Abstract
Air quality modeling requires three types of input data viz. emission, meteorology and geographical information and it can help to distinguish the influence of these factors for air pollution. In this present study, a constant emission has been considered for a region and it has been applied in vehicular pollution modeling with various averaging time period of seasons for the year. Chembur, the most polluted area of Mumbai city (India) due to industrial and vehicular sources, has been selected for this study. Generally, temporal and spatial interpolated meteorological data are used in air quality modeling, which is collected from a nearby meteorological station. In this paper, AERMOD was processed with onsite meteorological data, derived from Weather Research and Forecasting (WRF) model. It was applied for a 1 day period and 1 month of winter and monsoon season and again for whole year 2011. The results of AERMOD showed interesting behavior of the model for different averaging times. There is a general understanding in air quality modeling that concentration decreases with increase in averaging time. In this study, the results show that the concentration decreases with increasing of averaging time in winter season while concentration increases with increasing of averaging time period in monsoon season. Also, WRF model has been used for simulating for a year successfully which saves enormous time and resources of collecting meteorological data from a station and gives good result.
Similar content being viewed by others
References
ARAI (2008) Air quality monitoring project-Indian clean air programme (ICAP): emission factor development for Indian Vehicles. ARAI, Pune
Benson PE (1979) CALINE-3, a versatile dispersion model for predicting air pollutant levels near highways and arterial streets. FHWA/CA/TL-79/23, Cal. Dept of Trans., Sacraments
Borge R, Alexandrov V, José del Vas J, Lumbreras J, Rodríguez E (2008) A comprehensive sensitivity analysis of the WRF model for air quality applications over the Iberian Peninsula. Atmos Environ 42:8560–8574. doi:10.1016/j.atmosenv.2008.08.032
Brunner D, Savage N, Jorba O, Eder B, Giordano L, Bianconi R, Chemel C, Badia A, Balzarini A, Bar R, Hirtl M, Hodzic A, Curci G, Forkel R, Jim P, Honzak L, Im U, Knote C, Makar P, Manders-groot A, Pirovano G, San R, Van Meijgaard E, Neal L, Juan LP, Tuccella P, Werhahn J, Wolke R, Yahya K, Zabkar R, Zhang Y, Hogrefe C, Galmarini S (2014) Comparative analysis of meteorological performance of coupled chemistry-meteorology models in the context of AQMEII phase 2. Atmos Environ 115:470–498
Chen L, Peng S, Liu J, Hou Q (2012) Dry deposition velocity of total suspended particles and meteorological influence in four locations in Guangzhou, China. J Environ Sci 24:632–639
Chock DP (1978) A simple line-source model for dispersion near roadways. Atmos Environ 12:823–829
Cimorelli AJ, Perry SG, Venkatram A, Weil JC, Paine RJ, Wilson Robert B, Lee RF, Peters WD, Brode RW, Paumier JO (2004) AERMOD: Description of model formulation. EPA-454/R-03-004, USEPA, USA
CPCB (2003) Guidelines for ambient air quality monitoring. In: National Ambient Air Qual Monitoring. NAAQMS, 2003–2004. Central Pollution Control Board, Ministry of Environment & Forests, Govt. of India, Delhi
Csanady GT (1972) Crosswind shear effects on atmospheric diffusion. Atmos Environ 6:221–232
Gidde MR, Sonawane PP (2012) Assessment of traffic related air pollution and ambient air quality of metropolitan cities (case study of Pune city). IOSR J Eng 2:1382–1390
