Ozone pollution mitigation in guangxi (south China) driven by meteorology and anthropogenic emissions during the COVID-19 lockdown.
Identifieur interne : 000E96 ( Main/Corpus ); précédent : 000E95; suivant : 000E97Ozone pollution mitigation in guangxi (south China) driven by meteorology and anthropogenic emissions during the COVID-19 lockdown.
Auteurs : Shuang Fu ; Meixiu Guo ; Linping Fan ; Qiyin Deng ; Deming Han ; Ye Wei ; Jinmin Luo ; Guimei Qin ; Jinping ChengSource :
- Environmental pollution (Barking, Essex : 1987) [ 1873-6424 ] ; 2020.
Abstract
With the implementation of COVID-19 restrictions and consequent improvement in air quality due to the nationwide lockdown, ozone (O3) pollution was generally amplified in China. However, the O3 levels throughout the Guangxi region of South China showed a clear downward trend during the lockdown. To better understand this unusual phenomenon, we investigated the characteristics of conventional pollutants, the influence of meteorological and anthropogenic factors quantified by a multiple linear regression (MLR) model, and the impact of local sources and long-range transport based on a continuous emission monitoring system (CEMS) and the HYSPLIT model. Results show that in Guangxi, the conventional pollutants generally declined during the COVID-19 lockdown period (January 24 to February 9, 2020) compared with their concentrations during 2016-2019, while O3 gradually increased during the resumption (10 February to April 2020) and full operation periods (May and June 2020). Focusing on Beihai, a typical Guangxi region city, the correlations between the daily O3 concentrations and six meteorological parameters (wind speed, visibility, temperature, humidity, precipitation, and atmospheric pressure) and their corresponding regression coefficients indicate that meteorological conditions were generally conducive to O3 pollution mitigation during the lockdown. A 7.84 μg/m3 drop in O3 concentration was driven by meteorology, with other decreases (4.11 μg/m3) explained by reduced anthropogenic emissions of O3 precursors. Taken together, the lower NO2/SO2 ratios (1.25-2.33) and consistencies between real-time monitored primary emissions and ambient concentrations suggest that, with the closure of small-scale industries, residual industrial emissions have become dominant contributors to local primary pollutants. Backward trajectory cluster analyses show that the slump of O3 concentrations in Southern Guangxi could be partly attributed to clean air mass transfer (24-58%) from the South China Sea. Overall, the synergistic effects of the COVID-19 lockdown and meteorological factors intensified O3 reduction in the Guangxi region of South China.
DOI: 10.1016/j.envpol.2020.115927
PubMed: 33143981
PubMed Central: PMC7588315
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<front><div type="abstract" xml:lang="en">With the implementation of COVID-19 restrictions and consequent improvement in air quality due to the nationwide lockdown, ozone (O<sub>3</sub>
) pollution was generally amplified in China. However, the O<sub>3</sub>
levels throughout the Guangxi region of South China showed a clear downward trend during the lockdown. To better understand this unusual phenomenon, we investigated the characteristics of conventional pollutants, the influence of meteorological and anthropogenic factors quantified by a multiple linear regression (MLR) model, and the impact of local sources and long-range transport based on a continuous emission monitoring system (CEMS) and the HYSPLIT model. Results show that in Guangxi, the conventional pollutants generally declined during the COVID-19 lockdown period (January 24 to February 9, 2020) compared with their concentrations during 2016-2019, while O<sub>3</sub>
gradually increased during the resumption (10 February to April 2020) and full operation periods (May and June 2020). Focusing on Beihai, a typical Guangxi region city, the correlations between the daily O<sub>3</sub>
concentrations and six meteorological parameters (wind speed, visibility, temperature, humidity, precipitation, and atmospheric pressure) and their corresponding regression coefficients indicate that meteorological conditions were generally conducive to O<sub>3</sub>
pollution mitigation during the lockdown. A 7.84 μg/m<sup>3</sup>
drop in O<sub>3</sub>
concentration was driven by meteorology, with other decreases (4.11 μg/m<sup>3</sup>
) explained by reduced anthropogenic emissions of O<sub>3</sub>
precursors. Taken together, the lower NO<sub>2</sub>
/SO<sub>2</sub>
ratios (1.25-2.33) and consistencies between real-time monitored primary emissions and ambient concentrations suggest that, with the closure of small-scale industries, residual industrial emissions have become dominant contributors to local primary pollutants. Backward trajectory cluster analyses show that the slump of O<sub>3</sub>
