen et al. (2016) found an increase in total methane yield at 2.5 g/g-TSsludge (approximately equivalent to 3.6 g/g-VSsubstrate) and possible inhibitory effects on microbial activity from biochar at dosages of 4.4 and 4.97 g/g-TSsludge (approximately equivalent to 6.3 and 7.2 g/g-VSsubstrate) at thermophilic conditions. Sunyoto et al. (2016) found beneficial effects at dosages up to 25.1 g-biochar/L and a decrease in methane production compared to control at dosage of 33.3 g/L in AD of carbohydrate food waste. 85 Detrimental effects during the first five days were measured at all dosages tested for both granular and powdered ZMM® T-Carbon and were the highest during the first two days of digestion. A longer acclimation time (lag phase) was reported in other research involving wood ash amendment to AD but the specific cause remains unknown (Lo et al., 2010). At the lowest doses of granular and powdered ZMM® T-Carbon (0.3 and 0.6 g/g-VSsubstrate), there was no significant difference on methane yield compared to controls except between day 12 and 20, when there was a slight beneficial effect of 8.5-8.7% (day 17.5, p = 0.008, p = 0.004 for 0.3 and 0.6 g/g-VSsubstrate, respectively). However, at dosage of 0.9 g/g-VSsubstrate, granular ZMM® T-Carbon produced less daily methane than controls until day 15 (-5 ± 2%, p = 0.0045), after that the methane productions were similar until the end (-2 ± 2%, p = 0.10 at day 59). Interestingly, at 2.2 g/g-VSsubstrate, granular ZMM® T-Carbon outperformed controls between day 7 and 28 of digestion (p < 0.03), then from day 28 to 59 the methane productions were the same (p > 0.14). (p-values for each day are listed in Appendix B). Also, there was 97% less butyric acid accumulated in the liquid phase on day 10 and 98% less propionic acid on day 20 compared to controls. The fluctuations in total VFA concentrations between treatments are illustrated in Appendix E. Further increase in dose of ZMM® T-Carbon (3.7 g/g-VSsubstrate) resulted in less daily methane produced compared to controls throughout the duration of the AD (-13 ± 2%, day 49). It appears contradictory that a low dose of granular ZMM® T-Carbon was detrimental to the BMP in one group of assays and then beneficial when doubling the dose in another group of assays. This could be due to a difference in strength of substrate sludge. The BMP from controls in B4 was 579 ± 19 mL CH4/g-VSsubstrate by day 46, whereas in B5, it was 480 ± 6 mL CH4/g-VSsubstrate by day 49 as illustrated in Figure 4.6. The addition of ZMM® T-Carbon was more beneficial for degradation of higher strength substrate as it accelerated biodegradation of propionic and butyric acids, possibly by contributing essential nutrients and metal alkalis to the microorganisms (Lo et al., 2010; Podmirseg et al., 2013). There was no significant difference in final pH between the controls and the assays amended with ZMM® T-Carbon at 0.3 g/g- 86 VSsubstrate (p = 0.10) and 0.6 g/g-VSsubstrate (p = 0.38), however, at dosages higher than 0.9 g/g-VSsubstrate, the pH was higher in all ZMM® T-Carbon assays (Appendices F and G). The maximum was pH 8.00 ± 0.07 at the end of the AD period at a dosage of 3.7 g/g-VSsubstrate. Figure 4.6: Comparison of methane yield for controls in all batches of assays, SIR 4.4 g-VS/g-VS Points represent averages and error bars are standard deviation of triplicate assays. 4.3.1.3 Zeta Potential and Electrical Conductivity The effect of biochar and ZMM® T-Carbon on the stability of the colloidal material in the digestate was measured at the end of the BMP assays at highest dosage tested (3.7 g/g-VSsubstrate). The most negative zeta potential was measured in controls (-36.9 ± 0.5 mV), followed by granular biochar (-34.8 ± 0.4 mV), powdered biochar (-33.7 ± 1.3 mV), powdered ZMM® T-Carbon (-29.4 ± 1.2 mV) and granular ZMM® T-Carbon (-29.0 ± 1.3 mV). A neutral zeta potential is optimal for sludge dewaterability, therefore, the char material may have a modest beneficial effect on sludge conditioning. Electrical conductivity measures the ionic concentration by measuring the flow of electricity through the digestate. Inorganic compounds such as alkalis, carbonates, sulfides, 01002003004005006007000 10 20 30 40 50 60 70Cumulative methane yield (mL/g-VS)Time (days)B1B5B4B2B6B3B7 87 chlorides and cations may originate from the wastewater sludge, added buffer, char material and mineralization of the organic waste. EC offers insight into possible inhibitory conditions to microorganisms such as salt stress. However, EC is indiscriminate of the types of ions whereas salt toxicity depends on the elements present and their concentrations. AD was reported to occur even at an EC of 90 mS/cm (Scoma et al., 2017). At the highest dosage tested (3.7 g/g-VSsubstrate), the lowest EC was measured in assays with granular biochar (15.28 ± 0.03 mS/cm) followed by powdered biochar (17.97 ± 0.67 mS/cm), controls (18.48 ± 0.48 mS/cm), granular ZMM® T-Carbon (20.80 ± 0.61 mS/cm) and powdered ZMM® T-Carbon (21.07 ± 0.10 mS/cm). Pan and colleagues (2019) measured an EC in the range of 12-14 mS/cm in BMP assays with chicken manure substrate and biochar. They also measured a lower EC in biochar assays than controls and hypothesized it was because more ions were absorbed as nutrients by microorganisms because biochar stimulated their growth. In this case, the low EC associated with the biochar assays may also be caused by the lower degree of biodegradation as noticeable from the reduced BMP compared to controls shown in Figure 4.5. 4.3.1.4 Effect of Sludge to Inoculum Ratio on Methane Production Total COD and TS/VS are often used as rapid estimation tools but BMP assays are a more accurate mean of measuring waste degradability by AD as VFAs tend to volatilize below 105°C during TS/VS analysis. In phase 1, the controls with an SIR of 4.4 g-VS/g-VS exhibited the highest acid stress, as noticeable from the reduced total methane produced in experiment B1 for SIR 4.4 g-VS/g-VS (514 ± 11 mL CH4/g-VSsubstrate) compared to an SIR of 3.2 g-VS/g-VS (572 ± 20 mL CH4/g-VSsubstrate) and SIR 2.2 g-VS/g-VS (586 ± 29 mL CH4/g-VSsubstrate). In experiment B2, the SIRs of 4.4 and 3.2 g-VS/g-VS had similar total methane yield (480 ± 6 and 470 ± 10 mL CH4/g-VSsubstrate) and the SIR of 2.2 g-VS/g-VS had the highest (504 ± 15 mL CH4/g-VSsubstrate). BMP assays conducted in B2 had a less pronounced acid stress at all SIRs compared to B1 due to the lower strength of the mixed sludge at that period of time, as 88 noticeable by the low VFA production during the fermentation phase. As illustrated in Figures 4.7 and 4.8 the total VFA concentration in the assays by day 2 was 3,803 ± 674 mg/L and 2,019 ± 78 mg/L for B1 and B2, respectively, which led to less total methane being produced for B2 than B1 when normalized by initial VS in the substrate. Overall, the controls for B1, B2, B4, B5, B6 and B7 had BMPs ranging from 403 ± 5 mL CH4/g-VSsubstrate to 549 ± 16 mL CH4/g-VSsubstrate after 30-31 days. Fluctuations in BMP from acidified mixed sludge were caused by seasonal, environmental and operational variations at the WWTP. The mixed sludge used in this study was the same as was fed to the WWTP’s full-scale digesters and the ratio of primary/secondary sludge depended on operational conditions at the WWTP. The results for the characterization of the mixed sludge, substrate and inoculum used to setup BMPs are available in Appendix H. The performance of the BMPs was comparable to that from primary (BMP30 days = 495 mL CH4/g-VSsubstrate) and secondary (BMP30 days = 218 mL CH4/g-VSsubstrate) sludge from a WWTP in Guelph (Ontario, Canada) (Filer et al., 2019). Figure 4.7: Graph of total volatile fatty acids variation during BMP assays for B1, SIR = 4.4 g-VS/g-VS with powdered biochar Dosages of powdered (< 0.075 mm) biochar were 0.3, 0.6 and 0.9 g/g-VSsubstrate. Points represent averages and error bars are standard deviations of triplicate assays. 01000200030004000500060000 5 10 15 20Total VFA (mg/L)Time (days)ControlsBiochar powdered 0.3 g/g-VS substrateBiochar powdered 0.6 g/g-VS substrateBiochar powdered 0.9 g/g-VS substrate 89 Figure 4.8: Graph of total volatile fatty acids variation during BMP assay for B2 at SIR = 4.4 g-VS/g-VS with powdered ZMM® T-Carbon Dosages of powdered (< 0.075 mm) ZMM® T-Carbon were 0.3, 0.6 and 0.9 g/g-VSsubstrate. Points represent averages and error bars are standard deviations of triplicate assays. 4.3.1.5 Positive Controls Inoculum activity tests with pure substrates (acetic acid and glucose) used as positive controls resulted in net methane yields of 328 ± 7 mL CH4/g-CODacetic acid and 298 ± 8 mL CH4/g-CODglucose, corresponding to 94% and 85% of theoretical methane yield, respectively. These results met the recommended minimum of 85% of theoretical methane yield (Filer et al., 2019). The inoculum performed better with acetic acid substrate, which it was acclimated to utilize, since it was sourced from a TPAD process. 050010001500200025003000350040000 2 4 6 8 10 12Total VFA (mg/L)Time (days)ControlT-Carbon Powdered 0.3 g/g-VS substrateT-Carbon Powdered 0.6 g/g-VS substrateT-Carbon Powdered 0.9 g/g-VS substrate 90 4.3.2 Phase 2 4.3.2.1 Buffering Capacity of Biochar and ZMM® T-Carbon During AD, alkalinity is consumed by acids and then generated as a by-product of methanogenesis. The capacity of biochar to neutralize acidity is not directly indicated by its pH value, it is better estimated by its liming effect, or buffering capacity, which depends on the ash content and chemical composition of the biochar (Domingues et al., 2017). One hypothesis was that char alleviated acid stress by buffering the acids produced during the AD. In this respect, ZMM® T-Carbon would be the most beneficial since it contained six times more ash than biochar. A comparison between ZMM® T-Carbon and biochar with and without added sodium carbonate and potassium bicarbonate buffer showed that granular char amended assays at dosages of 2.2 g/g-VSsubstrate (SIR 4.4 g-VS/g-VS) benefitted nearly as much as controls from the addition of buffer throughout the BMP period (Figure 4.9). However, the main effects from lack of external buffer were lower rates of daily methane production (31–43 mL/g-VSsubstrate d compared to 46–55 mL/g-VSsubstrate d) and more variability. The instability of the digestion process led to standard deviations as high as 37.4 mL CH4/g-VSsubstrate compared to 10.5 mL CH4/g-VSsubstrate for assays with buffer, as illustrated by the large error bars in Figure 4.9. Consequently, the range of methane produced was too wide to establish