Etemadfard, H., Karami, R. (2025). Dust Source Identification Using Spatiotemporal Tensor of Aerosol Optical Depth in Ilam County. , (), -. doi: 10.22067/geoeh.2023.82988.1383
Hossein Etemadfard; Ramin Karami. "Dust Source Identification Using Spatiotemporal Tensor of Aerosol Optical Depth in Ilam County". , , , 2025, -. doi: 10.22067/geoeh.2023.82988.1383
Etemadfard, H., Karami, R. (2025). 'Dust Source Identification Using Spatiotemporal Tensor of Aerosol Optical Depth in Ilam County', , (), pp. -. doi: 10.22067/geoeh.2023.82988.1383
Etemadfard, H., Karami, R. Dust Source Identification Using Spatiotemporal Tensor of Aerosol Optical Depth in Ilam County. , 2025; (): -. doi: 10.22067/geoeh.2023.82988.1383
Dust Source Identification Using Spatiotemporal Tensor of Aerosol Optical Depth in Ilam County
جغرافیا و مخاطرات محیطی
Articles in Press, Accepted Manuscript, Available Online from 21 March 2025
1Civil Engineering Department, Engineering Faculty, Ferdowsi University of Mashhad (FUM)
2Msc.student of gis, Department of Civil Engineering, Faculty of Technical and Engineering, Ferdowsi University of Mashhad,Iran
Abstract
One of the factors of air pollution is the phenomenon of dust, which has caused a lot of damage to various economic, social and human resources. The phenomenon of dust occurs in parts of the world, including arid and semi-arid regions, which is caused by natural and human factors. This research has identified the origin of dust in Ilam city using spatio-temporal tensor of aerosol optical depth (AOD) with Madis sensor data in the period from March to June 2022. First, dusty days were extracted from meteorological data and the spatio-temporal tensor of aerosol optical depth was produced. The reason for using the tensor was to examine the changes of a large volume of data in a spatial and temporal manner in a study period simultaneously. The results of comparing the relevant tensor with the corresponding meteorological data showed that whenever the aerosol optical depth is higher than 0.5, there is dust in that range. The spatio-temporal dust tensor analysis showed that the amount of dust is directly related to the wind speed and when the wind speed exceeds 15 m/s, dust occurs. Finally, by identifying the spatial changes of AOD, there are four sources of dust (Beld, Mesopotamia, Misan, and Wasit) in the study area, and Mesopotamia was identified as one of the potential dust areas. The analysis of the time pattern of AOD indicates its increasing trend in May. The highest value of AOD with 3.85 in May indicates the amount of dust. By examining the correlation between Ilam dust and the identified centers, the regression model of Ilam city is more related to Wasit region and its correlation coefficient is 82.96%.