Temporal and Spatial Variations of Dust Days in Western Azarbaijan Province, Determination of The Influencing Factors and Source of Events

Document Type : Original Article

Authors

1 Assistant Professor, Soil Conservation and Watershed Management Research Department, West Azarbaijan Agricultural and Natural Resources Research and Education Center, AREEO, Urmia, Iran.

2 PhD, Faculty of Natural Resources, University of Tehran, Karaj, Iran.

3 Assistant Professor, Soil Conservation and Watershed Management Research Department, Kurdistan Agricultural and Natural Resources Research and Education Center, AREEO, Sanandaj, Iran.

4 Research Expert, Soil Conservation and Watershed Management Research Department, West Azarbaijan Agricultural and Natural Resources Research and Education Center, AREEO, Urmia, Iran.

Abstract

In addition to the increase in prone areas to wind erosion processes in western Azarbaijan province due to the drying of Lake Urmia, there is a growing concern regarding the intensification of dust storms. Considering the impacts of this phenomenon on the environment, public health, agriculture, and transportation sections, more detailed studies on its source, severity, and frequency is necessary. Therefore, this study was designed to assess the temporal and spatial changes of dust storm events using satellite data, to detect the dust source, and to analyze the factors affecting the occurrence of dust storms in western Azarbaijan province. Analysis of the number of dusty days using the MODIS-AOD product indicated that the years 2003, and 2008 to 2012 were the dust storm peaks during the period 2000-2020 at western Azarbaijan province. Most dust storm events have occurred in summer and spring seasons, and monthly changes indicate the maximum dust storm between March and October. Trend analysis indicated that there was no significant trend in AOD and dust storm events. Among vegetation and climate variables, there is a significant relationship between AOD and wind speed (i.e., the correlation is about 64%). Spatially, dust storms occur more frequently along the shores of Urmia Lake (mostly in the east and south and slightly in the west).  Southern areas of the province reported a higher frequency of dust event than the central and northern parts of the province.  Due to the direction of the prevailing wind, it seems to be most affected by dust storms coming from the neighboring country of Iraq, however, the areas around the Lake Urmia are the inner source of dust storms.

