Document Type : Original Article


1 Islamic Republic of Iran meteorological organization

2 Bushehr meteorology organization

3 Assistant Professor/Atmospheric science and meteorological research center

4 Lorestan meteorology organization



Introduction: Natural hazards such as floods, earthquakes, landslides, etc. frequently occur in Iran and other parts of the world, causing considerable economic, social, and environmental problems. In recent years, dust outbreaks in the west and southwest of Iran have been rising, becoming one of the most important environmental challenges in the region.

Material and methods: In this research, a number of intense dust episodes have been selected out of 15 years (2004-2018) of the statistical period, in the warm and cold seasons over the western and southwestern parts of the country. At the first step, in order to detect and observe the intensity of the dust concentration over the study area, the MODIS AOD product from the Deep blue and Dark target algorithms has been analyzed using the ENVI software, and the generated images have been displayed in the ArcGIS software. In the second step, dust source detection has been carried out by the WRF/Chem simulation of the dust concentration and tracking the dust path using the HYSPLIT Lagrangian model.

Results and discussion: The results of the simultaneous study of dust detection using satellite imagery, the simulation of dust concentration using the WRF-Chem coupled model, and the particle movement pattern with the HYSPLIT model showed that East of Syria and northern Iraq in the case studies of the warm season and the west and center of Iraq in the case studies of the cold season are the main sources of dust episodes in the west and southwest of Iran.
Conclusion: Studying the source and transport of dust with the aid of WRF-Chem simulations and the HYSPLIT Lagrangian model provided a complementary decision making to predict the direction of dust motions and using the results in the air quality prediction and management.


