Modeling the dispersion of traffic-derived black carbon emissions into hilly terrain
Abstract This study examines hilly terrain’s effect on black carbon (BC) dispersion. The apportionment of distinct sources obtained by a two-component mixing model (Aethalometer: AE-33) using improved radiative transfer equations showed the dominance of traffic-derived black carbon ($ BC_{FF} $) emi...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Singh, Sameer [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2023 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| Übergeordnetes Werk: |
Enthalten in: Environmental monitoring and assessment - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981, 195(2023), 8 vom: 15. Juli |
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| Übergeordnetes Werk: |
volume:195 ; year:2023 ; number:8 ; day:15 ; month:07 |
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| DOI / URN: |
10.1007/s10661-023-11554-6 |
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| Katalog-ID: |
SPR05226503X |
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| 520 | |a Abstract This study examines hilly terrain’s effect on black carbon (BC) dispersion. The apportionment of distinct sources obtained by a two-component mixing model (Aethalometer: AE-33) using improved radiative transfer equations showed the dominance of traffic-derived black carbon ($ BC_{FF} $) emissions in the study region. The AERMOD was used to model BC emissions from moving traffic as a line source and parking lot as area source using observational and WRF-processed meteorology for the winter (January to March 2020). The model results showed that the BC levels substantially vary with local meteorological conditions, traffic volume, and composition. The hilly terrain obstructs the winds and develops a negative pressure loading to a vacuum on the other side of the hills, which promotes the accumulation of emissions, causing high BC concentrations. The pockets of higher concentration were seen at the locations where steep slopes were associated with low winds (<1 m $ s^{−1} $) and hill fogs. The AERMOD model, after statistical evaluation against the observational datasets, has been applied to study the reduction in $ BC_{FF} $ concentrations due to the implementation of Indian emission norms as mitigation measures, i.e., BS-IV (equivalent to Euro 4) and BS-VI (equivalent to Euro 6). It was found that the $ BC_{FF} $ concentrations for BS-IV and BS-VI reduced by 35% and 75%, respectively. The model was also used to study the contribution of the different vehicular categories to BC concentration. | ||
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| 650 | 4 | |a Black carbon |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Dispersion |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Hilly terrain |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Vehicular emission |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Gokhale, Sharad |4 aut | |
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10.1007/s10661-023-11554-6 doi (DE-627)SPR05226503X (SPR)s10661-023-11554-6-e DE-627 ger DE-627 rakwb eng Singh, Sameer verfasserin (orcid)0000-0002-6287-5430 aut Modeling the dispersion of traffic-derived black carbon emissions into hilly terrain 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract This study examines hilly terrain’s effect on black carbon (BC) dispersion. The apportionment of distinct sources obtained by a two-component mixing model (Aethalometer: AE-33) using improved radiative transfer equations showed the dominance of traffic-derived black carbon ($ BC_{FF} $) emissions in the study region. The AERMOD was used to model BC emissions from moving traffic as a line source and parking lot as area source using observational and WRF-processed meteorology for the winter (January to March 2020). The model results showed that the BC levels substantially vary with local meteorological conditions, traffic volume, and composition. The hilly terrain obstructs the winds and develops a negative pressure loading to a vacuum on the other side of the hills, which promotes the accumulation of emissions, causing high BC concentrations. The pockets of higher concentration were seen at the locations where steep slopes were associated with low winds (<1 m $ s^{−1} $) and hill fogs. The AERMOD model, after statistical evaluation against the observational datasets, has been applied to study the reduction in $ BC_{FF} $ concentrations due to the implementation of Indian emission norms as mitigation measures, i.e., BS-IV (equivalent to Euro 4) and