Evaluation of control strategies for industrial air pollution sources using American Meteorological Society/Environmental Protection Agency Regulatory Model with simulated meteorology by Weather Research and Forecasting Model
Industrial air pollution creates severe problems and evaluation of control scenarios rationally which can be carried out using air quality models. In this study, an industrial region Chembur in Mumbai city was selected to estimate air quality change for various control scenarios. Weather Research an...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Kumar, Awkash [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2016transfer abstract |
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| Schlagwörter: |
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| Umfang: |
8 |
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| Übergeordnetes Werk: |
Enthalten in: Self-assembled 3D hierarchical MnCO - Rajendiran, Rajmohan ELSEVIER, 2020, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:116 ; year:2016 ; day:10 ; month:03 ; pages:110-117 ; extent:8 |
| Links: |
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| DOI / URN: |
10.1016/j.jclepro.2015.12.079 |
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ELV019589646 |
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| 245 | 1 | 0 | |a Evaluation of control strategies for industrial air pollution sources using American Meteorological Society/Environmental Protection Agency Regulatory Model with simulated meteorology by Weather Research and Forecasting Model |
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| 520 | |a Industrial air pollution creates severe problems and evaluation of control scenarios rationally which can be carried out using air quality models. In this study, an industrial region Chembur in Mumbai city was selected to estimate air quality change for various control scenarios. Weather Research and Forecasting (WRF) and AMS/EPA Regulatory Model (AERMOD) were used for this study. Since, the industries of Chembur region were already existing and residential and commercial zones were pre-set in the domain, so scenarios like increment of stack height and fuel change of industries can help to make better and healthier air quality. Scenarios selected were the 10% (SH1), 25% (SH2) and 50% (SH3) increment of height of stacks of industry and use of low emission fuel (F1 and F2) in the industries. Industrial air pollution modelling was done for current scenario as well as proposed control scenarios. The reduction of air quality level for each control scenario was calculated. Overall scenario SH3 as expected had more or less maximum reduction at ground level concentration for various temporal cases for all pollutants. However, it would cause more residence time of pollutants in atmosphere. Also this scenario was not based on source emission reduction strategy. Scenario F1 considers fuel with lowest emission and source emission reduction strategy. Therefore, scenario F1 seems to be the most preferred option for all pollutants among all scenarios. This study can help in taking objective and rational decisions for control scenarios for industrial sources. | ||
| 520 | |a Industrial air pollution creates severe problems and evaluation of control scenarios rationally which can be carried out using air quality models. In this study, an industrial region Chembur in Mumbai city was selected to estimate air quality change for various control scenarios. Weather Research and Forecasting (WRF) and AMS/EPA Regulatory Model (AERMOD) were used for this study. Since, the industries of Chembur region were already existing and residential and commercial zones were pre-set in the domain, so scenarios like increment of stack height and fuel change of industries can help to make better and healthier air quality. Scenarios selected were the 10% (SH1), 25% (SH2) and 50% (SH3) increment of height of stacks of industry and use of low emission fuel (F1 and F2) in the industries. Industrial air pollution modelling was done for current scenario as well as proposed control scenarios. The reduction of air quality level for each control scenario was calculated. Overall scenario SH3 as expected had more or less maximum reduction at ground level concentration for various temporal cases for all pollutants. However, it would cause more residence time of pollutants in atmosphere. Also this scenario was not based on source emission reduction strategy. Scenario F1 considers fuel with lowest emission and source emission reduction strategy. Therefore, scenario F1 seems to be the most preferred option for all pollutants among all scenarios. This study can help in taking objective and rational decisions for control scenarios for industrial sources. | ||
| 650 | 7 | |a Industrial sources |2 Elsevier | |
| 650 | 7 | |a AERMOD |2 Elsevier | |
| 650 | 7 | |a WRF |2 Elsevier | |
| 650 | 7 | |a Control scenarios |2 Elsevier | |
| 700 | 1 | |a Patil, Rashmi S. |4 oth | |
| 700 | 1 | |a Dikshit, Anil Kumar |4 oth | |
| 700 | 1 | |a Islam, Sahidul |4 oth | |
| 700 | 1 | |a Kumar, Rakesh |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |n Elsevier Science |a Rajendiran, Rajmohan ELSEVIER |t Self-assembled 3D hierarchical MnCO |d 2020 |g Amsterdam [u.a.] |w (DE-627)ELV003750353 |
