Journal of Environmental Studies
Year:2009 | Volume:35 | Issue:51|Papers Count:18

A vast amount of oily wastes is produced during activities related to exploration, production, refinement and transportation of oil and gas products, which cause serious damages especially to marine and estuarine environments. Persian Gulf region which contains about 57-66% of world oil reservoirs is exposed to enormous oil pollutions. Although the physical and chemical approaches for removing these pollutions are effective, but still unable to completely remediate the environment. Recently bioremediation is known as an applicable and cost effective technique for treatment of oil polluted environments. Success of oil spill bioremediation depends on our ability to optimize various physical, chemical, and biological conditions in the contaminated environment, including nitrogen and phosphorus sources, pH and temperature. The most important requirement is the presence of microorganisms with the appropriate metabolic capabilities.If these microorganisms are present, then optimal rates of growth and hydrocarbon biodegradation can be sustained by ensuring that adequate concentrations of nutrients and oxygen are present and that the pH and temperature is suitable for bacterial growth.Isolation of two petroleum biodegrading bacterial strains PG01 and PG02 from Persian Gulf and study of pH effect on oil mineralization have been previously reported. In this paper, the effect of temperature and nitrogen and phosphorus concentration on oil degradation by these bacteria was studied.Furthermore, the ability of the strains to degrade crude oil fraction was gravimetrically evaluated. All experiments were statistically repeated. Finally, the two strains were subjected to identification of using morphological and biochemical methods and determination of guano sine plus cytosine content of the DNA. The growth curves of strains PG01 and PG02 on crude oil as sole carbon source using different concentration of ammonium chloride as nitrogen source have been shown in Figure 1. In all experiments, both strain entered to exponential phase at second day of cultivation, but the amount of produced total protein and consequently the rate of degradation of oil varied in different concentrations of nitrogen source.Strain PG01 had similar growth curves in the presence of 0.146, 0.195 and 0.244 gram ammonium chloride per gram crude oil, but in the other amounts of nitrogen source degradation of oil was decreased (p<0.05). Therefore the minimum amount of nitrogen source per gram oil for this strain was 0.146 gram. For strain PG02 maxim growth was observed in the presence of 0.195 gram ammonium chloride per gram crude oil (p<0.05). The optnnum concentration of phosphorus source for biodegradation of petroleum hydrocarbons for both strains was equal to 0.024 gram disodium hydrogen phosphate per gram crude oil (fig. 2). Results of biodegradation experiments for evaluating the effect of incubation temperature on crude oil degradation by strains PG01 and PG02 showed that both strains were mesophile capable to grow at 25-37 with best results at 35-37 degree centigrade. No growth was observed at 41 degree centigrade (fig. 3). … In order to assay the biodegradation of different fractions of crude oil by strains PG01, PG02 and the mixture of them, gravimetric determination of crude oil fractions was performed. Crude oil was supplied by National Iranian Oil Company and was composed of 70.90% saturated hydrocarbons, 22.31% aromatic hydrocarbons, 3.99% resins and 2.80% asphaltenes. After a 5 day biodegradation period these fractions were reduced to 12.56%, 10.71%, 3.03% and 2.89% for strain PG01, 4.70%, 6.32%, 2.09% and 2.95% for strain PG02, and 2.32%, 4.97%, 1.32% and 2.97%, respectively.Overall ability of Strains PG01 and PG02 and the mixture of two strains to degrade crude oil was 70.81%, 83.94% and 87.61%, respectively.Identification of strains was performed using morphological, physiological and biochemical methods. For determination of guanosine plus cytosine content of bacterial DNA, the HPLC method was used. DNA was extracted and purified by cold isopropanol precipitation.Purified DNA and salmon DNA (standard DNA) were hydrolyzed by nuclease PI enzyme. The hydrolysates and a mixture of deoxy-nucleotide mono phosphate (dCMP, dTMP, dGMP and dAMP) were injected to high performance liquid chromatography. The HPLC conditions were as follow:Column:                       C18, MCH10Mobile phase:               10mM phosphate buffer (pH7)flow rate:                     0.5ml/minDetector:                      UV 260nmThe GC% of bacterial DNA was calculated using the resulted peak area of each base, which was 69.685 for strain PG01 and 67.817 for strain PG02. Regarding results from morphological, physiological and biochemical characteristics of strains PG01 and PG02, it seems that both strains are members of thegenus Mycobacterium. These characteristics are: curved rod cell shape; weakly gram positive; Acid fast in fresh culture; 2-3 day's growth duration; resistant to lysis by lysozyme; non-motile; aerobic and catalase positive; G+C content of DNA; round smooth colonies with orange and reddish color, respectively for PG01 and PG02; and resistant to penicillin. In specious level also both strains have similarities to M obuense, including growth in 5% NaCl concentration, degradation of polycyclic aromatic substrates, formation of colored colonies, unable to grow at 42 degree centigrade, nitrate reduction negative, and did not produce acid from arabinose and xylose.

