Cargando…
Spatial characteristics of change trends of air pollutants in Chinese urban areas during 2016–2020: The impact of air pollution controls and the COVID-19 pandemic
Air pollution is a threat to public health in China, and several actions and plans have been implemented by Chinese authorities in recent years to mitigate it. This study examined the spatial distribution of changes in urban air pollutants (UAP) in 336 Chinese cities from 2016 to 2020 and their resp...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9701570/ https://www.ncbi.nlm.nih.gov/pubmed/36465231 http://dx.doi.org/10.1016/j.atmosres.2022.106539 |
_version_ | 1784839562468524032 |
---|---|
author | Gao, Chanchan Zhang, Fengying Fang, Dekun Wang, Qingtao Liu, Min |
author_facet | Gao, Chanchan Zhang, Fengying Fang, Dekun Wang, Qingtao Liu, Min |
author_sort | Gao, Chanchan |
collection | PubMed |
description | Air pollution is a threat to public health in China, and several actions and plans have been implemented by Chinese authorities in recent years to mitigate it. This study examined the spatial distribution of changes in urban air pollutants (UAP) in 336 Chinese cities from 2016 to 2020 and their responses to air pollution controls and the COVID-19 pandemic. Based on the harmonic model, decreases in fine particles (PM(2.5)), inhalable particles (PM(10)), nitrogen dioxide (NO(2)), sulfur dioxide (SO(2)), and carbon monoxide (CO) levels were found in 90.7%, 91.9%, 75.2%, 94.3%, and 88.7% of cities, respectively, while an increase in ozone (O(3)) was found in 87.2% of cities. Notable spatial heterogeneity was observed in the air pollution trends. The greatest improvement in air quality occurred mainly in areas with poor air quality, such as Hebei province and its surrounding cities. However, some areas (i.e., Yunnan and Hainan provinces) with good air quality showed a worsening trend. During the 13th Five-Year Plan period (2016–2020), the remarkable effects of PM(2.5) and SO(2) pollution control plans were confirmed. Additionally, economic growth in 74.2% of the Chinese provinces decoupled from air quality after implementing pollution control measures. In 2020, several Chinese cities were locked down to reduce the spread of COVID-19. Except for SO(2), the national air pollution in 2020 improved to a greater extent than that in 2016–2019; In particularly, the contribution of simulated COVID-19 pandemic to NO(2) reduction was 66.7%. Overall, air pollution control actions improved urban PM(2.5), PM(10), SO(2), and CO, whereas NO(2) was reduced primarily because of the COVID-19 pandemic. |
format | Online Article Text |
id | pubmed-9701570 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-97015702022-11-28 Spatial characteristics of change trends of air pollutants in Chinese urban areas during 2016–2020: The impact of air pollution controls and the COVID-19 pandemic Gao, Chanchan Zhang, Fengying Fang, Dekun Wang, Qingtao Liu, Min Atmos Res Article Air pollution is a threat to public health in China, and several actions and plans have been implemented by Chinese authorities in recent years to mitigate it. This study examined the spatial distribution of changes in urban air pollutants (UAP) in 336 Chinese cities from 2016 to 2020 and their responses to air pollution controls and the COVID-19 pandemic. Based on the harmonic model, decreases in fine particles (PM(2.5)), inhalable particles (PM(10)), nitrogen dioxide (NO(2)), sulfur dioxide (SO(2)), and carbon monoxide (CO) levels were found in 90.7%, 91.9%, 75.2%, 94.3%, and 88.7% of cities, respectively, while an increase in ozone (O(3)) was found in 87.2% of cities. Notable spatial heterogeneity was observed in the air pollution trends. The greatest improvement in air quality occurred mainly in areas with poor air quality, such as Hebei province and its surrounding cities. However, some areas (i.e., Yunnan and Hainan provinces) with good air quality showed a worsening trend. During the 13th Five-Year Plan period (2016–2020), the remarkable effects of PM(2.5) and SO(2) pollution control plans were confirmed. Additionally, economic growth in 74.2% of the Chinese provinces decoupled from air quality after implementing pollution control measures. In 2020, several Chinese cities were locked down to reduce the spread of COVID-19. Except for SO(2), the national air pollution in 2020 improved to a greater extent than that in 2016–2019; In particularly, the contribution of simulated COVID-19 pandemic to NO(2) reduction was 66.7%. Overall, air pollution control actions improved urban PM(2.5), PM(10), SO(2), and CO, whereas NO(2) was reduced primarily because of the COVID-19 pandemic. Elsevier B.V. 2023-03-01 2022-11-28 /pmc/articles/PMC9701570/ /pubmed/36465231 http://dx.doi.org/10.1016/j.atmosres.2022.106539 Text en © 2022 Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Gao, Chanchan Zhang, Fengying Fang, Dekun Wang, Qingtao Liu, Min Spatial characteristics of change trends of air pollutants in Chinese urban areas during 2016–2020: The impact of air pollution controls and the COVID-19 pandemic |
title | Spatial characteristics of change trends of air pollutants in Chinese urban areas during 2016–2020: The impact of air pollution controls and the COVID-19 pandemic |
title_full | Spatial characteristics of change trends of air pollutants in Chinese urban areas during 2016–2020: The impact of air pollution controls and the COVID-19 pandemic |
title_fullStr | Spatial characteristics of change trends of air pollutants in Chinese urban areas during 2016–2020: The impact of air pollution controls and the COVID-19 pandemic |
title_full_unstemmed | Spatial characteristics of change trends of air pollutants in Chinese urban areas during 2016–2020: The impact of air pollution controls and the COVID-19 pandemic |
title_short | Spatial characteristics of change trends of air pollutants in Chinese urban areas during 2016–2020: The impact of air pollution controls and the COVID-19 pandemic |
title_sort | spatial characteristics of change trends of air pollutants in chinese urban areas during 2016–2020: the impact of air pollution controls and the covid-19 pandemic |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9701570/ https://www.ncbi.nlm.nih.gov/pubmed/36465231 http://dx.doi.org/10.1016/j.atmosres.2022.106539 |
work_keys_str_mv | AT gaochanchan spatialcharacteristicsofchangetrendsofairpollutantsinchineseurbanareasduring20162020theimpactofairpollutioncontrolsandthecovid19pandemic AT zhangfengying spatialcharacteristicsofchangetrendsofairpollutantsinchineseurbanareasduring20162020theimpactofairpollutioncontrolsandthecovid19pandemic AT fangdekun spatialcharacteristicsofchangetrendsofairpollutantsinchineseurbanareasduring20162020theimpactofairpollutioncontrolsandthecovid19pandemic AT wangqingtao spatialcharacteristicsofchangetrendsofairpollutantsinchineseurbanareasduring20162020theimpactofairpollutioncontrolsandthecovid19pandemic AT liumin spatialcharacteristicsofchangetrendsofairpollutantsinchineseurbanareasduring20162020theimpactofairpollutioncontrolsandthecovid19pandemic |