Application of WRF Model for Vehicular Pollution Modelling Using AERMOD
Affiliation(s)
1 Centre for Environmental Science and Engineering, Indian Institute of Technology, Mumbai, India. 2 School of Environment and Sustainable Development, Central University of Gujarat, Gandhinagar, India.
1 Centre for Environmental Science and Engineering, Indian Institute of Technology, Mumbai, India. 2 School of Environment and Sustainable Development, Central University of Gujarat, Gandhinagar, India.
ABSTRACT
Vehicular pollution is becoming significant in urban areas because of increasing population. This is at ground level, so it gives high population exposure. In this study, Chembur, which is the most polluted area in Mumbai city due to industrial and vehicular sources, is selected for vehicular pollution modeling using AMS/EPA Regulatory Model (AERMOD). Meteorological parameters, land use surface characteristics and source emission data are collected as required by AERMOD. The results of modelling depend upon reliability of input data and meteorological data has a vital role in the performance of the model. Generally, temporally and spatially interpolated meteorological data is used in modeling. This is generally collected from nearby meteorological station but this causes inaccuracy of the results. In this paper, the Weather Research and Forecasting (WRF) model has been used to generate onsite data on nine meteorological parameters. The modeling of six roads of Chembur has been performed using above meteorological data. This approach gives good results of traffic modeling. The results of AERMOD are compared with observed air quality which has contribution from all sources in the region and relative contribution of vehicular sources identified.
Vehicular pollution is becoming significant in urban areas because of increasing population. This is at ground level, so it gives high population exposure. In this study, Chembur, which is the most polluted area in Mumbai city due to industrial and vehicular sources, is selected for vehicular pollution modeling using AMS/EPA Regulatory Model (AERMOD). Meteorological parameters, land use surface characteristics and source emission data are collected as required by AERMOD. The results of modelling depend upon reliability of input data and meteorological data has a vital role in the performance of the model. Generally, temporally and spatially interpolated meteorological data is used in modeling. This is generally collected from nearby meteorological station but this causes inaccuracy of the results. In this paper, the Weather Research and Forecasting (WRF) model has been used to generate onsite data on nine meteorological parameters. The modeling of six roads of Chembur has been performed using above meteorological data. This approach gives good results of traffic modeling. The results of AERMOD are compared with observed air quality which has contribution from all sources in the region and relative contribution of vehicular sources identified.
Cite this paper
Kumar, A. , Dikshit, A. , Fatima, S. and Patil, R. (2015) Application of WRF Model for Vehicular Pollution Modelling Using AERMOD. Atmospheric and Climate Sciences, 5, 57-62. doi: 10.4236/acs.2015.52004.
Kumar, A. , Dikshit, A. , Fatima, S. and Patil, R. (2015) Application of WRF Model for Vehicular Pollution Modelling Using AERMOD. Atmospheric and Climate Sciences, 5, 57-62. doi: 10.4236/acs.2015.52004.
References
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http://dx.doi.org/10.1016/j.atmosenv.2008.05.026 [2] Cheng, S., Lang, J., Zhou, Y., Han, L., Wang, G. and Chen, D. (2013) A New Monitoring-Simulation-Source Apportionment Approach for Investigating the Vehicular Emission Contribution to the PM2.5 Pollution in Beijing, China. Atmospheric Environment, 79, 308-316.
http://dx.doi.org/10.1016/j.atmosenv.2013.06.043 [3] Fan, X., Lam, K.C. and Yu, Q. (2012) Differential Exposure of the Urban Population to Vehicular Air Pollution in Hong Kong. Science of the Total Environment, 426, 211-219.
http://dx.doi.org/10.1016/j.scitotenv.2012.03.057 [4] Fenger, J. (2009) Air Pollution in the Last 50 Years—From Local to Global. Atmospheric Environment, 43, 13-22.
http://dx.doi.org/10.1016/j.atmosenv.2008.09.061 [5] Nagendra, S.M.S. and Khare, M. (2002) Line Source Emission Modelling. Atmospheric Environment, 36, 2083-2098.
http://dx.doi.org/10.1016/S1352-2310(02)00177-2 [6] Neema, M.N. and Jahan, J. (2014) An Innovative Approach to Mitigate Vehicular Emission through Roadside Greeneries: A Case Study on Arterial Roads of Dhaka City. Journal of Data Analysis and Information Processing, 2, 32-39.
http://dx.doi.org/10.4236/jdaip.2014.21005 [7] Province, H., Wang, L., Yang, J., Zhang, P., Zhao, X., Wei, Z., Zhang, F., Su, J. and Meng, C. (2013) A Review of Air Pollution and Control in Hebei Province. Journal of Data Analysis and Information Processing, 2, 47-55. [8] Sharma, N., Chaudhry, K.K. and Rao, C.V.C. (2004) Vehicular Pollution Prediction Modelling: A Review of Highway Dispersion Models. Transport Review, 24, 409-435.
http://dx.doi.org/10.1080/0144164042000196071 [9] Sivacoumar, R. and Thanasekaran, K. (1999) Line Source Model for Vehicular Pollution Prediction near Roadways and Model Evaluation through Statistical Analysis. Environmental Pollution, 104, 389-395.