a clear divide in the methane production between the samples containing char and the controls. The Student’s t-test confirmed there was not enough evidence to prove that the buffering capacity of ZMM® T-Carbon could benefit AD of acidified sludge at the tested dosage compared to biochar and controls in the absence of external buffer, and the p-values were 0.88 and 0.27 respectively. The alkalinity measured at the end of the non-buffered assays was 6,068 ± 130 mg as CaCO3/L as for ZMM® T-Carbon and 5,450 ± 203 mg as CaCO3/L for controls, whereas buffer added assays had an alkalinity of 8,423 ± 126 mg as CaCO3/L for ZMM® T-Carbon and 8,491 ± 249 mg as CaCO3/L for controls (Appendix F). These results show that, at a dosage of 2.2 g/g- 91 VSSubstrate, ZMM® T-Carbon contributed minimally (550 ± 241 mg as CaCO3/L) to the total alkalinity in comparison to the addition of potassium bicarbonate and sodium carbonate. Figure 4.9: Graphs comparing the effects of granular char and buffer on methane yield BMP assays amended with biochar (a) and T-Carbon (b) of granular size (0.850 - 4.750 mm) at dosage of 2.2 g/g-VSsubstrate and SIR = 4.4 g-VS/g-VS with and without added sodium carbonate and potassium bicarbonate buffer. The graph shows that granular char did not contribute significantly to buffering capacity. BMP assays without added buffer had unstable methane production (black points) as noticed from the large error bars and slower rates of methane production compared to buffer added assays (white points). Points represent arithmetic average and error bars represent standard deviations of triplicates. 01002003004005006007000 10 20 30 40 50 60Cumulative methane yield (mL/g-VS)Time (days)Control with bufferControl without bufferBiochar with bufferBiochar without buffer(a)01002003004005006007000 10 20 30 40 50 60Cumulative methane yield (mL/g-VS)Time (days)Control with bufferControl without bufferT-Carbon with bufferT-Carbon without buffer(b) 92 For powdered biochar (< 0.075 mm) at 3.0 g/g-VSsubstrate,the assays without added buffer followed the same methane production trend as the ones with biochar and buffer, which outperformed controls (with buffer) during the first 9 days and improved the methane production rate by 211% on day 6 (Figure 4.12). Addition of external buffer to the biochar amended assays improved the production of methane by a maximum of 15% on day 10. On the 30 th day, the difference between biochar assays with and without additional buffer was only 3% (323.2 ± 6.9 mL CH4/g-VSsubtrate and 313.3 ± 6.1 mL CH4/g-VSsubstrate). The alkalinity measured at the end of the experiment was the highest for controls (8,984 ± 52 mg as CaCO3/L) followed by biochar with buffer (8,310 ± 182 mg as CaCO3/L) and biochar without buffer (5,597 ± 25 mg as CaCO3/L) which was within the range of value of the inoculum sludge (5,511 ± 631 mg as CaCO3/L). Therefore, the increase in methane production rate may not be entirely attributable to the buffering capacity of the biochar. Interestingly, powdered biochar (< 0.075 mm) at 0.9 g/g-VSsubstrate had less alkalinity (8,293 ± 59 mg as CaCO3/L) than controls (8,785 ± 41 mg as CaCO3/L) by the end of the experiment, although total methane yields (504 ± 19 and 514 ± 11 mL/g-VSsubstrate) and pH (7.715 ± 0.045 and 7.711 ± 0.023) were similar. Sampling during the digestion process revealed that after 18 days, the acetic and propionic acids were being degraded efficiently in the biochar assays (6.0 ± 5.2 and 1.9 ± 3.3 mg/L) but less so in the controls (342.7 ± 201 and 716.8 ± 523.2 mg/L) as shown in Figures 4.10 and 4.11. The same trend was measured in the granular biochar at dosage of 0.9 g/g-VSsubstrate, alkalinity was lower (7,957 ± 70 mg as CaCO3/L) compared to controls (8,231 ± 91 mg as CaCO3/L) despite similar methane production (p = 0.42). Acid stress was probably dampened by a combination of factors such as colonization of syntrophic bacteria and methanogenic archaea on char surfaces, DIET, buffering, adsorption of inhibitory compounds and surface biofilm. 93 Figure 4.10: Graph of acetic acid variation during BMP assays for B1, SIR = 4.4 g-VS/g-VS with powdered biochar Dosages of powdered (< 0.075 mm) biochar were 0.3, 0.6 and 0.9 g/g-VSsubstrate. Points represent averages and error bars are standard deviations of triplicate assays. Figure 4.11: Graph of propionic variation during BMP assays for B1, SIR = 4.4 g-VS/g-VS with powdered biochar Dosages of powdered (< 0.075 mm) biochar were 0.3, 0.6 and 0.9 g/g-VSsubstrate. Points represent averages and error bars are standard deviations of triplicate assays. 050010001500200025003000350040000 10 20 30 40 50Acetic acid (mg/L)Time (days)ControlsBiochar powdered 0.3 g/g-VS substrateBiochar powdered 0.6 g/g-VS substrateBiochar powdered 0.9 g/g-VS substrate050010001500200025000 10 20 30 40 50Propionic acid (mg/L)Time (days)ControlsBiochar powdered 0.3 g/g-VS substrateBiochar powdered 0.6 g/g-VS substrateBiochar powdered 0.9 g/g-VS substrate 94 Figure 4.12: Graph comparing the effects of powdered biochar and buffer on methane yield Powdered biochar (< 0.075 mm) at dosage of 3.0 g/g-VSsubstate and SIR = 4.4 g-VS/g-VS with (△) and without (▲) added buffer had similar methane production rates and outperformed controls with buffer (◯) in the first 10 days. Powdered biochar relieved acid stress despite not contributing significantly to overall alkalinity in the assays. Acetic acid addition showed that the reduction in ultimate methane yield compared to controls was not caused by inhibition. Points represent arithmetic average and error bars are standard deviations of triplicates. 4.3.2.2 Ammonia Nitrogen Protein and amino acid degradation produces ammonia that reacts with carbon dioxide, a product of the degradation of organics, in the solution to form ammonium carbonate, which in turn increases alkalinity. Ammonia nitrogen was reported to cause 50% inhibition of methane production at concentrations ranging from 1.7 to over 14 g/L (Jarrell et al., 1987). Several studies have mentioned the adsorption of ammonium by biochar as a factor for the improvement in methane yield (Fagbohungbe et al., 2017). The removal mechanism is by electrostatic exchanges of NH4+ with cations present on the surface of the biochar (Hale et al., 2013). Thus, the adsorption of ammonia nitrogen is related to the cation exchange capacity which depends on the source biomass and is inversely proportional to the pyrolytic process temperature (Domingues et al., 2017). Mumme and colleagues (2014) measured 2 - 6.8 mg N/g of 01002003004005000 10 20 30 40Cumulative methane yield (mL/g-VS) Time (days) Acetic acid addition (phase 3) 95 adsorption on pyrochar (another term for biochar), Lü and colleagues (2016) measured an ammonia adsorption capacity of 2-3 mg N/g biochar and Hale and colleagues (2013) found a maximum biochar sorption capacity of 0.852 mg NH4–N/g. In order to estimate adsorption of ammonium by char particles, BMP assays had to have had a similar methane yield and pH to controls to avoid confounding factors. Granular biochar and ZMM® T-Carbon at a dosage of 0.9 g/g-VSsubstrate yielded similar total methane than their respective controls as reported in Tables 4.4 and 4.5 and Figure 4.5. The lowest pH measured including the controls was pH 7.69 ± 0.01 and the highest was pH 7.78 ± 0.03 on the last day of the assays. For granular media, ammonia concentration was 6% and 14% lower in the biochar (1,272 ± 19 mg NH3-N/L, p = 0.036) and ZMM® T-Carbon assays (1,168 ± 30 mg NH3-N/L, p = 0.002) than controls (1,356 ± 36 mg NH3-N/L). The calculated adsorption by granular media was 5.55 ± 2.11 mg NH3-N/g-biochar and 12.48 ± 4.08 mg NH3-N/g-ZMM® T-Carbon, and by powdered media was 7.17 ± 1.65 mg NH3-N/g-biochar and 5.59 ± 1.81 mg NH3-N/g-ZMM® T-Carbon. Granular ZMM® T-Carbon was most effective at reducing ammonia concentrations. These results are in accordance with other research suggesting high metal elements, carbonates and SiO2 in the ash correlate with higher adsorption capacity because of cation exchange (Yu et al., 2016). It was evident throughout the experiments that the dosage of powdered biochar was negatively correlated to the total methane production (Table 4.4). Mumme and colleagues (2014) obtained similarly less total methane than controls when high concentrations of ammonium chloride were added to BMP assays containing pyrochar. They suggested the alkaline pyrochar may have shifted the equilibrium of NH4+/NH3 towards more cytotoxic ammonia and inhibited VFA degradation. When comparing biochar to ZMM® T-Carbon, the later had a higher pH and ash content and produced similar methane yields than controls at most dosages lower than 1.9 g/g-VSsubstrate (Tables 4.4 and 4.5). Ammonia inhibition typically leads to an accumulation of VFAs in the digester. However, there were less than 7 ± 6 mg/L of total VFAs left in the liquid phase and no difference 96 in pH with controls below dosages of 3.7 g/g-VSsubstrate by the end of the digestion process in all powdered biochar amended assays. The alkalinity levels at the end of the digestion also decreased (8,786 ± 41 > 8,493 ± 130 > 8,411 ± 51 > 8,293 ± 59 mg as CaCO3/L) as biochar dose increased (controls < 0.3 < 0.6 < 0.9 g/g-VSsubstrate, SIR = 4.4 g-VS/g-VS), while the controls had the highest measured alkalinity. This suggested that degradation of the VFA might not have occurred since the conversion of VFA into methane would have generated alkalinity. One possibility is that the VFAs were adsorbed by the biochar, rendering it unavailable to the aceticlastic methanogens. Ammonia toxicity was unlikely to have caused the inhibition of the BMP assays observed with powdered biochar since VFA accumulation did not occur and levels of ammonia were lower than inhibitory thresholds reported in the literature in all the assays. In addition, ZMM® T-Carbon assays were not as severely affected by inhibition despite being more alkaline. 