气候变化领域集成服务门户(CCPortal): Comparing different approaches for assessing the impact of COVID-19 lockdown on urban air quality in Reading, UK

CCPortal

DOI	10.1016/j.atmosres.2021.105730
	Comparing different approaches for assessing the impact of COVID-19 lockdown on urban air quality in Reading, UK
	Munir S.; Luo Z.; Dixon T.
发表日期	2021
ISSN	0169-8095
卷号	261
英文摘要	Many studies investigated the impact of COVID-19 lockdown on urban air quality, but their adopted approaches have varied and there is no consensus as to which approach should be used. In this paper we compare three of the main approaches and assess their performance using both estimated and measured data from several air quality monitoring stations (AQMS) in Reading, Berkshire UK. The approaches are: (1) Sequential approach – comparing pre-lockdown and lockdown periods 2020; (2) Parallel approach – comparing 2019 and 2020 for the equivalent time of the lockdown period; and (3) Machine learning modelling approach – predicting pollution levels for the lockdown period using business as usual (BAU) scenario and comparing with the observations. The parallel and machine learning approaches resulted in relative higher reductions and both showed strong correlation (0.97) and less error with each other. The sequential approach showed less reduction in NO and NOx, showed positive gain in PM10 and NO2 at most of the sites and demonstrated weak correlation with the other two approaches, and is not recommended for such analysis. Overall, the sequential approach showed −14, +4, −32, and + 56% change, the parallel approach showed −46, −43, −43 and + 7% change, and the machine learning approach showed −47, −44, −38 and + 5% change in NOx, NO2, NO and PM10 concentrations, respectively. The pollution roses demonstrated that the UK received easterly polluted winds from the central and eastern Europe, promoting secondary particulates and O3 formation during the lockdown. Changes in pollutant concentrations vary both in space and time according to the approach used, environment type of the monitoring site and the data type (e.g., deweathered vs. raw data). Therefore, the reported results (here or elsewhere) should be viewed in light of these factors before making any conclusion. © 2021
英文关键词	Air quality; COVID-19; Deweathering; Generalised additive model; Intervention; Lockdown
来源期刊	Atmospheric Research
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/236664
作者单位	Department of Construction Management & Engineering, School of the Built Environment, University of Reading, Reading, RG6 6AW, United Kingdom
推荐引用方式 GB/T 7714	Munir S.,Luo Z.,Dixon T.. Comparing different approaches for assessing the impact of COVID-19 lockdown on urban air quality in Reading, UK[J],2021,261.
APA	Munir S.,Luo Z.,&Dixon T..(2021).Comparing different approaches for assessing the impact of COVID-19 lockdown on urban air quality in Reading, UK.Atmospheric Research,261.
MLA	Munir S.,et al."Comparing different approaches for assessing the impact of COVID-19 lockdown on urban air quality in Reading, UK".Atmospheric Research 261(2021).