In recent decades, flood occurrences result in large casualties in Iran. Flood plains include at risk fertile farm lands. Flood map can be very useful in flood plains management studies. Nowadays, these maps are considered as basic and vital information for civil plans and assessed carefully to avoid losses before any investments or execution of developing plans in flood plains. Several factors can be considered in speed, depth and force of water stress during flood is one of them. Since there is no simple theorem relation between water cutting stress, slope and speed, experimental equations can be useful. Manning equation is used to calculate water speed as well as anticipate hydraulic behavior of rivers. There are various approaches to determine coefficient of "n". In Manning Method those coefficients which are dependent to river situation like grain of river-bed, plant coverage and river route curvature degree obstructs and varies. Manning coefficient varies in a river section with plant coverage variation in different seasons. This variation may affect on water speed distribution, water height and flood area in different return periods. Also, inaccuracy in Manning coefficient estimation can result in incorrect answers. Tite et al., proposed an approach to increase output accuracy of HEC-RAS software in geographic data system by matching land mapping data, river geometry and control structures with available land model in geographic data system. Motiie et al., mapped Sefid-Roof river flood by HEC- GeoRAS and HEC-RAS. Andem in his thesis named "Comparison of Jungle and Non-jungle Rivers Regimes" used HEC- GeoRAS and HEC-RAS to study speed variations and descent numbers of the two types of rivers. Also, he compared effects of plant coverage on regimes and physical behavior of flow, finally he conclude that HEC-RAS can be useful in producing appropriate values to study regime and the other hydraulic characteristics of river. Islam and Kimitro used remote sensing and GIS data to produce flood risk map of Bangladesh in 1988. Yazdan doost and Nasiri determined at risk regions of Is1amshar with different return periods. Safari mapped at risk areas of Neka river in east of Mazandaran province. Various studies performed to determine flood areas in different return periods in Iran and other countries, but programming to overcome natural hazards should be based on the most acute situations to be effective. The present study is performed to assess Manning coefficient season effect on flood hydraulic behavior anticipation.Materials and methods: Haraz river originate from Alborz mountains in north of Iran and passing Amol to Caspian Sea. This research is performed in a section of Haraz River and its flood plain at the entrance of Amol with 3250m length. The geographical conditionis 52o 22’ of eastern longitude and 36o 23’ to 36o 23’ northern latitude locate in Tarak-Kola, outskirt of Amol. Paddy plains of this section are fallow in cold seasons.In this paper, Cawon approach is used to determine the Manning coefficient in summer and winter for riverbed and left- right shores, separately to study the effects of season of Manning coefficient determination on flood hydrologic behavior anticipation.Also, GIS (the attached HEC-GeoRAS) and HEC-RAS software are used to simulate hydraulic behavior of the river for their high capability. At first, 50 years maximum instant debby records of Karesang, in Amol, are analyzed taking into consideration the adequacy, relation and homogeny. The sequence test confirmed 0.05 reliability level. Appropriate statistical distribution is determined by Smada software. In addition, maximum debbies with different return periods are specified by Pierson log, type III. In other words, the estimated and observed graphs of each statistic distribution are planed and statistical distribution with maximum overlap considered as the best statistical distribution. Then, river-bed situations and flood plain of Haraz River in the studied section, such as main flow route, shores, flood paths and breadthways sections are simulated by HEC- GeoRAS in the platform of ARC View- GIS and river map with 1:500 scale. 