Air Quality Evaluation Using Gaussian Plume Model and GIS at Gas Flaring Region in Kirkuk City, Iraq

Document Type : Original Research Paper

Authors

1 Department of Surveying Engineering Techniques, Technical Engineering College of Kirkuk, Northern Technical University, Kirkuk, Iraq

2 Department of Architecture and Construction Engineering Techniques, Technical Engineering College of Kirkuk, Northern Technical University, Kirkuk, Iraq

10.22059/poll.2025.394086.2902

Abstract

Gas flaring continues as an environmental issue across oil-producing regions since it generates air pollution and climate change conditions. The purpose of the research is to examine, and compare the spatial distribution of deterioration of air quality, the environmental and health risks within the poor air quality area close to the gas flaring location and assess the density of gases and pollutants produced using the Gaussian-Plume model (GPM). Geographic Information Systems GIS technology has been combined with GPM in dispersion modeling. The gases produced by gas flaring to be emitted include sulfur dioxide (SO2), Nitrogen dioxide (NO2), and particulate matter (PM). Such pollutants worsen the quality of air and, therefore, are harmful to the health of the surrounding communities. Findings demonstrate that pollution intensities increase the most in locations proximate to flaring sites since atmospheric factors govern the way pollutants disperse. The GPM indicates that pollution concentrations decrease as distance increases from the sources. While some areas near the flare still contain unsafe levels, even in inhabited sections. Strict regulations with improved monitoring, together with cleaner technologies, must be adopted. This is for reducing the environmental and health effects of gas flaring in Kirkuk. This paper adds to the environmental sustainability investigation by proving the power of GIS-based spatial analysis and dispersion modeling for monitoring air pollution variations at different locations. The research produces a combination of strategies that use GIS-based approaches in decision-making as well as dispersion modeling to inform better policymaking on environmental matters related to gas flaring. 

