[Spatiotemporal Pattern and Driving Mechanism of PM2.5 Population Exposure Risk in Urban Agglomerations in China].

Q2 Environmental Science
Jun Zhang, Lei-Yu Liu, Teng-Fei Zhang, Ya-Ni Geng
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引用次数: 0

Abstract

At present, China's urban agglomerations are high-risk and high-risk clusters of PM2.5 population exposure. Based on the remote sensing data of PM2.5 from 2000 to 2021, this study analyzed the temporal and spatial evolution characteristics of PM2.5 population exposure risk in urban agglomerations in China by using the population exposure risk model and spatial autocorrelation method and used seven factors such as average temperature, annual precipitation, and per capita GDP as independent variables, combined with geographic detectors and spatiotemporal geographically weighted regression models to explore the spatial differentiation mechanism of PM2.5 population exposure risk. The results showed that: ① From 2000 to 2021, the temporal range of PM2.5 exposure risk in urban agglomerations in China was small. ② From 2000 to 2021, the PM2.5 population exposure risk of China's urban agglomerations changed significantly in space, and the high-risk areas of PM2.5 population exposure were concentrated in the Beijing-Tianjin-Hebei urban agglomeration, the Yangtze River Delta urban agglomeration, and the central Shanxi urban agglomeration, and the PM2.5 population exposure risk in China's urban agglomerations showed a marked positive correlation in space, and the spatial agglomeration characteristics were obvious. ③ The exposure risk of urban agglomerations with low population density was greatly affected by annual precipitation and annual average temperature, while urban agglomerations with high population density were greatly affected by population density and environmental regulatory factors. Industrial structure and population density factors played a positive role in enhancing the population exposure risk of PM2.5 in urban agglomerations, energy consumption and environmental regulation factors played a negative inhibiting effect, and annual average wind speed and annual precipitation factors mainly played a positive role in enhancing and negatively inhibiting the population exposure risk of the urban agglomeration on the northern slope of the Tianshan Mountains. The results of this study provide a scientific basis for atmospheric environment management and pollution prevention and control in urban agglomerations in China.

中国城市群PM2.5人口暴露风险时空格局及驱动机制[j]。
目前,中国城市群是PM2.5人群暴露的高危区和高危聚集区。基于2000 - 2021年PM2.5遥感数据,采用人口暴露风险模型和空间自相关方法,以平均气温、年降水量、人均GDP等7个因素为自变量,分析了中国城市群PM2.5人口暴露风险的时空演变特征。结合地理探测器和时空地理加权回归模型,探讨PM2.5人群暴露风险的空间分异机制。结果表明:①2000 - 2021年,中国城市群PM2.5暴露风险的时间变化幅度较小;②2000 - 2021年,中国城市群PM2.5人口暴露风险空间变化显著,PM2.5人口暴露高风区集中在京津冀城市群、长三角城市群和山西中部城市群,城市群PM2.5人口暴露风险在空间上呈显著正相关;空间集聚特征明显。③人口密度低的城市群暴露风险受年降水量和年平均气温的影响较大,而人口密度高的城市群暴露风险受人口密度和环境调节因素的影响较大。产业结构和人口密度因子对城市群PM2.5人口暴露风险起正向增强作用,能源消耗和环境调节因子起负向抑制作用,年平均风速和年降水量因子对天山北坡城市群人口暴露风险主要起正向增强和负向抑制作用。研究结果为中国城市群大气环境管理和污染防治提供了科学依据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
环境科学
环境科学 Environmental Science-Environmental Science (all)
CiteScore
4.40
自引率
0.00%
发文量
15329
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