Applied Science, Faculty of
Engineering, School of (Okanagan)
DSpace
UBCO
Kumar, Vikas
Doctor of Philosophy - PhD
University of British Columbia
Municipal wastewater sludge disposal is a growing global environmental issue due to high concentrations organic pollutants and pathogens. Anaerobic digestion is a widely adopted process for treating municipal sludge and producing biogas as renewable energy. However, the complex structure of sludge and the difficulties retaining slow-growing archaea in bioreactors, leads to low organic conversion efficiency and lower biogas yield in anaerobic digestion. To address these issues, the present research develops a side-stream incubator reactor system that grows a dense population of syntrophic bacteria and archaea, with attention to microbial syntrophy. The research is divided into three main parts: developing a high-performance activated carbon cloth that retains beneficial cultures; a novel incubator using carbon cloth; and an effective bioaugmentation strategy to transfer microbial cultures from the incubator to a Control reactor (conventional digester, baseline scenario). To synthesize high-performance activated carbon cloth, two methods were implemented: a two-step activation process (acid pretreatment and air calcination at 525 ± 25°C), and metal-impregnation of carbon cloth that incorporated nickel and/or iron nanometals. Although metal impregnation enhanced the electrical conductivity however reduced the surface area for microbial attachment. The activated carbon cloth had a 435-times larger pore size area than the commercial carbon cloth, leading to improved microbial colonization and methane production rates in preliminary biochemical methane potential assays. Next, the activated carbon cloth braided ropes were used in a continuous-flow incubator reactor, with a packing density of 1.48 g activated carbon cloth/g volatile solids of substrate, determined from the preliminary assays. The developed incubator system produced a continuous supply of active microbial culture for bioaugmentation of the Control for process improvement. Finally, two bioaugmentation strategies, pellet bioaugmentation and liquid bioaugmentation, were tested to transfer microbial cultures from the incubator system to the Control digester. Pellet bioaugmentation outperformed the liquid bioaugmentation with 33 and 88% daily biogas increases at digester hydraulic retention times of 20 and 10, respectively, with a 2% higher methane compared to the Control reactor. Also, the pellet bioaugmentation strategy enhanced the Control digester's resilience to stress induced at higher organic loads and can be retrofitted to existing wastewater treatment plants.
EVALUATION OF VARIOUS CARBON CLOTH AS BIOMASS SUPPORT MEDIA FOR BIOAUGMENTATION OF ANAEROBIC DIGESTION OF MUNICIPAL SLUDGE by Vikas Kumar M. S. (by Research) Energy, Indian Institute of Technology Guwahati, 2017 B. Tech (Honours) Biochemical Engineering, Kumaon Engineering College, 2014 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE COLLEGE OF GRADUATE STUDIES (Civil Engineering) THE UNIVERSITY OF BRITISH COLUMBIA (Okanagan) May 2023 © Vikas Kumar, 2023 ii The following individuals certify that they have read and recommended to the College of Graduate Studies for acceptance a dissertation entitled: EVALUATION OF VARIOUS CARBON CLOTH AS BIOMASS SUPPORT MEDIA FOR BIOAUGMENTATION OF ANAEROBIC DIGESTION OF MUNICIPAL SLUDGE submitted by Vikas Kumar in partial fulfillment of the requirements of the degree of Doctor of Philosophy. Dr. Cigdem Eskicioglu, School of Engineering Supervisor, Professor Dr. Nicolas Peleato, School of Engineering Supervisory Committee Member, Assistant Professor Dr. Deborah Roberts, University of Northern British Columbia Supervisory Committee Member, Professor Dr. Miranda Hart, Department of Biology University Examiner, Professor Dr. Chul Park, University of Massachusetts Amherst External Examiner, Professor iii Abstract Municipal wastewater sludge disposal is a growing global environmental issue due to high concentrations organic pollutants and pathogens. Anaerobic digestion is a widely adopted process for treating municipal sludge and producing biogas as renewable energy. However, the complex structure of sludge and the difficulties retaining slow-growing archaea in bioreactors, leads to low organic conversion efficiency and lower biogas yield in anaerobic digestion. To address these issues, the present research develops a side-stream incubator reactor system that grows a dense population of syntrophic bacteria and archaea, with attention to microbial syntrophy. The research is divided into three main parts: developing a high-performance activated carbon cloth that retains beneficial cultures; a novel incubator using carbon cloth; and an effective bioaugmentation strategy to transfer microbial cultures from the incubator to a Control reactor (conventional digester, baseline scenario). To synthesize high-performance activated carbon cloth, two methods were implemented: a two-step activation process (acid pretreatment and air calcination at 525 ± 25°C), and metal-impregnation of carbon cloth that incorporated nickel and/or iron nanometals. Although metal impregnation enhanced the electrical conductivity however reduced the surface area for microbial attachment. The activated carbon cloth had a 435-times larger pore size area than the commercial carbon cloth, leading to improved microbial colonization and methane production rates in preliminary biochemical methane potential assays. iv Next, the activated carbon cloth braided ropes were used in a continuous-flow incubator reactor, with a packing density of 1.48 g activated carbon cloth/g volatile solids of substrate, determined from the preliminary assays. The developed incubator system produced a continuous supply of active microbial culture for bioaugmentation of the Control for process improvement. Finally, two bioaugmentation strategies, pellet bioaugmentation and liquid bioaugmentation, were tested to transfer microbial cultures from the incubator system to the Control digester. Pellet bioaugmentation outperformed the liquid bioaugmentation with 33 and 88% daily biogas increases at digester hydraulic retention times of 20 and 10, respectively, with a 2% higher methane compared to the Control reactor. Also, the pellet bioaugmentation strategy enhanced the Control digester's resilience to stress induced at higher organic loads and can be retrofitted to existing wastewater treatment plants. v Lay summary This study focused on enhancing the performance of existing biogas plants by developing a novel compact reactor that uses a carbon fabric to serve as a home to foster valuable microorganisms, which aid the methane fuel production from organic waste degradation. The study focusses on three main objectives: • Encouraging development of a valuable microorganism’s population using carbon fabric to boost methane production and organic waste removal. • Developing an effective method to transfer these valuable microorganisms to existing wastewater municipal biogas plants. • Examining the proportional influence of valuable microorganism transfer on biogas production and organic waste reduction in the biogas plants, particularly under elevated organic accumulation situations. The results signify that it is conceivable to treat larger volumes of municipal sludge without necessitating additional infrastructure construction. This is a noteworthy innovation for wastewater utilities to improve the wastewater treatment efficiencies. vi Preface The thesis author, with the guidance and feedback of supervisor Dr. Cigdem Eskicioglu, conducted research, including designing and constructing batch and semi-continuous flow anaerobic bioreactors, operating and weekly analysis of reactor inflows and effluents for over an extended period of 2.5 years, training new lab members and interns on bioreactor operation and characterization, and drafting research articles. The research findings were also shared at various workshops led by Dr. Eskicioglu and an industrial partner, Metro Vancouver, Canada. Dr. Timothy Abbott, a former Bioreactor Technology Laboratory (BTG) member, assisted with laboratory training and instrument set-up used in this research. Several undergraduate/master’s students assisted with setting up the reactors and sludge characterization. However, the bulk of the laboratory experiments were conducted by the thesis author. Microbial genomic fingerprinting analysis was conducted by Dr. Steven Hallam's research group at the University of British Columbia, Vancouver. The genomic results are not included in the thesis but have been incorporated into journal articles, which serve as the basis of the thesis. Two of these articles are currently in progress, and two have been accepted for publication. Chapters 1 and 2 Parts of Chapter 1 (Introduction) and Chapter 2 (Literature Review) were published as a review article entitled “Kumar, V., Nabaterega, R., Khoei, S., & Eskicioglu, C. (2021). Insight into interactions between syntrophic bacteria and archaea in anaerobic digestion amended with conductive materials. Renewable and Sustainable Energy Reviews, 144, 110965”. The article focuses on syntrophic vii metabolic pathways, process microbiology, the promotion of microbial symbiosis in anaerobic digestion (AD) and the study of the functional significance of various carrier media on AD performance. The manuscript was written by the thesis author, and comments and revisions were provided by Shiva Khoei, Resty Nabaterega and Dr. Eskicioglu. Additionally, portions of Chapters 1 and 2 were presented as an oral presentation at the 5th Annual Engineering Graduate Symposium (oral presentation) on February 9, 2019, at the University of British Columbia Okanagan Campus, Kelowna, Canada.” Chapter 3 Chapter 3 of the thesis presents preliminary laboratory experiments on synthesizing carbon cloth support media and optimizing the dosage for improved AD performance using biochemical methane potential (BMP) assays. The research was published as: Kumar, V., Kieft, B., Devi, P., Hallam, S. J., & Eskicioglu, C. (2022). Two-step activated carbon cloth enhances microbial interactions and methane production during anaerobic digestion of municipal sludge. Renewable Energy, 196, 366-374. The thesis author conducted the data analysis and manuscript writing, while genomic analysis was performed by Dr. Brandon Keift and Dr. Steven J. Hallam at Hallam's lab (University of British Columbia’s Vancouver Campus). Dr. Parmila Devi (Research Engineer at Bioreactor Technology Group) and Dr. Eskicioglu provided comments and reviewed the manuscript. Part of Chapter 3 was also presented at the 56th Virtual Central CAWQ Conference on March 25, 2021, entitled “Effect of acid pretreated carbon cloth on anaerobic digestion of municipal sludge.” viii Chapter 4 Chapter 4 of the thesis presents the results of laboratory experiments on synthesizing metal-impregnated activated carbon cloth (mA-CC) carriers and selecting the best carrier using BMP assays. The results are being prepared for submission to the Chemical Engineering Journal entitled “Synthesis and evaluation of metal-impregnated carbon cloth supplementation to enhance the rate and extent of anaerobic digestion of municipal sludge.” The thesis author performed the bulk of the data analysis and manuscript writing, with assistance from Abhishek Patil (an undergraduate researcher) for part of the initial experiment setup and characterization, Dr. Jake S Bobowski for measuring the electrical conductivity of the carbon cloth media, Juan Camilo Santana and Dr. Steven J. Hallam for genomic analysis, and Dr. Parmila Devi for writing the material characterization section. The manuscript also incorporated comments and feedback from all co-authors including Dr. Eskicioglu. Chapter 5 Results from Chapter 5 have been accepted as oral presentation by CHANIA 2023 10th International Conference on Sustainable Solid Waste Management and a full manuscript is in preparation for submission to a special issue in one of the collaborating journals with the conference organizing committee. Chapter 6 In Chapter 6 of the thesis, the results of both the literature review and laboratory experiments are presented, along with a discussion of limitations and recommendations for future research. ix In addition, the thesis author collaborated with other researchers within the Bioreactor Technology Group to publish a review article, entitled: Nabaterega, R., Kumar, V., Khoei, S., & Eskicioglu, C. (2021). A review on two-stage anaerobic digestion options for optimizing municipal wastewater sludge treatment process. Journal of Environmental Chemical Engineering, 9(4), 105502. x Table of Contents Abstract ………………………………………………………………………………………………………….iii Lay summary .............................................................................................................................................. v Preface …………………………………………………………………………………………………………vi Table of contents.. .................................................................................................................................... xx List of tables ............................................................................................................................................. xiii List of figures ............................................................................................................................................ xiv List of abbreviation ................................................................................................................................... xvi Acknowledgements ................................................................................................................................ xviii Dedication.. ............................................................................................................................................... xx Chapter 1. Introduction ............................................................................................................................... 1 1.1 Background .............................................................................................................................. 1 1.1.1 Model wastewater treatment plant (WWTP)....................................................................... 5 1.2 Scope of the study .................................................................................................................... 7 1.3 Research motivation and novelty ............................................................................................. 8 1.4 Research hypotheses ............................................................................................................... 9 1.5 Research tasks ....................................................................................................................... 10 1.6 Thesis organization ................................................................................................................ 12 Chapter 2. Literature review ..................................................................................................................... 14 2.1 Overview ................................................................................................................................. 14 2.2 Substrates and metabolism of methanogens ......................................................................... 17 2.3 Electroactivity mechanism of syntrophic bacteria and archaea ............................................. 21 2.4 Electron transfer through mediated interspecies electron transfer (MIET) ............................ 23 2.5 Electron transfer through direct interspecies electron transfer (DIET) via bacterial nanowires ………………………………………………………………………………………………………...25 2.6 Thermodynamics of methanogens for direct interspecies electron transfer (DIET) ............... 27 2.7 Electron transfer through direct interspecies electron transfer (DIET) via external additives 31 2.7.1 Conductive carbon-based material ................................................................................... 31 2.7.2 Robustness of carbon cloth .............................................................................................. 33 2.7.3 Conductive nanomaterials ................................................................................................ 39 2.7.4 Concept of metalloporphyrin nanoparticles (NPs) to coordinate with diverse methanogenesis products................................................................................................................ 60 2.7.5 Nanomaterials as toxicants to anaerobic digestion (AD) ................................................. 62 2.8 Effect of conductive materials addition on syntrophic microbial communities ....................... 63 xi 2.9 Bioaugmentation: Sustainable enhancement to improve the AD performance ..................... 65 2.10 Summary from literature review ............................................................................................. 68 Chapter 3. Two-step activated carbon cloth enhances microbial interactions and methane production during anaerobic digestion of municipal sludge ..................................................................... 70 3.1 Overview ................................................................................................................................. 70 3.2 Material and methods ............................................................................................................. 72 3.2.1 Materials ........................................................................................................................... 72 3.2.2 Synthesis of activated carbon cloth (A-CC)...................................................................... 72 3.2.3 Substrate and inoculum .................................................................................................... 73 3.2.4 Characterization of carbon cloth ....................................................................................... 75 3.2.5 Biochemical methane potential (BMP) assays setup ....................................................... 75 3.2.6 Analytical methods ........................................................................................................... 78 3.2.7 Kinetic modeling ............................................................................................................... 84 3.3 Results and discussion ........................................................................................................... 84 3.3.1 Characterization of activated carbon cloth (A-CC) and untreated carbon cloth (U-CC) .. 84 3.4 Effect of carbon cloth dose on methane increment ................................................................ 87 3.5 Effect on carbon cloth on volatile fatty acid accumulation and conversion ............................ 92 3.6 Kinetic modeling study ........................................................................................................... 95 3.7 Summary ................................................................................................................................ 97 Chapter 4. Synthesis and evaluation of metal-impregnated carbon cloth supplementation to improve anaerobic digestion performance from municipal sludge ....................................................... 98 4.1 Overview ................................................................................................................................. 98 4.2 Experimental section ............................................................................................................ 103 4.2.1 Preparation of metal-impregnated activated carbon cloth (mA-CC) using hydrothermal synthesis method ........................................................................................................................... 103 4.2.2 Substrate and inoculum .................................................................................................. 105 4.2.3 Characterization of carbon cloth samples ...................................................................... 105 4.2.4 Biochemical methane potential (BMP) experiment ........................................................ 106 4.2.5 Kinetic modeling ............................................................................................................. 106 4.3 Results and Discussion ........................................................................................................ 107 4.3.1 Characterization of untreated (U-CC), activated (A-CC) and metal-impregnated carbon cloth (mA-CC) ................................................................................................................................ 107 4.3.2 Anaerobic digestion (AD) performance .......................................................................... 114 4.3.3 Effect of various metal-impregnated carbon cloth (mA-CC) on volatile fatty acids (VFA) and pH profiles ............................................................................................................................... 116 4.3.4 Kinetic modeling ............................................................................................................. 118 4.4 Summary .............................................................................................................................. 121 xii Chapter 5. Novel bioaugmentation strategy with a syntrophic enrichment for enhanced digestion (SEED) system for maximizing methane yield from municipal sludge .............................................. 123 5.1 Overview ............................................................................................................................... 123 5.2 Materials and methods ......................................................................................................... 124 5.2.1 Experimental design and reactor operating conditions .................................................. 124 5.2.2 Bioaugmentation strategy ............................................................................................... 130 5.2.3 Analysis .......................................................................................................................... 131 5.3 Results and discussion ......................................................................................................... 133 5.3.1 Performance of SEED, Test and Control reactors ......................................................... 133 5.3.2 Fluorescent microscopy for microbial biofilm analysis ................................................... 142 5.4 Summary .............................................................................................................................. 143 Chapter 6. Conclusions .......................................................................................................................... 144 6.1 Overall summary and conclusions ....................................................................................... 144 6.2 Limitation and future recommendation ................................................................................. 146 Bibliography ............................................................................................................................................ 148 Appendices ............................................................................................................................................. 169 xiii List of tables Table 2.1. Thermodynamic relation in DIET and MIET mechanisms# ..................................................... 30 Table 2.2. Carbon-based materials used in anaerobic digestion (AD) systemsa .................................... 35 Table 2.3. Metal oxide nanoparticles (NPs) used in anaerobic digestion (AD) systems* ........................ 43 Table 2.4. Multi-compound nanoparticles (NPs) used in anaerobic digestion (AD) system.................... 49 Table 2.5. Zero-valent metallic nanoparticles (NPs) used in anaerobic digestion (AD) system .............. 52 Table 2.6. Carbon-based nanomaterials used in anaerobic digestion (AD) system ............................... 57 Table 3.1. Characterization of substrate and thermophilic inoculum used for BMP assays ................... 74 Table 3.2. The modified Gompertz model’s parameters for biochemical methane potential (BMP) assays with untreated carbon cloth (U-CC) and activated carbon cloth (A-CC)ǂ .................. 96 Table 4.1. Preparation of metal-impregnated carbon cloth (mA-CC) supplements ............................... 104 Table 4.2. Surface area and pore structure of untreated, activated and metal-impregnated carbon cloth .............................................................................................................................................. 108 Table 4.3. The modified Gompertz model's parameters for BMP bottles with various carbon cloth ..... 119 Table 5.2. Overall operational parameters for the SEED, Test and Control reactors ........................... 130 Table 5.3. Parameters measured to study the reactor performance ..................................................... 132 Table 5.4. Physiochemical characterization of SEED, Test and Control reactors ................................. 135 Table 5.5. Impact of bioaugmentation on methane increment at varying hydraulic retention time (HRT) .............................................................................................................................................. 140 xiv List of figures Figure 2.1. Methanogenesis routes for carbon recycling (modifed from the literature (Evans et al., 2019)). ...................................................................................................................................................... 19 Figure 2.2. Schematic diagram of microbial syntrophy in a) mediated interspecies electron transfer (MIET), b) direct interspecies electron transfer (DIET) with cytochromes, and c) DIET with conductive material (modified after (Malvankar and Lovley, 2014)). .......................................................................... 23 Figure 2.3. Effect of nanomaterials’ dose and size on % change in methane/biogas yield with respect to control AD without nanomaterials, compiled from studies in literature .................................................... 60 Figure 2.4. Structure of a) coenzyme-F430, and b) heme protein .......................................................... 62 Figure 3.1. a. Untreated carbon cloth represented as U-CC, and b. activated carbon cloth represented as A-CC .................................................................................................................................................... 73 Figure 3.2. Biochemical methane potential (BMP) bottles used in the study .......................................... 76 Figure 3.3 Fourier-transform infrared spectroscopy (FTIR) analysis of untreated carbon cloth (U-CC) and activated carbon cloth (A-CC) ........................................................................................................... 86 Figure 3.4. X-ray diffraction (XRD) analyses of untreated carbon cloth (U-CC) and activated carbon cloth (A-CC) .............................................................................................................................................. 86 Figure 3.5. Effect of carbon cloth dosing on (a, b) specific cumulative and (c, d) specific daily methane production at standard temperature and pressure (STP) (0ºC, 1 atm) from municipal sludge. U-CC: untreated carbon cloth, A-CC: activated carbon. Data represent average and error bars represent standard deviations of triplicates. ............................................................................................................. 90 Figure 3.6. Effect of untreated carbon cloth (U-CC) and activated carbon cloth (A-CC) addition on (a, b) acetic acid, (c, d) propionic acid, and (e, f) butyric acid accumulation in BMP bottles, respectively. Data represent average and error bars represent standard ............................................................................. 93 Figure 4.1. Schematic of the overall carbon cloth metal impregnation process .................................... 102 Figure 4.2. Hydrothermal reactor used for metal-impregnation of carbon cloth (CC) ........................... 103 Figure 4.3. a. Raman spectra and b. FTIR spectra of various carbon cloth samples. [U-CC, A-CC: untreated and activated carbon cloth; Fe/CC, Ni/CC, Ni/Fe/CC: iron, nickel, and iron/nickel metal-impregnated carbon cloth, respectively; NiPcS/Fe/CC: Nickel (II) phthalocyanine-tetrasulfonic acid tetrasodium salt complex with iron impregnated carbon cloth] .............................................................. 110 Figure 4.4. Scanning electron microscopy (SEM) image of a. A-CC. c. Fe/CC. e. Ni/CC. g. Ni/Fe/CC. i. NiPcS/Fe/CC, respectively, and EDx analysis and mapping of metallic nanostructures impregnated on b. A-CC. d. Fe/CC. f. Ni/CC. h. Ni/Fe/CC. j. NiPcS/Fe/CC, respectively. [U-CC, A-CC: untreated and activated CC; Fe/CC, Ni/CC, Ni/Fe/CC: iron, nickel, and iron/nickel metal-impregnated CC, respectively; NiPcS/Fe/CC: Nickel (II) phthalocyanine-tetrasulfonic acid tetrasodium salt complex with iron impregnated CC] .................................................................................................................................... 112 Figure 4.5. Effect of various carbon cloth supplements on a. specific cumulative and b. specific daily methane production from thermophilic biochemical methane potential assays utilizing municipal sludge at standard temperature and pressure (STP of 0ºC, 1 atm). Data represent average, and error bars represent standard deviations of triplicates. [CC: carbon cloth, U-CC, A-CC: untreated and activated carbon cloth, Fe/CC, Ni/CC, Ni/Fe/CC: iron, nickel, and iron/nickel metal-impregnated carbon cloth, respectively; NiPcS/Fe/CC: Nickel (II) phthalocyanine-tetrasulfonic acid tetrasodium salt complex with iron impregnated carbon cloth] ............................................................................................................... 115 xv Figure 4.6. Effect of various carbon cloth supplements on a. total volatile fatty acids (VFA), comprised of acetic, propionic and butyric acids and b. pH in thermophilic biochemical methane potential assays utilizing municipal sludge at standard temperature and presure (STP of 0oC, 1 atm). Data represent average, and error bars represent standard deviations of triplicates. [CC: carbon cloth, U-CC, A-CC: untreated and activated carbon cloth; Fe/CC, Ni/CC, Ni/Fe/CC: iron, nickel, and iron/nickel metal-impregnated carbon cloth, respectively; NiPcS/Fe/CC: Nickel (II) phthalocyanine-tetrasulfonic acid tetrasodium salt complex with iron impregnated carbon cloth] .............................................................. 117 Figure 4.7. Interaction of BET surface area, electrical conductivity of various carbon cloth on rate of methane production (Rm) ........................................................................................................................ 120 Figure 4.8. Lag phase (λ), methane production rate (Rm) and BET surface area for untreated carbon cloth (U-CC), activated carbon cloth (A-CC), metal-impregnated carbon cloth (CC) (Fe/CC, Ni/CC, Ni/Fe/CC: iron, nickel, and iron/nickel) samples .................................................................................... 121 Figure 5.1. Schematic flow diagram of the proposed bioaugmentation process with activated carbon cloth [AP: Acid phase, SEED: Syntrophic enrichment for enhanced digestion, #Centrifugation condition: 3500 revolution per minutes for 10 minutes] .......................................................................................... 126 Figure 5.2. Control, Test and SEED (syntrophic enrichment for enhanced digestion) reactors and overhead mixers ..................................................................................................................................... 129 Figure 5.3. Specific biogas production for SEED reactor at varying hydraulic retention times (HRT) [SEED: Syntrophic enrichment for enhanced digestion, AP: Acid phase reactor, COD: Chemical oxygen demand] .................................................................................................................................................. 