University of Kashan Desert Ecosystem Engineering 2538-6336 12 Issue 10 in English 2023 08 23 Investigating the Best Representative Dust Activities Index, Its Spatial-Temporal Changes, and Its Relationship with Environmental Factors in Iranian Dry Areas Investigating the Best Representative Dust Activities Index, Its Spatial-Temporal Changes, and Its Relationship with Environmental Factors in Iranian Dry Areas 25 38 114121 FA Zohre Ebrahimi Khusfi Department of Environmental Science and Engineering, Faculty of Natural Resources, University of Jiroft, Jiroft, Iran Mohsen Ebrahimi-Khusfi Department of Geography, Faculty of Humanities and Social Sciences, Yazd University, Yazd, Iran. Maryam Mirakbari Postdoctoral Researcher, Faculty of Geographical Sciences and Planning, University of Isfahan, Isfahan, Iran Journal Article 2023 12 30 The current study primarily sought to select the best index for elaborating on dust activities, analyze the temporal and spatial changes of the index’s trend, and examine the relationship of the index with environmental factors in Iranian dry regions. To this end, the study examined the data collected on dust concentration, dust storm index, the number of dusty days (NDD), the pollution caused by dust storms, and the frequency of all dust events over a period of 18 years (2001-2018) using the MODIS-aerosols optical depth (AOD) product. Moreover, Pearson's correlation coefficient was used to analyze the correlation between the indices and AOD data sets. On the other hand, the trend of the best index annual changes in twenty-eight Iranian urban areas was analyzed using the Mann-Kendall method. Also, the most important environmental factors controlling dust activities in high-risk areas were identified using the random forest model. The results of the study indicated a strong correlation between NDD and AOD in Iranian dry regions (r= 0.7; p-value= 0.001). It was also found that the trend of NDD’s annual changes significantly increased in Torbat Heydarieh, Nehbandan, and Anar (Z>+1.96). However, the trend significantly decreased in Chabahar and Iranshahr (Z>│-1.96│. Generally, the results indicated an insignificant decreasing trend of annual NDD changes across the entire Iranian arid regions from 2001 to 2018 (Z= -0.45). on the other hand, the random forest model suggested that air pressure and wind speed exerted the greatest influence on dust activities that occurred in Iran’s high-risk area throughout the study period. Therefore, it could be argued that the findings of this study can help better monitor dust events and reduce their environmental risks in Iranian dry areas. The current study primarily sought to select the best index for elaborating on dust activities, analyze the temporal and spatial changes of the index’s trend, and examine the relationship of the index with environmental factors in Iranian dry regions. To this end, the study examined the data collected on dust concentration, dust storm index, the number of dusty days (NDD), the pollution caused by dust storms, and the frequency of all dust events over a period of 18 years (2001-2018) using the MODIS-aerosols optical depth (AOD) product. Moreover, Pearson's correlation coefficient was used to analyze the correlation between the indices and AOD data sets. On the other hand, the trend of the best index annual changes in twenty-eight Iranian urban areas was analyzed using the Mann-Kendall method. Also, the most important environmental factors controlling dust activities in high-risk areas were identified using the random forest model. The results of the study indicated a strong correlation between NDD and AOD in Iranian dry regions (r= 0.7; p-value= 0.001). It was also found that the trend of NDD’s annual changes significantly increased in Torbat Heydarieh, Nehbandan, and Anar (Z>+1.96). However, the trend significantly decreased in Chabahar and Iranshahr (Z>│-1.96│. Generally, the results indicated an insignificant decreasing trend of annual NDD changes across the entire Iranian arid regions from 2001 to 2018 (Z= -0.45). on the other hand, the random forest model suggested that air pressure and wind speed exerted the greatest influence on dust activities that occurred in Iran’s high-risk area throughout the study period. Therefore, it could be argued that the findings of this study can help better monitor dust events and reduce their environmental risks in Iranian dry areas. https://deej.kashanu.ac.ir/article_114121_e1c29086fb1be520d741d4b407c76fa1.pdf