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厦门市-漳州市-泉州市城市群 PM 浓度的空间分异及大气健康格局分析。

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

机构信息

School of Architecture, Tianjin Chengjian University, Tianjin 300384, China.

School of Architecture, Tianjin University, Tianjin 300072, China.

出版信息

Int J Environ Res Public Health. 2023 Feb 14;20(4):3340. doi: 10.3390/ijerph20043340.

DOI:10.3390/ijerph20043340
PMID:36834036
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9963608/
Abstract

Exploring the spatial differentiation of PM 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 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 value of the area in 2020 was 19.16 μg/m, 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.

摘要

探索典型城市群中 PM 浓度的空间分异,分析其大气健康格局,是建设高质量城市群的必要条件。以厦门-漳州-泉州城市群为例,基于探索性数据分析和数理统计,探讨 PM 空间分布格局和特征,并采用层次分析法构建了由暴露-响应程度、区域脆弱性和区域适应性组成的大气健康评价体系,进而识别大气健康格局的空间分异特征及其关键成因。研究表明:(1)2020 年该地区年平均 PM 值为 19.16μg/m3,低于中国年均质量浓度限值,整体表现为清洁。(2)大气健康评价体系各组成部分的空间分布格局不同,整体清洁效益呈现“中北部-南部凹陷,其余地区混合”的特征,区域脆弱性表现为沿海到内陆衰减的特征,区域适应性呈现“北高南低、东高西低”的空间分异格局。(3)该地区大气健康模式的高值区呈“F 型”空间分布;低值区呈现“北-中-南”三足鼎立的格局。对上述地区健康模式的评估可为污染防控和健康城市建设提供理论参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e31/9963608/740171b0da4e/ijerph-20-03340-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e31/9963608/c9cbd3e96741/ijerph-20-03340-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e31/9963608/2dc519b953e3/ijerph-20-03340-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e31/9963608/7500f3f33313/ijerph-20-03340-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e31/9963608/1de01b917dda/ijerph-20-03340-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e31/9963608/2212f0f85f38/ijerph-20-03340-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e31/9963608/9c6eacc1f6f7/ijerph-20-03340-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e31/9963608/b3f40df1a8bc/ijerph-20-03340-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e31/9963608/b413c52e0ee2/ijerph-20-03340-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e31/9963608/2299cc2b7251/ijerph-20-03340-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e31/9963608/84eb12f3c230/ijerph-20-03340-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e31/9963608/740171b0da4e/ijerph-20-03340-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e31/9963608/c9cbd3e96741/ijerph-20-03340-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e31/9963608/2dc519b953e3/ijerph-20-03340-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e31/9963608/7500f3f33313/ijerph-20-03340-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e31/9963608/1de01b917dda/ijerph-20-03340-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e31/9963608/2212f0f85f38/ijerph-20-03340-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e31/9963608/9c6eacc1f6f7/ijerph-20-03340-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e31/9963608/b3f40df1a8bc/ijerph-20-03340-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e31/9963608/b413c52e0ee2/ijerph-20-03340-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e31/9963608/2299cc2b7251/ijerph-20-03340-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e31/9963608/84eb12f3c230/ijerph-20-03340-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e31/9963608/740171b0da4e/ijerph-20-03340-g011.jpg

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