134 Figure 5.4. Impact of bioaugmentation on specific biogas production of Test versus Control (LB: liquid bioaugmentation, PB: pellet bioaugmentation, COD: Chemical oxygen demand) ................................ 137 Figure 5.5. Microscopy images of activated carbon cloth from SEED reactor (at COD of ~3,500 rpm, 20 min) (a. and c.) bright field images and (b. and d.) flourscent images with FilmTracer™ SYPRO® Ruby biofilm and DAPI (4′,6-diamidino-2-phenylindole) cell staining .............................................................. 142 xvi List of abbreviation A-CC: Activated carbon cloth AD: Anaerobic digestion AP: Acid phase BC: British Columbia BET: Brunauer-Emmett-Teller BJH: Barrett-Joyner-Halenda BMP: Biochemical methane potential BTG: Bioreactor technology group COD: Chemical oxygen demand DIET: Direct interspecies electron transfer EC: Electrical conductivity Edx Spectroscopy: Energy-dispersive X-ray spectroscopy FTIR Spectroscopy: Fourier Transform Infrared spectroscopy GAC: Granular activated carbon HF: Hydrofluoric acid HRT: hydraulic retention time IHT: Interspecies hydrogen transfer LB: Liquid bioaugmentation mA-CC: metal-impregnated activated carbon cloth MIET: Mediated interspecies electron transfer MS: Mixed sluge NiPcS: Nickel (II) phthalocyanine-tetrasulfonic acid tetrasodium salt NPs: Nanoparticles xvii NSERC: Natural Sciences and Engineering Council of Canada NZVI: Nano zerovalent iron OLR: Organic loading rate PB: Pellet bioaugmentation SEED: Syntrophic enrichment for enhanced digestion SEM: Scanning electron microscopy SERB: Science and engineering research board TS: Total solids TSPS: Thickened screened primary sludge UBC: University of British Columbia U-CC: Untreated carbon cloth VS: Volatile solids VFA: Volatile fatty acids WWTP: Wastewater treatment plant XRD: X-ray diffraction ΔGo′: Gibbs free energy xviii Acknowledgements I would like to express my deep gratitude to my thesis supervisor, Dr. Cigdem Eskicioglu, for her invaluable guidance, unwavering support, and valuable suggestions throughout my thesis work. I am also grateful to my committee members, Dr. Nicolas Peleato and Dr. Deborah Roberts, for their valuable feedback and suggestions throughout my research. I would not have been able to complete this research without the collaboration, encouragement, and assistance from various individuals. I extend my special appreciation to the senior researchers from the Bioreactor Technology Group, Dr. Timothy Abbott, Dr. Muneer Ahmed, Dr. Gokce Kor Bicakci, Dr. Mohammad Islam, and Jacky Takeuchi, for their support and guidance throughout my PhD research. I am also grateful to the technical and support staff members of UBC Okanagan. This research work was made possible through the financial support of The University of British Columbia - Science and Engineering Research Board, India (UBC-SERB) doctoral scholarship and The Natural Sciences and Engineering Council of Canada (NSERC) – Collaborative Research and Development Grant (CRDPJ 530065–18) in collaboration with Metro Vancouver, Canada. I am also grateful to my friends and classmates for their support and encouragement throughout my research journey. I would like to express my appreciation to my overseas friends: Mr. Sukumar Purohit, Ms. Jyoti Rawat, Arpit Naugai, Nishchal, Prakash Bisht, Sunil Joshi, Shubham Chauhan, and Sushant Sharma. I am also grateful to Shiva Khoei, Dr. Resty Nabaterega, Ibrahim Alper Basar, Jesse Yuzik, and Milad Goodarzi for their xix cooperation and emotional support, which made my research experience both enjoyable and rewarding. I would like to express my gratitude to Abhishek Patil (undergraduate researcher) for his assistance in laboratory workload distribution during my research. I am also grateful to my former roommates, Dr. Viki Kumar Prasad, Dr. Hitendra Kumar, Braydon Devis, and Karl Korber for their support and encouragement. Lastly, I would like to extend my most immense thanks to all who have supported me throughout this journey. I am especially grateful to the Almighty for granting me the confidence, ability, and strength to complete this work. xx Dedication यह शोध प्रबंध मेरे माता-पिता और मेरे सभी शुभप ंतको ंको समपिित है। आि इस िीए डी यात्रा के दौरान मेरी पे्ररणा और समर्िन के पनरंतर स्रोत रहे हैं। This thesis is dedicated to my parents and to all my well-wishers. You all have been a constant source of inspiration and support during this PhD journey. 1 Chapter 1. Introduction This chapter outlines the general description of anaerobic digestion (AD) and the importance of supplementary material addition to AD improvement. It also discusses the importance of retrofitting existing AD infrastructure with conductive material to improve the digestion process rate and biogas quality. The retrofitted system offers optimal niche environments for accelerating fermentative, syntrophic, and methanogenic metabolisms to increase digestion system loading rates and enhance the digester microbiome. The retrofitted system enables existing plants to transition from an outdated solids-management model to enhanced methane production. Additionally, the chapter provides an overview of conventional and advanced AD techniques, which serves as the motivation for research and examines the current state of sludge treatment at the Annacis Island wastewater treatment plant (WWTP), that provided substrate and anaerobic inoculum for this research. Furthermore, the research hypotheses and summary of the research methodology are presented. 1.1 Background Due to rapid population growth and industrialization, wastewater production has greatly increased, thereby remarkably increasing wastewater sludge. Water utilities are facing unprecedented challenges in order to reduce operational risks and enhance resource recovery from wastewater. Though advanced processes have been invented for wastewater treatment in the last 100 years, wastewater sludge treatment/disposal still is one of the major challenges for treatment utilities. The production of municipal sludge as a by-product of wastewater treatment, linked to facility upgrades from primary to secondary treatments, is also increasing steadily. Municipal sludge is becoming a global environmental problem due to its 2 increasing production and high content of organic matter, pathogens, and heavy metals. Land application of municipal biosolids also contribute to the spread of organic micropollutants, as wastewater treatment does not entirely remove these compounds. Therefore, the development of alternative strategies for sludge treatment is urgently needed. Anaerobic digestion (AD) is a biochemical treatment process that occurs in an enclosed heated and mixed bioreactor in the presence of mixed anaerobic cultures of bacteria/archaea for stabilizing high-strength waste and simultaneously recovering energy in the form of methane. AD can provide effective means of achieving several goals for energy, environmental, and waste management policies. The process has been extensively researched, which drastically improved the process stability and efficacy of biodegradation. Despite these process benefits and improvements, AD has been largely underutilized due to challenges associated with process start-up, the sensitivity of microorganisms to changes in the operating environment, limited methane yields, long retention time requirements, and unfavorable economics in countries with lower electricity prices. Most commercial biogas plants often operate well below optimal performance levels due to some challenges, with estimated optimization potential in existing plants between 20% and 50% (Adu-Gyamfi et al., 2012). For the sustainable use of this technology, recent studies have focused on the modernization of existing methods such as coupling AD with bio-electrochemical processes, pretreatment of organic waste for enhanced hydrolysis, addition of trace elements/nutrients, use of various co-substrates, use of a conductive carrier medium, and the fusion of some of the aforementioned technologies (Cooney et 3 al., 2019). It is also critical to develop technologies or operating conditions that remove carbon dioxide, water vapour, and sulphur compounds more effectively so digester gas can be pipelined and used as a better combustion source. Anaerobic digestion (AD) is a multi-step biochemical process that involves hydrolysis, acetogenesis, and methanogenesis as its main stages, with methanogenesis being the rate-limiting step in the AD of municipal sludge. The composition of this complex AD microbial food chain is made up of hundreds of microbial species with varying levels of abundance. Microbial communities play a crucial role and are solely responsible for organic waste degradation. The cooperative interaction among the various species and the exchange of electrons is one of the critical processes in AD. Hydrolytic microorganisms convert large macromolecules into small organic compounds such as monosaccharides, fatty acids, and alcohols. These compounds are then converted to acetic acid by acetogenic microorganisms and, serve as a substrate for methanogenic archaea that exchange electrons and reduce them to methane and CO2 (Lee et al., 2012; Malvankar and Lovley, 2014; Sieber et al., 2012). Due to the specific properties/needs of the methanogens involved, the methanogenic stage of the entire process is susceptible. Their relatively slow specific growth rates make them poor competitors in AD (Björnsson et al., 1997). Despite the maturity of AD technology, there are still many opportunities to optimize the process and improve its economics and relevance across various sectors. Recent advances in molecular methodologies have greatly improved our understanding of the microbial diversity of wastewater treatment systems. Unlike bacteria, which have been widely studied in sludge treatment systems, 4 methanogenic archaea are yet be explored further. Proteobacteria dominate in municipal WWTPs and are the major fraction, ranging from 28% to 67%, with a typical abundance of 56% in all AD systems (engineered and natural), followed by Bacteroidetes (8.5% to 22%). Archaea are present in all stages of the engineered AD system ranging from 1 to 8% only compared to the total microbial population (Płaza et al., 2021). Despite their lower concentration, archaea play a vital role in the carbon and nitrogen cycle and methane production. Additionally, ammonia-oxidizing archaea play a crucial role in nitrogen metabolism in AD reactors. With the development of additional knowledge on archaea, more exciting breakthroughs in archaea-based engineered systems in wastewater treatment, from improving theory to technological innovations, are expected (Płaza et al., 2021). Bioaugmentation, the addition of external cultures to improve wastewater treatment, was first introduced in the 1960s to address slow biomass growth and supplementing lost bacterial populations (Rittmann and Whiteman, 1994). It can also potentially prevent biological oxygen demand (BOD) and chemical oxygen demand (COD) overload of bioreactors, improve pollutant degradation, induce or stabilize nitrification, facilitates speed recovery from plant disruptions, and prevent odors, and foaming. However, studies on bioaugmentation in wastewater treatment plants have often led to inconclusive results due to difficulties in monitoring relevant operational parameters and lack of reproducibility in full-scale digesters (Vaibhav, 2010). New advances in microbial ecology, immobilization techniques, and bioreactor design can improve the effectiveness of bioaugmentation. A comprehensive 5 understanding of biosystem ecology is necessary to establish treatment goals and determine effective methods for introducing and maintaining desired microorganisms in the community. Research in material synthesis biofilm support, bioprocess engineering, microbial fingerprinting, and sustainable design and management can also aid in the development of efficient bio-augmented bioreactors under real-world conditions. Supplementing carbon-based conductive materials such as carbon cloth in AD enhances microbial syntrophy and biofilm growth, improving overall performance (Kumar et al., 2022). High-performance carbon cloth act as a biocompatible surface for microbial attachment and act as a biocatalyst to improve overall microbial syntrophy. Also, being in long fibrous form the carbon cloth not only support microbial attachment but can be recovered within the digester without washout loss (Park et al., 2018). On the challenges side, current biogas digesters are engineered to have specific geometry and operate under specific mixing conditions in order to prevent issues such as short-circuiting and stratification, which can create challenges for retrofitting with conductive material. Furthermore, the initial capital and operational costs associated with retrofitting existing AD infrastructure to accommodate the addition of supplementary material would be expensive at full-scale plants. 1.1.1 Model wastewater treatment plant (WWTP) The Annacis Island WWTP located in Vancouver, British Columbia, Canada was chosen as a model plant (baseline scenario) to conduct the current research. This WWTP is the largest wastewater treatment plant in the Greater Vancouver Regional District, in British Columbia. It has a wet weather peak capacity (highest hourly flow) of 1089 million liters per day. The plant receives wastewater from 6 domestic, commercial, and industrial sources, and includes preliminary treatments such as screening and grit removal, primary settling, and a two-stage secondary treatment using trickling filters, followed by a solid contact tank process. The wastewater is then further treated through tertiary filtration, chlorine treatment, and ultraviolet disinfection before being discharged into the Fraser River. The facility typically discharges 483 million liters per day of secondary treated effluent into the Fraser River and generates around 2,500 m3/d of municipal sludge from primary and secondary treatment operations. This sludge is used as a feed for thermophilic anaerobic digesters, which generate biogas and class A biosolids for land application. For this research, the Annacis Island WWTP provided various sludge streams (substrate) bi-weekly and thermophilic digester effluent as seed (inoculum) to set-up/operate batch and semi-continuous flow digester studies at Bioreactor Technology Group (BTG)’s laboratory at UBC’s Okanagan campus, Kelowna, BC, Canada. Occasionally, BTG received sludge streams from another WWTP operated by Metro Vancouver (Lulu Island WWTP) with similar treatment process to Annacis Island WWTP with the exception of thermophilic digesters. At Lulu Island WWTP, mesophilic sludge digesters are used instead of thermophilic digesters. 7 1.2 Scope of the study This research is part of a 4-year research program funded by Natural Science and Engineering Research Council of Canada (NSERC) and Metro Vancouver, a major waste treatment utility in BC, Canada. Several researchers from UBC’s Bioreactor Technology Group (BTG) have been investigating the effects of adding various conductive material to AD, such as biochar (Khoei et al., 2021), biochar and wood ash (Cimon et al., 2020), and graphene nanocomposites to enhance retention of essential microbial cultures leading to an enhanced methane production rate and extent. Within the overall program, this study assessed the effect of using various carbon cloth, such as commercial (untreated) carbon cloth, activated carbon cloth (A-CC), and metal-impregnated activated carbon cloth (mA-CC) on the rate and extent of methane production using preliminary batch anaerobic sludge digestion studies. Later, the study developed a novel, bench-scale, side-stream incubator with A-CC to cultivate syntrophic bacteria and methanogenic archaea for bioaugmentation of a conventional, main sludge stream AD with semi-continuous flow operation. The incubator system has been patented (Patent number: US 11,274,054 B2) under the name of syntrophic enrichment for enhanced digestion (SEED). The primary goal of the SEED system was to deliver methanogen-rich microbial cultures to the main AD reactor, referred to as the "Test" reactor. The Test reactor performance was compared to the "Control" reactor without A-CC, representing the baseline scenario at the Annacis Island WWTP, for various process parameters. The study also examined the prospects for overcoming the challenges associated with reactor failure due to higher organic loading and/or fluctuating process parameters in a semi-continuously fed AD system utilizing municipal sludge at varying organic loading rates. Although the 8 technology has been developed with substrate and inoculum from Annacis Island WWTP operated by Metro Vancouver, it is applicable to other similar municipal sludge management facilities in Canada and around the world. 1.3 Research motivation and novelty Although the use of carbon cloth supplement has been assessed for AD enhancement previously, the following research gaps had been identified, which speak to the novelty of this research. i. To the best of my knowledge, most AD studies amended with various carbon cloth-based supplements have been conducted at a small scale (serum bottles used as a bioreactor with working volume 70 ml) with batch-fed reactors utilizing municipal sludge. Additional research is needed to assess the impact of different carbon cloth-based supplements on a larger scale, continuously-fed digesters simulating full-scale AD process more closely to provide further evidence for commercialization. ii. The effect of a two-step activation of carbon cloth, which includes acid pretreatment (nitric/sulfuric acid) followed by air carbonization, on the biomethane improvement is not clearly studied for AD application. Many studies also did not include the optimization of carbon cloth dosages for maximum methane yield and process stability for municipal sludge treatment. iii. The synthesis and functional significance of mA-CC, and its performance evaluation against other carbon cloth supplements as AD supplement, has not been studied. 9 iv. Previous research looked at placing carbon cloth within the main sludge stream AD, which presents challenges on cost (due to large volumes) and operational point of view. Instead, a smaller, side-stream digester with carbon cloth can be designed to grow dense population of beneficial cultures due to microbial symbiosis and used to bio-augment the mainstream AD for process enhancement. The bioaugmentation strategy can be implemented for any existing AD system as a lateral flow retrofit model without modifying the existing infrastructure. 1.4 Research hypotheses Based on the literature review and the aforementioned research gaps above, the following hypotheses were proposed: I. Two-step pretreatment of carbon cloth can significantly modify its surface characteristics leading to enhanced biocarrier potential compared to commercially available carbon cloth. Therefore, incorporating A-CC into AD utilizing municipal sludge treatment will achieve superior performance compared to AD with commercial carbon cloth. II. Physiochemical characteristics of biomass/biofilm carriers, such as surface area and electrical conductivity (EC), play a significant role in promoting microbial attachment and biofilm formation. Therefore, Ni/Fe metal impregnation on A-CC should further increase conductivity of A-CC, leading to superior AD performance compared to AD with A-CC. III. A side-stream anaerobic reactor with a surface modified carbon cloth can act as an incubator reservoir system for active/dense microbial population for bioaugmentation, improving digestion, increasing stability, and upgrading biogas quality in a bio-augmented main-stream AD treating municipal sludge. 10 1.5 Research tasks To validate the aforementioned hypotheses, the thesis had five major tasks: Task-1: Conduct a literature review on conventional and advanced AD processes, including various media/supplements for process enhancement and concepts of interspecies electron transfer and direct interspecies electron transfer (DIET). (Supports Hypotheses I-III). Task-2: Synthesize various carbon cloth-based supplements and determine the most appropriate arrangement based on chemical composition and exploratory experiments at the lab scale. (Supports Hypotheses I and II). This task is further divided into two sub-tasks: Task-2.1. Synthesis of two-step activated carbon cloth using acid pretreatment followed by air calcination to improve its surface characteristics. Task-2.2. Synthesis of mA-CC (iron oxide/nickel composites) using hydrothermal synthesis process. Task-3: Characterize and evaluate the potential of carbon cloth as a high-performance AD supplement using batch biochemical methane potential (BMP) assays (supports Hypotheses I and II). Task-3 was subdivided into the following sub-tasks: Task-3.1. Optimize carbon cloth dosage and compare the efficiency of all synthesized carbon cloth samples (untreated carbon cloth, activated carbon cloth, and mA-CC) to improve AD performance using BMP assays. 11 Task-3.2. Physicochemical characterization of all the carbon cloth samples obtained from BMP assays by performing various analyses, including Energy-dispersive X-ray spectroscopy (EDx), Fourier Transform Infrared (FTIR) spectroscopy, Brunauer-Emmett-Teller (BET) analysis, scanning electron microscopy (SEM), to correlate material characteristics to AD performance. Task-4: Design and fabrication of a novel bench-scale (5-litre) SEED reactor using a type of high-performance carbon cloth (determined from Tasks 2 and 3) as a side-stream incubator reactor to grow a dense population of microbial consortia rich in syntrophic bacteria and methanogenic archaea that can be utilized to enhance the performance of conventional anaerobic sludge digesters (supports Hypothesis III). Task-5: To develop a novel bioaugmentation strategy to periodically transfer anaerobic cultures grown with a readily biodegradable substrate in the SEED system to a conventional anaerobic sludge digester to accelerate biogas recovery rate and extent from municipal sludge. Task-5 was divided into two sub-parts: Task-5.1. To commission, monitor, and interpret various performance parameters of the side-stream SEED system itself, such as organic loading rate, biogas/methane production, COD conversion efficiency, and the characterization of microbial biofilm formed on carbon cloth. Task-5.2. Develop a novel bioaugmentation strategy to intermittently transfer active microbial cultures from the SEED system to a Test digester representing a mainstream conventional AD. Monitor and compare various AD performance parameters such as pH, volatile fatty acids (VFA), biogas yield/composition, methane yield, organic removals, ammonia, alkalinity, etc. with respect to a 12 baseline scenario (Control AD without bioaugmentation) at varying organic loading rates (OLRs) (supports Hypothesis III). 1.6 Thesis organization The thesis is divided into six chapters: Chapter 1 summarizes the general background information on AD and municipal sludge treatment. The chapter also discusses the details of the industrial partnership with the WWTP, followed by the scope of the study, research motivation, hypotheses, and tasks. Chapter 2 contains a detailed literature review providing in-depth information on the basics of AD, research problem description, the mechanism of microbial metabolism, and the advantages and limitations of various conductive materials for methanogenesis. The literature review provides the basis for filling current research gaps in the research. Chapter 3 discusses experimental results on carbon cloth activation and dosage requirements to improve AD performance by batch BMP assays. Chapter 4 provides an in-depth understanding of the different physicochemical parameters (surface area and electrical conductivity) of carbon cloth obtained by metal impregnation using a hydrothermal synthesis approach. The results provide a comparative analysis of varying carbon cloth surface area and electrical conductivity on AD improvement by batch BMP assays. Chapter 5 brings together the results obtained from chapters 1 to 3 and provides a solid basis for the development of a new bioaugmentation system. The chapter focuses on design and fabrication elements and develops a novel bioaugmentation strategy to improve AD performance in semi-continuous flow mode. 13 Chapter 6 presents general conclusions, limitations, and future recommendations for this research. 14 Chapter 2. Literature review This chapter summarizes the reviewed literature related to this study, including the basics of anaerobic digestion (AD), microbial syntrophy mechanism and the importance of various biofilm carriers/supplements to improve methanogenesis. 2.1 Overview AD is a well-documented biological treatment process that recovers energy from various organic materials, including wastewater sludge. The technology has created widespread interest in nutrient recovery (as digestate), renewable energy production (as biogas), and global greenhouse effect reduction (Holm-Nielsen et al., 2009; Metcalf & Eddy Inc et al., 2013). The utilization of AD has been hindered by various challenges such as process initiation difficulties, microorganism sensitivity to operational changes, limited methane yields, prolonged retention times, and unfavorable economics in low electricity price countries (Chen et al., 2008). To make this technology more sustainable, recent studies have focused on modernizing existing methods through AD and bio-electrochemical integration, organic waste pretreatment for increased hydrolysis, trace element/nutrient supplementation, use of co-substrates, conductive carrier medium utilization, and technology fusion (Cooney et al., 2019). Improving the removal of carbon dioxide, water vapor, and sulfur compounds through advanced technologies or operating conditions is also crucial to enable the effective use of digester gas as a better fuel source. AD requires complex interactions among diverse microbial groups: hydrolytic bacteria, acidogenic/acetogenic (fermentative) bacteria, and methanogenic archaea (Stams and Plugge, 2009). The microbial communities are generally 15 resistant and stable throughout the AD process, but alterations in the syntrophic cooperation between the bacterial and archaeal communities can lead to fluctuations in the process (Werner et al., 2011). Syntrophy is a strictly connected mutualistic interaction (Biebl and Pfennig, 1978). The syntrophic interaction between fermentative bacteria and archaeal methanogens involves the exchange of hydrogen and metabolites (such as formate) (Bryant et al., 1967; McInerney et al., 2007). Microbially, all the biological processes necessary for sustaining life (such as respiration and photosynthesis) are governed by a series of signals (Gray and Winkler, 1996). The fermentative syntrophic metabolizer produces hydrogen and formate from its growth substrate (e.g., acetate, propionate, butyrate, isobutyrate, valerate, and benzoate) (McInerney et al., 2008; Schink, 1997). The methanogenic partners utilize the metabolized products of fermentative bacteria and maintain them in a balanced concentration for syntrophic degradation and compatibility with chemical thermodynamics (Sieber et al., 2012). The depletion of a more energy-efficient electron acceptor, such as oxygen, nitrate, and/or iron, increases the efficacy of the methanogenic process (Evans et al., 2019; Thauer et al., 2008). The cooperative exchange of electrons among microbial populations is a critical player in the anaerobic degradation of organic substrates. Interspecies electron transfer (IET) is a well-studied electron exchange mechanism under controlled laboratory conditions for co-cultures, but syntrophic bacterial species in a natural environment habitually form multispecies aggregates (Summers et al., 2010). Nearly half a century ago, the discovery of the interspecies transfer of hydrogen represented a breakthrough in understanding the role of methanogenic microbial 16 communities (Rotaru et al., 2014b). Later, it was also discovered that it is essential for engineered biological waste treatment processes, such as the AD process. Studies reported the importance of conductive materials for DIET between syntrophic bacterial communities and methanogenic archaea (Park et al., 2018). The first documented evidence by Lovley’s team demonstrated the DIET mechanism between Geobacter and Methanosaeta species (Morita et al., 2011). Methanosaeta and Methanosarcina barkeri (Rotaru et al., 2014a) have also been identified to facilitate direct electrical connection with Geobacter metallireducens to facilitate the reduction of carbon dioxide (CO2) to methane. The relative percentage of electron fluxes during electron transfer or H2/formate species can stimulate the electron transfer rate, stabilize the microbial communities, and improve their capability to acclimatize to environmental stresses (Lovley, 2017; Martins et al., 2018; Park et al., 2018). However, most studies only include certain co-cultures in a controlled laboratory environment. Thus, their results cannot be directly transferable to the full-scale anaerobic treatment processes due to the complexities of microbial communities. The extent of the electron transfer mechanism and its environmental significance for methanogenesis is yet to be ascertained (Xiao et al., 2018). Nanotechnology, as an emerging technology, offers solutions to various sectors, including environmental engineering. The use of several nanomaterials for scientific development offers an alternative to overcome current technological barriers such as long retention times and low methane yields (Faisal et al., 2018). Electromethanogenesis, which differs from traditional hydrogenotrophic and acetoclastic methanogenesis, employs a novel direct electron transfer mechanism 17 and includes electronically conductive support (such as conductive carbon or conductive nanomaterials) for efficient methane production (Xiao et al., 2018). The use of nanomaterials can compensate for the absence of pilin-linked cytochrome-c in the exchange of cellular electrons (Liu et al., 2015). However, it is still unclear whether conductive nano-minerals, such as iron, nickel, cobalt, molybdenum, etc., can facilitate the fabrication of the carbon and/or electronic conductive pathways involved in the methanogenic processes in the natural environment (Xiao et al., 2018). Section 2.2 examines the metabolism of syntrophic bacteria and archaea and suggests mechanisms to increase their retention to improve AD by using various conductive materials. 2.2 Substrates and metabolism of methanogens Methane emission can be broadly grouped into three broad categories: thermogenic, pyrogenic, and biogenic. Thermogenic sources are mainly ground and natural volcanoes, while pyrogenic methane emissions result from the incomplete combustion of fossil fuels. On the other hand, biogenic sources include methanogens, water and wetland systems, ruminants, and organic wastes. Methane metabolism plays a considerable role in global carbon recycling, accounting for about half of the total methane produced on earth each year (Kirschke et al., 2013; Reeburgh, 2007). On the other hand, methanogens, as biocatalysts, can help solve future energy crises by producing methane as a storable energy source (Enzmann et al., 2018). Methanogens use the end products of fermentation, such as acetate, H2, CO2, and methylated compounds, to yield methane. Bacteria and fungi form these compounds as byproducts of organic matter degradation (Cord-Ruwisch et al., 18 1988; Sieber et al., 2012) (Figure. 