Dust storm occurs frequently in arid and semi-arid areas of the world. This natural phenomenon, which is the result of stormy winds, raises a lot of dust from desert surfaces and decreases visibility to less than 1 km. In recent years the temporal frequency of occurrences and their spatial extents has been dramatically increased. West of Iran, especially in spring and summer, suffers from significant increases of these events which cause several social and economic problems. Detecting and recognizing the extent of dust storms is very important issue in designing warning systems, management and decreasing the risk of this phenomenon. As the process of monitoring and prediction are related to detection of this phenomenon and it's separation from other atmospheric phenomena such as cloud, so the main aim of this research is establishing an automated process for detection of dust masses. In this study 20 events of dust happened in western part of Iran during 2000–2011 have been recognized and studied. To the aim of detecting dust events we used satellite images of MODIS sensor. Finally a model based on reflectance and thermal infrared bands has been developed. The efficiency of this method has been checked using dust events. Results show that the model has a good performance in all cases. It also has the ability and robustness to be used in any dust storm forecasting and warning system.

This study examined the potential of wind energy in 22 regions in eastern Iran. In this regard, it investigated the parameters of Weibull, mean wind speed, and wind power density in these areas. The results showed that the mean wind speed was above 4 m/s at all stations and in ten stations was above 5 m/s. Also, the study of monthly wind speed fluctuations in eastern parts of Iran and its comparison with the relevant variations of electricity consumption showed that the fluctuations of speed is clearly in line with the requirements of electrical energy consumption in Iran. In addition, the annual production of energy and the economic performance of four commercial turbine models at 22 sites were investigated. Generally, Mapna 2.5 MW and Vestas V100–1.8 MW 60 turbines were more efficient than the other two turbine models in terms of annual production of energy and cost of producing electricity. The results of the economic analysis showed that investment in wind farms in eastern parts of Iran could be associated with high profitability. Finally, the results of this study indicated that planning to exploit wind energy for electricity production in eastern parts of Iran is an appropriate strategy to reduce Iran's dependence on fossil fuels.

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