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经济集聚对雾霾污染影响的空间计量研究——以长江三角洲地区为例
引用本文:汪聪聪,王益澄,马仁锋,王静敏.经济集聚对雾霾污染影响的空间计量研究——以长江三角洲地区为例[J].长江流域资源与环境,2019,28(1):1-11.
作者姓名:汪聪聪  王益澄  马仁锋  王静敏
作者单位:宁波大学地理与空间信息技术系,浙江宁波,315211;宁波大学地理与空间信息技术系,浙江宁波,315211;宁波大学地理与空间信息技术系,浙江宁波,315211;宁波大学地理与空间信息技术系,浙江宁波,315211
基金项目:国家自然科学基金;宁波市软科学研究计划
摘    要:雾霾污染是困扰中国经济发展的重大民生与环境问题。基于改进产出密度模型,运用地统计和空间计量模型分析长三角城市2015~2017年雾霾污染空间格局和影响因素。研究发现:(1)雾霾污染存在季节性变化特征并且各城市雾霾污染状况逐渐好转。(2)雾霾污染具有显著的局域集聚特征和空间异质性,杭州、宁波和台州呈现低-低集聚特征,而滁州、扬州、镇江和泰州为高-高集聚型,污染区域集中于省界处,污染程度自西北向东南逐渐降低。雾霾污染存在显著的城际空间正相关和空间溢出效应,周边城市雾霾污染对本地区会产生负影响。(3)长三角城市人口集聚、研发投入、产业结构、工业烟粉尘排放及城市建设均对雾霾污染产生正向影响,对外开放、能源消耗以及降水等因素对雾霾污染产生负向影响;雾霾污染与经济增长之间不存在库兹涅茨曲线关系。经济集聚通过优化生产要素的空间分布与组合、共享治污基础设施等,形成雾霾污染抑制作用。

关 键 词:雾霾污染  经济集聚  空间溢出效应  长江三角洲

Impact of Economic Agglomeration on Pollution of Smog Based on Spatial Econometric Model:The Case Study of Yangtze River Delta
WANG Cong-cong,WANG Yi-cheng,MA Ren-feng,WANG Jing-min.Impact of Economic Agglomeration on Pollution of Smog Based on Spatial Econometric Model:The Case Study of Yangtze River Delta[J].Resources and Environment in the Yangtza Basin,2019,28(1):1-11.
Authors:WANG Cong-cong  WANG Yi-cheng  MA Ren-feng  WANG Jing-min
Institution:(Department of Geography & Spatial Information Techniques, Ningbo University, Ningbo 315211, China)
Abstract:Air pollution caused by fog and haze is one of the key issues concerning people’s livelihood and environment, which has plagued China’s economic development. In this research, the spatial pattern and influence factors of smog on air pollution in the Yangtze River Delta from 2015 to 2017 was empirically analyzed based on the improved output density model, statistical and spatial econometric models. The study found that: (1) Smog pollution possessed the characteristic of seasonal variation in the Yangtze River Delta and the situation of air quality in the cities of this region has gradually improved. (2) Smog pollution had the characteristics of significant local agglomeration and spatial heterogeneity. Hangzhou, Ningbo, and Taizhou presented the feature of low-level agglomeration, and Chuzhou, Yangzhou, Zhenjiang and Taizhou were high-level agglomeration. The polluted area has been concentrated at the provincial boundary, and the level of contamination has been gradually decreased from northwest to southeast. There was a significant intercity spatial positive correlation and spatial spillover effect of smog pollution, and the smog pollution in the surrounding areas has had a negative impact on this region. (3) The population concentration, R&D investment, industrial structure, industrial smoke and dust emissions and urban construction in the Yangtze River Delta have had positive impacts on smog pollution, while the factors such as the opening-up, energy consumption and precipitation have had a negative impact on smog pollution. There was no Kuznets curve relationship between smog pollution and economic growth. By optimizing the spatial distribution and combination of production factors, and sharing pollution control infrastructure, etc., economic agglomeration could have an inhibitory effect on smog pollution.
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