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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

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...

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Detalles Bibliográficos
Autores principales: Yang, Ye, Lan, Haifeng, Li, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6981823/
https://www.ncbi.nlm.nih.gov/pubmed/31861873
http://dx.doi.org/10.3390/ijerph17010074
Descripción
Sumario: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.