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Integrated approach for accurate quantification of methane generation at municipal solid waste landfills Abedini, Ali Reza 2014

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INTEGRATED APPROACH FOR ACCURATE QUANTIFICATION OF METHANE GENERATION AT MUNICIPAL SOLID WASTE LANDFILLS  by Ali Reza Abedini M.A.Sc. Civil and Environmental Engineering, Tehran University, 2003 B.Sc., Civil Engineering, Isfahan University of Technology, 1999  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Civil Engineering)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)   December 2014  © Ali Reza Abedini, 2014 ii  Abstract Municipal solid waste (MSW) landfills have been identified by regulators and policy-makers as primary sources of greenhouse gas (GHG) emissions. Landfill gas (LFG) generation is best described as a first order reaction which is the basis of many LFG generation models. These models are tools to predict a landfill’s lifespan methane generation, in lieu of costly full scale quantification methods. Moreover, modeling results are required to properly design LFG recovery and utilization systems. These results are also used by the GHG emission regulatory authorities to establish and enforce regulations, and modify and fine-tune the existing policies, regulations, and inventory reports. However, with a large number of variables affecting the biological decomposition process within landfills, exact quantification of methane generation and/or emission from these sources is literally impossible.  Several investigations have raised serious doubts about the accuracy of many existing models, hence, the validity of model-based emission statistics utilized by the national and international organizations. A quick modeling exercise presented in Chapter 1, involving 5 popular LFG generation models showed up to 340% variation for a single site, arguably showing the need for an advanced model which offers more realistic, consistent, and comparable results that could be used by landfill owners, engineers, and regulatory agencies.   In this research, an integrated LFG generation model was developed based on the waste decomposition principles and operational and environmental conditions. Methodologies for effective full scale quantification of fugitive methane emissions were also developed. With the unique opportunity which was made available at the Vancouver landfill (VLF), a newly iii  developed integrated gas generation model (iModel-110©) was calibrated and verified based on a comprehensive landfill methane mass balance investigation. The field investigations conducted at the VLF consisted of four major phases including: (i) development of an LFG recovery system database, (ii) monitoring the landfill’s behavior in time and with respect to changes in ambient conditions, (iii) measurement of fugitive methane emissions through an innovative approach, and (iv) quantification of the biological methane oxidation in the landfill’s cover soil using the stable isotope technique.     iv  Preface The overall supervision of this research was provided by Professor James W. Atwater.  Part of the work presented in this dissertation has been previously published in Journal of Waste Management and Research, is under review for publication, or has been presented at the national and international conferences. The following is a list of such manuscripts and or conference presentations:  Abedini, A. R., J. W. Atwater and G. Y. Fu (2012). “Effect of recycling activities on the heating value of solid waste: case study of the Greater Vancouver Regional District (Metro Vancouver).” Waste Management & Research 30(8): 839-848.  Abedini, A. R., J. W. Atwater and G. Y. Fu (2012) “Effects of Future Recycling Activities on Waste Disposal Options: Case Study of the Metro Vancouver, British Columbia.” ISWA 2012 World Congress Proceedings, Florence, Italy.   Abedini, A. R., J. W. Atwater, J. P. Chanton (2014). “Quantifying Methane Oxidation at Municipal Landfills Cover Soil Using the Stable Isotope Technique and Flux Chamber”. (currently under consideration for publication)  Abedini, A. R., J. W. Atwater, U. Mayer  (2014). “Quantifying Fugitive Methane Emissions from MSW Landfills Based on Surface Methane Concentrations”. (currently under consideration for publication) v  Table of Contents  Abstract .......................................................................................................................................... ii Preface ........................................................................................................................................... iv Table of Contents ...........................................................................................................................v List of Tables ............................................................................................................................... xii List of Figures ............................................................................................................................. xvi List of Abbreviations ................................................................................................................. xxi Acknowledgements .................................................................................................................. xxiii Dedication ...................................................................................................................................xxv Chapter  1: Introduction ...............................................................................................................1 1.1 Background ..................................................................................................................... 1 1.2 Landfill Gas Concept ...................................................................................................... 4 1.2.1 Biodegradation Phases ................................................................................................ 4 1.2.2 Anaerobic Digestion Principles .................................................................................. 6 1.2.2.1 Stoichiometric Estimate of Gas Production ........................................................ 7 1.3 Landfill Gas Generation Modeling ............................................................................... 12 1.4 Popular LFG Generation Models Overview ................................................................. 17 1.4.1 U.S. EPA LandGEM ................................................................................................. 18 1.4.1.1 LFG Generation Modeling for VLF-Phase 1: LandGEM ................................. 19 1.4.2 IPCC Model .............................................................................................................. 20 1.4.2.1 LFG Generation Modeling for VLF-Phase 1: IPCC Model ............................. 22 1.4.3 Environment Canada ................................................................................................. 23 vi  1.4.3.1 LFG Generation Modeling for VLF-Phase 1: Environment Canada ................ 24 1.4.4 Golder Model ............................................................................................................ 25 1.4.4.1 LFG Generation Modeling for VLF-Phase 1: Golder Method ......................... 26 1.4.5 BC MOE LFG Generation Assessment Tool............................................................ 27 1.4.5.1 LFG Generation Modeling for VLF-Phase 1: BC MOE Tool .......................... 29 1.4.6 Comparison of Different Modeling Results .............................................................. 30 1.5 Statement of the Problem .............................................................................................. 32 1.6 Objectives of the Study ................................................................................................. 33 Chapter  2: Materials and Methods ...........................................................................................35 2.1 Metro Vancouver .......................................................................................................... 35 2.2 Vancouver Landfill ....................................................................................................... 38 2.2.1 Gas Collection System at the VLF............................................................................ 38 2.2.2 Development of GCS Database ................................................................................ 40 2.2.3 Climatic Conditions .................................................................................................. 40 2.2.4 Historical Waste Tonnage at the VLF ...................................................................... 41 2.2.5 Research Boundary at the VLF ................................................................................. 43 2.3 Burnaby Waste-to-Energy Facility (WTEF) ................................................................. 43 2.4 Municipal Solid Waste Composition and Characteristics ............................................ 43 2.4.1 Heating Value of MSW ............................................................................................ 44 2.4.2 Composition of Wastes Deposited at the VLF ......................................................... 48 2.4.3 Moisture Content of Municipal Solid Waste ............................................................ 50 2.5 METRO Equation ......................................................................................................... 51 Chapter  3: Advanced Landfill Gas Generation Modeling ......................................................55 vii  3.1 Introduction ................................................................................................................... 55 3.2 Methane Yield (Lₒ, m3 tonne-1) ..................................................................................... 56 3.2.1 Degradability Factor (fdg) .......................................................................................... 59 3.2.2 Climate Factor (fcl) .................................................................................................... 64 3.2.3 Depth Factor (fdp) ...................................................................................................... 66 3.2.4 Other Factors ............................................................................................................. 67 3.2.5 Calculated Values for Methane Yield (Lₒ, m3 tonne-1) ............................................. 69 3.3 Decay Rate (k, year -1) .................................................................................................. 72 3.3.1 Temperature .............................................................................................................. 75 3.3.1.1 Landfill Temperature Investigations ................................................................. 77 3.3.1.2 Results and Discussion ..................................................................................... 84 3.3.1.3 Older Temperature Study at the Vancouver Landfill ....................................... 94 3.3.1.4 Conclusion ........................................................................................................ 95 3.3.2 Moisture Content ...................................................................................................... 97 3.3.2.1 The World Bank ................................................................................................ 99 3.3.2.2 Environment Canada and Golder Associates .................................................. 100 3.3.2.3 BC Ministry of Environment .......................................................................... 100 3.3.2.4 IPCC Methodology ......................................................................................... 101 3.3.3 Suggested Values for Decay Rates (k, year-1) ........................................................ 102 3.4 Delay Time.................................................................................................................. 104 3.5 The New Model .......................................................................................................... 105 3.5.1 The New Model Results for the Vancouver Landfill.............................................. 107 3.6 Discussion ................................................................................................................... 110 viii  Chapter  4: Fugitive Methane Emissions (E) ..........................................................................112 4.1 Introduction ................................................................................................................. 112 4.2 Fugitive Emission Measurement Techniques ............................................................. 113 4.3 Surface Methane Concentration (SMC) Measurements at VLF ................................. 115 4.4 Flux Chamber.............................................................................................................. 119 4.4.1 Dynamic and Static Flux Chambers ....................................................................... 119 4.4.2 Field Work Procedure ............................................................................................. 121 4.4.3 Modified Static Flux Chamber Measurements at VLF ........................................... 122 4.5 Effect of Barometric Pressure on Methane Emission Rates ....................................... 128 4.6 Results and Discussion ............................................................................................... 134 4.7 Total Fugitive Methane Emission from the Vancouver Landfill ................................ 137 Chapter  5: Methane Oxidation in Cover Soil (O) ..................................................................139 5.1 Introduction ................................................................................................................. 139 5.2 Characteristics of Cover Soils at the Vancouver Landfill .......................................... 140 5.3 Stable Isotope Technique ............................................................................................ 141 5.4 Oxidation Fractionation Factor (αox) ........................................................................... 145 5.5 Transport Fractionation Factor (αt) ............................................................................. 150 5.6 Results and Discussion ............................................................................................... 151 5.6.1 Residual Methane.................................................................................................... 152 5.6.2 Anaerobic Methane ................................................................................................. 153 5.6.3 Soil Incubation and Isotopic Fractionation Factor .................................................. 154 5.6.4 Fraction of Methane Oxidized (fox) ......................................................................... 160 5.7 Total Methane Oxidation at the Vancouver Landfill .................................................. 162 ix  Chapter  6: LFG Recovery at the Vancouver Landfill (R) ....................................................165 6.1 VLF Gas Collection System Operational Data ........................................................... 165 6.2 The Vancouver Landfill LFG Database ...................................................................... 166 6.3 Methane Recover Rate at the Vancouver Landfill (R) ............................................... 171 Chapter  7: LFG Generation Modeling Calibration and Verification..................................175 7.1 Initial iModel-110© Verification ................................................................................. 175 7.2 Uncertainties in the New Modeling Predictions ......................................................... 177 7.3 iModel-110© Calibration ............................................................................................. 179 7.3.1 LFG Generation Calibration Factor (CFG).............................................................. 179 7.3.2 Revised iModel-110© Verification ......................................................................... 181 7.3.3 LFG Generation Rates Calibration Factor (CFk) .................................................... 183 7.4 Methane Generation Estimates for the Entire Vancouver Landfill ............................ 186 Chapter  8: Landfill Gas Modeling Uncertainties and Sensitivity Analysis .........................189 8.1 Introduction ................................................................................................................. 189 8.2 LFG Modeling Errors Due to Input Parameters Uncertainties (Gi-Err) ..................... 190 8.2.1 LFG Modeling Errors Due to DOC Uncertainty Range (Gi-Err)DOC ...................... 194 8.2.2 LFG Modeling Errors Due to Decay Rates Uncertainty Range (Gi-Err)k .............. 197 8.2.3 MSW Moisture Content and the Associated LFG Modeling Errors (Gi-Err)w ....... 200 8.3 Calibration Errors Resulted from the Field Study Deviations (CFG-Err) ................... 201 8.3.1 Errors Due to the Methane Emission Measurement Uncertainties (CFG-Err)E ...... 202 8.3.2 Errors Due to the Methane Oxidation Measurement Uncertainties (CFG-Err)O ..... 204 8.3.3 Errors Due to the Methane Recovery Data Deviations (CFG-Err)R ........................ 207 8.4 Error Analyses Conclusion ......................................................................................... 208 x  Chapter  9: Summary and Conclusions ...................................................................................210 9.1 Common LFG Generation Modeling Methodologies and Shortfalls ......................... 210 9.2 Vancouver Landfill, the Unique Opportunity ............................................................. 212 9.3 Main Contributions to the LFG Industry .................................................................... 213 9.3.1 The New Model ...................................................................................................... 213 9.3.2 Other Outcomes of the Study .................................................................................. 215 9.3.3 Specific Results ....................................................................................................... 216 9.4 Significance of the Results from Regulatory Perspective........................................... 217 9.5 Applicability and Use of the New Model ................................................................... 218 9.6 Recommendations ....................................................................................................... 220 References ...................................................................................................................................222 Appendices ..................................................................................................................................234 Appendix A Landfill Gas Generation Modeling Full Results ................................................ 234 A.1 LFG Generation Modeling for VLF-Phase 1: LandGEM Model ........................... 234 A.2 LFG Generation Modeling for VLF-Phase 1: IPCC Model ................................... 242 A.3 LFG Generation Modeling for VLF-Phase 1: BC MOE Tool ................................ 245 Appendix B iModel-110©  Modeling Results – Vancouver Landfill ...................................... 247 B.1 iModel-110©  Modeling Results – Area 2W .......................................................... 247 B.2 iModel-110©  Modeling Results – Area 2E ........................................................... 258 B.3 iModel-110©  Modeling Results – Area 3 ............................................................. 270 B.4 iModel-110©  Modeling Results – Phase 1 ............................................................ 282 B.5 iModel-110©  Modeling Results – Entire Research Boundary .............................. 294 Appendix C Wellfield Inspection and Temperature Investigations ........................................ 306 xi  C.1 LFG Wells and Coordinates.................................................................................... 306 C.2 LFG Wells Temperature Survey Results ................................................................ 311 Appendix D LFG Emission Investigations ............................................................................. 329 D.1 Flux Chamber Survey Data - Vancouver Landfill (June - July 2012) .................... 329 D.2 Full Results of The Flux Chamber Survey and Measured Methane Emission Rates (MER) at the Vancouver Landfill ....................................................................................... 353 D.3 Graphical Presentation of the Recorded Barometric Pressure During Preliminary Surface Scan and Flux Measurement Test at the Vancouver Landfill................................ 355 D.4 Estimated Methane and Landfill Gas Emission Rate at the Vancouver Landfill Within the Study Boundary ................................................................................................ 364 Appendix E Stable Isotope Tests Raw Data and Full Results ................................................ 367 E.1 Flux Chamber Initial and Final Gas Samples ......................................................... 368 E.2 Soil Gas Samples Raw Data, GC-FID, and GCC-IRMS Results ........................... 369 Appendix F Landfill Gas Collection System Wellfield Readings .......................................... 373 F.1 Collected LFG Flow Rates at Manifolds, Adjusted to 50% Methane Content ....... 373    xii  List of Tables Table 1.1 Composition of waste deposited at the Vancouver Landfill in 2009 .............................. 8 Table 1.2 Chemical elements and formula of waste deposited in the VLF in 2009 ....................... 9 Table 1.3 LandGEM default modeling parameters ....................................................................... 19 Table 1.4 IPCC default decay rates for different climatic regions ............................................... 21 Table 1.5 IPCC default DOC content for different MSW components ........................................ 21 Table 1.6 IPCC model methane correction factors ....................................................................... 22 Table 1.7 Decay rates corresponding precipitation suggested by RTI  ........................................ 24 Table 1.8 BC MOE tool methane generation potential values  .................................................... 28 Table 1.9 BC MOE tool default methane generation rates  .......................................................... 29 Table 1.10 Waste composition for VLF Phase 1 based on the MOE waste categories ................ 29 Table 1.11 Comparison of modeling parameters and results for different methodologies_VLF Phase 1 .......................................................................................................................................... 32 Table 2.1 Historical waste generation and disposal tonnages at Metro Vancouver ..................... 37 Table 2.2 Climate Normals 1971-2000 for the Vancouver international airport weather station 41 Table 2.3 Historical waste disposal rates at different phases of the Vancouver Landfill ............. 42 Table 2.4 Historical and estimated MSW composition in Metro Vancouver (1991 - 2009) ........ 44 Table 2.5 Selected formulae for calculating heating value of MSW ............................................ 46 Table 2.6 Typical ultimate analysis data for combustible components of MSW ......................... 46 Table 2.7 Composition of the waste deposited at the Vancouver Landfill (w/w%) ..................... 49 Table 2.8 Moisture content of different components of MSW ..................................................... 51 Table 3.1 Dry base DOC content for different MSW components............................................... 58 xiii  Table 3.2 Optimum degradability extents for different materials reported by Eleazer et al. (1997)....................................................................................................................................................... 61 Table 3.3 Degradability factor for different waste components ................................................... 63 Table 3.4 Suggested climate factors for different precipitation levels ......................................... 66 Table 3.5 Suggested depth factors for different climatic conditions ............................................ 67 Table 3.6 Methane yield for different type of organic wastes deposited at the Vancouver Landfill....................................................................................................................................................... 70 Table 3.7 Calculated variable Lₒ values for advanced LFG generation assessment at VLF ........ 71 Table 3.8 Selected wells for the landfill's temperature investigation ........................................... 80 Table 3.9 Landfill temperature field investigation results (red entries represent invalid recorded data)............................................................................................................................................... 89 Table 3.10 Summary of landfill temperature investigations (Depths 8 to 10 m B.G.) ................. 95 Table 3.11 Decay rates corresponding precipitation suggested by the World Bank .................. 100 Table 3.12 Decay rates based on Environment Canada and Golder Associates methods .......... 100 Table 3.13 Decay rates suggested by the BC MOE modeling guideline .................................... 101 Table 3.14 IPCC default decay rates when merged over all ranges of ambient temperature ..... 102 Table 3.15 Suggested k values assigned to different precipitation levels for advanced LFG generation assessment ................................................................................................................. 104 Table 3.16 Suggested average delay time based on precipitation levels .................................... 105 Table 3.17 Summary of the initial methane generation modeling results (Gi) for the work site areas ............................................................................................................................................ 108 Table 3.18 Comparison between the iModel-110© initial results with the popular LFG generation models ......................................................................................................................................... 111 xiv  Table 4.1 Methane emission level zones and assigned average concentrations at VLF ............. 118 Table 4.2 Selected grids for flux chamber test at VLF ............................................................... 125 Table 4.3 Summary of MER resulted from the flux chamber survey at selected grids at VLF . 127 Table 4.4 Flux measurement duplicates for accuracy of the test ................................................ 131 Table 4.5 Methane flux measurement results and SMCa data for each emission zone .............. 135 Table 4.6 Total fugitive methane emissions from each area of the VLF .................................... 138 Table 5.1 Cover soil samples for incubation .............................................................................. 148 Table 5.2 Methane emission rates (MER) and residual methane δ13C values ............................ 152 Table 5.3 Anaerobic methane δ13C value at the Vancouver Landfill ......................................... 153 Table 5.4 Oxidation isotopic fractionation factor (αox) for different cover soil types at VLF .... 159 Table 5.5 Effect of temperature on methane oxidation fractionation factor ............................... 160 Table 5.6 Effect of soil moisture content on methane oxidation fractionation factor ................ 160 Table 5.7 Fraction of methane oxidized in the Vancouver Landfill cover soil .......................... 161 Table 5.8 Total methane oxidation at each area of VLF ............................................................. 164 Table 6.1 Wellfield manifolds (sub-headers) reading examples ................................................ 172 Table 6.2 Summary of methane recovery data for different areas of the work site .................... 174 Table 7.1 Summary of filed data for the study boundary ........................................................... 175 Table 7.2 Initial methane generation modeling lack of fit and suggested generation calibration factors .......................................................................................................................................... 177 Table 7.3 Summary of the calibrated modeling results (using CFG) and the corresponding methane capture efficiency ......................................................................................................... 180 Table 7.4 Calibrated decay rate values for different organic wastes at the VLF ........................ 183 xv  Table 7.5 Summary of the calibrated modeling results (using CFk) and the corresponding methane capture efficiency ......................................................................................................... 185 Table 7.6 Methane generation modeling results for the VLF using the iModel-110© and the MOE Tool ............................................................................................................................................. 187 Table 8.1 Low and high DOCdry values for different organic wastes deposited at VLF ............ 191 Table 8.2 Low and high ranges of half-lives and decay rates for different organic wastes at VLF..................................................................................................................................................... 193 Table 8.3 Methane generation and capture efficiency deviations in the VLF (within the study boundaries) resulted from application of lower and higher ranges of DOC values .................... 195 Table 8.4 Effect of DOC discount factors on methane generation estimates ............................. 196 Table 8.5 Methane generation uncertainties due to the decay rates uncertainty range ............... 198 Table 8.6 Maximum deviations in generation estimates due to decay rates for different lifespan periods ......................................................................................................................................... 199 Table 8.7 Methane generation uncertainties due to organic material moisture content ............. 200 Table 8.8 Deviation in methane oxidation rate due to fractionation factors uncertainties in Area A .................................................................................................................................................. 205 Table 8.9 Deviation in methane oxidation rate due to fractionation factors uncertainties in Area A .................................................................................................................................................. 205 Table 8.10 Generation calibration factor uncertainties due to the oxidation rate uncertainty range..................................................................................................................................................... 206 Table 8.11 Deviation in CFG due to uncertainty range in methane recovery data ...................... 207 Table 9.1 Summary of 2012 methane budget within the work site ............................................ 218   xvi  List of Figures Figure 1.1 Landfill gas production phases (ATSDR, 2001) ........................................................... 5 Figure 1.2 Methane generation rates at the VLF Phase 1– LandGEM v3.02 ............................... 20 Figure 1.3 Methane generation rates at the VLF Phase 1– IPCC Model ...................................... 23 Figure 1.4 Methane generation rates at the VLF Phase 1–  Environment Canada ....................... 25 Figure 1.5 Methane generation rates at the VLF Phase 1– Golder Associates ............................. 27 Figure 1.6 Methane generation rates at the VLF Phase 1– BC MOE Tool .................................. 30 Figure 1.7 Different methodologies LFG generation modeling results_VLF Phase 1 ................. 31 Figure 2.1 Overall historical waste diversion rates at Metro Vancouver (GVRD, 2010). ........... 36 Figure 2.2 Metro Vancouver and location of Vancouver Landfill and its operational phases ..... 39 Figure 2.3 Normalized components of MSW in Metro Vancouver.............................................. 48 Figure 2.4 Double ditch system at VLF site ................................................................................. 52 Figure 3.1 Recorded ambient temperature at the VLF site ........................................................... 78 Figure 3.2 Daily min. and max. temperature recorded at the Vancouver Int'l Airport weather station ............................................................................................................................................ 78 Figure 3.3 Location of selected LFG wells for landfill temperature investigations ..................... 79 Figure 3.4 Temperature data logger and chamber (left), and installation set-up at ~10m below ground just above leachate level in an LFG well (right) .............................................................. 81 Figure 3.5 Temperature profile in LFG well “A2W-V007”, December 13th, 2010 (ambient T ~8° C, depth of waste ~10m and area closed with interim cover soil since 1993) .............................. 82 Figure 3.6 Temperature profile in LFG well “A2W-V012”, December 13th, 2010 (ambient T ~8° C, depth of waste ~11m and area closed with interim cover soil since 1993) .............................. 82 xvii  Figure 3.7 Temperature profile in Gas Well P01-V034, December 13th, 2010 (ambient T ~8° C, depth of waste ~33m and area closed with geomembrane cover since 2009) .............................. 83 Figure 3.8 Temperature data for the LFG well "P01-V034" (5 m B.G.) ...................................... 85 Figure 3.9 Comparison of monthly average temperature data (Ambient vs. P01-V034) ............. 86 Figure 3.10 Hourly temperature fluctuations - ambient vs. landfill temperature (P01-V034) ..... 86 Figure 3.11 Temperature data for the LFG well "P01-V041" (9.5 m B.G.) ................................. 87 Figure 3.12 Temperature data for the LFG well "A2W-V056" (8 m B.G.) ................................. 88 Figure 3.13 Recorded data at well "P01-V054"_example of wellfield adjustment affecting recorded temperature .................................................................................................................... 90 Figure 3.14 Example of faulty temperature readings at LFG well "P01-V031" Due to the LFG collection system operational issues ............................................................................................. 91 Figure 3.15 System vacuum and LFG flow rate at P01-V031 ...................................................... 93 Figure 3.16 System vacuum and LFG flow rate at P01-V030 ...................................................... 93 Figure 3.17 LFG wellhead and LANDTEC GEM2000+ used to collect gas data at VLF ........... 94 Figure 3.18 A Snapshot of other available temperature data recorded through a comprehensive study by (Hanson et al. 2010) at several landfills including VLF (8 m B.G.) (Raw data were provided by COV)......................................................................................................................... 95 Figure 3.19 Average historical waste composition for different areas of VLF .......................... 108 Figure 3.20 Total waste deposition rate in the four areas within the study boundary at VLF .... 109 Figure 3.21 Methane generation rates from different waste components at VLF ...................... 109 Figure 3.22 Estimated landfill gas and methane generation rates at the work site ..................... 110 Figure 4.1 SMC measurement grids and IDs at the work site (VLF) ......................................... 116 Figure 4.2 Landtec SEM-500 (FID)............................................................................................ 116 xviii  Figure 4.3 VLF surface CH4 concentrations scan with FID (left), and Phase 1 measurement grids and scanned patterns (right) ........................................................................................................ 117 Figure 4.4 Work site divided into 5 different emission zones based on the SMC data .............. 118 Figure 4.5 Flux Chamber and GEM™ 2000+ set-up ................................................................. 123 Figure 4.6 Selected grids within the study boundary for flux chamber measurements at VLF . 125 Figure 4.7 Example of recorded methane concentration levels inside the flux chamber increasing over time ..................................................................................................................................... 126 Figure 4.8 Recorded barometric pressure and temperature at the Vancouver Landfill (July 16, 2012) ........................................................................................................................................... 129 Figure 4.9 Barometric pressure at the Vancouver Landfill (June 26, 2012) ............................... 130 Figure 4.10 Barometric pressure at Vancouver Landfill (July 16, 2012) ................................... 130 Figure 4.11 Correlation between rate of change in BP and adjusting multiplier for MER ........ 132 Figure 4.12 Averaged surface methane concentration (SMCa) and methane emission rate (MERa) for 12 measurement grids at VLF ................................................................................. 135 Figure 4.13 Correlation between SMC and MER values developed over 12 measurement grids at the VLF ....................................................................................................................................... 136 Figure 5.1 Sampling procedure for the stable isotope tests ........................................................ 142 Figure 5.2 Soil sample moisture/organic content and incubation tests ....................................... 147 Figure 5.3 Standard curves developed during the GC-FID tests ................................................ 149 Figure 5.4 A few FID test response snap shots ........................................................................... 149 Figure 5.5 Methane concentrations during the soil incubation tests for soil sample collected from Area A with 1.5% organic content, incubated at 25°C at two moisture content levels of 7.7% (1a) and 10.7% (1b) ............................................................................................................................ 154 xix  Figure 5.6 Methane concentrations during the soil incubation tests for soil sample collected from Area B with 6.8% organic content, Incubated at 25°C at two moisture content levels of 7.1% (3a) and 11.8% (3b) ............................................................................................................................ 155 Figure 5.7 Methane concentrations during the soil incubation tests for soil sample collected from Area B with 6.8% organic content, incubated at 5°C at two moisture content levels of 7.1% (4a) and 11.8% (4b) ............................................................................................................................ 156 Figure 5.8 Methane concentrations during the soil incubation tests for soil sample collected from Area A with 2.2% organic content and 9.7% moisture content (2a), incubated at 25°C ............ 156 Figure 5.9 E Methane concentrations during the soil incubation tests for soil sample collected from Area B with 5.4% organic content, incubated at 25°C at two moisture content levels of 12.4% (5a) and 16.0% (5b) ......................................................................................................... 157 Figure 5.10 Methane concentrations during the soil incubation tests for soil sample collected from Area B with 3.0% organic content, incubated at 25°C at two moisture content levels of 4.2% (6a) and 14.0% (6b). Results from incubation of this sample was excluded from the final analyses as the sample was not believed to represent the whole area. ....................................... 158 Figure 5.11 Soil gas samples methane isotopic signature........................................................... 159 Figure 5.12 Relationship between methane emission rates (MER) and fraction of methane oxidized (fox) ............................................................................................................................... 162 Figure 6.1 The Vancouver Landfill LFG database ..................................................................... 167 Figure 6.2 Graphical menu of the Vancouver Landfill LFG database ....................................... 167 Figure 6.3 Example graphical outputs of the LFG database ....................................................... 168 Figure 6.4 LFG database data entry form ................................................................................... 169 Figure 6.5 LFG database, an example tabulated output.............................................................. 170 xx  Figure 6.6 Collected LFG flow rates from the four areas of VLF (adjusted for 50% CH4 content)..................................................................................................................................................... 172 Figure 6.7 Captured LFG flow rates at VLF (flow rated are adjusted for 50% methane content)..................................................................................................................................................... 173 Figure 7.1 Comparison of initial modeling results and field data (Gi vs METRO) .................... 176 Figure 7.2 Upper limit and lower limit methane generation predictions for the study boundary178 Figure 7.3 Methane generation modeling results with calibrated generation potential (CFG) ... 180 Figure 7.4 Modeling results with calibrated k values in comparison to the results with lower and higher CFG .................................................................................................................................. 184 Figure 7.5 Methane generation and LFG flow rate estimates for the entire Vancouver Landfill site (for the disposal activities until end of 2011) ....................................................................... 187 Figure 7.6 Comparison of the new model predictions with other six popular LFG generation models ......................................................................................................................................... 188 Figure 8.1 Sensitivity analysis, ∆DOC vs. ∆CH4 (methane generation estimate for 2012) ....... 192 Figure 8.2 Sensitivity analysis, ∆k vs. ∆CH4 (methane generation estimate for 2012) .............. 194 Figure 8.3 Graphical illustration of methane generation with lower and higher DOC ranges in comparison with the initial (Gi) and the calibrated modeling results ......................................... 196 Figure 8.4 Effect of DOC discount factors on methane generation estimates ............................ 197 Figure 8.5 Methane generation uncertainties due to the decay rates uncertainty range ............. 199 Figure 8.6 Methane generation uncertainties due to organic material moisture content ............ 201    xxi  List of Abbreviations ASL Above Sea Level AR4 Fourth Assessment Report AR5 Fifth Assessment Report ATSDR Agency for Toxic Substances and Disease Registry BC British Columbia BC MOE British Columbia Ministry of Environment B.G. Below Ground BP Barometric Pressure CAA Clean Air Act CE Collection Efficiency COV City of Vancouver CRA Conestoga-Rovers & Associates DOC Degradable organic carbon ER Emission Reduction FID Flame Ionization Detector FOD First Order Decay FSU Florida State University GA Golder Associates Ltd GCC-IRMS Gas Chromatograph Combustion Isotope Ratio Mass Spectrometer GCS Gas Collection System GGRTA Greenhouse Gas Reductions Target Act GHG Greenhouse Gas GTE Gas-to-Energy GVRD Greater Vancouver Regional District HHV Higher Heating Value IPCC Intergovernmental Panel on Climate Change IR Infra-red LF Landfill LFG Landfill Gas LFGCS Landfill gas collection system LHV Lower Heating Value MAT Mean Annual Temperature MER Methane Emission Rate MOE Ministry of Environment MSW Municipal Solid Waste MV Metro Vancouver xxii  NHV Net Heating Value NMOC Non-methane Organic Compounds NSPS New Source Performance Standards OP-TDLAS Open-path tunable diode laser absorption spectroscopy ORS Optical Remote Sensing ROI Radius of Influence RPM Radial Plume Mapping SCFM Standard Cubic Feet per Minute SHA Sperling Hansen Associates Inc. SMC Surface Methane Concentration SWICS Solid Waste Industry for Climate Solutions SWMS Solid Waste Management System TNO The Netherlands Organization Of Applied Scientific Research TRI Technology Resource Inc. US-EPA The United States Environmental Protection Agency VLF Vancouver Landfill VOC Volatile Organic Compounds UV Ultra Violet UV-DOAS Ultraviolet Differential Absorption Spectroscopy WTE Waste-to-Energy WTEF Waste-to-Energy Facility    xxiii  Acknowledgements  It is my pleasure to convey my gratitude to a great number of people whose support and contribution in different ways helped me throughout my Ph.D. studies.  First and foremost, I would like to express my sincerest gratitude to Professor James W. Atwater (Jim) for his continuous support, supervision, advice, and guidance throughout the work. Thank you for your patience, motivation, enthusiasm, unflinching encouragement and your immense knowledge. Your advice on both my research and career has been priceless. I could not imagine having a better advisor and mentor for my Ph.D. studies. I would also like to thank the rest of my research technical committee: Dr. George Fu, Dr. Eric Hall, Dr. Uli Mayer, and Colin Wong, for their encouragement, insightful comments, and brilliant suggestions. I also thank Dr. Jeff Chanton of Florida State University, for his technical guidance. My sincere thanks also goes to Dr. Don Mavinic for trusting me and giving me the opportunity to be part of the Pollution Control and Waste Management (PCWM) Group at UBC.  I thank Paul Henderson (Manager of Solid Waste Services) and Chris Allan of Metro Vancouver for their generosity in sharing the regional district waste management data and for supporting my Ph.D. research. My special thanks also goes to the City of Vancouver (COV), for partial financial support and the unique opportunity provided through granting me full access to the Vancouver Landfill (VLF) site, including all the historical and ongoing data. In particular I thank Lynn Belanger (Manager of the VLF), Don Darrach, Nicole Steglich, and Eric Nielson.  I also offer my enduring gratitude to the faculty, staff and my fellow students at UBC-PCWM Group, who have inspired me to continue my work in the field of waste management. I thank my dear friends: Andrea Miskelly, Blair Fulton, Bonita Parsons, Colleen Chan, Daisy (Xi) Zhang, Eva Robertsson, Iqbal Bhuiyan, Isabel Londono, Kathy Bahadoorsingh, Mehrnoush Mohammadali, Parvez Fattah, Pattu Soubhagya, Saghi Kowsari, Sahar Kosari, Sepideh Jankhah, Zaki Abdullah, Wayn Lo, Wade xxiv  Archambault, and Winnie Chan. I also thank my colleagues at Sperling Hansen Associates, in particular Dr. Tony Sperling, for his understanding, support and patience.  I should also thank my incredible Kung-Fu folks in the morning training team, Sifu Daniel Pugh, Laurence Madera, Varun Saran, Lina Wang, and Mai Aoki. Healthy in mind and in body, and I owe you guys for this one. I owe particular thanks to Dr. Laurence Madera for proof reading my entire dissertation.   Last but definitely not least, I would like to thank my family: my siblings, especially my older brother Dr. Mohammadreza Abedini, who showed me the way to success more than 25 years ago. Thank you for being such a wonderful and supporting big brother, for having faith in me and encouraging me in every decision I made in my life. My mom, my mom, my mom; Words fail me to express my appreciation to my mother whose dedication, love and prayers have led me to this place. Thank you mom for sacrifices you made and for believing and supporting me in my choices.  The best outcome from the past few years of my studies, despite all the difficulties, is the even much stronger bond I made with my best friend, my soul-mate and my love, Hamideh. There are no words to convey how much I love her. She has been a true and great supporter and has unconditionally loved me, supported me, and pushed me when necessary. I truly thank you for being such a wonderful friend for me and our kids, and for continuously being so strong and taking loads off my shoulder. I should also thank Hamideh’s parents who let me take her hand in marriage and for their supports. My children, Daddy’s two angels, Danial and Dina whom with I have spent less time than I have on my research. I owe you two so many hours and weekends that I should have spent with you in the past few years. Daddy loves you so much and he promises to make it up to you.    