84 sections are considered to represent river condition. Then, the considered section separated to 7 equal ranges to determine the coefficient. This factor is calculated by Cawen method for river-bed and left-right shores in each 7 ranges in summer and winter, separately. Manning formula and Cawen approach to estimate the coefficient of Manning is presented in (1) and (2):(1)  V=1/n R2/3 I1/2(2)  n=(n0+n1+n2+n3+n4) m5Where, n is Manning coefficient of Manning in Cawen approach and n0 is Manning coefficient of river bed substances. Corrective coefficients, n1, n2, n3, n4 and m5 are the cross-section irregularity, cross-section variation, obstructs in river route, plant coverage and rote curvature degree, respectively. Manning coefficients are determined by field study as well as GIS device for each 84 sections. Manning coefficient of left-right shores vary in summer at the contrary of winter for growing plants and paddy farming, but main channel of the river remain constant considering no plant growth. Geometric data are entered from GIS to HEC-RAS software to present model and simulate Haraz river hydraulic behavior. Complex regime and normal depths are considered in this research. Moreover, due to the plant coverage variations in summer and winter, two simulation models with difference in Manning coefficients are used to compare the results.Discussion and Conclusion: River-bed and flood plain of Haraz River are simulated using GIS, HEC- RAS software and field studies considering their high capability in rivers hydraulic behavior studies. Maximum debbies are determined by Pierson log type III. Manning coefficient of main channel of Haraz and left-right shores of 84 sections is determined by Cawen approach in summer and winter separately. It can be seen that the coefficients vary in summer and winter for plant coverage variations at the contrary of river main channel. Geometric data of River bed and flood plain are entered from GIS to HEC-RAS software platform. The longitudinal profile of river-bed of the studied section is shown in figure 1. Then the two simulation models with different Manning coefficients are presented to anticipate Haraz river hydraulic behavior in the considered section. Speed distribution and water level profile in one of the breadth sections with summer and winter Manning coefficients are shown in figure 2 and 3, respectively. It can be seen that in summer, the flood height increase for Manning coefficient increment. According to the recent researches, high speed flood would be occurred in flat and impenetrable surfaces with artificial drainage. Water speed variation during flood with various return periods in left-right shores is shown in figure 4 and 5. It is obvious that Manning coefficient increment in summer results in significant reduction of shore speed compare to winter situation. Water speed variations during flood occurrence in main channel are shown in figure 6 and 7 as well as tables 4 and 5. It can be seen that water speed reduction in shores and flood plains because of plant coverage and Manning coefficient in summer. This result in no significant variations in river main channel compare to winter except to few hundredth meter per second water speed. Data of 61st breadth section are shown in table 4 and 5 according to 200 years flood for the two summer and winter model.Conclusion: According to the results of this paper, determination time of Manning coefficient, affect significantly on hydraulic behavior anticipation results, speed, height and area of flood. Considering plant coverage results in summer, the coefficient increases because of the plant coverage increment in Cawen method. This coefficient increment of flood plain and shore significantly reduce water speed as well as little speed water rate of main channel. Water sped reduction is accompanied by depth, height, area and cutting stress increment. In the other hand, the coefficient variation varies flood volume distribution of plain. Note that, most of remarkable floods in north of Iran, such as Neka and Gorgan flood in 4-5- 1999 and 27-2-1992, occurred in plant coverage growth season. Considering the research aim, to avoid flood damage as well as successful programming to control natural hazards, most acute situations should be concerned. It can be seen in the tables that plant coverage growth and Manning coefficient increment, increase flood area compare to winter. Cutting stress and Manning coefficient increment variations versus plant coverage growth are shown in figures 8, 9, 10 and 11. It is notable that plant coverage growth and Manning coefficient increment, increase cutting stress in river shores and main channel, especially in main channel. Also, according to table 4 and 5, water flow reduce notably by plant growth and Manning coefficient increment in shores and flood plain is less than main channel. Therefore considering the above in the studies such as flood mapping, Manning coefficient should be determined in plant growth season or at least flood plain coverage should be known by asking native habitants. In this study, Manning coefficients are considered for each section.