2.1). Methanogens metabolize acetate and H2, thereby reducing the concentration (acetate) and partial pressure (H2), hence, making it energetically favourable for their syntrophic allies (Jackson and McInerney, 2002; Sieber et al., 2012). Altogether, the organic matter decomposition into methane accounts for 2% of all CO2 fixed yearly (Thauer et al., 2008). Cofactors are mostly coenzymes or metal ions that catalyze enzymatic activities. Coenzymes are organic molecules with functionality not typically found in proteins and are catalytically crucial molecules that covalently bind to enzymes (Broderick, 2001). Most cofactors are specific for methanogens, but the basic skeleton resembles the general redox cofactors (Foster and Slonczewski, 2016). Methanogens process C1 and C2 compounds (i.e. acetate, formate, CO2, methanol, ethanol, methylamines, and methyl sulphides) for their growth and metabolism by converting them to methane (Garcia et al., 2000; Liu and Whitman, 2008). It has also been shown that some species of isolated methanogens have utilized compounds such as secondary alcohol and composite substrates, including aromatic-methoxylated compounds (methoxydotrophic methanogenesis) (Figure 2.1) (Hoedt et al., 2016; Mayumi et al., 2016). Depending on the nature of the substrate used, the classical Euryarchaeota methanogenic genealogy is mainly classified as hydrogenotrophic, acetoclastic, methylotrophic, and H2-dependent methylotrophs. 19 Figure 2.1. Methanogenesis routes for carbon recycling (modifed from the literature (Evans et al., 2019)).20 The methane generation by methanogens partially depends on the concentration of available hydrogen. Under hydrogen-rich conditions (Reaction 2.1), such as in oil wells and municipal sludge, it allows electron transfer along with the energy donation driven by the sodium ion potential (ΔNa+) (as in Methanosarcina) (Evans et al., 2019). Methanogenic archaea require sodium for growth and metabolism. Ultimately, methanogenesis generates a Na+ potential, leading to the synthesis of adenosine triphosphate (ATP). At a lower concentration of hydrogen (<0.0001 atm) (Reaction 2.2), such as in soil and water, free energy (∆G°´) becomes less favorable. 4H2 + CO2 → CH4 + 2H2O (∆G°´= -131 KJ/mol) Reaction 2.1 2H2 + Fd2-(ox) → Fd(red) (∆G°´= -3 KJ/mol) Reaction 2.2 Various transition metals are required for enzyme catalysis that promotes methanogenesis. For example, the hydrogenase enzyme that reduces F420 (F420 is a cofactor in the catalysis of many redox reactions in biology species) necessitates iron and nickel (Evans et al., 2019; Foster and Slonczewski, 2016). Another B12-linked cofactor with cobalt as a precursor is required when methanol or methylamine are used as a substrate (Foster and Slonczewski, 2016). Values of ΔG°' (KJ/mol) obtained from the literature help us understand the viability of the general pathway (Costa and Leigh, 2014; Kaster et al., 2011; Thauer et al., 2008). Similarly, anaerobic methanotrophy attained by various archaea is also an imperative progression of the global methane cycle. Methane is utilized as a source of carbon and energy by these methanotrophic archaea (Figure. 2.1). This is accomplished by directly reducing inorganic ions or by electronic transfer between 21 syntrophic bacteria (Boetius et al., 2000; McGlynn, 2017; Orphan et al., 2002; Timmers et al., 2017). These methanotrophs can also reverse their enzymatic reaction to synthesize trace amounts of methane (Holler et al., 2011). In comparison to archaeal methanotrophic microbes, bacterial methanotrophs catalyze diverse groups of enzymes and electron transporters proteins to oxidize methane in the presence of oxygen as the terminal electron acceptor (Figure. 2.1). The fundamental differences among biochemical processes for hydrolysis, acid and methane generation are well known. However, there is still a bottleneck in treating organic waste in anaerobic bioreactors due to rate-limiting steps of hydrolysis (for complex organic waste, such as municipal sludge, animal manure, lignocellulosic residues) and methanogenesis (for readily bioavailable substrate). The expansion of prototype species with genetic tools and bioinformatics has progressed in this area and provides additional information for the exploration and commercialization of methanogenesis in more advanced AD systems (Costa and Leigh, 2014). 2.3 Electroactivity mechanism of syntrophic bacteria and archaea The metabolism can also be visualized as the flow of electrons between the donor and the acceptor (Buan, 2018). The syntrophic microorganisms survive on the metabolic byproducts of another species. This creates a critical interdependency between these producer and consumer microorganisms. The exchange of the byproducts supports the flow of electrons and creates favourable conditions for microbes to survive (Summers et al., 2010). The cooperative interaction between the various species and the exchange of electrons is one of the essential processes in AD. Hydrolytic microorganisms oxidize large macromolecules into small organic 22 compounds such as monosaccharides, fatty acids, and alcohols. Finally, these compounds are then converted to acetic acid by acetogenic microorganisms and, thus, act as a substrate for methanogens that exchange electrons for reducing them to methane and CO2 (Lee et al., 2012; Malvankar and Lovley, 2014; Sieber et al., 2012). Section 2.7 below highlights the effect of conductive materials on the distribution of the microbial community of syntrophic microorganisms. Fascinatingly, there are specific microorganisms, generally referred to as electrochemically active bacteria, that can establish stable (long-term) and long-range (~4100 μm) electrical connections with extracellular acceptors (Kumar et al., 2017). Under a limited soluble electron acceptor concentration, these bacteria act as a catalyst to expedite the electron transfer to the external electron acceptor through a membrane. This process of extracellular electron transfer emerges as a unique model system because it limits the biotic-abiotic restrictions to attain direct energy translation from biological to electrical systems (Hsu et al., 2018). In recent years, many efforts have been made to investigate the mechanism of extracellular electron transfer, which occurs via indirect and direct routes (Kumar et al., 2017). In the indirect mode of electron transfer, the metabolites (phenazines, flavins, and quinones) conduct and transfer electrons to extracellular acceptors (Stams and Plugge, 2009). Under ideal conditions, these metabolites can be reintroduced into the bacteria to allow subsequent transport of electrons. This process is commonly referred to as electron shuttling (Hsu et al., 2018; Malvankar and Lovley, 2014) (Figure 2.2a). The electron transfers via mediated and direct routes are discussed below in detail. 23 Figure 2.2. Schematic diagram of microbial syntrophy in a) mediated interspecies electron transfer (MIET), b) direct interspecies electron transfer (DIET) with cytochromes, and c) DIET with conductive material (modified after (Malvankar and Lovley, 2014)). 2.4 Electron transfer through mediated interspecies electron transfer (MIET) Mediated interspecies electron transfer (MIET) is the conventional electron transfer model that integrates the dispersion of metabolites produced by one organism and often consumed by another. MIET, also known as the interspecies transfer of hydrogen, occurs in a variety of natural and engineered systems that embrace AD, such as freshwater/marine sediments, landfills, and so on (Heimann et al., 2006; Ishii et al., 2005; Stams et al., 2006). MIET requires that the metabolite remains at a sufficiently low flux in order to be thermodynamically favourable (Stams et al., 2006; Stams and Plugge, 2009). Hydrogen molecules play a significant role in microbial metabolism even though they exist at low concentrations in the biosphere (Conrad et al., 1986; Tilche and Galatola, 2008; Vignais and Billoud, 2007). The consumption of H2 at low partial pressure (<0.0001 atm) by methanogenic archaea typically allows the secondary fermentation of fatty acids and alcohol by syntrophic H2-producing bacteria (Cheng and Call, 2016). 24 In the microbial pathways, the utilization of hydrogen as a reducing power source, or the use of protons (H+) as the terminal electron acceptor, is mediated by hydrogenase. Anaerobic microorganisms utilize protons for hydrogen synthesis. Hydrogen generation is a simple oxidation-reduction process that involves composite active-center enzymes. The need for catalytic transition metal centers is explained by a significant increase in the acidity of molecular hydrogen when bound to them. There are three physiologically unrelated classes of these enzymes: [NiFe]-hydrogenases, [FeFe] -hydrogenases, and a third class in which hydrogen uptake is linked to the reduction of methenyl- tetrahydromethanopterin (methenyl‐H4MPT). In the reversible conversion of 2H+ + 2e-to H2 is the only substrate or product for [NiFe]- and [FeFe] -hydrogenases (Hedderich and Forzi, 2005; Vignais and Billoud, 2007). Many methanogens use hydrogen to reduce carbon dioxide, but there are distinctions between different species with and without cytochrome (Thauer et al., 2008). Cytochromes are a highly conserved protein across a spectrum of species found in plants, animals, and many unicellular organisms, including methanogenic archaea (Stams and Plugge, 2009; Thauer et al., 2008). Cytochromes c (Cytc) are abundant proteins involved in electron transfer and are essential enzymes in the global nitrogen and sulfur cycles. These proteins contain heme and are located in the region between the inner and outer mitochondrial membranes, where they play a critical role in transferring electrons within the respiratory chain. Cytochrome-deficient methanogens employ the redox mediator ferredoxin and factor-F420. At a very low concentration of hydrogen, these methanogens work as the most imperative hydrogen ion sequestrants in symbiotic communities (Stams and Plugge, 2009). 25 2.5 Electron transfer through direct interspecies electron transfer (DIET) via bacterial nanowires In engineered and natural anaerobic systems, the electron transfer mechanism between species of various bacteria and archaea plays an essential role in the biodegradation of organic matter. Evidence suggests that electron transport between these syntrophic species is not based solely on diffusible metabolites (such as H2) but also through several possible direct routes (Viggi et al., 2014). Under anaerobic conditions, DIET acts as a more efficient electron exchange mechanism than MIET for the reduction of molecules such as hydrogen and formate (Lovley, 2012, 2011a, 2011b). The discovery of DIET has significant implications for microbial community interactions. These interactions can be exploited by many natural and artificial systems, such as AD and electrochemical technologies (Cheng and Call, 2016). Electrochemically active microorganisms can also transfer electrons directly across their outer membrane by electron tunnelling or redox reactions with closely connected extracellular electron acceptors. These microorganisms can communicate remotely using various long-distance micro-to-nanoscale extracellular assemblies that enable long-distance extracellular electron transfer processes. The electronic interaction between these species is mainly performed by a series of conductive redox proteins, cytochrome type-C (cyts) (Richter et al., 2009; Shi et al., 2016). Currently, the two most studied bacterial species, Shewanella and Geobacter, show that they can develop a pilus-like structure (usually called bacterial nanowires) that aids long-distance electron transfer (Gorby et al., 2006; Pirbadian et al., 2014). These nanowires are involved in the flow of carbon and minerals in soil, sediment, 26 corrosion, bioremediation, and anaerobic degradation of organic waste into methane gas and electricity (Malvankar et al., 2011; Malvankar and Lovley, 2014). Researchers increasingly study these amino acid-based electronic nanostructures due to their low cost, no toxicity, and efficacy (Ashkenasy et al., 2006; Hauser and Zhang, 2010; Reynolds et al., 2019). Studies suggest that the mechanism of electron transfer in Shewanella and Geobacter is unusually dissimilar (Malvankar and Lovley, 2014). Two different extracellular electron transfer models have been proposed to explain the electron transfer mechanism in nanowires, namely: (1) metallic-like electron transfer and (2) electron hopping (Figure 2.2b). In metal-like electron transfer models (such as Geobacter sulfurreducens) (Tan et al., 2017), electron transfer is achieved through the overlying π-π orbitals of the aromatic amino acids in the nanowires, sharing like mechanisms such as synthetic organic polymers (Malvankar et al., 2011; Malvankar and Lovley, 2012; Qian and Li, 2011). A study (Wang et al., 2019) reported that the core protein of nanowires contains metal-containing molecules called hemes. Long-range transfer (>10 μm) of electrons in Geobacter sulfurreducens’ nanowires explain an imperative redox phenomenon. Previously, type IV pili were thought to be composed of PilA protein. However, it was found that conductive Geobacter sulfurreducens filaments are polymerized chains of OmcS that play an essential role in insoluble electron acceptors in bacterial growth. This is achieved by using a 3.7Å resolution cryo-electron microscopy structure (Wang et al., 2019). The desired conductivity strengths of individual filaments indicate that the OmcS are necessary for conductivity in the nanowires. The structures are reported to be 27 providing evidence about the sharing of energy and nutrients via supramolecular protein nanowires with the size of several hundred microns. Various extracellular soil bacteria use those structures for respiration and the symbiotic association with their partner species (Wang et al., 2019). In the electron-hopping model (Figure 2.2b), electron transfer is accomplished by a sequence of redox reactions through a strictly aligned cytochrome type-C along the nanowires. This can be described by the standard electron hopping mechanism of redox polymers. In Shewanella, transmembrane electron transport is accomplished by the transfer of electrons to external electron acceptors via CymA (tetrahemecytochrome c) followed by metal reduction proteins (e.g., MtrA, MtrB, and MtrC) (Coursolle et al., 2010; Yang et al., 2012). Self-excreted flavins also participate as electron shuttles in extracellular electron transfer (Marsili et al., 2008). The advancements in the structural origin of the conductivity of microbial nanowires discussed here provide the design principles for the expansion of forthcoming bio-electrochemical applications (Wang et al., 2019). 2.6 Thermodynamics of methanogens for direct interspecies electron transfer (DIET) In closed anaerobic systems, the metabolic bioactivity of any organism can be estimated by the change in the Gibbs free energy (ΔGo′). Various factors such as physiological change (pH, temperature, pressure, shear stress, etc.) and net metabolite flux can also affect population growth by increasing the entropy of cellular systems (Buan, 2018). The bioenergetics of methanogenic archaea have several unique features and are said to be near the edge of thermodynamic life (Buan, 2018). 28 The most common substrate for methanogenic archaea is CO2 and H2 (Morgavi et al., 2010). Reaction 2.1, presented earlier, describes the overall methanogenesis process by hydrogenotrophic bacteria at a high concentration of H2. The process has a free energy change (ΔGo′) of -131 KJ/mol (Conrad et al., 2007). In acetoclastic methanogens (Reaction 2.3), the ΔGo′ is -36 KJ/mol (Schlegel and Müller, 2013). In methylotrophic methanogens (methanol, methyl-amine consuming archaea) (Reactions 2.4, 2.5), the ΔGo′ for the substrate is relatively lower than in hydrogenotrophic methanogens (Schlegel and Müller, 2013). Therefore, the preferred thermodynamic route (at higher H2 concentrations) is the hydrogenotrophic route due to its higher negative ΔGo′ value. At very low concentrations of H2, the ΔGo′ (in hydrogenotrophs) is reduced to 1/3 of its original values (Hoehler et al., 2001; Schlegel and Müller, 2013). At lower H2 concentrations, the reduced ferredoxin is utilized to initiate the CO2 reduction to formylmethanofuran (CHO-MFR). This is accomplished through Na+ influx through membrane-bound energy-intense hydrogenases (Cheng and Call, 2016; Foster and Slonczewski, 2016), (Reaction 2.2). CH3COOH → CH4 + CO2 (ΔGo′ = -36 KJ/mol) Reaction 2.3 4CH3OH → 3CH4 + CO2 + 2H2O (ΔGo′ = -106 KJ/mol) Reaction 2.4 4(CH3)3NH+ + 6H2O → 9CH4 + 3CO2 + 4NH4+ (ΔGo′ = -76 KJ/mol) Reaction 2.5 DIET can provide additional energy benefits in promoting the syntrophic relationship between the anaerobic community. Thermodynamically, the available free energy compared to the interspecies hydrogen transfer mode is an essential consideration with respect to DIET in the methanogenesis process. This is because no energy loss is linked with the intermediate formation and subsequent redox 29 reactions. However, determining the energy gain of each partner during DIET is difficult. Table 2.1, revised from the literature (Cheng and Call, 2016), compares DIET and MIET half-reactions. DIET can thermodynamically promote the methanogenesis pathway conversion because of its higher ΔGo′ value above MIET under standard biological conditions (pH = 7). DIET electron-accepting half-reactions are thermodynamically endergonic, whereas, in MIETs, they are exergonic. The electron transfer phenomena in DIET and MIET are still unclear and require further study (Cheng and Call, 2016). 30 Table 2.1. Thermodynamic relation in DIET and MIET mechanisms# electron accepting electron donating Overall reaction CH3CH2OH + 1/2HCO3- → CH3COO- + 1/2CH4 + 1/2H+ + 1/2H2O (ΔGo′ = -58.1 KJ/mol) MIET* 1/2H+ + 2H2+ 1/2HCO3→1/2CH4 + 3/2H2O (ΔGo′ = -67.8 KJ/mol) CH3CH2OH + H2O → CH3COO + H+ + 2H2 (ΔGo′ = +9.7 KJ/mol) DIET** 9/2H+ + 4e- + 1/2HCO3→ 1/2CH4 + 3/2H2O (ΔGo′ = +91.5 KJ/mol) CH3CH2OH + H2O → CH3COO + 5H+ + 4e- (ΔGo′ = -149.6 KJ/mol) Overall reaction CH3CH2COO- + 3/4H2O → CH3COO- + 3/4CH4 + 1/4HCO3- + 1/4H+ (ΔGo′ = -25.2 KJ/mol) MIET 3/4H+ + 3H2+ 3/4HCO3 → 3/4CH4 + 9/4H2O (ΔGo′ = -101.7 KJ/mol) CH3CH2COO + 3H2O → CH3COO + HCO3+ H+ + 3H2 (ΔGo′ = +76.5 KJ/mol) DIET 27/4H+ + 6e- + 3/4HCO3 → 3/4CH4 + 9/4H2O (ΔGo′ = +137.3 KJ/mol) CH3CH2COO + 3H2O → CH3COO + HCO3 + 7H+ + 6e‐ (ΔGo′ = -162.5 KJ/mol) *MIET: Mediated interspecies electron transfer, **DIET: Direct interspecies electron transfer #modified from Cheng and Call, 2016 31 2.7 Electron transfer through direct interspecies electron transfer (DIET) via external additives Conductive pili (e-pili) can be the main electrical channel for the DIET. Electrical connections may still be established between the electron transport proteins bound to the outer membranes of the syntrophic partners. DIET associates may also be bonded to externally added conductive materials, facilitating electron transfer without using e-pili (Lovley, 2017). The additives that are used to improve microbial syntrophy in AD are classified into two parts: organic additives (i.e. green biomass, microorganisms, and enzymes) and inorganic additives (i.e., macro-and micro-nutrients and carbonaceous material) in nano, bulk, and/or salt form (Baniamerian et al., 2019). Researchers have effectively employed numerous nanomaterials to study their catalytic effect on improving bacterial syntrophy and methanogenic activity. The following section highlights the inorganic materials recently used to advance the AD process (Baniamerian et al., 2019). 2.7.1 Conductive carbon-based material The growing evidence on DIET stimulation by carbon conductive materials has motivated researchers to search for materials that can effectively increase bacterial syntrophy in an AD system (González et al., 2018). Carbon-based conductive materials (such as granular activated carbon, powdered activated carbon, biochar, carbon cloth, graphite, graphene oxide, etc.) are widely used to stimulate DIET due to their higher durability, high surface-to-volume ratio, conductivity, no ecotoxicity, and corrosion resistance (Pham et al., 2009). Meanwhile, various other positive aspects of incorporating a conductive carbon-based material in AD exist. Microbial 32 enrichment or biofilm formation is another favourable implication of increased methanogenesis which further contributes to DIET. The biofilm shields against harsh external conditions, promoting microbial attachment to conductive materials (He et al., 2020; Yang et al., 2020). Granular activated carbon (GAC) is often used because of fermentative bacteria and methanogens’ colonization, adsorption of toxins (ammonia, volatile fatty acids), and its higher surface/volume ratio for heavy metal accumulation that mitigates inhibition of methanogenic activity in AD liquid phase. The use of GAC in the co-culture of Geobacter metallireducens and Methanosarcina barkeri has also been shown to shorten the CH4 lag phase from 39 to 6 days. When GAC is exchanged for carbon cloth in the same culture, the methane lag phase is reduced from 40 days to 10 days (Rotaru et al., 2014a). In another study, powdered activated carbon (PAC) allowed for higher loading conditions than GAC (Zhao et al., 2016b). Biochar, a porous organic carbon material, is comparable to GAC in terms of the large surface area for adsorption and electrical conductivity. The use of biochar also stimulates syntrophy for DIET (Zhao et al., 2015). Furthermore, the use of various carbon nanomaterials (such as carbon nanotubes, graphite, and carbon nanoparticles (NPs)) also significantly increase DIET (discussed further in the next section). Most of these studies initially postulated that the increase in methanogens’ syntrophy (DIET) is based solely on the conductivity of the conductive material. However, the use of biochar gives comparable results with GAC despite having a conductivity 1000 times less than that of GAC (Chen et al., 2014). This result suggests that conductivity is not the only factor that governs syntrophy among cultures. 33 2.7.2 Robustness of carbon cloth Different materials have their own unique advantages. For example, carbon cloth (also known as graphite fibres, made of strong crystalline filaments of carbon material) has been found to require less maintenance for cleaning or sloughing colonized cultures by adjusting the hydraulic loading (shear) compared to reactors using fluidized or suspended powdered conductive media (Sasaki et al., 2009), which is an advantage. Also, it can be more difficult to recycle or reuse powdered media compared to carbon cloth fibres as it can easily be removed from the system. Like other conductive materials, carbon cloth has been reported to enhance methanogenesis by facilitating the transfer of electrons between cells, electrodes, and other cells (Dang et al., 2016; Zhao et al., 2017b). Furthermore, carbon cloth has the advantage of being able to remain in the reactor without being washed out, which can be a problem for granular or powdered conductive materials such as biochar or granular carbon (Park et al., 2018). Among the various conductive carbon materials commonly used, such as carbon cloth, graphite rod, and biochar, carbon cloth has been found to have superior performance in terms of enhancing COD removal during the syntrophic conversion of ethanol to methane using a mixed culture, and also provides a permanent conductive conduit for syntrophic metabolism (Zhao et al., 2015). Various efforts have been made to coat carbon cloth with polymeric binders to enhance redox reactions for battery applications (Chen et al., 2017; Kordek et al., 2019; Yu et al., 2017). The functionalization of carbon cloth matrix with heteroatoms 34 such as sulfur, phosphorus, and/or nitrogen leads to the formation of charge and spin redistribution in the sp2 carbon lattice, which creates active sites for carrying out oxidation-reduction reactions (Jiao et al., 2014; Kordek et al., 2019; Suryanto et al., 2016; Jibo Zhang et al., 2018). While oxygen doping on carbon cloth can be relatively easy through the introduction of air or water under mild conditions, the effects of oxygen doping on carbon cloth have not been well studied in literature (Kordek et al., 2019). Table 2.2 summarizes the effects of various carbon-based materials on AD operated under different supplement dose, AD temperature, reactor configurations and substrate type. In general reactors that received various conductive materials showed an increase in methane yield over control digesters (without conductive material); however, the extent of improvement varied depending on the dose, substrate, inoculum, reactor type, and operating temperature. For example, Dang and colleagues (Dang et al., 2017) reported a significantly higher increase in methane yield (1800%) in reactors amended with GAC in batch experiments, which may have been due to the use of additional trace elements and vitamins in these experiments, while Yang and colleagues (Yang et al., 2017) reported a minimal increase (17%) in methane yield from the addition of GAC. Both authors used waste-activated sludge (WAS) and it has relatively lower readily degradable organics and more microbial cells, making it difficult to digest in the conventional AD process. 35 Table 2.2. Carbon-based materials used in anaerobic digestion (AD) systemsa Dose (g/L) Inoculum Substrate type Reactor Type AD temperature (ºC) Methane increase (%) Remarks Ref. GAC 40 Anaerobic sludge obtained from a municipal treatment plant Artificial dairy wastewater Two-phase AD, semi-continuously fed 37 Methane was increased by 44% - (Zhao et al., 2017a) - Obtained from an anaerobic digester at a municipal WWTP Dog food Batch 37 Cumulative methane production was 1800% times higher compared to the control - (Dang et al., 2017) 33.3 Collected from a mesophilic anaerobic digester Acetate Batch 34 Methane production increased by 83% - (Zhang et al., 2017) 2.5 Taken from a conventional anaerobic digester Synthetic wastewater CSTR 35 GAC showed 80% higher methane production - (Lee et al., 2016) ~3 to 33 Taken from a sludge treatment plant Dewatered waste-activated sludge Batch 37 Methane production increased by 17.4% - (Yang et al., 2017) Biochar ~287 Coculture of Geobacter Ethanol Batch 37 - No methane generation was observed without biochar (Chen et al., 2014) ~66 Obtained from an on-farm biogas plant Pyrolyzed paper sludge and wheat husks (1:2) Batch 42 Hydrochar increased methane yield by 32% Pyrochar was ineffective in biogas production (Mumme et al., 2014) ~7.7-15.5 Obtained from a methane-phase digester Sludge obtained from an acid-phase digester Batch 55 19% methane increment was observed - (Shen et al., 2015) 36 Dose (g/L) Inoculum Substrate type Reactor Type AD temperature (ºC) Methane increase (%) Remarks Ref. 5 Obtained from the anaerobic digester of a municipal WWTP Propionate UASB 37 The methane production rate increased by 16% - (Zhao et al., 2016a) ~12 to 36 Digested municipal sludge Citrus peel Batch 35 Corn stover biochar increased methane production by 11.18% - (Fagbohungbe et al., 2016) Carbon cloth, Carbon felt, GAC, Graphite rods and Polyester clothes - Obtained from the anaerobic digester of a municipal wastewater treatment Artificial complex waste Batch fed 37 - Graphite was ineffective. Under high OLR, the control experiment failed; only GAC amended system survived (Dang et al., 2016) Carbon cloth - Anaerobic suspended sludge collected from a full-scale UASB Leachate collected from an MSW to energy incineration plant UASB 33 - At OLR higher than 30,000 mg COD/l inhibition was observed in control but not in the reactor with carbon cloth (Lei et al., 2016) - Obtained from an anaerobic digester of a local WWTP Artificial wastewater Semi-continuous 37 Methane production increased by 59% - (Zhao et al., 2017b) Carbon black 5 and 20 Sludge obtained from a municipal municipal plant Glucose and acetate Batch 37 - Addition of carbon black inhibited methanogenesis (Fujinawa et al., 2019) 37 Dose (g/L) Inoculum Substrate type Reactor Type AD temperature (ºC) Methane increase (%) Remarks Ref. Activated carbon 5 Taken from the secondary sedimentation tank of a WWTP Synthetic brewery wastewater UASB 35 Higher biogas volume and methane content observed (% not given) - (Xu et al., 2015) Carbon nanotubes 0.1 to 5 Methanobacterium formicicum, Methanosaeta concilii, Methanosarcina mazei, Methanospirillum hungatei, Syntrophomonas wolfei H2/CO2 Batch 37 Only for M. Formicicum, a significant increase was observed as 200% 5000 mg/l CNT inhibited methane production by M. Concilii (Salvador et al., 2017) ª AD: Anaerobic digestion, COD: Chemical oxygen demand, OLR: Organic loading rate, GAC: Granular activated carbon, WWTP: Wastewater treatment plant, CSTR: Continuous stirred tank reactor, UASB: Upflow anaerobic sludge blanket, MSW: Municipal solid waste, CNT: Carbon nanotubes. 38 Furthermore, a group of researchers (Cimon et al., 2020) reported a significantly higher methane yield in batch reactors amended with biochar compared to control experiments, corresponding to a 192 to 461% increase. The authors used acidified sludge from a temperature phased AD system (TPAD) (operated at 55°C) as substrate to set up the batch experiments. A TPAD is an advanced digestion method that contains two stages in series, the first stage is a thermophilic digester, and this is followed by the second stage in the mesophilic state. The first stage on a TPAD provides acidified sludge.This type of sludge is enriched in VFA, mainly acetic acid, a readily biodegradable substrate for acetoclastic methanogens responsible for more than 70% of methane production in AD. Another group of researchers (Salvador et al., 2017) reported a 200% increase in methane yield for reactors fed with Methanobacterium formicicum as inoculum and H2/CO2 as substrate after being amended with carbon nanotubes. This result is not surprising since Methanobacterium formicicum (pure culture) is a hydrogenotrophic methanogen that will perform well when provided with a suitable substrate (H2/CO2). It is crucial to note that the use of these materials in full-scale operation for continuous-flow AD amended with conductive materials requires more information, as most literature only provides data from small-scale batch-mode experiments conducted in serum bottles or reactors (Table 2.2). As previously mentioned, the effectiveness of carbon conductive materials is highly dependent on the type of substrate and inoculum used. The small-scale BMP assays are not standardized worldwide, thus, the type of substrate, type/activity of anaerobic inoculum, BMP setup conditions (substrate to inoculum ratio, buffer and nutrient media type/dosage), as 39 well as the dose/particle size of conductive material can significantly change the results. Therefore, scaling up for continuously-fed AD systems amended with conductive materials will require testing with various types of conductive materials for specific substrate/inoculum conditions. This will also enable researchers to study the economic feasibility, including capital and operational costs of AD with carrier materials for full-scale application. So far, various conductive carbon materials have been assessed in the digestion of composite wastes. New and innovative research techniques are being studied to improve methanogenesis in anaerobic reactors and to optimally select carbon-conductive materials by considering various physicochemical factors (González et al., 2018). The concept of DIET using carbon-conductive materials suggests that the biocarrier potential of the conductive material is an important property that needs to be addressed. This creates new directions and opportunities for multidisciplinary research bringing together expertise from environmental engineering, environmental genomics, and materials science to understand biocarrier potential and electron transfer mechanisms in AD with different substrates, inoculum, and microbial communities. 