Modeling Atmospheric Air Pollution of an Industrial City with Fine Particulate Matter
Abstract The paper deals with the quantification of fine particulate matter ($ PM_{10} $ ) dispersion in atmospheric air of an industrial city using the AERMOD model by an example of Zhlobin (the Gomel oblast, Belarus). Model input data and procedures for the emission inventory and obtaining spatial...
Ausführliche Beschreibung
Autor*in: |
Kakareka, S. V. [verfasserIn] |
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Format: |
Artikel |
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Sprache: |
Englisch |
Erschienen: |
2021 |
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Schlagwörter: |
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Anmerkung: |
© Pleiades Publishing, Ltd. 2021 |
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Übergeordnetes Werk: |
Enthalten in: Russian meteorology and hydrology - Pleiades Publishing, 1993, 46(2021), 5 vom: Mai, Seite 331-340 |
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Übergeordnetes Werk: |
volume:46 ; year:2021 ; number:5 ; month:05 ; pages:331-340 |
Links: |
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DOI / URN: |
10.3103/S1068373921050083 |
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Katalog-ID: |
OLC2127424336 |
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10.3103/S1068373921050083 doi (DE-627)OLC2127424336 (DE-He213)S1068373921050083-p DE-627 ger DE-627 rakwb eng 550 VZ 14 ssgn Kakareka, S. V. verfasserin aut Modeling Atmospheric Air Pollution of an Industrial City with Fine Particulate Matter 2021 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Pleiades Publishing, Ltd. 2021 Abstract The paper deals with the quantification of fine particulate matter ($ PM_{10} $ ) dispersion in atmospheric air of an industrial city using the AERMOD model by an example of Zhlobin (the Gomel oblast, Belarus). Model input data and procedures for the emission inventory and obtaining spatially distributed estimates are described. Emissions and dispersion of $ PM_{10} $ from the main categories of sources are considered, including industrial facilities, road and off-road mobile sources, domestic sector, and agriculture. It is shown that the main contribution to high $ PM_{10} $ concentrations in atmospheric air is made by industrial enterprises, the domestic sector, and road transport. The spatial pattern of urban air pollution is described. The simulation results are compared with the results of $ PM_{10} $ measurements at the monitoring site, their satisfactory consistency is demonstrated. atmospheric air emission PM dispersion modeling AERMOD Salivonchyk, S. V. aut Enthalten in Russian meteorology and hydrology Pleiades Publishing, 1993 46(2021), 5 vom: Mai, Seite 331-340 (DE-627)181990490 (DE-600)1180563-8 (DE-576)03887959X 1068-3739 nnns volume:46 year:2021 number:5 month:05 pages:331-340 https://doi.org/10.3103/S1068373921050083 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO SSG-OLC-OEU SSG-OPC-GGO AR 46 2021 5 05 331-340 |
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10.3103/S1068373921050083 doi (DE-627)OLC2127424336 (DE-He213)S1068373921050083-p DE-627 ger DE-627 rakwb eng 550 VZ 14 ssgn Kakareka, S. V. verfasserin aut Modeling Atmospheric Air Pollution of an Industrial City with Fine Particulate Matter 2021 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Pleiades Publishing, Ltd. 2021 Abstract The paper deals with the quantification of fine particulate matter ($ PM_{10} $ ) dispersion in atmospheric air of an industrial city using the AERMOD model by an example of Zhlobin (the Gomel oblast, Belarus). Model input data and procedures for the emission inventory and obtaining spatially distributed estimates are described. Emissions and dispersion of $ PM_{10} $ from the main categories of sources are considered, including industrial facilities, road and off-road mobile sources, domestic sector, and agriculture. It is shown that the main contribution to high $ PM_{10} $ concentrations in atmospheric air is made by industrial enterprises, the domestic sector, and road transport. The spatial pattern of urban air pollution is described. The simulation results are compared with the results of $ PM_{10} $ measurements at the monitoring site, their satisfactory consistency is demonstrated. atmospheric air emission PM dispersion modeling AERMOD Salivonchyk, S. V. aut Enthalten in Russian meteorology and hydrology Pleiades Publishing, 1993 46(2021), 5 vom: Mai, Seite 331-340 (DE-627)181990490 (DE-600)1180563-8 (DE-576)03887959X 1068-3739 nnns volume:46 year:2021 number:5 month:05 pages:331-340 https://doi.org/10.3103/S1068373921050083 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO SSG-OLC-OEU SSG-OPC-GGO AR 46 2021 5 05 331-340 |