Keywords


  1. Al-Dabbagh, S. K. (2020). The use of aerosol optical properties in identification of dust sources in Iraq. Physics: Conference Series,1660(1), 012049.
  2. Arjmand, M., Rashki, A., & Sargazi, H. (2018). Monitoring of spatial and temporal variability of desert dust over the Hamoun e Jazmurian, Southeast of Iran based on the Satellite Data. Geographical Data (SEPEHR)27(106), 153-168. (in Farsi)
  3. Bogan, M. A. B., Kul, S., Zengin, S., Oktay, M., Sabak, M., Gumusboga, H., & Bayram, H. (2021). The effects of desert dust storms, air pollution, and temperature on morbidity due to spontaneous abortions and toxemia of pregnancy: 5-year analysis. Biometeorology65(10), 1733-1739.
  4. Boroghani, M., Pourhashemi, S., Zanganeh Asadi, M., & Moradi, H. (2017). Dust source identification in the Middle East by using remote sensing. Natural Environmental Hazards6(11), 101-118. (in Farsi)
  5. Boroughani, M., Hashemi, H., Hosseini, S. H., Pourhashemi, S., & Berndtsson, R. (2019). Desiccating Lake Urmia: a new dust source of regional importance. IEEE Geoscience and Remote Sensing Letters17(9), 1483-1487.
  6. Boroughani, M., Pourhashemi, S., Hashemi, H., Salehi, M., Amirahmadi, A., Asadi, M. A. Z., & Berndtsson, R. (2020). Application of remote sensing techniques and machine learning algorithms in dust source detection and dust source susceptibility mapping. Ecological Informatics56, 101059.
  7. Cao, H., Amiraslani, F., Liu, J., & Zhou, N. (2015). Identification of dust storm source areas in West Asia using multiple environmental datasets. Science of the Total Environment502, 224-235.
  8. Ciren, P., & Kondragunta, S. (2014). Dust aerosol index (DAI) algorithm for MODIS. Geophysical Research: Atmospheres119(8), 4770-4792.
  9. Dehghan, A., Khanjani, N., Bahrampour, A., Goudarzi, G., & Yunesian, M. (2018). The relation between air pollution and respiratory deaths in Tehran, Iran-using generalized additive models. BMC pulmonary medicine18(1), 1-9.
  10. Delfi, S., Mosaferi, M., Hassanvand, M. S., & Maleki, S. (2019). Investigation of aerosols pollution across the eastern basin of Urmia lake using satellite remote sensing data and HYSPLIT model. Environmental Health Science and Engineering17(2), 1107-1120.
  11. El-Askary, H., Gautam, R., & Kafatos, M. (2004). Remote sensing of dust storms over the Indo-Gangetic basin. Indian Society of Remote Sensing32(2), 121-124.
  12. General Meteorological Department of West Azarbaijan Province (2022). Meteorological journals of West Azarbaijan province, Received on March 3, 2015 from http://www.azmet.ir/in/book/nashreh.htm. (in Farsi)
  13. Ghavidel Rahimi, Y., Farajzadeh, M., & Lashani Zand, E. (2018). The temporal analysis of dust storms in Khoramabad synoptic station. Applied researches in Geographical Sciences18(51), 87-102. (in Farsi)
  14. Gholami, H., Mohamadifar, A., & Collins, A. L. (2020). Spatial mapping of the provenance of storm dust: Application of data mining and ensemble modelling. Atmospheric Research233, 104716.
  15. Ginoux, P., Prospero, J. M., Gill, T. E., Hsu, N. C., & 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 Geophysics50,
  16. Hamzeh, N. H., Kaskaoutis, D. G., Rashki, A., & Mohammadpour, K. (2021). Long-term variability of dust events in southwestern Iran and its relationship with the drought. Atmosphere12(10), 1350.
  17. Karami, S., Hossein Hamzeh, N., Sabzezari, H., & Lo Alizadeh, M. (2021). Investigation of trend analysis of the number of dust stormy days and aerosol concentration derived from satellite in Khuzestan province by using non-parametric Mann-Kendall test. Climate Research1399(44), 91-103.
  18. Khaledi, K. (2017). Estimating the economic losses of dust storms on agriculture sector in the western provinces of the Iran. Eqtesad-E Keshavarzi Va Towse'e, 24(96), 151-183. (in Farsi)
  19. Kheirandish, Z., Bodagh Jamali, J., & Rayegani, B. (2018). Identification of the best algorithm for dust detection using MODIS data. Natural Environmental Hazards7(15), 207-220. (in Farsi)
  20. Levy, R. C., Remer, L. A., Mattoo, S., Vermote, E. F., & Kaufman, Y. J. (2007). Second‐generation operational algorithm: Retrieval of aerosol properties over land from inversion of Moderate Resolution Imaging Spectroradiometer spectral reflectance. Geophysical Research: Atmospheres112(D13211).
  21. Moridnejad, A., Karimi, N., & Ariya, P. A. (2015). A new inventory for middle east dust source points. Environmental monitoring and assessment187(9), 1-11.
  22. NOAA Research. (2020). NOAA ESRL global monitoring laboratory: SURFRAD aerosol optical depth, Retrieved March 03, 2020, from https://www.esrl.noaa.gov/gmd/grad/surfrad/aod/.
  23. Prospero, J. M., Ginoux, P., Torres, O., Nicholson, S. E., & Gill, T. E. (2002). Environmental characterization of global sources of atmospheric soil dust identified with the Nimbus 7 Total Ozone Mapping Spectrometer (TOMS) absorbing aerosol product. Reviews of geophysics40(1), 2-1.
  24. Rahmati, O., Panahi, M., Ghiasi, S. S., Deo, R. C., Tiefenbacher, J. P., Pradhan, B., Jahani, A., Goshtasb, H., Kornejady, A., Shahabi, H., Shirzadi, A., Khosravi, H., Davoudi Moghaddam, D., Mohtashamian, M., & Bui, D. T. (2020). Hybridized neural fuzzy ensembles for dust source modeling and prediction. Atmospheric Environment224, 117320.
  25. Rashki, A., Middleton, N. J., & Goudie, A. S. (2021). Dust storms in Iran–Distribution, causes, frequencies and impacts. Aeolian Research48, 100655.
  26. Song, H., Zhang, K., Piao, S., & Wan, S. (2016). Spatial and temporal variations of spring dust emissions in northern China over the last 30 years. Atmospheric environment126, 117-127.
  27. Toofan, M. (2010). The challenges and the prospect of regional cooperation in curbing micro dust phenomenon. Foreign Policy, 24(4), 943-958. (in Farsi)
  28. Van Donkelaar, A., Martin, R. V., Brauer, M., Kahn, R., Levy, R., Verduzco, C., & Villeneuve, P. J. (2010). Global estimates of ambient fine particulate matter concentrations from satellite-based aerosol optical depth: development and application. Environmental health perspectives118(6), 847-855.