فصلنامه محیط شناسی
سال چهل و یکم شماره 3 (پیاپی 75، پاییز 1394)

Flooding, which is an overflow of water, brings massive biological and economic problems all around the world and disrupts many people’s lives. Based on several effective factors in flood occurrence as well as unknown relationships between parameters, researchers have used various methods to forecast flood over the past decade. An investigation of the conducted studies on flood forecasting reveal that most studies have used measured data such as river flow, temperature or moisture for forecasting. These data are collected over several years and they are used in the above methods. Indeed, the point common to all studies is using data model for model training and flood forecasting. However, as issue that has received less attention is the presence of uncertainty in the data used for extracting flood occurrence model. Taking uncertainty into account, due to high data volume used for model extraction, improves the results. The current research aims to investigate the relationship between flood occurrence and effective parameters by selecting rough sets theory as well as taking into account the uncertainty present in the data during the forecasting process; moreover, following the extraction of these relationships, some rules are extracted which, in addition to their simplicity, present the simultaneous effect of effective parameters on flood occurrence. Then, using the existent relationships in this theory, the correlation between the parameters is investigated in multiple form and the most efficient rules for identifying the most probable conditions of flood occurrence are obtained. For this purpose, the above parameters, spanning four years (2003-2007), related to Jiroft dam is used for analysis and extraction of rules. In this way, first, data processing is performed and intervals of flood occurrence are separated from each year. Then, data discrete manufacturing is performed followed by data approximation and data reduction; the most probable rules are then extracted for flood occurrence by identifying effective core features. The region under study for the current research is Halilrood river located in southeast of Iran, Kerman province. Nowadays, flood occurrence is one of the major issues associated with natural disaster management. Accordingly, the current research proposes a method for prediction of flood occurrence on a daily basis by using rough sets theory to both manage its occurrence risk and analyze the uncertainty obtained from the used data. Given that rules extraction using rough sets theory is done only through previous data analysis, data selection has high sensitivity. The parameters used in this study include precipitation amount, minimum daily temperature, evaporation and the recorded river flow. Application of rough sets theory and simultaneous model extraction of effective parameters in flood occurrence are among the main objectives of the current research. Among the data of four years (2003-7), monthly data, which are obtained from hydrometer devices installed at the entrance of Jiroft Dam for the time period of 2003-7, are selected for analysis. In this way, first, data processing is performed and intervals of flood occurrence are separated from each year. Then, data discrete manufacturing is performed followed by data approximation and data reduction; the most probable rules are then extracted for flood occurrence by identifying effective core features. Finally, the data related to 2009 is used to evaluate the power of the extracted rules;. Rough sets theory, proposed in 1980 by Pawlak, is a powerful mathematical tool for dealing with uncertainty and ambiguity of data. It relies on analysis of data Tables. These Tables may be obtained from measurements or by experts. The approximation synthesis of concepts from the acquired data is the main objective of the rough set analysis. It also provides some methods for reducing imprecise or redundant data in data bases. The process of eliminating redundant data is performed based on training without losing basic data of data base. As a result of data reduction, a set of tabloid and meaningful rules is extracted, which makes the process of decision-making easier. Discussion and In the first stage which includes data selection, all data of the years 2003-7 were annually and completely selected for processing. In the next stage for data discrete manufacturing, since it is impossible to put all data in an information system Table due to different average evaporation and minimum temperature for different seasons of the year, therefore, the data were selected based on different seasons and then they were prepared as four tables of information system. After data selection, data discrete manufacturing was performed by taking their average into account. In the next stage, in order to evaluate the data, Lower and Upper Approximations of each information system were individually calculated. Given that the current research aims to extract flood occurrence rules, only the information systems can be selected for the next stage so that they can have maximum approximation accuracy for Class 1 of decision. The information systems of spring and winter were first mixed in this research for Reduction of Attributes which created an information system. Then, Reduction of Attributes for this new information system was performed by using the discussed relations in rough sets theory, following which no attribute was eliminated, the reason of which may be attributed to a variety of situations as well as high volume of data in this system. Afterwards, in order to obtain simple decision rules, Reduction of Attributes was performed by dividing the new information system into seasons as well as forming individual information systems for each month of spring. Finally, the hydrology data of 2007 was used to evaluate the obtained rules. This data evaluation shows that there are 29 river flow occurrences with more than 10 m3/s. The results obtained from data discrete manufacturing associated with flood occurrence of 2007 show 21 cases out of 29 floods based on the extracted rules for Class 1. The results show that 72% of the extracted rules are consistent with the cases of flood occurrence which shows the ability of these rules in identifying the probable cases of flood occurrence. However, it should be mentioned that the powerful rules extracted by rough sets theory are based on lower approximation of Class 1; therefore, the elements forming the border or uncertainty are not used in these rules; however, border elements and upper approximation of Class 1 are used only for approximation rules. Using the values obtained from confusion matrix, Kappa value was calculated to be 0.84. In addition, an overall accuracy rate of 95% was obtained for the research results regarding the fact that this parameter also involves forecasting of flood non-occurrence. Moreover, based on the frequency, the overall accuracy has increased for more cases of flood non-occurrence than occurrence. Therefore, the uncertainties present in the data are identified and then eliminated from the process of rules extraction. This issue was one objective of the current research which was obtained using rough sets theory. Flood occurrence is one natural disaster which is a serious threat to social infrastructures and financial compensation of damage due to floods is impossible. Given that this phenomenon depends on several factors, many researches have been performed to forecast flood over the recent years. In many cases, those researches employ flood occurrence model for forecasting by taking the previous data into account. One considerable point common to those researches is that they do not consider the uncertainty present in high volume of the data used for identifying flood occurrence model. Moreover, some of these methods individually investigate the correlation between effective parameters and flood occurrence; then, the effect coefficients were calculated for them; it is necessary to compare all parameters with each other as well as to investigate them for forecasting due to complexity of natural phenomena and interdependency and simultaneous impact of various factors. However, the current research, taking into account data uncertainties and their elimination from the process, aims to extract the rules and investigate the correlation between parameters and flood occurrence simultaneously by using rough sets theory. The results of the current research show that 72% of flood occurrences recorded in 2007 are consistent with the obtained rules, which indicate the ability of rough sets theory in extracting forecasting rules of natural phenomena occurrence which have the highest complexity. The results of this research can be utilized in crisis management planning and natural disasters control.

