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Disentangling drivers of air pollutant and health risk changes during the COVID-19 lockdown in China
The COVID-19 restrictions in 2020 have led to distinct variations in NO(2) and O(3) concentrations in China. Here, the different drivers of anthropogenic emission changes, including the effects of the Chinese New Year (CNY), China’s 2018–2020 Clean Air Plan (CAP), and the COVID-19 lockdown and their...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9244310/ https://www.ncbi.nlm.nih.gov/pubmed/35789740 http://dx.doi.org/10.1038/s41612-022-00276-0 |
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author | Shen, Fuzhen Hegglin, Michaela I. Luo, Yuanfei Yuan, Yue Wang, Bing Flemming, Johannes Wang, Junfeng Zhang, Yunjiang Chen, Mindong Yang, Qiang Ge, Xinlei |
author_facet | Shen, Fuzhen Hegglin, Michaela I. Luo, Yuanfei Yuan, Yue Wang, Bing Flemming, Johannes Wang, Junfeng Zhang, Yunjiang Chen, Mindong Yang, Qiang Ge, Xinlei |
author_sort | Shen, Fuzhen |
collection | PubMed |
description | The COVID-19 restrictions in 2020 have led to distinct variations in NO(2) and O(3) concentrations in China. Here, the different drivers of anthropogenic emission changes, including the effects of the Chinese New Year (CNY), China’s 2018–2020 Clean Air Plan (CAP), and the COVID-19 lockdown and their impact on NO(2) and O(3) are isolated by using a combined model-measurement approach. In addition, the contribution of prevailing meteorological conditions to the concentration changes was evaluated by applying a machine-learning method. The resulting impact on the multi-pollutant Health-based Air Quality Index (HAQI) is quantified. The results show that the CNY reduces NO(2) concentrations on average by 26.7% each year, while the COVID-lockdown measures have led to an additional 11.6% reduction in 2020, and the CAP over 2018–2020 to a reduction in NO(2) by 15.7%. On the other hand, meteorological conditions from 23 January to March 7, 2020 led to increase in NO(2) of 7.8%. Neglecting the CAP and meteorological drivers thus leads to an overestimate and underestimate of the effect of the COVID-lockdown on NO(2) reductions, respectively. For O(3) the opposite behavior is found, with changes of +23.3%, +21.0%, +4.9%, and −0.9% for CNY, COVID-lockdown, CAP, and meteorology effects, respectively. The total effects of these drivers show a drastic reduction in multi-air pollutant-related health risk across China, with meteorology affecting particularly the Northeast of China adversely. Importantly, the CAP’s contribution highlights the effectiveness of the Chinese government’s air-quality regulations on NO(2) reduction. |
format | Online Article Text |
id | pubmed-9244310 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-92443102022-06-30 Disentangling drivers of air pollutant and health risk changes during the COVID-19 lockdown in China Shen, Fuzhen Hegglin, Michaela I. Luo, Yuanfei Yuan, Yue Wang, Bing Flemming, Johannes Wang, Junfeng Zhang, Yunjiang Chen, Mindong Yang, Qiang Ge, Xinlei NPJ Clim Atmos Sci Article The COVID-19 restrictions in 2020 have led to distinct variations in NO(2) and O(3) concentrations in China. Here, the different drivers of anthropogenic emission changes, including the effects of the Chinese New Year (CNY), China’s 2018–2020 Clean Air Plan (CAP), and the COVID-19 lockdown and their impact on NO(2) and O(3) are isolated by using a combined model-measurement approach. In addition, the contribution of prevailing meteorological conditions to the concentration changes was evaluated by applying a machine-learning method. The resulting impact on the multi-pollutant Health-based Air Quality Index (HAQI) is quantified. The results show that the CNY reduces NO(2) concentrations on average by 26.7% each year, while the COVID-lockdown measures have led to an additional 11.6% reduction in 2020, and the CAP over 2018–2020 to a reduction in NO(2) by 15.7%. On the other hand, meteorological conditions from 23 January to March 7, 2020 led to increase in NO(2) of 7.8%. Neglecting the CAP and meteorological drivers thus leads to an overestimate and underestimate of the effect of the COVID-lockdown on NO(2) reductions, respectively. For O(3) the opposite behavior is found, with changes of +23.3%, +21.0%, +4.9%, and −0.9% for CNY, COVID-lockdown, CAP, and meteorology effects, respectively. The total effects of these drivers show a drastic reduction in multi-air pollutant-related health risk across China, with meteorology affecting particularly the Northeast of China adversely. Importantly, the CAP’s contribution highlights the effectiveness of the Chinese government’s air-quality regulations on NO(2) reduction. Nature Publishing Group UK 2022-06-30 2022 /pmc/articles/PMC9244310/ /pubmed/35789740 http://dx.doi.org/10.1038/s41612-022-00276-0 Text en © The Author(s) 2022 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Shen, Fuzhen Hegglin, Michaela I. Luo, Yuanfei Yuan, Yue Wang, Bing Flemming, Johannes Wang, Junfeng Zhang, Yunjiang Chen, Mindong Yang, Qiang Ge, Xinlei Disentangling drivers of air pollutant and health risk changes during the COVID-19 lockdown in China |
title | Disentangling drivers of air pollutant and health risk changes during the COVID-19 lockdown in China |
title_full | Disentangling drivers of air pollutant and health risk changes during the COVID-19 lockdown in China |
title_fullStr | Disentangling drivers of air pollutant and health risk changes during the COVID-19 lockdown in China |
title_full_unstemmed | Disentangling drivers of air pollutant and health risk changes during the COVID-19 lockdown in China |
title_short | Disentangling drivers of air pollutant and health risk changes during the COVID-19 lockdown in China |
title_sort | disentangling drivers of air pollutant and health risk changes during the covid-19 lockdown in china |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9244310/ https://www.ncbi.nlm.nih.gov/pubmed/35789740 http://dx.doi.org/10.1038/s41612-022-00276-0 |
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