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

IF 2.7 Q1 GEOGRAPHY Annals of GIS Pub Date : 2021-12-05 DOI:10.1080/19475683.2022.2121855
Yangyang Li, Yi Zhu, Jia Yu Karen Tan, H. Teo, Andrea Law, Dezhan Qu, W. Luo
{"title":"The impact of COVID-19 on NO2 and PM2.5 levels and their associations with human mobility patterns in Singapore","authors":"Yangyang Li, Yi Zhu, Jia Yu Karen Tan, H. Teo, Andrea Law, Dezhan Qu, W. Luo","doi":"10.1080/19475683.2022.2121855","DOIUrl":null,"url":null,"abstract":"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. Graphical Abstract","PeriodicalId":46270,"journal":{"name":"Annals of GIS","volume":"25 1","pages":"515 - 531"},"PeriodicalIF":2.7000,"publicationDate":"2021-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of GIS","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/19475683.2022.2121855","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOGRAPHY","Score":null,"Total":0}
引用次数: 3

Abstract

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. Graphical Abstract
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
2019冠状病毒病对新加坡二氧化氮和PM2.5水平的影响及其与人类流动模式的关系
在2019冠状病毒病疫情期间,全球范围内NO2和PM2.5污染物水平均出现下降,尤其是在封城期间。以前的研究解释说,这种观测到的下降与人类流动性的减少有关,忽略了可能同时调节空气污染水平的气象变化。这一缺陷可能导致高估或低估COVID-19对空气污染的影响。因此,本研究旨在利用机器学习方法,结合气象参数对2020年NO2和PM2.5基线预测的影响,重新评估COVID-19对新加坡NO2和PM2.5污染物水平的影响。结果表明:在不考虑气象参数影响的情况下,NO2和PM2.5的平均降幅分别为12%和19%,均小于观测值(54%和29%)。作为人类流动性变化的两个指标,出租车可用性和停车场可用性在2020年比2019年分别最多增加12.6%和减少9.8%。在空间分辨率为0.01°的空间尺度上,对PM2.5日变化与流动性变化的相关性分析和NO2周变化与流动性变化的相关性分析探讨了人类流动性对大气污染物水平的影响。研究发现,二氧化氮的变化与人类流动性的变化更相关,在新加坡的南部和东部海岸发现了一系列更强的相关性。相反,PM2.5与流动性的相关性较弱,这可能是由于粗糙的空间分辨率的限制。图形抽象
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Annals of GIS
Annals of GIS Multiple-
CiteScore
8.30
自引率
2.00%
发文量
31
期刊最新文献
Zero watermarking algorithm for BIM data based on distance partitioning and local feature Controlling for spatial confounding and spatial interference in causal inference: modelling insights from a computational experiment Application of GIS and fuzzy sets to small-scale site suitability assessment for extensive brackish water aquaculture Revealing intra-urban hierarchical spatial structure through representation learning by combining road network abstraction model and taxi trajectory data The time- and distance-decay effects of hurricane relevancy on social media: an empirical study of three hurricanes in the United States
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1