Tsunami is a series of water waves caused by the displacement of a large amount of water which is generated by underwater earthquake, volcano, landslide or other disturbances below water. The Makran Subduction Zone (MSZ) is one of the regions that have potential to generate tsunami which also has been occurred in 1985 and is capable of another one. In MSZ, the coasts of Chabahar Bay are at risk of tsunami. This bay is an important region from economical aspect for Iran and there are two important ports there which make it strategic for economy and international trade. According to their location in bay, in case of tsunami, there will be huge loss because of delay in ships schedule for import and export and to the ports facilities. So in this study, the aim is to estimate total economic loss from Makran zone tsunami for local economy. According to a numerical simulation of tsunami based on a probable earthquake, all coastal zones areas in Chabahar bay with inundation map are considered in three assumed scenarios (weak, moderate and strong) which is shown in Figure 1. Figure 1- Inundation tsunami area in Chabahar Bay in worst scenario To have a better view of total economic loss, we estimate TEL for two scenarios. In worst scenario with earthquake magnitude of about 9.1 Richter and maximum inundation all sectors will be affected by tsunami but in best scenario with earthquake magnitude of about 8.1 Richter only human life lost and two damaged trade ports will be the significant items. Although we have tried to consider as much as possible items, but because of lack of data, the Total Economic Loss (TEL) is minimum loss to Chabahar bay. Marine hazard costs are categorized in three groups include direct costs, indirect costs and hidden costs. In this study we have applied Probable Maximum Loss (PML) to estimate total costs. The damage of tsunami could consider in four sectors include: social sectors, infrastructure, productive sectors and cress-sector. Among all mentioned sectors, buildings are more vulnerable to tsunami which PTVA model is used for that. This model was developed to provide first order assessment of building vulnerability and by calculating Relative Vulnerability Index (RVI) for each coastal zone building, the probable loss in residential zones in Chabahar Bay is estimated. RVI for each building has estimated as follow: RVI = 2/3 (SV) + 1/3 (WV) Where SV is the standardized score for the structural vulnerability and WV is the standardized score for the vulnerability to water intrusion. For other sectors we have applied appropriate economic methods include damage cost and replacement cost approach and for those that there were no data and accurate documents, benefit transfer method have been used. Each coastal region is divided to sub areas and in accordance with inundation map, via google map and other official documents, numbers of buildings and their characteristics are provided. Then with economic methods and PTVA model, economic loss for all sectors has been calculated. Discussion of Results & The purpose of this study is to estimate the total economic loss of probable tsunami in Makran zone and especially in Chabahar bay in Iran. As this bay is very strategic for international trade and fishery in south of Iran, the costs of marine hazards like tsunami is economically important. For doing that affected sectors is categorized to four items includes: social sector, infrastructure, productive sector and cross-sectoral. In social sector, housing is the most vulnerable and important item which needs additional consideration. So the special model for buildings are provided by Papathoma et al. in 2003 and by considering each building characteristics, the vulnerability index and the total loss could be estimate. The second important item is human life loss that is one of the most costs in all marine hazards especially tsunami. In 2011 tsunami in Japan, about 15,000 people were lost or died which is a huge loss. Infrastructures and constructions in coastal areas are more fragile in tsunami and by stop their services, additional costs will occur after tsunami. In Chabahar bay only in Chabahar province and Konarak province there is population and production firms and because of that only the inundation map for these two regions are considered. Inside bay, only one desalination plant is working and there are no residential places. These maps are shown in figure 2. Figure 2- Inundation map of tsunami in residential regions in Chabahar Bay The total estimate of damages and losses from probable tsunami in MSZ in Chabahar Bay in two scenarios (worst scenario and best scenario) is summarized in table 1. As shown in table 1, in worst scenario human life lost and ports is the first and second item of economic costs. In this scenario the total impact is about US$ 1.4 billion that could accrue if suitable management risk don’t establish in this area. In best scenario total loss is equal to US$ 828 million and ports are the first target for damages of tsunami waves. Table 1- Summary of damage and losses from probable tsunami in Chabahar bay Sectors for damage Total Impact (Damage and Losses) ($ 2014) In worst case Total Impact (Damage and Losses) ($ 2014) In best case Social sector Housing 16,455,660 - Health 18,000 18,000 Human life 500,000,000 250,000,000 Education 5,468,750 - Culture and religion 16,900 - Infrastructure Transports 1,321,370 - Ports (50% damage) 450,000,000 450,000,000 Energy 622,525 - Communication 1,414,430 - Water and sanitation 3,859,957 1,278,985 Breakwater 6,338,683 4,282,218 Productive sector Fisheries and lobsters 121,090,836 121,090,836 Enterprises 308,456,107 - Corss-sectoral Governance 201,000 -Environment 1,305,057 1,305,057 Total Impact 1,416,568,295 827,975,096 The total impact in best scenario is about US$ 827 million which is still considerable. The second stage impacts is make low GDP growth and reciprocate of that needs much time an effort. Although it is not possible to omit all damages and losses but by put some rules for building construction, provide appropriate guide and evacuation map to resident and give informational brochures to resident and tourists, we could diminish economic costs of tsunami in Chabahar Bay.

The average annual precipitation in Iran is about 250 mm that is not regularly distributed spatially and temporally. More than 70 percent of total precipitation is not accessible due to evapotranspiration. Total renewable water resources of the country are estimated to be around 130 billion cubic meters. In spite of limitation in water resources, they are not used properly. Agriculture is considered as the biggest sector that uses around 90 percent of total accessible water. Accordingly, any mismanagement of water usage in this section can make a remarkable damage to the country water resources. Paying attention to virtual water content of products is one of the methods to reduce water usage in this section by selecting proper agricultural products for each area. Virtual water is a measure of the total water used in production of a good or service. The concept was initially used to illustrate the advantages to water scarce nations of trade with other nations, rather than attempting to produce all goods locally. In recent times the concept has been applied to argue against production of commodities with high embodied water content, or to argue against their export on the basis that these activities waste scarce water resources. Virtual water estimates have also been used as an indicator of environmental damage of certain production activities. Estimation of a product’s virtual water content contains more than just considering water directly applied to growth or to process. In the case of agriculture, it should also attribute, for example, the water contained in producing fertilizers and pesticides used on a farm, and the water used to grow and process grains fed to animals. Moreover, it must do so over the full lifespan of a plant, and also include all the water used at postharvest stages of production, including any inputs to those stages. Generally, water associated with transportation must also be included, but this usually turns out to be a small and negligible amount. Regarding its remarkable demand all around the world, wheat is one of the most strategic agricultural products. Accordingly any decision towards changing the crop production may have distinct local, regional and global effects. On the other hand, considering the dominance of conventional irrigation methods in Iran which impose remarkably higher stress on water resources in comparison with developed countries, an effort should be made. To achieve a wheat farming template through which the optimized amount of water is needed to have the maximum potential crop, a survey should be run and the whole country should be classified in categories. The wheat farming priority then should be attributed to provinces where the most optimized conditions are observed. Wheat is the main agricultural product in Iran and considering its significance and remarkable consumption, its farming in areas with lower water consumption would cause a reduction of water usage in agriculture section. Wheat virtual water is equal to the amount of net water required for farming divided by produced wheat per hectare in each province. In this paper wheat yield, net water required for farming, irrigation water and farming area in each province has been investigated and by comparing these data for each province, proper areas for farming this important and strategic agricultural product is recommended. In order to evaluate the water demand in different areas CROPWAT software is used. Finalized data are shown through maps in GIS environment. As it is seen in Figure 1 net water demand for wheat crop in central parts of Iran is higher than marginal areas. Minimal values are seen in Caspian Sea coastline. Figure 1- Net water demand for wheat crop in different provinces of Iran As it is seen in Figure 2 the highest values of irrigation need are observed in central and southeastern parts (Qom, Isfahan, Yazd, Kerman, Sistan and Baluchestan provinces). Figure 2- Wheat irrigation need in different provinces of Iran On the other hand the lowest values are seen in north and northwestern areas (Guilan, Mazandaran, Golestan, Ardebil, East and West Azerbaijans, Ilam, Kohkilooyeh and Boyerahmad and Kermanshah provinces). Besides water demand and irrigation need, wheat yield should also be taken into consideration. Wheat yield in different provinces of Iran is shown in this paper. As it is seen the lowest yield is observed in eastern provinces and also in Bushehr where remarkable water shortage and conventional irrigation methods exist. Wheat yield in provinces like Tehran and Kordestan are estimated to be more than five tons per hectare, while provinces like Qazvin, Hamedan, Zanjan and Hormozgan have wheat yields greater than four tons per hectare. As a rule of thumb, the farming priority should be done to provinces where the highest wheat yields are observed. The largest wheat farms are located in Khuzestan province. This province holds the 13th rank in irrigation need and 18th rank in wheat yield. Accordingly, any enhancement project should be stopped. A similar status is seen in provinces like Fars, Khorasan razavi and Kerman. According to the results there is no coincidence between the optimization of water demand, wheat yield and surface area of wheat farming in different provinces. This fact would be terminated in more water loss and stress. The largest wheat farming areas are located in provinces like Khuzestan, Fars and Khorasan razavi where a remarkable irrigation demand is observed. Accordingly a shift should be occurred towards northern and western provinces where less irrigation need is observed.

