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Article: Can urban polycentricity improve air quality? Evidence from Chinese cities

TitleCan urban polycentricity improve air quality? Evidence from Chinese cities
Authors
KeywordsAir pollution
China
PM2.5
Urban polycentricity
Issue Date2023
Citation
Journal of Cleaner Production, 2023, v. 406, article no. 137080 How to Cite?
AbstractThis study utilizes high-resolution population grid data from 2004 to 2018 to assess the extent of urban polycentricity in 284 Chinese prefecture-level cities. A new method for measuring urban polycentricity is devised using the Clauset-Newman-Moore grey modularity maximization algorithm. Additionally, the Spatial Durbin Model is applied to investigate the effect of urban polycentricity on the mean and spatial variation of PM2.5 concentrations. Our statistical results show that the increased distance between urban centers and the increased size disparity between the large and small centers effectively reduces air pollution within the city. On the other hand, in cities with a strong clustering of urban centers and significant size disparity between main and sub-centers, the polycentric urban structure cannot help reduce air pollution but merely shift it to other urban centers within the city. Hence, interpreting the severity of urban air pollution solely on the basis of the citywide average of air pollution may be insufficient. It is necessary to consider the possible relocation of air-polluting activities associated with polycentric urban structures. Policymakers should take into account the potential spatial inequality of air pollution driven by urban polycentricity.
Persistent Identifierhttp://hdl.handle.net/10722/329937
ISSN
2023 Impact Factor: 9.7
2023 SCImago Journal Rankings: 2.058
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorQiang, Will W.-
dc.contributor.authorLuo, Haowen-
dc.contributor.authorXiao, Yuxuan-
dc.contributor.authorWong, David W.H.-
dc.contributor.authorShi, Alex S.-
dc.contributor.authorLin, Ziwei-
dc.contributor.authorHuang, Bo-
dc.contributor.authorLee, Harry F.-
dc.date.accessioned2023-08-09T03:36:34Z-
dc.date.available2023-08-09T03:36:34Z-
dc.date.issued2023-
dc.identifier.citationJournal of Cleaner Production, 2023, v. 406, article no. 137080-
dc.identifier.issn0959-6526-
dc.identifier.urihttp://hdl.handle.net/10722/329937-
dc.description.abstractThis study utilizes high-resolution population grid data from 2004 to 2018 to assess the extent of urban polycentricity in 284 Chinese prefecture-level cities. A new method for measuring urban polycentricity is devised using the Clauset-Newman-Moore grey modularity maximization algorithm. Additionally, the Spatial Durbin Model is applied to investigate the effect of urban polycentricity on the mean and spatial variation of PM2.5 concentrations. Our statistical results show that the increased distance between urban centers and the increased size disparity between the large and small centers effectively reduces air pollution within the city. On the other hand, in cities with a strong clustering of urban centers and significant size disparity between main and sub-centers, the polycentric urban structure cannot help reduce air pollution but merely shift it to other urban centers within the city. Hence, interpreting the severity of urban air pollution solely on the basis of the citywide average of air pollution may be insufficient. It is necessary to consider the possible relocation of air-polluting activities associated with polycentric urban structures. Policymakers should take into account the potential spatial inequality of air pollution driven by urban polycentricity.-
dc.languageeng-
dc.relation.ispartofJournal of Cleaner Production-
dc.subjectAir pollution-
dc.subjectChina-
dc.subjectPM2.5-
dc.subjectUrban polycentricity-
dc.titleCan urban polycentricity improve air quality? Evidence from Chinese cities-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.jclepro.2023.137080-
dc.identifier.scopuseid_2-s2.0-85151791176-
dc.identifier.volume406-
dc.identifier.spagearticle no. 137080-
dc.identifier.epagearticle no. 137080-
dc.identifier.isiWOS:001031709500001-

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