Background and Objective: Land degradation modeling is one of the environmental impact assessment methods that quantitatively represents the effects of human activities. The purpose of applying this model is to identify the destruction factors and susceptibility degree in ecosystems in order to prevent further destruction by other projects and to show the feasibility of future development to decision markers. Method: The study area was firstly partitioned into 94 cells (1600 ha) and then 14 degradation factors along with their intensity were identified using land use map, field observations and expert views. Ecological susceptibility and physiological density were then determined and all cells were classified into four categories as recommended for development, required for reconstruction, required for protection and cells with no development potential based on fuzzy theory. Findings: The results show that 22 cells (23. 40% of the total area) out of 94 cells require reconstruction, 37 cells (39. 36% of total area) have no development potential, and 35 cells (37. 22% of total area) are recommended for development. Discussion and Conclusion: The effects of destructive activities in this region (that is mainly due to the detrimental effects of tourism activities) were evident, so that the destructive activities such as change in land use and land cover, on the one hand, and waste and rivers pollution, on the other hand, were found as the main causes of destruction in the region. Out of 94 cells, 21 cells and 16 cells had no development potential due to faults and due to being in Binalood protected area respectively. 35 cells are recommended for development in first to third priorities; these cells are in low physiological density area. 22 cells, due to high physiological density and severity of the destructive agents, have a high degradation coefficient and need to be reconstructed, and therefore should be excluded from any future development.

Background and Objective: The goal of this research was to assess the severity of diseases caused by suspended particulate matters for the residents of the area and the health risk assessment in Sanandaj. Methods: The statistical information about the concentration of particulate matters was taken in 2012 from the Sanandaj Department of Environment. The field measurement of particulate matters was also carried out in 17 monitoring stations in Sanandaj for different months during a year by using portable devices. Then for quantifying the effects of air pollutants, Air Quality Health Impact Assessment (AirQ) software was used. Next, calculations were made in Excel for preparation of the input data. Finally, prediction of mortality and comparing it with the available statistics was performed and the health risk assessment was conducted for the region. Findings: The study of air pollution due to particulate matters in the city of Sanandaj showed that most of the days, the area was contaminated with low intensity and the days of unhealthy and dangerous including less than two months from June to August. The highest amounts of the average concentrations of particulate matters in different months of the year were seen in the first five months of the year and especially in June. However, the number of patients admitted by health centers due to air pollution, in the winter and April, were the greatest. Most of the air pollution was seen in the northeast (Area A) due to the repairing workshops, passenger terminal and industrial park located in that area. Assessment of the number of patients admitted by the medical centers in the city of Sanandaj and comparing it with the amounts predicted by AirQ, showed that the results of AirQ were less than the real data, while the predicted mortality rates were more than the real data. In terms of demographic categories indifferent parts of the city, the distribution was almost equal. However, it was the highest rate in the area number 3, which had the lowest air pollution. Prediction of health risk in the area showed the highest risk in the area number one and for the people in age of 20-44 years old. The main cause was the more exposure of people living in this area to air pollutants. Discussion and Counclusion: In cold seasons of the year, due to inversion and the topographical situation of the region, respiratory diseases and mortality rate increased in the study area. Based on the diseases recorded in the statistical year, 581 cases of chronic lung diseases, 570 cases of angina thoracic, 23 cases of asthma and 39 deaths attributed to air pollution has been reported.

Background and Objective: Increasing industrial activities associated with the production of pollutants, including heavy metals, is one of the main causes of water and soil pollution. Mineral activities are one of the human activities that cause pollution of the natural resources such as soil. Method: In this study, the zoning concentration of copper as soil contamination around Meyduk copper mine was investigated. The direction samples were taken according to the situation of surrounding villages. Systematic sampling of 360 samples had been collected through the directions. Measuring the concentration of sample was done using atomic absorption method in the laboratory. To indicate the degree of soil pollution with heavy metals, Muller’ s geoaccumulation index was used. Finally, in order to estimate the normal concentration of Cu and pollution of soil, Kriging method was used. Results: Results showed that the maximum amount of Cu concentration is 697. 5 mg/kg and the minimum is 6. 35 mg/kg. The Cu concentration trend in direction D was more than direction M due to the direction of local dominant wind. Discussion and Conclusion: By receding from location of mine, the overall trend of Cu concentration decreased. This indicated the role of mine activities on soil pollution.