Ali Reza Abedini  December, 2014 xxv  Dedication   To the loving memory of my father who made the ultimate sacrifice for his country. To my mother, who had the arduous task of raising me and my siblings all by herself. To my wife, who has supported me in all my endeavors. And To my son and daughter who make life fun and meaningful for daddy.     Danial and Dina’s Birthday, January 2014   1  Chapter  1: Introduction 1.1 Background Landfilling, as the most common solid wastes disposal option worldwide, has been practiced for more than 70 years (Vesilind P. Aarne et al., 2002). Compared to other disposal options, landfills are relatively cheap, easy to operate with minimal capital costs required. While there are many initiatives to minimize the landfilling of waste, especially organic waste, the author’s expectation is that landfills will remain the predominant waste disposal strategy in many solid waste management systems (SWMS). However, despite the many benefits of waste land disposal, this strategy poses significant environmental risks, including the production of landfill gas. Landfill gas (LFG) is a by-product of natural decomposition of organic materials in landfills that can create unsafe air quality, health issues, unpleasant odours, and contribute to global climate change. LFG predominantly consists of methane (CH4) and carbon dioxide (CO2), potent greenhouse gases (GHG). While CO2 produced in the waste sector (e.g. municipal landfills, wastewater treatment plants, and burning of non-fossil fuel waste) is not counted as a GHG as it is of biogenic origin, the emission of CH4 is of significant concern (IPCC, 2006).  Methane is a naturally occurring GHG with a global warming potential (GWP) 28 to 34 times greater than carbon dioxide over a 100-year timeframe (IPCC, 2013). The atmospheric concentration of methane has increased since 1750 due to human activities, such that in 2011, the concentration of this gas was 1,803 ppb, exceeding the pre-industrial levels by 150% (IPCC, 2013). Landfills are considered a major contributor, responsible for 3-7% of global methane emissions (Bogner and Matthews, 2003).  In Canada, about 3% of the 2010 national GHG emissions were reported to be from the waste sector. About 91% of these emissions were 2  attributed to be fugitive methane emissions from landfills (Environment Canada, 2012a). The Ministry of Environment (MOE) of the province of British Columbia (BC) also concluded that 6.6% of the 2010 GHG emissions in BC were sourced from the waste sector with the primary source being methane emissions from solid waste landfills (BC MOE, 2012). The provincial government of BC, like many other countries, has recently developed a new LFG regulation targeting more LFG recovery as a mitigation measure to achieve its provincial GHG reduction goals. The BC government, in support of the Greenhouse Gas Reductions Target Act1 (GGRTA), has committed to reduce its GHG emissions by at least 33% below 2007 emission levels by 2020 and achieve an 80% reduction by 2050.  There have been significant technological improvements in the LFG collection and utilization industry since the first full-scale project was implemented in Palos Verdes, California, USA. in 1975 (Spokas et al., 2006). However, an integrated approach to evaluate the production and the final fate of the generated methane is yet to be developed.  The intergovernmental panel on climate change (IPCC), the world’s foremost authority on climate change, issued 2007 and 2013 assessment reports (Fourth and Fifth Assessment Reports) concluding the climate is changing as a result of human activities and that it will worsen if no action is taken (Bogner et al., 2007; IPCC, 2013). With landfills being point sources of GHG emissions, it would be very easy to apply quantifiable mitigation measures (e.g. capturing LFG for energy recovery and/or the thermal or biological oxidation of methane) which can significantly change the concluded                                                  1 See: http://www.bclaws.ca/EPLibraries/bclaws_new/document/ID/freeside/00_07042_01 3  methane budget in the inventory reports. However, proper design and operation of such LFG recovery systems requires accurate information about the quantity, quality, and the mass balance of generated methane at the landfills. This information will also help regulatory entities enforce applicable regulations and fine-tune their GHG emission inventory reports.  There are several tools developed to predict gas generation in landfills which most commonly use first-order reaction kinetics and are based on the decay of the biodegradable materials. These models are generally developed for municipal solid waste (MSW) landfills and are heavily dependent on the availability of data on the type of landfill as well as the characteristics of the deposited waste. However, reliability and accuracy of these models have been questioned due to the discrepancy between the predicted values and actual data from the gas recovery systems (Vogt and Augenstein, 1997; Scharff and Jacobs, 2006). Vogt and Augenstein (1997) have suggested that these inaccuracies are mainly due to (i) the poor quality of data used for the development of these models, (ii) the limited time frames of available data used, (iii) the inappropriate application of available data, (iv) variable climatic conditions, and (v) variable landfill design and operation factors. Scharff and Jacobs (2006) conducted a comprehensive evaluation of six different gas generation models and showed that the minimum variation in the results in the best case scenario was between 20 - 125% while the estimation in the worst case scenario varied between 40 to 570%.  These investigations raise serious doubts about the accuracy of these models as well as the precision, and even the validity, of model-based emission statistics utilized by the national and international organizations.  4  1.2 Landfill Gas Concept Landfill gas (LFG) predominantly consists of methane and carbon dioxide and is a by-product of anaerobic decomposition of organic wastes deposited at the landfill. Depending on a number of factors, including waste composition and the age of the landfill, the percentage of each component of LFG varies. Typically municipal solid waste LFG consists of 45- 60% methane (CH4), 40 - 60% carbon dioxide (CO2), small amounts of nitrogen (N2), oxygen (O2), ammonia (NH3), hydrogen sulfide (H2S), hydrogen (H2), reduced sulfur compounds (RS), carbon monoxide (CO), and non-methane organic compounds (NMOCs) such as trichloroethylene, benzene, and vinyl chloride (Tchobanoglous et al., 1993).  Principal substrates which are ultimately decomposed to methane are cellulose, hemicellulose, proteins, and lipids. Higler and Barlaz (2001) reported that about 90% of the biodegradable portion of the municipal solid waste (MSW) in the United States (US) is comprised of cellulose and hemicellulose. There are different types of anaerobic bacteria involved in this conversion, which occurs though a complex series of reactions explained below as four sequencing phases.  1.2.1 Biodegradation Phases These phases are defined as aerobic, anoxic non-methanogenic, anaerobic unsteady methanogenic, and anaerobic steady methanogenic phases which are illustrated in Figure 1.1 (Farquhar and Rovers, 1973; ATSDR, 2001).  5  Aerobic phase (Phase I): Phase I starts with placement of waste in the landfill, resulting in the introduction of oxygen to the landfill body. In this phase, which lasts only a few days, oxygen is depleted via aerobic biodegradation and is gradually removed as CO2.  Figure 1.1 Landfill gas production phases (ATSDR, 2001) Anoxic, Nonmethanogenic phase (Phase II): In this phase, acid fermentation occurs, resulting in a significant rise in CO2 and H2 production. Full establishment of this phase takes about two weeks at the end of which, and in total absence of oxygen, methane-producing bacteria begin to establish themselves.  Anaerobic, unsteady Methanogenic phase (Phase III): Methanogenesis begins but, depending on the moisture content, it takes about 3-4 months to become established. LFG generation becomes significant in this phase and it takes a few years until this generation rate stabilizes (Edward A. McBean et al., 1995; ATSDR, 2001). 6   Anaerobic, steady Methanogenic phase (Phase IV): Constant composition of LFG, of which 40-70% by volume consists of methane (Edward A. McBean et al., 1995), can be observed during this phase. The duration of methane production depends on the percentage of slowly degradable organic matter (e.g., paper, wood, etc.) in the landfilled waste, but in general, the rate of gas production significantly decreases after about 30 years (Edward A. McBean et al., 1995).  Normally, the duration of each phase is variable and depends on factors such as the distribution of organic components in the landfill, availability of nutrients, moisture content of the waste, moisture routing through the waste materials, and the degree of the initial compaction (Tchobanoglous and Kreith, 2002).  1.2.2 Anaerobic Digestion Principles  In the presence of enough moisture and bacteria, the anaerobic decomposition of waste starts in the complete absence of oxygen. This anaerobic decomposition of organic materials leads to the generation of methane and can be described as a simple two stage process (EMCON Associates, 1980). In this process, complex organic materials such as cellulose, fats, carbohydrates, and proteins are hydrolyzed and fermented by acid forming bacteria into organic fatty acids such as propionic and acetic acids. Products of hydrolysis also include simple sugars, amino acids, and other low molecular weight organic compounds. In the second stage organic acids are consumed by methanogenic bacteria and converted to methane and carbon dioxide (EMCON Associates, 1980).   7  The amount of methane generated directly depends on the level of bacterial activity in the landfill. Therefore, by providing favorable conditions for bacterial fermentation, the methane generation rate can be optimized. These conditions include sufficient  moisture content, optimum temperatures (30-40˚ C for mesophilic and 50-55˚ C for thermophilic bacteria), sufficient nutrients (optimal C/N ratio of 16 (Farquhar and Rovers, 1973)), an absence of oxygen and toxic materials, pH of 6.7 - 7.2, alkalinity greater than 2000 mg/L as CaCO3, and organic acid concentration of less than 3000 mg/LCH3COOH (Schamucher, 1983). These landfill conditions provide the maximal production of methane gas.  1.2.2.1 Stoichiometric Estimate of Gas Production The following equation describes the general transformation of organic matter in the presence of appropriate bacteria in an anaerobic environment (Tchobanoglous and Kreith, 2002).    Equation 1.1  There are many references assuming a complete conversion of biodegradable matter where all the carbon content of the disposed waste is assumed to be converted to CO2 and CH4. This assumption results in the following stoichiometric equation to calculate the total amount of gas produced in landfills.      34228324                                                               83244324dNHCHdcbaCOdcbaOHdcbaNOHC dcba Equation 1.2 heatSHNHCHCO                                                       matter  organicresistant cells newnutrientsOH matter Organic234228   This approach has resulted in variable gas yields2 reported in a number of studies ranging from 170 – 453 m3 per tonne of wet waste, from which approximately 85 – 244 m3 is reported to be the quantity of methane (Schamucher, 1983).   As an example, the following calculations show the stoichiometric estimate for the gas production from waste at the Vancouver Landfill (VLF).  For the purpose of these calculations, the results of the MSW composition study conducted in 2009 by Technology Resource Inc. (TRI) in the Surrey Transfer Station were used (TRI, 2010). These values were adjusted for the wastes from demolition and land clearing (DLC), which were separately hauled to the VLF (See Table 2.3 in Page 42). Other information required to conduct this analysis included the moisture content of different waste components (See Table 2.8 in Page 51). Furthermore, dry percentages of the chemical elements (i.e. C, H, O, N, and S) contained in the                                                  2 Total amount of gases produced by unit weight of landfilled waste over the gas-generating lifespan of a landfill. Table 1.1 Composition of waste deposited at the Vancouver Landfill in 2009 Waste Components Waste Composition in 2009 (wet%) MSW MSW + DLC Paper and Paperboard 21.2 17.9% 17.9% Glass  1.7 1.4% 1.4% Ferrous Metals 3.2 2.7% 2.7% Non-ferrous Metals 0.8 0.7% 0.7% Plastics  12.3 10.4% 10.4% Organic Waste 26.6 22.5% 22.5% Yard and Garden Waste 3.3 2.8% 2.8% Wood and Wood Products 12.4 10.4% 21.4% DLC  - 15.6% - textiles  3.1 2.6% 2.6% Rubber  0.9 0.8% 0.8% Nappies  2.0 1.7% 1.7% Composite Products 4.0 3.4% 3.4% Hazardous Wastes 4.2 3.5% 3.5% Other  4.4 3.7% 8.4% Total 100.0 100.0% 100.0% MSW Deposited in 2009: 469,765 Tonnes  DLC Deposited in 2009: 86,760 Tonnes  Total Waste Deposited in 2009: 556,525 Tonnes  Assumed Wood Content in DLC: 70%     9  organic waste were calculated based on the typical ultimate analysis data presented in Table 2.6 (See page 46). Accordingly, the initial assessments showed that 47.5% of the waste deposited at the VLF in 2009 was dry organics and the proportion of chemical elements were 22.75%, 2.93%, 19.27%, 0.54%, and 0.10% for C, H, O, N, and S, respectively. These results, along with the determined chemical formula of the waste, are presented in Table 1.2.  Table 1.2 Chemical elements and formula of waste deposited in the VLF in 2009 Organic Waste Components Weight  in 100 kg Chemical Elements (dry weight in 100kg) Wet Dry C H O N S Ash Paper 17.9 14.3 6.21 0.86 6.28 0.04 0.03 0.86 Food Waste 22.5 11.2 5.39 0.72 4.22 0.29 0.04 0.56 Yard Waste 2.8 1.5 0.74 0.09 0.59 0.05 0.00 0.07 Wood Waste 21.4 17.5 8.67 1.05 7.48 0.04 0.02 0.26 Textile 2.6 2.2 1.23 0.15 0.70 0.10 0.00 0.06 Rubber 0.8 0.7 0.52 0.07 0.00 0.01 0.00 0.07 Total 67.8 47.5 22.75 2.93 19.27 0.54 0.10 1.87 Normalized (%) 47.94 6.18 40.60 1.13 0.21 3.95 Atomic Weight 12.00 1.00 16.00 14.00 32.10 NA Mole Ratio 4.00 6.18 2.54 0.08 0.01 NA Chemical Formula of Waste (N=1) NOHC 317649    Therefore, the stoichiometric equation for this particular waste composition is as follows: NOHC 317649 + 15.3 ∙ H2O  23.3 ∙ CO2 + 26.0 ∙ CH4 + 1 ∙ NH3   When the atomic weights of the elements are used, the following equation is seen:   (1183)      + (276)    (1026)   +     (416)      +    (17)  Therefore, methane generation potential for the wastes deposited at the VLF in 2009 is:  10   Mₒ = (416 / 1183) ∙ (47.5 / 100) = 0.1668 kg CH4/ kg wet waste Where: Mₒ is the methane yield (kg CH4/ kg wet waste), (416 / 1183) is the molecular weight ratio of CH4 to the deposited organics, and (47.5 / 100) represents the amount of dry organics (presents, or kg in 100 kg of wet waste)  Considering methane density in standard conditions (i.e. 15 °C and 1 atm) equals 0.678 kg/m3, then methane yield per tonne of waste equals:   Mₒ = 0.1668 / 0.678 ∙ 1000 = 246 m3 CH4 /tonne of waste  This value represents the maximum methane yield under favorable environmental conditions for bacterial activity. Comparison of the data achieved from the stoichiometric estimates with actual landfill gas measurements has absolutely proved the over-estimation of this methodology (Schamucher, 1983).   Bookter and Ham (1982) investigated the level of MSW stability in several municipal landfills across the U.S. and compared the findings with laboratory samples developed within 9 years. They observed a reduction of cellulose content, as well as a significant reduction in cellulose-to-lignin ratio over time, suggesting an overall trend of decomposition. They observed that the material decomposed more rapidly under optimum conditions; however, complete degradation was never achieved. They reported a low pH as a sign of slower degradation. Although the lab results did not show any correlation between moisture level and degradation, they concluded that landfills located in areas with more precipitation had higher level of biological degradation. This discrepancy may be due to the fact that in actual landfills the temperature in the deeper zones of 11  the landfill is positively regulated by bacterial metabolism, which is enhanced under optimum moisture levels. In contrast, the temperature of the lab samples was in equilibrium with ambient temperature and subject to unfavorable thermal conditions. During the course of the present study, as will be fully explained in Chapter 3, the actual temperature in the different zones and depths of the VLF was continuously monitored over different seasons and compared with fluctuations of the ambient temperature.  Eleazer et al. (1997) in a comprehensive study compared the theoretical methane yields with the actual methane generated from biodegradation of these materials under optimum conditions in the lab. They showed that the extent of decomposition in different materials varies from 28 to 94% with an average value of 58% decomposition for a typical MSW. Besides the levels of some refractory components in the waste (e.g. lignin), there are other factors resulting in inaccuracies with stoichiometric gas generation estimates.  These factors include (i) moisture limitation in some parts of the landfill due to the rate of compaction, landfill depth, presence of impermeable barriers, etc., (ii) existence of plastic bags resulting in inaccessibility of some organic fractions, and (iii) presence of chemical materials in the landfills which are toxic to the gas producing bacteria, thus slowing down the biodegradation process in some sections of the landfills.  In this thesis, the author attempted the use of these variables as reduction indexes (discount factors) for the total portion of the deposited carbon which ultimately forms methane in MSW landfills.  12  1.3 Landfill Gas Generation Modeling Quantitative and qualitative information about the generated gas at landfills are one the basic data required to design proper LFG recovery and utilization systems. The GHG emission regulatory authorities also need accurate information about the levels of emissions from landfills to evaluate the performance of the existing systems, establish and enforce regulations, and modify and fine-tune the existing policies and regulations. Physical measurements of emission levels from all landfills can be very costly and ineffective. Therefore, LFG generation models are often used to estimate the emissions from landfills. Using a model is particularly advantageous when the goal is to estimate the past and future LFG generation and/or emission. However, with many factors affecting methane generation at municipal landfills, it is very difficult to conduct an accurate LFG generation assessment. While there are many tools which simulate the gas generation process, a definitive and industry-accepted methodology is yet to be developed. Normally, the amount of disposed degradable waste is used as a basis in all existing methodologies, and using an empirical formula for the biodegradation of waste is one of the common ways that many researchers estimate methane generation rates from landfills (Barlaz et al., 1990; Peer et al., 1992; Bogner and Spokas, 1993; Oonk, 1994).   Landfill gas models were first developed to predict gas flow rates in the 1970’s when sanitary landfilling increased and LFG utilization, as an alternative source of energy, became more popular (Walsh, 1994). While the “rule of thumb” modeling was the main basis for estimations in the LFG industry, Farquhar and Rovers (1973) developed a quantitative approach to estimate the LFG generation followed by other quantitative approaches (Robert K. Ham et al., 1979; EMCON Associates, 1980) which were developed based on limited available empirical data 13  (Walsh, 1994). Some of the most well-known initial models include; (i) the direct decay model, (ii) the zero order decay model, and (iii) the simplified first order decay model (EMCON Associates, 1980; Peer et al., 1992; IPCC, 1996).  With increasing concerns about GHG emissions in mid 1990’s, second generation models were developed for GHG emission evaluation, regulation and control purposes. Most of the more recent LFG generation models commonly use first-order reaction kinetics, which best describe the anaerobic degradation of organic material (EMCON Associates, 1980; Hoeks, 1983; Oonk, 1994). This methodology is based on the decay of biodegradable materials and is generally developed for municipal solid waste (MSW) landfills. Unlike the direct decay and the zero-order models, the first-order methodology considered the impact of the age of waste on gas generation. Based on this model, the gas generation from each unit-mass of the deposited waste exponentially declines over time.  In the first order decay models, expression of gas generation is based on the following equation: tt kCdtdC  Equation 1.3 Where: t = time (year)  Ct = amount of decomposable carbon available at the landfill at time t  k = decomposition rate (year-1)  Integration of Equation 1.3 over time results: Ct = Cₒ e-kt  Equation 1.4 14  Where Cₒ is the amount of decomposable carbon available at the landfill at time t = 0  Therefore, total (cumulative) carbon decomposed (Cdec) until time t is: Cdec = Cₒ (1- e-kt) Equation 1.5  In this methodology, the total production of “carbon containing gas” (i.e. CO2 and CH4) is calculated based on the total carbon available for degradation at the landfill. This amount has its maximum value at the beginning, when the waste is placed in the landfill, and exponentially decreases over time. Assuming 50% (v/v) concentration of methane in the generated LFG, total methane generated due to the decomposition of the Cdec would be equal to:  Mt = Cₒ (1- e-kt) ∙ 0.5 ∙ 16/12  Equation 1.6 Where Mt is the cumulative methane generated until time t and 16/12 is the molecular weight ratio of methane to carbon.  LFG generation behavior predicted by the first order decay model has been successfully validated at landfills and through lab experiments. As such, this methodology is the basis for many current generation models used in Europe and North America, including the Netherlands Organization of Applied Scientific Research (TNO), the United States Environmental Protection Agency (US-EPA), the Intergovernmental Panel On Climate Change (IPCC), and the British Columbia Ministry of Environment (BC MOE) (Oonk and Boom, 1995; USEPA, 2005; IPCC, 2006; CRA, 2009).   15  There are two types of first order decay models commonly practiced: single-phase and multi-phase methodologies. The single-phase models consider all organic waste degrading at a single decay rate.  This type of LFG generation modeling is widely used and is the basis of the US-EPA LandGEM model and the Dutch TNO model. These models assume a delay period in gas production, during which no methane is initially produced. An important weak point about these models is unreliable gas production estimates due to long term variations in landfill conditions and the composition of waste deposited at landfills (Huitric and Soni, 1997).  The multi-phase first order decay models are based on the same principles but differ between different types of organic wastes. This yields a more sophisticated approach which results in more reliable generation predictions (Hoeks, 1983; Oonk, 1994). This methodology considers different decay rates for different types of organic materials based on their half-lives, which is the time in which half of the initial amounts of the decomposable organics are decayed. The multi-phase models are more flexible and provide more accurate estimates for the methane generation at MSW landfills. However, this methodology requires more information about the historical and future composition of the MSW stream. Oonk and Boom (1995) conducted a comprehensive gas generation modeling study involving full scale data collection from 12 different Dutch landfills over 3 years. They showed that the multi-phase methodology best matched the actual LFG generation rates followed by the single-phase first order and zero order methodologies.   The IPCC FOD model, the British GasSim model and the BC MOE Tool are based on the multi-phase model principles. For example, the GasSim model considers three different waste types, 16  each with different decomposition rates, which theoretically is a good assumption of the mechanism happening in a landfill. However, the practicality of this model is highly criticized due to a lack of detailed information at most of the landfills and difficulties to break down waste composition into minor categories with appropriate modeling parameters (Huitric and Soni, 1997).  Despite all the improvement in LFG generation modeling, better projections for future LFG generation are still required. As an example, the overall kinetic parameters must still be empirically adjusted so that the current modeling results match the actual gas flow rates (Spokas et al., 2006). Considering the recent considerations and changes in waste management and organic diversion strategies worldwide, the author believes that the multi-phase first order decay methodology will provide the best approximation for methane generation at MSW landfills. However, an integrated approach using site-specific modeling parameters must be defined and incorporated into the model.  In Section 1.4 an overview of five well known models is provided. For this purpose, and considering the location of the present research (i.e. the Vancouver Landfill), two of the most well-known North American models (known and used worldwide), the methodology adopted by the Environment Canada, as well as two of the recently developed models in BC, Canada were selected. These five models are: (i) The U.S. EPA LandGEM model (USEPA, 2005), (ii) The IPCC FOD model (IPCC, 2006) (iii) Environment Canada (Environment Canada, 2012a) 17  (iv) The inventory of BC GHG generation from landfills developed by the Golder Associates Ltd. (GA) for the BC Ministry of Environment (MOE) (Golder Associates Ltd., 2008a), and  (v) The LFG generation assessment tool “Tool” developed by Conestoga-Rovers & Associates (CRA) for the BC MOE (CRA, 2009).  1.4 Popular LFG Generation Models Overview In this section, a comprehensive overview is conducted on four different gas generation methodologies which are most applicable to the research work site. To provide a more in-depth comparison between the selected models, LFG generation from the Phase 1 section of the VLF was estimated using these models. This phase was selected for this practice as very good knowledge about the deposited waste tonnage and composition was available for this phase, the phase has been recently completed and capped according to high engineering standards, and a well-engineered and aggressive LFG collection system was installed and operated at this phase. In fact, based on the closure system and the active LFG collection system in place at this phase of the VLF, it was expected that this area of the landfill would have a methane capture efficiency of 90% to 95%, as reported for similar landfills (Spokas et al., 2006; SCS Engineers, 2009). The suggested collection efficiency values by Spokas et al. (2006) and SCS Engineers (2009) are used as the default values for guidelines by the French Environment Agency (ADEME), and the U.S. Solid Waste Industry for Climate Solutions (SWICS), respectively.  The information about the historical waste tonnages and composition deposited in this area of the landfill are provided in Table 2.3 and Table 2.7, respectively (See page 42 and page 49). The comparisons of the LFG 18  generation modeling results were conducted on the peak, current and total lifespan methane generation as well as the collection efficiency of the existing system in Phase 1 of the VLF. These results are summarized in Table 1.11 and illustrated in Figure 1.7.   1.4.1 U.S. EPA LandGEM The U.S. EPA landfill gas emission model (LandGEM) determines the mass of methane generated based on the methane generation capacity (Lₒ) and mass of waste deposited. LandGEM was developed by the U.S. EPA in 1991 based on the first order decay methodology with pre-defined modeling parameters for different climatic conditions (i.e. k and Lₒ) developed based on empirical data from U.S. landfills (Debra R. Reinhart et al., 2005). The last version of LandGEM, v3.02, was released in 2005 (USEPA, 2005). The major improvement in this version is that the model calculates the gas generation from the waste deposited in 1/10th of a year (as opposed to the annual tonnage). Equation 1.7 below describes the U.S. EPA LandGEM model v3.02:  ni jktioCHijeMkLQ111.0 104 Equation 1.7 Where: QCH4 = annual methane generation in the year of the calculation (m3 year-1) k = methane generation rate (year -1) Lo = potential methane generation capacity (m3 tonne-1) Mi = mass of waste accepted in the ith year (tonne)   19  There are two sets of modeling parameters proposed in LandGEM. (i) CAA default parameters, used when the modeling is to screen MSW landfills under the Clean Air Act (CAA) based on the maximum emissions, and (ii) AP-42 inventory default parameters, which are used to estimate emissions for inventory reports under the U.S. EPA’s Compilation of Air Pollutant Emission Factors (USEPA, 2005). In either set, both parameters are selected based on the annual precipitation with 635 mm as the separating line between arid and conventional area. The U.S. EPA LandGEM default modeling parameters are provided in Table 1.3 below.  Table 1.3 LandGEM default modeling parameters  k (year -1) Lₒ (m3 tonne-1) CAA Inventory CAA Inventory Conventional 0.05 0.04 170 100 Arid Area 0.02 0.02 170 100 Wet (Bioreactor) -- 0.70 -- 96  1.4.1.1 LFG Generation Modeling for VLF-Phase 1: LandGEM Based on the data provided to the U.S. EPA LandGEM model using the CAA and inventory conventional modeling parameters, the current (i.e. 2012) methane generation rate from Phase 1 of the VLF is approximately 16,700 and 8,500 tonnes per year, respectively. The peak methane generation was in 2007, for both sets of modeling parameters, at approximately 20,400 and 9,900 tonnes per year. LandGEM also estimated that this area will generate at least 300,000 tonnes of methane during its lifespan. When the CAA default parameters were used, this amount was as high as 515,000 tonnes. Methane generation rates from the Phase 1 of the VLF estimated by the U.S. EPA LandGEM model are illustrated in Figure 1.2. Full results of this modeling practice are provided in the Appendix A.1. 20   Figure 1.2 Methane generation rates at the VLF Phase 1– LandGEM v3.02  1.4.2 IPCC Model The intergovernmental panel on climate change (IPCC) has introduced the first order decay (FOD) model, developed by an international team of experts to estimate methane emissions from individual landfills and at the national level (IPCC, 2006). The IPCC FOD model is a multi-phase first order decay model which calculates methane generation from decomposition of each waste component separately based on the respective decay rates and degradable carbon content. This model includes default decay rates for four different climatic conditions including (i) dry temperate, (ii) wet temperate, (iii) dry tropical, and (iv) moist and wet tropical. The thresholds to classify these regions are mean annual temperature (MAT) of 20°C and mean annual precipitation of 1,000 mm. The IPCC default decay rates are based on the half-lives of waste  - 2,500 5,000 7,500 10,000 12,500 15,000 17,500 20,000 22,500199920052011201720232029203520412047205320592065207120772083208920952101210721132119212521312137Methane Generation Rate (tonnes/year)YearsCAAInventory200721  components under different environmental conditions. These default values for different climatic regions are presented in Table 1.4 below.   Table 1.4 IPCC default decay rates for different climatic regions Waste Components/ Types Decay Rates (k) (years-1) Dry Moist and Wet MAT<20°C MAT>20°C MAT<20°C MAT>20°C Food waste / Sewage sludge 0.05 - 0.08 0.07 - 0.10 0.10 - 0.20 0.17 - 0.70 Garden and park waste (non-food) 0.04 - 0.06 0.05 - 0.08 0.06 - 0.10 0.15 - 0.20 Paper and Textiles 0.03 - 0.05 0.04 - 0.06 0.05 - 0.07 0.06 - 0.085 Wood and straw 0.01 - 0.03 0.02 - 0.04 0.02 - 0.04 0.03 - 0.05 Bulk MSW or industrial waste  0.04 - 0.06 0.05 - 0.08 0.08 - 0.10 0.15 - 0.20  The IPCC model calculates methane yield based on the amount of degradable organic carbon (DOC) deposited into the landfill during its lifespan. DOC content, which is based on the composition of waste, can be calculated from the weighted average of the carbon content of various components of the waste stream. IPCC (2006) has suggested the default DOC values for the major types of waste presented in Table 1.5.   Table 1.5 IPCC default DOC content for different MSW components Waste Stream DOC content in % of wet waste Range Default A. Paper and Cardboard 36 – 45 40 B. Textiles* and Nappies 18 – 40 24 C. Food waste 8 – 20 15 D. Wood 39 – 46 43 E. Garden and park waste 18 – 22 20 F. Rubber and Leather** 39 39 G. Plastics, Metal, Glass and other inert materials 0 0  Bulk MSW Waste 12 - 28 15 * 40 percent of textiles are assumed to be synthetic ** Natural rubbers would likely not degrade under anaerobic condition at landfills, hence only half is incorporated  22  The IPCC model also considers a correction factor for methane generation depending on the operational practices at the landfill. The methane correction factor (MCF) is defined for five different categories as presented in Table 1.6 below. In the following section the first year of operations in Phase 1 of the VLF was assumed to fall under the fourth category (i.e. MCF = 0.5) and advancing to the first category in the following years. This assumption was made based on the dimensions of this phase, disposal rate, and waste density.   Table 1.6 IPCC model methane correction factors Landfill Operation Category MCF 1. Managed Anaerobic 1.0 2. Unmanaged Deep 0.8 3. Uncategorized 0.6 4. Managed Semi-Aerobic 0.5 5. Unmanaged Shallow 0.4  1.4.2.1 LFG Generation Modeling for VLF-Phase 1: IPCC Model Based on the assumptions made and the data provided to the IPCC model using the default modeling parameters for the Vancouver region, this model estimates that the  2012 methane generation rate from the Phase 1 of the VLF is in the order of 10,100 tonnes year-1. The peak methane generation was in 2007 at 14,000 tonnes year-1. The IPCC model also estimated that this area will generate about 315,000 tonnes of methane during its lifespan, which considering the total tonnage of waste in place, translates to a methane yield of about 104 m3 per tonne of waste. Methane generation rates from the Phase 1 of the VLF estimated by the IPCC model are illustrated in Figure 1.3 below. The related modeling input parameters, along with the full results are presented in the Appendix A.2. 23   Figure 1.3 Methane generation rates at the VLF Phase 1– IPCC Model  1.4.3 Environment Canada Environment Canada, in its inventory report for the National GHG sources and sinks between 1990 and 2010, reported that methane emission from landfills makes up about 91% of the overall emissions from the Waste Sector, which was reported at about 22 million tonnes CO2 equivalent (CO2-e) in 2010 (Environment Canada, 2012a).  Environment Canada’s LFG generation estimates are based on the first order reaction methodology using province-specific modeling parameters. The decay rates (k) are assumed to have a direct relation with landfill moisture content, which is a direct function of annual precipitation levels. Environment Canada evaluated each province based on the annual precipitation data from 1941 to 2007 and determined k values using a relationship that was developed by the Research Triangle Institute (RTI) in 2004 (Environment Canada, 2012a). The RTI-suggested k values are shown in Table 1.7.  These  - 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000199920052011201720232029203520412047205320592065207120772083208920952101210721132119212521312137Methane Generation Rate (tonnes/year)Years24  values show a linear relationship between decay rate and precipitation. With these data, Environment Canada has calculated provincial k values for landfills in each province based on the provincial precipitation data.  For the provinces of Alberta, British Columbia and Ontario, for example, decay rates of 0.012, 0.083 and 0.046 were selected, respectively.  Table 1.7 Decay rates corresponding precipitation suggested by RTI (Environment Canada, 2012a) Annual Precipitation (mm) Decay Rates (k) (Year -1) 0 - 500 0.02 500 to 1000 0.038 >1000 0.057 Provincial  Values (Examples) Alberta 0.012 British Columbia 0.083 Ontario 0.046  Environment Canada (2012a) defined methane generation potentials (Lₒ) for each province based on the waste composition reported for three distinct time periods (i.e. 1941-1975, 1976-1989, and 1990-2010). The values for Lₒ are then calculated based on the DOC content of each waste category, assuming a 50% methane concentration in the generated LFG and that 40% of the carbon content will ultimately be sequestered in the landfills. The suggested Lₒ values for landfills located in BC for the three time periods are respectively 161.8, 98.0, and 88 m3 methane per tonne of waste.  1.4.3.1 LFG Generation Modeling for VLF-Phase 1: Environment Canada  Since waste disposal in Phase 1 of the VLF was started post-1990, the modeling parameters applicable to this phase based on the Environment Canada method would be k = 0.083 year -1 (provincial value) and Lₒ = 88 m3 per tonne of waste. Applying these modeling parameters to the 25  first order decay model resulted the 2012 methane generation rate of 10,900 tonnes per year from this phase. Also the peak methane generation rate was in 2007 at 15,700 tonnes per year. This model also estimated that this area will generate about 267,500 tonnes of methane during its lifespan. Methane generation rates from the Phase 1 of the VLF, estimated by the Environment Canada methodology, are illustrated in the Figure 1.4 below.  Figure 1.4 Methane generation rates at the VLF Phase 1–  Environment Canada  1.4.4 Golder Model Golder Associates Ltd. (2008b) presented an inventory of GHG emissions from landfills in BC. In this report, Golder used the LandGEM v3.02 first order decay model and found it suitable for GHG generation estimate from landfills in BC. However, Golder developed an empirical formula based on data collected from 12 landfills to better estimate the modeling parameters (i.e. k and Lₒ) for landfills in BC. Based on this methodology, the modeling parameters were correlated  - 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000199920052011201720232029203520412047205320592065207120772083208920952101210721132119212521312137Methane Generation Rate (tonnes/year)Years26  with the average annual precipitation (mm) with an assumption that all 12 landfills had 75% methane collection efficiency. The following equations show the Golder methodology in selecting modeling parameters (Golder Associates Ltd., 2008b):  Lₒ (m3 methane per tonne of waste) = 0.031 x Precipitation (mm) + 100 Equation 1.8 k (year-1) = 0.00013 x Precipitation (mm) – 0.019 Equation 1.9  1.4.4.1 LFG Generation Modeling for VLF-Phase 1: Golder Method  The average annual precipitation value for the VLF was 1,199 mm, as reported by the Vancouver International Airport weather station (see Table 2.2 in Page 41). This value resulted in the modeling parameters of Lₒ = 137 (m3 methane per tonne of waste) and k = 0.137 (year-1) based on Equations 1.8 and 1.9, respectively. Applying these modeling parameters to LandGEM v3.02 resulted in methane generation rate of about 18,400 tonnes per year for 2012. Also, the peak methane generation rate was in 2007 at about 34,000 tonnes per year. This model also estimated that this area will generate about 416,000 tonnes of methane during its lifespan. Methane generation rates from the Phase 1 of the VLF estimated by Golder methodology are illustrated in Figure 1.5.  27   Figure 1.5 Methane generation rates at the VLF Phase 1– Golder Associates  1.4.5 BC MOE LFG Generation Assessment Tool Conestoga-Rovers & Associates, CRA (2009) prepared the Landfill Gas Generation Assessment Procedure Guidance Report for the British Columbia Ministry of Environment (BC MOE), in accordance with the requirements of MOE’s Landfill Gas Management Regulation that was approved and ordered on December 8, 2008. This was the latest regulatory requirement in BC which required landfills generating more than 1,000 tonnes of methane annually to install an active LFG collection system and a methane thermal destruction system; the MOE LFG Generation Assessment Tool (MOE Tool) was used to screen landfills in terms of their methane generation rates. CRA suggested that the first order decay model was adequate for estimating methane generation from landfills in BC and suggested that modeling parameters of Lₒ and k were correlated with waste composition and the climatic conditions, respectively.   - 5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000199920052011201720232029203520412047205320592065207120772083208920952101210721132119212521312137Methane Generation Rate (tonnes year-1)Years28   As outlined in the MOE guideline, landfilled wastes are grouped into three major decomposition categories of; (i) relatively inert, (ii) moderately decomposable, and (iii) decomposable waste. Where food waste and yard waste (including grass, leaves, plant chipping and trees) are defined as decomposable and the rest of biodegradable materials (e.g. paper, newsprint, cardboard, wood, textile) are classified as moderately decomposable wastes.  Different default values for Lₒ are assigned to each of these categories and the weighted average defines the overall methane generation potential for the landfill. The suggested Lₒ values in the MOE Tool are presented in Table 1.8.   Table 1.8 BC MOE tool methane generation potential values (CRA, 2009) Waste Category Methane Generation Potential, Lₒ (m3 methane per tonne of waste) Relatively Inert 20 Moderately Decomposable 120 Decomposable 160  MOE guidelines also defined default values for decay rates for each waste category and for different regional areas based on the reported annual precipitation (mm). These methane generation rates for each waste category and precipitation ranges are presented in Table 1.9.  The MOE Tool also considers a water addition factor, a value ranging between 0.9 – 1.1 which accounts for dryness of the landfill and whether or not storm water is directed to, or diverted from, the landfill.  29  Table 1.9 BC MOE tool default methane generation rates (CRA, 2009) Annual Precipitation Methane Generation Rate (k) Values Relatively Inert Moderately Decomposable Decomposable <250 mm 0.01 0.01 0.03 >250 to <500 mm 0.01 0.02 0.05 >500 to <1,000 mm 0.02 0.04 0.09 >1,000 to <2,000 mm 0.02 0.06 0.11 >2,000 to <3,000 mm 0.03 0.07 0.12 >3,000 mm 0.03 0.08 0.13  1.4.5.1 LFG Generation Modeling for VLF-Phase 1: BC MOE Tool  Based on the waste classifications, the deposited wastes at the Phase 1 of the VLF were divided into three waste categories as presented in Table 1.10. These values are the best estimates for the composition of the waste historically deposited at this phase and include DLC waste (see Table 2.7 in Page 49).  Table 1.10 Waste composition for VLF Phase 1 based on the MOE waste categories Year Relatively Inert Moderately Decomposable Decomposable 1999 25.6% 55.1% 19.2% 2000 26.1% 56.9% 17.0% 2001 30.9% 46.6% 22.5% 2002 30.8% 49.7% 19.5% 2003 30.9% 47.7% 21.5% 2004 32.0% 48.1% 19.9% 2005 32.0% 47.8% 20.2% 2006 32.1% 47.3% 20.6% 2007    2008 29.6% 48.3% 22.0%  Based on the assumptions made and the data provided to the BC MOE Tool using the default modeling parameters described above, this model estimated that the 2012 methane generation rate from the Phase 1 of the VLF was 11,200 tonnes year-1. The peak methane generation was in 30  2007 at about 15,800 tonnes year-1. The BC MOE model also estimated that this area will ultimately generate a total amount of 300,000 tonnes of methane, which translates to methane yield of about 99 m3 methane per tonne of waste based on the total tonnage of waste deposited at this area. Methane generation rates from the Phase 1 of the VLF estimated by the BC MOE Tool are illustrated in Figure 1.6. The related modeling input parameters, along with the full results, are presented in the Appendix A.3.  Figure 1.6 Methane generation rates at the VLF Phase 1– BC MOE Tool  1.4.6 Comparison of Different Modeling Results The LFG generation estimates obtained from the six different methodologies are illustrated in Figure 1.7. This comparison shows the significance and magnitude of the differences between the outcomes of these modeling exercises which vary with the age of the landfill and the time  - 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000199920052011201720232029203520412047205320592065207120772083208920952101210721132119212521312137Methane Generation Rate (tonnes year-1)Years31  that has elapsed since closure of the site. It should be noted that this exercise was conducted for the particular environmental conditions of the VLF, and that for a different site with different climatic conditions (i.e. a dryer site) the result may be completely different. Nevertheless, this comparison shows that depending on the methodology adopted to evaluate the LFG generation, collection and/or emission from a landfill (or in a different scale) different findings will result.   Figure 1.7 Different methodologies LFG generation modeling results_VLF Phase 1  For this particular example for the Phase 1 of the VLF, as shown in Table 1.11, the peak methane generation ranged between 10,000 to 34,000 tonnes per year. Maximum variation in the results of this evaluation occurred at the peak methane generation in 2007 and was approximately 340%, which is in agreement with pervious finding of a similar evaluation by Scharff and Jacobs (2006).  Since LFG collection systems are always designed to accommodate the maximum LFG generation expected from landfills, these uncertainties on the peak generation may result in  - 5,000 10,000 15,000 20,000 25,000 30,000 35,00019992003200720112015201920232027203120352039204320472051205520592063206720712075207920832087209120952099Methane Generation Rate (tonnes/year)YearsLandGEM CAALandGEM InventoryIPCC FODEnvironment CanadaGolder AssociateBC MOE Tool32  systems significantly oversized or undersized. Furthermore on the above example, while the methane capture efficiency at Phase 1 of the VLF was expected to be between 90% and 95% (Spokas et al., 2006; SCS Engineers, 2009), the resulting values in this analysis ranged between 37% and 73%. This shows that, depending on the methodology adopted to assess the LFG generation from this phase, there would be a different understanding about the LFG collection system performance and efficiency. A summary of modeling parameters and assumptions, along with the findings for the six methodologies discussed above, are presented in Table 1.11. Full results of these analyses are provided in Appendix A.  Table 1.11 Comparison of modeling parameters and results for different methodologies_VLF Phase 1 Methodologies CH4 Generation (tonnes year-1) Methane Yield, Lₒ (m3 tonne-1) Decay Rate, k (year -1) 2012 Collection Efficiency Current (2012) Peak (2007) Lifespan Total 1. LandGEM CAA 16,669 20,411  515,386  170 0.05 37% 2. Inventory 8,520 9,947  302,038  100 0.04 73% 3. IPCC 10,112 14,046  319,542  106 0.03-0.15 62% 4. Environment Canada 10,949 15,683  267,524  88 0.083 57% 5. Golder Associates 18,400 33,966  416,067  137 0.137 34% 6. BC MOE 11,198 15,783  300,360  99 0.02-0.11 56%  Assumptions:     Average 53%  Total waste tonnage:    4,470,903   tonnes Methane Density:     0.677 kg m-3 Average LFG Flow Rate in 2012:  1,239 scfm = 6,242 tonnes CH4 StDev. ±15%   1.5 Statement of the Problem Despite all the progress that has been made in LFG generation modeling, there are still many uncertainties involved which could be reduced by more comprehensive studies conducted based on empirical data and field work results. Models are used as tools and protocols to generate GHG emission data to be disclosed to the general public and regulators. However, the results of 33  different modeling exercises are inconsistent.  There is certainly a need for advanced, industry-accepted models offering more realistic and consistent results that could be used by the landfill owners, engineers, and national and international regulatory agencies. Whether the course of the evaluation takes place at smaller scales, such as evaluating the LFG collection efficiency in a landfill, or over larger scales, such as in national or international GHG emissions surveys, it is very important to have reliable and transparent data enabling us to make knowledgeable decisions. Such comprehensive studies shall not only look into improving modeling parameters provided based on the improved  quality of data that are now available with regard to waste generation, composition, diversion, etc., but also should consider using advanced technologies to better understand and quantify methane pathways including lateral migrations, atmospheric emissions, and surface oxidations occurring at landfills.  