A Comprehensive Research of Air Quality Modeling Methods: A Case Study Kirkuk, Iraq

Abstract

This review presents a clear comparison of the most popular air quality modeling techniques. The main aims of the review were to compare the generally applied air quality modelling methods regarding assumptions, data demand, and applicability, assess how they can be used in urban areas with limited data, and to support the choice of the Box Model BM to assess air quality in Kirkuk, Iraq. The reviewed modeling approaches were Gaussian Dispersion Models GDM and Lagrangian Models LM of point source emissions in meteorological inputs. Computational Fluid Dynamics CFD and Eulerian Grid Models EGM to perform the high-resolution spatial and temporal analysis. The BM simplified model incorporates homogeneous mixing of pollutants in a given volume. The BM was used in this research to estimate the pollutant levels in Kirkuk, which allows referring to its limitations in combination with the Air Quality Index AQI analysis. The findings on the relevance of the BM in Kirkuk indicate that it can be utilized in initial analyses and rapid scenario testing in cities with limited data. Although the spatial detail is lower, it gives quite satisfactory pollutant estimates in combination with the analysis of AQI. Comparison indicates that BM is a relevant policy and cost-effective tool with minimal data access used to support air quality management in Kirkuk.