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10.1016/j.jclepro.2015.12.079 doi GBVA2016016000005.pica (DE-627)ELV019589646 (ELSEVIER)S0959-6526(15)01904-6 DE-627 ger DE-627 rakwb eng 690 330 690 DE-600 330 DE-600 540 VZ 35.18 bkl Kumar, Awkash verfasserin aut Evaluation of control strategies for industrial air pollution sources using American Meteorological Society/Environmental Protection Agency Regulatory Model with simulated meteorology by Weather Research and Forecasting Model 2016transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Industrial air pollution creates severe problems and evaluation of control scenarios rationally which can be carried out using air quality models. In this study, an industrial region Chembur in Mumbai city was selected to estimate air quality change for various control scenarios. Weather Research and Forecasting (WRF) and AMS/EPA Regulatory Model (AERMOD) were used for this study. Since, the industries of Chembur region were already existing and residential and commercial zones were pre-set in the domain, so scenarios like increment of stack height and fuel change of industries can help to make better and healthier air quality. Scenarios selected were the 10% (SH1), 25% (SH2) and 50% (SH3) increment of height of stacks of industry and use of low emission fuel (F1 and F2) in the industries. Industrial air pollution modelling was done for current scenario as well as proposed control scenarios. The reduction of air quality level for each control scenario was calculated. Overall scenario SH3 as expected had more or less maximum reduction at ground level concentration for various temporal cases for all pollutants. However, it would cause more residence time of pollutants in atmosphere. Also this scenario was not based on source emission reduction strategy. Scenario F1 considers fuel with lowest emission and source emission reduction strategy. Therefore, scenario F1 seems to be the most preferred option for all pollutants among all scenarios. This study can help in taking objective and rational decisions for control scenarios for industrial sources. Industrial air pollution creates severe problems and evaluation of control scenarios rationally which can be carried out using air quality models. In this study, an industrial region Chembur in Mumbai city was selected to estimate air quality change for various control scenarios. Weather Research and Forecasting (WRF) and AMS/EPA Regulatory Model (AERMOD) were used for this study. Since, the industries of Chembur region were already existing and residential and commercial zones were pre-set in the domain, so scenarios like increment of stack height and fuel change of industries can help to make better and healthier air quality. Scenarios selected were the 10% (SH1), 25% (SH2) and 50% (SH3) increment of height of stacks of industry and use of low emission fuel (F1 and F2) in the industries. Industrial air pollution modelling was done for current scenario as well as proposed control scenarios. The reduction of air quality level for each control scenario was calculated. Overall scenario SH3 as expected had more or less maximum reduction at ground level concentration for various temporal cases for all pollutants. However, it would cause more residence time of pollutants in atmosphere. Also this scenario was not based on source emission reduction strategy. Scenario F1 considers fuel with lowest emission and source emission reduction strategy. Therefore, scenario F1 seems to be the most preferred option for all pollutants among all scenarios. This study can help in taking objective and rational decisions for control scenarios for industrial sources. Industrial sources Elsevier AERMOD Elsevier WRF Elsevier Control scenarios Elsevier Patil, Rashmi S. oth Dikshit, Anil Kumar oth Islam, Sahidul oth Kumar, Rakesh oth Enthalten in Elsevier Science Rajendiran, Rajmohan ELSEVIER Self-assembled 3D hierarchical MnCO 2020 Amsterdam [u.a.] (DE-627)ELV003750353 volume:116 year:2016 day:10 month:03 pages:110-117 extent:8 https://doi.org/10.1016/j.jclepro.2015.12.079 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 35.18 Kolloidchemie Grenzflächenchemie VZ AR 116 2016 10 0310 110-117 8 045F 690 |
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10.1016/j.jclepro.2015.12.079 doi GBVA2016016000005.pica (DE-627)ELV019589646 (ELSEVIER)S0959-6526(15)01904-6 DE-627 ger DE-627 rakwb eng 690 330 690 DE-600 330 DE-600 540 VZ 35.18 bkl Kumar, Awkash verfasserin aut Evaluation of control strategies for industrial air pollution sources using American Meteorological Society/Environmental Protection Agency Regulatory Model with simulated meteorology by Weather Research and Forecasting Model 2016transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Industrial air pollution creates severe problems and evaluation of control scenarios rationally which can be carried out using air quality models. In this study, an industrial region Chembur in Mumbai city was selected to estimate air quality change for various control scenarios. Weather Research and Forecasting (WRF) and AMS/EPA Regulatory Model (AERMOD) were used for this study. Since, the industries of Chembur region were already existing