2.7.3 Conductive nanomaterials In the past few decades, the fast-evolving field of nanotechnology has created a wide variety of nanomaterials (size: 1-100 nm). These are generally considered "engineered nanomaterials or in some cases in the form of nanoparticles (NPs)" and are questionable to many communities. In fact, the concept of nanotechnology is not 40 new to natural ecosystems that provide an assortment of NPs from organic and inorganic sources such as ash, soot particles from volcanic eruptions, minerals and many organic/inorganic NPs produced by several microorganisms (Griffin et al., 2017). The NPs are sub-categorized according to their physicochemical composition into four main categories: organic, inorganic, composite, and carbon-based NPs. At the nanoscale, the properties of materials alter impulsively, and the particle behaves in an entirely different way compared to the particle at its macroscale (Faisal et al., 2018). Nanoparticle synthesis is a growing technology due to the unique thermal, mechanical, and structural properties and the high specificity of conductive nanomaterials (Ünşar and Perendeci, 2018). Carbon nanotubes and graphene have been successfully utilized to promote methanogenesis (Kang et al., 2007) because of their higher mechanical strength, electrical and thermal conductivity compared to various organic and synthesized conductive materials such as biochar, conductive polymers etc. (Behabtu et al., 2013). In these studies, conductive polymers can also replace carbon-based or iron-based nanomaterials. For example, the use of polyaniline nanorods has been reported to promote methane formation in anaerobic reactors (Hu et al., 2017). Several studies report the use of magnetite for methane enhancement and state that it promotes DIET by substituting the conductive nanowires with magnetite for electrical communication (Viggi et al., 2014). The addition of magnetite particles allows mutants of Geobacter sulfurreducens, which cannot express the OmcS, to carry electrons extracellularly. This means that 41 magnetite could replace the OmcS sequence during DIET (Lovley, 2017). Since the microbial growth and development of biological structures such as cytochromes requires a large amount of energy, the anaerobic microorganisms (for example, obligate syntrophic organisms) may efficiently utilize synthetic and natural conductive materials as electron channels for DIET (Nozhevnikova et al., 2020). Nanomaterials can interact with biological systems (such as microorganisms) by penetrating their cell membranes (Huangfu et al., 2019). Conductive nano-minerals reinforce the link between electricity-producing bacteria and methanogenic archaea (Xiao et al., 2018). Supplementing micronutrients in the form of NPs has been shown to improve AD performance. The slow dissolution of NPs promotes their bioavailability in AD systems and thereby enhances enzymatic activity (Abdelsalam et al., 2017a, 2017b). Increased bacterial syntrophy between specific microbial populations (e.g., Geobacter and Methanosaeta species) has been proposed, leading to a higher overall methane yield by using iron-oxide as a conductive mineral material. The results suggest that these materials are electrically cross-linked (i.e., DIET) between Geobacter and Methanosaeta species (Kato et al., 2012). A series of studies reveal the favourable effect of nano-iron oxides on methanogenesis from various substrates such as ethanol, acetate, propionate, and butyrate (Abdelsalam et al., 2016; Suanon et al., 2016; Xiao et al., 2018). Nevertheless, it has been observed to take several days to demonstrate the function of nano-Fe3O4 to upsurge methane formation (Xiao et al., 2018). Table 2.3 illustrates an upward trend in methane production rates in AD systems supplemented with multi-compound NPs. A group of researcher (Amen et al., 2017) 42 demonstrated a superior performance when multiple NPs were added in AD compared to control digesters without additives, with the highest biogas accumulation in samples modified with zeolite coated with nano-zerovalent iron (NZVI) by adding more iron NPs. These results may be due to the high reactivity of NPs with NZVI, which improved electron transfer in methanogenesis. Additionally, Beckers et al. (2013) reported improved hydrogen production through the potential influence of NPs as chemical catalysts on interactions and electron transfer between hydrogen-producing microorganisms (Beckers et al., 2013). 43 Table 2.3. Metal oxide nanoparticles (NPs) used in anaerobic digestion (AD) systems* Metal oxide size (nm) Dose (mg/l) Substrate type Inoculum type Reactor type AD temperature (ºC) Methane increase (%) Remarks Ref. Mn2O3 - 1500 Acetate and hydrogen Granular sludge Batch 30 - No toxic effects on methanogens (Gonzalez-Estrella et al., 2013) Fe3O4 7 100 Crystalline cellulose Mesophilic anaerobic reactor Batch 37 8 (Casals et al., 2014) 15-22 50-125 Municipal solid waste Animal dung biogas plant Batch 37 53.3 (Ali et al., 2017) - 25000 Artificial dairy wastewater Anaerobic sludge from a municipal treatment plant Continuous-flow two-phase AD 37 44 (Zhao et al., 2017a) - 1257 Acetate and propionate Thermophilic anaerobic digester Batch 55 Slight increase in methane production (Yamada et al., 2015) - 1400 Fe atom Benzoate Rice paddy field soil Batch 30 2 (Zhuang et al., 2015) - 1563 Cheese whey Anaerobic sludge CSTR 35 - Magnetite supplementation had a beneficial effect on methane production and process stability (Baek et al., 2016) - 10000 Synthetic wastewater Anaerobic sludge from a lab-scale reactor ASBR 35 15.4 Lag phase was shortened by 13.9% (Yin et al., 2017) - 10000 Synthetic wastewater Secondary sedimentation ASBR 35 78.3 (Yin et al., 2018) 44 Metal oxide size (nm) Dose (mg/l) Substrate type Inoculum type Reactor type AD temperature (ºC) Methane increase (%) Remarks Ref. tank of a WWTP - 1400 Sodium acetate Paddy soil Batch 30 261 (Zhou et al., 2014) - 1116.8 Fe atom Whey Anaerobic sludge from a municipal WWTP Batch 35 316 (Baek et al., 2015) - 1116.8 Fe atom Propionate Rice field soil samples Batch 30 93 (Yang et al., 2016) - 558 Fe atom Sodium butyrate Lake sediment Batch 30 50 (Zhang and Lu, 2016) Fe2O3 128 100 mg/g TSS Waste activated sludge - Batch 35 117 (Casals et al., 2014) 20 750 Beet sugar industrial wastewater Anaerobic granular sludge Granular sludge bed reactor 36 29 (Ambuchi et al., 2017) - 750 Beet sugar industrial wastewater Anaerobic granular sludge Granular sludge bed reactor 36 35 (Ambuchi et al., 2018) 40 1500 Acetate and hydrogen Granular sludge Batch 30 No toxic effects on methanogens (Gonzalez-Estrella et al., 2013) Al2O3 <50 1500 Acetate and hydrogen Granular sludge Batch 30 No toxic effects on methanogens (Gonzalez-Estrella et al., 2013) MgO 45 Metal oxide size (nm) Dose (mg/l) Substrate type Inoculum type Reactor type AD temperature (ºC) Methane increase (%) Remarks Ref. 154 500 mg/g TSS Waste activated sludge Batch 35 99% methane yield reduction (Casals et al., 2014) CuO 30 7.5-480 Cattle manure Municipal anaerobic treatment reactor Batch 36 30% reduction in biogas production (Luna-delRisco et al., 2011) 30-50 5-1000 mg/g TS Centrifuged municipal waste activated sludge Anaerobic digester reactors Batch 37 Decline of biogas yield up to 84% (Ünşar et al., 2016) 40 10-1500 Acetate and hydrogen Granular sludge Batch 30 Inhibition on acetoclastic methanogens with IC50 value of 223 mg/l (Gonzalez-Estrella et al., 2013) CeO2 12 640 Cellulose Mesophilic and thermophilic anaerobic reactors Batch 37, 55 Decline of biogas yield nearly up to 100% (García et al., 2012) - 10,100, 500, 1000 Glucose Anaerobic sludge from UASB reactor, brewery company Batch 30 Decline of biogas yield up to 35% (Nguyen et al., 2015) 15-30 11, 110, 330, 550, 1100 Municipal waste, activated sludge 37 9.2% at the highest dosage (Ünşar et al., 2016) 50 1500 Acetate and hydrogen Granular sludge Batch 30 No toxic effects on methanogens (Gonzalez-Estrella et al., 2013) ZnO 46 Metal oxide size (nm) Dose (mg/l) Substrate type Inoculum type Reactor type AD temperature (ºC) Methane increase (%) Remarks Ref. 140 ±20 1,30,150 mg/g TSS Waste activated Sludge Secondary sedimentation tank of a municipal WWTP Batch 35 Decline of methane yield up to 75% (Mu and Chen, 2011) 145 5, 50, 100, 250, 500 Waste activated Sludge from municipal WWTP - Batch 37 Decline of methane yield by 50% (Zhang et al., 2017) 120-140 6, 30, 150 mg/g TSS Mixed primary and Waste activated sludge - Batch 35 Decrease of the abundance of methanogenic archaea/ methane yield (Zheng et al., 2015) - 10, 100, 500, 1000 Glucose Anaerobic sludge from UASB reactor, brewery company Batch 30 Decline of biogas yield up to 65% (Nguyen et al., 2015) 50-70 7.5-480 Cattle manure Municipal anaerobic treatment reactor Batch 36 Decline of biogas yield up to 74% (Luna-delRisco et al., 2011) 10-30 10-1500 Acetate and hydrogen Granular sludge Batch 30 Severe inhibition on acetoclastic and hydrogenotrophic methanogens with IC50 values of 62- 250 mg/l (Gonzalez-Estrella et al., 2013) SiO2 10-20 1500 Acetate and hydrogen Granular sludge Batch 30 No toxic effects on methanogens (Gonzalez-Estrella et al., 2013) TiO2 47 *CSTR: Continuously stirred tank reactor, ASBR: anaerobic sludge bed reactor, WWTP: Wastewater treatment plant, TSS: Total suspended solids, TS: Total solids, IC50: half maximal inhibitory concentration, UASB: Upflow anaerobic sludge blanket.Metal oxide size (nm) Dose (mg/l) Substrate type Inoculum type Reactor type AD temperature (ºC) Methane increase (%) Remarks Ref. 7.5 840 Cellulose Mesophilic and thermophilic anaerobic reactors Batch 37, 55 No effect (García et al., 2012; Gonzalez-Estrella et al., 2013) 150-170 6, 30, 150 mg/g TSS Mixed primary and waste activated sludge - Batch 35 No measurable effects on methanogens (Zheng et al., 2015) 25 1500 Acetate and hydrogen Granular sludge Batch 30 No toxic effects on methanogens (Gonzalez-Estrella et al., 2013) 48 Table 2.4 shows the impact of nano-zerovalent metallic NPs on AD. Amen and their group reported a 105.5% increase in methane production when NZVI was added to AD batch reactors treating domestic activated sludge (Amen et al., 2017). Other researchers reported a 120% methane increase when treating activated sludge in batch AD amended with NZVI using granular sludge as inoculum (Wang et al., 2016). Abdelsalam et al. (2016) reported an 86% methane increment when Co metal was used in batch AD that utilized manure. Similarly, a 74% increment was observed in the same experiment when Co was replaced with Ni metal (Abdelsalam et al., 2016). Yang et al. (2013a) reported a 20% decrease in methane production from batch AD-fed glucose when AD was amended with NZVI. High concentrations of NZVI (1 mM and above) can be dissolved in AD, promoting more rapid production and accumulation of hydrogen which further inhibits methanogenic activities (Yang et al., 2013a). Additionally, a decrease in methane yield in reactors amended with Ag was attributed to the long-term release of silver ions that destroy the cell membrane and inactivate enzymes during AD (Ünşar et al., 2016). Cu NPs in AD were found to decrease methane yield in AD presumably due to toxicant to the methanogenesis process (Amen et al., 2018; Gonzalez-Estrella et al., 2013). However, NPs of zero-valent transition metals, such as NZVI, Co, and Ni, improved the methane yield when dose adjustments were correctly made. 49 Table 2.4. Multi-compound nanoparticles (NPs) used in anaerobic digestion (AD) system Metal oxide size (nm) Dose (mg/l) Inoculum Substrate type Reactor type AD temperature (oC) Methane increase (%) Remarks Ref. Zeolite - 4000 Anaerobic digester sludge Domestic activated sludge Batch 37 24.86% increase in biogas production (Amen et al., 2017) NZVI and zeolite mixture - 500 mg NZVI + 4 g/L zeolite Anaerobic digester sludge Domestic activated sludge Batch 37 130.87% increase in biogas production (Amen et al., 2017) 45 nm NZVI NPs coated on 7.13 mm zeolite particles 500, 1000 mg/l regard to NZVI Anaerobic digester sludge Domestic activated sludge Batch 37 149.95%, 286.75% increase in biogas production (Amen et al., 2017) Iron oxide-zeolite system 20 nm iron oxide NPs coated on 0.5 -1mm zeolite particles Provide (20 mM); 1120 mg/l Fe element Anaerobic digestate Cow manure and rice straw Batch lab scale 35 372.85% (Lu et al., 2017) M/SiO2 - 10-5 mol/L Hydrogen-producing microorganism (C. butyricum) Acetate Batch hydrogen potential tests 55 M= Ni: 70%; Co: 48%; Fe: 7%; Pt: 6% (Beckers et al., 2013) NiO/TiO2 50 Metal oxide size (nm) Dose (mg/l) Inoculum Substrate type Reactor type AD temperature (oC) Methane increase (%) Remarks Ref. ~ 10 0.252 mg/g TS Anaerobic digestate Wheat straw Batch 55 Up to 13% increased soluble COD and up to 67% increase of VFA concentration, increased methane production rate (Baniamerian et al., 2019) NZVI: Nano zero valent iron, TS: Total solids, M: Metal, COD: Chemical oxygen demand, VFA: Volatile fatty acids. 51 The use of carbon-based nanomaterials in AD systems has been found to enhance methane production and VFA production while preventing hydrogen inhibition. Studies have shown that AD systems supplemented with single-wall carbon nanotubes at a dose of 1000 mg/l yielded the most promising results in terms of increased methane yield. These nanotubes have a high specific surface area that allows for the colonization of syntrophic microorganisms that aid in the digestion process. Additionally, the use of carbon nanotubes also speed up substrate use and shortened the lag phase (Li et al., 2015; Yan et al., 2017). From Tables 2.3 to 2.6, in terms of overall methane yield, the use of NPs or nanomaterials (nanotubes etc.) had a significant impact. However, some NPs can be toxic to the AD process, such as Cu, Ag, Zn, and Ce NPs. Carbon-based NPs and NPs with transition metals (Mn, Fe, Co, and Ni) have been found to be beneficial for increasing methane yield and reducing the lag phase, regardless of the substrate, inoculum, or AD system used. Among the transition metals, iron-containing NPs have been found to yield the highest methane gains in most studies, likely due to iron's abundance in nature and its role in growth and metabolism in organisms. Iron plays a major role in methanogenesis in AD systems. Acetogens and methanogens mutually interact with iron by establishing a series of reactions for acetate (Reaction 2.6) or methane formation (Reaction 2.7) (Palacios and Andrea, 2019). 4Feo + 2CO2 + 4HCO3- + 4H+ → 4FeCO3 + CH3COOH + 2H2O (ΔGo′ = -388 KJ/mol) Reaction 2.6 4Feo + CO2 + 4HCO3- + 4H+ → 4FeCO3 + CH4 + 2H2O (ΔGo′ = -446 KJ/mol) Reaction 2.752 Table 2.5. Zero-valent metallic nanoparticles (NPs) used in anaerobic digestion (AD) system Metal oxide size (nm) Dose (mg/l) Inoculum Substrate type Reactor type AD temperature (ºC) Methane increase (%) Remarks Ref. Silver (Ag) 30 130 Mesophilic and thermophilic anaerobic digestate Cellulose Batch 37 and 55 (García et al., 2012) <100 15,000 Methanogenic granular sludge Acetate and hydrogen substrate Batch acetoclastic and hydrogenotrophic methanogenic activity bioassays 30 No toxic effects on the methanogenic activity (Gonzalez-Estrella et al., 2013) 20-40 5-1000 mg/g TS WAS AD reactors Municipal waste activated sludge Batch 37 12.1% decrease in the methane production at the highest dosage (Ünşar et al., 2016) 170 500mg/g TSS Mesophilic anaerobic reactor digestate Waste activated sludge Batch 35 Decrease 27% of methane production. (Casals et al., 2014) 10-15 0.5, 1, 5 and 100 Two weeks starved anaerobic biosolids Cellulose Batch 37 Up to complete inhibition of anaerobic biogas production (Gitipour et al., 2016) NZVI 46-50 1500 Methanogenic granular sludge Acetate and hydrogen substrate Batch acetoclastic and hydrogenotrophic methanogenic activity bioassays 30 No toxic effects on the methanogenic activity (Gonzalez-Estrella et al., 2013) 53 Metal oxide size (nm) Dose (mg/l) Inoculum Substrate type Reactor type AD temperature (ºC) Methane increase (%) Remarks Ref. 55 56, 560 and 1680 Digested sludge from two stage mesophilic digester Glucose Batch 37 20% decrease in methane production (Yang et al., 2013a) 9 20 Slurry Fresh raw livestock manure Batch 37 Biogas and methane increased by 1.5 and 11.67 times respectively in comparison to the control, (Abdelsalam et al., 2016) 20 10 Dewatered WAS Batch 37 40.4% increase in methane production 30.4% increase in biogas production (Su et al., 2013) 45 1000 Anaerobic digester sludge Domestic activated sludge Batch 37 105.46% increase in biogas production (Amen et al., 2017) 160 100 Municipal sludge Batch 37 25.2% increase in methane production 10% increase in COD removal (Suanon et al., 2017) 50 750 and 1500 Anaerobic sludge Sludge Batch 37 The produced methane was 67,091, 97,804, and 47,186 ml/kg VSadded in the control, at 750 mg/l concentration and 1500 mg/l concentration, respectively Methane production improved at low concentration and inhibited at high concentration (Suanon et al., 2016) 9 5, 10 and 20 Slurry Fresh raw livestock manure Batch 37 59% increase in methane production 45% increase in biogas production (Abdelsalam et al., 2017a) 54 Metal oxide size (nm) Dose (mg/l) Inoculum Substrate type Reactor type AD temperature (ºC) Methane increase (%) Remarks Ref. 128 10 mg/g TSS Anaerobic granular sludge Waste activated sludge Semi-continuous flow reactors 35 Increase of 120% in methane production (Wang et al., 2016) 55 1, 2, 10, and 15 mM Anaerobic sludge Glucose Batch 37 H2 production due to NZVI dissolution was higher than that of control and methanogenesis was inhibited (Huang et al., 2016) 40-60 7 mg/g VS Lab-scale anaerobic sludge Municipal sludge Batch 35 The biogas yield increased from 106 (control) to 308 ml/g VS Ultrasonic pretreatment with NZVI (Lizama et al., 2019) 0.2 mm 0, 1000, 2000, 5000 and 10000 No inoculum addition WAS Batch 35 The lag time of methane production was shortened, and the methane yield increased by 91.5% compared to the control group (Zhang et al., 2015) Copper (Cu) 40-60 10-15,000 Methanogenic granular sludge Acetate and hydrogen substrate Batch acetoclastic and hydrogenotrophic methanogenic activity bioassays 30 Highly inhibitory to acetoclastic and hydrogenotrophic methanogens with IC50 values of 62 and 68 mg/l (Gonzalez-Estrella et al., 2013) 200 1500; 3000 Anaerobic digestate Municipal sludge Batch 37 At 1500 mg/l increased the biogas production three It was a bimetallic i.e., copper-iron (Amen et al., 2018) 55 Metal oxide size (nm) Dose (mg/l) Inoculum Substrate type Reactor type AD temperature (ºC) Methane increase (%) Remarks Ref. times the control. based (NZVL/Cuº) At 3000mg/l showed inhabitation of methanogens due to its disruption of cell integrity Cobalt (Co) 28 1 Slurry Fresh raw livestock manure Batch 37 86% increase in methane production Decrease lag phase, 64% increase in biogas production (Abdelsalam et al., 2016) 1 Slurry Fresh raw livestock manure Batch 37 Increased methane volume by 1.86 times than the control (Abdelsalam et al., 2017b) Nickel (Ni) 17 2 Slurry Fresh raw livestock manure Batch 37 74% increase in methane production Decrease lag phase, 101% increase in biogas production (Abdelsalam et al., 2016) 100 5-10 mg/ Kg VS Anaerobic digestate Mixed municipal sludge Batch 37 Increased methane yields up to 10% (Tsapekos et al., 2018) 2 Slurry Fresh raw livestock manure Batch 37 Increased methane volume by 2.01 times than the control (Abdelsalam et al., 2017b) 60 0-100 Enterobacter cloacae and mixed culture Glucose BHP 55 23% improvement in hydrogen production at an optimum dosage of 60 mg/l Decreased hydrogen production at high dose of 100 mg/l (Mohanraj et al., 2014) 56 Metal oxide size (nm) Dose (mg/l) Inoculum Substrate type Reactor type AD temperature (ºC) Methane increase (%) Remarks Ref. Gold (Au) 20 75 Mesophilic and thermophilic anaerobic digestate Cellulose Batch 37 and 55 Zero or slight toxicity effect on ordinary heterotrophic organisms, ammonia-oxidizing bacteria, and anaerobic bacteria (García et al., 2012) Others 87 5 Enterobacter cloacae and mixed culture Glucose BHP 37 Hydrogen yield was 1.48, 2.48 mol H2/mol glucose for different inoculum, respectively Palladium nanoparticles (PdNPs) synthesized from PdCl2 (Mohanraj et al., 2014) TSS: Total suspended solids, TS: Total solids, NZVI: Nano zero valent iron, WAS: Waste activated sludge, COD: Chemical oxygen demand, VS: Volatile solids, BHP: Biogas hydrogen potential test, IC50: half maximal inhibitory concentration. 57 Table 2.6. Carbon-based nanomaterials used in anaerobic digestion (AD) system Particle size (nm) Dose (mg/l) Substrate type Inoculum type Reactor type AD temperature (ºC) Methane increase (%) Remarks Ref. Length (nm) Diameter (nm) Multiwall carbon nanotubes NR NR 1500 Sugar beet industrial wastewater Anaerobic granular sludge Granular sludge bed reactor 35 Methane increased by 20% (Ambuchi et al., 2018) NR 10-20 1500 Sugar beet industrial wastewater Anaerobic granular sludge Granular sludge bed reactor 36 12.6% more methane than the control (Ambuchi et al., 2017) Single walled carbon nanotubes 5-20 1-2 1000 Sucrose Anaerobic granular sludge UASB 35 CH4 production rate increased by 100% No effect on the maximum CH4 yield (Li et al., 2015) 5-30 µm 1-2 1000 Glucose Lab-scale mesophilic CSTR Batch 55 CH4 production rate increased by 92% (Yan et al., 2017) Graphene (G) 4-20, thickness 5-10 µm 500-2000 Ethanol Activated sludge from lab-scale anaerobic digester Batch 35 Increase of 25% in methane yield and 19.5% in biogas production rate The optimal concentration of graphene (Lin et al., 2017) 58 Particle size (nm) Dose (mg/l) Substrate type Inoculum type Reactor type AD temperature (ºC) Methane increase (%) Remarks Ref. was 1000 mg/l NR NR 30-120 Glucose Activated sludge UASB 35 Up to 51.4% increase in methane production rate (Tian et al., 2017) 5-10 µm 3-6 thickness 7.5 Slurry (wheat straw fresh manure, cow urine, cow dung and food waste) - Batch 40 Increased methane yield by 2.54 times more than the control Graphene oxide was used (Kaushal and Baitha, 2018) 2 µm 16 thickness 250-1000 Amino acid glycine Lab scale CSTR Batch 35 Methane increased by 28% (Lin et al., 2018) NR: Not reported, UASB: Upflow anaerobic sludge blanket process, CSTR: Continuous stirred tank reactor, BHP: Biochemical hydrogen potential G: Graphene. 59 As mentioned earlier, when iron (Feº) is supplemented, methanogenesis becomes more favourable because of the higher negative ΔGo′ value. In addition, several groups of methanogens can use Fe (such as Methanosarcina, Methanobacterium and Methanococcus) (Palacios and Andrea, 2019). Unlike methanogens, acetogens (such as Clostridium), containing Fe-Fe hydrogenase, help to exploit iron at low temperatures and high H2 concentrations (Reaction 2.6) (Peters et al., 2015). The literature underlines the significant potential of iron-containing materials for progressive bacterial and archaeal syntrophy and DIET improvement. The effect of the size and dosage of conductive carrier materials on methane generation improvement with respect to conventional AD through digestion-induced enrichment (DIET) is summarized in Figure 2.3. Data from various sources (listed in Tables 2.3-2.6) were analyzed to understand the relationship between carrier material size (in nanometers) and dose (in mg/l or mg/total solids) on methane/biogas yield. The results show that smaller nanomaterials lead to larger increases in methane production and require lower doses for DIET enrichment. Therefore, it is important to consider the optimal size, dosage, and type of support material when attempting to improve methanogenesis in engineered anaerobic treatment systems. 60 Figure 2.3. Effect of nanomaterials’ dose and size on % change in methane/biogas yield with respect to control AD without nanomaterials, compiled from studies in literature 2.7.4 Concept of metalloporphyrin nanoparticles (NPs) to coordinate with diverse methanogenesis products Research in supramolecular chemistry has shown that molecular assemblies and intermolecular bonds (non-covalent weak and reversible interactions) can lead to the formation of various chemical derivatives with diverse functionalities. Polyporphyrins and related structures such as corroles and phthalocyanines are important molecules that play key roles in many biological processes (Shao et al., 2019; Zukerman-Schpector et al., 2012). Metalloporphyrins in microbial systems are known to participate in various bioactivities, with a notable role in methanogenesis. Recent studies have found that iron minerals coordinated with porphyrins help conductivity in Change in methane/biogas yield compared to control (%) 61 bacterial nanowires in the anaerobic microbial community. This suggests that iron conjugated with porphyrins is an important element in microbial biochemistry. The study by Wang et al., (2019) has found that the G. sulfurreducens nanowires are polymerized in hexaheme cytochrome OmcS, and the heme is packed within about 3.5-6 Å of each other. This heme coordination complex contains iron minerals (shown in Figure 2.4a), coordinated with porphyrins, that help the conductivity of bacterial nanowires (Wang et al., 2019). Another integral molecule in methanogenesis is the coenzyme F430 tetrapyrrole (as discussed above) that escalates the terminal reduction reaction of CO2 to CH4. As shown in Figure 2.4b, the coenzyme F430 contains a redox-active Ni atom coordinated by adjacent nitrogen atoms (Wongnate and Ragsdale, 2015). The upsurge in methane production in AD systems utilizing the Ni NPs may be due to the fact that Ni atom is one of the most important elements in the methane metabolism based on the findings obtained. Taking inspiration from nature, metalloporphyrin NPs could provide efficient support to adapt methanogenesis pathways to promote the growth of methanogens. Recent computational studies also provide evidence that molecular structures with a metal center coordinated with nitrogen atoms are remarkably robust under various conditions, provide excellent redox properties and can be easily adjusted by choosing the metal atom used (Y. Wu et al., 2019). For the reduction of CO2 to CH4, the use of metal phthalocyanine nanocomposites that resembles that of porphyrin could also be used due to its greater availability and lower cost at an industrial scale (Drain et al., 2006). The concept of metalloporphyrin NPs for the AD application creates curiosities and opens new doors in AD technology. 62 Figure 2.4. Structure of a) coenzyme-F430, and b) heme protein 2.7.5 Nanomaterials as toxicants to anaerobic digestion (AD) One of the main drawbacks of the AD process is its high sensitivity to toxic substances. Methanogens are one of the most sensitive microbial community members in the AD system (Venkiteshwaran et al., 2015). The varying degree of toxicity can come from metabolic activity (such as free ammonia, acids, and sulfides accumulation) or could be through external supplements such as nanomaterials (Chen et al., 2014). Therefore, the choice of nanomaterial for AD is crucial for efficient high methane recovery. The NPs of Ag, ZnO, TiO2, NZVI (nano zerovalent iron) (listed earlier in Tables 2.3-2.6) can damage microbial cells by causing oxidative stress and/or reactive oxygen species formation (Yang et al., 2013b). NZVI interferes with microbial metabolism and produces H2 gas quickly and uniquely alters the process stability. The release of metal ions (Ag and Zn) from the NPs also causes metal toxicity (Yang et al., 2013b). Ce, Copper (Cuo) and ZnO NPs are extremely toxic for 63 acetoclastic and hydrogenotrophic methanogenic activity, whereas CuO NPs inhibit acetoclastic methanogens but not the hydrogenotrophs (Gonzalez-Estrella et al., 2013). Solubilization of NPs has been advocated as one of the main causes of toxicity to microbial cells, whereas, methanogens are not affected by NPs of SiO2, Al2O3 and TiO2 even at higher concentrations (1500 mg/l) due to their lower solubility (Gonzalez-Estrella et al., 2013). 2.8 Effect of conductive materials addition on syntrophic microbial communities A deeper analysis of the complex microbial association (i.e., DIET) not only helps to understand the syntrophy among different classes of microorganisms, but also aids in creating novel strategies for more efficient organic waste conversion to bioenergy. The key syntrophic chemical reactions (2.8-2.12) in AD for different substrates are summarized below (Thauer et al., 1977). Ethanol oxidation: CH3CH2OH + H2O → CH3COOH + 2H2 (ΔGo′ = +10 KJ/mol) Reaction 2.8 Propionate oxidation: CH3CH2COOH + 2H2O → CH3COOH + CO2 + 3H2 (ΔGo′ = +72 KJ/mol) Reaction 2.9 Butyrate oxidation: CH3CH2CH2COOH + 2H2O → 2CH3COOH + 2H2 (ΔGo′= +48 KJ/mol) Reaction 2.10 Acetate oxidation: CH3COOH + 2H2O → 2CO2 + 4H2 (ΔGo′= +95 KJ/mol) Reaction 2.11 Homoacetogenesis: 2CO2+ 4H2 → CH3COOH + 2H2O (ΔGo′ = -95 KJ/mol) Reaction 2.12 64 As discussed in Section 2.3, it has been postulated by recent studies that addition of specific conductive materials to AD not only facilitates methanogenesis but also helps syntrophic microorganisms in their metabolism and growth. In one study, it was observed that the addition of magnetite could enhance the abundance of the Tepidoanaerobacter and Coprothermobacter genera in the system, which further enhanced acetate degradation in a mutual association with methanogenic archaea (Yamada et al., 2015). In another study, a coculture of Geobacter metallireducens and Methanosarcina barkeri could oxidize ethanol and produce methane in the presence of charcoal and could not function in the absence of charcoal. Similarly, the addition of carbon nanotubes led to the selective enrichment of Clostridia (from the Ruminococcaceae and Clostridiaceae families) in AD from lignocellulosic material, which represented 85% of the overall microbial consortium (Liu et al., 2012). Adding GAC/Fe° had no effect on species types, however, the change in abundance could be observed with the presence of GAC/Fe°. The density of Bacteroidetes, Proteobacteria, and Firmicutes decreased from 20.59%, 18.69% and 26.23% to 15.45%, 12.58% and 19.49%, respectively, while Chloroflexi, Thermotogae and Synergistetes clearly increased from 6.39%, 3.83%, and 3.19% to 15.42%, 7.28% and 3.65%, respectively. However, the Spirochetes were not affected by the addition of GAC/Fe° (Zhang et al., 2018). Considering the wide natural diversity of microorganisms, there are a variety of unique molecular mechanisms that serve to enhance syntrophy between various bacteria and archaea and have significant potential to shift microbial community contribution to improve the AD performance, electrons transfer, and methane yield. 65 2.9 Bioaugmentation: Sustainable enhancement to improve the AD performance In biochemical sludge treatment, various approaches and external chemical addition discussed above have been used to improve microbial degradation and remove pollutants. One of the major drawbacks of these methods is that they are often expensive to implement, especially on a large scale. Additionally, some of these approaches generate toxic by-products that can be harmful to the environment. Although, AD of organic pollutants by microorganisms inoculated from animal manure or effluent from AD utilizing municipal sludge is a sustainable approach, unfortunately, many pollutants, including very complex compounds, are not readily biodegraded by microorganisms and remain untreated, thus increasing treatment and disposal cost of AD effluent, known as digestate. To address this issue, bioaugmentation can be used, which involves adding vital biological catalysts or microorganisms to improve the enzymatic degradation of recalcitrant molecules. This approach has been successful in removing contaminants in soil and is gaining attention as a more sustainable solution for WWTPs (Herrero and Stuckey, 2015). In the context of an anaerobic digester, bioaugmentation can increase the methane yield by introducing more efficient microorganisms at converting the organic matter in municipal sludge into methane. There are several ways to carry out bioaugmentation of a mixed microbial culture in an anaerobic digester. One approach is to add a commercially available culture of methane-producing microorganisms to the anaerobic digester. This culture should be carefully selected to ensure that it is well-suited to the conditions present in the digester and that it can outcompete the native microorganisms for the substrate (Li et al., 2017) . 