Climate change is one of the most significant challenges in sustainable development that has negative effects on land and marine ecosystems. This phenomenon leads to imbalances that cause effects including hydrological changes, increased soil erosion, increased runoffs and reduced groundwater aquifer feeding, etc. Effects of climate changes over the past decade have significantly increased in Ecology and Hydrology Literature. Therefore, researches have increased in this area with focusing on climate change. Furthermore, researchers know pressure on wetlands likely due to changes in the hydrological regime directly, and the effects of temperature change and lands-use indirectly. The purpose of this study is to predict climate change important parameters in the study area and management planning of Agh Gol wetland in the predicted conditions to be protected against drought in the coming years. Also, knowing the drought years can provide better and more comprehensive management model for the study area. The study area: Natural and seasonal Agh Gol wetland is located in 34 degrees and 49 minutes into eastern longitude and 29 degrees and 2 minutes into northern latitude. This wetland that is a Hunting Prohibited Area in Hamedan province in recent years as other water sources was exposed to extra (ecological) pressure of sources, which led to drying up of wetlands in recent years. In this study, we tried to detect the characteristics, climatic and hydrological changes in addition to land-use and factors influencing the revival of the dry wetland and present the strategies affecting the revival of this wetland. This study was based on data obtained from synoptic stations of around Agh Gol wetland. To determine the severity of the drought, indices including SPI, RAI, and PNPI were used over the last 30 years. Also in this study to show the trend of changes and calculation of time series in climatic parameters, Mann-Kendall graphical test was used. In Mann Kendall graphical test each value in the time series, is compared continuously and subsequently with the rest of the series values. Discussion of Kendall graphical test results in Figure (2) shows that with respect to collision of Diagrams u and u' for temperature indicator outside the critical range a significant trend for the temperature indicator can be recognized in Nozheh Station. Results and the trend of graph changes indicate the occurrence of mutation for temperature indicator in Nozheh station, in the years 2007, 2010, and 2012. Also through 1999, the temperature indicator at the station has shown a positive trend. On the other hand, with the analysis of rainfall indicator at this station the existence of a significant trend in recent years is emphasized and the results indicate observing a mutation in 2013. The rainfall index shows a negative trend at this station and it can be due to reduction of precipitation at the station in recent years. Figure 1. GraphicalKendalltest, Hamedan-Nozhehweather station The results of the analysis of Kendall graph in Weather Station of Hamedan-Airport (Figure 3) in the time period of study (1984-2013) confirm a significant trend for temperature indicator with regard to cross of Line u from the critical point. The results show that in temperature indicator of Hamadan-Airport Station in the years 2008 and 2009 a mutation has occurred that can be a trigger for abrupt climatic change. Changes of Line u in this station has a positive trend considering that this line in the range u> +1.96 has experienced an upward turn and can confirm the existence of time series in Hamedan-Airport station. Figure 2. GraphicalKendalltest, Hamadan-airportweather station The results of Mann-Kandall model in weather station of Malayer in the period 1994 to 2013, due to inclusion of Line u for two indicators of temperature and precipitation in the range and failure to observe the trend due to placement of random series in data of this station does not show a significant trend for these indicators. Figure 3. GraphicalKendalltest, Malayer weather station Investigation of drought indices according to Figure 5 represents that based on RAI index in the years 1985, 1990, 1995, 2001, 2008, Hamedan- Airport Station has experienced very dry years and in the rest of the study period, the region has experienced moderate or mild drought. Figure 4.Trends of changes of Drought Indices in Hamadan- Airport weather station Investigating the drought index in Hamedan- Nozheh station showed that for the years 2013, 2012 and 1999, the region has experienced severe dry years according to RAI index. In other years, the region has not been in satisfactory condition, and has experienced years with relative drought. Figure 5. Trends of changes of Drought Indices in Hamadan- Nozheh weather station Evaluating trend of changes of drought in Malayer Station in terms of RAI index showed that in the years 1995, 1997, 1998, 1999 and 2008, the drought index has been in cute conditions. And the rest years of the study period in this station are associated with normal or mildly drought. Figure 6. Trends of changes of Drought Indices in Malayer weather station The study area around the wetland, over a 30-year study period (1984-2013), according to climatic conditions in meteorological stations did not have stable conditions. Thus, analysis of the climatic results emphasizes that in the years 1999, 2001, 2005, 2008 and recent years (2010- 2013) a significant trend of drought has been experienced in terms of all analyses. The use of drought indices in this study suggests the tensions that region has endured over a period of 30 years. Comparing these results with evaluating the trend of changes and time course of changes and modifications indicated that the greatest changes occurred in the temperature indicator and precipitation variations usually appear with a delay of up to several years after the temperature mutations in the region. Therefore, by a careful planning and consideration of the interests of all concerned and influential parties we can present a comprehensive plan for the sustainable management, and controlling and mitigating the effects of drought and climate change, in Agh Gol wetland,, to be witness of dewatering of wetlands in the coming years. Also presenting a sustainable agriculture program in accordance with the climatic conditions of the region may contribute to regional stability a lot.

