STIMULATORY EFFECT OF VERMICOMPOST ON THE ANAEROBIC DIGESTION OF CAFETERIA FOOD WASTE By WEI WU-HAAN A DISSERTATION Submitted to Michigan State University in partial fulfilment of the requirements for the degree of Biosystems Engineering-Doctor of Philosophy 2013 ABSTRACT STIMULATORY EFFECT OF VERMICOMPOST ON THE ANAEROBIC DIGESTION OF CAFETERIA FOOD WASTE By WEI WU-HAAN The overall objectives of this study were to evaluate the effectiveness of utilizing manure vermicompost as an additive to enhance anaerobic digestion of post-consumer cafeteria food waste in a single-stage digestion system and investigate the mechanisms associated with such enhancement. Vermicompost was chosen because of its buffering capacity, abundance of humic substance, and variety of trace metals, all of which may enhance the digestion process. The experiment was first conducted using a batch-scale biochemical methane potential assay and found that manure vermicompost added to the food waste reactors at concentrations of 2 g/L and 6 g/L both significantly increased ultimate methane yield and methane production rate. Then, a long-term study was conducted using twelve semi-continuous single-stage reactors to confirm such enhancement and further investigate the associated mechanism. The specific methanogenic activity and trace metal (iron, nickel, and cobalt) bioavailability were also evaluated. Results showed that the food waste digester without any supplement (control) had unstable and low methane production (254 mL/g VS added/day and 455 mL/g VS destroyed/day). During the experimental period, the control reactor experienced a dramatic reduction in pH (less than 6) due to a significant accumulation of volatile fatty acids (more than 2,600 mg/L). The trace metal bioavailability tests further demonstrated that the control digester could be deficient in nickel and iron. In contrast, the food waste digesters supplemented with manure vermicompost (2 g/L), trace metals (a mixture of 0.01 mg/L nickel, 0.5 mg/L Fe, and 0.01 mg/L Co) or humic acids (0.4 g/L) all had stable and significantly greater methane production compared to the control. The pH was approximately 7 and volatile fatty acids were less than 200 mg/L. Among all treatments, the food waste digesters supplemented with manure vermicompost had the greatest methane production (625 mL/g VS destroyed/day). In comparison to the control, supplementation of manure vermicompost also nearly doubled the acetate utilization rate and enhanced the propionate utilization rate by 60%. It was found that such enhanced digestion performance was likely related to the trace metals (particularly iron and nickel) provided by the vermicompost. Humic acids, naturally presented in mature vermicompost, also contributed to the enhanced performance of food waste digestion. In summary, manure vermicompost (without any additional chemical amendments) stabilized and increased methane production from anaerobic digestion of food waste in the single-stage digestion system. ACKNOWLEDGEMENTS I would like to express my deep and sincere gratitude to my supervisor, Dr. Steve Safferman, not only for his invaluable guidance, and suggestions but also for his support and efforts while I was trying to find a route for my research. I also would like to thank my committee members Dr. Wei Liao, Dr. Susie Liu, and Dr. David K. Beede for their direction and guidance on my research. A special thanks to Dr. John Biernbaum for helping me with vermicomposting. I am particularly grateful to my co-workers for keeping up my spirit and especially my colleague Harun Armagan for his great support on the project. Finally, words alone cannot express the thanks I owe to my parents for their trust in me and encouraging me in what I choose, and who have always been exceptional and loving to me. Thank you to my wonderful husband, Mathew Haan, for being patient and supportive. Most important thanks here go to my daughter Maggie who shared her Mommy’s attention and energy with this dissertation since she was born. She is the best kid in the world! Maggie’s happy face and great personality allowed me to finish this degree. iv TABLE OF CONTENTS LIST OF TABLES ........................................................................................... ix LIST OF FIGURES ......................................................................................... xiv KEY TO ABBREVIATIONS ............................................................................ xvi CHAPTER 1 INTRODUCTION ........................................................................................... 1.1 Background .................................................................................... 1.2 Problem Statement ........................................................................ 1.3 Hypotheses .................................................................................... 1.4 Rationale........................................................................................ 1.5 Objectives ...................................................................................... 1 1 4 5 5 7 CHAPTER 2 LITERATURE REVIEW .................................................................................. 2.1 Overview of Anaerobic Digestion .................................................. 2.1.1 Historical Development and Present Status .................... 2.1.2 Principals of Anaerobic Digestion ................................... 2.1.3 Anaerobic Microorganisms .............................................. 2.1.3.1 Acetate-Forming Bacteria ................................. 2.1.3.2 Sulfate-Reducing Bacteria ................................ 2.1.3.3 Methanogens .................................................... 2.1.4 Optimization of Anaerobic Digestion................................ 2.1.4.1 pH and Alkalinity ............................................... 2.1.4.2 Temperature ..................................................... 2.1.4.3 Solid Retention Times ...................................... 2.1.4.4 Mixing .............................................................. 2.1.4.5 Organic Loading Rate ...................................... 2.1.4.6 Macronutrients ................................................. 2.1.4.7 Micronutrients .................................................. 2.1.4.8 Inhibition/Toxicity ............................................. 2.1.5 Anaerobic Biodegradability Assays .............................. 2.1.5.1 Overview .......................................................... 2.1.5.2 Batch and Continuous System ........................ 2.1.5.3 Biochemical Methane Potential Assay ............. 2.2 Trace Metals in Anaerobic Digesters ............................................ 2.2.1 Functions of Nickel, Iron and Cobalt ................................ 2.2.2 Requirements of Nickel, Iron and Cobalt ......................... 2.2.3 Bioavailability ................................................................... 2.3 The Use of Additives to Stimulate Anaerobic Digestion Process 2.3.1 Hydrolytic Enzyme .......................................................... 8 8 8 10 13 13 14 14 16 16 17 17 18 18 18 19 19 21 21 22 23 24 24 25 27 28 28 v 2.3.2 Trace Metal .................................................................... 2.3.3 Humic Substances .......................................................... 2.4 Anaerobic Digestion of Food Waste .............................................. 2.4.1 Characteristic and Methane Potential of Food Waste 2.4.2 Current Development and Issues ................................... 2.4.3 Case Studies .................................................................. 2.5 Vermicomposting ........................................................................... 2.5.1 Principles ........................................................................ 2.5.2 Vermicomposting vs. Traditional Composting ................ 2.5.3 Vermicompost as Additive in Anaerobic Digestion ......... 30 31 32 32 33 34 35 35 38 39 CHAPTER 3 USE OF BIOCHEMICAL METHANE POTENTIAL ASSAYS TO EVALUATE THE EFFECTS OF MANURE VERMICOMPOST ON ANAEROBIC DIGESTIBILITY OF FOOD WASTE ............................................................................................. 40 3.1 Introduction.................................................................................. 40 3.2 Material and Methods ................................................................. 40 3.2.1 Food Waste ..................................................................... 40 3.2.2 Dairy Manure Vermicompost .......................................... 43 3.2.3 Biochemical Methane Potential Assay ............................ 44 3.2.3.1 Experimental Design ........................................ 44 3.2.3.2 Inoculum and Vermicompost ............................ 45 3.2.3.3 Sample Preparation .......................................... 47 3.2.3.4 BMP Set Up ...................................................... 47 3.2.3.5 Biogas Production Measurement...................... 48 3.2.3.6 Methane Production Rate Constant Calculation 48 3.2.4 Analytical Methods .......................................................... 49 3.2.5 Statistic Methods ............................................................. 50 3.3 Results and Discussion ............................................................. 50 3.3.1 Characteristics of Cafeteria Food Waste ......................... 51 3.3.2 Estimated Biogas Production of Manure Vermicompost . 51 3.3.3 Volatile Solid Destruction ................................................ 53 3.3.4 Biogas and Methane Production from Food Waste ......... 53 3.3.5 Methane Content ............................................................. 58 3.3.6 pH Change ...................................................................... 58 3.4 Conclusions and Implication ....................................................... 59 CHAPTER 4 USE OF SINGLE-STAGE CONTINUOUS DIGESTION SYSTEM TO EVALUATE THE EFFECTS OF MANURE VERMICOMPOST ON ANAEROBIC DIGESTIBILITY OF FOOD WASTE ........................................................................................ 60 4.1 Introduction.................................................................................. 60 4.2 Material and Methods .................................................................. 60 4.2.1 Experimental Design ....................................................... 60 4.2.2 Food Waste and Manure Vermicompost ........................ 62 vi 4.3 4.4 4.2.3 Inoculum and Start-up ..................................................... 4.2.4 Experimental Setup and Biogas Measurement .............. 4.2.5 Digester Operation and Monitoring ................................. 4.2.6 Statistic Methods ........................................................... Results and Discussion .............................................................. 4.3.1 Biogas Production, VFA Concentration, and pH ............. 4.3.2 Biogas Composition and Methane Production Rate ....... 4.3.3 Trace Metal Analysis ....................................................... 4.3.4 Digester Effluent Measurement ....................................... 4.3.5 Specific Methane Production ........................................... Conclusions and Implication ........................................................ CHAPTER 5 EFFECTS OF VERMICOMPOST ON METHANOGENIC ACTIVITY DURING ANAEROBIC DIGESTION OF FOOD WASTE .............................................. 5.1 Introduction.................................................................................. 5.2 Material and Methods .................................................................. 5.2.1 Sampling and Experimental Design ................................ 5.2.2 Experimental Setup ........................................................ 5.2.3 Data Processing .............................................................. 5.3 Results and Discussion ............................................................... 5.3.1 Maximum Acetate Utilization Rate................................... 5.3.2 Maximum Propionate Utilization Rate ............................. 5.4 Conclusions and Implication ........................................................ 63 64 65 66 67 67 72 74 76 77 78 80 80 81 81 82 83 84 84 85 87 CHAPTER 6 ASSESSMENT OF BIOAVAILABILITY AND STIMULATION EFFECTS OF NICKEL, IRON AND COBALT ON ANAEROBIC DIGESTIONOF FOOD WASTE ....... 88 6.1 Introduction.................................................................................. 88 6.2 Material and Methods .................................................................. 88 6.2.1 Experimental Design and Setup ...................................... 88 6.2.2 Data Process and Interpretation ..................................... 89 6.3 Results and Discussion ............................................................... 90 6.3.1 Nickel Addition................................................................. 90 6.3.2 Iron Addition ................................................................... 91 6.3.3 Cobalt Addition ................................................................ 92 6.4 Conclusions ................................................................................ 93 CHAPTER 7 GENERAL CONCLUSIONS .................................................... 94 APPENDICES ................................................................................................ APPENDIX A: Biochemical Methane Potential Assays Data Summary APPENDIX B: Semi-Continuous Study Data Summary ....................... APPENDIX C: Methanogenic Activity Study Data Summary ................ APPENDIX D: Metal Bioavailability Study Data Summary ................... 100 101 106 138 149 vii BIBLIOGRAPHY ............................................................................................ viii 163 LIST OF TABLES Table 1.1 Structure of dissertation research .............................................. 7 Table 2.1 Trace metal stimulation of pure cultures of methanogens .......... 26 Table 2.2 Stimulation of biologic conversion in anaerobic digesters by trace metal supplementation ..................................................... 30 Table 2.3 Characteristic of reported cafeteria or restaurant food wastes ... 32 Table 2.4 Effect of earthworm activity on nutrients in organic waste .......... 37 Table 2.5 Comparison of trace element content in initial cattle manure and final cattle manure vermicompost ............................................... 37 Table 3.1 Experimental design of BMP Assay ........................................... 45 Table 3.2 Experimental design for determination of methane potential of manure vermicompost ............................................................... 46 Characteristics of food waste and comparison with literature report .......................................................................................... 51 Estimated biogas potential of manure vermicompost under various nutrient conditions .......................................................... 52 The ultimate biogas and methane productions of manure vermicompost ............................................................................. 52 Volatile solid content before (pre-digestion) and after 30 days of digestion (post-digestion) as well as total VS destroyed.............. 53 Table 3.7 Ultimate methane yields and methane production rate ............... 55 Table 3.8 pH change before and after digestion ........................................ 59 Table 4.1 Experimental design of semi-continuous study .......................... 61 Table 4.2 Characteristics of raw food waste ........................................... 63 Table 4.3 Characteristics of manure vermicompost ................................... 63 Table 4.4 Specific biogas production rate, total VFA concentrations, and pH during steady-state period .................................................... 69 Table 4.5 Average biogas compositions during the steady-state period ..... 73 Table 4.6 Digester effluent measurement during steady-state period ......... 77 Table 3.3 Table 3.4 Table 3.5 Table 3.6 ix Table 5.1 Experimental design of the methanogenic activity test ................ 82 Table 6.1 Experimental design of trace metal bioavailability trial ................ 88 Table A1.1 Characteristic of raw food waste ................................................ 102 Table A1.2 Characteristic of dairy manure vermicomposts .......................... 102 Table A1.3 pH change during the BMP assay .............................................. 102 Table A1.4 Ammonia-N change during the BMP assay (mg/kg) .................. 102 Table A1.5 COD change during digestion (g/kg) .......................................... 103 Table A1.6 Average weekly cumulative biogas yield (mL) ........................... 103 Table A1.7 Average specific biogas production rate (mL/g VS added) ........ 103 Table A1.8 Average methane content (%) ................................................... 103 Table A1.9 Average cumulative methane yield (mL) ................................... 104 Table A1.10 Average specific methane production rate (mL/g FW VS added) 104 Table A1.11 Normalized volatile solid reduction of food waste………………. 105 Table A2.1 Characteristics of raw food waste .............................................. 107 Table A2.2 Characteristics of dairy manure vermicompost .......................... 107 Table A2.3 Average influent pH of all reactors ............................................. 107 Table A2.4 Average effluent pH of all reactors ............................................. 108 Table A2.5 Average influent alkalinity of all reactors (mg/L as CaCO3) ....... 109 Table A2.6 Average effluent alkalinity of all reactors (mg/L as CaCO3) ....... 109 Table A2.7 Average influent total solid content of all reactors (g/L) ............. 110 Table A2.8 Average influent volatile solid content of all reactors (g/L) ......... 110 Table A2.9 Average effluent total solid content of all reactors (g/L) ............. 111 Table A2.10 Average effluent volatile solid content of all reactors (g/L) ....... 112 Table A2.11 Average volatile solid reduction during the steady-state period 113 Table A2.12 Average influent COD of all reactors (g/L) ............................... 113 x Table A2.13 Average effluent COD of all reactors (g/L) ............................... 114 Table A2.14 Average effluent ammonia-N of all reactors (mg/L) .................. 114 Table A2.15 Average influent TKN of all reactors (mg/L) ............................. 114 Table A2.16 Average effluent TKN of all reactors (mg/L) ............................ 115 Table A2.17 Average Influent total phosphorus of all reactors (mg/L) .......... 115 Table A2.18 Average effluent total phosphorus of all reactors (mg/L) .......... 116 Table A2.19 Average volatile fatty acids of all reactors (mg/L) ..................... 116 Table A2.20 Soluble Ni concentrations of food waste digesters with different additives .................................................................... 117 Table A2.21 Soluble Co concentrations of food waste digesters with different additives .................................................................... 117 Table A2.22 Soluble Fe concentration of food waste digesters with different additives .................................................................... 117 Table A2.23 Comparison of soluble metals concentration of food waste digesters with different additives .............................................. 117 Table A2.24 Daily biogas productions from food waste reactors.................. 118 Table A2.25 Daily biogas productions from trace elements supplemented reactors .................................................................................... 120 Table A2.26 Daily biogas productions from humic acids supplemented reactors .................................................................................... 122 Table A2.27 Daily biogas productions from vermicomposts supplemented reactors .................................................................................... 124 Table A2.28 Daily biogas productions from trace elements and humic acids supplemented reactors ................................................... 127 Table A2.29 Daily biogas productions from trace elements and vermicopmosts supplemented reactors ................................... 129 Table A2.30 Biogas composition of FW only reactors .................................. 132 Table A2.31 Biogas composition of trace elements supplemented reactors 133 Table A2.32 Biogas composition of humic acids supplemented reactors ..... 134 Table A2.33 Biogas composition of vermicomposts supplemented reactors 135 xi Table A2.34 Biogas composition of trace elements and humic acids supplemented reactors ............................................................. 136 Table A2.35 Biogas composition of trace elements and vermicomposts supplemented reactors ............................................................ 137 Table A3.1 Acetate utilization rates of food waste only (control) digesters... 139 Table A3.2 Acetate utilization rates of trace elements supplemented food waste digesters .......................................................................... 140 Table A3.3 Acetate utilization rates of humic acids supplemented food waste digesters .......................................................................... 141 Table A3.4 Acetate utilization rates of vermicomposts supplemented food waste digesters .......................................................................... 142 Table A3.5 Propionate utilization rates of food waste only digesters ........... 144 Table A3.6 Propionate utilization rates of trace elements supplemented food waste digesters .................................................................. 145 Table A3.7 Propionate utilization rates of humic acids supplemented food waste digesters .......................................................................... 146 Table A3.8 Propionate utilization rates of vermicomposts supplemented food waste digesters .................................................................. 147 Table A4.1 Cumulative methane production from acetate oxidation in the food waste digester .................................................................... 150 Table A4.2 Effect of 0.01mg/L Co on acetate utilization rate in the food waste digester ............................................................................ 151 Table A4.3 Effect of 1 mg/L Co on acetate utilization rate in the food waste digester....................................................................................... 152 Table A4.4 Effect of 10 mg/L Co on acetate utilization rate in the food waste digester ............................................................................ 153 Table A4.5 Effect of 0.01mg/L Ni on acetate utilization rate in the food waste digester ............................................................................ 154 Table A4.6 Effect of 1 mg/L Ni on acetate utilization rate in the food waste digester ............................................................................ 156 Table A4.7 Effect of 10 mg/L Ni on acetate utilization rate in the food waste digester ............................................................................ 157 Table A4.8 Effect of 0.5 mg/L Fe on acetate utilization rate in the food waste digester ............................................................................ 158 xii Table A4.9 Effect of 5 mg/L Fe on acetate utilization rate in the food waste digester ............................................................................ 160 Table A4.10 Effect of 100 mg/L Fe on acetate utilization rate in the food waste digester ............................................................................ 161 xiii LIST OF FIGURES Figure 2.1 Anaerobic Digestion Process .................................................... 10 Figure 3.1 Process diagram of FW pulper/extractor system ....................... 41 Figure 3.2 Pupler component of the FW processing system at Brody Dining Hall ............................................................................... 42 Hydro-extractor component of the FW processing system at Brody Dining Hall ....................................................................... 42 Storage container component of the FW processing system at Brody Dining Hall ........................................................................ 43 Figure 3.5 Vermicomposting facilitate at the MSU Student Organic Farm 44 Figure 3.6 Vermicomposting bins used for this research............................ 44 Figure 3.7 BMP assays serum bottles in a shaker being incubated in o constant 35 C temperature room ............................................. 48 Cumulative biogas yields from digestion of food waste with and without vermicompost ................................................................ 54 Cumulative methane yields from digestion of food waste with and without vermicompost ........................................................ 55 Figure 3.10 Methane content from digestion of food waste with and without VC ................................................................................. 58 Figure 4.1 Experimental setup of the semi-continuous digestion study ...... 64 Figure 4.2 AER-208 - Research Respirometer Aerobic/Anaerobic gas measuring cells ......................................................................... 65 Specific biogas production rates from digestion of food waste with and without additives ......................................................... 67 Total VFA concentrations from digestion of food waste with and without additives ................................................................ 68 pH change from digestion of food waste with and without additives .................................................................................... 68 Methane content from digestion of food waste with and without additives .................................................................................... 72 Figure 3.3 Figure 3.4 Figure 3.8 Figure 3.9 Figure 4.3 Figure 4.4 Figure 4.5 Figure 4.6 xiv Figure 4.7 Specific methane production rates (per gram VS added) of food waste digesters with and without additives ........................ 74 Soluble metal concentrations of food waste digesters with and without additives ........................................................................ 75 Specific methane production rates (per gram VS destroyed) of food waste digesters with and without additives ........................ 78 Figure 5.1 Methanogenic activity test experimental set-up......................... 83 Figure 5.2 Maximum acetate utilization rates of food waste digesters with and without additives ................................................................ 84 Maximum propionate utilization rates of food waste digesters with and without additives ......................................................... 85 Effects of nickel on daily methane yield from the food waste digester ..................................................................................... 91 Effects of iron on daily methane yield from the food waste digester ..................................................................................... 91 Effects of cobalt on daily methane yield from the food waste digester ..................................................................................... 93 Figure 7.1 Summary of research……………………………………………… 94 Figure 7.2 Mechanisms associated with enhanced digestion performance of food waste digester supplemented with vermicompost ........ 96 Integrated vermicomposting and anaerobic digestion system for food waste management .................................................... 98 Normalized volatile solid (VS) destruction of food waste after 30 days of AD ............................................................................ 