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Investigation of PM(2.5) pollution during COVID-19 pandemic in Guangzhou, China

The COVID-19 pandemic has raised awareness about various environmental issues, including PM(2.5) pollution. Here, PM(2.5) pollution during the COVID-19 lockdown was traced and analyzed to clarify the sources and factors influencing PM(2.5) in Guangzhou, with an emphasis on heavy pollution. The lockd...

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Detalles Bibliográficos
Autores principales: Wen, Luyao, Yang, Chun, Liao, Xiaoliang, Zhang, Yanhao, Chai, Xuyang, Gao, Wenjun, Guo, Shulin, Bi, Yinglei, Tsang, Suk-Ying, Chen, Zhi-Feng, Qi, Zenghua, Cai, Zongwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8279957/
https://www.ncbi.nlm.nih.gov/pubmed/34969472
http://dx.doi.org/10.1016/j.jes.2021.07.009
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author Wen, Luyao
Yang, Chun
Liao, Xiaoliang
Zhang, Yanhao
Chai, Xuyang
Gao, Wenjun
Guo, Shulin
Bi, Yinglei
Tsang, Suk-Ying
Chen, Zhi-Feng
Qi, Zenghua
Cai, Zongwei
author_facet Wen, Luyao
Yang, Chun
Liao, Xiaoliang
Zhang, Yanhao
Chai, Xuyang
Gao, Wenjun
Guo, Shulin
Bi, Yinglei
Tsang, Suk-Ying
Chen, Zhi-Feng
Qi, Zenghua
Cai, Zongwei
author_sort Wen, Luyao
collection PubMed
description The COVID-19 pandemic has raised awareness about various environmental issues, including PM(2.5) pollution. Here, PM(2.5) pollution during the COVID-19 lockdown was traced and analyzed to clarify the sources and factors influencing PM(2.5) in Guangzhou, with an emphasis on heavy pollution. The lockdown led to large reductions in industrial and traffic emissions, which significantly reduced PM(2.5) concentrations in Guangzhou. Interestingly, the trend of PM(2.5) concentrations was not consistent with traffic and industrial emissions, as minimum concentrations were observed in the fourth period (3/01-3/31, 22.45 μg/m(3)) of the lockdown. However, the concentrations of other gaseous pollutants, e.g., SO(2), NO(2) and CO, were correlated with industrial and traffic emissions, and the lowest values were noticed in the second period (1/24-2/03) of the lockdown. Meteorological correlation analysis revealed that the decreased PM(2.5) concentrations during COVID-19 can be mainly attributed to decreased industrial and traffic emissions rather than meteorological conditions. When meteorological factors were included in the PM(2.5) composition and backward trajectory analyses, we found that long-distance transportation and secondary pollution offset the reduction of primary emissions in the second and third stages of the pandemic. Notably, industrial PM(2.5) emissions from western, southern and southeastern Guangzhou play an important role in the formation of heavy pollution events. Our results not only verify the importance of controlling traffic and industrial emissions, but also provide targets for further improvements in PM(2.5) pollution.
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spelling pubmed-82799572021-07-20 Investigation of PM(2.5) pollution during COVID-19 pandemic in Guangzhou, China Wen, Luyao Yang, Chun Liao, Xiaoliang Zhang, Yanhao Chai, Xuyang Gao, Wenjun Guo, Shulin Bi, Yinglei Tsang, Suk-Ying Chen, Zhi-Feng Qi, Zenghua Cai, Zongwei J Environ Sci (China) Article The COVID-19 pandemic has raised awareness about various environmental issues, including PM(2.5) pollution. Here, PM(2.5) pollution during the COVID-19 lockdown was traced and analyzed to clarify the sources and factors influencing PM(2.5) in Guangzhou, with an emphasis on heavy pollution. The lockdown led to large reductions in industrial and traffic emissions, which significantly reduced PM(2.5) concentrations in Guangzhou. Interestingly, the trend of PM(2.5) concentrations was not consistent with traffic and industrial emissions, as minimum concentrations were observed in the fourth period (3/01-3/31, 22.45 μg/m(3)) of the lockdown. However, the concentrations of other gaseous pollutants, e.g., SO(2), NO(2) and CO, were correlated with industrial and traffic emissions, and the lowest values were noticed in the second period (1/24-2/03) of the lockdown. Meteorological correlation analysis revealed that the decreased PM(2.5) concentrations during COVID-19 can be mainly attributed to decreased industrial and traffic emissions rather than meteorological conditions. When meteorological factors were included in the PM(2.5) composition and backward trajectory analyses, we found that long-distance transportation and secondary pollution offset the reduction of primary emissions in the second and third stages of the pandemic. Notably, industrial PM(2.5) emissions from western, southern and southeastern Guangzhou play an important role in the formation of heavy pollution events. Our results not only verify the importance of controlling traffic and industrial emissions, but also provide targets for further improvements in PM(2.5) pollution. The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V. 2022-05 2021-07-15 /pmc/articles/PMC8279957/ /pubmed/34969472 http://dx.doi.org/10.1016/j.jes.2021.07.009 Text en © 2021 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V. 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
Wen, Luyao
Yang, Chun
Liao, Xiaoliang
Zhang, Yanhao
Chai, Xuyang
Gao, Wenjun
Guo, Shulin
Bi, Yinglei
Tsang, Suk-Ying
Chen, Zhi-Feng
Qi, Zenghua
Cai, Zongwei
Investigation of PM(2.5) pollution during COVID-19 pandemic in Guangzhou, China
title Investigation of PM(2.5) pollution during COVID-19 pandemic in Guangzhou, China
title_full Investigation of PM(2.5) pollution during COVID-19 pandemic in Guangzhou, China
title_fullStr Investigation of PM(2.5) pollution during COVID-19 pandemic in Guangzhou, China
title_full_unstemmed Investigation of PM(2.5) pollution during COVID-19 pandemic in Guangzhou, China
title_short Investigation of PM(2.5) pollution during COVID-19 pandemic in Guangzhou, China
title_sort investigation of pm(2.5) pollution during covid-19 pandemic in guangzhou, china
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8279957/
https://www.ncbi.nlm.nih.gov/pubmed/34969472
http://dx.doi.org/10.1016/j.jes.2021.07.009
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