Identifying the centers of dust and analyzing the factors influencing its occurrence Based on Remote Sensing Data (Case Study: Southwest Iran)

Document Type : Research Article

Authors

• Saeed Negahban ¹
• Hamid Ganjaeian ²
• Seyed Saedi Ghisarian ³
• Atrin Ebrahimi ⁴

¹ Associate Professor in Geomorphology, Department of Geography, Shiraz University, Shiraz, Iran.

² PhD in Geomorphology, University of Tehran, Tehran, Iran.

³ Bachelor of Natural Resources, Rangeland and Watershed Management, University of Malayer, Malayer, Iran.

⁴ PhD in Geomorphology, University of Tabriz, Tabriz, Iran.

10.22067/geoeh.2024.89088.1504

Abstract

Extended Abstract

Introduction
Dust, or fine dust, refers to very small and light particles of silt, clay, or sand that are transported by the wind over long distances due to wind erosion and the spread of desertification. Dust storms have emerged as a significant threat to public health in recent years. This phenomenon is influenced by natural factors, such as climatic conditions, climate change, hydrogeomorphological features, and vegetation, as well as human factors, including land use changes, erosion, and other anthropogenic activities. Dust is one of the most harmful natural disasters in arid and semi-arid regions of the world, particularly in Iran, and has caused substantial environmental and human problems in these areas.
This phenomenon has significantly affected various aspects of life in the region in recent years. Among the areas exposed to dust-related hazards are the southwestern regions of Iran. Due to climatic conditions, wind speed and direction, and the presence of sand dunes, these areas are prone to becoming dust centers. This has resulted in frequent occurrences of dust storms over a large portion of the year in the southwestern regions of the country. Given the importance of the issue, this research investigates the concentration of dust in the southwestern region of Iran and analyzes the factors influencing its occurrence.
Material and Methods

In this research, Google Earth images, MODIS satellite images, CHIRPS satellite images, and a 30-meter SRTM digital elevation model were utilized. The most important tools used in the research were Google Earth Engine (for preparing dust concentration maps and average precipitation and temperature maps of the region), Google Earth (for creating geomorphological unit maps), ArcGIS (for generating desired maps), and IDRISI (for implementing the WLC model).
Additionally, various indices and models were applied, the most notable being the AOD index (for generating dust concentration maps) and the WLC model (for identifying areas prone to dust center formation). This research was conducted in several stages.
In the first stage, the Google Earth Engine system, AOD index, and MODIS satellite images were used to prepare the dust concentration map for the study area from 2018 to 2022. In the second stage, the correlation between dust concentration and environmental factors, such as vegetation parameters, wind speed, precipitation, temperature, geomorphological units, and altitude, was analyzed. In the third stage, areas prone to dust center formation were identified using the WLC model.
 
Results and Discussion
Google Earth Engine and the AOD index were employed to assess the dust concentration in the southwest of the country. The analysis involved utilizing MODIS satellite images to generate dust concentration maps for the years 2018 to 2022. Based on these maps, the highest dust concentration was observed in the central regions of Khuzestan Province and the southern regions of Ilam Province. Conversely, the lowest dust concentration was recorded in areas adjacent to Horulazim Wetland, the Arvand River, and the southern coastline.
The relationship between the dust concentration index and environmental factors indicated that the highest dust concentrations were associated with areas characterized by low NDVI coefficients, low rainfall, high temperatures, low altitudes, and sand dunes.
 
Conclusion
The findings of this research showed that the correlation coefficients between dust concentration and the parameters of NDVI, wind speed, precipitation, temperature, and altitude were 0.63, 0.156, 0.557, 0.489, and 0.602, respectively. Additionally, the dust concentration coefficients in sand hills, plains, hills, and mountains were 0.71, 0.64, 0.47, and 0.23, respectively.
After analyzing the factors affecting dust concentration, a map of areas prone to dust center formation was generated based on the identified parameters. The results revealed that a significant portion of the study area, including the northwestern parts of Ahvaz City and the northern parts of Hovizeh City, showed a high potential for forming dust centers. Similarly, the areas between the cities of Omidieh and Ahvaz also demonstrated substantial potential for dust center formation.
The overall findings indicate that under the influence of environmental factors, a large portion of the southwestern regions of Iran is prone to dust center formation. Among the environmental factors, vegetation density played the most significant role in dust control. Therefore, the most effective solution to reduce and manage dust in the region is to establish vegetation in barren areas, particularly in the sand fields of the region.

