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

Mingyun Gao; Honglin Yang; Qinzi Xiao; Mark Goh

doi:10.1016/j.seps.2022.101228

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

Socioecon Plann Sci. 2022 Oct:83:101228. doi: 10.1016/j.seps.2022.101228. Epub 2022 Jan 11.

Authors

Mingyun Gao^{1

2}, Honglin Yang¹, Qinzi Xiao^{1

3}, Mark Goh²

Affiliations

¹ School of Business Administration, Hunan University, Changsha, Hunan, 410082, PR China.
² NUS Business School and The Logistics Institute-Asia Pacific, National University of Singapore, S(117592), Singapore.
³ Asper School of Business, University of Manitoba, Winnipeg, MB, R3T 2N2, Canada.

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%).

Keywords: Grey spatiotemporal model; Momentum effect; PM2.5 forecasting; Spillover effect.