104 Figure 4.8 Figure 4.9 Figure 5.3 Figure 6.1 Figure 6.2 Figure 6.3 Figure 7.3 Figure 8.1 xv KEY TO ABBREVIATIONS AD: Anaerobic Digestion AVG: Average BMP: Biochemical Methane Potential CH4: Methane Co: Cobalt CO2: Carbon Dioxide COD: Chemical Oxygen Demand CSTR: Continuous Stirred Tank Reactor DI: Demonized Fe: Iron FW: Food Waste FWVC: Food Waste with Vermicompost HA: Humic Acids H2S: Hydrogen Sulfide HRT: Hydraulic Retention Time LCFA: Long Chain Fatty Acids MAUR: Maximum Acetate Utilization Rate MPUR: Maximum Propionate Utilization Rate MSW: Municipal Solid Waste N: Nitrogen N2: Nitrogen Gas Ni: Nickel xvi OLR: Organic Loading Rate P: Phosphorous SEM: Standard Error of the Means SRT: Solid Retention Time STD: Standard Deviation of the Means TE: Trace Elements TS: Total solids VC: Vermicompost VFA: Volatile Fatty Acids VOC: Volatile Organic Compounds VS: Volatile solids xvii CHAPTER 1 INTRODUCTION This chapter contains the background, problem statement, hypothesis, rationale, and objectives of the dissertation. Chapter 2 is a literature review which is followed by a description of the four stage of the research (Chapter 3, 4, 5, and 6). General conclusion and suggestions for future research then follow in Chapter 7. 1.1 Background The term “food waste” is defined by the U.S. Environmental Protection Agency (EPA) as any food substance, raw or cooked, which is discarded, or intended or required to be discarded (US EPA, 2012). In 2010, more than 34 million tons of food waste was generated in the U.S., the second-largest component of municipal solid waste stream (US EPA, 2012). Only less than 3% of the total food waste was recovered and recycled, while the remaining 97% was simply thrown away (US EPA, 2012). This makes food waste the single largest component of municipal solid waste reaching landfills (US EPA, 2012). Food waste decomposition in landfills produces significant amounts of methane gas (CH4), a greenhouse gas (GHG) with 21 times the global warming potential (100 year) of carbon dioxide (CO2) (US EPA, 2012). An estimated 117.5 Tg CO2 (or million metric tons of CO2 equivalent) of methane were generated from landfills in 2009, the third- largest human-related source of methane in the U.S. (US EPA, 2012). The negative environmental impact and rising costs associated with landfill disposal have led to the development of alternative technologies for food waste management (Arvanitoyannis and Varzakas, 2008). The implementation of government initiatives, for example the European Union (EU) Landfill Directive (1999/31/EC), will further promote the diversion of food waste from landfill in pursuit 1 of alternative technologies such as composting, thermochemical conversion, and anaerobic digestion (AD). Composting is a common alternative to landfill disposal of food waste, however, it requires large areas of land, emits volatile organic compounds (VOCs), and consumes energy (Mata-Alvarez et al., 2000). Food waste generally contains 74-90% mositure which makes thermochemical conversion technologies such as direct combustion or gasification undesirable due to the considerable decrease in energy efficiency (> 60%; Appels et al., 2011). In contrast, anaerobic digestion produces energy and reduces the emissions of CH4 gas and VOCs (Mata-Alvarez et al., 2000). The residual material (digestate) contains the entire complement of nutrients originallly in the raw feedstocks which can be directly used or further composted and then used as nutrient soil amendments (Tambone et al.,2009). With such potential benefits, AD should be explored as a better recycling alternatives to landfill disposal of food waste. What is AD? Anaerobic digestion (also called anaerobic fermentation) is a biological process that converts organic material at a modest temperature, ambient pressures, and nearly neutral pH to biogas in the absence of external electron acceptors (such as free molecule oxygen) (Klass et al., 1984). Biogas consists largely of CH4 and CO2 and trace amount of nitrogen (N2), nitrogen oxides, and hydrogen sulfide (H2S). Anaerobic digestion is a highly complex and dynamic system where microbiological, biochemical, and physical–chemical reactions are closely linked (Klass et al., 1984). If the substrate consists of high molecular weight carbohydrates, fats, and/or protein, it is first hydrolyzed to soluble polymers (simple sugars, fatty acids, alcohols, and amino acids) by 2 enzymatic reactions from hydrolytic bacteria. These soluble polymers are then fermented into volatile fatty acids (VFAs), alcohols, hydrogen (H2), and CO2 by acidogenic bacteria. The VFAs longer than two carbons are converted to acetate and H2 gas by the obligate hydrogen-producing acetogenic bacteria. Finally the acetate, CO2, and H2 are converted to CH4 by methanogens. As a result of the CH4 and CO2 formation, the originally organic bound, non-carbon compounds are released to their soluble inorganic forms (Angelidaki and Sanders, 2004). The stability of the process is dependent on the critical balance between the symbiotic growth rates of the principal microbial organisms (Speece, 1996). AD is a mature biological treatment method that can be cost effective, environmentally sound and a source of renewable energy when implemented correctly (Mata-Alvarez et al., 2000). Many types of biomass containing carbohydrates, proteins, fats, cellulose, and hemicelluloses can be used as substrates (Weiland, 2009) including sewage sludge (Chynoweth et al., 1993), animal manure (Al-Masri, 2001), dedicated energy crop and crop residue (Amon, 2007), grass (Wilkie, 1986), wastewater from food processing plants (Tekin and Dalgic, 2000), fruit and vegetable waste (Knol et al., 1978), and the organic fraction of municipal solid waste (Bouallagui et al., 2003; Han et al., 2005; Xu et al., 2002). Food waste contains a high content of readily degradable organic matter and is a desirable substrate for AD (Zhang et al., 2011). Various types of food waste have been evaluated individually for their biochemical methane potential (BMP) and showed promising results including cooked meat (482 mL/g volatile solid (VS) added), boiled rice (294 mL/g VS added), fruits, (180 to 430 mL/g VS added) and 3 vegetables (190 to 400 mL/g VS added) (Cho et al., 1995; Gunaseelan, 2004). The reported BMP of the post-consumer food waste collected from restaurant and cafeterias ranged from 435 to 480 mL/g VSadded (Cho et al, 1995; Zhang et al., 2007; Zhang et al., 2011). 1.2 Problem Statement Despite the high methane potential, using restaurant and cafeteria food waste as a single substrate for AD was not very successful. Several researchers report elevated VFAs concentrations that resulted in digester instability and failure (ElMashad et al., 2008; Climenhaga and Banks, 2008; Zhang et al., 2011; Banks et al., 2012). In a single-stage digestion system, food waste is often rapidly acidified to VFAs that accumulate and decrease the pH in the reactor, inhibiting the activity of methanogenic microorganisms. Recently, several studies reported that this accumulation of VFAs is likely caused by trace element deficiencies (Climenhaga and Banks, 2008; Zhang et al., 2011; Banks et al., 2012). Previous research showed that a sophisticated two-stage digestion system can overcome these deficiencies (Lee et al., 1999; Xu et al., 2002; Wang et al., 2005). However, the application of a two-stage system is limited as the majority of full-scale anaerobic digesters around the world are in a traditional one-stage configuration (Zhang et al., 2011). An alternative method is co-digestion with animal wastes that are rich in trace element (Liu et al., 2009; El-Mashad and Zhang, 2010; Zhang et al., 2011; Zhang et al., 2012). However, this strategy may not be practical in urban areas where most food waste is generated. Untreated animal waste and food waste both have a high moisture content preventing the economical long distant transport to a centralized 4 anaerobic digester. Additionally, having manure in highly urban areas may be unacceptable from a nuisance standpoint. In summary, food waste has great energy potential and can be used as a substrate for AD to produce energy. However, there is a lack of practical and economical strategies to ensure stable and efficient digestion. 1.3 Hypotheses The central hypothesis of this dissertation research is that the supplementation of manure vermicompost (VC) to a single-stage AD system using food waste as the sole substrate will stimulate methane production and enhance process stability. 1.4 Rationale The rationale for this central hypothesis is that manure VC contains a wide range of trace minerals at concentrations favorable for AD (Heravs et al., 1989). Additionally, VC originating from animal manure contains high levels of humic acids (Canellas et al., 2000) that are reported to increase methane production and improve digestion stability (Hartung, 1989). A detailed literature reviews is in Chapter 2. There are numerous reasons why manure VC was selected as the test nutrient-rich supplement for enhancing the AD of food waste, as discussed below. 1. Manure VC vs. raw manure. The earthworms used in the production of manure VC modify the physical, biological, and chemical properties of the original manure. The final product is an odor free, granular, and peat-like material with moisture content in the range of 45-60%. This makes it more suitable for transport and land application as a soil amendment. Moreover, 5 the concentrations of calcium (Ca), potassium (K), iron (Fe), copper (Cu), zinc (Zn), chromium (Cr), and cadmium (Cd) increase (Yadav and Garg, 2010) as a result of carbon and nitrogen loss due to mineralization and decompositions of organic matter (Deolalikar et al., 2005). 2. Vermicompost vs. thermophilic compost. Vermicompost has much higher concentrations of available (water-soluble) nutrients, in comparison to traditional thermophilic compost derived from identical feedstocks (Subler et al., 1998; Short et al., 1999; Tognetti et al., 2005). Additionally, earthworm activity accelerates the humification of organic matter, producing a larger amount of humic acids compared to thermophilic composting (Edwards, 2004). 3. Vermicompost vs. commercial mineral nutrients. In recent years, several studies evaluated the feasibility of supplying commercially available, relatively pure trace elements to ensure stable and effective AD of food waste (Climenhaga and Banks, 2008; Zhang et al., 201; Banks et al., 2012). However, VC is potentially a more eco-friendly, economically viable, and sustainable alternative to commercial minerals, which are primarily produced from nonrenewable resources. In summary, vermicompost serving as an AD supplement appears to be a viable, novel approach to improve the stability of AD and increase biogas production. However, its effectiveness is not demonstrated and the potential mechanisms of improvement not understood. In fact, there is no previously published research on the utilization of manure VC or conventional thermal compost to improve AD of food waste. 6 1.5 Objectives The overall objectives of the study were to evaluate the effectiveness of utilizing dairy manure VC as an additive to enhance the AD of cafeteria food waste in a single-stage digestion system and investigate the associated mechanisms. To achieve these objectives, a four stage studies were conducted as described in Chapters 3-6. A brief summary of the structure of the dissertation research is shown in Table 1.1. Stage Table 1.1 Structure of dissertation research Experiment Objective 1 BMP assay 2 Long term semicontinuous digestion trial 3 Specific methanogenic activity test 4 Metal bioavailability study Preliminarily examine the feasibility of utilizing VC as an additive to enhance the AD of cafeteria food waste Examine the effectiveness of VC as an additive in a long-term operation and identify the stimulatory factors present Determine the effect of VC on the acetate utilization rate and propionate utilization rate Determine if the deficiencies of selected trace metals cause the low acetate utilization rate in a food waste digester 7 CHAPTER 2 LITERATURE REVIEW In this chapter, the principles of the anaerobic process were briefly discussed first followed by in-depth reviews of: 1) the functions and requirements for trace metals; 2) the use of additives to stimulate AD; and 3) food waste digestion. A brief review of the VC process is also presented, including principles of its production, a comparison of VC and traditional composting, and the use of VC in the digestion process. 2.1 Overview of Anaerobic Digestion Anaerobic digestion is the decomposition of organic matter by a microbial consortium in an oxygen-free environment (Ward et al., 2008). Organic carbon is converted by subsequent oxidation and reduction steps to its most oxidized state. CO2, and its most reduced state. CH4. In addition to CH4 and CO2, minor quantities of other gaseous products are generated such as N2, nitrogen oxides, H2, NH4, and H2S (Angelidaki and Sanders, 2004). 2.1.1 Historical Development and Present Status Volta is recognized as the first to report the conversion of organic matter to CH4 through an anaerobic digestion process (McCarty, 2001). In 1776 he showed that “combustible air” was derived from sediments in lakes, ponds, and streams. In 1856, Reiset reported that methane was formed from decomposing manure (McCarty, 2001). The first full-scale application of anaerobic treatment was a septic tank used for treating domestic wastewater, developed by Moigno in 1881 (McCarty, 2001). He named this system “Mouras’ Automatic Scavenger’’ and described this airtight chamber in the French journal Cosmos. In 1890, Moncrieff constructed the first 8 hybrid anaerobic system that consisted of a tank digester and an anaerobic filter that was designed to decrease the volume of sludge (McCarty, 2001). Imhoff modified a septic tank to enable a longer solid retention time and, by the end of 1914, about 75 cities in the United States received a license to use the system, termed an Imhoff tank (McCarty, 2001). Beginning in the 1920s, Bunswell and his colleagues conducted extensive research on applications of the anaerobic process for the management of industrial wastewater and agricultural residues (McCarty, 2001). Later, Stander discovered the importance of the solids residence time for reducing the reactor’s size (McCarty, 2001). Taylor developed the first large-scale anaerobic filter to treat wheat starch wastewater in 1972 (McCarty, 2001). In 1970s, Lettinga developed the up-flow anaerobic sludge blanket reactor, which is now the one of the most successful new reactor designs because of its broad application to a variety of industrial and municipal wastewaters (McCarty, 2001). By the end of 20 th century, AD has become widely applied worldwide. In the U.S., AD is used at large farms for manure treatment, at municipal wastewater treatment plants, and to treat industrial wastewater. AD is more prominent in Europe, especially in Germany, Denmark, Austria, and Sweden because of strong government initiatives (Holm-Nielsen et al., 2009). Although AD is a widely applied, the design is still generally empirical (De Baere, 2006). This is mainly due to the complexity of the biological process, that is still not fully understood, and the increasing range of feedstocks. Many problems associated with the AD technology such as poor operational stability and a long retention time limit its application and researchers are in agreement that more research is needed to further advance AD technology. Included are 1) improving 9 process efficiency by the pretreatment of substrates and the addition of biological and chemical additives; 2) identifying microbial community dynamics; 3) modeling of AD; and 4) upgrading and utilizing of biogas (Appels et al., 2011; Hom-Nielsen et al., 2009; Ward et al., 2008; Mata-Alvarez et al., 2000). 2.1.2 Principals of Anaerobic Digestion Anaerobic digestion consists of a series of biochemical processes as illustrated in Figure 2.1. Figure 2.1 Anaerobic Digestion Process (Adapted from Gujer and Zehnder, 1983). Percentages indicate substrate flow (stoichiometrically) in the form of COD or CH4, as described by Gujer and Zehnder, 1983. 10 Six distinct processes occur:  Hydrolysis of complex polymers including proteins, carbohydrates, and lipids  Fermentation of amino acids and sugars  Anaerobic oxidation of long chain fatty acids  Anaerobic oxidation of intermediary products such as VFAs (with the exception of acetate)  Conversion of acetate to CH4.  Conversion of H2 and CO2 to CH4. Fermentation is defined as a microbial process in which organic matters serve both as electron donors and as electron acceptors. Anaerobic oxidation is defined as microbial process in which molecular H2 is the main sink for electrons (Gujer and Zehnder, 1983). These six processes are typically simplified to four stages: hydrolysis, acidogenesis, acetogenesis, and methanogenesis. The trophic groups relevant for anaerobic process design and control are hydrolytic bacteria, acidogenic (or fermentative) bacteria, acetate-forming (also known as acetogenic) bacteria, and methanogens (archaea). If complex insoluble compounds such as particulate and colloidal organic matter are used as substrates, the first stage of the AD process is hydrolysis. Hydrolysis is defined as the breakdown of organic substrates into smaller products, which then can be taken up and degraded by microorganisms (Morgenroth et al., 2002). Complex organic matter such as proteins, carbohydrates, and fats are complex polymeric substances which consist of many small molecules joined 11 together by unique chemical bonds. In general, most microorganisms are unable to directly use these substances, therefore, microorganisms first excrete extracellular hydrolytic enzymes to hydrolyze these complex polymer to soluble polymers or monomers such as amino acids, simple sugars (oligo- and monosaccharides), and long-chain fatty acids (Gujer and Zehnder, 1983). Typical hydrolytic enzymes include protease, cellulase, cellobiase, xylanase, amylase, and lipase. The soluble substrates entered the bacteria cells for ultimate degradation. In the acidogenesis stage, soluble compounds produced through hydrolysis or directly fed to the digester are degraded by acidogenic bacteria. The degradation of these compounds results in the production of CO2, H2, alcohols (such as butanol, ethanol, methanol, and propanol), organic acids (such as acetate, butyrate, formate, lactate, propionate, and succinate), organic-nitrogen compounds, and organic-sulfur compounds (Geradi, 2003). The presence of organic-nitrogen compounds and organic sulfur compounds is due to the degradation of proteins CO2 and H2 can be converted directly to acetate or methane. Many alcohols and acids generated during the acidogenesis stage (such as propionate, butyrate, and ethanol) are further degraded to acetate, formate, CO2, and H2 during the acetogenesis stage, by acetate-and H2-forming bacteria (also called acetogenic bacteria). The accumulation of hydrogen can inhibit the metabolism of acetogenic bacteria; therefore, the maintenance of an extremely low partial pressure of hydrogen is essential. The final stage in AD is methanogenesis, where CH4 is produced from acetate, CO2, and H2 by the methanogens. Methane can also be formed from 12 formate and methanol although this is not common. Acids, alcohols, and organicnitrogen compounds not used by methanogens accumulate in the digester. Methanogens are classified as archaea, a biology domain distinct from bacteria. There are three principal groups of methanogens, acetotrophic, hydrogenotrophic, and methylotrophic, which will be discussed in more details in the next section. Although many details on the metabolic networks in a methanogenic consortium are not clear, present knowledge suggests that H2 may be a limiting substrate (Bagi et al., 2007). This assumption is based on findings that the addition of H2-forming bacteria to the natural biogas-forming consortium increases daily biogas production. 2.1.3 Anaerobic Microorganisms Three groups of anaerobic microorganisms including acetate-forming bacteria, sulfate-reducing bacteria and methanogens are reviewed in this subsection. 2.1.3.1 Acetate-Forming Bacteria Acetate-forming bacteria grow in a symbiotic relationship with methanogens. When acetate-forming bacteria produce acetate, hydrogen is also produced and used by methanogens for CH4 production. Acetate-forming bacteria survive only if their metabolic waste—H2—is continuously removed by methanogens or other hydrogen-utilizing bacteria. If H2 accumulates, acetate-forming bacteria cease and depress acetate production, causing the AD to fail (Amani et al., 2010). Failure to maintain the balance between these two groups of microorganisms is the primary cause of reactor instability (Wang et al., 2009). 13 2.1.3.2 Sulfate-Reducing Bacteria There are two groups of sulfate-reducing bacteria—incomplete oxidizers and complete oxidizers. Incomplete oxidizers degrade organic compounds to new bacterial cells, CO2, and acetate, ethanol, formate, lactate, and propionate. Complete oxidizers degrade organic compounds to new bacterial cells and CO2 (Geradi, 2003). If sulfates are present, sulfate-reducing bacteria compete with methanogens for the same substrates (H2 and acetate) and reduce sulfate to hydrogen sulfide. At substrate-to-sulfate ratios <2 (mass basis), sulfate-reducing bacteria out-compete methane-forming bacteria for acetate while at substrate-tosulfate ratios between 2 and 3, competition is very intense (Geradi, 2003). At substrate-to-sulfate ratios >3, methane-forming bacteria are favored (Geradi, 2003). 2.1.3.3 Methanogens Methanogens are a morphologically diverse group of the archaea that have many shapes, growth patterns, and sizes but unified by their ability to gain energy by reducing carbon monoxide (CO), CO2, formate, methanol, methylamines, or acetate to CH4. Methanogens employ hydrogenase, formate dehydrogenase, carbon monoxide dehydrogenase, methyl reductase and secondary alcohol dehydrogenase to obtain reducing equivalents for generating methane from molecular hydrogen, formate, acetate, methyl groups and secondary alcohols, respectively (Reeve, 1992). Coenzymes that are unique to methanogens are coenzyme M and the nickelcontaining coenzymes F420 and F430 (Geradi 2003). Coenzyme M is used to 14 reduce CO2 to CH4. The nickel-containing coenzymes are important H2 carriers in methanogens. In the AD process, there are three principal groups of methanogens: 1) hydrogenotrophic, 2) acetotrophic (also known as aceticlastic), and 3) methylotrophic (Amani et al., 2010). The hydrogenotrophic methanogens typically use H2 and convert CO2 to CH4 (Eq. 2.1) however, some use CO to produce CH4 (Eq. 2.2). By converting CO2 and H2 to CH4, these organisms help to maintain a low partial hydrogen pressure in the digester that is required for acetogenic bacteria (Amani et al., 2010). 2 2 Eq. 2.1 2 2 2 Eq. 2.2 The acetotrophic methanogens “split” acetate into CH4 and CO2 (Eq. 2.3). This process is known as an aceticlastic reaction. The CO2 produced from acetate may be further converted by hydrogenotrophic methanogens to methane (Eq. 2.1). 2 Eq. 2.3 Acetate degradation is also carried out by acetate oxidizing reactions. In contrast to the former reaction, the latter is very energetically unfavorable (Hattori, 2008). However, this reaction can occur from syntrophic interaction between certain bacteria and methanogenic archaea. The bacteria, namely syntrophic acetateoxidizing bacteria, can oxidize acetate to produce H2/CO2 only when their products are subsequently utilized by the hydrogenotrophic methanogens (Hattori, 2008). 15 Surprisingly, some of these bacteria can also reversibly utilize H2/CO2 to produce acetate (Hattori, 2008). The methylotrophic methanogens grow on substrates that contain the methyl group (-CH3). Examples of these substrates include methanol (CH3OH) (Eq. 2.4) and methylamines [(CH3)3-N] (Eq.2.5). Eq. 2.4 2 2 2 Eq. 2.5 Methanogens reproduce very slowly due to the relatively small amount of energy obtained from the use of their limited number of substrates (Gerardi, 2003). Under optimal conditions, the range of generation times varies from three days to several weeks. Therefore, if the solid retention time is too short, the population of methanogens is not able to increase accumulate. 2.1.4 Optimization of Anaerobic Digestion Like any other microorganisms based process, successful AD operation depends on maintaining environmental conditions to optimize the microbial activity and increasing the system efficiency. Important operational parameters that must be satisfied for a stable and efficient digestion process are discussed below. 2.1.4.1 pH and Alkalinity In general, CO2 and VFAs tends to lower pH, while alkalinity-generating cations, like ammonium ions from protein degradation reacting with CO2 to form ammonium biocarbonate, stabilize the pH (Bhattacharya and Parkin, 1989). The 16 best pH range for acetate-forming bacteria is 5.5-6.5 and for methanogens is 6.7-8.0 (Owens et al., 1979). The pH of an anaerobic digester should be maintained in a range of approximately 6.5 to 8.2 (Liu et al., 2008; Speece, 1996). A decrease in pH below 6 significantly reduces the activity of the methanogens and causes a buildup of VFAs and H2. At higher partial pressure of H2, acetate-forming bacteria are severely inhibited resulting in even more accumulation of VFAs and a further decrease of the pH. Further, if food waste is used for feedstocks, rapid hydrolysis of lipids can result in the accumulation of VFA and the lower methanogenic activity (Griffin et al., 1998). 2.1.4.2 Temperature Temperature plays an important role in microbial growth and metabolism rates and the physicochemical properties of the substrate. The two optimum primary temperature ranges for AD are mesophilic (30-35° and thermophilic (50-55° C) C). AD can also occur at a psychrophilic temperate, below 20° (Boullagui et al., 2003). C The structures of the active microbial communities are dependent on the temperature range (Ward et al., 2008) and a rapid change from mesophilic to thermophilic may cause a temporary, substantial decrease in biogas yield (Ortega, 2008). 2.1.4.3 Solid Retention Times The solid retention time (SRT), average time solids (microorganisms) spend in the AD, significantly affects digestion performance (Appels et al., 2008). For an anaerobic digester operating at 35° the minimum recommended SRT is 10 – 20 C, 17 days so that the rate of organism growth exceeds the rate of wash out (Appels et al., 2008; Keshtkar et al., 2003). 2.1.4.4 Mixing For optimal performance, mixing must ensure that the entire digester volume is utilized, there is extensive contact between the bacteria and the substrate, and heat is being transferred effectively (Kaparaju et al., 2008). For wastes with higher solids content, efficient mixing is a necessity to maximize biogas yields (Karim et al., 2005). However, excessive mixing can reduce biogas production, likely due to the disruption of the granule structure of acetate-forming bacteria and methanogens resulting in a reduced rate of VFA oxidation and ultimately, digester instability (McMahon et al., 2001). 2.1.4.5 Organic Loading Rate Biogas production rate is highly dependent on the organic lading rate (OLR) (Yadvika et al., 2004). Wide and rapid variations may upset the balance between acidogenesis and methanogenesis resulting in a decrease in biogas production. The maximum OLR is determined by many factors including the mass transfer rate between substrate and microbial biomass, microbial proximity of syntrophic reactions, temperature, pH, toxicity level, design of reactor, characteristics of feedstocks, settleability, and activity of microbial biomass (Amani et al., 2007; Speece, 1996). 2.1.4.6 Macronutrients As with any biological treatment process, nitrogen (N) and phosphorous (P) are the two macronutrients of most concern in AD. Availability to anaerobic 18 microorganisms is typically as soluble ammonium-nitrogen (NH4+–N) and orthophosphate-phosphorus (Speece, 1996). For optimal gas production, the carbon (C) to N ratio of at least 25:1 is suggested. A high C/N ratio may limit microbial biomass growth while a lower ratio may cause ammonia accumulation resulting in pH values exceeding 8.5, which are toxic to methanogens. For the AD of fruit and vegetable waste, an optimum ratio of 100–130:4:1 was reported for the chemical oxygen demand (COD), N, and P, respectively (Bouallagui et al. 2003). 