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Background & Aims of the Study: Air pollution is currently one of the most important industry challenges for countries. Much progress has been made in modeling air pollution, one of which is the AERMOD model, which is based on the Gaussian model. This study investigates the temporal changes of NO2 , SO2 , and CO pollutants emitted from the stack of turbines and gas furnaces of Maroon oil and gas facilities in Omidieh City, Iran. Materials and Methods: First, the concentration of pollutants was measured using a Testo x-350 analyzer with an average accuracy of ±3 ppm for all three pollutants in cold and hot seasons from 2018 to 2019. Each pollutant was measured 3 times for 15 minutes at 24-hour intervals. Then, the emission rate of each pollutant from the stack was obtained by calculations. The modeling was performed in 2500 Km2 by entering the emission rate data, technical specifications of the turbines and furnaces, and topographic and meteorological data into the AERMOD program. For validation, the concentrations of all three pollutants were measured by an aeroqual-200 analyzer with an accuracy of 0-25 ppm for CO, 0-1 ppm for NO2 , and 0-10 ppm for SO2 in 10 stations. Each pollutant was measured 3 times for 20 minutes at 24-hour intervals. The modeled results were then compared with the Iranian and US-EPA environmental standards and measurements. Results: The hourly concentrations for CO pollutants in hot and cold seasons were 102 μg/m3 and 156 μg/m3 , respectively, and less than the standard (40000 μg m3 ), SO2 1.18 μg/m3 and 1.78 μg/m3 and less than the standard (196 μg/m3 ), NO2 16 μg/m3 and 27 μg/m3 and less than the standard (200 μg/m3 ). The measured results were higher than the modeled ones. Conclusion: The results of the concentration of SO2 and NO2 pollutant gases showed a close agreement with the modeled results. The concentration of the produced pollutants was higher in the cold season than in the warm season due to reasons such as the increase in the volume of heavier compounds and moisture in the gases, as well as the decrease in the wind. AERMOD model had a good estimate in places where there was no background concentration of pollutant.