Spatial Econometric Analysis of the Impact of Socioeconomic Factors on PM 2.5 Concentration in China’s Inland Cities: A Case Study from Chengdu Plain Economic Zone

Ye Yang, Haifeng Lan and Jing Li
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Ye Yang: School of Architecture and Urban-Rural Planning, Sichuan Agriculture University, Dujiangyan 611830, China
Haifeng Lan: School of Civil Engineering and Architecture, Southwest University of Science and Technology, Mianyang 621010, China
Jing Li: School of Architecture and Urban-Rural Planning, Sichuan Agriculture University, Dujiangyan 611830, China

IJERPH, 2019, vol. 17, issue 1, 1-19

Abstract: Particulate matter with a diameter less than 2.5 µm (PM 2.5 ), 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 PM 2.5 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 PM 2.5 concentration and the socioeconomic factors underlying it from 2006 to 2016. Moran’s index indicates that PM 2.5 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 PM 2.5 concentration, while greening rate and per capita park space have a negative effect. Additionally, those factors have identified spatial spillover effects on PM 2.5 concentration. This study could be a reference and support for the formulation of more efficient air pollution control policies in inland cities.

Keywords: spatiotemporal distribution; socioeconomic factors; spatial econometrics; PM 2.5 concentration; spillover effects (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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