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长江经济带工业污染排放空间分布格局及其影响因素

本站小编 Free考研考试/2021-12-31

中文关键词长江经济带工业污染空间格局影响因素对数平均迪氏分解模型(LMDI) 英文关键词Yangtze River economic beltindustrial pollutionspatial patternimpacting factorslogarithmic mean Divisia index model (LMDI)
作者单位E-mail
李芸邑重庆大学三峡库区生态环境教育部重点实验室, 重庆 400045liyunyi@cqu.edu.cn
刘利萍重庆大学三峡库区生态环境教育部重点实验室, 重庆 400045
刘元元重庆大学三峡库区生态环境教育部重点实验室, 重庆 400045liuyuanyuan@cqu.edu.cn
中文摘要 长江经济带发展强调"不搞大开发,共抓大保护"战略,长江生态环境修复成为该地区发展的重要内容,因此探明长江经济带工业污染排放空间分布格局及其影响因素具有重要意义.选取2013~2017年长江经济带102个城市的工业SO2、工业废水以及工业烟粉尘排放量作为基础数据,运用空间自相关分析和冷热点分析方法(Getis-Ord Gi*),揭示了长江经济带工业污染排放空间分布格局;采用对数平均迪氏分解模型(logarithmic mean Divisia index,LMDI)对长江经济带工业污染排放的影响因素进行分解.结果表明,2013~2017年长江经济带的工业SO2、工业废水以及工业烟粉尘排放量呈降低趋势,高排放城市减少,低排放城市增多;各工业污染物随时间变化,空间关联程度增强;技术改善对工业污染排放有显著抑制作用,是影响长江经济带工业污染排放的最主要因素. 英文摘要 The development of Yangtze River economic belt emphasizes the strategy of "no large-scale development, joint efforts in large-scale protection". The restoration of the Yangtze River environment has become an important part of the development of the region. Therefore, it is important to explore the spatial distribution of industrial pollution emissions and its influencing factors in the Yangtze River economic belt. Using industrial SO2, wastewater, and soot emission data from 102 cities in the Yangtze River economic belt, from 2013 to 2017, this study analyzes the spatial distribution of industrial pollution emissions in the Yangtze River economic belt. This was achieved using spatial autocorrelation analysis and Getis-Ord Gi* methods, and by adopting the logarithmic mean Divisia index model to decompose the influencing factors of industrial pollution emissions in the Yangtze River economic belt. The results show that from 2013 to 2017, the emissions of industrial SO2, wastewater, and soot in the Yangtze River economic belt exhibited a downward trend, with a decrease in the number of high-emission cities and an increase in the number of low-emission cities. The spatial correlation of industrial pollutants increased with time, and technological improvements had the most significant inhibitory effect, making it the most important factor affecting industrial pollution emissions in the Yangtze River economic belt.

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