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长江三角洲城市群工业污染时空演化及其驱动因素
引用本文:郭政,陈爽,董平,陆玉麒.长江三角洲城市群工业污染时空演化及其驱动因素[J].中国环境科学,2019,39(3):1323-1335.
作者姓名:郭政  陈爽  董平  陆玉麒
作者单位:1. 中国科学院南京地理与湖泊研究所, 江苏 南京 210008;2. 南京师范大学, 虚拟地理环境教育部重点实验室, 江苏 南京 210023;3. 江苏省地理信息资源开发与利用协同创新中心, 江苏 南京 210023
基金项目:国家自然科学基金资助项目(41771140,41430635)
摘    要:基于2003~2015年长江三角洲(以下简称长三角)城市群26个城市工业废水和工业SO2排放数据,采用标准差椭圆、地理集中指数、工业环境绩效指数、空间形态差异指数等方法从宏观和微观视角对长三角城市群工业污染时空演化进行分析,同时采用对数平均迪氏分解(LMDI)模型对其工业污染排放主要驱动因素进行分解.研究发现:2003~2015年工业废水和工业SO2排放量分别下降了16.97%和28.79%,但占全国比重仍然较高,尤其是工业废水对生态环境胁迫较大.2种工业污染空间形态均呈现出北(偏西)-南(偏东)的空间分布形态,而2种工业污染重心移动轨迹并不一致,工业废水重心总体上朝向东(偏南)方向迁移了12.85km,而工业SO2重心总体上朝向西(偏北)方向迁移了26.89km.此外,2种工业污染主要集中分布于长江沿岸城市且污染集中度指数由高到低大致呈半圈层状向周围递减.工业发展与工业污染空间形态演变具有一致性,工业废水重心和工业SO2重心与工业发展重心距离均在逐渐缩小,而2种工业污染-环境绩效空间分布格局并不完全一致.驱动因素方面,环境规制引起的技术改善效应是工业污染排放量减少的主要原因,而由环境规制引起的产业结构效应对工业污染排放量的影响则取决于区域发展政策,经济发展效应是工业污染排放量增加的主要原因,人口规模效应对工业污染排放量的影响较小.

关 键 词:长三角城市群  工业污染  时空演化  标准差椭圆  LMDI  驱动因素  
收稿时间:2018-08-20

Spatio-temporal evolution of industrial pollution in the Yangtze River Delta urban agglomeration and its driving factors
GUO Zheng,CHEN Shuang,DONG Ping,LU Yu-qi.Spatio-temporal evolution of industrial pollution in the Yangtze River Delta urban agglomeration and its driving factors[J].China Environmental Science,2019,39(3):1323-1335.
Authors:GUO Zheng  CHEN Shuang  DONG Ping  LU Yu-qi
Institution:1. Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China;2. Key Laboratory of Virtual Geographic Environment of Ministry of Education, Nanjing Normal University, Nanjing 210008, China;3. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, 210008, China
Abstract:Based on data of industrial wastewater discharge and industrial SO2 emission of the 26 cities in the Yangtze River Delta (YRD) urban agglomeration from 2003 to 2015, the spatial and temporal evolution of industrial pollution was analyzed from the macro and micro perspectives by using the methods of standard deviation ellipse, geographic concentration index, industrial environmental performance index and spatial shape difference index. At the same time, the logarithmic mean decomposition (LMDI) model was used to decompose the main driving factors of industrial pollution discharge. The study found that: from 2003 to 2015, industrial wastewater and industrial SO2 emissions decreased by 16.97% and 28.79%, respectively, but their proportions are still relatively high in China, especially for the stress of industrial wastewater on ecological environment. The both spatial patterns of industrial pollution show the spatial distribution pattern of north (west)-south (east), however the two types of industrial pollution have different movement trajectories of the center of gravity. The center of gravity of industrial wastewater moved 12.85km to the east (south) direction, while the center of gravity of industrial SO2 migrated to the west (north) direction by 26.89km. In addition, the two types of industrial pollution are mainly concentrated in the cities along the Yangtze River and the pollution concentration index decreases to the surrounding areas with the shape of semi-circle layer. The evolution form of industrial development is consistent with that of industrial pollution, both the distances of the industrial development center of gravity between the industrial wastewater center of gravity and the industrial SO2 center of gravity are gradually reduced, and the spatial distribution patterns of two industrial pollution-environmental performances are not completely consistent. In terms of driving factors, the technological improvement effect caused by environmental regulation is the main reason for the reduction of industrial pollution emissions, while the influence of industrial structure caused by environmental regulation on industrial pollution emissions depends on regional development policies. The economic development effect is the main reason for the increase of industrial pollution emission, and population scale effect has little influence on industrial pollution emission.
Keywords:Yangtze River Delta urban agglomeration  industrial pollution  space-time evolution  standard deviation ellipse  LMDI  driving factors  
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