66 The modern design and process of bioreactors in WWTPs is essential to develop suitable environmental conditions so that the most desirable microorganisms can be selected and maintained under adequate physiological conditions. This extends to process engineering, heat and mass transfer limitations, and reactor performance to achieve large-scale processing goals. Until recently, bioreactors in wastewater treatment were considered "black boxes"; their operations and biocontrol rely only on empirical knowledge and, therefore, they are difficult to predict and maintain. Even today, their implementation can only be assessed by applying material balances. However, advanced bioreactor design can benefit from compartmentalization and the integration of interdisciplinary approaches, including novel biocompatible surfaces like conductive materials (biochar, carbon cloth, GAC) discussed earlier or hybrid reactors to retain microorganisms for key processes within a bioreactor (Herrero and Stuckey, 2015). The application of bioaugmentation to existing WWTPs is not well established. Therefore, to implement the technology on a larger scale, it is essential to conduct long-term research to assess the performance under different physicochemical and biochemical conditions. The main attribute before implementing bioaugmentation is to assess the overall health of the bioreactor. The physiochemical operating conditions coupled with molecular techniques such as high-throughput sequencing open up a broader vision to understand the ecological community of bioprocesses effectively (Lasken, 2012; Logares et al., 2012). Bioaugmentation with mixed culture also extends the prospect of investigating unculturable microorganisms and thus increasing the biodegradation of complex or recalcitrant organics in bioreactors (Herrero and Stuckey, 2015) 67 Additionally, successful bioaugmentation strategies can be implemented to achieve desired goals in the event that existing wastewater treatment facilities become insufficient to handle increasing volumes of waste. For example, in one study, due to the increase in petrochemical volumes and bioproducts in the existing activated sludge process, bioaugmentation was chosen to upgrade the existing facilities. It was found to be an effective option without increasing the size of the treatment facility (Ma et al., 2009). The frequency of bioaugmentation is a crucial factor in determining its effectiveness in enhancing the degradation of contaminants. A study by a group of researchers found that bioaugmentation of activated sludge by Comamonas testosteroni improved the degradation of 3-chloroaniline, but regular strain supplementation was necessary to maintain the treatment's effectiveness (Boon et al., 2000), The microbial community was analyzed using 16s rRNA and denaturing gradient gel electrophoresis (DGGE) before and after bioaugmentation. The study concluded that although bioaugmentation with microbial strains native to the ecosystem is effective, but not permanent. Therefore, regular strain supplementation will likely be necessary to ensure the continued efficacy of treatment. It is frequently reported that bioaugmentation can dramatically improve the performance of bioreactors. However, the frequency of bioaugmentation plays an important role in the overall effectiveness of enhanced biological activity (Boon et al., 2000; Patureau et al., 2001; Yu et al., 2010). 68 2.10 Summary from literature review • In summary, understanding the metabolic pathways and process microbiology of AD can help upgrade existing AD systems. This includes understanding electron transfer mechanisms and the concept of microbial syntrophy, as well as investigating the functional significance of various additives. • Most of the AD studies amended with conductive material have been conducted at the small-scale with batch-fed reactors, therefore, a significant amount of additional research is needed to assess the impact of conductive materials on continuously-fed digesters that simulate full-scale AD operation. • Among the nanoparticles used in literature, those containing iron, such as Fe3O4, Fe2O3, and NZVI, are the most promising in promoting growth and metabolism in organisms. However, care must be taken as other materials such as Cu and Zn can be highly toxic to the methanogenesis process. Pyrroles with transition metal at the center (Ni, Fe, and Co) are an integral part of methane metabolism pathways. The fusion of supramolecular chemistry and the use of various pyrrole nanoparticles could help induce DIET effectively. A deeper understanding of microbial biochemistry can open new opportunities for fine-tuning AD systems. • Regardless of the approach taken, monitoring biodigester performance after bioaugmentation is essential to ensure desired improvements in product yield or degradation efficacy. Tailor-made or enriched microbial consortia can be used for large-scale applicability of bioaugmentation. • The frequency of bioaugmentation and the microbial ecosystem of the bioreactor is critical for an effective bioaugmentation strategy. Interdisciplinary 69 approaches such as the supplementation of conductive nanomaterials and the development of biocompatible membranes can shift microbial diversity for improved bio-catalysis and refine non-culturable beneficial microorganisms within the system which can be used for more effective bioaugmentation of conventional bioreactors. Interspecies electron transfer (IET) can improve anaerobic metabolism and methane production by facilitating electron transfer between microbial species. A conductive surface is needed for IET, and carbon cloth being conductive also serves as a physical support for microbial attachment and biofilm growth (Zhao et al., 2018). The thesis focuses on the use of carbon cloth as a biocarrier to improve the performance of anaerobic digestion (AD). Carbon cloth has been found to be advantageous over polymer-based membranes in membrane bioreactors (MBRs) due to its availability, cost-effectiveness, and high surface area for microbial attachment, which enhances mass transfer and reduces fouling. In contrast, MBRs are more expensive and require more maintenance (Wu et al., 2019; Zhang et al., 2021). The selection of biocarrier and reactor design for AD systems will depend on various factors, such as the specific application, available resources, and desired outcomes. By assessing the benefits of using carbon cloth as a biocarrier and comparing it with other approaches, we can optimize AD technology and improve its environmental and economic sustainability. 70 Chapter 3. Two-step activated carbon cloth enhances microbial interactions and methane production during anaerobic digestion of municipal sludge The literature suggests that supplementing carbon cloth can enhance the overall AD of municipal sludge. This chapter investigated the impact of carbon cloth supplementation and carbon cloth dose optimization to improve syntrophic microbial association in AD utilizing municipal sludge. The chapter also provided an easy two-step activation process of carbon cloth (A-CC). The goal with the two-step pretreatment of carbon cloth was to significantly modify its surface characteristics leading to enhanced biocarrier potential compared to commercially available carbon cloth. Therefore, in this chapter, hypothesis I: “incorporating A-CC into AD utilizing municipal sludge will achieve superior performance compared to AD with commercial carbon cloth” was tested. 3.1 Overview Anaerobic digestion performance constraints include slow hydrolysis of complex organic matter, long solid retention times (SRT) increasing AD volume requirements, and accumulation of inhibitory substances including ammonia or VFA such as propionate, that can reduce biogas production (González et al., 2018). Given the importance of AD in waste treatment services, efforts to overcome these constraints are ongoing across multiple sectors with increasing attention focused on the role of microbial interactions and electron transfer efficiency in AD. Interspecies electron transfer (IET) between AD microorganisms is integral to efficient conversion of complex organic matter into methane-rich biogas through a process known as syntrophy (Cheng and Call, 2016). The use of different types of 71 conductive materials to immobilize AD microorganisms to improve IET is an active research area (Yang et al., 2004). Previous studies have confirmed that redox active functional groups and electrical conductivity of conductive materials could mediate electron transfer between syntrophic acetogenic/methanogenic communities in AD (Zhao et al., 2017b). Microbial attachment to conductive materials is strongly influenced by physical parameters including surface area and roughness, porosity and pore size (Yang et al., 2004). Conductive materials including biochar (Cimon et al., 2020; Khoei et al., 2021), graphite (Muratçobanoğlu et al., 2020), carbon cloth (Dang et al., 2016; Feng et al., 2021a), carbon felt and synthetic membranes (González et al., 2018) have been demonstrated to support biofilm growth and improve AD performance by enabling DIET (Adu-Gyamfi et al., 2012). Being available in sheet form, an advantage of carbon cloth is that it can be secured within the digester preventing washout loss, which may be an issue for granular conductive media, such as biochar or granular carbon (Park et al., 2018). Recently, various efforts have been made to functionalize carbon cloth matrices with polymeric binders to enhance electrical conductivity (Kordek et al., 2019; Yu et al., 2017). Matrix functionalization with various heteroatoms such as sulphur, phosphorus, and/or nitrogen leads to the formation of a charge and spin redistribution in the sp2 carbon lattice to redistribute electroneutrality and thus create active sites for enhanced microbial energy metabolism (Jiao et al., 2014; Kordek et al., 2019). Oxygen doping on carbon cloth matrices can be accomplished relatively easily by carbonizing the material in the presence of air or water under mild conditions. This 72 generates nano-porous and hydrophilic surface structures with oxygenated functional groups and significantly increases surface area (Kordek et al., 2019). Previous studies have shown that a two-step activation, using acid pre-treatment (H2SO4/HNO3) followed by calcination in air (525 ± 25℃), can improve the oxidation-reduction potential of carbon cloth electrodes for high-performance battery applications (Fu et al., 2019; Wang et al., 2018). The application of two-step activated carbon cloth specifically for AD applications is promising. But it also worth as biomass support media in AD remains unknown. The following sections evaluate the impacts of two-step activation of carbon cloth on methane production rate, microbial community structure and process stability in batch thermophilic digesters utilizing municipal sludge. 3.2 Material and methods 3.2.1 Materials Carbon cloth samples were purchased from FibreGlast Developments Corporation, USA. The type of carbon cloth was 6K (6,000) Carbon Multifilament Continuous Tow. First, the carbon cloth was cut into smaller pieces (2 cm × 5 cm, weight: 0.20 g). The carbon cloth strips were then used for further experimentation. All the analytical-grade chemicals used were purchased from Sigma-Aldrich Ltd. or Fisher Scientific. Deionized water was used in all experiments. 3.2.2 Synthesis of activated carbon cloth (A-CC) Untreated carbon cloth (U-CC) was activated in two steps: Step-1, acid pre-treatment in 2 M H2SO4 for 24 hours, followed by 20% HNO3 solution for 24 hours to 73 remove impurities, followed by rinsing several times with deionized water. In Step-2, the acid treated carbon cloth was dried in an oven at 80℃ overnight followed by calcination in air at 525 ± 25℃ for 3 hours in a muffle furnace. Figure 3.1a shows commercial untreated carbon cloth (U-CC) and Figure 3.1b shows the resulting A-CC after two-step activation process (images were clicked using mobile phone camera). 3.2.3 Substrate and inoculum The inoculum used for the biochemical methane potential (BMP) assays was prepared using an automated 5 L anaerobic digester. The digester was operated at a sludge retention time (SRT) of 20 days, a temperature of 55℃ and stirred at 150 revolutions per minute (rpm). The substrate sources were drawn from clarifier sludge streams at Lulu Island Municipal WWTP in Vancouver, Canada. The sources were thickened screened primary sludge (TSPS) and thickened waste secondary sludge (TWSS), which are combined to form the mixed sludge fed to the digester. The TSPS and TWSS samples were shipped overnight in a cooler to the BTG laboratory in Figure 3.1. a. Untreated carbon cloth represented as U-CC, and b. activated carbon cloth represented as A-CC b. 74 Kelowna, BC, every two weeks and stored at 4°C until used. Upon the arrival of each batch of sludge to the lab, the characteristics of the sludge were routinely assessed and compared to the previous batch. It was observed that the characteristics of the incoming shipped sludge did not show significant variation. Anaerobic digestion results were normalized for organic content of sludge streams. The 5 L anaerobic digester was fed with 250 ml of mixed sludge (65 ± 5% TSPS and 35 ± 5% TWSS by volume) in a semi-continuous flow mode (fed once a day, 7 days a week) daily for 5 months before collecting the inoculum for the BMP experiment. For all the BMP assays which were set-up as batch experiments, TSPS was used as the substrate due to the higher soluble (readily biodegradable) organics available compared to TWSS and mixed sludge streams. The characteristics of TSPS (substrate) and thermophilic anaerobic inoculum used for the BMP assays are shown in Table 3.1. Table 3.1. Characterization of substrate and thermophilic inoculum used for BMP assays Parameters Substrate (TSPS) Thermophilic inoculum pH 6.02 (0.30)* 7.91 (0.10) % TS (w/w) 3.52 (0.88) 1.73 (0.65) %VS (w/w) 3.24 (0.40) 1.32 (0.32) Total alkalinity (mg as CaCO3/L) 415 (1) 4384 (1) Total COD (g/l) 53 (2) 12 (4) Total ammonium nitrogen (mg/l) 212 (0) 1531 (0) VFA (mg/l) 1206 (35) 47 (0) TSPS: Thickened screened primary sludge, TS: Total solids, VS: Volatile solids, COD: Chemical oxygen demand, VFA: Volatile fatty acids as summation of acetic, propionic, and butyric acids, *(standard deviation of triplicates). 75 3.2.4 Characterization of carbon cloth The structural changes of carbon cloth were investigated using various analytical techniques. Fourier-transform infrared spectroscopy (FTIR) was conducted on the Nicolet iS20 instrument, Brunauer-Emmett-Teller (BET) surface area analysis was performed using equipment from Micromeritics, and X-ray diffraction (XRD) was carried out with the Bruker D8-Advance X-ray diffractometer for both U-CC and A-CC samples. The carbon cloth samples were sent to different laboratories for analysis: the Nanomaterials and Polymer Nanocomposites Laboratory (NPNL) at UBC Okanagan for FTIR analysis, the Department of Chemistry at UBC Vancouver for XRD analysis, and the Catalysis and Chemical Reaction Engineering Laboratories at the University of Saskatchewan, Canada for BET and Barrett-Joyner-Halenda (BJH) analysis. All samples were prepared similarly: the U-CC and A-CC samples were dried at 80°C for 24 hours and packed in Ziploc bags for analysis. The XRD analysis was used to measure the crystallinity index, which was determined using Equation 3.1 (Park et al., 2010). 𝐶𝑟𝑦𝑠𝑡𝑎𝑙𝑙𝑖𝑛𝑖𝑡𝑦 = 𝐴𝑟𝑒𝑎 𝑜𝑓 𝑐𝑟𝑦𝑠𝑡𝑎𝑙𝑙𝑖𝑛𝑒 𝑝𝑒𝑎𝑘𝐴𝑟𝑒𝑎 𝑜𝑓 𝑎𝑙𝑙 𝑝𝑒𝑎𝑘𝑠 (𝑐𝑟𝑦𝑠𝑡𝑎𝑙𝑙𝑖𝑛𝑒 + 𝑎𝑚𝑜𝑟𝑝ℎ𝑜𝑢𝑠)× 100 𝐸𝑞𝑢𝑎𝑡𝑖𝑜𝑛 3.1 3.2.5 Biochemical methane potential (BMP) assays setup Batch BMP assays were adopted from previous studies (Angelidaki et al., 2009; Cimon et al., 2020). Briefly, BMP assays were performed using 160 ml serum bottles as digesters (see Figure 3.2). Before BMP assay set-up, the thermophilic inoculum 76 was starved for 6 days in an automated shaker at a temperature of 55°C and 90 rpm to eliminate residual VFA and to minimize biogas production from inoculum itself. The food-to-microorganism ratio was fixed to 1.0 g volatile solids (VS)substrate/g VSinoculum, which was determined by preliminary experiments to avoid starvation or overloading (VFA accumulation) of cultures. The final liquid volume was adjusted to 70 ml using deionized water for all digesters. A buffer mixture (20 mmol/l of Na2CO3 and KHCO3) was added to each reactor to keep the BMP bottles in the neutral range (6.5-7.2). Figure 3.2. Biochemical methane potential (BMP) bottles used in the study Experiments were designed in three separate batches (Batches 1-3) comprising of 173 BMP bottles in total including triplicates of each unique digester operating condition. Batch-1 (comprised of 27 preliminary assays) was set up to evaluate the individual carbon cloth activation steps: partial activation using H2SO4 (represented as CC[H2SO4]), partial activation using H2SO4 with HNO3 (represented as CC [H2SO4, HNO3]), and direct air calcination without acid pretreatment (represented as U-CC [550°C]) and two-step activation: acid pretreatment followed by air calcination (represented as A-CC) on rate and extent of methane improvement at a single dose of 0.60 g carbon cloth (1.11 g carbon cloth/g-VSsubstrate). For brevity, the results of 77 Batch-1 are included in Appendix 1 (Section A1, Figures A1 and A2). Based on the preliminary results obtained from Batch-1 experiments, Batch-2 experiments (comprised of 48 assays) were conducted to vary/optimize carbon cloth dosage. BMP experiments with U-CC and A-CC were set up in parallel at dosages of 0.20 g, 0.40 g, 0.60 g, 0.80 g, 1.00 g, and 1.20 g respectively. These dosages correspond to 0.37, 0.74, 1.11, 1.48, 1.85 and 2.22 g U-CC or A-CC/g-VSsubstrate, respectively. BMP results from Batch-2 are presented in the results Section 3.3 of this chapter. Batch-3 experiments (comprised of 98 assays) were conducted using the same operating conditions from Batch-2 in order to sample and evaluate microbial community structure with special emphasis on syntrophic bacteria and methanogens. Analysis of the microbial community structure provided insight into the overall process and was utilized to publish the research results as a journal article (Kumar et al., 2022) in collaboration with the Hallam laboratory at the University of British Columbia in Vancouver, British Columbia, Canada. The genomic analysis was not included in the main part of this thesis as sample analysis, including DNA/RNA extraction, and bioinformatics were conducted by the members of Hallam laboratory, but part of the genomic analysis is shown in Appendix 1 (Note A1, Figure A5) to facilitate discussion as complimentary information. All BMP experiments were performed including the Controls (no carbon cloth) and three sets of Blanks: Blank-1 (with inoculum only, no substrate); Blank-2 (inoculum with 1.00 g U-CC, no substrate) Blank-3 (inoculum with 1.00 g A-CC, no substrate). The objective of Blank-2 and Blank-3 were to distinguish the contribution of carbon cloth as a source of organic carbon or as potentially inhibitory factor for methane production. During initial set-up, each bottle’s liquid content was purged by 78 bubbling N2 gas for 5 minutes to remove the oxygen and immediately sealed with butyl rubber and an aluminium cap. All the bottles were incubated at 55°C and rotated at 90 rpm while resting horizontally to improve mixing and monitored for biogas production (40-60 days) until they stopped developing pressure measured using a hand-held digital manometer. Various physicochemical analysis such as biogas volume at standard temperature and pressure (0°C, 1 atm), biogas composition, pH, VFA were monitored during BMP experiments. Details of the analytical method are discussed in section 3.2.6. and the calibration curves can be found in Appendix 1 (Section A3). 3.2.6 Analytical methods The parameters analyzed for all the BMP experimentation used in the current study are summarized below: i. Biogas volume and composition in reactor headspace Biogas pressures were measured using handheld digital manometers (LEO 2, Keller, Winterthur, Switzerland) at room temperature to calculate the volume of biogas and methane produced from each reactor. Methane volumes were converted and reported at standard temperature and pressure (STP: 0oC, 1 atm). The manufacturer calibrated the manometer, which had a 14" NPT adaptor, a swivel fitting with an O-ring seal, and a 7/16" UNF male thread, allowing for 360-degree rotation of LEO 2. The stoppers were punctured by a needle connected to the manometer, with pressure measured and displayed twice per second. The volume of biogas produced was normalized to the STP condition after measuring its composition. Equations 3.2 and 79 3.3 were utilized to calculate the cumulative methane volume generated from the gas pressure readings obtained via the manometer. ΔV(j) = ΔN(j)RTο𝑃𝜊 𝐸𝑞𝑢𝑎𝑡𝑖𝑜𝑛 3.2 ΔV(j) = [y(j)P(j)Vℎ𝑅𝑇] − [y(j − 1)𝑃𝑎𝑡𝑚(j − 1)Vℎ𝑅𝑇] 𝐸𝑞𝑢𝑎𝑡𝑖𝑜𝑛 3.3 Where, P(j) represents the initial pressure of the BMP bottle at the current time of measurement (Pa); 𝑃𝑎𝑡𝑚(𝑗 − 1) represents the atmospheric pressure at the time of the previous measurement (Pa); 𝑃𝜊 is standard pressure (101326 Pa); ΔN(j) is number of moles of methane gas in the headspace since the previous measurement (mol); y(j): methane concentration in the bottle for the current measurement (%); y(j-1) is methane concentration in the bottle at the previous measurement (%); R is Gas constant (8.314 J °K-1 mol-1); T: Temperature (°K); Tο is standard temperature (273.15 °K); Vh: Headspace volume (m3); ΔV(j): methane volume at standard temperature and pressure produced (m3). The composition of methane, oxygen, nitrogen, and carbon dioxide in the BMP bottle headspace was analyzed using an Agilent 7820A Gas Chromatograph (GC) equipped with a thermal conductivity detector (with an oven temperature of 70°C, inlet temperature of 100°C, and outlet temperature of 150°C) and using Agilent G3591-80002 and an Agilent G3591-8000 packed columns with a 2 mm internal diameter. The first column was packed with Haye Sup Q and the second with Mol Sieve 13x packing materials. The GC employed helium from Linde Gas as the carrier gas at a flow rate of 25 ml/min. The biogas sample was collected by puncturing the stopper from the headspace of the BMP bottles with using an Agilent 1 ml gas-tight syringe, a volume of 0.6 ml was collected. The collected gas was then manually injected into 80 the GC inlet septum. After the analysis, the punctured section of the BMP bottles septum were sealed with silicone gel. ii. pH The BMP bottles were inverted, and 1 ml (out of which 500 µl sample were used for VFA measurement, discussed below) of liquid sample was collected from each BMP bottle using a syringe, ensuring that no air entered the bottles, for pH measurement after measuring the biogas pressure. The pH of BMP reactor content at different digestion time was measured using the standard methods 4500-Hp B (“Standard methods for the examination of water and wastewater: 20th ed,” 2000). A pH electrode was attached to an Accumet™ Excel XL25 pH/mV/Temperature/ISE meter (Thermo Fisher Scientific, Inc., Ottawa) to measure the pH ranging from 1-14. iii. Solids The total solids (TS) and volatile solids (VS) of both the inoculum and substrate was determined according to APHA 2540 B and 2540 E methods (“Standard methods for the examination of water and wastewater,” 2012). Crucibles were first conditioned by immersing them in diluted sulfuric acid (20%) for 2 hours and then cleaned, heated to 550°C to eliminate contaminants, and placed in a desiccator for weight stabilization. Empty crucibles were weighed using a Mettler-Toledo Excellence XA-105 analytical balance and mixed sludge samples (10 ml) were added and weighed. Samples were then dried overnight at 98 ± 2°C, raised to 103–105°C for three hours, cooled to room temperature and weighed. The VS were burned for 30 minutes at 550°C in a furnace, cooled and weighed again. The TS and VS were calculated according to the Equation 3.4 and 3. 5. 81 𝑇𝑜𝑡𝑎𝑙 𝑠𝑜𝑙𝑖𝑑𝑠 (%, 𝑔/𝑔) = 𝑆𝑎𝑚𝑝𝑙𝑒 + 𝑐𝑟𝑢𝑐𝑖𝑏𝑙𝑒 (𝑔) − 𝑑𝑟𝑖𝑒𝑑 𝑠𝑎𝑚𝑝𝑙𝑒 𝑖𝑛 105°C (g)𝑎𝑚𝑝𝑙𝑒 + 𝑐𝑟𝑢𝑐𝑖𝑏𝑙𝑒 (𝑔)× 100 𝐸𝑞𝑢𝑎𝑡𝑖𝑜𝑛 3.4 𝑉𝑜𝑙𝑎𝑡𝑖𝑙𝑒 𝑠𝑜𝑙𝑖𝑑𝑠 (%, 𝑔/𝑔) = 𝑆𝑎𝑚𝑝𝑙𝑒 + 𝑐𝑟𝑢𝑐𝑖𝑏𝑙𝑒 (𝑔) − 𝑏𝑢𝑟𝑛𝑒𝑑 𝑠𝑎𝑚𝑝𝑙𝑒 𝑎𝑡 550°C (g)𝑠𝑎𝑚𝑝𝑙𝑒 + 𝑐𝑟𝑢𝑐𝑖𝑏𝑙𝑒 (𝑔)× 100 𝐸𝑞𝑢𝑎𝑡𝑖𝑜𝑛 3.5 iv. Total chemical oxygen demand (COD) The closed reflux colorimetric method based on Standard Method (“Standard methods for the examination of water and wastewater,” 2012) is commonly employed to rapidly determine the organic content of wastewater sludge as COD. In this method, dichromate ions are used to oxidize the organics, reducing them from Cr6+ to Cr3+. Chromic ions (Cr3+) absorb light in the 600 nm range. For samples with COD above the method's upper limit, dilution ratios were selected to maintain COD values within the calibration range of 100-700 mg-COD/L. Appendix 1 (Section A3) displays the calibration curve for COD. The diluted substrate and inoculum samples were homogenized for 5 minutes at 10,000 rpm in a KinematicaTM PolytronTM PT 10/35 GT homogenizer. Then, 3 ml of digestion solution (aqueous solution of sulfuric acid + mercuric sulfate + potassium dichromate) and 1.5 ml of catalyst solution (mixture of concentrated sulfuric acid + silver sulfate) were added to 2.5 ml of homogenized sample in COD glass vials. Each sample was tested in triplicate. Samples were heated for 3 hours at 150°C in a Thermotron S-1.5C Benchtop Environmental Chamber (Thermotron Industries, Holland, Michigan) before being measured for absorption using a spectrophotometer at 600 nm. Using a calibration curve created by digesting known amounts of potassium hydrogen phthalate solution (Sigma BioXtra > 99.95% pure), COD values were calculated. 82 v. Volatile fatty acids (VFA) A portion of the sample (500 µl) collected for pH measurement was utilized to measure the VFA of the content in the BMP bottle. To analyze VFA (a combination of propionic, acetic, and butyric acids), the samples (substrate, inoculum or BMP bottle content) were first centrifuged (10,000 rpm for 30 min) and the supernatant (aqueous) phase was filtered through 0.22 μm membrane filters. Approximately 0.5 ml of the filtered sample was pipetted into a 1.5 ml glass vial and stored at -20°C for later batch analysis. Before analysis, the VFA samples were thawed, and 0.5 ml of an internal standard, which contained 2% iso-butyric acid, formic and sulfuric acids was added (Ackman, 1972). An Agilent 7890A GC with a 25-m Agilent HP-FFAP 25 m x 0.32mm id, 0.5 um film capillary column and a flame ionization detector was used to analyze the VFA. The flame ionization detector consisted of oxidizer, fuel, and make-up gas flows of 400 (air), 40 (hydrogen), and 25 ml/minute (nitrogen), respectively. The GC had an autosampler for injecting 1.0 μl sample into the inlet in a 10:1 split mode. The inlet was set to a constant temperature of 220°C. The GC carrier gas (Helium) flowed at a constant rate of 25.2 mL/minute, along with a 3 ml/minute inlet purge (Ackman, 1972). The GC column flow rate was 2.52 mL/minute, and the oven temperature was programmed to increase from 70°C to 200°C, over 6.5 minutes, with an initial hold time of 0.2 minutes. To verify GC performance before analyzing the samples, the primary standard containing known concentrations of propionic, butyric, and acetic acids was run. vi. Alkalinity To determine the alkalinity of the substrate or inoculum samples, the supernatant of samples obtained after centrifugation (10,000 rpm for 30 min) were 83 subjected to the titration method outlined in standard method 2320B (“Standard methods for the examination of water and wastewater,” 2012). In this method, approximately 10 mL of the supernatant sample was titrated with 0.1 M sulfuric acid to an endpoint of pH 4.6. The concentration of alkalinity (mg CaCO3/l) was calculated by determining the amount of acid required for the titration. The alkalinity (mg CaCO3/l) was determined using Equation 3.6. 𝐴𝑙𝑘𝑎𝑙𝑖𝑛𝑖𝑡𝑦 (𝑚𝑔𝐶𝑎𝐶𝑂3𝑙) = 𝑠𝑢𝑙𝑓𝑢𝑟𝑖𝑐 𝑎𝑐𝑖𝑑 𝑎𝑑𝑑𝑒𝑑 (𝑚𝑙) × 𝑛𝑜𝑟𝑚𝑎𝑙𝑖𝑡𝑦 (𝑚𝑜𝑙𝑙 ) × 50,000𝑣𝑜𝑙𝑢𝑚𝑒 𝑜𝑓 𝑠𝑎𝑚𝑝𝑙𝑒 (𝑚𝑙) 𝐸𝑞𝑢𝑎𝑡𝑖𝑜𝑛 3.6 vii. Total ammonium nitrogen To determine the concentration of total ammonium nitrogen (mg NH4-N/L), the 4500-NH3F phenate colorimetric method (“Standard methods for the examination of water and wastewater,” 2012) was employed. Similar to the determination of COD, the supernatant obtained from centrifugation of samples was used. One thousand ppm ammonium stock solution (ammonium chloride) in type 1 water (18.2 MΩ·cm resistivity, ultra-pure reagent water) was diluted to prepare seven calibration standards in the range 0 (water), 0.25, 0.5, 1.0, 2.5, 5 and 7.5 ppm ammonium chloride. These standards were processed in the same manner as the samples and a standard calibration curve (Appendix 1, Section A3) was created. For the colorimetric determination, 0.61 mL of sample was mixed with 2.0 mL of complexing agent and 0.86 mL of phenol solution. Subsequently, 0.01 mL of sodium hypochlorite stock solution was added, mixed, and then stored in the dark for one hour. The complexing agent contained 3.3 g potassium sodium tartrate and 2.4 g sodium citrate-dihydrate in 100 mL of water, while the phenol solution comprised of 84 8.5 g of sodium hydroxide and 2.64 g of phenol in 250 mL of water. During the one-hour storage period, indophenol, a blue compound, was formed. The concentration of total ammonium nitrogen in the samples was determined by measuring the intensity of the blue color using a spectrophotometer at a 660 nm wavelength. 3.2.7 Kinetic modeling Kinetic modeling allows for the numerical estimation of empirical coefficients for AD process simulation. The specific cumulative methane production values from the Batch-2 BMP assays were fitted using the Modified Gompertz model (Equation 3.7) to study the rate and extent of carbon cloth activation on overall AD. In Equation 3.7, Y represents the specific cumulative methane production (ml/g-VSsubstrate) at time t (in days, d), P represents ultimate specific cumulative methane production (ml/g-VSsubstrate), Rm is the maximum methane production rate (ml/g-VSsubstrate/d), e is the natural logarithm constant and λ represents the lag phase time (in days). The model parameters were evaluated using MS Excel. 𝑌 = 𝑃 × 𝑒𝑥𝑝 [−𝑒𝑥𝑝 {𝑅𝑚 × 𝑒𝑃(𝜆 − 𝑡) + 1}] 𝐸𝑞𝑢𝑎𝑡𝑖𝑜𝑛 3.7 3.3 Results and discussion 3.3.1 Characterization of activated carbon cloth (A-CC) and untreated carbon cloth (U-CC) FTIR analysis was performed to investigate the effect of two-step activation on functional group modification associated with carbon cloth before BMP assays. Figure 3.3 illustrates the FTIR spectrum of U-CC and A-CC. The IR spectrum of A-85 CC corresponding to 3500-4000 cm-1 represents the O-H stretch in the hydroxyl group (Nandiyanto et al., 2019; Zu et al., 2013). The peak at 2918 cm-1 represents the C-H bond in the asymmetric/symmetrical binding stretch of methylene. In addition, the peak corresponding to 2365.25 cm-1 is related to the C≡C stretch. The peak at 1560 cm-1 relates to nitro aliphatic compounds that correspond to the N-H bond (Nandiyanto et al., 2019). The bend stretch of the N-H compound can be from HNO3 used in the two-step activation of carbon cloth. In addition, the flexural stretch between 1120 and 1250 cm-1 corresponds to the C-O stretch. Improved bond stretching corresponds to electron mediator or shuttling capacity for DIET (Wang et al., 2021). It is evident from the FTIR analysis that the two-step activation of carbon cloth improved the hydrophilicity by introducing functional groups (Kordek et al., 2019), which can further improve the biocarrier potential and efficiency of A-CC for increased production of methane (discussed in Section 3.2) and thus may facilitate DIET. A similar behavior was reported for biochar at a pyrolytic temperature between 300-500℃, which causes stretching of the redox-active organic functional group. The altered structural characteristics of biochar resulted in higher rate and extent of AD (Wang et al., 2021). In another study, similar results were obtained with two-step carbon cloth activation enhancing hydrophilicity due to carbon cloth oxidation used to design high performance self-supporting metal-free electrodes for high-performance 86 battery applications (Kordek et al., 2019). XRD analysis was performed to investigate the degree of crystallinity for U-CC and A-CC surfaces. The XRD results, shown in Figure 3.4 indicate that the crystallinity of U-CC, calculated using Equation 3.1, was 65.59%. In contrast, the crystallinity of A-CC was 68.68%, an increase of 3.09%. The XRD pattern for both U-Figure 3.3. X-ray diffraction (XRD) analyses of untreated carbon cloth (U-CC) and activated carbon cloth (A-CC) Figure 3.4 Fourier-transform infrared spectroscopy (FTIR) analysis of untreated carbon cloth (U-CC) and activated carbon cloth (A-CC) 87 CC and A-CC shows a typical graphite peak (Wei et al., 2015). The minor increment in the crystallinity suggests that some structural changes occurred in A-CC over U-CC which appeared to enhance methane production. The BET and BJH surface area analysis of U-CC and A-CC indicated that the surface area of A-CC was greatly increased after activation. The external laboratory analyzing the samples attempted to analyze BET of U-CC twice. Unfortunately, the methodology presented challenges for the U-CC sample but was successful for the A-CC sample. The BET surface area of A-CC was 386.15 ± 6.88 m2/g (BJH: 195.60 m2/g) compared to the U-CC (BJH: 0.45 m2/g). The total single-point adsorption pore volume of the pores in A-CC samples was 0.151 cm3/g compared to that of U-CC with 0.001 cm3/g. The BET surface area is an important parameter to evaluate the adsorption capacity of carbon cloth (Zhang et al., 2019). In another study, similar results were obtained for two-step carbon cloth activation and the BET surface was doubled from the initial value (Kordek et al., 2019). The average pore size with a two-step activation was reduced for A-CC with 3.08 nm compared to the U-CC pores with 16.13 nm. This is due to the effect of HNO3, which reduces the average pore size of carbon cloth samples and thus improves the surface/volume ratio (Thamilselvan et al., 2015). Given these results, two-step activation improves the carbon cloth surface area available for microbial attachment. 