Air Pollution Dispersion Modeling from Point Sources Using Gaussian Plume Model: A Case Study of Kirkuk, Iraq
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Abstract
The present study models the dispersion of air pollutants from Kirkuk Oil Refinery to Kirkuk City. The study considers the impact of pollution type, wind speed, and wind direction on the dispersion patterns. The simulated pollutants concentrations were in μg/m3 to provide valuable knowledge of the pollution levels. The Gaussian plume model was used to simulate various pollutants’ air pollution concentrations produced by the refinery. The results showed a wide concentration range, i.e., from 1.19×10-28 μg/m3 to 11.26 μg/m3. The mean concentration was 0.46 μg/m3. Different wind directions caused a minimum concentration of 0 μg/m3, i.e., negligible or low pollution levels away from the emission source. The mean concentration slightly varied with the wind direction, i.e., from 8.37×10-3 to 8.56 ×10-3 μg/m3. In other words, the mean pollution levels remained adequately low regardless of the wind direction. On the other hand, the wind direction impacted the maximum concentration. At 235°, the highest maximum concentration was 23.807 μg/m3, and at 174°, the lowest maximum concentration was 9.28569 μg/m3. Also, the results regarding the pollutant revealed that Co2 showed the highest mean concentration, i.e., 5.321 μg/m3, and the highest maximum concentration, i.e., 6734.623 μg/m3. Gases, e.g., Co, No2, and So2, showed higher concentrations than PM1, PM2.5, PM5, and PM10, implying that atmospheric behavior and emission sources differ. These results expand understanding of the air pollution dispersion patterns and provide a clear vision for policymakers and environmental managers. Future works should focus on refining modeling approaches and utilizing real-time data to obtain accurate pollutant dispersion pattern predictions.
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