2.1.4.7 Micronutrients Methanogens unique enzyme systems result in diverse micronutrient requirements. Included are cobalt (Co), iron (Fe), nickel (Ni), sulfide (S), selenium (Se) and tungsten (W) (Gerardi, 2003). Their incorporation is essential to ensure not only proper degradation of substrate but also efficient operation. Deficiencies of micronutrients in ADs often have been mistaken for toxicity (Speece, 1996). A more detailed literature review regarding trace metals is presented in section 2.2. 2.1.4.8 Inhibition/Toxicity A variety of organic and inorganic matters have been reported to be inhibitory to ADs. Propionate is the most toxic VFA and can inhibit digestion at concentrations of 3000 mg/L. Long-chain fatty acids (LCFAs) can also inhibit methanogens (Kabara et al., 1977; Zeikus, 1977) by adsorbing onto the cell membrane and interference with the transport or protective function (Rinzema et al., 1994). 19 Ammonia produced by the biological degradation of the nitrogenous matter, (mostly in the form of proteins and urea) may cause inhibition (Chen et al., 2008). In general, concentrations below 200 mg/L are beneficial to anaerobic process since nitrogen is an essential nutrient for anaerobic microorganisms (Liu and Sung, 2002) but values from 1700 to 14000 mg/L are inhibitory (Chen et al., 2008). Competition with sulfate reducing bacteria for available acetate, H2, propionate, and butyrate can suppress methanogens and acetogens(McCartney and Oleszkiewicz, 1993; Colleran et al., 1995). Sulfide formed from the reduction of sulfate and the degradation of organic compounds such as sulfur-containing amino acids and proteins may inhibit the metabolic activity of anaerobic bacteria (Tursman and Cork, 1988). Hydrogen sulfide is likely the toxic form of sulfide since it can diffuse more rapidly into the cell membrane than ionized sulfide (Gerardi, 2003). Sulfide toxicity is pH dependent and increases as pH increases (McCartney and Oleszkiewicz, 1991). The inhibitory sulfide levels reported in the literature were in the range of 100–800 mg/L dissolved sulfide or approximately 50–400 mg/L dissolved H2S (Parkin et al., 1990). In addition, excessive concentrations of soluble metals may cause toxicity by blocking enzyme functions (Vallee and Ulner, 1972). Such toxic effect is primarily 3+ nonspecific and reversible (Nies, 1999). For example, Cr concentration of 12 mg/L or higher can cause a 50% reduction in acetoclastic methanogenic activity. However, supplying additional Fe could revert this inhibition (Soubes et al., 1994). This type of inhibition is characterized by the reversible binding of the inhibitor with either the enzyme or the enzyme-substrate complex. Less frequently, metals act as competitive inhibitors (compete with the substrate). This type of inhibition depends 20 on the concentration and affinity of the metal to the enzyme (Oleszkiewicz and Sharma, 1990). 2.1.5 Anaerobic Biodegradability Assays A brief review of anaerobic biodegradability measurements is presented in this subsection. 2.1.5.1 Overview Anaerobic biodegradability (also called anaerobic digestibility) is defined as the fraction of a compound(s) that can be converted to biogas (or methane) under anaerobic condition (Guwy, 2004). Such assays are used to assess the quantity and rate production of biogas or methane from ADs. Anaerobic biodegradability is typically determined based on the measurement of either substrate depletion or product formation during the digestion process. Substrate depletion can be determined either by measuring generic parameters such as VS or COD or directly by analysis of the specific substrate (Rozzi and Remigi, 2001). Determination of COD is sometimes problematic. The method for analysis of COD was developed for water and wastewater, which may not be suitable for materials with a high level of solid organic matter like food waste. Therefore, VS is usually used as primary parameters for digestibility tests for solid organic matter. Methods based on product formation monitor the end product (biogas) and/or intermediates products such as VFAs. Because of the ease in measuring biogas, this is the most common approach. Biogas production can be determined either as volume increase under constant pressure (volumetric methods) or pressure change in constant volume (manometric methods) (Angelidaki and Sanders, 2004). 21 The volumetric method entails transferring the volume of biogas produced into a device that allows for its measurement to be recorded. A common approach is to collect the biogas in a lubricated syringe in which the plunger expands to balance the overpressure generated inside the reactor (Rozzi and Remigi, 2004). The syringe is inserted through a septum that is part of the reactor cap (Owen et al., 1979) or used as the reactor itself (Cohen, 1992). In a different arrangement, the biogas proceeds into an external vessel containing a barrier solution that displaces an equivalent volume of liquid, which can be manually or automatically measured. An alternative is the anaerobic respirometer equipped with a bubble courter which can measure 3 biogas production as small as 0.1cm (Rozzi and Remigi, 2004). The biogas is transformed into small gas bubbles when passing through a liquid filled cell. A laser counter recognizes each bubble as it moves out of the cell which is then correlated to a volume (Kuss & Young1992). 2.1.5.2 Batch and Continuous System The biodegradability of a specific substrate can be evaluated in a batch, semicontinuous or continuous system. In the batch system, the substrate remains in the reactor until the end of experimental period. While, in semi-continuous and continuous systems, substrate is withdrawn and fresh, untreated substrate is added routinely, typically daily. The batch system is the more common method because it uses simpler equipment and requires less time to complete. However, the accumulation of byproducts in continuous system is minimal, avoiding potential inhibition that may occur in batch tests. Additionally, the continuous system is also used to simulate a 22 field-scale digester allowing the data to be used for design and cost purposes (Rozzi and Remigi, 2004). 2.1.5.3 Biochemical Methane Potential Assay One example of such experimental set-ups is the BMP assay (Owen et al., 1979). The BMP is defined as the ultimate specific methane production – regardless of how long it takes to reach this level (Angelidaki and Sanders, 2004). However, in practice, degradation time is capped at a practical limit and the methane potential is estimated by extrapolation of a methane production curve. Methane potential can be expressed specifically per amount of initial mass of waste (L CH4/kg- substrate), volume of the initial waste (L CH4/L- substrate), mass of VS added (L CH4/kg-VS), initial COD added (L CH4/kg-COD), or the mass of the substrate, VS or COD that was removed (requires measurement of the parameter before and a projection of the amount remaining when the ultimate biogas volume is reached). The primary purpose of BMP assay is to determine if mathematical prediction of the methane potential is reasonable and to verify the digestibility of a substrate. Methane potential determined by batch BMP assays is a preliminary estimation and is not intended to use for stimulating a real-scale digester (Speece, 1996). Many technical issues influence the outcome of a BMP assay, including the following. 1) Inoculum. The source of inoculum greatly influences its ability to utilize the substrate being tested (Rozzi and Remigi, 2004). Wasted solids from a stable AD with a similar substrate is often the used as inoculum as the microorganisms are pre-acclimated to the expected conditions (Owen et al. 1979). 23 Another important factor is the amount of inoculum added. A low amount is often desired to minimize its biogas production. However, inadequate amounts can lead to an overload of the substrate resulting in accumulation of VFAs and, consequently, reducing the pH and methane production. 2) Substrate. Substrate concentration should be large enough to have good representatively and measurable biogas production but still practical. Also large quantities of substrate in a batch reactor can cause toxicity. In general, inoculum-to-substrate ratio (mass basis) should be maintained above 0.5:1 to avoid negative effect on methane production (Raposo et al., 2009). 3) Headspace Volume and Pressure. The volume of biogas produced, can be affected by variations of CO2 solubility in the bioreactor liquor or manometric liquid. Frequent release of the headspace pressure has been shown to reduce associated errors (Johnson and Young, 1983). Maintaining a small headspace volume also improves the accuracy of biogas measurement (Rozzi and Remigi, 2004). 2.2 Trace Metals in Anaerobic Digesters Many trace metals are essential for the growth of anaerobic microorganisms (Fermonso et al., 2008). During AD, trace metals act as: 1) microelements essential for various enzymatic reactions (Eichenberger, 1984); 2) inhibitors of sulfide toxicity (Oleszkiewicz and Sharma, 1989); 3) biomass stimulants, beyond the presumed enzymatic requirements (Takashima and Speece, 1990); 4) promoters of microbial aggregation (Oleszkiewicz, 1989). Trace metals essential for AD include nickel (Ni), iron (Fe), cobalt (Co), selenium (Se), molybdenum (Mo), tungsten (W) , Manganese (Mn), zinc (Zn) , and copper (Cu) (Oleszkiewicz and Sharma, 1989). The commonly 24 reported metals that have a stimulatory effect on AD are Ni, Fe, and Co (Oleszkiewicz and Sharma, 1989; Speece, 1996). 2.2.1 Functions of Nickel, Iron, and Cobalt Trace metals including Ni, Fe, and Co are crucial components of essential enzymes that catalyze metabolic reactions during methanogenesis (Zandvoort et al., 2006). Ni is vital to the last step of methanogenesis where methyl-coenzyme M (CH3-S-CoM) and coenzyme B (HS-CoB) are converted to methane and CoM-S-SCoB. This key step is catalyzed by methyl-coenzyme M reductase (MCR) complex, which includes a Ni-containing cofactor called F430 (Harmer et al., 2008). Ni and Fe are two critical elements for CO dehydrogenase (CODH) complex (Friedman et al., 1990). The CODH cleaves the C-C and C-S bonds in the acetyl moiety of acetylCoA, oxidizes the carbonyl group to CO2, transfers the methyl group to Coenzyme M, and is involved in the formation of acetate from H2/CO2 and methanol (Ferry, 1999; Bainotti and Nishio, 2000). Additionally, Ni and Fe are contained in F420-reducing hydrogenase that catalyzes the reduction of CO2 to CH4 (Michel et al., 1995). Co is required for the synthesis of the Co/corrinoid containing methyl-H4MPT: Coenzyme M methyltransferase complex (Thauer, 1998), and Methanol: Coenzyme M methyltransferase (Sauer and Thauer, 2000). 2.2.2 Requirements of Nickel, Iron, and Cobalt The intracellular concentrations of trace metals in unstressed condition are regarded as indicative of the essential requirement under optimal nutrient and process conditions (Oleszkiewicz and Sharma, 1989). 25 Various species of methanogens require different optimum or stimulatory concentrations of trace metals including Ni, Fe and Co as well as other essential metals such as Se, Mo, and W (Takashima and Speece, 1990). Zandvoort et al. (2006) provided an extensive list as shown in Table 2.2. Trace metal requirements could be impacted by operation parameters such as temperature (mesophilic vs. thermophilic) and the experimental set-up (batch vs. continuous). It is known that the required minimum concentrations of Ni, Fe, and Co are significantly greater for thermophilic digestion than mesophilic digestion for the same substrate (Zitomer et al., 2008). Most research on trace metal requirements has been studied in batch growth modes. However, quantifying the minimum requirements using batch-scale system could be biased due to the slow response of anaerobic microorganisms, particularly methanogens (Takashima et al., 2011). Table 2.1 Trace metal stimulation of pure cultures of methanogens Stimulation Methanogen Species Substrate Concentration (μM) Fe (20-100) Co (2) Methanothrix soehngenii VNBF Acetate Ni (2) Mo (2) Fe (> 5) Co (> 0.01) Ni (> 0.1) M. thermoautotrophicum H2/CO2 Mo (> 0.01) Se (1) W (10) Fe (35) Co (1) Methanosarcina barkeri Methanol Ni (1) Mo (1) Adapt from Zandvoort et al., 2006. 26 2.2.3 Bioavailability The bioavailability of trace metals in AD is defined as the availability of trace metals that can be freely uptake by anaerobic microorganisms (Speece, 1990). The fact that trace metals are present in an AD process does not assure that they are readily available for uptake (Speece, 1990). The bioavailability of trace metals is controlled by the total metal concentration in the digester and the environmental conditions affecting speciation including 1) precipitation, primarily by sulfide, carbonate, and phosphate; 2) chelation or complexing with inorganic species (ion pairs) and organic ligands, both present or synthesized by organisms to facilitate metal uptake; 3) the kinetics of precipitation and chelation reactions (Callander and Barford, 1983a). The uptake of metals by microorganisms is generally assumed to proceed mainly via the transport of free metal ions across the cell membrane (Zandvoort et al., 2006). The precipitation and formation of inorganic and organic complexes can reduce their availabilities (Zandvoort et al., 2006). However, in some cases, specific metal complexes can be taken up directly by anaerobic microorganisms (Jansen et al., 2005). The main species capable of precipitating metals in anaerobic digesters are 2 2- 3 sulfide (S -), carbonate (CO3 ), and, less importantly, phosphate (PO4 -) anions (Callander and Barford, 1983a). The presence of these anions poses a significant problem in trace metal bioavailability because of the reduced solubility associated with trace metal precipitates (Speece, 1996). In a typical digester with a pH of 7.3, Fe, Co, and Ni likely are precipitated as sulfides if the total concentration of metals - 2- (Fe, Co, Ni, Cu and Zn) is less than the total of sulfide (gas-liquid H2S, HS and S ) level (Callander and Barford, 1983b). 27 Essential trace metals (Fe, Co, Ni, Se, Mo, and W) can form soluble inorganic - 2- - 2- 2- complexes with a number of anions (HCO3 , CO3 , OH , SO4 , S ) and soluble organic complexes with organic complexes (such as EDTA, NTA, citric, and cysteine). The formation of these chelating complexes prevents precipitation of free metal ions. However, it is unknown if these complexes assist in trace metals uptake (Speece, 1996). Additionally, ADs often contain a high concentration of soluble microbial products (SMP) (Barker and Stuckey, 1999) that can bind metals such as nickel (Kuo and Parking, 1996). In summary, the speciation of metals has a significant impact on their bioavailability (Fernando et al., 2009). The presence of sufficient free trace metal ions (not precipitated) and selected soluble metal complexes are a prerequisite for their uptake by anaerobic microorganisms. 2.3 The Use of Additives to Stimulate the Anaerobic Digestion Process Various biological and chemical additives have been used in AD to increase gas production by stimulating the microbial activity (Yadvika et al., 2004). Examples include hydrolytic enzyme, trace metals, and humic substances as discussed below. 2.3.1 Hydrolytic Enzyme Polymeric carbohydrates, lipids, and proteins present in particulate organic matter cannot be taken up by microbial cells. Therefore, microorganisms secrete hydrolytic enzymes to breakdown and solubilize these macromolecular structures into soluble monomers that can transport through the cell membrane such as simple sugars, amino acids, and fatty acids. During the hydrolysis stage, starch is converted to glucose by amylase enzymes; hydrolysis of cellulose by the cellulase 28 enzyme complex yields glucose; protein is converted to amino acids by proteases and fatty acids are produced by lipases degradation of lipids. The hydrolysis is typically the rate-limiting step if the substrate is in particulate form such as for lignocelluloses-rich matter. A significant number of studies have examined the impact of supplying hydrolytic enzymes to increase the rate of hydrolysis. These enzymes are often added in a pretreatment process (in a separate reactor) before the substrate enters the reactor (Sonakya et al., 2001). The benefit of this method is that temperatures and pH can be adjusted (typically 50° and 5-7, respectively) to optimize enzyme C activity. Hydrolytic enzymes also can be directly supplied to anaerobic digesters (Romano et al., 2009) if the environment within the reactor allow for effective hydrolysis. The effectiveness of most hydrolytic enzyme additives is strongly dependent on the characteristic of substrates. For examples, Higgins and Swartzbaugh et al. (1986) added cellulase and β-glucosidase to anaerobic digesters to treat sewage and observed an increased biogas and methane yields of 12% and 15%, respectively. Sonakya et al. (2001) pretreated wheat grains with cellulase, αamylase, and protease prior to AD and found a 7-14% increase in methane production. In contrast, Rowena et al. (2009) evaluated the effects of the addition of enzyme products containing cellulase, hemicellulase, and β-glucosidase to AD systems using wheat grass as model substrates and found no significant effects on the biogas production and methane yield. Unlike other hydrolytic enzymes, lipase has consistently been demonstrated to be a promising enzyme additive for the AD of high fats and grease such as 29 slaughterhouse wastewater (Pereira, et al., 2006; Valladao et al., 2009) and dairy wastewater (Mendes et al., 2006; Cammarota et al., 2001). 2.3.2 Trace Metal Table 2.2 provides a partial list of reported stimulatory effects of trace metal supplementation on the AD of simple substrates and complex organic materials within various digestion systems. Noteworthy, all of the research was conducted under mesophilic condition (30-35C). Table 2.2 Stimulation of biologic conversion in anaerobic digesters by trace metal supplementation Trace Metals Observation and Substrate System Compared with no Reference Concentration Supplementation (mg/L) Hoban and Acetate Batch Fe (300-600) Increase AUR Van Den, 1979 Ni (6) Murray and Increase Acetate Batch Co (3) Van Den AUR Mo (4.8) Berg, 1981 Fe (70) Continuous Increase Speece et al., Acetate Ni (2.5) (CSTR) AUR 1983 Co (2.5) Fe (2.1) Continuous Increase Ma et al., Propionate Ni (0.00038) (UASB) PUR 2009 Co (0.00003) Ni (0.05) Volatile Continuous Increase Shen et al., Co (0.075) fatty acids (UASB) COD removal 1993 Fe (1.1) Potato and Fe(40) pea Continuous Maintain granular Oleszkiewicz, Ni (0.5) processing (UASB) form 1989 Co (0.5) wastewater CanovasCheese Continuous Increase CH4 Ni (7.4) Diaz and factory (fixed-film) production Howell, 1986 Fe (10) Improve Distillery Sharma and Batch Ni (0.5) methanogenic wastewater Singh, 2001 Co(0.1) activity CSTR: continuous stirred tank reactor; UASB: upflow anaerobic sludge blanket AUR: acetate utilization rate; PUR: propionate utilization rate 30 Metal deficiencies can severely impact the performance of AD (Speece, 1996). Elevated concentrations of VFAs in the effluent (over 500 mg/L) of an anaerobic digester can indicate trace metal deficiency (Speece, 1996). Several researchers verified that the addition of trace metals improved the performance of AD (Kim et al., 2002; Noyola and Tinajero, 2005; Pobeheim et al., 2010) by increasing the utilization rate of specific intermediate products such as acetate, propionate, and methanol (Takashima and Speec e, 1989; Kida and et al., 2001; Osuna et al., 2003). The chemical form of trace metals additives can impact their effectivness during the AD process. Chloride forms (NiCl2, FeCl2, and CoCl2) are generally recommended because of their high solubility (Speece, 1996). 2.3.3 Humic Substances Humic substances are naturally occurring, heterogeneous, high molecular weight organic compounds composed mainly of humic acids. Humic acids are a series of similar aromatic polyfunctional compounds with medium to high molecular weights (Hayes and Clapp, 2001) that are resistant to microbial degradation (Hayes and Clapp, 2001; Lovely, et al., 1996). Humic substances interact strongly with a range of trace metals and have the potential to modify their adsorption (Laxen, 1984). For example, it is known that humic acids promote the formation of chelating complexes with Fe resulting in an increase of its bioavailability for microbial (Chen and Wang, 2008) and plant cells (Mina-Garcia, 2003). Additionally, humic acids can increase the growth rate of a variety of microorganisms (Visser, 1984; Pouneva, 2005). Under anaerobic conditions, some microorganisms are able to use humic 31 substances as an electron acceptor for the anaerobic fermentation of organic compounds and H2 (Lovely, 1996). A two-year study at a municipal wastewater treatment plant demonstrated that humic substances stimulate the AD of sewage sludge by increasing methane production and improving digestion stability (Hartung, 1989). Unfortunately, the mechanism was not investigated. 2.4 Anaerobic Digestion of Food Waste Food waste contains a high content of readily degradable organic matter and is a desirable substrate for AD that can produce a tremendous amount of energy (Zhang et al., 2011) although it is not always conducive for stable operations. The characteristic and methane potential are discussed in the following subsection. 2.4.1 Characteristic and Methane Potential of Food Waste The characteristics are highly variable. Macronutrients are adequate for anaerobic microorganisms (Zhang et al., 2011). However, the concentrations of some trace metals are relatively low, particularly Co, Ni, and Fe (Speece, 1996). Considering the important role of these trace elements for activating and maintaining enzyme activities of anaerobic microorganisms, this deficiency may cause instability and poor efficiency. Reported characteristics of food wastes are shown in Table 2.3. Table 2.3 Characteristic of reported cafeteria or restaurant food wastes Source Han and Zhang et Zhang et Banks et Parameter Shin, al. (2007) al. (2011) al. (2004) (2011) pH NA NA 6.5 ± 0.2 4.7±0.1 TS (wt. %) 20.5 30.9± 0.1 18.1± 0.6 23.7± 0.1 32 VS (wt. %) VS (% of TS) Total COD (g/L) Total Carbon (% of TS) Alkalinity (g CaCO3/L) Table 2.3 (Cont’d) 19.5 26.4± 0.1 95 85±0.1 NA NA 51.4 46.8± 1.2 NA NA 17.1± 0.6 94±0.1 238± 4 46.7 0.3±0.1 21.7± 0.1 91.4± 0.4 NA NA NA Macro Nutrients (% of TS) Total Nitrogen (TN) Total Phosphorus (TP) Total Sulphur (TS) Total Calcium (Ca) Total Potassium (K) Total Magnesium (Mg) 3.5 NA 0.1 NA NA NA 3.2±0.2 0.5±0.1 0.8±0.1 2.2±0.3 0.9±0.1 0.14 3.5 1.5±0.1 0.33 NA NA NA NA 0.5±0.1 NA NA 1.4±0.1 NA NA 31±1 766± 402 60±30 NA 2±1 NA NA 76±22 <0.03 11.8 12.2 3.7 0.1 0.8 NA NA 31.9 <0.06 1.7±0.2 54 20±3 0.1±0.1 1.7±0.7 <0.07 <0.25 7.8±2.6 14.6 NA 13.2 0.2±0.1 NA NA Trace metals (mg/kg fresh samples) Cobalt (Co) NA Copper(Cu) NA Iron (Fe) NA Manganese (Mn) NA Molybdenum (Mo) NA Nickel (Ni) NA Selenium (Se) NA Tungsten (W) NA Zinc (Zn) NA Other parameters C/N ratio Ammonia-N (g/L) Errors= standard deviations 14.7 NA 2.4.2 Current Development and Issues Despite the high biochemical methane potential, using food waste as single substrate for AD is not very successful with frequent reports on elevated level of VFAs causing digester instability and even process failure (El-Mashad et al., 2008; Climenhaga and Banks, 2008; Zhang et al., 2011;Banks et al., 2012). In a singlestage digestion system, food waste could be rapidly acidified to VFAs accumulated VFAs consequently decrease the pH and inhibiting the activity of methanogenic microorganisms. Banks et al. (2012) suggested that this accumulation of VFAs 33 begins with an increase in the acetic acid concentration which reaches a peak around day 100 then declines followed by a longer-term accumulation of propionic acid. Previous efforts to solve this problem include using a sophisticated two-stage digestion system (Lee et al., 1999; Xu et al., 2002; Wang et al., 2005). However, the application of two-stage system is still limited and the majority of full-scale anaerobic digesters around the world remain the traditional one-stage configuration. Another alternative method is co-digestion with animal manure (Liu et al., 2009; El-Mashad and Zhang, 2010; Zhang et al., 2012). However, this strategy may not be practical for urban area where most food waste is generated. In summary, anaerobic digestion of food waste still remains as a challenge. 2.4.3 Case Studies Prior literature investigating the AD of food waste as a sole substrate in semicontinuous and continuous single-stage digestion systems is briefly reviewed below. Climenhaga and Banks (2008) evaluated the effect of micronutrients on the AD of cafeteria food waste containing a mix of fruits, vegetables, meats, and fried foods at the bench scale. Without micronutrients supplementation, the reactors exhibited methanogenic failure as a result of accumulation of VFAs and concluded that trace element addition (a mixture of Fe, Cu, Co, Zn, Mn, Mo, Al, and Se) was required for stable digestion. Similarly, Zhang et al. (2011) demonstrated that when food waste was used as a sole substrate, the digester suffered from accumulation of VFAs up to 18,000 mg/L and a drop of pH from 7.2 to 4.4 which ultimately led to a process failure. The cafeteria food waste was also found to be deficient in some trace metals (likely Co, Ni, Fe, and Mo). AD of the food waste supplemented with trace element-rich piggery 34 wastewater or synthetic trace elements resulted in a significantly improved biogas production rate and enhanced process stability. Banks et al. (2012) further investigated the trace element requirements for stable food waste digestion at elevated ammonia concentrations and confirmed that without supplementation VFAs accumulated. The main component was initially acetic acid which then shifted to propionate after around day 100. The authors used the fluorescent in situ hybridization (FISH) technique to analyze the microbial community structure and found that the dominant metabolic pathway of food waste digestion with or without trace metal additions was syntrophic acetate oxidation and hydrogenotrophic methanogenesis due to significant loss of acetoclastic methanogens under the high ammonia concentrations (above 5000 mg/L). In this case, Se was demonstrated to be vital to the proper function of this pathway and is recommended as trace metal supplementation for food waste digestion. 2.5 Vermicomposting A brief review of vermicomposting process is presented in this subsection. 2.5.1 Principles Vermicomposting is a simple biotechnological process in which earthworms convert the organic waste material into VC (Benitez et al., 2000). During the process microbial degrade organic matter and the earthworm acts as mechanical blenders by comminuting the organic matter, modifying its biological, physical, and chemical state, gradually reducing its C to N ratio and increasing the surface area exposed to microorganisms (Yadav and Garg, 2010). The end-product of vermicomposting is VC which is a good structural amendment for poor soils as it provides nutrients and minimizes soil erosion. 