Air quality improvement from COVID-19 lockdown: evidence from China.
Identifieur interne : 000C81 ( Main/Corpus ); précédent : 000C80; suivant : 000C82Air quality improvement from COVID-19 lockdown: evidence from China.
Auteurs : Meichang Wang ; Feng Liu ; Meina ZhengSource :
- Air quality, atmosphere, & health [ 1873-9318 ] ; 2020.
Abstract
As we move through 2020, our world has been transformed by the spread of COVID-19 in many aspects. A large number of cities across the world entered "sleep mode" sequentially due to the stay-at-home or lockdown policies. This study exploits the impact of pandemic-induced human mobility restrictions, as the response to COVID-19 pandemic, on the urban air quality across China. Different from the "traditional" difference-in-differences analysis, a human mobility-based difference-in-differences method is used to quantify the effect of intracity mobility reductions on air quality across 325 cities in China. The model shows that the air quality index (AQI) experiences a 12.2% larger reduction in the cities with lockdown. Moreover, this reduction effect varies with different types of air pollutants (PM2.5, PM10, SO2, NO2, and CO decreased by 13.1%, 15.3%, 4%, 3.3%, and 3.3%, respectively). The heterogeneity analysis in terms of different types of cities shows that the effect is greater in northern, higher income, more industrialized cities, and more economically active cities. We also estimate the subsequent health benefits following such improvement, and the expected averted premature deaths due to air pollution declines are around 26,385 to 38,977 during the sample period. These findings illuminate a new light on the role of a policy intervention in the pollution emission, while also providing a roadmap for future research on the pollution effect of COVID-19 pandemic.
DOI: 10.1007/s11869-020-00963-y
PubMed: 33193909
PubMed Central: PMC7652049
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Air quality improvement from COVID-19 lockdown: evidence from China.</title><author><name sortKey="Wang, Meichang" sort="Wang, Meichang" uniqKey="Wang M" first="Meichang" last="Wang">Meichang Wang</name><affiliation><nlm:affiliation>School of Economics and Management, Southeast University, No 2, Sipailou, Nanjing, 210096 Jiangsu China.</nlm:affiliation></affiliation></author><author><name sortKey="Liu, Feng" sort="Liu, Feng" uniqKey="Liu F" first="Feng" last="Liu">Feng Liu</name><affiliation><nlm:affiliation>School of Economics and Management, Southeast University, No 2, Sipailou, Nanjing, 210096 Jiangsu China.</nlm:affiliation></affiliation></author><author><name sortKey="Zheng, Meina" sort="Zheng, Meina" uniqKey="Zheng M" first="Meina" last="Zheng">Meina Zheng</name><affiliation><nlm:affiliation>School of Transportation, Southeast University, No 2, Sipailou, Nanjing, 210096 Jiangsu China.</nlm:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2020">2020</date><idno type="RBID">pubmed:33193909</idno><idno type="pmid">33193909</idno><idno type="doi">10.1007/s11869-020-00963-y</idno><idno type="pmc">PMC7652049</idno><idno type="wicri:Area/Main/Corpus">000C81</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">000C81</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Air quality improvement from COVID-19 lockdown: evidence from China.</title><author><name sortKey="Wang, Meichang" sort="Wang, Meichang" uniqKey="Wang M" first="Meichang" last="Wang">Meichang Wang</name><affiliation><nlm:affiliation>School of Economics and Management, Southeast University, No 2, Sipailou, Nanjing, 210096 Jiangsu China.</nlm:affiliation></affiliation></author><author><name sortKey="Liu, Feng" sort="Liu, Feng" uniqKey="Liu F" first="Feng" last="Liu">Feng Liu</name><affiliation><nlm:affiliation>School of Economics and Management, Southeast University, No 2, Sipailou, Nanjing, 210096 Jiangsu China.</nlm:affiliation></affiliation></author><author><name sortKey="Zheng, Meina" sort="Zheng, Meina" uniqKey="Zheng M" first="Meina" last="Zheng">Meina Zheng</name><affiliation><nlm:affiliation>School of Transportation, Southeast University, No 2, Sipailou, Nanjing, 210096 Jiangsu China.</nlm:affiliation></affiliation></author></analytic><series><title level="j">Air quality, atmosphere, & health</title><idno type="ISSN">1873-9318</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">As we move through 2020, our world has been transformed by the spread of COVID-19 in many aspects. A large number of cities across the world entered "sleep mode" sequentially due to the stay-at-home or lockdown policies. This study exploits the impact of pandemic-induced human mobility restrictions, as the response to COVID-19 pandemic, on the urban air quality across China. Different from the "traditional" difference-in-differences analysis, a human mobility-based difference-in-differences method is used to quantify the effect of intracity mobility reductions on air quality across 325 cities in China. The model shows that the air quality index (AQI) experiences a 12.2% larger reduction in the cities with lockdown. Moreover, this reduction effect varies with different types of air pollutants (PM<sub>2.5</sub>, PM<sub>10</sub>, SO<sub>2</sub>, NO<sub>2</sub>, and CO decreased by 13.1%, 15.3%, 4%, 3.3%, and 3.3%, respectively). The heterogeneity analysis in terms of different types of cities shows that the effect is greater in northern, higher income, more industrialized cities, and more economically active cities. We also estimate the subsequent health benefits following such improvement, and the expected averted premature deaths due to air pollution declines are around 26,385 to 38,977 during the sample period. These findings illuminate a new light on the role of a policy intervention in the pollution emission, while also providing a roadmap for future research on the pollution effect of COVID-19 pandemic.