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Air quality characteristics during 2016–2020 in Wuhan, China
Implementation of a clean air policy in China has high national importance. Here, we analyzed tempo-spatial characteristics of the concentrations of PM(2.5) (PM(2.5)_C), PM(10) (PM(10)_C), SO(2) (SO(2) _C), NO(2) (NO(2) _C), CO (CO _C), and maximum 8-h average O(3) (O(3)_8h_C), monitored at 22 stati...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10209956/ https://www.ncbi.nlm.nih.gov/pubmed/37231046 http://dx.doi.org/10.1038/s41598-023-35465-1 |
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author | Chen, Yuanyuan Liu, Hongtao Alatalo, Juha M. Jiang, Bo |
author_facet | Chen, Yuanyuan Liu, Hongtao Alatalo, Juha M. Jiang, Bo |
author_sort | Chen, Yuanyuan |
collection | PubMed |
description | Implementation of a clean air policy in China has high national importance. Here, we analyzed tempo-spatial characteristics of the concentrations of PM(2.5) (PM(2.5)_C), PM(10) (PM(10)_C), SO(2) (SO(2) _C), NO(2) (NO(2) _C), CO (CO _C), and maximum 8-h average O(3) (O(3)_8h_C), monitored at 22 stations throughout the mega-city of Wuhan from January 2016 to December 2020, and their correlations with the meteorological and socio-economic factors. PM(2.5)_C, PM(10)_C, SO(2) _C, NO(2) _C, and CO _C showed similar monthly and seasonal trends, with minimum value in summer and maximum value in winter. However, O(3_)8h_C showed an opposite monthly and seasonal change pattern. In 2020, compared to the other years, the annual average PM(2.5)_C, PM(10)_C, SO(2) _C, NO(2) _C, and CO _C were lower. PM(2.5)_C and PM(10)_C were higher in urban and industrial sites and lower in the control site. The SO(2)_C was higher in industrial sites. The NO(2)_C was lower, and O(3_)8h_C was higher in suburban sites, while CO showed no spatial differences in their concentrations. PM(2.5) _C, PM(10) _C, SO(2) _C, NO(2) _C, and CO _C had positive correlations with each other, while O(3_)8h_C showed more complex correlations with the other pollutants. PM(2.5)_C, PM(10)_C, SO(2) _C, and CO _C presented a significantly negative association with temperature and precipitation, while O(3) was significantly positively associated with temperature and negatively associated with relative air humidity. There was no significant correlation between air pollutants and wind speed. Gross domestic product, population, number of automobiles, and energy consumption play an important role in the dynamics of air quality concentrations. These all provided important information for the decision and policy-makers to effectively control the air pollution in Wuhan. |
format | Online Article Text |
id | pubmed-10209956 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-102099562023-05-26 Air quality characteristics during 2016–2020 in Wuhan, China Chen, Yuanyuan Liu, Hongtao Alatalo, Juha M. Jiang, Bo Sci Rep Article Implementation of a clean air policy in China has high national importance. Here, we analyzed tempo-spatial characteristics of the concentrations of PM(2.5) (PM(2.5)_C), PM(10) (PM(10)_C), SO(2) (SO(2) _C), NO(2) (NO(2) _C), CO (CO _C), and maximum 8-h average O(3) (O(3)_8h_C), monitored at 22 stations throughout the mega-city of Wuhan from January 2016 to December 2020, and their correlations with the meteorological and socio-economic factors. PM(2.5)_C, PM(10)_C, SO(2) _C, NO(2) _C, and CO _C showed similar monthly and seasonal trends, with minimum value in summer and maximum value in winter. However, O(3_)8h_C showed an opposite monthly and seasonal change pattern. In 2020, compared to the other years, the annual average PM(2.5)_C, PM(10)_C, SO(2) _C, NO(2) _C, and CO _C were lower. PM(2.5)_C and PM(10)_C were higher in urban and industrial sites and lower in the control site. The SO(2)_C was higher in industrial sites. The NO(2)_C was lower, and O(3_)8h_C was higher in suburban sites, while CO showed no spatial differences in their concentrations. PM(2.5) _C, PM(10) _C, SO(2) _C, NO(2) _C, and CO _C had positive correlations with each other, while O(3_)8h_C showed more complex correlations with the other pollutants. PM(2.5)_C, PM(10)_C, SO(2) _C, and CO _C presented a significantly negative association with temperature and precipitation, while O(3) was significantly positively associated with temperature and negatively associated with relative air humidity. There was no significant correlation between air pollutants and wind speed. Gross domestic product, population, number of automobiles, and energy consumption play an important role in the dynamics of air quality concentrations. These all provided important information for the decision and policy-makers to effectively control the air pollution in Wuhan. Nature Publishing Group UK 2023-05-25 /pmc/articles/PMC10209956/ /pubmed/37231046 http://dx.doi.org/10.1038/s41598-023-35465-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Chen, Yuanyuan Liu, Hongtao Alatalo, Juha M. Jiang, Bo Air quality characteristics during 2016–2020 in Wuhan, China |
title | Air quality characteristics during 2016–2020 in Wuhan, China |
title_full | Air quality characteristics during 2016–2020 in Wuhan, China |
title_fullStr | Air quality characteristics during 2016–2020 in Wuhan, China |
title_full_unstemmed | Air quality characteristics during 2016–2020 in Wuhan, China |
title_short | Air quality characteristics during 2016–2020 in Wuhan, China |
title_sort | air quality characteristics during 2016–2020 in wuhan, china |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10209956/ https://www.ncbi.nlm.nih.gov/pubmed/37231046 http://dx.doi.org/10.1038/s41598-023-35465-1 |
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