Thermal Infrared Integrated Dust Index (TIIDI) is one of indices that is presented in this direction. The index operates based on four brightness temperature difference including Wavelengths 3.7, 8.6, 11 and 12 micrometer. According to the studies, BTD (BT12-BT11) is used for cloud detection. BTD (BT8.6-BT11) is the index for separation for dust from sandy surface and BTD (BT3.7-BT11) is employed for differentiating dust from vegetation in addition it shows dust intensity. In general, according to Weather Meteorological Organization (WMO) protocol, dust phenomena is divided four categories based on reducing of horizontal visibility: Dust-in-Suspension: Its development is suspended, visibility of less than 10 km Blowing Storm: Reduced visibility from 1 to 10 km Dust Storm: Reduced visibility from 200 to 1000 m Severe Dust Storm: strong gust of wind with large dust particles and reduced visibility from less than 200 m. Yang by combining these tree parameters created the TIIDI index. (1) Dust Sky without dust and cloud Cloud In formula (1), if the get the positive value,‘a’ would be 10 and in otherwise it would be. Based on the has a small value for sky without dust and cloud, the index TIIDI get less value for sky without dust and cloud than dust. Therefore, using this index appears reasonable according to topographic complexity that exists in west and southwest of Iran. Because in these areas there is a combination of mountainous terrain with vegetation or bare land and vegetation. Consequently, the suggested index by Yang is developed and customized. The modified can estimate dust storm intensity with improved accuracy. Data :In this research we used MODIS products including MOD021, MCD12Q1, MOD35, topographic map 1:25000 of Ilam ()and Khuzestan () to obtain land cover types and also meteorological data of the two provincesduring (2005-2012) years are used to implement the algorithmsand evaluate it. The ground data is for the 30 stations of the two mentioned provinces, thus all analysis related to computing and image processing is done on the pixel location of the 30 stations in the image. As mentioned before, the aim of this study is detection of dust pixels using corrected TIIDI. Considering the fact that in the study area there are three types of classes namely cloud, dust and sky without clouds and dust. As a results, the radiative behavior of these three classes in thermal infrared bands of MODIS should be checked. Hence, in the first step appropriate training data must be collected for all three classes and then diagram of three classes’ radiation in thermal bands is obtained and analyzed. According to the results of previous research for sky without cloud and dust, BTD (BT31-BT32) is negative. Which means the slope line of band 31 to band 32 must be negative but it is positive like cloud due to the complexity of study area. Since a pixel in study area not only contains one class but also it contains more than one class such as building, vegetation, desert lands and wasteland. Because the spectral changes in surface emissivity will also cause change in the behavior of the index. If BTD (BT31-BT32) is positive for sky without cloud and dust, then cannot be concluded that TIIDI is positive. In this case, the dust and the sky without cloud and dust will have not a similar behavior. Dust based on the horizontal visibility is separated into four groups(See the introduction section). As previously mentioned dust intensity is defined based on four categories. Because one of the challenges that exist in dust detection is lower intensity dust event and horizontal visibility of more than a kilometer and also inability to detect them on true color MODIS image.According to what was said,TIIDI index must be improved for study area. Figure 1 shows that slope line of band 29 to band 32 for both dust and sky without cloud and dust is same and for both cases is positive. As a result, in the formula (2) BTD (BT32-BT29) can be replaced by BTD (BT31-BT32). (2) Dust Sky without dust and cloud Cloud Figure 1: reflectance behavior diagram of cloud, dust and sky without dust and cloud pixels in thermal infraredbands of MODIS Our studies on the iTIIDI for cloudy days, days of dust and the days when the sky is free of clouds and dust reveals that this index have smaller value (10-25) for sky without cloud and dust but in during dust event the values will be increased (more than 25). Also, iTIIDI index have negative value for cloud pixel. Therefore, first, by choosing zero threshold on iTIIDI cloud pixels can be eliminated then those have values more than 25 is classified as the dust pixels. From pixels that are known as dust pixels, if corrected index value is between 25 to 50 it shows weaker dust otherwise, if iTIIDI is more than 50 it specifies the dust with more intensity. Discussion of To assess the accuracy of the proposed indices and its success rate in dust detection, the indices on 6 July, 2009 (15 Tir, 1388) is calculated, where a severe dust storm occurred over the region. In this image that was taken at 10:35 AM local time, meteorological data shows the minimum and maximum horizontal visibility of 200 m and 6000 m, respectively in the study area. Based on beginning categories (See the introduction section), in this day severe dust storm is occurred. In the figure 4, results of enforcement iTIIDI index is shown on the image and is compared with the true color MODIS image for same day. As can be seen there is good agreement between image (a) and image (b). In addition, improved index can be able to detect dust as well as the severity of dust. In other hand, the accuracy of the developed method is evaluated using the ground observation data. 30 synoptic stations of meteorological data located in the provinces of the study area are listed in Table 1. These information includes horizontal visibility and meteorological codes. According to meteorological organization standards, during dust event and reducing the horizontal visibility, this parameter reaches less than 10 km and meteorological codes determine with value 05 or 06 or 07. The overall accuracy of corrected index corrected iTIIDI is about 65% for detection of dust pixel and the accuracy of 64 percent is achieved by using the TIIDI index. Figure (2) shows result of index implementation (iTIIDI)on image that is compared with RGB image on the same day (6 July, 2009). A C B Figure 2: Comparison of (A) MODIS RGB image that was taken on 6 July, 2009 (B) TIIDI index by Yang and (C) Improved index (iTIIDI) for dust detection for same day. In conclusion because of the land cover presented in the west and southwest of Iran that there are combined different classes such as Vegetation, Bare land or Sandy land, and Mountainous areas, a review of the indices proposed at a global level is inevitable. Since in this review, on the one hand, the former index is improved and on the other hand its threshold is customized. ThereforeThermal Infrared Integrated Dust Index (TIIDI)has been developed for dust detection and the improved index is presented. Although the accuracy achieved in this study is not more than 65 percent, the results obtained demonstrate the simplicity and accessibility of the method and by having an extensive coverage of MODIS data and its products would all increase the speed of the algorithm in dust detection. Also by comparing two indices the result show that the improved method not only is able to detect sever dust storm but also is able to detect less intense dust storm.

Inrtoduction :Developing countries and newly industrialized countries face the twin challenges of protecting the environment while also strengthening their economies. Over the past few decades, the intensified process of urbanization and industrialization undertaken by these countries, coupled with rapid population growth, has resulted in the degradation of the environmental quality. Particularly, the emission of harmful pollutants such as particulate matter has contributed considerably to a rapid drop in the air quality in the cities. Recent studies on the effects of chronic exposure to air pollution have identified PM10 as the pollutant most responsible for the life-shortening effect of dirty air. The major concerns for human health include effects on breathing and respiratory symptoms, aggravation of existing respiratory and cardiovascular disease, alterations in the body’s defense systems against foreign materials, damage to lung tissue, carcinogenesis and premature death. Particulate exposure might increase susceptibility to bacterial or viral respiratory infections, leading to an increased incidence of pneumonia in vulnerable members of the population. It might also aggravate the severity of underlying chronic lung disease, causing more frequent or severe exacerbation of airway disease or more rapid loss of lung function. Besides its adverse impact on human health, particulate matter can also result in visibility degradation. Matherial& this paper attempts to provide more insights into the epidemiological and valuation relationships of particulate air pollution which is apparently lacking in Iran. If cost of particulate air pollution were substantial, it would highlight the importance of not ignoring the environment in pursuing economic progresses. Given the available epidemiological data, PM10 