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Main Subjects

References

Agbonifo, P. E., Shafeeq, O., Abdal, G., & Bhatti, U. (2024). Gas Flaring and its Socioeconomic Implications for Rural Communities in Kurdistan Region of Iraq (KRI): Reflections on the Impact of Gas Flaring in Tawke Community. Journal of Ecohumanism, 3(7), 4076-4089.
Ajaj, Q. M., Awad, N. A., Jumaah, H. J., & Rizeei, H. M. (2025). Air quality regression analysis over Iraq during severe dust periods using GIS and remotely sensed PM2. 5. DYSONA-Applied Science, 6(2), 300-308.
Ajaj, Q. M., Mohd Shafri, H. Z., Ramli, M. F., & Wayayok, A. (2023). Prediction of Air Pollutants Concentration Emitted from Kirkuk Cement Plant Based on Deep Learning and Gaussian Equation Outputs. Pollution, 9(2), 810-820.
Ajaj, Q. M., Shafri, H. Z. M., & Ramli, A. W. A. F. (2022). Common Analysis Methods for Gaseous and Solid Contaminants Emitted from Different Pollution Sources: a Review Paper. Poll Res. 441 (2), 416-439.
Ameen, M. H., Azmi, M., & Jumaah, H. J. (2025). Evaluating exposure to road traffic air and noise pollution: A comprehensive review of assessment methods. Tikrit Journal of Engineering Sciences, 32(2), 1-19.
Ameen, M. H., Jumaah, H. J., Kalantar, B., Ueda, N., Halin, A. A., Tais, A. S., & Jumaah, S. J. (2021). Evaluation of PM2.5 particulate matter and noise pollution in Tikrit University based on GIS and statistical modeling. Sustainability, 13(17), 9571.
Anejionu, O. C., Whyatt, J. D., Blackburn, G. A., & Price, C. S. (2015). Contributions of gas flaring to a global air pollution hotspot: Spatial and temporal variations, impacts and alleviation. Atmospheric Environment, 118, 184-193.
Arshad, K., Hussain, N., Ashraf, M. H., & Saleem, M. Z. (2024). Air pollution and climate change as grand challenges to sustainability. Science of The Total Environment, Volume 928, 172370. https://doi.org/10.1016/j.scitotenv.2024.172370
Hamed, H. H., Jumaah, H. J., Kalantar, B., Ueda, N., Saeidi, V., Mansor, S., & Khalaf, Z. A. (2021). Predicting PM2. 5 levels over the north of Iraq using regression analysis and geographical information system (GIS) techniques. Geomatics, Natural Hazards and Risk, 12(1), 1778-1796.
Hesketh, H. D. (2023). Air pollution control: traditional hazardous pollutants. CRC Press.
Jamal Jumaah, H., Ghassan Abdo, H., Habeeb Hamed, H., Mohammed Obaid, H., Almohamad, H., Abdullah Al Dughairi, A., & Saleh Alzaaq, M. (2023). Assessment of corona virus (COVID-19) infection spread pattern in Iraq using GIS and RS techniques. Cogent Social Sciences, 9(2), 2282706.
Jumaah, H. J., & Kamran, K. V. (2024). AQI-based box model using GIS and remote sensing over Kirkuk city, Iraq. Advanced Engineering Days, 9, 144-146
Jumaah, H. J., Ameen, M. H., Mahmood, S., & Jumaah, S. J. (2023). Study of air contamination in Iraq using remotely sensed Data and GIS. Geocarto International, 38(1), 2178518.
Jumaah, H. J., Ameen, M. H., Mohamed, G. H., & Ajaj, Q. M. (2022). Monitoring and evaluation Al-Razzaza lake changes in Iraq using GIS and remote sensing technology. The Egyptian Journal of Remote Sensing and Space Science, 25(1), 313-321.
Jumaah, H. J., Dawood, M. A., & Mahmood, S. (2024). Estimating Chemical Concentrations of Dust PM2. 5 in Iraq: A Climatic Perspective Using Polynomial Model and Remote Sensing Technology. Journal of Atmospheric Science Research| Volume, 7(03), 44-56.
Jumaah, H. J., Hasan, W. A., & Jumaah, S. J. (2025). A Regional Investigation of Inverse Distance Weighting Particulate Matter Prediction within Kirkuk City, Iraq. Int. J. Econ. Environ. Geol. Vol, 16(1), 5-13.
Khan, S., & Hassan, Q. (2020). Review of developments in air quality modelling and air quality dispersion models. Journal of Environmental Engineering and Science, 16(1), 1-10.
Kumar, A., Somani, V., Purohit, P. K., & Amarawat, G. Comprehensive Study of Computational Methodologies for Air Pollution Control (2025). In Computational Techniques in Environmental Engineering (pp. 21-37). CRC Press.
Lindvall, T. (1985). Recommendations for air quality standards for nitrogen dioxide and ozone. Scandinavian Journal of Work, Environment & Health, Vol. 11, 3-9.