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10.3103/S1068373921050083 doi (DE-627)OLC2127424336 (DE-He213)S1068373921050083-p DE-627 ger DE-627 rakwb eng 550 VZ 14 ssgn Kakareka, S. V. verfasserin aut Modeling Atmospheric Air Pollution of an Industrial City with Fine Particulate Matter 2021 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Pleiades Publishing, Ltd. 2021 Abstract The paper deals with the quantification of fine particulate matter ($ PM_{10} $ ) dispersion in atmospheric air of an industrial city using the AERMOD model by an example of Zhlobin (the Gomel oblast, Belarus). Model input data and procedures for the emission inventory and obtaining spatially distributed estimates are described. Emissions and dispersion of $ PM_{10} $ from the main categories of sources are considered, including industrial facilities, road and off-road mobile sources, domestic sector, and agriculture. It is shown that the main contribution to high $ PM_{10} $ concentrations in atmospheric air is made by industrial enterprises, the domestic sector, and road transport. The spatial pattern of urban air pollution is described. The simulation results are compared with the results of $ PM_{10} $ measurements at the monitoring site, their satisfactory consistency is demonstrated. atmospheric air emission PM dispersion modeling AERMOD Salivonchyk, S. V. aut Enthalten in Russian meteorology and hydrology Pleiades Publishing, 1993 46(2021), 5 vom: Mai, Seite 331-340 (DE-627)181990490 (DE-600)1180563-8 (DE-576)03887959X 1068-3739 nnns volume:46 year:2021 number:5 month:05 pages:331-340 https://doi.org/10.3103/S1068373921050083 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO SSG-OLC-OEU SSG-OPC-GGO AR 46 2021 5 05 331-340 |
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10.3103/S1068373921050083 doi (DE-627)OLC2127424336 (DE-He213)S1068373921050083-p DE-627 ger DE-627 rakwb eng 550 VZ 14 ssgn Kakareka, S. V. verfasserin aut Modeling Atmospheric Air Pollution of an Industrial City with Fine Particulate Matter 2021 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Pleiades Publishing, Ltd. 2021 Abstract The paper deals with the quantification of fine particulate matter ($ PM_{10} $ ) dispersion in atmospheric air of an industrial city using the AERMOD model by an example of Zhlobin (the Gomel oblast, Belarus). Model input data and procedures for the emission inventory and obtaining spatially distributed estimates are described. Emissions and dispersion of $ PM_{10} $ from the main categories of sources are considered, including industrial facilities, road and off-road mobile sources, domestic sector, and agriculture. It is shown that the main contribution to high $ PM_{10} $ concentrations in atmospheric air is made by industrial enterprises, the domestic sector, and road transport. The spatial pattern of urban air pollution is described. The simulation results are compared with the results of $ PM_{10} $ measurements at the monitoring site, their satisfactory consistency is demonstrated. atmospheric air emission PM dispersion modeling AERMOD Salivonchyk, S. V. aut Enthalten in Russian meteorology and hydrology Pleiades Publishing, 1993 46(2021), 5 vom: Mai, Seite 331-340 (DE-627)181990490 (DE-600)1180563-8 (DE-576)03887959X 1068-3739 nnns volume:46 year:2021 number:5 month:05 pages:331-340 https://doi.org/10.3103/S1068373921050083 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO SSG-OLC-OEU SSG-OPC-GGO AR 46 2021 5 05 331-340 |
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Abstract The paper deals with the quantification of fine particulate matter ($ PM_{10} $ ) dispersion in atmospheric air of an industrial city using the AERMOD model by an example of Zhlobin (the Gomel oblast, Belarus). Model input data and procedures for the emission inventory and obtaining spatially distributed estimates are described. Emissions and dispersion of $ PM_{10} $ from the main categories of sources are considered, including industrial facilities, road and off-road mobile sources, domestic sector, and agriculture. It is shown that the main contribution to high $ PM_{10} $ concentrations in atmospheric air is made by industrial enterprises, the domestic sector, and road transport. The spatial pattern of urban air pollution is described. The simulation results are compared with the results of $ PM_{10} $ measurements at the monitoring site, their satisfactory consistency is demonstrated. © Pleiades Publishing, Ltd. 2021 |
abstractGer |
Abstract The paper deals with the quantification of fine particulate matter ($ PM_{10} $ ) dispersion in atmospheric air of an industrial city using the AERMOD model by an example of Zhlobin (the Gomel oblast, Belarus). Model input data and procedures for the emission inventory and obtaining spatially distributed estimates are described. Emissions and dispersion of $ PM_{10} $ from the main categories of sources are considered, including industrial facilities, road and off-road mobile sources, domestic sector, and agriculture. It is shown that the main contribution to high $ PM_{10} $ concentrations in atmospheric air is made by industrial enterprises, the domestic sector, and road transport. The spatial pattern of urban air pollution is described. The simulation results are compared with the results of $ PM_{10} $ measurements at the monitoring site, their satisfactory consistency is demonstrated. © Pleiades Publishing, Ltd. 2021 |