This paper presents distribution and seasonal variations of pH over the southern Caspian Shelf adjacent to Iran. The pH data were collected down to 200m depth in two areas in east (off Babolsar in Mazandaran) and west (off Kiyashahr in Gilan) of the Caspian Sea southern coast. The data were collected using a pH sensor of a CTD probe in summer 2003 and spring and autumn 2004. In slimmer, when the surface water temperature was highest and the strongest seasonal thermo cline existed, the maximum value for pH was observed. In this season, pH had a value of 8.35-8.4 at the water surface. This amount reduced to 8.2 at 80-m level and even deeper waters. In autumn, the pH was less than summer and was mainly 8.25 at the water surface outside of the shelf and 8.3-8.35 in the shelf and it gradually reduced by decreasing the depth. In early spring, during the formation process of new seasonal thermo cline, low temperature and maximum local river inflow, pH at the water surface was mainly 8.25 and reduced to 8.2 at 30-m level.The results showed that seasonal variations of pH in the southern Caspian Shelf and the coastal waters adjacent to Iran is a function of seasonal variations in water temperature, characteristics of thermo cline, local rivers chemical characteristics and discharges, and production or degradation processes.Introduction: pH in the Caspian Sea has seasonal and spatial variations. In summer, the increase in phytoplankton production results in the absorption of CO2 and a chain of reaction that take the free Hydrogen ion from the sea water, reduces the acidity and increases the pH. In autumn, the oxidation processes prevails the production processes and the amount of CO2 increases in the water while the water pH reduces.In the southern area of Caspian Sea, adjacent to Iran, the field measurements and data of physical and chemical characteristics of water, including pH value is very limited. In this paper by using field data analysis, the characteristics and seasonal variations of pH in the southern shelf of the Caspian Sea are presented and discussed. The data collected in summer 2003 and spring and autumn of 2004.Study areas: The study areas are located in the east and west of the southern coast of Caspian Sea in Iran. The eastern site extends between Babolsar and Sorkhehesar in Mazandaran province. The western site is located in Kiashahr near the mouth of the Sepid Rood River in the Gilan province.Data collection: pH measurements were conducted using the pH sensor of an Ocean Seven 316 CTD probe manufactured by Idronaut. The sensor has an accuracy of 0.01 in measuring the pH. The CTD was used in a free falling mode with a speed of 1ms-1.The pH profiles in the eastern site were collected at 27 sampling stations in 4 transects (3 perpendicular and 1 parallel to the coast) in summer 2003 and spring 2004. In the western site, the data was collected at 17 sampling stations in a transect perpendicular to the coast in the autumn 2004.Results and discussion the vertical structures of the pH in the eastern site in august 2003 are shown in figures 1a and lb. At this time, the water temperature structure was characterized by a strong thermo cline located between 20 and 50m levels. Outside of the shelf (figure 2a) the pH was mainly 8.35 at the top 40m of water column. The pH slightly increased and reached to 8.4 between 40 and 50m level. Below 50m, the pH gradually decreased to 8.2 at 80m level and then remained almost constant. Over the shelf, pH changed between 8.35 and 8.4.The vertical structure of the pH in the western site in October 2004 is presented in Figure 2c. At this time, there was a thin thermo cline between 30 and 40m levels. Outside of the shelf, pH was measured 8.25 at the top 30m of water column. The pH gradually decreased to 8 at 70m level and 7.9 at 120m and then remained almost constant.The vertical structure of pH in spring 2004 is presented in Figure 2d. At this time the process of them cline formation started and vertical temperature structure was characterized by a warm surface layer of 10m with a temperature of 14oC and then gradually decreased. Outside of the shelf, the pH was 8.1 at the top 30m of the water column and reduced to 8 at 40m level and even for deeper waters.The results indicated seasonal variations of pH in the southern coastal areas of the Caspian Sea adjacent to Iran. The pH variations were partly due to the seasonal changes in the processes of production or degradation and prevalence of either of them. Also, it depends on the seasonal variations in the discharge of local rivers and their water characteristics.The maximum amounts of pH were observed in summer when the temperature was high. There was a strong thermo cline and high level of phytoplankton productivity. In autumn the decrease of temperature and the prevalence of degradation process, the pH decreased significantly and in particular in deeper depths reduced to 7.9. Similarly observations in spring, when water temperature was low and river discharges highly affected coastal areas, the observed pH was between 8.05 and 8.1....