BS-VI (equivalent to Euro 6). It was found that the $ BC_{FF} $ concentrations for BS-IV and BS-VI reduced by 35% and 75%, respectively. The model was also used to study the contribution of the different vehicular categories to BC concentration. AERMOD (dpeaa)DE-He213 Aethalometer (dpeaa)DE-He213 Black carbon (dpeaa)DE-He213 Dispersion (dpeaa)DE-He213 Hilly terrain (dpeaa)DE-He213 Vehicular emission (dpeaa)DE-He213 Gokhale, Sharad aut Enthalten in Environmental monitoring and assessment Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981 195(2023), 8 vom: 15. Juli (DE-627)31281738X (DE-600)2012242-1 1573-2959 nnns volume:195 year:2023 number:8 day:15 month:07 https://dx.doi.org/10.1007/s10661-023-11554-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 195 2023 8 15 07 |
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10.1007/s10661-023-11554-6 doi (DE-627)SPR05226503X (SPR)s10661-023-11554-6-e DE-627 ger DE-627 rakwb eng Singh, Sameer verfasserin (orcid)0000-0002-6287-5430 aut Modeling the dispersion of traffic-derived black carbon emissions into hilly terrain 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract This study examines hilly terrain’s effect on black carbon (BC) dispersion. The apportionment of distinct sources obtained by a two-component mixing model (Aethalometer: AE-33) using improved radiative transfer equations showed the dominance of traffic-derived black carbon ($ BC_{FF} $) emissions in the study region. The AERMOD was used to model BC emissions from moving traffic as a line source and parking lot as area source using observational and WRF-processed meteorology for the winter (January to March 2020). The model results showed that the BC levels substantially vary with local meteorological conditions, traffic volume, and composition. The hilly terrain obstructs the winds and develops a negative pressure loading to a vacuum on the other side of the hills, which promotes the accumulation of emissions, causing high BC concentrations. The pockets of higher concentration were seen at the locations where steep slopes were associated with low winds (<1 m $ s^{−1} $) and hill fogs. The AERMOD model, after statistical evaluation against the observational datasets, has been applied to study the reduction in $ BC_{FF} $ concentrations due to the implementation of Indian emission norms as mitigation measures, i.e., BS-IV (equivalent to Euro 4) and BS-VI (equivalent to Euro 6). It was found that the $ BC_{FF} $ concentrations for BS-IV and BS-VI reduced by 35% and 75%, respectively. The model was also used to study the contribution of the different vehicular categories to BC concentration. AERMOD (dpeaa)DE-He213 Aethalometer (dpeaa)DE-He213 Black carbon (dpeaa)DE-He213 Dispersion (dpeaa)DE-He213 Hilly terrain (dpeaa)DE-He213 Vehicular emission (dpeaa)DE-He213 Gokhale, Sharad aut Enthalten in Environmental monitoring and assessment Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981 195(2023), 8 vom: 15. Juli (DE-627)31281738X (DE-600)2012242-1 1573-2959 nnns volume:195 year:2023 number:8 day:15 month:07 https://dx.doi.org/10.1007/s10661-023-11554-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 195 2023 8 15 07 |
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10.1007/s10661-023-11554-6 doi (DE-627)SPR05226503X (SPR)s10661-023-11554-6-e DE-627 ger DE-627 rakwb eng Singh, Sameer verfasserin (orcid)0000-0002-6287-5430 aut Modeling the dispersion of traffic-derived black carbon emissions into hilly terrain 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract This study examines hilly terrain’s effect on black carbon (BC) dispersion. The apportionment of distinct sources obtained by a two-component mixing model (Aethalometer: AE-33) using improved radiative transfer equations showed the dominance of traffic-derived black carbon ($ BC_{FF} $) emissions in the study region. The AERMOD was used to model BC emissions from moving traffic as a line source and parking lot as area source using observational and WRF-processed meteorology for the winter (January to March 2020). The model results showed that the BC levels substantially vary with local meteorological conditions, traffic volume, and composition. The hilly terrain obstructs the winds and develops a negative pressure loading to a vacuum on the other side of the hills, which promotes the accumulation of emissions, causing high BC concentrations. The pockets of higher concentration were seen at the locations where steep slopes were associated with low winds (<1 m $ s^{−1} $) and hill fogs. The AERMOD model, after statistical evaluation against the observational