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Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.seps.2022.101228
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dc.titleCOVID-19 lockdowns and air quality: Evidence from grey spatiotemporal forecasts
dc.contributor.authorGao, M
dc.contributor.authorYang, H
dc.contributor.authorXiao, Q
dc.contributor.authorGoh, M
dc.date.accessioned2022-07-14T08:17:16Z
dc.date.available2022-07-14T08:17:16Z
dc.date.issued2022-01-01
dc.identifier.citationGao, M, Yang, H, Xiao, Q, Goh, M (2022-01-01). COVID-19 lockdowns and air quality: Evidence from grey spatiotemporal forecasts. Socio-Economic Planning Sciences : 101228-. ScholarBank@NUS Repository. https://doi.org/10.1016/j.seps.2022.101228
dc.identifier.issn00380121
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/228577
dc.description.abstractThis paper proposes a novel grey spatiotemporal model and quantitatively analyzes the spillover and momentum effects of the COVID-19 lockdown policy on the concentration of PM2.5 (particulate matter of diameter less than 2.5 μm) in Wuhan during the COVID-19 pandemic lockdown from 23 January to 8 April 2020 inclusive, and the post-pandemic period from 9 April 2020 to 17 October 2020 inclusive. The results suggest that the stringent lockdowns lead to a reduction in PM2.5 emissions arising from a momentum effect (9.57–18.67%) and a spillover effect (7.07–27.60%).
dc.publisherElsevier BV
dc.sourceElements
dc.subjectGrey spatiotemporal model
dc.subjectMomentum effect
dc.subjectPM2.5 forecasting
dc.subjectSpillover effect
dc.typeArticle
dc.date.updated2022-07-08T06:31:23Z
dc.contributor.departmentANALYTICS AND OPERATIONS
dc.description.doi10.1016/j.seps.2022.101228
dc.description.sourcetitleSocio-Economic Planning Sciences
dc.description.page101228-
dc.published.statePublished
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