http://dx.doi.org/10.1016/S0269-7491(98)00190-0 [10] Benson P.E. (1979) CALINE-3, a Versatile Dispersion Model for Predicting Air Pollutant Levels near Highways and Arterial Streets. FHWA/CA/TL-79/23, California Department of Transportation, Sacraments. [11] Petersen, W.B. (1980) Users Guide for HIWAY-2. Highway Air Pollution Model EPA-600/8-80-018. [12] Chock, D.P. (1978) A Simple Line-Source Model for Dispersion near Roadways Atmospheric Environment, 12, 823-829. [13] Luhar, A.K. and Patil, R.S. (1989) A General Finite Line Source Mode for Vehicular Pollution Prediction. Atmospheric Environment, 23, 555-562.
http://dx.doi.org/10.1016/0004-6981(89)90004-8 [14] Noll, E.K., Miller, T.L. and Claggett, M. (1978) A Comparison of Three Highway Line Source Dispersion Models. Atmospheric Environment, 12, 1323-1329.
http://dx.doi.org/10.1016/0004-6981(78)90072-0 [15] Csanady, G.T. (1972) Crosswinds Shear Effects on Atmospheric Diffusion. Atmospheric Environment, 6, 221-232.
http://dx.doi.org/10.1016/S0004-6981(72)80150-1 [16] Air Quality Monitoring Project-Indian Clean Air Programme (ICAP) (2008) Emission Factor Development for Indian Vehicles. ARAI, Pune. [17] Kumar, A. (2012) Urban Air Quality Modelling. M.Sc. Thesis, Center for Environmental Science and Engineering, IIT Bombay, Mumbai.
[1] Amundsen, A.H., Kl?boe, R. and Fyhri, A. (2008) Annoyance from Vehicular Air Pollution: Exposure-Response Relationships for Norway. Atmospheric Environment, 42, 7679-7688.
http://dx.doi.org/10.1016/j.atmosenv.2008.05.026 [2] Cheng, S., Lang, J., Zhou, Y., Han, L., Wang, G. and Chen, D. (2013) A New Monitoring-Simulation-Source Apportionment Approach for Investigating the Vehicular Emission Contribution to the PM2.5 Pollution in Beijing, China. Atmospheric Environment, 79, 308-316.
http://dx.doi.org/10.1016/j.atmosenv.2013.06.043 [3] Fan, X., Lam, K.C. and Yu, Q. (2012) Differential Exposure of the Urban Population to Vehicular Air Pollution in Hong Kong. Science of the Total Environment, 426, 211-219.
http://dx.doi.org/10.1016/j.scitotenv.2012.03.057 [4] Fenger, J. (2009) Air Pollution in the Last 50 Years—From Local to Global. Atmospheric Environment, 43, 13-22.
http://dx.doi.org/10.1016/j.atmosenv.2008.09.061 [5] Nagendra, S.M.S. and Khare, M. (2002) Line Source Emission Modelling. Atmospheric Environment, 36, 2083-2098.
http://dx.doi.org/10.1016/S1352-2310(02)00177-2 [6] Neema, M.N. and Jahan, J. (2014) An Innovative Approach to Mitigate Vehicular Emission through Roadside Greeneries: A Case Study on Arterial Roads of Dhaka City. Journal of Data Analysis and Information Processing, 2, 32-39.
http://dx.doi.org/10.4236/jdaip.2014.21005 [7] Province, H., Wang, L., Yang, J., Zhang, P., Zhao, X., Wei, Z., Zhang, F., Su, J. and Meng, C. (2013) A Review of Air Pollution and Control in Hebei Province. Journal of Data Analysis and Information Processing, 2, 47-55. [8] Sharma, N., Chaudhry, K.K. and Rao, C.V.C. (2004) Vehicular Pollution Prediction Modelling: A Review of Highway Dispersion Models. Transport Review, 24, 409-435.
http://dx.doi.org/10.1080/0144164042000196071 [9] Sivacoumar, R. and Thanasekaran, K. (1999) Line Source Model for Vehicular Pollution Prediction near Roadways and Model Evaluation through Statistical Analysis. Environmental Pollution, 104, 389-395.
http://dx.doi.org/10.1016/S0269-7491(98)00190-0 [10] Benson P.E. (1979) CALINE-3, a Versatile Dispersion Model for Predicting Air Pollutant Levels near Highways and Arterial Streets. FHWA/CA/TL-79/23, California Department of Transportation, Sacraments. [11] Petersen, W.B. (1980) Users Guide for HIWAY-2. Highway Air Pollution Model EPA-600/8-80-018. [12] Chock, D.P. (1978) A Simple Line-Source Model for Dispersion near Roadways Atmospheric Environment, 12, 823-829. [13] Luhar, A.K. and Patil, R.S. (1989) A General Finite Line Source Mode for Vehicular Pollution Prediction. Atmospheric Environment, 23, 555-562.
http://dx.doi.org/10.1016/0004-6981(89)90004-8 [14] Noll, E.K., Miller, T.L. and Claggett, M. (1978) A Comparison of Three Highway Line Source Dispersion Models. Atmospheric Environment, 12, 1323-1329.
http://dx.doi.org/10.1016/0004-6981(78)90072-0 [15] Csanady, G.T. (1972) Crosswinds Shear Effects on Atmospheric Diffusion. Atmospheric Environment, 6, 221-232.
http://dx.doi.org/10.1016/S0004-6981(72)80150-1 [16] Air Quality Monitoring Project-Indian Clean Air Programme (ICAP) (2008) Emission Factor Development for Indian Vehicles. ARAI, Pune. [17] Kumar, A. (2012) Urban Air Quality Modelling. M.Sc. Thesis, Center for Environmental Science and Engineering, IIT Bombay, Mumbai.