and residential and commercial zones were pre-set in the domain, so scenarios like increment of stack height and fuel change of industries can help to make better and healthier air quality. Scenarios selected were the 10% (SH1), 25% (SH2) and 50% (SH3) increment of height of stacks of industry and use of low emission fuel (F1 and F2) in the industries. Industrial air pollution modelling was done for current scenario as well as proposed control scenarios. The reduction of air quality level for each control scenario was calculated. Overall scenario SH3 as expected had more or less maximum reduction at ground level concentration for various temporal cases for all pollutants. However, it would cause more residence time of pollutants in atmosphere. Also this scenario was not based on source emission reduction strategy. Scenario F1 considers fuel with lowest emission and source emission reduction strategy. Therefore, scenario F1 seems to be the most preferred option for all pollutants among all scenarios. This study can help in taking objective and rational decisions for control scenarios for industrial sources. Industrial air pollution creates severe problems and evaluation of control scenarios rationally which can be carried out using air quality models. In this study, an industrial region Chembur in Mumbai city was selected to estimate air quality change for various control scenarios. Weather Research and Forecasting (WRF) and AMS/EPA Regulatory Model (AERMOD) were used for this study. Since, the industries of Chembur region were already existing and residential and commercial zones were pre-set in the domain, so scenarios like increment of stack height and fuel change of industries can help to make better and healthier air quality. Scenarios selected were the 10% (SH1), 25% (SH2) and 50% (SH3) increment of height of stacks of industry and use of low emission fuel (F1 and F2) in the industries. Industrial air pollution modelling was done for current scenario as well as proposed control scenarios. The reduction of air quality level for each control scenario was calculated. Overall scenario SH3 as expected had more or less maximum reduction at ground level concentration for various temporal cases for all pollutants. However, it would cause more residence time of pollutants in atmosphere. Also this scenario was not based on source emission reduction strategy. Scenario F1 considers fuel with lowest emission and source emission reduction strategy. Therefore, scenario F1 seems to be the most preferred option for all pollutants among all scenarios. This study can help in taking objective and rational decisions for control scenarios for industrial sources. Industrial sources Elsevier AERMOD Elsevier WRF Elsevier Control scenarios Elsevier Patil, Rashmi S. oth Dikshit, Anil Kumar oth Islam, Sahidul oth Kumar, Rakesh oth Enthalten in Elsevier Science Rajendiran, Rajmohan ELSEVIER Self-assembled 3D hierarchical MnCO 2020 Amsterdam [u.a.] (DE-627)ELV003750353 volume:116 year:2016 day:10 month:03 pages:110-117 extent:8 https://doi.org/10.1016/j.jclepro.2015.12.079 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 35.18 Kolloidchemie Grenzflächenchemie VZ AR 116 2016 10 0310 110-117 8 045F 690 |
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10.1016/j.jclepro.2015.12.079 doi GBVA2016016000005.pica (DE-627)ELV019589646 (ELSEVIER)S0959-6526(15)01904-6 DE-627 ger DE-627 rakwb eng 690 330 690 DE-600 330 DE-600 540 VZ 35.18 bkl Kumar, Awkash verfasserin aut Evaluation of control strategies for industrial air pollution sources using American Meteorological Society/Environmental Protection Agency Regulatory Model with simulated meteorology by Weather Research and Forecasting Model 2016transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Industrial air pollution creates severe problems and evaluation of control scenarios rationally which can be carried out using air quality models. In this study, an industrial region Chembur in Mumbai city was selected to estimate air quality change for various control scenarios. Weather Research and Forecasting (WRF) and AMS/EPA Regulatory Model (AERMOD) were used for this study. Since, the industries of Chembur region were already existing and residential and commercial zones were pre-set in the domain, so scenarios like increment of stack height and fuel change of industries can help to make better and healthier air quality. Scenarios selected were the 10% (SH1), 25% (SH2) and 50% (SH3) increment of height of stacks of industry and use of low emission fuel (F1 and F2) in the industries. Industrial air pollution modelling was done for current scenario as well as proposed control scenarios. The reduction of air quality level for each control scenario was calculated. Overall scenario SH3 as expected had more or less maximum reduction at ground level concentration for various temporal cases for all pollutants. However, it would cause more residence time of pollutants in atmosphere. Also this scenario was not based on source emission reduction strategy. Scenario F1 considers fuel with lowest emission and source emission reduction strategy. Therefore, scenario F1 seems to be the most preferred option for all pollutants among all scenarios. This study can help in taking