TY - JOUR ID - 97334 TI - Impact of Meteorological Parameters on Dispersion Modeling of Sulfur Dioxide from Gas Flares (Case Study: Sirri Island) JO - Iranica Journal of Energy & Environment JA - IJEE LA - en SN - 2079-2115 AU - Mirrezaei, M. A. AD - Department of Environmental Engineering, College of Engineering, University of Tehran, Tehran, Iran Y1 - 2019 PY - 2019 VL - 10 IS - 4 SP - 288 EP - 295 KW - California Puff Model KW - Flares KW - Meteorological data KW - Oil Field KW - Simulation KW - Weather Research and Forecasting DO - 10.5829/ijee.2019.10.04.10 N2 - 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. UR - https://www.ijee.net/article_97334.html L1 - https://www.ijee.net/article_97334_73339feacb059f501434c7cc22338542.pdf ER -