35 Vermicompost can be produced from almost any kind of organic waste with suitable preprocessing and controlled processing conditions. Included are animal waste (poultry, pigs, cattle, sheep, goats, horses, and rabbits) (Edwards et al., 1985), horticultural residues from dead plants, yard wastes (Edwards, 1995), sewage sludge, and solids from wastewater (Neuhauser et al., 1988). Cattle manure is considered to be one of the easiest animal wastes to VC (Edwards, 2004). The earthworm species most commonly used is Eisenia Fetida (E. Fetida) and the very closely related species E. Andrei. These species (epigeic) have a more complete enzymatic system than do endogeic species (Brown and Doube, 2004), a wide temperature tolerance ranging from 10-25˚C, and can live in organic wastes with a range of moisture contents (55-88%, Loehr et al., 1985). During the vermicomposting process, total organic carbon is gradually lost due to mineralization (Edwards, 2004). Earthworm activity provided conditions that favor nitrification, resulting in the rapid conversion of ammonium into nitrates (Hartenstein, 1981). Humification of organic matter is also accelerated. This acceleration is not only due to the fragmentation and size reduction of the organic matter, but also by the significant increase in microbial activity within the intestines of the earthworms and by aeration and turnover of the organic matter that occurs as the earthworms move(Edwards, 2004). The final physical structure of VC depends on the original organic wastes. However, VC produced from most organic wastes are usually finely divided, wellstabilized, and humified, peat-like materials with excellent structure, porosity, aeration, drainage, and a low C: N ratio (Edwards, 1983). During the processing of organic wastes by earthworms, many of the macronutrients are changed to forms that are more readily available for uptake by 36 plants (Table 2.4). A comparison of the physicochemical characteristics of final cattle and pig manure VC to the initial feedstock indicates that there is an increase in the concentration of Fe, Cu, Zn, Cr, and Cd (Table 2.5). The carbon and nitrogen loss was likely due to mineralization and decompositions of organic matter (Deolalikar et al., 2005; Hartenstein, 1981; Suthar et al., 2008). Table 2.4 Effect of earthworm activity on nutrients in organic waste Exchangeable (% dry Readily Nitrate mass) Soluble P Organic Wastes Nitrogen (% dry (ppm) K Ca Mg mass) Cattle waste without worms 8.8 0.11 0.19 0.35 0.05 with worms 259.4 0.18 0.41 0.59 0.08 Pig waste without worms 31.6 1.05 1.49 1.56 0.45 with worms 110.3 1.64 1.76 2.27 0.72 Adapted from Edwards, 2004 Table 2.5 Comparison of trace element content in initial cattle manure and final cattle manure vermicompost Trace element Initial Cattle Manure Final Cattle Manure (mg/kg) Vermicompost (mg/kg) Fe 1810 2280 Cu 32.4 52.6 Zn 145 193 Cd 4.29 5.84 Cr 82 194 Additionally, VC originating from animal manure and food wastes has been reported to contain high levels of humic substances (Canellas et al., 2000; Atiyeh et al., 2002). Cattle manure VC typically contains about 20% humic acids (Hervas et al., 1989; Senesi et al., 1992). Additionally, Senesi et al. (1992) analyzed the characteristic of metal-humic acid complexes of manure VC using spectroscopic and 37 found that humic acid –like components of vermicompost are able to bind large amounts of Fe and Cu ions in water-stable, inner-sphere complexes. Vermicomposting systems range from very simple to complex and can be operated manually or completely automated. Reactor systems can be either batch or continuous flow. The basic principle of all successful processing system is to add the wastes at frequent intervals in small, thin layers to the surface of the system to allow earthworms movement unto the fresh, aerobic layers. The earthworms will always concentrate themselves in the upper 15 cm of waste (Edwards, 2004). 2.5.2 Vermicomposting vs. Traditional Composting Traditional thermophilic composting involves the degradation of organic matter by microorganisms under controlled conditions. There are two stages. During the thermophilic stage, the decomposition takes place intensively at a high temperature (> 50 C). In the maturing stage, the temperature is in the mesophilic range (20- 30 C) and the remaining organic compounds are degraded at a slower rate (Lazcano et al., 2008). Composting is well established at the industrial scale for solid organic waste treatment, although the loss of nitrogen through volatilization of NH3 during the thermophilic stage of the process is one of the major drawbacks (Eghball et al., 1997). A major difference between vermicomposting and traditional composting is the temperature. The temperature of traditional compost pile can exceed 70˚C compared with relatively low temperatures of typically 25˚C for vermicomposting. As a result, thermophilic microbes are the main contributors for traditional composting, while worms, mesophilic aerobic microbes, and fungi are responsible for vermicomposting. 38 The difference between traditional composting and vermicomposting is also reflected in the unique properties of their products. VC has a much higher nutrient concentrations that are in more available (water-soluble) forms (Subler et al., 1998; Short et al., 1999; Tognetti et al., 2005). Moreover, earthworm activity accelerates humic acids production during the humification process (Edwards, 2004). In addition, greater extra-cellular enzymatic activities including cellulose, amylase, invertase, protease, perioxidase, and urease activities are observed during vermicomposting process as compared to traditional composting process (Edwards and Bohlen, 1996). Devi et al. (2009) also found that vermicomposting achieved greatest enzyme activity by 28 day of decomposition compared to 42 days for traditional composting. 2.5.3 Vermicompost as Additive in Anaerobic Digestion Only limited data is available on utilization VC as an additive in AD. Chen et al. (2010) reported that under mesophilic condition, anaerobic co-digestion of corn stalk with VC generated from cow manure increased biogas yield by up to 59%. Zhang et al. (2007) found that supplying VC (produced by decomposition of cow manure as well) at the concentration of 1,5, and 10% of TS to synthetic wastewater resulted in an increase in methane yield up to 25% and improved buffering. Neither study provided the mechanism of observed enhancement. Studies regarding the use of VC for enhancing anaerobic digestion of food waste have not been found. 39 CHAPTER 3 USE OF BIOCHEMICAL METHANE POTENTIAL ASSAYS TO EVALUATE THE EFFECTS OF MANURE VERMICOMPOST ON ANAEROBIC DIGESTIBILITY OF FOOD WASTE The first stage of dissertation research is presented in this chapter including introduction; material and methods; results and discussion; and conclusions and implication sections. 3.1 Introduction The objective of this research stage was to evaluate the effects of manure VC on the anaerobic biodegradability of food waste. Anaerobic biodegradability is evaluated using the BMP test, first established by Owen et al (1979). The BMP test is a simple and rapid method to evaluate the anaerobic biodegradability of a feedstock in a nutrient defined medium. From the BMP test, cumulative biogas yield, ultimate methane yield, and the kinetic rate constant can be determined. 3.2 Material and Methods Experimental material and methods are presented in this subsection. 3.2.1 Food Waste University cafeteria food waste (FW) was utilized as sample substrate to represent the typical American food waste mixture containing fruits, vegetable, meats, and grains. Post-consumer cafeteria food waste was collected from the Brody Dining Hall at Michigan State University (MSU). An estimated 200 ton/year of food waste is generated from this cafeteria. A pulper/extractor system (Somat Remote Pulping System, Somat Company, Lancaster, PA) is used for food waste processing at the Brody Dining Hall (Figure 3.1). All FW first enters the pupler (Figure 3.2), is ground, and then mixed with water to create pulpable slurry 40 comprised of approximately 95% liquid and 5% solids. Next, the slurry is pumped through a pipe to a remotely located hydra-extractor (Figure 3.3). The hydraextractor removes most of the water using specialized brushed screw augers and a cylindrical screen. Finally, the semi-dry pulp is discharged into a storage container (Figure 3.4) for disposal. FW used for this research was collected from the storage container and stored in a freezer at -18° Before use, the frozen food waste was C. thawed and stored at 4° for no more than one week. Prior to the BMP test, three C sub-samples were taken for chemical analysis to determine its initial characteristic. Pulper For interpretation of the references to color in this and all other figures, the reader is referred to the electronic version of this dissertation Figure 3.1 Process diagram of FW pulper/extractor system (source: http://www.somatcompany.com/Products) 41 Figure 3.2 Pulper component of the FW processing system at Brody Dining Hall Figure 3.3 Hydro-extractor component of the FW processing system at Brody Hall 42 Figure 3.4 Storage container component of the FW processing system at Brody Dining Hall 3.2.2 Dairy Manure Vermicompost Cattle manure is one of the easiest animal wastes for VC (Edwards, 2004). Therefore it was selected as the substrate to produce manure VC. Dairy manure was collected from the Dairy Teaching and Research Center at MSU. The MSU dairy herd consists of approximately 180 Holstein milking cows ranging from 2 to 12 years of age with an average of 40 months. Most of the milking herd is housed in tie stalls and receive forage and grain mixed diet. Dairy manure used for the study was collected directly from tie stalls instead of the manure storage facility to minimize bedding materials. The earthworm specie used for vermicomposting was Eisenia Fetida, and was obtained from the Student Organic Farm at MSU (Figure 3.5). These earthworms were previously cultivated in horse manure and pre-consumer food waste (fruits and vegetable scraps). The vermicomposting process for this research was carried out in plastic commercial storage bins (Figure 3.6) at a temperature range from 15-25˚C. The moisture content was checked on weekly basis and maintained at 60-70% by spraying water on the surface. Dairy manure was composted to maturity, approximately 60 days. The final product (VC) was a 43 dark, odourless, homogeneous, and peat like. After manually removing the earthworms, the VC was then stored at 4° prior to use. The TS and VS of VC C were 34.8% and 16.6%, respectively (Appendix Table A1.2). Figure 3.5 Vermicomposting facilitate at the MSU Student Organic Farm Figure 3.6 Vermicomposting bins used for this research 3.2.3 Biochemical Methane Potential Assay 3.2.3.1 Experimental Design 44 The experimental unit for this study was 12 identical batch-scale reactors. The completely randomized design was achieved by randomly assigning reactors to 4 treatments as shown in Table 3.1 (3 replicates per treatment). Table 3.1 Experimental design of BMP Assay Treatments Inoculum Food Vermicompost Initial Con. (g TS) [g waste (g TS) [g VS] substrate of VS] (g TS) [g organic VC VS] loading (g/L) (g VS) Control 1.30 [1.02] 0.48 [0.45] 0 0.45 0 FWVC1 1.30 [1.02] 0.47 [0.44] 0.02 [0.01] 0.45 0.4 FWVC2 1.30 [1.02] 0.43 [0.40] 0.10 [0.05] 0.45 2 FWVC3 1.30 [1.02] 0.32 [0.30] 0.31 [0.15] 0.45 6 FWVC= food waste supplemented with vermicompost; VC= vermicompost; TS= total solids; VS= organic solids; Con. =concentration Table 3.1 also shows the constituents of each treatment. All treatments had the same amount of inoculum (1.30 g TS, 1.02 g VS) and same initial substrate organic loading of 0.45 g VS. The working volume of each reactor was 0.15 L, achieved by adding the needed amount of deionized (DI) water. Detailed methods are provided in the subsections below. 3.2.3.2 Inoculum and Vermicompost An active inoculum was obtained from a100 L pilot-scale mesophilic (35° C) CSTR treating dairy manure for more than 6 months. The HRT and OLR of the pilot-scale reactor were 20 days and 2 g VS/L/day, respectively. The TS and VS were 3.3% and 2.6%, respectively. Three reactors containing only inoculum (1.30 g TS) were included as blanks to measure the methane production originating from the inoculum. 45 Significant methane production is not expected from the AD of mature VC. However, in order to confirm this assumption several additional BMP tests were conducted (Table 3.2) to indirectly estimate the biogas potential of VC. Table 3.2 Experimental design for determination of methane potential of manure vermicompost Inoculum Food Manure VC Conc. Test gTS waste gTS gTS of VC Purpose Number [g VS] gTS [g VS] [g VS] [g/L] [g VS] 1.27 0.32 0.14 Control 0 0 [1.00] [0.30] [0.10] 1 1.27 0.32 0.14 0.10 Treatment 2 [1.00] [0.30 [0.10] [0.05] 1.27 0.21 0.28 Control 0 0 [1.00] [0.20] [0.20] 2 1.27 0.21 0.28 0.10 Treatment 2 [1.00] [0.20] [0.20] [0.05] 1.27 0.11 0.41 Control 0 0 [1.00] [0.10] [0.30] 3 1.27 0.11 0.41 0.10 Treatment 2 [1.00] [0.10] [0.30] [0.05] 1.27 0.55 Control 0 0 0 [1.00] [0.40] 4 1.27 0.55 0.10 Treatment 0 2 [1.00] [0.40] [0.05] VC 1.30 0.90 5 0 0 18 Control [1.02] [0.45] These four tests represented four different nutrient conditions (such as different C/N ratios and metal concentrations) as the result of the change of substrate composition (Table 3.2). Dairy manure provided macro and micro nutrients and buffering capacity and the trace metals are assumed to be adequately supplied by the manure. The control served as blank without VC and the estimated biogas contribution from VC was calculated by subtracting the biogas production of the control from those of the treatment. Test 5 was used to directly measure the methane potential of VC. As previously, after the addition of all components the volume of each flask was brought up to 0.15 L with DI water. Consequently, the 46 impact of VC on biogas production for blends with different nutritional values could be surmised as without the VC. 3.2.3.3 Sample Preparation In order to ensure representative sampling and minimize loading errors, food waste was prepared using the procedure described by Hansen et al. (2004). A large subsample was first taken to determine the dry matter content. Thereafter, water was added and the large subsample was diluted to a dry matter content of 15% and blended in a commercial high-speed mixer for 5 minutes. This resulted in homogeneous slurry that allowed for the collection of small samples could easily be drawn for further chemical analysis and the BMP test. 3.2.3.4 BMP Set Up The reactors were 225 mL borosilicate glass serum bottles sealed with aluminium caps (manufactured by Kimble Chase). For each bottle, 30 g of rigorously stirring inoculum was transferred. Three reactors were picked randomly for each treatment. Then, the required amounts of FW and VC (as described in Table 3.1) were added to each bottle. Thereafter, additional DI water was added to bring the volume to 150 mL and each serum bottled was sealed with septa and covered with a septa cap. The headspace was flushed with pure N2 gas at a flow rate of approximately 0.5 L/min for 5 min to ensure anaerobic conditions were present in the head-space. This was achieved using a B-D 20 gauge needle that purged the bottle septum and extended into the liquid to introduce N2 gas and a second needle in the headspace to allow gasses to escape. The sealed reactors were then placed on a shaker (100-150 rpms) and incubated at 35° for 30 days (Figure 3.7). C 47 Figure 3.7 BMP assays serum bottles in a shaker being incubated in constant 35oC temperature room 3.2.3.5 Biogas Production Measurement To measure the biogas, a glass syringe (30 mL or 100 mL capacity) with a BD 20 gauge needle was used. DI water was applied to the inside of the glass syringe case and plunger to allow for the plunger to move freely. The serum bottles were held at a 45°angle and a needle was inserted into the headspace. The pressure from the headspace biogas caused the plunger to move upward until it reached atmospheric pressure. The volume of the biogas was then measured on the syringe scale. Initially, biogas was measured daily until the biogas production decreased and only needed to be measured every 2 – 5 days. Biogas production was recorded under room temperature (~ 22° and corrected to standard ambient C) temperature and pressure (SATP, 25° and 1 atm) using idea gas law. Biogas C production from seed (determined by blank reactors) was subtracted from total biogas production for all treatments. 48 Biogas composition (CH4, CO2, N2, and H2S) was analyzed weekly using SRI 8610C Gas Chromatograph (GC) and Peak simple computer software (SRI Multiple GAS Analyzer #1, SRI Instruments, Torrance, CA). The GC was equipped with a 6 inch molecular sieve column and a FID and TCD combined detector. For each measurement, a 2 mL of biogas sample was extracted from the headspace of the serum bottles using an air-tight syringe and then injected to the GC column. The concentrations of CH4, CO2, and N2 gas were reported as percentage and H2S content was reported as ppm. 3.2.3.6 Methane Production Rate Constant Calculation The degradation of each sample was assumed to follow a first-order rate of decay, in accordance with Equation 3.1 (Chen et al., 1978). B = B0 (1 − e −kt ) Eq. 3.1 B: cumulative methane yield at time t expressed in mL CH4/g VS added. B0: ultimate methane yield, assumed to equal the final B after 30 days of digestion. k: methane production rate constant (1/day) The k was estimated by plotting Ln (1- B/B0) versus t which yield a straight line with slope equal to negative k. 3.2.4 Analytical Methods Biological triplicate samples were taken and each sample was analyzed in technical triplicate. The pH was measured immediately after sampling using a pH 49 meter (accumet Excel XL60, Fisher Scientific) and electrode (accuCap, Fisher Scientific). Samples for TS and VS were stored at 4° for at most three days using C EPA method 1684. Alkalinity tests were performed within 24hrs after sampling using HACH Method 8203. Samples for chemical oxygen demand (COD), ammonianitrogen(Ammonia-N), total Kjeldahl nitrogen (TKN) and total phosphorus (TP) measurements were collected in plastic containers and either analyzed with 24hrs, or adjusted with acids to pH< 2, stored at 4° and analyzed within 5 days. COD was C determined according to USEPA approved Hach Method 8000 (0 to 1500 mg COD/L) (Hach Company). Ammonia-nitrogen analysis was measured using Hach Method 10031(Hach Company). TKN were determined according to EPA method 351.3. Total phosphorus was analyzed according to USEPA accepted Hach Method 8190 (Hach Company). 3.2.5 Statistic Methods The experiment contains one independent variable (VC supplementation) with 4 levels (concentrations of vermicompost at 0, 0.4, 2, and 6 g/L).The dependent variable was the digestion performance as indicated by the ultimate biogas production and ultimate methane production. There was one measure on each dependent variable for each experimental unit. The significant differences among treatments were determined by a one-way analysis of variance (ANOVA) with the Tukey-Kramer test of SAS software version 9.1(SAS Institute Inc.). Significant differences among the means were assumed to correspond to P ≤ 0.05. 3.3 Results and Discussion Experimental results and discussion are presented in this subsection. 50 3.3.1Characteristics of Cafeteria Food Waste The characteristics of FW are shown in Table 3.3. Table 3.3 Characteristics of food waste and comparison with literature report Current Zhang et al, Banks et al., Components a b b study 2011 2012 (wet basis) pH 6.6 ± 0.1 6.5 ± 0.2 4.7 ± 0.2 TS (%) 22.5 ± 0.6 18.1 ± 0.6 23.7 ± 0.1 VS (%) 20.9 ± 0.5 17.1 ± 0.6 21.7 ± 0.1 VS/TS (%) 93.0 ± 0.4 94 ± 1 91 ± 1 Total COD (g/kg) 253.6 ± 3.4 238.5 ± 3.8 NA TKN (mg/kg) 7.7 ± 0.2 5.42 ± 0.26 8.12 ± 0.01 TP (mg/kg) 1.6 ± 0.1 1.49 ± 0.09 1.28 ± 0.08 Ammonia-Nitrogen (g/kg) 0.24 ± 0.02 NA NA Alkalinity (g CaCO3/kg) 0.49 ± 0.01 NA NA TS= total solids; VS= organic solids; COD= chemical oxygen demand; TKN = total Kjeldahl nitrogen; TP= total phosphorus; a values were reported as average ± SEM (SEM is short for the standard error of the mean); the sample size was three; b values were reported as average ± STD (STD is short for the standard deviation) All values are reported on a wet weight basis. The average TS and VS of food waste used in the BMP assays were 22.5% and 20.9%, respectively. The VS was 93% of the TS, indicating that the FW contained highly digestible organic matters, as expected. Additionally, the food waste also contained 253.6 g/kg COD, 7.7 g/kg TKN, and 1.6 g/kg TP, resulting in an approximately COD:N:P ratio of 159:5:1. This is slightly lower than the optimum ratio of 350:7:1suggested by Gerardi (2003). However, these results were similar to literature reports on the characteristic of food waste originating from restaurants or source segregated domestic food waste (Zhang et al., 2011; Banks et al., 2012). 3.3.2 Estimated Biogas Production of Manure Vermicompost As shown in Table 3.4, under different nutrient conditions, little biogas was produced from VC which suggested that the digestibility of VC (mixed with food 51 waste or manure) was very low and contributed to negligible amount of biogas. Additionally, when desirable conditions for digestion of food waste were achieved by adding dairy manure (Test 1, 2 and 3) (which provided buffer capacity and macro and micro nutrients), supplementation of additional VC had no significant impact on biogas production. Table 3.4 Estimated biogas potential of manure vermicompost under various nutrient conditions1 Test Number 1 2 3 4 1 a 8 26 12 24 0 265 ± 1 269 ± 7 248 ± 1 261 ± 1 219 ± 3 231 ± 2 182 ± 1 171 ± 1 Estimated biogas potential of VC (mL/g VS a added) 13 Control Treatment Control Treatment Control Treatment Control Treatment Estimated biogas production from VC (mL) 4 Treatment Cumulative biogas production (mL) 0 VS= organic solids; VC=vermicompost; error=SEM Estimated biogas potential of VC = estimated biogas production from VC/g VS of VC added Manure VC was also tested. The ultimate biogas and methane yields after 30 day digestion were 38 and 14 mL/g VS added, respectively. As expected, only very small amounts of biogas and methane were produced from the AD of VC (Table 3.5). This is likely due to the lack of readily digestible organic matter present after 60 days of composting. Table 3.5 The ultimate biogas and methane productions of manure vermicompost Parameter Unit Average SEM Biogas yield mL/g VS added 38 5 Methane yield mL/g VS added 14 5 Average methane content % 36.3 3.6 1 VS= organic solids; SEM= standard error of means 52 3.3.3 Volatile Solid Destruction With the lack of biogas production associated with VC, the impact on nutritional value was studied. Consequently, the food waste was supplemented only with VC and not with manure. Table 3.6 shows the VS content of the control and treatment reactors before and after 30 days of digestion. Table3.6 Volatile solid content before (pre-digestion) and after 30 days of digestion (post-digestion) as well as total VS destroyed Treatment PrePostTotal Average digestion digestion volatile solid total volatile (g VS/L) (g VS/L) change solid 1 destroyed (g VS/L) 2 (g VS) Control 9.57 ± 0.05 7.68 ± 0.04 2.02 ± 0.05 0.303 FWVC1 9.44 ± 0.04 7.45 ± 0.02 1.87 ± 0.03 0.299 FWVC2 9.65 ± 0.45 7.76± 0.02 1.89 ± 0.05 0.284 FWVC3 9.49 ± 0.03 7.85 ± 0.05 1.64 ± 0.05 0.246 Vermicompost 9.51 ± 0.01 9.38 ± 0.02 0.13 ± 0.01 0.020 Blank 6.82 ± 0.03 6.79 ± 0.02 0.03 ± 0.01 0.005 Values were reported as average ± SEM; FWVC= food waste supplemented with vermicompost 1 Total volatile solid change = Pre-digestion (g VS/L) – Post-digestion (g VS/L) 2 Volatile solid destroyed = Total volatile solid change (g VS/L) ×Working volume of reactor (0.15L) As previously determined, this study also confirmed that only very minimal amounts of VS of VC (0.02 g) and inoculum (0.005 g) were destroyed after 30 days of AD. The poor VS destruction of VC resulted in less VS and TS destruction for all treatments compared to the control as the VS from the VC were included in the total VS used for the calculations. 3.3.4 Biogas and Methane Production from Food Waste The cumulative biogas and methane production per gram VS destroyed (mL /g VS destroyed) were calculated by dividing cumulative biogas or methane 53 production by the average total VS destroyed (values of the average total VS destroyed are shown in Table 3.6, column 5). The results are shown in Figure 3.8, Figure 3.9, and Table 3.7. Cumulative biogas yield per gram VS destroyed (mL/g VS destroyed) 1200 1000 800 Control 600 FWVC1 400 FWVC2 200 FWVC3 0 0 5 10 15 20 Digestion period (days) 25 30 FWVC= food waste supplemented with vermicompost; error=SEM Figure 3.8 Cumulative biogas yields from digestion of food waste with and without vermicompost 54 Cumulative methane yield per gram VS destroyed (mL/g VS destroyed) 700 600 500 400 Control 300 FWVC1 200 FWVC2 100 FWVC3 0 0 5 10 15 20 Digestion period (days) 25 30 FWVC= food waste supplemented with vermicompost; error=SEM Figure 3.9 Cumulative methane yields from digestion of food waste with and without vermicompost Table 3.7 Ultimate methane yields and methane production rate Treatment Ultimate Ultimate Methane biogas yield methane production rate (mL/g VS yield constant destroyed) 1 (mL/g VS (k, 1/day) destroyed) a a Control 0.134 918 ± 10 512 ± 13 a ab FWVC1 0.141 938 ± 29 573 ± 30 FWVC2 FWVC3 1034 ± 32 c 605 ± 35 b b b 0.149 0.149 973 ± 30 627± 33 Values were reported as average ± SEM; FWVC= food waste supplemented with vermicompost abc Means within a column lacking common superscript differ significantly (P < 0.05) 55 Supplementing FW with VC at the concentrations of 2 and 6 g/L (FWVC2 and FWVC3) both increased the ultimate biogas and methane yield per gram VS destroyed (determined based on 30 days of digestion; P < 0.05). The ultimate biogas yield of FW supplemented with VC at the concentrations of 2 and 6 g/L (FWVC2 and FWVC3) were 1034 and 973 mL/g VS destroyed respectively, which were both greater than the control (918 mL/g VS destroyed; P < 0.05). While, the ultimate methane yield from the FW digesters with VC at the concentrations of 2 and 6 g/L (FWVC2 and FWVC3) were 605 and 627 mL/g VS destroyed respectively, which were both greater than the control (512 mL/g VS destroyed; P < 0.05). There was no significant difference between the control and FWVC1. Vermicompost addition not only increased ultimate methane yield but also improved the methane production rate as shown in Table 3.7. The methane production rate constant of food waste supplement with VC at 2 g/L (FWVC2) and 6 g/L (FWVC3) were both 0.149 1/day which is numerically greater than the k of the control (k=0.134 1/day). Across treatments and control, biogas and methane production increased sharply until day 15 (Figure 3.8 and 3.9) and then remained at a slow rate of production until the end of the experiments (30 days). As a result, more than 80% of biogas and methane yield was obtained within the first 15 days of digestion. This is in agreement with the result found by Zhang et al. (2007) that methane production from food waste (collected from commercial restaurants in San Francisco, CA) increased until day 16 and then remained almost constant at a low level thereafter. After 15 days of digestion, supplemented with vermicompost at the concentrations of 2 and 6 g/L (FWVC2 and FWVC3) significantly increased biogas yield by 27 and 56 25%, respectively, compared to the control (Figure 3.8; P ≤ 0.05). Similarly, the average methane yield from the FW digesters with 2 and 6 g/L VC (FWVC2 and FWVC3) produced 33 and 35%, respectively, more methane than those of controls after 15 days of digestion (Figure 3.9; P ≤ 0.05). The methane potential of food waste without any supplementation was 351 mL/g VS added (Appendix A1.10). Previously, Cho and Park (1995) conducted BMP experiments using typical Korean food waste and obtained methane yields of 482, 294, 277, and 472 mL/g VS added for cooked meat, boiled rice, fresh cabbage, and mixed food waste (containing 73% rice, 6.4% rice, and 1.3% cabbage), respectively, after 40 days of digestion at 35° Heo et al. (2003) also evaluated the methane C. potential of Korean food waste and found similar results. Zhang et al. (2007) investigated BMP of food waste collected from American restaurants under thermophilic conditions (50° with the organic loading rate of 6.8 g VS/L and C) founded a methane potential of 425 mL /g VS added. The methane yield of food waste (control) obtained in this study was lower than the values reported by the above authors. This is likely due to the variation of food waste compositions. For instances, vegetable have much lower methane potential (in a range of 200-400 mL/g VS added; Gunaseelan, 2003) compared to fat or oil components in food waste, such as cooked meat (482 mL/g VS added; Cho and Park, 1995) or cooking oil (940 mL/g VS added; Chynoweth et al., 1993). Therefore, food wastes containing greater amounts of vegetable have a lower methane potential than those containing more fats and oils. It should also be mentioned that BMP test values are sensitive to several parameters, e.g. operating conditions (temperature, pH, and agitation intensity), the inoculum/substrate ratio, and initial organic loading (Lesteur et al., 2010). This makes it very difficult to compare BMP results among different studies. 