Modeling Surface Air Pollution with Reduced Emissions during the COVID-19 Pandemic Using CHIMERE and COSMO-ART Chemical Transport Models
Russian Meteorology and Hydrology
; 47(3):174-182, 2022.
Article
in English
| ProQuest Central | ID: covidwho-1910961
ABSTRACT
The results of numerical modeling of air pollution using CHIMERE and COSMO-ART chemical transport models are presented. The modeling was performed according to the scenarios of the 50–60% reduction of emissions from anthropogenic sources in the Moscow region during the period of March–July 2020. Scenario calculations of pollutant concentrations were compared with baseline simulations using regionally adapted inventory of anthropogenic pollutant emissions to the atmosphere. The most significant decrease in the concentrations of NO2 and CO was reproduced by the models when emissions from two sectoral sources (vehicles and nonindustrial plants) were reduced. The PM10 drop was mostly influenced by the reduction of emissions from industrial combustion. With the total reduction of emissions from anthropogenic sources as compared to the baseline calculations, the pollutant concentration decreased by 44–54% for NO2, by 38–44% for CO, and by 26–39% for PM10. This generally coincides with the quantitative estimates of the pollution level drop obtained by other authors. The greatest effect of reducing pollutant emissions into the atmosphere was found during the episodes of adverse weather conditions for air purification, when the simulated and observed pollution level increases by 3–5 times as compared to the conditions of intense pollutant dispersion.
Earth Sciences--Hydrology; anthropogenic emissions; air pollution; pandemic; chemical transport model; Pandemics; Pollutants; Reduction; Nitrogen dioxide; Atmospheric pollution; Pollution dispersion; Anthropogenic factors; Emissions; Transportation models; Atmosphere; Weather conditions; Air purification; Modelling; COVID-19; Human influences; Pollution control; Pollution levels; Transport; Industrial pollution; Emissions control; Emission inventories; Atmospheric models; Particulate matter; Water purification; Chemical transport; Weather; Carbon monoxide
Full text:
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Collection:
Databases of international organizations
Database:
ProQuest Central
Language:
English
Journal:
Russian Meteorology and Hydrology
Year:
2022
Document Type:
Article
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