concentrations in Southern Guangxi could be partly attributed to clean air mass transfer (24-58%) from the South China Sea. Overall, the synergistic effects of the COVID-19 lockdown and meteorological factors intensified O<sub>3</sub>
reduction in the Guangxi region of South China.</div>
</front>
</TEI>
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<DateRevised><Year>2020</Year>
<Month>11</Month>
<Day>06</Day>
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<Title>Environmental pollution (Barking, Essex : 1987)</Title>
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<ArticleTitle>Ozone pollution mitigation in guangxi (south China) driven by meteorology and anthropogenic emissions during the COVID-19 lockdown.</ArticleTitle>
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<Abstract><AbstractText>With the implementation of COVID-19 restrictions and consequent improvement in air quality due to the nationwide lockdown, ozone (O<sub>3</sub>
) pollution was generally amplified in China. However, the O<sub>3</sub>
levels throughout the Guangxi region of South China showed a clear downward trend during the lockdown. To better understand this unusual phenomenon, we investigated the characteristics of conventional pollutants, the influence of meteorological and anthropogenic factors quantified by a multiple linear regression (MLR) model, and the impact of local sources and long-range transport based on a continuous emission monitoring system (CEMS) and the HYSPLIT model. Results show that in Guangxi, the conventional pollutants generally declined during the COVID-19 lockdown period (January 24 to February 9, 2020) compared with their concentrations during 2016-2019, while O<sub>3</sub>
gradually increased during the resumption (10 February to April 2020) and full operation periods (May and June 2020). Focusing on Beihai, a typical Guangxi region city, the correlations between the daily O<sub>3</sub>
concentrations and six meteorological parameters (wind speed, visibility, temperature, humidity, precipitation, and atmospheric pressure) and their corresponding regression coefficients indicate that meteorological conditions were generally conducive to O<sub>3</sub>
pollution mitigation during the lockdown. A 7.84 μg/m<sup>3</sup>
drop in O<sub>3</sub>
concentration was driven by meteorology, with other decreases (4.11 μg/m<sup>3</sup>
) explained by reduced anthropogenic emissions of O<sub>3</sub>
precursors. Taken together, the lower NO<sub>2</sub>
/SO<sub>2</sub>
ratios (1.25-2.33) and consistencies between real-time monitored primary emissions and ambient concentrations suggest that, with the closure of small-scale industries, residual industrial emissions have become dominant contributors to local primary pollutants. Backward trajectory cluster analyses show that the slump of O<sub>3</sub>
concentrations in Southern Guangxi could be partly attributed to clean air mass transfer (24-58%) from the South China Sea. Overall, the synergistic effects of the COVID-19 lockdown and meteorological factors intensified O<sub>3</sub>
reduction in the Guangxi region of South China.</AbstractText>
<CopyrightInformation>Copyright © 2020 Elsevier Ltd. All rights reserved.</CopyrightInformation>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Fu</LastName>
<ForeName>Shuang</ForeName>
<Initials>S</Initials>
<AffiliationInfo><Affiliation>School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.</Affiliation>
</AffiliationInfo>
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<Author ValidYN="Y"><LastName>Guo</LastName>
<ForeName>Meixiu</ForeName>
<Initials>M</Initials>
<AffiliationInfo><Affiliation>Beihai Ecology and Environment Agency, Beihai, Guangxi, 536000, China.</Affiliation>
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<Author ValidYN="Y"><LastName>Fan</LastName>
<ForeName>Linping</ForeName>
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<Initials>Q</Initials>
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<Author ValidYN="Y"><LastName>Han</LastName>
<ForeName>Deming</ForeName>
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<ForeName>Jinmin</ForeName>
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</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Qin</LastName>
<ForeName>Guimei</ForeName>
<Initials>G</Initials>
<AffiliationInfo><Affiliation>School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Cheng</LastName>
<ForeName>Jinping</ForeName>
<Initials>J</Initials>
<AffiliationInfo><Affiliation>School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China. Electronic address: jpcheng@sjtu.edu.cn.</Affiliation>
</AffiliationInfo>
</Author>
</AuthorList>
<Language>eng</Language>
<PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType>
</PublicationTypeList>
<ArticleDate DateType="Electronic"><Year>2020</Year>
<Month>10</Month>
<Day>27</Day>
</ArticleDate>
</Article>
<MedlineJournalInfo><Country>England</Country>
<MedlineTA>Environ Pollut</MedlineTA>
<NlmUniqueID>8804476</NlmUniqueID>
<ISSNLinking>0269-7491</ISSNLinking>
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<CitationSubset>IM</CitationSubset>
<KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">CEMS</Keyword>
<Keyword MajorTopicYN="N">COVID-19</Keyword>
<Keyword MajorTopicYN="N">Lockdown</Keyword>
<Keyword MajorTopicYN="N">MLR model</Keyword>
<Keyword MajorTopicYN="N">Ozone</Keyword>
<Keyword MajorTopicYN="N">South China</Keyword>
</KeywordList>
<CoiStatement>Declaration of competing interest 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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<ReferenceList><Reference><Citation>Sci Total Environ. 2020 Nov 1;741:140244</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32592975</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Atmos Chem Phys. 2018;18(20):15003-15016</Citation>
<ArticleIdList><ArticleId IdType="pubmed">30930942</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Sci Total Environ. 2019 Feb 10;650(Pt 2):2624-2639</Citation>
<ArticleIdList><ArticleId IdType="pubmed">30373049</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Sci Total Environ. 2020 Aug 1;728:138878</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32335409</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Environ Pollut. 2020 Jul;262:114276</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32179215</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Sci Total Environ. 2020 Nov 10;742:140516</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32629257</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Sci Total Environ. 2019 Feb 20;652:1228-1241</Citation>
<ArticleIdList><ArticleId IdType="pubmed">30586809</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Sci Total Environ. 2020 Nov 10;742:140739</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32721760</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Sci Rep. 2015 Oct 15;5:14884</Citation>
<ArticleIdList><ArticleId IdType="pubmed">26469995</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Sci Total Environ. 2020 Aug 25;732:139282</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32413621</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Sci Total Environ. 2020 Nov 20;744:140825</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32755775</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Sci Total Environ. 2020 Oct 15;739:140000</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32540668</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>J Environ Sci (China). 2016 Jun;44:13-25</Citation>
<ArticleIdList><ArticleId IdType="pubmed">27266298</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Environ Pollut. 2020 Sep;264:114694</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32402710</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Sci Total Environ. 2020 Sep 15;735:139542</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32447070</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Environ Pollut. 2020 Mar;258:113659</Citation>
<ArticleIdList><ArticleId IdType="pubmed">31806463</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Sci Total Environ. 2020 Oct 1;737:139765</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32480061</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Sci Total Environ. 2019 Mar 20;657:1491-1500</Citation>
<ArticleIdList><ArticleId IdType="pubmed">30677915</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Sci Total Environ. 2017 Apr 15;584-585:1056-1065</Citation>
<ArticleIdList><ArticleId IdType="pubmed">28161040</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Sci Total Environ. 2020 Aug 1;728:138861</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32344226</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Sci Total Environ. 2020 Nov 20;744:140837</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32693282</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Sci Total Environ. 2017 Jan 1;575:1582-1596</Citation>
<ArticleIdList><ArticleId IdType="pubmed">27789078</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Sci Total Environ. 2020 Aug 20;731:139052</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32413655</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Sci Total Environ. 2020 Nov 15;743:140879</Citation>
<ArticleIdList><ArticleId IdType="pubmed">32758857</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
</PubmedData>
</pubmed>
</record>
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