abstract_unstemmed |
Abstract The paper deals with the quantification of fine particulate matter ($ PM_{10} $ ) dispersion in atmospheric air of an industrial city using the AERMOD model by an example of Zhlobin (the Gomel oblast, Belarus). Model input data and procedures for the emission inventory and obtaining spatially distributed estimates are described. Emissions and dispersion of $ PM_{10} $ from the main categories of sources are considered, including industrial facilities, road and off-road mobile sources, domestic sector, and agriculture. It is shown that the main contribution to high $ PM_{10} $ concentrations in atmospheric air is made by industrial enterprises, the domestic sector, and road transport. The spatial pattern of urban air pollution is described. The simulation results are compared with the results of $ PM_{10} $ measurements at the monitoring site, their satisfactory consistency is demonstrated. © Pleiades Publishing, Ltd. 2021 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">OLC2127424336</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230505130517.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">230505s2021 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.3103/S1068373921050083</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2127424336</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)S1068373921050083-p</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">550</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">14</subfield><subfield code="2">ssgn</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Kakareka, S. V.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Modeling Atmospheric Air Pollution of an Industrial City with Fine Particulate Matter</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2021</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Pleiades Publishing, Ltd. 2021</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract The paper deals with the quantification of fine particulate matter ($ PM_{10} $ ) dispersion in atmospheric air of an industrial city using the AERMOD model by an example of Zhlobin (the Gomel oblast, Belarus). Model input data and procedures for the emission inventory and obtaining spatially distributed estimates are described. Emissions and dispersion of $ PM_{10} $ from the main categories of sources are considered, including industrial facilities, road and off-road mobile sources, domestic sector, and agriculture. It is shown that the main contribution to high $ PM_{10} $ concentrations in atmospheric air is made by industrial enterprises, the domestic sector, and road transport. The spatial pattern of urban air pollution is described. The simulation results are compared with the results of $ PM_{10} $ measurements at the monitoring site, their satisfactory consistency is demonstrated.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">atmospheric air</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">emission</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">PM</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">dispersion modeling</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">AERMOD</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Salivonchyk, S. V.</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Russian meteorology and hydrology</subfield><subfield code="d">Pleiades Publishing, 1993</subfield><subfield code="g">46(2021), 5 vom: Mai, Seite 331-340</subfield><subfield code="w">(DE-627)181990490</subfield><subfield code="w">(DE-600)1180563-8</subfield><subfield code="w">(DE-576)03887959X</subfield><subfield code="x">1068-3739</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:46</subfield><subfield code="g">year:2021</subfield><subfield code="g">number:5</subfield><subfield code="g">month:05</subfield><subfield code="g">pages:331-340</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">https://doi.org/10.3103/S1068373921050083</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-GEO</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-OEU</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OPC-GGO</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">46</subfield><subfield code="j">2021</subfield><subfield code="e">5</subfield><subfield code="c">05</subfield><subfield code="h">331-340</subfield></datafield></record></collection>
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