Estimation of the methane generation rate constant using a large-scale respirometer at a landfill site

  • Park, Jin-Kyu (Ecowillplus Co., Ltd.) ;
  • Tameda, Kazuo (AIG Collaborative Research Institute for Resource Recycling and Environmental Pollution Control, Fukuoka University) ;
  • Higuchi, Sotaro (Recycling and Eco-Technology Specialty Graduate School of Engineering, Fukuoka University) ;
  • Lee, Nam-Hoon (Department of Environmental and Energy Engineering, Anyang University)
  • Received : 2017.01.02
  • Accepted : 2017.04.04
  • Published : 2017.12.31


The objective of this study is the evaluation of the performance of a large-scale respirometer (LSR) of 17.7 L in the determination of the methane generation rate constant (k) values. To achieve this objective, a comparison between anaerobic (GB21) and LSR tests was conducted. The data were modeled using a linear function, and the resulting correlation coefficient ($R^2$) of the linear regression is 0.91. This result shows that despite the aerobic conditions, the biodegradability values that were obtained from the LSR test produced results that are similar to those from the GB21 test. In this respect, the LSR test can be an indicator of the anaerobic biodegradability for landfill waste. In addition, the results show the high repeatability of the tests with an average coefficient of variance (CV) that is lower than 10%; furthermore, the CV for the LSR is lower than that of the GB21, which indicates that the LSR-test method could provide a better representation of waste samples. Therefore, the LSR method allows for both the prediction of the long-term biodegradation potential in a shorter length of time and the reduction of the sampling errors that are caused by the heterogeneity of waste samples. The k values are $0.156y^{-1}$ and $0.127y^{-1}$ for the cumulative biogas production (GB21) and the cumulative oxygen uptake for the LSR, respectively.


Biodegradability;First-order decay (FOD) model;Landfill;Large-scale respirometer;Methane-generation rate constant


Supported by : National Research Foundation of Korea (NRF)


