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Spatial Econometric Analysis of the Impact of Socioeconomic Factors on PM2.5 Concentration in China’s Inland Cities: A Case Study from Chengdu Plain Economic Zone

by 1, 2 and 1,*
1
School of Architecture and Urban-Rural Planning, Sichuan Agriculture University, Dujiangyan 611830, China
2
School of Civil Engineering and Architecture, Southwest University of Science and Technology, Mianyang 621010, China
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2020, 17(1), 74; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17010074
Received: 20 November 2019 / Revised: 11 December 2019 / Accepted: 18 December 2019 / Published: 20 December 2019
(This article belongs to the Special Issue Urban Environment and Health)
Particulate matter with a diameter less than 2.5 µm (PM2.5), one of the main sources of air pollution, has increasingly become a concern of the people and governments in China. Examining the socioeconomic factors influencing on PM2.5 concentration is important for regional prevention and control. Previous studies mainly concentrated on the economically developed eastern coastal cities, but few studies focused on inland cities. This study selected Chengdu Plain Economic Zone (CPEZ), an inland region with heavy smog, and used spatial econometrics methods to identify the spatiotemporal distribution characteristics of PM2.5 concentration and the socioeconomic factors underlying it from 2006 to 2016. Moran’s index indicates that PM2.5 concentration in CPEZ does have spatial aggregation characteristics. In general, the spatial clustering from the fluctuation state to the stable low state decreased by 1% annually on average, from 0.190 (p < 0.05) in 2006 to 0.083 (p < 0.1) in 2016. According to the results of the spatial Durbin model (SDM), socioeconomic factors including population density, energy consumption per unit of output, gross domestic product (GDP), and per capita GDP have a positive effect on PM2.5 concentration, while greening rate and per capita park space have a negative effect. Additionally, those factors have identified spatial spillover effects on PM2.5 concentration. This study could be a reference and support for the formulation of more efficient air pollution control policies in inland cities. View Full-Text
Keywords: spatiotemporal distribution; socioeconomic factors; spatial econometrics; PM2.5 concentration; spillover effects spatiotemporal distribution; socioeconomic factors; spatial econometrics; PM2.5 concentration; spillover effects
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MDPI and ACS Style

Yang, Y.; Lan, H.; Li, J. Spatial Econometric Analysis of the Impact of Socioeconomic Factors on PM2.5 Concentration in China’s Inland Cities: A Case Study from Chengdu Plain Economic Zone. Int. J. Environ. Res. Public Health 2020, 17, 74. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17010074

AMA Style

Yang Y, Lan H, Li J. Spatial Econometric Analysis of the Impact of Socioeconomic Factors on PM2.5 Concentration in China’s Inland Cities: A Case Study from Chengdu Plain Economic Zone. International Journal of Environmental Research and Public Health. 2020; 17(1):74. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17010074

Chicago/Turabian Style

Yang, Ye, Haifeng Lan, and Jing Li. 2020. "Spatial Econometric Analysis of the Impact of Socioeconomic Factors on PM2.5 Concentration in China’s Inland Cities: A Case Study from Chengdu Plain Economic Zone" International Journal of Environmental Research and Public Health 17, no. 1: 74. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17010074

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