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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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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. |
format | Online Article Text |
id | pubmed-6981823 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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