57 3.3.5 Methane Content The methane content during digestion of food waste with and without VC is shown in Figure 3.10. After 5 days of digestion, the methane content remained almost constant. No significant difference was observed among the control and different treatments (Appendix A1.9). The average methane content was measured to be approximately 60% which is similar to the value of 63% reported by Banks et al., (2011) using a CSTR to digest source segregated domestic food waste. 70.0 Methane content (%) 65.0 60.0 55.0 50.0 Control 45.0 FWVC1 40.0 FWVC2 35.0 FWVC3 30.0 0 10 20 Digestion period (days) 30 40 FWVC= food waste supplemented with vermicompost Figure 3.10 Methane content from digestion of food waste with and without VC 3.3.6 pH Change The pH values of all reactors before and after digestion are shown in Table 3.8. No significant difference was observed among the control and treatments before and after 30 day of digestion (P >0.05). 58 Table 3.8 pH change before and after digestion Treatments Pre-digestion Post-digestion Control 7.6 ± 0.1 6.9 ± 0.1 FWVC1 7.5 ± 0.1 6.9 ± 0.1 FWVC2 7.6 ± 0.1 6.9 ± 0.1 FWVC3 7.7 ± 0.1 6.8 ± 0.1 Vermicompost 7.9 ± 0.1 6.7 ± 0.1 FWVC= food waste supplemented with vermicompost; values were reported as average ± SEM 3.4 Conclusions and Implication More than 80% of the methane yield from the AD of food waste was obtained during the first 15 days of digestion. Dairy manure VC added to the food waste reactors at concentrations of 2 g/L and 6 g/L significantly increased the ultimate methane yield and the methane production rate of food waste. The concentration of VC at 6 g/L had the most promising results with approximately 20% greater ultimate methane yield and 10% increase in methane production rate than those of controls. In conclusion, results from BMP assays proved the hypothesis that manure VC can enhance methane production from AD of FW under batch-scale experimental setup. Biogas and methane potential determined by batch BMP assays are preliminary estimation and are not intended for use in simulating a field-scale digester. Therefore, further research was conducted to determine if the positive effect of VC on AD of FW observed using batch experimental set-up remains in a continuous system as well as the likely cause of improvement and the results are presented in following chapters. 59 CHAPTER 4 USE OF SINGLE-STAGE CONTINUOUS DIGESTION SYSTEM TO EVALUATE THE EFFECTS OF MANURE VERMICOMPOST ON ANAEROBIC DIGESTIBILITY OF FOOD WASTE The second stage of dissertation research is presented in this chapter including introduction; material and methods; results and discussion; and conclusions and implication sections. 4.1 Introduction The previous BMP trial demonstrated that the addition of VC significantly enhanced anaerobic digestibility of FW and increased biogas and methane production. However, BMP assays provide a preliminary estimation and are not intended for use in simulating a field-scale digester. Semi-continuous systems can simulate a field-scale digester under existing or planned operating conditions (Rozzi and Remigi, 2004). Therefore, the second phase of this research was conducted to confirm the results found by the BMP trial. Additionally, this phase was designed to identify the key components of VC responsible for enhancing the digestion of food waste, including the investigation of trace minerals and humic acids. 4.1 Material and Methods Experimental material and methods are presented in this subsection. 4.2.1 Experimental Design A completely randomized design was used by randomly assigning the 12 identical reactors to six treatments (2 replicates per treatment) as shown in Table 4.1. The study was designed to evaluate the effects of different additives (particularly VC, trace elements, and humic acids) on the AD of FW. There was 1 independent 60 variable (additive) and 6 levels including no additive (control), trace elements (TE), humic acids (HA), VC, combination of trace elements and humic acids (TE+HA), and a combination of trace elements and vermicompost (TE+VC). A 15 day SRT was selected and the OLR of food waste was set at 0.6 g VS/L/day for both controls and treatments to remove this from being a variable. A relatively low OLR was selected to prevent over loading caused digester failure. The total OLR of the food waste digesters supplemented with vermicompost was 0.62 g VS/L/day (0.6 g VS/L/day of food waste and 0.02 g VS/L/day of vermicompost). Table 4.1 Experimental design of semi-continuous study Concentration SRT OLR Treatment Additives of additives (days) (g VS/L/d) FW 0.01 mg/L Ni FW + TE Trace elements 0.5 mg/L Fe 0.01 mg/L Co FW + HA Humic acids 0.4 g/L HA FW + VC Vermicompost 2 g/L VC 0.01 mg/L Ni 15 0.6 Trace elements 0.5 mg/L Fe FW + TE + HA and humic acids 0.01 mg/L Co 0.4 g/L HA 0.01 mg/L Ni Trace elements 0.5 mg/L Fe FW + TE + VC and 0.01 mg/L Co vermicompost 2 g/L VC -: Not applicable; FW= food waste; TE= trace elements; HA= humic acids; VC= vermicompost; SRT= solid retention time; OLR=organic loading rate The concentration of VC was determined based on the BMP trail. The two likely stimulatory substances contained in manure VC are trace elements and humic acids. Both were also used as independent additives to provide a comparison to the VC. The trace element additives were Ni, Fe, and Co, selected because of their crucial roles for catalysing metabolic reactions during methanogenesis (Oleszkiewicz and Sharma, 1989; Speece, 1996; Shen et al., 1993; Speece, 1996; Sharma and Singh, 2001; Kim et al., 2002; Noyola and Tinajero, 2005; Ma et al., 2009; Pobeheim 61 et al., 2010). Concentrations of the supplemental Ni, Fe, and Co were 0.01 mg/L, 0.5 mg/L, and 0.01 mg/L, respectively, determined based on recommended values reported by previous studies (Climenhaga and Banks; 2008). The stock solution was prepared by completely dissolving laboratory grade NiCl2· 2O (solubility in water: 6H 2540 g/L, 20 ° FeCl3· 2O (solubility in water: 900 g/L, 20 ° and CoCl2· 2O C), 4H C), 6H (solubility in water: 529 g/L, 20 ° in DI water. The concentration of humic acids C) (0.4 g/L) was estimated based on its estimated content in manure VC, approximately 20% (Hervas et al., 1989; Senesi et al., 1992) and was added as a sodium salt. 4.2.2 Food Waste and Manure Vermicompost Three batches of FW were used for this study. A new batch was started on day 1, 25, and 56 of the digestion period. As with the BMP, the source was from the MSU Brody Dining Hall. Characteristics of each FW batch were analyzed immediately after collection and then it was stored at 4oC. The same VC was used throughout the entire study (day 1-90) and was prepared using the same procedures as previously described in Chapter 3, Section 3.2. The pH, TS, VS, alkalinity, and ammonia-nitrogen of both FW and VC were determined using the same methods as described in Chapter 3, Section 3.2. For TKN and TP measurements, FW were analyzed within 24 hrs of collection using EPA method 351.3 and Hach Method 8190 (HACH Company), respectively. VC were analyzed at MSU’s Soil and Plant Nutrient Laboratory for TKN, TP, and iron using the recommended chemical soil test procedures for the north central region (source: http://extension.missouri.edu/explorepdf/specialb/sb1001.pdf). Total concentrations of Ni, Fe, and Co of food waste were analyzed using HACH method 8150, 8008, and 62 8078, respectively. Technical triplicate samples were conducted for all analysis. Results are shown in Table 4.2 and Table 4.3. Table 4.2 Characteristics of raw food waste Batch 1 Batch 2 Batch 3 Items (wet basis) (day1-30) (day31-60) (day61-90) 6.6 6.2 6.8 pH 23.4 22.1 25.2 TS (%) 21.8 20.4 23.6 VS (%) 93.2 92.7 94.4 VS/TS (%) 7.7 6.4 8.1 TKN (g/kg) 1.6 1.1 1.3 TP (g/kg) 0.24 0.16 0.11 Ammonia-Nitrogen (g/kg) 0.49 0.31 0.52 Alkalinity (g CaCO3/kg) Fe (mg/kg) 63 175 1.2 Ni (mg/kg) 3.3 3.0 Co (mg/kg) 4.6 TS= total solids; VS= organic solids;TKN = total Kjeldahl nitrogen; TP= total phosphorus; - data is not available; Fe = iron; Ni=nickel, Co= cobalt Table 4.3 Characteristics of manure vermicompost Items (wet basis) Vermicompost pH 6.98 TS (w.t. %) 35.4 VS (w.t.%) 15.0 TKN (g/kg) 7.9 TP (g/kg) 0.5 Ammonia-Nitrogen (g/kg) 0.03 Fe (mg/kg) 81 TS= total solids; VS= organic solids; TKN = total kjeldahl nitrogen; TP= total phosphorus; Fe = iron 4.2.3 Inoculum and Start-up The inoculum was obtained from a100-L pilot-scale mesophilic CSTR that previously used for digestion of dairy manure for more than 6 months. The HRT and OLR were 20 days and 2 g VS/L/day, respectively. The TS and VS were 3.2% and 2.1%, respectively. 63 All reactors were started with the same amount of inoculum (0.9 L). During the initial 3 weeks, no substrate was fed and no effluent was removed until the biogas production from the inoculum ceased (less than 30 mL/day). Thereafter, FW (with or without additives) was fed and the effluent was taken daily. The first SRT of this experiment was started at this time. 4.2.4 Experimental Setup and Biogas Measurement This experiment was carried out using anaerobic respirometers (AER-208 Research Respirometer Aerobic/Anaerobic, Challenge Technologies Inc., Springdale, AR). Specifically, 12 identical (duplicate reactors for each treatment and control) PYREX 1L aspirator bottles with bottom outlets were used as the CSTR reactors (Figure 4.2). Figure 4.1 Experimental setup of the semi-continuous digestion study Each reactor contained a magnetic stir bar and was placed on a magnetic stir plate for mixing at 80 rpm. The bottles were PVC-coated to contain reagents and prevent shattering of glass if the bottle broke. The bottom outlet was used for 64 feeding substrates and removing of digestate. The bottle was sealed with a size 6 rubber stopper that was tightly tied by plastic cable tie. A needle attached to the gas collection line was inserted through the rubber stopper of each reactor. Biogas flowed through the needle and collection line to individual gas measuring cells (Figure 4.2). When biogas passed through the oil filled volume measurement cell, the computer equipped with the Challenge Technology AER computer software (Challenge Technologies Inc., Springdale, AR) automatically measured, calculated, and recorded cumulative biogas production (volume and rate). The compositions of biogas were measured three times a week using the GC, as described in section 3.2.3.5. Figure 4.2 AER-208 - Research Respirometer Aerobic/Anaerobic gas measuring cells 4.2.5 Digester Operation and Monitoring The temperature was maintained at 35º for the entire 90 day experiment (6 C SRT, 15 days for each SRT). Digestate was removed and FW and additives (VC, 65 trace elements, and humic acids) were added daily to give the desired OLR of 0.6 g VS/L/day and concentrations of additives. The working volume was maintained at 0.9 L. During first SRT (days 1-14), 1 g/L of sodium bicarbonate (NaHCO3) was added to all reactors for buffering. However, no additional NaHCO3 was used after that. The pH was monitored every 2 days and TS and VS were measured every 3 days using the methods described in Chapter 3, Section 3.2. Alkalinity, TKN, and TP were analyzed once a week using the same procedures described in Chapter 3, Section 3.2.3. VFAs were determined once a week using the titration method established by O’Brien and Donlan (1977). During the fifth SRT, digester effluents were assessed for soluble trace metal concentrations to enable the estimation of metal bioavailability. Soluble metals in the AD are usually considered bioavailable (Oleszkiewicz and Sharma, 1990) which were measured as those remaining in solution (digester effluent) after centrifugation (~3500 rmp for at least 15 min) and filtration through a 0.45 µm fibreglass filter. Filtered samples were then measured for Ni, Fe, and Co using HACH method 8150, 8008, and 8078, respectively. 4.2.6 Statistic Methods The experimental units in this study were 12 identical reactors. A completely randomized design was achieved by randomly assigning reactors to six treatments (2 replicates per treatment). There was 1 independent variable (additive) and 6 levels including no additive (control), TE, HA, VC, TE+HA, and TE+VC. The dependent variable was the digestion performance such as daily biogas and methane production, pH, and the concentration of VFAs. The dependent variable was measured repeatedly (time-series) throughout the experimental period. The 66 significance of the differences between treatments was determined by the PROC MIXED procedure of SAS software version 9.1 (SAS Institute Inc.). Differences were considered significant at a P value of ≤ 0.05. 4.3 Results and Discussion Experimental results and discussion are presented in this subsection. 4.3.1 Biogas Production, VFA Concentration, and pH Specific biogas production rate (mL/g VS added), total VFA concentrations, and pH are shown in Figures 4.3, 4.4, and 4.5, respectively. For biogas production rate calculation, the total VS added of the digesters supplemented with VC were 0.62 g VS/L/day and all other digesters were 0.6 g VS/L/day. 1,400 FW Specific biogas production rate (mL/g VS added/day) FW+VC FW+TE+HA 1,000 FW+TE FW+HA 1,200 FW+TE+VC 800 600 400 200 0 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 Days FW= food waste; TE= trace elements; HA= humic acids; VC= vermicompost Figure 4.3 Specific biogas production rates from digestion of food waste with and without additives 67 Total VFA concentration (mg/L) 2,800 2,600 2,400 2,200 2,000 1,800 1,600 1,400 1,200 1,000 800 600 400 200 0 FW (control) FW + TE FW + HA FW + VC FW + TE + HA FW + TE + VC 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 Time (days) FW= food waste; TE= trace elements; HA= humic acids; VC= vermicompost Figure 4.4 Total VFA concentrations from digestion of food waste with andwithout additives 7.8 7.5 7.3 7.0 6.8 FW (control) 6.3 FW+TE 6.0 FW+HA 5.8 FW+VC 5.5 FW+TE+HA 5.3 PH 6.5 FW+TE+VC 5.0 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 Time (days) FW= food waste; TE= trace elements; HA= humic acids; VC= vermicompost Figure 4.5 pH change from digestion of food waste with and without additives 68 Table 4.4 Specific biogas production rate, total VFA concentrations, and pH during steady-state period Items FW FW + TE FW +HA FW + VC Biogas yield a b b b 505 ±73 719 ±21 718 ±24 749 ± 24 (mL/g VS added/day) pH value a b 6.4 ± 0.3 7.3 ± 0.1 a b b 7.2 ± 0.1 b b 7.2 ± 0.1 c 1419 ±554 158 ±9 151 ±15 100 ±13 Total VFA (mg/L) Values were reported as average ± SEM; FW= food waste; TE= trace elements; HA= humic acids; VC= vermicompost abc Means within a row lacking common superscript differ significantly (P 0.05) The food waste reactor without any additives (FW) were unstable and had low biogas production (Figure 4.3) due to the significant accumulation of VFA (Figure 4.4) that resulted in a decrease in pH (Figure 4.5) after the first two SRTs (corresponding to the time necessary for washout of the inoculum). In contrast, digesters with additives including VC, trace metals, and HAs all had stable biogas production, desirable pH, and low VFA concentrations (Figures 4.3, 4.4, and 4.5). The observed unstable and low biogas production from the FW reactor without any additives (control) is consistent with results reported previously by other researchers. El-Mashad et al. (2008) found that a single-stage mesophilic AD with food waste as sole substrate was not stable at the OLR of 2 or 4 g VS/L/day as indicated by the accumulation of VFAs, low pH, and low biogas production. Similarly, Banks et al. (2008) utilized a thermophilic digester to digest source segregated domestic food waste and also observed digester instability in terms of the sudden dropping of pH and biogas production as a result of the accumulation of VFA (up to 45,000 mg/L). The food waste reactor supplemented with trace elements maintained a stable biogas production rate of average 719 mL/g VSadded/day, significantly higher than the control (505 mL/g VS added/day; Table 4.3). This result was similar to the result 69 found by Banks et al. (2011) who reported a specific biogas production rate of 750 mL/g VSadded/day from semi-continuous digestion of source-sorted food waste supplemented with additional trace elements. Moreover, the observed improvement suggests that the FW reactors operating under current experimental condition were deficient in trace elements, likely Ni, Co or Fe. However, this stage research did not identify which one of those three metals was the key factor that contributed to the enhanced performance. A further study aimed to determine which of the three metals being studied played the most crucial role is presented in Chapter 6. Several other researchers also found that unsuccessful digestions of cafeteria food waste were likely due to trace element deficiencies. For example, Zhang et al. (2011) demonstrated that when food waste is used as a sole substrate, the digester suffered from accumulation of VFAs, up to 18,000 mg/L, which dropped the pH from 7.2 to 4.4, ultimately led to a process failure. In this study, the waste was found to be deficient in Co, Ni, Fe, and Mo, all of which are required for robust and stable AD. Climenhaga and Banks (2008) evaluated the effect of micronutrients on AD of cafeteria food waste containing a varied mix of fruits, vegetables, meats, and fried foods in single-stage ADs. Without the supplement of micronutrients, the reactors exhibited methanogenic failure as a result of accumulation of VFAs and it was concluded that trace element addition (a mixture of Fe, Cu, Co, Zn, Mn, Mo, Al, and Se) was required . The food waste reactor supplemented with humic acids (FW+HA) was also stable and had an average biogas production rate of 718 mL/g VS added/day, significantly greater than the control (505 mL/g VS added/day; Table 4.4). Little is known regarding the impacts of humic acids on the AD of organic waste. Hartung 70 (1989) conducted a two-year study using a full-scale operating plant to investigate the effect on the AD of sewage sludge and reported that supplementation of humic substances stimulated the process as evidenced by greater methane production and less sludge volume. The humic acid sodium salt (> 0.25 g/L) was also found to delay in protein hydrolysis extending the lag-phase, and ultimately, the ultimate hydrolysis rate (Brons et al., 1985). Such “inhibition” may be beneficial for the AD of food waste as it could prevent rapid hydrolysis of protein caused VFA accumulation. The food waste reactor supplemented with VC had the greatest biogas production of 749 mL/g VS added/day. Such improvement could be a combination effect of trace elements and humic acids that naturally presented in manure vermicompost. A recovery of digestion performance was observed for the control reactor during the fifth and sixth SRT. For example, daily biogas production jumped from the average of 202 mL for the fourth SRT up to the average of 289 and 284 mL for the fifth and sixth SRT (Appendix A2.24). The pH increased from below 6 during fourth SRT up to 6.8 during the fifth and sixth SRT (Appendix A2.4). However, the VFAs were remained high for the control (Appendix A2.29). The cause was not clear but it is worth noting that there was a change of food waste on fifth and sixth SRT when batch 3 was used as shown in Table 4.2. Although the TS and VS of this new batch were similar to the previous batches, it had higher concentrations of trace elements, particularly Fe. The recovery of biogas production may be also due to the acclimation of methanogens. Methanogens are known for their exceptional acclimation capability to some inhibitors (Speece, 1996). In this alternative scenario, during the first SRT, the inoculum and additional NaHCO3 provided adequate buffering capacity and neutralized excessive free VFAs which helped to maintain the 71 balance between anaerobic bacteria and methanogens. This also allowed methanogens to adapt to food waste. After washing out inoculum and stopping the supplementation of NaHCO3, free VFAs produced by anaerobic bacteria were not utilized by methanogens resulting in the accumulation of VFAs that partially inhibited methanogenesis. Later, methanogens acclimated to the environment and started to produce biogas again. Regardless, supplementation of trace elements appeared to resulted in no significant reduction in biogas production for the food waste digester. Similarly, no significant drops of biogas production were observed for the food waste digesters supplemented with humic acids and VC. In these cases, the buffering capacities of humic acids and VC were likely also assistant the acclimation process. 4.3.2 Biogas Composition and Methane Production Rate The methane content of biogas as a function of time during the entire trial period is shown in Figure 4.6 and the statistic results were shown in Table 4.5. 65 60 Methane Content (% of biogas) 55 50 FW (control) FW+TE FW+HA FW+VC FW+TE+HA FW+TE+VC 45 40 35 30 25 0 20 40 Time (days) 60 80 FW= food waste; TE= trace elements; HA= humic acids; VC= vermicompost Figure 4.6 Methane content from digestion of food waste with and without additives 72 Table 4.5 Average biogas compositions during the steady-state period Items Methane (% of biogas) Carbon dioxide (% of biogas) Nitrogen (% of biogas) Hydrogen sulfide (ppm of biogas) FW FW + TE FW +HA FW + VC 49a± 6 57b± 1 56b± 2 56b±1 39a± 4 33b± 1 33b± 1 33b±1 9± 4 7± 2 8± 2 8± 2 711± 445 394± 98 164± 104 88±44 Values were reported as average ± SEM; FW= food waste; TE=trace elements; HA= humic acids; VC= vermicompost ab Means within a row lacking common superscript differ significantly (P < 0.05) Except for the control, all treatments had similar methane content ranging from 50% to 60% with an average of approximately 57% after first SRT. This value is within the range reported for AD of food waste (52-63% CH4; Banks et al., 2011; Zhang et al., 2011). The calculated average specific methane production rate (mL/g VS added) during the steady-state period is shown in Figure 4.7. The non-supplemented control (FW) had an average specific methane production rate of 254 mL/g VS added/day which were significantly lower than the food waste reactor supplemented with trace elements (FW+TE), humic acids (FW+HA) and vermicompost (Figure 4.7, P< 0.05). The observed greater specific methane production rates (more than 400 mL/g VS added/day) for the digesters supplemented with trace elements, humic acids, and VC were similar to the results found by Zhang et al. (2011) who reported the specific methane yield up to 450 mL/g VS added/day) from long-term anaerobic digestion of cafeteria food waste supplemented with trace elements (Co, Fe, Mo and Ni) in semi-continuous single-stage reactors. 73 450 Specific methane production rate (mL/g VS added/day) 430 ** ** ** 410 390 370 350 330 * 310 290 270 250 FW FW+TE FW+HA FW+VC FW= food waste; TE= trace elements; HA= humic acids; VC= vermicompost * Data with different superscript differ significantly (P <0.05); error = SEM Figure 4.7 Specific methane production rates (per gram VS added) of food waste digesters with and without additives 4.3.3 Trace Metal Analysis Since only soluble metal ions are considered to be available for uptake by anaerobic microorganisms (Callander and Barford, 1983; Zandvoort et al., 2006); the concentrations of soluble Ni, Fe, and Co of digester effluents were analyzed to estimate bioavailability (Figure 4.8). As shown in Figure 4.8, the concentrations of soluble Ni and Co of the food waste digester supplemented with trace elements and vermicompost were significantly greater than the control (FW; P < 0.05). No differences in the concentration of soluble Ni and Co were observed between the food waste digester supplemented with or without humic acid. This suggested that enhanced methane production by supplementation of humic acid (Figure 4.7) was not related to change in the concentrations of Ni or Co. 74 0.022 0.020 0.018 Soluble Ni (mg/L)** ** * * 0.016 0.014 0.012 0.010 FW 0.044 0.042 0.040 0.038 0.036 0.034 0.032 0.030 0.028 FW+HA Soluble Co (mg/L) ** FW+VC ** * FW 2.70 2.40 2.10 1.80 1.50 1.20 0.90 0.60 0.30 0.00 FW+TE * FW+TE FW+HA Soluble Fe (mg/L) FW+VC **** *** ** * FW FW+TE FW+HA FW+VC FW= food waste; TE= trace elements; HA= humic acids; VC= vermicompost * Data with different superscript differ significantly (P <0.05); error = SEM Figure 4.8 Soluble metal concentrations of food waste digesters with and without additives In the other hand, the soluble Fe concentrations of the food waste reactor supplemented with additives (trace elements, humic acid, and VC) were all 75 significantly higher than the control (Figure 4.8, P<0.05). This suggested that the control reactor had less available Fe for microorganism to uptake which may be related to its unstable and lower biogas production rate compared to other treatments. Because humic acids contains negligible amount of Fe (an estimated 0.01 mg/L of Fe in the reactors originated from humic acids), it was surprising to discover that the soluble Fe concentration of the FW+HA reactor was significantly greater than the control. One possible explanation is that the humic acids increased the solubility of Fe as its presence could prevent the formation of insoluble Fe salts (Rashid and Leonard, 1973). Fe (II) can chelate with humic acids to form soluble humic acid-Fe complexes (Chen et al., 2004). In this study, it is possible that humic acids and Fe (II) (ferrous iron originating from food waste) formed soluble humic acid-Fe complexes that decreased the precipitation of Fe (II) and, consequently, increased its solubility. 4.3.4 Digester Effluent Measurement The alkalinity, total VS reduction, and ammonia-N concentration of digester effluents during the steady-state period were analyzed and reported in the Table 4.6. Compared to the control, the food waste digester supplemented with trace elements, humic acids, and VC had greater alkalinity (Table 4.6). The reactor supplemented with VC had highest alkalinity suggested that supplementation of VC likely increased the capacity of the food waste reactor to buffer the pH in the presence of additional acids. The total VS reduction of the food waste digester supplemented with vermicompost, trace elements and humic acids were greater than the control. The 76 less total VS destruction of the control was likely attributed to the accumulation of VFAs and drop of the digester pH. Table 4.6 Digester effluent measurement during steady-state period Items FW FW + TE FW +HA FW + VC Alkalinity b b c a 1419 1345 1717 (mg/L as 943 ± 110 ± 30 ± 49 ±15 CaCO3) Total VS a b b b reduction 54 ± 5 70 ± 2 68 ± 4 70 ± 3 (%) Ammonia-N 223± 6 219± 7 220± 8 227± 8 (mg/L) 176:21:1 168:22:1 139:18:1 120:10:1 COD: N: P Values were reported as average ± SEM; FW= food waste; TE= trace elements; HA= humic acids; VC= vermicompost; COD= chemical oxygen demand; N= nitrogen; P= phosphorus abc Means within a row lacking common superscript differ significantly (P< 0.05) There was no significant difference in the concentrations of ammonia-N between the control and other treatments (Table 4.6) which indicated that ammoniaN inhibition is not the cause of poor performance. In fact, the digester ammonia-N concentrations were much lower than the toxic level of 1,700 to 14,000 mg/l reported in the literature (Chen et al., 2008). The COD/N/P ratios of FW digesters with or without additives were not in the recommended range of 100-130:4:1 (Bouallagui et al., 2003) for optimal gas production from fruit and vegetable waste. This suggested that the COD/N ratio was not effectively adjusted by adding manure VC. 4.3.5 Specific Methane Production The specific methane production per gram VS destroyed (mL/g VS destroyed/day) was calculated by dividing daily biogas or methane production by total 77 VS destroyed (VS of food waste and vermicompost) during steady-state are shown in Figure 4.9 Specific methane production rate (mL/g VS destoryed/day) 700 ** 650 ** ** 600 550 * 500 450 400 350 300 FW FW+TE FW+HA FW+VC FW= food waste; TE= trace elements; HA= humic acids; VC= vermicompost * Data with different superscript differ significantly (P <0.05); error = SEM Figure 4.9 Specific methane production rates (per gram VS destroyed) of food waste digesters with and without additives The non-supplemented control (FW) had an average specific methane production rate of 455 mL/g VS destroyed/day, which was significantly lower than the food waste reactors supplemented with trace elements, humic acids, and vermicompost. There was no significant difference between the food waste reactors supplemented with different additives. Numerically, the food waste digester receiving vermicompost (FW+VC) as the supplement had the greatest specific methane production rate of 625 mL/g VS destroyed/day. 4.4 Conclusions and Implication The FW used in the study (particularly second batch) appeared to be deficient in trace elements which caused the failure of single-stage AD in terms of unstable 78 and low biogas productions, decreased pH, and the significant accumulation of VFA. With the supplementations of manure VC, trace metals (Ni, Fe, and Co), or humic acids, biogas production and the pH were maintained at desirable ranges while the concentration of VFAs in the reactors remained low. Additionally, it was also found that humic acids naturally presented in mature manure vermicompost were able to increase the solubility of Fe (II). 