1.6 Objectives of the Study The main objective of this research was to develop an integrated approach to produce robust and defensible estimates for collection efficiency of existing LFG management systems and GHG emissions from municipal landfills.   The specific objective of this research was to improve the accuracy of the LFG generation estimation, incorporating fine-tuned modeling parameters which were developed based on a series of full scale field investigations. Furthermore, the approach involved verification and calibration of the results, supported with extensive field work and measurement conducted at the Vancouver Landfill (VLF). The field work consisted of four major sections including: (i) development of an LFG recovery system database as well as collection of operational data during 34  the course of the research, (ii) monitoring landfills behavior in time and with respect to changes in ambient conditions, (iii) measurement of fugitive methane emissions through an innovative approach, and (iv) quantification of the biological methane oxidation in landfill’s cover soil using the stable isotope technique. 35  Chapter  2: Materials and Methods 2.1 Metro Vancouver Metro Vancouver (MV), previously called Greater Vancouver Regional District (GVRD), is the largest regional district by population in the province of British Columbia (BC), Canada, with approximately 2.4 million residents (BC Stats, 2011). MV consists of twenty-two members and municipal cities, including Vancouver, Richmond, North Vancouver, Surrey, and Burnaby among others, with an average annual population growth rate of about 1.5%.   GVRD (2010) reported the generation of approximately 3.1 million tonnes of waste in 2010, which translates to an average per capita generation rate of roughly 3.6 kg day-1 or 1.3 tonnes year-1. There are seven transfer stations in the region which receive wastes, either collected by municipalities and private haulers or directly from residents and businesses. Except for segregated materials (i.e. recyclables and yard trimmings) all wastes are sent to one of the three waste disposal facilities approved by the district. These disposal facilities are the Burnaby Incinerator, the Vancouver Landfill, and the Cache Creek Landfill (GVRD, 2010).   The records show that there have been extensive improvements in recycling in MV during the past 10 to 15 years. The rate of waste recycling was 44% in 1999, which increased to 55% by 2007. Maximizing the recycling rate is one of the major goals defined in MV’s integrated waste management plan (GVRD, 2010). As shown in Table 2.1, the overall recycled waste per capita in this regional district is estimated to be 0.81 tonnes year-1 and the disposed waste per capita is 0.66 tonnes year-1. These values have been more or less constant since 2007 (GVRD, 2010).   36  Shown in Table 2.1 are the service population, per capita waste generated, recycled and disposed from 1998 through 2010, as well as estimated values for 2011. As shown in this table, and also illustrated in Figure 2.1, the overall recycling rate in MV has increased every year since 1998 to 2007 with an exception in 1999. This rate has remained more or less constant since 2007 and MV reported the same recycling rate of 55% for 2010 (GVRD, 2010). These overall recycling rates include the recycling of residential (both single-family and multi-family units), industrial, commercial and institutional (ICI), and demolition and land clearing (DLC) wastes, as well as materials recycled through “take-back” programs (industry-managed programs in which industries are fully responsible for management of goods throughout their life cycles).   Figure 2.1 Overall historical waste diversion rates at Metro Vancouver (GVRD, 2010).  40%45%50%55%60%19981999200020012002200320042005200620072008Waste Diversion Rate at MV (%)Years37   Table 2.1 Historical waste generation and disposal tonnages at Metro Vancouver Year Service populationa Annual Growth Rate Waste Generationa Recycleda Disposed tonnes Per Capita tonnes % Per Capita tonnes % Per Capita Waste to Energyb Landfilled & other % tonnes/year tonnes/year tonnes/year tonnes tonnes 1998 1,984,743   2,609,913 1.31 1,261,680 48% 0.64 1,348,233 52% 0.68 247,075 1,101,158 1999 2,013,201 1.43% 2,618,538 1.30 1,151,130 44% 0.57 1,467,408 56% 0.73 254,803 1,212,605 2000 2,041,399 1.40% 2,657,076 1.30 1,183,611 45% 0.58 1,473,465 55% 0.72 256,367 1,217,098 2001 2,073,662 1.58% 2,851,208 1.37 1,418,489 50% 0.68 1,432,719 50% 0.69 246,666 1,186,053 2002 2,102,244 1.38% 2,903,894 1.38 1,470,445 51% 0.70 1,443,449 50% 0.69 264,013 1,179,436 2003 2,128,965 1.27% 2,775,455 1.30 1,414,390 51% 0.66 1,361,065 49% 0.64 249,521 1,111,544 2004 2,153,998 1.18% 3,072,702 1.43 1,595,999 52% 0.74 1,476,703 48% 0.69 275,174 1,201,529 2005 2,188,573 1.61% 3,245,796 1.48 1,701,414 52% 0.78 1,544,382 48% 0.71 277,571 1,266,811 2006 2,218,026 1.35% 3,434,617 1.55 1,794,613 52% 0.81 1,640,004 48% 0.74 273,318 1,366,686 2007 2,251,887 1.53% 3,598,142 1.60 1,980,751 55% 0.88 1,617,391 45% 0.72 289,900 1,327,491 2008 2,273,095 0.94% 3,336,123 1.47 1,866,892 56% 0.82 1,499,231 45% 0.66 274,697 1,224,534 2009 2,314,163 1.49% 3,374,840 1.46 1,922,840 57% 0.83 1,452,001 43% 0.63 276,650 1,175,351 2010 2,351,496 1.61% 3,075,392 1.31 1,676,117 55% 0.71 1,399,275 45% 0.60 280,213 1,119,062 2011c 2,386,063 1.47% 3,501,921 1.47 1,927,782 55% 0.81 1,575,865 45% 0.66 280,000 1,295,865 a GVRD Annual Recycling and Solid Waste management Report, 2010 b Burnaby WTE Plant's Data          c Estimated Values 38  2.2 Vancouver Landfill Vancouver Landfill (VLF) is located in the south-west corner of Burns Bog, 16 km south of Vancouver, serving nearly 1 million residents of the greater Vancouver area. VLF is located on a 635 ha property with a landfilling footprint of about 225 ha. This facility has been receiving waste since 1967 and currently receives about 600,000 tonnes year-1 of MSW and DLC. Between 1967 and 2000, the VLF was developed to an elevation of 10 to 12 m above sea level (ASL). The entire landfill is divided into 7 operational areas/phases, each occupying approximately 20 to 40 hectare, measuring 800 m intervals north-south by about 200 to 500 m intervals east-west. These phases from west to east are; (i) Western 40, (ii) Phase 2, (iii) Phase 3, (iv) Area 2W, (v) Area 2E, (vi) Area 3, and (vii) Phase 1, each built separately to the originally designed level. A new plan was developed in 2000 to vertically expand the entire landfill to a maximum height of 39 m (Figure 2.2). Based on the new plan, the landfill is estimated to reach its full capacity in 2040 (SHA, 2000b). Figure 2.2 below shows the location of the Vancouver Landfill in Metro Vancouver as well as the operational phases with approximate footprint areas.  2.2.1 Gas Collection System at the VLF The active landfill gas (LFG) management system in the VLF has been operating since 1991. The system includes horizontal and vertical collectors, lateral pipes, header and sub-headers, condensate management system, LFG extraction facility, and flare. The original system covered approximately 84 hectares of the site and included 190 vertical collection wells, however, the system has been continuously expanded and the numbers of vertical wells, blowers, and flares have increased overtime. Currently there are 330 vertical LFG wells and 30 horizontal collectors actively collecting more than 6,700 m3 hr-1 LFG.  39  The initial goals for the City of Vancouver (COV) were the installation of the LFG management system to reduce landfill gas emissions and associated odor nuisance, as well as to conduct energy recovery from the LFG. However, the new BCMOE LFG regulation requires that the VLF actively collect and thermally oxidize at least 75% of the generated methane.   Figure 2.2 Metro Vancouver and location of Vancouver Landfill and its operational phases  North Vancouver  Vancouver  Burnaby  Coquitlam  Maple Ridge  Surrey  Langley  Delta  Richmond  VLF   Phase 3  Western 40  Area 2E  Area 3  Phase 1 Phase 2  Area 2W  Port Moody  West Vancouver  WTE Facility  1990-1993  1994-1995  1996-1998  1999-2008  40  2.2.2 Development of GCS Database  A large amount of historical LFG collection system data were generated by the COV over more than 20 years of operation of the LFG system. These data were collected using handheld gas analyzer devices or at the central control system at the location of the flare system. The data were stored in different formats for different reporting purposes mainly as separate Microsoft (MS) excel spreadsheets. Because there was no easy way to compile and utilize the historical data, a database in MS Access environment was developed as a part of this study, allowing a more comprehensive and meaningful mining of the existing data. Furthermore, a LANDTEC GEM2000+ LFG analyzer was used during the course of the field works to collect gas data from various locations in the collection system including LFG wellheads and manifold. These data were also added to the new LFG database. Outputs of the database provided the recovery data (R) for the METRO equation as fully presented in Chapter 6.  2.2.3 Climatic Conditions The City of Vancouver experiences cool rainy winters and relatively warm dry summers. The monthly mean temperatures of the area between 1971 and 2000, as reported by the Vancouver International Airport weather station, ranged from a low of 3.3 oC in January to a high of 17.6 oC in August. The mean annual temperature for the same time period was 10.1 oC. Most precipitation in Vancouver Landfill falls in the form of rain. In general, the VLF has experienced at least one significant snowfall every year. The average annual precipitation in the area between 1971 and 2000 was reported to be 1,199 mm.  Presented in Table 2.2 are the climate statistics for the Vancouver area between 1971 and 2000.  41  Table 2.2 Climate Normals 1971-2000 for the Vancouver international airport weather station  Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec. Year TEMPERATURE (°C) Daily Average  3.3 4.8 6.6 9.2 12.5 15.2 17.5 17.6 14.6 10.1 6.0 3.5 10.1 Standard Deviation 1.9 1.5 1.1 1.0 1.0 0.9 0.9 1.0 1.0 0.8 1.7 1.7 0.7 Daily Maximum 6.1 8.0 10.1 13.1 16.5 19.2 21.7 21.9 18.7 13.5 9.0 6.2 13.7 Daily Minimum  0.5 1.5 3.1 5.3 8.4 11.2 13.2 13.4 10.5 6.6 3.1 0.8 6.5 PRECIPITATION  Rainfall (mm) 139.1 113.8 111.8 83.5 67.9 54.8 39.6 39.1 53.5 112.5 178.5 160.6 1,154.7 Snowfall (cm) 16.6 9.6 2.6 0.4 0.0 0.0 0.0 0.0 0.0 0.1 2.5 16.3 48.2 Precipitation (mm) 153.6 123.1 114.3 84.0 67.9 54.8 39.6 39.1 53.5 112.6 181.0 175.7 1,199  Also, a hydrogeological review by Sperling Hansen Associates Inc. (SHA) in 2008 showed that the evapotranspiration over the VLF footprint was about 416 mm, or 35% of the average precipitation in the landfill (SHA, 2008).   2.2.4 Historical Waste Tonnage at the VLF Waste disposal at the VLF started in the Western 40 in 1967, at a rate of about 140,000 tonnes year-1. Disposal progressed towards the eastern phases as the elevation of the active phase reached the original design level limit of 12 m. With the implementation of the new vertical expansion plan, waste filling in Phase 1 of the landfill continued until it reached the new permitted height of 39 m, after which waste filling continued in Phases 2 and 3 of the landfill. Table 2.3 below shows the tonnages of MSW and DLC historically deposited in each phase of the VLF.     42  Table 2.3 Historical waste disposal rates at different phases of the Vancouver Landfill  MSW DLC Total (Tonnes) (Tonnes) (Tonnes) (Tonnes) (Tonnes) (Tonnes) (Tonnes)1967 136,365      0 136,365 A 136,3651968 169,210      0 169,210 A 169,2101969 199,284      0 199,284 A 199,2841970 196,577      0 196,577 A 196,5771971 206,830      0 206,830 A 206,8301972 193,733      0 193,733 A 193,7331973 217,968      0 217,968 A 217,9681974 223,083      0 223,083 A 223,0831975 219,638      0 219,638 A 219,6381976 215,728      0 215,728 A 215,7281977 196,532      0 196,532 A 196,5321978 187,941      0 187,941 A 187,9411979 185,907      0 185,907 A 185,9071980 213,792      0 213,792 A 213,7921981 199,934      0 199,934 A 199,9341982 259,006      0 259,006 A 259,0061983 328,796      0 328,796 A 328,7961984 511,006      0 511,006 A 511,0061985 588,400      0 588,400 A 588,4001986 678,509      0 678,509 A 678,5091987 762,919      0 762,919 A 762,9191988 591,773      0 591,773 A 591,7731989 467,329      0 467,329 A 467,3291990 468,883      0 468,883 A 468,8831991 464,881      0 464,881 A 464,8811992 453,028      0 453,028 A 453,0281993 461,700      162,000 623,700 B 623,7001994 436,800      0 436,800 B 436,8001995 429,700      79,700 509,400 B 509,4001996 401,810      102,300 504,110 B 504,110  1997 361,600      48,450 410,050 B 410,050  1998 350,569      101,559 452,128 B 452,128  1999 371,005      112,567 483,572 B 483,5722000 308,773      147,893 456,666 B 456,6662001 383,784      70,597 454,381 C 454,3812002 388,560      142,215 530,775 C 530,7752003 446,034      107,918 553,951 C 553,9512004 483,875      139,145 623,019 D 623,0192005 545,696      146,151 691,847 D 691,8472006 621,437      150,602 772,039 D 257,346 514,6922007 515,043      124,709 639,752 E 639,7522008 512,174      145,042 657,216 E 495,216 162,0002009 469,765      86,760 556,526 E 445,221 111,3052010 571,952      84,090 656,042 E 656,0422011 577,362      84,090 661,452 E 661,452Total 17,174,690 2,035,786 19,210,476 2,962,522 3,524,742 3,929,329 2,010,492 946,200 1,366,288 4,470,903Phase 1* Waste Composition Study conducted by GVRD in 1991, 1998, 2001, 2004, and 2007. Results are adjusted for DLC waste deposited at the Vancouver Landfill.Western 40YearWaste TonnageWaste Composition Used*Waste Disposal History (MSW + DLC)Phase 2 Phase 3 Area 2W Area 2E Area 343  2.2.5 Research Boundary at the VLF In order to conduct the field investigations planned for this study, four phases (areas) of the VLF were selected as the study boundary (work site). The waste filling activities were planned to be conducted at Phase 2 and Phase 3 of the VLF during the course of this research (2009 – 2014). Therefore, Area 2W, Area 2E, Area 3, and Phase 1 were selected as the study boundary. These areas were completed in 1993, 1995, 1998, and 2008, respectively. These areas have clear footprints, each with a distinct gas collection system with dedicated LFG manifolds and gas quality and quantity metering stations. Therefore, each of these four areas were treated as an individual site equipped with active LFG collection systems, as well as, with known waste in place tonnage, age, and composition (see Table 2-3).   2.3 Burnaby Waste-to-Energy Facility (WTEF) The Burnaby Waste-to-Energy Facility (WTEF) is located in the commercial/ industrial zone of south Burnaby. The plant has been operating since 1988 and currently receives approximately 280,000 tonnes year-1 of MSW from Burnaby, New Westminster, West Vancouver, the City of North Vancouver, and the District of North Vancouver. Since the service area covered by this plant represents the full range of housing types and social-economic neighborhoods, MV has chosen this location to conduct several waste composition analyses on a regular basis and the results are believed to accurately represent the waste generated in the MV regional district.  2.4 Municipal Solid Waste Composition and Characteristics Metro Vancouver has conducted several waste composition studies since 1991. These physical analyses are performed in different locations but mainly at the Burnaby WTEF, where the 44  sampled wastes are representative of the MSW characteristics in the region and the wastes deposited at the VLF. Results of these MSW physical analyses are summarized in Table 2.4.  Table 2.4 Historical and estimated MSW composition in Metro Vancouver (1991 - 2009) Waste Components Waste Composition (wet %)a A B C D E F 1991 1998 2001 2004 2007 2009 Paper and Paperboard 37.77 32.13 15.34 22.24 27.12 21.15 Glass 1.95 3.09 2.46 1.75 1.97 1.66 Ferrous Metals 3.49 2.57 6.51 1.82 3.23 3.20 Non-ferrous Metals 0.91 0.77 0.51 1.33 0.53 0.83 Plastics 9.19 13.98 10.46 11.76 14.83 12.32 Organic Waste 6.05 18.69 15.62 20.62 23.75 25.72 Yard and Garden Waste 14.12 5.49 10.12 4.10 3.62 3.33 Wood and Wood Products 8.19 7.38 12.05 8.46 8.10 12.37 textiles 6.42 7.61 8.15 8.25 4.10 3.08 Rubber 0.09 0.98 4.61 1.06 0.80 0.91 Nappies 1.57 2.51 2.12 1.83 2.09 2.03 Animal Litter 0.29 0.91 0.93 0.88 0.90 0.88 Composite Products 1.14 0.69 1.14 4.63 1.05 3.97 Hazardous Wastes 0.49 2.13 0.41 1.89 1.20 4.18 Other 8.33 1.07 9.57 9.38 6.71 4.37 Total 100.00 100.00 100.00 100.00 100.00 100.00 a Data acquired directly from the Engineering & Construction Department of MV’s head office.  2.4.1 Heating Value of MSW One of the initial aims of this research was to utilize a modified version of a methodology used by Fellner et al. (2007) to separately determine the energy produced in a WTEF from incineration of the biogenic and fossil portions of MSW. Our goal was to apply this method and, using the historical plant’s operational data, determine the biogenic portion of wastes historically incinerated at the Burnaby WTEF. However, due to some limitations, including lack of sufficient CO2 readings at the plant’s stacks, this method did not result in reasonable and defendable numbers.   45  However, the investigation produced valuable knowledge regarding the effect of historical changes in the waste management strategies in MV on the net heating value (NHV) of MSW in this regional district.  The calculations were conducted using five different, widely-used formulae where heating value of MSW is derived through ultimate analysis of waste. These methods are: (i) Boie formula used by Kathiravale (2003), and Mason and Gandhi (1983), (ii) Dulong formula (Mason and Gandhi, 1983; Tchobanoglous et al., 1993; Tian et al., 2001; Kathiravale et al., 2003), (iii) Mendeliev formula (Magrinho and Semiao, 2008), (iv) Scheurer – Kestner formula (Tian et al., 2001; Kathiravale et al., 2003; Magrinho and Semiao, 2008), and (v) Steuer formula (Tian et al., 2001; Kathiravale et al., 2003).  Some of these formulae directly calculate the NHV (also called lower heating value (LHV)) of waste while others give the higher heating value (HHV) of waste. Different available formulae are also expressed in different units of heating values, such as MJ kg-1, kcal kg-1, or Btu lb-1. In order to be able to compare values resulted from different formulae, the author used the suggested methodology by Finet (1987) where the heat of vaporization of water is deducted and HHV is translated to NHV (or LHV). This formula is presented below as Equation 2.1. For similar purposes, we also converted all values to the common unit of kJ kg-1. (Note: 1 cal = 4.1868 Joules and 1 Btu lb-1 = 2.326014 kJ kg-1).  LHV(kj kg-1) = HHV (1 - W) - 2,440 (W + 9H)   Equation 2.1 Where: W is the moisture content of MSW and H is the hydrogen content of MSW (% wet basis).   Table 2.5 shows the five formulae used to calculate the heating value of waste in the 46  MV. In this table, W is the moisture content of solid waste and C, H, O, N, and S are, respectively, the weight percentages of carbon, hydrogen, oxygen, nitrogen, and sulphur on a dry or wet basis as indicated in the second last column of the table. These values were calculated through the ultimate analysis of waste components based on the typical amounts of these elements in each organic component of waste reported by Alter (1974), Tchobanoglous (1993), and Kaiser (1966).  Table 2.5 Selected formulae for calculating heating value of MSW Name Value Unit Formula Note Equation Boie HHV Btu lb-1 151.2C + 499.77H + 45S - 47.7O + 27N dry basis 2.2 Dulong LHV Btu lb-1 145C + 610(H-O/8) +40S + 10N wet basis 2.3 Mendeliev LHV kcal kg-1 81C +300H - 26(O-S) - 6(9H+W) wet basis 2.4 Scheurer - Kestner HHV kcal kg-1 81(C-3O/4) + 342.5H + 22.5S + 57 x 3O/4 - 6(9H+W) dry basis 2.5 Steuer HHV kcal kg-1 81(C-3O/8) + 345(H-O/16) + 25S + 57 x 3O/8 - 6(9H+W) dry basis 2.6 1 Btu lb-1 = 2.326014 kJ kg-1  Table 2.6 Typical ultimate analysis data for combustible components of MSW3 Combustibles Percent by Weight (dry basis) C H O N S Ash Food wastes 48.0 6.4 37.6 2.6 0.4 5.0 Paper 43.5 6.0 44.0 0.3 0.2 6.0 Cardboard 44.0 5.9 44.6 0.3 0.2 5.0 Plastics 60.0 7.2 22.8 - - 10.0 Textiles 55.0 6.6 31.2 4.6 0.2 2.5 Rubber 78.0 10.0 - 2.0 - 10.0 Yard wastes 47.8 6.0 38.0 3.4 0.3 4.5 Wood 49.5 6.0 42.7 0.2 0.1 1.5                                                   3 (Tchobanoglous et al., 1993) (Kaiser, 1966) (Tchobanoglous et al., 1993) (Kaiser, 1966) 47  Investigations on the historical waste composition data, previously presented in Table 2.4, showed a 4% reduction in NHV of waste within 10 years (1998 – 2007). A comparison between these theoretical results and the actual Burnaby WTEF operational data showed a very close agreement between the actual plant’s data and the predictions that resulted from the Dulong methodology. Furthermore, these analyses showed that wet percentages of C, H, O, N, S, and ash in combustible MSW in 2010 were 30.92, 6.65, 43.59, 0.63, 0.11, and 3.74, respectively. The total amount of wet combustible waste excluding ash and inert (glass, metals, etc.) in 100 kg of MSW received at WTEF in 2010 was 81.90 kg. Accordingly, the chemical formula of wet combustible MSW in MV for 2010 was C748 H1,163 O449 N13 S.   Also, as shown in Figure 2.3, as a result of the historical waste diversion programs in the regional district, the mass of biogenic waste (mB) in the waste stream has fluctuated between 40% and 50%. Currently, this level is higher than 45%. The overall wet weight moisture content of the waste deposited at the MV’s disposal facilities was found to be between 22-24% (w/w). 48   Figure 2.3 Normalized components of MSW in Metro Vancouver  2.4.2 Composition of Wastes Deposited at the VLF Since 1993, approximately one-third of DLC wastes generated in the MV were separately hauled to the VLF (Table 2.3). Therefore, the MSW composition reported in Table 2.4 was adjusted for the DLC wastes received at the VLF each year assuming that 70% of the DLC received at this site is wood waste.  Presented in Table 2.7 are the average wet weight percentages of major waste components deposited at the VLF. 0.000.100.200.300.400.500.601991 1998 2001 2004 2007 2009Normalized Mass of MSW ComponentsYearsmB (Mass of Biogenic Waste) mF (Mass of Fossil Waste)mI (Mass of Inert) mW (Mass of Water)49  Table 2.7 Composition of the waste deposited at the Vancouver Landfill (w/w%) Study Year Organic waste Garden waste Paper &Rubber Wood Textile Nappies Plastics & other inert % % % % % % % Waste Composition "A"* 1967 19.6 5.5 32.1 7.4 8.6 2.5 24.3 1968 19.6 5.5 32.1 7.4 8.6 2.5 24.3 1969 19.6 5.5 32.1 7.4 8.6 2.5 24.3 1970 19.6 5.5 32.1 7.4 8.6 2.5 24.3 1971 19.6 5.5 32.1 7.4 8.6 2.5 24.3 1972 19.6 5.5 32.1 7.4 8.6 2.5 24.3 1973 19.6 5.5 32.1 7.4 8.6 2.5 24.3 1974 19.6 5.5 32.1 7.4 8.6 2.5 24.3 1975 19.6 5.5 32.1 7.4 8.6 2.5 24.3 1976 19.6 5.5 32.1 7.4 8.6 2.5 24.3 1977 19.6 5.5 32.1 7.4 8.6 2.5 24.3 1978 19.6 5.5 32.1 7.4 8.6 2.5 24.3 1979 19.6 5.5 32.1 7.4 8.6 2.5 24.3 1980 19.6 5.5 32.1 7.4 8.6 2.5 24.3 1981 19.6 5.5 32.1 7.4 8.6 2.5 24.3 1982 19.6 5.5 32.1 7.4 8.6 2.5 24.3 1983 19.6 5.5 32.1 7.4 8.6 2.5 24.3 1984 19.6 5.5 32.1 7.4 8.6 2.5 24.3 1985 19.6 5.5 32.1 7.4 8.6 2.5 24.3 1986 19.6 5.5 32.1 7.4 8.6 2.5 24.3 1987 19.6 5.5 32.1 7.4 8.6 2.5 24.3 1988 19.6 5.5 32.1 7.4 8.6 2.5 24.3 1989 19.6 5.5 32.1 7.4 8.6 2.5 24.3 1990 19.6 5.5 32.1 7.4 8.6 2.5 24.3 1991 19.6 5.5 32.1 7.4 8.6 2.5 24.3 1992 19.6 5.5 32.1 7.4 8.6 2.5 24.3 1993 14.5 4.1 23.8 23.6 6.4 1.9 25.8 1994 19.6 5.5 32.1 7.4 8.6 2.5 24.3 1995 16.5 4.6 27.1 17.2 7.2 2.1 25.2 1996 15.6 4.4 25.6 20.1 6.8 2.0 25.5 1997 17.3 4.8 28.3 14.8 7.6 2.2 25.0 B 1998 15.2 4.3 24.9 21.4 6.7 1.9 25.6 1999 15.0 4.2 24.7 22.0 6.6 1.9 25.6 2000 13.3 3.7 21.7 27.7 5.8 1.7 26.1 C 2001 14.0 8.5 13.0 21.1 10.8 1.8 30.9 2002 12.1 7.4 11.2 27.6 9.3 1.6 30.8 2003 13.3 8.1 12.4 23.3 10.3 1.7 30.9 D 2004 16.7 3.2 17.3 22.2 7.2 1.4 32.0 2005 17.0 3.2 17.5 21.5 7.3 1.4 32.0 2006 17.3 3.3 17.9 20.5 7.5 1.5 32.1 E 2007 19.8 2.9 21.8 20.2 3.9 1.7 29.6 2008 19.2 2.8 21.1 21.8 3.8 1.6 29.6 F 2009 22.5 2.8 17.9 21.4 3.4 1.7 30.4 2010 23.2 2.9 18.4 19.8 3.5 1.8 30.5 2011 23.2 2.9 18.5 19.7 3.5 1.8 30.5 * Waste composition A through F as shown in Table 2.4 Highlighted rows indicate years in which a MSW characterization study was conducted. Other years’ data are calculated based on the tonnages of MSW and DLC waste deposited at the VLF in each year.  50  2.4.3 Moisture Content of Municipal Solid Waste Unfortunately, among the physical analyses conducted by MV from 1998 through 2007, the moisture content of waste was not measured. However, in 2009 Technology Resource Inc. (TRI) conducted a study in the region (Surrey Transfer Station) whereby the moisture content of each waste component was analyzed and reported (TRI, 2010). Results of these analyses (shown in Table 2.8), although not conducted at the location of interest, are believed to be fairly close to that at the Burnaby incinerator.  Furthermore, these results were compared with two other available datasets which are also shown in Table 2.8. These studies were completed by (i) Bird and Hale (1978), where similar analyses were conducted on different waste components after collection and transportation of waste, and (ii) Tchobanoglous (1993), who reported moisture contents of these components at the source, before mixed collection and transportation of waste was carried out.  In general, consumption behavior, MSW collection and transportation systems, as well as climate condition are the major parameters affecting moisture content of waste. While the overall moisture content of the collected waste tends to remain more or less constant, water may move from waste components with higher moisture content to other materials with lower moisture, like papers and textiles. With the available information about the collection and transportation system in the region, along with the results of the fairly recently conducted study by TRI (2010), it was concluded that the data presented in the last column of Table 2.8 are good approximations for the moisture content of wastes deposited at the VLF. However, it should be acknowledged that in reality, more source separation and recycling of materials with lower initial moisture content and high water absorption capacity (e.g. paper and cardboard) results in less water loss of materials 51  with higher moisture content (e.g. food waste). For simplicity, it was assumed throughout this research that different waste components in different years would have constant moisture contents.  Table 2.8 Moisture content of different components of MSW Waste Components Moisture Content (% wet basis) at Source* Bird & Hale 1978 TRI 2010 This Study Food waste 70 58.78 48 50 Paper 7 15 23 20 Cardboard 7 15 26 20 Plastic 2 15.48 -  10 Textile 4 13.41 14 14 Rubber 4 13.41 14 14 Yard Waste 50 45.12 50 45 Wood 15 15.01 18 18 DLC** 2 4 - 5 * (Tchobanoglous et al., 1993) ** Separately hauled (not mixed with MSW during storage and transportation)  2.5 METRO Equation Bogner and Spokas (1993) reported that the fate of a landfill’s methane would include: (i) methane fugitive emission to the atmosphere through landfill cover soil, (ii) methane oxidation by methanotrophic bacteria naturally existing in landfill cover soil, and (iii) methane capture and combustion via active LFG collection and treatment systems.   In the present study, all possible pathways for the generated methane were considered in the context of an integrated methane mass balance investigation in order to conduct a comprehensive evaluation on the fate of the generated methane at the selected work site (i.e. the Vancouver 52  Landfill). The following “METRO equation” was introduced, representing this comprehensive landfill methane mass balance investigation.   G = M + E + T + R + O Equation 2.7 Where:  G = Generated Methane  M = Migrated Methane (i.e. lateral migration)  E = Emitted Methane (i.e. atmospheric emissions) T = Trapped Methane  R = Recovered Methane  O = Oxidized Methane   The METRO equation considers all possible pathways for the methane generated within a landfill. However, in the particular case of the VLF, the amount of trapped methane (T) was considered insignificant and therefore was excluded from the equation. SHA (2000a), assessed the potential offsite lateral migration of LFG from the Vancouver Landfill to nearby properties and concluded that LFG migration (M) at this site is effectively blocked by the site’s perimeter double ditch system (leachate and run-off ditches). Figure 2.4 shows   Figure 2.4 Double ditch system at VLF site  53  the double ditch system at VLF which extends around the entire site.   Therefore a “simplified METRO” equation, as presented below, was used in this study to investigate the generated methane mass balance. This is also suggested by number of recent studies, including Bogner et al. (2007).  G = E + R + O Equation 2.8  Based on the simplified equation, the total carbon placed in the Vancouver Landfill, if not sequestered, is ultimately either collected or emitted to the atmosphere as methane and carbon dioxide. During the course of this study, different sets of field work, measurements, calculations, and analyses were conducted between 2009 and 2013 in order to improve the estimation and/or measurement of each of these mechanisms.   The estimation of generated methane (G) utilized the widely accepted first order decay reaction. However, selection of modeling parameters was based on a series of advanced analytical methods supported by practical full scale field investigations described in Chapter 3. Methodologies to calculate variable methane generation potentials were developed in that chapter, reflecting the historical changes in waste consumption, recycling, and disposal strategies. The new modeling results were then calibrated by completing the right side of the simplified METRO equation through a comprehensive and integrated series of field investigations as described in Chapters 4, 5, and 6. These surveys were conducted at four different phases of the VLF site. These phases/areas, which form the study boundary within the 54  work site, are: Area 2W, Area 2E, Area 3, and Phase 1 of the Vancouver Landfill.  These areas are separate filling phases/cells, which were previously shown in Figure 2.2.   Chapter 4 presents the results of the methane emission measurements (E) using a modified flux chamber technique paired with a full scale landfill surface methane concentration scan. Also, for the first time, methodologies were developed to translate qualitative methane emission data to quantitative methane flux. Chapter 5 presents the outcomes of the methane oxidation study (O) conducted using the stable isotope technique and a flux chamber. Furthermore, numerous field readings were taken from the existing LFG collection system over each area of the VLF. An LFG collection system database was also developed during the course of this study, which facilitated use of the old recovery information along with the newly collected data. A summary of the developed data base and the recovery data (R) are presented in Chapter 6.    55  Chapter  3: Advanced Landfill Gas Generation Modeling  3.1 Introduction In this chapter methodologies to provide better LFG generation estimates are presented. The first order decay reaction, which is generally accepted to best describe the decomposition of the biodegradable materials in landfills, was used as the modeling basis in this study (EMCON Associates, 1980; Hoeks, 1983; Oonk, 1994; Oonk and Boom, 1995; USEPA, 2005; IPCC, 2006; CRA, 2009). However, the method of assigning values to the modeling parameters, which is in fact what differentiates various modeling methodologies, was based on a series of full-scale field investigations and the results from fundamental research studies and investigations carried out by others world-wide. Methodologies to define the values of methane generation potential (Methane Yield) and methane generation rate (Decay Rate) are discussed below. Variable methane yield, reflecting the historical changes in the waste stream, and fine-tuned decay rates, representing a landfill’s actual environmental and operational conditions, allowed for a more accurate estimation of the LFG generation rates. A new integrated model (iModel-110©) was developed in the Microsoft excel environment in various (i) data input, (ii) analyses, and (iii) results output spread sheets with user friendly interfaces (See Appendix B).   This chapter includes methodologies to develop G, representing the left side of the simplified METRO equation (Equation 2.8). Generation estimates were then verified based on the field data, the parameter values on the right side of the equation (i.e. E, O, and R). The E, O, and R values were determined based on a comprehensive series of field studies conducted between 2009 to 2012 from four different filling areas of the Vancouver Landfill (VLF) as described in Chapters 4, 5, and 6, respectively.  Furthermore, the new model was calibrated based on these 56  field data, using two different methodologies presented in Chapter 7; (i) by application of a generation calibration factor (CFG) to fit the generation estimates for the year of study to the field data, and (ii) by fine-tuning the decay rates values within the suggested ranges and based on a sensitivity analysis presented in Chapter 8.    3.2 Methane Yield (Lₒ, m3 tonne-1) In accurate modeling practices, the estimation of Lₒ is derived from the degradable organic carbon (DOC) deposited into the landfill. However, a portion of the deposited DOC will be sequestered indefinitely and only a portion will be accessible to biochemical degradation and ultimately dissimilated. The ultimate level of organic waste biodegradation and gas generation at landfills depends on various factors. Many researchers have concluded that the most important of these factors are pH, moisture, and temperature (Ham et al., 1993; Edward A. McBean et al., 1995; Eleazer et al., 1997; Ivanova et al., 2008). Methane generation is reported to be inhibited at pH levels as low as 5.5 and when alkalinity is lower than 1500 mg/l as CaCO3 (Farquhar and Rovers, 1973). While methane generation occurs at MSW landfills with pH levels between 6.5 and 8 (EMCON Associates, 1980), the maximum methane production is reported to occur within the optimum pH range of 6.7 to 7.5 (Edward A. McBean et al., 1995).   Theoretical calculations presented in Section 1.2.2.1 showed that the maximum methane yield under favorable conditions for the typical MSW deposited at the VLF in 2009 was about 246 m3 per tonne of waste. Being located in a relatively wet environment, with a mean annual precipitation of about 1,200 mm/year, and historical pH levels of approximately 6.7 to 7.3 (SHA, 2008), it appears that the decomposition of waste at the VLF occurs under near optimal 57  conditions. Nevertheless, the Lₒ values suggested by different methodologies presented in Section 1.4 ranged from 88 to 170 m3 of methane per tonne of waste (See Table 1.11). These values are only about 35% to 70% of the maximum theoretical yield and are based on the percentage of the total DOC ultimately degraded within the landfill. Moreover, as discussed during the overview of different methodologies presented in Section 1.4, most of the models (with the exception of IPCC and BC MOE models) consider a fixed value for Lₒ throughout the landfill’s lifespan, ignoring many variables that can affect the organic carbon balance within the waste stream, such as Metro Vancouver’s aggressive waste diversion programs illustrated in Figure 2.1 in Page 36.  As part of this study, the author attempted to incorporate various index factors based on existing findings and data in the literature to calculate a more reliable methane yield based on these parameters. Among the existing models, the IPCC FOD model has the most detailed and accurate approach for defining the methane yield value. As described in Section 1.4.2, this methodology calculates methane yield based on the amount the DOC deposited in the landfill during its lifespan. The DOC value for each year is calculated based on the composition of waste and the weighted average of the carbon content of various components of the waste stream reported by Bingemer and Crutzen (1987) (See Table 1.5).  Bingemer and Crutzen (1987), in order to estimate the worldwide generation of methane from municipal waste, selected the average DOC content values for each type of waste material based on the existing information reported by Mantell (1975), Bowerman et al. (1977), and Suess (1985). The IPCC model uses wet weight percentages of carbon content values for each component. While the moisture content of any particular waste component “at source” can be assumed to be somewhat constant in any 58  place in the world, this value can vary depending on waste composition, climatic conditions, storage, collection, and transportation methods, as well as the location where the waste physical analyses have taken place.  In the present study, a similar approach to IPCC methodology was used to calculate methane yield based on DOC. However, the dry weight percentages of the carbon content for each material was used along with the dry weight of each component deposited each year, which was calculated based on the moisture content previously presented in Table 2.8. Dry base DOC content for different waste components are presented in Table 3.1.   Table 3.1 Dry base DOC content for different MSW components Waste Components DOC content in % of dry waste Range4 Default A. Paper and Cardboard 40 – 50 44 B. Textiles and Nappies 25 – 50 305 C. Food waste 20 – 50 38 D. Wood 46 – 54 50 E. Garden and park waste 45 – 55 49 F. Rubber and Leather 47 47 G. Plastics, Metal, Glass and other inert materials 0 0  Bulk MSW Waste (deposited at VLF)6 21 – 24                                                   4 These ranges and defaults are based on the (IPCC, 2006) suggested based on the maximum and minimum values in consultation of  (Jager and Blok, 1993; Gangdonggu Go"mi, 1997; Dehoust et al., 2002; Zeschmar-Lahl, 2002; Guendehou, 2004). 5 It is assumed that only 60% of the textile is degradable. 6 Calculated based on the waste composition from 1967 to 2011 presented in Table 2.7 and the waste moisture content presented in Table 2.8. 59  The total DOC content of the bulk MSW would depend on the composition of the waste deposited at the landfill and can be calculated for each year using the equation below: DOCMSW= 0.44(A) + 0.30(B) + 0.38(C) + 0.50(D) + 0.49(E) + 0.47(F)  Equation 3.1 Where A, B, C, D, E, and F are the dry percentages of paper, textile, food waste, wood, yard waste and rubber in MSW, respectively.  Of the total DOC deposited in a landfill, a portion will be inaccessible. The remainder will be available DOC (DOCa) which will be biodegraded to form LFG under optimum conditions. DOCa is a function of DOC multiplied by correction factors selected based on the author’s knowledge of landfill geometry and operations, as well as from the available studies, therefore:  DOCa  =  DOC × fdg × fcl × fdp × fst Equation 3.2 Where DOCa is the available DOC for methane generation through the landfill’s lifespan and fdg, fcl, fdp, fst are the degradability, climate, depth and storage discount factors, respectively. These discount factors are equal to, or less than 1.0 and are explained in the following sections.  3.2.1 Degradability Factor (fdg) Studies have shown various numbers for ultimate degradability of organic material under optimum conditions and the ultimate methane with respect to the DOC content of MSW (Ham et al., 1993; Akin et al., 1995; IPCC, 1996; Eleazer et al., 1997; Chugh et al., 1999; Ivanova et al., 2008; Wang et al., 2011). The IPCC (1996) in the GHG emission inventory guideline initially suggested 67% overall degradation and that 33% of the deposited carbon would be sequestered in the landfill, however, the revised guideline in 2006 acknowledged the overestimation resulting 60  from that assumption and suggested the revised value of 50% ultimate decomposition (IPCC, 2006). The IPCC FOD model applies the same default number to all waste categories regardless of the waste type and degradability, filling conditions, landfill design, etc. However, in order to improve the accuracy of methane generation estimates in the present study, different sequestration and/or degradability factors are applied to each type of waste.   The degradability of different waste components has been examined in a number of studies, showing its dependency on lignin content. These studies have shown that the average extent of degradability for main waste components can vary between 20 and 90% (Ham et al., 1993; Eleazer et al., 1997; Ivanova et al., 2008; Wang et al., 2011). Baldwin et al. (1998) was one of the first studies which reported the extent of decomposition of different waste components in MSW landfill at full scale, along with baseline data for samples. They also reported a correlation between lignin content and the rate of degradation for different types of materials. However, lignin content has not always been a good indication of the degree to which lignin inhibits the bioavailability of cellulose. A good example is a comparison between the degradability of grass and woody branches with approximately similar lignin content. The lignin in the grass does not inhibit the degradability as much as it does in branches (Akin et al., 1995; Eleazer et al., 1997).   Eleazer et al. (1997), in a comprehensive study, compared the theoretical methane yields based on the cellulose and hemicellulose contents of different waste components with the actual methane generated from biodegradation of these materials under optimum lab conditions. They showed that the extent of decomposition of different materials varied from 28% to 94%, with an 61  average of 58%, for the overall MSW. This study was later used as the basis for several other studies. Table 3.2 below shows more detail about the results of the study by Eleazer et al. (1997).  Table 3.2 Optimum degradability extents for different materials reported by Eleazer et al. (1997)  Waste Components Methane Yield (Lₒ) Cellulose Hemi-Cellulose Lignin Decomposition Extent (m3/tonne dry) (%) (%) (%) (%) 1 Grass 144.4 ± 15.5 26.5 10.2 28.4 94.3 2 Leaves 30.6 ± 8.6 15.3 10.5 43.8 28.3 3 Branch 62.6 ± 13.3 35.4 18.4 32.6 27.8 4 Food 300.7 ± 10.6 55.4 7.2 11.4 84.1 5 Coated Paper 84.4 ± 8.1 42.3 9.4 15.0 39.2 6 Old Newsprint 74.3 ± 6.8 48.5 9.0 23.9 31.1 7 Old Corrugated Containers 152.3 ± 6.7 57.3 9.9 20.8 54.4 8 Office Paper 217.3 ± 15.0 87.4 8.4 2.3 54.6 9 MSW 92.0 ± 4.1 28.8 9.0 23.1 58.4  As shown in Table 3.2 above, Eleazer et al. (1997) reported methane yields of about 30 to 300 m3 tonne -1 for different waste components with an overall methane generation potential of 92 m3 per tonne of dry MSW.  Chugh et al. (1999) conducted a similar study using shredded waste (with an average particle size of 10 cm) under enhanced biodegradation conditions in batch reactors and concluded 70 – 75% overall degradability for the MSW. Their findings showed approximately 20 to 30% higher overall degradability of MSW in comparison with Eleazer et al. (1997). Staley and Barlaz (2009) used the original findings by Eleazer et al. (1997)  and corrected the decomposition extent (or sequestration percentages) excluding fossil-derived materials from the calculations. They reported the methane yield for different waste components from 11 separate statewide studies conducted in different states of the USA and reported an average methane yield of 78 m3 per tonne of dry waste, which translates to 64 m3 methane per 62  tonne of wet waste. Based on the composition of waste in different states of the USA, they concluded that about 42% of the methane generated in the US landfills was from paper and cardboard, followed by 19% from food waste, with the remainder originating from yard waste, wood waste, and other organics.  Wood waste contributes a major part of the DOC deposited at landfills (Wang et al., 2011). As previously shown, about 12% of the MSW generated in MV is wood waste and this amount increases to about 20% when the amount of DLC deposited at VLF is included (See Table 2.4 and Table 2.7, respectively).  Ximenes et al. (2008) compared the actual decomposition rate of up to 46 year old wood waste mined from MSW landfills with data acquired from wood waste decomposition simulations in the laboratory. Wood waste samples, which were reported to have a moisture content between 42% to 68%, were evaluated for their carbon, cellulose, hemicellulose and lignin concentrations. They concluded that their ultimate decomposition rate of less than 20% for wood waste was significantly less than the 50% default value for wood degradability used in the IPCC model. Wang et al. (2011) also conducted a comprehensive laboratory scale study on the biodegradation of different types of wood and reported carbon conversion rates between 0% and 19.9%.   In the present study, degradability factors for different waste types are selected mainly based on the decomposition extents originally reported by Eleazer et al. (1997) and the improved values reported from more recent studies by Ximenes et al. (2008), Staley and Barlaz (2009), and Wang et al. (2011).  Table 3.3 below presents the selected values of the degradability factors used in this study.  63    Table 3.3 Degradability factor for different waste components      There are other studies showing an enhancement of biodegradation through the reduction of waste particle size. However, shredding of waste is more applicable to composting processes and not normally performed before land disposal. Therefore, a correction factor for particle size was not considered in the present study. Nevertheless, there are many other factors in the real-world environment that cause the actual DOCa for methane generation at landfills be less than what is calculated by applying the DOC and fdg values. Many researchers have concluded that the most important of these factors are pH, moisture, and temperature (Farquhar and Rovers, 1973; Ham et al., 1993; Eleazer et al., 1997; Ivanova et al., 2008). In the following section, some of these factors are further explained and correction factors are assigned wherever possible.                                                  7 Derived based on (Eleazer et al., 1997; Chugh et al., 1999) 8 Weighted average based on relative contribution of office paper, Newsprint, corrugated cardboard and other mixed papers reported by Metro Vancouver from 1991 to 2009 (Abedini et al., 2012). 9 Derived in conclusion from (Kollmann and Cote, 1968; Ximenes et al., 2008; Staley and Barlaz, 2009; Wang et al., 2011). 10 Weighted average based on relative contribution of grass, leaves, and brush reported by Oshins and Block (2000) and relative carbon sequestration factors reported by Staley and Barlaz (2009).  Waste Components Degradability Factor (fdg) (%) 1. Food Waste7 84% 2. Paper 8 46% 3. Wood9 20% 4. Yard Waste10 66% 5. Other Organics 50% 64   3.2.2 Climate Factor (fcl) Among many other factors affecting the bioavailability of DOC for methane production, a landfill’s water content plays a major role (Farquhar and Rovers, 1973; Ham et al., 1993; Barlaz et al., 1997; Ivanova et al., 2008). Moisture affects the availability of nutrients and bacteria for biological degradation. Therefore, a lack of moisture in the landfill may completely inhibit the biodegradation process. Many studies reported that the minimum water content required for biodegradation is between 15% and 50% dry basis (Barlaz et al., 1990; Baldwin et al., 1998; Pommier et al., 2007). However, Hartz and Ham (1983) studied MSW samples acquired from landfills under controlled moisture content and reported that methane production occurred at 10% moisture content (wet basis).   The large discrepancy between the findings of different studies on minimum moisture required for biodegradation may be due to the fact that different materials with different particle sizes and degradability were analyzed. There is also a wide range for the typical MSW moisture content. Depending on the composition of the MSW, the moisture content of waste “as generated” is historically reported to be  between 25% and 65% (Pommier et al., 2007). Pommier et al. (2007) also concluded that the moisture content of a landfill not only affects the degradation rate but also greatly impacts the bioavailability of the degradable organics within the landfill, hence an effect on methane yield.  Among the models reviewed in Chapter 1, the LandGEM and Golder models consider different methane yields for different climatic zones. Golder Associates Ltd. (2008b) developed a 65  relationship between methane yield and precipitation based on published data and their empirical experience from various projects in BC.  While sufficient data do not exist in the literature to define a clear and robust relationship between bioavailability of DOC and landfill moisture content, annual precipitation of more than 1,000 mm appears to be a good threshold that is repeatedly used to distinguish wet environments from dryer zones (CRA, 2004; IPCC, 2006; Environment Canada, 2012b).    