Monitoring of dust phenomenon and Investigate its correlation with temperature and humidity parameters‌ (Case study: Khuzestan Province)

Dust is a phenomenon in arid and semi-arid areas due to high wind speeds on the un-polluted soil surface and prone to erosion. The occurrence of dust has always been a problem for residents in the western and southwestern regions of the country, has gradually spread to other provinces, including the capital. The study area is southwest of Iran, Khuzestan province. The latitude and longitude of the study area is, 47° 50´ E and 30° 33´ N respectively and is considered the centerm for Iranian oil and gas production. Khuzestan is the fifth most populous city in Iran. Ahvaz is the capital of Khuzestan province. Negative consequences of this phenomenon include damage caused by pests and diseases, increased road accidents due to reduced visibility and failure of this risk in human life. And retinal detachment, skin allergies, and so on. In the environment, water pollution is affected by the process of plant photosynthesis and reduced yield. The phenomenon of dust usually occurs in arid and semi-arid regions. In order to investigate the dust phenomenon in Khuzestan province using synoptic data and remote sensing data, the dust days of 20 synoptic stations were analyzed on a daily basis and from 2010 to 2017. MOD021KM product material data were obtained in accordance with the date of the dust days announced at the station, to identify dust phenomena, visual interpretation method, TDI dust parameters and D parameter. After detection of dust, the correlation between the data with horizontal visibility less than 1000 m and the meteorological parameters of relative temperature and relative humidity were evaluated by regression method. Finally, it shows the correlation and relationship between dust characteristics and meteorological parameters (temperature and humidity). According to Figures 9-10-11-12, it is possible to determine which dust index (TDI, D) has the highest and lowest correlation with meteorological parameters (temperature, humidity). Due to the fact that the data are related to the warm seasons of the year (spring and summer) And temperature changes are less volatile. The above figures show that there is the least correlation between dust indicators and synoptic parameters. The highest correlation in the TDI index with relative humidity is about 0.22. Also, the correlation coefficient of the other indicators with TDI meteorological parameters with temperature is 6.9, parameter D with temperature is 0.9, parameter D with humidity is 11.9. Therefore, there is a weak relationship between dust and temperature and humidity parameters. Correlation and regression analysis showed that meteorological parameters had the least correlation (R²) with dust indices. The results also show that TDI index compared to parameter D has the best performance in detecting dust phenomenon. And by examining the temperature, humidity and correlation with the TDI and D indices, the dust was not of domestic origin and was transient. By examining the temperature and humidity parameters and their correlation with TDI and D indicators, we came to the conclusion that dust did not have an internal origin and was transient, and also there is no correlation between dust index and meteorological parameter. According to previous studies, Iraq, Saudi Arabia, and Syria have the most dust, despite the hot, dry climate, with most of the dust coming to Iran coming from neighboring countries.