objective and rational decisions for control scenarios for industrial sources. Industrial air pollution creates severe problems and evaluation of control scenarios rationally which can be carried out using air quality models. In this study, an industrial region Chembur in Mumbai city was selected to estimate air quality change for various control scenarios. Weather Research and Forecasting (WRF) and AMS/EPA Regulatory Model (AERMOD) were used for this study. Since, the industries of Chembur region were already existing and residential and commercial zones were pre-set in the domain, so scenarios like increment of stack height and fuel change of industries can help to make better and healthier air quality. Scenarios selected were the 10% (SH1), 25% (SH2) and 50% (SH3) increment of height of stacks of industry and use of low emission fuel (F1 and F2) in the industries. Industrial air pollution modelling was done for current scenario as well as proposed control scenarios. The reduction of air quality level for each control scenario was calculated. Overall scenario SH3 as expected had more or less maximum reduction at ground level concentration for various temporal cases for all pollutants. However, it would cause more residence time of pollutants in atmosphere. Also this scenario was not based on source emission reduction strategy. Scenario F1 considers fuel with lowest emission and source emission reduction strategy. Therefore, scenario F1 seems to be the most preferred option for all pollutants among all scenarios. This study can help in taking objective and rational decisions for control scenarios for industrial sources. Industrial sources Elsevier AERMOD Elsevier WRF Elsevier Control scenarios Elsevier Patil, Rashmi S. oth Dikshit, Anil Kumar oth Islam, Sahidul oth Kumar, Rakesh oth Enthalten in Elsevier Science Rajendiran, Rajmohan ELSEVIER Self-assembled 3D hierarchical MnCO 2020 Amsterdam [u.a.] (DE-627)ELV003750353 volume:116 year:2016 day:10 month:03 pages:110-117 extent:8 https://doi.org/10.1016/j.jclepro.2015.12.079 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 35.18 Kolloidchemie Grenzflächenchemie VZ AR 116 2016 10 0310 110-117 8 045F 690 |
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10.1016/j.jclepro.2015.12.079 doi GBVA2016016000005.pica (DE-627)ELV019589646 (ELSEVIER)S0959-6526(15)01904-6 DE-627 ger DE-627 rakwb eng 690 330 690 DE-600 330 DE-600 540 VZ 35.18 bkl Kumar, Awkash verfasserin aut Evaluation of control strategies for industrial air pollution sources using American Meteorological Society/Environmental Protection Agency Regulatory Model with simulated meteorology by Weather Research and Forecasting Model 2016transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Industrial air pollution creates severe problems and evaluation of control scenarios rationally which can be carried out using air quality models. In this study, an industrial region Chembur in Mumbai city was selected to estimate air quality change for various control scenarios. Weather Research and Forecasting (WRF) and AMS/EPA Regulatory Model (AERMOD) were used for this study. Since, the industries of Chembur region were already existing and residential and commercial zones were pre-set in the domain, so scenarios like increment of stack height and fuel change of industries can help to make better and healthier air quality. Scenarios selected were the 10% (SH1), 25% (SH2) and 50% (SH3) increment of height of stacks of industry and use of low emission fuel (F1 and F2) in the industries. Industrial air pollution modelling was done for current scenario as well as proposed control scenarios. The reduction of air quality level for each control scenario was calculated. Overall scenario SH3 as expected had more or less maximum reduction at ground level concentration for various temporal cases for all pollutants. However, it would cause more residence time of pollutants in atmosphere. Also this scenario was not based on source emission reduction strategy. Scenario F1 considers fuel with lowest emission and source emission reduction strategy. Therefore, scenario F1 seems to be the most preferred option for all pollutants among all scenarios. This study can help in taking objective and rational decisions for control scenarios for industrial sources. Industrial air pollution creates severe problems and evaluation of control scenarios rationally which can be carried out using air quality models. In this study, an industrial region Chembur in Mumbai city was selected to estimate air quality change for various control scenarios. Weather Research and Forecasting (WRF) and AMS/EPA Regulatory Model (AERMOD) were used for this study. Since, the industries of Chembur region were already existing and residential and commercial zones were pre-set in the domain, so scenarios like increment of stack height and fuel change of industries can help to make better and healthier air quality. Scenarios selected were the 10% (SH1), 25% (SH2) and 50% (SH3) increment of height of stacks of industry and use of low emission fuel (F1 and F2) in the industries. Industrial air pollution modelling was done for current scenario as well as proposed control scenarios. The reduction of air quality level for each control scenario