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Article: Investigating the influence of urban land use and landscape pattern on PM2.5 spatial variation using mobile monitoring and WUDAPT

TitleInvestigating the influence of urban land use and landscape pattern on PM2.5 spatial variation using mobile monitoring and WUDAPT
Authors
KeywordsAir pollution
Land use
Landscape pattern
Mobile monitoring
WUDAPT
Issue Date2019
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/landurbplan
Citation
Landscape and Urban Planning, 2019, v. 189, p. 15-26 How to Cite?
AbstractParticulate matter that <2.5 µm in aerodynamic diameter (PM2.5) has been recognized as one of the principal pollutants that degrades air quality and increases health burdens. In this study, we employ the MLR and GWR modelling method to obtain estimation models for PM2.5 with a set of land use/landscape metrics as predictor variables. The study focused on investigating the influence of urban land use and landscape pattern on PM2.5 spatial variation, specifically, on identification of influential landscape classes/types that regulate PM2.5 concentration levels. The spatial PM2.5 concentration in the compact urban scenario of Hong Kong was sampled by conducting a series of mobile monitoring campaigns. The Local Climate Zone (LCZ) Scheme and World Urban Database and Portal Tools (WUDAPT) level 0 database were adopted as the basis of the calculation of land use/landscape metrics. These metrics were then adopted as the predictors to explain the spatial variations in PM2.5. 62% of the variance in PM2.5 can be explained by the resultant GWR model using only five land use/landscape classes, and without using any traffic-related variables or data from emission inventory. The findings can inform the urban planning strategies for mitigating air pollution and also indicate the usefulness of LCZ and WUDAPT in estimating the spatial variation of urban air quality.
Persistent Identifierhttp://hdl.handle.net/10722/274787
ISSN
2017 Impact Factor: 4.994
2015 SCImago Journal Rankings: 1.699
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorShi, Y-
dc.contributor.authorRen, C-
dc.contributor.authorLau, K-
dc.contributor.authorNg, E-
dc.date.accessioned2019-09-10T02:28:41Z-
dc.date.available2019-09-10T02:28:41Z-
dc.date.issued2019-
dc.identifier.citationLandscape and Urban Planning, 2019, v. 189, p. 15-26-
dc.identifier.issn0169-2046-
dc.identifier.urihttp://hdl.handle.net/10722/274787-
dc.description.abstractParticulate matter that <2.5 µm in aerodynamic diameter (PM2.5) has been recognized as one of the principal pollutants that degrades air quality and increases health burdens. In this study, we employ the MLR and GWR modelling method to obtain estimation models for PM2.5 with a set of land use/landscape metrics as predictor variables. The study focused on investigating the influence of urban land use and landscape pattern on PM2.5 spatial variation, specifically, on identification of influential landscape classes/types that regulate PM2.5 concentration levels. The spatial PM2.5 concentration in the compact urban scenario of Hong Kong was sampled by conducting a series of mobile monitoring campaigns. The Local Climate Zone (LCZ) Scheme and World Urban Database and Portal Tools (WUDAPT) level 0 database were adopted as the basis of the calculation of land use/landscape metrics. These metrics were then adopted as the predictors to explain the spatial variations in PM2.5. 62% of the variance in PM2.5 can be explained by the resultant GWR model using only five land use/landscape classes, and without using any traffic-related variables or data from emission inventory. The findings can inform the urban planning strategies for mitigating air pollution and also indicate the usefulness of LCZ and WUDAPT in estimating the spatial variation of urban air quality.-
dc.languageeng-
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/landurbplan-
dc.relation.ispartofLandscape and Urban Planning-
dc.subjectAir pollution-
dc.subjectLand use-
dc.subjectLandscape pattern-
dc.subjectMobile monitoring-
dc.subjectWUDAPT-
dc.titleInvestigating the influence of urban land use and landscape pattern on PM2.5 spatial variation using mobile monitoring and WUDAPT-
dc.typeArticle-
dc.identifier.emailRen, C: renchao@hku.hk-
dc.identifier.authorityRen, C=rp02447-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.landurbplan.2019.04.004-
dc.identifier.scopuseid_2-s2.0-85064381577-
dc.identifier.hkuros302574-
dc.identifier.volume189-
dc.identifier.spage15-
dc.identifier.epage26-
dc.identifier.isiWOS:000474330500003-
dc.publisher.placeNetherlands-

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