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

Waste Manag Res. 2011 Apr;29(4):371-8. doi: 10.1177/0734242X10380114. Epub 2010 Aug 10.

Abstract

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.

MeSH terms

  • China
  • Cities
  • Data Interpretation, Statistical
  • Economic Development / statistics & numerical data
  • Gross Domestic Product / statistics & numerical data
  • Humans
  • Principal Component Analysis
  • Refuse Disposal / statistics & numerical data*
  • Socioeconomic Factors
  • Urban Population / statistics & numerical data
  • Waste Products / statistics & numerical data*

Substances

  • Waste Products