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Spatial Differentiation of PM(2.5) Concentration and Analysis of Atmospheric Health Patterns in the Xiamen-Zhangzhou-QuanZhou Urban Agglomeration

Exploring the spatial differentiation of PM(2.5) concentrations in typical urban agglomerations and analyzing their atmospheric health patterns are necessary for building high-quality urban agglomerations. Taking the Xiamen-Zhangzhou-Quanzhou urban agglomeration as an example, and based on explorato...

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Autores principales: Zeng, Suiping, Tian, Jian, Song, Yuanzhen, Zeng, Jian, Zhao, Xiya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9963608/
https://www.ncbi.nlm.nih.gov/pubmed/36834036
http://dx.doi.org/10.3390/ijerph20043340
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author Zeng, Suiping
Tian, Jian
Song, Yuanzhen
Zeng, Jian
Zhao, Xiya
author_facet Zeng, Suiping
Tian, Jian
Song, Yuanzhen
Zeng, Jian
Zhao, Xiya
author_sort Zeng, Suiping
collection PubMed
description Exploring the spatial differentiation of PM(2.5) concentrations in typical urban agglomerations and analyzing their atmospheric health patterns are necessary for building high-quality urban agglomerations. Taking the Xiamen-Zhangzhou-Quanzhou urban agglomeration as an example, and based on exploratory data analysis and mathematical statistics, we explore the PM(2.5) spatial distribution patterns and characteristics and use hierarchical analysis to construct an atmospheric health evaluation system consisting of exposure–response degree, regional vulnerability, and regional adaptation, and then identify the spatial differentiation characteristics and critical causes of the atmospheric health pattern. This study shows the following: (1) The average annual PM(2.5) value of the area in 2020 was 19.16 μg/m(3), which was lower than China’s mean annual quality concentration limit, and the overall performance was clean. (2) The spatial distribution patterns of the components of the atmospheric health evaluation system are different, with the overall cleanliness benefit showing a “north-central-south depression, the rest of the region is mixed,” the regional vulnerability showing a coastal to inland decay, and the regional adaptability showing a “high north, low south, high east, low west” spatial divergence pattern. (3) The high-value area of the air health pattern of the area is an “F-shaped” spatial distribution; the low-value area shows a pattern of “north-middle-south” peaks standing side by side. The assessment of health patterns in the aforementioned areas can provide theoretical references for pollution prevention and control and the construction of healthy cities.
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spelling pubmed-99636082023-02-26 Spatial Differentiation of PM(2.5) Concentration and Analysis of Atmospheric Health Patterns in the Xiamen-Zhangzhou-QuanZhou Urban Agglomeration Zeng, Suiping Tian, Jian Song, Yuanzhen Zeng, Jian Zhao, Xiya Int J Environ Res Public Health Article Exploring the spatial differentiation of PM(2.5) concentrations in typical urban agglomerations and analyzing their atmospheric health patterns are necessary for building high-quality urban agglomerations. Taking the Xiamen-Zhangzhou-Quanzhou urban agglomeration as an example, and based on exploratory data analysis and mathematical statistics, we explore the PM(2.5) spatial distribution patterns and characteristics and use hierarchical analysis to construct an atmospheric health evaluation system consisting of exposure–response degree, regional vulnerability, and regional adaptation, and then identify the spatial differentiation characteristics and critical causes of the atmospheric health pattern. This study shows the following: (1) The average annual PM(2.5) value of the area in 2020 was 19.16 μg/m(3), which was lower than China’s mean annual quality concentration limit, and the overall performance was clean. (2) The spatial distribution patterns of the components of the atmospheric health evaluation system are different, with the overall cleanliness benefit showing a “north-central-south depression, the rest of the region is mixed,” the regional vulnerability showing a coastal to inland decay, and the regional adaptability showing a “high north, low south, high east, low west” spatial divergence pattern. (3) The high-value area of the air health pattern of the area is an “F-shaped” spatial distribution; the low-value area shows a pattern of “north-middle-south” peaks standing side by side. The assessment of health patterns in the aforementioned areas can provide theoretical references for pollution prevention and control and the construction of healthy cities. MDPI 2023-02-14 /pmc/articles/PMC9963608/ /pubmed/36834036 http://dx.doi.org/10.3390/ijerph20043340 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zeng, Suiping
Tian, Jian
Song, Yuanzhen
Zeng, Jian
Zhao, Xiya
Spatial Differentiation of PM(2.5) Concentration and Analysis of Atmospheric Health Patterns in the Xiamen-Zhangzhou-QuanZhou Urban Agglomeration
title Spatial Differentiation of PM(2.5) Concentration and Analysis of Atmospheric Health Patterns in the Xiamen-Zhangzhou-QuanZhou Urban Agglomeration
title_full Spatial Differentiation of PM(2.5) Concentration and Analysis of Atmospheric Health Patterns in the Xiamen-Zhangzhou-QuanZhou Urban Agglomeration
title_fullStr Spatial Differentiation of PM(2.5) Concentration and Analysis of Atmospheric Health Patterns in the Xiamen-Zhangzhou-QuanZhou Urban Agglomeration
title_full_unstemmed Spatial Differentiation of PM(2.5) Concentration and Analysis of Atmospheric Health Patterns in the Xiamen-Zhangzhou-QuanZhou Urban Agglomeration
title_short Spatial Differentiation of PM(2.5) Concentration and Analysis of Atmospheric Health Patterns in the Xiamen-Zhangzhou-QuanZhou Urban Agglomeration
title_sort spatial differentiation of pm(2.5) concentration and analysis of atmospheric health patterns in the xiamen-zhangzhou-quanzhou urban agglomeration
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9963608/
https://www.ncbi.nlm.nih.gov/pubmed/36834036
http://dx.doi.org/10.3390/ijerph20043340
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