  1. Manfredi S, Tonini D, Christensen TH. Landfilling of waste: Accounting of greenhouse gases and global warming contribution. Waste Manage. Res. 2009;27:825-836.
  2. Siddiqui FZ, Zaidi S, Pandey S, Khan ME. Review of past research and proposed action plan for landfill gas-to-energy applications in India. Waste Manage. Res. 2013;31:3-22.
  3. IPCC. IPCC guidelines for national greenhouse gas inventories: Intergovernmental panel on climate change. Vol. 5. Waste, IGES: Japan; 2006.
  4. US EPA. Landfill gas emissions model (LandGEM) version 3.02 user's guide. Washington D.C.: US Environmental Protection Agency; 2005.
  5. Govindan SS, Agamuthu P. Quantification of landfill methane using modified Intergovernmental Panel on Climate Change's waste model and error function analysis. Waste Manage. Res. 2014;32:1005-1014.
  6. Amini HR, Reinhart DR, Niskanen A. Comparison of first-order- decay modeled and actual field measured municipal solid waste landfill methane data. Waste Manage. 2013;33:2720-2728.
  7. Kim H, Townsend TG. Wet landfill decomposition rate determination using methane yield results for excavated waste samples. Waste Manage. 2012;32:1427-1433.
  8. Calabro PS, Orsi S, Gentili E, Carlo M. Modelling of biogas extraction at an Italian landfill accepting mechanically and biologically treated municipal solid waste. Waste Manage. Res. 2011;29:1277-1285.
  9. Jung Y, Imhoff P, Finsterle S. Estimation of landfill gas generation rate and gas permeability field of refuse using inverse modelling. Transport Porous Med. 2011;90:41-58.
  10. Tolaymat TM, Green RB, Hater GR, et al. Evaluation of landfill gas decay constant for municipal solid waste landfills operated as bioreactors. J. Air Waste Manage. Assoc. 2010;60:91-97.
  11. Mou Z, Scheutz C, Kjeldsen P. Evaluation and application of site-specific data to revise the first-order decay model for estimating landfill gas generation and emissions at Danish landfills. J. Air Waste Manage. Assoc. 2015;65:686-698.
  12. Cho HS, Moon HS, Kim JY. Effect of quantity and composition of waste on the prediction of annual methane potential from landfills. Bioresour. Technol. 2012;109:86-92.
  13. Bayard R, Morais J de A, Ducom MG, Achour F, Rouez M, Gourdon R. Assessment of the effectiveness of an industrial unit of mechanical-biological treatment of municipal solid waste. J. Hazard. Mater. 2010;175:23-32.
  14. Gomez RB, Lima FV, Ferrer AS. The use of respiration indices in the composting process: A review. Waste Manage. Res. 2006;24:37-47.
  15. Binner E, Zach A. Biological reactivity of residual wastes and dependence on the duration of pretreatment. Waste Manage. Res. 1999;17:543-554.
  16. Lesteur M, Bellon-Maurel V, Gonzalez C, et al. Alternative methods for determining anaerobic biodegradability: A review. Process Biochem. 2010;45:431-440.
  17. Kallel A, Matsuto T, Tanaka N. Determination of oxygen consumption for landfilled municipal solid wastes. Waste Manage. Res. 2003;21:346-355.
  18. Binner E, Bohm K, Lechner P. Large scale study on measurement of respiration activity ($AT_4$) by Sapromat and OxiTop. Waste Manage. 2012;32:1752-1759.
  19. Laner D, Fellner J, Brunner PH. Site-specific criteria for the completion of landfill aftercare. Waste Manage. Res. 2012;30:88-99.
  20. Chung J, Kim S, Baek S, et al. Acceleration of aged-landfill stabilization by combining partial nitrification and leachate recirculation: A field-scale study. J. Hazard. Mater. 2015;285:436-444.
  21. Ritzkowski M, Heyer KU, Stegmann R. Fundamental processes and implications during in situ aeration of old landfills. Waste Manage. 2006;26:356-372.
  22. Scaglia B, Confalonieri R, D'Imporzano G, Adani F. Estimating biogasproduction of biologically treated municipal solid waste. Bioresour. Technol. 2010;101:945-952.
  23. Valipour M, Banihabib ME, Behbahani SMR. Comparison of the ARMA, ARIMA, and the autoregressive artificial neural network models in forecasting the monthly inflow of Dez dam reservoir. J. Hydrol. 2013;476:433-441.
  24. Valipour M. How much meteorological information is necessary to achieve reliable accuracy for rainfall estimations? Agriculture 2016;6:53.
  25. Rezael M, Valipour M, Valipour M. Modelling evapotranspiration to increase the accuracy of the estimations based on the climatic parameters. Water Conserv. Sci. Eng. 2016;1:197-207.
  26. Valipour M, Sefidkouhi MAG, Raeini-Sarjaz M. Selecting the best model to estimate potential evapotranspiration with respect to climate change and magnitudes of extreme events. Agr. Water Manage. 2017;180:50-60.
  27. Valipour M. Variations of land use and irrigation for next decades under different scenarios. Irriga: Braz. J. Irrig. Drain. 2016;1:262-288.
  28. Wang X, Nagpure AS, DeCarolis JF, Barlaz MA. Using observed data to improve estimated methane collection from select U.S. landfills. Environ. Sci. Technol. 2013;47:3251-3257.
  29. Wang X, Nagpure AS, DeCarolis JF, Barlaz MA.Characterization of uncertainty in estimation of methane collection from select U.S. landfills. Environ. Sci. Technol. 2015;49:1545-1551.
  30. Amini HR, Reinhart DR, Mackie KR. Determination of first-order landfill gas modelling parameters and uncertainties. Waste Manage. 2012;32:305-316.
  31. Sormunen K, Laurila T, Rintala J. Determination of waste decay rate for a large Finnish landfill by calibrating methane generation models on the basis of methane recovery and emissions. Waste Manage. Res. 2013;31:975-985.
  32. Jeon EJ, Bae SJ, Lee DH, et al. Methane generation potential and biodegradability of MSW components. In: Eleventh International Waste Management and Landfill Symposium; 1-5 October 2007; Sardinia, Italy. S. Margherita di Pula: CISA; 2007.
  33. Ximenes FA, Gardner WD, Cowie AL. The decomposition of wood products in landfill in Sydney, Australia. Waste Manage. 2008;28:2344-2354.