3.4 Effect of carbon cloth dose on methane increment The results from Batch-1 indicate that each activation step improved the performance of partially activated carbon cloth in AD differently. The specific cumulative methane improvements, over the Control BMP, at Day 8 for assays 88 amended with CC [H2SO4], CC [H2SO4; HNO3], U-CC@550°C and A-CC were 1.23, 1.76, 2.46 and 2.22-fold, respectively. The acid pretreatment induces the oxidation of U-CC with oxygen-containing function groups (Kordek et al., 2019), which moderately improved the rate of methane generation. Furthermore, U-CC BMP experiments showed inhibition due to the accumulation of propionic acid while two-step activation had an additional advantage in terms of the degradation of propionic acid to acetic acid earlier during digestion (see Appendix 1; section A1, Figure A1). The results from Batch-2 indicate that the methane production rate highly depends on the dose of the carbon cloth used. Figures 3.5a and b present the cumulative methane production from assays with U-CC and A-CC, respectively. In U-CC amended BMP bottles (Figure 3.5a), inhibition of methane generation was observed at lower doses (< 0.80 g carbon cloth). For example, the cumulative methane yields from BMP bottles amended with 0.20 g, 0.40 g, and 0.60 g U-CC were 0.22, 0.29, and 0.36 times that of the Control (no carbon cloth) on Day 6. However, for the BMPs with 0.80 g, 1.00 g, and 1.20 g U-CC, it was clear that cumulative methane yields had increased significantly, corresponding to 1.7-, 2.3-, and 2.4-times higher methane yields, respectively, over 8 days, compared to the Controls. The results suggest that within the range tested (1.47-2.21 g U-CC/g-VSsubstrate), higher doses of U-CC improved methane production rates. The results also indicate that methane rate inhibition at the lower dosage of U-CC is due to accumulation of propionic acid produced during a shift in microbial community structure (Kumar et al., 2022). This shift is discussed in more detail in Appendix 1, sections A1 and A2. 89 Although the U-CC dose above 0.80 g (1.48 g CC/g-VSsubstrate) did not result in inhibition of the methane production rate, higher U-CC dosages resulted in reduced methane production due to mass transfer effects (Lin et al., 2016). 90 Figure 3.5. Effect of carbon cloth dosing on (a, b) specific cumulative and (c, d) specific daily methane production at standard temperature and pressure (STP) (0ºC, 1 atm) from municipal sludge. U-CC: untreated carbon cloth, A-CC: activated carbon. Data represent average and error bars represent standard deviations of triplicates. 91 The culture incubated with two-step carbon cloth activation outperformed those incubated with U-CC with respect to methane yield even at the low dosages (Figure 3.5b). The BMP bottles amended with the lowest dose of 0.20 g A-CC (0.37 g A-CC/g-VSsubstrate) yielded 2.2 times the specific cumulative methane yield within Day 3 compared to the Control reactor (no carbon cloth). However, in the case of 0.20 g U-CC (0.37 g U-CC/g-VSsubstrate) amended BMPs, the methane production was inhibited and produced 0.44-fold (56%) lower cumulative methane yield than the Control (Figure 3.5a). Likewise, BMP bottles with A-CC dosages of 0.40 g (0.74 g A-CC/g-VSsubstrate), 0.60 g (1.12 g A-CC/g-VSsubstrate), 0.80 g (1.48 g A-CC/g-VSsubstrate), 1.00 g (1.85 g A-CC/g-VSsubstrate), and 1.20 g (2.2 g A-CC/g-VSsubstrate) achieved 3.6, 4.0, 3.7, 3.9 and 4.4 times higher specific cumulative methane yield compared to the Control, respectively, in the first 3 days (Figure 3.5b). The results suggest that two-step carbon cloth activation reduces the dose of carbon cloth required in BMPs to obtain higher methane yields. The optimal dose to achieve a similar effect in terms of methane rate increment by a maximum of 2.8 times over the Control is at least 1.20 g U-CC (2.2 g A-CC/g-VSsubstrate) compared to only 0.40 g A-CC (0.74 g A-CC/g-VSsubstrate) for 3.6-fold increment over the Control. Similar results were obtained when a failing AD utilizing wastewater with high VFA from dark fermentation in continuous-flow mode was supplemented with 667 cm2 U-CC/L (relative to the present study, equivalent to ~1.73 g of CC/g-VSsubstrate), where a 200-260% increase in methane production was obtained (Feng et al., 2021b). In another study, a 10.1-23% increase in methane production rate was observed when 33.33 cm2 U-CC/L was added to an anaerobic reactor treating wastewater (Feng et al., 92 2021a). Daily methane production rates for U-CC and A-CC are indicated in Figures 3.5c and d, respectively. With an increase in the dose of U-CC, there is a shift in the peak height and the time of emergence observed. For 0.20 g of U-CC, the methane peak is on Day 22 compared to the Control peak, which is on Day 14, which confirms the inhibition at low U-CC dosages. However, for doses of 0.80 g, 1.00 g, and 1.20 g of U-CC, the maximum peak occurs on Day 8, consistent with increased activity at higher dosages (Figure 3.5c). Interestingly, peak heights in assays with > 0.8 g U-CC were lower than the Controls. This is likely due to decreased mixing with concomitant mass transfer limitation at higher U-C doses. Peak heights for <0.80 g A-CC were above the Control and appeared earlier than U-CC bottles (Figure 3.5d). This bodes well for capital cost savings when scaling up, as a much lower dose of A-CC is needed to achieve process improvement compared to U-CC. Again, the reduced peak height for >0.8 g A-CC is likely caused by mass transfer limitation. Taken together, these results indicate that the optimal dose of A-CC is 0.80 g (1.48 g A-CC/g-VSsubstrate) for maximum methane production rate. 3.5 Effect on carbon cloth on volatile fatty acid accumulation and conversion The accumulation and conversion of VFA over time can be used to assess the activity of fermentative microorganisms in batch AD. The production of VFA including acetic, propionic, and butyric acid levels with digestion time are indicated in Figures 3.6 (a, b) and 3.6 (c, d) and 3.6 (e, f) for U-CC and A-CC added BMP bottles, respectively. As shown in Figures 3.6 (a, b), at the lower dose of U-CC (0.20 g, 0.40 g, and 0.60 g), VFA accumulation (dominated by acetic acid) occurs on Day 10, yet for 0.80 g U-CC, the peak shifts to Day 8. 93 Figure 3.6. Effect of untreated carbon cloth (U-CC) and activated carbon cloth (A-CC) addition on (a, b) acetic acid, (c, d) propionic acid, and (e, f) butyric acid accumulation in BMP bottles, respectively. Data represent average and error bars represent standard 94 However, for assays with 1.00 g and 1.20 g U-CC, maximum VFA accumulation was observed on Day 3 consistent with increased microbial activity. Accumulation of propionic acid, even at low concentration, is associated with the inhibition of methane production (Dang et al., 2016). In AD, conversion of propionic acid requires syntrophic activity of propionate-oxidizing bacteria and hydrogenotrophic methanogenic archaea (Worm et al., 2011). In BMP bottles amended with 0.20 g, 0.40 g, and 0.60 g of U-CC, propionic acid accumulation prevailed after Day 18 (Figure 3.6c) . In BMP bottles, the time-dependent pH and VFA data followed an opposite pattern. Higher VFA led to lower pH values; however due to sufficient addition of buffer in the beginning of the assays, digester pH values fluctuated in a safe, near neutral range (between 8.6 – 7.6 in U-CC and A-CC amended assays) for microbial cultures. In A-CC amended BMP bottles, the VFA peaks of 0.20 g and 0.40 g carbon cloth appeared on Day 6, while for 0.60 g, 0.80 g, 1.00 g, and 1.20 g amended BMPs, the peaks shifted to Day 3, respectively (Figures 3.6b, d, and f). In a batch AD system, the maximum accumulation of VFA corresponds to a higher solubility, however, simultaneous utilization of VFA is also important to prevent digesters from failure (Feng et al., 2021b). In A-CC amended BMPs, higher VFA led to lower pH values (for example VFA>2000mg/l lowers the pH between 6.9-7.3) but with a quick recovery (within day 5), supports enhanced microbial activity within the A-CC bottles. In addition, as expected, the time of occurrence of peak 95 VFA curves (Figures 3.6a-f) and the peak daily methane production curves (see Figures 3.5 c, d) were similar. This also explains that at a high dosage of carbon cloth, the maximum peak height maybe hampered due to mixing and mass transfer limitations. These results suggest that the optimal dose of A-CC addition not only improved methane production rates but also provided a more stable association between methanogenic archaea and syntrophic partners. 3.6 Kinetic modeling study The Modified Gompertz model was applied to determine the various kinetic parameters (P, Rm, k, and λ) based on the best-fit to the cumulative methane yield data. The goodness of fit for the model was also measured with the regression coefficient (R2) >0.94. As shown in Table 3.2, it is clear that carbon cloth addition has a significant impact on the rate of methane production (Rm) increment and lag phase (λ) reduction (p<0.05) for all the carbon cloth dosages. The lower dose of U-CC leads to inhibition of AD and therefore a lag phase increment was observed for 0.20 g, 0.40 g, and 0.60 g U-CC as compared to the Control (without carbon cloth). In addition, the rate of methane production (Rm) also decreased from 25.46 ± 0.33 ml/g-VSsubstrate/d for the Control to 15.40 ± 1.51, 15.70 ± 2.60, and 17.25 ± 3.15 ml/g-VSsubstrate/d respectively, when U-CC at a dose of 0.20 g, 0.40 g, and 0.60 g was added to the reactors. However, at higher doses of 0.80 g, 1.00 g and 1.20 g U-CC, the Rm value increased to 32.99 ± 0.87, 40.71 ± 1.91 and 42.49 ± 6.11 ml/g-VSsubstrate/d, respectively, while the λ decreased to 2.03 ± 0.44, 2.11 ± 0.10 96 and 2.07 ± 0.06 days for 0.80 g, 1.0 g, and 1.20 g, respectively, compared to the Control (4.85 ± 0.05 days). Table 3.2. The modified Gompertz model’s parameters for biochemical methane potential (BMP) assays with untreated carbon cloth (U-CC) and activated carbon cloth (A-CC)ǂ BMP amendment conditions Ultimate specific methane production (P) (ml/g-VSsubstrate) Rate of methane production (Rm) (ml/g-VSsubstrate/d) λ = Lag phase (day) R2 Measured Simulated Control (no CC) 477.40 ± 5.55* 482.08 ± 3.53 25.46 ± 0.33 4.85 ± 0.05 0.98 0.2 g U-CC± 457.40 ± 22.29 534.90 ± 27.15 15.40 ± 1.51 9.10 ± 0.97 0.93 0.4 g U-CC 406.25 ± 22.16 494.29 ± 31.45 15.70 ± 2.60 8.09 ± 1.69 0.93 0.6 g U-CC 455.65 ± 41.28 503.87 ± 46.45 17.25 ± 3.15 7.34 ± 1.12 0.94 0.8 g U-CC 488.69 ± 37.91 473.65 ± 36.22 32.99 ± 0.87 2.03 ± 0.44 0.99 1.0 g U-CC 485.81 ± 5.33 449.57 ± 6.97 40.71 ± 1.91 2.11 ± 0.10 0.98 1.2 g U-CC 458.35 ± 24.68 424.33 ± 20.48 42.49 ± 6.11 2.07 ± 0.06 0.98 0.2 g A-CC 485.67 ± 9.03 484.58 ± 7.84 32.37 ± 0.24 3.36 ± 0.11 0.98 0.4 g A-CC 458.39 ± 27.44 462.31 ± 23.64 31.03 ± 1.64 2.69 ± 0.81 0.98 0.6 g A-CC 500.75 ± 3.53 488.55 ± 23.64 35.24 ± 3.00 2.10 ± 0.19 0.98 0.8 g A-CC 450.51 ± 49.54 406.79 ± 20.35 37.03 ± 11.94 0.31 ± 0.34 0.97 1.0 g A-CC 480.91 ± 26.07 462.39 ± 27.34 38.17 ± 3.25 1.37± 0.34 0.99 1.2 g A-CC 486.81 ± 5.40 469.59 ± 8.37 36.82 ± 3.79 1.01 ± 0.39 0.99 ǂVS: volatile solids, CC: carbon cloth, U-CC: untreated carbon cloth, A-CC: activated carbon cloth. ±The dosages of 0.20, 0.40, 0.60, 0.80, 1.00, and 1.20 g carbon cloth correspond to 0.37, 0.74, 1.11, 1.48, 1.85 and 2.22 g U-CC or A-CC/g-VSsubstrate, respectively. *mean ± standard deviation of triplicate BMP bottles There was a significant (p<0.05) increment in Rm up to 0.80 g dose between U-CC and A-CC added BMP bottles, however for 1 g and 1.2 g dosages, the Rm values were 97 not statistically significant with p>0.05 between U-CC and A-CC added BMP bottles. Furthermore, there was a consequent decrement (p<0.05) in λ values with the increase of the A-CC supplementation over the U-CC added bottles at all dosages. The details of the statistical calculations are available in Appendix 1 Section A3. In the BMP with 0.80 g A-CC, 15.6 times reduction in the lag phase was observed over the Control reactor. The results obtained in Table 3.2 validate Hypothesis I: incorporating A-CC into AD utilizing municipal sludge will achieve superior performance compared to AD with commercial carbon cloth. While higher carbon cloth dosages improved the reactor performance, as discussed in previous sections, the carbon cloth dosages per liter of liquid volume must be optimized to overcome mixing and mass transfer limitations. 3.7 Summary In summary, this chapter showcases that employing a two-step activation procedure on commercial carbon cloth generated an improved biocompatible surface, which is termed A-CC. A-CC is linked with enhanced rates of methane production and lower inhibition for methanogenesis. The chapter highlights the following observations: • In BMP experiments, the use of lower dosages of U-CC resulted in a prolonged lag phase and a reduction in overall digester performance. • The optimization of A-CC dosing rate is essential to enhance methane production. Nonetheless, excessive dosing (above 1.48 g A-CC/g-VSsubstrate) impeded mixing and mass transfer in BMP experiments. 98 Chapter 4. Synthesis and evaluation of metal-impregnated carbon cloth supplementation to improve anaerobic digestion performance from municipal sludge This study examined the impact of metal-impregnated-carbon cloth (mA-CC) on thermophilic AD of municipal sludge. Four types of metal impregnated carbon cloth materials (Fe/CC, Ni/CC, Ni/Fe/CC, NiPcS/Fe/CC) were synthesized via hydrothermal synthesis from activated carbon cloth (A-CC) (discussed in Chapter 3) and compared with untreated carbon cloth (U-CC) to assess their functional significance for enhancing AD. The primary factors analyzed for conductive material characterization were electrical conductivity (EC) and Brunauer–Emmett–Teller (BET) surface area. Enhancement of methane generation with and without conductive material was studied by BMP assays. In this chapter, Hypothesis II: “Physiochemical characteristics of biomass/biofilm carriers, such as surface area and EC, play a significant role in promoting microbial attachment and biofilm formation. Therefore, Ni/Fe metal impregnation on A-CC should further increase conductivity of A-CC, leading to superior AD performance when this is added compared to AD with A-CC” was tested. 4.1 Overview Various intensification techniques have been used to improve the AD process, such as co-digestion, pretreatment of substrates, AD process control, and additive supplementation (Kumar et al., 2021; Qin et al., 2020). Due to ease of implementation, additive supplementation is considered an economically tractable way to improve AD performance. For example, direct metal addition of Iron (Fe), Zinc (Zn), or Nickel (Ni) has been demonstrated to impact AD performance although such results are nuanced and can vary according to biomass input and elemental form (Paritosh et al., 2020). 99 The use of the addition of Ni to stimulate AD performance is particularly interesting given its essential role in methanogenesis. The methyl-coenzyme M reductase (MCR) holoenzyme uses the Ni porphyrin cofactor F430 as a prosthetic group to catalyze the last step in methanogenesis by converting methyl-coenzyme M (CH3–S–CoM) and coenzyme B (HS–CoB) to methane (CH4) and heterodisulfide (CoB–S–S–CoM) indicating that the direct addition of Ni or Ni porphyrin analogs of F430 could be used to stimulate methane production under certain circumstances (Thauer, 2019). Within AD ecosystems different microbial groups play specialized roles in the biomass conversion process. In addition to hydrolysis and fermentative metabolisms, some AD microorganisms are specifically involved in syntrophic exchange of electrons via donors such as H2 and formate in a process known as indirect interspecies electron transfer, or through direct interspecies electron transfer (DIET) via electrically conductive pili and outer membrane c-type cytochromes (Lovley, 2011a). The cooperative exchange of electronic signals via conductive materials for DIET has proven to be an effective way to improve AD performance (Baek et al., 2018; Yin and Wu, 2019). DIET is associated with increased electron transfer rates compared to indirect interspecies electron transfer and can overcome process instability associated with elevated H2 partial pressure and volatile fatty acid accumulation (Lin et al., 2017). In engineered AD ecosystems, various conductive materials have been used to promote DIET, including carbon-based materials such as granular activated carbon (GAC), biochar, carbon cloth, graphite, and transition metal containing materials (Kumar et al., 2021). Materials containing Fe, Zn and Ni show the most significant improvement of AD performance and resilience under different operating conditions (Paritosh et al., 2020). 100 While direct metal addition raises important regulatory questions related to downstream environmental impacts of residual solids, the addition of carbon-based materials such as carbon cloth to improve AD performance provides an opportunity to reuse or recycle components with reduced environmental impacts. Such materials increase the available surface area for biomass growth, promote longer retention times and decrease microbial cell loss from the system. If the material is also conductive, supplementation in AD increases the available surface area and electrical conductivity (EC) simultaneously (Liu et al., 2020; Najafpour et al., 2006). Although this combination can enhance microbial adhesion and promote electron transfer such combined usage confounds efforts to measure the impact of individual performance features (Baek et al., 2021). Moreover, each material used has unique properties, making comparisons between studies using different materials more challenging (Chen et al., 2014). For example, biochar with conductivity 1000 times lower than GAC provides similar results in terms of AD enhancement (Shao et al., 2019). In other studies, AD performance was evaluated using two dissimilar carbon materials (a graphite plate and a carbon brush) but the material properties (surface roughness, EC, biocarrier potential, etc.) were not compared directly (Al-Amshawee et al., 2021; Liu et al., 2020). In this chapter, Hypothesis II of the thesis was examined and evaluated how the biocarrier potential of carbon cloth can be enhanced for better microbial activity by evaluating the influence of surface area and EC. To validate this hypothesis, different properties of carbon cloth in the context of AD performance using five different composite materials synthesized (as shown in Figure 4.1) with varying surface areas and ECs. Electrical conductivity was changed by adding Fe, Ni, and Ni-phthalocyanine precursors during the hydrothermal synthesis of carbon cloth composite material. 101 Finally, synthesized carbon cloth composites were used in biochemical methane potential (BMP) assays to determine their impact on methane generation rates and overall reactor performance. 102 Figure 4.1. Schematic of the overall carbon cloth metal impregnation process 103 4.2 Experimental section 4.2.1 Preparation of metal-impregnated activated carbon cloth (mA-CC) using hydrothermal synthesis method The hydrothermal synthesis is a closed pressure vessel-based approach for cultivating single crystals. The reactor, depicted in Figure 4.2, comprises a high-quality stainless steel outer shell and a Teflon-lined inner chamber. The method involves heating a liquid mixture containing a carbon cloth supplement above its boiling point inside the autoclave and adding metal precursor salts in water as nutrients. The size and type of crystal growth on the surface are determined by the synthesis temperature and duration (Boris et al., 2012). In this study, two-step A-CC was employed (detailed in Chapter 3, Section 3.2.2) as the active surface for impregnating Ni and Fe complexes at various concentrations. The iron oxide/CC (Fe/CC), Nickel/CC (Ni/CC,) Nickel (II) phthalocyanine complex/CC (NiPcS/CC), and metal composites/CC (represented as Fe/Ni/CC and Fe/NiPcS/CC) were synthesized using a hydrothermal method at 150ºC for 72 hours. Figure 4.2. Hydrothermal reactor used for metal-impregnation of carbon cloth (CC) 104 Briefly, 6 mmol of urea (NH2CONH2) and 4.5 mmol of ammonium fluoride (NH4F) and metal precursor concentration (as shown in Table 4.1) were added to 125 mL of deionized water. A standard operating procedure (SOP) was established and followed for the safe handling of NH4F, which can generate hydrofluoric acid (HF) (see Appendix 1 Section A4). Although very low concentrations of NH4F were used, the UBC Risk Assessment Services guidelines were implemented to prevent the potential danger of HF production. It is to be noted that polyethylene glycol with a molecular weight of 20000 g/mol (PEG 20,000) was used for Fe/CC synthesis. The PEG 20,000 is generally used to synthesize metallic particles to control the morphology of the synthesized metal deposited material. The solution was stirred for 30 minutes and then transferred to a Teflon-lined autoclave. To the solution, 0.22 g (2 cm × 5 cm) of A-CC was added, and the hydrothermal reactor was heated at 150°C for 72 hours in an oven. The reactor was then cooled to room temperature in a fume hood. The synthesized metal-impregnated CC was washed several times with deionized water to remove loosely bound impurities. Finally, the synthesized samples were burned at 350ºC for two hours to fix the metal deposition on A-CC firmly. Table 4.1. Preparation of metal-impregnated carbon cloth (mA-CC) supplements Precursor sampleǂ FeCl3 (mmol) FeCl2 (mmol) NiCl2 (mmol) NiPcS (mmol) PEG-20,000* (w/v) NH2CONH2 (mmol) NH4F (mmol) Fe/CC 1.5 3 - - 1 6 4.5 Ni/CC - - 4 - - 6 4.5 Ni/Fe/CC 2 - 2 - - 6 4.5 NiPcS/Fe/CC 2 - - 2 - 6 4.5 ǂFe/CC, Ni/CC, Ni/Fe/CC: iron, nickel, and iron/nickel metal-impregnated carbon cloth, respectively; NiPcS/Fe/CC: Nickel (II) phthalocyanine-tetrasulfonic acid tetrasodium salt complex with iron impregnated carbon cloth. *PEG 20,000: polyethylene glycol with a molecular weight of 20000. 105 4.2.2 Substrate and inoculum Thickened screened primary sludge (TSPS) as a substrate was obtained from a Lulu Island municipal WWTP in Vancouver (BC, Canada). The inoculum used for this study was prepared using an automated 5 L anaerobic digester. The digester was operated at an SRT of 20 days, a temperature of 55℃ and stirred at 150 rpm. The detailed characteristics of substrate and inoculum are provided in Chapter 3 Section 3.2.3. 4.2.3 Characterization of carbon cloth samples The specific surface area, average pore size, and total pore volume of carbon cloth samples were determined through nitrogen physisorption experiments through the BET and BJH conducted at -196°C using Micromeritics ASAP 2000 equipment. Prior to analysis, the samples were degassed under a vacuum at 200°C for two hours. BET and BJH methods were utilized for the analysis, which was conducted at the Catalysis and Chemical Reaction Engineering Laboratories at the University of Saskatchewan, Canada. Raman spectra were obtained using a LabRam spectrometer with a charge-coupled device and a 532 nm excitation source emitting at 20 mW laser power. Attenuated total reflectance infrared (ATR-IR) spectra were recorded using a Nicolet Magna 850 Fourier transform spectrometer with a liquid nitrogen-cooled narrow band MCT detector. Each spectrum was acquired through the acquisition of 32 scans at a 4 cm-1 resolution ranging from 4000 to 400 cm-1. The Tescan Mira 3 XMU Scanning Electron Microscope was used to examine the structural modifications of carbon cloth with and without metal impregnation, while the elemental composition of carbon cloth was visualized using an Oxford Instruments X-106 Max Energy Dispersive X-ray Spectra (EDx) detector. The samples for SEM and EDx analysis were sent to the FiLTER (Fipke Laboratory for Trace Element Research) Laboratory at UBC Okanagan. The samples for EC analysis were analyzed by Dr. Jake Bobowski's research group at UBC Okanagan. Further information on EC measurement can be found in Appendix 1, Section A5. 4.2.4 Biochemical methane potential (BMP) experiment The procedure for the batch BMP assay was adopted from Chapter 3, with details available in Section 3.2.5. Two separate batches of BMP experiments were conducted with U-CC, A-CC, and synthesized mA-CC samples, with a dose of 0.80 g carbon cloth (1.48 g carbon cloth/g VSfed). Batch-1 included 21 assays and evaluated the impact of different types of carbon cloth (U-CC, A-CC, Fe/CC, Ni/CC, Ni/Fe/CC, and NiPcS/Fe /CC) on AD improvement with experiments set up in triplicate with blank (inoculum only) and control (no carbon cloth) reactors. Batch-2 included 34 assays and aimed to assess microbial community structure and the impact of metal impregnation on syntrophic microbial association compared to control and U-CC assays. All bottles were purged with nitrogen gas to remove oxygen, sealed with a butyl rubber stopper, and incubated at 55°C and 90 rpm. Methane production, VFA measurement, and pH were measured for 30 days, and detailed analytical methods for VS, pH, VFA, and headspace biogas volume/composition can be found in Chapter 3 section 3.2.6. 4.2.5 Kinetic modeling In order to estimate the performance of BMP reactors utilizing different carbon cloth media (U-CC, A-CC and mA-CC), the Modified Gompertz model was employed. 107 Further information regarding the equation and kinetic modeling parameters can be found in Chapter 3, Section 3.2.7. 4.3 Results and Discussion 4.3.1 Characterization of untreated (U-CC), activated (A-CC) and metal-impregnated carbon cloth (mA-CC) Surface areas of A-CC, Fe/CC, Ni/CC, Ni/Fe/CC, and NiPcS/Fe/CC were measured using the BET nitrogen adsorption-desorption isotherms, while the BJH desorption method was used for surface area determination of U-CC. Commercial CC (U-CC) had a shiny surface, and unfortunately, BET analysis could not provide results for U-CC. It can be seen from Table 4.2 that A-CC had the highest surface area (386.15 m2/g), followed by Fe/CC (140.96 m2/g) and NiPcS/Fe/CC (52.27 m2/g). The micropore volume of A-CC, Fe/CC, Ni/CC, Ni/Fe/CC, and NiPcS/Fe/CC was calculated using the t-method. The t-micropore area also showed a similar trend, contributing 27-34% of the total BET area in different samples. It is evident from the data that the surface area and pore volume of A-CC increased post-acid activation. However, the surface area decreased after metal impregnation on A-CC. This may be due to the agglomeration of Fe and/or Ni particles on the CC surface and pores. The total pore volume of metal-impregnated CC (Fe/CC, Ni/CC, Ni/Fe/CC, NiPcS/Fe/CC) ranged from 0.005 to 0.028 cm3/g, while the pore volume of A-CC was significantly higher (0.058 cm3/g). These results indicate that the impregnation of Fe and/or Ni on A-CC leads to a decrease in pore volume due to aggregation of excess Fe and/or Ni microcrystals in the micropores (Devi et al., 2020). Furthermore, the pore diameter of Ni/Fe/CC (11.8 nm) was higher than that of A-CC (3.08 nm), Fe/CC (4.01 nm), Ni/CC (5.91 nm), and NiPcS/Fe/CC 108 (4.66 nm). Fe and Ni likely exist as bulk material separated from CC, which yields a higher value of average pore size in Ni/Fe/CC. This inference was also noticed and supported by the SEM images (discussed below in detail) of Ni/Fe/CC, where agglomerated Fe and Ni particles were observed separated from CC. The existence of a bulk phase of Fe and Ni could be responsible for the higher pore diameter of Ni/Fe/CC compared to A-CC, Fe/CC, Ni/CC, and NiPcS/Fe/CC. Although, BET surface area provides a very significant result, a standardized method for all the synthesized material is difficult. Due to change in various physicochemical characterization of CC, the adsorption-desorption method with liquid nitrogen may provide biased results, therefore, it is also important to acknowledge the importance of material intrinsic properties for comparison when two dissimilar materials are analyzed. Table 4.2. Surface area and pore structure of untreated, activated and metal-impregnated carbon cloth Materialsǂ BET surface area (m2/g) t-plot micropore area (m2/g) % t-micropore area out of total BET area Micropore volume (cm3/g) Pore size (nm) Electrical conductivity (1/ohm.m) Diameter of single carbon fibre (µm) U-CC 3.46 *104 7.33 A-CC 386 122 32 0.058 3.08 2.25 *104 7.13 Fe/CC 141 54 39 0.028 4.01 3.72 *104 6.30 Ni/CC 44 12 28 0.005 5.91 3.06 *104 7.40 Ni/Fe/CC 36 11 30 0.006 11.8 3.58 *104 7.16 NiPcS/Fe/CC 52 18 34 0.010 4.66 2.62 *104 6.88 ǂU-CC: untreated carbon cloth, A-CC: activated carbon cloth, Fe/CC, Ni/CC, Ni/Fe/CC: iron, nickel, and iron/nickel metal-impregnated carbon cloth, respectively; NiPcS/Fe/CC: Nickel (II) phthalocyanine-tetrasulfonic acid tetrasodium salt complex with iron impregnated carbon cloth. 109 Further, Table 4.2 presents the EC values for various samples, with Fe/CC exhibiting the highest EC, followed by Ni/Fe/CC, U-CC, and Ni/CC. The increase in EC of Fe/CC may be attributed to the presence of iron oxide on the carbon cloth surface. The higher EC of U-CC, on the other hand, could be attributed to a greater degree of graphitization or higher surface charges resulting from active dispersion of metal ions on the carbon cloth surface. The degree of graphitization was determined by Raman analysis and will be discussed in more detail below (Li et al., 2022). Figure 4.3a shows the Raman spectra for six different samples: U-CC, A-CC, Fe/CC, Ni/CC, Ni/Fe/CC, and NiPCS/Fe/CC. The prominent peaks at 1350 and 1583 cm-1 were identified as the D-band (ID) and G band (IG), respectively, where ID is associated with structural defects in the sp2 lattice and IG is due to graphitic carbon . All spectra showed both the D-band and G-band vibrations, with different intensities among the samples. The intensity of the D-band and G-band decreased in the following order: U-CC < A-CC < Fe/CC < Ni/CC < Ni/Fe/CC < NiPCS/Fe/CC. The ID/IG ratios were calculated to determine the relative degree of defects among the carbon cloth samples. The order of ID/IG ratios was as follows: U-CC (0.88), A-CC (0.92), Fe/CC (0.95), Ni/CC (0.98), Ni/Fe/CC (0.98) and NiPcS/Fe/CC (1.04). A-CC, Fe/CC, Ni/CC, Ni/Fe/CC, and NiPcS/Fe/CC showed a higher degree of disorder than U-CC, indicating that surface defects were increased after acid activation followed by metal impregnation. The lowest ID/IG ratio (0.88) for U-CC indicates the highest degree of graphitization, which supports the higher EC values for U-CC. In addition, smaller peaks at 461 cm-1, 565 cm-1, and 1105 cm-1 were observed in Ni/CC and NiPcS/Fe/CC, which indicate the presence of Si-O-Si, Si-O-C, and NiO, respectively. 