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Spatiotemporal variation and influencing factors of air pollution in Anhui Province
Anhui Province locates in the Yangtze River Delta region. The spatial difference between the north and the south is significant, and the air quality is improved over time. Studying the spatial and temporal changes of air pollution and its influencing factors for the coordinated control of air pollut...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10189381/ https://www.ncbi.nlm.nih.gov/pubmed/37205997 http://dx.doi.org/10.1016/j.heliyon.2023.e15691 |
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author | Jia, Li Sun, Jianping Fu, Yanfang |
author_facet | Jia, Li Sun, Jianping Fu, Yanfang |
author_sort | Jia, Li |
collection | PubMed |
description | Anhui Province locates in the Yangtze River Delta region. The spatial difference between the north and the south is significant, and the air quality is improved over time. Studying the spatial and temporal changes of air pollution and its influencing factors for the coordinated control of air pollutants in the Yangtze River Delta region is significant. This study used the annual and monthly average data of six pollutants, PM(2.5), PM(10), O(3), NO(2), SO(2), and CO, in Anhui Province and various cities from 2015 to 2021 and analyzed the spatiotemporal change characteristics using Excel and GIS software. Meanwhile, this paper used the SPSS correlation analysis method to analyze the correlation between pollutants and meteorological factors and analyzed the impact of economic development and environmental protection policies. The results are shown below. (1) The concentrations of SO(2), NO(2), and CO showed an overall downward trend at an interannual level. Meanwhile, the concentrations of PM(10) and PM(2.5) first increased slowly before 2017 and then declined, while the concentrations of O(3) increased significantly before 2018 and then declined slowly. On a monthly scale, O(3) presented an M-shaped change, while the other five pollutants basically presented a U-shaped change mode. The top monthly pollutants in each city followed the order of PM(2.5), O(3), PM(10), and NO(2). (2) PM(2.5) and PM(10) showed apparent characteristics of high concentrations in the north and low concentrations in the south in space. There were no significant differences in NO(2), SO(2), and CO pollution between the north and the south in space, and the differences in spatial pollution among cities were reduced significantly. (3) Five pollutants (SO(2), NO(2), PM(10), PM(2.5), and CO) except O(3) were positively correlated, and the degree of correlation was correlated, strongly correlated, and above. However, five pollutants were negatively correlated with O(3). The temperature had the most significant impact of negative correlation on five pollutants except for O(3). The sunshine duration had the most significant impact on O(3). (4) Economic growth and environmental protection policies in Anhui Province have positively affected environmental governance. |
format | Online Article Text |
id | pubmed-10189381 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-101893812023-05-18 Spatiotemporal variation and influencing factors of air pollution in Anhui Province Jia, Li Sun, Jianping Fu, Yanfang Heliyon Research Article Anhui Province locates in the Yangtze River Delta region. The spatial difference between the north and the south is significant, and the air quality is improved over time. Studying the spatial and temporal changes of air pollution and its influencing factors for the coordinated control of air pollutants in the Yangtze River Delta region is significant. This study used the annual and monthly average data of six pollutants, PM(2.5), PM(10), O(3), NO(2), SO(2), and CO, in Anhui Province and various cities from 2015 to 2021 and analyzed the spatiotemporal change characteristics using Excel and GIS software. Meanwhile, this paper used the SPSS correlation analysis method to analyze the correlation between pollutants and meteorological factors and analyzed the impact of economic development and environmental protection policies. The results are shown below. (1) The concentrations of SO(2), NO(2), and CO showed an overall downward trend at an interannual level. Meanwhile, the concentrations of PM(10) and PM(2.5) first increased slowly before 2017 and then declined, while the concentrations of O(3) increased significantly before 2018 and then declined slowly. On a monthly scale, O(3) presented an M-shaped change, while the other five pollutants basically presented a U-shaped change mode. The top monthly pollutants in each city followed the order of PM(2.5), O(3), PM(10), and NO(2). (2) PM(2.5) and PM(10) showed apparent characteristics of high concentrations in the north and low concentrations in the south in space. There were no significant differences in NO(2), SO(2), and CO pollution between the north and the south in space, and the differences in spatial pollution among cities were reduced significantly. (3) Five pollutants (SO(2), NO(2), PM(10), PM(2.5), and CO) except O(3) were positively correlated, and the degree of correlation was correlated, strongly correlated, and above. However, five pollutants were negatively correlated with O(3). The temperature had the most significant impact of negative correlation on five pollutants except for O(3). The sunshine duration had the most significant impact on O(3). (4) Economic growth and environmental protection policies in Anhui Province have positively affected environmental governance. Elsevier 2023-04-23 /pmc/articles/PMC10189381/ /pubmed/37205997 http://dx.doi.org/10.1016/j.heliyon.2023.e15691 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Jia, Li Sun, Jianping Fu, Yanfang Spatiotemporal variation and influencing factors of air pollution in Anhui Province |
title | Spatiotemporal variation and influencing factors of air pollution in Anhui Province |
title_full | Spatiotemporal variation and influencing factors of air pollution in Anhui Province |
title_fullStr | Spatiotemporal variation and influencing factors of air pollution in Anhui Province |
title_full_unstemmed | Spatiotemporal variation and influencing factors of air pollution in Anhui Province |
title_short | Spatiotemporal variation and influencing factors of air pollution in Anhui Province |
title_sort | spatiotemporal variation and influencing factors of air pollution in anhui province |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10189381/ https://www.ncbi.nlm.nih.gov/pubmed/37205997 http://dx.doi.org/10.1016/j.heliyon.2023.e15691 |
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