may be regarded as an important and useful indicator for the health risk of air pollution. We use PM10 as the main indicator for air pollution and its impact on health as the proxy for the estimation of the economic cost of particulate air pollution. The most troubling finding from many recent scientific health studies in the air pollution epidemiological literature is that increase in ambient concentrations of particulate matter under 10 mg (PM10) is associated with increase in the risk of premature mortality. The most troubling finding from many recent scientific health studies in the air pollution epidemiological literature is that increase in ambient concentrations of particulate matter under 10 mg (PM10) is associated with increase in the risk of premature mortality. Once the links between emissions to human health effect have been established, the next stage requires the assignment of economic (monetary) value to the predicted health effects. In the case of health effects, the monetarization approach should determine values according to individual stated preferences (willingness to pay). It has been argued that E. Quah, T.L. Boon / Journal of Asian Economics 14 (2003) 73–90 75 if people’s preferences are a valid basis upon which to make judgments concerning changes in human well being, then it follows that changes in human mortality and morbidity should also be valued according to what individuals are willing to pay or willing to accept as compensation to forgo the change in health status. The value of a statistical life (VOSL) is the value of a small change in the risks associated with an unnamed member of a large group dying. COI measures the total cost of illness that is imposed on the society. These costs include value of the lost productivity (loss in earnings) due to illness, medical costs such as hospital care, home health care, medicine, services of the doctors and nurses; and other related out-of-pocket expenditures. We adopt the DRFs developed by Ostro (1994) and Rowe, (1995). The estimated health impact can be calculated by the following relationship: =where, dHij is the change in population’s risk of health impact i due to pollutant j; aij, slope from the dose response curve for health impact i due to pollutant j; POPi, population at risk of health effect i and dAj is the change in ambient concentration of air pollutant j. DRFs relate information on changes in ambient air quality for different pollutants to different health outcomes. The principle is that changes in ambient air pollution levels for certain pollutants can be statistically related to observed changes in morbidity and mortality in a population. Since there are great variations in the coefficients estimated by the various studies, three alternative assumptions about health effects are presented with the central estimate being given the most weight. The high (low) end estimates are calculated by increasing (decreasing) the coefficient by one estimated standard deviation. Ostro (1994) suggests to use 0.062, 0.096 and 0.13 as the lower, central and upper coefficient, respectively for the estimation of percentage change in mortality. Following the DRF in following formula, the number of cases of premature mortality due to PM10 can then be expressed as: Mortality = b 0.01 Crude Mortality Rate POP where b is the mortality coefficient (0.062, 0.096 and 0.13 for lower, central and higher estimate, respectively) and POP is the population exposed to risk. A similar approach is also used to estimate the effects of changes in air quality on air pollution-related illnesses. The increase in number of morbidity cases in terms of respiratory health admission (RHA), emergency room visits (ERV), restricted activity days (RAD), lower respiratory illness in children (LRI), asthma attacks, respiratory symptoms and chronic bronchitis can be estimated using the following formula: Morbidity = POP where ci is the morbidity coefficients for each discrete measure of morbidity effect and POP is the population exposed to risk. In recent years, environmental economists and policy makers have taken a lot of effort to estimate the value of change in the quality of the environment, and especially in reducing air pollution and its effect on the reduction of mortality in developing countries. One of these efforts is estimating V.S.L. through income elasticity method. This elasticity, which Bowled and Beghin estimate to range from 1.52 to 2.269, can be expressed as part of the following formula: = Where and are the value of statistical life in two countries, and Y denotes the per capital income in each nation. The e term is the income elasticity of WTP. To provide a check on the validity of our previous V.S.L. estimates, we use this Bowland- Beghin along with our Iranian V.S.L. numbers, to infer the value of a for Iran. Assuming a US value of statistical life of $5 million, PPP-adjusted per capital incomes to estimate the V.S.L. through this method, the simple concept of income elasticity in microeconomics is used. Using this method, it is possible to use the V.S.L. of other countries to determine the V.S.L. for Iran. When the V.S.L. of another country is used to estimate the V.S.L. of Iran, the effect of income should be considered in the estimation and the V.S.L. should be adjusted on that basis. In order to achieve more precision and care, in this study the researchers used three income elasticity of 1, 1.5, and 2. If WTPA is kept constant, the elasticity of 1 will show a higher elasticity compared to 1.5. Similarly, the income elasticity of 1.5 demonstrates a higher elasticity compared to income elasticity of 2 for Iran. Therefore, the income elasticity of 1 is Upper Limit, the income elasticity of 2 is Lower Limit and the income elasticity of 1.5 is mid Limit. In order to estimate the direct medical costs, sufficient number of general hospitals were selected. Then, all the files pertaining to the illnesses caused by air pollution were extracted. the required information were extracted from the files and registered in the prepared forms. This information included the number of the patient’s file, age, sex, the costs of hoteling, cost of drugs, cost of physician, cost of surgery, cost of physiotherapy, cost of consumed materials, duration of hospitalization, type of insurance, job and the total expenditure. In the end, the mean of the total direct costs of each illness in each and every group of hospitals was estimated. Discussion of Result & A recent dust phenomenon cover in the South West and the West's has adverse effects on human health the most important effects is on Mortality and diseases such as chronic bronchitis, asthma, and Infections respiRatory in children mild. The aim of this study was to estimate the number of premature Mortality and morbidity and economic costs of the effects of particulate matter (pm10) in Khuzestan, Kermanshah and Kurdistan in 1389, which are calculated using the dose response, the value of statistical life and cost of illness methods. The paper adopts a three-step procedure to estimate the cost of particulate air pollution. Firstly, the ambient concentration of the pollutant, PM10, is determined. The second step involves the use of one increasingly accepted methodology—the damage function approach using dose–response relationships—to estimate the health impacts of PM10 pollution. The health impacts considered here are the increase in mortality or morbidity. The last step then assigns economic (monetary) values to the increase in mortality and morbidity.The results show that attributable to air pollution 2783, 752 and 370 of Mortality (central estimate) in the province of Khuzestan, Kermanshah and Kurdistan PM10 in 1389 and is also about 12 361 hospital admissions, 244,157 visits to emergency, 44534793 restricted activity days (days when the N¬ days, some but not all activities are normal-width), 446008 lower respiratory infections in children, 59751598 asthma attacks, and 63,047 chronic bronchitis, in the Selected province outcome dust occurred. The total cost of mortality associated with particulate pollution PM10 is calculated using the statistical value of life method in the province of Khuzestan, Kermanshah and Kurdistan, 3506580000, 947520000 and 466200000 dollars respectively,that is 0.8, 0.2 and 0.1 percent of Iran”s GDP respectively, and using the money blood is estimated, 100,000, 20,715 and 10,332 dollars respectively. Direct medical costs of disease, asthma, chronic bronchitis and lower respiratory infections in children associated with particulate pollution PM10 is calculated in selected provinces in 1389, 35 645, 37 and 266 billion dollars (central estimate) and the average opportunity cost per patient (during hospital stay) is calculated 85775. According to increasing importance of air pollution from dust particles and adverse effects on human health And the need to estimate the health damage caused by this phenomenon, this phenomenon has been increasing recognition of the importance and necessity of this phenomenon, And it must be admitted that this requires detailed knowledge and resources that leads to the release of particulate matter have been provided. One of the major problems in this area, prevent and find the causes of increase or decrease air pollution and also are predicted pollution-reducing factors.