79 CHAPTER 5 EFFECTS OF VERMICOMPOST ON METHANOGENIC ACTIVITY DURING ANAEROBIC DIGESTION OF FOOD WASTE The third stage of dissertation research is presented in this chapter including introduction; material and methods; results and discussion; and conclusions and implication sections. 5.1 Introduction The semi-continuous study (Chapter 4) indicated that the single-stage food waste digester without supplements experienced a significant accumulation of VFA. VFA accumulation reflects a kinetic uncoupling between acid producers and acid consumers which is typical for stress situations (Ahring et al., 1995). Digesters supplemented with VC, on the other hand, maintained stable biogas productions with no significant VFA accumulation. To better understand the cause, methanogenic activities were assessed. The specific methanogenic activity test enables the measurement of activity for the various physiological groups of microorganisms involved in the terminal processes of methanogenesis (Sorensen and Ahring, 1993). Activity is estimated by supplying sufficient substrate (such as acetate and propionate) to saturate the catabolic systems of the various physiological groups and then measuring the specific methane production rate or the substrate utilization rate (Sorensen and Ahring, 1993; Switzenbaum et al., 1990). Although there are three principal groups of methanogens, including acetotrophic (also known as acetoclastic), hydrogenotrophic, and methlotrophic methanogens, involved in utilizing substrates to produce CH4. A 70% of CH4 is typically derived from acetate through the activity of acetoclastic methanogens 80 (Gujer and Zehnder, 1983). Also, CH4 is produced by the syntrophic activity of acetate-oxidizing bacteria and hydrogenotrophic methanogens under certain environmental conditions (Hattori, 2008). Therefore, the maximum acetate utilization rate (MAUR) is a simple and good indicator of methanogenic activities (Dolfing and Bloemen, 1985; James et al., 1990; Nopharatana et al., 1997) and was used in this study to evaluate methanogenic activities. In addition to acetate, propionate is another key intermediate in AD. It has been reported that its accumulation was the primary cause for the food waste digester failure (Banks et al. 2012). Therefore, the maximum propionate utilization rate (MPUR) also was used for assessment of methanogenic activities. In summary, the objective of this study is to determine the effects of VC on specific methanogenic activities in terms of MAUR and MPUR during the AD of food waste. 5.2 Material and Methods Experimental material and methods are presented in this subsection. 5.2.1 Sampling and Experimental Design During the sixth SRT of semi-continuous study (Chapter 4), digester effluents from the food waste reactor without any additive (Control), the food waste reactor with trace elements (FW+TE), the food waste reactor with humic acids (FW+HA), and the food waste reactor with vermicompost (FW+VC) were collected to represent the digester contents. The methanogenic activity test followed immediately and was repeated three times (on three different days) to ensure repeatability. The experimental design is shown in Table 5.1. 81 Table 5.1 Experimental design of the methanogenic activity test Treatments Sample (inoculum) MAUR test MPUR test source substrate substrate Control FW only reactors 7500 mg/L 3000 mg/L Acetate Propionate FW+TE FW+TE reactors FW+HA FW+HA reactors FW+VC FW+VC reactors FW= food waste; TE= trace elements; HA= humic acids; VC= vermicompost; MAUR= the maximum acetate utilization rate; MPUR= the maximum propionate utilization rate 5.2.2 Experimental Setup The MAUR and MPUR tests were performed using the assays described by Speece (1988) with slight modifications. A 120 mL representative sample of the digestate was placed in a 225 mL liquid capacity serum bottle (same as those used in the BMP trial; Chapter 3, section 3.2.3). An additional 100 mL of DI water was added to bring the total volume to 220 mL and the bottles were covered tightly with septa caps. The DI water was added to minimize the volume of head space which improves accuracy as discussed in Chapter 2 section 2.1.5. The headspace was flushed with pure N2 gas at a flow rate of approximately 0.5 L/min for 5 min to ensure anaerobic conditions. All bottles were placed on a shaker (100-150 rpms) and incubated at 35° After reaching temperature equilibration (about 2 hours), each C. bottle was injected with a small volume (5 mL) of sodium acetate (the MAUR test) or sodium propionate (the MPUR test) stock solution. The target concentration of acetate and propionate were 7500 mg/L and 3000 mg/L, respectively. These levels are sufficient to allow the methanogens to function at their maximum rate. A needle attached to the gas collection line was inserted through the caps of each bottle (Figure 5.1). 82 Figure 5.1 Methanogenic activity test experimental set-up Biogas first flowed through the needle to a carbon dioxide adsorption unit (a bottle containing 220 mL sodium hydroxide solution with a blue color indicator) and then into the individual automatic gas measuring cells manufactured by Challenge Technologies (AER-208 - Research Respirometer Aerobic/Anaerobic, Challenge Technologies Inc., Springdale, AR) (Figure 5.1). Attachment of a carbon dioxide adsorption unit in the gas line allowed for the direct determination of the specific methane production. Methane production was continuously monitored for 24 hrs using computer software as described in Chapter4, section 4.2. 5.2.3 Data Processing The 24-hr cumulative methane production was divided by the volume of effluent sample (120 mL) to normalize the data as volumes of methane per volume of effluent sample per day (L/L/day). The experimental units of the study were 12 identical reactors. There was 1 independent variable (additive) and 4 levels including no additive (control), TE, HA, and VC. Each was run in triplicate. The dependent variable in this experiment was 83 the MAUR and the MPUR. Statistical analysis was performed using SAS software version 9.1(SAS Institute Inc.). Significant differences among treatments were determined by one-way ANOVA with the Tukey-Kramer multiple-comparison test. Differences were considered significant at a P value of ≤ 0.05. 5.3 Results and Discussion Experimental results and discussion are presented in this subsection. 5.3.1 Maximum Acetate Utilization Rate The maximum acetate utilization rate is shown in Figure 5.2. 0.70 ** 0.65 ** ** FW+TE FW+HA MAUR (L/L/day) 0.60 0.55 0.50 0.45 0.40 0.35 * 0.30 Control FW+VC *Data with different superscript differed significantly, P<0.05; FW= food waste; TE= trace elements; HA= humic acids; VC= vermicompost; MAUR= the maximum acetate utilization rate; error bars represents SEM Figure 5.2 Maximum acetate utilization rates of food waste digesters with and without additives The food waste reactor supplemented with vermicompost had the greatest maximum acetate utilization rate, 0.68 L/L/day, nearly double that of the control (0.34 L/L/day) (Figure 5.2). However, the difference among the reactors supplemented 84 with trace elements, humic acids, and VC were not significant. Results showed that food waste reactors with supplements all contained more soluble Fe than the control reactors (Chapter 4, Figure 4.8) which may be the cause of the observed MAUR improvement. Iron is essential for enzymes that catalyze metabolic reactions during methanogenesis (Zandvoort et al., 2006). Hoban and Berg (1979) indicated that addition of Fe to methanogenic cultures (obtained from AD treated food processing waste) significantly increased the conversion of acetate to methane. 5.3.2 Maximum Propionate Utilization Rate The maximum propionate utilization rate is shown in Figure 5.3. 0.230 ** 0.210 MPUR (L/L/day) 0.190 0.170 0.150 0.130 * * * 0.110 0.090 FW(control) FW+TE FW+HA FW+VC *Data with different superscript differed significantly, P<0.05 FW= food waste; TE= trace elements; HA= humic acids; VC= vermicompost; MPUR= the maximum propionate utilization rate; error bars represents SEM Figure 5.3 Maximum propionate utilization rates of food waste reactors with and without additives The food waste reactor supplemented with vermicompost had a much greater maximum propionate utilization rate (0.197 L/L/day) than the control and other 85 treatments (Figure 5.3). There was no difference among the control and the reactors supplemented with trace elements or humic acids (average 0.12 L/L/day). Consequently, Ni, Fe, Co, and humic acids do not appear to have an impact. However, some previously undetermined factors of VC significantly enhanced the MPUR of food waste digesters. This enhancement in corresponded to the increased overall biogas and methane production (reported in Chapter 4) from the food waste reactor supplemented with vermicompost compared to those from the reactors supplemented with trace elements and humic acids Propionate is a key intermediate in the conversion of complex organic matter under methanogenic conditions (De Bok et al., 2004). Propionate oxidation can only proceed if the products, H2 and formate are removed by methanogens or H2 or formate utilizing bacteria (Stams, 1994). Mo, W, and Se are crucial components of essential enzymes catalyzing formate dehydrogenase (FDH) (Dong et al., 1994). In defined cultures of Syntrophobacter fumaroxidans and Methanospirillum hungatei with propionate as the sole substrate, limitation of Mo and W lowered the methane production rate and the FDH activity (Jiang, 2006). Therefore, insufficient amounts of Mo and W could result in a slow rate of propionate utilization (Fernando et al., 2009). This could be the case for current findings. Unfortunately, Mo, W, and Se were not measured in this study but the literature shows that manure VC is abundant with these trace metals (Hervas et al., 1989). Finally, the MAUR and MPUR were analyzed during the last SRT. Therefore, results only reflected the MAUR and MPUR of reactors operated during the sixth SRT. It is expected that the MAUR and MPUR of the food waste reactors supplemented with trace elements (FW+TE), humic acids (FW+HA), and vermicompost (FW+VC) were relatively consistent as evidenced by stable biogas 86 and methane production. In contrast, the MAUR and MPUR of the control reactor during the third and fourth SRT would have been likely lower than the values reported in this chapter, if they would have been measured, as the result of depressed methanogens activities. 5.4 Conclusions and Implication Manure VC significantly improved methanogenic activities of FW digesters as evidenced by a nearly doubled MAUR and a 60% increase in MPUR compared to FW digesters with no supplements. Improvement in acetate and propionate utilization by VC is likely the cause of the overall enhancement in digestion performance described in earlier chapters. 87 CHAPTER 6 ASSESSMENT OF BIOAVAILABILITY AND STIMULATION EFFECTS OF NICKEL, IRON AND COBALT ON ANAEROBIC DIGESTION OF FOOD WASTE The fourth stage of dissertation research is presented in this chapter including introduction; material and methods; results and discussion; and conclusions and implication sections. 6.1 Introduction To further quantify the stimulatory effect of trace metals (Ni, Co, and Fe) (individually instead of as a mixture) on the methanogenesis of FW digestion, the bioavailability assay procedure described by Speece (1987) was used in this phase of the research. 6.2 Material and Methods Experimental material and methods are presented in this subsection. 6.2.1 Experimental Design and Setup The experimental design is shown in Table 6.1. Table 6.1 Experimental design of trace metal bioavailability trial Trace metal Treatments Inoculum source Substrate concentrations Control 0 mg/L T1 Ni (0.01 mg/L) T2 Ni (1 mg/L) T3 Ni (10 mg/L) Food waste T4 Fe (0.5 mg/L) digesters (control Acetate (7500 digesters in mg/L) T5 Fe (5 mg/L) chapter 4) T6 Fe (100 mg/L) T7 Co (0.01 mg/L) T8 Co (1 mg/L) T9 Co (10 mg/L) 88 Effluents from the semi-continuous FW reactors (control reactors) during the sixth SRT were used for sample evaluation in the current study. The experimental design consisted of one control and 9 treatments (Table 6.1) with each run in triplicate (total of 30 reactors). Due to the limitation of equipment, the study was completed in series. For each trace metal, three dosages were evaluated; low, medium, and high. The low dosage was set equal to the concentrations used during the semi-continuous study. These concentrations were 0.01, 0.5, and 0.01 mg/L for Ni, Fe, and Co, respectively (Chapter 4, Table 4.2). The medium dosages of Ni, Fe, and Co were 1, 5, and 1 mg/L, respectively. The purpose of this dosage was to evaluate if further improvement is possible at an elevated concentration. The high dosages of Ni, Fe, and Co were 10, 100, and 10 mg/L, respectively. The objective of this group is to determine if these levels are toxic. The experimental setup was similar to the MAUR and MPUR assays described in Chapter 5, Section 5.2. A 120 mL sample (inoculum) was placed in each 225 mL serum bottles, diluted with additional DI water, flushed with N2 gas, and sealed for incubation at 35º After initial temperature equilibration (2 hours), all C. reactors were then injected with 5 mL of a sodium acetate stock solution to bring the acetate concentrations to 7500 mg/L. Then additional trace metal solutions with the desired Ni, Fe, and Co concentrations (Table 6.1) were injected. The methane production was monitored using the same procedure as described in Chapter 5, Section 5.2. 6.2.2 Data Process and Interpretation The experimental units were 30 identical batch-scale reactors. A completely randomized design was achieved by randomly assigning reactors to 10 treatments (3 89 replicate per treatment). However, the statistical analysis was conducted separately to study the effects of each individual metal on digestion of FW. For each metal, there was one independent variable with 4 levels (concentrations of metal at 0, low, medium, and high). The dependent variable was the daily methane production. Significant differences were determined by one-way ANOVA with the Tukey-Kramer multiple-comparison test. Differences were considered significant at a P ≤ 0.05. In addition, any treatment that produced more methane (P< 0.05) than the control was considered to stimulate methane production. 6.3 Results and Discussion Experimental results and discussion are presented in this subsection. 6.3.1 Nickel Addition As shown in Figure 6.1, there was no difference between the control and 0.01 mg/L Ni treatment, suggesting that the daily methane yield was not stimulated by Ni at this concentration. Therefore, the observed improvement in earlier studies (semicontinuous study and methanogenic activity assays) was not likely due to the existence of additional Ni at 0.01 mg/L. However, nickel stimulated the methane production rate significantly at the concentration of 1 mg/L (P < 0.05). Nickel is essential for the methyl-coenzyme M reductase (Harmer et al., 2008) and carbon monoxide dehydrogenase (Friedman et al., 1990). This indicated that food waste as sole substrate for AD could be deficient in Ni and supplementation of additional Ni may result in greater methanogenic activity and consequently increase the methane production. However, inhibition 90 could occur at the concentration of 10 mg/L under the current experimental condition (Figure 6.1). 80 *** Methane Yield (mL/day) 70 60 50 40 ** ** 30 * 20 Control Ni (0.01 mg/L) Ni (1 mg/L) Ni (10 mg/L) *Data with different superscript differ significantly, P < 0.05; error =SEM Figure 6.1 Effects of nickel on daily methane yield from the food waste digester 6.3.2 Iron Addition Effects of iron on daily methane yield are shown in Figure 6.2. 60 Methane Yield (mL/day) 55 ** ** ** 50 45 40 * 35 Control Fe (0.5 mg/L) Fe (5 mg/L) Fe (100 mg/L) *Data with different superscript differ significantly, P < 0.05; error =SEM Figure 6.2 Effects of iron on daily methane yield from the food waste digester 91 Iron supplementation at 0.5, 5 or 100 mg/L all significantly improved daily methane yields (Figure 6.2). Combined with the results found in the earlier studies, the FW (especially batches 2) used for current study was deficient in Fe which resulted in a slow rate of acetate conversion and suppressed methane production. This low acetate utilization rate resulted in the accumulation of acetate which could explain the higher concentration of VFA and pH drop observed in the semicontinuous study. Iron is a critical element for carbon monoxide dehydrogenase complex (Friedman et al., 1990), an enzyme complex involved in the formation of acetate and methanol (Ferry, 1999; Bainotti and Nishio, 2000). Iron is also needed for F420reducing hydrogenase that catalyzes the reduction of CO2 to CH4 (Michel et al., 1995). Due to its essential role in metabolizing enzymes, it has been frequently reported that supplementation of Fe enhances AD (Hoban and van den, 1979; Ma et al., 2009; Oleszkiewicz, 1989; Sharma and Singh, 2001; Shen et al., 1993). 6.3.3 Cobalt Addition The effect of cobalt on the acetate conversion rate in food waste digester is shown in Figure 6.3. No significant improvements were observed at any concentrations of Co supplementation and methane production was inhibited at the concentration of 10 mg/L. Consequently, Co was not likely impacting AD performance. 92 Methane Yield (mL/day) 45 40 ** ** ** 35 30 * 25 20 Control Co (0.01 mg/L) Co (1 mg/L) Co (10 mg/L) *Data with different superscript differ significantly; error =SEM Figure 6.3 Effects of cobalt on daily methane yield from the food waste digester 6.4 Conclusions Additional nickel and iron could stimulate the AD of FW. In contrast, cobalt had no significant effects on the methane yield under current experimental conditions. 93 CHAPTER 7 GENERAL CONCLUSIONS In summary, this research proved its central hypothesis that the supplementation of manure VC to a single-stage AD system using food waste as the substrate stimulated methane production and enhance process stability. A brief summary of this research is shown in Figure 7.1. Sub-hypothesis 1: supplementation of manure VC stimulate methane production from AD of food waste using batch-scale reactor Proved hypothesis 1 BMP Assay (Chapter 3) Results Supplementation of manure VC significantly increased the ultimate methane yield Supplementation of manure VC enhanced methane production rate Question s Why manure VC stimulated methane production? Could manure VC stimulate methane production from continuous operated reactors? Sub-hypothesis 2: trace metals contained in VC stimulate methane production Sub-hypothesis 3: humic acids contained in VC stimulate methane production Sub-hypothesis 4: supplementation of manure VC stimulate methane production from AD of food waste using semi-continuous reactor Long term semi-continuous trial (Chapter 4) Figure 7.1 Summary of research 94 Figure 7.1 (cont’d) Proved hypothesis 2 Proved hypothesis Results 3 Supplementation of trace metals (mixture of Ni, Fe, and Co) significantly increased methane yield Proved hypothesis 4 Supplementation of humic acids significantly increased methane yield Supplementation of manure VC significantly increased methane yield Question Question Which one of the three metals stimulate methane yield from food waste? Which stage of digestion process was stimulated? Sub-hypothesis 8: manure VC stimulate methanogenesis stage Sub-hypothesis 5: Ni stimulate methane yield Sub-hypothesis 6: Fe stimulate methane yield Proved hypothesis 8 Specific methanogenic activity test (Chapter 5) Sub-hypothesis 7: Co stimulate methane yield Results VC stimulate acetate utilization Metal bioavailability study (Chapter 6) Results VC stimulate propionate utilization Ni stimulated methane yield Fe stimulated methane yield Co stimulated methane yield Proved hypothesis 5 Proved hypothesis 6 Reject hypothesis 7 This study demonstrated that the AD of cafeteria FW without supplementation experienced unstable and low methane production resulting from a dramatic pH drop 95 and the accumulation of VFAs. Supplementation of manure VC to the food waste digester was an effective strategy to improve digestion performance. In this research, supplementation of VC increased biogas and methane production from food waste by 53% and 70%, respectively, nearly doubled the acetate utilization rate, and enhanced the propionate utilization rate by 60%. Such enhancements were likely due to the trace metals (particularly iron and nickel) and humic acids naturally presented in manure VC. The likely mechanism is illustrated in Figure 7.2. Supplementation of manure vermicompost Without any additives Slow conversions of acetate and proprionate Increase acetate and proprionate utilization rates Accumulation of VFAs Prevent accumulation of VFAs pH drop Prevent pH drop Further inhibit methanogenesis Improved digestion performance Digester failure Figure 7.2 Mechanisms associated with enhanced digestion performance of the food waste digester supplemented with vermicompost Many trace metals that are essential for AD of food waste, such as Se, Mo, W, and Mn, were not investigated in this study but are likely contained in VC. Banks et al. (2012) found that additional Se is critical for stabile digestion of high OLR food 96 waste (5 g VS/L/day) with elevated ammonia concentrations (5000 mg/L). Similarly, a trace element supplementation experiment conducted by Feng et al. (2010) using food industry waste showed that addition of Se and W increased methane yield as well as maintained low VFA concentrations. Interestingly, the third batch of food waste (containing similar VS as the other batches but with greater trace metals) resulted in the slow recovery of methane production yet still a reduced level of methane production. This may further supports that a variety of bioavailable trace metals in imperative need for the AD of food waste and the benefits of supplementation with VC. Although the metal bioavailability studies conducted in this research allowed for the efficient realization of the hypothesis, a more in-depth understanding of the impact of vermicompost on methanogenic activity and optimization of dosage is possible using microbial community analyses tools. A number of analyses targeting rRNA or protein-coding genes have been used for the purpose of studying the microbial communities’ composition of anaerobic process (Feng et al., 2010). For example, Fermoso et al. (2008) used fluorescence in situ hybridization to quantify the abundance of key microorganisms in a mesophilic anaerobic reactor (fed with methanol) under cobalt limiting conditions. It was suggested by Talbot et al. (2008) that microbial community fingerprinting techniques using small subunit rRNA gene may be the most suitable molecular method for detecting changes in community composition or metabolic activities during AD process. Examples of such fingerprinting techniques include denaturing gradient gel electrophoresis, ribosomal RNA intergenic spacer analysis, and terminal restriction fragment length polymorphism. 97 Compared to commercial mineral nutrient products, which are primarily produced from nonrenewable resources, VC is a more eco-friendly additive. The main production requirements for the vermicomposting process are land, shelter, labors and mechanical energy to move materials on site. A future study should entail conducting a life cycle analyses to fully quantify both options. Supplementation of VC in the food waste digester should also consider some possible disadvantages such as the additional volume requirements within the digester, skill to manage the vermicomposting system, and the difficulty in controlling the concentration of specific trace metals. This study demonstrated that trace metals and humic acids are the major stimulatory factors contained in manure VC. However, from a system design standpoint, using food waste itself as the feedstock for the vermicomposting process is desirable as the addition of manure is not required. However, carbon is lost during vermicomposting process, reducing valuable energy output from the digester. Therefore, an alternative to consider is the use of digestate from a food waste digester as the substrate for the vermicomposting procss as nutrients and metals are still present. This allows for an integrated vermicomposting and AD system as shown in Figure 7.3. Some vermicompost used as the additive Food waste Anaerobic digester Continuous flow vermicomposting reactor Digestate Land applied Figure 7.3 Integrated vermicomposting and anaerobic digestion system for food waste management 98 Food waste is fed to the anaerobic digester for energy production. The digestate is then added to the continuous flow vermicomposting reactor, in thin layers to the surface from mobile gantries at 1 to 2 day intervals, and the VC is collected mechanically at the bottom of the reactor. Portion of the VC is added back to the anaerobic digester for stimulation of digestion process. The remaining VC can be used as soil amendment. Such an integrated system should be tested as it allows for more stable and efficient digestion of food waste for energy recovery, produces higher value fertilizer, and produces worms that could be used for baits and fish food. 99 APPENDICES 100 APPENDIX A Biochemical Methane Potential Assays Data Summary 101 Table A1.1 Characteristic of raw food waste Subsamples Parameter 1 2 3 pH 6.5 6.6 6.6 TS (w.t. %) 22.6 21.2 23.8 VS (w.t.%) 21.1 19.8 21.9 VS/TS (%) 93.4 93.5 92.0 Total COD (g/kg) 246.0 260.5 254.3 TKN (g/kg) 7.7 7.2 8.1 TP (g/kg) 1.6 1.4 1.7 Ammonia-N (g/kg) 0.23 0.20 0.29 Alkalinity (g CaCO3/kg) 0.46 0.50 0.52 AVG 6.6 22.5 20.9 93.0 253.6 7.7 1.6 0.24 0.49 Table A1.2 Characteristic of dairy manure vermicomposts Subsamples Parameter 1 2 3 AVG STD pH 6.9 6.8 6.9 6.9 0.1 TS (w.t. %) 15.4 15.8 15.2 15.5 0.3 VS (w.t.