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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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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
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author Yang, Ye
Lan, Haifeng
Li, Jing
author_facet Yang, Ye
Lan, Haifeng
Li, Jing
author_sort Yang, Ye
collection PubMed
description 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.
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spelling pubmed-69818232020-02-07 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 Yang, Ye Lan, Haifeng Li, Jing Int J Environ Res Public Health Article 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. MDPI 2019-12-20 2020-01 /pmc/articles/PMC6981823/ /pubmed/31861873 http://dx.doi.org/10.3390/ijerph17010074 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yang, Ye
Lan, Haifeng
Li, Jing
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
title 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
title_full 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
title_fullStr 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
title_full_unstemmed 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
title_short 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
title_sort 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
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6981823/
https://www.ncbi.nlm.nih.gov/pubmed/31861873
http://dx.doi.org/10.3390/ijerph17010074
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