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The spatio-temporal dynamic pattern of urban solid waste emission in China |
KONG Ling-qiang, TIAN Guang-jin, LIU Xiao-juan |
State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China |
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Abstract Based on the urban solid waste data of China in 2006~2014, it built the spatial and temporal dynamic pattern model.The study showed that the urban solid waste was distributed mainly in Eastern China. The total emissions of Southern China and Eastern China accounted for 35.0% and 34.9%, respectively. In 2006~2010, the urban solid waste was distributed mainly in Eastern China. In 2010~2014, the urban solid waste was distributed mainly in Southern China. Over the past ten years, the urban population increased. The urban population had increased from 3.33×108 to 3.86×108. The proportion of urban population increased from 25.3% to 28.2%. The urban solid waste increased by 20.9%. The correlation of China's urban living garbage emission with urban population, economy and built-up area was significantly positive. The correlation coefficients between the urban garbage emissions and the total population were 0.950, 0.942 and 0.903, respectively in 2006, 2010 and 2014. The correlation coefficients between emissions and GDP of provinces were 0.863, 0.930 and 0.930, respectively. The correlation coefficients between emissions and built-up area were 0.933, 0.947 and 0.925, respectively. It indicated that the population, GDP and built-up area were the important factors which influence the urban living garbage emissions in China. The clustering results using waste emissions per capita and GDP per capita indicated that the provinces of our country could be divided into four groups. "Low emission, low economic" group was the main type. "Low emission, high economy" group was the ideal mode of development, but its proportion was relatively low. The amount of urban living garbage emissions in China was increasing year by year, and presented different spatial characteristics.
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Received: 23 May 2016
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