%) 6.3 6.8 6.4 6.5 0.3 Table A1.3 pH change during the BMP assay Pre-digestion Post-digestion Treatments AVG STD AVG STD Control (C) 7.6 0.1 6.9 0.1 FWVC1 7.5 0.1 6.9 0.1 FWVC2 7.6 0.1 6.9 0.1 FWVC3 7.7 0.1 6.8 0.1 VC 7.9 0.1 6.7 0.1 Table A1.4 Ammonia-N change during the BMP assay (mg/kg) Pre-digestion Post-digestion Treatments AVG STD AVG STD Control (C) 111 2 186 2 FWVC1 112 3 201 6 FWVC2 111 4 204 4 FWVC3 114 2 195 4 VC 109 1 144 1 102 STD 0.1 1.3 1.0 0.8 7.3 0.5 0.2 0.05 0.03 Table A1.5 COD change during digestion (g/kg) Pre-digestion Post-digestion Treatments AVG SEM AVG SEM Control (C) 16.0 0.1 11.9 0.1 FWVC1 16.2 0.3 12.0 0.1 FWVC2 16.4 0.2 11.6 0.2 FWVC3 16.9 0.2 11.8 0.1 VC 15.5 0.1 14.9 0.1 Blank 9.6 0.1 9.2 0.1 Day 5 10 15 20 25 30 Table A1.6 Average weekly cumulative biogas yield (mL) Control FWVC1 FWVC2 FWVC3 VC AVG STD AVG STD AVG STD AVG STD AVG STD 89 4 88 5 102 5 100 2 3 1 170 4 174 5 216 8 186 4 11 1 221 6 229 6 264 7 224 6 13 1 250 6 259 6 280 8 233 6 15 2 267 5 272 7 294 9 238 7 16 2 278 4 280 9 294 10 239 8 17 2 Table A1.7 Average specific biogas production rate (mL/g FW VS added) Control FWVC1 FWVC2 FWVC3 VC Day AVG STD AVG STD AVG STD AVG STD AVG STD 5 199 9 201 12 256 14 333 7 6 2 10 378 9 395 12 541 20 621 15 24 2 15 491 13 521 14 659 18 745 18 28 3 20 556 13 589 14 700 19 778 18 33 4 25 594 11 617 16 735 22 793 22 36 5 30 618 10 637 19 734 25 798 26 38 5 Day 5 10 15 20 25 30 Overall Mean Table A1.8 Average methane content (%) Control FWVC1 FWVC2 FWVC3 AVG STD AVG STD AVG STD AVG STD 39.0 0.4 38.8 0.4 39.2 0.4 38.5 0.4 57.9 0.6 63.5 0.6 65.4 0.7 64.2 0.6 63.3 0.6 64.1 0.6 62.4 0.6 63.1 0.6 66.7 0.7 65.8 0.7 65.3 0.7 66.1 0.7 58.4 0.6 58.6 0.6 61.2 0.6 59.1 0.6 55.1 0.6 56.7 0.6 56.8 0.6 58.1 0.6 60.3 61.7 62.2 103 62.1 VC AVG STD 30.7 0.3 38.4 0.4 40.7 0.4 38.0 0.4 36.0 0.4 34.0 0.3 37.4 Day 5 10 15 20 25 30 Table A1.9 Average cumulative methane yield (mL) Control FWVC1 FWVC2 FWVC3 VC AVG STD AVG STD AVG STD AVG STD AVG STD 50 4 52 5 54 5 60 2 1 1 106 4 123 5 137 8 121 4 4 1 122 6 140 6 161 7 134 6 5 1 145 6 160 6 170 8 141 6 5 2 149 5 166 7 176 9 148 7 6 2 155 4 171 9 182 10 154 8 6 2 Table A1.10 Average specific methane production rate (mL/g FW VS added) Control FWVC1 FWVC2 FWVC3 Day AVG STD AVG STD AVG STD AVG STD 5 113 9 116 12 145 14 194 5 10 240 9 267 12 326 20 381 10 15 289 13 315 14 384 18 435 12 20 328 13 347 14 405 19 451 12 25 337 11 357 16 418 22 462 15 30 351 10 369 19 429 25 475 29 Normalized volatile solid reduction of food waste (%) 81 79 77 75 73 71 69 67 65 Control (C) FWVC1 FWVC2 FWVC3 Figure 8.1 Normalized volatile solid (VS) destruction of food waste after 30 days of AD* * The normalized VS destruction of food waste was calculated by subtracting volatile solid destruction of vermicompost and inoculum); total VS destructions of control and treatments were shown in Table 3.5, column 5; The VS destruction of inoculum was 0.005 g; The VS destruction of vermicompost = 0.02 g-0.005 g = 0.015 g (with a 0.45 g initial VS). The calculated vermicompost destruction rate (%) =0.015 g/0.45 g = 3.3%; for each treatment, vermicompost destruction = initial VS of supplemented vermicompost (g) ×vermicompost destruction rate (%). The calculation is shown in the following table 104 Table A1.11 Normalized volatile solid reduction of food waste Item Control FWVC1 FWVC2 FWVC3 Average total VS destroyed (g) Vermicompost and inoculum VS destruction (g) Normalized destroyed VS of food waste (g) 0.303 0.299 0.284 0.246 0.005 0.005 0.007 0.01 0.298 0.294 0.277 0.236 105 Initial VS of food waste (g) Normalized VS destruction of food waste (%) 0.45 0.44 0.4 0.3 66 67 70 79 APPENDIX B Semi-continuous Study Data Summary 106 Table A2.1 Characteristics of raw food waste Batch Items 1 2 3 AVG 6.6 6.2 6.8 6.5 pH 23.4 22 25 23.5 TS (w.t. %) 21.8 20.4 23.6 21.9 VS (w.t.%) 93.2 92.7 94.4 93.4 VS/TS (%) 7.7 6.4 8.1 7.4 TKN (g/kg) 1.6 1.1 1.3 1.3 TP (g/kg) 0.24 0.16 0.11 0.2 Ammonia-N (g/kg) 0.49 0.31 0.52 0.4 Alkalinity (g CaCO3/kg) STD 0.2 1.2 1.3 0.7 0.7 0.2 0.1 0.1 Table A2.2 Characteristics of dairy manure vermicompost Samples Items 1 2 3 AVG pH 6.9 6.8 6.9 6.9 TS (w.t. %) 35.7 35.0 35.6 35.4 VS (w.t.%) 15.0 15.0 14.9 15.0 Total COD (g/kg) TKN (g/kg) 7.9 7.9 TP (g/kg) 0.47 0.5 Ammonia-N (g/kg) 0.03 0.028 0.038 0.032 Alkalinity (g CaCO3/kg) 3.6 3.2 2.8 3.2 - Data is not available SRT 1 2 3 4 5 6 AVG STD Table A2.3 Average influent pH of all reactors FW + FW only FW + TE FW + HA FW + VC TE + HA 6.5 6.5 6.5 6.5 6.5 6.6 6.6 6.6 6.6 6.6 6.6 6.7 6.6 6.6 6.6 6.6 6.6 6.6 6.6 6.6 6.6 6.6 6.5 6.5 6.5 6.6 6.6 6.7 6.7 6.6 6.6 6.6 6.6 6.6 6.6 0.1 0.1 0.1 0.1 0.1 107 STD 0.1 0.4 0.1 0.000 0.005 0.4 FW + TE + VC 6.5 6.6 6.7 6.6 6.5 6.6 6.6 0.1 SRT 1 2 3 4 5 6 Table A2.4 Average effluent pH of all reactors FW FW+ FW+ FW+ FW+ Days Only TE HA VC TE+HA 2 7.6 7.6 7.6 7.6 7.7 4 7.5 7.5 7.5 7.6 7.7 6 7.5 7.5 7.5 7.5 7.5 8 7.2 7.2 7.2 7.5 7.5 10 7.3 7.2 7.3 7.2 7.2 12 7.3 7.2 7.2 7.2 7.3 14 7.3 7.3 7.2 7.2 7.2 16 7.2 7.3 7.2 7.2 7.3 18 7.3 7.3 7.2 7.3 7.2 20 7.3 7.2 7.2 7.2 7.2 22 7.2 7.2 7.3 7.2 7.2 24 7.2 7.3 7.2 7.3 7.3 26 7.2 7.3 7.2 7.2 7.3 28 7.2 7.2 7.3 7.2 7.2 30 7.2 7.2 7.2 7.2 7.3 32 6.8 7.3 7.2 7.3 7.2 34 6.5 7.2 7.2 7.3 7.2 36 6.3 7.1 7.2 7.2 7.2 38 6.2 7.3 7.3 7.1 7.1 40 6.3 7.2 7.3 7.3 7.2 42 6.4 7.2 7.3 7.1 7.3 44 6.6 7.3 7.3 7.3 7.3 46 6.1 7.3 7.3 7.4 7.3 48 5.8 7.2 7.3 7.3 7.2 50 5.9 7.2 7.2 7.2 7.2 52 5.8 7.2 7.2 7.2 7.2 54 5.8 7.3 7.2 7.2 7.2 56 5.7 7.3 7.3 7.2 7.3 58 5.7 7.3 7.2 7.2 7.2 60 5.8 7.3 7.3 7.2 7.3 62 6.0 7.3 7.2 7.2 7.3 64 6.4 7.3 7.3 7.3 7.3 66 6.5 7.3 7.3 7.2 7.3 68 6.6 7.3 7.3 7.3 7.3 70 6.7 7.3 7.2 7.2 7.3 72 6.7 7.3 7.2 7.2 7.2 74 6.7 7.3 7.2 7.3 7.2 76 6.8 7.3 7.2 7.3 7.3 78 6.8 7.3 7.2 7.3 7.3 80 6.8 7.3 7.2 7.2 7.2 82 6.7 7.3 7.2 7.3 7.2 84 6.7 7.3 7.3 7.2 7.3 108 FW+ TE+VC 7.6 7.6 7.5 7.5 7.2 7.2 7.2 7.2 7.2 7.2 7.2 7.2 7.2 7.2 7.2 7.2 7.2 7.2 7.1 7.3 7.2 7.3 7.3 7.2 7.2 7.2 7.2 7.3 7.3 7.3 7.3 7.2 7.2 7.3 7.3 7.2 7.2 7.3 7.2 7.3 7.2 7.3 86 6 88 90 Steady-state AVG Steady-state STD. Overall AVG Overall STD 6.8 6.7 6.8 Table A2.4 (cont’d) 7.2 7.3 7.3 7.3 7.2 7.3 7.2 7.2 7.3 7.3 7.2 7.3 7.3 7.2 7.3 6.4 7.3 7.2 7.2 7.3 7.2 0.4 6.7 0.5 0.1 7.3 0.1 0.1 7.3 0.1 0.1 7.3 0.1 0.2 7.3 0.2 0.01 7.3 0.1 Table A2.5 Average influent alkalinity of all reactors (mg/L as CaCO3) FW FW + FW + SRT FW + TE FW + HA FW + VC only TE + HA TE + VC 1 208 209 211 221 208 221 2 205 206 204 211 207 213 3 209 207 205 216 208 214 4 205 204 207 214 206 217 5 187 189 186 201 187 204 6 186 184 185 204 187 206 AVG 200 200 200 211 201 213 STD 10 10 10 7 10 6 Table A2.6 Average effluent alkalinity of all reactors (mg/L as CaCO3) FW + FW + FW FW + FW + FW + SRT TE + TE + only TE HA VC HA VC 1,487 1,521 1,495 1,758 1,513 1,698 1 1,425 1,534 1,492 1,737 1,547 1,742 1,253 1,472 1,459 1,690 1,456 1,703 2 1,105 1,511 1,472 1,682 1,448 1,721 1,116 1,514 1,478 1,691 1,452 1,723 3 1,009 1,414 1,287 1,708 1,427 1,690 863 1,440 1,264 1,703 1,448 1,706 4 823 1,432 1,271 1,712 1,436 1,711 721 1,402 1,314 1,723 1,418 1,726 5 775 1,383 1,375 1,745 1,404 1,713 1,123 1,375 1,383 1,755 1,404 1,729 6 1,113 1,391 1,388 1,698 1,427 1,719 Steady-state AVG 943 1,419 1,345 1,717 1,427 1,715 Steady-state STD. 156 42 69 21 17 12 Overall AVG 1,068 1,449 1,390 1,717 1,448 1,715 Overall STD 245 59 89 26 43 15 109 Table A2.7 Average influent total solid content of all reactors (g/L) SRT Days FW FW+TE FW+HA FW+VC FW+TE+HA FW+TE+VC 1 3 11.0 11.3 12.8 11.7 10.9 12.4 2 17 10.7 11.2 11.7 11.6 11.5 11.1 3 31 10.9 11.8 10.6 12.8 10.9 10.3 3 38 10.7 11.1 11.0 11.4 10.5 10.8 4 46 10.8 11.5 12.3 12.3 10.9 11.5 4 53 10.5 10.8 12.4 11.1 10.9 11.5 5 61 10.8 11.3 11.5 11.9 10.9 11.3 5 68 10.5 10.8 11.9 11.1 10.9 12.1 6 76 10.7 11.0 11.8 11.2 11.7 11.9 6 83 10.1 10.8 12.1 11.6 11.3 11.5 Table A2.8 Average influent volatile solid content of all reactors (g/L) SRT Days FW FW+TE FW+HA FW+VC FW+TE+HA FW+TE+VC 1 3 9.3 10.1 8.9 9.4 8.9 10.4 2 17 9.1 9.3 9.2 9.7 9.2 9.5 3 31 9.3 9.1 8.9 9.2 8.9 9.8 3 38 9.1 9.0 9.0 9.4 9.0 9.7 4 46 9.3 9.8 9.2 9.7 9.2 10.0 4 53 9.0 9.4 8.9 9.3 8.9 9.2 5 61 9.3 9.6 9.2 10.0 9.2 9.5 5 68 9.0 9.3 8.9 9.1 8.9 9.8 6 76 9.0 9.5 9.2 9.8 9.2 10.0 6 83 8.9 9.3 9.3 9.6 9.3 9.5 110 Table A2.9 Average effluent total solid content of all reactors (g/L) Days FW FW+TE FW+HA FW+VC FW+TE+HA FW+TE+VC 3 15.3 15.7 15.5 16.2 15.8 16.3 7 13.3 13.2 14.3 13.7 13.6 14.1 10 9.2 9.6 10.2 10.4 10.0 10.7 14 9.2 9.3 10.1 9.6 9.5 9.8 17 7.3 7.2 8.2 7.7 8.7 9.4 21 6.4 6.8 7.8 7.0 8.0 8.3 24 5.6 6.6 7.6 6.9 7.6 8.0 28 4.9 5.6 7.4 5.8 6.5 6.7 31 4.6 4.6 6.0 4.7 5.9 6.0 35 4.9 4.5 4.9 4.8 5.0 5.4 38 4.8 4.5 5.0 4.8 5.0 5.4 42 4.7 4.4 5.1 4.5 4.6 4.7 46 5.4 4.6 5.2 4.5 4.7 4.6 50 6.3 4.5 5.3 4.4 4.4 4.4 53 5.1 4.5 5.6 4.7 5.6 5.9 57 6.8 4.7 6.1 5.0 4.9 5.1 61 6.7 4.4 4.9 4.5 4.8 5.0 65 6.6 4.4 5.1 4.6 4.7 4.9 68 6.6 4.2 4.7 4.4 4.9 5.1 72 5.7 4.3 4.3 4.5 4.6 4.8 76 5.4 4.6 5.1 5.0 5.1 5.5 80 5.6 4.7 5.4 4.8 4.9 5.0 83 6.1 4.4 4.9 4.7 5.1 5.5 87 6.8 4.5 4.5 4.7 4.8 5.0 111 Table A2.10 Average effluent volatile solid content of all reactors (g/L) Days FW FW+TE FW+HA FW+VC FW+TE+HA FW+TE+VC 3 10.0 10.1 10.3 10.4 10.1 10.4 7 9.7 10.0 10.0 10.4 9.7 10.1 10 8.2 8.2 8.8 8.9 8.6 9.3 14 8.3 8.1 9.0 8.3 9.0 9.2 17 5.9 5.8 6.4 6.2 6.6 7.0 21 5.6 5.8 5.9 6.0 6.2 6.4 24 4.5 4.0 4.9 4.2 5.0 5.2 28 4.4 4.3 4.9 4.4 4.9 5.1 31 3.2 3.8 2.4 3.9 3.6 3.6 35 3.3 3.2 2.6 3.4 3.5 3.8 38 3.5 2.5 3.0 2.7 2.8 3.1 42 3.5 2.7 3.6 2.8 2.9 3.0 46 4.7 2.9 3.2 2.8 3.0 2.9 50 4.9 2.6 3.7 2.6 3.1 3.1 53 4.6 2.6 3.4 2.8 2.6 2.8 57 4.3 2.5 3.5 2.7 2.6 2.7 61 5.1 2.8 2.6 2.9 2.6 2.7 65 5.1 2.5 2.6 2.6 2.6 2.7 68 4.8 2.6 2.6 2.8 2.7 2.8 72 3.9 2.7 2.7 2.8 2.5 2.6 76 3.6 2.9 2.8 3.1 2.4 2.6 80 3.8 2.7 2.9 2.7 2.6 2.7 83 4.3 2.7 2.5 2.9 2.5 2.6 87 4.1 2.6 2.7 2.7 2.6 2.7 112 SRT Days 31 35 38 3 42 46 50 53 4 57 61 65 68 5 72 76 80 83 6 87 AVG SEM SRT 1 2 3 4 5 6 AVG STD Table A2.11 Total volatile solid reduction (%) FW FW+TE FW+HA FW+VC FW+TE+HA FW+TE+VC 66 65 62 62 49 48 49 52 46 46 46 56 60 58 51 54 58 65 72 70 70 73 72 73 71 74 72 71 69 72 71 72 73 71 67 60 65 59 62 61 72 71 71 70 70 68 73 71 58 63 71 71 71 73 70 71 71 74 70 69 68 72 70 72 60 60 68 68 68 67 70 71 72 72 70 72 74 72 73 72 63 61 68 70 71 69 70 70 72 71 71 74 74 73 72 72 54 5 70 2 68 3 70 3 69 3 70 2 Table A2.12 Average influent COD of all reactors (g/L) FW + FW + FW + TE + FW FW + HA FW + VC TE TE + HA VC 13.3 13.4 13.2 18.3 13.3 18.1 13.3 13.1 13.0 17.8 14.6 19.5 13.1 13.2 13.1 18.1 13.1 17.9 13.3 13.0 12.8 17.6 14.4 19.3 13.5 13.6 13.5 18.7 13.5 18.4 13.7 13.4 13.2 18.2 14.9 19.9 13.4 13.3 13.1 18.1 14.0 18.9 0.2 0.2 0.2 0.4 0.7 0.8 113 Table A2.13 Average effluent COD of all reactors (g/L) FW + FW + FW + FW + FW + SRT FW TE HA VC TE + HA TE + VC 5.8 5.1 5.4 8.7 5.4 8.0 1 5.9 5.1 5.5 8.7 5.4 8.0 4.7 3.8 4.5 7.0 4.6 7.6 2 5.0 3.8 4.3 7.1 4.5 7.6 4.9 4.1 4.1 7.4 4.3 7.7 3 4.6 4.2 4.4 7.4 4.2 7.9 4.8 4.0 4.2 6.8 4.2 6.3 4 4.7 4.1 4.4 7.0 4.3 6.5 4.6 3.6 4.3 6.8 4.4 7.4 5 4.8 3.8 4.2 6.9 4.4 7.4 4.7 4.0 4.0 7.3 4.2 7.5 6 4.9 4.3 4.6 7.7 4.3 8.2 Steady-state AVG 4.7 4.0 4.3 7.1 4.3 7.3 Steady-state STD. 0.1 0.2 0.2 0.3 0.1 0.6 Overall AVG 4.6 4.2 4.5 7.4 4.5 7.5 Overall STD 1.3 0.5 0.5 0.7 0.4 0.6 Table A2.14 Average effluent ammonia-N of all reactors (mg/L) FW + TE FW + TE SRT FW FW + TE FW + HA FW + VC + HA + VC 3 213 232 224 223 245 242 4 226 216 236 212 236 230 5 215 224 205 245 226 238 6 236 204 215 229 205 212 AVG 223 219 220 227 228 231 STD 9 10 11 12 15 12 Table A2.15 Average influent TKN of all reactors (mg/L) FW + FW + FW + TE FW + TE SRT FW FW + TE HA VC + HA + VC 3 612 610 614 756 618 750 4 615 612 621 740 620 743 5 624 623 600 735 603 740 6 625 636 612 770 623 732 AVG 619 620 612 750 616 741 STD 6 10 8 14 8 6 114 Table A2.16 Average effluent TKN of all reactors (mg/L) FW + FW + FW + FW + FW + SRT FW TE HA VC TE + HA TE + VC 590 535 550 600 560 595 3 587 565 575 620 585 610 578 540 555 635 570 630 4 574 560 545 625 560 655 580 550 575 620 540 625 5 596 540 585 615 555 645 583 570 565 635 540 630 6 592 565 585 640 580 650 AVG 585 553 567 624 561 630 STD. 7 13 15 12 16 19 Table A2.17 Average Influent total phosphorus of all reactors (mg/L) FW + FW + FW + TE SRT FW FW + TE FW + HA VC TE + HA + VC 3 25 26 32 97 30 96 4 27 27 34 96 33 97 5 29 28 30 92 30 92 6 23 23 35 99 35 98 AVG 26 26 33 96 32 96 STD 2 2 2 3 2 2 115 Table A2.18 Average effluent total phosphorus of all reactors (mg/L) FW + FW + FW + FW + FW + SRT FW TE + TE + TE HA VC HA VC 30 26 28 54 29 57 3 29 28 30 51 28 53 27 25 31 74 39 64 4 25 24 32 66 41 64 31 24 34 62 31 70 5 25 24 34 70 32 67 28 24 33 55 34 58 6 24 25 36 59 37 61 AVG 27 25 32 61 34 62 STD. 2 1 2 8 4 5 Table A2.19 Average volatile fatty acids of all reactors (mg/L) FW + FW + FW + TE FW + TE Days FW FW + TE HA VC + HA + VC 3 80 80 70 90 90 90 10 90 90 80 80 100 80 17 100 110 120 80 110 110 24 250 140 130 90 140 120 31 300 140 150 110 190 110 38 450 160 120 80 140 90 46 680 140 160 70 160 80 53 1,920 150 170 90 170 100 61 2,600 180 190 100 130 80 68 2,000 170 130 130 140 90 76 1,800 160 150 120 160 100 83 1,600 160 140 100 130 120 Steady-state AVG 1,419 158 151 100 153 96 Steady-state STD. 783 13 21 19 20 13 116 Table A2.20 Soluble Ni concentrations of food waste digesters with different additives Days FW FW+TE FW+HA FW+VC 69 0.013 0.019 0.012 0.018 70 0.010 0.018 0.015 0.020 71 0.016 0.020 0.016 0.019 72 0.017 0.022 0.013 0.017 73 0.014 0.015 0.019 0.021 74 0.015 0.018 0.012 0.015 AVG 0.014 0.019 0.015 0.018 STD 0.002 0.002 0.003 0.002 Table A2.21 Soluble Co concentrations of food waste digesters with different additives Days FW FW+TE FW+HA FW+VC 69 0.030 0.039 0.032 0.042 70 0.034 0.038 0.032 0.041 71 0.038 0.039 0.035 0.039 72 0.036 0.042 0.038 0.036 73 0.031 0.040 0.034 0.038 74 0.030 0.042 0.031 0.044 AVG 0.033 0.040 0.034 0.040 STD 0.003 0.002 0.002 0.003 Table A2.22 Soluble Fe concentration of food waste digesters with different additives Days FW FW+TE FW+HA FW+VC 69 0.17 0.45 0.57 2.34 70 0.15 0.42 0.61 2.37 71 0.10 0.47 0.54 2.31 72 0.19 0.40 0.62 2.28 73 0.09 0.44 0.54 2.26 74 0.16 0.39 0.53 2.32 AVG 0.14 0.43 0.57 2.31 STD 0.04 0.03 0.04 0.04 Table A2.23 Comparison of soluble metals concentration of food waste digesters with different additives Trace Metals FW FW+TE FW+HA FW+VC a b a Ni (mg/L) 0.014 ± 0.002 0.019 ±0.002 0.015 ± 0.003 0.018b±0.002 Fe (mg/L) 0.14a± 0.04 0.43b± 0.03 0.57c± 0.04 2.31d± 0.04 a b a b Co (mg/L) 0.033 ± 0.003 0.040 ±0.002 0.034 ± 0.002 0.040 ±0.003 117 Table A2.24 Daily biogas productions from food waste reactors FW reactors (mL/day) Days Duplicate 1 Duplicate 2 AVG STD 1 46 51 49 3 2 71 90 80 10 3 93 93 93 0 4 131 112 122 10 5 163 199 181 18 6 201 184 193 9 7 240 203 221 19 8 197 191 194 3 9 186 206 196 10 10 253 262 257 5 11 273 313 293 20 12 341 375 358 17 13 433 473 453 20 14 386 423 405 19 15 432 451 441 9 16 383 410 396 13 17 435 415 425 10 18 425 391 408 17 19 419 432 426 7 20 397 378 388 10 21 279 265 272 7 22 335 369 352 17 23 382 462 422 40 24 401 477 439 38 25 378 469 424 45 26 411 481 446 35 27 398 465 432 34 28 461 485 473 12 29 447 439 443 4 30 373 364 368 5 31 353 349 351 2 32 349 354 352 2 33 357 347 352 5 34 339 355 347 8 35 344 321 333 11 36 360 369 364 4 37 365 368 367 1 38 366 335 350 16 39 343 335 339 4 40 319 294 307 13 41 283 283 283 0 42 247 256 252 5 118 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 279 291 292 248 229 191 222 191 176 155 157 185 208 214 225 210 276 227 258 203 280 321 359 327 315 265 318 330 343 281 294 306 262 292 294 301 279 286 272 279 291 272 286 295 Table A2.24 (cont’d) 289 205 266 238 204 181 204 210 166 157 165 148 149 164 182 200 198 221 216 236 244 300 356 344 349 254 338 263 308 271 252 244 220 299 281 299 293 . . . . . . . 119 284 248 279 243 217 186 213 200 171 156 161 167 178 189 203 205 237 224 237 219 262 310 358 335 332 259 328 297 325 276 273 275 241 296 287 300 286 286 272 279 291 272 286 295 5 43 13 5 12 5 9 9 5 1 4 18 30 25 22 5 39 3 21 16 18 10 2 8 17 5 10 33 18 5 21 31 21 4 7 1 7 . . . . . . . 87 292 88 289 89 272 90 276 . Data is not available Table A2.24 (cont’d) . . . . 292 289 272 276 . . . . Table A2.25 Daily biogas productions from trace elements supplemented reactors FW+TE rectors Days Duplicate 1 Duplicate 2 AVG STD 1 77 72 74 3 2 97 103 100 3 3 126 125 126 0 4 168 173 171 2 5 215 211 213 2 6 249 239 244 5 7 304 285 294 10 8 267 239 253 14 9 251 232 241 10 10 345 331 338 7 11 393 390 392 1 12 450 451 450 0 13 467 487 477 10 14 339 347 343 4 15 406 412 409 3 16 378 328 353 25 17 405 397 401 4 18 312 332 322 10 19 563 535 549 14 20 503 491 497 6 21 395 392 393 1 22 476 482 479 3 23 461 496 479 18 24 393 371 382 11 25 323 309 316 7 26 297 305 301 4 27 405 406 406 1 28 444 438 441 3 29 381 374 377 3 30 375 380 377 3 31 376 398 387 11 32 370 359 365 5 33 379 371 375 4 120 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 406 404 400 377 377 399 365 387 396 392 369 377 371 356 377 395 424 427 396 373 401 423 410 391 384 391 418 409 358 389 406 368 371 359 386 383 391 404 395 352 374 393 351 348 Table A2.25 (cont’d) 398 410 412 379 378 374 371 379 394 374 358 358 392 391 396 422 393 409 378 362 389 419 423 384 395 392 405 401 376 409 404 376 415 372 392 371 391 407 408 385 358 383 359 354 121 402 407 406 378 377 386 368 383 395 383 363 367 381 374 387 409 409 418 387 368 395 421 417 388 390 391 412 405 367 399 405 372 393 365 389 377 391 406 402 368 366 388 355 351 4 3 6 1 1 12 3 4 1 9 5 10 11 17 9 13 16 9 9 5 6 2 7 3 6 1 7 4 9 10 1 4 22 7 3 6 0 2 7 16 8 5 4 3 78 386 79 386 80 406 81 386 82 366 83 409 84 391 85 393 86 402 87 392 88 398 89 396 90 385 . Data is not available Table A2.25 (cont’d) 383 396 . . . . . . . . . . . 384 391 406 386 366 409 391 393 402 392 398 396 385 1 5 . . . . . . . . . . . Table A2.26 Daily biogas productions from humic acids supplemented reactors FW+HA Days Duplicate 1 Duplicate 2 AVG STD 1 49 46 48 1 2 74 73 74 0 3 94 93 94 0 4 144 137 141 4 5 157 141 149 8 6 240 177 208 32 7 291 223 257 34 8 242 189 216 26 9 200 221 211 10 10 276 282 279 3 11 327 318 322 5 12 417 372 395 22 13 519 441 480 39 14 443 392 417 26 15 441 455 448 7 16 357 426 391 35 17 394 429 412 17 18 349 386 368 18 19 372 423 398 26 20 390 394 392 2 21 292 270 281 11 22 402 355 379 23 23 447 390 419 28 24 470 398 434 36 122 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 459 490 439 440 406 393 395 387 408 357 415 407 403 402 402 396 369 378 394 365 396 403 372 376 367 358 386 367 378 367 390 378 388 377 376 387 392 384 372 394 408 424 360 Table A2.26 (cont’d) 405 420 425 464 466 390 380 399 411 360 398 406 408 391 386 362 408 383 414 397 393 379 359 358 381 356 392 342 374 363 368 353 395 399 366 367 387 380 376 364 399 426 325 123 432 455 432 452 436 392 388 393 410 358 407 406 405 397 394 379 389 380 404 381 395 391 365 367 374 357 389 355 376 365 379 365 391 388 371 377 389 382 374 379 403 425 342 27 35 7 12 30 2 8 6 1 2 9 1 3 6 8 17 19 3 10 16 2 12 7 9 7 1 3 13 2 2 11 13 4 11 5 10 3 2 2 15 4 1 17 68 388 69 372 70 422 71 411 72 417 73 390 74 375 75 417 76 391 77 370 78 394 79 392 80 388 81 366 82 372 83 390 84 371 85 398 86 407 87 405 88 413 89 389 90 397 . Data is not available Table A2.26 (cont’d) 367 369 425 440 450 387 398 391 405 391 406 402 . . . . . . . . . . . 377 370 423 426 434 388 386 404 398 381 400 397 388 366 372 390 371 398 407 405 413 389 397 11 2 2 15 16 1 11 13 7 10 6 5 . . . . . . . . . . . Table A2.27 Daily biogas productions from vermicompost supplemented reactors FW+VC Days Duplicate 1 Duplicate 2 AVG STD 1 63 50 56 6 2 73 75 74 1 3 67 91 79 12 4 119 131 125 6 5 159 167 163 4 6 203 211 207 4 7 267 242 254 13 8 226 217 221 4 9 224 193 209 16 10 274 260 267 7 11 286 326 306 20 12 422 393 407 14 13 489 507 498 9 14 435 480 457 22 124 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 446 423 439 436 428 363 248 361 398 391 394 395 393 438 438 436 409 404 409 366 391 409 413 422 402 402 374 375 425 410 398 400 393 398 391 499 468 420 404 445 434 420 414 413 Table A2.27 (cont’d) 483 426 430 343 421 409 332 444 537 525 529 497 370 437 414 411 422 412 401 383 387 419 398 410 416 399 392 392 434 432 392 409 407 406 404 460 470 429 415 422 408 436 427 424 125 464 424 434 389 424 386 290 403 467 458 461 446 381 437 426 423 415 408 405 374 389 414 406 416 409 401 383 384 430 421 395 404 400 402 398 479 469 425 410 434 421 428 420 418 19 1 4 47 4 23 42 42 70 67 67 51 11 1 12 13 6 4 4 8 2 5 7 6 7 1 9 8 5 11 3 5 7 4 6 20 1 5 5 11 13 8 7 5 59 441 60 421 61 397 62 378 63 415 64 411 65 409 66 409 67 416 68 388 69 394 70 424 71 445 72 439 73 394 74 392 75 402 76 410 77 406 78 424 79 413 80 448 81 409 82 416 83 407 84 417 85 424 86 434 87 406 88 425 89 421 90 411 . Data is not available Table A2.27 (cont’d) 428 417 403 420 426 439 429 423 414 379 393 461 450 457 411 403 438 461 457 435 416 . . . . . . . . . . . 126 434 419 400 399 421 425 419 416 415 384 394 443 447 448 403 398 420 435 432 429 415 448 409 416 407 417 424 434 406 425 421 411 7 2 3 21 6 14 10 7 1 5 1 18 2 9 8 6 18 26 26 5 1 . . . . . . . . . . . Table A2.28 Daily biogas productions from trace elements and humic acids supplemented reactors FW+TE+HA Days Duplicate 1 Duplicate 2 AVG STD 1 48 48 48 0 2 68 72 70 2 3 86 86 86 0 4 127 139 133 6 5 152 191 172 20 6 181 314 247 67 7 239 280 260 21 8 186 229 208 22 9 196 50 123 73 10 253 262 257 5 11 284 340 312 28 12 364 415 389 25 13 469 511 490 21 14 403 388 395 8 15 437 356 397 41 16 305 338 321 16 17 372 322 347 25 18 371 346 359 13 19 419 415 417 2 20 389 404 396 7 21 288 295 291 3 22 327 380 353 26 23 373 423 398 25 24 392 394 393 1 25 413 419 416 3 26 435 441 438 3 27 454 449 452 2 28 507 453 480 27 29 521 335 428 93 30 376 387 382 6 31 386 398 392 6 32 373 398 385 13 33 372 389 380 8 34 377 356 367 10 35 401 403 402 1 36 441 443 442 1 37 416 402 409 7 38 406 392 399 7 39 431 418 425 7 40 379 410 394 15 41 361 393 377 16 42 379 408 394 14 127 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 383 393 384 399 361 386 387 401 407 402 410 428 417 421 391 402 411 379 427 384 385 398 393 404 338 383 394 409 436 414 387 396 394 370 365 381 378 388 381 380 408 391 427 416 398 Table A2.28 (cont’d) 378 371 394 401 361 389 395 408 415 410 395 404 424 409 413 397 418 392 429 397 405 408 376 386 343 369 369 414 428 402 373 378 385 386 385 391 390 . . . . . . . . 128 381 382 389 400 361 387 391 405 411 406 403 416 420 415 402 399 414 386 428 390 395 403 385 395 340 376 381 411 432 408 380 387 390 378 375 386 384 388 381 380 408 391 427 416 398 3 11 5 1 0 2 4 4 4 4 7 12 4 6 11 3 3 6 1 6 10 5 9 9 3 7 13 3 4 6 7 9 4 8 10 5 6 . . . . . . . . 88 384 89 388 90 396 . Data is not available Table A2.28 (cont’d) . 384 . 388 . 396 . . . Table A2.29 Daily biogas productions from trace elements and vermicompost supplemented reactors FW+TE+VC Days Duplicate 1 Duplicate 2 AVG STD 1 72 66 69 3 2 104 94 99 5 3 138 118 128 10 4 192 164 178 14 5 206 219 212 6 6 302 256 279 23 7 384 306 345 39 8 334 253 293 41 9 282 282 282 0 10 355 355 355 0 11 385 385 385 0 12 463 463 463 0 13 653 653 653 0 14 543 543 543 0 15 578 578 578 0 16 439 380 410 30 17 446 437 441 5 18 359 368 363 4 19 527 553 540 13 20 519 395 457 62 21 463 306 384 78 22 546 374 460 86 23 560 472 516 44 24 579 491 535 44 25 488 434 461 27 26 367 304 336 32 27 458 421 439 19 28 471 478 474 4 29 386 441 414 27 30 404 402 403 1 31 411 411 411 0 32 447 461 454 7 33 462 468 465 3 34 422 455 438 17 35 435 451 443 8 36 423 457 440 17 37 406 439 423 17 129 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 450 455 449 406 443 419 404 426 423 430 428 410 447 423 411 415 431 445 450 425 434 423 420 409 409 421 430 414 418 424 433 428 428 455 436 406 407 421 431 425 434 436 449 411 424 410 411 Table A2.29 (cont’d) 463 476 428 382 424 408 385 436 416 437 450 437 456 458 431 431 459 453 453 429 425 418 442 416 422 428 447 414 413 432 416 406 411 448 438 401 419 411 442 420 427 428 . . . . . 130 457 465 438 394 433 413 395 431 419 434 439 423 452 440 421 423 445 449 451 427 429 421 431 412 415 425 439 414 415 428 424 417 420 452 437 404 413 416 437 422 430 432 449 411 424 410 411 6 10 10 12 9 5 9 5 4 4 11 13 4 18 10 8 14 4 2 2 5 2 11 3 7 4 8 0 2 4 8 11 8 4 1 2 6 5 5 2 4 4 . . . . . 85 422 86 431 87 419 88 428 89 438 90 426 . Data is not available Table A2.29 (cont’d) . . . . . . 131 422 431 419 428 438 426 . . . . . . Days 3 7 10 14 17 21 24 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64 66 68 70 72 74 76 78 80 82 84 Table A2.30 Biogas composition of FW only reactors FW N2 (%) CH4 (%) CO2 (%) H2S (ppm) AVG STD AVG STD AVG STD AVG STD 23 5 33 2 40 2 4800 106 9 1 41 1 43 0 4964 127 9 1 50 0 38 1 1613 214 5 1 50 1 38 1 1925 255 5 1 55 0 35 1 1501 233 5 1 55 1 35 0 1501 0 5 0 56 0 34 0 431 0 8 2 58 2 33 0 641 99 5 0 60 1 32 1 497 58 5 1 60 1 32 0 391 22 5 1 58 2 34 2 269 11 5 2 57 2 34 1 292 100 5 1 57 2 35 1 413 71 6 1 56 3 36 2 298 99 4 0 56 3 36 2 431 49 6 1 59 1 31 1 509 34 5 0 53 2 39 2 665 87 9 3 45 6 42 3 331 211 14 5 40 8 44 4 153 134 15 6 33 9 50 3 83 30 24 8 29 9 47 2 58 9 13 7 33 14 50 7 166 51 13 7 33 14 50 7 166 51 14 9 36 17 47 9 439 299 10 3 42 9 46 7 1198 957 6 1 49 2 41 3 1189 965 7 1 51 1 38 2 2808 2046 10 2 54 4 32 3 1174 780 12 1 49 4 36 3 1950 143 9 1 51 6 37 5 1586 923 9 0 52 6 34 6 1267 891 8 1 53 6 36 5 1183 787 8 0 53 6 36 6 832 449 1 0 56 6 38 6 883 484 9 4 51 6 35 3 234 34 6 2 51 4 39 2 453 361 132 Table A2.31 Biogas composition of trace elements supplemented reactors FW+TE Days N2 (%) CH4 (%) CO2 (%) H2S (ppm) AVG STD AVG STD AVG STD AVG STD 3 36 15 33 4 29 8 2740 2269 7 22 13 42 2 31 8 2729 2222 10 14 7 53 1 29 5 1225 805 14 7 2 56 1 29 3 1394 769 17 8 3 58 1 29 3 1041 543 21 11 7 55 2 30 4 740 282 24 7 2 61 0 27 2 550 89 28 6 0 63 2 29 3 509 58 30 9 4 57 1 29 5 560 67 32 6 0 61 4 28 4 396 38 34 7 2 60 2 29 4 399 103 36 5 1 59 3 31 3 600 14 38 7 2 59 1 30 3 623 68 40 6 0 62 3 30 4 577 49 42 5 0 61 3 28 4 511 37 44 5 0 62 2 28 3 681 95 46 9 4 61 6 27 2 485 35 48 6 0 62 3 27 4 407 10 50 8 1 61 4 28 4 407 10 52 8 2 62 2 28 4 313 96 54 8 3 61 2 29 5 267 34 56 12 1 57 3 27 3 252 74 58 7 2 61 4 29 2 391 125 60 7 0 60 2 31 2 266 81 62 6 0 62 4 30 4 275 44 64 8 1 61 3 29 4 132 118 66 6 1 62 3 28 3 329 30 68 4 1 63 3 28 4 421 190 70 7 0 63 4 27 4 252 55 72 14 1 55 5 28 6 223 58 74 11 0 56 5 28 5 471 307 76 12 3 57 2 28 5 444 105 78 14 2 57 5 26 4 470 84 80 7 4 59 1 29 6 432 95 82 5 2 61 3 29 5 239 30 84 4 2 61 5 30 7 203 111 133 Table A2.32 Biogas composition of humic acids supplemented reactors FW+HA Days N2 (%) CH4 (%) CO2 (%) H2S (ppm) AVG STD AVG STD AVG STD AVG STD 3 32 1 28 1 37 0 3745 27 7 14 0 38 1 42 1 4419 297 10 9 1 50 1 38 0 1665 32 14 5 0 53 0 36 1 1685 113 17 6 2 56 2 33 0 1151 57 21 7 1 55 1 34 0 542 123 24 7 0 56 0 33 0 382 8 28 7 1 59 1 32 0 279 1 30 6 1 61 2 31 1 167 67 32 6 0 59 0 32 0 154 81 34 6 0 59 0 32 0 132 38 36 4 1 59 1 33 0 163 49 38 7 0 57 0 33 0 97 15 40 6 1 59 0 33 0 94 38 42 7 0 57 0 32 0 121 26 44 7 0 59 0 31 0 139 35 46 5 0 59 0 33 0 140 16 48 6 1 57 0 32 1 165 1 50 8 1 56 1 33 0 62 24 52 9 1 51 2 37 0 105 66 54 14 3 50 3 35 0 72 33 56 9 1 54 2 34 1 67 5 58 7 2 58 4 33 2 76 43 60 5 0 60 1 32 1 82 32 62 6 1 60 1 31 0 53 12 64 6 0 61 0 31 0 68 19 66 5 0 58 0 34 0 197 66 68 8 1 59 2 29 1 91 6 70 8 0 57 1 32 0 111 44 72 9 2 54 1 34 1 107 9 74 8 1 54 0 33 1 374 27 76 11 2 53 1 33 1 573 203 78 8 1 55 0 33 0 424 260 80 3 1 58 1 36 0 623 482 82 16 10 49 6 31 3 94 29 84 4 2 55 2 36 1 37 3 134 Table A2.33 Biogas composition of vermicompost supplemented reactors FW+ VC Days N2 (%) CH4 (%) CO2 (%) H2S (ppm) AVG STD AVG STD AVG STD AVG STD 3 28 2 32 0 37 1 4709 19 7 11 1 40 1 42 0 4425 232 10 7 2 52 2 37 0 1466 28 14 5 0 53 1 36 0 1462 71 17 5 0 57 0 33 0 851 3 21 6 1 55 0 34 0 851 0 24 7 2 55 1 34 0 349 9 28 7 2 58 3 32 1 282 9 30 5 1 60 3 32 2 152 57 32 6 1 58 1 33 0 145 71 34 9 0 54 2 34 2 84 24 36 5 1 55 4 36 3 154 29 38 7 0 55 3 36 3 197 22 40 5 1 57 0 36 1 198 80 42 4 0 61 3 31 3 158 1 44 6 1 60 2 30 2 201 4 46 4 0 60 0 32 0 165 7 48 6 0 58 0 32 0 107 0 50 8 1 58 1 32 0 83 31 52 8 2 58 1 32 1 103 37 54 20 1 50 0 29 1 43 6 56 7 2 57 2 32 0 30 6 58 7 1 59 0 32 0 37 3 60 8 2 56 1 33 1 35 16 62 6 0 57 1 34 0 39 5 64 7 1 58 1 32 0 10 2 66 6 0 57 0 34 0 167 62 68 12 0 56 0 29 1 18 8 70 6 0 57 0 34 1 62 3 72 13 3 51 2 34 1 45 22 74 9 0 54 1 33 0 58 8 76 12 2 53 1 33 1 53 13 78 8 1 56 1 33 0 42 4 80 5 0 56 0 35 1 29 29 82 7 2 55 2 34 0 29 12 84 3 0 55 0 35 0 22 1 135 Table A2.34 Biogas composition of trace elements and humic acids supplemented reactors FW+ TE+HA Days N2 (%) CH4 (%) CO2 (%) H2S (ppm) AVG STD AVG STD AVG STD AVG STD 3 32 1 28 1 37 0 3874 27 7 15 1 37 2 42 1 3870 206 10 11 3 49 2 37 1 1152 25 14 5 1 53 2 35 0 1412 95 17 8 1 55 1 33 0 528 20 21 7 2 55 2 34 0 528 0 24 5 1 56 1 35 0 240 28 28 8 3 57 2 33 0 169 1 30 5 1 61 2 31 1 96 39 32 5 1 61 1 31 0 97 21 34 5 0 60 2 32 2 83 6 36 7 2 57 1 33 1 61 7 38 7 0 57 0 33 0 131 57 40 6 0 58 0 34 0 87 18 42 5 1 59 0 32 1 115 1 44 5 0 60 0 31 0 134 6 46 4 1 60 0 33 0 120 5 48 6 0 57 0 32 0 48 0 50 10 1 54 0 34 1 22 12 52 