Waste landfill plant and waste disposal plant efficiencies in China


As resident awareness of environmental issues has grown, waste disposal has become an important part of urban environmental governance. Most previous research from developed countries that has sought to evaluate the technical, energy and environmental efficiencies of urban waste disposal have employed DEA. However, as there has been little research into China’s waste disposal efficiencies, this study used a dynamic DDF (directional distance function) DEA (Data Envelopment Analysis) to analyze the total waste disposal efficiencies in 23 provinces in China from 2012 to 2016, from which it was found that nine had excellent efficiencies of 1, but significant efficiency improvements were needed in 14 others.

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  1. 1.

    Rogge N, De JS (2012) Evaluating the efficiency of municipalities in collecting and processing municipal solid waste: a shared input DEA-model. Waste Manage 32(10):1968–1978

    Article  Google Scholar 

  2. 2.

    Perez-Lopez G, Prior D, Zafra-Gomez JL (2018) Temporal scale efficiency in DEA panel data estimations. An application to the solid waste disposal service in Spain. Omega 76:18–27

    Article  Google Scholar 

  3. 3.

    Halkos G, Petrou KN (2019) Assessing 28 EU member states’ environmental efficiency in national waste generation with DEA. J Clean Prod 208:509–521

    Article  Google Scholar 

  4. 4.

    Brukh R, Barat R, Mitra S (2006) The effect of waste concentration on destruction efficiency during incineration. Environ Eng Sci 23(2):383–392

    Article  Google Scholar 

  5. 5.

    Solheimslid T, Harneshaug HK, Lümmen N (2015) Calculation of first-law and second-law-efficiency of a Norwegian combined heat and power facility driven by municipal waste incineration—A case study. Energy Convers Manage 95:149–159

    Article  Google Scholar 

  6. 6.

    Tsai WT (2016) Analysis of municipal solid waste incineration plants for promoting power generation efficiency in Taiwan. J Mater Cycles Waste Manag 18(2):393–398

    Article  Google Scholar 

  7. 7.

    Petridis K, Dey PK (2016) A DEA/Goal programming model for incineration plants performance in the UK. Waste Manag Resour Util 35:257–264

    Google Scholar 

  8. 8.

    Kuusik A, Pachel K, Kuusik A (2016) Assessment of landfill wastewater pollutants and efficiency of different treatment methods. Proc Estonian Acad Sci 65(4):452–471

    Article  Google Scholar 

  9. 9.

    Martorana R, Capizzi P, D’Alessandro A (2016) Electrical resistivity and induced polarization tomographies to test the efficiency and safety of the new landfill of Bellolampo (Palermo, Italy). BOLLETTINO DI GEOFISICA TEORICA ED APPLICATA 57(4):313–327

    Google Scholar 

  10. 10.

    Bae J (2018) Evaluation of power generation efficiency and GHG reduction effect in municipal waste incineration facilities—enhancement of waste heat recovery capability. New Renew Energy 14(3):20–29

    Article  Google Scholar 

  11. 11.

    Gun PC (2018) A study on improvement measures of energy recovery efficiency through analysis of operational status of municipal solid waste incineration facilities. J Korea Soc Waste Manage 35(8):762–769

    Article  Google Scholar 

  12. 12.

    Beylot A, Hochar A, Michel P (2018) Municipal solid waste incineration in France: an overview of air pollution control techniques, emissions, and energy efficiency. J Ind Ecol 22(5):1016–1026

    Article  Google Scholar 

  13. 13.

    Vakalis S, Moustakas K (2019) Applications of the 3T Method and the R1 Formula as Efficiency Assessment Tools for Comparing Waste-to-Energy and Landfilling. Energies 12(6):1066

    Article  Google Scholar 

  14. 14.

    Magalhaes, V., Moutinho, V., and Marques, A. Scoring method of eco-efficiency using DEA approach: evidence from European waste sectors. 2019, 4th International Conference on Energy and Environment—Bringing together Engineering and Economics.

  15. 15.

    Ayodele TR, Alao MA, Ogunjuyigbe ASO (2020) Effect of collection efficiency and oxidation factor on greenhouse gas emission and life cycle cost of landfill distributed energy generation. Sustainable Cities and Society 52:13-18

    Article  Google Scholar 

  16. 16.

    Li J, He C, Tian T (2020) UASB-modified Bardenpho process for enhancing bio-treatment efficiency of leachate from a municipal solid waste incineration plant. Waste Manage 102:97–105

    Article  Google Scholar 

  17. 17.

    Antic K, Sremacki M, Petrovic M (2019) Analysis of leachate from a non-sanitary landfill and assessment of removal efficiency of caffeine using material and substance flow analysis. Electron J Fac Civil Eng OSIJEK-E-GFOS 19:58–67

    Google Scholar 

  18. 18.

    Sisani, F., Contini, S. and Di, M. F. Energetic efficiency of landfill: An Italian case study. 2016, 71st Conference of the Italian-Thermal-Machines-Engineering-Association (ATI).

