COVID-19 lockdowns and air quality: Evidence from grey spatiotemporal forecasts

Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.seps.2022.101228

Title:	COVID-19 lockdowns and air quality: Evidence from grey spatiotemporal forecasts
Authors:	Gao, M Yang, H Xiao, Q Goh, M
Keywords:	Grey spatiotemporal model Momentum effect PM2.5 forecasting Spillover effect
Issue Date:	1-Jan-2022
Publisher:	Elsevier BV
Citation:	Gao, 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
Abstract:	This 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%).
Source Title:	Socio-Economic Planning Sciences
URI:	https://scholarbank.nus.edu.sg/handle/10635/228577
ISSN:	00380121
DOI:	10.1016/j.seps.2022.101228
Appears in Collections:	Elements Staff Publications

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