Food waste, yard waste, paper, and wood are the major contributors to methane generation in landfills.  The water contents of food and yard wastes are near their water holding capacities (Pommier et al., 2007), Therefore, unless the landfill is located in a wet environment with high levels of precipitation, hydrolysis and decomposition of other deposited organics may be limited. As previously calculated and shown in Figure 2.3 in Page 48, the overall moisture content of the generated waste in MV is approximately 22 to 25%. Nevertheless, due to the high precipitation level in this area, the VLF would be considered to be a wet landfill and exempted from the application of a reduction factor for climate (i.e. fcl). However, based on author’s experience and limited findings in the literature, it is suggested as a best practice approach to include the following fcl values appreciating the effect of landfills moisture content on bioavailability of organic material for decomposition to form LFG.   Based on the suggested values, the 1,000 mm threshold is considered as an optimum annual precipitation level. This precipitation level is reportedly considered to provide optimum condition for decomposition of the organics in landfills, hence discount factors are suggested for precipitation levels below this threshold.   66   Table 3.4 Suggested climate factors for different precipitation levels Annual Precipitation (mm) Climate Factor (fcl) 0 - 500  0.5 – 0.7 500 to 1,000  0.7 - 0.9 >1,000  1  3.2.3 Depth Factor (fdp) The depth of a landfill plays a major role in providing suitable conditions for anaerobic degradation of DOC placed into the landfill.  Shallow landfills have more extensive oxygen infiltration into the waste mass, resulting in aerobic degradation and reduced methane generation (Vogt and Augenstein, 1997).  Also, in cold climates, unless the landfill is capped with an impermeable layer (e.g. geomembrane cap), shallower sections of landfills are subject to low temperatures, which may not be optimal for bacterial activity.  In such landfills, the increased depth results in a relatively higher percentage of waste mass undergoing optimum conditions for anaerobic degradation and methane generation. On the other hand, when the depth of the landfill exceeds certain levels, increased pressure due to compaction results in limited mobility of nutrients and reduced bioavailability of DOC, and methane generation (Hoeks, 1983). Based on the author’s experience and available literature, landfill depth within the range of 8 m to 30 m is considered optimum for methane generation (Hoeks, 1983; Vogt and Augenstein, 1997; Howard Robinson, 2010).   Therefore, for landfills located in temperate climates, with MAT < 20 °C (e.g. all landfills in BC), the following values for depth factor are suggested. Any shallow landfill (< 8 m depth) is suggested to be assigned an fdp of 0.80. For landfills exceeding that depth an fdp of 0.90 is 67  recommended to account for the top layers. Based on this terminology, there should be a smaller discount factor for much deeper landfills (> 30 m depth) as there will be much less waste mass affected by the ambient temperature relative to the unaffected zone. However, as reported by Hoeks (1983), in very deep zones of MSW landfills less methane fermentation occurs due to the increased compaction. Therefore, a constant fdp of 0.9 (i.e. discount factor of 10%) for landfills located in cold climates would conveniently account for both, (i) the top portion affected by low ambient temperatures and (ii) the pressurized bottom portion of the landfill. Obviously, the discount factor for deep landfills would apply to landfills located in any climatic condition. Table 3.5 shows the suggested depth factors assigned to landfills located in different climatic zones.  Table 3.5 Suggested depth factors for different climatic conditions Depth of Landfill (m) Depth Factor (fdp) MAT < 20°C MAT > 20°C < 8 0.80 1 8 to 30 0.90 1 > 30 0.90 0.90  3.2.4 Other Factors There are many other parameters which could be incorporated in fine-tuning a more accurate methane yield for LFG generation estimates. However, this requires more information to interpret suitable correction factors. Compaction rate is one of these parameters. However, calculation of the actual compaction rate (or waste density at landfills) is difficult. Available information about airspace consumption and waste-to-cover ratio may allow for a theoretical calculation of the compaction ratio, however, factors like the landfill’s settlement, which itself 68  depends on factors such as landfill depth, waste composition, and waste type, makes it a rather complex process to predict the actual value across an entire landfill.   Deposition of toxic materials at landfills is another important factor that affects gas generation. In general, especially in wet MSW landfills, it is good practice to ensure that the naturally existing optimum conditions for methane generation are not interrupted. While the pH of MSW landfills varies by age of the landfill, it normally stabilizes within the range of 6.6 to 7.5 (Tchobanoglous et al., 1993). Maximum methane production occurs within the optimum pH range of 6.7 to 7.5 (Edward A. McBean et al., 1995). Therefore, any drift from this range can be a good indicator that the optimum conditions are interrupted and methane generation assessment should be adjusted accordingly.   Another less important factor that has an effect on the sequestration of DOC at MSW landfills is the waste storage methods practiced at the generation stage (i.e. households). While food wastes are known to be readily degradable with a half-life of about 1 year (Robert K. Ham et al., 1979; Vesilind P. Aarne et al., 2002), it has always been uncertain what percentage of these materials are isolated within plastic bags used to store the material at the generation stage. Most of the food wastes sourced from commercial and industrial zones as well as from the multi-family residential zones are stored in plastic bags before waste collection occur. That includes approximately 50% to 75% of the food waste generated in a typical municipality such as Vancouver. Depending on type of collection system as well as the disposal and compaction of the waste during disposal, most of these wastes are mixed and ‘exposed’. However, the authors visual observations from various MSW landfills have shown that about 20% of the generated food wastes remain isolated in plastic bags. This value may be much lower and closer to zero in 69  developing countries and where scavenging activities occur at MSW landfills. Nevertheless, as shown in the next section, it is suggested that a storage factor of fst = 0.80 be assigned to the calculation of DOCa for the food waste component of the MSW, unless any sort of waste shredder is used at the disposal site.  3.2.5 Calculated Values for Methane Yield (Lₒ, m3 tonne-1) The DOC placed in a landfill will partly sequestrate and the rest will ultimately leave the landfill in the form of CH4 and CO2 and in leachate in early stages.  (Note: the amount of carbon leaving the landfill in form of leachate is insignificant in comparison with the carbon released as LFG, hence ignored). For each landfill, the parameters discussed above define the ultimate amount of CH4 generated as a result of deposition of each substance (i.e. methane yield). Table 3.6 summarizes these parameters for this study’s work site (i.e. the Vancouver Landfill) as well as the methane yield calculated for each waste component based on Equation 3.3 below.    Lₒ (m3 CH4 / tonne waste) = ½ × DOCa × 16/12 ÷ 0.000678 Equation 3.3 Where:  “½” applies the assumption of 50% CH4 concentration in the generated LFG,  “DOCa” is the available DOC for ultimate CH4 generation during landfill’s lifespan (tonnes), calculated based on waste tonnage, composition, moisture content and DOCdry  “16/12” applies the ratio of molecular weights of CH4 and DOC, and  “0.000678” is the density of CH4 (tonne/m3) under standard conditions11.                                                   11 Methane has the density of 0.677577 kg/m3 at temperature of 15°C and pressure of 1 atm (standard condition). 70   Table 3.6 Methane yield for different type of organic wastes deposited at the Vancouver Landfill Waste Components DOCdry12 Degradability Factor  (fdg) Climate Factor  (fcl) Depth Factor (fdp) Storage Factor  (fst) Methane Yield (Lₒ) m3/tonne Food Waste 0.38 0.84 1.0 0.9 0.8 113 Paper Waste 0.44 0.46 1.0 0.9 1.0 143 Wood Waste 0.50 0.20 1.0 0.9 1.0 73 Yard Waste 0.49 0.66 1.0 0.9 1.0 157 Other Organics 0.30 0.50 1.0 0.9 1.0 114 2009 MSW (e.g.) 0.2213     76.7  Based on the composition of the waste historically deposited at the Vancouver Landfill (presented in Table 2.7) and Equation 3.3 above, the following methane generation yields presented in Table 3.7 are assigned to each year’s activity of this site. Variations in Lₒ values reflect the changes in waste generation and recycling activities historically practiced in Metro Vancouver.                                                      12 See Table 3.1 13 Calculated based on Equation 3.1 and reported waste composition in Table 2.7 and waste moisture content in Table 2.8. 71  Table 3.7 Calculated variable Lₒ values for advanced LFG generation assessment at VLF Year Organic waste Garden waste Paper &Rubber Wood Textile Nappies DOCdry DOCa Lₒ % % % % % % % % m3 tonne-1 1967 19.6% 5.5% 32.1% 7.4% 8.6% 2.5% 22.4% 9.6% 94.9 1968 19.6% 5.5% 32.1% 7.4% 8.6% 2.5% 22.4% 9.6% 94.9 1969 19.6% 5.5% 32.1% 7.4% 8.6% 2.5% 22.4% 9.6% 94.9 1970 19.6% 5.5% 32.1% 7.4% 8.6% 2.5% 22.4% 9.6% 94.9 1971 19.6% 5.5% 32.1% 7.4% 8.6% 2.5% 22.4% 9.6% 94.9 1972 19.6% 5.5% 32.1% 7.4% 8.6% 2.5% 22.4% 9.6% 94.9 1973 19.6% 5.5% 32.1% 7.4% 8.6% 2.5% 22.4% 9.6% 94.9 1974 19.6% 5.5% 32.1% 7.4% 8.6% 2.5% 22.4% 9.6% 94.9 1975 19.6% 5.5% 32.1% 7.4% 8.6% 2.5% 22.4% 9.6% 94.9 1976 19.6% 5.5% 32.1% 7.4% 8.6% 2.5% 22.4% 9.6% 94.9 1977 19.6% 5.5% 32.1% 7.4% 8.6% 2.5% 22.4% 9.6% 94.9 1978 19.6% 5.5% 32.1% 7.4% 8.6% 2.5% 22.4% 9.6% 94.9 1979 19.6% 5.5% 32.1% 7.4% 8.6% 2.5% 22.4% 9.6% 94.9 1980 19.6% 5.5% 32.1% 7.4% 8.6% 2.5% 22.4% 9.6% 94.9 1981 19.6% 5.5% 32.1% 7.4% 8.6% 2.5% 22.4% 9.6% 94.9 1982 19.6% 5.5% 32.1% 7.4% 8.6% 2.5% 22.4% 9.6% 94.9 1983 19.6% 5.5% 32.1% 7.4% 8.6% 2.5% 22.4% 9.6% 94.9 1984 19.6% 5.5% 32.1% 7.4% 8.6% 2.5% 22.4% 9.6% 94.9 1985 19.6% 5.5% 32.1% 7.4% 8.6% 2.5% 22.4% 9.6% 94.9 1986 19.6% 5.5% 32.1% 7.4% 8.6% 2.5% 22.4% 9.6% 94.9 1987 19.6% 5.5% 32.1% 7.4% 8.6% 2.5% 22.4% 9.6% 94.9 1988 19.6% 5.5% 32.1% 7.4% 8.6% 2.5% 22.4% 9.6% 94.9 1989 19.6% 5.5% 32.1% 7.4% 8.6% 2.5% 22.4% 9.6% 94.9 1990 19.6% 5.5% 32.1% 7.4% 8.6% 2.5% 22.4% 9.6% 94.9 1991 19.6% 5.5% 32.1% 7.4% 8.6% 2.5% 22.4% 9.6% 94.9 1992 19.6% 5.5% 32.1% 7.4% 8.6% 2.5% 22.4% 9.6% 94.9 1993 14.5% 4.1% 23.8% 23.6% 6.4% 1.9% 24.0% 8.5% 83.4 1994 19.6% 5.5% 32.1% 7.4% 8.6% 2.5% 22.4% 9.6% 94.9 1995 16.5% 4.6% 27.1% 17.2% 7.2% 2.1% 23.4% 8.9% 88.0 1996 15.6% 4.4% 25.6% 20.1% 6.8% 2.0% 23.7% 8.7% 85.9 1997 17.3% 4.8% 28.3% 14.8% 7.6% 2.2% 23.1% 9.1% 89.6 1998 15.2% 4.3% 24.9% 21.4% 6.7% 1.9% 23.8% 8.6% 85.0 1999 15.0% 4.2% 24.7% 22.0% 6.6% 1.9% 23.9% 8.6% 84.6 2000 13.3% 3.7% 21.7% 27.7% 5.8% 1.7% 24.4% 8.2% 80.6 2001 14.0% 8.5% 13.0% 21.1% 10.8% 1.8% 21.4% 7.9% 77.4 2002 12.1% 7.4% 11.2% 27.6% 9.3% 1.6% 22.4% 7.5% 73.9 2003 13.3% 8.1% 12.4% 23.3% 10.3% 1.7% 21.7% 7.7% 76.2 2004 16.7% 3.2% 17.3% 22.2% 7.2% 1.4% 21.4% 7.6% 74.6 2005 17.0% 3.2% 17.5% 21.5% 7.3% 1.4% 21.3% 7.6% 75.0 2006 17.3% 3.3% 17.9% 20.5% 7.5% 1.5% 21.2% 7.7% 75.5 2007 19.8% 2.9% 21.8% 20.2% 3.9% 1.7% 22.0% 8.1% 79.4 2008 19.2% 2.8% 21.1% 21.8% 3.8% 1.6% 22.2% 8.0% 78.4 2009 22.5% 2.8% 17.9% 21.4% 3.4% 1.7% 21.4% 7.8% 76.7 2010 23.2% 2.9% 18.4% 19.8% 3.5% 1.8% 21.1% 7.9% 77.5 2011 23.2% 2.9% 18.5% 19.7% 3.5% 1.8% 21.1% 7.9% 77.6    Avg. 88.9  Min. 73.9  Max 94.9  72  As shown in Table 3.7, the methane generation potential of waste that has been historically deposited at VLF since 1967 has varied within the range of 73.9 to 95.9 m3 methane per tonne of MSW deposited. An increase in organic waste diversion activities in MV has reduced this value to its current amount of 77.6 m3 tonne-1.   3.3 Decay Rate (k, year -1) The decay rate defines how fast the organic materials are broken down in the landfill and the rate of LFG generated. In the first order kinetic reaction, decay rate is defined as the biodegradation half-life of the organic material. Half-life (t1/2) is the time it takes 50% of the original amount of organic material to be decomposed.  Fine-tuning the value of the decay rate(s) would have a significant effect on a landfill’s operation evaluation parameters, such as the LFG collection system efficiency and level of GHG emission rates from the landfill.  Selecting more accurate decay rates also largely affects the LFG collection system design parameters, such as the design capacity of the extraction system (i.e. blower facility and piping network), sizing flares, and/or energy recover systems. However, the total methane generated during the landfill’s lifespan is not related to the selected decay rates. For instance, as shown in Table 1.11, comparison of LFG modeling results for Phase 1 of the VLF based on different methodologies, the total lifespan methane generation resulted by LandGEM (when inventory modeling parameters were used), and BC MOE methodologies were both around 301,000 tonnes (±0.3%). However, the “current collection efficiencies” derived from these two methodologies were 73% and 56%, respectively.  The relationship between half-life and decay rate based on the fundamental first-order decay equation presented in Chapter 1 (see Equation 1.4), would be as follows: 73   k (year -1) = ln(2) / t1/2  Equation 3.4  For example, a half-life of 3 years would result from a decay rate of k = 0.23 year-1.  In general, there are two major approaches in selecting half-lives and decay rates for predicting LFG and/or methane generation rates. Some models, such as LandGEM and Golder models, use an average k value as the decay rate of the entire MSW mass (i.e. single phase methodology). Other models, such as BC MOE tool and IPCC FOD, assign different decay rates to different types of organic materials (i.e. multi-phase methodology). As was previously discussed in Chapter 1, a comparison of these two groups of models indicated that the multi-phase first-order decay methodologies yielded more reliable methane generation predictions (Hoeks, 1983; Oonk, 1994).   There are several factors affecting the degradation rate constant. Some relate to the chemical characteristics of the waste material (e.g. lignin content), and some are based on the physical properties and environmental conditions (e.g. particle size, moisture content, temperature and pH)  (Rovers et al., 1977; EMCON Associates, 1980; Bookter and Ham, 1982; Hoeks, 1983; Bingemer and Crutzen, 1987; Ham et al., 1993; Oonk, 1994; Eleazer et al., 1997; Ivanova et al., 2008).  Rovers et al. (1977) conducted one of the first studies reporting different decomposition rates for various types of organic materials in MSW landfills. They suggested that food waste and yard 74  wastes are among the fastest decaying materials, decomposing within 1 to 5 years. Paper wastes were the second most readily decomposable component and were reported to decompose within approximately 5 to 10 years. Finally, wood waste (excluding approximately 30% of the lignin portion) was reported to decay in 20-100 years. More detailed studies were later conducted on the decay rates and half-lives for different organic wastes. Robert K. Ham et al. (1979) estimated that the half-life of food waste was 1 year and the half -lives of paper waste, wood waste, and yard waste were about 15 years. He also concluded that the food waste decay rate under optimum conditions in landfills can be as high as 0.7 year-1, which yields a half-life of 1 year.  While there does not appear to be a large discrepancy between the suggested values for decay rates under optimum conditions at landfills, assignment of parameters value for a particular landfill seems to be slightly different according to different models. In all methodologies, k is related to the moisture content of the landfill, which is defined by the precipitation levels in the area. However, in the IPCC model, the decay rates are also dependent on the ambient temperature.  IPCC (2006) used an ambient temperature of 20 °C as a threshold, reflecting the fact that the biodegradation rate of the organic material and methane generation under anaerobic conditions slows down significantly at temperatures below 20° C (Maly and Fadrus, 1971; Debra R. Reinhart et al., 2005). Maly and Fadrus (1971) concluded that anaerobic biodegradation is enhanced at temperatures ranging from 20° to 50° C. Edward A. McBean et al. (1995) also reported the optimum temperature ranges for mesophilic and thermophilic bacterial activities within MSW landfills to be between 30° and 35°C and 45° and 65°C, respectively.   75  While there is enough evidence and data on the effect of temperature on the biodegradation process in landfills, there is a limited number of studies looking into the actual temperature of landfills and that how it fluctuates with the ambient temperature. Maurice and Lagerkvist (2003) studied the effects of seasonal variations on biodegradation activities and methane generation from landfills located in cold climates and concluded there were no significant variations caused by low ambient temperatures. Similarly, Bingemer and Crutzen (1987) and Thompson and Tanapat (2005) reported insignificant differences in methane generation rates between the winter and summer seasons.   In the present study, the half-lives previously developed in various studies were used as a basis for estimation of decay rate constants for the degradable components of MSW. The effects of the two major environmental affecting parameters, i.e. temperature and moisture, on the assigned k values were also considered where necessary. However, to recap the debate over the relationship between ambient temperature and internal landfill temperature, a comprehensive field investigation, presented in Section 3.3.1, was conducted to study the Vancouver Landfill temperature and its fluctuations in relation to the ambient temperature variations from the coldest to the warmest day of 2011.  3.3.1 Temperature It is widely known that bacterial degradation is enhanced with increased temperatures within the optimum range (Maly and Fadrus, 1971; Barlaz et al., 1997; Baldwin et al., 1998). One of the most well-known equations in this regard is the van't Hoff-Arrhenius equation developed in 1884 defining the temperature dependency of the bacterial degradation process (Metcalf & Eddy, 76  1991). Likewise, waste mass temperature is repeatedly reported to be a major parameter affecting the rate of waste decomposition in MSW landfills. Optimum temperatures within the range of 30 to 65°C are reported for methanogenic activities, whereas, the thermophilic bacteria active in the upper end of this range are more effective in methane generation (Edward A. McBean et al., 1995).   The relationship between temperature and methane generation was also formulated by Hartz et al. (1982). They concluded that the methane generation rate was optimized at temperatures between 30° to 41°C. That study further showed that the decay rate decreased when temperature was decreased and that it tripled for each 10°C rise in the temperature (Hartz, 1983). Other studies also identified a similar range up to 45 °C as the optimum temperature range for gas production at landfills (DeWalle et al., 1978; Rees, 1980b; Mata-Alvarez and Martinez-Viturtia, 1986).  There have been only a few full-scale studies conducted on the actual temperature within landfills. Nevertheless, it is a well-known belief that landfill temperatures in central and deeper zones do not significantly fluctuate with ambient temperature (Bingemer and Crutzen, 1987; Edward A. McBean et al., 1995; Maurice and Lagerkvist, 2003; Thompson and Tanapat, 2005). Anaerobic degradation is an exothermic process, so bacterial activity continues to generate heat until optimum temperatures are reached (Maurice and Lagerkvist, 2003).  Edward A. McBean et al. (1995) reported that the temperature in the top layers of a dry landfill may be more affected by ambient temperature, while deeper zones (deeper than 15 m) are unaffected by ambient air temperature. Maurice and Lagerkvist (2003), Thompson and Tanapat (2005) and Bingemer and 77  Crutzen (1987) all report no dependency of MSW landfill temperature on ambient air temperature. However, IPCC (2006) elected to choose different decay rates based on the ambient mean annual temperature (MAT) (See Table 1.4).   During the course of the present study, an investigation was conducted at the VLF to test the hypothesis that landfill temperatures in deeper zones are primarily driven by exothermic biodegradation reactions and not the ambient temperature. Provided that the optimum conditions were met (i.e. enough moisture content, availability of nutrients and the pH being at the optimum levels) it was believed that bacterial activity maintains the temperature at optimum levels. The landfill temperature investigations at the VLF are described in next section.  3.3.1.1 Landfill Temperature Investigations Landfill temperature investigations were conducted at the four different phases of the VLF during a course of eight months from January to August 2011. Historical climate records show that Vancouver experiences the absolute maximum and minimum ambient temperatures within this time range. Ambient temperature was recorded with high resolution (i.e. every 10 minutes) using an S-TMB-M002, 12-Bit Temp Smart Sensors and a HOBO temperature data logger installed at the VLF site. As shown in Figure 3.1, the ambient temperature recorded during the course of the field work varied from a minimum of -8.9°C (occurred in Feb. 25th, 2011 at 7:10 AM) to a maximum of 32.5°C (occurred in Aug. 17th, 2011 at 4:50 PM).  Figure 3.2 also illustrates the minimum and maximum daily temperature recorded at the Vancouver International Airport weather station, showing the ambient temperature varying from minimum of -8.1°C to maximum of 27.4°C during the course of the field work.  78   Figure 3.1 Recorded ambient temperature at the VLF site   Figure 3.2 Daily min. and max. temperature recorded at the Vancouver Int'l Airport weather station  -10-505101520253035Temperature (oC)Time-10-5051015202530Temperature (°C)TimeDaily Min.Daily Max.79  After conducting an initial wellfield survey (October to December 2010) on the existing LFG wells, 27 LFG wells were selected for the purpose of monitoring temperature at different depths of the landfill. This inspection was to study the accessibility of wells, available depths, leachate water level, and any obstruction in the wells that may have occurred due to landfill settlement (full inspection results are provided in Appendix C.1). The inspection showed that despite the expected depth of approximately 25 m for the new LFG wells installed in Phase 1, all the wells were either obstructed or flooded (i.e. filled with water and/ or leachate) at depths of approximately 10 to 12 m below ground (B.G.). Figure 3.3 below shows the location of the selected wells for temperature investigations.   Figure 3.3 Location of selected LFG wells for landfill temperature investigations   As shown in Figure 3.3, out of a total of 27 wells, 11 wells were selected from Phase 1 of the VLF where the waste depth exceeded 30 m and was partially capped with a geomembrane cap in 2009 (extent of the geomembrane cap is shown with a dash line in the Figure). Another 16 wells Phase 1 Area 3 Area 2E Area 2W 80  were located in the older areas of the landfill (Area 3, Area 2E and Area 2W previously shown in Figure 2.2). These areas contained older waste with a depth of 10 to 12 m and had been closed with interim cover soil in 1998, 1995, and 1993, respectively. Table 3.8 below shows a list of the selected wells, their coordinates, elevations, pipe diameters, and available depth at the time of the survey.  Table 3.8 Selected wells for the landfill's temperature investigation  choose 111 F07 5438634.3 500804.2 24.10 25.67 2.070 11.732 F10 5438777.7 500810.0 24.69 26.15 2.070 13.353 F26 5438831.8 500845.1 30.76 33.04 2.070 11.234 P01-V030 5438480.6 500885.9 33.21 34.47 2.070 10.605 P01-V031 5438540.4 500940.1 19.97 21.63 2.070 11.506 P01-V034 5438576.2 500883.9 35.24 36.70 2.070 11.007 P01-V036 5438623.7 500881.2 35.76 37.41 2.070 9.758 P01-V041 5438793.4 500944.3 18.48 20.35 2.070 9.809 P01-V042 5438773.2 500883.8 34.18 35.73 2.070 8.5510 P01-V054 5438386.0 500934.7 19.88 21.24 2.070 13.9511 P01-V056 5438379.3 500881.7 18.71 20.14 2.070 11.00choose 912 A2W-V007 5438615.7 499977.2 11.59 12.7667 2.095 9.0213 A2W-V012 5438668.8 499937.6 12.63 13.8852 2.095 9.2014 A2W-V018 5438720.7 499907.9 12.64 13.7835 2.095 8.5615 A2W-V029 5438779.3 499606.6 9.81 11.0670 2.095 8.4316 A2W-V050 5438925.9 500031.9 10.85 12.1874 2.095 8.0217 A2W-V055 5438926.6 499738.4 13.74 15.0517 2.095 10.4518 A2W-V056 5438926.5 499678.1 13.50 14.8397 2.095 9.0519 A2W-V060 5438971.7 500003.0 11.26 12.5123 2.095 8.6520 A2W-V066 5438978.4 499648.3 12.28 13.6361 2.095 11.08choose 621 A2E-V010 5438506.1 500282.4 12.24 13.6055 2.095 9.8522 A2E-V013 5438558.7 500312.6 11.86 13.3392 2.095 9.9023 A2E-V017 5438610.5 500282.8 11.92 13.2526 2.095 8.7024 A2E-V022 5438662.3 500218.3 10.38 11.8330 2.095 6.2025 A2E-V032 5438817.9 500342.0 10.78 12.0630 2.095 6.8026 A2E-V033 5438818.0 500281.9 12.03 13.2470 2.095 8.20choose 127 A03-V019 2.095Area 2E (1/45 Wells)Phase 1 (11/42 Wells)WellName Northing EastingGround Elevation (m)Pipe ID (in)Area 2W (9/70 Wells)Top Casing Elevation (m)Water Depth below ground level (m)Area 2E (6/45 Wells)81   ACR Data Loggers (Smart Buttons) were used to log temperatures every hour at various depths of the selected LFG wells. Chambers were custom made for the smart buttons using a ½″ Brass Plug and a ½″ Brass Cap, sealed with Teflon tape and hung in wells using brass aircraft cable. Figure 3.4 below shows the smart button’s chamber as well as an installed position example inside one of the LFG wells at the depth of 10 m B.G..   Figure 3.4 Temperature data logger and chamber (left), and installation set-up at ~10m below ground just above leachate level in an LFG well (right)  During the initial field investigation, a quick temperature survey was conducted on a limited number of selected wells on December 13th, 2010. This investigation assessed, in real-time, the temperatures inside the LFG wells at various depths while the ambient temperature was about 8° C. During this survey, the temperature profile was recorded for the total available depth of the 82  wells. Figures 3.5, 3.6 and 3.7 below show the temperature profiles for the LFG wells “A2W-V007”, “A2W-V012” and “P01-V034”, respectively.    Figure 3.5 Temperature profile in LFG well “A2W-V007”, December 13th, 2010 (ambient T ~8° C, depth of waste ~10m and area closed with interim cover soil since 1993)   Figure 3.6 Temperature profile in LFG well “A2W-V012”, December 13th, 2010 (ambient T ~8° C, depth of waste ~11m and area closed with interim cover soil since 1993) 0.02.04.06.08.010.012.014.016.00 1 2 3 4 5 6Temperature (oC)Depth (m below ground )0.02.04.06.08.010.012.014.016.00 1 2 3 4 5 6 7 8 9Temperature (oC)Depth (m below ground)83   Figure 3.7 Temperature profile in Gas Well P01-V034, December 13th, 2010 (ambient T ~8° C, depth of waste ~33m and area closed with geomembrane cover since 2009)  It should be noted that while this initial survey provided useful information with regard to the temperature gradient and  the temperature in deeper zones, these data would not be accurate, especially in shallower sections of the wells, as the wellhead cap had to be removed to access the well, resulting in cold air being drawn down to the well. Nevertheless, these initial investigations showed that in both cases (old phases and the recently closed Phase 1) the temperature inside the wells was higher than the ambient temperature. However, the old areas showed slight differences between ambient temperature and landfill temperature. In contrast, a significant temperature difference was observed in the new phase as shown in Figure 3.7. Since the design of the LFG vertical wells included solid PVC and/ or HDPE pipes for the first 5 meters of the well, the recorded temperature would be the temperature of the gas collected and conveyed from the depth of 5 m B.G. and below. Therefore, the reported landfill deep zone temperatures would be those recorded from the screened sections of the LFG well pipes (i.e. below 5 meter B.G.).  0.010.020.030.040.050.060.00 1 2 3 4 5 6 7 8 9 10 11Temperature (oC)Depth (m below ground)84  Based on this initial quick survey, it was decided that one temperature logger would be installed in each gas well selected in Area 3, Area 2E and Area 2W, and two data loggers would be installed in wells located in Phase 1 of the VLF. Temperatures were logged every hour at ~5 m and 10 m B.G. in Phase 1 and approximately 8 m B.G. in Areas 2W, 2E, and 3. It is worth mentioning that the total number of selected wells and temperature recording points was also limited due to limitations on available resources. Other limitations in these series of field work included limited storage capacity of the smart buttons as well as their frailty against moisture that could potentially leak into the data logger chambers. Due to these limitations, the smart buttons were replaced at least once every month during the 8 months course of these field studies. Even with frequent replacement, some of the data loggers burned out, resulting in a loss of data.   3.3.1.2 Results and Discussion During the course of the landfill temperature field study, over 100,000 data points were collected from the selected 27 wells located in 4 different areas of VLF. Illustrations of all recorded data are provided in Appendix C.2, of which a few examples are presented below.  In general, results showed that the landfill temperature was not affected by ambient temperature fluctuations and appeared to be constant throughout the cold and warm seasons, similar to previous findings by Bingemer and Crutzen (1987), Maurice and Lagerkvist (2003) and Thompson and Tanapat (2005). However, different ranges of temperatures were observed for wastes of different ages. Areas with newer waste showed higher temperatures, representing more bacterial activity occurring in those areas. Recorded data also showed how the LFG system operational glitches can affect the landfill’s temperature.  Figure 3.8 below shows the recorded 85  data at 5 m B.G. in vertical LFG well #34 located in Phase 1 of VLF (i.e. Well “P01-V034”). An almost constant temperature of about 40 °C was recorded at this location throughout the course of the study. Also shown in the figure, three incidents of LFG collection system shut-downs occurred when cooled gas from the header pipe (buried near the ground surface) was pulled back to the fill and resulted in lower recorded temperatures (shown as operational errors, excluded from valid recorded data point).  Figure 3.8 Temperature data for the LFG well "P01-V034" (5 m B.G.)  Figure 3.9 and Figure 3.10 respectively illustrate the monthly averages and hourly temperatures in this well. These data are plotted against the ambient temperature, clearly showing independency of the landfill temperature from short term and seasonal temperature variations.  05101520253035404550Temperature (oC)DateData Logger Burnt OutOperationalErrors86   Figure 3.9 Comparison of monthly average temperature data (Ambient vs. P01-V034)   Figure 3.10 Hourly temperature fluctuations - ambient vs. landfill temperature (P01-V034)  0.05.010.015.020.025.030.035.040.045.0Temperature (°C)MonthsP01-V034 Ambient05101520253035404550Temperature (°C)TimeLandfill TemperatureAmbient Temperature87  Similarly, Figure 3.11 below is an example of the recorded temperatures in a deeper zone of the landfill at approximately 10 m below ground. When operational errors were excluded, the recorded temperature at this point showed a fluctuation of only 1 °C from mid-January to mid-June around the average temperature of 43.1 °C.    Figure 3.11 Temperature data for the LFG well "P01-V041" (9.5 m B.G.)  Figure 3.12 shows the recorded temperatures in well A2W-V056 located in the older zone of VLF. Temperatures recorded at this location were fairly constant, around 15.5 °C with a maximum fluctuation of 1 °C between mid-January to mid-June. 36373839404142434445Temperature (oC)Date88    Figure 3.12 Temperature data for the LFG well "A2W-V056" (8 m B.G.)  The results of the 8 months landfill temperature investigations conducted at VLF are tabulated in Table 3.9. Well ID, depth of temperature probe, age of waste at the location, and landfill cover type are also shown, along with the average temperature, minimum and maximum values recorded, range of temperature fluctuations, standard deviation, and coefficient of variation. Out of 35 deep and shallow data recording points, four probes (3 shallow and 1 deep, data are shown in red) showed a large range of fluctuation in recorded temperatures (the red entries in Table 3.9). These variations are not correlated to the ambient temperature fluctuations and are believed to be a result of (i) faulty operation of, and/ or (ii) adjustments made to the LFG wellfield at VLF. (Note: wellfield adjustment is referred to the adjustments made to an LFG collection system to provide required amount of vacuum to each wellhead to actively collect the LFG in an 5791113151719Temperature (oC)Date89  effective manner). Two examples of these “invalid” recorded data are further explained below, whereas these data are excluded from the final summary of findings and the conclusions resulting from this section of the study.  Table 3.9 Landfill temperature field investigation results (red entries represent invalid recorded data)   (°C) (°C) (°C) (°C) (°C) (%)5.0 7 Soil Cap 1,367          42.0 45.0 3.0 44.7 0.41 0.9%10.0 7 Soil Cap 1,367          46.0 47.0 1.0 46.5 0.05 0.1%P01-V010 10.0 7 Soil Cap 1,823          42.0 47.5 5.5 45.4 1.29 2.8%5.0 7 Geomem. 1,523          42.5 44.0 1.5 43.1 0.48 1.1%10.0 7 Geomem. 865             46.0 51.0 5.0 46.6 1.03 2.2%5.0 7 Geomem. 3,051          20.5 46.0 25.5 32.4 6.94 21.4%10.0 7 Geomem. 1,460          29.5 37.0 7.5 33.7 1.57 4.7%5.0 7 Geomem. 2,508          38.5 43.5 5.0 39.8 0.73 1.8%10.0 7 Geomem. 2,520          50.5 53.0 2.5 52.1 0.73 1.4%5.0 7 Geomem. 2,522          42.5 45.0 2.5 43.8 0.44 1.0%9.5 7 Geomem. 2,522          47.5 48.5 1.0 48.4 0.25 0.5%5.0 7 Geomem. 2,048          31.5 42.0 10.5 40.7 0.80 2.0%9.5 7 Geomem. 3,554          42.5 43.5 1.0 43.1 0.22 0.5%3.5 7 Geomem. 2,673          38.5 42.0 3.5 39.6 0.30 0.8%8.5 7 Geomem. 1,535          48.5 52.5 4.0 50.1 0.79 1.6%5.0 7 Geomem. 3,188          35.0 45.0 10.0 41.7 2.71 6.5%10.0 7 Geomem. 1,523          43.5 46.0 2.5 45.9 0.24 0.5%P01-V056 10.0 7 Geomem. 3,195          43.5 45.5 2.0 45.0 0.22 0.5%A3--V019 6.5 14 Soil Cap 1,034          20.5 21.5 1.0 21.0 0.12 0.6%A2E-V010 8.0 16 Soil Cap 4,089          14.5 16.5 2.0 15.7 0.48 3.1%A2E-V013 8.0 16 Soil Cap 4,090          14.0 15.0 1.0 14.6 0.35 2.4%A2E-V017 8.0 16 Soil Cap 4,090          15.5 16.5 1.0 16.0 0.22 1.4%A2E-V029 6.5 16 Soil Cap 4,090          14.0 16.0 2.0 15.1 0.37 2.5%A2E-V032 6.5 16 Soil Cap 4,090          8.5 11.0 2.5 10.2 0.58 5.7%A2E-V033 8.0 16 Soil Cap 4,090          16.5 17.5 1.0 16.9 0.23 1.4%A2W-V007 8.0 18 Soil Cap 4,090          12.5 16.0 3.5 15.0 0.72 4.8%A2W-V012 8.0 18 Soil Cap 4,090          16.5 18.0 1.5 17.1 0.41 2.4%A2W-V018 8.0 18 Soil Cap 4,090          15.5 17.0 1.5 16.1 0.58 3.6%A2W-V029 8.0 18 Soil Cap 4,088          12.5 13.5 1.0 13.3 0.25 1.9%A2W-V050 8.0 18 Soil Cap 2,043          14.0 14.5 0.5 14.4 0.17 1.2%A2W-V055 8.0 18 Soil Cap 4,088          12.5 16.0 3.5 14.4 0.88 6.1%A2W-V056 8.0 18 Soil Cap 3,986          15.0 16.0 1.0 15.5 0.27 1.8%A2W-V060 8.0 18 Soil Cap 4,090          15.5 16.5 1.0 15.8 0.31 1.9%A2W-V066 7.5 18 Soil Cap 4,089          14.5 16.0 1.5 15.9 0.17 1.0%P01-V054P01-V007No. of Valid data PointsMin. Temp.Max. Temp.Fluctuation RangeP01-V030P01-V042Depth of Probe from Surface (m)LFG Well IDAverage Temp.Standard Dev.Coef. of VariationCover TypeAverage Waste Age (yr)P01-V031P01-V034P01-V036P01-V04190  Figure 3.13 is an example of how wellfield adjustments affected the recorded temperature at LFG well P01-V054. As mentioned before, the shallower probes, mainly installed at approximately 5 m B.G., were located in the section of the well with solid well piping. Therefore, the recorded temperatures were expected to be a function of the gas temperature from deeper zones (landfill temperature) and perhaps the temperature of surrounding environment which would be slightly lower than the values recorded in deeper zones. This means that there would be less difference between the temperature values recorded at shallow and deep probes in wells from which higher LFG flow rates are collected.     Figure 3.13 Recorded data at well "P01-V054"_example of wellfield adjustment affecting recorded temperature  35373941434547Temperature (°C)Date5m B.G.10m B.G.91  In this particular example, shown above for the well P01-V054, the wellhead was turned down (i.e. applied vacuum to the well was reduced) on April 27th, 2011 resulting in a temperature decrease in the shallower section of the well, however the temperature in the deeper zone of the landfill (i.e. 10 m B.G.) remained constant at 45.9 ± 0.2 °C.   Another cause of error in the temperature data was observed in P01-V031 where the recorded temperatures showed fluctuation patterns as if the gas temperatures in the sub-surface header pipe were recorded. Figure 3.14 below shows the recorded data at this location.   Figure 3.14 Example of faulty temperature readings at LFG well "P01-V031" Due to the LFG collection system operational issues  These temperature values recorded at P01-V031 indicated that no LFG might have been collected from this location. Zero flow situations, when the wellhead is not shut down, can stem 2022242628303234363840Temperature (°C)Date10m B.G.5m B.G.92  from two causes. The first is due to a total blockage of the well screens due to the high water table, resulting in the well screens being silted over time. This hypothesis was disproved by video inspection of the well conducted during the course of the field investigations. The second hypothesis was an application of excess vacuum in neighboring wells. The vacuum applied to LFG wells is normally defined by several parameters, including well spacing (i.e. expected radius of influence), waste compaction and/or porosity, cover system design and type, depth of well, and depth to the top of the screened section of the well pipe.  Typically, 5 to 10 inches of water column is applied to LFG wells to effectively collect the generated gas at acceptable collection efficiencies. Applying too much vacuum to the LFG wells, which potentially causes air intrusion into the landfill, may result in adjacent wells overlapping each other’s zone of influence to a greater extent. This is especially a concern in cold climate/ seasons and may have significant negative effects on methanogenic activity via the interruption of optimum temperatures maintained by the exothermic bacterial-mediated reactions. Nevertheless, further mining into the LFG flow rate data, which was collected from the selected wells during the course of these field investigations, supported this hypothesis. The gas flow rate data showed that although there was system vacuum provided at this gas collection point, no gas was collected from this location starting from May 2011. Figure 3.15 shows the applied vacuum and the LFG flow rate at well P01-V031. Figure 3.16 provides similar data for P01-V030, showing significantly higher gas flow rates at approximately similar system vacuum conditions as was provided to P01-V031.  93   Figure 3.15 System vacuum and LFG flow rate at P01-V031   Figure 3.16 System vacuum and LFG flow rate at P01-V030  Figure 3.17 below shows wellhead P01-V054 at VLF and a Landtec. GEM™ 2000+ LFG analyzer which was used during the field investigations to monitor the collected LFG flow rate and composition from the selected wells. -12-10-8-6-4-20012345678910Applied Vacuum (inches H2O)LFG Flow Rate (scfm)DateLFG Flow RateApplied Vacuum-12-10-8-6-4-20010203040506070Applied Vacuum (inches H2O)LFG Flow Rate (scfm)DateLFG Flow RateApplied Vacuum94   Figure 3.17 LFG wellhead and LANDTEC GEM2000+ used to collect gas data at VLF  3.3.1.3 Older Temperature Study at the Vancouver Landfill Yeşiller et al. (2005) conducted a comprehensive study on landfill temperatures at four different landfills in North America, including the VLF. That study, which was conducted at shallower areas of VLF (maximum waste depth of approximately 12 m), showed a maximum temperature of 43 °C at this site, confirming that the high temperatures recorded during the course of the present study at Phase 1 of VLF are not solely due to the greater depth of the fill in this phase. Under the study conducted by Yeşiller et al. (2005) at VLF, temperature sensors were located at various locations of the landfill, recording temperatures at various depths starting in 2004. That study continued for a number of years and the following illustration shows a snapshot of the raw recorded temperature data at representative locations from each area of the landfill at a depth of 8 m B.G. (Hanson et al., 2010).  95   Figure 3.18 A Snapshot of other available temperature data recorded through a comprehensive study by (Hanson et al. 2010) at several landfills including VLF (8 m B.G.) (Raw data were provided by COV)  3.3.1.4 Conclusion Approximately 100,000 landfill temperature data points were collected in different phases of VLF over a period of 8 months, covering the coldest and warmest days of 2011. Results showed no dependency of landfill temperature on ambient temperature. This is in great disagreement with methodologies that base LFG generation modeling parameters on ambient temperature. Landfill temperature fluctuations were observed to be within 0.5 to 5.5 °C, mainly due to adjustments made to the LFG extraction and collection systems. This is in contrast to the 41.4 °C fluctuation observed in ambient 051015202530354045Temperature (oC)DateA2W (1990-1993)A2E (1994-1995)A3 (1996-1998)Table 3.10 Summary of landfill temperature investigations (Depths 8 to 10 m B.G.) Area Average Waste Age (yr) Cover Type Average Temp. Standard Dev. (°C) (°C) Phase 1 7 Soil Cap 45.9 0.91 Phase 1 7 Geomem. 47.3 0.59 Area 3 14 Soil Cap 21.0 0.12 Area 2E 16 Soil Cap 15.8 0.34 Area 2W 18 Soil Cap 15.3 0.48   96  temperature recording. Table 3.10 shows the average values for the valid recorded temperature data in deeper zones of the Vancouver Landfill’s different phases.   Similar to what was reported more than three decades ago by Rovers et al. (1977), these field investigations showed that even in temperate climates like Canada, landfill temperatures remain at optimum ranges for methane production with no significant variations due to ambient temperature fluctuations. Average temperatures of Phase 1 in areas covered with a soil cap were 45.9 ± 0.9 °C, which is slightly lower than areas covered with geomembrane cap with average temperature of 47.3 ± 0.6 °C. This may be due to the different permeability of these two types of cap systems and the effect of cold rain percolating through the soil cap to the fill. Average temperatures of the landfill in Area 3, Area 2E and Area 2W were 21.0 ± 0.1°C, 15.8 ± 0.3°C, and 15.3 ± 0.5°C, respectively.    Another very important finding of these investigations was the correlation between waste age and landfill temperature. Each phase, containing MSW with various average ages ranging between 7 to 18 years, showed a different temperature profile which remained constant throughout the study.  Acknowledging the effect of temperature on biodegradation rates, these results suggest that use of a constant k value for the entire landfill’s lifespan may not be an accurate choice. However, the decomposable portion of readily biodegradable organics, such as food waste and yard waste, will be almost entirely decomposed by the time the degradation process and the fill temperature decrease. Therefore, application of variable decay rates for slowly degradable waste components, such as wood waste, will likely offer little improvement to the accuracy of the long term LFG generation predictions.  97    While the effect of temperature fluctuation on the biodegradation process is very well known, and fundamental equations such as van't Hoff-Arrhenius equation are very well developed, application of this knowledge to the complex anaerobic process occurring at MSW landfills appears difficult. There are different types of microorganisms involved in the overall methane generation process, each with a range of optimum temperatures. Some of these microorganisms themselves also regulate and maintain landfill temperatures within a certain range. Furthermore, it must be acknowledged that “landfill temperature” is a generalized term. In reality, not only depending on the distance to the landfill surface and sides as well as many other factors, such as height of the leachate mound, the temperature of different locations of the landfill might be different. There may also be several pockets within the landfill with drastically different profiles due to the heterogeneous nature of a landfill. Therefore, relating and fine-tuning the decay rate values based on temperature and formulae such as the Arrhenius equation is not suggested. Instead, the author suggests that the concept of this knowledge be applied to an average value representing the landfill temperature, and to assign decay rates based on factors that cause a drift from optimum conditions for decomposition reactions.   3.3.2 Moisture Content Studies have repeatedly reported that moisture is the primary limiting factor in the rate of waste decomposition and methane generation in landfills (Rees, 1980b; Rees, 1980a; Hartz and Ham, 1983; Edward A. McBean et al., 1995; Reinhart and Al-Yousfi, 1996; Barlaz et al., 1997; Baldwin et al., 1998; Wreford et al., 2000). Sufficient moisture in landfills is required for optimal hydrolysis and decomposition of complex organic materials to occur. Furthermore, moisture is 98  an essential element for the biodegradation process in landfills as it serves as the means of transportation for nutrients and bacteria within the landfills (Edward A. McBean et al., 1995).  Therefore, increased landfill moisture enhances the anaerobic degradation process within the landfill. Also, as described in the previous section, the exothermic anaerobic degradation process increases the temperature of the landfill, which further enhances the biodegradation process.   Rowe (1998), in a comprehensive study showed that the moisture content of landfills deeper than 6 m plays a major role in temperature rise within the fill. Rees (1980b) reported that optimum gas generation conditions at a landfill occurs when the base of the landfill is fully saturated and a waste density of 1 tonne per m3 is achieved. A different study by Hartz and Ham (1983) reported that even at moisture levels as low as 10% on a wet weight basis (% w/w) some methane production occurs. Therefore even at dry sites, and with no additional moisture added, some biodegradation is expected to occur. Similarly, Edward A. McBean et al. (1995) reported that LFG generation occurs even in very dry MSW landfills and, as the moisture content increases so do the degradation process and LFG generation. Farquhar and Rovers (1973) reported that waste decomposition and methane generation in MSW landfills slows down at field moisture levels above 80% w/w. According to Hartz and Ham (1983), this situation can only occur at landfills located in wet climates with no leachate collection system, as they concluded that free moisture conditions at landfills (i.e. field capacity threshold) occurs at approximately 40% w/w moisture content. Edward A. McBean et al. (1995) argued that even if the landfill’s moisture content exceeds field capacity, the mobility of nutrients and bacteria provided by the moving liquid will further increase the gas production. Typically, the field capacity of MSW landfills has a direct relation with waste composition and compaction ratio at the time of landfilling and reported to be 99  within 20% to 40% w/w (Edward A. McBean et al., 1995; Yuen et al., 2001; De Velásquez et al., 2003).  MSW moisture content, as received at landfills, is reported to be somewhere between 15 to 40% w/w (Edward A. McBean et al., 1995). In Canada, the average MSW moisture content is approximately 24.4% (Levelton, 1991). As previously shown on Figure 2.3 on page 48, the moisture content of the generated MSW in Metro Vancouver in the past 20 years has been between approximately 22% to 24% w/w. Nevertheless, landfill moisture content is normally derived by the climatic conditions. Precipitation levels are typically used as an index to describe landfill moisture content and leachate generation rates. There are many LFG modeling methodologies which relate the decay rates of the organic materials deposited into the landfill to the precipitation levels in the area. The following shows a few examples where the decay rate(s) is related to the level of precipitation.  