datasets, has been applied to study the reduction in $ BC_{FF} $ concentrations due to the implementation of Indian emission norms as mitigation measures, i.e., BS-IV (equivalent to Euro 4) and BS-VI (equivalent to Euro 6). It was found that the $ BC_{FF} $ concentrations for BS-IV and BS-VI reduced by 35% and 75%, respectively. The model was also used to study the contribution of the different vehicular categories to BC concentration. AERMOD (dpeaa)DE-He213 Aethalometer (dpeaa)DE-He213 Black carbon (dpeaa)DE-He213 Dispersion (dpeaa)DE-He213 Hilly terrain (dpeaa)DE-He213 Vehicular emission (dpeaa)DE-He213 Gokhale, Sharad aut Enthalten in Environmental monitoring and assessment Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981 195(2023), 8 vom: 15. Juli (DE-627)31281738X (DE-600)2012242-1 1573-2959 nnns volume:195 year:2023 number:8 day:15 month:07 https://dx.doi.org/10.1007/s10661-023-11554-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 195 2023 8 15 07 |
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10.1007/s10661-023-11554-6 doi (DE-627)SPR05226503X (SPR)s10661-023-11554-6-e DE-627 ger DE-627 rakwb eng Singh, Sameer verfasserin (orcid)0000-0002-6287-5430 aut Modeling the dispersion of traffic-derived black carbon emissions into hilly terrain 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract This study examines hilly terrain’s effect on black carbon (BC) dispersion. The apportionment of distinct sources obtained by a two-component mixing model (Aethalometer: AE-33) using improved radiative transfer equations showed the dominance of traffic-derived black carbon ($ BC_{FF} $) emissions in the study region. The AERMOD was used to model BC emissions from moving traffic as a line source and parking lot as area source using observational and WRF-processed meteorology for the winter (January to March 2020). The model results showed that the BC levels substantially vary with local meteorological conditions, traffic volume, and composition. The hilly terrain obstructs the winds and develops a negative pressure loading to a vacuum on the other side of the hills, which promotes the accumulation of emissions, causing high BC concentrations. The pockets of higher concentration were seen at the locations where steep slopes were associated with low winds (<1 m $ s^{−1} $) and hill fogs. The AERMOD model, after statistical evaluation against the observational datasets, has been applied to study the reduction in $ BC_{FF} $ concentrations due to the implementation of Indian emission norms as mitigation measures, i.e., BS-IV (equivalent to Euro 4) and BS-VI (equivalent to Euro 6). It was found that the $ BC_{FF} $ concentrations for BS-IV and BS-VI reduced by 35% and 75%, respectively. The model was also used to study the contribution of the different vehicular categories to BC concentration. AERMOD (dpeaa)DE-He213 Aethalometer (dpeaa)DE-He213 Black carbon (dpeaa)DE-He213 Dispersion (dpeaa)DE-He213 Hilly terrain (dpeaa)DE-He213 Vehicular emission (dpeaa)DE-He213 Gokhale, Sharad aut Enthalten in Environmental monitoring and assessment Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981 195(2023), 8 vom: 15. Juli (DE-627)31281738X (DE-600)2012242-1 1573-2959 nnns volume:195 year:2023 number:8 day:15 month:07 https://dx.doi.org/10.1007/s10661-023-11554-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 195 2023 8 15 07 |
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10.1007/s10661-023-11554-6 doi (DE-627)SPR05226503X (SPR)s10661-023-11554-6-e DE-627 ger DE-627 rakwb eng Singh, Sameer verfasserin (orcid)0000-0002-6287-5430 aut Modeling the dispersion of traffic-derived black carbon emissions into hilly terrain 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract This study examines hilly terrain’s effect on black carbon (BC) dispersion. The apportionment of distinct sources obtained by a two-component mixing model (Aethalometer: AE-33) using improved radiative transfer equations showed the dominance of traffic-derived black carbon ($ BC_{FF} $) emissions in the study region. The AERMOD was used to model BC emissions from moving traffic as a line source and parking lot as area source using observational and WRF-processed meteorology for the winter (January to March 2020). The model results showed that the BC levels substantially vary with local meteorological conditions, traffic volume, and composition. The hilly terrain obstructs the winds and develops a negative pressure loading to a vacuum on the other side of the hills, which promotes the accumulation of emissions, causing high BC concentrations. The pockets of