气候变化领域集成服务门户(CCPortal): An investigation of the impacts of a successful COVID-19 response and meteorology on air quality in New Zealand

CCPortal

DOI	10.1016/j.atmosenv.2021.118322
	An investigation of the impacts of a successful COVID-19 response and meteorology on air quality in New Zealand
	Talbot N.; Takada A.; Bingham A.H.; Elder D.; Lay Yee S.; Golubiewski N.E.
发表日期	2021
ISSN	1352-2310
卷号	254
英文摘要	The COVID-19 pandemic brought about national restrictions on people's movements, in effect commencing a socially engineered transport emission reduction experiment. In New Zealand during the most restrictive alert level (Level 4), roadside concentrations of nitrogen dioxide (NO2) were reduced 48–54% compared to Business-as-usual (BAU) values. NO2 concentrations rapidly returned to near mean levels as the alert levels decreased and restrictions eased. PM10 and PM2.5 responded differently to NO2 during the different alert levels. This is due to particulates having multiple sources, many of natural origin and therefore less influenced by human activity. PM10 and PM2.5 concentrations were reduced during alert level 4 but to a lesser extent than NO2 and with more variability across regions. Particulate concentrations increased notably during alert level 2 when many airsheds reported concentrations above the BAU means. To provide robust BAU reference concentrations, simple 5-year means were calculated along with predictions from machine learning modelling that, in effect, removed the influence of meteorology on observed concentrations. The results of this study show that latter method was found to be more closely aligned to observed values for NO2 as well as PM2.5 and PM10 away from coastal regions. © 2021 Elsevier Ltd
关键词	Atmospheric pollutants COVID-19 Machine learning On-road vehicles
语种	英语
scopus关键词	Air quality; Emission control; Meteorology; Nitrogen oxides; Particles (particulate matter); Atmospheric pollutants; Business-as-usual; COVID-19; Level 4; Machine-learning; New zealand; NO $-2$; On-road vehicle; PM$-10$; PM$-2.5$; Machine learning; nitrogen dioxide; air quality; concentration (composition); COVID-19; emission control; health impact; human activity; meteorology; particulate matter; pollutant source; pollutant transport; roadside environment; air pollutant; air quality; air transportation; airflow; atmosphere; circadian rhythm; concentration (parameter); controlled study; coronavirus disease 2019; exhaust gas; human; humidity; machine learning; meteorology; neighborhood; New Zealand; particulate matter 10; particulate matter 2.5; prediction; priority journal; random forest; sea surface temperature; traffic pollution; wind speed; New Zealand
来源期刊	ATMOSPHERIC ENVIRONMENT
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/248442
作者单位	Ministry for the Environment, Auckland, New Zealand; Ministry for the Environment, Wellington, New Zealand; University of Auckland, School of Environment, Auckland, New Zealand
推荐引用方式 GB/T 7714	Talbot N.,Takada A.,Bingham A.H.,et al. An investigation of the impacts of a successful COVID-19 response and meteorology on air quality in New Zealand[J],2021,254.
APA	Talbot N.,Takada A.,Bingham A.H.,Elder D.,Lay Yee S.,&Golubiewski N.E..(2021).An investigation of the impacts of a successful COVID-19 response and meteorology on air quality in New Zealand.ATMOSPHERIC ENVIRONMENT,254.
MLA	Talbot N.,et al."An investigation of the impacts of a successful COVID-19 response and meteorology on air quality in New Zealand".ATMOSPHERIC ENVIRONMENT 254(2021).