How do socioeconomic factors influence urban PM2.5 pollution in China? Empirical analysis from the perspective of spatiotemporal disequilibrium

Dan Yan; Ying Kong; Peng Jiang; Ruixian Huang; Bin Ye

doi:10.1016/j.scitotenv.2020.143266

How do socioeconomic factors influence urban PM_2.5 pollution in China? Empirical analysis from the perspective of spatiotemporal disequilibrium

Sci Total Environ. 2021 Mar 20:761:143266. doi: 10.1016/j.scitotenv.2020.143266. Epub 2020 Nov 12.

Authors

Dan Yan¹, Ying Kong², Peng Jiang³, Ruixian Huang⁴, Bin Ye⁵

Affiliations

¹ School of Environmental Science and Engineering, Guangzhou University, Guangzhou 510006, China; Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen 518055, China.
² Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen 518055, China; Department of Economics, York University, Toronto M3J1P3, Canada.
³ Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen 518055, China.
⁴ Business School, East China University of Political Science and Law, Shanghai 200042, China.
⁵ School of Environmental Science & Engineering, Southern University of Science and Technology, Shenzhen 518055, China. Electronic address: yeb@sustech.edu.cn.

PMID: 33250250
DOI: 10.1016/j.scitotenv.2020.143266

Abstract

PM_2.5 pollution has harmed the health and social lives of residents, and although evidence of PM_2.5 pollution caused by human activities has been reported in a large body of literature, traditional econometric and spatial models can explain the contribution of a given factor from only a global perspective. Given this limitation, this study quantitatively investigated the effects of the spatiotemporal heterogeneity of various socioeconomic factors on PM_2.5 pollution in 273 Chinese cities from 2010 to 2016 by exploratory spatial data analysis (ESDA) and geographically weighted regression (GWR). The spatiotemporal distribution pattern and intrinsic driving mechanism of city-level PM_2.5 pollution were systematically examined. The results indicate the following: (1) The cities with high PM_2.5 pollution are located north of the Yangtze River and east of the Hu line. A notable positive spatial correlation was observed between these cities, and nearly one-third of the cities are in the HH clustering area. (2) From the global regression point of view, population size and economic development are the main factors causing the deterioration and spread of PM_2.5 pollution in Chinese cities, and population size undoubtedly exerts the strongest influence. Industrial structure, economic development, openness degree, urbanization and road intensity also play weak roles in promoting urban PM_2.5 pollution. (3) The socioeconomic factors influencing pollution exhibit significant spatial heterogeneity. Specifically, the cities in which pollution is promoted by economic development are mainly concentrated in the northeast and western regions. The cities in which population size exerts a positive driving effect are in most regions, except for a few central and western cities. Three targeted strategies for developing more sustainable cities are comprehensively discussed by building on the understanding of the socioeconomic driving mechanism for PM_2.5 pollution.

Keywords: China; Geographically weighted regression; PM(2.5) pollution; Spatiotemporal disequilibrium.