4.3.3 Phase 3 4.3.3.1 Methane Production from Char BMP assays with inoculum and char exclusively (without substrate) were carried out to determine background methane production. When the methane production of pyrochar alone was studied, researchers (Mumme et al., 2014) calculated only a 0.6% labile carbon fraction and specified that the pyrochar contained mostly high molecular weight and aromatic compounds that were non-degradable by AD. The carbon in wood ash is also very recalcitrant and hence did not degrade even with cattle manure inoculum acclimated to refractory organic fibers (Podmirseg et al., 2013). For dosages of 1, 2 and 3 g/g-TSinoculum, the volume of methane produced by assays with inoculum and biochar was 4.01 ± 0.96 mL, 2.76 ± 1.44 mL and 1.7 ± 0.4 mL compared to 5.87 ± 0.33 mL for blanks (inoculum only). For assays with inoculum and ZMM® T-Carbon at the same dosages, the total volume of methane was 13.49 ± 1.25 mL, 10.98 ± 0.46 mL, 8.54 ± 0.71 mL compared to 13.82 ± 0.53 mL for blanks. Hence, both biochar and 97 ZMM® T-Carbon showed less methane production than blanks. At first, high pH appeared to have caused inhibition of inoculum. The pH ranged between 7.6 (inoculum only) and 7.9 (inoculum and ZMM® T-Carbon, 3 g/g-TSinoculum) at the beginning of the assays but increased to pH 7.7-8.4. The rise in pH may have occurred because of the slow dissolution of carbonates, oxides and hydroxides contained in biochar and ZMM® T-Carbon, and low amounts of acidic surface functional groups (Domingues et al., 2017). The pH range for AD is typically between pH 6 – 8.3 (Angelidaki and Sanders, 2004). However, it is unlikely that alkaline pH prevented anaerobic degradation since the control assays with substrate also had a high initial pH of 8.5 because of buffer addition and it gradually decreased to neutral (pH 7.5) as VFAs were being generated. Possible inhibition of methane production from char is discussed in more details in the following sections. 4.3.3.2 Salt Toxicity Salt toxicity was hypothesized as the mechanism of BMP inhibition after the exponential methane phase for powdered biochar at concentrations higher than 1.8 g/g-VSsubstrate. Salt toxicity could be induced by the rapid increase in VFAs and subsequent neutralization by cations contained in the biochar and carbonated buffer in addition to ammonium cations produced during protein degradation. These can generate salts that are toxic at various levels to microorganisms present in AD, particularly ammonium salts (McCarty and McKinney, 1961). The decrease in methane production in AD of food waste with increasing dosage of walnut shell biochar was also attributed to cation toxicity (Linville et al., 2017). The BMP was less affected by high dosages of ZMM® T-Carbon than biochar, with 6-13% lower methane yield than controls compared to 12-25% for biochar at dosages of 1.8-3.7 g/g-VSsubstrate, although the EC of ZMM® T-Carbon was higher. This could be because ZMM® T-Carbon had a high content of calcium carbonate which is not as toxic as other salts in high concentrations because of its propensity to precipitate (McCarty and McKinney, 1961). Moreover, the rapidity of the degradation may 98 restrict acclimation in the powdered biochar amended bottles compared to controls. Usually inhibition of methane forming archaea is accompanied by an accumulation of organic acids, which did not occur in any of the assays. Therefore, if salt toxicity was indeed responsible, only the acidogenic bacteria were affected. In such case, the presence of porous material favorable to biofilm formation may have sheltered the acetogenic bacteria and methanogenic archaea from the inhibitory salts. Fixed-film processes were reported in other studies to have higher tolerance to inhibitory compounds than suspended biomass systems (Fagbohungbe et al., 2017). 4.3.3.3 Type of Inhibition The nature of the inhibition was investigated by comparing inoculum activity tests with and without powdered biochar (Figure 4.13). The assays contained 4.76 g/L of acetic acid substrate and 50 g/L of powdered biochar mixed with inoculum (9 g/g-TSinoculum). The results showed that the detrimental effect caused by the biochar were significant throughout the digestion process. The most important inhibition was after 1.8 days when the controls had produced 252 ± 40 mL CH4/g-COD, and biochar assays, 82 ± 4 mL CH4/g-COD. In total, the biochar assays produced 15% less methane and 175% more carbon dioxide (168 ± 8 mL CO2/g-COD) than controls (61 ± 6 mL CO2/g-COD). These results diverge from those obtained with the acidified mixed sludge substrate, where the rate of methane production was slower than controls only after the initial exponential methane production phase and the volumes of carbon dioxide produced were similar. In order to determine if the inhibition was permanent or reversible, BMP assays dosed at 3 g-biochar/g-VSsubstrate were injected with 1.7 mg/L of acetic acid solution after 30 days of digestion (Figure 4.12). Prior to the injection, there was 19% less total methane generated from the biochar assays than controls. The production of methane from the acetic acid occurred simultaneously in biochar amended assays and controls. The biochar amended bottles produced 355 ± 15 mL CH4/g-COD, 8.5% less than controls (388 ± 16 mL 99 CH4/g-COD, p = 0.063). The difference was caused, at least partially, by the continued degradation of the initial substrate being more pronounced in the controls than in the biochar assays. Interestingly, when the assays were terminated at day 38, the controls had more acetic acid remaining in the liquid phase (27.1 ± 10.4 mg/L) than biochar amended assays (5.3 ± 0.7 mg/L). The same trend was measured for propionic (5.7 ± 3.5 mg/L and 0.0 ± 0.0 mg/L) and butyric acid (7.8 ± 3.2 mg/L and 3.0 ± 0.3 mg/L). Carbon dioxide production was the same in controls (156 ± 9 mL CO2/g-COD) and biochar amended bottles (159 ± 12 mL CO2/g-COD). There was no significant difference in methane produced from the acetic acid between the biochar assays with and without added buffer (p = 0.369). Evidence pointed towards either a reversible type of inhibition or a possible adsorption of the VFAs on the surface of the biochar. Figure 4.13: Graphs of cumulative methane and carbon dioxide production for inoculum activity test with acetic acid substrate Points represent averages and error bars are standard deviations of triplicate assays. 4.3.3.4 Adsorption of Volatile Fatty Acids To the best of the author’s knowledge, no isotherms are available in the literature for VFA adsorption on biochar surface. In this study, adsorption by biochar was estimated based on a theoretical methane yield of 374.5 mL CH4/g acetic acid. For simplification, only acetic acid 0501001502002503003504004500 2 4 6 8 10Cumulative gas yield (mL/g-COD)Time (days)CH4 from controls CH4 from assays with powdered biocharCO2 from controls CO2 from assays with powdered biochar 100 was considered in this exercise. Based on the difference in ultimate methane yield between the powdered biochar amended assays and controls, the adsorption of acetic acid by biochar was approximated to be 78 mg/g. In assays with only acetic acid substrate, the adsorption was calculated to be 16.6 mg/g powdered biochar. Therefore, like activated carbon, biochar may have a higher adsorption capacity for other types of organic acids. da Silva and Miranda (2013) characterized the adsorption mechanism of acetic, propionic and butyric acids on the surface of GAC made from coconut shells. The adsorption capacities for single acids were measured to be 68.38 mg/g (Ceq = 3.51 g/L), 116.85 mg/g (Ceq = 2.67 g/L) and 151.28 mg/g (Ceq = 1.93 g/L) for acetic acid, propionic acid and butyric acid, respectively, at 40°C. The activated carbon had a higher affinity for long aliphatic chain acids than shorter ones because of hydrophobic surfaces. They found that prediction models were inaccurate when two types of VFAs were present because of competition for adsorption sites on the activated carbon surface. In the context of sewage sludge, the complexity would be multiplied. The authors also reported that the adsorption equilibrium was reached within 14 hours. Assuming a similar mechanism was occurring with biochar, most of the adsorption would have happened before the first measurement of methane production in the BMP assays. More research studies would be necessary to find the VFA adsorption capacity of biochar from wood feedstock. 4.3.4 Phase 4 4.3.4.1 Biofilm Formation The main objective of this research was to assess if biochar or wood ash would be suitable media for the Archaea Incubator. The media’s main function would be to carry the essential microorganisms for the production of methane from the Archaea Incubator to the methane-phase AD reactor. A series of experiments, referred to as first and second-generation, were designed to determine if the media was colonized by the appropriate microorganisms to 101 carry out this function. To this effect, measuring the methane production rate in BMP assays can serve as an indicating parameter for the presence and abundance of methanogenic archaea and syntrophic bacteria population. This is because the multiplication of methanogens is slow so a less numerous population leads to a longer lag phase in BMP assays. In the first colonization experiment, the first-generation BMP assays (B3-A) were conducted with granular biochar at three dosages. The cumulative methane production results for the first-generation are shown in Figure 4.14. There was a slight decrease in methane production in assays amended with granular biochar compared to the controls between day 8 and 15 but otherwise, the assays produced similar volumes of methane (p-values for each day of measurement are available in Appendix B). The second-generation (B3-B), were set-up using the granular biochar from the first-generation (B3-A) which was transferred after 19 days of AD. As controls, BMP assays (in triplicates) were set-up with substrate sludge and new granular biochar at the three same dosages. The colonization of methanogenic archaea and syntrophic bacteria on biochar was confirmed by the methanogenic activity in the second-generation BMP assays and SEM images. The controls that lacked external inoculum sludge addition during set-up still produced methane, albeit at a much slower rate (Figure 4.15). Therefore, the substrate sludge from the acid-phase (55°C, 2 d) of the TPAD reactor certainly contained methanogenic archaea and syntrophic bacteria in its microflora. However, the extensive lag phase (10 days) indicates that their population was relatively small in proportion to the one from the inoculum sludge originating from the methane-phase (38°C, 28 d) reactor of the TPAD system. Addition of colonized granular biochar decreased the lag phase for methane production by 7 days compared to controls and generated methane at a faster rate than the controls belonging to the first-generation assays. 