In order to achieve sustainable development, it is necessary to obtain and adopt planning procedures based on Multi Criteria Evaluation of natural environment. Since biophysical (natural) environment has limited ecological capabilities for human use, ecological capability assessment, as an essence for environmental studies and with the aim of preventing existing crises, yields proper grounds for environmental planning. The analysis of land capability and sufficiency for urban development is one of the main categories with which urban planners deal. The country's political divisions Yasuj city is center Kohgiluyeh and Boyerahmad, is located in the eastern part of the province and in the Zagros mountains and cold. The area to the north of the province Esfahan, of the south and East to the province fars and the West and South West Provinces cities Gachsaran and Dehdasht is limited. Yasuj population in the years 1345, 1355, 1365, 1375,1385,1390 respectively 931 people, 4524 people, 29,991 people, 69,133 people, 100,544 people, 108,505 people. Undoubtedly among all cities Kohgiluyeh and Boyerahmad, Yasuj is the only city population and its area considerably, will increase the concentrations of various services. It is due to the special characteristics such as the political and administrative center of the province, the establishment of institutions and government agencies and enjoyment of the services and facilities more than other cities and towns and villages moved to the city, yet has a high population growth. Therefore, the optimal plan based on scientific principles and standards of ecological and Estimation of land for urban development in the future prospects of future problems can be minimized or even prevented. Extent of the scope of the study, 127/6 square kilometers and 1:100,000 scale used in this study have been selected. To do so, after detecting the ecological resources of the area (scale 1: 100000) the obtained data was introduced to Arc GIS software. Since implementation and applicability of urban land use necessitated synchronized evaluation of numerous criteria or variables, the study utilized spatial multi criteria evaluation method (SMCEM). And therefore, the initial attempts focused on preparation and standardization of the criteria maps. Fuzzy expert system and linear functions were used for the purpose of the study. To analyze land proportion for the development of the expected application, Weighted Linear Combination (WLC) method was utilized and then by combining layers of information and analysis on fuzzy evaluation software can be ecologically relevant maps were prepared. Sustainable and unsustainable resources were identified in a research scale. Also, the criteria and variables were identified for evaluation yasuj city for implementation urban land use. Overall, data were obtained through twenty-one layers as criteria maps for spatial evaluation of implementation urban land use. Analytic Hierarchy Process (AHP) In this research, each criterion or sub criterion was weighing using pair wise comparison method and to selecting the preferred criteria, the preference,s value table of the saaty is used. To ease the calculating of the weights in purpose of preference degrees and hierarchies the Expert Choice software was used. The operations of AHP, the weights and compared with CR are evaluated. It is a condition of accepting the CR ratio is less than 0/1. Remarkably, in this study, the number of CR 06/0, respectively, which represents the result is acceptable. Weights were calculated by the method of integrated layers methods WLC is used. Weighted Linear Combination (WLC) Weighted linear combination (WLC) technique was applied to select the best option (site), according to criteria evaluation method. The site which obtained the highest score is identified as the suitable site or class. In this method, the value of each criterion is calculated by the following equation: Ai = Sj Wj Xij Where, Xij is the value of i alternative towards j criterion, is a standardized weight as aggregation of all weights is equal to one (S WJ = 1). The calculated weights showed the relative importance of each criterion and preferred alternative is selected by defining of maximum value of Ai (i = 1, 2,3, …, n). To applying the weighted linear combination (WLC) method. Finally, Standard raster layers all factors in all three of the physicochemical and biological and socio - economic weights derived from the techniques of analytic hierarchy process multiple groups. W1 S1 + W2 S2 + … + Wi Si Wi = Weight Layer Si = Layer standard then Layers of standardized weight criteria for Multi-criteria evaluation analysis of software GIS, Using the orders Raster Calculate Were called. In order to achieve the overall assessment rating based on the proposed mathematical model and order Fuzzy Overlay overlay were tagged. Urbun Land Use= ([Slop 01] × 0.263) + ([Land Use 01] × 0.162) + ([Quantity Water 01] × 0.150) + ([Soil Type 01]× 0.089) + ([hypso 01] × 0.072) + ([Surface Water 01] × 0.05) + ([Vegetation Density 01] × 0.05) + ([aspect 01] × 0.041) + ([Bed rock 01] × 0.031) + ([Wind power 01] × 0.021) + ([Vegetation type 01] × 0.016) + ([Fault 01] × 0.014) + ([Depth 01] × 0.013) + |([Geo 01] × 0.011) + ([Forest 01] × 0.008) + ([Rain 01] × 0.005) + ([Agriculture 01] × 0.005) + ([temperature 01] × 0.003) + ([River 01] × 0.003) + ([Airport 01] × 0.001) + ([Indst complex 01] × 0.001) Map of the final classification of thevaluation of ecological capability on yasuj city for implementation urban land use in this study shows that that a total of 12736 hectare area of ​​about 3541 acres in the study area has high potential and 5153 acres area has good potential, 1678 hectares of medium power and 1,898 acres low power and 466 acres of the study area is very weak power. Table 1 shows an ecological potential classes of yasuj city for implementation urban land use. Table 1: ecological potential classes of yasuj city potential classes Area (hectare) Area (square kilometers) high 3541 35414807/14 Good 5153 51528911/01 Medium 1678 16782526/77 Low 1898 18976520/63 very weak 466 4660145/622 Total 12736 127362911/2 Studies show that in parts of East and South and South West yasuj city by natural constraints such as Zagros Mountains and Dense forests oak and high slope land are confronted. By conducting WLC model, direction are found that conform to the present realities based on field evidences and comparison of obtained results. Limiting factors such as the Zagros heights, high slope, oak mass foret, fault, agriculturad lands, rivers to prevent some of the environmental allocation for the urban development opplication. The mapping final shows regions suitable for physical urban development of the city. The results and finding of this research were applied by urban planners.

