Application of Remote Sensing and Spatial Fuzzy Multi-criteria Decision Analysis to Identify Potential Dust Sources in Lake Urmia Basin, Northwest Iran

Air pollution as a result of desertification and dust transportation is one of the critical environmental challenges in the arid and semi-arid regions. Urmia Lake, the largest inland lake of Iran has lost most of its water over the past 2 decades. The lake bed is known as one of the aerosol pollution sources in the northwestern Iran. Although recent studies contributed to investigate the impacts of the drying up of Urmia Lake on the local and regional air quality, there is still a need to identify spatiotemporal aerosol pollution and dust generation sources in the study area. In this study, remote sensing techniques, fuzzy logic and Principal Component Analysis (PCA) were used to identify dust hot spots in the south and east parts of the Lake, where recent studies have highlighted the dramatic extent of salinization and desertification. Based on the results of this study, the lake's contribution to the local aerosol pollution declines with increasing distance from it. The results indicated that the potential of dust forming on the east side of the lake has increased, presenting a variety of challenges for inhabitants, including health and biological hazards. The fuzzy results have a high correlation with Electrical Conductivity (EC) (0.69), Aerosol Optical Depth (AOD) (0.46), and Leaf Area Index (0.45), respectively, while wind speed (0.22) and slope (0.24) have the lower correlation. The results of PCA indicate that AOD, Digital Elevation Model, and EC have the highest percentage in identifying dust generation sources among the effective parameters in determining dust production sources.