3.3.2.1 The World Bank CRA (2004), in the LFG modeling handbook prepared for the World Bank, suggested different decay rates defined based on four different ranges of annual precipitation. These values, which were divided into three different decomposition categories, are provided in Table 3.11. These values are suggested for landfills located in Latin America and Caribbean regions.  100  Table 3.11 Decay rates corresponding precipitation suggested by the World Bank (CRA, 2004) Annual Precipitation Range of k Values (year -1) Relatively Inert Moderately Decomposable Highly Decomposable <250 mm 0.01 0.02 0.03 >250 to <500 mm 0.01 0.03 0.05 >500 to <1,000 mm 0.02 0.05 0.08 >1,000 mm 0.02 0.06 0.09  3.3.2.2 Environment Canada and Golder Associates Environment Canada (2012b) and Golder Associates Ltd. (2008b) both suggested a linear correlation between decay rate and precipitation levels. These methodologies both use single phase 1st order decay models, meaning that a single k is defined for the entire mass of MSW. Table 3.12 below shows the resulting k values for different annual precipitation levels based on these two methodologies.  Table 3.12 Decay rates based on Environment Canada and Golder Associates methods Annual Precipitation (mm) Decay Rates (k) (Year -1) Environment Canada Golder Associates 0 - 500  0.020 0.023 500 to 1,000 (avg. 750) 0.038 0.079 1,000  0.057 0.111  3.3.2.3 BC Ministry of Environment BC MOE in its LFG Generation Assessment Procedure Guidance Report prepared by CRA (2009), defined default values for decay rates for each waste category and for different regional areas based on the reported annual precipitation. These values, which were divided into three different decomposition categories, are provided in Table 3.13. According to CRA (2009), 101  decomposable materials include food waste, leaves, grass, plant clipping, Christmas trees, slaughterhouse waste and yard waste. Also, all different types of paper, wood waste, textile, leather and DLC waste fall into the “moderately decomposable” and the rest of materials are considered “relatively inert”.  Table 3.13 Decay rates suggested by the BC MOE modeling guideline (CRA, 2009) Annual Precipitation Range of k Values (year -1) Relatively Inert Moderately Decomposable Decomposable <250 mm 0.01 0.01 0.03 >250 to <500 mm 0.01 0.02 0.05 >500 to <1,000 mm 0.02 0.04 0.09 >1,000 to <2,000mm 0.02 0.06 0.11 >2,000 to <3,000mm 0.03 0.07 0.12 >3,000 mm 0.03 0.08 0.13  Furthermore, the BC MOE guideline has defined a “Water Addition Factor” which is a number within the range of 0.9 to 1.1, and is to be selected based on the storm water and leachate management/recirculation practices applied to the landfill. While a value of 1.0 represents the normal conditions (i.e. partial infiltration or water addition to the waste mass), values of 0.9 and 1.1 are to be applied to the k values selected for dry tomb and bioreactor landfills, respectively.   3.3.2.4 IPCC Methodology As discussed in Section 1.4.2 in page 20, the IPCC appreciated the ambient temperature values in the selection procedure for the decay rates to be applied in the FOD model. The recommended decay values assigned to the suggested thresholds for ambient temperature (i.e. 20 °C) and annual precipitation (i.e. 1,000 mm) were previously shown in Table 1.4.  102   Table 3.14 IPCC default decay rates when merged over all ranges of ambient temperature Waste Components Decay Rates (k) (years-1) Dry Moist and Wet Food waste / Sewage sludge 0.05 - 0.10 0.10 - 0.70 Garden and park waste (non-food) 0.04 - 0.08 0.06 - 0.20 Paper and Textiles 0.03 - 0.06 0.05 - 0.085 Wood and straw 0.01 - 0.04 0.02 - 0.05 Bulk MSW or industrial waste  0.04 - 0.08 0.08 - 0.20  3.3.3 Suggested Values for Decay Rates (k, year-1) Most of the methodologies suggest different k values for different precipitation levels with 1,000 mm annual precipitation being the maximum level after which constant values for decay rates are proposed. This is in agreement with findings by Yeşiller et al. (2005) where annual precipitation levels beyond approximately 840 mm were found not to further elevate the landfill temperature. This is perhaps due to the limited amount of water that can be held within the waste fill (i.e. field capacity) after which it will continue to percolate through the waste mass, and may even cause solubilized material and nutrients to be washed out in the form of leachate. Therefore, the author believes that while there should be higher decay rate values adopted for higher precipitation levels, there must also be a limit to that relationship with a threshold after which the decay rates to be considered constant.    Farquhar and Rovers (1973) reported that methane generation was inhibited at landfill moisture content levels higher than 80%. Therefore, having a leachate collection system installed at a landfill may be considered as an enhancement for the biodegradation process as it will avoid the moisture content reaching levels higher than the field capacity. However, by removing the 103  generated leachate through the landfill’s leachate collection system, a portion of the nutrients potentially available for bacterial activity will be removed (Wreford et al., 2000). Therefore, the author believes that these two factors would cancel out each other and that having a leachate collection system, especially for wet environment, would not pose a significant positive effect on the biological degradation process in the landfill. Leachate recirculation, however, can be considered as an enhancement to the overall degradation and methane formation process as long as excessive water infiltration is avoided.  Rees (1980b) reported that an excessive water infiltration at landfills may result in the cooling of the waste mass, slowing down or inhibiting the degradation process.  Table 3.15 presents suggested  decay rate values for different waste components assigned to different precipitation levels. These values are selected based on the fact that depending on the landfill moisture, which is primary derived by the precipitation levels in the area, bacterial activity would provide an optimum condition and the degradation process will continue at the suggested rates. However, should the landfill’s conditions for any reason drift from the optimum situation (i.e. pH drifts from optimum range of 6.7 to 7.5 (Edward A. McBean et al., 1995) and /or landfill temperature drops below 30 °C (Hartz, 1983; Edward A. McBean et al., 1995)) these suggested decay rate values shall be adjusted accordingly.    104  Table 3.15 Suggested k values assigned to different precipitation levels for advanced LFG generation assessment Waste Components Decay Rates (k, year -1) Annual Precipitation (mm) < 500 500 to 1,000 > 1,000 Food Waste 0.07 0.15 0.3514 Yard Waste 0.04 0.08 0.1415 Paper and Textile 0.02 0.05 0.0716 Wood Waste 0.02 0.03 0.04  3.4 Delay Time As previously shown in Figure 1.1, there is a lag time between the moments of waste placement in a landfill until steady anaerobic/ methanogenic conditions are reached. The length of this “delay time” depends on various factors including climatic condition and waste composition, and can vary between 3 months and one year (ATSDR, 2001; Gregory et al., 2003; Barlaz, 2004; USEPA, 2004).  Lay et al. (1996) reported that the lag time between waste placement and methane production decreases at higher landfill moisture contents. IPCC (2006) recommended a delay time of between zero and six months. Most of the existing models, including the IPCC FOD and the US-EPA LandGEM, use the default value of six months for the delay time in all types of landfills. Considering the six month delay as an average residence time for the total                                                  14 Average value based on half-life of 1-3 years under optimum condition adopted in consultation of (Rovers et al., 1977; Robert K. Ham et al., 1979; Jensen and Pipatti, 2002; IPCC, 2006).  15 Based on an average half-life of 5 years under optimum condition adopted in consultation with (Rovers et al., 1977; IPCC, 2006). 16 Based on average half-life of 10 years under optimum condition adopted in consultation with (Rovers et al., 1977; CRA, 2004; IPCC, 2006; CRA, 2009) 105  mass of MSW deposited throughout year A, these models consider the steady methane generation phase to start at the beginning of year A+1.   In the current advanced modeling exercise, it is suggested that instead of a flat assumption for all landfills, the delay time to be correlated to the level of precipitation in the area. Dependency of the decay reaction rates on landfill moisture was previously shown in Section 3.3.3 and is the main driving force for this suggestion. However, should the landfill conditions for any reason drift from the optimum situation (i.e. pH drifts from optimum range of 6.7 to 7.5 (Edward A. McBean et al., 1995) and /or landfill temperature drops below 30 °C (Hartz, 1983; Edward A. McBean et al., 1995)) these suggested delay times shall be investigated and adjusted accordingly. Table 3.16 shows the suggested delay time values for different cilatic conditions.   Table 3.16 Suggested average delay time based on precipitation levels  Annual Precipitation (mm) Average Delay Time (Td)  (months) >1,000 4 500 to 1,000 5 < 500 6  3.5 The New Model Based on the multi-phase first order decay methodology, an integrated LFG generation model (iModel-110©), incorporating the modeling parameters and correction factors explained above, was developed in an excel workbook. The fundamental model equation is shown in Equation 3.5:  106  𝐆 =∑∑(𝟗𝟖𝟑. 𝟐𝟖𝟒𝟐 × 𝒌𝒋 × 𝑴𝒊𝒋 × 𝒘𝒋 × 𝑫𝑶𝑪𝒂𝒋 × 𝒆−𝒌𝒋×𝒕𝒊𝟓𝒋=𝟏)𝒏𝒊=𝟏  Equation 3.5  Where:  “G” is the methane generation rate (m3 year-1) “i” represents each year of the landfill lifespan “j” represents five different type of the organic materials deposited to the landfill “983.2842” is a conversion factor (See Equation 3.3) “Mij” is the mass of organic waste type j disposed in year i (tonnes, wet basis) “wj”  is the moisture content of the organic waste type j (See Table 2.8) “DOCaj” is the actual amount of organic carbon in the organic waste type j which is ultimately converted to methane (See Equations 3.2 and Table 3.6)   The model was developed with a user-friendly interface consisted of five major interlinked spread sheets and several hidden sheets for calculations. The major interface spread sheets include Parameters, MSW Tonnage, Dry Tonnages, LFG Results, and Graphics.   In the “Parameters” sheet the site-specific information such as the landfill name, opening year, site design, operational and climate factors as well as waste components characteristics such as moisture content (wj), DOCdry-j and decay factors (kj) are to be entered. Landfill activity data, including tonnages and composition of the MSW historically deposited at the landfill or expected to be landfilled in the future (Mj), are entered in the “MSW Tonnage” sheet. The total amount of 107  carbon annually deposited at the site is calculated based on the DOC and moisture content values in the “Dry Tonnage” sheet. The “LFG Results” sheet presents the calculated methane generation yield for each year based on the waste data, estimated annual methane generation from each waste component in tonnes per year, and the expected LFG flow rates in standard cubic feet per minute (scfm). These results, along with average waste tonnage and composition data, are graphically illustrated in “Graphics” sheet.   3.5.1 The New Model Results for the Vancouver Landfill The iModel-110© was run separately for the VLF’s four sub-areas within the boundaries of the study. One of the model’s graphical outputs is the illustration of average waste composition that historically has been deposited into the landfill. These illustrations are very useful when the model is used as a tool for report preparation.  Figure 3.19 a, b, c, and d shows these results for Area 2W, Area 2E, Area 3, and Phase 1 of VLF, respectively.  Figure 3.20 shows annual tonnages, as well as the total tonnage of MSW historically deposited at VLF within the study boundary previously defined in Section 2.2.5. Also shown in Figure 3.21, are the initial methane generation estimates from each of the waste components historically deposited in these areas. Figure 3.22 illustrates the total methane generation rate and LFG flow rate estimated to be generated from the boundary of the study (Gi). Summary of the results are presented in Table 3.17. Full results and outputs of the models for Area 2W, Area 2E, Area 3, Phase 1, and the entire work site boundary at VLF are presented in Appendices B.1 through B.5, respectively.    108  Table 3.17 Summary of the initial methane generation modeling results (Gi) for the work site areas Area/ Phase Footprint (m2) Waste in Place (tonnes) Years of Activity Average Methane Yield, Lₒ (m3 tonne-1) 2012 CH4 Generation (Gi),  (tonnes year-1) Area 2W 259,700 2,010,492  1990 - 1993 91.3 1,585 Area 2E 189,010 946,200  1994 - 1995 91.1 922 Area 3 140,550 1,366,288  1996 - 1998 86.7 1,547 Phase 1 242,261 4,470,903  1999 - 2008 77.0 7,798 Total 831,521 8,793,883   83.2 11,851  a) Area 2W (1990 – 1993) b) Area 2E (1994 – 1995)   c) Area 3 (1996 – 1998) d) Phase 1 (1999 – 2008)    Figure 3.19 Average historical waste composition for different areas of VLF 109   Figure 3.20 Total waste deposition rate in the four areas within the study boundary at VLF       Figure 3.21 Methane generation rates from different waste components at VLF  - 1 2 3 4 5 6 7 8 9 100.00.10.20.30.40.50.60.70.8Waste In Place (Millions Tonnes)Annual Tonnage (Millions Tonnes)110   Figure 3.22 Estimated landfill gas and methane generation rates at the work site  3.6 Discussion In order to conduct an initial comparison between the results of the new model with the popular models previously discussed in Section 1.4, the initial methane generation estimates achieved from the first run of the iModel-110©  were put against the results previously presented in Table 1.11. As shown in Table 3.18 below the initial results show higher methane capture efficiency for the Phase 1 of the VLF. The overestimation of the other models in comparison to the new model is obvious and mainly due the arbitrarily assigned modeling parameters, methane yields and reaction rates, in these models. However, the magnitude of the overestimation may vary from year to year (e.g. see BC MOE and iModel-110 for years 2012 and 2007).   - 1,000 2,000 3,000 4,000 5,00005,00010,00015,00020,00025,0001990199419982002200620102014201820222026203020342038204220462050205420582062206620702074207820822086209020942098LFG Flow Rate (scfm)Methane Generation Rate (tonnes year-1)YearEstimated Methane and LFG Generation Rates at VLFArea 2WArea 2EArea 3Phase 1 Research Boundary111  It is worth noting that the presented results in this chapter are the initial (raw) results and before calibration of the iModel-110©. Therefore, further discussion is presented in Chapter 7, where the new model is calibrated based on the field data and the final results are presented.   Table 3.18 Comparison between the iModel-110© initial results with the popular LFG generation models Methodologies CH4 Generation (tonnes year-1) Methane Yield, Lₒ (m3 tonne-1) Decay Rate, k (year -1) 2012 Collection Efficiency Current (2012) Peak (2007) Lifespan Total 1. LandGEM CAA 16,669 20,411  515,386  170 0.05 37% 2. Inventory 8,520 9,947  302,038  100 0.04 73% 3. IPCC 10,112 14,046  319,542  106 0.03-0.15 62% 4. Environment Canada 10,949 15,683  267,524  88 0.083 57% 5. Golder Associates 18,400 33,966  416,067  137 0.137 34% 6. BC MOE 11,198 15,783  300,360  99 0.02-0.11 56% 7. iModel-110 7,798 15,228  198,642  77 0.04-0.35 80%  112  Chapter  4: Fugitive Methane Emissions (E) 4.1 Introduction Methane (CH4) is an important GHG with a much shorter atmospheric lifetime (~10 years) in comparison with other greenhouse gases (Bogner and Matthews, 2003). Therefore, changes made to CH4 emission sources can affect the atmospheric concentrations on relatively shorter timescales. In Canada, about 3% of the 2010 national GHG emissions were reported to be from the waste sector, of which about 91% was attributed to fugitive methane emissions from landfills (Environment Canada, 2012a). With landfills being point sources of CH4 emissions, it would be easy to apply quantifiable mitigation measures. That includes capturing LFG for energy recovery and/or thermal or biological oxidation of methane which can significantly change the concluded methane budget of current inventory reports.   There have been significant technological improvements in the LFG collection and utilization industry since the first full-scale project was implemented in Palos Verdes, California, USA. in 1975 (Spokas et al., 2006). There are several regulatory requirements developed worldwide to monitor and reduce methane emissions from MSW landfills. Normally, landfills generating methane at levels higher than a defined threshold are required to capture the generated gas through active gas collection systems (GCS) and oxidize the collected methane via thermal combustion techniques. Such “regulated landfills” are also required to have a performance control and monitoring system in place to evaluate the effectiveness and efficiency of the active GCS. For example, landfill owners and/or operators in the US are required to conduct regular semi-quantitative assessments of the effectiveness of the GCS via monitoring of the landfill’s surface methane concentrations (SMC). This regulatory requirement was developed by the US-113  EPA under the Clean Air Act as New Source Performance Standards (NSPS) compliance to assess the performance of the GCS of the regulated landfills. Canadian officials in BC, however, require solid quantitative measurements of GCS collection efficiency. Such assessments require nearly 100% accurate LFG generation estimates or solid fugitive methane emission numbers, along with the captured gas quantity and quality.   The adopted approach for the present study also relied on reliable quantitative information about methane emission levels (E) at VLF. This information was required to integrate the right side of the simplified METRO© equation, allowing quantification of a necessary calibration factor to be applied to generation estimates (G) on the left side of the equation.  4.2 Fugitive Emission Measurement Techniques There are qualitative and quantitative methodologies to evaluate the efficiency of an LFG collection system. Qualitative approaches include visual observation of vegetation and/ or vegetation stress on the landfill cover, or measurement of near-ground methane concentrations. These techniques can provide valuable information about the performance of the closure and the GCS at the landfill and can identify major LFG emission “hot-spots”. However, quantification of emissions (i.e. methane flux) cannot be achieved through these methodologies.   There are also various quantitative methodologies to estimate the level of methane emission from landfills. These techniques identify hot-spots at the landfill surface and then quantify methane flux from those areas. Within these methodologies, the flux chamber technique is the most well-known and widely accepted approach allowing for relatively reliable quantification of methane 114  emissions at landfills. The flux chamber technique is the only “approved methodology” recognized internationally and suggested by various agencies including the US-EPA, the Australian EPA and the Wales Environment Agency.  Remote sensing techniques represent a more integrated approach for quantification of methane flux. These techniques have gained popularity in recent years. One of these techniques is the Radial Plume Mapping (RPM) methodology recognized by the US-EPA as “other test method 10 (OTM-10)” since July 200617 (USEPA, 2006). This technique uses optical remote sensing (ORS) instrumentation to characterize gas emissions from non-point sources. Some of these ORS instruments include; (i) Open-Path Fourier Transform Infrared (OP-FTIR) spectroscopy, (ii) Ultraviolet Differential Absorption Spectroscopy (UV-DOAS), and (iii) Open-Path Tunable Diode Laser Absorption Spectroscopy (OP-TDLAS) (USEPA, 2007).  The RPM techniques carry many advantages over the “close range measurement” methodologies, such as the flux chamber technique. However,  the relatively high cost of the RPM method, as well as the uncertainties associated with the possible effect of the methane plume buoyancy on the results, made the flux chamber methodology a more suitable option for the present research.   The required capital cost for the flux chamber technique is relatively low. However, the large footprint area of the work site (approximately 100 hectares for Areas 2w, 2E, 3 and Phase 1)                                                  17 See www.epa.gov/ttn/emc/tmethods.html  115  would considerably increase the required time and labour cost for the application of this method in this research project. Nevertheless, considering the availability of surface methane concentration (SMC) data, which was generated with collaboration of a third party hired by the COV, a unique approach was developed under this research allowing for quantification of the fugitive methane from the entire area at much lower cost in comparison with the above-mentioned conventional methods. This approach is fully explained in the following sections.   4.3 Surface Methane Concentration (SMC) Measurements at VLF During the course of the present study (2010-2011), the COV hired a consultant to conduct a methane surface scan of the entire landfill site. This is a routine exercise for large landfills in the US, and is conducted based on the US-EPA’s New Source Performance Standards (NSPS) for MSW landfills. In this technique, surface methane concentrations (SMC) are measured following the US-EPA’s “Method 21” procedure, which is developed for measurement of volatile organic compounds (VOC) (USEPA, 1999). Under NSPS compliance, the LFG flux is not directly measured. However, the semi-quantitative information of the SMC is used to evaluate the effectiveness of the landfill’s cover system and the LFG collection system in regulated landfills.    In order to conduct the present field survey, the site work (i.e. Areas 2W, 2E, 3 and Phase 1 of VLF) was divided into 101 measurement grids of about 1 hectare each as shown in Figure 4.1. Also shown in this figure, are the measurement grids and their IDs in different areas of the work site.   116   Figure 4.1 SMC measurement grids and IDs at the work site (VLF)  The SMC were measured using a Landtec SEM-500, a portable flame ionization detector (FID) shown in Figure 4.2.    Figure 4.2 Landtec SEM-500 (FID)  Area 2W  Area 2E  Area 3  Phase 1      117  The methane concentration levels were measured within 5 to 10 cm of the landfill surface along a pattern that traversed each grid at 10 meter intervals as shown in Figure 4.3.         Figure 4.3 VLF surface CH4 concentrations scan with FID (left), and Phase 1 measurement grids and scanned patterns (right)  For each grid, approximately 500 to 1000 data points were recorded to assess methane concentration at parts per million volume (ppmv) levels. The average of these readings formed a surface methane concentration number for each grid (SMCa) which was used to categorize the work site into 5 different methane emission level zones as presented in Table 4.1. As described in the following sections, an approach was developed to translate these qualitative (semi-quantitative) SMCa data to quantitative methane emission rates (MER) (i.e. methane flux) at VLF. This approach involved measurement of MER through application of the flux chamber Phase 1  118  technique in a selected number of grids from each emission zone (see Section 4.4) and finding a good correlation between the MER and the SMC data.  Table 4.1 Methane emission level zones and assigned average concentrations at VLF Codes Emission Zones Average Surface Methane Concentration Levels, SMCa (ppmv)  Zone 1 0 ppm < SMCa < 10 ppm  Zone 2 10 ppm < SMCa < 20 ppm  Zone 3 20 ppm < SMCa < 30 ppm  Zone 4 30 ppm < SMCa < 40 ppm  Zone 5 50 ppm < SMCa  The following illustration shows the work site boundary and the SMC survey grids which are colour coded based on the surface scan results.   Figure 4.4 Work site divided into 5 different emission zones based on the SMC data Note: Numbers in the grids represent the average SMC data for that grid 119  4.4 Flux Chamber The application of flux chambers in landfills is a well-established method to measure fugitive emissions from a soil surface through isolating and monitoring the emitting gas from soil. This technique has been used in several LFG emission monitoring studies for the measurement of methane emissions from a section of a landfill or to estimate total emissions from an MSW landfill  (Eklund, 1992; Mosher et al., 1999; Börjesson et al., 2001; Abichou et al., 2006a; Scheutz et al., 2009; Chanton et al., 2011b).  The flux chamber technique includes placing a closed chamber (box) on the landfill surface and monitoring the change of methane concentration in the box over time.  The rate of change in methane concentration in the chamber with time (∆C/∆t), chamber volume (V), and area (A) results in the methane flux emitted from landfill’s surface (Spokas et al., 2006).  Methane flux = V/A × (∆C/∆t) Equation 4.1  4.4.1 Dynamic and Static Flux Chambers There are two general groups of flux chambers known as dynamic and static chambers. A dynamic flux chamber utilizes a carrier gas (sweep air) that is directed through the chamber through an inlet and outlet pipe. Samples are then acquired from the outlet pipe, or directly from a sampling port, and the change in methane concentrations is used to calculate methane flux from the landfill surface to the chamber. It should be noted that the dynamic flux chamber method requires perfect sealing of the chamber edges. This time consuming step of the test is usually completed using a penetrated collar installed on the landfill surface (to which the chamber 120  connects) or the application of a bentonite seal around the chamber after placement at the point(s) of interest. Because of the complete isolation applied, the gas emissions from the landfill surface entering the chamber may cause pressure build-up within the chamber, which could result in a reduction in methane flux, and thus inaccurate readings. Therefore, this method uses a pressure gauge to monitor the pressure within the chamber and ensure it is equal to the ambient pressure levels by adjusting the sweep air flow rate. It is also usually recommended to use a fan inside the chamber in order to provide enough mixing of the gas before it is sampled. However, depending on the dimensions and design of the chamber, simply directing the air flow through the chamber may provide enough turbulence and mixing.  The second type of flux chamber is known as static flux chamber. The static flux chamber method does not involve the use of a carrier gas. Instead, a small hole in the chamber’s body is used to ensure that the pressure inside the chamber is maintained at atmospheric pressure levels. While it is recommended that the chamber be slightly pushed/penetrated into the soil, this method does not require the use of sealant for complete isolation. A fan is recommended inside the chamber to provide the necessary mixing of the gases. A portable gas analyzer can be used on site to measure real-time concentration of the gas of interest. Alternatively, gas samples could be stored in glass vials, Tedlar® bags, or steel canisters to be later analyzed in the laboratory.   The static flux chamber method can be completed in a matter of minutes. Consequently, it offers a relatively low-cost and low-tech solution for measurement of methane emission rates (MER) at MSW landfills. This has increased the attractiveness and popularity of the flux chamber 121  technique over other alternative fugitive emission measurement techniques. However, unlike air born techniques such as US-EPA’s OTM-10, it is possible that the flux chamber method underestimates the level of emissions due to possible leaks from cracks, the LFG collection system piping, and other infrastructure flaws.  Studies comparing these two methodologies are scarce, but available investigations have shown that the total fugitive CH4 emission flux measured by the flux chamber technique at MSW landfills represents approximately 66% of the total actual emissions at the site (Chanton, 2011). Therefore, in order to avoid underestimating actual methane emission levels at the work site, an emission correction factor (CFE) of CFE = 1.52 was applied to the result of the flux chamber field work conducted at VLF.  4.4.2 Field Work Procedure  The accuracy and reliability of fugitive emission measurement studies using the flux chamber technique depend on the number of tests (flux chambers) conducted in the area of interest (Klenbusch, 1986). The guideline originally developed by the US-EPA for “measurement of gaseous emission rates from land surfaces using an emission isolation flux chamber” (EPA/600/8-86/008) is commonly used world-wide to define the required number of flux chamber tests based on the footprint area of the site of interest.  This guideline suggests that, as a first step, the work site be divided into different zones based on the expected level of emissions. This initial “zoning” is suggested to maximize the between-zone variability while minimizing the within-zone variability in emission results (Klenbusch, 1986). Zoning can be done based on visual observations (e.g. poor vs. rich vegetation), physical properties (e.g. cover type), and design features (e.g. side slopes, crest, roads, etc.). Alternatively, if possible, results of a 122  preliminary site survey, similar to what was previously explained in Section 4.3, can be used to define different zones in the study site.  The next step is to determine the sample size (the required number of flux measurements) for each zone based on its size (area). The US-EPA guideline’s methodology to select the sample size is based on achieving a 95% confidence that the estimated emission rates are within 20% of the true value (Klenbusch, 1986). This methodology suggests the following equation used to calculate the total number of flux measurements (n) based on each zone’s footprint area:  ni = 6 + 0.15 × √Ai Equation 4.2 where:  ni = sample size (required number of flux measurements) in zone i to estimate methane emission rate from that zone with 95% confidence that the results are within 20% of the true value, and  Ai (m2) = footprint area of the zone i Furthermore, the guideline suggests that the zones with footprint area between 0.4 ha and 3.2 ha  be divided into 160 units (sub-grids), and flux measurements be randomly distributed within these units.   4.4.3 Modified Static Flux Chamber Measurements at VLF During the course of the present study, a static flux chamber was built and used to quantify methane emission rates (MER) from the different phases of VLF. The 100 mm tall chamber was 123  built using a 300 mm (12″) Diameter plexiglass cylinder with sharpened edges, allowing for easy penetration into the soil, as well as a plexiglass top. The chamber was equipped with a temperature probe port which was also used as a pressure relief port at the time of chamber placement on landfill’s surface. Two 1/4ʺ NPT quick-connect ports were also used for air recirculation and gas sampling. A portable LFG analyzer, Landtec GEM™ 2000+ was paired with the flux chamber. Connecting the inlet and outlet tubes of the GEM™ 2000+ to the chamber allowed for continuous monitoring of methane concentration at ± 0.1% resolution, while also allowing  mixing of the gas inside the chamber at the same time. The temperature probe linked to the GEM™ 2000+ instrument to monitor internal gas temperature ensures that methane density is adjusted for the actual temperature at the time of sampling. Figure 4.5 shows the flux chamber test set-up built and used in this study.   Figure 4.5 Flux Chamber and GEM™ 2000+ set-up  124  The sensitivity of the conventional flux chamber technique depends on the detection limit of the analytical method used in the test (Klenbusch, 1986). However, because the main purpose of the flux measurements in the present study was to find a correlation with the SMC data, it was preferred to deploy a portable and much quicker instrument (i.e. GEM™ 2000+) with relatively less sensitive measurements. With a maximum flux chamber test duration of 10 to 30 minutes, and the chamber volume of V = 0.007 m3, as well as the gas analyzer sensitivity of ± 0.1% CH4, the method overall detection limit was determined to be in the order of 3 to 10 g CH4 m-2 d-1.   Approximately 23 to 30 hectares of each defined emission zone at VLF were selected for flux chamber testing. This included 3 grids from each zone (15 grids in total), plus 1 grid from the “western 40” area of the Vancouver Landfill (Grid #11, with no LFG collection system in place) and 1 grid in Phase 1 with “suspiciously” high SMC results. The total footprint area of the selected grids was approximately 16 hectares, about 19% of the total footprint within the boundary of the study. Even though the within-zone variability was minimized by the preliminary SMC field survey, the distribution of the selected grids within each zone was set so that different possible features (e.g. access road, toe ditch, sloped vs. flat surfaces, vegetated vs. non-vegetated area, etc.) were included in the selected areas for the flux chamber survey. The minimum required number of flux measurements for each zone was determined based on Equation 4.2. Furthermore, in order to increase the accuracy of the flux chamber measurement results, instead of randomly distributing the sampling point over the entire area of each zone, all visually observable features would be sampled. For instance, if 10 flux measurements were to be made in a grid with total area consisting of 10% road, 60% side slope and 30% crest, total number of tests conducted in these three features were 1, 6 and 3, respectively. In some cases, 125  the total number of tests was increased to ensure that the distribution of the sampling locations in the zone of the interest resulted in estimates best representing the actual emissions in that zone. Figure 4.6 and Table 4.2 below present information about the selected grids, areas and number of flux measurements conducted.  Figure 4.6 Selected grids within the study boundary for flux chamber measurements at VLF Note: Selected grids are shown with black border lines. Numbers are avg. SMC data  Table 4.2 Selected grids for flux chamber test at VLF  Emission Zones Selected Grid IDs Footprint Area (m2) Number of Flux Measurements (n) Required Conducted  Zone 1 113, 135, 139 30,000 32 30  Zone 2 112, 151, 173 30,000 32 38  Zone 3 102, 158, 172 30,000 32 39  Zone 4 104, 146, 149 23,000 28 30  Zone 5 103, 147, 162 26,000 30 30  Others 11, 163 20,000 27 22 Total 159,000 181 189  126  A total of 189 flux chamber measurements were conducted in approximately six weeks, between June and July 2012. Depending on the rate of emissions at the sampling location, the duration of each chamber test was between 5 and 30 minutes. Where methane emissions were detected, methane concentration readings were plotted against time to calculate the rate of change in methane concentration over time (∆C/∆t). Figure 4.7 below illustrates an example of recorded methane concentration levels increasing over time. A graphical presentation of the entire flux chamber field readings are presented in Appendix D.1.  Figure 4.7 Example of recorded methane concentration levels inside the flux chamber increasing over time  The rate of change in methane concentration was then translated to methane emission rate (MER, g CH4 m-2 d-1) using the following equation:  MER (g CH4 m-2 d-1) = V/A × (∆C/∆t) × ρ Equation 4.3 Where:  MER = methane emission rate (methane flux)  V = chamber volume (~ 0.007 m3 depending on chamber penetration depth) y = 0.0042x + 0.0022R² = 0.99720.0%0.5%1.0%1.5%2.0%2.5%3.0%3.5%4.0%4.5%0 1 2 3 4 5 6 7 8 9 10Methane Concentration (%)Time (min)127   A = landfill’s surface covered by chamber (0.07 m2)  (∆C/∆t) = rate of change in methane concentration within chamber  ρ = methane density at the measured temperature within chamber (~ 680 – 710 g m-3) Out of the 189 flux chamber measurements, only about 60 non-zero readings were acquired and the rest were classified as no emission or below detection limit (BDL). The measured non-zero MER ranged between 17 and 4,709 g CH4 m-2 d-1 and are presented in the Appendix D.2.  Table 4.3 presents a summary of results for each grid compared with SMC data.  Table 4.3 Summary of MER resulted from the flux chamber survey at selected grids at VLF # Emission Zones Location at VLF Grid Number SMC (ppmv) MER (g m-2 day-1) Note  1 Other West 40 11 52.6 19.5  2 Zone 3 Area 2W 102 14.0 6.6  3 Zone 5 Area 2W 103 25.8 9.8  4* Zone 4 Area 2W 104 22.0 4.2 Very Steep Slope  5 Zone 2 Area 2W 112 7.8 3.5  6 Zone 1 Area 2W 113 3.9 2.8  7 Zone 1 Area 2E 135 3.6 0.7  8 Zone 1 Area 2E 139 3.6 2.4  9 Zone 4 Area 3 146 16.1 5.5  10 Zone 5 Area 3 147 39.6 12.5  11 Zone 4 Area 3 149 15.3 3.8  12 Zone 2 Area 3 151 5.9 4.9  13 Zone 3 Area 3 158 10.6 8.3  14* Zone 5 Phase 1 162 29.7 2.0 Toe Ditch was not accessible 15* Other Phase 1 163 258.8 46.2 open LFG well increased SMC results 16* Zone 3 Phase 1 172 10.8 0.0 New layer of soil cover was placed  before Flux Chamber Test started 17* Zone 2 Phase 1 173 9.1 0.0 * these grids were excluded from data analysis due to unreliable flux chamber survey conditions as noted above  128  4.5 Effect of Barometric Pressure on Methane Emission Rates Variations in the weather conditions, and in particular the barometric pressure (BP), has an impact on rate of methane fugitive emissions from landfill’s surface (Prosser, 1985; Young, 1990; Poulsen et al., 2003; Scharff et al., 2003; Gebert and Groengroeft, 2006). Higher emission rates at landfills are reported to occur at lower ambient pressures (Scharff et al., 2003; Gebert and Groengroeft, 2006). In general, variations in atmospheric pressure happen due to several factors including; (i) auto oscillation of air (reported to have an insignificant effect) , (ii) daily warming and cooling of air caused by solarization (causing diurnal variations), and (iii) passage of atmospheric pressure lows and highs (leading to long term variations). Therefore, short term (daily) and long term (seasonal) variations in atmospheric pressure should be taken into account when conducting methane fugitive emission measurements at a landfill site (Poulsen et al., 2003).  Young (1990), in a comprehensive study, showed that the rate of change in atmospheric pressure, and not the pressure itself, controls the gas flux intensity. That is perhaps due to the transient effect of gas storage in landfill void spaces, such that if the BP remains constant at a certain level the landfill pressure will reach an equilibrium state and the emission flux will reach a true value driven by the LFG generation rates.  In order to study and incorporate the effect of barometric pressure variations on methane emission rates at VLF, a HOBO® Smart Barometric Pressure data logger was installed at the site. The BP and ambient temperature (T) variations were recorded at high resolution (every 10 129  minutes) during the initial landfill surface scan, as well as at the time of the flux measurement field work. Figure 4.8 illustrates these records for one day as an example.  Figure 4.8 Recorded barometric pressure and temperature at the Vancouver Landfill (July 16, 2012)  As shown in the following Figure 4.9 and Figure 4.10, the recorded BP values were plotted against time, and the rate of change in atmospheric pressure (∆P/t) at the time of conducting the field work was calculated. Depending on variations in the weather conditions at the time of flux measurement, ∆P/t could have a positive or negative value recorded in millibars per hour (mbar/hr). Graphical presentations of the recorded BP and the rate of change during emission sampling (∆P/t) are presented in Appendix D.3.  130   Figure 4.9 Barometric pressure at the Vancouver Landfill (June 26, 2012)   Figure 4.10 Barometric pressure at Vancouver Landfill (July 16, 2012)   The accuracy of the measured MER would depend on the sign and the magnitude of ∆P/t, with an underestimated MER(s) for positive ∆P/t and overestimated MER(s) for negative ∆P/t. In order to evaluate the accuracy of the measured MER(s), as well as to study how the magnitude of the ∆P/t would affect the recorded MER(s), two sets of duplicate flux measurements were 131  conducted during this part of the field work. The first set included replicates of the flux measurement at the same location and same time. Ideally, these duplicates should have resulted in the same MER for both runs of the measurements. Results showed a relative standard deviation (RDS) (also known as coefficient of variation (CV)) of between 0.2% and 7.8%, confirming the accuracy of the measurement technique. Table 4.4 below summarizes the results of the first set of flux measurement duplicates.  Table 4.4 Flux measurement duplicates for accuracy of the test Chamber ID #71  #56  #35  #48  ∆P/t (mbar/hr) - 0.488 + 0.601 - 0.138 - 0.067 MER (g CH4 m2 d-1) Run#1 388.80 204.52 4709.27 796.75 Run#2 361.03 185.04 4698.58 890.00 Mean 374.9 194.8 4703.9 843.4 StDev 19.6 13.8 7.6 65.9 %CV 5.2% 7.1% 0.2% 7.8%  The second set of flux measurement duplicates included repeats of the test at the same locations but on a different day for each run. Therefore, for each of these locations (flux measurements) two MER values were developed, each subject to a different value of ΔP/t. The difference between the two recorded ΔP/t (i.e. |RΔP| = |(∆P/t)1 – (∆P/t)2|) values were plotted against the magnitude of the difference between the two MER values (i.e. |∆MER| = |MER2 - MER1)/MER1|), resulting in a very good correlation between the absolute values of RΔP and ∆MER with a coefficient of determination of R2 = 0.92.  Figure 4.11 shows this correlation illustrating the extent of drift in measured MER from the true value based on the magnitude of the ΔP/t at the time of the field measurement.  132    Figure 4.11 Correlation between rate of change in BP and adjusting multiplier for MER  The true value of MER at the landfill could be measured when the atmospheric pressure remained constant, causing an equilibrium condition between landfill and the surrounding environment. Therefore, all measured MER values were adjusted to the true values (MERa) based on the recorded ∆P/t at the time of sampling relative to the equalized condition  (i.e. ∆P/t = 0).   Therefore, when; (i) ∆P/t > 0 → R∆P > 0 and  MERa > MER  Based on the developed correlation, for R∆P > 0: (MERa – MER) / MER = 1.9731 × R∆P  Equation 4.4  y = 1.9731xR² = 0.91880.000.501.001.502.002.503.000 0.2 0.4 0.6 0.8 1 1.2Methane Emission Rate Multiplier|R∆P| (mbar/hr)133  hence;  MERa = MER × (1 + 1.9731 × ∆P/t) (for ∆P/t > 0) Equation 4.5 where; MERa = adjusted methane emission rate (g CH4 m2 d-1)  MER = measured methane emission rate via flux chamber (g CH4 m2 d-1)  ∆P/t = rate of change in barometric pressure at the time of flux measurement (mbar/hr)  When the atmospheric pressure at the time of sampling exhibited a declining trend (i.e. ∆P/t < 0), the measured MER was overestimated. That meant; (ii) ∆P/t < 0 → R∆P < 0 and  MERa < MER  therefore; (MER – MERa) / MER = 1.9731 × |R∆P| Equation 4.6  hence;  MERa = MER / (1 + 1.9731 × |∆P/t|) (for ∆P/t < 0) Equation 4.7  By combining Equations 4.5 and 4.7, the following equations were developed to calculate the adjusted MER (MERa) based on the magnitude and sign of the rate of change in atmospheric pressure at the time of flux measurements.  MERa = MER × (1 + 1.9731 × |∆P/t|) ^ (∆P/t /|∆P/t|) Equation 4.8 where (∆P/t /|∆P/t|) would be equal to (-1) or (+1), represent the sign of the ∆P/t.  134  Accordingly, all the flux measurement results were adjusted for the variations of the atmospheric pressure. Similar adjustments were made to the average SMC values for each measurement grid.   4.6 Results and Discussion Methane emission rates have been reported in several similar studies to span a wide range, depending on landfill type, waste age, cover soil type, climatic conditions etc.  Bogner and Spokas (1993), reported emission rates of between 319 and 1,896 g CH4 m-2 d-1. Chanton and Liptay (2000), reported emission rates of about 0 to 200 g CH4 m-2 d-1 in topsoil and 0 to 9,000 g CH4 m-2 d-1 in clay.    In the present study, flux chamber measurements showed methane emission rates varying between 0 and 4,709 g CH4 m-2 d-1. Most of the emissions were observed on side slopes and areas closer to the toe of closure phases. Out of a total of 17 grids initially selected at VLF for methane flux measurements, 5 grids were excluded from the data compilation and analyses (due to reasons noted in Table 4.3). Therefore, only 12 grids were deemed to have developed representative results and qualified to be compared with the surface methane concentration survey.   The average MERa for the five defined emission zones at VLF ranged from 1.96±1.12 g CH4 m2 d-1 to 11.14±1.87 g CH4 m2 d-1, relative to the SMCa values, which ranged between 3.70±0.21 ppmv and 32.70±9.77 ppmv CH4, respectively. Table 4.5 shows the average MERa, as well as the adjusted SMCa values for each emission zone.  135  Table 4.5 Methane flux measurement results and SMCa data for each emission zone Zones SMCa [CH4] (ppmv) MERa (g CH4 m-2 day-1) Zone 1 3.70 ± 0.21 1.96 ± 1.12 Zone 2 6.84 ± 1.32 4.22 ± 0.98 Zone 3 12.27 ± 2.38 7.44 ± 1.16 Zone 4 15.73 ± 0.55 4.67 ± 1.22 Zone 5 32.70 ± 9.77 11.14 ± 1.87 Grid#11 52.59 19.48  The average MERa for these grids ranged from 0.7 to 19.5 g CH4 m2 d-1, relative to the SMCa values, which ranged between 3.57 and 52.59 ppmv CH4, respectively. Figure 4.12 illustrates the methane flux and methane concentration for the 12 grids (approximately 11.4 ha) at VLF.   Figure 4.12 Averaged surface methane concentration (SMCa) and methane emission rate (MERa) for 12 measurement grids at VLF  01020304050600.05.010.015.020.025.011102103112113135139146147149151158Grid NumberSMCa(ppmv CH4)MERa(g m-2d-1 CH4)MERa SMCa136  As shown Figure 4.13, plotting the SMCa data against the MERa values showed a reasonable correlation between the measured methane fluxes and the qualitative methane concentrations. This correlation appears to be better at higher values.   Figure 4.13 Correlation between SMC and MER values developed over 12 measurement grids at the VLF  Data points shown in Figure 4.13 with ∆ represent the invalid data which were excluded from the analysis for the reasons previously noted in Table 4.3. Furthermore, the error of this developed linear regression was examined and the standard errors of the slope and y-intercept of the regression line were calculated at 95% confidence limit. Results of the error analysis are reflected in Table 4.6.   Based on this correlation; y = 0.3202x + 1.3867R² = 0.8990.05.010.015.020.025.00.00 10.00 20.00 30.00 40.00 50.00 60.00MER (g m-2d-1)SMC (ppm)137   MER = SMC × (0.32 ± 0.034) + (1.39 ± 0.755) Equation 4.9 where; MER = methane emission rate (g CH4 m2 d-1)  SMC = surface methane concentration (ppmv CH4)  The development of this correlation can be practically very important in the LFG management industry, saving time and money when full scale fugitive methane emission measurements are required. This correlation may be applicable in other landfills, however, it is recommended that it be re-developed or checked for landfills with different conditions. Depending on the size of each emission zone in a particular landfill, approximately 10 to 15 flux chamber tests per hectare will be required along with a full scale SMC scan. This correlation, once developed, would allow for a quick calculation of total landfill emission through a simple methane concentration scan at the surface of any MSW landfill.  4.7 Total Fugitive Methane Emission from the Vancouver Landfill  The Equation 4.10 presented below was developed to quantify the total methane emissions within the boundary of the study (E). This equation includes all of the above mentioned findings and assumptions, where the measured SMC data would be adjusted for the effect of the barometric pressure rate of change at the time of sampling and translated to the total methane flux based on the developed correlation, as well as the total area under the study. As discussed in Section 4.4.1, the emission correction factor was also applied to account for underestimations associated with flux measurements using flux chamber technique.  138    𝐄 =  𝐂𝐅𝐄 × ∑ (𝐀𝐢 × (𝐒𝐌𝐂𝐢 ×𝐧𝐢=𝟏 𝟎. 𝟑𝟐 + 𝟏. 𝟑𝟗) × 𝟑. 