110 Figure 4.3. a. Raman spectra and b. FTIR spectra of various carbon cloth samples. [U-CC, A-CC: untreated and activated carbon cloth; Fe/CC, Ni/CC, Ni/Fe/CC: iron, nickel, and iron/nickel metal-impregnated carbon cloth, respectively; NiPcS/Fe/CC: Nickel (II) phthalocyanine-tetrasulfonic acid tetrasodium salt complex with iron impregnated carbon cloth] a. b. 111 The FTIR spectra in Figure 4.3b show U-CC, A-CC, Fe/CC, Ni/CC, Ni/Fe/CC, and NiPcS/Fe/CC recorded in the range of 600 to 4000 cm-1. The broader band in the 3485-3700 cm-1 is attributed to the O-H stretching of alcohols. The intensity of this peak was slightly decreased after acid activation in A-CC and metal impregnation in Fe/CC, Ni/CC, Ni/Fe/CC, and NiPcS/Fe/CC. The transmittance peaks at 2360 and 2330 cm-1 are associated with O=C=O stretching. The intensity of these peaks was significantly decreased in Ni/Fe/CC and NiPcS/CC suggesting the strong coupling between Fe and Ni particles and functional groups present on the CC surface. The activation of U-CC led to the formation of a weak band in the region of 1990 cm-1 that might be attributed to the N=C=S stretching of the isothiocyanate group originating from nitric acid and sulfuric acid treatments. However, this peak disappeared in the Fe/CC, Ni/CC, Ni/Fe/CC, and NiPcS/Fe/CC. The transmittance band in the region of 1500-1550 cm-1 in A-CC, Fe/CC, Ni/CC, Ni/Fe/CC, and NiPcS/Fe/CC is associated with the N-O stretching of nitro compounds due to activation of CC with nitric acids. Furthermore, the vibrational stretch of C-O observed at 1066 cm-1 and the small peaks in the region of 1380-1415 cm-1 could be attributed to the stretching vibration of sulfonated groups, confirming the change in surface functionality in A-CC, Fe/CC, and Ni/CC, Ni/Fe/CC and NiPcS/Fe/CC compared to U-CC. Additionally, the peaks observed at 690 cm-1 were due to the bending vibrations of the O–H bonds in Fe/CC, Ni/CC, Ni/Fe/CC, and NiPcS/Fe/CC. The SEM and EDx images of A-CC, Fe/CC, Ni/CC, Ni/Fe/CC, and NiPcS/Fe/CC are shown in Figure 4.4. The diameter of a single carbon fibre varies between 6.3 and 7.3 μm for all CC samples, as shown in Table 4.2. Figures 4.4a and 4.4b show that the carbon cloth is smooth and consistent over the entire surface of the carbon cloth. Figures. 3c and 3d show the SEM and EDx images of Fe/CC, 112 respectively. The EDx spectra confirmed that the introduction of PEG 20,000 supports Fe3+/Fe2+ precursor (1:2 ratio as shown in Table 4.1) to form a rod-like structure of iron metal deposition on the CC surface. Figure 4.4. Scanning electron microscopy (SEM) image of a. A-CC. c. Fe/CC. e. Ni/CC. g. Ni/Fe/CC. i. NiPcS/Fe/CC, respectively, and EDx analysis and mapping of metallic nanostructures impregnated on b. A-CC. d. Fe/CC. f. Ni/CC. h. Ni/Fe/CC. j. NiPcS/Fe/CC, respectively. [U-CC, A-CC: untreated and activated CC; Fe/CC, Ni/CC, Ni/Fe/CC: iron, nickel, and iron/nickel metal-impregnated CC, respectively; NiPcS/Fe/CC: Nickel (II) phthalocyanine-tetrasulfonic acid tetrasodium salt complex with iron impregnated CC] 113 Similarly, Figures 4.4e and 4.4f display the SEM and EDx images for the Ni/CC sample, respectively. The EDx spectra confirmed the presence of Ni. As a whole, PEG 20,000 supported the growth of the tiny rod-like structure. However, PEG 20,000 also hindered the attachment of Ni precursors to carbon cloth and, therefore, was not used (as shown in Table 4.1) in any of the Ni-based material synthesis on carbon cloth. No PEG 20,000 was used in Ni/CC, so the architecture formed flat, irregular Ni composite flakes on carbon cloth. Furthermore, SEM and EDx of Ni/Fe/CC materials are shown in Figures 4.4g and 4.4h, respectively. Introducing Fe3+ precursor solution might help to tune a uniform metal deposition on carbon cloth. The attached Ni and Fe metal was confirmed using EDx. The smaller Fe and Ni metal peak also suggests a lower concentration of these metals on the carbon cloth surfaces. The metalloporphyrin cofactor F430 is an integral component of the methyl coenzyme M reductase holoenzyme complex driving the terminal step in biological methane production. In NiPcS/Fe/CC sample synthesis, the precursor NiPcS (Nickel(II) phthalocyanine-tetrasulfonic acid tetrasodium salt) was used to immobilize the Ni-phthalocyanine layers on the Fe composite to improve the biocarrier potential of carbon cloth further, as reported in the literature (Liu et al., 2007; Rezaeifard et al., 2012; Shao et al., 2019). It is to be noted that in Figures 4.4i and 4.4j, the thread-like twisted structure was uniformly formed on carbon cloth. The spiral morphology of the synthesized composite may be due to the complexity of the NiPcS precursor used for the synthesis. The Ni and Fe atom on the carbon cloth surface was confirmed using EDx spectra. 114 4.3.2 Anaerobic digestion (AD) performance It is important to note that the specific cumulative methane production curves, shown in Figure 4.5a. from BMP assays supplemented with various carbon cloth had a very similar trend with the supplement’s BET surface and did not entirely correlate to the EC of carbon cloth samples. In this study, the BET surface varied for each treatment as a function of the type of metal added to the carbon cloth. A significantly higher rate and extent of specific methane generation were observed for BMP assays containing A-CC with the highest BET of 386.15 m2/g followed by those containing Fe/CC, NiPcS/Fe/CC, Ni/CC, and Ni/Fe/CC with 140.96, 52.27, 43.52 and 36.07 m2/g respectively. Within nine days, the A-CC and Fe/CC supplemented assays produced 3.45- and 2.70-fold higher specific methane over the Control assays (without carbon cloth). Supplementing reactors with U-CC, Ni/CC, Ni/Fe/CC and NiPcS/Fe/CC did not yield significant methane increment and produced 0.87-, 1.26-, 1.01- and 1.29- fold higher methane, respectively, over Control reactors in the first nine days. Previous studies have reported that electrically conductive material promotes DIET and methanogenesis in the AD context (Gahlot et al., 2020). However, EC could only partially explain the higher methanogenic activity in this study. The assays supplemented with U-CC with a higher EC of 3.46 × 104 (1 ℧⁄ ∙ 𝑚) produced the lowest methane. Conversely, A-CC with the lowest EC of 2.25 × 104 (1 ℧⁄ ∙ 𝑚) produced the highest methane in 9 days. The change in EC by impregnating metal on CC did not impact on increase in methane production. This is however consistent with our previous study in which non-conductive horsehair brushes showed methanogenic efficiency comparable to conductive stainless-steel brushes and CC brushes. These results also confirm that the biocarrier potential and DIET of any material in AD are not 115 a crucial function of EC (Baek et al., 2021). In contrast, the BET surface was directly correlated with increased methane production, a function of higher microbial activity that catalogues the biocarrier potential of each CC type for higher methane increment. Figure 4.5. Effect of various carbon cloth supplements on a. specific cumulative and b. specific daily methane production from thermophilic biochemical methane potential assays utilizing municipal sludge at standard temperature and pressure (STP of 0ºC, 1 atm). Data represent average, and error bars represent standard deviations of triplicates. [CC: carbon cloth, U-CC, A-CC: untreated and activated carbon cloth, Fe/CC, Ni/CC, Ni/Fe/CC: iron, nickel, and iron/nickel metal-impregnated carbon cloth, respectively; NiPcS/Fe/CC: Nickel (II) phthalocyanine-tetrasulfonic acid tetrasodium salt complex with iron impregnated carbon cloth] 116 The daily specific methane production rate increment observed from BMP assays supplemented with various carbon cloth (Figure. 4.5b) shows a clear shift in the peak height and the time of emergence for all carbon cloth used. For A-CC, the methane peak emerged on Day 6 compared to the Control peak on Day 13. Similarly, the peak of daily specific methane production rate for A-CC was the highest (49.78 mL/day/g VSfed) among all the other BMPs. These results also support that A-CC possesses unique features (large surface area and pore volume/structure, Table 4.2 that promote syntrophic interactions and biocarrier potential for microbial attachment culminating in higher methanogenesis rates (Figure 4.5b) with concomitant increase in methane production (Figure 4.5a) when compared to the Control and BMPs with other carbon cloth supplements. 4.3.3 Effect of various metal-impregnated carbon cloth (mA-CC) on volatile fatty acids (VFA) and pH profiles During healthy BMP progression, at the initial stage, the substrate is hydrolyzed and converted into VFAs by fermentative bacteria. The rapid accumulation of VFAs and their simultaneous use to form biogas indicates higher microbial activity. As shown in Figure 4.6a the highest peak of VFA production (dominated by acetic acid) was observed on Day 3 for the A-CC and Fe/CC bottles, representing a higher acidogenic activity for these two reactors compared to the Control where the peak observed at Day 9. Consistent with cumulative methane production results discussed earlier, VFA production by fermentative bacteria and subsequent utilization by archaea followed similar trends to the BET surface. The larger the microbial attachment surface, the higher the acidogenic activity. For example, in BMPs supplemented with A-CC and 117 Fe/CC, the VFA peaks appeared on Day 3, followed by the peaks of NiPcS/Fe/CC, Ni/CC, and Ni/Fe/CC, observed on Day 6, respectively, and U-CC and control VFA peaks were only observed on Day 9. Rapid recovery from VFA accumulation/pH decline in batch bioreactors is associated with improved syntrophic interactions (Nelabhotla and Dinamarca, 2019). Figure 4.6. Effect of various carbon cloth supplements on a. total volatile fatty acids (VFA), comprised of acetic, propionic and butyric acids and b. pH in thermophilic biochemical methane potential assays utilizing municipal sludge at standard temperature and presure (STP of 0oC, 1 atm). Data represent average, and error bars represent standard deviations of triplicates. [CC: carbon cloth, U-CC, A-CC: untreated and activated carbon cloth; Fe/CC, Ni/CC, Ni/Fe/CC: iron, nickel, and iron/nickel metal-impregnated carbon cloth, respectively; NiPcS/Fe/CC: Nickel (II) phthalocyanine-tetrasulfonic acid tetrasodium salt complex with iron impregnated carbon cloth] 118 In this study, higher VFAs resulted in lower pH and vice versa in BMP bottles (Figure 4.6b). The pH in BMPs supplemented with A-CC and Fe/CC reached the lowest value of 7.13 and 7.31 on Day 3 but still acquired the neutral pH values of 7.52 and 7.44 on Day 6, respectively, due to sufficient buffer addition during the initial set-up. However, pH decline and recovery were slower in other reactors, including Controls. 4.3.4 Kinetic modeling Mathematically, using the Modified Gompertz model, the various kinetic parameters (P, Rm, and λ) can be determined for all BMP reactors based on the best fit to the cumulative methane production data. In this study, the regression coefficient (R2) for the model's goodness of fit was greater than 0.90 (Table 4.3). As shown in Table 4.3, it is clear that adding carbon cloths with varying BET surface area and pore structure substantially impacts specific methane production rate (Rm) and duration of the lag phase (λ) compared to the Control (without carbon cloth). In the case of A-CC with higher BET surface area and improved biocarrier potential, the Rm was significantly increased by 2.6 times, and λ was reduced by 3.9 times compared to the Control. The U-CC reactor leads to the inhibition of methane production; therefore, an increase in the lag phase (λ) (1.35 times) and a decrease in the Rm to 1.2 times compared to the Control (without carbon cloth) were observed. Moreover, for NiPcS/Fe/CC, the methane production rate (Rm) also decreased to 1.11 times compared to the Control. However, the λ for NiPcS/Fe/CC was 11.25 times lower than that of the control reactor. Overall, BMPs with Fe/CC, Ni/CC, and Ni/Fe/CC improved the Rm value by 1.67, 1.1, and 1.03 times, respectively. The λ values for Fe/CC and Ni/CC were reduced to 8.33, 1.32 times compared to the Control. 119 Yet, the λ value for Ni/Fe/CC was 1.27 times higher than that of the Control. Table 4.3. The modified Gompertz model's parameters for BMP bottles with various carbon cloth BMP amendment conditionsǂ P = Ultimate specific methane production (ml/g-VS fed) Rm = rate of methane production (ml/g-VS fed/d) λ = Lag phase (day) R2 Measured Simulated Control (no carbon cloth) 428.60 ± 7.99* 530.93 ± 15.51 20.95 ± 1.01 2.25 ± 0.30 0.95 U-CC 414.95 ± 3.06 733.53 ± 124.86 17.46 ± 0.51 3.04 ± 0.65 0.93 A-CC 517.62 ± 3.61 503.42 ± 0.77 53.76 ± 3.46 0.58 ± 0.13 1.00 Fe/CC 485.58 ± 10.16 493.94 ± 7.48 35.11 ± 2.64 0.27 ± 0.11 0.99 Ni/CC 460.89 ± 4.10 550.40 ± 16.29 23.10 ± 1.70 1.71 ± 0.97 0.97 Ni/Fe/CC 470.33 ± 26.81 681.33 ± 119.09 21.62 ± 3.42 2.87 ± 0.88 0.91 NiPcS/Fe/CC 400.03 ± 15.33 481.08 ± 22.75 18.78 ± 0.79 0.20 ± 0.17 0.93 ǂU-CC: untreated carbon cloth, A-CC: activated carbon cloth, Fe/CC, Ni/CC, Ni/Fe/CC: iron, nickel, and iron/nickel metal-impregnated carbon cloth, respectively; NiPcS/Fe/CC: Nickel (II) phthalocyanine-tetrasulfonic acid tetrasodium salt complex with iron impregnated carbon cloth; VS: volatile solids; *mean ± standard deviation of triplicate BMP bottles. Additionally, a two-dimensional surface contour plot was constructed to visualize the interaction of independent factors, i.e., BET surface and EC, on the response parameter (Rm) within the experimental design range. Using the Origin software tools, the experimental dataset was first converted into matrix form using the Renka-Cline gridding method. This method automatically interpolates and estimates the gradient used to construct the contour plot for any two independent and one dependent variable. Contour plots were built to find the most favorable combination of two independent variables (BET and EC) on the Rm value. In Figure 4.7, the bluish-purple shared region represents the least favorable interaction, and the red shared 120 region provides the most favorable result for methane generation from municipal sludge. The results of the contour plot are aligned with experimental observation. At the lower values of each factor, the BET surface area and EC appear to have a direct relationship with Rm values. However, it should be noted that at a higher BET surface (>350 m2/g), the surface area becomes a more dominant factor, and the increase of EC value (>2.9*104 1/Ω.m) does not contribute to a further increase of Rm. The rate of methane production (Rm), BET surface area and lag phase (λ) were three imperative process parameters used to select the best performing carbon cloth material for enhanced methane production. To summarize the results obtained from the aforementioned parameters, the data were plotted together in Figure 4.8 to Figure 4.7. Interaction of BET surface area, electrical conductivity of various carbon cloth on rate of methane production (Rm) 121 visualize the relationship among the process parameters utilizing U-CC, A-CC and metal-impregnated carbon cloth samples. The graph illustrates that the Rm value is a crucial performance parameter for selecting high-performance carbon cloth. It is noteworthy that an increase in Rm is directly proportional to the BET surface area, while lower λ values have little impact. For instance, in A-CC pretreated assays, a higher surface area corresponds to a higher Rm value. However, the lowest λ value in NiPcS/Fe/CC did not enhance the Rm values. Therefore, the information compiled in Figure 4.8 agrees that BET surface area is the key factor in enhancing Rm. 4.4 Summary This Chapter focused on improving AD performance by incorporating metal-impregnated CC composite (i.e., Fe/CC, Ni/CC, Ni/Fe/CC, NiPcS/Fe/CC) with a variable surface area and EC. Using hydrothermal synthesis, the BET surface area and the EC Figure 4.8. Lag phase (λ), methane production rate (Rm) and BET surface area for untreated carbon cloth (U-CC), activated carbon cloth (A-CC), metal-impregnated carbon cloth (CC) (Fe/CC, Ni/CC, Ni/Fe/CC: iron, nickel, and iron/nickel) samples 122 of CC were modified by incorporating biocompatible metal precursors (such as Ni and Fe) mentioned in the literature. The objective was to test Hypothesis II of the thesis, which suggests that surface area and EC are crucial in enhancing AD performance. Although the metal impregnation improved the EC of the CC, the architecture of metallic deposits blocked the available pores of the CC, which reduced the accessible surface area for microbial attachment. However, it invalidates the hypothesis and suggest that AD enhancement is directly proportional to the available BET surface area and is partially supported by the EC of the supplementary material added. 123 Chapter 5. Novel bioaugmentation strategy with a syntrophic enrichment for enhanced digestion (SEED) system for maximizing methane yield from municipal sludge This chapter aimed to develop a novel bioaugmentation process to improve the overall anaerobic municipal sludge digestion efficiency under continuous flow conditions, simulating full-scale sludge treatment operation. A syntrophic enrichment for enhanced digestion (SEED) system with activated carbon cloth (A-CC) was fabricated and commissioned as a side-stream incubator reservoir to grow/retain beneficial cultures for methane generation. The SEED system was designed to provide a continuous flow of slow-growing methanogen-rich microbial cultures for bioaugmentation of a conventional anaerobic sludge digester (without carbon cloth) with a goal of enhancing the overall digestion efficiency in the existing or future biogas plants. The SEED system was tested for its bioaugmentation benefits/effectiveness to conventional anaerobic digesters under various organic loadings for process reliability. Therefore, in this chapter, Hypothesis III: “an incubator reservoir system for active/dense microbial population for bioaugmentation will improve digestion, increase process stability, and upgrade biogas quality in a bio-augmented main-stream anaerobic digester treating municipal sludge” was tested. 5.1 Overview In the previous chapters, it has been established that adding A-CC with significantly enhanced surface area to anaerobic sludge digesters will enhance methane production. However, previous experiments were constrained to small-scale batch assays, which do not simulate full-scale digesters with continuous-flow operation. Also, adding conductive materials to conventional digesters with large 124 volumes, due to long sludge retention time (SRT) requirements, would be costly and may present other challenges. For example, existing biogas digesters are designed according to a specific reactor geometry and mixing regimes to avoid short-circuiting and stratification, which could present challenges to retrofit them with conductive materials. Furthermore, if conductive materials are in powdered or granular forms, they may be washed out and interfere with dewaterability of the digestate necessary before land application of biosolids. In order to minimize these operational problems, adding conductive materials as biomass support media to a small, compact side-stream incubator and periodically slough off and transfer cultures grown on the biomass media to a mainstream sludge digester is a more practical approach, which is tested in this Chapter. The chapter included multiple reactors operated simultaneously, each with specific purpose explained in detail below. 5.2 Materials and methods 5.2.1 Experimental design and reactor operating conditions The experimental design, as illustrated in Figure 5.1, involved four continuously-stirred semi-continuously-fed digesters operated for 304 days at a thermophilic temperature of 55 ± 1ºC. These reactors were named SEED (syntrophic enrichment for enhanced digestion), Control, Test, and acid phase (AP) fermenters, respectively. The primary objective of the SEED assembly was to supply the Test reactor with methanogen-rich microbial cultures, which was then compared with the Control digester to evaluate the effectiveness of bioaugmentation on various process parameters monitored in conventional treatment plants. 125 As depicted in Figure 5.1, the bench-scale SEED reactor was constructed using an airtight glass vessel and a mixing shaft with a working volume of 5-litre. The A-CC were braided as a rope (length of each rope was ~25 cm) and tied to the agitator shaft using stainless steel wires. An optimal carbon cloth dose of 1.48 g A-CC/ VSfed was determined in Chapter 3. To ensure liquid mixing and mass transfer in the SEED reactor, the agitator was rotated at a low speed of 60 rpm. During bioaugmentation cycles (every 7-15 days), the speed of the mechanical mixer in the SEED reactor was increased from 60 to 120 rpm for 2 hours to mechanically slough off the slime layer on A-CC and cultures in effluent were transferred to the Test digester. Furthermore, the SEED reactor was equipped with a long hollow tube through which additional A-CC was immersed in the reactor mixture to collect samples for the microbial attachment (using fluorescence microscopy) on the carbon cloth surface. Two different types of substrates, (TSPS) and mixed sludge (MS), were used in this Chapter and were obtained from Annacis Island WWTP (Vancouver, BC). The thermophilic (55°C) inoculum to seed the Test and Control reactors was collected from a 5-liter anaerobic digester at BTG lab. First the Test digester was commissioned and after reaching steady-state, effluent from the Test reactor was used to seed the Control sludge digester. This ensured that both Test and Control digesters started with identical inoculum conditions for comparison. 126 Figure 5.1. Schematic flow diagram of the proposed bioaugmentation process with activated carbon cloth [AP: Acid phase, SEED: Syntrophic enrichment for enhanced digestion, #Centrifugation condition: 3500 revolution per minutes for 10 minutes] 127 The AP reactor was an anaerobic fermenter operated with a working volume of 6-litre and was fed with thickened screened primary sludge (TSPS) at an organic loading rate (OLR) of 20 g COD/L/day, a mixing speed of 350 rpm, and a sludge retention time (SRT) of 3 days only to wash out methanogenic archaea as its primary purpose was to generate VFA-rich hydrolyzed sludge for SEED. It is worth noting that TSPS in wastewater treatment plants usually contains higher levels of soluble organics that can be readily fermented to VFA. Table 5.1 shows the characterization of substrates and inoculum used in the current study. Other researchers at UBC’s BTG laboratory conducted the optimization of process parameters for the AP reactor utilizing Metro Vancouver’s wastewater sludge streams, resulting in higher VFA production (Nabaterega, 2023). The effluent of the AP reactor was centrifuged at 3,500 revolutions per minute (rpm) for 10 minutes, and only the soluble (supernatant) phase of the effluent was used as the substrate for the SEED system to accelerate the culture growth rates and to prevent premature clogging of A-CC surfaces with influent particulate matter, with the exception of initial 4 weeks of acclimation when AP effluent was fed to SEED without centrifugation. As illustrated in Figure 5.2, the Control and Test reactors had working volumes of 1.5 and 5 liters respectively and were fed with mixed sludge as a typical substrate for sludge digesters. The reactor contents were stirred using high-torque overhead mixers (make, Heidolph Hei-TORQUE overhead stirrer) with mixer stands. In the AP reactor, the mixing speed was fixed at 350 rpm, while in both Test and Control reactors, it was set at 150 rpm. Hot water (55 ± 1ºC) was circulated through a water jacket surrounding the glass wall of the reactors. An automated biogas counter unit (RITTER 128 MilliGascounters) was utilized to measure the daily gas volume produced in all reactors. Rubber septa were introduced to all the biogas outlet lines to analyze the biogas composition, which was determined using an Agilent 7820A Gas Chromatograph equipped with a thermal conductivity detector. More information on biogas measurement can be found in Chapter 3, Section 3.2.6. Table 5.1. Characterization of feeds (TSPS, MS, AP effluent) and inoculum Parameters Substrates Thermophilic inoculum TSPS MS AP effluent AP effluent (centrifuged)* TEST and Control reactor AP reactor pH 6.0 (0.3)* 5.4 (1) 5.5 (0.5) 5.5 (0.5) 7.91 (0) 8.10 (0) % TS (w/w) 3.52 (0.88) 4.40 (0.55) 2.9 (0) NA 1.73 (0.65) 1.70 (0.5) %VS (w/w) 3.24 (0.40) 3.90 (0.30) 2.7 (0) NA 1.32 (0.32) 1.28 (0.4) Total alkalinity (mg CaCO3/L) 415 (50) 1200 (100) 1.2 (0) 1.2(0) 4384 (1) 5150 (200) Total COD (g/l) 53 (2) 60 (1) 51(3) 15(1) 12 (4) 18 (1) Total ammonium nitrogen (mg/l) 210 (0) 800 (0) 504 (24) 504 (24) 1531 (0) 1551 (150) VFA (mg/l) 1206 (35) 2700 (600) 2990 (200) 2990 (200) 47 (0) 42 (0) *Centrifuged at 3,500 rpm for 10 min, TSPS: Thickened screened primary sludge, AP: acid phase reactor, MS: mixed sludge, TS: total solids, VS: volatile solids, COD: chemical oxygen demand, VFA: volatile fatty acids as summation of acetic, propionic, and butyric acids, *(standard deviation of triplicates). 129 The sludge digesters (Test and Control), presented in Table 5.2, were operated at two hydraulic retention time (HRT) periods (equal to SRT due to lack of biomass recycle): 20 days and 10 days. The digesters were fed once a day and 7 days a week. However, the SEED reactor had a different feeding pattern than the Test and Control reactors. The SEED reactor was intermittently fed with centrifuged AP effluent on the 2nd, 4th, and 6th day of the week. Intermittent feeding allowed time for the growth of syntrophic microbes and methanogens on A-CC. The SEED reactor was initially operated at an HRT of 20 days and using a similar feeding pattern, the HRT of the SEED reactor gradually decreased to 16, 8, and ultimately 5 days with a goal of designing a small, compact, cost-effective side-stream incubator. Outside the bioaugmentation periods, the SEED reactor effluent was centrifuged at 3500 rpm for 20 minutes, and the captured pellets were returned to the SEED reactor to prevent the loss of active microbial culture due to effluent washout from the SEED system, which made the SRT of the SEED reactor much longer than its HRT, as intended. Figure 5.2. Control, Test and SEED (syntrophic enrichment for enhanced digestion) reactors and overhead mixers 130 Table 5.2. Overall operational parameters for the SEED, Test and Control reactors Digester Substrate HRT (day) OLR (g COD/L/day) Working volume (L) Test Mixed sludge 20 10 3 6 5 3.5 Control Mixed sludge 20 10 3 6 1.5 AP reactor TSPS 3 20 6 SEED Centrifuged# filtrate from AP effluent 20 16 8 5 3-4 4-5 5-6 7-8 (3-4)* 5 *Note: SEED is fed 3 times a week each at ~7.5 gCOD/L/day, corresponding to an average ~3.2 gCOD/L/day over 7 days; #3500 rpm for 10 minutes; COD: Chemical oxygen demand; TSPS: Thickened screened primary sludge; SEED: Syntrophic enrichment for enhanced digestion, HRT: Hydraulic retention time, SRT: Solid retention time, VFA: Volatile fatty acids, OLR: organic loading rate; AP: Acid phase. 5.2.2 Bioaugmentation strategy The effluent from the SEED reactor was expected to contain a high concentration of syntropic bacteria and methanogenic archaea, which would be used to bio-augment the Test reactor. Test and Control digesters were first operated at 20-d HRT (OLR of 3 g COD/L/d) for 200 days, and the HRT was gradually reduced to 10-d (OLR of 6 g COD/L/d) over 90 days to assess the effectiveness of bioaugmentation at various HRTs. Two bioaugmentation strategies were tested at 20-day HRT: Liquid bioaugmentation (LB) and Pellet bioaugmentation (PB). During LB, 30% volume of the Test digester was replaced with effluent carrying microbial cultures from the SEED reactor, however during PB, the effluent from the SEED was first centrifuged (3,500 rpm for 20 minutes), and only the recovered microbial pellets were transferred to the Test reactor, which demanded much smaller (0.7-1.6%) volume replacement in the 131 Test digester to keep liquid volume and therefore HRTs consistent between the Test and Control digesters for better process comparison. At a shorter HRT 10 days, only PB was applied. The shorter HRT of 10 days was employed to assess the effectiveness of bioaugmentation under challenging biochemical conditions (such as pH shift, VFA and ammonia accumulation, which may arise due to higher organics at HRT 10 days) in terms of biogas yield, percent COD removal, and percentage methane in headspace. 5.2.3 Analysis The analytical methods were used in this chapter to analyze the various physiochemical characterizations available in Chapter 3 Section 3.2.6. Table 5.3 displays the parameters that were measured along with the frequency of sample collection for Control, Test and SEED reactors. The results obtained from the Test reactor were then compared to the Control reactor, which served as the baseline scenario. It should be noted that the analysis of various parameters such as TS, VS, total COD removal, alkalinity, total ammonia nitrogen, and VFA was carried out three days after each bioaugmentation cycle for the Test reactor. This was implemented to be able to compare performance of Test and Control digesters when both digesters were receiving identical substrate of mixed sludge at the same flowrate. Furthermore, fluorescence microscopy was employed to visualize the microbial biomass attachment on A-CC when the SEED reactor content reached a chemical oxygen demand (COD) of 3500 mg/l or higher. Two fluorescent stains were used to visualize the constituents of the biofilm adhered to the A-CC sample, which is composed of microbial cells, extracellular polymeric substances, and resilient microbial surfaces. The A-CC samples collected from the SEED reactor were examined using 132 FilmTracer™ SYPRO® Ruby biofilm stain and DAPI (4′,6-diamidino-2-phenylindole) stain. Fluorescence microscopy (Zeiss-Axioimager) was employed to investigate the biofilm growth on the carbon cloth surface. Prior to staining, the carbon cloth samples were washed with phosphate saline buffer to remove any loosely bound sludge samples. The carbon cloth samples were then coated with 200 µL of FilmTracer™ SYPRO® Ruby biofilm staining solution and left in the dark for 30 minutes. Following several washes with phosphate buffer saline (PBS), the carbon cloth samples were coated with DAPI stain (1 µg/ml) and left in the dark for 30 minutes. The samples were then washed with PBS several times and mounted on a glass slide for microbial analysis. An active biofilm coating around the carbon cloth provides additional supportive data that helped in determining the frequency of bioaugmentation. Table 5.3. Parameters measured to study the reactor performance Parameter Frequency Sample location Biogas volume Daily AD headspace of each digester* Biogas percentage composition Twice a week AD headspace of each digester pH Thrice a week Influent and effluent of each digester TS Once a week Influent and effluent of each digester VS Once a week Influent and effluent of each digester Total COD Once a week Influent and effluent of each digester Total ammonium nitrogen Once a week Influent and effluent of each digester Alkalinity Once a week Influent and effluent of each digester VFA (acetic, propionic, and butyric acid) Once a week Influent and effluent of each digester Fluorescence microscopy Before bioaugmentation The effluent of each digester TS: total solids, VS: volatile solids, COD: Chemical oxygen demand, VFA: volatile fatty acids, AD: anaerobic digestion. Influent is the substrate, and effluent is from digester wasting, *each digester includes SEED digester, Test digester, and Control digesters. 133 5.3 Results and discussion 5.3.1 Performance of SEED, Test and Control reactors Figure 5.3 demonstrates the performance of the SEED reactor, as the HRT was gradually reduced from 20 to 5 days over 50 weeks. Initially, the HRT was reduced to 16 days and increased organic loading improved the specific biogas yield per COD added. However, further shortening of HRT caused initial fluctuation in specific biogas production. However, at an HRT of 5 days, the SEED reactor stabilized and continued to deliver methane yield equivalent to the theoretical methane yield (0.35 L/g COD degraded at STP of 0oC, 1 atm). The average specific biogas production for the SEED reactor was 478 ml/g COD added. As previously discussed, the SEED reactor was fed intermittently with effluent biomass centrifuged/recycled to allow slow-growing methanogens to proliferate and attach onto A-CC. The average methane content in the SEED reactor was 74%, which was the highest among all the reactors. This high methane content also suggests the presence of methanogen-rich cultures in the SEED reactor. 