Modeling Surface Air Pollution with Reduced Emissions during the COVID-19 Pandemic Using CHIMERE and COSMO-ART Chemical Transport Models.
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| Title: | Modeling Surface Air Pollution with Reduced Emissions during the COVID-19 Pandemic Using CHIMERE and COSMO-ART Chemical Transport Models. |
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| Authors: | Kuznetsova, I. N.1 (AUTHOR) labmuza@mail.ru, Rivin, G. S.1,2 (AUTHOR), Borisov, D. V.1,3 (AUTHOR), Shalygina, I. Yu.1 (AUTHOR), Kirsanov, A. A.1 (AUTHOR), Nakhaev, M. I.1,3 (AUTHOR) |
| Source: | Russian Meteorology & Hydrology. Mar2022, Vol. 47 Issue 3, p174-182. 9p. |
| Subject Terms: | *Emissions (Air pollution), *Chemical models, *Air pollutants, *COVID-19 pandemic, *Air purification, *Air pollution, *Atmosphere, *Atmospheric methane |
| Geographic Terms: | Moscow (Russia) |
| 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. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: enr DbLabel: Energy & Power Source An: 157713280 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Modeling Surface Air Pollution with Reduced Emissions during the COVID-19 Pandemic Using CHIMERE and COSMO-ART Chemical Transport Models. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Kuznetsova%2C+I%2E+N%2E%22">Kuznetsova, I. N.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> labmuza@mail.ru</i><br /><searchLink fieldCode="AR" term="%22Rivin%2C+G%2E+S%2E%22">Rivin, G. S.</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Borisov%2C+D%2E+V%2E%22">Borisov, D. V.</searchLink><relatesTo>1,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Shalygina%2C+I%2E+Yu%2E%22">Shalygina, I. Yu.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kirsanov%2C+A%2E+A%2E%22">Kirsanov, A. A.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Nakhaev%2C+M%2E+I%2E%22">Nakhaev, M. I.</searchLink><relatesTo>1,3</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Russian+Meteorology+%26+Hydrology%22">Russian Meteorology & Hydrology</searchLink>. Mar2022, Vol. 47 Issue 3, p174-182. 9p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Emissions+%28Air+pollution%29%22">Emissions (Air pollution)</searchLink><br />*<searchLink fieldCode="DE" term="%22Chemical+models%22">Chemical models</searchLink><br />*<searchLink fieldCode="DE" term="%22Air+pollutants%22">Air pollutants</searchLink><br />*<searchLink fieldCode="DE" term="%22COVID-19+pandemic%22">COVID-19 pandemic</searchLink><br />*<searchLink fieldCode="DE" term="%22Air+purification%22">Air purification</searchLink><br />*<searchLink fieldCode="DE" term="%22Air+pollution%22">Air pollution</searchLink><br />*<searchLink fieldCode="DE" term="%22Atmosphere%22">Atmosphere</searchLink><br />*<searchLink fieldCode="DE" term="%22Atmospheric+methane%22">Atmospheric methane</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Moscow+%28Russia%29%22">Moscow (Russia)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: 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. [ABSTRACT FROM AUTHOR] |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3103/S1068373922030025 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 9 StartPage: 174 Subjects: – SubjectFull: Emissions (Air pollution) Type: general – SubjectFull: Chemical models Type: general – SubjectFull: Air pollutants Type: general – SubjectFull: COVID-19 pandemic Type: general – SubjectFull: Air purification Type: general – SubjectFull: Air pollution Type: general – SubjectFull: Atmosphere Type: general – SubjectFull: Atmospheric methane Type: general – SubjectFull: Moscow (Russia) Type: general Titles: – TitleFull: Modeling Surface Air Pollution with Reduced Emissions during the COVID-19 Pandemic Using CHIMERE and COSMO-ART Chemical Transport Models. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Kuznetsova, I. N. – PersonEntity: Name: NameFull: Rivin, G. S. – PersonEntity: Name: NameFull: Borisov, D. V. – PersonEntity: Name: NameFull: Shalygina, I. Yu. – PersonEntity: Name: NameFull: Kirsanov, A. A. – PersonEntity: Name: NameFull: Nakhaev, M. I. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: Mar2022 Type: published Y: 2022 Identifiers: – Type: issn-print Value: 10683739 Numbering: – Type: volume Value: 47 – Type: issue Value: 3 Titles: – TitleFull: Russian Meteorology & Hydrology Type: main |
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