Impacts of COVID-19 lockdown, Spring Festival and meteorology on the NO2 variations in early 2020 over China based on in-situ observations, satellite retrievals and model simulations.
Identifieur interne : 001420 ( Main/Corpus ); précédent : 001419; suivant : 001421Impacts of COVID-19 lockdown, Spring Festival and meteorology on the NO2 variations in early 2020 over China based on in-situ observations, satellite retrievals and model simulations.
Auteurs : Zhe Wang ; Itsushi Uno ; Keiya Yumimoto ; Syuichi Itahashi ; Xueshun Chen ; Wenyi Yang ; Zifa WangSource :
- Atmospheric environment (Oxford, England : 1994) [ 1352-2310 ] ; 2021.
Abstract
The lockdown measures due to COVID-19 affected the industry, transportation and other human activities within China in early 2020, and subsequently the emissions of air pollutants. The decrease of atmospheric NO2 due to the COVID-19 lockdown and other factors were quantitively analyzed based on the surface concentrations by in-situ observations, the tropospheric vertical column densities (VCDs) by different satellite retrievals including OMI and TROPOMI, and the model simulations by GEOS-Chem. The results indicated that due to the COVID-19 lockdown, the surface NO2 concentrations decreased by 42% ± 8% and 26% ± 9% over China in February and March 2020, respectively. The tropospheric NO2 VCDs based on both OMI and high quality (quality assurance value (QA) ≥ 0.75) TROPOMI showed similar results as the surface NO2 concentrations. The daily variations of atmospheric NO2 during the first quarter (Q1) of 2020 were not only affected by the COVID-19 lockdown, but also by the Spring Festival (SF) holiday (January 24-30, 2020) as well as the meteorology changes due to seasonal transition. The SF holiday effect resulted in a NO2 reduction from 8 days before SF to 21 days after it (i.e. January 17 - February 15), with a maximum of 37%. From the 6 days after SF (January 31) to the end of March, the COVID-19 lockdown played an important role in the NO2 reduction, with a maximum of 51%. The meteorology changes due to seasonal transition resulted in a nearly linear decreasing trend of 25% and 40% reduction over the 90 days for the NO2 concentrations and VCDs, respectively. Comparisons between different datasets indicated that medium quality (QA ≥ 0.5) TROPOMI retrievals might suffer large biases in some periods, and thus attention must be paid when they are used for analyses, data assimilations and emission inversions.
DOI: 10.1016/j.atmosenv.2020.117972
PubMed: 33013178
PubMed Central: PMC7521432
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variations in early 2020 over China based on in-situ observations, satellite retrievals and model simulations.</title>
<author><name sortKey="Wang, Zhe" sort="Wang, Zhe" uniqKey="Wang Z" first="Zhe" last="Wang">Zhe Wang</name>
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<author><name sortKey="Uno, Itsushi" sort="Uno, Itsushi" uniqKey="Uno I" first="Itsushi" last="Uno">Itsushi Uno</name>
<affiliation><nlm:affiliation>Research Institute for Applied Mechanics (RIAM), Kyushu University, Fukuoka, 8168580, Japan.</nlm:affiliation>
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<author><name sortKey="Yumimoto, Keiya" sort="Yumimoto, Keiya" uniqKey="Yumimoto K" first="Keiya" last="Yumimoto">Keiya Yumimoto</name>
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<author><name sortKey="Chen, Xueshun" sort="Chen, Xueshun" uniqKey="Chen X" first="Xueshun" last="Chen">Xueshun Chen</name>
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<author><name sortKey="Yang, Wenyi" sort="Yang, Wenyi" uniqKey="Yang W" first="Wenyi" last="Yang">Wenyi Yang</name>
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<author><name sortKey="Wang, Zifa" sort="Wang, Zifa" uniqKey="Wang Z" first="Zifa" last="Wang">Zifa Wang</name>
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<front><div type="abstract" xml:lang="en">The lockdown measures due to COVID-19 affected the industry, transportation and other human activities within China in early 2020, and subsequently the emissions of air pollutants. The decrease of atmospheric NO<sub>2</sub>
due to the COVID-19 lockdown and other factors were quantitively analyzed based on the surface concentrations by in-situ observations, the tropospheric vertical column densities (VCDs) by different satellite retrievals including OMI and TROPOMI, and the model simulations by GEOS-Chem. The results indicated that due to the COVID-19 lockdown, the surface NO<sub>2</sub>
concentrations decreased by 42% ± 8% and 26% ± 9% over China in February and March 2020, respectively. The tropospheric NO<sub>2</sub>
VCDs based on both OMI and high quality (quality assurance value (QA) ≥ 0.75) TROPOMI showed similar results as the surface NO<sub>2</sub>
concentrations. The daily variations of atmospheric NO<sub>2</sub>
during the first quarter (Q1) of 2020 were not only affected by the COVID-19 lockdown, but also by the Spring Festival (SF) holiday (January 24-30, 2020) as well as the meteorology changes due to seasonal transition. The SF holiday effect resulted in a NO<sub>2</sub>
reduction from 8 days before SF to 21 days after it (i.e. January 17 - February 15), with a maximum of 37%. From the 6 days after SF (January 31) to the end of March, the COVID-19 lockdown played an important role in the NO<sub>2</sub>
reduction, with a maximum of 51%. The meteorology changes due to seasonal transition resulted in a nearly linear decreasing trend of 25% and 40% reduction over the 90 days for the NO<sub>2</sub>
concentrations and VCDs, respectively. Comparisons between different datasets indicated that medium quality (QA ≥ 0.5) TROPOMI retrievals might suffer large biases in some periods, and thus attention must be paid when they are used for analyses, data assimilations and emission inversions.</div>