134 Figure 5.3. Specific biogas production for SEED reactor at varying hydraulic retention times (HRT) [SEED: syntrophic enrichment for enhanced digestion, AP: Acid phase reactor, COD: Chemical oxygen demand] Table 5.4 presents the physiochemical parameters of the SEED, Test, and Control reactors before and after bioaugmentation. Prior to bioaugmentation, the Test and Control reactors had similar characteristics and performances (66-67% VS and COD removals, 63% methane in reactor headspace, 373-383 ml biogas/COD added at HRT of 20 d). These results are typical for thermophilic digesters utilizing mixed sludge at HRT of 20 d. The SEED reactor had a slightly alkaline pH (7.6) which is favorable for the growth of methane-producing microorganisms with a COD reduction above 88% which was the highest among all reactors. This was expected as SEED reactor received acidified, VFA-rich, readily biodegradable soluble substrate while Test and Control digesters received slowly biodegradable mixed sludge. The recycling of biomass in SEED effluent back to the reactor had an impact on the calculation of TS and VS removal, making it difficult to observe a clear pattern in the SEED reactor and therefore, the VS and TS removal in the SEED reactor were not presented. 135 Table 5.4. Physiochemical characterization of SEED, Test and Control reactors Parameters Test Control SEED SRT 20 days (No bioaugmentation) Bioaugmentation (HRT 20 days) Bioaugmentation (HRT 10 days) SRT 20 days SRT 10 days AP reactor % CH4 63 (1; 27) * 65 (2; 15) 65 (1; 12) 63 (1; 28) 63 (1; 6) 74 (1.22; 54) NA pH 7.8 (0.1; 47) 7.6 (0.1; 51) 7.6 (0.1; 13) 7.8 (0.1; 60) 7.7 (0.1; 8) 7.6 (0.1; 30) NA Total ammonium nitrogen (mg/l) 1379 (229; 12) 1401 (100; 14) 1499 (199; 10) 1467 (203; 20) 1500 (303; 8) 1083 (0.09; 34) 915 (24; 60) Total COD removal (%) 67 (1; 12) 74 (2; 14) 70 (1; 10) 66 (1; 20) 64 (1; 8) 88 (2.9; 34) NA TS removal (%) 58 (1; 12) 57 (2; 16) 56 (2; 8) 58 (1; 20) 58 (2; 8) NA NA VS removal (%) 68 (0.3; 12) 64 (1; 16) 63 (1; 8) 67 (1; 20) 66 (2; 8) NA NA Total alkalinity (mg/l) 4905 (198; 12) 4395 (300; 14) 3985 (298; 10) 5189 (199; 20) 3889 (204; 8) 3566 (99; 34) 1450 (42; 20) VFA (mg/l) <100 <100 <100 <100 <100 <100 4020 (66; 33) VFA/Alkalinity ratio (-) ~0.02 ~0.02 ~0.02 ~0.02 ~0.02 ~0.02 NA Average specific biogas (ml/g CODadded) 373 (23; 90) 508 (71; 81) 576 (88; 95) 383 (43; 137) 306 (37; 103) 478(58, 53) NA *Data represent arithmetic mean of measurements (standard deviation; number of samples), SEED: Syntrophic enrichment for enhanced digestion, SRT: Solid retention time, HRT: Hydraulic retention time, VFA: volatile fatty acids, TS: Total solids, VS: Volatile solids, COD: Chemical oxygen demand, NA: not analyzed 136 Figure 5.4 illustrates the impact of bioaugmentation on daily specific biogas production of the Test reactor with respect to Control digester. At 20-d HRT, prior to bioaugmentation, both the Test and Control reactors were monitored for 30 days to ensure similar reactor performance. The initial LBs were conducted on the 92nd, 100th, and 107th days, with 7-day intervals between each bioaugmentation, with 30% volume of the Test digester replaced with effluent carrying microbial cultures from the SEED reactor (Figure 5.4 and Table 5.5). LB resulted in process fluctuations in the Test digester due to significant volume (30%) of biomass that had to be withdrawn/replaced for each bioaugmentation cycle. Performance parameters, such as daily biogas volume, headspace methane content and COD removal of the Test digester, started to decline drastically. The total COD of the Test reactor effluent decreased by over 10,000 mg/l compared to that of the Control reactor. 137 Figure 5.4. Impact of bioaugmentation on specific biogas production of Test versus Control (LB: liquid bioaugmentation, PB: pellet bioaugmentation, COD: Chemical oxygen demand) 138 After three bioaugmentations (LB-1, LB-2 and LB-3), the LB strategy was immediately discontinued to prevent operational failure in the Test reactor (Figure 5.4). Regular monitoring of performance parameters (COD, biogas volume, and methane percentage) were continued for the Test reactor to compare its operational parameters to those of the Control reactor. Once the Test and Control reactors achieved similar baseline operational parameters again, the PB strategy was initiated (Figure 5.4 and Table 5.5). The PB positively impacted Test reactor performance and was used for the subsequent bioaugmentations. As mentioned earlier, the main goal with PB was to transfer a dense population of active microbial biomass in a small volume. Hence, the COD of the centrifuged pellets from the SEED effluent was chosen as a critical performance parameter to determine the frequency of bioaugmentation. From reactor monitoring, it was established that the COD of pellet obtained from SEED effluent above 3,500 mg/L accumulates enough biomass concentration equivalent to 1-2% of the Test reactor volume. Even after the first PB (PB-1), Figure 5.4 illustrated an overall increase in specific biogas yield in the Test reactor. Table 5.5 presents calculations for biogas increment expected from pellet COD transfer from SEED to Test reactor, based on theoretical methane yield of 0.35 L/g COD degraded at STP of 0oC, 1 atm and assumed 70% COD removal. It was essential to offset (subtract) theoretical biogas production from COD of pellet biomass transferred, which reflects the pellet COD being used as additional substrate to mixed sludge, rather than acting as bioaugmented biomass consuming substrate (mixed sludge) fed to Test reactor. To achieve this, the COD of the SEED effluent was measured before and after centrifugation (3500 rpm, 20 min), and the difference between the SEED effluent and centrifuged filtrate provided the COD of pellet biomass transferred during bioaugmentation. 139 The frequency of bioaugmentation varied depending on the SEED reactor effluent pellet concentration. For example, between two bioaugmentations, it took over 7 days for the SEED reactor to reach content of COD >3500 mg/l, corresponding to 1% of the Test reactor volume. The PB strategy positively impacted overall Test reactor performance, as shown in Figure 5.4, with improved COD reduction, higher methane volume, and methane percentages. Additionally, PB helped to maintain stable operation at shorter HRTs (10 days). The Test reactor showed significant improvements (p<0.0001, statistical calculations table available in Appendix 1 Section A3) in specific biogas production, with an increase of 33% and 88% at HRTs of 20 days and 10 days, respectively, compared to the Control reactor, highlighting the impact of enhanced microbial activity on biogas production as a result of bioaugmentation, with a 2% increase in the reactor headspace methane percentage. Results also indicate that bioaugmentation of the Test reactor using active microbial consortia from the SEED reactor increased the COD removal to 74% compared to the Control reactor with a COD removal rate of 66% (Table 5.5). However, it was also observed that the VS removal rate in the Test reactor was reduced by 3% compared to the Control reactor. This could be attributed to the addition of bio-augmented biomass pellets from the SEED reactor, which changed VS content between Test and Control digesters. Furthermore, the alkalinity/VFA ratio in Test Control and SEED reactors remained around 0.02, indicating stable anaerobic digestion operating conditions. 140 Table 5.5. Impact of bioaugmentation on methane increment at varying hydraulic retention time (HRT) Bioaugmentation Transferred COD from SEED to Test (mg) Volume transferred from SEED to Test (ml) Theoretical biogas produced from transferred COD (ml) % Volume of Test reactor replaced Surplus biogas produced after bioaugmentation (ml) [in days] Biogas increment from bioaugmentation [–theoretical biogas from transferred pellets (COD basis)) (ml) Biogas increment from bioaugmentation (% per day) bioaugmentation 1 [LB (I)] 8578 1500 ml (liquid SEED Effluent) 4765 30% 3558.65 [in 7 days] -1206 -0.55 bioaugmentation 1 [LB (II)] 8070 1500 ml (liquid SEED Effluent) 4483 30% 4779 [in 7 days] 296 0.11 bioaugmentation 1 [LB (III)] 7620 1500 ml (liquid SEED Effluent) 4033 30% 6100 [in 7 days] 2067 0.84 bioaugmentation 2 [PB-1 (I)] 8561 2000 ml centrifuged (82 g) SEED pellets 3277 1.6% 16,942 [in 9 days] 13,665 3.42 bioaugmentation 2 [PB-1 (II)] 7302 2000 ml centrifuged (68 g) SEED pellets 2795 1.4% 12,636 [in 7 days] 9,841 3.68 bioaugmentation 2 [PB-1 (III)] 7260 2000 ml centrifuged (67 g) SEED pellets 2779 1.4% 20,226 [in 15 days] 16,663 1.30 bioaugmentation 2 [PB-1 (IV)] 6346 2333 ml centrifuged (40 g) SEED pellets 2429 0.7% 27,713 [in 16 days] 25,284 1.98 bioaugmentation 2 [PB-1 (V)] 5464 2333 ml centrifuged (34 g) SEED pellets 2091 0.7% 26,031 [in 12 days] 23,940 2.53 bioaugmentation 2 [PB-1 (VI)] 4715 2333 ml centrifuged (33 g) SEED pellets 1805 0.7% 57,733 [in 21 days] 55,928 2.71 141 Bioaugmentation Transferred COD from SEED to Test (mg) Volume transferred from SEED to Test (ml) Theoretical biogas produced from transferred COD (ml) % Volume of Test reactor replaced Surplus biogas produced after bioaugmentation (ml) [in days] Biogas increment from bioaugmentation [–theoretical biogas from transferred pellets (COD basis)) (ml) Biogas increment from bioaugmentation (% per day) bioaugmentation 3 [PB-2 (I)] 11,283 2000 ml centrifuged (88 g) SEED pellets 4319 2.5% 11,515 [in 7 days] 8,216 1.77 bioaugmentation 3 [PB-2 (II)] 8618 2000 ml centrifuged (72 g) SEED pellets 3299 2.1% 11,125 [in 7 days] 21,394 1.87 bioaugmentation 3 [PB-2 (III)] 7339 2000 ml centrifuged (60 g) SEED pellets 2809 1.7% 23,929 [in 7 days] 21,120 5.39 bioaugmentation 3 [PB-2 (IV)] 6636 2000 ml centrifuged (36 g) SEED pellets 2540 1% 23,794 [in 7 days] 21,254 5.30 bioaugmentation 3 [PB-2 (V)] 4534 1400 ml centrifuged (34 g) SEED pellets 1735 1% 24,425 [in 7 days] 22,690 5.64 bioaugmentation 3 [PB-2 (VI)] 3694 1400 ml centrifuged (34 g) SEED pellets 905 1% 30,736 [in 7 days] 29,831 8.64 bioaugmentation 3 [PB-2 (VII)] 3654 1200 ml centrifuged (36 g) SEED pellets 1399 1% 47,054 [in 17 days] 58,941 2.39 bioaugmentation 3 [PB-2 (VIII)] 3414 1200 ml centrifuged (36 g) SEED pellets 1306 1% 30,499 [in 9 days] 29,193 5.18 PB: Pellet bioaugmentation, LB: Liquid bioaugmentation, COD: Chemical oxygen demand, SEED: Syntrophic enrichment for enhanced digestion142 5.3.2 Fluorescent microscopy for microbial biofilm analysis Figure 5.5 illustrates the development of biofilm on the surface of A-CC. To enhance the visualization of microbial cells and extracellular matrix, a combination of two stains was used. DAPI was used to stain the active nuclei of microbial cells, while the FilmTracer™ SYPRO® Ruby biofilm dye was used to penetrate the biofilm matrix and stain various components, including polysaccharides, amino acids, and other loosely attached extracellular polymeric matrix, as per the user manual. The bright field and fluorescent images obtained provide a clear view of the biofilm development around the A-CC. The carbon cloth surface appears to be biocompatible, attracting microorganisms, as evidenced by the microbial community structure observed. These observations indicate a higher probability of microbial immobilization of active syntrophic microbes and methanogens in the SEED reactor but require supplementary information from genomics analysis to confirm. Figure 5.5. Microscopy images of activated carbon cloth from SEED reactor (at COD of ~3,500 rpm, 20 min) (a. and c.) bright field images and (b. and d.) flourscent images with FilmTracer™ SYPRO® Ruby biofilm and DAPI (4′,6-diamidino-2-phenylindole) cell staining 143 5.4 Summary The results of this chapter validate Hypothesis III, which stated that a side-stream anaerobic reactor with a surface-modified carbon cloth can serve as an incubator reservoir system for a dense population of active microbes to improve digestion, increase stability, and upgrade biogas quality in a bio-augmented main-stream anaerobic digester treating municipal sludge. The developed thermophilic SEED system with A-CC is a novel incubator system rich in syntrophic bacteria and archaea that can be utilized to bio-augment conventional anaerobic sludge digesters. The pellet bioaugmentation (PB) method developed enables active microbial biomass to be transferred to anaerobic digestion at a shorter HRT, reducing the size of the reactor required to process a significant amount of waste. The A-CC’s synergistic interaction with syntrophic cultures in the SEED incubator reactor enhances microbial symbiosis and can be applied to any existing digester system as a lateral flow retrofit model without modifying the current infrastructure. These results have important implications for the development of sustainable waste management systems. 144 Chapter 6. Conclusions 6.1 Overall summary and conclusions Anaerobic digestion (AD) has been established as a viable technology for the treatment of organic pollutants and pathogenic microorganisms, as well as the generation of renewable energy in the form of biogas. Despite this, there are numerous challenges that impede the efficient application of AD to municipal sludge. In addition, there is a significant lack of knowledge regarding the improvement of robustness in industrial-scale AD systems. The current study addressed these issues through the development of an integrated support system for wastewater utilities, with a focus on the bottleneck of microbial syntrophy in existing AD plants. Three main research questions guided this study were: i. Is it possible to design a biocompatible surface that can retain syntrophic bacteria and methanogens, promoting microbial attachment and reducing microbial loss due to washout from effluent? ii. Can a microbial reservoir ecosystem be developed to continually supply active microbial culture to existing AD plants, serving as a sustainable side-stream compact reservoir system, to enhance microbial activity and methane production utilizing municipal sludge? iii. Is it feasible to develop an effective bioaugmentation strategy for existing AD plants that requires minimal operational changes on an industrial scale? The following conclusions were drawn from the research presented in the preceding chapters: • A literature review suggests that among commonly used conductive carbon materials, carbon cloth showed superior performance in terms of COD removal. 145 The conductive properties of carbon cloth also promote microbial adhesion and improve AD. Additionally, carbon cloth appears to be advantageous as it can be retained in the reactor without washout loss. • The two-step activation (acid pretreatment (H2SO4/HNO3) followed by air calcination at 525 ± 25℃) of commercial untreated carbon cloth improves its available surface area and biocarrier potential by adding oxygen doping. The resulting biocompatible activated carbon cloth surface enhances microbial attachment and methane production rate. • Optimizing A-CC dosing is crucial for increasing methane yield. Dosages above 1.48 g A-CC/g-VSsubstrate obstructed mixing and mass transfer in batch reactors obtained from BMP experimentation. • Incorporating metal-impregnated carbon cloth composites (i.e., Fe/CC, Ni/CC, Ni/Fe/CC, NiPcS/Fe/CC) with a variable surface area and electrical conductivity (EC) helps to understand the individual impact of surface area and EC for methane rate and extent increment in AD. Using hydrothermal synthesis, the BET surface area and the EC of carbon cloth were modified by incorporating biocompatible metal precursors (such as Ni and Fe) mentioned in the literature. Although the metal impregnation improved the EC of the carbon cloth, the architecture of deposited metallic composite blocked the available pores of the carbon cloth, which reduced the accessible surface area for microbial attachment. The methane enhancement for all carbon cloth materials follows a similar trend where the AD enhancement is directly proportional to the available BET surface. • The thermophilic SEED system with activated carbon cloth is a novel incubator that can be utilized to bio-augment conventional anaerobic sludge digesters. The pellet 146 bioaugmentation developed in current study, allows active microbial biomass to be transferred to AD at a shorter-HRT, thereby reducing the size of the AD needed to process a large amount of waste. • The synergistic interaction of activated caron cloth with syntrophic cultures in the SEED incubator reactor enhances microbial symbiosis and can be implemented for any existing AD system as a lateral flow retrofit model without modifying the existing infrastructure. This work addresses and incorporates the bottleneck of AD problems by incorporating bioaugmentation into the existing systems. 6.2 Limitation and future recommendation The following areas of research were not pursued in the current study due to limitations in time and resources, however, are recommended for future investigation. • A reliable method for visualizing and quantifying microbial attachment on conductive material surface must be developed in order to determine bioaugmentation frequency. This can be done by developing microscopy-based techniques to quickly assess the health and performance of the SEED reactor. This would also facilitate accurate determination of the SRT in the SEED reactor. • Exploration of the potential benefits of supplementing H2 to existing AD of municipal sludge systems, in order to better utilize hydrogenotrophic methanogens, in order to improve methane production. 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Supramolecular Self-assembly of Transition Metal Carbonyl Molecules Through M–CO(Lone Pair)…π(Arene) Interactions. Advances in Organometallic Chemistry Volume 60. https://doi.org/10.1016/b978-0-12-396970-5.00002-5 169 Appendices Appendix 1 Section A1: Batch-1 supplementary data: Effects of individual synthesis steps of AD performance The individual batch BMPs bottles were set up with CC[H2SO4], CC[H2SO4; HNO3] and U-CC[550°C] respectively at a dose of 0.60 g carbon cloth (1.11 g carbon cloth/g-VSsubstrate) to compare and finalize the contribution of each activation step on rate and extent of methane improvement. The specific cumulative methane yield, VFA and pH profiles results from batch-1 setup are shown in Figure. A1. Figure. A1a. showed that each activation step has some individual pattern on improving the catalytic performance of carbon cloth. The specific cumulative methane at day 8 for CC [H2SO4], CC [H2SO4; HNO3], U-CC@550°C and A-CC were 1.23, 1.76, 2.46 and 2.22, respectively. The acid pretreatment induces the oxidation of U-CC and enriches the U-CC surface with oxygen-containing function groups (Kordek et al., 2019), which partially helps to improve the rate and extent of methane production. The VFA production (Figure A1 b-e) and specific cumulative methane graphs follow similar trends. It can clearly be seen that air calcination has a significant impact on carbon cloth activation. U-CC shows inhibition to the overall methane yields due to the accumulation of propionic acid in the reactors. However, two-step activation has an additional advantage in terms of the degradation of propionic acid over U-CC. In addition, a drop in pH is an indication of higher production of VFA. However, the rapid recovery from the drop in pH (as in A-CC) is an indication of higher syntrophic microbial activities. From the BMP assay results obtained from Batch 1 experiments, Batch-2 170 experiments were conducted to optimize carbon cloth dosage. The VFA production (Appendix 1 Section A2 Figure A4) and specific cumulative methane graphs follow similar trends during Batch-2 experiments. The accumulation and conversion of VFA over time can be used to assess the activity of fermentative microorganisms in batch AD. For example, accumulation of propionic acid, even at low concentration, is associated with the inhibition of methane production. Two-step activation appeared to promote removal of propionic acid over U-CC. In addition, a drop in pH is an indication of higher production of VFA. The rapid recovery from the drop in pH is an indication that microbial interactions driving methane production are robust to perturbation in the A-CC bottles. 171 Figure A1. Effects of each step of carbon cloth activation on (a) rate and extent of methane production in terms of specific cumulative methane production, (b-e) volatile fatty acids (VFA) and (f) pH during thermophilic BMP experiments (Batch-1). Total VFA comprise acetic, propionic, and butyric acids. Data represents average and error bars represent standard deviations of triplicates. 172 Effects of individual synthesis steps of AD performance The individual batch BMPs bottles were set up with CC[H2SO4], CC[H2SO4; HNO3] and U-CC[550°C] respectively at a dose of 0.60 g carbon cloth (1.11 g carbon cloth/g-VSsubstrate) to compare and finalize the contribution of each activation step on rate and extent of methane improvement. The specific cumulative methane yield, VFA and pH profiles results from batch-1 setup are shown in Fig. A1. As shown in Fig. A1a. that each activation step has some individual pattern on improving the catalytic performance of carbon cloth. The specific cumulative methane at day 8 for CC [H2SO4], CC [H2SO4; HNO3], U-CC@550°C and A-CC were 1.23, 1.76, 2.46 and 2.22, respectively. The acid pretreatment induces the oxidation of U-CC and enriches the U-CC surface with oxygen-containing function groups (Kordek et al., 2019), which partially helps to improve the rate and extent of methane production. The VFA production (Figure. A2 b-e) and specific cumulative methane graphs follow similar trends. It can clearly be seen that air calcination has a significant impact on carbon cloth activation. U-CC shows inhibition to the overall methane yields due to the accumulation of propionic acid in the reactors. However, two-step activation has an additional advantage in terms of the degradation of propionic acid over U-CC. In addition, a drop in pH is an indication of higher production of VFA. However, the rapid recovery from the drop in pH (as in A-CC) is an indication of higher syntrophic microbial activities. From the BMP assay results obtained from Batch 1 experiments, Batch-2 experiments were conducted to optimize carbon cloth dosage. The VFA production (Appendix 1 Section A2) and specific cumulative methane graphs follow similar trends during Batch-2 experiments. The accumulation and conversion of VFA over time can be used to assess the activity of fermentative microorganisms in batch AD. For 173 example, accumulation of propionic acid, even at low concentration, is associated with the inhibition of methane production. Two-step activation appeared to promote removal of propionic acid over U-CC. In addition, a drop in pH is an indication of higher production of VFA. The rapid recovery from the drop in pH is an indication that microbial interactions driving methane production are robust to perturbation in the A-CC bottles. 174 Figure A2 Effects of each step of carbon cloth activation on (a) rate and extent of methane production in terms of specific cumulative methane production, (b-e) volatile fatty acids (VFA) and (f) pH during thermophilic BMP experiments (Batch-1). Total VFA comprise acetic, propionic, and butyric acids. Data represents average and error bars represent standard deviations of triplicates. Note: The BMP bottle results in Batch-3 experiments in Chapter 3 were designed to evaluate microbial community structure associated with U-CC and A-CC addition in relation to methane production published as a journal article (Kumar et al., 2022). The experimental design was changed with the removal of specific carbon cloth doses. For example, 1.2 g of carbon cloth not included in Batch-3 due to mass transfer limitations. For the most part A-CC BMPs in Batch-3 exhibited similar activities to Batch-2 experiments. 175 Section A2 Batch-2 and Batch-3 supplementary data: Figure A3 Effect of carbon cloth dosing on rate and extent of methane production in terms of specific cumulative (a-b) and specific daily (c-d) methane production (Batch-3). U-CC: untreated carbon cloth, A-CC: acid treated carbon cloth. Data represents average and error bars represent standard deviations of triplicates.176 Figure A4. Effect of untreated carbon cloth (U-CC) and activated carbon cloth (A-CC) addition on total VFAs and pH during thermophilic BMP experiments (Batch-2). Total VFA comprise acetic, propionic, and butyric acids. Data represents average and error bars represent standard deviations of triplicates. 177 Figure A5. Microscopy images of activated carbon cloth after 30 days of bioreactor incubation by unfiltered light micrograph (A, B) and 461nm-filtered light micrograph for DAPI (4′,6-diamidino-2-phenylindole) cell staining (C). Panel A shows a material film formed around the carbon cloth under medium magnification. Panels B and C are overlays of one another under higher magnification; B shows biofilm material and C shows cells attached to the carbon cloth. 178 Section A3: Analytical method Figure A6. Chemical oxygen demand (COD) calibration curve. Figure A7. Ammonia calibration curve R² = 0.9867y = 2.3224x - 8.030701002003004005006007000 50 100 150 200 250 300Concentration (mg/l)Absorbance (nm)y = 1E-06x2 + 0.0051x + 0.0628R² = 0.99980123456780 200 400 600 800 1000 1200Concentration (mg/l)Absorbance (nm)179 Table A3.1 Statistical analysis for samples with dosage of 0.20-0.80 g U-CC/A-CC using t-Test Rm (U-CC) Rm (A-CC) Mean 20.335 33.9175 Variance 71.83457 7.3896917 Observations 4 4 Pearson Correlation 0.814953 Hypothesized Mean Difference 0 df 3 t Stat -4.20814 P(T<=t) one-tail 0.012253 t Critical one-tail 2.353363 P(T<=t) two-tail 0.024506 t Critical two-tail 3.182446 Table A3.2 Statistical analysis for samples (Rm) with dosage of 1 g and 1.2 U-CC/A-CC using t-Test Rm (U-CC) Rm (A-CC) Mean 41.6 37.495 Variance 1.5842 0.91125 Observations 2 2 Pearson Correlation -1 Hypothesized Mean Difference 0 df 1 t Stat 2.623003 P(T<=t) one-tail 0.115939 t Critical one-tail 6.313752 P(T<=t) two-tail 0.231877 t Critical two-tail 12.7062 Table A3.3 Statistical analysis for samples (λ) with dosage of 0.2 g and 1.2 U-CC/A-CC using t-Test λ (U-CC) λ (A-CC) Mean 5.123333 1.8066667 Variance 11.50007 1.2689067 Observations 6 6 Pearson Correlation 0.933288 Hypothesized Mean Difference 0 df 5 t Stat 3.421297 P(T<=t) one-tail 0.009406 t Critical one-tail 2.015048 P(T<=t) two-tail 0.018812 t Critical two-tail 2.570582 180 Table A3.4 Statistical analysis for daily biogas production for Test and Control reactor samples using t-Test Control reactor Test reactor Mean 380.962 512.4865 Variance 4211.099 9437.536 Observations 242 242 Pearson Correlation -0.39992 Hypothesized Mean Difference 0 df 241 t Stat -14.9657 P(T<=t) one-tail 1.49E-36 t Critical one-tail 1.651201 P(T<=t) two-tail 2.99E-36 t Critical two-tail 1.969856 181 Section A4: Standard operating procedure (SOP) used to handle for safe handling/working with the NH4F • All operations involving concentrated HF were performed in a fully functioning chemical fume hood. • A secondary containment liner was used in the fume hood for chemical and equipment, to contain the potential spill. • The laboratory worker used all personal protective equipment (particularly double nitrile gloves) specified. • Hands must wash immediately after removing gloves. • No work with concentrated HF was performed alone. A second person aware of the dangers and emergency procedures for handling HF contact was present at all times within the laboratory while the operations with concentrated HF was carried out. • For unattended operations, warning signs were posted in the laboratory. • Detailed hazard assessment was performed of all the steps, with proper control measures for decontamination neutralization procedure for equipment, and tools. • Decontamination was performed in the fume hood with a detailed disposal procedure in place. • NH4F stock solution was always stored in the refrigerator. • NH4F waste was kept in separate plastic bottles (not in glass bottles). • Since HF can be used to etch metals, all used vessels and laboratory equipment were cleaned, with proper care to avoid using metallic items while working with HF. • Calcium gluconate (2.5%) cream was also added to the First Aid kit. 182 • If any exposure is made, calcium gluconate gel must be applied to the affected area immediately. • The cream was applied even if the NH4F solution is only spilled onto the gloves (i.e., even if it does not touch your skin directly). • Lime soda, ash, sodium bicarbonate, or a spill absorbent specified for HF was used for cleanup. Organic spill kits that contain Floor-dri, kitty litter, or sand will not be used because HF reacts with silica to produce silicon tetrafluoride, a toxic gas. • Warning signs were always posted on the chemical hood and laboratory door until the HF had been returned to storage. 183 Section A5: Experimental setup to measure the Electrical conductivity (EC) of carbon cloth A standard four-probe measurement was used to determine the resistance R of individual carbon fibers. The resistance was measured over a short section of each fiber’s total length. The measured fibers were then photographed under a calibrated optical microscope and the images were analyzed to determine their diameter d, and hence, cross-sectional area (𝐴 = 𝜋𝑑2/4). Finally, the DC electrical conductivity of the measured fibers was calculated from Eq. (A1) 𝜎 = 𝑅−1ℓ/𝐴 𝐸𝑞. (𝐴1) where ℓ is the length of the section of fiber measured. Figure A8a shows an example ribbon of carbon fibers removed from a carbon cloth sample. Individual fibers were extracted from the ribbon using fine tweezers. The individual fibers were 10 μm (b) 6.43 μm (c) (a) (f ) (e) single carbon fiber (d) 𝐼+ 𝑉+ 𝐼− 𝑉− Figure A8. a. A ribbon of carbon fibers extracted from a woven carbon cloth, b. Photograph of the microscope calibration slide. Each division marked on the slide is 10 m wide, c. Photograph of a single carbon fiber using the same magnification used in (b), d. The sample holder and electrodes used to make the four-probe resistance measurements. The electrodes are made from copper-foil tape, e. Photograph of a single carbon fiber sandwiched between two glass slides while lying perpendicularly across the four copper electrodes. Under this magnification, the fiber is difficult to resolve, f. Same as (e), but at a higher magnification. 184 photographed using a ×2500-magnification optical microscope equipped with a digital camera. As shown in Figure A8b, a calibration image was first recorded in order to establish a known length that was used to calibrate distances in subsequent images of individual fibers. Each division of the calibration slide was 10 μm. Figure A8c shows an example photograph of an untreated carbon fiber with a diameter of 𝑑 = 6.43 μm. Four-probe resistance measurements were made using a Keysight 34401A digital multimeter. To make electrical contact to the fibers, a simple, but effective, sample holder was constructed using glass microscope slides and copper-foil tape (90 μm thick). Four thin strips of copper tape were cut from the foil and wrapped around a glass slide, as shown in Figure A8d. Electrical leads were soldered to strips which facilitated connections to the multimeter. The two outside contacts were connected to a current source supplying current 𝐼 and the resulting voltage drop ∆𝑉 was measured across the pair of inner contacts. The distance l≈2.7 mm between the inner contacts determines the length over which the resistance (R) (Eq. (A2) was measured. 𝑅 =∆𝑉𝐼 𝐸𝑞. (𝐴2) Carbon fiber was first laid perpendicularly across the four contacts. Next, a second glass slide (with no electrical contacts) was placed on top of the first with the carbon fiber sample sandwiched between the pair. Electrical tape or elastic bands were used to apply light pressure between the plates in order to establish good electrical contact between the fiber sample and the copper-foil contacts on the bottom slide, allowing for reliable resistance measurements. For each type of carbon cloth 185 studied, 𝑁 individual fibers were measured using the methods described above, where 𝑁 ≈ 20 was typical. In Table 4.2 (Chapter 4, Section 4.3.1), the electrical conductivities and diameters reported are the averages obtained from each set of 𝑁 measurements.
Thesis/Dissertation
eng
Civil Engineering
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Eskicioglu, Cigdem
Evaluation of various carbon cloth as biomass support media for bioaugmentation of anaerobic digestion of municipal sludge
Text