Farshad Soleimani Sardoo; Tayebeh Mesbahzadeh; Ali Salajeghe; Gholamreza Zehtabian; Abbas Ranjbar; Mario Marcello miglietta; Sara Karami
Abstract
Introduction: Today, dust is a major challenge for human societies. Dusts have a significant impact on the Earth's radiation budget, global biochemical cycles, soil formations, and chemical compounds in the atmosphere. This phenomenon can affect public health indicators. The Iranian Central Plateau is ...
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Introduction: Today, dust is a major challenge for human societies. Dusts have a significant impact on the Earth's radiation budget, global biochemical cycles, soil formations, and chemical compounds in the atmosphere. This phenomenon can affect public health indicators. The Iranian Central Plateau is located in arid and semi-arid climates; it is more likely to face this phenomenon than other regions. Dust management and control depend on identifying critical hotspots and stabilizing the harvesting area. The aim of this study was to identify internal dust sources using the vertical dust flux parameter. Material and methods: Kavir and Loot deserts cover a large area of the Iranian Central Plateau. In this study, the WRF-Chem model and GOCART and AFWA wind erosion schemas were used to identify dust springs. Emission fluxes were used to detect dust springs. In this regard, a severe storm was selected on 05/22/2018 by WRF-Chem model for simulation. In order to verify and select the best wind erosion schematic of the Iranian Central Plateau, the data of MERRA2 re-analysis database and surface dust concentration values were used. Results and discussion: The results showed that the outputs of GOCART and AFWA schemas were different. The GOCART schemas identified three strong dust sources in the study area that were located in the Jazmourian Basin, the Loot Basin, and the Central Desert (Kavir Desert), but the AFWA schemas were able to identify only one weak source in the Loot area. The results showed that Loot Desert Center, south of Jazmourian Basin, as well as Dasht-e Kavir Desert Center (Central Desert) are known as internal dust sources. So that from one square meter of these areas, it is possible for 5800 micrograms of dust to rise into the atmosphere per second. Due to the fact that the storm lasted for 12 hours, about 2 tons and 505 kg of dust were transferred to the atmosphere from each hectare of internal dust springs. The results of the GOCART schema were more consistent with the three-hour time-series data of the MERRA2 re-analysis database and were selected as the best wind erosion schematic in the Iranian Central Plateau. Conclusion: The results showed that the WRF-Chem model had a good ability to resemble the dust flux in the study area. The results of the GOCART and AFWA schemas were different. The AFWA model estimated the internal dust sources to be very weak. However, the GOCART model well detected internal dust sources.
Mehdii Jafari; Gholamreza Zehtabian; Hasan Ahmadi; Tayebeh Mesbahzadeh; Ali Akbar Norouzi
Abstract
Introduction: The phenomenon of dust in Iran is a serious risk that caused major problems for the environment and human health. Research has shown that the frequency and severity of these storms have increased in recent years. In addition, numerical weather models alone are not capable of storm detection, ...
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Introduction: The phenomenon of dust in Iran is a serious risk that caused major problems for the environment and human health. Research has shown that the frequency and severity of these storms have increased in recent years. In addition, numerical weather models alone are not capable of storm detection, which requires the use of dust detection methods based on data remote sensing. The purpose of this research was to analyze the statistical data and identify the days with dust, the source of dust entering the Isfahan area, and identify the route of its movement. Material and methods: For data analysis of dust, data from dust collecting data was collected from the selected station in the study area with a suitable statistical period from the meteorological organization on a daily basis for 8 hours, in the form of special codes for the period of 2010 to 2013, which were processed and analyzed using statistical methods. In order to zoning the dust abundance in the province, the IDW method was used to interpolate and transform point-to-area data. The dispersion zonation map for the 2010-2013 period was mapped using the GIS software. In order to visualize the dust phenomenon, after the geometric correction of the images, the radian values of the images were converted to brightness temperature using the Planck function. Corrections and processing of images were done in ENVI software. Due to the large influence of dust particles on the reflection and brightness temperature of the 31 and 32 bands of the material, the difference between the two bands' brightness was used to represent the dust mass. Also, to prevent the detection of cloud areas, the threshold of 290 K was applied to the 12-micron range. HYSPLIT Lagrangian model was used to trace the dust particles' path. Results and disscussion: The results of this study indicated that a total of 1467 days of dust phenomena were reported for selected stations from 2010 to 2013, in which the Naein station was the largest with 634 days and the Kashan station had the least frequency of dust with 50 days. The results also indicated the greatest frequency percentage occurred in May, June and April and the lowest frequency percentages in December and January. The frequency of monthly dust data showed that 44.57% of the total dust incidence occurred in April, May and June and 32.4% in December and January. Accordingly, it can be concluded that monthly dust changes occur frequently in the region consistent with the regional climate during all months of the year. The zoning results showed that during the study period, the southeast of the province, especially Naien station, had the highest incidence of dust. The application of brightness temperature and temperature threshold in order to separate the dust from the terrain, especially in areas with backlight, was helpful in the detection of dust. The results of the tracking showed that the main route for the transfer of dust to the studied area was southwest-northeast. Conclusion: In general, according to satellite images on the first and the peak day of dust, the main sources of dust in the region were northern Arabian deserts. Based on the results obtained from image processing and the output of the model, the northern part of Saudi Arabia and the southwest-northeast route were the origin and main route of dust entering Isfahan.