higher concentration were seen at the locations where steep slopes were associated with low winds (<1 m $ s^{−1} $) and hill fogs. The AERMOD model, after statistical evaluation against the observational datasets, has been applied to study the reduction in $ BC_{FF} $ concentrations due to the implementation of Indian emission norms as mitigation measures, i.e., BS-IV (equivalent to Euro 4) and BS-VI (equivalent to Euro 6). It was found that the $ BC_{FF} $ concentrations for BS-IV and BS-VI reduced by 35% and 75%, respectively. The model was also used to study the contribution of the different vehicular categories to BC concentration. AERMOD (dpeaa)DE-He213 Aethalometer (dpeaa)DE-He213 Black carbon (dpeaa)DE-He213 Dispersion (dpeaa)DE-He213 Hilly terrain (dpeaa)DE-He213 Vehicular emission (dpeaa)DE-He213 Gokhale, Sharad aut Enthalten in Environmental monitoring and assessment Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981 195(2023), 8 vom: 15. Juli (DE-627)31281738X (DE-600)2012242-1 1573-2959 nnns volume:195 year:2023 number:8 day:15 month:07 https://dx.doi.org/10.1007/s10661-023-11554-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 195 2023 8 15 07 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR05226503X</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230811064758.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230716s2023 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s10661-023-11554-6</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR05226503X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s10661-023-11554-6-e</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="100" ind1="1" ind2=" "><subfield code="a">Singh, Sameer</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0002-6287-5430</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Modeling the dispersion of traffic-derived black carbon emissions into hilly terrain</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</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">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract This study examines hilly terrain’s effect on black carbon (BC) dispersion. The apportionment of distinct sources obtained by a two-component mixing model (Aethalometer: AE-33) using improved radiative transfer equations showed the dominance of traffic-derived black carbon ($ BC_{FF} $) emissions in the study region. The AERMOD was used to model BC emissions from moving traffic as a line source and parking lot as area source using observational and WRF-processed meteorology for the winter (January to March 2020). The model results showed that the BC levels substantially vary with local meteorological conditions, traffic volume, and composition. The hilly terrain obstructs the winds and develops a negative pressure loading to a vacuum on the other side of the hills, which promotes the accumulation of emissions, causing high BC concentrations. The pockets of higher concentration were seen at the locations where steep slopes were associated with low winds (<1 m $ s^{−1} $) and hill fogs. The AERMOD model, after statistical evaluation against the observational datasets, has been applied to study the reduction in $ BC_{FF} $ concentrations due to the implementation of Indian emission norms as mitigation measures, i.e., BS-IV (equivalent to Euro 4) and BS-VI (equivalent to Euro 6). It was found that the $ BC_{FF} $ concentrations for BS-IV and BS-VI reduced by 35% and 75%, respectively. 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Singh, Sameer |
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Modeling the dispersion of traffic-derived black carbon emissions into hilly terrain AERMOD (dpeaa)DE-He213 Aethalometer (dpeaa)DE-He213 Black carbon (dpeaa)DE-He213 Dispersion (dpeaa)DE-He213 Hilly terrain (dpeaa)DE-He213 Vehicular emission (dpeaa)DE-He213 |
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modeling the dispersion of traffic-derived black carbon emissions into hilly terrain |
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Modeling the dispersion of traffic-derived black carbon emissions into hilly terrain |
| abstract |