</front>
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<ArticleTitle>Impacts of COVID-19 lockdown, Spring Festival and meteorology on the NO<sub>2</sub>
variations in early 2020 over China based on in-situ observations, satellite retrievals and model simulations.</ArticleTitle>
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<Abstract><AbstractText>The lockdown measures due to COVID-19 affected the industry, transportation and other human activities within China in early 2020, and subsequently the emissions of air pollutants. The decrease of atmospheric NO<sub>2</sub>
due to the COVID-19 lockdown and other factors were quantitively analyzed based on the surface concentrations by in-situ observations, the tropospheric vertical column densities (VCDs) by different satellite retrievals including OMI and TROPOMI, and the model simulations by GEOS-Chem. The results indicated that due to the COVID-19 lockdown, the surface NO<sub>2</sub>
concentrations decreased by 42% ± 8% and 26% ± 9% over China in February and March 2020, respectively. The tropospheric NO<sub>2</sub>
VCDs based on both OMI and high quality (quality assurance value (QA) ≥ 0.75) TROPOMI showed similar results as the surface NO<sub>2</sub>
concentrations. The daily variations of atmospheric NO<sub>2</sub>
during the first quarter (Q1) of 2020 were not only affected by the COVID-19 lockdown, but also by the Spring Festival (SF) holiday (January 24-30, 2020) as well as the meteorology changes due to seasonal transition. The SF holiday effect resulted in a NO<sub>2</sub>
reduction from 8 days before SF to 21 days after it (i.e. January 17 - February 15), with a maximum of 37%. From the 6 days after SF (January 31) to the end of March, the COVID-19 lockdown played an important role in the NO<sub>2</sub>
reduction, with a maximum of 51%. The meteorology changes due to seasonal transition resulted in a nearly linear decreasing trend of 25% and 40% reduction over the 90 days for the NO<sub>2</sub>
concentrations and VCDs, respectively. Comparisons between different datasets indicated that medium quality (QA ≥ 0.5) TROPOMI retrievals might suffer large biases in some periods, and thus attention must be paid when they are used for analyses, data assimilations and emission inversions.</AbstractText>
<CopyrightInformation>© 2020 Elsevier Ltd. All rights reserved.</CopyrightInformation>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Wang</LastName>
<ForeName>Zhe</ForeName>
<Initials>Z</Initials>
<AffiliationInfo><Affiliation>Research Institute for Applied Mechanics (RIAM), Kyushu University, Fukuoka, 8168580, Japan.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences (CAS), Beijing, 100029, China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Uno</LastName>
<ForeName>Itsushi</ForeName>
<Initials>I</Initials>
<AffiliationInfo><Affiliation>Research Institute for Applied Mechanics (RIAM), Kyushu University, Fukuoka, 8168580, Japan.</Affiliation>
</AffiliationInfo>
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<Author ValidYN="Y"><LastName>Yumimoto</LastName>
<ForeName>Keiya</ForeName>
<Initials>K</Initials>
<AffiliationInfo><Affiliation>Research Institute for Applied Mechanics (RIAM), Kyushu University, Fukuoka, 8168580, Japan.</Affiliation>
</AffiliationInfo>
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<Author ValidYN="Y"><LastName>Itahashi</LastName>
<ForeName>Syuichi</ForeName>
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<AffiliationInfo><Affiliation>Environmental Science Research Laboratory, Central Research Institute of Electric Power Industry (CRIEPI), Chiba, 270-1194, Japan.</Affiliation>
</AffiliationInfo>
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<Author ValidYN="Y"><LastName>Chen</LastName>
<ForeName>Xueshun</ForeName>
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<AffiliationInfo><Affiliation>State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences (CAS), Beijing, 100029, China.</Affiliation>
</AffiliationInfo>
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<Author ValidYN="Y"><LastName>Yang</LastName>
<ForeName>Wenyi</ForeName>
<Initials>W</Initials>
<AffiliationInfo><Affiliation>State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences (CAS), Beijing, 100029, China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Wang</LastName>
<ForeName>Zifa</ForeName>
<Initials>Z</Initials>
<AffiliationInfo><Affiliation>State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences (CAS), Beijing, 100029, China.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>College of Earth and Planetary Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, 100049, China.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Center for Excellence in Urban Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China.</Affiliation>
</AffiliationInfo>
</Author>
</AuthorList>
<Language>eng</Language>
<PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType>
</PublicationTypeList>
<ArticleDate DateType="Electronic"><Year>2020</Year>
<Month>09</Month>
<Day>28</Day>
</ArticleDate>
</Article>
<MedlineJournalInfo><Country>England</Country>
<MedlineTA>Atmos Environ (1994)</MedlineTA>
<NlmUniqueID>9888534</NlmUniqueID>
<ISSNLinking>1352-2310</ISSNLinking>
</MedlineJournalInfo>
<KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">COVID-19</Keyword>
<Keyword MajorTopicYN="N">China</Keyword>
<Keyword MajorTopicYN="N">GEOS-Chem</Keyword>
<Keyword MajorTopicYN="N">NO2</Keyword>
<Keyword MajorTopicYN="N">OMI</Keyword>
<Keyword MajorTopicYN="N">TROPOMI</Keyword>
</KeywordList>
<CoiStatement>The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.</CoiStatement>
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