Keywords

• Dust Storms
• AOD Index
• NDVI Analysis
• Environmental Factors
• Southwest Iran

Main Subjects

• Micro pollen

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References

Azizi, G., Miri, M., & Nabavi, S. O. (2012). Tracking the phenomenon of dust in the western half of Iran. Journal of Arid Regions Geographic Studies, 3(7), 63-81. [In Persian] https://jargs.hsu.ac.ir/article_161302.html

Azizi, G., Neghah, S., Farid Mojtahedi, N., & Shojaie, Y. (2023). Detection of the new dust source for the north of the Iran. Journal of Spatial Analysis Environmental Hazards, 10(1), 157-174. [In Persian]  http://dx.doi.org/10.61186/jsaeh.10.1.157

Beegum, S. N., Gherboudj, I., Chaouch, N., Temimi, M., & Ghedira, H. (2018). Simulation and analysis of synoptic scale dust storms over the Arabian Peninsula. Atmospheric Research, 199, 62-81. https://doi.org/10.1016/j.atmosres.2017.09.003

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 Environment, 502, 224-235. http://dx.doi.org/10.1016/j.scitotenv.2014.09.025

Cheki Forak, M., Doostan, R., & Minaei, M. (2023). Identification of Dust Centers in Birjand City. Geography and Territorial Spatial Arrangement, 13(46), 61-84. [In Persian] https://doi.org/10.22111/gaij.2023.42530.3034

Dargahian, F., Lotfi Nasab Asl, S., & Khosroshahi, M. (2019). Analysis of the role of internal dust sources in creating critical conditions in Ahvaz with an emphasis on the southeastern area. Iranian Journal of Forest and Range Protection Research, 16(2), 157-170. [In Persian] https://doi.org/10.22092/ijfrpr.2019.118689

Deep, A., Pandey, C. P., Nandan, H., Singh, N., Yadav, G., Joshi, P. C., ... & Bhatt, S. C. (2021). Aerosols optical depth and Ångström exponent over different regions in Garhwal Himalaya, India. Environmental Monitoring and Assessment, 193(6), 324. https://link.springer.com/article/10.1007/s10661-021-09048-4

Esfandiary Darabad, F., Layeghi, S., Mostafazadeh, R., & Haji, K. (2021). The zoning of flood risk potential in the Ghotorchay watershed with ANP and WLC multi-criteria decision making methods. Journal of Spatial Analysis Environmental Hazards, 8(2), 135-150. [In Persian]  http://dx.doi.org/10.52547/jsaeh.8.2.135

Fathallah zadeh, M., Ranjbar Barough, Z., Motamedirad, M., & Hajikarimi Dolabi, Z. (2023). Investigating the characteristics of wind and its relationship with the occurrence of dust in Zabol city using the system Google Earth Engine. Quantitative Geomorphological Research, 12(3), 167-183. [In Persian] https://doi.org/10.22034/gmpj.2023.416114.1455

Guan, X., Huang, J., Zhang, Y., Xie, Y., & Liu, J. (2016). The relationship between anthropogenic dust and population over global semi-arid regions. Atmospheric Chemistry and Physics, 16(8), 5159-5169. http://dx.doi.org/10.5194/acp-16-5159-2016

Hermas, E., Leprince, S., & El-Magd, I. A. (2012). Retrieving sand dune movements using sub-pixel correlation of multi-temporal optical remote sensing imagery, northwest Sinai Peninsula, Egypt. Remote Sensing of Environment, 121(2), 51-60. http://dx.doi.org/10.1016/j.rse.2012.01.002

Hu, Z., Huang, J., Zhao, C., Bi, J., Jin, Q., Qian, Y., ... & Ma, J. (2019). Modeling the contributions of Northern Hemisphere dust sources to dust outflow from East Asia. Atmospheric Environment, 202, 234-243. https://doi.org/10.1016/j.atmosenv.2019.01.022

