About: Response of major air pollutants to COVID-19 lockdowns in China

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Response of major air pollutants to COVID-19 lockdowns in China
Creator	Su, Hang Gong, Wei Ma, Xin Han, Ge Pei, Zhipeng
Source	Elsevier; Medline; PMC
abstract	Abstract COVID-19 suddenly struck Wuhan at the end of 2019 and soon spread to the whole country and the rest of world in 2020. To mitigate the pandemic, China authority has taken unprecedentedly strict measures across the country. That provides a precious window to study how the air quality response to quick decline of anthropogenic emissions in terms of national scale, which would be critical basis to make atmospheric governance policies in the future. In this work, we utilized observations from both remote sensing and in-situ measurements to investigate impacts of COVID-19 lockdown on different air pollutions in different regions of China. It is witnessed that the PM2.5 concentrations exhibited distinct trends in different regions, despite of plunges of NO2 concentrations over the whole country. The steady HCHO concentration in urban area provides sufficient fuels for generations of tropospheric O3, leading to high concentrations of O3, especially when there is not enough NO to consume O3 via the titration effect. Moreover, the SO2 concentration kept steady at a low level regardless of cities. As a conclusion, the COVID-19 lockdown indeed helped reduce NO2 concentration. However, the atmospheric quality in urban areas of China has not improved overall due to lockdown measures. It underscores the significance of comprehensive control of atmospheric pollutants in cleaning air. Reducing VOCs (volatile organic compounds) concentrations in urban areas would be a critical mission for better air quality in the future.
has issue date	2020-07-11(xsd:dateTime)
bibo:doi	10.1016/j.scitotenv.2020.140879
bibo:pmid	32758857
has license	els-covid
sha1sum (hex)	c5a7f0db2f9edb762f26b8050ca0807da8780eac
schema:url	https://doi.org/10.1016/j.scitotenv.2020.140879
resource representing a document's title	Response of major air pollutants to COVID-19 lockdowns in China
has PubMed Central identifier	PMC7351666
has PubMed identifier	32758857
schema:publication	Sci Total Environ
resource representing a document's body	covid:c5a7f0db2f9edb762f26b8050ca0807da8780eac#body_text
is schema:about of	named entity 'lockdown' named entity 'impacts' named entity 'China' named entity 'critical' named entity 'policies' named entity 'STUDY' named entity 'TERMS' named entity 'MITIGATE' named entity 'MEASURES' named entity 'WITNESSED' named entity 'CONCENTRATION' named entity 'TAKEN' named entity 'VOCS' named entity 'LEADING' named entity 'SUDDEN' named entity '2019' named entity 'QUICK' named entity 'lockdown' named entity 'quick' named entity 'PM2.5' named entity 'regions' named entity 'cities' named entity 'SO2' named entity 'sudden' named entity 'titration' named entity 'China' named entity 'PM2.5' named entity 'remote sensing' named entity 'COVID-19' named entity 'China' named entity 'China' named entity 'medical care' named entity 'North China Plain' named entity 'atmospheric environment' named entity 'China' named entity 'PM 2.5' named entity 'China' named entity 'Guangzhou' named entity 'Wuhan' named entity 'Guangzhou' named entity 'climatic' named entity 'COVID-19' named entity 'titration' named entity 'China' named entity 'TROPOMI' named entity 'remote sensing' named entity 'rural areas' named entity 'Wuhan' named entity 'pollutant' named entity 'Wuhan' named entity 'PM 2.5' named entity 'remotely sensed' named entity 'VOCs' named entity 'China' named entity 'China' named entity 'HCHO' named entity 'China' named entity 'COVID-19' named entity 'Guangzhou' named entity 'weather conditions' named entity 'China' named entity 'PM 2.5' named entity 'Beijing' named entity 'heavy industry' named entity 'social media' named entity 'Guangzhou' named entity 'remote sensing' named entity 'PM 2.5' named entity 'time series' named entity 'China' named entity 'Data Hub' named entity 'PM2.5' named entity 'Meteorological data' named entity 'Wuhan' named entity 'Wuhan' named entity 'atmospheric pollutants' named entity 'atmospheric pollutants'

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