6 0 60 1 31 1 40 10 54 14 4 55 4 29 0 27 17 56 7 3 57 2 31 1 21 14 58 6 1 59 0 32 0 44 6 60 5 0 58 0 34 0 25 1 62 6 1 57 1 34 1 25 15 64 7 1 57 1 34 0 29 6 66 7 2 56 1 34 1 99 36 68 6 1 58 1 32 0 33 8 70 20 6 51 4 28 2 25 3 72 9 0 53 0 35 0 37 2 74 8 2 53 1 34 1 203 28 76 7 0 56 0 35 0 281 41 78 5 2 57 2 35 1 415 137 80 4 0 58 0 35 0 299 143 82 11 5 53 4 32 1 71 56 84 5 3 55 3 35 1 44 34 136 Table A2.35 Biogas composition of trace elements and vermicomposts supplemented reactors FW+TE+VC Days N2 (%) CH4 (%) CO2 (%) H2S (ppm) AVG STD AVG STD AVG STD AVG STD 3 23 0 35 0 38 0 4824 34 7 9 1 43 2 41 3 4465 6 10 7 0 54 0 35 0 1447 0 14 24 20 39 13 32 4 1268 295 17 10 4 53 5 33 2 730 119 21 3 0 59 1 33 1 344 96 24 8 2 57 2 31 0 182 138 28 9 2 58 2 31 1 106 66 30 11 6 56 3 30 2 193 84 32 6 0 59 1 31 1 171 52 34 4 2 59 0 33 2 107 20 36 7 2 57 0 32 2 127 33 38 6 0 59 0 32 0 162 61 40 6 0 59 0 33 0 141 32 42 6 0 58 0 32 0 103 0 44 6 2 59 1 31 0 262 139 46 5 0 60 0 32 0 194 86 48 6 0 58 0 32 0 143 45 50 8 0 57 0 32 0 135 53 52 6 2 59 1 32 1 152 55 54 11 1 56 1 32 0 108 38 56 7 1 57 1 32 1 132 53 58 6 1 59 0 32 0 98 46 60 7 0 57 0 33 0 95 59 62 6 0 58 0 33 0 80 55 64 10 2 56 1 31 1 76 59 66 7 0 58 0 32 0 97 68 68 4 1 60 0 32 1 122 112 70 10 1 57 0 31 0 215 0 72 6 0 56 0 35 0 37 0 74 8 0 54 0 33 1 79 0 76 7 0 56 0 33 0 49 0 78 9 1 57 1 31 0 21 21 80 1 0 59 0 35 0 12 6 82 6 1 56 1 33 0 0 0 84 3 1 57 1 35 0 21 8 137 APPENDIX C Methanogenic Activities Study Data Summary 138 Table A3.1 Acetate utilization rates of food waste only (control) digesters FW Hours AVG STD 1 2 3 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.7 0.9 0.7 0.8 0.1 1.0 1.0 1.4 1.6 1.3 0.3 1.5 1.1 1.7 2.2 1.7 0.5 2.0 1.3 1.9 2.5 1.9 0.5 2.5 1.8 2.1 2.8 2.2 0.4 3.0 2.1 2.4 2.9 2.5 0.3 3.5 2.5 2.7 3.1 2.8 0.3 4.0 3.0 3.1 4.3 3.5 0.6 4.5 3.7 3.5 4.4 3.9 0.4 5.0 4.3 4.3 4.4 4.3 0.1 5.5 5.0 5.0 4.4 4.8 0.3 6.0 5.7 5.6 4.4 5.3 0.6 6.5 6.5 6.2 5.4 6.1 0.4 7.0 7.2 6.8 7.1 7.1 0.2 7.5 8.2 7.4 8.2 7.9 0.3 8.0 9.0 8.3 9.1 8.8 0.3 8.5 9.8 9.1 9.8 9.6 0.3 9.0 10.7 9.9 10.8 10.5 0.4 9.5 11.6 10.6 12.0 11.4 0.6 10.0 12.5 11.4 12.9 12.3 0.6 10.5 13.4 12.1 13.8 13.1 0.7 11.0 14.6 12.9 14.6 14.0 0.8 11.5 15.4 13.6 15.5 14.9 0.9 12.0 16.4 14.7 16.8 16.0 0.9 12.5 17.5 15.6 17.7 17.0 0.9 13.0 18.5 16.6 18.6 17.9 1.0 13.5 19.5 17.4 19.4 18.8 1.0 14.0 20.7 18.4 20.5 19.8 1.1 14.5 21.8 19.2 21.5 20.8 1.2 15.0 22.8 20.1 22.4 21.8 1.2 15.5 23.9 21.2 23.2 22.8 1.2 16.0 25.0 22.3 23.9 23.8 1.1 16.5 26.1 23.4 25.1 24.9 1.1 17.0 27.1 24.4 26.1 25.9 1.1 17.5 28.4 25.4 26.9 26.9 1.2 18.0 29.4 26.4 27.8 27.9 1.2 18.5 30.5 27.4 29.1 29.0 1.3 19.0 31.6 28.6 30.1 30.1 1.2 19.5 32.8 29.8 30.9 31.2 1.2 20.0 33.8 30.9 32.1 32.3 1.2 20.5 35.1 31.9 33.2 33.4 1.3 139 21.0 21.5 22.0 22.5 23.0 23.5 24.0 36.2 37.4 38.5 39.6 40.7 42.0 43.2 Table A3.1 (cont’d) 33.0 34.1 34.4 35.1 35.6 36.0 36.8 36.7 37.9 37.4 39.3 38.2 40.6 39.0 34.5 35.6 36.7 37.7 38.7 39.8 40.9 1.3 1.3 1.3 1.4 1.4 1.6 1.7 Table A3.2 Acetate utilization rates of trace elements supplemented food waste digesters FW+TE Hours AVG STD 1 2 3 0.0 0.0 0.0 0.0 0.0 0.0 0.5 1.2 1.7 1.2 1.4 0.2 1.0 1.7 2.3 2.5 2.2 0.4 1.5 2.0 2.7 3.5 2.7 0.6 2.0 2.3 3.0 4.6 3.3 0.9 2.5 3.1 3.4 5.5 4.0 1.1 3.0 3.7 4.0 6.4 4.7 1.2 3.5 4.3 4.8 7.6 5.6 1.4 4.0 5.2 5.6 9.1 6.7 1.8 4.5 6.3 6.6 10.4 7.7 1.8 5.0 7.4 7.9 11.6 9.0 1.9 5.5 8.7 9.2 12.9 10.2 1.9 6.0 9.9 10.4 14.1 11.5 1.9 6.5 11.2 11.7 15.5 12.8 1.9 7.0 12.5 12.9 17.1 14.2 2.1 7.5 14.1 14.1 18.5 15.6 2.1 8.0 15.5 15.6 19.9 17.0 2.1 8.5 16.8 17.2 21.2 18.4 2.0 9.0 18.5 18.6 22.7 19.9 1.9 9.5 20.0 20.0 24.5 21.5 2.1 10.0 21.6 21.5 25.9 23.0 2.1 10.5 23.2 22.9 27.4 24.5 2.1 11.0 25.1 24.3 28.8 26.1 2.0 11.5 26.6 25.7 30.3 27.5 2.0 12.0 28.3 27.5 32.1 29.3 2.0 12.5 30.1 29.1 33.6 31.0 1.9 13.0 31.9 30.8 35.1 32.6 1.8 13.5 33.7 32.4 36.6 34.2 1.8 14.0 35.6 34.0 38.4 36.0 1.8 14.5 37.5 35.5 40.1 37.7 1.9 15.0 39.3 37.1 41.7 39.4 1.9 140 15.5 16.0 16.5 17.0 17.5 18.0 18.5 19.0 19.5 20.0 20.5 21.0 21.5 22.0 22.5 23.0 23.5 24.0 41.2 43.1 45.0 46.8 48.9 50.7 52.6 54.6 56.5 58.4 60.6 62.4 64.5 66.4 68.3 70.2 72.5 74.5 Table A3.2 (cont’d) 38.9 43.3 40.7 44.8 42.5 46.9 44.3 48.6 46.0 50.2 47.7 51.9 49.4 54.0 51.4 55.6 53.3 57.4 55.1 59.6 57.0 61.5 58.9 63.3 61.0 65.2 63.0 67.0 65.1 68.6 67.0 70.3 69.3 71.9 71.5 73.4 41.1 42.9 44.8 46.6 48.4 50.1 52.0 53.9 55.7 57.7 59.7 61.5 63.6 65.5 67.3 69.2 71.3 73.1 1.8 1.7 1.8 1.8 1.7 1.8 1.9 1.8 1.8 1.9 1.9 1.9 1.8 1.7 1.6 1.5 1.4 1.2 Table A3.3 Acetate utilization rates of humic acids supplemented food waste digesters FW+HA Hour AVG STD s 1 2 3 0.0 0.0 0.0 0.0 0.0 0.0 0.5 1.3 1.6 1.6 1.5 0.2 1.0 1.7 2.4 2.3 2.1 0.3 1.5 2.0 3.2 3.5 2.9 0.6 2.0 2.4 4.1 4.4 3.6 0.9 2.5 3.2 5.0 5.2 4.4 0.9 3.0 3.8 5.9 5.9 5.2 1.0 3.5 4.4 6.9 6.8 6.0 1.1 4.0 5.3 7.9 7.9 7.0 1.2 4.5 6.4 8.9 9.5 8.3 1.3 5.0 7.6 10.2 10.7 9.5 1.4 5.5 8.9 11.3 12.0 10.7 1.4 6.0 10.1 12.6 13.3 12.0 1.4 6.5 11.4 13.8 14.6 13.3 1.3 7.0 12.8 15.0 16.2 14.7 1.4 7.5 14.4 16.3 17.5 16.1 1.3 8.0 15.9 17.7 19.0 17.5 1.3 8.5 17.2 19.2 20.2 18.9 1.2 9.0 18.9 20.7 21.7 20.4 1.2 9.5 20.5 22.1 23.6 22.1 1.2 141 10.0 10.5 11.0 11.5 12.0 12.5 13.0 13.5 14.0 14.5 15.0 15.5 16.0 16.5 17.0 17.5 18.0 18.5 19.0 19.5 20.0 20.5 21.0 21.5 22.0 22.5 23.0 23.5 24.0 22.1 23.7 25.7 27.3 29.0 30.9 32.7 34.5 36.5 38.4 40.2 42.2 44.2 46.1 47.9 50.1 51.9 53.8 55.9 57.8 59.8 62.0 63.9 66.0 68.0 70.0 71.9 74.2 76.2 Table A3.3 (cont’d) 23.6 25.1 25.0 26.6 26.4 28.0 27.8 29.7 29.5 31.5 31.1 33.1 32.8 34.5 34.3 36.0 35.9 38.0 37.3 39.8 38.8 41.4 40.5 43.0 42.3 45.0 44.0 46.9 45.7 48.6 47.3 50.8 48.8 52.6 50.4 54.4 52.3 56.1 54.1 57.7 55.8 59.3 57.5 60.8 59.2 62.3 61.2 63.7 63.0 65.8 64.9 67.6 66.7 69.3 68.7 70.9 72.0 72.5 23.6 25.1 26.7 28.2 30.0 31.7 33.3 34.9 36.8 38.5 40.2 41.9 43.8 45.7 47.4 49.4 51.1 52.9 54.8 56.5 58.3 60.1 61.8 63.6 65.6 67.5 69.3 71.3 73.6 1.2 1.2 0.9 1.0 1.1 1.0 0.8 0.7 0.9 1.0 1.1 1.1 1.2 1.2 1.2 1.5 1.6 1.8 1.8 1.7 1.8 1.9 2.0 2.0 2.0 2.1 2.1 2.3 1.9 Table A3.4 Acetate utilization rates of vermicompost supplemented food waste digesters FW+VC Hours AVG STD 1 2 3 0.0 0.0 0.0 0.0 0.0 0.0 0.5 1.3 1.7 2.0 1.7 0.3 1.0 1.8 2.7 3.2 2.6 0.6 1.5 2.1 3.6 4.2 3.3 0.9 2.0 2.5 4.5 5.2 4.1 1.1 2.5 3.4 5.6 6.1 5.0 1.2 3.0 4.0 6.5 7.1 5.9 1.3 142 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0 10.5 11.0 11.5 12.0 12.5 13.0 13.5 14.0 14.5 15.0 15.5 16.0 16.5 17.0 17.5 18.0 18.5 19.0 19.5 20.0 20.5 21.0 21.5 22.0 22.5 23.0 23.5 24.0 4.7 5.6 6.8 8.1 9.4 10.7 12.1 13.5 15.3 16.8 18.2 20.0 21.7 23.4 25.1 27.2 28.8 30.7 32.6 34.6 36.5 38.6 40.6 42.5 44.7 46.7 48.7 50.7 52.9 54.9 56.9 59.1 61.1 63.2 65.6 67.6 69.8 71.9 74.0 76.0 78.5 80.6 Table A3.4 (cont’d) 7.6 8.4 8.7 9.8 9.8 11.1 11.2 12.5 12.6 13.8 14.0 15.2 15.4 17.0 16.8 18.5 18.1 20.0 19.7 21.4 21.3 22.8 23.1 24.8 24.7 26.6 26.3 28.3 27.9 29.9 29.5 31.6 31.2 33.7 33.2 35.5 35.2 37.2 37.1 38.9 38.9 40.8 40.8 42.8 42.6 44.6 44.3 46.4 46.3 48.0 48.4 50.2 50.5 52.2 52.5 54.0 54.4 55.7 56.3 58.0 58.2 59.8 60.4 61.6 62.5 64.0 64.6 66.0 66.6 68.0 68.6 70.0 70.9 71.8 73.1 73.5 75.2 75.1 77.3 76.8 79.6 78.3 81.9 80.5 143 6.9 8.0 9.2 10.6 11.9 13.3 14.8 16.2 17.8 19.3 20.8 22.6 24.3 26.0 27.6 29.5 31.2 33.1 35.0 36.8 38.7 40.7 42.6 44.4 46.3 48.4 50.4 52.4 54.4 56.4 58.3 60.4 62.5 64.6 66.7 68.7 70.8 72.8 74.7 76.7 78.8 81.0 1.6 1.8 1.8 1.9 1.9 1.9 2.0 2.1 1.9 1.9 1.9 2.0 2.0 2.0 2.0 1.8 2.0 2.0 1.9 1.8 1.8 1.7 1.6 1.6 1.4 1.4 1.4 1.4 1.1 1.3 1.2 1.0 1.2 1.2 1.0 1.0 0.8 0.7 0.5 0.5 0.6 0.6 Table A3.5 Propionate utilization rates of food waste only digesters FW only Hours AVG STD 1 2 3 0.0 0.0 0.0 0.0 0.0 0.0 0.5 1.4 1.9 1.9 1.7 0.2 1.0 2.1 2.5 2.3 2.3 0.2 1.5 2.5 2.6 2.5 2.5 0.1 2.0 2.8 2.9 2.6 2.8 0.1 2.5 3.0 3.2 3.3 3.2 0.1 3.0 3.2 3.4 3.4 3.3 0.1 3.5 3.4 4.1 3.6 3.7 0.3 4.0 3.6 4.5 4.1 4.0 0.4 4.5 4.1 4.7 4.4 4.4 0.3 5.0 4.4 5.0 4.5 4.6 0.3 5.5 4.8 5.3 4.8 4.9 0.2 6.0 5.0 5.8 5.3 5.4 0.3 6.5 5.2 6.0 5.5 5.6 0.3 7.0 5.4 6.3 5.7 5.8 0.4 7.5 5.9 6.4 6.2 6.2 0.2 8.0 6.3 7.1 6.5 6.6 0.3 8.5 6.6 7.4 6.6 6.9 0.4 9.0 6.8 7.5 7.1 7.2 0.3 9.5 7.1 7.6 7.4 7.4 0.2 10.0 7.3 8.3 7.6 7.7 0.4 10.5 7.8 8.5 7.9 8.0 0.3 11.0 8.1 8.7 8.3 8.4 0.2 11.5 8.3 8.9 8.6 8.6 0.2 12.0 8.5 9.4 8.7 8.8 0.4 12.5 9.0 9.5 9.1 9.2 0.2 13.0 9.3 9.7 9.4 9.5 0.2 13.5 9.5 10.2 9.5 9.7 0.3 14.0 9.6 10.4 9.7 9.9 0.3 14.5 10.1 10.7 10.2 10.3 0.3 15.0 10.3 10.7 10.5 10.5 0.1 15.5 10.5 11.2 10.6 10.8 0.3 16.0 10.7 11.5 11.2 11.1 0.3 16.5 11.1 11.6 11.4 11.4 0.2 17.0 11.3 12.2 11.6 11.7 0.4 17.5 11.7 12.4 11.7 11.9 0.3 18.0 12.0 12.8 12.3 12.4 0.3 18.5 12.2 13.1 12.5 12.6 0.4 19.0 12.4 13.3 12.7 12.8 0.4 19.5 12.5 13.5 12.8 12.9 0.4 20.0 12.6 13.9 13.3 13.3 0.5 20.5 13.1 14.1 13.6 13.6 0.4 144 21.0 21.5 22.0 22.5 23.0 23.5 24.0 13.3 13.5 13.6 13.7 14.0 14.3 15.0 Table A3.5 (cont’d) 14.1 13.8 14.5 13.8 14.8 14.3 15.0 14.6 15.0 14.7 15.6 14.8 15.6 14.9 13.7 13.9 14.2 14.4 14.6 14.9 15.2 0.3 0.4 0.5 0.5 0.4 0.5 0.3 Table A3.6 Propionate utilization rates of trace elements supplemented food waste digesters FW+TE Hours AVG STD 1 2 3 0.0 0.0 0.0 0.0 0.0 0.0 0.5 1.2 1.4 1.3 1.3 0.1 1.0 1.9 1.9 1.6 1.8 0.1 1.5 2.2 2.2 1.9 2.1 0.1 2.0 2.5 2.5 2.2 2.4 0.1 2.5 2.6 2.8 2.7 2.7 0.1 3.0 2.9 3.1 2.9 3.0 0.1 3.5 3.0 3.9 3.1 3.3 0.4 4.0 3.2 4.4 3.6 3.7 0.5 4.5 3.6 4.8 3.9 4.1 0.5 5.0 3.9 5.1 4.0 4.4 0.5 5.5 4.1 5.5 4.3 4.6 0.6 6.0 4.2 6.2 4.7 5.0 0.9 6.5 4.3 6.5 4.9 5.2 1.0 7.0 4.3 6.9 5.0 5.4 1.1 7.5 4.7 7.2 5.4 5.8 1.0 8.0 5.0 7.8 5.6 6.2 1.2 8.5 5.3 8.2 5.8 6.4 1.3 9.0 5.4 8.4 6.1 6.7 1.3 9.5 5.4 8.7 6.4 6.8 1.3 10.0 5.6 9.2 6.5 7.1 1.5 10.5 6.0 9.6 6.7 7.4 1.5 11.0 6.3 9.8 7.0 7.7 1.5 11.5 6.4 10.1 7.2 7.9 1.6 12.0 6.5 10.6 7.3 8.1 1.8 12.5 7.0 10.8 7.7 8.5 1.7 13.0 7.1 11.0 7.8 8.6 1.7 13.5 7.4 11.4 7.9 8.9 1.8 14.0 7.5 11.7 8.1 9.1 1.9 14.5 7.9 12.0 8.4 9.4 1.8 15.0 8.1 12.1 8.6 9.6 1.8 145 15.5 16.0 16.5 17.0 17.5 18.0 18.5 19.0 19.5 20.0 20.5 21.0 21.5 22.0 22.5 23.0 23.5 24.0 8.2 8.4 8.7 8.9 9.3 9.6 9.8 10.0 10.1 10.1 10.6 10.9 11.0 11.1 11.2 11.5 11.8 12.4 Table A3.6 (cont’d) 12.6 8.7 12.8 9.1 13.0 9.2 13.4 9.4 13.6 9.5 14.0 9.9 14.4 10.1 14.5 10.2 14.7 10.2 15.1 10.7 15.3 10.8 15.5 11.0 15.8 11.1 16.1 11.4 16.3 11.6 16.4 11.7 16.8 11.8 16.9 11.9 9.8 10.1 10.3 10.6 10.8 11.2 11.4 11.5 11.7 12.0 12.2 12.4 12.6 12.9 13.0 13.2 13.5 13.7 2.0 1.9 1.9 2.0 2.0 2.0 2.1 2.1 2.1 2.2 2.2 2.1 2.3 2.3 2.3 2.3 2.4 2.2 Table A3.7 Propionate utilization rates of humic acids supplemented food waste digesters PW+HA Hours AVG STD 1 2 3 0.0 0.0 0.0 0.0 0.0 0.0 0.5 2.4 2.7 2.0 2.4 0.3 1.0 3.2 3.4 2.4 3.0 0.4 1.5 3.7 3.6 2.5 3.3 0.6 2.0 3.9 3.7 2.7 3.5 0.5 2.5 4.1 3.8 3.3 3.7 0.3 3.0 4.2 3.8 3.5 3.8 0.3 3.5 4.4 4.5 3.6 4.1 0.4 4.0 4.5 4.8 4.0 4.4 0.3 4.5 5.2 4.9 4.4 4.8 0.3 5.0 5.5 4.9 4.5 5.0 0.4 5.5 5.7 5.2 4.8 5.2 0.4 6.0 5.8 5.8 5.3 5.6 0.2 6.5 5.8 6.0 5.4 5.7 0.2 7.0 5.8 6.2 5.5 5.8 0.3 7.5 6.4 6.2 6.2 6.3 0.1 8.0 6.7 6.8 6.4 6.7 0.2 8.5 7.0 7.1 6.5 6.9 0.2 146 9.0 9.5 10.0 10.5 11.0 11.5 12.0 12.5 13.0 13.5 14.0 14.5 15.0 15.5 16.0 16.5 17.0 17.5 18.0 18.5 19.0 19.5 20.0 20.5 21.0 21.5 22.0 22.5 23.0 23.5 24.0 7.1 7.2 7.4 7.9 8.1 8.2 8.2 8.8 9.1 9.2 9.2 9.8 10.0 10.1 10.3 10.7 10.9 11.2 11.7 11.9 12.0 12.0 12.0 12.5 12.8 12.9 12.9 12.9 13.3 13.6 14.2 Table A3.7 (cont’d) 7.2 7.0 7.2 7.3 7.9 7.5 8.1 7.7 8.1 8.2 8.3 8.4 8.9 8.4 9.1 8.9 9.1 9.2 9.6 9.3 9.9 9.5 10.0 10.0 10.1 10.2 10.6 10.2 10.8 10.9 10.9 11.2 11.5 11.3 11.7 11.4 12.2 12.0 12.5 12.3 12.6 12.4 12.6 12.4 13.0 13.0 13.2 13.3 13.2 13.4 13.7 13.4 13.9 13.9 13.9 14.2 14.0 14.3 14.6 14.4 14.6 14.4 7.1 7.2 7.6 7.9 8.1 8.3 8.5 8.9 9.1 9.4 9.5 9.9 10.1 10.3 10.7 10.9 11.2 11.4 12.0 12.2 12.3 12.4 12.7 13.0 13.1 13.3 13.6 13.7 13.9 14.2 14.4 0.1 0.1 0.2 0.2 0.1 0.1 0.3 0.1 0.1 0.2 0.3 0.1 0.1 0.2 0.3 0.2 0.3 0.2 0.2 0.2 0.2 0.3 0.5 0.3 0.3 0.3 0.5 0.5 0.4 0.4 0.1 Table A3.8 Propionate utilization rates of vermicompost supplemented food waste digesters FW+VC Hours AVG STD 1 2 3 0.0 0.0 0.0 0.0 0.0 0.0 0.5 1.7 2.1 2.3 2.0 0.2 1.0 2.5 2.9 2.9 2.8 0.2 1.5 3.2 3.4 3.2 3.2 0.1 2.0 3.5 3.7 3.6 3.6 0.1 2.5 3.7 4.0 4.2 4.0 0.2 3.0 3.9 4.3 4.5 4.3 0.3 147 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0 10.5 11.0 11.5 12.0 12.5 13.0 13.5 14.0 14.5 15.0 15.5 16.0 16.5 17.0 17.5 18.0 18.5 19.0 19.5 20.0 20.5 21.0 21.5 22.0 22.5 23.0 23.5 24.0 4.0 4.1 4.8 5.2 5.6 5.7 5.9 6.0 6.8 7.2 7.7 8.0 8.2 8.6 9.3 9.8 10.1 10.3 11.1 11.6 11.9 12.2 13.0 13.5 13.8 14.1 14.8 15.2 15.9 16.5 17.0 17.4 17.6 17.9 18.6 19.1 19.5 19.7 19.9 20.5 21.1 22.1 Table A3.8 (cont’d) 5.2 4.8 5.7 5.4 6.1 5.9 6.4 6.2 6.8 6.7 7.7 7.3 8.2 7.7 8.5 8.0 8.8 8.7 9.7 9.1 10.3 9.4 10.7 10.0 10.9 10.6 11.8 10.9 12.3 11.2 12.7 11.9 13.1 12.3 13.9 12.5 14.4 13.2 14.7 13.6 15.4 13.9 16.0 14.3 16.4 14.9 16.7 15.2 17.5 15.5 18.0 16.3 18.4 16.7 19.3 17.0 19.7 17.2 20.5 17.9 21.1 18.4 21.5 18.7 21.8 19.0 22.6 19.7 23.0 20.1 23.3 20.4 24.0 20.7 24.6 21.2 25.0 21.7 25.2 22.0 26.0 22.3 26.1 22.5 148 4.7 5.1 5.6 6.0 6.3 6.9 7.2 7.5 8.1 8.7 9.1 9.5 9.9 10.4 11.0 11.5 11.8 12.3 12.9 13.3 13.7 14.2 14.8 15.1 15.6 16.1 16.7 17.2 17.6 18.3 18.8 19.2 19.5 20.1 20.6 20.9 21.4 21.8 22.2 22.6 23.1 23.6 0.5 0.7 0.5 0.5 0.6 0.9 1.0 1.1 1.0 1.1 1.1 1.2 1.2 1.4 1.2 1.2 1.3 1.5 1.3 1.3 1.4 1.6 1.4 1.3 1.5 1.6 1.5 1.7 1.6 1.7 1.7 1.7 1.8 2.0 1.8 1.8 1.9 2.0 2.1 2.0 2.1 1.8 APPENDIX D Metal Bioavailability Study Data Summary 149 Table A4.1 Cumulative methane production from acetate oxidation in the food waste digester FW only Hours 1 2 3 4 5 6 AVG STD 0.5 1.3 1.2 1.3 1.2 0.8 0.77 1.1 0.2 1.0 2.5 2.2 2.3 2.2 1.8 1.69 2.1 0.3 1.5 3.4 2.9 2.9 2.9 2.4 2.23 2.8 0.4 2.0 4.3 3.6 3.7 3.6 3.0 2.76 3.5 0.5 2.5 5.5 4.3 4.4 4.3 3.7 3.43 4.3 0.7 3.0 6.2 4.9 5.0 4.9 4.3 3.92 4.9 0.8 3.5 7.0 5.5 5.6 5.5 5.3 4.84 5.6 0.7 4.0 7.7 5.9 6.1 5.9 6.4 5.85 6.3 0.7 4.5 8.5 6.6 6.7 6.6 7.0 6.48 7.0 0.8 5.0 9.2 7.1 7.3 7.1 7.6 7.01 7.6 0.8 5.5 9.8 7.9 8.0 7.9 8.3 7.60 8.2 0.8 6.0 10.5 8.6 8.8 8.6 9.1 8.37 9.0 0.8 6.5 11.6 9.4 9.6 9.4 10.4 9.59 10.0 0.9 7.0 12.2 10.0 10.2 10.0 10.9 10.06 10.6 0.9 7.5 12.9 10.7 10.9 10.7 11.6 10.65 11.2 0.9 8.0 13.6 11.2 11.4 11.2 12.2 11.23 11.8 1.0 8.5 14.3 12.3 12.5 12.3 12.8 11.81 12.7 0.9 9.0 14.9 13.1 13.3 13.1 14.3 13.17 13.6 0.8 9.5 15.7 13.8 14.1 13.8 15.0 13.84 14.4 0.8 10.0 16.7 14.7 15.0 14.7 15.6 14.33 15.1 0.9 10.5 17.3 15.4 15.7 15.4 16.3 14.96 15.8 0.8 11.0 17.9 16.0 16.4 16.0 16.8 15.49 16.4 0.9 11.5 18.6 16.8 17.2 16.8 17.5 16.07 17.2 0.9 12.0 19.3 17.8 18.2 17.8 19.0 17.48 18.3 0.7 12.5 20.0 18.7 19.1 18.7 19.6 18.01 19.0 0.7 13.0 21.2 19.5 19.9 19.5 20.2 18.59 19.8 0.9 13.5 21.8 20.2 20.7 20.2 20.9 19.22 20.5 0.9 14.0 22.4 21.0 21.4 21.0 22.6 20.77 21.5 0.8 14.5 23.1 21.6 22.0 21.6 23.3 21.44 22.2 0.8 15.0 23.8 22.7 23.2 22.7 24.0 22.07 23.1 0.7 15.5 24.8 23.6 24.1 23.6 24.7 22.70 23.9 0.8 16.0 25.6 24.4 24.9 24.4 26.0 23.96 24.9 0.8 16.5 26.3 25.1 25.6 25.1 26.9 24.74 25.6 0.8 17.0 27.0 25.8 26.4 25.8 27.4 25.22 26.3 0.8 17.5 27.8 26.9 27.5 26.9 28.2 25.90 27.2 0.8 18.0 28.5 27.8 28.4 27.8 29.7 27.30 28.2 0.8 18.5 29.4 28.6 29.2 28.6 30.3 27.83 29.0 0.8 19.0 30.0 29.4 30.0 29.4 31.1 28.62 29.7 0.8 19.5 30.7 30.0 30.6 30.0 31.8 29.25 30.4 0.9 20.0 31.4 31.3 31.9 31.3 33.3 30.65 31.6 0.9 20.5 32.1 32.1 32.8 32.1 34.0 31.28 32.4 0.9 150 21.0 21.5 22.0 22.5 23.0 23.5 24.0 33.1 33.8 34.5 35.3 36.1 36.8 37.4 32.8 33.5 34.5 35.3 36.1 36.9 37.6 Table A4.1 (cont’d) 33.5 32.8 34.7 34.2 33.5 35.7 35.2 34.5 36.7 36.1 35.3 37.9 36.9 36.1 39.2 37.6 36.9 39.9 38.4 37.6 40.8 31.95 32.83 33.79 34.90 36.02 36.75 37.52 33.1 33.9 34.9 35.8 36.7 37.5 38.2 0.9 1.0 1.0 1.1 1.2 1.2 1.3 Table A4.2 Effect of 0.01mg/L Co on acetate utilization rate in the food waste digester Co (0.01 mg/L) Hours AVG STD 1 2 3 0.5 1.3 1.2 1.2 1.2 0.0 1.0 2.2 2.2 2.2 2.2 0.0 1.5 2.9 3.0 2.9 2.9 0.0 2.0 3.6 3.6 3.5 3.6 0.0 2.5 4.1 4.3 4.2 4.2 0.1 3.0 4.9 5.0 4.9 4.9 0.1 3.5 5.4 5.6 5.5 5.5 0.1 4.0 6.0 6.2 6.0 6.1 0.1 4.5 6.6 6.8 6.6 6.6 0.1 5.0 7.2 7.4 7.2 7.3 0.1 5.5 7.9 8.1 7.8 7.9 0.1 6.0 8.5 8.7 8.4 8.5 0.1 6.5 9.2 9.4 9.1 9.2 0.1 7.0 9.8 9.9 9.6 9.8 0.1 7.5 10.6 10.6 10.3 10.5 0.1 8.0 11.2 11.3 11.0 11.2 0.1 8.5 12.4 12.6 12.2 12.4 0.2 9.0 13.3 13.5 13.1 13.3 0.2 9.5 14.1 14.4 14.0 14.2 0.2 10.0 15.0 15.3 14.8 15.0 0.2 10.5 15.5 16.1 15.6 15.7 0.3 11.0 16.2 16.7 16.2 16.4 0.2 11.5 17.0 17.6 17.0 17.2 0.3 12.0 18.1 18.7 18.1 18.3 0.3 12.5 19.0 19.6 19.0 19.2 0.3 13.0 19.8 20.5 19.9 20.1 0.3 13.5 20.6 21.2 20.6 20.8 0.3 14.0 21.2 21.9 21.3 21.4 0.3 14.5 21.8 22.5 21.9 22.1 0.3 15.0 22.9 23.8 23.1 23.3 0.4 15.5 23.8 24.8 24.0 24.2 0.4 16.0 24.6 25.7 24.9 25.0 0.5 151 16.5 17.0 17.5 18.0 18.5 19.0 19.5 20.0 20.5 21.0 21.5 22.0 22.5 23.0 23.5 24.0 25.2 25.9 27.1 28.0 28.9 29.6 30.3 31.4 32.3 33.1 33.7 34.8 35.8 36.6 37.4 38.0 Table A4.2 (cont’d) 26.4 25.6 27.1 26.3 28.3 27.5 29.3 28.4 30.2 29.3 31.0 30.1 31.8 30.9 33.2 32.2 34.1 33.1 35.0 34.0 35.8 34.7 37.0 35.9 38.0 36.8 38.9 37.7 39.7 38.5 40.5 39.3 25.7 26.5 27.6 28.6 29.5 30.2 31.0 32.3 33.2 34.0 34.7 35.9 36.8 37.7 38.5 39.3 0.5 0.5 0.5 0.5 0.6 0.6 0.6 0.7 0.7 0.8 0.9 0.9 0.9 0.9 0.9 1.0 Table A4.3 Effect of 1 mg/L Co on acetate utilization rate in the food waste digester Co (1 mg/L) Hours AVG STD 1 2 3 0.5 0.9 0.8 0.8 0.8 0.0 1.0 1.7 1.7 1.6 1.7 0.1 1.5 2.5 2.5 2.4 2.5 0.1 2.0 3.3 3.2 3.0 3.2 0.1 2.5 4.5 4.3 4.1 4.3 0.2 3.0 5.1 5.0 4.7 4.9 0.2 3.5 5.9 5.8 5.4 5.7 0.2 4.0 6.7 6.6 6.2 6.5 0.2 4.5 7.4 7.4 7.0 7.3 0.2 5.0 8.1 8.2 7.7 8.0 0.2 5.5 8.7 8.9 8.4 8.7 0.2 6.0 9.4 9.6 9.0 9.3 0.2 6.5 10.3 10.6 9.9 10.3 0.3 7.0 11.1 11.2 10.5 10.9 0.3 7.5 11.9 11.9 11.2 11.7 0.3 8.0 12.6 12.7 11.9 12.4 0.3 8.5 13.3 13.4 12.6 13.1 0.3 9.0 13.9 14.1 13.3 13.8 0.4 9.5 14.6 14.9 14.0 14.5 0.4 10.0 15.5 15.8 14.9 15.4 0.4 10.5 16.2 16.5 15.5 16.1 0.4 11.0 17.0 17.3 16.3 16.9 0.4 152 11.5 12.0 12.5 13.0 13.5 14.0 14.5 15.0 15.5 16.0 16.5 17.0 17.5 18.0 18.5 19.0 19.5 20.0 20.5 21.0 21.5 22.0 22.5 23.0 23.5 24.0 17.8 18.5 19.1 20.3 21.0 21.8 22.5 23.2 24.1 25.0 25.7 26.6 27.3 28.1 29.1 29.7 30.6 31.3 32.1 33.2 34.0 34.9 35.6 36.3 37.1 37.7 Table A4.3 (cont’d) 18.1 17.0 18.8 17.7 19.6 18.4 20.8 19.6 21.5 20.2 22.3 21.0 23.1 21.7 24.1 22.6 25.4 23.8 26.4 24.8 27.4 25.7 28.5 26.8 29.5 27.8 30.6 28.8 32.0 30.1 33.0 31.0 33.9 31.9 34.8 32.7 35.6 33.4 36.8 34.6 37.5 35.3 38.5 36.1 39.5 37.1 40.4 37.9 41.3 38.8 42.0 39.5 17.6 18.3 19.0 20.2 20.9 21.7 22.4 23.3 24.4 25.4 26.3 27.3 28.2 29.2 30.4 31.2 32.1 32.9 33.7 34.8 35.6 36.5 37.4 38.2 39.0 39.7 0.5 0.5 0.5 0.5 0.5 0.5 0.6 0.6 0.7 0.7 0.8 0.8 1.0 1.1 1.2 1.3 1.4 1.4 1.4 1.5 1.5 1.5 1.6 1.7 1.7 1.8 Table A4.4 Effect of 10 mg/L Co on acetate utilization rate in the food waste digester Co (10 mg/L) Hours AVG STD 1 2 3 0.5 0.7 0.6 0.7 0.7 0.0 1.0 1.9 1.3 2.0 1.7 0.3 1.5 2.1 1.6 2.3 2.0 0.3 2.0 2.5 2.0 2.6 2.4 0.2 2.5 2.8 2.4 2.9 2.7 0.2 3.0 3.0 2.8 3.2 3.0 0.2 3.5 3.6 3.5 3.7 3.6 0.1 4.0 4.3 4.3 4.5 4.4 0.1 4.5 4.6 4.7 4.9 4.7 0.1 5.0 4.9 5.1 5.2 5.1 0.1 5.5 5.3 5.5 5.5 5.4 0.1 6.0 5.9 6.0 6.1 6.0 0.1 153 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0 10.5 11.0 11.5 12.0 12.5 13.0 13.5 14.0 14.5 15.0 15.5 16.0 16.5 17.0 17.5 18.0 18.5 19.0 19.5 20.0 20.5 21.0 21.5 22.0 22.5 23.0 23.5 24.0 6.8 7.1 7.4 7.8 8.1 9.1 9.5 9.8 10.1 10.5 10.8 11.8 12.1 12.4 12.6 13.4 13.6 13.8 14.1 15.0 15.4 15.6 16.0 16.6 16.9 17.2 17.5 18.3 18.5 18.7 19.4 20.0 20.6 21.3 21.7 22.0 Table A4.4 (cont’d) 7.0 7.2 7.3 7.5 7.8 7.8 8.1 8.2 8.4 8.5 9.4 9.5 9.9 9.9 10.3 10.3 10.6 10.7 11.0 11.0 11.4 11.4 12.5 12.4 12.9 12.7 13.2 13.0 13.6 13.2 14.8 14.0 15.2 14.3 15.6 14.5 16.0 14.8 17.1 15.7 17.5 16.1 17.8 16.4 18.2 16.8 19.3 17.5 19.6 17.8 20.0 18.0 20.3 18.4 21.4 19.2 21.7 19.5 22.2 19.7 23.0 20.4 23.6 21.0 24.3 21.7 25.1 22.4 25.6 22.8 26.0 23.1 154 7.0 7.3 7.6 8.0 8.4 9.3 9.8 10.1 10.5 10.8 11.2 12.2 12.6 12.8 13.1 14.1 14.3 14.6 15.0 16.0 16.3 16.6 17.0 17.8 18.1 18.4 18.7 19.7 19.9 20.2 20.9 21.6 22.2 22.9 23.4 23.7 0.1 0.1 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.3 0.3 0.3 0.4 0.4 0.6 0.7 0.7 0.8 0.9 0.9 0.9 0.9 1.1 1.1 1.2 1.2 1.3 1.4 1.4 1.5 1.5 1.6 1.6 1.6 1.7 Table A4.5 Effect of 0.01 mg/L Ni on acetate utilization rate in the food waste digester Hours 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0 10.5 11.0 11.5 12.0 12.5 13.0 13.5 14.0 14.5 15.0 15.5 16.0 16.5 17.0 17.5 18.0 18.5 19.0 19.5 20.0 1 1.0 1.9 2.7 3.3 3.9 4.5 5.0 5.5 6.1 6.6 7.2 7.8 8.5 9.1 9.8 10.4 11.7 12.7 13.6 14.4 15.1 15.8 16.6 17.8 18.7 19.5 20.3 20.9 21.5 22.9 23.9 24.7 25.4 26.2 27.3 28.3 29.3 30.1 30.8 32.1 Ni (0.01 mg/L) 2 1.0 2.0 2.8 3.4 4.0 4.6 5.2 5.7 6.3 6.7 7.3 8.0 8.6 9.3 9.9 10.5 11.9 12.9 13.9 14.8 15.5 16.2 17.1 18.3 19.3 20.2 20.9 21.6 22.3 23.8 24.8 25.5 26.4 27.1 28.3 29.5 30.5 31.4 32.0 33.5 155 3 1.1 2.1 2.8 3.5 4.1 4.7 5.3 5.9 6.4 7.0 7.6 8.3 9.0 9.7 10.4 11.0 12.4 13.4 14.4 15.3 16.0 16.7 17.5 18.8 19.8 20.7 21.5 22.2 22.8 24.2 25.3 26.2 27.0 27.7 29.0 30.0 31.0 31.9 32.6 34.0 AVG STD 1.0 2.0 2.8 3.4 4.0 4.6 5.1 5.7 6.3 6.8 7.4 8.0 8.7 9.4 10.0 10.7 12.0 13.0 14.0 14.8 15.5 16.2 17.1 18.3 19.3 20.1 20.9 21.6 22.2 23.6 24.6 25.5 26.3 27.0 28.2 29.3 30.3 31.1 31.8 33.2 0.0 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.2 0.2 0.2 0.2 0.3 0.3 0.3 0.3 0.3 0.4 0.4 0.4 0.4 0.4 0.5 0.5 0.5 0.5 0.5 0.6 0.6 0.6 0.6 0.6 0.7 0.7 0.7 0.8 0.8 0.8 20.5 21.0 21.5 22.0 22.5 23.0 23.5 24.0 33.1 33.9 34.7 35.8 37.0 37.9 38.7 39.5 Table A4.5 (cont’d) 34.6 35.1 35.5 36.0 36.4 36.8 37.7 38.0 38.9 39.2 39.9 40.2 40.8 41.1 41.6 41.8 34.3 35.1 36.0 37.2 38.3 39.3 40.2 41.0 0.8 0.9 0.9 1.0 1.0 1.0 1.0 1.1 Table A4.6 Effect of 1 mg/L Ni on acetate utilization rate in the food waste digester Ni (1 mg/L) Hours AVG STD 1 2 3 0.5 1.4 1.3 1.3 1.3 0.0 1.0 2.7 2.6 2.6 2.6 0.1 1.5 4.0 3.8 3.8 3.9 0.1 2.0 5.1 4.9 4.9 5.0 0.1 2.5 6.9 6.6 6.6 6.7 0.2 3.0 8.2 7.8 7.9 8.0 0.2 3.5 9.7 9.2 9.3 9.4 0.2 4.0 11.0 10.5 10.6 10.7 0.2 4.5 12.3 11.7 11.8 12.0 0.3 5.0 13.6 12.9 13.1 13.2 0.3 5.5 14.8 14.1 14.2 14.4 0.3 6.0 16.0 15.2 15.3 15.5 0.3 6.5 17.8 16.9 17.1 17.3 0.4 7.0 19.0 18.1 18.3 18.5 0.4 7.5 20.5 19.5 19.7 19.9 0.4 8.0 22.0 20.9 21.1 21.3 0.5 8.5 23.3 22.1 22.4 22.6 0.5 9.0 24.6 23.4 23.6 23.9 0.5 9.5 26.1 24.8 25.1 25.3 0.6 10.0 27.9 26.5 26.7 27.0 0.6 10.5 29.3 27.8 28.1 28.4 0.6 11.0 30.8 29.2 29.6 29.9 0.7 11.5 32.3 30.6 31.0 31.3 0.7 12.0 33.7 32.0 32.3 32.7 0.7 12.5 35.0 33.3 33.6 34.0 0.8 13.0 37.0 35.2 35.5 35.9 0.8 13.5 38.4 36.5 36.9 37.3 0.8 14.0 40.0 38.0 38.4 38.8 0.9 14.5 41.5 39.4 39.8 40.3 0.9 15.0 42.9 40.8 41.2 41.6 0.9 156 15.5 16.0 16.5 17.0 17.5 18.0 18.5 19.0 19.5 20.0 20.5 21.0 21.5 22.0 22.5 23.0 23.5 24.0 44.7 46.3 47.8 49.4 50.9 52.5 54.4 55.9 57.5 59.0 60.5 62.4 63.9 65.6 67.2 68.7 70.2 71.6 Table A4.6 (cont’d) 42.5 42.9 44.0 44.5 45.4 45.9 46.9 47.5 48.3 48.9 49.9 50.4 51.7 52.3 53.1 53.7 54.6 55.2 56.0 56.7 57.4 58.0 59.3 59.9 60.7 61.4 62.3 63.0 63.8 64.5 65.2 66.0 66.7 67.4 68.0 68.8 43.4 44.9 46.4 47.9 49.4 50.9 52.8 54.2 55.8 57.2 58.6 60.5 62.0 63.6 65.1 66.6 68.1 69.5 1.0 1.0 1.0 1.1 1.1 1.1 1.2 1.2 1.3 1.3 1.3 1.4 1.4 1.4 1.5 1.5 1.5 1.6 Table A4.7 Effect of 10 mg/L Ni on acetate utilization rate in the food waste digester Ni (10 mg/L) Hours AVG STD 1 2 3 0.5 0.4 0.5 0.5 0.5 0.0 1.0 1.8 2.0 1.9 1.9 0.1 1.5 1.9 2.1 2.0 2.0 0.1 2.0 1.9 2.1 2.1 2.0 0.1 2.5 2.0 2.2 2.1 2.1 0.1 3.0 2.0 2.2 2.2 2.1 0.1 3.5 2.3 2.5 2.4 2.4 0.1 4.0 3.1 3.4 3.3 3.3 0.1 4.5 3.2 3.5 3.4 3.4 0.1 5.0 3.4 3.7 3.6 3.6 0.1 5.5 3.6 3.9 3.8 3.8 0.2 6.0 3.7 4.0 3.9 3.9 0.2 6.5 4.6 5.1 5.0 4.9 0.2 7.0 4.8 5.3 5.1 5.1 0.2 7.5 5.0 5.5 5.4 5.3 0.2 8.0 5.2 5.7 5.6 5.5 0.2 8.5 5.3 5.9 5.8 5.7 0.2 9.0 6.5 7.2 7.0 6.9 0.3 9.5 6.8 7.5 7.3 7.2 0.3 10.0 7.0 7.7 7.5 7.4 0.3 157 10.5 11.0 11.5 12.0 12.5 13.0 13.5 14.0 14.5 15.0 15.5 16.0 16.5 17.0 17.5 18.0 18.5 19.0 19.5 20.0 20.5 21.0 21.5 22.0 22.5 23.0 23.5 24.0 7.2 7.5 7.7 9.0 9.2 9.4 9.6 10.9 11.2 11.4 11.7 12.9 13.3 13.5 13.7 15.0 15.3 15.5 15.8 17.1 17.3 17.6 18.4 19.1 19.9 20.7 21.0 21.4 Table A4.7 (cont’d) 8.0 7.8 8.2 8.0 8.4 8.3 9.9 9.7 10.1 9.9 10.3 10.1 10.5 10.3 12.0 11.8 12.3 12.0 12.5 12.3 12.8 12.6 14.2 13.9 14.6 14.3 14.8 14.5 15.1 14.8 16.5 16.2 16.8 16.5 17.1 16.7 17.3 17.0 18.8 18.4 19.0 18.6 19.3 19.0 20.2 19.8 21.0 20.6 21.8 21.4 22.7 22.3 23.1 22.6 23.5 23.0 7.7 7.9 8.1 9.5 9.7 9.9 10.2 11.6 11.8 12.0 12.4 13.7 14.0 14.2 14.6 15.9 16.2 16.4 16.7 18.1 18.3 18.6 19.5 20.3 21.0 21.9 22.3 22.6 0.3 0.3 0.3 0.4 0.4 0.4 0.4 0.5 0.5 0.5 0.5 0.5 0.6 0.6 0.6 0.6 0.6 0.7 0.7 0.7 0.7 0.7 0.8 0.8 0.8 0.9 0.9 0.9 Table A4.8 Effect of 0.5 mg/L Fe on acetate utilization rate in the food waste digester Fe (0.5 mg/L) Hours AVG STD 1 2 3 0.5 2.9 3.3 3.1 3.1 0.1 1.0 3.8 4.1 4.0 4.0 0.1 1.5 5.2 5.7 5.5 5.5 0.2 2.0 6.1 6.7 6.4 6.4 0.2 2.5 7.0 7.7 7.4 7.3 0.3 3.0 8.0 8.7 8.4 8.4 0.3 3.5 8.9 9.6 9.4 9.3 0.3 4.0 9.8 10.5 10.4 10.2 0.3 4.5 10.6 11.3 11.3 11.1 0.3 5.0 11.4 11.8 12.1 11.8 0.3 158 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0 10.5 11.0 11.5 12.0 12.5 13.0 13.5 14.0 14.5 15.0 15.5 16.0 16.5 17.0 17.5 18.0 18.5 19.0 19.5 20.0 20.5 21.0 21.5 22.0 22.5 23.0 23.5 24.0 12.8 13.6 14.5 15.4 16.3 17.2 18.2 19.3 20.1 21.1 22.0 22.9 23.7 25.2 26.0 26.9 27.9 28.7 30.1 31.1 31.9 32.9 33.9 35.0 36.3 37.1 38.1 39.0 40.0 41.4 42.3 43.3 44.3 45.3 46.3 47.2 48.4 49.5 Table A4.8 (cont’d) 13.3 13.6 14.3 14.4 15.4 15.3 16.4 16.3 17.4 17.3 18.5 18.2 19.6 19.2 20.9 20.5 21.5 21.3 22.4 22.3 23.4 23.3 24.5 24.3 25.3 25.2 26.6 26.7 27.7 27.5 29.0 28.5 30.2 29.5 31.1 30.5 32.4 31.9 33.4 32.9 34.6 33.8 35.9 34.9 37.0 35.9 38.2 37.0 39.9 38.4 41.0 39.3 42.3 40.4 43.2 41.4 44.0 42.4 45.2 43.9 45.8 44.8 46.7 45.9 47.5 47.0 48.3 48.0 49.0 49.0 49.9 50.0 51.1 51.3 52.5 52.4 159 13.2 14.1 15.1 16.1 17.0 17.9 19.0 20.2 20.9 21.9 22.9 23.9 24.7 26.1 27.1 28.1 29.2 30.1 31.5 32.5 33.4 34.6 35.6 36.7 38.2 39.2 40.2 41.2 42.1 43.5 44.3 45.3 46.3 47.2 48.1 49.0 50.3 51.5 0.3 0.4 0.4 0.5 0.5 0.6 0.6 0.7 0.6 0.6 0.6 0.7 0.7 0.7 0.8 0.9 1.0 1.0 1.0 1.0 1.1 1.2 1.3 1.3 1.5 1.6 1.7 1.7 1.7 1.6 1.5 1.5 1.4 1.3 1.3 1.3 1.3 1.4 Table A4.9 Effect of 5 mg/L Fe on acetate utilization rate in the food waste digester Fe (5 mg/L) Hours AVG STD 1 2 3 0.5 3.1 3.2 3.3 3.2 0.1 1.0 3.9 4.0 4.2 4.0 0.1 1.5 4.6 4.7 4.9 4.8 0.1 2.0 5.4 5.5 5.7 5.5 0.1 2.5 6.1 6.2 6.4 6.2 0.2 3.0 6.8 6.9 7.2 7.0 0.2 3.5 7.4 7.6 7.8 7.6 0.2 4.0 8.2 8.3 8.6 8.4 0.2 4.5 9.0 9.1 9.5 9.2 0.2 5.0 9.7 9.9 10.3 9.9 0.2 5.5 10.6 10.8 11.2 10.8 0.3 6.0 11.4 11.6 12.1 11.7 0.3 6.5 12.1 12.4 12.8 12.4 0.3 7.0 12.8 13.1 13.6 13.1 0.3 7.5 14.2 14.5 15.1 14.6 0.4 8.0 15.3 15.6 16.2 15.7 0.4 8.5 16.4 16.7 17.3 16.8 0.4 9.0 17.3 17.7 18.3 17.8 0.4 9.5 18.2 18.6 19.3 18.7 0.5 10.0 18.9 19.3 20.1 19.5 0.5 10.5 19.9 20.3 21.1 20.5 0.5 11.0 21.2 21.7 22.5 21.8 0.5 11.5 22.3 22.8 23.7 22.9 0.6 12.0 23.4 23.8 24.8 24.0 0.6 12.5 24.3 24.8 25.7 24.9 0.6 13.0 25.1 25.6 26.6 25.7 0.6 13.5 25.8 26.3 27.3 26.5 0.6 14.0 27.2 27.8 28.8 27.9 0.7 14.5 28.3 28.9 30.0 29.1 0.7 15.0 29.4 30.0 31.1 30.2 0.7 15.5 30.3 30.9 32.1 31.1 0.8 16.0 31.1 31.8 33.0 32.0 0.8 16.5 32.4 33.1 34.4 33.3 0.8 17.0 33.6 34.3 35.6 34.5 0.8 17.5 34.6 35.4 36.7 35.6 0.9 18.0 35.6 36.3 37.7 36.5 0.9 18.5 36.5 37.2 38.7 37.5 0.9 19.0 38.0 38.8 40.3 39.0 0.9 19.5 39.2 40.0 41.5 40.2 1.0 20.0 40.2 41.0 42.6 41.2 1.0 20.5 41.1 42.0 43.6 160 42.2 1.0 21.0 21.5 22.0 22.5 23.0 23.5 24.0 42.4 43.7 44.8 45.8 46.7 48.2 49.3 Table A4.9 (cont’d) 43.3 44.9 44.6 46.3 45.7 47.5 46.8 48.6 47.7 49.5 49.1 51.0 50.3 52.3 43.5 44.9 46.0 47.1 48.0 49.4 50.6 1.1 1.1 1.1 1.1 1.2 1.2 1.2 A4.10 Effect of 100 mg/L Fe on acetate utilization rate in the food waste digester Fe (100 mg/L) Hours AVG STD 1 2 3 0.5 1.6 1.6 1.8 1.7 0.1 1.0 4.0 3.5 4.6 4.1 0.5 1.5 4.5 4.3 5.2 4.7 0.4 2.0 4.9 5.1 5.7 5.2 0.3 2.5 5.4 6.0 6.2 5.9 0.3 3.0 6.1 6.8 7.1 6.7 0.4 3.5 7.7 8.4 8.8 8.3 0.5 4.0 9.0 10.1 10.3 9.8 0.6 4.5 9.7 11.0 11.1 10.6 0.7 5.0 10.4 12.0 11.9 11.4 0.8 5.5 10.8 12.9 12.4 12.0 0.9 6.0 11.5 14.2 13.3 13.0 1.1 6.5 12.8 16.0 14.8 14.5 1.3 7.0 13.3 16.9 15.3 15.2 1.5 7.5 14.0 17.6 16.1 15.9 1.5 8.0 14.5 18.5 16.7 16.6 1.6 8.5 15.1 19.3 17.4 17.2 1.7 9.0 16.8 21.1 19.3 19.1 1.8 9.5 17.4 22.1 20.1 19.9 1.9 10.0 17.9 22.9 20.6 20.5 2.0 10.5 18.8 23.7 21.6 21.4 2.0 11.0 19.3 24.5 22.3 22.0 2.1 11.5 19.9 25.1 22.9 22.6 2.2 12.0 21.4 26.8 24.7 24.3 2.2 12.5 21.9 27.4 25.2 24.8 2.3 13.0 22.4 28.2 25.8 25.5 2.4 13.5 23.3 29.1 26.8 26.4 2.4 14.0 24.9 31.1 28.7 28.3 2.6 14.5 25.6 32.2 29.5 29.1 2.7 15.0 26.4 33.3 30.4 30.0 2.8 161 15.5 16.0 16.5 17.0 17.5 18.0 18.5 19.0 19.5 20.0 20.5 21.0 21.5 22.0 22.5 23.0 23.5 24.0 27.1 28.7 29.6 30.2 30.8 33.4 34.9 36.2 37.6 40.4 41.3 42.2 43.5 44.8 46.1 47.5 48.4 49.4 Table A4.10 (cont’d) 34.1 31.2 35.6 33.1 36.5 34.1 37.3 34.8 38.1 35.5 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