“Green infrastructure” is a term that describes the abundance and distribution of natural features providing ecological services necessary for community wellbeing specially in urban areas where these are limited. Green infrastructure is increasingly espoused by landscape conservation and metropolitan planning because it is an effective way to surrogate ecological network functions where landscapes are highly impacted by anthropogenic changes. In this study structural characteristic of open and green patch network called green infrastructure was central in deciding urban management strategies because of their life support services. Finally, applicable strategies have been presented for a gradual regeneration according to the intensity and extent of degradation these patches and other natural elements face in each urban district. Decision making regarding selection of each strategy and priorities are estimated in correlation to the current condition of green infrastructure as well as the speed of alteration they are experiencing in Tehran (with very rapid change or alteration). City of Tehran, with 730 km2 area is located in the southern slope of Alrborz Mountains and Northern margins of central desert of Iran, and has 22 urban districts. Tehran's urban landscape structure, viability and environment have incredible speed of fluctuation in time and in space. This pace of change forced us to focus on conservative policies and protection of natural conditions, in order to prevent landscape structure destruction before any other objective (for rehabilitation). The method used in this study based on structure - function interdependency is basic concepts of landscape ecology such as patch features are considered to evaluate the degree of fragmentation and connectivity of green infrastructure network at the landscape scale while considering its alteration speed. In order to present optimized ecological services and effective function at the scale of urban landscape, these infrastructures are required to have sufficient presence, high stability with appropriate composition and configuration regarding their spatial distribution. Therefore, landscape metrics were used to evaluate these features of green infrastructure quantitatively. Selected metrics regarding evaluation of composition and configuration of landscape elements related to our research goal were selected to be PD, MPS, MNND and CAP. Their quantities were then used at landscape and patch type levels as finding for discussions and conclusion. Discussion and Landsat satellite image was used for derivation land cover information and then landscape metrics was estimated based on time series land cover maps (Fig. 1 and 2). Structural analysis of the current conditions of greenspace: Districts in the north of Tehran specially district one and three had better conditions in terms of many parameters (like presence of green patches, their stability and distribution) rather than the other ones. In turn, central districts specially districts 10 and 17 and also those located from center to east and west had inappropriate conditions in terms of most metrics. The presence of green patches in these districts was very low, and the patches were fine grain with low stability. Structural analysis of the current conditions of open space: In terms of open space of Tehran, it can be noted that in districts located on the west edge like 19 and 22 and specially 22, the condition of the patches was better than the others. The result showed highly presence and stability of large open patches in these areas. Nevertheless, the conditions of open patches distributions in these districts were low and the north districts had better distribution of open patches. In turn, conditions of open patches in central districts especially 10, 17 and also 8 in northeast were inappropriate and presence of open patches of fine with low stability and relatively inappropriate distribution were observed. Total analysis of changes in Tehran green space (2003-2013): In green space of Tehran, during the studied period, the process of all metrics changes except CAP was similar in all districts such that MNND and MPS have decreased and PD has increased in all districts. Therefore, it can be concluded that decrease of the patch size and their fine size has decreased their stabilities in all districts. Despite of MNND decrease in all districts which shows a relatively high connectivity among green patches, this change cannot be considered as a positive one as regarding to PD and MPS changes, it can be concluded that green patches have fragmented. CAP of green patches had been increased in 12 districts and decreased in 6 districts. This trend was constant in four districts. Total analysis of changes in open space of Tehran (2003 -2013): During the studied time, in terms of open space metrics, CAP has decreased in all districts except districts 7, 12 and 14, PD had been increased in most districts and constant in some ones. MPS and MNND had been a decreased in all districts. Regarding to the process of open patches changes, it can be noted that open patches have had a destructive process (decrease presence and stability of open patches) in most districts. The trend of PD and MNND changes also showed the fragmentation of open patches in Tehran. Fig. 1: Classified image of study area in 2003 Fig. 2: Classified image of study area in 2013 Planning Strategies: Protective strategy: where the existing landscape supports sustainable process and patterns, a protective strategy should be employed (even along with defensive strategy in some cases suffering a regressive tendency). This strategy can be recommended for greenspace protection in districts located in north, west and southwestern of Tehran and for open space protection, northern and northwester districts are prioritized, too. Rehabilitation strategy: for where the existing landscape is disturbed and fragmented, such as in those districts of northern and southwestern Tehran. These should have rehabilitation of natural elements as priority task. Development (offensive) strategy: is to be recommended for those urban districts with a low presence of green and open patch as well as with low connectedness. Districts located in south, east and central of Tehran, are required to development of greenspace. Defensive strategy: was most needed in districts where these contain valuable natural elements (such as north and west of Tehran) that provide desire function. Utilization strategy can be employed for these districts but defensive attitudes are needed to sustain the present situation. Findings show that the main problem of green infrastructural network in Tehran may be its uneven distribution, with low connectivity and almost non-existing in the central city matrix. This along with the much reduced natural matrix connectivity, have created an unsustainable urban texture with very low livability and polluted atmosphere. It can be noted that in terms of green space, expanding the area has been the only plan with no consideration regarding advantageous use of all natural spaces of Tehran at micro up to macro scale planning. Hence a better configuration of natural patches with connectedness to each other (specially to 9 river valleys and the row of hills crossing them in perpendicular) should be also part of a comprehensive green structural renovation and development strategy for the future of Tehran. In order to overcome landscape structural degradation an strategic perspective is needed to be based on pattern-process principles and to be implemented based on landscape linking concepts. This planning may well follow strategic perspectives found by this research which is also based on several years of research by others along with frequent revisions. Added value of all these efforts is here presented by our final completion looking for a comprehensive synthesis.

Growing use of hydrocarbon constituents in various industries have generated significant quantities of hazardous wastes which lead to environmental pollution. In recent years, the strong global demands for fossil fuels and industrial chemicals have resulted in the release of some of these compounds into soil, water and air.Hydrocarbon-contaminated soils are among the important environmental issues which could be present around refineries, fuel stations, pipelines and storage tanks. Selection of an effective solution for cleanup of contaminated sites depends on several factors including soil conditions and pollutant concentrations, thus requiring one or more treatment techniques for cleanup of such site. In general, contaminated sites remediation methods can be classified as in situ or ex situ types. Several technologies, such as chemical oxidation, biostimulation and bioagumentation, or electrokinetic oxidation, can be used for the treatment of these specific polluted sites. Therefore, many different technologies have been developed for remediation of contaminated soils: biological treatment, soil washing with surfactants, air stripping, thermal desorption, incineration, etc. Among the various processes, thermal desorption is a very attractive one because it can promptly treat the contaminated soils with high efficiency, irrespective of their chemical species.They are the most popular and versatile due to their removal efficiency, cost and required time. According to their treatment temperatures, treatments can be classified as low-temperature (100–350 ◦C) and high-temperature (350–600 ◦C) thermal desorption, involving the physical separation of contaminants from the soil, and thermal destruction (600–1000 ◦C), involving the chemical modification of contaminants. In this study, soil samples were collected from Baghershahr contaminated area in south of Tehran, adjacent to Tehran oil refinery.The soil in the area is polluted with different hazardous hydrocarbons due to the leaching of the refinery. LTTD remediation method were evaluated for decontamination of this area soil. To assess the temperature and residence time on removal efficiency of gasoline from contaminated soil, LTTD were conducted on temperature of 90, 110, and 150 ° C and residence time of 10, 20 and 25 minutes. Soil sampling was carried out at the vicinity of Tehran oil refinery area. Samples were collected from 10-30 cm depths of the ground surface and placed in glass jars. After transferring the samples to the laboratory, tests were performed to determine the moisture content and geotechnical properties of the samples such as soil texture, Atterberg’s limits, soil classification and the amount of organic matter. The EPA and ASTM methodswere applied to test the samples. Due to low concentrations of hydrocarbons