Abstract This study examines hilly terrain’s effect on black carbon (BC) dispersion. The apportionment of distinct sources obtained by a two-component mixing model (Aethalometer: AE-33) using improved radiative transfer equations showed the dominance of traffic-derived black carbon ($ BC_{FF} $) emissions in the study region. The AERMOD was used to model BC emissions from moving traffic as a line source and parking lot as area source using observational and WRF-processed meteorology for the winter (January to March 2020). The model results showed that the BC levels substantially vary with local meteorological conditions, traffic volume, and composition. The hilly terrain obstructs the winds and develops a negative pressure loading to a vacuum on the other side of the hills, which promotes the accumulation of emissions, causing high BC concentrations. The pockets of higher concentration were seen at the locations where steep slopes were associated with low winds (<1 m $ s^{−1} $) and hill fogs. The AERMOD model, after statistical evaluation against the observational datasets, has been applied to study the reduction in $ BC_{FF} $ concentrations due to the implementation of Indian emission norms as mitigation measures, i.e., BS-IV (equivalent to Euro 4) and BS-VI (equivalent to Euro 6). It was found that the $ BC_{FF} $ concentrations for BS-IV and BS-VI reduced by 35% and 75%, respectively. The model was also used to study the contribution of the different vehicular categories to BC concentration. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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Abstract This study examines hilly terrain’s effect on black carbon (BC) dispersion. The apportionment of distinct sources obtained by a two-component mixing model (Aethalometer: AE-33) using improved radiative transfer equations showed the dominance of traffic-derived black carbon ($ BC_{FF} $) emissions in the study region. The AERMOD was used to model BC emissions from moving traffic as a line source and parking lot as area source using observational and WRF-processed meteorology for the winter (January to March 2020). The model results showed that the BC levels substantially vary with local meteorological conditions, traffic volume, and composition. The hilly terrain obstructs the winds and develops a negative pressure loading to a vacuum on the other side of the hills, which promotes the accumulation of emissions, causing high BC concentrations. The pockets of higher concentration were seen at the locations where steep slopes were associated with low winds (<1 m $ s^{−1} $) and hill fogs. The AERMOD model, after statistical evaluation against the observational datasets, has been applied to study the reduction in $ BC_{FF} $ concentrations due to the implementation of Indian emission norms as mitigation measures, i.e., BS-IV (equivalent to Euro 4) and BS-VI (equivalent to Euro 6). It was found that the $ BC_{FF} $ concentrations for BS-IV and BS-VI reduced by 35% and 75%, respectively. The model was also used to study the contribution of the different vehicular categories to BC concentration. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstract_unstemmed |
Abstract This study examines hilly terrain’s effect on black carbon (BC) dispersion. The apportionment of distinct sources obtained by a two-component mixing model (Aethalometer: AE-33) using improved radiative transfer equations showed the dominance of traffic-derived black carbon ($ BC_{FF} $) emissions in the study region. The AERMOD was used to model BC emissions from moving traffic as a line source and parking lot as area source using observational and WRF-processed meteorology for the winter (January to March 2020). The model results showed that the BC levels substantially vary with local meteorological conditions, traffic volume, and composition. The hilly terrain obstructs the winds and develops a negative pressure loading to a vacuum on the other side of the hills, which promotes the accumulation of emissions, causing high BC concentrations. The pockets of higher concentration were seen at the locations where steep slopes were associated with low winds (<1 m $ s^{−1} $) and hill fogs. The AERMOD model, after statistical evaluation against the observational datasets, has been applied to study the reduction in $ BC_{FF} $ concentrations due to the implementation of Indian emission norms as mitigation measures, i.e., BS-IV (equivalent to Euro 4) and BS-VI (equivalent to Euro 6). It was found that the $ BC_{FF} $ concentrations for BS-IV and BS-VI reduced by 35% and 75%, respectively. The model was also used to study the contribution of the different vehicular categories to BC concentration. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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Modeling the dispersion of traffic-derived black carbon emissions into hilly terrain |
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https://dx.doi.org/10.1007/s10661-023-11554-6 |
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| score |
7.4004345 |