Gokhale S (2011) Traffic flow pattern and meteorology at two distinct urban junctions with impacts on air quality. Atmos Environ 45:1830–1840. doi:10.1016/j.atmosenv.2011.01.015
Gupta I, Kumar R (2006) Trends of particulate matter in four cities in India. Atmos Environ 40:2552–2566. doi:10.1016/j.atmosenv.2005.12.021
Hogrefe C, Porter PS, Gego E, Gilliland A, Gilliam R, Swall J, Irwin J, Rao ST (2006) Temporal features in observed and simulated meteorology and air quality over the Eastern United States. Atmos Environ 40:5041–5055. doi:10.1016/j.atmosenv.2005.12.056
Skamarock WC, Klemp JB, Dudhia J, Gill DO, Barker DM, Duda MG, Huang, X-Y, Wang W, Powers JG (2008) A description of the advanced research WRF Version 3. NCAR Tech. Note NCAR/TN-45
Joseph A, Ad S, Srivastava A (2003) PM(10) and its impacts on health—a case study in Mumbai. Int J Environ Health Res 13:207–214
Kesarkar AP, Dalvi M, Kaginalkar A, Ojha A (2007) Coupling of the Weather Research and Forecasting Model with AERMOD for pollutant dispersion modeling. A case study for PM10 dispersion over Pune, India. Atmos Environ 41:1976–1988
Kumar A (2012) Urban air quality modeling, M.Sc. Thesis, Center for Environmental Science and Engineering, IIT Bombay, Mumbai
Kumar A, Dikshit AK, Fatima S, Patil RS (2015) Application of WRF model for vehicular pollution modelling using AERMOD. Atmos Clim Sci 5:57–62
Kumar A, Gupta I, Brandt J, Kumar R, Kumar A, Patil RS (2016a) Air quality mapping using GIS and economic evaluation of health impact for Mumbai city, India. J Air Waste Manag Assoc 4:XX–12
Kumar A, Patil RS, Dikshit AK, Islam S, Kumar R (2016b) 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. J Clean Prod 116:110–117. doi:10.1016/j.jclepro.2015.12.079
Kumar A, Patil RS, Dikshit AK, Kumar R (2016c) Air quality assessment using interpolation technique. EnvironmentAsia 9:140–149. doi:10.14456/ea.2010.32
Kumar A, Patil RS, Dikshit AK, Kumar R (2016d) Comparison of predicted vehicular pollution concentration with air quality standards for different time periods. Clean Technol Environ Policy. doi:10.1007/s10098-016-1147-6
Kumar A, Patil RS, Kumar A, Kumar R, Brandt J, Hertel O (2016e) Assessment of impact of unaccounted emission on ambient concentration using DEHM and AERMOD in combination with WRF. Atmos Environ 142:406–413. doi:10.1016/j.atmosenv.2016.08.024
Luhar AK, Patil RS (1989) A general finite line source mode for vehicular pollution prediction. Atmos Environ 23:555–562
Ma J, Yi H, Tang X, Zhang Y, Xiang Y, Pu L (2013) Application of AERMOD on near future air quality simulation under the latest national emission control policy of China: a case study on an industrial city. J Environ Sci 25:1608–1617. doi:10.1016/S1001-0742(12)60245-9
Mahalakshmi DV, Sujatha P, Naidu CV, Chowdary VM (2014) Contribution of vehicular emission on urban air quality: results from public strike in Hyderabad. Indian J Radio Sp Phys 43:340–348
Mcguire T, Noll KE (1971) Relationship between concentrations of atmospheric pollutants and averaging time. Atmos Environ 5:291–298
Mohan M (2011) Performance evaluation of AERMOD and ADMS-urban for total suspended particulate matter concentrations in Megacity Delhi. Aerosol Air Qual Res. doi:10.4209/aaqr.2011.05.0065
Mokhtar MM, Hassim MH, Taib RM (2014) Health risk assessment of emissions from a coal-fired power plant using AERMOD modeling. Proc Saf Environ Prot 92(5):476–485
NEERI (2010) Air quality assessment, emission inventory and source apportionment studies: Mumbai. Natl Environ Eng Res Inst CPCB, New Delhi
Noll EK, Miller TL, Claggett M (1978) A comparison of three highway line source dispersion models. Atmos Environ 12:1323–1329