was calculated. Overall scenario SH3 as expected had more or less maximum reduction at ground level concentration for various temporal cases for all pollutants. However, it would cause more residence time of pollutants in atmosphere. Also this scenario was not based on source emission reduction strategy. Scenario F1 considers fuel with lowest emission and source emission reduction strategy. Therefore, scenario F1 seems to be the most preferred option for all pollutants among all scenarios. This study can help in taking objective and rational decisions for control scenarios for industrial sources. Industrial sources Elsevier AERMOD Elsevier WRF Elsevier Control scenarios Elsevier Patil, Rashmi S. oth Dikshit, Anil Kumar oth Islam, Sahidul oth Kumar, Rakesh oth Enthalten in Elsevier Science Rajendiran, Rajmohan ELSEVIER Self-assembled 3D hierarchical MnCO 2020 Amsterdam [u.a.] (DE-627)ELV003750353 volume:116 year:2016 day:10 month:03 pages:110-117 extent:8 https://doi.org/10.1016/j.jclepro.2015.12.079 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 35.18 Kolloidchemie Grenzflächenchemie VZ AR 116 2016 10 0310 110-117 8 045F 690 |
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10.1016/j.jclepro.2015.12.079 doi GBVA2016016000005.pica (DE-627)ELV019589646 (ELSEVIER)S0959-6526(15)01904-6 DE-627 ger DE-627 rakwb eng 690 330 690 DE-600 330 DE-600 540 VZ 35.18 bkl Kumar, Awkash verfasserin aut Evaluation of control strategies for industrial air pollution sources using American Meteorological Society/Environmental Protection Agency Regulatory Model with simulated meteorology by Weather Research and Forecasting Model 2016transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Industrial air pollution creates severe problems and evaluation of control scenarios rationally which can be carried out using air quality models. In this study, an industrial region Chembur in Mumbai city was selected to estimate air quality change for various control scenarios. Weather Research and Forecasting (WRF) and AMS/EPA Regulatory Model (AERMOD) were used for this study. Since, the industries of Chembur region were already existing and residential and commercial zones were pre-set in the domain, so scenarios like increment of stack height and fuel change of industries can help to make better and healthier air quality. Scenarios selected were the 10% (SH1), 25% (SH2) and 50% (SH3) increment of height of stacks of industry and use of low emission fuel (F1 and F2) in the industries. Industrial air pollution modelling was done for current scenario as well as proposed control scenarios. The reduction of air quality level for each control scenario was calculated. Overall scenario SH3 as expected had more or less maximum reduction at ground level concentration for various temporal cases for all pollutants. However, it would cause more residence time of pollutants in atmosphere. Also this scenario was not based on source emission reduction strategy. Scenario F1 considers fuel with lowest emission and source emission reduction strategy. Therefore, scenario F1 seems to be the most preferred option for all pollutants among all scenarios. This study can help in taking objective and rational decisions for control scenarios for industrial sources. Industrial air pollution creates severe problems and evaluation of control scenarios rationally which can be carried out using air quality models. In this study, an industrial region Chembur in Mumbai city was selected to estimate air quality change for various control scenarios. Weather Research and Forecasting (WRF) and AMS/EPA Regulatory Model (AERMOD) were used for this study. Since, the industries of Chembur region were already existing and residential and commercial zones were pre-set in the domain, so scenarios like increment of stack height and fuel change of industries can help to make better and healthier air quality. Scenarios selected were the 10% (SH1), 25% (SH2) and 50% (SH3) increment of height of stacks of industry and use of low emission fuel (F1 and F2) in the industries. Industrial air pollution modelling was done for current scenario as well as proposed control scenarios. The reduction of air quality level for each control scenario was calculated. Overall scenario SH3 as expected had more or less maximum reduction at ground level concentration for various temporal cases for all pollutants. However, it would cause more residence time of pollutants in atmosphere. Also this scenario was not based on source emission reduction strategy. Scenario F1 considers fuel with lowest emission and source emission reduction strategy. Therefore, scenario F1 seems to be the most preferred option for all pollutants among all scenarios. This study can help in taking objective and rational decisions for control scenarios for industrial sources. Industrial sources Elsevier AERMOD Elsevier WRF Elsevier Control scenarios Elsevier Patil, Rashmi S. oth Dikshit, Anil Kumar oth Islam, Sahidul oth Kumar, Rakesh oth Enthalten in Elsevier Science Rajendiran, Rajmohan ELSEVIER Self-assembled 3D hierarchical MnCO 2020 Amsterdam [u.a.] (DE-627)ELV003750353 volume:116 year:2016 day:10 month:03 pages:110-117 extent:8 https://doi.org/10.1016/j.jclepro.2015.12.079 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 35.18 Kolloidchemie Grenzflächenchemie VZ AR 116 2016 10 0310 110-117 8 045F 690 |