102 Figure 4.14: Graph of methane yield for first-generation BMP assays in B3-A All BMPs were set-up with substrate and inoculum sludge at an SIR of 4.4 g-VS/g-VS. Some of the BMP assays were amended with granular (0.850 – 4.75 mm) biochar at various dosages. Points represent averages and error bars are standard deviations of triplicate assays. Figure 4.15: Graph of methane yield for second-generation BMP assays in B3-B Some of the BMP assays were set-up with substrate sludge and colonized granular (0.850 – 4.750 mm) biochar, recovered from the first-generation assays, without inoculum addition, to assess bioaugmentation. Additional BMP bottles with substrate sludge and new granular biochar were also set-up, without inoculum addition, for comparison. Controls with substrate sludge and inoculum, from the first-generation were also graphed to facilitate discussion. Points represent averages and error bars are standard deviations of triplicate assays. 0501001502002503003504004500 2 4 6 8 10 12 14 16 18 20Cumulative methane yield (mL/g-VS)Time (days)ControlsGranular biochar 0.16 g/g-VS substrateGranular biochar 0.24 g/g-VS substrateGranular biochar 0.3 g/g-VS substrate01002003004005006000 10 20 30 40 50 60 70Cumulative methane yield (mL/g-VS)Time (days)New biochar 0.16 g/g-VS substrateNew biochar 0.24 g/g-VS substrateNew biochar 0.32 g/g-VS substrateColonized biochar 0.16 g/g-VS substrateColonized biochar 0.24 g/g-VS substrateColonized biochar 0.32 g/g-VS substrateControls first-generationNon-inoculated BMP assays (new biochar only)Non-inoculated BMP assays(colonized biochar from generation 1 only)Control generation 1 103 The previously described experiment (B3-A and B3-B) provided evidence that the amount of methanogens colonized on the granular biochar after 19 days of AD was greater than the population present in the substrate sludge. However, it was not possible from that experiment to compare the production of methane from colonized biochar with that of inoculum sludge because there were no assays containing inoculum sludge (the composition of bottles is listed in Appendix A). A comparison between methane production rate from colonized ZMM® T-Carbon and biochar was also desirable. Therefore, a second colonization experiment was conducted during B4 and B5, this time, the second-generation experiment (B5) included a set of controls with substrate and inoculum sludge and triplicate assays with colonized granular ZMM® T-Carbon and biochar. As discussed in section 4.3.1.2, in the first-generation BMP assays (B4), the rate of methane was faster (5.5 – 80%) for ZMM® T-Carbon amended bottles than controls between day 3 and 28, while biochar amended bottles produced less methane than controls in the first 18 days, and all bottles performed similarly from day 28 to the end of the experiment as shown in Figure 4.16. At day 59, the granular media was transferred to new bottles with fresh substrate for the second-generation (B5) experiment. As illustrated in Figure 4.17, the colonized biochar performed better than the colonized ZMM® T-Carbon throughout the assays’ duration. Both biochar and ZMM® T-Carbon produced methane at a slightly slower rate than controls until day 25 when all assays reached a similar cumulative methane yield with p = 0.086 and p = 0.370, respectively (the p-values calculated for each day of measurements are available in Appendix B). Results indicated that 1 g of colonized wet char was nearly as efficient for inoculation of BMP assays as 31 g of liquid inoculum sludge. 104 Figure 4.16: Graph of methane yield for first-generation BMP assays in B4 BMP assays were amended with granular (0.850 – 4.75 mm) biochar and ZMM® T-Carbon and with inoculum and substrate sludge. Points represent averages and error bars are standard deviations of triplicate assays. Figure 4.17: Graph of methane yield for second-generation BMP assays in B5 Some of the BMP assays were set-up with substrate sludge and colonized granular (0.850 – 4.750 mm) biochar and ZMM T-Carbon, recovered from the first-generation assays, without inoculum addition, to assess bioaugmentation. The controls contained substrate and inoculum sludge. Points represent averages and error bars are standard deviations of triplicate assays. 01002003004005006007000 10 20 30 40 50 60Cumulative methane yield (mL/g-VS)Time (days)ControlsGranular biochar 2.2 g/g-VS substrateGranular ZMM T-Carbon 2.2 g/g-VS substrate01002003004005000 10 20 30 40 50Cumulative methane yield (mL/g-VS)Time (days)ControlsColonized granular biochar 0.8 g/g-VS substrateColonized granular ZMM T-Carbon 0.8 g/g-VSsubstrate 105 SEM images for both experiments confirmed that microorganisms colonized the granular biochar (Figure 4.18) and ZMM T-Carbon (Figure 4.19). The cells in the images lost their rounded shape and appear to have been damaged. This may have been because the specimen chamber was at a vacuum (requirement of the instrument) and the chemical fixation and dehydration was not sufficient to prevent partial cell wall collapse. Nonetheless, the size and general aspects of the cells and clusters resemble Methanosaeta and Methanosarcina, which are usually the most abundant acetate utilizing genera found in AD. Methanosaeta are non-motile rods of 2 to 6 μm in length and 0.8 to 1.3 μm wide (Patel and Sprott, 1990). Methanosarcina barkeri are non-motile coccoid and measure 1 to 2 μm in diameter (Whitman, 1985). Figure 4.18: SEM images of microorganisms growing inside the pores of the biochar at a magnification of 20,000x (left) and 5,000x (right) 106 Figure 4.19: SEM images of microorganisms growing inside the pores of the ZMM® T-Carbon at a magnification of 5,000x (left) and 10,000x (right) The results for pH, ammonia and alkalinity were significantly different for the BMP assays inoculated with colonized char than controls. The difference measured was probably caused by the inoculum sludge added to controls but not to the assays with second-generation char. The liquid phase of the digestate contained high concentrations of ammonia and alkalinity (Table 4.6) which also affected the pH. Total VFAs were not significantly different from controls for either types of char (p=0.19 and 0.12). Transferring microorganisms using char material instead of digestate had the secondary benefit of having BMP assays with lower ammonia concentrations. These results suggest that addition of granular char could increase methane production by supplementing the methane formers and syntrophic bacteria. In AD reactors operating at low SRTs (< 20 days), retention of methanogenic archaea is a bottleneck for methane production. Supplementing methane formers in AD reactors using char as a carrier media may increase overall process efficiency. Moreover, bioaugmentation processes using 107 biochar is a promising solution to accelerate the recovery of failing AD reactors or reduce the start-up time for new AD reactors. Table 4.6: Results of analyses of the liquid phase of second-generation BMP assays Parameter Controls BMP Assays with Colonized Biochar BMP Assays with Colonized ZMM® T-Carbon pH 7.69 (0.01)1 7.56 (0.04) 7.56 (0.01) Alkalinity (mg as CaCO3/L) 8,231 (91) 5,903 (52) 5,871 (61) Ammonia (mg/L) 1,356 (36) 690 (28) 707 (15) Total Volatile Fatty Acids (mg/L) 35 (10) 20 (3) 24 (3) 1Arithmetic average and, in parenthesis, standard deviation of triplicate assays. 108 Chapter 5: Conclusion Summary of Findings The Archaea Incubator is a novel technology in the design phase with an aim to increase methane production in anaerobic digestion reactors by bioaugmenting the relative population of methane producing microorganisms. The goal of this research was to assess the suitability of biochar and wood ash to serve as carrier media for the Archaea Incubator. The biochar was selected based on evidence from the literature of its beneficial effects in anaerobic digesters and as a soil amendment. Benefits associated with biochar are related to its high surface area for biofilm formation, electrical conductivity, adsorption of inhibitory compounds such as ammonium and pH buffering capacity. In studies with anaerobic digesters, these beneficial effects translated in higher total methane yield, increased rate of methane production and a shorter lag phase. In this research study, biochar and ZMM® T-Carbon amendment had similar effects as reported in the literature with the exception of an earlier plateau in methane production than controls when powdered (< 0.075 mm) biochar was added to the biochemical methane potential assays. Indirect experimental evidences led to the hypothesis that volatile fatty acid adsorption might have been responsible for the early stationary methane production phase. Adsorption of volatile fatty acid by biochar was not previously documented in the literature, although studies have measured volatile fatty acid adsorption on activated carbon. The outcomes of each objectives defined at the start of this research study are summarized in the following paragraphs. Biochemical methane potential assays were conducted to evaluate the effect of size, amount and type of char particles on the anaerobic digestion of acidified mixed sludge from Lulu Island wastewater treatment plant. Powdered (<0.075 mm) biochar increased the rate of production of methane by 192 ± 65% to 461 ± 195% in biochemical methane potential assays amended with 0.8-3.7 g/g-VSsubstrate compared to controls, during the first 16 days. Powdered 109 (<0.075 mm) biochar amended assays reached an early stationary methane production phase leading to a reduction of total methane yield ranging from 9 ± 4% at the lowest dosage to 25 ± 1% at the highest dosage. There was generally no significant difference in total methane yield from granular (0.85-4.75 mm) biochar at dosages up to 2.2 g/g-VSsubstrate. However, production was hindered at a dosage of 3.7 g/g-VSsubstrate. Ultimate methane yields from ZMM® T-Carbon amended assays were either not significantly different from controls or were lower throughout the digestion process except for granular (0.85-4.75 mm) ZMM® T-Carbon at 2.2 g/g-VSsubstrate. ZMM® T-Carbon might provide nutrients that stimulate microbial activity when degradable organic loading is high. There was a decline in methane yield of 11 ± 2% to 13 ± 2% was measured for both particle sizes of ZMM® T-Carbon at a dosage of 3.7 g/g-VSsubstrate. The biochemical methane potential assays were analyzed for ammonia nitrogen, volatile fatty acids, pH and alkalinity, in order to determine if the benefits of char could be tied with high concentrations of inhibitory compounds, which occur when the organic loading rate is high. In this study, the controls from two separate experiments yield the highest methane yield at sludge to inoculum ratio of 2.2 g-VS/g-VS, and the lowest at a sludge to inoculum ratio of 