## 1 Introduction  
Dust particles are among the air pollutants that have a significant impact on the radiation budget [1]. They can also reduce air quality and threaten human health [2], and drastically limit horizontal visibility [3; 4]. Dust is generated as a result of wind erosion in arid and semi-arid regions. Since Iran is located in the arid belt of the world (approximately 88% of Iran is arid or semi-arid [5]), wind erosion is one of the most important processes of land degradation and landscape change there [6; 7; 8]. Dust emission occurs in widespread events that are variable in size, time, and particle concentration [9]. Iran is a country with an average annual rainfall of about 243 mm. Most of the country has a dry or semi-arid climate, which has created dry deserts. The deserts of Loot and Kavir are the most important of them. Low rainfall, high evaporation and, as a result, limited soil moisture and poor vegetation are prominent features of these areas. These conditions make the area prone to wind erosion. Wind erosion involves the separation, transfer, and deposition of soil particles by erosive winds [10; 11]. Soil drought, lack of vegetation and erosive winds are the main causes of wind erosion, which is more likely to occur in dry and sparsely vegetated areas. Therefore, the dust phenomenon is one of the most important natural hazards of the Central Plateau of Iran. In case of suitable meteorological and hydrological conditions, conditions for dust storms will be promoted. Numerical prediction models have been designed to simulate dust emissions. Dust storm prediction models have been used operationally in Europe [12], Australia [13], and East Asia [14; 15; 16; 17]. At the U.S. Naval Research Laboratory, the U.S. Navy Mesoscale Prediction System's Coupled Ocean-Atmospheric Mesoscale Prediction System (COAMPS), with an embedded dust aerosol model [18], has produced three-day forecasts for southwest Asia in real-time runs since March 2003. Due to the climatic and environmental importance of soil dust, considerable efforts have been devoted to simulating the production and transport of soil dust aerosols at regional and global scales [18; 19; 20; 21]. [PERSON] [22] emphasizes a mechanistic model of forces acting on dust particles to predict dust flux. Additionally, [PERSON] et al. [18] used satellite data and horizontal visibility to validate the results of the numerical model of dust prediction. One such model that is able to simulate dust particle transport and its feedbacks simultaneously with meteorological fields is the Weather Research and Forecasting model coupled to Chemistry chemistry (WRF-Chem) model [23; 24]. Extensive studies have been carried out using WRF-Chem. [PERSON] et al. [25] examined the sensitivity of WRF-Chem to dust emissions in order to determine dust sensitive areas in West Asia. The results showed that the tested implementation of WRF-Chem was skillful in some regions (Iraq and Syria). [PERSON] and [PERSON] [26] examined the response of dust transport in WRF-Chem to dust flux as well as land surface characteristics in predicting the sources of dust in East Asia. [PERSON] and [PERSON] [27] investigated the effects of soil moisture on sand leakage and dust emission observed in Hur Qian sandy lands in China, and [PERSON] et al. [28] investigated several dust events in the central Mediterranean region of Apulia (southeastern Italy) in order to assess the sensitivity of WRF-Chem to land surface models. [PERSON] et al. [29] used the WRF-Chem model to simulate dust emission and evaluate its relationship with climate change in East Asia. [PERSON] et al. [30] used WRF-Chem to investigate its sensitivity to vertical resolution during a 22-23 June 2012 dust event over North Africa; results indicated that the model was able to transport particles from the ground to higher layers. [PERSON] et al. [31] examined the spatial and temporal characteristics of dust events and their contribution to the budget of aerosols in Eastern Asia, using WRF-Chem and a parametric tool for dust analysis.