Liu, H., Gao, P., Xiang, S., Zhu, H., Chen, J., & Fu, Q. (2025). A Python toolkit for integrating geographic information system into regulatory dispersion models for refined pollution modeling. Environmental Modelling & Software, 183, 106219.
Mahmood, M. R., & Jumaah, H. J. (2023). NBR index-based fire detection using sentinel-2 images and GIS: A case study in mosul park, Iraq. International Journal of Geoinformatics, 19(3), 67-74.
Mahmood, M. R., Abrahem, B. I., Jumaah, H. J., Alalwan, H. A., & Mohammed, M. M. (2025). Drought monitoring of large lakes in Iraq using remote sensing images and normalized difference water index (NDWI). Results in Engineering, 25, 103854. https://doi.org/10.1016/j.rineng.2024.103854 
Mahmood, S., Ali, A., & Jumaah, H. J. (2024). Geo-visualizing the hotspots of smog-induced health effects in district Gujranwala, Pakistan: a community perspective. Environmental Monitoring and Assessment, 196(5), 457.
Mills, R. (2018). A new hope: Iraq oil’s way forward. Al-Bayan Center Publications Series, Iraq. https://qamarenergy.com/sites/default/files/A%20New%20Hope-%20IRAQ%20-%20FINAL.pdf 
Mohammadi, M., Mohammadi, M., & Moezzi, S. M. M. (2025). Air pollution meteorology and dispersion. In Air Pollution, Air Quality, and Climate Change (pp. 51-82). Elsevier. https://doi.org/10.1016/B978-0-443-23816-1.00007-0 
Nasehi, S., & Nohegar, A. (2025). Analyzing the relationship between spatial distribution of air pollutant concentrations and land cover over Iran. Pollution, 11(2), 246-260.‏
Nuckols, J. R., Ward, M. H., & Jarup, L. (2004). Using geographic information systems for exposure assessment in environmental epidemiology studies. Environmental health perspectives, 112(9), 1007-1015.
Obi, N., Akuirene, A., Bwititi, P., Adjene, J., & Nwose, E. U. (2021). Impact of gas flaring on communities in Delta region of Nigeria, narrative review part 1: environmental health perspective. International Journal of Scientific Reports, 7(3), 186-193.
Ogele, F. O. (2016). Governance of oil and gas sector in Nigeria: implications for biodiversity and ecosystem services in the Niger Delta region (Doctoral dissertation, Newcastle University). http://theses.ncl.ac.uk/jspui/handle/10443/3541
Oyewunmi, T. (2021). Natural gas in a carbon-constrained world: Examining the role of institutions in curbing methane and other fugitive emissions. LSU J. Energy L. & Resources, 9, 87.
Patel, J., Sharma, N., & Mohan, S. (2025). Introduction to Remote Sensing and GIS. In Smart Buildings and Cities with Remote Sensing and GIS (pp. 3-34). Chapman and Hall/CRC.
S Altraiki, M., Sharif, A., F Alnaas, J., & O Kratim, M. (2024). A Flare gas recovery unit for refineries in Libya: Innovative technologies are a step towards a sustainable environment (zero flare in 2030).
Saleh, S. H. (2024). Assessment of Air Pollutants for Baba Industrial Area at Kirkuk Oil Field, Iraq. The Iraqi Geological Journal, 125-137.
Shabbir, A. (2024). Environmental Degradation and Smog: Assessing the Governance Mechanism in Lahore. Journal of Climate and Community Development, 3(2), 232-243.
Snoun, H., Krichen, M., & Chérif, H. (2023). A comprehensive review of Gaussian atmospheric dispersion models: current usage and future perspectives. Euro-Mediterranean Journal for Environmental Integration, 8(1), 219-242.
Stockie, J. M. (2011). The mathematics of atmospheric dispersion modeling. Siam Review, 53(2), 349-372.
Tikle, S., Anand, V., & Das, S. (2024). Geospatial practices for airpollution and meteorological monitoring, prediction, and forecasting. In Geospatial Practices in Natural Resources Management (pp. 549-566). Cham: Springer International Publishing.
Valle, M., Cardona, J. A., & Viloria-Nuñez, C. (2025). Predicting Atmospheric Dispersion of Industrial Chemicals Using Machine Learning Approaches. IEEE Access.Vol. 13, 47587-47604.
Walters, K., Jacobson, J., Kroening, Z., & Pierce, C. (2015). PM2. 5 airborne particulates near frac sand operations. Journal of environmental health, 78(4), 8-12.
Whittle, M., & Ong, J. M. (2024). Global Literature and the Environment. Taylor & Francis.
Yerramilli, A., Dodla, V. B. R., & Yerramilli, S. (2011). Air pollution, modeling and GIS based decision support systems for air quality risk assessment. Advance air pollution, 295-324.
Pollution
Volume 11, Issue 4
October 2025
Pages 1447-1461

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