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Assessing the change of ambient air quality patterns in Jiangsu Province of China pre-to post-COVID-19
Following the outbreak of the novel coronavirus in early 2020, to effectively prevent the spread of the disease, major cities across China suspended work and production. While the rest of the world struggles to control COVID-19, China has managed to control the pandemic rapidly and effectively with...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Published by Elsevier Ltd.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8514250/ https://www.ncbi.nlm.nih.gov/pubmed/34655644 http://dx.doi.org/10.1016/j.chemosphere.2021.132569 |
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author | Bhatti, Uzair Aslam Zeeshan, Zeeshan Nizamani, Mir Muhammad Bazai, Sibghatullah Yu, Zhaoyuan Yuan, Linwang |
author_facet | Bhatti, Uzair Aslam Zeeshan, Zeeshan Nizamani, Mir Muhammad Bazai, Sibghatullah Yu, Zhaoyuan Yuan, Linwang |
author_sort | Bhatti, Uzair Aslam |
collection | PubMed |
description | Following the outbreak of the novel coronavirus in early 2020, to effectively prevent the spread of the disease, major cities across China suspended work and production. While the rest of the world struggles to control COVID-19, China has managed to control the pandemic rapidly and effectively with strong lockdown policies. This study investigates the change in air pollution (focusing on the air quality index (AQI), six ambient air pollutants nitrogen dioxide (NO(2)), ozone (O(3)), sulphur dioxide (SO(2)), carbon monoxide (CO), particulate matter with aerodynamic diameters ≤10 μm (PM(10)) and ≤2.5 μm (PM(2.5))) patterns for three periods: pre-COVID (from 1 January to May 30, 2019), active COVID (from 1 January to May 30, 2020) and post-COVID (from 1 January to May 30, 2021) in the Jiangsu province of China. Our findings reveal that the change in air pollution from pre-COVID to active COVID was greater than in previous years due to the government's lockdown policies. Post-COVID, air pollutant concentration is increasing. Mean change PM(2.5) from pre-COVID to active COVID decreased by 18%; post-COVID it has only decreased by 2%. PM(10) decreased by 19% from pre-COVID to active COVID, but post-COVID pollutant concentration has seen a 23% increase. Air pollutants show a positive correlation with COVID-19 cases among which PM(2.5), PM(10) and NO(2) show a strong correlation during active COVID-19 cases. Metrological factors such as minimum temperature, average temperature and humidity show a positive correlation with COVID-19 cases while maximum temperature, wind speed and air pressure show no strong positive correlation. Although the COVID-19 pandemic had numerous negative effects on human health and the global economy, the reduction in air pollution and significant improvement in ambient air quality likely had substantial short-term health benefits; the government must implement policies to control post-COVID environmental issues. |
format | Online Article Text |
id | pubmed-8514250 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Published by Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-85142502021-10-14 Assessing the change of ambient air quality patterns in Jiangsu Province of China pre-to post-COVID-19 Bhatti, Uzair Aslam Zeeshan, Zeeshan Nizamani, Mir Muhammad Bazai, Sibghatullah Yu, Zhaoyuan Yuan, Linwang Chemosphere Article Following the outbreak of the novel coronavirus in early 2020, to effectively prevent the spread of the disease, major cities across China suspended work and production. While the rest of the world struggles to control COVID-19, China has managed to control the pandemic rapidly and effectively with strong lockdown policies. This study investigates the change in air pollution (focusing on the air quality index (AQI), six ambient air pollutants nitrogen dioxide (NO(2)), ozone (O(3)), sulphur dioxide (SO(2)), carbon monoxide (CO), particulate matter with aerodynamic diameters ≤10 μm (PM(10)) and ≤2.5 μm (PM(2.5))) patterns for three periods: pre-COVID (from 1 January to May 30, 2019), active COVID (from 1 January to May 30, 2020) and post-COVID (from 1 January to May 30, 2021) in the Jiangsu province of China. Our findings reveal that the change in air pollution from pre-COVID to active COVID was greater than in previous years due to the government's lockdown policies. Post-COVID, air pollutant concentration is increasing. Mean change PM(2.5) from pre-COVID to active COVID decreased by 18%; post-COVID it has only decreased by 2%. PM(10) decreased by 19% from pre-COVID to active COVID, but post-COVID pollutant concentration has seen a 23% increase. Air pollutants show a positive correlation with COVID-19 cases among which PM(2.5), PM(10) and NO(2) show a strong correlation during active COVID-19 cases. Metrological factors such as minimum temperature, average temperature and humidity show a positive correlation with COVID-19 cases while maximum temperature, wind speed and air pressure show no strong positive correlation. Although the COVID-19 pandemic had numerous negative effects on human health and the global economy, the reduction in air pollution and significant improvement in ambient air quality likely had substantial short-term health benefits; the government must implement policies to control post-COVID environmental issues. Published by Elsevier Ltd. 2022-02 2021-10-14 /pmc/articles/PMC8514250/ /pubmed/34655644 http://dx.doi.org/10.1016/j.chemosphere.2021.132569 Text en © 2021 Published by Elsevier Ltd. 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 Bhatti, Uzair Aslam Zeeshan, Zeeshan Nizamani, Mir Muhammad Bazai, Sibghatullah Yu, Zhaoyuan Yuan, Linwang Assessing the change of ambient air quality patterns in Jiangsu Province of China pre-to post-COVID-19 |
title | Assessing the change of ambient air quality patterns in Jiangsu Province of China pre-to post-COVID-19 |
title_full | Assessing the change of ambient air quality patterns in Jiangsu Province of China pre-to post-COVID-19 |
title_fullStr | Assessing the change of ambient air quality patterns in Jiangsu Province of China pre-to post-COVID-19 |
title_full_unstemmed | Assessing the change of ambient air quality patterns in Jiangsu Province of China pre-to post-COVID-19 |
title_short | Assessing the change of ambient air quality patterns in Jiangsu Province of China pre-to post-COVID-19 |
title_sort | assessing the change of ambient air quality patterns in jiangsu province of china pre-to post-covid-19 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8514250/ https://www.ncbi.nlm.nih.gov/pubmed/34655644 http://dx.doi.org/10.1016/j.chemosphere.2021.132569 |
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