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Municipal solid waste generation in China: influencing factor analysis and multi-model forecasting

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Abstract

In the developing countries, the inadequacy of basic waste data is a significant obstacle for municipal solid waste management. To evaluate an effective waste management plan, identification of influencing socio-economic factors and projection of municipal solid waste generation (MSWG) plays a crucial role. Yet, several forecasting methods have been utilized to quantify future MSWG. In this study, we investigated the influencing socio-economic factors for MSWG in China using the fuzzy logic method, and a short-term forecasting of MSWG was conducted using multi-model approach. The Grey (1, 1), linear regression, and artificial neural network (ANN) models were evaluated for short-term forecasting. The factor analysis results show that urban population growth is the most influencing socio-economic factor for MSWG, and the influence of GDP on waste generation is not so obvious. Afterward, the multi-model forecasting results indicate an increasing trend of MSWG. Based on the absolute percentage error, root mean-squared error, mean absolute error, and coefficient of determination (R2), ANN found as the most acceptable model to forecast MSWG in China. Hence, the forecasting by ANN model illustrates that MSWG in China will be 24666.65 (104 tons) by 2030.

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Acknowledgements

We thank the editors and anonymous reviewers for giving us many constructive comments that significantly improved the paper.

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Authors and Affiliations

  1. School of Management, University of Science and Technology of China, Hefei, 230026, China

    Leaksmy Chhay

  2. School of Public Affair, University of Science and Technology of China, Hefei, 230026, China

    Md Amjad Hossain Reyad & Rathny Suy

  3. School of Economic and Business Administration, Chongqing University, Chongqing, China

    Md Rafiqul Islam

  4. CAS Key Laboratory of Crust-Mantle Materials and the Environments, School of Earth and Space Sciences, University of Science and Technology of China, Hefei, 230026, China

    Md Manik Mian

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  1. Leaksmy Chhay
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  2. Md Amjad Hossain Reyad
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Correspondence to Md Manik Mian.

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Chhay, L., Reyad, M.A.H., Suy, R. et al. Municipal solid waste generation in China: influencing factor analysis and multi-model forecasting. J Mater Cycles Waste Manag 20, 1761–1770 (2018). https://doi.org/10.1007/s10163-018-0743-4

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