  19. 19.

    Madon I, Drev D, Likar J (2019) Long-term groundwater protection efficiency of different types of sanitary landfills: Data description. Data in Brief 26:104488

    Article  Google Scholar 

  20. 20.

    Haruki K (2010) An environmental evaluation of household waste processors. Electron Commun Japan 93(7):42–52

    Article  Google Scholar 

  21. 21.

    Duan Z, Scheutz C, Kjeldsen P (2020) Trace gas emissions from municipal solid waste landfills: a review. Waste Manage 119(1):39–62

    Google Scholar 

  22. 22.

    Ishimura Y, Takeuchi K (2019) The spatial concentration of waste landfill sites in Japan. Resour Energy Econ 58:101121

    Article  Google Scholar 

  23. 23.

    Charnes A, Cooper WW, Rhodes E (1978) Measuring the efficiency of decision making units. Eur J Oper Res 2(6):429–444

    MathSciNet  Article  Google Scholar 

  24. 24.

    Banker RD, Charnes A, Cooper WW (1984) Some models for estimating technical and scale inefficiencies in data envelopment analysis. Manag Sci 30(9):1078–1092

    Article  Google Scholar 

  25. 25.

    Tone K (2001) A slacks-based measure of efficiency in data envelopment analysis. Eur J Oper Res 130(3):498–509

    MathSciNet  Article  Google Scholar 

  26. 26.

    Chung YH, Färe R, Grosskopf S (1997) Productivity and undesirable outputs: a directional distance function approach. J Environ Manage 51:229–240

    Article  Google Scholar 

  27. 27.

    Färe R, Grosskopf S (2010) Directional distance functions and slacks-based measures of efficiency. Eur J Oper Res 200:320–322

    Article  Google Scholar 

  28. 28.

    Chen PC, Yu MM, Chang CC, Hsu SH, Managi S (2015) The enhanced Russell-based directional distance measure with undesirable outputs: numerical example considering CO2 emissions. Omega 53:30–40

    Article  Google Scholar 

  29. 29.

    Kloop, G. The Analysis of the efficiency of production system with multiple inputs and outputs, 1985, University of Illinois at Chicago. Industrial and Systems Engineering College.

  30. 30.

    Malmquist S (1953) Index numbers and indifference surfaces. Trabajos de Estadistica 4:209–242

    MathSciNet  Article  Google Scholar 

  31. 31.

    Färe R, Grosskopf S, Norris M, Zhang Z (1994) Productivity growth, technical progress, and efficiency change in industrialized countries. Am Econ Rev 84(1):66–83

    Google Scholar 

  32. 32.

    Färe R, Grosskopf S (1996) Productivity and intermediate products: a frontier approach. Econ Lett 50:65–70

    Article  Google Scholar 

  33. 33.

    Nemoto J, Goto M (1999) Dynamic data envelopment analysis: modeling intertemporal behavior of a frim in the presence of productive inefficiencies. Econ Lett 64(1):51–56

    Article  Google Scholar 

  34. 34.

    Nemoto J, Goto M (2003) Measurement of dynamic efficiency in production: an application of data envelopment analysis. J Prod Anal 19(2–3):191–210

    Article  Google Scholar 

  35. 35.

    Sueyoshi T, Sekitani K (2005) Returns to scale in dynamic DEA. Eur J Oper Res 161(2):536–544

    MathSciNet  Article  Google Scholar 

  36. 36.

    Amirteimoori A (2006) Data envelopment analysis in dynamic framework. Appl Math Comput 181(1):21–28

    MathSciNet  MATH  Google Scholar 

  37. 37.

    Tone K, Tsutsui M (2010) Dynamic DEA: a slacks-based measure approach. Omega 38:145–156

    Article  Google Scholar 

  38. 38.

    Zhou P, Ang BW, Wang H (2012) Energy and CO2 emission performance in electricity generation: a non-radial directional distance function approach. Eur J Oper Res 221:625–635

    Article  Google Scholar 

  39. 39.

    Zhang N, Zhou P, Choi Y (2013) Energy efficiency, CO2 emission performance and technology gaps in fossil fuel electricity generation in Korea: a meta-frontier non-radial directional distance function analysis. Energy Policy 56:653–662

    Article  Google Scholar 

  40. 40.

    Hu JL, Wang SC (2006) Total-factor energy efficiency of regions in China. Energy Policy 34:3206–3217

    Article  Google Scholar 

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This research is supported by National Natural Science Fund in China, No. 71773082; Sichuan Science Project, No. 2020JDR0079; The Fundamental Research Funds for the Central Universities (Grants No. SCU-BS-PY201016).

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Correspondence to Yung-ho Chiu.

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Li, Y., Cen, H., Chiu, Yh. et al. Waste landfill plant and waste disposal plant efficiencies in China. J Mater Cycles Waste Manag (2021). https://doi.org/10.1007/s10163-021-01178-8

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  • Waste disposal
  • Dynamic DDF
  • Data envelopment analysis model