Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/115507
DC FieldValueLanguage
dc.contributorDepartment of Land Surveying and Geo-Informaticsen_US
dc.contributorResearch Institute for Sustainable Urban Developmenten_US
dc.contributorResearch Institute for Land and Spaceen_US
dc.creatorYu, Xen_US
dc.creatorWong, MSen_US
dc.creatorQin, Ken_US
dc.creatorZhu, Ren_US
dc.creatorYou, Len_US
dc.creatorWei, Jen_US
dc.date.accessioned2025-10-02T06:14:27Z-
dc.date.available2025-10-02T06:14:27Z-
dc.identifier.issn0301-4797en_US
dc.identifier.urihttp://hdl.handle.net/10397/115507-
dc.language.isoenen_US
dc.publisherAcademic Pressen_US
dc.subjectAir pollutionen_US
dc.subjectElectric vehicleen_US
dc.subjectEV charging demanden_US
dc.subjectRandom forest modelen_US
dc.subjectScenario analysisen_US
dc.titleElectric vehicle attributed future air pollution alleviation : A case study in Guangdong province, Chinaen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume391en_US
dc.identifier.doi10.1016/j.jenvman.2025.126442en_US
dcterms.abstractElectric vehicles (EVs) are advocated to combat the effects of tailpipe emissions. This study synergizes EV charging consumption and charging stations from six cities in Guangdong (GD) province, China, to reveal the potential impacts of EVs on four relevant air pollutants (PM2.5, NO2, SO2, CO) based on a data-driven attention-based Random Forest model and scenario analysis. Measurements from traffic-affected air pollution monitoring stations show that NO2 concentrations have a higher mean decrease trend (−2.39 year−1) in the PRD region after EV adoption, followed by PM2.5 (−0.29 year−1). In contrast, the environmental benefits of EVs for SO2 and CO are relatively lower, with decreasing trends of −0.12 year−1 and -0.013 year−1, respectively. Pronounced alleviations of these four air pollutants were presented for most districts in other cities under the assumption of conducting comparative EV policy, with mean reductions of −1.86 μg/m3, -1.08 μg/m3, -0.17 μg/m3 and -0.01 mg/m3 (by 7.8 %, 4.9 %, 1.9 % and 1.4 % with the reference of average values in 2023) for PM2.5, NO2, SO2 and CO, respectively. Moreover, the concentrations tend to decline as the increase in EV charging consumption and the number of EV charging stations. Results show that a 30 % increase in both EV charging consumption and stations results in a further decline in PM2.5 (−0.46 μg/m3), NO2 (−0.37 μg/m3), SO2 (−0.048 μg/m3), and CO (−0.0043 mg/m3) in Guang Dong (GD) province. To the best of our knowledge, it is the first time to assess environmental benefits of EVs with the involvement of actual EV charging demand and charging stations.en_US
dcterms.accessRightsembargoed accessen_US
dcterms.bibliographicCitationJournal of environmental management, Sept. 2025, v. 391, 126442en_US
dcterms.isPartOfJournal of environmental managementen_US
dcterms.issued2025-09-
dc.identifier.scopus2-s2.0-105009459458-
dc.identifier.eissn1095-8630en_US
dc.identifier.artn126442en_US
dc.description.validate202510 bcwcen_US
dc.description.oaNot applicableen_US
dc.identifier.SubFormIDG000176/2025-07-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThis project is substantially funded by the General Research Fund (Grant No. 15603923 and 15609421), and the Collaborative Research Fund (Grant No. C5062\u201321GF) and Young Collaborative Research Fund (Grant No. C6003\u201322Y) from the Research Grants Council , Hong Kong, China. The authors acknowledge the funding support (Grant No. BBG2 and CD81) from the Research Institute for Sustainable Urban Development, Research Institute of Land and Space, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China. We also thank the China Environmental Monitoring Center, the research teams of LandScan, OpenStreetMap, ERA-5, MODIS, Shuttle Radar Topography Mission, the Resource and Environmental Science Data Platform and Global Power Plant Database for providing high-quality data to make this study possible.en_US
dc.description.pubStatusPublisheden_US
dc.date.embargo2027-09-30en_US
dc.description.oaCategoryGreen (AAM)en_US
Appears in Collections:Journal/Magazine Article
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Embargo End Date 2027-09-30
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