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A platform for research: civil engineering, architecture and urbanism
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.
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.
Characteristics and Forecasting of Municipal Solid Waste Generation in China
2019
Article (Journal)
Electronic Resource
Unknown
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