3.2 and 4.4 g-VS/g-VS, due to inhibitory conditions. The biochar was shown to alleviate acid stress at the highest sludge to inoculum ratio of 4.4 g-VS/g-VS. The assays amended with biochar had less acetic, butyric and propionic acids than controls, and shorter lag phases. The leading explanation was adsorption of volatile fatty acids, followed by the buffering effect of biochar and adsorption of ammonium. Biofilm formation comprised of syntrophic bacteria and methanogenic archaea facilitating direct interspecies electron transfer may also be favorable factors. Salt toxicity and presence of toxic compounds were considered as possible sources of inhibition. Permanent inhibition and ammonia toxicity was disproven as a cause for the early plateau in methane yield and evidence point towards adsorption of volatile fatty acids by biochar. Granular 110 (0.85-4.75 mm) ZMM® T-Carbon reduced concentrations of ammonia nitrogen by 14% relative to controls. Biochemical methane potential assays inoculated with granular (0.85 – 4.75 mm) biochar and ZMM® T-Carbon selected from anaerobic digesters, and fresh substrate were conducted to assess the suitability of biochar and wood ash media to carry syntrophic bacteria and methanogenic archaea for bioaugmentation of a methane forming anaerobic digester. The second-generation biochemical methane potential assays produced methane at a similar rate than controls when biochar and ZMM® T-Carbon in granular form (0.85-4.75 mm) were used as inoculant. Therefore, methanogenic archaea and syntrophic bacteria successfully colonized both types of char. Scanning electron micrograph images showed microorganisms and biofilm on the surface of both granular media. In light of the results, both media would be suitable microorganism carriers for the Archaea Incubator. Strength and Limitations of Research The performance of biochar and ZMM® T-Carbon was assessed in controlled conditions in a laboratory setting in batch bioassays, which ensured replicability. However, the substrate sludge was sourced from a wastewater, which may fluctuate at full-scale. This complicated the comparison of results from different batches of biochemical methane potential assays. Moreover, mixed cultures fed with sewage sludge make it challenging to find evidence of direct interspecies electron transfer because of the complexity and diversity of biochemical pathways occurring. Therefore, in this study, occurrence of direct interspecies electron transfer was not investigated. Ideally, all treatment variations would have been performed simultaneously although this was not possible because of limited time and resources such as space in the shaker and volume of inoculum sludge. Conducting the biochemical methane potential analyses in several batches had the beneficial effect of allowing an iterative approach to determine the appropriate dosage of char and to answer some of the questions that arose during the 111 experiments. Results from biochemical methane potential assays notoriously translate poorly to full-scale reactors. It is recommended to use the biochemical methane potential assay method as an estimation tool to screen the most performant treatments and repeat the treatment in a semi-continuously fed bench-scale configuration, before the pilot scale. The Bioreactor Technology Group laboratory does not specialize in genomics. Samples for the microbial fingerprinting analyses are stored at -80°C and will be analyzed at a later date by Dr. Hallam’s expert group at the University of British Columbia in Vancouver. The procedure used for the bioaugmentation test (first and second-generation biochemical methane potential assays with granular media) was effective at rapidly identifying the presence of methane forming microorganisms on the media. The procedure was designed by the Bioreactor Technology Group and inspired from classical microbiology techniques but it should be refined and standardized. Potential Applications of Research Findings The temperature phase anaerobic digester process of wastewater sludge is amongst the most efficient for methane generation. Based on batch biochemical methane potential assays, the results suggest that addition of powdered (<0.075 mm) biochar could further reduce the sludge retention time by stimulating methane formation. Powdered biochar may also be suitable to be added to failing anaerobic digestion reactors to decrease the accumulation of volatile fatty acids. Digesters with nutrient deficiencies and high in inhibitory ammonium concentrations may benefit from the addition of granular ZMM® T-Carbon since it was found to reduce by up to 14% the ammonia nitrogen in biochemical methane potential assays. Both granular biochar and ZMM T-Carbon would be suitable media for bioaugmentation with the Archaea Incubator. 112 Future Work Directions Future work at the Bioreactor Technology Group should investigate the following: • The effects of biochar amendment to various other substrate types such as mixed sludge, primary sludge, secondary sludge and pre-treated sludge from several different wastewater treatment plants to determine if the effects of biochar on anaerobic digestion vary with substrate origin. • Test other carbon based materials such as carbon cloth, felt, mesh and brush. • Preliminary batch volatile fatty acid adsorption studies (not included in this study) indicated adsorption of volatile fatty acids may be a factor. Adsorption of volatile fatty acids should be studied more extensively and kinetic parameters calculated to verify it is occurring and its extent. • Develop a method to fix microorganisms on the powdered char material for scanning electron micrograph analysis. • Design a system for retention of powdered biochar to facilitate bioaugmentation of an anaerobic digestion reactor. • Build a larger-scale Archaea Incubator with amended powdered biochar, continuously-fed to simulate full-scale digester operation. • Investigate further the reduction of ammonium by ZMM® T-Carbon. • Measure the pore area and surface area of the char material. 113 References Ahring, B.K., Sandberg, M., Angelidaki, I., 1995. Volatile fatty acids as indicators of process imbalance in anaerobic digestors. Appl. Microbiol. Biotechnol. 43, 559–565. Aktaş, Ö., Çeçen, F., 2007. Bioregeneration of activated carbon: A review. Int. Biodeterior. 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Technol. 191, 140–145. https://doi.org/10.1016/j.biortech.2015.05.007 124 APPENDICES Composition of BMP Assays 125 Table A-1: BMP assay composition for each BMP assay treatmenta SIRb Char Dosage Char Size Type of Char Volume Substrate Volume Inoculum Weight Char Volume Water VSe Substrate VS Inoculum TSf Substrate TS Inoculum Na2CO3 KHCO3 g-VS/g-VS g/g-TS Inoculum g/g-VS Substrate G pr Pc B or Zd mL mL g mL g g g g g g B1 2.2 1 0.6 P B 19 20 0.37 41 0.64 0.29 0.75 0.40 0.17 0.16 2.2 2 1.2 P B 19 20 0.75 41 0.64 0.29 0.75 0.40 0.17 0.16 2.2 3 1.8 P B 19 20 1.12 41 0.64 0.29 0.75 0.40 0.17 0.16 3.2 1 0.4 P B 28 20 0.37 32.5 0.92 0.29 1.09 0.40 0.17 0.16 3.2 2 0.8 P B 28 20 0.75 32.5 0.92 0.29 1.09 0.40 0.17 0.16 3.2 3 1.2 P B 28 20 1.12 32.5 0.92 0.29 1.09 0.40 0.17 0.16 4.4 1 0.3 P B 38 20 0.37 22 1.27 0.29 1.51 0.40 0.17 0.16 4.4 2 0.6 P B 38 20 0.75 22 1.27 0.29 1.51 0.40 0.17 0.16 4.4 3 0.9 P B 38 20 1.12 22 1.27 0.29 1.51 0.40 0.17 0.16 N/A 1 N/A P B 0 20 0.37 0 0.00 0.29 0.00 0.40 0.00 0.00 N/A 2 N/A P B 0 20 0.75 0 0.00 0.29 0.00 0.40 0.00 0.00 N/A 3 N/A P B 0 20 1.12 0 0.00 0.29 0.00 0.40 0.00 0.00 N/A N/A N/A N/A N/A 0 20 0 0 0.00 0.29 0.00 0.40 0.00 0.00 2.2 N/A N/A N/A N/A 19 20 0 41 0.64 0.29 0.75 0.40 0.17 0.16 3.2 N/A N/A N/A N/A 28 20 0 32.5 0.92 0.29 1.09 0.40 0.17 0.16 4.4 N/A N/A N/A N/A 38 20 0 22 1.27 0.29 1.51 0.40 0.17 0.16 B2 2.2 1 0.6 P Z 13 20 0.30 37.00 0.49 0.22 0.55 0.30 0.15 0.14 2.2 2 1.2 P Z 13 20 0.60 37.00 0.49 0.22 0.55 0.30 0.15 0.14 2.2 3 1.9 P Z 13 20 0.90 37.00 0.49 0.22 0.55 0.30 0.15 0.14 2.2 0 N/A N/A N/A 13 20 0.00 37.00 0.49 0.22 0.55 0.30 0.15 0.14 3.2 1 0.4 P Z 19 20 0.30 31.00 0.71 0.22 0.81 0.30 0.15 0.14 3.2 2 0.8 P Z 19 20 0.60 31.00 0.71 0.22 0.81 0.30 0.15 0.14 3.2 3 1.3 P Z 19 20 0.90 31.00 0.71 0.22 0.81 0.30 0.15 0.14 126 SIRb Char Dosage Char Size Type of Char Volume Substrate Volume Inoculum Weight Char Volume Water VSe Substrate VS Inoculum TSf Substrate TS Inoculum Na2CO3 KHCO3 g-VS/g-VS g/g-TS Inoculum g/g-VS Substrate G pr Pc B or Zd mL mL g mL g g g g g g 3.2 0 N/A N/A N/A 19 20 0.00 31.00 0.71 0.22 0.81 0.30 0.15 0.14 4.4 1 0.3 P Z 26 20 0.30 24.00 0.98 0.22 1.10 0.30 0.15 0.14 4.4 2 0.6 P Z 26 20 0.60 24.00 0.98 0.22 1.10 0.30 0.15 0.14 4.4 3 0.9 P Z 26 20 0.90 24.00 0.98 0.22 1.10 0.30 0.15 0.14 4.4 0 N/A N/A N/A 26 20 0.00 24.00 0.98 0.22 1.10 0.30 0.15 0.14 0 N/A N/A P Z 0 20 0.30 0.00 0.00 0.22 0.00 0.30 0.00 0.00 0 N/A N/A P Z 0 20 0.60 0.00 0.00 0.22 0.00 0.30 0.00 0.00 0 N/A N/A P Z 0 20 0.90 0.00 0.00 0.22 0.00 0.30 0.00 0.00 0 N/A N/A N/A N/A 0 20 0.00 0.00 0.00 0.22 0.00 0.30 0.00 0.00 B3-A 4.4 0.5 0.16 G B 39 23 0.21 18 1.27 0.29 1.40 0.41 0.17 0.16 4.4 0.75 0.24 G B 39 23 0.31 18 1.27 0.29 1.40 0.41 0.17 0.16 4.4 1 0.33 G B 39 23 0.41 18 1.27 0.29 1.40 0.41 0.17 0.16 4.4 0 N/A N/A N/A 39 23 0.00 18 1.27 0.29 1.40 0.41 0.17 0.16 0 0 N/A N/A N/A 0 23 0.00 0.00 0.00 0.29 0.00 0.41 0.00 0.00 B3-B N/A N/A 0.16 G B 35 0 0.21 41.00 1.27 N/A 1.47 N/A 0.15 0.16 N/A N/A 0.24 G B 35 0 0.31 41.00 1.27 N/A 1.47 N/A 0.15 0.16 N/A N/A 0.33 G B 35 0 0.41 41.00 1.27 N/A 1.47 N/A 0.15 0.16 N/A N/A 0.16 G B 35 0 0.21 41.00 1.27 N/A 1.47 N/A 0.15 0.16 N/A N/A 0.24 G B 35 0 0.31 41.00 1.27 N/A 1.47 N/A 0.15 0.16 N/A N/A 0.33 G B 35 0 0.41 41.00 1.27 N/A 1.47 N/A 0.15 0.16 B4 4.4 0 2.2 N/A N/A 38 26 0 16 1.25 0.28 1.42 0.46 0.00 0.00 4.4 0 2.2 N/A N/A 38 26 0 16 1.25 0.28 1.42 0.46 0.17 0.16 4.4 6 2.2 G B 38 26 2.78 16 1.25 0.28 1.42 0.46 0.00 0.00 127 SIRb Char Dosage Char Size Type of Char Volume Substrate Volume Inoculum Weight Char Volume Water VSe Substrate VS Inoculum TSf Substrate TS Inoculum Na2CO3 KHCO3 g-VS/g-VS g/g-TS Inoculum g/g-VS Substrate G pr Pc B or Zd mL mL g mL g g g g g g 4.4 6 2.2 G B 38 26 2.78 16 1.25 0.28 1.42 0.46 0.17 0.16 4.4 6 2.2 G B+Z 38 26 2.78 16 1.25 0.28 1.42 0.46 0.00 0.00 4.4 6 2.2 G B+Z 38 26 2.78 16 1.25 0.28 1.42 0.46 0.17 0.16 4.4 6 2.2 G Z 38 26 2.78 16 1.25 0.28 1.42 0.46 0.00 0.00 4.4 6 2.2 G Z 38 26 2.78 16 1.25 0.28 1.42 0.46 0.17 0.16 N/A 6 2.2 N/A N/A 0 26 0 0 0.00 0.28 0.00 0.46 0.00 0.00 B5 4.4 0 0.0 N/A N/A 31 27 0.00 18 1.25 0.29 1.40 0.38 0.17 0.16 N/A N/A 0.0 G Z 31 0 0.00 45 1.25 0.00 1.40 0.00 0.17 0.16 N/A N/A 0.0 G B 31 0 0.00 45 