in the soil, the samples were spiked with gasoline at two concentrations of 4000 and 10000 ppm. The spiking of the samples was carried out to acquire more clear results regarding the performance of LTTD experiments. Low temperature thermal desorption experiments were performed in a reaction glass.Moreover, two thermometers were used for measuring temperatures inside the chamber and the exhaust gas. A condenser was also connected to reaction glass to liquidity the generated vapors during the test. In order to investigate the effects of temperature and residence times on the removals of contaminants, the experiments were performed at different temperatures of 90, 110, 150 ° C and at three residence times of 10, 20 and 25 minutes. A gas chromatography with Flame Ionization Detector(GC-FID) instrumentwas used for analyzing the gasoline concentration. Results Moisture content :The solids processing capacity of a thermal desorption system is inversely proportional to the moisture content of the feed material. The presence of moisture in the excavated soils to be treated in the LTTD unit will determine the residence time required and heating requirements for effective removal of contaminants. In order for desorption of petroleum constituents to occur, most of the soil moisture must be evaporated in the desorber. This process can require significant additional thermal input to the desorber and excessive residence time for the soil in the desorber. In many LTTD studies which were conducted on the petroleum contaminated soils, the optimum ranges of moisture contents were between 10% to 20%(W/W). In this study, however the moisture content of the soil was measured to be 15%. Effects of operating parameters were investigated for the thermal treatment of petroleum contaminated soils in a desorber. Batch operation result shows that achieving to the significant efficiency depends on temperature and residence time. Removal efficiency :The minimum removal efficiency achieved for the soils with the 10000 ppm contaminants was 70.1% at the residence time of 10 minutes and temperature of 90 ° C. Nevertheless, regarding the 10000 ppm samples, the maximum removal efficiency of 87% was achieved for the samples at residence time of 25 minute and temperature of 150°C.Likewise, for 4000 ppm gasoline concentration soil samples, Maximum and minimum removal efficiencies were 80% and 94.45%, respectively. The overall results indicate that LTTD method is an appropriate remediation method for hydrocarbon contaminated sites. Temperature :In this study, temperature effect on the low temperature thermal desorbtion were evaluated. Treatment temperature is a key parameter affecting the degree of treatment of organic components. The required treatment temperature depends upon the specific types of petroleum contamination in the soil. The recommended treatment temperatures for various petroleum products and the operating temperature is in the range of boiling point of the chemicals. The actual temperature achieved by an LTTD system is a function of the moisture content and heat capacity of the soil, soil particle size, and the heat transfer and mixing characteristics of the thermal desorber. The results indicate that more significant removal efficiencies of removing gasoline from contaminated soil samples will achieve as temperature increased. For instance, as temperature increased from 110 to 150 °C in 4000 ppm gasoline contaminated sample and resident time of 25 minutes, the removal efficiencies increase from 90.3% to 93.4%. Residence Time :To demonstrate the effects of residence time on removal of gasoil from soil, experiments were conducted under 10, 20, and 25 residence time, which is a key parameter affecting the degree to which decontamination is achievable. Residence time depends upon the design and operation of the system, characteristics of the contaminants and the soil, and the degree of treatment required.Moreover, the removals of contaminants from the samples increased by increasing heating residence times. The maximum LTTD removal efficiency of 94.5% occurred in a time period between 20 to 25 minutes (i.e. 23 minutes) for the samples with 4000 ppm concentration, which is considered as optimum time for this concentration. Nevertheless, greater residence time is essential for decontamination of contaminated soil whit concentration of 10000 ppm of gasoline. Discussion and For sites with petroleum contaminated soils, the primary concern is to reduce the residual concentration of the organic constituents to or below regulatory levels. This criterion applies to both the soil surrounding the excavation and the soil that was excavated and thermally treated. The results indicate that LTTD remediation method is capable of gasoline contaminated soil removal with efficiency of greater than 90%. The resultsof LTTD tests also indicated that the increase in temperature from 90 to 110 and 150 °C increases the gasoline removal efficiencies. Furthermore, as residence time of process increased, the removal efficiencies of gasoline from soil increased. For instance, removal efficiency increased from 71% to 82.5% for 4000 ppm contaminated samples as the residence times increased from 10 minutes to 25 minutes.The data obtained from the low temperature thermal desorption experiments indicate that the higher removal efficiencies of volatile gasoline hydrocarbons in soils with concentrations of 10000 ppm will be achieved at residence times and temperature of above 25 minutes and 150 °C.

PCBs belong to a broad family of man-made organic chemicals known as chlorinated hydrocarbons. They have a range of toxicity and vary in consistency from thin, light-colored liquids to yellow or black waxy solids. Due to their non-flammability, chemical stability, high boiling point, and electrical insulating properties, PCBs were used in hundreds of industrial and commercial applications including electrical, heat transfer, and hydraulic equipment; as plasticizers in paints, plastics, and rubber products; in pigments, dyes, and carbonless copy paper; and many other industrial applications.PCB (or PCBs) is a category, or family, of chemical compounds formed by the addition of Chlorine (Cl2) to Biphenyl (C12H10), which is a dual-ring structure comprising two 6-carbon Benzene rings linked by a single carbon-carbon bond. Polychlorinated biphenyl, commonly referred to as PCB, was in widespread use as a dielectric fluid due to its special physical and chemical properties. Since then, PCBs have developed a notorious reputation due to their potential for environmental contamination and for their potential to react to form other, highly toxic substances. Under incomplete combustion, PCBs can form products such as furans and dioxins. Due also to the stability of PCB and its potential for environmental accumulation and harm. Many different process can and have been used to destroy PCBs, but each has its limitations and potential risks. High temperature incineration has been widely used, but has the inherent risk that if inadequate temperatures are attained at the point of destruction of the PCB, dioxins and furans can be formed. Another dechlorination process is the gas-phase reduction, in which the main difference is the chemical used as reducing reagents. The molten salt process has been used on a small scale since 1950 [9]. In the process, a bed of alkaline molten salt, usually sodium carbonate oxidizes organic materials. Any chlorine, sulfur, phosphorous, or ash products in the feed are converted to inorganic salts and retained in the salt bed. This process cannot treat soils and other materials with a high content of inert material. With bench and pilot scale systems, PCBs was destroyed in molten sodium carbonate/sodium chloride with efficiencies of 99.99 Percent. Destruction efficiency with chlordane was apparently not determined. Indeed, the use of performance measures, "destruction efficiency" and DRE, in describing the performance of this technology suggests that one may have been used inaccurately. i.e., destruction efficiency can be determined only if all process residues are analyzed for the presence of undestroyed chemicals of concern. Chemical dehalogenation (or dechlorination) is a chemical process used to remove halogens (usually chlorine) from a chemical contaminant by hydrogen or a reducing radical containing hydrogen donor. In the case of based catalyzed dechlorination, the process key is the hydrogen donor with an oxidation potential low enough to produce nucleophilic hydrogen in the presence of base Na+. On the other hand, for the Eco-Logic process gaseous hydrogen at high temperature is the reducing reagent to destroy chlorinated organic compounds. Chemical dehalogenation technologies are applicable to halogenated aromatic compounds, including PCBs, PCDDs, PCDFs, …. Treated transformer oil was segregated from the contents (Fig.1.). Figure 1- PCB Destruction Flow Chart In this study a practical and efficient disposal dechlorination process has been reported for Tehran Besat Power Plant PCBs less than 10000 ppm. The transformer oil containing commercial PCB mixtures (Aroclor 1242, 1254 and 1260) was treated by chemical process. 74000 lit (666000Kg) of PCBs oil (less than 7000 ppm) from Tehran Besat power plant sent to site plan. Content of 4 transformer oil samples is reported in Fig.2. Results of PCB content of transformer oil sample. The diluted is cleaned with solvent and then analyzed by a capillary Gas Chromatograph with an electron capture detector for the detection of PCBs. Results are reported as mg of PCB per liter of oil (ppm). Samples containing less than 2 mg/l PCB will be reported as Figure.2- Tehran Besat Power Plant PCBs waste less than 7000 ppm The destruction and removal efficiency of PCBs was 99.99% and/ or less than 2 ppm. After destruction, the reactor content was drained. The treated transformer oil was segregated from the contents by filtering, washing, dehydrating under vacuum. Such segregation steps described standard treatment of treated transformer oil before reuse. Treated transformer oil passed IEC60296 (oil quality standard). We have developed a safe, inexpensive and efficient chemical dechlorinating process for the disposal of Besat Plant PCBs directly in transformer oil. Disposal/decontamination of slightly PCB contaminated transformer oils could be established in Iran quite rapidly if decisions and resources can be secured. A destruction and removal of PCBs in Transformer Oil by a Chemical Process is one of the commercial technologies. Considerable PCB issue in Iran and firm steps needs to be taken in order to avoid releases in the environment from inappropriate waste management or spillage.