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Characteristics and Forecasting of Municipal Solid Waste Generation in China

Author

Listed:
  • Ane Pan

    (School of Management, Wuhan University of Technology, Wuhan 430070, China)

  • Linxiu Yu

    (School of Management, Wuhan University of Technology, Wuhan 430070, China)

  • Qing Yang

    (School of Management, Wuhan University of Technology, Wuhan 430070, China)

Abstract

The clear understanding of characteristics and trends of solid waste generation is essential for the optimization of waste collection and treatment systems. Taking 651 cities in China as a sample, this study adopts correlation analysis and the Q-type clustering model to explore the characteristics and general trends of solid waste generation (SWG) of five cities of different scale from 2007 to 2016. The results show that the trends of average amount and the annual per capita SWG are diversified in cities of different scale. The permanent residents and regional GDP have prominent impacts on SWG in large cities, megacities, and super megacities compared to those from small and medium-sized cities. The urban area is highly correlated with the SWG of all cities. Nearly one third of cities are characterized by high population density, high economic growth and low SWG. Furthermore, the factor models are developed to forecast the amount of SWG, which have a descriptive capacity of 96%, 95.4%, 92.6%, and 84.2% for the overall cities, large cities, medium-sized cities and small cities respectively.

Suggested Citation

  • Ane Pan & Linxiu Yu & Qing Yang, 2019. "Characteristics and Forecasting of Municipal Solid Waste Generation in China," Sustainability, MDPI, vol. 11(5), pages 1-11, March.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:5:p:1433-:d:212116
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    References listed on IDEAS

    as
    1. Giovanni De Feo & Sabino De Gisi, 2010. "Domestic Separation and Collection of Municipal Solid Waste: Opinion and Awareness of Citizens and Workers," Sustainability, MDPI, vol. 2(5), pages 1-30, May.
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    Cited by:

    1. Johanna Karina Solano Meza & David Orjuela Yepes & Javier Rodrigo-Ilarri & María-Elena Rodrigo-Clavero, 2023. "Comparative Analysis of the Implementation of Support Vector Machines and Long Short-Term Memory Artificial Neural Networks in Municipal Solid Waste Management Models in Megacities," IJERPH, MDPI, vol. 20(5), pages 1-20, February.
    2. Bei Xiong & Ruimei Wang, 2020. "Effect of Environmental Regulation on Industrial Solid Waste Pollution in China: From the Perspective of Formal Environmental Regulation and Informal Environmental Regulation," IJERPH, MDPI, vol. 17(21), pages 1-17, October.
    3. Ludovic Fontaine & Dominique Morau & Jean-Philippe Praene, 2022. "Analysis and Estimation of Short Term Residual Household Waste Production: Case Study Reunion Island," Sustainability, MDPI, vol. 15(1), pages 1-24, December.
    4. Bogusław Wowrzeczka, 2021. "City of Waste—Importance of Scale," Sustainability, MDPI, vol. 13(7), pages 1-14, April.
    5. Altaf Hussain Kanhar & Shaoqing Chen & Fei Wang, 2020. "Incineration Fly Ash and Its Treatment to Possible Utilization: A Review," Energies, MDPI, vol. 13(24), pages 1-35, December.
    6. Fu Chen & Xiaoxiao Li & Yongjun Yang & Huping Hou & Gang-Jun Liu & Shaoliang Zhang, 2019. "Storing E-waste in Green Infrastructure to Reduce Perceived Value Loss through Landfill Siting and Landscaping: A Case Study in Nanjing, China," Sustainability, MDPI, vol. 11(7), pages 1-15, March.
    7. Vidas Raudonis & Agne Paulauskaite-Taraseviciene & Linas Eidimtas, 2022. "ANN Hybrid Model for Forecasting Landfill Waste Potential in Lithuania," Sustainability, MDPI, vol. 14(7), pages 1-16, March.

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