1.25 0.00 1.40 0.00 0.17 0.16 4.4 6 1.8 P B 31 27 2.29 18 1.25 0.29 1.40 0.38 0.17 0.16 4.4 6 1.8 P Z 31 27 2.29 18 1.25 0.29 1.40 0.38 0.17 0.16 4.4 12 3.7 G B 31 27 4.58 18 1.25 0.29 1.40 0.38 0.17 0.16 4.4 12 3.7 P B 31 27 4.58 18 1.25 0.29 1.40 0.38 0.17 0.16 4.4 12 3.7 G Z 31 27 4.58 18 1.25 0.29 1.40 0.38 0.17 0.16 4.4 12 3.7 P Z 31 27 4.58 18 1.25 0.29 1.40 0.38 0.17 0.16 4.4 3 0.9 G B 31 27 1.15 18 1.25 0.29 1.40 0.38 0.17 0.16 4.4 3 0.9 G Z 31 27 1.15 18 1.25 0.29 1.40 0.38 0.17 0.16 N/A N/A N/A N/A N/A 0 27 0.00 0 0.00 0.29 0.00 0.38 0.00 0.00 B6 4.4 0 0.0 N/A N/A 35.5 24 0.00 20.5 1.28 0.29 1.52 0.43 0.17 0.16 4.4 9 3.0 P B 35.5 24 3.85 20.5 1.28 0.29 1.52 0.43 0.00 0.00 4.4 9 3.0 P B 35.5 24 3.85 20.5 1.28 0.29 1.52 0.43 0.17 0.16 N/A N/A N/A N/A N/A 0.00 24 0.00 0.0 0.00 0.29 0.00 0.43 0.00 0.00 B7 4.4 0 0.0 N/A N/A 35 22 0 13 1.3195 0.2992 1.54665 0.4114 0.15 0.14 128 SIRb Char Dosage Char Size Type of Char Volume Substrate Volume Inoculum Weight Char Volume Water VSe Substrate VS Inoculum TSf Substrate TS Inoculum Na2CO3 KHCO3 g-VS/g-VS g/g-TS Inoculum g/g-VS Substrate G pr Pc B or Zd mL mL g mL g g g g g g 4.4 1 0.3 G Z 35 22 0.416 13 1.3195 0.2992 1.54665 0.4114 0.15 0.14 4.4 2 0.6 G Z 35 22 0.831 13 1.3195 0.2992 1.54665 0.4114 0.15 0.14 N/A N/A N/A N/A N/A 0 22 0 0 0 0.2992 0 0.4114 0.00 0.00 a: Table summarizes composition of each treatment, which was identical in the triplicate bottles. b: Substrate to inoculum ratio c: B is for biochar and Z is for ZMM T-Carbon d: G is for granular (0.085-4.75 mm) and P is for powder (< 0.075 mm) e: Volatile solids f: Total solids 129 Statistical Analysis Table B-1: Example of statistical analysis using the two sample Student’s t-testa Cumulative Time (days) Methane production in mL/g-VSsubstrate for Controls (μ1) Methane production in mL/g-VSsubstrate ZMM T-Carbon 0.6 g/g-VSsubstrate (μ2) Two Sample Student’s t-Test Replicate 1 Replicate 2 Replicate 3 Replicate 1 Replicate 2 Replicate 3 P-value 2 tails 0 0 0 0 0 0 0 - 2.4 8.8 6.8 7.1 5.1 4.3 7.2 0.132b 3.3 18.8 13.2 15.2 10.6 9.1 16.1 0.236 4.4 34.5 27.5 31.0 24.4 22.0 30.7 0.184 5.6 55.1 51.3 51.4 47.7 45.3 48.7 0.029 6.3 71.6 68.8 67.3 66.7 64.9 62.7 0.061 7.4 116.9 115.8 111.4 119.9 117.1 107.5 0.980 8.3 168.2 165.1 161.0 167.5 162.3 163.1 0.858 9.5 214.4 220.2 224.1 232.3 220.2 225.9 0.220 10.4 265.2 273.0 272.6 283.7 265.8 274.1 0.511 11.5 314.4 325.7 324.9 328.0 318.2 320.9 0.886 12.5 332.9 345.7 342.5 351.9 344.8 341.6 0.311 13.6 357.3 358.5 355.7 365.5 361.3 362.1 0.026 14.3 371.1 377.3 365.7 376.2 371.5 374.8 0.509 15.4 383.3 390.7 383.0 397.3 388.0 391.6 0.150 17.5 424.9 417.7 409.4 461.5 442.6 454.1 0.008 20.6 468.6 477.0 467.4 474.9 475.8 472.7 0.364 24.4 481.4 488.3 478.9 484.8 486.9 484.6 0.463 30.5 502.7 508.3 501.5 501.0 502.3 502.7 0.409 36.3 514.1 523.2 514.7 509.7 514.2 510.2 0.167 48.3 524.4 532.9 524.6 522.2 526.1 524.5 0.402 a: Using Microsoft Excel function TTEST with 2 tails, assuming population are normally distributed, are independent and have unequal variance. Null hypothesis H0: μ1 = μ2 and alternate hypothesis H1: μ1 ≠ μ2 b: The lower the p-value and the higher the probability that the null hypothesis should be rejected in favor of the alternate hypothesis. Although there are some outliers (day 5.6, 6.3, 13.6 and 17.5), in general, the Char amended assays were not significantly different from Controls throughout the BMP period. 130 Table B-2: Statistical analysis of cumulative methane production assays with powdered biochar (μ2) and controls (μ1) using the two sample Student’s t-test for B1 at SIR = 2.2 g-VS/g-VS Cumulative Time (days) P-value, 2 Tailsa Powdered Biochar 0.6 g/g-VSsubstrate Powdered Biochar 1.2 g/g-VSsubstrate Powdered Biochar 1.8 g/g-VSsubstrate 1 0.712 0.210 0.101 3 0.065 0.013 0.000 4 0.090 0.004 0.000 5 0.079 0.001 0.000 7 0.334 0.001 0.000 8 0.316 0.002 0.001 9 0.094 0.006 0.009 10 0.093 0.002 0.009 11 0.117 0.002 0.022 13 0.062 0.035 0.176 16 0.278 0.747 0.134 20 0.101 0.159 0.035 24 0.117 0.133 0.030 31 0.133 0.118 0.033 49 0.108 0.078 0.025 a: Null hypothesis H0: μ1 = μ2 and alternate hypothesis H1: μ1 ≠ μ2 131 Table B-3: Statistical analysis of cumulative methane production assays with powdered biochar (μ2) and controls (μ1) using the two sample Student’s t-test for B1 at SIR = 3.2 g-VS/g-VS Cumulative Time (days) P-value, 2 Tailsa Powdered Biochar 0.4 g/g-VSsubstrate SIR = 3.2 g-VS/g-VS Powdered Biochar 0.8 g/g-VSsubstrate SIR = 3.2 g-VS/g-VS Powdered Biochar 1.2 g/g-VSsubstrate SIR = 3.2 g-VS/g-VS 1 0.494 0.943 0.922 3 0.052 0.002 0.052 4 0.034 0.002 0.010 5 0.101 0.009 0.019 6 0.917 0.109 0.022 8 0.357 0.364 0.019 10 0.099 0.949 0.006 11 0.102 0.998 0.018 12 0.167 0.520 0.015 13 0.185 0.277 0.015 14 0.128 0.112 0.026 16 0.045 0.242 0.295 19 0.617 0.185 0.141 25 0.834 0.149 0.089 33 0.876 0.091 0.057 45 0.767 0.062 0.037 49 0.530 0.034 0.021 a: Null hypothesis H0: μ1 = μ2 and alternate hypothesis H1: μ1 ≠ μ2 132 Table B-4: Statistical analysis comparing cumulative methane production assays with powdered biochar (μ2) and controls (μ1) using the two sample Student’s t-test for B1 at SIR = 4.4 g-VS/g-VS a: Null hypothesis H0: μ1 = μ2 and alternate hypothesis H1: μ1 ≠ μ2 Cumulative Time (days) P-value, 2 Tailsa Powdered Biochar 0.3 g/g-VSsubstrate Powdered Biochar 0.6 g/g-VSsubstrate Powdered Biochar 0.9 g/g-VSsubstrate 1 0.575 0.324 0.880 3 0.978 0.113 0.805 4 0.760 0.162 0.557 5 0.030 0.300 0.830 6 0.030 0.664 0.398 7 0.047 0.727 0.063 8 0.045 0.295 0.009 9 0.535 0.826 0.014 10 0.973 0.594 0.083 11 0.790 0.667 0.126 12 0.244 0.441 0.454 13 0.163 0.341 0.966 14 0.089 0.228 0.530 15 0.061 0.044 0.138 16 0.010 0.014 0.032 18 0.095 0.164 0.251 21 0.253 0.720 0.880 26 0.120 0.909 0.553 34 0.206 0.931 0.535 41 0.159 0.931 0.377 49 0.188 0.923 0.470 133 Table B-5: Statistical analysis comparing cumulative methane production assays with powdered ZMM® T-Carbon (μ2) and controls (μ1) using the two sample Student’s t-test for B2 at SIR = 2.2 g-VS/g-VS Cumulative Time (days) P-value, 2 Tailsa Powdered ZMM T-Carbon 0.6 g/g-VSsubstrate Powdered ZMM T-Carbon 1.2 g/g-VSsubstrate Powdered ZMM T-Carbon 1.9 g/g-VSsubstrate 2 0.367 0.034 0.014 4 0.541 0.063 0.012 6 0.703 0.037 0.029 7 0.466 0.054 0.046 9 0.396 0.078 0.101 11 0.286 0.148 0.273 14 0.222 0.427 0.228 18 0.117 0.850 0.075 24 0.314 0.382 0.047 32 0.493 0.393 0.092 49 0.403 0.534 0.148 a: Null hypothesis H0: μ1 = μ2 and alternate hypothesis H1: μ1 ≠ μ2 134 Table B-6: Statistical analysis comparing cumulative methane production assays with powdered ZMM® T-Carbon (μ2) and controls (μ1) using the two sample Student’s t-test for B2 at SIR = 3.2 g-VS/g-VS Cumulative Time (days) P-value, 2 Tailsa Powdered ZMM T-Carbon 0.4 g/g-VSsubstrate Powdered ZMM T-Carbon 0.8 g/g-VSsubstrate Powdered ZMM T-Carbon 1.3 g/g-VSsubstrate 2 0.041 0.102 0.003 4 0.207 0.230 0.006 5 0.913 0.878 0.046 6 0.426 0.214 0.129 7 0.197 0.052 0.852 8 0.126 0.044 0.455 9 0.182 0.101 0.651 10 0.189 0.128 0.708 11 0.227 0.148 0.702 13 0.427 0.148 0.182 16 0.766 0.027 0.899 20 0.922 0.100 0.397 24 0.756 0.142 0.325 32 0.637 0.131 0.421 49 0.460 0.097 0.447 a: Null hypothesis H0: μ1 = μ2 and alternate hypothesis H1: μ1 ≠ μ2 135 Table B-7: Statistical analysis comparing cumulative methane production assays with powdered ZMM® T-Carbon (μ2) and controls (μ1) using the two sample Student’s t-test for B2 at SIR = 4.4 g-VS/g-VS a: Null hypothesis H0: μ1 = μ2 and alternate hypothesis H1: μ1 ≠ μ2 Cumulative Time (days) P-value, 2 Tails Powdered ZMM T-Carbon 0.3 g/g-VSsubstrate Powdered ZMM T-Carbon 0.6 g/g-VSsubstrate Powdered ZMM T-Carbon 0.9 g/g-VSsubstrate 2 0.354 0.434 0.012 3 0.404 0.442 0.010 4 0.957 0.720 0.035 5 0.886 0.871 0.208 6 0.638 0.724 0.579 7 0.204 0.193 0.062 8 0.131 0.154 0.101 9 0.097 0.242 0.575 10 0.045 0.310 0.774 11 0.022 0.253 0.518 12 0.107 0.305 0.353 14 0.016 0.282 0.175 17 0.353 0.422 0.811 20 0.653 0.215 0.388 24 0.316 0.336 0.885 32 0.421 0.147 0.988 49 0.361 0.144 0.810 136 Table B-8: Statistical analysis comparing cumulative methane production assays with granular biochar (μ2) and controls (μ1) using the two sample Student’s t-test for B3-A at SIR = 4.4 g-VS/g-VS Cumulative Time (days) P-value, 2 Tailsa Granular Biochar 0.16 g/g-VSsubstrate Granular Biochar 0.24 g/g-VSsubstrate Granular Biochar 0.33 g/g-VSsubstrate 2 0.078 0.130 0.059 3 0.218 0.052 0.009 4 0.350 0.288 0.208 5 0.107 0.151 0.020 6 0.384 0.528 0.115 7 0.436 0.376 0.105 8 0.009 0.006 0.011 9 0.007 0.001 0.003 10 0.003 0.000 0.001 11 0.001 0.009 0.002 12 0.000 0.167 0.001 13 0.006 0.097 0.001 14 0.053 0.172 0.001 15 0.186 0.439 0.024 16 0.373 0.671 0.070 18 0.388 0.850 0.188 19 0.505 0.897 0.169 a: Null hypothesis H0: μ1 = μ2 and alternate hypothesis H1: μ1 ≠ μ2 137 Table B-9: Statistical analysis comparing cumulative methane production assays with granular char (μ2) and controls (μ1) with added buffer using the two sample Student’s t-test for B4 at SIR = 4.4 g-VS/g-VS Cumulative Time (days) P-value, 2 Tails Granular Biochar 2.2 g/g-VSsubstrate Granular ZMM T-Carbon 2.2 g/g-VSsubstrate Granular Biochar and ZMM T-Carbon (1:1) 2.2 g/g-VSsubstrate 2 0.113 0.316 0.156 3 0.645 0.289 0.426 4 0.485 0.009 0.026 5 0.381 0.032 0.090 6 0.600 0.185 0.733 7 0.046 0.024 0.468 8 0.036 0.055 0.293 9 0.072 0.047 0.289 10 0.345 0.029 0.785 11 0.186 0.047 0.777 12 0.085 0.038 0.329 13 0.050 0.022 0.180 14 0.038 0.041 0.103 15 0.063 0.106 0.127 16 0.151 0.082 0.907 17 0.487 0.054 0.227 18 0.889 0.047 0.282 19 0.655 0.040 0.141 21 0.484 0.016 0.012 23 0.246 0.048 0.019 25 0.126 0.104 0.093 28 0.971 0.633 0.660 31 0.727 0.728 0.737 46 0.848 0.838 0.598 59 0.883 0.811 0.585 a: Null hypothesis H0: μ1 = μ2 and alternate hypothesis H1: μ1 ≠ μ2 138 Table B-10: Statistical analysis comparing cumulative methane production assays with granular char (μ2) and controls (μ1) without added buffer using the two sample Student’s t-test for B4 at SIR = 4.4 g-VS/g-VS Cumulative Time (days) P-value, 2 Tailsa Granular Biochar 2.2 g/g-VSsubstrate Granular ZMM T-Carbon 2.2 g/g-VSsubstrate Granular Biochar and ZMM T-Carbon (1:1) 2.2 g/g-VSsubstrate 2 0.018 0.693 0.304 3 0.007 0.745 0.613 4 0.002 0.090 0.987 5 0.570 0.224 0.273 6 0.119 0.207 0.289 7 0.251 0.200 0.300 9 0.307 0.351 0.871 10 0.203 0.500 0.943 11 0.160 0.487 0.684 12 0.199 0.480 0.405 13 0.125 0.481 0.124 14 0.115 0.522 0.111 15 0.143 0.598 0.140 16 0.277 0.620 0.291 17 0.566 0.671 0.610 18 0.856 0.764 0.916 19 0.986 0.886 1.000 20 0.979 0.928 0.971 21 0.912 0.958 0.969 22 0.747 0.931 0.947 23 0.756 0.882 0.928 24 0.928 0.997 0.912 25 0.863 0.809 0.755 26 0.531 0.524 0.527 