Document Type : Original Article


Department of Environmental Engineering, College of Engineering, University of Tehran, Tehran, Iran


In this study, in 2011 for the duration of two months, the dispersion of a major air pollutant, sulfur dioxide from gas flares of an oil field, in Iran, was investigated. Due to the complexity of meteorological parameters in modeling area, California Puff (CALPUFF) model was used in this study. CALPUFF is a more advanced model than AERMOD which considers the effects of meteorological parameters in coastal areas, which was applied with meteorological and geophysical parameters produced by the Weather Research and Forecasting (WRF) model for the selected days of modeling period to investigate the impact of these parameters on modeling results. Since there is no option in the model for flares, flare parameters including emission rate and effective height and diameter were calculated based on EPA method to simulate better the real condition of flaring. Simulation results revealed that CALPUFF model could adequately express the effect of meteorological condition on results of modeling in each hour of the simulation period. The results of the simulation showed that low-height flares have the most impact on the ground level concentration of air pollutant on the island. The effects of elevated flares were at a far distance from flaring activity and mostly occurred outside of the island. CALPUFF model showed excellent compatibility with meteorological data produced by WRF and could properly account for the effect of meteorological and terrain parameters on dispersion modeling.


 1.     Soltanieh, M., Zohrabian, A., Gholipour, M.J. and Kalnay, E., 2016. A review of global gas flaring and venting and impact on the environment: Case study of Iran. International Journal of Greenhouse Gas Control49, pp.488-509.
2.     Umukoro, G.E. and Ismail, O.S., 2017. Modelling emissions from natural gas flaring. Journal of King Saud University-Engineering Sciences29(2), pp.178-182.
3.     Martin, J., Lumbreras, J. and Rodríguez, M.E., 2003. Testing flare emission factors for flaring in refineries. In 12th Annual Emission Inventory Conference, San Diego, USA, pp.1-7.
4.     Tuaycharoen, P., Wongwises, P., Aram, R.P. and Satayopas, B., 2008. Nitrogen Oxide (NOx) dispersion model for Khanom power plant area. In International conference on environmental research and technology (ICERT 2008), Penang, Malaysia, pp.653-657.
5.     De Melo, A.M.V., Santos, J.M., Mavroidis, I. and Junior, N.C.R., 2012. Modelling of odour dispersion around a pig farm building complex using AERMOD and CALPUFF. Comparison with wind tunnel results. Building and Environment56, pp.8-20.
6.     Abdul-Wahab, S.A., Al-Hajri, A. and Yetilmezsoy, K., 2016. Impact of the ambient air quality due to the dispersion of non-methane organic compounds from Barka Landfill. International journal of environmental science and technology13(4), pp.1099-1108.
7.     Holnicki, P., Kałuszko, A. and Trapp, W., 2016. An urban scale application and validation of the CALPUFF model. Atmospheric Pollution Research7(3), pp.393-402.
8.     Indumati, S., Oza, R.B., Mayya, Y.S., Puranik, V.D. and Kushwaha, H.S., 2009. Dispersion of pollutants over land–water–land interface: Study using CALPUFF model. Atmospheric Environment43(2), pp.473-478.
9.     Nagendra, S.S., Diya, M., Chithra, V.S., Menon, J.S. and Peter, A.E., 2016. Characteristics of air pollutants at near and far field regions of a national highway located at an industrial complex. Transportation Research Part D: Transport and Environment, 48, pp.1-13.
10.   Yang, D., Wang, Z. and Zhang, R., Estimating Air Quality Impacts of Elevated Point Source Emissions in Chongqing, China. Aerosol and Air Quality Research, 8(3), pp.279-294.
11.   Kesarkar, A.P., Dalvi, M., Kaginalkar, A. and 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. Atmospheric Environment41(9), pp.1976-1988.
12.   Abdul-Wahab, S.A., Ali, S., Sardar, S., Irfan, N. and Al-Damkhi, A., 2011. Evaluating the performance of an integrated CALPUFF-MM5 modeling system for predicting SO2 emission from a refinery. Clean Technologies and Environmental Policy13(6), pp.841-854.
13.   Ghannam, K. and El-Fadel, M., 2013. Emissions characterization and regulatory compliance at an industrial complex: an integrated MM5/CALPUFF approach. Atmospheric Environment69, pp.156-169.
14.   Wu, H., Zhang, Y., Yu, Q. and Ma, W., 2018. Application of an integrated Weather Research and Forecasting (WRF)/CALPUFF modeling tool for source apportionment of atmospheric pollutants for air quality management: A case study in the urban area of Benxi, China. Journal of the Air & Waste Management Association68(4), pp.347-368.
15.   Pazoki, M. and Hasanidarabadi, B., 2017. Management of toxic and hazardous contents of oil sludge in Siri Island. Global Journal of Environmental Science and Management3(1), pp.33-42.
16.   Iranian offshore oil company (IOOC) 2018. Available: [Accessed].
17.   Scire, J.S., Strimaitis, D.G. and Yamartino, R.J., 2000. A User’s Guide for the CALPUFF Dispersion Model (Version 5), Earth Tech.
18    Ep-d, E. C. N., Brashers, B. and Emery, C. 2013. The Mesoscale Model Interface Program (MMIF) Version 3.0, 2013-09-30.
19.   Azadi, M., Shirgholami, M.R., Hajjam, S. and Sahraian, F., 2012. WRF Model Output Postprocessing for Daily Precipitation over Iran. Iran-Water Resources Research, 7(4), pp.71-81.
20.   Cimorelli, A.J., Perry, S.G., Venkatram, A., Weil, J.C., Paine, R.J., Wilson, R.B., Lee, R.F., Peters, W.D. and Brode, R.W., 2005. AERMOD: A dispersion model for industrial source applications. Part I: General model formulation and boundary layer characterization. Journal of applied meteorology44(5), pp.682-693.
21.   Brode, R. W., 1995. SCREEN 3 Model User's Guide. NASA 19980015351.
22.   Leahey, D.M. and Davies, M.J.E., 1984. Observations of plume rise from sour gas flares. Atmospheric Environment, 18(5), pp.917-922.