A new application of multi-criteria decision making in identifying critical dust sources and comparing three common receptor-based models

Abstract

Dust storms are a common phenomenon in arid and semi-arid regions in West Asia, which has led to high levels of PM10 in local and remote area. The Yazd city in Iran with a high PM10 level located downstream of dust sources in the Middle East and Central Asia. In this study, based on meteorological and PM10 monitoring data, backward trajectory modeling of air parcels related to dust events at Yazd station was performed using the HYSPLIT model in 2012–2019. The trajectory cluster analysis was used to identify the main dust transport pathways and wind systems. Three methods of Cross-referencing Backward Trajectory (CBT), Potential Source Contribution Function (PSCF) and Concentration Weighted Trajectory (CWT) were used to identify the most critical dust sources. Multi-Criteria Decision Making (MCDM) methods were also used to integrate the results. Nine dust sources affecting central Iran were determined, and six criteria from different aspects were considered. To prioritize the dust sources affecting central Iran from four new MCDM methods, including WASPAS, EDAS, ARAS and TOPSIS were used. The results showed that the Levar wind system (51%), the Shamal wind system (32%) and the Prefrontal wind system (18%) were the most important wind systems to cause dust events in central Iran. The MCDM approach to identify dust sources also showed that Dasht-e-Kavir in central Iran was the most critical dust source. The results also showed that in hot seasons (spring and summer), local and Central Asia dust sources and cold seasons (autumn and winter), Middle East dust sources have the greatest impact on dust events in central Iran. Also, a comparison of common receptor-based methods for identifying dust sources showed that CBT, CWT and PSCF were the most appropriate methods for identifying dust sources, respectively.