O’Shaughnessy PT, Altmaier R (1994) 2011: use of AERMOD to determine a hydrogen sulfide emission factor for swine operations by inverse modeling. Atmos Environ 45:4617–4625. doi:10.1016/j.atmosenv.2011.05.061
Pan L, Yao E, Yang Y (2016) Impact analysis of traffic-related air pollution based on real-time traffic and basic meteorological information. J Environ Manag 183:1–11. doi:10.1016/j.jenvman.2016.09.010
Patankar AM, Trivedi PL (2011) Monetary burden of health impacts of air pollution in Mumbai, India: implications for public health policy. Public Health 125:157–164. doi:10.1016/j.puhe.2010.11.009
Petersen WB (1980) Users guide for HIWAY-2, High Air Pol Mod, EPA-600/8-80-018
Ritter M, Müller MD, Tsai MY, Parlow E (2013) Air pollution modeling over very complex terrain: an evaluation of WRF-Chem over Switzerland for two 1-year periods. Atmos Res 132–133:209–222. doi:10.1016/j.atmosres.2013.05.021
Russell A, Dennis R (2000) NARSTO critical review of photochemical models and modeling. Atmos Environ 34:2283–2324
Seaman NL (2000) Meteorological modeling for air-quality assessments. Atmos Environ 34:2231–2259
Seaman NL (2003) Future directions of meteorology related to air-quality research. Environ Int 29:245–252. doi:10.1016/S0160-4120(02)00183-6
Seangkiatiyuth K, Surapipith V, Tantrakarnapa K, Lothongkum AW (2011) Application of the AERMOD modeling system for environmental impact assessment of NO2 emissions from a cement complex. J Environ Sci 23:931–940. doi:10.1016/S1001-0742(10)60499-8
Sistla G, Zhou N, Hao W, Ku J-Y, Rao ST, Bornstein R, Freedman F, Thunis P (1996) Effects of uncertainties in meteorological inputs on urban airshed model predictions and ozone control strategies. Atmos Environ 30:2011–2025. doi:10.1016/1352-2310(95)00268-5
Srivastava A, Kumar R (2002) Economic valuation of health impacts of air pollution in mumbai. Environ Monit Assess 75:135–143
Su JG, Apte JS, Lipsitt J, Garcia-Gonzales DA, Beckerman BS, de Nazelle A, Texcalac-Sangrador JL, Jerrett M (2015) Populations potentially exposed to traffic-related air pollution in seven world cities. Environ Int 78:82–89. doi:10.1016/j.envint.2014.12.007
Thaker P, Gokhale S (2015) The impact of traffic-flow patterns on air quality in urban street canyons. Environ Pollut. doi:10.1016/j.envpol.2015.09.004
Varghese S, Langmann B, Ceburnis D, O’Dowd CD (2011) Effect of horizontal resolution on meteorology and air-quality prediction with a regional scale model. Atmos Res 101:574–594. doi:10.1016/j.atmosres.2011.02.007
Venkatram A, Cimorelli AJ (2007) On the role of nighttime meteorology in modeling dispersion of near surface emissions in urban areas. Atmos Environ 41:692–704
Wang KY, Shallcross DE, Hadjinicolaou P, Giannakopoulos C (2004) Ambient vehicular pollutants in the urban area of Taipei: comparing normal with anomalous vehicle emissions. Water Air Soil Pollut 156:29–55
WHO (2006) Air quality guidelines for particulate matter, ozone, nitrogen, dioxide and sulfur dioxide—summary of risk assessment WHO press
Zou B, Zhan FB, Wilson JG, Zeng Y (2010) Performance of AERMOD at different time scales. Simul Model Pract Theory 18:612–623
Author information
Authors and Affiliations
Corresponding author
Appendix 1
Appendix 1
(See Table 1).
Rights and permissions
About this article
Cite this article
Kumar, A., Patil, R.S., Dikshit, A.K. et al. Impact of seasonal meteorology and averaging time on vehicular pollution modeling. Int J Syst Assur Eng Manag 8 (Suppl 2), 1937–1944 (2017). https://doi.org/10.1007/s13198-017-0624-6
Received:
Revised:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13198-017-0624-6