𝟔𝟓 × 𝟏𝟎−𝟒  Equation 4.10 Where: E = total annual methane emission from each area (tonnes/year)  CFE = 1.52, emission correction factor for flux chamber method (Chanton, 2011)  Ai = grid footprint area (m2)  SMCi = average surface methane concentration for each grid (ppmv CH4)  3.65 × 10-4 = unit conversion multiplier  The sum of grid emissions from each area/phase at VLF are summarized in Table 4.6, reported as the total fugitive methane emissions from that area. Results showed that the total average methane emission from Area 2W, Area 2E, Area 3, and Phase 1 of the VLF in the year of the study were 466, 252, 367, and 396 tonnes methane year-1, respectively. These results along with other field work results are utilized to calibrate the new model as presented in Chapter 7.  Fugitive methane emission results for all 102 grids of the VLF are provided in Appendix D.4.  Table 4.6 Total fugitive methane emissions from each area of the VLF Area/ Phase Number of Grids Total Footprint Area (m2) Total CH4 Emissions (tonnes year-1) (E) St. Dev. (∆E) Area 2W 30 259,700 466  ± 137 Area 2E 24 189,010 252  ± 90 Area 3 16 140,550 367  ± 86 Phase 1 32 242,261 396  ± 118 Total 102 831,521 1,481  ± 431   139  Chapter  5: Methane Oxidation in Cover Soil (O) 5.1 Introduction Methane oxidation in landfill cover soil reduces GHG emissions from landfills, and in some cases even reduces the atmospheric methane concentration (Hilger and Barlaz, 2007). A number of studies have reported methane oxidation fractions through landfill cover soil at 22% to 55% (Whalen et al., 1990; Chanton et al., 2009; Chanton et al., 2011b). Scharff et al. (2003), in a comprehensive study on four Dutch landfills with similar climatic conditions to those of Vancouver, measured the methane oxidation fraction at about 20% to 40%. USEPA (2004), also reported an average methane oxidation fraction of 10 to 25% with lower values for clay cover soils and higher rates for topsoil. However, due to the challenges of accurately measuring methane oxidation and lack of standard quantifying methods, they recommended a default value of 10% (USEPA, 2004). Despite recent findings, the IPCC has not deviated from the default values of 0-10% proposed in 1995 (Mahieu et al., 2006; Chanton et al., 2009).   Results of recent studies using more advanced methodologies have proven the effectiveness of methanotrophic bacteria in mitigating fugitive methane emissions from landfills (Powelson et al., 2006; Huber-Humer et al., 2008; Bogner et al., 2010; Chanton et al., 2011a). These advanced methodologies allow more accurate measurements of the amount of methane oxidization in landfill cover soil, another essential element in the METRO equation required for iModel-110©  calibration. One of the advanced methodologies for quantification of methane oxidation rate is the stable isotope technique. This technique is based upon the preference of methanotrophic bacteria to consume lighter isotope methane (12CH4) over heavier isotope methane (13CH4), 140  resulting in a shift in isotopic composition of  the LFG methane as it passes through landfill cover soil and is partially oxidized (Silverman and Oyama, 1968).  The field investigations described in this chapter were conducted to quantify methane oxidation (O) naturally occurring at the work site. The stable isotope technique, paired with the flux chamber measurements described in the previous chapter, were conducted at each area of the Vancouver Landfill and methane oxidation rates (in g CH4 m2- d-1) were quantified for the two different types of cover soils within the study boundaries.  Other useful outputs of this portion of the study included: (i) measurement of the isotopic signature of anaerobic methane in different areas/phases of VLF, (ii) development of isotopic fractionation factor for methane oxidation for each soil type, (iii) and investigations on the effects of soil moisture content and temperature on oxidation isotopic fraction factor.   5.2 Characteristics of Cover Soils at the Vancouver Landfill For this part of the study, the operational sub-areas/phases of VLF were grouped into two major areas of “Area A” and “Area B”. Half of Area A, which included Phase 1 of VLF, was covered by geomembrane cap and the other half with till as an interim cover with no or very poor vegetation. This area had active gas collection with system vacuum of 25 to 35 inches of water column (w.c.). Area B, which consisted of Area 2W, Area 2E, and Area 3, contained older municipal waste and was covered by organically modified till and a vegetation layer. This area also had an active gas collection system applying approximately 5 to 15 inches w.c. of vacuum.  141  The moisture and organic content of the cover soil samples, collected from Areas A and B, were determined following the “ASTM D2974 – 07a” standard test methods. The organic content of the cover soil in Area A was in the range of 1.5 to 2.2%, with field moisture contents of 7.8 to 9.7% (samples collected in early August and tested on the same day). Soil samples from Area B had organic contents between 5.4% and 6.8% and field moisture contents between 7.1% and 11.8%. Sample no.6 from Area B had a lower organic content of 3% and moisture content of 4.1%. This sample was collected from an area which appeared to be a new layer of impermeable soil placed on top of the old soil cover, and it was not believed to represent the whole area, hence was excluded from the final analysis. Results of the soil characteristics tests are presented in Section 5.4, Table 5.1.  5.3 Stable Isotope Technique The stable isotope technique is based upon the preference of methanotrophic bacteria to consume lighter isotope methane (12CH4) over heavier isotope methane (13CH4) resulting in a shift in isotopic composition of  the LFG methane as it passes through landfill cover soil and is partially oxidized (Silverman and Oyama, 1968). Isotope quantification was accomplished using a GCC-IRMS (Finnegan Mat Delta V-gas chromatograph combustion isotope ratio mass spectrometer) as described by Popp et al. (1995).    Mahieu et al. (2006) and De Visscher et al. (2004), suggested that the stable isotope technique is a conservative approach to quantify methane oxidation rates. Underestimation of methane oxidation using the stable isotope technique is partly due to the fact that in some areas of MSW landfills no trace of the isotope and enrichment of methane in 13C isotope content can be 142  measured due to the complete oxidation of methane in those areas. Another reason for it being considered conservative would be the isotope fractionation effect due to mass transfer (transport fractionation) which is normally disregarded. The transport fractionation effect can be correctly ignored in landfills with no active gas collection system (De Visscher et al., 2004).  During the course of the flux chamber field work, gas samples from the chamber were taken from one third of the non-zero chamber measurements, previously discussed and shown in Appendices D.1 and D.2. Based on the test procedure suggested by Chanton et al. (2011b), initial and final isotope samples were obtained during the flux chamber tests. These data are presented in Appendix E.1. Furthermore, a total number of ten methane samples from anaerobic zones of the landfill were collected directly from the gas collection system manifolds of each area/phase. Gas samples from the flux chamber and manifolds were acquired using 60 mL disposable syringes and immediately injected into 30 mL pre-evacuated glass vials. Figure 5.1 below shows the isotope sample acquisition steps.      Figure 5.1 Sampling procedure for the stable isotope tests  143   The isotope quantification test is an advanced and costly analysis and there are only a few laboratories in North America which are equipped with GCC-IRMS. Therefore, the isotope samples were shipped to the Department of Earth, Ocean and Atmospheric Science of the Florida State University (FSU) in order to quantify the isotope ratio (Rsample) of the methane samples (i.e. 13C/12C). The isotopic signatures of samples were then calculated using Equation 5.1 below (Coleman et al., 1981):  𝛅𝟏𝟑𝐂 = (𝐑𝐬𝐚𝐦𝐩𝐥𝐞𝐑𝐬𝐭𝐚𝐧𝐝𝐚𝐫𝐝− 𝟏) . 𝟏𝟎𝟎𝟎 ‰ Equation 5.1 Where:  δ13C = isotopic signature reported in parts per thousand (ppt)  Rsample = isotope ratio (13C/12C) of sampled methane  Rstandard = 13C/12C ratio of the reference standard (PeeDee belemnite (PDB) standard, 0.0112372)18  In this methodology, δ13C value of zero was assigned to the PDB standard which has a relatively high (13C enriched) isotopic signature resulting in negative δ13C values for most other naturally existing samples. Typical δ13C values for methane sampled from LFG collection systems (anaerobic methane) are reported to be in the order of -53 to -58‰ ± 1.5‰, with no significant                                                  18 The common reference for δ13C, the Chicago PDB Marine Carbonate Standard, was obtained from a Cretaceous marine fossil, Belemnitella americana, from the PeeDee formation in South Carolina. This material has a higher 13C/12C ratio than nearly all other natural carbon-based substances; for convenience it is assigned a δ13C value of zero, giving almost all other naturally-occurring samples negative δ values. 144  seasonal variations (Chanton et al., 1999; Chanton and Liptay, 2000; Börjesson et al., 2001; Chanton et al., 2011b). Chanton et al. (2011b), in a study involving 20 landfills across the U.S., concluded that the isotopic signature of anaerobic methane varied by region with an average value of -57.5 ± 1.5‰ for landfills in humid and cool climate regions.  A total of 38 flux chamber gas samples (residual methane), as well as 10 captured LFG samples (anaerobic methane) were analyzed. Residual methane samples were collected at the start (δ13i) and end (δ13f) of each chamber test, both with known methane concentrations, previously shown in Appendices D.1 and D.2. The 13C isotope content of residual methane for each chamber test was then calculated using Equation 5.2 below (Börjesson et al., 2001; Chanton et al., 2011b):  𝛅𝐑 = (𝛅𝐟× [𝐂𝐇𝟒]𝐟) − (𝛅𝐢× [𝐂𝐇𝟒]𝐢)[𝐂𝐇𝟒]𝐟 − [𝐂𝐇𝟒]𝐢 Equation 5.2 Where:  δR = 13C isotope content (δ13C value) of residual methane  [CH4]i = initial methane concentration in the flux chamber  [CH4]f = final methane concentration in the flux chamber δi = initial sample’s δ13C of methane  δf = final sample’s δ13C of methane   The oxidized fraction of methane at the location of each flux chamber test was then calculated using Equation 5.3 below (Blair et al., 1985; Liptay et al., 1998; Chanton and Liptay, 2000; Börjesson et al., 2001): 145   𝒇𝒐𝒙 =𝛅𝐑−𝛅𝐚𝟏𝟎𝟎𝟎 (𝛂𝐨𝐱−𝛂𝐭) Equation 5.3 Where:  fox = fraction of methane oxidized  δa = δ13C value for methane sampled from anaerobic zone of the landfill  αox = isotope fractionation factor due to oxidation (see Chapter 5.4)  αt = isotope fractionation factor due to transport (see Chapter 5.5)  5.4 Oxidation Fractionation Factor (αox) The oxidation isotope fractionation factor (αox) defines the preference of methanotrophs in consuming lighter isotope (i.e. 12CH4) over heavier isotopes (i.e. 13CH4). In fact, αox is a key factor in quantifying methane oxidation using the stable isotope technique. This parameter has been found to be different in different types of landfill cover soils and varies with seasonal climate change (Chanton and Liptay, 2000; Hilger and Barlaz, 2007; Chanton et al., 2008).   Factors affecting methane oxidation within a landfill cover include soil moisture content, organic content, temperature, and  pH (Chanton et al., 1999; Börjesson et al., 2001; Meraz et al., 2003) with temperature being the dominate factor (Czepiel et al., 1996; Chanton et al., 1999). Chanton et al. (1999) and Borjesson et al. (2001), reported the influence of variation in ambient temperature on methane oxidation rate in a landfill final cover. This is due to the effect of ambient temperature fluctuations on rates of enzymatic processes of methanotrophs.   146  Coleman et al. (1981), reported αox of 1.025 and 1.013 for 26°C and 11.5°C, respectively. King et al. (1989), observed similar patterns in the relationship between the temperature and isotope fractionation factor. Results of that study were αox of 1.027 and 1.014 for 14 and 4°C, respectively. Börjesson et al. (2001), determined αox for two temperatures of 4 and 25°C at two different landfills. The reported values were αox of 1.0270 ± 0.0039 and 1.0375 ± 0.0003 at 4°C and 1.0234 ± 0.0017 and 1.0281 ± 0.0009 at 25°C, both showing a decline in αox with a temperature increase. Chanton et al. (2008), also determined average αox values of 1.022 ± 0.0015 at 25°C that declined as the temperature increased. They showed that over the temperature range of 3°C to 35°C, αox decreases at a rate of about 0.04% for every 1°C increase in ambient temperature. Chanton and Liptay (2000), also showed that α inversely changed with temperature. While Tyler et al. (1994) showed increase in αox as a result of increased temperature at rates of 0.00043 to 0.00046/°C.  In the present study, five soil samples of the two different soil types present at VLF were taken and the isotope fractionation factor tests were conducted following the instructions provided by Chanton and Liptay (2000). Soil samples were collected from 10 cm to 15 cm below ground and incubated at two moisture levels of; (i) actual moisture content as collected (field moisture), and (ii) with added moisture. Exactly 100 g of each sample were placed in previously baked-out 1,000 mL Erlenmeyer flasks as shown in Figure 5.2. Flasks were sealed with septum/rubber corks and 50 mL of tank methane gas were injected into each flask, resulting in an initial methane concentration of approximately 4% to 5% (i.e. [CH4]0). Moisture and organic matter content of each soil sample were measured following ASTM D2974 – 07a standard test methods.  147       Figure 5.2 Soil sample moisture/organic content and incubation tests  Soil samples, collected from both Areas A and B, were incubated at the two moisture content levels of actual moisture content (field moisture) and increased moisture content. For the isotope fractionation factor test, the majority of the soil incubations were conducted at 25°C with two additional samples tested at 5°C. Soil sample characteristics, as well as the temperature at which each sample was incubated, are summarized in Table 5.1.    148  Table 5.1 Cover soil samples for incubation Major Areas Sample # ID. Temperature (°C) Moisture (%) Organic content (%) Area A 1 1a 25 7.7 1.5 1b 25 10.7 2 2a 25 9.7 2.2 Area B 3 3a 25 7.1 6.8 3b 25 11.8 4 4a  5 7.1 6.8 4b 5 11.8 5 5a 25 12.4 5.4 5b 25 16.0 6 6a 25 4.2 3.0 6b 25 14.0   Soil incubation was completed within two consecutive days, with several “soil gas samples” collected every 1 to 3 hours, depending on the observed rate of change in concentration.  Using a 50 μL gas tight syringe, samples were injected and analyzed with a gas chromatograph-flame ionization detector (GC-FID) to measure methane concentrations. When appropriate, 15 mL of the soil gas samples were injected into 10 mL pre-evacuated glass vials for δ13C measurements. As shown in Figure 5.3 (a) and (b), standard curves were developed during the test for methane concentrations of more than 1% and less than 1%, respectively. These standard curves were used to convert the FID responses to volumetric methane concentrations. Figure 5.4 shows example snap shots of the chromatograms, visual observation on the screen during the test which assisted collection of the isotope samples in appropriate times. 149   Figure 5.3 Standard curves developed during the GC-FID tests      Figure 5.4 A few FID test response snap shots  y = 571386x + 313.62R² = 0.999505,00010,00015,00020,00025,00030,00035,00040,00045,00050,0000% 2% 4% 6% 8% 10%Area (GC-FID Results)% CH4(a) Standard Curve for GC FID Results (for [CH4]>1%)y = 677368xR² = 105001,0001,5002,0002,5003,0003,5004,0004,5005,0005,5006,0000.0% 0.2% 0.4% 0.6% 0.8% 1.0%Area (GC-FID Results)% CH4(b) Standard Curve for GC FID Results (for [CH4]<1%)150  A total number of 78 soil gas samples with known methane concentrations were prepared and immediately shipped to the FSU for δ13C levels measurement. From the isotopic signature (δ13C) and the methane concentrations ([CH4]), αox was calculated using the Rayleigh approach as shown in Equation 5.4 below (De Visscher et al., 2004; Mahieu et al., 2006; Chanton et al., 2008): 𝛅𝟏𝟑𝐂𝐭+𝟏𝟎𝟎𝟎𝛅𝟏𝟑𝐂𝟎+𝟏𝟎𝟎𝟎= ([𝐂𝐇𝟒]𝐭[𝐂𝐇𝟒]𝟎)𝟏−𝛂𝐨𝐱𝛂𝐨𝐱 Equation 5.4 Where:  δ13Ct = 13C isotope content of enriched methane in soil incubation test in time t  δ13C0 = 13C isotope content of methane at the beginning of test (t=0)  [CH4]t = methane concentration in incubation flask at time t  [CH4]0 = initial methane concentration in incubation flask (t=0)  5.5 Transport Fractionation Factor (αt) The transport fractionation factor (αt) defines magnitude of the isotopic fractionation due to methane transport mechanism in landfill cover, advection vs. diffusion. Several similar studies have adopted the value of 1 for the transport isotope fractionation factor, suggesting that gas transport across the cover soil was dominated by advection rather than diffusion (Liptay et al., 1998; Chanton and Liptay, 2000). Although this may result in underestimation of the methane oxidation rate occurring in the landfill cover (De Visscher et al., 2004; Chanton et al., 2008), many researchers found it to be a reasonable assumption for landfills with no active gas collection system (Liptay et al., 1998; Chanton and Liptay, 2000; Abichou et al., 2006b; Stern et al., 2007; Bogner et al., 2010). This suggests that when LFG is being actively collected, αt would 151  be greater than 1 and closer to the value of fractionation factor due to diffusion (αdiffusion). This theoretical value is 1.0197 suggested by Marrero and Mason (1972) based on the difference between binary diffusion coefficient of 12CH4 and 13CH4 in air (i.e. 12CH4 diffuses 1.0197 times faster than 13CH4). An experiment by De Visscher et al. (2004), in a landfill in France with an active LFG collection system, resulted αt of 1.0178 ± 0.0009. Chanton et al. (2011a), in a four year study, used this value as a base and developed αt for 20 landfills across the U.S. Based on 155 samples, this study showed a mean value of αt =1.0106 ± 0.007 for landfills in cool and humid climate, based on 155 samples.  In the present study, although the LFG collection system vacuum was larger in Area A comparing with Area B, the fugitive emissions were observed in locations far from the LFG collection wells. These locations were beyond the usual radius of influence of the LFG wells (normally about 25m to 30 m) and believed to be less impacted by the high applied vacuum. Therefore, a value of 1.0106 was used for αt for both Areas A and B, in areas with active LFG collection system. For the grid# 11 in Western 40, as well as the areas where the collection system was shut down during the course of the field work, a value of αt =1 was adopted.   5.6 Results and Discussion As previously reported in Chapter 4, the flux chamber measurements showed methane emission rates varying from 0 to 4,709 g CH4 m-2 d-1 within the study boundaries. Averaging the results for the two major areas defined in the present chapter, showed mean values of 744 g CH4 m-2 d-1 and 489 g CH4 m-2 d-1 for Area A and Area B, respectively.  Median values for the two areas were 216 g CH4 m-2 d-1 and 396 g CH4 m-2 d-1, respectively.  152   5.6.1 Residual Methane The δ13C of the residual methane emitted into chambers ranged from -34.84‰ to -55.78‰. This value averaged -47.8±7.4‰ at area A with a median value of -48.8‰. At area B, the isotopic signature of the emitted methane averaged -49.7±2.4‰ with a median value of -50.1‰. The similarity of the mean and median is the result of a normal distribution for the isotope data as reported by Abichou et al. (2011). Methane emission rate (MER) and δ13C value of residual methane (δR) calculated with Equation 5.2 for each chamber are tabulated in Table 5.2 below.  Table 5.2 Methane emission rates (MER) and residual methane δ13C values Area Chamber ID. MER (g CH4 m-2 d-1) δR (‰) Area A 44 419 -53.07 47 37 -44.02 48 797 -46.88 108 18 -37.52 91A 256 -50.67 35 4709 -55.55 38 135 -54.47 300 760 -55.78 402 130 -34.84 406 175 -45.75 Area B 200 402 -51.87 205 1817 -52.60 214 444 -46.38 309 28 -47.48 114 82 -46.35 91B 302 -50.46 71 389 -50.79 78 528 -52.36 311 750 -49.83 62 148 -48.59   153  5.6.2 Anaerobic Methane Anaerobic methane samples collected from the LFG collection manifolds of each phase of VLF had δ13C values within ranges previously reported in similar studies (Chanton et al., 1999; Chanton and Liptay, 2000; Börjesson et al., 2001; Chanton et al., 2011b). However, there was a significant difference between the two areas averaging -54.12 ± 0.06‰ for older areas (Area B) and -58.19 ± 0.05‰ for Area A, the newer one. Differences between Areas A and B included: average waste age (7 vs. 15 years), depth of waste (30 vs. 10 m), and cover system (Area A is partially capped with geomembrane while the rest of the landfill is covered with an interim cover soil and topsoil). Also, as reported in Chapter 3, Phase 1 of VLF was much warmer in comparison with other areas of the landfill with an approximate average temperature of 46°C vs. 15-21°C in the older areas. (See Table 3.10 on Page 95).   Table 5.3 below summarizes the anaerobic methane δ13C value at VLF.  Table 5.3 Anaerobic methane δ13C value at the Vancouver Landfill Landfill Areas Methane Concentration [CH4], (%) Anaerobic Methane Isotopic Signature (δA), (ppt) Samples StDev. Average Area A Phase 1 43.2 -58.17 0.003 -58.19 ± 0.05 43.5 -58.21 0.067 Area B Area 2W 46.3 -54.23 0.058 -54.33 ± 0.05 46.4 -54.43 0.030 Area 2E 45.7 -54.05 0.036 -54.04 ± 0.03 45.9 -54.03 0.009 Area 3 50.6 -54.07 0.013 -53.97 ± 0.10 50.5 -53.88 0.137   154  5.6.3 Soil Incubation and Isotopic Fractionation Factor Soil incubations were conducted at different moisture contents and temperatures. The incubation tests started at methane concentrations between 4% and 4.5%, and continued for about 1.5 days or until the concentrations dropped below 0.5%. The soil gas methane concentrations are illustrated in Figure 5.5 through Figure 5.10. These results are also presented in full in Appendix E.2.   Figure 5.5, shows the incubation results for the soil sample collected from Area A (with a lower level of organic content). This test was conducted at two different soil moisture contents of 7.7% and 10.7%, labeled (1a) and (1b), respectively. Results for this sample, showed a higher level of methanotrophic activity for the test with the lower moisture content (i.e. 1a).   Figure 5.5 Methane concentrations during the soil incubation tests for soil sample collected from Area A with 1.5% organic content, incubated at 25°C at two moisture content levels of 7.7% (1a) and 10.7% (1b)  0%1%2%3%4%5%0:004:489:3614:2419:1224:0028:4833:36Methane Concentration (% Volume)Time (hh:mm)1a1bBlank 1155  Figure 5.6 below shows the results for the soil sample collected from Area B, which had a higher organic content of about 6.8%. This time an opposite behaviour was observed with a lower level of methanotrophic activity observed for the test with lower soil moisture content.  Figure 5.6 Methane concentrations during the soil incubation tests for soil sample collected from Area B with 6.8% organic content, Incubated at 25°C at two moisture content levels of 7.1% (3a) and 11.8% (3b)  The same soil sample acquired from Area B at the initial moisture content of 7.1% showed almost no methanotrophic activity at temperature equal to 5°C. However, at a moisture content of 11.8%, these activities proceeded at slightly higher rates in comparison with the same sample at the initial moisture content and at 25°C (see Figure 5.7 below). As the VLF is located in an area with daily average temperatures of 4 and 17 °C in winter and summer months respectively, as well as monthly precipitation of 151 and 45 mm during these two seasons, these results may suggest similar oxidation rates for wet winters as for dryer summers.    0%1%2%3%4%5%0:004:489:3614:2419:1224:0028:4833:36Methane Concentration (% Volume)Time (hh:mm)3a3bBlank 1156   Figure 5.7 Methane concentrations during the soil incubation tests for soil sample collected from Area B with 6.8% organic content, incubated at 5°C at two moisture content levels of 7.1% (4a) and 11.8% (4b)   Figure 5.8 Methane concentrations during the soil incubation tests for soil sample collected from Area A with 2.2% organic content and 9.7% moisture content (2a), incubated at 25°C  0%1%2%3%4%5%0:004:489:3614:2419:1224:0028:4833:36Methane Concentration (% Volume)Time (hh:mm)4a4bBlank 20%1%2%3%4%5%0:004:489:3614:2419:1224:0028:4833:36Methane Concentration (% Volume)Time (hh:mm)2aBlank 1157  Soil sample no.5 acquired from Area B, with a relatively high organic content of about 5.4% and field moisture content of about 12%, already had a high level of methanotrophic activity and adding more moisture to this soil sample did not significantly change the oxidation rate (See Figure 5.9 below).  Figure 5.9 E Methane concentrations during the soil incubation tests for soil sample collected from Area B with 5.4% organic content, incubated at 25°C at two moisture content levels of 12.4% (5a) and 16.0% (5b)  Soil sample no.6, with a relatively low organic and moisture content, did not show reasonable results (See Figure 5.10). This sample was taken from an area which appeared to be a new layer of impermeable soil recently placed on top of the old soil cover, and was not believed to represent the whole area, hence was excluded from the final analyses. 0%1%2%3%4%5%0:004:489:3614:2419:1224:0028:4833:36Methane Concentration (% Volume)Time (hh:mm)5a5bBlank 1158    Figure 5.10 Methane concentrations during the soil incubation tests for soil sample collected from Area B with 3.0% organic content, incubated at 25°C at two moisture content levels of 4.2% (6a) and 14.0% (6b). Results from incubation of this sample was excluded from the final analyses as the sample was not believed to represent the whole area.  The isotopic signature values of the soil gas samples, developed during the soil incubation tests, were quantified at the FSU. Figure 5.11 shows two examples of these results. The increase in methane δ13C over time indicates faster consumption of 12CH4 in comparison with 13CH4. This degree of preference of bacteria was translated to the oxidation isotopic fractionation factor (αox) using Equation 5.4.   As shown in Table 5.4, the αox value was calculated for every soil sample at different moisture levels and, for two samples, at two different temperatures. The averages of results for samples at field conditions (i.e. field moisture content and at 25°C) for Areas A and B were very close at values of 1.0265 ± 0.0010 and 1.0266 ± 0.0052, respectively.  0%1%2%3%4%5%0:004:489:3614:2419:1224:0028:4833:36Methane Concentration (% Volume)Time (hh:mm)6a6bBlank 1159   Figure 5.11 Soil gas samples methane isotopic signature  Table 5.4 Oxidation isotopic fractionation factor (αox) for different cover soil types at VLF Area Sample ID Temperature (°C) Moisture Content (%) Organic Content (%) fractionation factor (αox) A  1a 25 7.7 1.5 1.0266 ± 0.0012 1b 25 10.7 1.5 1.0222 ± 0.0034 2a 25 9.7 2.2 1.0264 ± 0.0008 B 3a 25 7.1 6.8 1.0298 ± 0.0044 3b 25 11.8 6.8 1.0231 ± 0.0023 4a 5 7.1 6.8 1.0185 ± 0.0058 4b 5 11.8 6.8 1.0104 ± 0.0019 5a 25 12.4 5.4 1.0234 ± 0.0059 5b 25 16.0 5.4 1.0194 ± 0.0006 6a 25 4.8 3.0 Excluded from calculations 6b 25 14.0 3.0 Average results at actual moisture and ambient temperature Area A 25 8.7 ± 1.4 1.9 ± 0.5 1.0265 ± 0.0010 Area B 25 9.7 ± 3.7 6.1 ± 1.0 1.0266 ± 0.0052  Similarly to the observations of Coleman et al. (1981), King et al. (1989) and Tyler et al. (1994), the present results showed an increase in αox as a result of increased temperature. As shown in Table 5.5 this increase was 0.00057/°C and 0.00064/°C for the soil samples with moisture contents of 7.1% and 11.8%, respectively. -40-35-30-25-20-15-100:004:489:3614:2419:1224:0028:4833:36Methane Isotopic Signatureδ13 C (‰)Time (hh:mm)3a (25°C)4b (5°C)160   Table 5.5 Effect of temperature on methane oxidation fractionation factor  Sample ID Soil Moisture (%) Temperature (°C) fractionation factor (αox) Rate (Δαox/ΔT) 3a 7.1 25 1.0298 ± 0.0044 + 0.00057 /°C 4a 7.1 5 1.0185 ± 0.0058 3b 11.8 25 1.0231 ± 0.0023 + 0.00064 /°C 4b 11.8 5 1.0104 ± 0.0019 Mean Value + 0.0006 /°C  An increase in the moisture content of the soil samples also resulted in decreased values for the isotopic fractionation factor in all cases. As shown in Table 6, for the tests conducted at a temperature of 25°C, this reduction was more significant in soil samples from Area A. However, the largest reduction rate in αox due to increased moisture content occurred at 5°C for the soil sample from Area B.   Table 5.6 Effect of soil moisture content on methane oxidation fractionation factor Source of Soil Sample Sample ID Temperature (°C) Soil Moisture (%) fractionation factor (αox) Rate (Δαox/ΔW) Area A 1a 25 7.7 1.0266 ± 0.0012 - 0.0015 1b 25 10.7 1.0222 ± 0.0034 Area B 5a 25 12.4 1.0234 ± 0.0059 - 0.0011 5b 25 16.0 1.0194 ± 0.0006 3a 25 7.1 1.0298 ± 0.0044 - 0.0014 3b 25 11.8 1.0231 ± 0.0023 4a 5 7.1 1.0185 ± 0.0058 - 0.0017 4b 5 11.8 1.0104 ± 0.0019  5.6.4 Fraction of Methane Oxidized (fox) Finally, the methane oxidation was calculated with Equation 5.3, which quantified the total amount of methane oxidized (O). The methane oxidation is the oxidized fraction (fox) of methane 161  that migrated through the cover soil and entered the flux chambers. Obviously, this number could be calculated only when smaller than 100%, or no residual methane would be left in the chamber to be sampled. The values of fox ranged between 3.4% to 72.7%, with average values of 33.7±21.6% and 27.9±14.9% for cover soil types used in Areas A and B, respectively. These values translate to average methane oxidation rates of 219 g CH4 m-2 d-1 and 141 g CH4 m-2 d-1 for the cover soil applied at these areas. These results are presented in Table 5.7.  Table 5.7 Fraction of methane oxidized in the Vancouver Landfill cover soil Areas Chamber ID δR  (‰) δa (‰) αox αt ** fox  (%) fox (avg.) (%) Rox (CH4) g m-2 d-1 Area A 44 -53.07 -53.97 1.0265 1.0000 3.4 33.7 219 47 -44.02 -53.97 1.0265 1.0000 37.6 48 -46.88 -53.97 1.0265 1.0000 26.8 108 -37.52 -53.97 1.0265 1.0000 62.1 91A -50.67 -58.19 1.0265 1.0106 47.3 35 -55.55 -58.19 1.0265 1.0106 17.5 38 -54.47 -58.19 1.0265 1.0106 23.4 300 -55.78 -58.19 1.0265 1.0106 15.1 402* -34.84 -54.12 1.0265 1.0000 72.7 406* -45.75 -54.12 1.0265 1.0000 31.6 Area B 200 -51.87 -54.33 1.0266 1.0106 15.4 27.9 141 205 -52.60 -54.33 1.0266 1.0106 10.8 214 -46.38 -54.33 1.0266 1.0106 49.7 309 -47.48 -54.33 1.0266 1.0106 42.8 114 -46.35 -54.04 1.0266 1.0106 48.1 91B -50.46 -54.04 1.0266 1.0106 22.4 71 -50.79 -53.97 1.0266 1.0106 19.9 78 -52.36 -53.97 1.0266 1.0106 10.1 311 -49.83 -53.97 1.0266 1.0106 25.9 62 -48.59 -53.97 1.0266 1.0106 33.7 * no LFG collection system in this section, therefore, average value of δa from other similar phases of the landfill was used in calculation for this Flux Chamber ** αt =1 was used for areas with no or shut-down active gas collation system    162  Methane emission rates (MER) measured by the flux chamber tests (see Table 5.2) were plotted against the methane oxidation percentages reported above. For ease of analysis, the rates of emissions were arbitrarily grouped to MER < 550 g CH4 m-2 d-1, and MER > 750 g CH4 m-2 d-1 (Figure 5.12(A) and Figure 5.12(B), respectively). For the lower emission rates, the oxidation rates increased with decreasing emission rates. This comparison showed that fox was an inverse function of MER as shown in Equation 5.5 below. This trend was similar to findings of studies done by Powelson et al. (2006), Huber-Humer et al. (2008), Chanton et al. (2011a), and Chanton et al. (2011b). For the locations with relatively higher emission rates, fox was found to be in the order of 10 to 25% with no obvious trend.  𝐟𝐨𝐱 (%) = 𝟓𝟏. 𝟏𝟗 − 𝟎. 𝟎𝟕 ×𝐌𝐄𝐑(𝐠 𝐂𝐇𝟒 𝐦−𝟐 𝐝−𝟏) Equation 5.5     Figure 5.12 Relationship between methane emission rates (MER) and fraction of methane oxidized (fox)  5.7 Total Methane Oxidation at the Vancouver Landfill The current analyses showed that 10% oxidation would be an appropriate minimum default value. However, the actual oxidation fraction in MSW landfills with active gas collection 0%10%20%30%40%50%60%70%80%0 100 200 300 400 500 600Fraction Oxidized (%)MER (g CH4 m-2 d-1)(A) for MER < 550 g CH4 m-2 d-1Area AArea B0%5%10%15%20%25%30%0 1000 2000 3000 4000 5000Fraction Oxidized (%)MER (g CH4 m-2 d-1)(B) for  MER > 750 g CH4 m-2 d-1𝑌(%) = 51.19 − 0.07𝑋 R2=0.39 163  systems in place could be much higher depending on methane emission rates (i.e. the methane loading rate applied to the landfill cover soil).   The results showed average methane oxidation rates of 219 g CH4 m-2 d-1 and 141 g CH4 m-2 d-1 for the cover soil applied at Areas A and B of VLF, respectively. This translates to methane oxidation percentages of 33.7% and 27.9% for these two areas. It is important to note that the methane oxidation rates should only be applied to the fugitive methane emissions from the landfill cover soil. Therefore, the possible methane leaks from cracks, the LFG collection system piping, and other infrastructure flaws, which were previously factored in by the emission correction factor (CFE), were excluded from calculations of the total methane oxidation (O) at VLF.   It should also be noted that, without the methanotrophic activity and methane oxidations, the measured methane emissions from VLF cover soil would have been higher than the amount determined by the flux chamber tests (i.e. E/CFE). The total amount of methane oxidized relative to the measured emissions would be: 𝐎 =𝐟𝐨𝐱 ×(𝐄𝐂𝐅𝐄)𝟏−𝐟𝐨𝐱   Equation 5.6 Where: O = total methane oxidized (tonnes/year)  fox = methane oxidation rate (%)  E = total methane emissions (tonnes/year)  CFE = emission correction factor (1.52)  164  Using Equation 5.6, the total amounts of methane oxidized in different areas of VLF were calculated and summarized in Table 5.8. Results showed that the total average methane oxidized in Area 2W, Area 2E, Area 3, and Phase 1 of the VLF in the year of the study were 119, 64, 94, and 133 tonnes methane year-1, respectively  Table 5.8 Total methane oxidation at each area of VLF Area/ Phase Total Avg. Methane Emissions (E) Methane  Emissions from Cover Soil (E/CFE) Methane Oxidation Rate, (fox) Total Methane Oxidized  (O ± ∆O) (tonnes year-1) (tonnes year-1) (%) (tonnes year-1) Area 2W 466 307 27.9 ± 14.9 119 ± 54 Area 2E 252 167 27.9 ± 14.9 64 ± 29 Area 3 367 242 27.9 ± 14.9 94 ± 42 Phase 1 396 261 33.7 ± 21.6 133 ± 72 Total 1,481 978  410 ± 197  In summary, the results of this portion of the study showed that the effectiveness of methanotrophic bacteria in mitigating fugitive methane emissions from landfills is significantly underestimated when the default value of 10% oxidation is used. The current analyses showed that while a 10% oxidation would be an appropriate minimum default value, the actual oxidation percentage in landfills with active gas collection systems could be much higher and dependent on methane emission rates. Using the correct and region-specific values will change the methane budget in GHG emission inventory reports.   In this chapter of the study, the O values for the four areas of the Vancouver Landfill were calculated. These values would be applied to the simplified METRO equation to calibrate the developed integrated LFG generation model.  165  Chapter  6: LFG Recovery at the Vancouver Landfill (R) 6.1 VLF Gas Collection System Operational Data As previously mentioned, the VLF landfill gas management system has been operating since 1991. The system includes (i) an LFG collection system (vertical and horizontal wells and piping network), (ii) a condensate handling system, (iii) an LFG extraction plant (blowers), and (iv) an LFG flare system.    The collection system is the main component of an LFG management system. It includes vertical gas extraction wells and horizontal gas collectors (trenches), as well as wellheads, lateral pipes, sub-header pipes, and a main gas header pipe. Based on the system design, waste depth, well spacing, and the required radius of influence (ROI) of the LFG wells, a minimum amount of vacuum at collection points (wellheads) is required to maintain an acceptable level of LFG collection efficiency, hence, minimal GHG emissions. However, excessive levels of vacuum applied to the system may result in air intrusion into the landfill, which increases the risk of spontaneous combustion and landfill fire (Sperling, 2009). Furthermore, when beneficial use of the collected LFG is intended, it is important to ensure that the quality of the collected gas (i.e. methane, nitrogen and oxygen content) is maintained within an acceptable range, dictated by the gas treatment facility/technology.   Therefore, the operation of an active LFG management system involves an extensive amount of field monitoring, wellfield adjustments, and wellfield data collection. Some of the information recorded as the LFG operational and gas quality data include: gas composition (% CH4, % CO2, % O2, balance gas, H2S (ppm), CO (ppm), gas temperature), operational data (wellhead’s % 166  opening, system pressure (vacuum), vacuum applied, gas flow rate), and system status (broken wells, leachate levels in the well, upcoming repairs, etc.).   For larger landfills, such as the Vancouver Landfill, with more than 250 data collection points just in the four areas within the study boundaries, the monthly readings would add up to more than 10,000 data points each year. These data were historically stored in various excel spread sheets as weekly and monthly readings. While the available historical LFG data provided an invaluable opportunity to study the VLF historical behavior and operational challenges, a better organization of these data was deemed necessary for data mining.  6.2 The Vancouver Landfill LFG Database As one of the initial steps of the study, the large amount of existing historical LFG collection system data had to be organized. A site-specific LFG database in Microsoft (MS) Access environment was developed for the VLF. The new data base allowed for the comprehensive and meaningful mining of the existing data. New gas collection data from the work site, including data from new wells generated during the course of the study, were incorporated into the data base. Figure 6.1 through Figure 6.5 below show example snapshots of the developed LFG database. As shown in the following examples, the database was designed to develop graphical and/or tabulated reports for selected parameters and the selected sampling/monitoring point. Data entry can be done line-by-line for each monitoring location and date/time, or could be imported all at once from an MS word table or an excel spread sheet. The stored data could also be exported as excel worksheets, if required.   167   Figure 6.1 The Vancouver Landfill LFG database   Figure 6.2 Graphical menu of the Vancouver Landfill LFG database 168       Figure 6.3 Example graphical outputs of the LFG database 169    Figure 6.4 LFG database data entry form  170   Figure 6.5 LFG database, an example tabulated output 171  6.3 Methane Recover Rate at the Vancouver Landfill (R) In order to calibrate the iModel-110© methane generation results with the simplified METRO equation, the amount of recovered methane (R) during the course of the field study was required. The data for 2012 were used for this purpose. Weekly data were collected from the sub-header sampling/flow meter stations of each area using a GEM™ 2000+. The recorded LFG flow rate, as well as the volumetric percentage of methane, was used to calculate the total tonnage of methane. Table 6.1 shows a few examples of the conducted wellfield readings where gas flow rate, methane, carbon dioxide, and oxygen content, along with other parameters such as CO and H2S levels, temperature, system pressure, etc. are indicated.  Due to the type of flow metering device used at the VLF gas collection system, reliable gas flow read out was not possible at all operational conditions.  Therefore, out of 65 attempts for each of the four study areas, 40, 35, 40, 49 valid R readings were achieved for Area 2W, Area 2E, Area 3, and Phase 1, respectively. Invalid flow rate readings were considered to be the recorded data at significant fluctuation (surging) of the system, and flow rates recorded in extreme operational conditions (system freeze-up, etc.). The valid recorded data are illustrated in Figure 6.6 and Figure 6.7 (a) through (d), and also are presented in Appendix F.1.   172  Table 6.1 Wellfield manifolds (sub-headers) reading examples Area Date CH4 (%v) CO2 (%v) O2 (%v) Measured Flow Q (cfm) Adjusted Q for 50% CH4 (scfm) Recovered Methane (R) (tonnes) Area 2W 30/06/2011 51.0 32.9 1.1 192 196 987 Area 2E 30/06/2011 50.1 32.6 0.7 214 214 1081 Area 3 30/06/2011 40.9 27.5 4.4 211 173 870 Phase 1 29/06/2011 53.1 38.1 0.3 1,086 1153 5815 Area 2W 21/07/2011 51.7 32.9 0.7 134 139 699 Area 2E 21/07/2011 53.5 31.1 0.6 -- -- No Data Area 3 21/07/2011 65.2 34.4 0.3 146 190 960 Phase 1 22/07/2011 54.0 37.9 0.4 1,139 1230 6202 Area 2W 28/07/2011 51.1 32.8 0.6 -- -- No Data Area 2E 28/07/2011 53.0 32.1 0.6 -- -- No Data Area 3 28/07/2011 65.2 34.4 0.3 -- -- 960 Phase 1 29/07/2011 53.3 37.9 0.5 1,249 1331 6713 Area 2W 05/08/2011 47.1 32.4 0.7 115 108 546 Area 2E 05/08/2011 49.9 31.2 0.6 117 117 589 Area 3 05/08/2011 47.3 29.2 3.1 113 107 539 Phase 1 05/08/2011 50.6 37.4 0.4 1,415 1432 7220 Area 2W 02/09/2011 48.5 33.0 0.6 162 157 792 Area 2E 02/09/2011 44.3 32.3 1.0 150 133 670 Area 3 02/09/2011 52.0 29.0 3.9 74 77 388 Phase 1 02/09/2011 48.8 37.5 0.5 1,459 1424 7179   Figure 6.6 Collected LFG flow rates from the four areas of VLF (adjusted for 50% CH4 content) 02004006008001,0001,2001,4001,600LFG Flow Rate (scfm)Area 2W Area 2E Area 3 Phase 1173      Figure 6.7 Captured LFG flow rates at VLF (flow rated are adjusted for 50% methane content)   As shown in the Appendix F.1. from the 65 attempts during the course of the field work to measure the collected LFG flow rates from the metering stations of each area/phase, only 35 to 49 valid flow readings were achieved, with only 27 events generating flow reading data for all four metering stations. The main reason for failing to read the gas flow rates in some of the events was the type of the flow meter that was installed on manifolds at VLF in the past. The COV is currently replacing all of these metering devices with a new type of flow meter. The fluctuation in the recorded flow rate values is due to the inaccuracy of the flow metering technique, operational field adjustments made to the manifolds, as well as a result of the 050100150200250300350400450500LFG Flow Rate (scfm) a) The Vancouver Landfill, Area 2W050100150200250300350400450500LFG Flow Rate (scfm) b) The Vancouver Landfill, Area 2E050100150200250300350400450500LFG Flow Rate (scfm) c) The Vancouver Lanndfill, Area 302004006008001,0001,2001,4001,600LFG Flow Rate (scfm) d) The Vancouver Landfill, Phase 1174  barometric pressure changes and its effect on the amount of methane being stored within the landfill’s pore spaces. These effects are temporary and are cancelled out over a long period of time. Therefore, averaging the values over a long period would result in a good and representative flow rate data recorded for each area.  Based on the collected data, the total LFG recovery within the study boundaries in 2012 was approximately 1,758 ± 151 scfm, which is equivalent to nearly 9,000 tonnes of methane captured annually.  Most of the captured methane was from Phase 1 with relatively newer waste, as well as greater amount of waste in place. Table 6.2 below presents the breakdown of the recovered methane for the four areas.   Table 6.2 Summary of methane recovery data for different areas of the work site Area Footprint (m2) Waste in Place (tonnes) Closure Year Average LFG Flow Rate  (scfm) Annual CH4 Recovery  (R ± ∆R)  (tonnes year-1) Area 2W 259,700 2,010,492  1994 157 ± 43 792 ± 217 Area 2E 189,010 946,200  1996 142 ± 38 716 ± 207 Area 3 140,550 1,366,288  1999 193 ± 73 973 ± 378 Phase 1 242,261 4,470,903  2009 1264 ± 112 6,373 ± 565 Total 831,521 8,793,883   1756 ± 151 8,853 ±761   175  Chapter  7: LFG Generation Modeling Calibration and Verification 7.1 Initial iModel-110© Verification The advanced LFG generation modeling verification was completed by conducting a methane mass balance under the simplified METRO equation. This would also allow for model calibration, which is described in the next section.  The results of the initial methane generation assessment (see Table 3.17), fugitive methane emissions (see Table 4.6), methane oxidation (see Table 5.8), and methane recovery data (see Table 6.2), were used in this analysis. A summary of the methane mass balance analyses, for the entire study boundary is presented in Table 7.1.  Table 7.1 Summary of filed data for the study boundary Source Field Data (tonnes CH4 year -1) Average Std. Dev. Emissions E 1,481 ± 431 Recovered R 8,853 ± 761 Oxidized O 410 ± 197 Total METRO 10,744 ± 1,390  According to the field data and based on the uncertainties associated with the measurement techniques, the total methane budget at the VLF in the year of the study was between 9,355 tonnes year-1 and 12,134 tonne year-1 of methane.  Comparison of the results of the new model for the year of the study with this filed data was conducted based on the Equation 7.1 below:  𝐆𝒊 = ∑ ∑ (𝟗𝟖𝟑. 𝟐𝟖𝟒𝟐 × 𝒌𝒋 ×𝑴𝒊𝒋 × 𝒘𝒋 ×𝑫𝑶𝑪𝒂𝒋 × 𝒆−𝒌𝒋×𝒕𝒊𝟓𝒋=𝟏 )𝒏𝒊=𝟏  = E + R + O ± (∆ERO)  Equation 7.1 176  Where the ∆ERO is the sum of uncertainties associated with the three different field works described in Chapter 4, 5, and 6.  Figure 7.1 illustrates the initial methane generation modeling results for the entire work site lifespan, as well as the collected field data for the year of the study (2012). As shown in this figure, the initial methane generation estimate (Gi) is slightly higher than actual field data (ERO). However, the modeling results lies within the range of the field data taking into account the uncertainties associated with these field work experiments (i.e. ERO ± ∆ERO).   Figure 7.1 Comparison of initial modeling results and field data (Gi vs METRO)  05001,0001,5002,0002,5003,0003,5004,0004,5005,00005,00010,00015,00020,00025,00019901993199619992002200520082011201420172020202320262029203220352038204120442047205020532056205920622065LFG Flow Rate (scfm)Methane Generation rate (tonnesyear-1)2012 Field Data (METRO)Methane Generation Rate∆ ERO177  Furthermore, this comparison for the four individual sites within the study boundary showed that the initial modelled methane generation rates (Gi) had approximately between -10% and +15% lack of fit with the field data. The average results for the study boundary showed an overestimation of 10.3% ± 11.8%. This suggested generation calibration factors (CFG) of between 0.87 and 1.12 for these sites, with an average value of CFG = 0.91 ± 0.12. A summary of the methane mass balance analyses for the four individual sites, as well as the associated calibration factors, are presented in Table 7.2.  Table 7.2 Initial methane generation modeling lack of fit and suggested generation calibration factors Area/ Phase Methane Emissions Methane Recovery Oxidized Methane initial Generation Assessment Initial Assessment Overestimation Correction Factors E R O Gi (Gi-∑ERO)/∑ERO CFG (tonnes) (tonnes) (tonnes) (tonnes) (%)   Area 2W 466 792 119           1,585  15.2% 0.87 Area 2E 252 716 64              922  -10.7% 1.12 Area 3 367 973 94           1,547  7.9% 0.93 Phase 1 396 6,373 133           7,798  13.0% 0.89          Average  10.3% 0.91         StDev. 11.8% 0.12   7.2 Uncertainties in the New Modeling Predictions A 10% lack of fit of the new model results with the average field data is relatively small and acceptable in the LFG industry. Nevertheless, it was tried to increase the accuracy of the predictions made by iModel-110 through calibration of the model based on the field data. Looking at Equation 3.5 and all the variables involved in development of the model’s 178  predictions, the values for DOCdry and k are the ones with a known range of uncertainties from which the default average values were selected and applied to the model. Based on the sensitivity analyses presented in the next Chapter, the extreme gas generation estimates (Upper Limit and Lower Limit) were identified. Sensitivity analyses showed that the maximum gas generation prediction in 2012 is achieved when the higher DOCdryH values (See Table 8.3) are used along with the lower ranges of kL values (See Table 8.5). Similarly, the lower gas generation prediction limit occurs when the lower DOCdryL with higher kH ranges are utilized.   Figure 7.2 illustrates these “extreme” Gi predictions for the work site, along with the initial gas generation estimates (Gi), as well as the field data (METRO) for 2012.   Figure 7.2 Upper limit and lower limit methane generation predictions for the study boundary 05001,0001,5002,0002,5003,0003,5004,0004,5005,00005,00010,00015,00020,00025,00019901993199619992002200520082011201420172020202320262029203220352038204120442047205020532056205920622065LFG Flow Rate (scfm)Methane Generation rate (tonnesyear-1)2012 Field Data (METRO)Initial Model Results (Gi)Maximum Gi for 2012 (Upper Limit)Minimum Gi for 2012 (Lower Limit)Gmax2012 = Gi + 26% Gmin2012 = Gi - 45% 179  7.3 iModel-110© Calibration There are two methods discussed here to calibrate the new model. Both of these methods involve fine tuning of the modeling parameters, more specifically, the DOCdry and k values. The default values for these parameters are selected from a range for each organic waste type. Fine-tuning the value of these parameters based on the field data is believed to further increase the accuracy of the new model methane generation predictions.   