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Evaluation of control strategies for industrial air pollution sources using American Meteorological Society/Environmental Protection Agency Regulatory Model with simulated meteorology by Weather Research and Forecasting Model |
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Industrial air pollution creates severe problems and evaluation of control scenarios rationally which can be carried out using air quality models. In this study, an industrial region Chembur in Mumbai city was selected to estimate air quality change for various control scenarios. Weather Research and Forecasting (WRF) and AMS/EPA Regulatory Model (AERMOD) were used for this study. Since, the industries of Chembur region were already existing and residential and commercial zones were pre-set in the domain, so scenarios like increment of stack height and fuel change of industries can help to make better and healthier air quality. Scenarios selected were the 10% (SH1), 25% (SH2) and 50% (SH3) increment of height of stacks of industry and use of low emission fuel (F1 and F2) in the industries. Industrial air pollution modelling was done for current scenario as well as proposed control scenarios. The reduction of air quality level for each control scenario was calculated. Overall scenario SH3 as expected had more or less maximum reduction at ground level concentration for various temporal cases for all pollutants. However, it would cause more residence time of pollutants in atmosphere. Also this scenario was not based on source emission reduction strategy. Scenario F1 considers fuel with lowest emission and source emission reduction strategy. Therefore, scenario F1 seems to be the most preferred option for all pollutants among all scenarios. This study can help in taking objective and rational decisions for control scenarios for industrial sources. |
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Industrial air pollution creates severe problems and evaluation of control scenarios rationally which can be carried out using air quality models. In this study, an industrial region Chembur in Mumbai city was selected to estimate air quality change for various control scenarios. Weather Research and Forecasting (WRF) and AMS/EPA Regulatory Model (AERMOD) were used for this study. Since, the industries of Chembur region were already existing and residential and commercial zones were pre-set in the domain, so scenarios like increment of stack height and fuel change of industries can help to make better and healthier air quality. Scenarios selected were the 10% (SH1), 25% (SH2) and 50% (SH3) increment of height of stacks of industry and use of low emission fuel (F1 and F2) in the industries. Industrial air pollution modelling was done for current scenario as well as proposed control scenarios. The reduction of air quality level for each control scenario was calculated. Overall scenario SH3 as expected had more or less maximum reduction at ground level concentration for various temporal cases for all pollutants. However, it would cause more residence time of pollutants in atmosphere. Also this scenario was not based on source emission reduction strategy. Scenario F1 considers fuel with lowest emission and source emission reduction strategy. Therefore, scenario F1 seems to be the most preferred option for all pollutants among all scenarios. This study can help in taking objective and rational decisions for control scenarios for industrial sources. |
| abstract_unstemmed |
Industrial air pollution creates severe problems and evaluation of control scenarios rationally which can be carried out using air quality models. In this study, an industrial region Chembur in Mumbai city was selected to estimate air quality change for various control scenarios. Weather Research and Forecasting (WRF) and AMS/EPA Regulatory Model (AERMOD) were used for this study. Since, the industries of Chembur region were already existing and residential and commercial zones were pre-set in the domain, so scenarios like increment of stack height and fuel change of industries can help to make better and healthier air quality. Scenarios selected were the 10% (SH1), 25% (SH2) and 50% (SH3) increment of height of stacks of industry and use of low emission fuel (F1 and F2) in the industries. Industrial air pollution modelling was done for current scenario as well as proposed control scenarios. The reduction of air quality level for each control scenario was calculated. Overall scenario SH3 as expected had more or less maximum reduction at ground level concentration for various temporal cases for all pollutants. However, it would cause more residence time of pollutants in atmosphere. Also this scenario was not based on source emission reduction strategy. Scenario F1 considers fuel with lowest emission and source emission reduction strategy. Therefore, scenario F1 seems to be the most preferred option for all pollutants among all scenarios. This study can help in taking objective and rational decisions for control scenarios for industrial sources. |
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