Abdolkhani, A, 2010. Detection and classification of dust masses over the south western Iran, using remote sensing and GIS, M.Sc. Thesis. Shahid Chamran University of Ahvaz, Department of Geology, Faculty of Remote Sensing and GIS (In Persian with English abstract).
Ackerman, S.A., 1997. Remote sensing serosols using satellite infrared observations. Journal of Geophysical Research. Vol. 102, No. D14, 17069-17080
Ackerman, S.A., 1989. Using the radiative temperature difference at 3.7μm and 11μm to trace dust outbreaks. Remote Sensing Environment. 27, 129-133.
Adeli, Sh; Amini, V; Abdsherafat, A; 2012. Investigation of dust storms using the Modis data, case study: East Azerbayjan. First national conference of the approaches to sustainable development, Tehran, March 14, 2003; [in persian]
Adhami, S., 2006. fundamentals of of image processing with the ERDAS Software, Omid Mehr publications, Sabzevar [in persian]
Aliabadi, K; Asadi, M; Dadashi, A, 2015. Monitoring and investigation of dust storms using remote sensing, case study: west and south west of Iran. Journal of rescuing. Vol 7, No 1 [in persian]
Alizadeh Choobari, O., Zawar-Reza, P. and Sturman, A. 2014. The wind of 120 days and dust storm
activity over the Sistan Basin. Journal of Atmospheric Research. 143, 328-341.
Ansari, H, Serajian, H; Akhundzadeh, M., 2005. investigation of Modis data to identify the particulae matters (case study of Alborz Province). second national conference of geographic information systems, K. N. Toosi University of Technology [in persian]
Azizi, Gh, Miri, M, Nabavi, S, 2012. Detection of dust storms in western Iran; Geographical studies of arid regions. No 7, 63-81 [in persian]
Bensana, E., Lemaitre, M. and Verfaillie, G., 1999. Earth observation satellite management. Constraints, 4(3), 293-299.
Darvishi, A; Nabavi, A; Azizi, R; Dehghani, M., 2012. Determination of dust sources in western Iran using remote sensing techniques, wind trajectory, and investigation of the region’s local features. First international conference of combatting dust storms and its adverse effects. The university of agricultur and natural resources, Ramin, Khuzestan [in persian]
Draxler, Ronald.R., Hess, G.D., 1998. An overview of the HYSPLIT_4 modelling system for trajectories, dispersion, and deposition. Australian Meteorological Magazine 47, 295e308.
Ensafi-moghaddam, T; Khoshakhlagh, F; Shamsipour, A, Akhavan, R; 2006; Monitoring and assessment of dust impact on the rain variations over south-west of Iran, using remote sensing and GIS. Journal of remote sensing and GIS. Vol 9, No 2, 79-98 [in persian]
Foroushani, A., Opp, M., Groll, C., and Nikfal, A., 2020. Evaluation of WRF-Chem Predictions for Dust Deposition in Southwestern Iran. Atmosphere. 11(7), 757.
Ginoux, P., Prospero, J M., Gill, T E., Hsu, N C. and Zhao M., 2012. Global‐scale attribution of anthropogenic and natural dust sources and their emission rates based on MODIS Deep Blue aerosol products. Reviews of Geophysics, No: 50.
Hamish, M., Andrew, C, 2008. Identification of dust transport pathways from Lake Eyre, Australia using Hysplit. Atmospheric Environment. 42, 6915- 6925.
Hsu, N.C.; M. Jeong, C. Bettenhausen, AM. Sayer, R. Hansell, C. Seftor, J. Huang, and S.C. Tsay. 2013. Enhanced Deep Blue aerosol retrieval algorithm: The second generation. J. Geophys. Res. Atmos., 118, 9296–9315. DOI 10.1002/jgrd.50712
Karegar, E., Bodagh Jamali, J., Goshtasb, H., Ranjbar Saadat Abadi, A. and Moeinaddini, M., 2017. Numerical simulation of extreme sand and dust storm in east of Iran, by the WRF_Chem model case study; 1 may & 1 June 2011. Journal of Natural Environment. 69(4), 1077-1089.
Karimi, Kh, Taheri, H, Habibi, H, Hafez, N; 2011. detection of dust sources in the Middle East using remote sensing; Journal of climatology. Vol 2, No 7-8, 57-72 [in persian]
Kheirandish, Z., Bodagh, J.J. and Rayegani, B., 2018. Identification of the best algorithm for dust detection using MODIS data.
Klingmüller, K.; A. Pozzer; S. Metzger; G.L. Stenchikov, and J. Lelieveld. 2016. Aerosol optical depth trend over the Middle East. Atmospheric Chemistry and Physics. 16, 5063-5073.
Li, L. and Sokolik, I.N., 2018. Analysis of dust aerosol retrievals using satellite data in Central Asia. Atmosphere. 9(8), 288.
Marticorena, B. and Bergametti, G., 1995. Modeling the atmospheric dust cycle: 1. Design of a soil‐derived dust emission scheme. Journal of geophysical research: atmospheres. 100(D8), 16415-16430.
Miller, S. D., 2003. A Consolidated Technique for Enhancing Desert Dust Storms With MODIS, Geophysical Research Letters. Vol. 30, No. 20, 2071-4.
Mofidi, A; Jafari, S, 2011. Investigation of the atmosphere’s regional circulation over the Middle East in the summer-time dust storms of south-western Iran; Georaphical studies of the arid regions. No 5, 40-45 [in persian]
Nikfal, A; Rnajbar, A; Karami, S; Sehatkashani, S., 2016. The capabilities of the WRF-Chem model in ther prediction of dust concentration (case study: Tehran’s dust storm), Journal of environmental science, Shahid Beheshti University. Vol 15, No 1, 115-126 [in persian]
Rangzan, K; Zarasvandi, A; Abdolkhani, A; Mojaradi, B., 2014. Air qualiy modeling with the Modis images, case study: Khuzestan’s dust storms. Journal of advanced applied geology. No 14, 38-45 [in persian]
Rasouli, A, 2008; Fundamentals of remote sensing, with an emphasis on satellite images, University of Tabriz publication [in Persian]
Rayegani, B., Barati, S., Goshtasb, H., Gachpaz, S., Ramezani, J. and Sarkheil, H., 2020. Sand and dust storm sources identification: A remote sensing approach. Ecological Indicators. 112, 106099.
Rezazadeh, M., Irannejad, P. and Shao, Y., 2013. Climatology of the Middle East dust events. Aeolian Research. 10, 103-109.
Shi Y, Zhang J, Reid J, Hyer E, Hsu N. 2013. Critical evaluation of the MODIS Deep Blue aerosol optical depth product for data assimilation over North Africa. Atmospheric Measurement Techniques. 6(4), 949-969.
Sorek-Hamer, M.; I. Kloog; P. Koutrakis; A.W. Strawa; R. Chatfield; A. Cohen; W.L. Ridgway, and D.M. Broday, 2015. Assessment of PM 2.5 concentrations over bright surfaces using MODIS satellite observations. Remote Sensing of Environment. 163, 180-185.