7.3.1 LFG Generation Calibration Factor (CFG) As discussed before, the CFG is a multiplier to the values of the DOCdry which have a direct relation with the final value of methane generation potential (methane yield). Therefore, application of CFG shifts the entire gas generation curve to fit the 2012 generation estimate to the 2012 field data.  As shown in Section 7.1, the average resulting generation correction factor from the field work was CFG = 0.91 ± 0.12. This average correction factor, and the deviation range, was incorporated into the model to develop lower range and higher range methane generation estimates for the work site.  The results of the calibrated model, using the average CFG, showed that the methane yield for Areas 2W, 2E, 3, and Phase 1 was respectively, 83, 83, 79, and 70 m3 CH4 per tonne of waste. Furthermore, the collection efficiencies of the active LFG collection systems in these areas were 55%, 86%, 69%, and 90%, respectively, with an overall collection efficiency of 82% within the study boundaries.  The calibrated methane generation estimates for each area, using the average calibration factor, as well as the lower range and the higher range of the methane generation estimates for the entire study boundaries, are illustrated in Figure 7.3. These results are also summarized in Table 7.3. 180    Figure 7.3 Methane generation modeling results with calibrated generation potential (CFG)  Table 7.3 Summary of the calibrated modeling results (using CFG) and the corresponding methane capture efficiency Area/ Phase Cover System Waste in Place Average Methane Yield 2012 Methane Generation Estimate Methane Capture Efficiency (tonnes)  (m3 tonne-1) (tonnes year-1)  (%) Area 2W Intermediate 2,010,492 83  1,437 55 70 ± 15 Area 2E Intermediate 946,200 83  836 86 Area 3 Intermediate 1,366,288 79  1,402 69 Phase 1 Final Cover 4,470,903 70  7,069 90 Total  8,793,883 76 10,744 82  Based on the calibrated model using the generation calibration factor (CFG) the average methane collection efficiency for areas with an intermediate cover system (i.e. Areas 2W, 2E, and 3) was  - 1,000 2,000 3,000 4,000 5,00005,00010,00015,00020,00025,000199019931996199920022005200820112014201720202023202620292032203520382041204420472050205320562059LFG Flow Rate (scfm)Methane Generation Rate (tonnes year-1)YearArea 2WArea 2EArea 3Phase 1 Research Boundary (Average) Research Boundary (Lower Range) Research Boundary (Higher Range)181  70% ± 15%. The modeling results and the historical methane recovery data for Phase 1 showed that the methane capture efficiency in this phase, before installation of the geomembrane cap, was approximately 65% to 70%. However, this capture efficiency has increased to approximately 80% to 90% since 2009, due to the installation of the geomembrane cap and the modifications made to the LFG collection system. These capture efficiency values are in good agreement with what Spokas et al. (2006) and SCS Engineers (2009), reported for the capture efficiencies for active LFG collection systems. Results of the comprehensive study by Spokas et al. (2006), which are used as the default values for the guidelines by the French environment agency (ADEME), showed collection efficiencies of: 35% for an active (operating) phase, 65% for phases covered with a temporary cap, 85% for phases covered with an impermeable (clay) cover soil, and 90% for phases covered with a geomembrane final cover. SCS Engineers (2009), in a study conducted at the national level in the U.S. for the Solid Waste Industry for Climate Solutions (SWICS), concluded that the methane collection efficiency at regulated sites in the US landfills, where the best LFG management practices were applied, were  between 75% and 95%. Accordingly, for landfills with an active LFG collection system, the SWICS has adopted its GHG reporting rule based on the methane capture efficiencies of: 95% for areas with final cover, 75% for areas with intermediate cover, and 60% for areas that have a daily cover system in place.  7.3.2 Revised iModel-110© Verification In order to verify the results of the calibrated model, methane generation rates from the Phase 2 of the Vancouver Landfill were estimated using the iModel-110© over the defined range for the generation calibration factor. As shown in Table 2.3, this phase has received approximately 3.5 182  million tonnes of waste within the two operational periods of 1982-1985 and 2006-2009. Based on the available data, three different waste compositions were applicable to these periods. These data were applied to the model to estimate the methane yield value for this phase. Furthermore, the available SMC data for this phase were expressed in terms of the total amount of methane emission (E) from the area. A conservative oxidation efficiency of 28% was used to estimate the total methane oxidation. Also, the average collected LFG flow rate, adjusted for 50% methane content, was used to estimate the methane recovery (R).   The modeling results for the Phase 2 of the VLF showed a methane generation rate between 6,509 tonnes year-1 and 8,419 tonnes year-1, with an average value of 7,464 tonnes year-1. These values show the lower range and higher range for the generation estimate, which results from using the CFG range, which was previously developed over the areas within the study boundaries. Furthermore, the total methane emission, the total amount of recovered methane, and the total amount of oxidized methane for this phase was, 3,123 tonnes year-1, 3,529 tonnes year-1, and 798 tonnes year-1, respectively. Therefore, the total mass of methane calculated from the simplified METRO was approximately 7,450 tonnes year-1, which was very close to the field data and within ±13% of the higher range and the lower range of the model predictions. The results suggested that the methane capture efficiency for this phase of the VLF ranged between 42% and 54%.  Phase 2 had an intermediate cover system and horizontal LFG collectors at the time of the analyses.   183  7.3.3 LFG Generation Rates Calibration Factor (CFk) In this method, the value of the decay rates for different organic waste types were calibrated based on the results of the field work as well as the sensitivity analyses presented in the next chapter. This approach is somewhat similar to what is achieved through conducting a LFG pump test.  The LFG pump test is a standard approach developed by the US EPA (EPA – Method 2e) to define site specific LFG modeling parameters. In this method the methane generation potential is selected based on the best knowledge about the site, and a site specific k value is calculated based on the volume of methane extracted from a known volume of organic waste.   This approach was followed to calibrate the value of the decay rates for the work site based on the comprehensive field investigations data and considering that methane generation potential was estimated based on good quality data available for the VLF. The initial decay rate values were initially selected from literature and based on the average of the suggest half-lives range for each organic waste type (See Table 3.15). Calibration of the values was conducted based on the results of the sensitivity analysis illustrated in Figure 8.2.  Table 7.4 presents the range, default, and calibrated decay rate values for different types of organic waste at the VLF.  Table 7.4 Calibrated decay rate values for different organic wastes at the VLF Waste Components Decay Rate Values (k, year-1) Range Default Calibrated Food waste 0.23 0.69 0.35 0.455 Garden 0.10 0.23 0.14 0.182 Paper 0.05 0.14 0.07 0.063 Wood and straw 0.03 0.05 0.04 0.032 Textiles 0.05 0.14 0.07 0.063 Disposable nappies 0.05 0.14 0.07 0.063 184   The calibrated model, using the calibrated decay rates, showed a slightly higher methane generation results in comparison to the initial generation estimates (Gi).  Comparing the results of the calibrated model with the results derived from application of the lower range and the higher range CFG to Gi, showed that the calibrated predictions lies within the previous methane generation estimation range.  The calibrated methane generation estimates for each area and the entire work site as well as the values based on the lower range and the higher range CFG are illustrated in Figure 7.4Figure 7.3   Figure 7.4 Modeling results with calibrated k values in comparison to the results with lower and higher CFG   - 1,000 2,000 3,000 4,000 5,00005,00010,00015,00020,00025,000199019931996199920022005200820112014201720202023202620292032203520382041204420472050205320562059LFG Flow Rate (scfm)Methane Generation Rate (tonnes year-1)YearArea 2W (Calibrated Model)Area 2E (Calibrated Model)Area 3 (Calibrated Model)Phase 1 (Calibrated Model) Research Boundary (Calibrated k) Research Boundary (Lower Range CFG) Research Boundary (Higher Range CFG)185  As expected, calibrating the decay rate had no effect on the methane generation potential values.  Therefore, according to the calibrated model, the methane yield values for Areas 2W, 2E, 3, and Phase 1 of the VLF was respectively, 91, 91, 87, and 77 m3 CH4 per tonne of waste. Furthermore, the collection efficiencies of the active LFG collection systems in these areas were 50%, 80%, 67%, and 93%, respectively, with an overall collection efficiency of 82% within the study boundaries. These results are also summarized in Table 7.5.   Table 7.5 Summary of the calibrated modeling results (using CFk) and the corresponding methane capture efficiency Area/ Phase Cover System Waste in Place Average Methane Yield 2012 Methane Generation Estimate Methane Capture Efficiency (tonnes)  (m3 tonne-1) (tonnes year-1)  (%) Area 2W Intermediate 2,010,492 91  1,568 50 66 ± 15 Area 2E Intermediate 946,200 91  890 80 Area 3 Intermediate 1,366,288 87  1,455 67 Phase 1 Final Cover 4,470,903 77  6,886 93 Total  8,793,883 83 10,798 82  Based on the calibrated model using the decay rate calibration factor (CFk) the average methane collection efficiency for areas with an intermediate cover system (i.e. Areas 2W, 2E, and 3) was 66% ± 15%. The calibrated model also showed that the methane capture efficiency in Phase 1 of the VLF was 93% in the year of the study. This value for the entire study boundary was 82% in 2012.  186  7.4 Methane Generation Estimates for the Entire Vancouver Landfill The new model was run for the entire Vancouver Landfill site, including the MSW and DLC waste disposal activities between 1967 and 2011. Furthermore, the methane generation assessment was conducted using the BC MOE Tool, where the refined waste composition information was used for both models. The iModel-110© was run for three scenarios: Scenarios A1 and A2, respectively using the lower range and the higher range CFG (i.e. CFG.L = 0.7906, and CFG.H = 1.0226), and Scenario A3 based on the CFG = 1 and utilization of the calibrated values of the decay rates. The BC MOE Tool was also run for two scenarios: Scenario B1, based on the entire amount of waste that was historically deposited at the site, and Scenario B2, based on the MOE recommendation, considering the waste mass that has deposited during only the past 30 years.   Based on the results achieved from the calibrated iModel-110©, the average methane yield for the entire VLF ranged between 68 and 89 m3 CH4 per tonne of waste, while the MOE Tool used a higher value of 102 m3 CH4 per tonne of waste. This translates to 15% to 49% overestimation of the BC MOE Model in comparison to the methane generation prediction range achieved by the new model. Consequently, the resulting methane capture efficiency for the entire VLF in 2012, based on the new model lower range and the higher range estimates, was between 79% and 61%.  Whereas, the MOE Tool concluded collection efficiencies of 53% and 55%, based on the Scenarios B1 and B2, respectively.  The modeling results for the entire VLF site based on the five scenarios are illustrated in Figure 7.5. Results are also summarized Table 7.6. 187   Figure 7.5 Methane generation and LFG flow rate estimates for the entire Vancouver Landfill site (for the disposal activities until end of 2011)  Table 7.6 Methane generation modeling results for the VLF using the iModel-110© and the MOE Tool Scenarios Average Methane Yield*  Lₒ (m3 tonne-1) 2012  Generation Estimates 2012 Capture Efficiency** CH4  (tonnes year-1)   LFG  (scfm) Sc. A1 - iModel-110 (Lower Range CFG)  68  23,546 4,670 79% Sc. A2 - iModel-110 (Higher Range CFG)  89  30,456 6,041 61% Sc. A3 - iModel-110 (Calibrated k)  86  29,159 5,784 64% Sc. B1 - MOE Tool (Lifespan)  102  35,064 6,955 53% Sc. B2 - MOE Tool (30 year disposal)   102  34,107 6,765 55% *  Calculated based on the lifespan methane generation and the tonnage of waste in place **  Based on ~3,700 scfm collected LFG flow rate during spring 2012, adjusted for 50% methane content  01,0002,0003,0004,0005,0006,0007,0008,00005,00010,00015,00020,00025,00030,00035,00040,0001967197119751979198319871991199519992003200720112015201920232027203120352039204320472051205520592063206720712075LFG Flow Rate (scfm)Methane Generation Rate (tonnes year-1)YearSc. A1 - iModel-110 (Lower Range CFG) Sc. B1 - MOE Tool (Lifespan)Sc. A2 - iModel-110 (Higher Range CFG) Sc. B2 - MOE Tool (30 year)Sc. A3 - iModel-110 (CFk)188  Furthermore, in order to compare the new model predictions to the popular models previously discussed in Chapter 1, the iModel-110© was run for the VLF Phase 1. The modeling was conducted using the lower limit and higher limit CFG, as well as using the calibrated decay rates. The methane generation estimates obtained from the six different methodologies previously discussed in Chapter 1, along with the new model predictions are illustrated in Figure 7.6.   Figure 7.6 Comparison of the new model predictions with other six popular LFG generation models  - 5,000 10,000 15,000 20,000 25,000 30,000 35,00019992003200720112015201920232027203120352039204320472051205520592063206720712075207920832087209120952099Methane Generation Rate (tonnes year-1)YearsGolder AssociateEnvironment CanadaLandGEM CAALandGEM InventoryIPCC FODBC MOE TooliModel-110 (Higher Limit)iModel-110 (Lower Limit)iModel-110 (Calibrated k)189  Chapter  8: Landfill Gas Modeling Uncertainties and Sensitivity Analysis 8.1 Introduction Given the heterogeneity of landfills, field measurement inaccuracies, discrepancies between the “selected” values for some parameters vs. their “true” values, and the variety of design and operational conditions between landfills, uncertainty in a LFG generation assessment is unavoidable. These “modeling errors” are mainly associated with a lack of reliable historical records regarding disposal tonnages, measurement inaccuracies, as well as lack of an advanced procedure for selection of site-specific modeling parameters, methane yield (L˳, m3 CH4 tonne-1), and methane generation rate (k, year-1). Many studies have compared limited site-specific field data with modeled results, concluding an overestimation of the theoretical assessments (Vogt and Augenstein, 1997; Spokas et al., 2006). Nevertheless, the magnitude of modeling errors has rarely been quantified in large scale for any of the existing models.   One of the main objectives of the present study was to use the results of many well-established research studies as fundamental grounds for the purpose of reducing modeling uncertainties through the selection of more meaningful and site-specific modeling parameters. Furthermore, several field investigations were carried out to conduct a full scale methane mass balance in four separate areas of the Vancouver landfill, based on the concept of the METRO equation, and the field data with regard to methane recovery and all other possible pathways. Therefore, the modeling error was further reduced by application of the developed calibration factors, CFG and CFk, to the site-specific L˳ and k values, respectively. However, two main sources of uncertainty remain, which may create discrepancies between the model predictions and the field data.   190  These two uncertainty groups are: (i) modeling errors and (ii) calibration errors, which are discussed in this chapter.   8.2 LFG Modeling Errors Due to Input Parameters Uncertainties (Gi-Err) The modeling errors are sourced from the input data and the modeling parameters. Reported waste disposal tonnages, composition, and as-received moisture content are the main sources of uncertainty in this category. These values are translated to the available DOC in the landfill and ultimately to methane yield (L˳) and uncertainty in these parameters will eventually result in modeling errors and uncertainties in the estimation of the total methane generation throughout the landfill’s lifespan. Error in the decay rate, however, only affects the distribution of the generated methane throughout the landfill’s lifespan.   In general, variables contributing to the uncertainty in methane yield or the total amount of methane generation include: (i) waste disposal rate, (ii) waste composition, (iii) waste moisture content,  (iv) DOC content, and (v) degradability of DOC. As discussed in Section 1.4, the suggested methane yield in different LFG generation models for VLF varied between 88 and 170 m3 methane per tonne of waste.  The IPCC FOD, as the most sophisticated methodology amongst them, calculates the L˳ value based on the DOC content of 191  wet components of the waste, as well as a constant decomposable fraction of 0.5 for all the waste components.   As described in Section 3.2, development of a variable value for L˳, suggested in iModel-110©, minimized the modeling errors to some extent. The variable L˳ values were developed based on the weighed data at VLF, moisture content of the waste component as received at the disposal facility, DOCdry content associated with each organic material, and the actual waste composition physical analysis data, generated by Metro Vancouver since 1991 (See Table 2.4). Furthermore, instead of using the constant decomposable fraction of 0.5, suggested by IPCC (2006), various values for different types of organic material were introduced based on degradability and bio-availability of the materials in the landfill. Nevertheless, one of the major uncertainty sources for L˳ relates to the uncertainty range given for values of DOCdry for different waste components (see Table 3.1). These uncertainty ranges, suggested based on the maximum and minimum values developed by well-established and widely accepted research studies, result in an uncertainty in methane generation estimates ((Gi-Err)DOC).   Table 8.1 Low and high DOCdry values for different organic wastes deposited at VLF Organic Wastes DOCdry (%) Lower Range Higher Range Paper and Cardboard 40 50 Textiles and Nappies 25 50 Food waste 20 50 Wood waste 46 54 Yard waste 45 55  As shown in Table 8.1, the values for most of the organics have a narrow range (mean±10%). Food waste and textiles have the highest variability with lower range and higher range within 192  ±40% of the default value.  Nevertheless, to conduct a sensitivity analysis, effect of up to 50% variation in the default DOCdry values on the model predictions was studied. As illustrated in Figure 8.1, variations in DOCdry value of paper waste had the highest effect in model predictions for 2012. However, considering the range of this value (DOCdry paper = 0.45 ± 11%), the actual effect of variation of this value within the range was about 5% of the 2012 methane generation prediction. This effect was similar for textile and food waste respectively with maximum of 42% and 39% variation in the DOC value, resulting in approximately 5% variation in the 2012 methane generation predictions.    Figure 8.1 Sensitivity analysis, ∆DOC vs. ∆CH4 (methane generation estimate for 2012)  The DOC bio-availability discount factors are also parameters related to possible uncertainty in methane generation estimates (Gi-Err)∑d. These parameters are considered to account for operational, climatic, and design conditions which cause the landfill environment to drift from -25%-20%-15%-10%-5%0%5%10%15%20%25%-50% -40% -30% -20% -10% 0% 10% 20% 30% 40% 50%∆ DOC(%)∆ CH4 (%), 2012Food waste (±39%)Yard waste (±10%)Paper (±11%)Wood waste (±8%)Textiles (±42%)Disposable nappies (±42%)193  one that is optimal for anaerobic biodegradation. (Gi-Err)DOC and (Gi-Err)∑d are further discussed in Section 8.2.1 below.  Furthermore, to increase the modeling accuracy, given the actual environmental conditions provided for the anaerobic bacterial activity within VLF, the use of different decay rates for six different types of organic materials were suggested. The field investigations, previously discussed in Section 3.3.1, showed that the temperate climatic condition of Vancouver does not affect the landfill temperature and the decomposition reaction rates. Therefore, the half-lives of organic materials suggested by well-established research studies were used to define more accurate values for decay rates. These values were the average values from the suggested ranges for the half-lives of different organic materials. Table 8.2 presents the ranges of half-lives and the associated decay rates selected for VLF, with an explanation that the lower k values correspond to the longer half-lives.   Table 8.2 Low and high ranges of half-lives and decay rates for different organic wastes at VLF Waste Components Half-life (year)  decay rates  (k, year -1) Low High Low High Food Waste 1 3 0.23 0.69 Yard Waste 3 7 0.10 0.23 Paper and Textile 5 15 0.05 0.14 Wood Waste 15 20 0.03 0.05  With a similar approach explained above, a sensitivity analysis for the decay rates was conducted and the effect of up to 50% variation in the default k values on the model predictions was studied. As illustrated in Figure 8.2, variations in k value of food waste had the highest effect in 194  model predictions for 2012. The analysis showed that if the k value assigned to food waste is smaller than the “true” value for this parameter, this can result in more than 10% overestimation of the model prediction. Result of this analysis was utilized as a basis to calibrate the decay rate values for the new model based on the field data collected over the four sites within the study boundary.    Figure 8.2 Sensitivity analysis, ∆k vs. ∆CH4 (methane generation estimate for 2012)  The uncertainty in methane generation estimates resulting from the uncertainty ranges ((Gi-Err)k) are further discussed in Section 8.2.2.  8.2.1 LFG Modeling Errors Due to DOC Uncertainty Range (Gi-Err)DOC A sensitivity analysis was performed on the effect of the uncertainty range for the DOCdry values by re-running the model for the entire work site. The predicted methane generation results from application of the lower range DOC values (Scenario A), and the higher range values (Scenario -15%-10%-5%0%5%10%15%-50% -40% -30% -20% -10% 0% 10% 20% 30% 40% 50%∆k (%)∆CH4 (%), 2012Food waste (±75%)Yard waste (±50%)Paper (±18%)Wood waste (±38%)Textiles (±18%)Disposable nappies (±18%)195  B), were compared with the results with the initial and the calibrated methane generation estimates (Gi and G, respectively). This analysis showed that the average methane yield value in the study boundaries could vary between 62 and 93 m3 CH4 per tonne of waste, resulting in current methane capture efficiency of 96% to 67% for Scenarios A and B, respectively. As shown in Table 8.3, the deviation in L˳ value from the calibrated L˳ was between -18% (18% underestimation) and 24% (overestimation).   Figure 8.3 shows that this deviation in methane generation rate, hence methane capture efficiency, varies depending on the year of assessment. For instance, the deviation in the assessed methane generation rate in 2006 was between -22% and 25%, while this value for 2012 was between 14% and 23%.  Table 8.3 Methane generation and capture efficiency deviations in the VLF (within the study boundaries) resulted from application of lower and higher ranges of DOC values Scenarios Methane Generation Estimates (tonnes) Methane Yield, L˳ (m3 tonne-1) Capture Efficiency (CE2012) Deviation from Field Measurements (Gi-Err)DOC Life time Peak 2012 Initial Assessment (Gi) 496,354 21,706  11,851 83 75% 10.3% Calibrated Model (G = Gi × CFG) 449,994 19,678  10,744 76 82% 0.0% A. Lower Range (DOCL) 367,820 15,349  9,193 62 96% -18.3% B. Higher Range (DOCH) 556,079 24,614  13,236 93 67% 23.6%  While the developed methane generation calibration factor (CFG) lies within the resulting uncertainty range in this analysis, the variations of the results for different assessment years may suggest that conducting the field work to develop this number in a different year would have resulted in a different CFG value.  196   Figure 8.3 Graphical illustration of methane generation with lower and higher DOC ranges in comparison with the initial (Gi) and the calibrated modeling results   Other parameters affecting the final values of the available DOC and L˳ include a series of discount factors discussed in Section 3.2. In order to evaluate the impact of these factors on the refined model results, a value of 1 was assigned to all discount factors except for the degradability factor. Methane generation results were compared with the initial and the calibrated results as presented in Table 8.4.   Table 8.4 Effect of DOC discount factors on methane generation estimates Scenarios Methane Generation Estimates (tonnes) Methane Yield, L˳ (m3 tonne-1) Capture Efficiency (CE2012) Deviation from True Value (Gi-Err)∑d Life time Peak 2012 Initial Assessment 496,354 21,706  11,851 83 75% 10.3% Calibrated Model 449,994 19,678  10,744 76 82% 0.0% ∑discount factor = 1 581,869 26,041  13,546 98 65% 29.3%  01,0002,0003,0004,0005,0006,00005,00010,00015,00020,00025,00030,00019901993199619992002200520082011201420172020202320262029203220352038204120442047205020532056205920622065LFG Flow Rate (scfm)Methane Generation rate (tonnesyear-1) DOCL (Lower Range)DOCH (Higher Range)Initial Assessment (Gi)Calibrated Results (CFG)197  In this scenario, the value of L˳ for VLF between 1990 and 2008 ranged from 88 to 112 m3 methane per tonne of waste, with an average amount of 97.7 m3 tonne-1. This analysis showed that the elimination of the DOC bio-availability discount factors, which were defined to increase the accuracy of the modeling results, will change the modeling results from the true value (calibrated results) as much as 29%.   Figure 8.4 Effect of DOC discount factors on methane generation estimates  8.2.2 LFG Modeling Errors Due to Decay Rates Uncertainty Range (Gi-Err)k Similarly, a sensitivity analysis was performed on the effect of the uncertainty range for the decay values by re-running the model for the entire work site. The methane generation results from application of the lower range decay values (kL), and the higher range values (kH), were 01,0002,0003,0004,0005,0006,00005,00010,00015,00020,00025,00030,00019901993199619992002200520082011201420172020202320262029203220352038204120442047205020532056205920622065LFG Flow Rate (scfm)Methane Generation rate (tonnesyear-1) ∑discount factor = 1Initial AssessmentCalibrated Results198  compared with the results of the methane generation assessment. The uncertainties related to the decay rates only affect the distribution of the methane generation levels over the landfill’s lifespan and would not change the total lifespan methane generation or the methane yield values. Therefore, in order to conduct a valid comparison, results of the initial methane generation assessment (Gi) were used as the basis, where the CFG = 1 allowing similar L˳ values for the three model re-runs.  As shown in Table 8.5, the maximum deviations in the current methane generation rates, in comparison with the initial methane generation assessment results, were 0.2% and -16.5% for the lower and the higher range k values, respectively.   Table 8.5 Methane generation uncertainties due to the decay rates uncertainty range  Scenarios Methane Generation Estimates (tonnes) Methane Yield, L˳ (m3 tonne-1) Capture Efficiency (CE) Deviation from the Initial Assessment (Gi-Err)k Life time Peak 2012 Initial Assessment 496,354 21,706 11,851 83 75% n/a Lower Range (kL) 495,685 18,571 11,877 83 75% 0.2% Higher Range (kH) 496,537 25,790 9,890 83 90% -16.5%  The resulting deviations due to the decay rates’ uncertainty range seemed to be relatively small. However, depending on the year of assessment, this deviation can increase to more than 100% of the modeling results. As shown in Table 8.6, for the period of 1991 to 2038, when approximately 95% of the lifespan methane generation from the work site would occur, the decay rates uncertainty range resulted in 103% deviation from the estimated methane generation  (i.e. (Gi-Err)k = ±103%). Similarly, for the period of 2001 to 2016, with approximately 50% of the 199  total methane estimated to be generated within this timeframe, the (Gi-Err)k value was about 37%, as illustrated in Figure 8.5.  Table 8.6 Maximum deviations in generation estimates due to decay rates for different lifespan periods Selected Period Methane Generation within Period Percent of Total Generation Deviation from Modeling Results (Gi-Err)k 2001 - 2016 211,521 ~50% 37% 1992 - 2032 378,168 ~90% 88% 1991 - 2038 393,338 ~95% 103%    Figure 8.5 Methane generation uncertainties due to the decay rates uncertainty range  01,0002,0003,0004,0005,0006,00005,00010,00015,00020,00025,00030,00019901993199619992002200520082011201420172020202320262029203220352038204120442047205020532056205920622065LFG Flow Rate (scfm)Methane Generation Rate (tonnesyear-1)kL (Lower Range)kH (Higher Range)Initial Assessment50% of the lifespangeneration(Gi-Err)k = 0.37 x Gi2001 - 2016 200  8.2.3 MSW Moisture Content and the Associated LFG Modeling Errors (Gi-Err)w One of the steps to increase the accuracy of the methane generation estimates was the attempt to consider the moisture content of waste components as they are received at the disposal facility (as-received), instead of basing the DOC value calculations on reported waste moisture content at the sources of waste generation, such as households, schools, etc. (as-generated). Therefore, a sensitivity analysis was performed on the effect of application of the moisture content reported for MSW organic components by Tchobanoglous et al. (1993), in comparison with the moisture content that was initially used to assess the methane generation within the study boundaries. The methane generation results from the application of the as-generated moisture content was relatively close to the initial methane generation assessment, with methane yield of 83 and 82 m3 methane per tonne of waste, respectively. As shown in Table 8.7, the resulting deviation in the current methane generation estimate and the capture efficiency from the calibrated modeling results was 9%, very close to the generation correction factor (CFG) which was developed based on the field study at VLF.   Table 8.7 Methane generation uncertainties due to organic material moisture content Scenarios Methane Generation Estimates (tonnes) Methane Yield  (m3 tonne-1) 2012 Capture Efficiency Deviation from Field Measurements Life time Peak 2012 L˳ (CE) (Gi-Err)w Initial Assessment 496,354 21,706 11,851 83 75% 10.2% Calibrated Model 449,994 19,678 10,744 76 82% 0.0% Moisture Content at  Source 490,481 20,267 12,346 82 72% 9.0%  201   Figure 8.6 Methane generation uncertainties due to organic material moisture content  Even though the effect of the organic material moisture content seems to be relatively insignificant, a proper waste composition analysis, including waste moisture content measurements, at VLF will provide useful information. This information will allow for an even more accurate estimation of L˳, methane generation rate, and methane capture efficiency.  8.3 Calibration Errors Resulted from the Field Study Deviations (CFG-Err) As part of the iModel-110©, the methane generation calibration factor (CFG) was developed based on the field investigations on methane emission, oxidation, and recovery, described in Chapters 4, 5, and 6, respectively. This information was required to integrate the right side of the simplified METRO equitation, allowing for the quantification of a necessary methane generation calibration factor (CFG) to be applied to the initial generation estimates on the left side of the 05001,0001,5002,0002,5003,0003,5004,0004,5005,00005,00010,00015,00020,00025,00019901993199619992002200520082011201420172020202320262029203220352038204120442047205020532056205920622065LFG Flow Rate (scfm)Methane Generation rate (tonnesyear-1)Generation Based on WasteMoisture as GeneratedInitial Methane GenerationAssessment (Gi)Calibrated MethaneGeneration Results (G)202  equation. However, field measurements themselves bear uncertainty associated with measurement techniques, instrumentation limitations, and sampling errors. These uncertainties created a range of error in the calibration factor (CFG-Err), which results in a deviation in the final modeling results from the true value.   The CFG-Err values corresponding to different field work were recognized through three different distinct values: (i) errors due to emission measurement uncertainties ((CFG-Err)E), (ii) errors due to the uncertainties in the methane oxidation quantification ((CFG-Err)O), and (iii) errors resulted by the uncertainties in the methane recovery data ((CFG-Err)R). A collective overlook of these uncertainties and errors resulted from these field investigations was previously discussed in Section 7.1. These errors are individually assessed and described in Sections 8.3.1, 8.3.2, and 8.3.3, respectively.   8.3.1 Errors Due to the Methane Emission Measurement Uncertainties (CFG-Err)E As described in Chapter 4, the total methane emission (E) from the study boundaries within VLF was quantified using the surface methane concentration (SMC) data from the entire work site (approximately 83 hectares), and a correlation that was developed between these data and the methane emission rate (MER) data (see Equation 4.9). The MER values were measured through the flux chamber technique conducted for approximately 20% of the total footprint, and the total E was estimated using the regression equation with coefficient of determination of R2 = 0.90. This value is a function of: (i) the deviation of the MER values from their mean (SSy) and (ii) the deviation of the MER values from their predicted values (SSE). In principle, the R2 is a number between 0 and 1, where lower numbers mean that X values (SMC in this case) provide 203  no information about Y values (MER in this case) (SSy and SSE are almost identical). However, R2 values closer to 1 suggests that X contributes lots of information about Y (SSE is very small).   The resulting number for R2 for the developed regression equation between the SMC and the MER data confirmed that 90% of the variability observed in the MER values (measured in the selected areas of the work site) could be explained by the assessed SMC values in those areas. As presented in Figure 4.13, showing the suggested correlation between SMC and MER, there are bigger uncertainties at grids with lower levels of methane emission recorded. Therefore, in the worst case scenario, 10% of the MER values estimated by the developed regression equation, hence estimated total E, could be defined as the max error in methane emission measurements. Furthermore, the statistical analysis of the developed linear regression in Chapter 4 showed a standard deviation of approximately 28% with 95% confidence limit (see Table 4.6). Nevertheless, even 28% error in the quantified emission levels translates to approximately 400 tonnes of methane which is very insignificant in comparison with the total methane generation estimate of more than 10,000 tonnes year-1.    It should be noted that the error discussed above does not include the possible errors and uncertainties associated with the sampling procedure and instrumentation used for the surface methane concentration scan and the flux chamber measurements. However, these instrument were calibrated based on the manufacturer’s recommendations and believed to have an insignificant errors.   204  8.3.2 Errors Due to the Methane Oxidation Measurement Uncertainties (CFG-Err)O The total amount of methane oxidation (O) at VLF was calculated based on the total methane emission through landfill cover soil, as well as the fox value, the fraction of methane oxidized. The fox value, as described in Chapter 5, was estimated for two different types of cover soil on site using the stable isotope technique. As shown in Equation 5.3, fox depends on four different parameters: (i) anaerobic methane δ13C value (δa), (ii) residual methane δ13C value (δR), (iii) oxidation fractionation factor (αox), and (iv) fractionation factor due to transport (αt). In order to increase the accuracy of the fox results, grid-specific δ values were generated and used in the calculations. However, the mean values of αox and αt, respectively from the soil incubation lab works and literature, were used to calculate the fox value for each grid, and ultimately for the entirety of Area A (average fox of 34%) and Area B (average fox of 28%), each covered with one of the two soil types.   As previously shown in Table 5.4 of Chapter 5, the average αox value for Areas A and B were 1.0265 ± 0.0010 and 1.0266 ± 0.0052, respectively. The average αt value of 1.0106 ± 0.007 was adopted from the literature (Chanton et al., 2011a). The average values of fractionation factors resulted in the mean oxidation rates of 33.7% and 27.9%, for Areas A and B, respectively. However, there could be eight other scenarios for each area based on the deviations in the αox and αt, values. Therefore, a 9 × 9 matrix was created for each area to calculate the fox value for all possible combinations of low range, high range, and average value of αox and αt.  Table 8.8 and Table 8.9 show the resulting deviations in fox values for Areas A and B due to uncertainties in fractionation factor values. It should be noted that these uncertainties in fox values do not 205  include the possible errors and uncertainties associated with the field and lab work sampling procedures and instrumentation errors.  Table 8.8 Deviation in methane oxidation rate due to fractionation factors uncertainties in Area A fox Area-A αt low high average Mean StDev αox low 31.8 45.1 35.3 37.4 6.9 high 29.4 39.1 32.3 33.6 5.0 average 30.6 41.8 33.7 35.4 5.8 Mean 30.6 42.0 33.8 35.5 ± 5.4 StDev 1.2 3.0 1.5   Table 8.9 Deviation in methane oxidation rate due to fractionation factors uncertainties in Area A fox Area-B αt low high average Mean StDev αox low 25.0 83.1 41.3 49.8 30.0 high 15.8 31.4 21.0 22.7 7.9 average 19.4 49.5 27.9 32.3 15.5 Mean 20.1 54.7 30.1 34.9 ± 21.0 StDev 4.7 26.2 10.3  In order to evaluate the effects of uncertainty levels of the methane oxidation rates on the methane generation modeling results, a sensitivity analysis of these deviations on the CFG value was conducted. The METRO equation was re-run using the lower range and the higher range oxidation rates and the results were compared with the initial assessment where the average values have been used. Results showed that the applicable calibration factor would range from 1.09 to 1.18, in comparison with the initial calibration factor of 1.10. Furthermore, the analysis showed that the overall oxidation rate at VLF ranged between 26% to 63% for Scenarios 1 and 2, respectively. Summary of these results are presented in Table 8.10. 206   Table 8.10 Generation calibration factor uncertainties due to the oxidation rate uncertainty range Scenarios Fraction of Methane Oxidized (fox, %) Oxidized Methane (O) Methane Emissions (E)  Methane Recovery (R)  Total Methane within Boundaries  (∑ METRO) Initial Modeling Results (Gi) Methane Generation Correction Factors Area A Area B (tonnes) (%)* (%)** (tonnes) (%) (tonnes) (%) CE (tonnes) (tonnes) CFG Initial Assessment (Mean Values) 33.7 27.9 268 4.1% 30% 1,481 14.7% 8,853 87.7% 10,744 11,852 1.103 Scenario 1. Lower Range Oxidation 30.1 13.9 228 2.3% 26% 972 9.7% 8,853 88.8% 10,053 11,852 1.179 Scenario 2. Higher Range Oxidation 40.9 56.0 1,093 10.4% 63% 972 9.2% 8,853 83.9% 10,919 11,852 1.085 * percent of total generated methane (G) ** percent of emitted methane through cover soil (Es) 207  8.3.3 Errors Due to the Methane Recovery Data Deviations (CFG-Err)R As previously reported in Chapter 6, the amount of recovered methane (R) was calculated based on the collected LFG flow rate and composition. A GEM™ 2000+ LFG analyzer was used to measure these parameters in 65 events during the course of the field study. A full list of the sampling events and recorded values is presented in Appendix F.1.  The recorded LFG flow rates showed an average result of 1,758 ± 151 standard cubic feet per minute (scfm), which translates to total recovered methane of R = 8,863 ± 761 tonnes per year. A sensitivity analysis on the effect of this deviation in R value on the CFG value ((CFG-Err)R), and eventually on the modeling results, was conducted by re-running the METRO equation for two scenarios of: (i) R1 = 8,092 tonnes CH4 year-1 and (ii) R2 = 9,614 tonnes CH4 year-1. The average values for the total amount of methane oxidation (O) and methane emission (E) were applied in both scenarios. The results of this analysis are presented in Table 8.11.  Table 8.11 Deviation in CFG due to uncertainty range in methane recovery data Scenarios Methane Recovery Methane Emissions Methane Oxidation  Total Methane within Boundaries Initial Methane Generation Estimate Resulted Calibration Factor R E O ∑ METRO Gi CFG (tonnes) (tonnes) (tonnes) (tonnes) (tonnes)   Average Value 8,853 1,481 410 10,744 11,852 1.103 Scenario 1. Lower Range Methane Recovery 8,092 1,481 410 9,983 11,852 1.187 Scenario 2. Higher Range Methane Recovery 9,614 1,481 410 11,505 11,852 1.030  208  The calibration factors resulting from these two scenarios were 1.19 and 1.03, respectively corresponding to the lower and the higher range of the amount of captured methane. This resulting deviation in CFG was higher than what was concluded for (CFG-Err)O, which is mainly due to the relatively larger R values in comparison with the O values. It is worth noting that the deviation reported for R values, hence the calculated (CFG-Err)R, result from wellfield operational adjustments, LFG flow surging in the manifolds, and the inaccuracies associated with the type of the gas flow meter used at VLF. The reported errors do not include uncertainties due to the LFG analyzer instrument.  8.4 Error Analyses Conclusion  The error analysis was conducted to evaluate the effects of uncertainties in various parameters on (i) methane generation modeling (Gi-Err), and (ii) modeling calibration factor (CFG-Err).   As expected, uncertainty in k values did not have any effect on L˳ or on the total methane generation. However, the effect of this value was the most substantial on the methane capture efficiency. This effect depends on the year of assessment with respect to the landfill closure year. When the assessment was conducted within approximately 10-15 years of the landfill/phase closure year, during which about 50% of the lifespan methane was generated, the effect of the k value became the second most substantial after the effects of the uncertainties in the DOC values. The analysis also showed the importance of the DOC discount factors, where the ignorance of these parameters could increase the overestimation of the initial methane generation assessment from 10% to 29%.   209  Furthermore, a sensitivity analysis on the effect of uncertainties on methane oxidation and recovery was performed by re-running the entire analyses under the simplified METRO equation and developing a new calibration factor. The developed values for the minimum and maximum values of O and R within their deviation range showed that the effect of R deviations was more substantial, suggesting a methane generation overestimation within range of 3% to 18%.   210  Chapter  9: Summary and Conclusions Landfill gas generation modeling results are in general relied upon as a basis for both design of LFG recovery and utilization systems, as well as for GHG legislative emission concerns. These data are also used by the authorities to modify and fine-tune the existing GHG emission policies, regulations, and inventory reports. However, given the number of variables affecting the degradation process within landfills, exact quantification of LFG generation and fugitive methane emissions is very difficult such that serious uncertainties and doubts are reported about the validity of the existing LFG generation models. Many researchers have reported model “errors”. These errors are in most cases significant overestimation of the gas generation relative to field measurements, thus resulting in oversized LFG management systems. In larger scales, errors aggregate and create much larger overestimations of the waste management sector methane budget registered in national and international GHG emission inventory reports.  9.1 Common LFG Generation Modeling Methodologies and Shortfalls The first order reaction is the basis of many of the existing LFG generation models. The main differences between these models lie in both the formulation of gas mass balances and the values assumed for the key influencing “modeling parameters”.  These modeling parameters define how much (L˳, m3 CH4 per tonne of waste) and how fast (k, year-1) the methane gas is produced in a landfill as a result of anaerobic decomposition of the organic material deposited in the landfill. Some models, such as the US EPA LandGEM model, make simplified assumptions in selection of the modeling parameters, disregarding many factors including the waste composition and the fact that composition can significantly change throughout the landfill’s lifespan.  Similarly, the degradability of the organic material deposited at landfills under given conditions is an important 211  parameter affecting the methane yield. Even though these data are very well researched and known, they are not properly reflected in the modeling parameters.   There are some models which do consider the waste composition to calculate the L˳ value, however, some other factors such as the actual moisture and/or carbon content, as well as the ultimate degradability of waste components are selected based on flat assumptions. In some cases the k values also are almost arbitrarily selected. For example, the IPCC model suggests a flat 50% degradability rate for all the materials deposited in landfills. This model also assumes warm region landfills decompose more rapidly than cold region landfills with suggested k values for those affected by the low temperature. Nevertheless, there are many studies that suggest independency of landfill temperature from the ambient temperature due to the exothermic nature of anaerobic degradation process.  A quick modeling exercise presented in Chapter 1 of the present research, involving five popular LFG generation models, including the most popular models used in the North America and BC, showed up to a 340% variation in the results for a single site, arguably demonstrating the need for an enhanced model which offers more realistic and consistent results that could be used by landfill owners, engineers, and regulatory agencies.   With more LFG collection systems installed, superior quality data are being collected by many people. However, this information is not reflected back into the models. A unique opportunity was provided at the Vancouver Landfill (VLF) through the course of this research, making it possible to refine current LFG generation models aiming at reducing uncertainties. Historical 212  landfill operation and LFG collection data along with very well recorded data with regard to waste generation, composition, and diversion, was integrated into a refined LFG generation model. The latest technological advances in lab and field measurement techniques were also employed to enhance data quality. The iModel-110© was developed based on the widely accepted multiphase first order decay reaction, supported by METRO equation concept which was developed as a quality control basis for this research. Based on the METRO equation, a comprehensive methane mass balance was conducted considering all possible pathways for the generated methane from the four sites within the study boundary and to calibrate and verify the integrated model.  9.2 Vancouver Landfill, the Unique Opportunity This research was conducted at the Vancouver Landfill (VLF), owned and operated by the City of Vancouver (COV). Working on this site provided a unique opportunity to incorporate results and findings of various research studies into practice, which in turn resulted in more accurate LFG generation estimations. This was achieved through fine tuning the new model for more accurate and educated projection of current and future methane generation, methane capture efficiency, and methane emissions within VLF.    