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The impact of COVID-19 on NO2 and PM2.5 levels and their associations with human mobility patterns in Singapore

Authors :
Yangyang Li
Yihan Zhu
Jia Yu Karen Tan
Hoong Chen Teo
Andrea Law
Dezhan Qu
Wei Luo
Source :
Annals of GIS, Pp 1-17 (2022)
Publication Year :
2022
Publisher :
Taylor & Francis Group, 2022.

Abstract

The decline in NO2 and PM2.5 pollutant levels were observed during COVID-19 around the world, especially during lockdowns. Previous studies explained such observed decline with the decrease in human mobility, overlooking the meteorological changes that could simultaneously mediate air pollution levels. This pitfall could potentially lead to over- or under-estimation of the effect of COVID-19 on air pollution. This study, thus, aims to re-evaluate the impact of COVID-19 on NO2 and PM2.5 pollutant levels in Singapore, by incorporating the effect of meteorological parameters in predicting NO2 and PM2.5 baseline in 2020 using machine learning methods. The results show that the mean NO2 and PM2.5 declined by 12% and 19%, which were less than the observed drops (i.e. 54% and 29%, respectively) without considering the effect of meteorological parameters. As two proxies for change in human mobility, taxi availability and carpark availability were found to increase and decrease by a maximum of 12.6% and 9.8%, respectively, in 2020 from 2019. Two correlation analyses were conducted to investigate how human mobility influenced air pollutant levels: one between daily PM2.5 and mobility changes at a regional scale and the other between weekly NO2 and mobility changes at a spatial resolution of 0.01°. The NO2 variation was found to be more associated with the change in human mobility and a cluster of stronger correlations was found in the South and East Coast of Singapore. Contrarily, PM2.5 and mobility had a weak correlation, which could be due to the limit of a coarse spatial resolution.

Details

Language :
English
ISSN :
19475683 and 19475691
Database :
Directory of Open Access Journals
Journal :
Annals of GIS
Publication Type :
Academic Journal
Accession number :
edsdoj.13af3b8e789042e18a3ab51f535e72a9
Document Type :
article
Full Text :
https://doi.org/10.1080/19475683.2022.2121855