Jooybari, S. A., Rezaee, P., Soleimani, F., & Davoodi, H. (2019). Dust and its centers: basics and methods of identifying and stabilizing, with a special attitude to the Khuzestan Plain. Applied Sedimentology, 7(14), 129-142. [In Persian] https://doi.org/10.22084/psj.2019.3501

Karam, A., Sffari, A., Ahmadabadi, A., & Anari, A. (2022). Identification of dust centers based on wind characteristics and land cover condition (Case study: Qom province). Quantitative Geomorphological Research, 11(1), 44-61. [In Persian] https://doi.org/10.22034/GMPJ.2021.296815.1290

Katra, I. (2020). Soil erosion by wind and dust emission in semi-arid soils due to agricultural activities. Agronomy, 10(1), 89. http://dx.doi.org/10.3390/agronomy10010089

Kim, J. (2008). Transport routes and source regions of Asian dust observed in Korea during the past 40 years (1965–2004). Atmospheric Environment, 42(19), 4778-4789. https://doi.org/10.1016/j.atmosenv.2008.01.040

Kok, J. F., Adebiyi, A. A., Albani, S., Balkanski, Y., Checa-Garcia, R., Chin, M., ... & Wan, J. S. (2021). Contribution of the world's main dust source regions to the global cycle of desert dust. Atmospheric Chemistry and Physics, 21(10), 8169-8193. https://doi.org/10.5194/acp-21-8127-2021

Namdari, S., Hajibaglou, A., & Abazari, G. (2022). Analysis of changes in Iran's Dust hotspots in the last twenty years. Journal of Geography and Planning, 25(78), 345-361. [In Persian] https://doi.org/10.22034/gp.2021.42751.2739

Noroozi, A. A., & Shoaee, Z. (2020). Dust storm identification using satellite imagery & field observation. Agricultural Information Sciences and Technology, 2(2), 29-35. [In Persian] https://doi.org/10.22092/aistj.2020.342192.1040

Parajuli, S. P., & Zender, C. S. (2017). Connecting geomorphology to dust emission through high-resolution mapping of global land cover and sediment supply. Aeolian Research, 27, 47-65. http://dx.doi.org/10.1016/j.aeolia.2017.06.002

Ranjbar, H., Bazgir, M., Namdar Khojasteh, D., & Rostaminia, M. (2019). Identification of dust sources in Ilam province. Iranian Journal of Range and Desert Research, 26(3), 675-688. [In Persian] https://doi.org/10.22092/ijrdr.2019.120016

Rasouli, A. A., Mahmoudzadeh, H., Yazdchi, S., & Zarinbal, M. (2012). The Application of Analytic Hierarchy Process (AHP) and Weighted Linear Combination (WLC) methods for landfill of Urban Solid Waste maerials Case Study: Marand County. Geography and Territorial Spatial Arrangement, 2(4), 41-52. [In Persian] https://doi.org/10.22111/gaij.2012.875

Shayeshteh, K., Gharib, S., Safikhani, M., & Arabi, S. A. (2020). Identifying Dust generation potential sources using fuzzy logic in Hamadan province. Environmental Erosion Research Journal, 10(2), 59-74. [In Persian] http://dorl.net/dor/20.1001.1.22517812.1399.10.2.4.7

Wei, T., Dong, Z., Kang, S., Rostami, M., Ulbrich, S., & Shao, Y. (2019). Hf-Nd-Sr isotopic fingerprinting for aeolian dust deposited on glaciers in the northeastern Tibetan Plateau region. Global and Planetary Change, 177, 69- 80. https://doi.org/10.1016/j.gloplacha.2019.03.015

Zhang, B., Tsunekawa, A., & Tsubo, M. (2015). Identification of Dust Hot Spots from MultiResolution Remotely Sensed Data in Eastern China and Mongolia. Water, Air, & Soil Pollution, 226(117), 23-34. http://dx.doi.org/10.1007/s11270-015-2300-2