29 0.201 0.257 0.220 32 0.193 0.212 0.136 35 0.526 0.443 0.359 42 0.574 0.801 0.945 46 0.214 0.479 0.582 59 0.112 0.265 0.231 a: Null hypothesis H0: μ1 = μ2 and alternate hypothesis H1: μ1 ≠ μ2 139 Table B-11: Statistical analysis comparing cumulative methane production assays with char (μ2) and controls (μ1) using the two sample Student’s t-test for B5 at SIR = 4.4 g-VS/g-VS Cumulative Time (days) P-value, 2 Tails G Biochar 3.7 g/g-VSsubstrate G ZMM T-Carbon 3.7 g/g-VSsubstrate P Biochar 3.7 g/g-VSsubstrate P ZMM T-Carbon 3.7 g/g-VSsubstrate P Biochar 1.8 g/g-VSsubstrate P ZMM T-Carbon 1.8 g/g-VSsubstrate G Biochar 0.9 g/g-VSsubstrate G ZMM T-Carbon 0.9 g/g-VSsubstrate 2 0.077 0.021 0.000 0.000 0.001 0.000 0.162 0.268 3 0.205 0.018 0.000 0.004 0.000 0.009 0.149 0.235 4 0.035 0.011 0.000 0.000 0.000 0.002 0.201 0.211 5 0.080 0.017 0.000 0.001 0.000 0.010 0.427 0.136 6 0.043 0.098 0.000 0.001 0.000 0.053 0.252 0.040 7 0.003 0.044 0.000 0.003 0.000 0.318 0.021 0.013 8 0.001 0.014 0.000 0.005 0.000 0.037 0.002 0.028 9 0.000 0.001 0.001 0.017 0.000 0.002 0.001 0.048 10 0.000 0.000 0.001 0.194 0.001 0.006 0.006 0.030 11 0.000 0.000 0.001 0.009 0.000 0.091 0.009 0.026 12 0.000 0.000 0.002 0.004 0.000 0.084 0.016 0.021 13 0.001 0.001 0.018 0.010 0.000 0.199 0.010 0.025 14 0.000 0.005 0.002 0.000 0.000 0.418 0.004 0.008 15 0.000 0.002 -b 0.003 - 0.844 0.006 0.010 16 0.000 0.004 0.000 0.019 0.006 0.260 0.009 0.013 17 0.000 0.004 - 0.228 - 0.099 0.033 0.017 18 0.000 0.009 - 0.117 - 0.123 0.192 0.222 20 0.000 0.002 - 0.003 - 0.076 - - 22 - 0.002 0.000 0.002 0.006 0.060 - - 25 0.001 0.003 0.000 0.002 0.002 0.044 0.792 0.314 32 - 0.002 - 0.001 - 0.020 - 0.084 38 - 0.002 - 0.001 - 0.014 - 0.108 49 0.003 0.002 0.000 0.001 0.000 0.011 0.541 0.104 a: Null hypothesis H0: μ1 = μ2 and alternate hypothesis H1: μ1 ≠ μ2 b: Assays were not measured on that day. 140 Table B-12: Statistical analysis comparing cumulative methane production assays using the two sample Student’s t-test for B5 Cumulative Time (days) P-value, 2 Tailsa Colonized Biochar (μ2) versus Controls (μ1) Colonized ZMM T-Carbon (μ2) versus Controls (μ1) Colonized Biochar (μ1) versus ZMM T-Carbon (μ2) 2 0.001 0.001 0.062 4 0.000 0.001 0.063 5 0.000 0.000 0.021 6 0.006 0.001 0.005 7 0.185 0.002 0.014 8 0.174 0.001 0.013 9 0.017 0.001 0.016 10 0.004 0.000 0.036 11 0.016 0.001 0.125 12 0.015 0.001 0.137 13 0.020 0.000 0.096 14 0.015 0.000 0.011 15 0.002 0.001 0.004 16 0.001 0.004 0.033 17 0.001 0.002 0.069 18 0.011 0.002 0.043 19 0.006 0.001 0.041 21 0.003 0.003 0.381 23 0.125 0.068 0.678 25 0.086 0.370 0.689 29 0.220 0.584 0.893 36 0.326 0.992 0.650 49 0.500 0.832 0.606 a: Null hypothesis H0: μ1 = μ2 and alternate hypothesis H1: μ1 ≠ μ2 141 Table B-13: Statistical analysis comparing cumulative methane production assays using the two sample Student’s t-test for B6 at SIR = 4.4 g-VS/g-VS Cumulative Time (days) P-value, 2 Tailsa Powdered Biochar 3.0 g/g-VSsubstrate With Buffer (μ2) Versus Controls (μ1) Powdered Biochar 3.0 g/g-VSsubstrate Without Buffer (μ2) Versus Controls (μ1) Powdered Biochar With Buffer (μ1) Versus Without Buffer (μ2) 1 0.080 0.222 0.465 2 0.001 0.029 0.065 3 0.000 0.021 0.061 4 0.000 0.025 0.068 5 0.000 0.022 0.074 6 0.000 0.015 0.067 7 0.003 0.002 0.024 8 0.000 0.001 0.004 9 0.001 0.471 0.003 10 0.195 0.018 0.007 11 0.611 0.040 0.024 12 0.445 0.046 0.047 13 0.369 0.020 0.048 14 0.045 0.003 0.020 16 0.015 0.002 0.018 19 0.000 0.000 0.019 23 0.000 0.000 0.025 30 0.000 0.000 0.043 a: Null hypothesis H0: μ1 = μ2 and alternate hypothesis H1: μ1 ≠ μ2 142 Table B-14: Statistical analysis comparing cumulative methane production assays with Granular ZMM® T-Carbon (μ2) and controls (μ1) using the two sample Student’s t-test for B7 at SIR = 4.4 g-VS/g-VS Cumulative Time (days) P-value, 2 Tailsa Granular ZMM T-Carbon 0.3 g/g-VSsubstrate Granular ZMM T-Carbon 0.6 g/g-VSsubstrate 2 0.132 0.120 3 0.236 0.177 4 0.184 0.241 6 0.029 0.180 6 0.061 0.395 7 0.980 0.565 8 0.858 0.680 10 0.220 0.448 10 0.511 0.593 11 0.886 0.916 12 0.311 0.469 14 0.026 0.076 14 0.509 0.076 15 0.150 0.022 18 0.008 0.004 21 0.364 0.197 24 0.463 0.206 31 0.409 0.049 36 0.167 0.020 48 0.402 0.029 a: Null hypothesis H0: μ1 = μ2 and alternate hypothesis H1: μ1 ≠ μ2 143 Calibration Curves for Laboratory Analyses Figure C-1: Graph of calibration curve of the U-shape manometer Figure C-2: Graph of chemical oxygen demand calibration sample curve y = 6,2208xR² = 0,99940501001502002503003504004505000 10 20 30 40 50 60 70 80Volume of gas (mL)Measured level (cm)y = 2,2548x + 5,8639R² = 0,999401002003004005006007008000 50 100 150 200 250 300 350COD Concentration (mg/L)Absorbance 144 Figure C-3: Graph of ammonia nitrogen calibration curve Figure C-4: Graph of daily methane production of second-stage TPAD reactor (38°C, 28 d) For BMP assay inoculation, large amounts (50 - 80%) of the liquid volume was withdrawn from the reactor. Measurements of methane production was resumed once the liquid volume was restored. y = 0,00000x2 + 0,00590x - 0,01414R² = 0,999980123456780 200 400 600 800 1000 1200 1400Ammonia Concentration (mg/L)Absorbance 01002003004005006007000 50 100 150 200 250 300Methane Production STP (ml/g-VS fed)Time (Days) 145 Cumulative Methane Production Graphs Figure D-1: Cumulative methane production graph for BMP assays for B1 with SIR 2.2 = g-VS/g-VS and powdered (< 0.075 mm) biochar Points represent averages and error bars are standard deviation of triplicate assays. Figure D-2: Cumulative methane production graph for SIR = 3.2 g-VS/g-VS for B1 and powdered (< 0.075 mm) biochar Points represent averages and error bars are standard deviation of triplicate assays. 01002003004005006007000 5 10 15 20 25 30 35 40 45 50Cumulative methane yield (mL/g-VS)Time (days)ControlsPowdered biochar 0.6 g/g-VS substratePowdered biochar 1.2 g/g-VS substratePowdered biochar 1.8 g/g-VS substrate01002003004005006000 10 20 30 40 50Cumulative methane yield (mL/g-VS)Time (days)ControlsPowdered biochar 0.4 g/g-VS substratePowdered biochar 0.8 g/g-VS substratePowdered biochar 1.2 g/g-VS substrate 146 Figure D-3: Cumulative methane production graph for BMP assays for B1 with SIR = 4.4 g-VS/g-VS and powdered (< 0.075 mm) biochar Points represent averages and error bars are standard deviation of triplicate assays. Figure D-4: Cumulative methane production graph for BMP assays for B2 with SIR = 2.2 g-VS/g-VS and powdered (< 0.075 mm) ZMM® T-Carbon Points represent averages and error bars are standard deviation of triplicate assays. 01002003004005006000 10 20 30 40 50Cumulative methane yield (mL/g-VS)Time (days)ControlsPowdered biochar 0.3 g/g-VS substratePowdered biochar 0.6 g/g-VS substratePowdered biochar 0.9 g/g-VS substrate01002003004005006000 10 20 30 40 50 60Cumulative methane yield (mL/g-VS)Time (days)ControlsPowdered T-Carbon 0.6 g/g-VS substratePowdered T-Carbon 1.2 g/g-VS substratePowdered T-Carbon 1.9 g/g-VS substrate 147 Figure D-5: Cumulative methane production graph for BMP assays for B2 with SIR = 3.2 g-VS/g-VS and powdered (< 0.075 mm) ZMM® T-Carbon Points represent averages and error bars are standard deviation of triplicate assays. Figure D-6: Cumulative methane production graph for BMP assays for B2 with SIR = 4.4 g-VS/g-VS and powdered (< 0.075 mm) ZMM® T-Carbon Points represent averages and error bars are standard deviation of triplicate assays. 01002003004005006000 10 20 30 40 50 60Cumulative methane yield (mL/g-VS)Time (days)ControlsPowdered T-Carbon 0.4 g/g-VS substratePowdered T-Carbon 0.8 g/g-VS substratePowdered T-Carbon 1.3 g/g-VS substrate01002003004005006000 10 20 30 40 50Cumulative Methane Yield (mL/g-VS)Time (days)ControlsPowdered T-Carbon 0.3 g/g-VS substratePowdered T-Carbon 0.6 g/g-VS substratePowdered T-Carbon 0.9 g/g-VS substrate 148 Figure D-7: Cumulative methane production graph for BMP assays for B7 with SIR = 4.4 g-VS/g-VS and granular (0.85 – 4.75 mm) ZMM® T-Carbon Points represent averages and error bars are standard deviations of triplicate assays. 01002003004005006000 10 20 30 40 50Cumulative methane yield (mL/g-VS) Time (Days) ControlsGranular T-Carbon 0.3 g/g-VS substrateGranular T-Carbon 0.6 g/g-VS substrate 149 Total Volatile Fatty Acid Graphs Figure E-1: Graph of total volatile fatty acids variation during BMP assays for B1 at SIR = 2.2 g-VS/g-VS with powdered biochar Dosages of powdered (< 0.075 mm) biochar were 0.6, 1.2 and 1.8 g/g-VSsubstrate. Points represent averages and error bars are standard deviations of triplicate assays. Figure E-2: Graph of total volatile fatty acids variation during BMP assays for B1, SIR = 3.2 g-VS/g-VS with powdered biochar Dosages of powdered (< 0.075 mm) biochar were 0.4, 0.8 and 1.2 g/g-VSsubstrate. Points represent averages and error bars are standard deviations of triplicate assays. 0500100015002000250030003500400045000 5 10 15 20Total VFA (mg/L)Time (days)ControlsBiochar powdered 0.6 g/g-VS substrateBiochar powdered 1.2 g/g-VS substrateBiochar powdered 1.8 g/g-VS substrate05001000150020002500300035004000450050000 2 4 6 8 10 12 14 16 18 20 22Total Volatile Fatty Acids (mg/L)Time (days)ControlsBiochar powdered 0.4 g/g-VS substrateBiochar powdered 0.8 g/g-VS substrateBiochar powdered 1.2 g/g-VS substrate 150 Figure E-3: Graph of total volatile fatty acids variation during BMP assays for B2 at SIR = 2.2 g-VS/g-VS with powdered ZMM® T-Carbon Dosages of powdered (< 0.075 mm) ZMM® T-Carbon were 0.6, 1.2 and 1.9 g/g-VSsubstrate. Points represent averages and error bars are standard deviations of triplicate assays. Figure E-4: Graph of total volatile fatty acids variation during BMP assay for B2 at SIR = 3.2 g-VS/g-VS with powdered ZMM® T-Carbon Dosages of powdered (< 0.075 mm) ZMM® T-Carbon were 0.4, 0.8 and 1.3 g/g-VSsubstrate. Points represent averages and error bars are standard deviations of triplicate assays. 02004006008001000120014001600180020000 2 4 6 8 10 12Total VFA (mg/L)Time (days)ControlT-Carbon Powdered 0.6 g/g-VS substrateT-Carbon Powdered 1.2 g/g-VS substrateT-Carbon Powdered 1.9 g/g-VS substrate0500100015002000250030000 2 4 6 8 10 12Total Volatile Fatty Acids (mg/L)Time (days)ControlT-Carbon Powdered 0.4 g/g-VS substrateT-Carbon Powdered 0.8 g/g-VS substrateT-Carbon Powdered 1.3 g/g-VS substrate 151 Figure E-5: Graph of total VFA variation during the colonization test of biochar with BMP assays for Batch 3B Dosages of granular (0.85 – 4.75 mm) biochar were 0.16, 0.24 and 0.33 g/g-VSsubstrate . Points represent averages and error bars are standard deviations of triplicate assays. Figure E-6: Graph comparing the effects of buffer addition on total VFA variation during BMP assay for Batch 4 with biochar and ZMM® T-Carbon Dosages of granular (0.85 – 4.75 mm) char was 2.2 g/g-VSsubstrate and SIR = 4.4 g-VS/g-VS. Points represent averages and error bars are standard deviations of triplicate assays. 