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Spatio-Temporal Variation of PM(2.5) Concentrations and Their Relationship with Geographic and Socioeconomic Factors in China
The air quality in China, particularly the PM(2.5) (particles less than 2.5 μm in aerodynamic diameter) level, has become an increasing public concern because of its relation to health risks. The distribution of PM(2.5) concentrations has a close relationship with multiple geographic and socioeconom...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3924439/ https://www.ncbi.nlm.nih.gov/pubmed/24362546 http://dx.doi.org/10.3390/ijerph110100173 |
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author | Lin, Gang Fu, Jingying Jiang, Dong Hu, Wensheng Dong, Donglin Huang, Yaohuan Zhao, Mingdong |
author_facet | Lin, Gang Fu, Jingying Jiang, Dong Hu, Wensheng Dong, Donglin Huang, Yaohuan Zhao, Mingdong |
author_sort | Lin, Gang |
collection | PubMed |
description | The air quality in China, particularly the PM(2.5) (particles less than 2.5 μm in aerodynamic diameter) level, has become an increasing public concern because of its relation to health risks. The distribution of PM(2.5) concentrations has a close relationship with multiple geographic and socioeconomic factors, but the lack of reliable data has been the main obstacle to studying this topic. Based on the newly published Annual Average PM(2.5) gridded data, together with land use data, gridded population data and Gross Domestic Product (GDP) data, this paper explored the spatial-temporal characteristics of PM(2.5) concentrations and the factors impacting those concentrations in China for the years of 2001–2010. The contributions of urban areas, high population and economic development to PM(2.5) concentrations were analyzed using the Geographically Weighted Regression (GWR) model. The results indicated that the spatial pattern of PM(2.5) concentrations in China remained stable during the period 2001–2010; high concentrations of PM(2.5) are mostly found in regions with high populations and rapid urban expansion, including the Beijing-Tianjin-Hebei region in North China, East China (including the Shandong, Anhui and Jiangsu provinces) and Henan province. Increasing populations, local economic growth and urban expansion are the three main driving forces impacting PM(2.5) concentrations. |
format | Online Article Text |
id | pubmed-3924439 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-39244392014-02-18 Spatio-Temporal Variation of PM(2.5) Concentrations and Their Relationship with Geographic and Socioeconomic Factors in China Lin, Gang Fu, Jingying Jiang, Dong Hu, Wensheng Dong, Donglin Huang, Yaohuan Zhao, Mingdong Int J Environ Res Public Health Article The air quality in China, particularly the PM(2.5) (particles less than 2.5 μm in aerodynamic diameter) level, has become an increasing public concern because of its relation to health risks. The distribution of PM(2.5) concentrations has a close relationship with multiple geographic and socioeconomic factors, but the lack of reliable data has been the main obstacle to studying this topic. Based on the newly published Annual Average PM(2.5) gridded data, together with land use data, gridded population data and Gross Domestic Product (GDP) data, this paper explored the spatial-temporal characteristics of PM(2.5) concentrations and the factors impacting those concentrations in China for the years of 2001–2010. The contributions of urban areas, high population and economic development to PM(2.5) concentrations were analyzed using the Geographically Weighted Regression (GWR) model. The results indicated that the spatial pattern of PM(2.5) concentrations in China remained stable during the period 2001–2010; high concentrations of PM(2.5) are mostly found in regions with high populations and rapid urban expansion, including the Beijing-Tianjin-Hebei region in North China, East China (including the Shandong, Anhui and Jiangsu provinces) and Henan province. Increasing populations, local economic growth and urban expansion are the three main driving forces impacting PM(2.5) concentrations. MDPI 2013-12-20 2014-01 /pmc/articles/PMC3924439/ /pubmed/24362546 http://dx.doi.org/10.3390/ijerph110100173 Text en © 2013 by the authors; licensee MDPI, Basel, Switzerland. http://creativecommons.org/licenses/by/3.0/ This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Article Lin, Gang Fu, Jingying Jiang, Dong Hu, Wensheng Dong, Donglin Huang, Yaohuan Zhao, Mingdong Spatio-Temporal Variation of PM(2.5) Concentrations and Their Relationship with Geographic and Socioeconomic Factors in China |
title | Spatio-Temporal Variation of PM(2.5) Concentrations and Their Relationship with Geographic and Socioeconomic Factors in China |
title_full | Spatio-Temporal Variation of PM(2.5) Concentrations and Their Relationship with Geographic and Socioeconomic Factors in China |
title_fullStr | Spatio-Temporal Variation of PM(2.5) Concentrations and Their Relationship with Geographic and Socioeconomic Factors in China |
title_full_unstemmed | Spatio-Temporal Variation of PM(2.5) Concentrations and Their Relationship with Geographic and Socioeconomic Factors in China |
title_short | Spatio-Temporal Variation of PM(2.5) Concentrations and Their Relationship with Geographic and Socioeconomic Factors in China |
title_sort | spatio-temporal variation of pm(2.5) concentrations and their relationship with geographic and socioeconomic factors in china |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3924439/ https://www.ncbi.nlm.nih.gov/pubmed/24362546 http://dx.doi.org/10.3390/ijerph110100173 |
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