The availability of historical data and information on design and operational phasing of VLF was amongst the key advantages of conducting research on this site. Historically, this site was divided into seven distinct operational phases filled from west to east between 1967 and 2008 (see Figure 2.2). Since 2009, the waste disposal activities were switched back to Phase 2 and Phase 3 with an anticipation that no waste filling would occur in the four eastern phases (areas) 213  between 2009 and 2015. Therefore, these four phases (Area 2W, Area 2E, Area 3, and Phase 1) were selected as the study boundary. These areas were completed respectively in 1993, 1995, 1998, and 2008, with clear geometric boundaries, each equipped with a distinct active LFG collection system, dedicated LFG manifolds and gas quality and quantity metering stations. Therefore, each of these four areas could be treated as an individual site that has received a known tonnage of MSW and DLC (scaled at the entrance of the landfill) and matching known waste composition which was regularly studied by Metro Vancouver at transfer stations or the Burnaby WTEF.   9.3 Main Contributions to the LFG Industry 9.3.1 The New Model The METRO© equation concept was developed as a basis for this research to calibrate and verify the integrated model. The iModel-110© was developed based on the widely accepted multiphase first order decay reaction. Variable methane generation potential (L˳) was developed based on the actual decomposable organic carbon (DOCdry) historically deposited in each phase and reflecting the historical changes in waste consumption, recycling, and disposal strategies. Degradability extents as well as the moisture content of each waste component were also included in the calculation of the L˳ values. Several other factors defining bioavailability of the total deposited DOC were also identified through literature and incorporated into development of the historical and future projection of L˳ value for each year throughout the landfill’s lifespan. Through application of the METRO© equation to the four individual sites and conducting a series of full scale investigations, all possible methane pathways were quantified. Accordingly, results of the new model were compared against actual field data for the modeling year and a range of 214  correction factors for gas generation (CFG) were obtained which were used to further refine the L˳ values. This provided a narrow range for the LFG generation prediction developed by the new model, with the true value believed to sit within the lower and the higher prediction values.   The decay rate (k) for each organic component of the waste was defined based on the biodegradation half-life of that component. Major variables reported as primary factors defining the decay rate for each component are moisture content and temperature. However, this research showed that in optimum moisture content conditions (such as at the VLF) the rates of decay are independent from the ambient temperature fluctuations and/or annual mean temperature. While the decay rates would not affect the lifespan methane generation from a landfill, this finding specifically is of importance for evaluation of methane capture efficiency at some point in time depending on the year of the evaluation related to the site closure year.   Whether the course of the application is in smaller scales, such as evaluating LFG collection efficiency or designing LFG collection and treatment systems for a particular landfill, or in larger scales, such as national or international GHG emissions surveys, it is very important to use reliable data generated by an accurate model, allowing knowledgeable decisions. Even though a very exact quantification of LFG generation is impossible, the gas generation estimates generated by iModel-110© are much closer to the true value in comparison with estimations by other existing models. This model was developed based on nothing more than putting together the available data and knowledge and taking advantage of the unique opportunity at the VLF to test and calibrate the model.   215  In order to verify the results of the developed model, methane generation rates from the Phase 2 of the Vancouver Landfill, located outside of the research boundary, were estimated using the iModel-110 with the defined range for the generation calibration factor. Similar to the calibration process approach and use of the METRO equation, the actual field data were compared against the predicted values of LFG generation rates. Results indicated reasonably low deviation from actual data at the year of the study ranging from 1.5% to a maximum value of 19.3%.  9.3.2 Other Outcomes of the Study A crucial component of model calibration process was quantification of fugitive methane emissions. As described in Chapter 4, through the technique developed in this research, total fugitive methane emission from the work site was quantified in a very efficient and cost effective manner. In this technique, surface methane concentrations were translated to methane emission rates from the landfill surface. Another equally important part of the study was quantification of the effectiveness of methanotrophic bacteria in mitigating fugitive methane emissions from landfills, using the stable isotope technique. These analyses, presented in Chapter 5, showed that while the default 10% oxidation rate would be an appropriate minimum value, this could be a significant underestimation for the actual methane oxidation rate in landfills with active gas collection systems. Therefore, using appropriate and region-specific oxidation rate values based on estimated methane emission rates may modify methane budget in GHG emission inventory reports.   216  9.3.3 Specific Results Through the calibration and verification process of the new model over the four sites at the VLF, a number of conclusions were made which offer useful information for the LFG industry stakeholders. These results and findings are listed below. - For landfills located in wet climates, the landfill temperature is governed by the self-warming anaerobic decomposition reactions and is not influenced by ambient temperature fluctuations. Therefore, the decay rates of the organic materials deposited at these landfills are constant throughout the year and independent of ambient temperature (see Section 3.3.1).  - The rate of methane emission from a landfill surface is affected by the rate of change in barometric pressure. This relationship was quantified such that a measured emission rate at a given time can be translated to the actual values in stable weather conditions (see Equation 4.8) - Total methane fugitive emissions from a landfill are directly related to the landfill surface methane concentration. This relationship was developed for the VLF and the total emissions were quantified (see Equation 4.10). - Approximately 30% of the non-collected methane at the VLF is oxidized by the methanotrophic bacteria naturally existing in the landfill’s cover soil. This oxidation rate is significantly higher than the default value historically used by the regulatory agencies.   217  9.4 Significance of the Results from Regulatory Perspective According to the new BC MOE landfill gas regulation, the VLF is a regulated site and is required to capture and flare at least 75% of the generated methane. Many other jurisdictions require that the best LFG management practices be applied at the regulated sites and GHG emissions be monitored on a regular basis. While the author believes that quantification of fugitive emissions from landfills should be used by regulatory bodies to evaluate LFG management system performance, the use of more accurate and site specific or (at a minimum) region specific models could be another option for these agencies. The overestimation of the gas generation tools used by a regulatory agency can simply lead to spending millions of dollars for unnecessary expansion and improvement of a gas collection system to collect gas which does not exist.  Based on the results achieved in this research, the average methane generation potential for the VLF ranged between 68 and 89 m3 CH4 per tonne of waste, while the BC MOE Tool used a higher value of 102 m3 CH4 per tonne of waste. Consequently, the resulting methane capture efficiency for the entire VLF in 2012, based on the new model’s lower range and the higher range estimates, ranged between 61% and 79%. This result based on the calibrated (site-specific) decay rates was 64%. The MOE Tool concluded collection efficiency of 55%.  Furthermore, the average methane collection efficiency at the areas within the study boundaries with an intermediate cover system (i.e. Areas 2W, 2E, and 3) was 75% ± 15%.  The modeling results and the historical methane recovery data for Phase 1 showed that the methane capture efficiency in this phase, before installation of the geomembrane cap, was approximately 65% to 70%. However, this capture efficiency was increased to approximately 80% to 90% since 2009, due to the installation of the geomembrane cap and the modifications made to the LFG collection 218  system. These capture efficiency values are in good agreement with what (Spokas et al., 2006) and (SCS Engineers, 2009) reported for the capture efficiencies for active LFG collection systems with similar landfill cover types.  Taking into account the determined methane oxidation in the landfill cover soil, the total atmospheric methane emissions within the study boundaries in 2012 ranged from 6% to 34%.    A summary of the field investigation results is presented in Table 9.1.   Table 9.1 Summary of 2012 methane budget within the work site Area/ Phase Waste in Place Closure year 2012 Methane Budget within the Study Boundaries Generation (G) Recovered (R) Oxidized (O)  Emissions (E)** tonnes   (tonnes) (scfm)* (tonnes) (%) (tonnes) (% of G) (% of Es) (tonnes) (%) Area 2W 2,010,492  1994 1,376 273  792 58% 119 8.6% 28% 466 34% Area 2E 946,200  1996 1,033 205  716 69% 64 6.2% 28% 252 24% Area 3 1,366,288  1999 1,434 284  973 68% 94 6.5% 28% 367 26% Phase 1 4,470,903  2009 6,901 1,369  6,373 92% 133 1.9% 34% 396 6% Total 8,793,883    10,744 2,131  8,853  82% 410  3.8% 30%    1,481  14% * LFG flow calculated based on 50% methane content ** Emission includes emissions from cover soil (Es) and emission from pipe and leaks (El), E = Es+El  9.5 Applicability and Use of the New Model The iModel-110© is developed in an excel workbook with a user-friendly interface. The model consists of five major interlinked spread sheets, as well as six calculation sheets hidden in the workbook. The major interface spread sheets include Parameters, MSW Tonnage, Dry Tonnages, LFG Results, and Graphics.  In the “Parameters” sheet the site-specific information such as the landfill’s name, opening year, site’s design, operational and climate factors, as well as waste components’ parameters such as moisture content, DOCdry and decay factors are to be entered 219  and or updated by the user. Also in this sheet, based on the precipitation levels, assigned half-lives of different type of organic materials are translated to six different decay rates with much longer half-lives suggested for dryer sites. Landfill activity data, including tonnages and composition of the MSW historically deposited at the landfill or expected to be landfilled in the future, are entered in the “MSW Tonnage” sheet. The total amount of carbon annually deposited at the site is calculated based on the DOC and moisture content values in the “Dry Tonnage” sheet. The “LFG Results” sheet presents the calculated methane generation yield for each year based on the waste data, estimated annual methane generation from each waste component in tonnes per year, and the expected LFG flow rates in standard cubic feet per minute (scfm). These results, along with average waste tonnage and composition data, are graphically illustrated in the “Graphics” sheet.   Any landfill with records of tonnage and composition of deposited waste can benefit from the accuracy of this new enhanced model. The principal advantage of this model over other models is that this model incorporates waste composition and moisture data, when available, along with reasonably good k values which are selected from the literature and calibrated based on the field data. The accuracy of the new model was verified though comparison of the predictions with the filed data. The model predictions was within the narrow uncertainty range associated with the field data. Nevertheless, it was attempted to further calibrate the new model through two different methodologies; (i) calibrating the L˳by application of generation calibration factor (CFG), and (ii) through fine-tuning the decay rates which was selected from a suggested range for each organic waste (CFk). During the calibration phase of the study, the lower and upper range CFG, as well as the calibrated decay rates were generated for landfills situated in wet climates 220  similar to that of the Vancouver landfill (i.e. annually receiving close to 1,000 mm or more precipitation).  Therefore, owners and operators of such landfills will be able to utilize the new model simply by completing the data entry sheets (i.e. Parameters and MSW Tonnage). For drier sites, the CFG multiplier and/or site specific decay rates have to be regenerated as recommended in the following section. To benefit from the new model, landfill owners and operators need to know what is being put into the landfill. Keeping good records of the waste composition, as well as moisture content of the materials as received at the landfill, is a key factor that enables users to accurately assess the LFG generation from the landfill.  When site specific historical waste composition data are not available, it would be beneficial to use default values or the waste composition data from the region or cities and communities with similar socio economic properties.   9.6 Recommendations Appropriate Record Keeping at landfills is essential: As noted above, keeping good records of the waste composition, as well as moisture content of the materials as received at the landfill, is a key factor that enables users to accurately assess the LFG generation from the landfill. Incorporation of these data into modeling practice, as well as utilizing very well researched fundamental facts about anaerobic decomposition of organic material in landfills, are the principal advantage of the new model over other models.   Calibration Factors for other climatic conditions: The integrated methane mass balance conducted at the four sites within the study boundaries showed the accuracy of the iModel-110© with a range of generation calibration factors developed to further refine the model’s predictions. 221  However, all of the sites, as well as the VLF Phase 2, on which the model was verified, are located in the same climatic conditions. Therefore, it is necessary that a range of CFG and/ or calibrated site-specific decay rates be generated for other sites with different climatic and operational conditions. This has to be done through conducting a similar practice (i.e. application of METRO equation) to these sites, where good quality information from the LFG collection, as well as the historical waste composition exist. It should be mentioned that the initial generation estimate before application of any calibration factor was only 10% off from the field data. This was within the uncertainty range associated with the field data.   Decay Rate Calibration (CFk): It is important to note that the calibration of the new model was conducted over a single point (year) of the Vancouver Landfill’s lifespan gas generation curve. Personal observations of the author on the six years of field operational LFG data of the VLF Phase 1 confirms suitability of the calibrated decay rates for this site. 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Provided as a Reference of (IPCC, 2006) in GERMAN https://www.itad.de/information/studien/295_oekoinstitut2002_beitragthermabfallbeh.pdf.234  Appendices  Appendix A  Landfill Gas Generation Modeling Full Results A.1 LFG Generation Modeling for VLF-Phase 1: LandGEM Model A.1.1 CAA Modeling Parameters  USER INPUTS Landfill Name or Identifier:TRUE4: ENTER WASTE ACCEPTANCE RATES1: PROVIDE LANDFILL CHARACTERISTICS Mg/yearLandfill Open Year 1999Landfill Closure Year 2008 Input Units Calculated UnitsHave Model Calculate Closure Year?FALSE(Mg/year) (short tons/year)Waste Design Capacitymegagrams1999 483,572 531,9292000 456,666 502,3322001 454,381 499,8192: DETERMINE MODEL PARAMETERS 2002 530,775 583,852Methane Generation Rate, k (year-1)2003 553,951 609,3460.052004 623,019 685,321Potential Methane Generation Capacity, Lo (m3/Mg )2005 691,847 761,0321702006 514,692 566,162NMOC Concentration (ppmv as hexane )2007 040002008 162,000 178,200Methane Content (% by volume )2009502010201120123: SELECT GASES/POLLUTANTS 2013Gas / Pollutant #1 Default pollutant parameters are currently being used by model.2014Total landfill gas2015Gas / Pollutant #22016Methane2017Gas / Pollutant #32018Carbon dioxide2019Gas / Pollutant #42020NMOC202120222023Description/Comments:2024202520262027202820292030Waste Composition for the these three years was C, D, and E (as per GVRD waste composition studies in 2001, 2004, and 2007 and corrected for DLC). DLC received at VLF are included in the the reported tonnagesInput Units:YearVancouver Landfill_Phase 1CAA Conventional - 0.05CAA Conventional - 170CAA - 50% by volumemegagramsRestore Default Model ParametersMg/yearTotal landfill gasClear ALL Non-Parameter Inputs/SelectionsCAA - 4,000MethaneCarbon dioxideNMOCEdit Existing or Add New Pollutant ParametersRestore Default Pollutant Parameters235    RESULTS Landfill Name or Identifier:Closure Year (with 80-year limit) = 2008Methane = 50 % by volume User-specified Unit: av ft 3^/min(Mg/year) (short tons/year) (Mg) (short tons) (Mg/year) (m3/year) (av ft^3/min) (Mg/year) (m3/year) (av ft^3/min)1999 483,572 531,929 0 0 0 0 0 0 0 02000 456,666 502,332 483,572 531,929 1.004E+04 8.039E+06 5.401E+02 2.681E+03 4.019E+06 2.701E+022001 454,381 499,819 940,237 1,034,261 1.903E+04 1.524E+07 1.024E+03 5.083E+03 7.619E+06 5.119E+022002 530,775 583,852 1,394,618 1,534,080 2.753E+04 2.205E+07 1.481E+03 7.355E+03 1.102E+07 7.407E+022003 553,951 609,346 1,925,393 2,117,932 3.721E+04 2.980E+07 2.002E+03 9.939E+03 1.490E+07 1.001E+032004 623,019 685,321 2,479,344 2,727,278 4.690E+04 3.755E+07 2.523E+03 1.253E+04 1.878E+07 1.262E+032005 691,847 761,032 3,102,363 3,412,600 5.754E+04 4.608E+07 3.096E+03 1.537E+04 2.304E+07 1.548E+032006 514,692 566,162 3,794,211 4,173,632 6.910E+04 5.533E+07 3.718E+03 1.846E+04 2.767E+07 1.859E+032007 0 0 4,308,903 4,739,793 7.641E+04 6.119E+07 4.111E+03 2.041E+04 3.059E+07 2.056E+032008 162,000 178,200 4,308,903 4,739,793 7.269E+04 5.820E+07 3.911E+03 1.942E+04 2.910E+07 1.955E+032009 0 0 4,470,903 4,917,993 7.250E+04 5.806E+07 3.901E+03 1.937E+04 2.903E+07 1.950E+032010 0 0 4,470,903 4,917,993 6.897E+04 5.523E+07 3.711E+03 1.842E+04 2.761E+07 1.855E+032011 0 0 4,470,903 4,917,993 6.560E+04 5.253E+07 3.530E+03 1.752E+04 2.627E+07 1.765E+032012 0 0 4,470,903 4,917,993 6.241E+04 4.997E+07 3.358E+03 1.667E+04 2.499E+07 1.679E+032013 0 0 4,470,903 4,917,993 5.936E+04 4.753E+07 3.194E+03 1.586E+04 2.377E+07 1.597E+032014 0 0 4,470,903 4,917,993 5.647E+04 4.522E+07 3.038E+03 1.508E+04 2.261E+07 1.519E+032015 0 0 4,470,903 4,917,993 5.371E+04 4.301E+07 2.890E+03 1.435E+04 2.151E+07 1.445E+032016 0 0 4,470,903 4,917,993 5.109E+04 4.091E+07 2.749E+03 1.365E+04 2.046E+07 1.374E+032017 0 0 4,470,903 4,917,993 4.860E+04 3.892E+07 2.615E+03 1.298E+04 1.946E+07 1.307E+032018 0 0 4,470,903 4,917,993 4.623E+04 3.702E+07 2.487E+03 1.235E+04 1.851E+07 1.244E+032019 0 0 4,470,903 4,917,993 4.398E+04 3.521E+07 2.366E+03 1.175E+04 1.761E+07 1.183E+032020 0 0 4,470,903 4,917,993 4.183E+04 3.350E+07 2.251E+03 1.117E+04 1.675E+07 1.125E+032021 0 0 4,470,903 4,917,993 3.979E+04 3.186E+07 2.141E+03 1.063E+04 1.593E+07 1.070E+032022 0 0 4,470,903 4,917,993 3.785E+04 3.031E+07 2.036E+03 1.011E+04 1.515E+07 1.018E+032023 0 0 4,470,903 4,917,993 3.600E+04 2.883E+07 1.937E+03 9.617E+03 1.442E+07 9.686E+022024 0 0 4,470,903 4,917,993 3.425E+04 2.742E+07 1.843E+03 9.148E+03 1.371E+07 9.213E+022025 0 0 4,470,903 4,917,993 3.258E+04 2.609E+07 1.753E+03 8.702E+03 1.304E+07 8.764E+022026 0 0 4,470,903 4,917,993 3.099E+04 2.482E+07 1.667E+03 8.278E+03 1.241E+07 8.337E+022027 0 0 4,470,903 4,917,993 2.948E+04 2.360E+07 1.586E+03 7.874E+03 1.180E+07 7.930E+022028 0 0 4,470,903 4,917,993 2.804E+04 2.245E+07 1.509E+03 7.490E+03 1.123E+07 7.543E+022029 0 0 4,470,903 4,917,993 2.667E+04 2.136E+07 1.435E+03 7.125E+03 1.068E+07 7.175E+022030 0 0 4,470,903 4,917,993 2.537E+04 2.032E+07 1.365E+03 6.777E+03 1.016E+07 6.825E+022031 0 0 4,470,903 4,917,993 2.413E+04 1.933E+07 1.299E+03 6.447E+03 9.663E+06 6.493E+022032 0 0 4,470,903 4,917,993 2.296E+04 1.838E+07 1.235E+03 6.132E+03 9.192E+06 6.176E+022033 0 0 4,470,903 4,917,993 2.184E+04 1.749E+07 1.175E+03 5.833E+03 8.743E+06 5.875E+022034 0 0 4,470,903 4,917,993 2.077E+04 1.663E+07 1.118E+03 5.549E+03 8.317E+06 5.588E+022035 0 0 4,470,903 4,917,993 1.976E+04 1.582E+07 1.063E+03 5.278E+03 7.911E+06 5.316E+022036 0 0 4,470,903 4,917,993 1.880E+04 1.505E+07 1.011E+03 5.021E+03 7.526E+06 5.056E+022037 0 0 4,470,903 4,917,993 1.788E+04 1.432E+07 9.620E+02 4.776E+03 7.159E+06 4.810E+022038 0 0 4,470,903 4,917,993 1.701E+04 1.362E+07 9.150E+02 4.543E+03 6.809E+06 4.575E+022039 0 0 4,470,903 4,917,993 1.618E+04 1.295E+07 8.704E+02 4.321E+03 6.477E+06 4.352E+022040 0 0 4,470,903 4,917,993 1.539E+04 1.232E+07 8.280E+02 4.111E+03 6.161E+06 4.140E+022041 0 0 4,470,903 4,917,993 1.464E+04 1.172E+07 7.876E+02 3.910E+03 5.861E+06 3.938E+022042 0 0 4,470,903 4,917,993 1.392E+04 1.115E+07 7.492E+02 3.719E+03 5.575E+06 3.746E+022043 0 0 4,470,903 4,917,993 1.325E+04 1.061E+07 7.126E+02 3.538E+03 5.303E+06 3.563E+022044 0 0 4,470,903 4,917,993 1.260E+04 1.009E+07 6.779E+02 3.365E+03 5.045E+06 3.389E+022045 0 0 4,470,903 4,917,993 1.198E+04 9.597E+06 6.448E+02 3.201E+03 4.798E+06 3.224E+022046 0 0 4,470,903 4,917,993 1.140E+04 9.129E+06 6.134E+02 3.045E+03 4.564E+06 3.067E+022047 0 0 4,470,903 4,917,993 1.084E+04 8.684E+06 5.835E+02 2.897E+03 4.342E+06 2.917E+022048 0 0 4,470,903 4,917,993 1.032E+04 8.260E+06 5.550E+02 2.755E+03 4.130E+06 2.775E+022049 0 0 4,470,903 4,917,993 9.812E+03 7.857E+06 5.279E+02 2.621E+03 3.929E+06 2.640E+022050 0 0 4,470,903 4,917,993 9.334E+03 7.474E+06 5.022E+02 2.493E+03 3.737E+06 2.511E+022051 0 0 4,470,903 4,917,993 8.879E+03 7.110E+06 4.777E+02 2.372E+03 3.555E+06 2.388E+022052 0 0 4,470,903 4,917,993 8.446E+03 6.763E+06 4.544E+02 2.256E+03 3.381E+06 2.272E+022053 0 0 4,470,903 4,917,993 8.034E+03 6.433E+06 4.322E+02 2.146E+03 3.217E+06 2.161E+022054 0 0 4,470,903 4,917,993 7.642E+03 6.119E+06 4.112E+02 2.041E+03 3.060E+06 2.056E+022055 0 0 4,470,903 4,917,993 7.269E+03 5.821E+06 3.911E+02 1.942E+03 2.910E+06 1.956E+022056 0 0 4,470,903 4,917,993 6.915E+03 5.537E+06 3.720E+02 1.847E+03 2.768E+06 1.860E+022057 0 0 4,470,903 4,917,993 6.577E+03 5.267E+06 3.539E+02 1.757E+03 2.633E+06 1.769E+022058 0 0 4,470,903 4,917,993 6.257E+03 5.010E+06 3.366E+02 1.671E+03 2.505E+06 1.683E+022059 0 0 4,470,903 4,917,993 5.952E+03 4.766E+06 3.202E+02 1.590E+03 2.383E+06 1.601E+022060 0 0 4,470,903 4,917,993 5.661E+03 4.533E+06 3.046E+02 1.512E+03 2.267E+06 1.523E+022061 0 0 4,470,903 4,917,993 5.385E+03 4.312E+06 2.897E+02 1.438E+03 2.156E+06 1.449E+022062 0 0 4,470,903 4,917,993 5.123E+03 4.102E+06 2.756E+02 1.368E+03 2.051E+06 1.378E+022063 0 0 4,470,903 4,917,993 4.873E+03 3.902E+06 2.622E+02 1.302E+03 1.951E+06 1.311E+022064 0 0 4,470,903 4,917,993 4.635E+03 3.712E+06 2.494E+02 1.238E+03 1.856E+06 1.247E+022065 0 0 4,470,903 4,917,993 4.409E+03 3.531E+06 2.372E+02 1.178E+03 1.765E+06 1.186E+022066 0 0 4,470,903 4,917,993 4.194E+03 3.358E+06 2.256E+02 1.120E+03 1.679E+06 1.128E+022067 0 0 4,470,903 4,917,993 3.989E+03 3.195E+06 2.146E+02 1.066E+03 1.597E+06 1.073E+022068 0 0 4,470,903 4,917,993 3.795E+03 3.039E+06 2.042E+02 1.014E+03 1.519E+06 1.021E+022069 0 0 4,470,903 4,917,993 3.610E+03 2.891E+06 1.942E+02 9.642E+02 1.445E+06 9.711E+012070 0 0 4,470,903 4,917,993 3.434E+03 2.750E+06 1.847E+02 9.172E+02 1.375E+06 9.237E+012071 0 0 4,470,903 4,917,993 3.266E+03 2.615E+06 1.757E+02 8.725E+02 1.308E+06 8.787E+012072 0 0 4,470,903 4,917,993 3.107E+03 2.488E+06 1.672E+02 8.299E+02 1.244E+06 8.358E+012073 0 0 4,470,903 4,917,993 2.955E+03 2.367E+06 1.590E+02 7.894E+02 1.183E+06 7.951E+012074 0 0 4,470,903 4,917,993 2.811E+03 2.251E+06 1.513E+02 7.509E+02 1.126E+06 7.563E+012075 0 0 4,470,903 4,917,993 2.674E+03 2.141E+06 1.439E+02 7.143E+02 1.071E+06 7.194E+012076 0 0 4,470,903 4,917,993 2.544E+03 2.037E+06 1.369E+02 6.795E+02 1.018E+06 6.843E+012077 0 0 4,470,903 4,917,993 2.420E+03 1.938E+06 1.302E+02 6.463E+02 9.688E+05 6.509E+012078 0 0 4,470,903 4,917,993 2.302E+03 1.843E+06 1.238E+02 6.148E+02 9.215E+05 6.192E+012079 0 0 4,470,903 4,917,993 2.189E+03 1.753E+06 1.178E+02 5.848E+02 8.766E+05 5.890E+012080 0 0 4,470,903 4,917,993 2.083E+03 1.668E+06 1.121E+02 5.563E+02 8.339E+05 5.603E+012081 0 0 4,470,903 4,917,993 1.981E+03 1.586E+06 1.066E+02 5.292E+02 7.932E+05 5.329E+012082 0 0 4,470,903 4,917,993 1.884E+03 1.509E+06 1.014E+02 5.034E+02 7.545E+05 5.069E+012083 0 0 4,470,903 4,917,993 1.793E+03 1.435E+06 9.644E+01 4.788E+02 7.177E+05 4.822E+012084 0 0 4,470,903 4,917,993 1.705E+03 1.365E+06 9.174E+01 4.555E+02 6.827E+05 4.587E+012085 0 0 4,470,903 4,917,993 1.622E+03 1.299E+06 8.727E+01 4.332E+02 6.494E+05 4.363E+012086 0 0 4,470,903 4,917,993 1.543E+03 1.235E+06 8.301E+01 4.121E+02 6.177E+05 4.151E+012087 0 0 4,470,903 4,917,993 1.468E+03 1.175E+06 7.896E+01 3.920E+02 5.876E+05 3.948E+012088 0 0 4,470,903 4,917,993 1.396E+03 1.118E+06 7.511E+01 3.729E+02 5.589E+05 3.756E+012089 0 0 4,470,903 4,917,993 1.328E+03 1.063E+06 7.145E+01 3.547E+02 5.317E+05 3.572E+012090 0 0 4,470,903 4,917,993 1.263E+03 1.012E+06 6.796E+01 3.374E+02 5.058E+05 3.398E+012091 0 0 4,470,903 4,917,993 1.202E+03 9.622E+05 6.465E+01 3.210E+02 4.811E+05 3.232E+012092 0 0 4,470,903 4,917,993 1.143E+03 9.153E+05 6.150E+01 3.053E+02 4.576E+05 3.075E+012093 0 0 4,470,903 4,917,993 1.087E+03 8.706E+05 5.850E+01 2.904E+02 4.353E+05 2.925E+012094 0 0 4,470,903 4,917,993 1.034E+03 8.282E+05 5.564E+01 2.763E+02 4.141E+05 2.782E+012095 0 0 4,470,903 4,917,993 9.838E+02 7.878E+05 5.293E+01 2.628E+02 3.939E+05 2.647E+012096 0 0 4,470,903 4,917,993 9.358E+02 7.493E+05 5.035E+01 2.500E+02 3.747E+05 2.517E+012097 0 0 4,470,903 4,917,993 8.902E+02 7.128E+05 4.789E+01 2.378E+02 3.564E+05 2.395E+012098 0 0 4,470,903 4,917,993 8.468E+02 6.780E+05 4.556E+01 2.262E+02 3.390E+05 2.278E+012099 0 0 4,470,903 4,917,993 8.055E+02 6.450E+05 4.334E+01 2.151E+02 3.225E+05 2.167E+012100 0 0 4,470,903 4,917,993 7.662E+02 6.135E+05 4.122E+01 2.047E+02 3.068E+05 2.061E+012101 0 0 4,470,903 4,917,993 7.288E+02 5.836E+05 3.921E+01 1.947E+02 2.918E+05 1.961E+012102 0 0 4,470,903 4,917,993 6.933E+02 5.551E+05 3.730E+01 1.852E+02 2.776E+05 1.865E+012103 0 0 4,470,903 4,917,993 6.594E+02 5.281E+05 3.548E+01 1.761E+02 2.640E+05 1.774E+012104 0 0 4,470,903 4,917,993 6.273E+02 5.023E+05 3.375E+01 1.676E+02 2.512E+05 1.687E+012105 0 0 4,470,903 4,917,993 5.967E+02 4.778E+05 3.210E+01 1.594E+02 2.389E+05 1.605E+012106 0 0 4,470,903 4,917,993 5.676E+02 4.545E+05 3.054E+01 1.516E+02 2.273E+05 1.527E+012107 0 0 4,470,903 4,917,993 5.399E+02 4.323E+05 2.905E+01 1.442E+02 2.162E+05 1.452E+012108 0 0 4,470,903 4,917,993 5.136E+02 4.113E+05 2.763E+01 1.372E+02 2.056E+05 1.382E+012109 0 0 4,470,903 4,917,993 4.885E+02 3.912E+05 2.628E+01 1.305E+02 1.956E+05 1.314E+012110 0 0 4,470,903 4,917,993 4.647E+02 3.721E+05 2.500E+01 1.241E+02 1.861E+05 1.250E+012111 0 0 4,470,903 4,917,993 4.420E+02 3.540E+05 2.378E+01 1.181E+02 1.770E+05 1.189E+012112 0 0 4,470,903 4,917,993 4.205E+02 3.367E+05 2.262E+01 1.123E+02 1.684E+05 1.131E+012113 0 0 4,470,903 4,917,993 4.000E+02 3.203E+05 2.152E+01 1.068E+02 1.601E+05 1.076E+012114 0 0 4,470,903 4,917,993 3.805E+02 3.047E+05 2.047E+01 1.016E+02 1.523E+05 1.024E+012115 0 0 4,470,903 4,917,993 3.619E+02 2.898E+05 1.947E+01 9.667E+01 1.449E+05 9.736E+002116 0 0 4,470,903 4,917,993 3.443E+02 2.757E+05 1.852E+01 9.196E+01 1.378E+05 9.261E+002117 0 0 4,470,903 4,917,993 3.275E+02 2.622E+05 1.762E+01 8.747E+01 1.311E+05 8.809E+002118 0 0 4,470,903 4,917,993 3.115E+02 2.494E+05 1.676E+01 8.321E+01 1.247E+05 8.380E+002119 0 0 4,470,903 4,917,993 2.963E+02 2.373E+05 1.594E+01 7.915E+01 1.186E+05 7.971E+002120 0 0 4,470,903 4,917,993 2.819E+02 2.257E+05 1.516E+01 7.529E+01 1.128E+05 7.582E+002121 0 0 4,470,903 4,917,993 2.681E+02 2.147E+05 1.443E+01 7.162E+01 1.073E+05 7.213E+002122 0 0 4,470,903 4,917,993 2.550E+02 2.042E+05 1.372E+01 6.812E+01 1.021E+05 6.861E+002123 0 0 4,470,903 4,917,993 2.426E+02 1.943E+05 1.305E+01 6.480E+01 9.713E+04 6.526E+002124 0 0 4,470,903 4,917,993 2.308E+02 1.848E+05 1.242E+01 6.164E+01 9.239E+04 6.208E+002125 0 0 4,470,903 4,917,993 2.195E+02 1.758E+05 1.181E+01 5.863E+01 8.789E+04 5.905E+002126 0 0 4,470,903 4,917,993 2.088E+02 1.672E+05 1.123E+01 5.577E+01 8.360E+04 5.617E+002127 0 0 4,470,903 4,917,993 1.986E+02 1.590E+05 1.069E+01 5.305E+01 7.952E+04 5.343E+002128 0 0 4,470,903 4,917,993 1.889E+02 1.513E+05 1.017E+01 5.047E+01 7.565E+04 5.083E+002129 0 0 4,470,903 4,917,993 1.797E+02 1.439E+05 9.669E+00 4.801E+01 7.196E+04 4.835E+002130 0 0 4,470,903 4,917,993 1.710E+02 1.369E+05 9.198E+00 4.566E+01 6.845E+04 4.599E+002131 0 0 4,470,903 4,917,993 1.626E+02 1.302E+05 8.749E+00 4.344E+01 6.511E+04 4.375E+002132 0 0 4,470,903 4,917,993 1.547E+02 1.239E+05 8.323E+00 4.132E+01 6.193E+04 4.161E+002133 0 0 4,470,903 4,917,993 1.471E+02 1.178E+05 7.917E+00 3.930E+01 5.891E+04 3.958E+002134 0 0 4,470,903 4,917,993 1.400E+02 1.121E+05 7.531E+00 3.739E+01 5.604E+04 3.765E+002135 0 0 4,470,903 4,917,993 1.331E+02 1.066E+05 7.163E+00 3.556E+01 5.331E+04 3.582E+002136 0 0 4,470,903 4,917,993 1.266E+02 1.014E+05 6.814E+00 3.383E+01 5.071E+04 3.407E+002137 0 0 4,470,903 4,917,993 1.205E+02 9.647E+04 6.482E+00 3.218E+01 4.823E+04 3.241E+002138 0 0 4,470,903 4,917,993 1.146E+02 9.176E+04 6.166E+00 3.061E+01 4.588E+04 3.083E+002139 0 0 4,470,903 4,917,993 1.090E+02 8.729E+04 5.865E+00 2.912E+01 4.364E+04 2.932E+00Waste-In-PlaceWaste AcceptedVancouver Landfill_Phase 1Please choose a third unit of measure to represent all of the emission rates below.Total landfill gas MethaneYearav ft^3/min236    RESULTS Landfill Name or Identifier:Closure Year (with 80-year limit) = 2008Methane 50 % by volume User-specified Unit: av ft 3^/min(Mg/year) (short tons/year) (Mg) (short tons) (Mg/year) (m 3 /year) (av ft^3/min) (Mg/year) (m 3 /year) (av ft^3/min)1999 483,572 531,929 0 0 0 0 0 0 0 02000 56 666 02 332 483,572 531,929 1.004E+04 8.0 9E+06 5.401E+02 2.681E+03 4.019E+06 2.701E+021 4 381 499 81 940 237 1,0 4 261 9 3 1 524 7 1 024 3 5 0 3 7 6 5 1192 530,7 5 83, 5 1,394 618 08 2 75 2 205 8 7 355 1 102 7 7 4 73 95 6 46 25,393 2 117, 32 3. 21 .980 2. 2 9.939 .490 1.0 34 623 019 5 21 2 79 44 ,72 78 4 690 3 75 5 3 1 2 4 878 2622005 91,847 761,032 3,102 6 3 4 2 600 5 4E+04 4 6 8E+0 3 96E+0 5 7E+0 2 3 4E+0 548E+06 14 692 5 6 16 7 ,2 1 4 73, 6.91 5.533 7 .718 3 .846 .767 .8597 0 0 4 3 8 90 , 39 793 7 4 6 119 4 1 1 2 0 1 3 059 7 2 68 162, 0 178,20 , 3 269 820 9 9 2 910 1 9 5 39 470, 917,9 . 50 . 06 . 0 1. 3 4 . 03 . 02010 , 897E+04 E+0 3 E+0 E+0 2 1E+0 E+01 , 4 6 5 5 253 7 530 3 75 627 762 0 0 4 ,90 , 93 . 41 4.997 .358 .667 .499 7 .6793 3 , 5 936 7 194 586 37 1 597 34 ,470 917 9 6 522 0 1 08 4 26 12015 , , .37 E+04 .301E+0 2.8 E+0 .435E+0 2.151E+0 .445E+06 4, 109 0 7 749 3 3 046 3 47 0 0 4, 90 93 4 860 3 89 615 29 1 9 7 08 , 3 , . 23 .7 .487 . .8 1.2 39 470 ,917 9 98 52 366 1 17 4 76 1832020 , 8 E+04 350E+0 2 251E+0 17E+0 675E+0 25E+01 , 4 , 3.979 .186 7 .14 3 .063 .593 .0702 0 0 4 90 , 93 7 5 3 031 03 1 1 1 7 183 , 3 600 2 8 3 1 9 7 9 6 3 442 9 6 6 24 470, 917,9 .42 .742 .8 3 .148 .3 1 .2 32025 , 258E+04 609E+0 75 E+0 8 702E+0 04E+0 8 764E+06 , 4 3 099 48 7 66 3 27 2 3377 0 0 4 ,90 , 93 2.94 .360 .586 7.8 4 1.180 7 7.9 08 3 , 804 2 2 5 1 09 490 3 23 54 29 ,470 917 9 667 136 435 125 068 1752030 , , .53 E+04 .0 2E+0 .3 E+0 6.7 7E+0 . 16E+0 6.82 E+01 4, 413 1 9 3 7 29 3 4 9 6 6 4932 0 0 4, 90 93 2 296 8 8 32 192 63 , 3 , .184 .749 1.17 5.8 3 3 8.743 5. 24 470 ,917 9 077 66 18 5 9 3 7 5882035 , 1 9 E+04 582E+0 063E+0 278E+0 7 911E+0 31 E+06 , 4 , .8 0 1. 05 7 . 1 3 .021 .526 6 .057 0 0 4 90 , 93 7 8 43 9 620 2 4 7 6 159 4 8 08 , 3 01 3 15 43 3 6 80 75 29 470, 917,9 .61 .29 8.704 .3 .477 . 22040 , 1 539E+04 2E+0 28 E+0 11 E+0 61E+0 14 E+01 , 4 464 1 17 7 7 876 3 9 0 5 6 3 9382 0 0 4 ,90 , 93 .392 . 15 .492 2 .7 9 .5 5 .7 63 3 , 25 061 12 538 3 303 563 24 ,470 917 9 2 0 09 6 7 9 365 04 3892045 , , 1.1 8E+04 9.597E+06 . 48E+0 .201E+0 4.798E+0 .224E+06 4, 4 12 34 3 04 64 6 3 0 77 0 0 4, 90 93 084 8 684 5 8 5 2 2 897 2 2 918 , 3 , . 32 .260 .550 .75 3 .130 .775 29 470 ,917 9 9 81 3 7 85 279 62 3 929 6402050 , 3 E+0 47 E+06 022E+0 4 3E+0 7 7E+0 5 1E+01 , 4 , 8. 79 .11 4.7 7 .372 .555 6 .3882 0 0 4 90 , 93 446 6 7 3 44 2 2 2 6 381 2 2 23 , 3 034 3 3 14 3 21 16 24 470, 917,9 7.6 2 3 . 9 .11 .0 1 3.060 .0562055 , 26 E+0 5 821E+06 3 9 1E+0 1 9 E+0 2 9 E+0 1 9 E+06 , 4 6 915 5 7 720 8 7 7 8 6 8 07 0 0 4 ,90 , 93 .577 .26 .539 2 .75 .633 .7 98 3 , 5 010 366 67 3 505 683 29 ,470 917 9 5 2 3 4 7 6 202 590 38 012060 , , .661E+0 . 33E+06 3.04 E+0 1. 12E+0 2.267E+0 1.52 E+01 4, 385 3 2 2 897 438 156 6 442 0 0 4, 90 93 123 10 75 2 36 0 1 3783 , 3 , 4.87 3.9 .62 . 0 3 1.9 . 1 24 470 ,917 9 3 3 71 4 4 2 8 2 72065 , 409E+0 531E+06 372E+0 1 17 E+0 765E+0 1 186E+06 , 4 , . 94 .358 2.2 6 . 20 .679 6 . 27 0 0 4 90 , 93 3 98 195 14 2 066 597 0738 , 3 7 5 3 0 9 0 14 3 1 1 1 29 470, 917,9 .610 3 2.8 1.9 9.642 2 .44 9.71 12070 , 43 E+0 7 0E+06 8 7E+0 17 E+0 3 5E+0 237E+01 , 4 266 61 75 8 725 08 6 8 82 0 0 4 ,90 , 93 3.107 .488 .672 2 .299 .2 4 .3583 3 , 2 955 367 590 7 8 4 1 183 7 9 14 ,470 917 9 811 3 2 251 1 13 50 2 26 563 12075 , , .674E+0 .14 E+06 .439E+0 .143E+0 .071E+0 .194E+06 4, 54 03 36 6 7 5 18 6 6 847 0 0 4, 90 93 420 1 9 8 02 2 46 9 6 5 098 , 3 , 2.302 .8 3 .2 8 . 8 .2 5 . 29 470 ,917 9 189 3 75 1 17 5 8 2 8 766 5 0 12080 , 0 3E+0 66 E+06 21E+0 5 3E+0 339E+0 6 3E+01 , 4 , 1.9 1 .586 .066 .292 7.9 2 .322 0 0 4 90 , 93 8 4 1 09 14 2 034 54 5 0693 , 3 79 435 9 64 1 4 788 177 4 8 24 470, 917,9 . 05 3 .3 .17 . 55 2 6.82 .587 12085 , 622E+0 29 E+06 8 727E+0 3 E+0 494E+0 3E+06 , 4 1 543 301 121 1517 0 0 4 ,90 , 93 .468 1.17 7.896 3.9 0 5. 6 5 3.9488 3 , 396 18 51 1 7 9 589 7 69 ,470 917 9 3 063 145 547 2 317 572 12090 , , .2 E+0 . 2E+06 6.7 E+0 .374E+0 .058E+0 .39 E+01 4, 1 02 9 62 5 46 21 4 8 1 232 0 0 4, 90 93 143 15 50 3 053 76 5 3 0 53 , 3 , .087 8.706 5.8 1 2.90 . 3 2.924 470 ,917 9 34 3 28 5 4 76 2 14 782 12095 , 9 8 8E+02 7 878E+0 293E+0 628E+0 3 939E+0 647E+06 , 4 , .35 .493 5 .035 .5 0 .7 7 .517 0 0 4 90 , 93 8 902 12 4 789 37 564 5 3958 , 3 46 6 7 0 56 1 2 2 2 390 2 2789 470, 917,9 .0 5 . 5 .3 4 .151 2 .225 .16 12100 , 7 6 E+02 35E+0 122E+0 047E+0 3 0 8E+0 0 1E+01 , 4 288 5 8 6 5 3 9 1 1 9 2 91 1 92 0 0 4 ,90 , 93 6.933 .5 1 .730 .8 .776 5 .8 53 3 , 594 28 548 1 76 640 7744 ,470 917 9 7 023 375 676 2 5 2 687 12105 , , 5. 67E+02 4.778E+0 .21 E+0 .594E+0 .389E+0 . 0 E+06 4, 6 6 45 5 3 054 1 1 2 2 3 1 527 0 0 4, 90 93 3 9 3 2 90 442 16 5 4528 , 3 , .13 .11 .763 1 .3 .056 .39 470 ,917 9 4 885 3 9 2 628 05 2 1 9 14 12110 , 47E+02 721E+0 5 0E+0 2 1E+0 8 1E+0 2 0E+01 , 4 , .420 .540 5 .37 1.18 .770 1.1892 0 0 4 90 , 93 20 367 2 2 2 23 684 5 313 , 3 0 203 15 1 068 0 0764 470, 917,9 3.8 5 3.0 .047 . 16 2 1.523 . 24 12115 , 619E+02 2 898E+0 1 9 E+0 9 6 7E+01 449E+0 9 7 E+006 , 4 443 75 5 8 19 378 267 0 0 4 ,90 , 93 .27 .622 .762 8.74 . 11 5 8.8098 3 , 1 4 4 676 1 321 2 7 3809 ,470 917 9 2 96 373 594 7 915 1 186 7 9712120 , , .819E+02 2.2 7E+0 1. 1 E+0 .5 9E+01 . 2 E+0 .5 2E+001 4, 681 14 5 443 162 073 2132 0 0 4, 90 93 550 0 2 3 2 6 8 1 5 6 863 , 3 , .426 1.9 . 05 1 .480 9.71 4 . 264 470 ,917 9 2 308 8 8 2 4 239 082125 , 195E+02 75 E+0 1 181E+0 5 3E+01 8 8 E+0 5 9 5E+006 , 4 , .08 .67 5 . 23 .577 .360 .6177 0 0 4 90 , 93 1 9 590 069 305 7 952 3438 , 3 8 9 1 13 17 1 04 5 5 4 089 470, 917,9 .7 7 .439 9.6 0 4.8 1 .196 4.832130 , 10E+02 36 E+0 198E+0 66E+01 6 84 E+0 599E+001 , 4 626 02 5 8 74 4 11 752 0 0 4 ,90 , 93 1.54 .2 .323 .132 . 3 .1613 3 , 471 1 178 7 917 3 9 0 5 4 3 9584 ,470 917 9 0 21 531 0 7 9 604 72135 , , .33 E+02 .066E+0 .16 E+0 .556E+01 .33 E+0 .582E+006 4, 266 14 5 6 8 4 383 071 4077 0 0 4, 90 93 1 5 9 647 4 482 218 4 823 2418 , 3 , .14 .17 . 6 3.061 .588 4 3.0 39 470 ,917 9 090 8 729 5 5 0 2 9 2 64 2 93Waste-In-PlaceWaste AcceptedVancouver Landfill_Phase 1lease choose a third unit o  measure to represent all of the emission rate  below.Total landfill gas MethaneYeara  ft^3/min2066 0 0 4,470,903 4,917,993 4.194E+03 3.358E+06 2.256E+02 1.120E+03 1.679E+06 1.128E+022067 0 0 4,470,903 4,917,993 3.989E+03 3.195E+06 2.146E+02 1.066E+03 1.597E+06 1.073E+022068 0 0 4,470,903 4,917,993 3.795E+03 3.039E+06 2.042E+02 1.014E+03 1.519E+06 1.021E+022069 0 0 4,470,903 4,917,993 3.610E+03 2.891E+06 1.942E+02 9.642E+02 1.445E+06 9.711E+012070 0 0 4,470,903 4,917,993 3.434E+03 2.750E+06 1.847E+02 9.172E+02 1.375E+06 9.237E+012071 0 0 4,470,903 4,917,993 3.266E+03 2.615E+06 1.757E+02 8.725E+02 1.308E+06 8.787E+012072 0 0 4,470,903 4,917,993 3.107E+03 2.488E+06 1.672E+02 8.299E+02 1.244E+06 8.358E+012073 0 0 4,470,903 4,917,993 2.955E+03 2.367E+06 1.590E+02 7.894E+02 1.183E+06 7.951E+012074 0 0 4,470,903 4,917,993 2.811E+03 2.251E+06 1.513E+02 7.509E+02 1.126E+06 7.563E+012075 0 0 4,470,903 4,917,993 2.674E+03 2.141E+06 1.439E+02 7.143E+02 1.071E+06 7.194E+012076 0 0 4,470,903 4,917,993 2.544E+03 2.037E+06 1.369E+02 6.795E+02 1.018E+06 6.843E+012077 0 0 4,470,903 4,917,993 2.420E+03 1.938E+06 1.302E+02 6.463E+02 9.688E+05 6.509E+012078 0 0 4,470,903 4,917,993 2.302E+03 1.843E+06 1.238E+02 6.148E+02 9.215E+05 6.192E+012079 0 0 4,470,903 4,917,993 2.189E+03 1.753E+06 1.178E+02 5.848E+02 8.766E+05 5.890E+012080 0 0 4,470,903 4,917,993 2.083E+03 1.668E+06 1.121E+02 5.563E+02 8.339E+05 5.603E+012081 0 0 4,470,903 4,917,993 1.981E+03 1.586E+06 1.066E+02 5.292E+02 7.932E+05 5.329E+012082 0 0 4,470,903 4,917,993 1.884E+03 1.509E+06 1.014E+02 5.034E+02 7.545E+05 5.069E+012083 0 0 4,470,903 4,917,993 1.793E+03 1.435E+06 9.644E+01 4.788E+02 7.177E+05 4.822E+012084 0 0 4,470,903 4,917,993 1.705E+03 1.365E+06 9.174E+01 4.555E+02 6.827E+05 4.587E+012085 0 0 4,470,903 4,917,993 1.622E+03 1.299E+06 8.727E+01 4.332E+02 6.494E+05 4.363E+012086 0 0 4,470,903 4,917,993 1.543E+03 1.235E+06 8.301E+01 4.121E+02 6.177E+05 4.151E+012087 0 0 4,470,903 4,917,993 1.468E+03 1.175E+06 7.896E+01 3.920E+02 5.876E+05 3.948E+012088 0 0 4,470,903 4,917,993 1.396E+03 1.118E+06 7.511E+01 3.729E+02 5.589E+05 3.756E+012089 0 0 4,470,903 4,917,993 1.328E+03 1.063E+06 7.145E+01 3.547E+02 5.317E+05 3.572E+012090 0 0 4,470,903 4,917,993 1.263E+03 1.012E+06 6.796E+01 3.374E+02 5.058E+05 3.398E+012091 0 0 4,470,903 4,917,993 1.202E+03 9.622E+05 6.465E+01 3.210E+02 4.811E+05 3.232E+012092 0 0 4,470,903 4,917,993 1.143E+03 9.153E+05 6.150E+01 3.053E+02 4.576E+05 3.075E+012093 0 0 4,470,903 4,917,993 1.087E+03 8.706E+05 5.850E+01 2.904E+02 4.353E+05 2.925E+012094 0 0 4,470,903 4,917,993 1.034E+03 8.282E+05 5.564E+01 2.763E+02 4.141E+05 2.782E+012095 0 0 4,470,903 4,917,993 9.838E+02 7.878E+05 5.293E+01 2.628E+02 3.939E+05 2.647E+012096 0 0 4,470,903 4,917,993 9.358E+02 7.493E+05 5.035E+01 2.500E+02 3.747E+05 2.517E+012097 0 0 4,470,903 4,917,993 8.902E+02 7.128E+05 4.789E+01 2.378E+02 3.564E+05 2.395E+012098 0 0 4,470,903 4,917,993 8.468E+02 6.780E+05 4.556E+01 2.262E+02 3.390E+05 2.278E+012099 0 0 4,470,903 4,917,993 8.055E+02 6.450E+05 4.334E+01 2.151E+02 3.225E+05 2.167E+012100 0 0 4,470,903 4,917,993 7.662E+02 6.135E+05 4.122E+01 2.047E+02 3.068E+05 2.061E+012101 0 0 4,470,903 4,917,993 7.288E+02 5.836E+05 3.921E+01 1.947E+02 2.918E+05 1.961E+012102 0 0 4,470,903 4,917,993 6.933E+02 5.551E+05 3.730E+01 1.852E+02 2.776E+05 1.865E+012103 0 0 4,470,903 4,917,993 6.594E+02 5.281E+05 3.548E+01 1.761E+02 2.640E+05 1.774E+012104 0 0 4,470,903 4,917,993 6.273E+02 5.023E+05 3.375E+01 1.676E+02 2.512E+05 1.687E+012105 0 0 4,470,903 4,917,993 5.967E+02 4.778E+05 3.210E+01 1.594E+02 2.389E+05 1.605E+012106 0 0 4,470,903 4,917,993 5.676E+02 4.545E+05 3.054E+01 1.516E+02 2.273E+05 1.527E+012107 0 0 4,470,903 4,917,993 5.399E+02 4.323E+05 2.905E+01 1.442E+02 2.162E+05 1.452E+012108 0 0 4,470,903 4,917,993 5.136E+02 4.113E+05 2.763E+01 1.372E+02 2.056E+05 1.382E+012109 0 0 4,470,903 4,917,993 4.885E+02 3.912E+05 2.628E+01 1.305E+02 1.956E+05 1.314E+012110 0 0 4,470,903 4,917,993 4.647E+02 3.721E+05 2.500E+01 1.241E+02 1.861E+05 1.250E+012111 0 0 4,470,903 4,917,993 4.420E+02 3.540E+05 2.378E+01 1.181E+02 1.770E+05 1.189E+012112 0 0 4,470,903 4,917,993 4.205E+02 3.367E+05 2.262E+01 1.123E+02 1.684E+05 1.131E+012113 0 0 4,470,903 4,917,993 4.000E+02 3.203E+05 2.152E+01 1.068E+02 1.601E+05 1.076E+012114 0 0 4,470,903 4,917,993 3.805E+02 3.047E+05 2.047E+01 1.016E+02 1.523E+05 1.024E+012115 0 0 4,470,903 4,917,993 3.619E+02 2.898E+05 1.947E+01 9.667E+01 1.449E+05 9.736E+002116 0 0 4,470,903 4,917,993 3.443E+02 2.757E+05 1.852E+01 9.196E+01 1.378E+05 9.261E+002117 0 0 4,470,903 4,917,993 3.275E+02 2.622E+05 1.762E+01 8.747E+01 1.311E+05 8.809E+002118 0 0 4,470,903 4,917,993 3.115E+02 2.494E+05 1.676E+01 8.321E+01 1.247E+05 8.380E+002119 0 0 4,470,903 4,917,993 2.963E+02 2.373E+05 1.594E+01 7.915E+01 1.186E+05 7.971E+002120 0 0 4,470,903 4,917,993 2.819E+02 2.257E+05 1.516E+01 7.529E+01 1.128E+05 7.582E+002121 0 0 4,470,903 4,917,993 2.681E+02 2.147E+05 1.443E+01 7.162E+01 1.073E+05 7.213E+002122 0 0 4,470,903 4,917,993 2.550E+02 2.042E+05 1.372E+01 6.812E+01 1.021E+05 6.861E+002123 0 0 4,470,903 4,917,993 2.426E+02 1.943E+05 1.305E+01 6.480E+01 9.713E+04 6.526E+002124 0 0 4,470,903 4,917,993 2.308E+02 1.848E+05 1.242E+01 6.164E+01 9.239E+04 6.208E+002125 0 0 4,470,903 4,917,993 2.195E+02 1.758E+05 1.181E+01 5.863E+01 8.789E+04 5.905E+002126 0 0 4,470,903 4,917,993 2.088E+02 1.672E+05 1.123E+01 5.577E+01 8.360E+04 5.617E+002127 0 0 4,470,903 4,917,993 1.986E+02 1.590E+05 1.069E+01 5.305E+01 7.952E+04 5.343E+002128 0 0 4,470,903 4,917,993 1.889E+02 1.513E+05 1.017E+01 5.047E+01 7.565E+04 5.083E+002129 0 0 4,470,903 4,917,993 1.797E+02 1.439E+05 9.669E+00 4.801E+01 7.196E+04 4.835E+002130 0 0 4,470,903 4,917,993 1.710E+02 1.369E+05 9.198E+00 4.566E+01 6.845E+04 4.599E+002131 0 0 4,470,903 4,917,993 1.626E+02 1.302E+05 8.749E+00 4.344E+01 6.511E+04 4.375E+002132 0 0 4,470,903 4,917,993 1.547E+02 1.239E+05 8.323E+00 4.132E+01 6.193E+04 4.161E+002133 0 0 4,470,903 4,917,993 1.471E+02 1.178E+05 7.917E+00 3.930E+01 5.891E+04 3.958E+0013 9 4 2 1 5 7 3 0 3 7 1 5 4 3 5 01 33 2 0 6 5 7 0 3 5 1 5 3 4 3 013 1 2 1 4 5 6 14 0 3 383 1 5 0 1 4 3 40 03 1 9 647 4 6 4 0 3 18 1 4 8 3 4 3 4 08 1 6 0 1 588 0 32139 0 0 4,470,903 4,917,993 1.090E+02 8.729E+04 5.865E+00 2.912E+01 4.364E+04 2.932E+00237      GRAPHS Landfill Name or Identifier: Vancouver Landfill_Phase 10.000E+001.000E+042.000E+043.000E+044.000E+045.000E+046.000E+047.000E+048.000E+049.000E+04EmissionsYearMegagrams Per YearTotal landfill gas Methane Carbon dioxide NMOC0.000E+001.000E+072.000E+073.000E+074.000E+075.000E+076.000E+077.000E+07EmissionsYearCubic Meters Per YearTotal landfill gas Methane Carbon dioxide NMOC238  A.1.2 Inventory Modeling Parameters   USER INPUTS Landfill Name or Identifier:TRUE4: ENTER WASTE ACCEPTANCE RATES1: PROVIDE LANDFILL CHARACTERISTICS Mg/yearLandfill Open Year 1999Landfill Closure Year 2008 Input Units Calculated UnitsHave Model Calculate Closure Year?FALSE(Mg/year) (short tons/year)Waste Design Capacitymegagrams1999 483,572 531,9292000 456,666 502,3322001 454,381 499,8192: DETERMINE MODEL PARAMETERS 2002 530,775 583,852Methane Generation Rate, k (year-1)2003 553,951 609,3460.042004 623,019 685,321Potential Methane Generation Capacity, Lo (m3/Mg )2005 691,847 761,0321002006 514,692 566,162NMOC Concentration (ppmv as hexane )2007 040002008 162,000 178,200Methane Content (% by volume )2009502010201120123: SELECT GASES/POLLUTANTS 2013Gas / Pollutant #1 Default pollutant parameters are currently being used by model.2014Total landfill gas2015Gas / Pollutant #22016Methane2017Gas / Pollutant #32018Carbon dioxide2019Gas / Pollutant #42020NMOC202120222023Description/Comments:2024202520262027202820292030Waste Composition for the these three years was C, D, and E (as per GVRD waste composition studies in 2001, 2004, and 2007 and corrected for DLC). DLC received at VLF are included in the the reported tonnagesInput Units:YearVancouver Landfill_Phase 1Inventory Conventional - 0.04Inventory Conventional - 100CAA - 50% by volumemegagramsRestore Default Model ParametersMg/yearTotal landfill gasClear ALL Non-Parameter Inputs/SelectionsCAA - 4,000MethaneCarbon dioxideNMOCEdit Existing or Add New Pollutant ParametersRestore Default Pollutant Parameters239   RESULTS Landfill Name or Identifier:Closure Year (with 80-year limit) = 2008Methane = 50 % by volume User-specified Unit: av ft 3^/min(Mg/year) (short tons/year) (Mg) (short tons) (Mg/year) (m3/year) (av ft^3/min) (Mg/year) (m3/year) (av ft^3/min)1999 483,572 531,929 0 0 0 0 0 0 0 02000 456,666 502,332 483,572 531,929 4.745E+03 3.800E+06 2.553E+02 1.268E+03 1.900E+06 1.277E+022001 454,381 499,819 940,237 1,034,261 9.040E+03 7.239E+06 4.864E+02 2.415E+03 3.620E+06 2.432E+022002 530,775 583,852 1,394,618 1,534,080 1.314E+04 1.053E+07 7.072E+02 3.511E+03 5.263E+06 3.536E+022003 553,951 609,346 1,925,393 2,117,932 1.784E+04 1.428E+07 9.597E+02 4.765E+03 7.142E+06 4.799E+022004 623,019 685,321 2,479,344 2,727,278 2.257E+04 1.808E+07 1.215E+03 6.030E+03 9.038E+06 6.073E+022005 691,847 761,032 3,102,363 3,412,600 2.780E+04 2.226E+07 1.496E+03 7.426E+03 1.113E+07 7.479E+022006 514,692 566,162 3,794,211 4,173,632 3.350E+04 2.683E+07 1.802E+03 8.949E+03 1.341E+07 9.012E+022007 0 0 4,308,903 4,739,793 3.724E+04 2.982E+07 2.004E+03 9.947E+03 1.491E+07 1.002E+032008 162,000 178,200 4,308,903 4,739,793 3.578E+04 2.865E+07 1.925E+03 9.557E+03 1.433E+07 9.625E+022009 0 0 4,470,903 4,917,993 3.597E+04 2.880E+07 1.935E+03 9.607E+03 1.440E+07 9.675E+022010 0 0 4,470,903 4,917,993 3.456E+04 2.767E+07 1.859E+03 9.230E+03 1.384E+07 9.296E+022011 0 0 4,470,903 4,917,993 3.320E+04 2.659E+07 1.786E+03 8.868E+03 1.329E+07 8.931E+022012 0 0 4,470,903 4,917,993 3.190E+04 2.554E+07 1.716E+03 8.520E+03 1.277E+07 8.581E+022013 0 0 4,470,903 4,917,993 3.065E+04 2.454E+07 1.649E+03 8.186E+03 1.227E+07 8.245E+022014 0 0 4,470,903 4,917,993 2.945E+04 2.358E+07 1.584E+03 7.865E+03 1.179E+07 7.921E+022015 0 0 4,470,903 4,917,993 2.829E+04 2.265E+07 1.522E+03 7.557E+03 1.133E+07 7.611E+022016 0 0 4,470,903 4,917,993 2.718E+04 2.177E+07 1.462E+03 7.261E+03 1.088E+07 7.312E+022017 0 0 4,470,903 4,917,993 2.612E+04 2.091E+07 1.405E+03 6.976E+03 1.046E+07 7.026E+022018 0 0 4,470,903 4,917,993 2.509E+04 2.009E+07 1.350E+03 6.702E+03 1.005E+07 6.750E+022019 0 0 4,470,903 4,917,993 2.411E+04 1.930E+07 1.297E+03 6.440E+03 9.652E+06 6.485E+022020 0 0 4,470,903 4,917,993 2.316E+04 1.855E+07 1.246E+03 6.187E+03 9.274E+06 6.231E+022021 0 0 4,470,903 4,917,993 2.225E+04 1.782E+07 1.197E+03 5.945E+03 8.910E+06 5.987E+022022 0 0 4,470,903 4,917,993 2.138E+04 1.712E+07 1.150E+03 5.711E+03 8.561E+06 5.752E+022023 0 0 4,470,903 4,917,993 2.054E+04 1.645E+07 1.105E+03 5.487E+03 8.225E+06 5.527E+022024 0 0 4,470,903 4,917,993 1.974E+04 1.581E+07 1.062E+03 5.272E+03 7.903E+06 5.310E+022025 0 0 4,470,903 4,917,993 1.896E+04 1.519E+07 1.020E+03 5.066E+03 7.593E+06 5.102E+022026 0 0 4,470,903 4,917,993 1.822E+04 1.459E+07 9.803E+02 4.867E+03 7.295E+06 4.902E+022027 0 0 4,470,903 4,917,993 1.751E+04 1.402E+07 9.419E+02 4.676E+03 7.009E+06 4.709E+022028 0 0 4,470,903 4,917,993 1.682E+04 1.347E+07 9.050E+02 4.493E+03 6.734E+06 4.525E+022029 0 0 4,470,903 4,917,993 1.616E+04 1.294E+07 8.695E+02 4.317E+03 6.470E+06 4.347E+022030 0 0 4,470,903 4,917,993 1.553E+04 1.243E+07 8.354E+02 4.147E+03 6.217E+06 4.177E+022031 0 0 4,470,903 4,917,993 1.492E+04 1.195E+07 8.026E+02 3.985E+03 5.973E+06 4.013E+022032 0 0 4,470,903 4,917,993 1.433E+04 1.148E+07 7.712E+02 3.828E+03 5.739E+06 3.856E+022033 0 0 4,470,903 4,917,993 1.377E+04 1.103E+07 7.409E+02 3.678E+03 5.514E+06 3.705E+022034 0 0 4,470,903 4,917,993 1.323E+04 1.059E+07 7.119E+02 3.534E+03 5.297E+06 3.559E+022035 0 0 4,470,903 4,917,993 1.271E+04 1.018E+07 6.839E+02 3.396E+03 5.090E+06 3.420E+022036 0 0 4,470,903 4,917,993 1.221E+04 9.780E+06 6.571E+02 3.262E+03 4.890E+06 3.286E+022037 0 0 4,470,903 4,917,993 1.173E+04 9.397E+06 6.314E+02 3.135E+03 4.698E+06 3.157E+022038 0 0 4,470,903 4,917,993 1.127E+04 9.028E+06 6.066E+02 3.012E+03 4.514E+06 3.033E+022039 0 0 4,470,903 4,917,993 1.083E+04 8.674E+06 5.828E+02 2.894E+03 4.337E+06 2.914E+022040 0 0 4,470,903 4,917,993 1.041E+04 8.334E+06 5.600E+02 2.780E+03 4.167E+06 2.800E+022041 0 0 4,470,903 4,917,993 1.000E+04 8.007E+06 5.380E+02 2.671E+03 4.004E+06 2.690E+022042 0 0 4,470,903 4,917,993 9.608E+03 7.693E+06 5.169E+02 2.566E+03 3.847E+06 2.585E+022043 0 0 4,470,903 4,917,993 9.231E+03 7.392E+06 4.966E+02 2.466E+03 3.696E+06 2.483E+022044 0 0 4,470,903 4,917,993 8.869E+03 7.102E+06 4.772E+02 2.369E+03 3.551E+06 2.386E+022045 0 0 4,470,903 4,917,993 8.521E+03 6.823E+06 4.585E+02 2.276E+03 3.412E+06 2.292E+022046 0 0 4,470,903 4,917,993 8.187E+03 6.556E+06 4.405E+02 2.187E+03 3.278E+06 2.202E+022047 0 0 4,470,903 4,917,993 7.866E+03 6.299E+06 4.232E+02 2.101E+03 3.149E+06 2.1