0500100015002000250030003500400045000 10 20 30 40 50 60 70Total Volatile Acid (mg/L)Time (days)Colonized biochar 0.16 g/g-VS substrateColonized biochar 0.24 g/g-VS substrateColonized biochar 0.33 g/g-VS substrateNew biochar 0.16 g/g-VS substrateNew biochar 0.24 g/g-VS substrateNew biochar 0.33 g/g-VS substrate05001000150020002500300035004000450050000 10 20 30 40 50 60 70Total VFA (mg/L)Time (days)Controls without bufferControls with bufferBiochar without bufferBiochar with bufferT-Carbon without bufferT-Carbon with buffer 152 Summary of Results for Laboratory Analyses at the End of BMP Assays Table F-1: Properties of BMP assay digestate on final day of B1 Sludge to Inoculum Ratio (g-VSsubstrate/g-VSInoculum) Biochar Dosage (g/g-VSsubstrate) Average Ammonia (mg/L) Alkalinity (mg as CaCO3/L) pH 2.2 Controls 1070a (16)b 6852 (30) 7.69 (0.04) 0.6 1025 (0) 6729 (22) 7.71 (0.02) 1.2 1022 (5) 6637 (21) 7.66 (0.01) 1.8 995 (5) 6589 (123) 7.67 (0.03) 3.2 Controls 1298 (13) 7706 (54) 7.66 (0.02) 0.4 1256 (3) 7414 (120) 7.70 (0.01) 0.8 1239 (9) 7403 (45) 7.71 (0.01) 1.2 1203 (6) 7393 (22) 7.68 (0.01) 4.4 Controls 1571 (13) 8786 (41) 7.71 (0.02) 0.3 1532 (19) 8493 (130) 7.73 (0.02) 0.6 1502 (12) 8411 (51) 7.70 (0.02) 0.9 1471 (19) 8293 (59) 7.71 (0.04) a: Data represent average of triplicate BMP assays b: Data in parenthesis is the standard deviation of triplicate BMP assays 153 Table F-2: Properties of BMP assays’ digestate on final day of B2 Sludge to Inoculum Ratio (g-VSsubstrate/g-VSInoculum) ZMM T-Carbon Dosage (g/g-VSsubstrate) Average Ammonia (mg/L) Alkalinity (mg as CaCO3/L) pH 2.2 Controls 700a (4)b 6177 (96) 7.62 (0.01) 0.6 662 (48) 6137 (49) 7.61 (0.03) 1.2 661 (14) 6311 (4) 7.66 (0.04) 1.9 619 (23) 6415 (93) 7.68 (0.03) 3.2 Controls 818 (15) 6481 (34) 7.61 (0.03) 0.4 760 (27) 6451 (417) 7.69 (0.05) 0.8 740 (17) 6924 (252) 7.68 (0.03) 1.3 744 (7) 6909 (31) 7.71 (0.07) 4.4 Controls 974 (23) 7075 (171) 7.65 (0.06) 0.3 956 (33) 7237 (59) 7.67 (0.08) 0.6 929 (11) 7361 (191) 7.69 (0.09) 0.9 901 (5) 7456 (78) 7.70 (0.10) a: Data represent average of triplicate BMP assays b: Data in parenthesis is the standard deviation of triplicate BMP assays 154 Table F-3: Properties of BMP assays’ digestate on final day of B4 Treatment Average Ammonia (mg/L) Alkalinity (mg as CaCO3/L) pH Controls without buffer 1443a (82)b 5450 (203) 7.38 (0.02) Controls with buffer 1261 (115) 8491 (249) 7.61 (0.04) Biochar without buffer 1322 (43) 4967 (48) 7.37 (0.01) Biochar with buffer 1338 (49) 7909 (121) 7.66 (0.04) ZMM T-Carbon without buffer 1287 (18) 6068 (130) 7.51 (0.05) ZMM T-Carbon with buffer 1162 (46) 8423 (126) 7.66 (0.02) a: Data represent average of triplicate BMP assays b: Data in parenthesis is the standard deviation of triplicate BMP assays 155 Table F-4: Properties of BMP assays’ digestate on final day of B5 Treatment and Dosage NH3-N (mg/L) Alkalinity (mg as CaCO3/L) pH Acetic acid (mg/L) Propionic Acid (mg/L) Butyric Acid (mg/L) Controls 1356a (36)b 8231 (91) 7.69 (0.01) 20 (5) 6 (3) 9 (3) 2nd generation ZMM T-Carbon 707 (15) 5871 (61) 7.56 (0.01) 19 (2) 1 (2) 4 (1) 2nd generation biochar 690 (28) 5903 (52) 7.56 (0.04) 17 (3) 0 (0) 3 (0) Powdered biochar 1.8 g/g-VSsubstrate 1054 (116) 7603 (48) 7.74 (0.00) 3 (2) 0 (0) 2 (0) Powdered ZMM T-Carbon 1.8 g/g-VSsubstrate 1180 (37) 9052 (58) 7.90 (0.04) 9 (2) 0 (0) 1 (1) Granular biochar 3.7 g/g-VSsubstrate 1103 (48) 7331 (58) 7.89 (0.13) 2 (3) 3 (3) 4 (1) Powdered biochar 3.7 g/g-VSsubstrate 1037 (17) 7237 (149) 7.67 (0.02) 2 (3) 0 (0) 3 (0) Granular ZMM T-Carbon 3.7 g/g-VSsubstrate 1055 (37) 9219 (83) 8.00 (0.07) 2 (4) 0 (0) 1 (2) Powdered ZMM T-Carbon 3.7 g/g-VSsubstrate 1076 (5) 9587 (56) 7.90 (0.07) 0 (0) 0 (0) 0 (0) Granular biochar 0.9 g/g-VSsubstrate 1272 (19) 7957 (70) 7.78 (0.03) 7 (1) 0 (0) 0 (0) Granular ZMM T-Carbon 0.9 g/g-VSsubstrate 1167 (30) 8424 (113) 7.78 (0.02) 10 (1) 0 (0) 0 (0) a: Data represent average of triplicate BMP assays b: Data in parenthesis is the standard deviation of triplicate BMP assays 156 Table F-5: Properties of BMP assays’ digestate on final day of B6 Treatment and Dosage NH3-N (mg/L) Alkalinity (mg as CaCO3/L) Acetic acid (mg/L) Propionic Acid (mg/L) Butyric Acid (mg/L) Controls 1,710a (18)b 8,984 (52) 27 (10) 6 (4) 8 (3) Biochar with alkalinity 1,408 (28) 8,310 (182) 5 (1) 0 (0) 3 (0) Biochar without alkalinity 1,408 (22) 5,597 (25) 7 (0) 0 (0) 4 (1) a: Data represent average of triplicate BMP assays b: Data in parenthesis is the standard deviation of triplicate BMP assays 157 pH Variation Graphs for BMP Assays Figure G-1: Graph of pH variation during BMP assays for B1 at SIR = 2.2 g-VS/g-VS with powdered biochar Dosages of powdered (< 0.075 mm) biochar were 0.6, 1.2 and 1.8 g/g-VSsubstrate. Points represent averages and error bars are standard deviations of triplicate assays. Figure G-2: Graph of pH variation during BMP assays for B1 at SIR = 3.2 g-VS/g-VS with powdered biochar Dosages of powdered (< 0.075 mm) biochar were 0.4, 0.8 and 1.2 g/g-VSsubstrate. Points represent averages and error bars are standard deviations of triplicate assays. 5,566,577,588,599,50 2 4 6 8 10 12 14 16 18 20pHTime (days)ControlsBiochar powdered 0.6 g/g-VS substrateBiochar powdered 1.2 g/g-VS substrateBiochar powdered 1.8 g/g-VS substrate5,566,577,588,599,50 2 4 6 8 10 12 14 16 18 20pHTime (days)ControlsBiochar powdered 0.4 g/g-VS substrateBiochar powdered 0.8 g/g-VS substrateBiochar powdered 1.2 g/g-VS substrate 158 Figure G-3: Graphs of pH variation during BMP assays for B1 at SIR = 4.4 g-VS/g-VS with powdered biochar Dosages of powdered (< 0.075 mm) biochar were 0.3, 0.6 and 0.9 g/g-VSsubstrate. Points represent averages and error bars are standard deviations of triplicate assays. Figure G-4: Graphs of pH variation during BMP assay for B2 at SIR = 2.2 g-VS/g-VS with powdered ZMM® T-Carbon Dosages of powdered (< 0.075 mm) ZMM® T-Carbon were 0.6, 1.2 and 1.9 g/g-VSsubstrate. Points represent averages and error bars are standard deviations of triplicate assays. 5,566,577,588,50 2 4 6 8 10 12 14 16 18 20pHTime (days)ControlsBiochar powdered 0.3 g/g-VS substrateBiochar powdered 0.6 g/g-VS substrateBiochar powdered 0.9 g/g-VS substrate5,566,577,588,590 5 10 15 20pHTime (days)ControlT-Carbon Powdered 0.6 g/g-VS substrateT-Carbon Powdered 1.2 g/g-VS substrateT-Carbon Powdered 1.9 g/g-VS substrate 159 Figure G-5: Graphs of pH variation during BMP assay for B2 at SIR = 3.2 g-VS/g-VS with powdered ZMM® T-Carbon Dosages of powdered (< 0.075 mm) ZMM® T-Carbon were 0.4, 0.8 and 1.3 g/g-VSsubstrate. Points represent averages and error bars are standard deviations of triplicate assays. Figure G-6: Graphs of pH variation during BMP assay for B2 at SIR = 4.4 g-VS/g-VS with powdered ZMM® T-Carbon Dosages of powdered (< 0.075 mm) ZMM® T-Carbon were 0.3, 0.6 and 0.9 g/g-VSsubstrate. Points represent averages and error bars are standard deviations of triplicate assays. 5,566,577,588,50 2 4 6 8 10 12 14 16 18 20pHTime (days)ControlT-Carbon Powdered 0.4 g/g-VS substrateT-Carbon Powdered 0.8 g/g-VS substrateT-Carbon Powdered 1.3 g/g-VS substrate5,566,577,588,50 2 4 6 8 10 12 14 16 18 20pHTime (days)ControlT-Carbon Powdered 0.3 g/g-VS substrateT-Carbon Powdered 0.6 g/g-VS substrateT-Carbon Powdered 0.9 g/g-VS substrate 160 Figure G-7: Graph of pH variation during the colonization test of biochar BMP assays for B3-B Dosages of granular (0.85 – 4.75 mm) biochar were 0.16, 0.24 and 0.33 g/g-VSsubstrate. Points represent averages and error bars are standard deviations of triplicate assays. Figure G-8: Graph comparing the effects of buffer addition on pH variation during BMP assays for B4 with granular char The granular (0.85 – 4.75 mm) biochar and T-Carbon dosage was 2.2 g/g-VSsubstrate at SIR = 4.4 g-VS/g-VS. Points represent averages and error bars are standard deviations of triplicate assays.66,26,46,66,877,27,47,67,880 10 20 30 40 50 60pHTime (days)Colonized biochar 0.16 g/g-VS substrateColonized biochar 0.24 g/g-VS substrateColonized biochar 0.33 g/g-VS substrateNew biochar 0.16 g/g-VS substrateNew biochar 0.24 g/g-VS substrateNew biochar 0.33 g/g-VS substrate66,26,46,66,877,27,47,67,880 10 20 30 40 50 60 70pHTime (days)Control without bufferControl with bufferBiochar without bufferBiochar with bufferT-Carbon without bufferT-Carbon with buffer 161 Characterisation of Inoculum and Substrate Sludge Added to BMP Assays Table H-1: Properties of inoculum and substrate sludge for each batch of assays Batch Total Solids (g/kg) Volatile Solids (g/kg) COD (g/L) NH3-N (mg/L) Alkalinity (mg as CaCO3/L) pH Acetic acid (mg/L) Propionic Acid (mg/L) Butyric Acid (mg/L) Sa Ib S I S I S I S I S I S I S I S I B1 39.65c (0.15)d 19.74(0.51) 33.52 (0.42) 14.49 (0.38) 63.1 - 1,128 2,154 1,530 6,566 5.00 7.80 -g -g -g -g -g -g B2 42.50 (0.71) 15.08 (0.17) 37.60 (0.59) 11.06 (0.21) 61.1 (4.6) 17.6 (1.1) 809 (4) 1,349 (14) 1,341 4,962 5.34 7.35 1,651 6 1,606 0 740 6 B3-Ae 36.06 (1.99) 18.01 (0.64) 32.68 (0.36) 12.53 (0.26) 50.8 (3.0) 18.3 (0.7) 801 (3) 1,192 (7) 2,117 4,804 5.68 7.42 1,599 (13) 25 1,302 (61) 28 592 (1) 11 B3-Bf 42.04 (0.23) - 36.39 (0.34) - 69.0 (3.6) - 1,281 (1) - 3,011 - 5.94 - 2,004 (29) - 1,267 (5) - 608 (1) - B4 37.49 (0.83) 17.83 (0.3) 32.99 (0.58) 12.39 (0.17) 58.3 (1.0) 17.9 (0.2) 1,349 (6) 1,504 (10) 2,778 5,527 5.78 7.41 2,369 (66) 17 1,391 (66) 13 609 (27) 7 B5 45.14 (0.87) 14.15 (0.38) 40.17 (0.78) 10.58 (0.10) 68.6 (2.5) 16.7 (0.4) 730 (21) 1,544 (16) 2,190 6,212 5.60 7.64 1,649 30 (1) 1,581 24 (1) 768 15 (1) B6 42.89 (0.13) 17.81 (0.08) 36.23 (0.09) 12.17 (0.05) 62.4 (4.3) 18.7 (1.0) 1,557 (10) 1,374 (15) 3,325 5,864 6.38 7.46 2,300 9 1,505 4 539 4 B7 44.19 (0.12) 18.71 (0.43) 37.69 (0.28) 13.60 (0.20) 68.5 (2.9) 26.3 (1.3) 847 (6) 1,520 (14) 2,227 5,778 5.65 7.47 1,918 10 1,934 7 632 4 a: Substrate b: Inoculum c: Data represent average of three measurements of the same sample d: Data in parenthesis is the standard deviation of triplicate measurement of the sample e: First-generation bioaugmentation experiment f: Second generation bioaugmentation experiment, no inoculum was added g: Results were lost by mistake 162
Thesis/Dissertation
eng
Civil Engineering
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Effect of biochar and wood ash amendment on biochemical methane production of wastewater sludge from a temperature phase anaerobic digestion process
Text