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first_pagesettingsOrder Article Reprints Open AccessArticle Application of WRF-Chem and HYSPLIT Models for Dust Storm Analysis in Central Iran (Case Study of Isfahan Province, 21–23 May 2016) by Farshad Soleimani Sardoo 1,*,Nasim Hossein Hamzeh 2 andNir Krakauer 3 1 Department of Natural Engineering, Faculty of Natural Resources, University of Jiroft, Kerman 78671-55311, Iran 2 Air and Climate Technology Company (ACTC), Tehran 15996-16313, Iran 3 Department of Civil Engineering, The City College of New York, New York, NY 10031, USA * Author to whom correspondence should be addressed. Atmosphere 2025, 16(4), 383; https://doi.org/10.3390/atmos16040383 Submission received: 21 January 2025 / Revised: 18 March 2025 / Accepted: 20 March 2025 / Published: 27 March 2025 (This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling) Downloadkeyboard_arrow_down Browse Figures Versions Notes Abstract Dust is one of the most important problems of human societies in arid and semi-arid areas. This study analyzed the rising and propagation of the dust storm occurring from 21 to 23 May 2016 in Isfahan province (Central Iran) by using the WRF-Chem and HYSPLIT models. The dust storm was visualized using visible imagery and coarse-mode aerosol optical depth data from satellite sensor data, and dust emission and transport were simulated for Central Iran by using WRF-Chem with the AFWA and GOCART schemes. The results show that the dust concentration in Sistan and Baluchistan province and the Persian Gulf was as high as 2000 µg/m3, and both schemes estimate the highest amount of dust emissions from the central parts of Iran and the eastern part of Isfahan province. PM10 data of Yazd station was used to verify the model outputs, which showed that the AFWA dust scheme has a higher correlation coefficient with observations (0.62) than the GOCART dust scheme. This case study suggests that WRF-Chem dust schemes simulate dust rising and propagation in Central Iran with reasonably good reliability, though further determination and enhancement are still required for an accurate prediction of dust concentration and extents.