</div></front></TEI><pubmed><MedlineCitation Status="Publisher" Owner="NLM"><PMID Version="1">33193909</PMID><DateRevised><Year>2020</Year><Month>11</Month><Day>17</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Print">1873-9318</ISSN><JournalIssue CitedMedium="Print"><PubDate><Year>2020</Year><Month>Nov</Month><Day>09</Day></PubDate></JournalIssue><Title>Air quality, atmosphere, & health</Title><ISOAbbreviation>Air Qual Atmos Health</ISOAbbreviation></Journal><ArticleTitle>Air quality improvement from COVID-19 lockdown: evidence from China.</ArticleTitle><Pagination><MedlinePgn>1-14</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1007/s11869-020-00963-y</ELocationID><Abstract><AbstractText>As we move through 2020, our world has been transformed by the spread of COVID-19 in many aspects. A large number of cities across the world entered "sleep mode" sequentially due to the stay-at-home or lockdown policies. This study exploits the impact of pandemic-induced human mobility restrictions, as the response to COVID-19 pandemic, on the urban air quality across China. Different from the "traditional" difference-in-differences analysis, a human mobility-based difference-in-differences method is used to quantify the effect of intracity mobility reductions on air quality across 325 cities in China. The model shows that the air quality index (AQI) experiences a 12.2% larger reduction in the cities with lockdown. Moreover, this reduction effect varies with different types of air pollutants (PM<sub>2.5</sub>, PM<sub>10</sub>, SO<sub>2</sub>, NO<sub>2</sub>, and CO decreased by 13.1%, 15.3%, 4%, 3.3%, and 3.3%, respectively). The heterogeneity analysis in terms of different types of cities shows that the effect is greater in northern, higher income, more industrialized cities, and more economically active cities. We also estimate the subsequent health benefits following such improvement, and the expected averted premature deaths due to air pollution declines are around 26,385 to 38,977 during the sample period. These findings illuminate a new light on the role of a policy intervention in the pollution emission, while also providing a roadmap for future research on the pollution effect of COVID-19 pandemic.</AbstractText><CopyrightInformation>© Springer Nature B.V. 2020.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Wang</LastName><ForeName>Meichang</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>School of Economics and Management, Southeast University, No 2, Sipailou, Nanjing, 210096 Jiangsu China.</Affiliation><Identifier Source="GRID">grid.263826.b</Identifier><Identifier Source="ISNI">0000 0004 1761 0489</Identifier></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Liu</LastName><ForeName>Feng</ForeName><Initials>F</Initials><AffiliationInfo><Affiliation>School of Economics and Management, Southeast University, No 2, Sipailou, Nanjing, 210096 Jiangsu China.</Affiliation><Identifier Source="GRID">grid.263826.b</Identifier><Identifier Source="ISNI">0000 0004 1761 0489</Identifier></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Zheng</LastName><ForeName>Meina</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>School of Transportation, Southeast University, No 2, Sipailou, Nanjing, 210096 Jiangsu China.</Affiliation><Identifier Source="GRID">grid.263826.b</Identifier><Identifier Source="ISNI">0000 0004 1761 0489</Identifier></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>11</Month><Day>09</Day></ArticleDate></Article><MedlineJournalInfo><Country>Netherlands</Country><MedlineTA>Air Qual Atmos Health</MedlineTA><NlmUniqueID>101317801</NlmUniqueID><ISSNLinking>1873-9318</ISSNLinking></MedlineJournalInfo><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Air pollution</Keyword><Keyword MajorTopicYN="N">COVID-19 pandemic</Keyword><Keyword MajorTopicYN="N">Health benefit</Keyword><Keyword MajorTopicYN="N">Heterogeneity</Keyword><Keyword MajorTopicYN="N">Lockdown</Keyword></KeywordList><CoiStatement>Conflict of interestThe authors declare that they have no conflict of interest.</CoiStatement></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2020</Year><Month>08</Month><Day>17</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2020</Year><Month>11</Month><Day>02</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>11</Month><Day>16</Day><Hour>8</Hour><Minute>49</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>11</Month><Day>17</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>11</Month><Day>17</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>aheadofprint</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">33193909</ArticleId><ArticleId IdType="doi">10.1007/s11869-020-00963-y</ArticleId><ArticleId IdType="pii">963</ArticleId><ArticleId IdType="pmc">PMC7652049</ArticleId></ArticleIdList><pmc-dir>pmcsd</pmc-dir>
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