Factors influencing municipal solid waste generation in China: A multiple statistical analysis study

被引:86
|
作者
Liu, Chen [1 ]
Wu, Xin-Wu [1 ]
机构
[1] Tongji Univ, Natl Engn Res Ctr Urban Pollut Control, Shanghai 200092, Peoples R China
关键词
Municipal solid waste (MSW); multiple statistical analysis; principal components analysis; cluster analysis; waste generation; MANAGEMENT;
D O I
10.1177/0734242X10380114
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
A relationship between the waste production and socio-economic factors is essential in waste management. In the present study, the factors influencing municipal solid waste generation in China were investigated by multiple statistical analysis. Twelve items were chosen for investigation: GDP, per capita GDP, urban population, the proportion of urban population, the area of urban construction, the area of paved roads, the area of urban gardens and green areas, the number of the large cities, annual per capita disposable income of urban households, annual per capita consumption expenditure of urban households, total energy consumption and annual per capital consumption for households. Two methodologies from multiple statistical analysis were selected; specifically principal components analysis (PCA) and cluster analysis (CA). Three new dimensions were identified by PCA: component 1: economy and urban development; component 2: energy consumption; and component 3: urban scale. The three components together accounted for 99.1% of the initial variance. The results show that economy and urban development are important items influencing MSW generation. The proportion of urban population and urban population had the highest loadings in all factors. The relationship between growth of gross domestic product (GDP) and production of MSW was not as clear-cut as often assumed in China, a situation that is more likely to apply to developed countries. Energy consumption was another factor considered in our study of MSW generation. In addition, the annual MSW quantity variation was investigated by cluster analysis.
引用
收藏
页码:371 / 378
页数:8
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