Yazd province is one of arid regions of Iran with limitation of water resources. Utilization of industrial wastewater on agriculture lands can somehow compensate the lack of water. This study first evaluated the data and results of previous research carried out and a new producer of textile waste were determined. The important textile producers Afshar, Selkbaf and Yazdbaf were selected and the effluent quality and its effect on soil, plant and underground water was studied for a period of two years. Results showed that discharge of industrial wastewater to the surface water pH, TDS, TSS, sulfate, chloride, zinc and cadmium, for discharge of effluent to the absorbent wells TDS, sulfate, chloride, zinc and cadmium and for irrigation agricultural lands of the effluent pH, salinity, TDS, TSS, sulfate, chloride, bicarbonate, copper, zinc and cadmium effluent was limiting. The result showed that the concentration of heavy metals in well waters was less than the permit limit and no limitation was existed.But there were limitation value for the characteristics of pH, salinity, TDS, sulfate, chloride and bicarbonate. Moreover, the heavy metal concentrations of soils were studied. The amounts of zinc and cadmium concentrations in soil samples were in critical range and the organic matter, total nitrogen, available phosphorus and potassium of soils were significantly high. Also, the results showed that the plants were infected by heavy metals, zinc and copper. In all studied areas heavy metals in soil were higher than the limitation to be controlled. The concentration of some heavy metals in soil and plant were beyond the permit limit.Introduction: The topic that recently received attention of researchers and scholars of environmental issues is the measurement of heavy metals in industrial wastewater and its effect on fann receiver and cultivated plants in that region. Water consumption by industries in many countries has had significant growth. For example, in China, water consumption by industry in 1995 is equal to 52 billion tons and by 2030 it is predicted that this amount reach to 269 billion tons. On the other hand, each year more than 400 small and medium industrial cities in China produce more than 10 billion tons of wastewater. In Pakistan the effluent irrigation is used for 32, 500 hectares of land.In India 25 percent and in South Africa 24 percent of wastewater produced used in agricultural lands forirrigation. The accumulation of heavy metals (especially cadmium and lead) in soil is one of important environmental concerns. Cadmium is very toxic for plants and animals. The highest concentration of cadmium in a study in brown rice grown on contaminated soils was measured 5.9 mg/kg which is critical in value World Health Organization and many countries for food security and health, create standards and guidelines for the use of wastewater that provide the chance to be adjusted with the regional conditions.Materials and Methods: In this research the quality of EW of Yazdbaf, Afshar and Selkbaf and its impact on soil, plants and water resources (well-water) was studied for two years. The EW was sampled; seasonally every 6 hours during 24 hours periods and, well-water from an area irrigated with EW were sampled seasonally. During a two-year study, in area using irrigated with industrial EW two zone were selected, one irrigated with industrial EW from Yazdbaf and one irrigated With EW from Selkbaf.In each zone, 3 farms of approximately 0.5 ha were selected. In each farm, composite soil sample from three fields from 0-30 cm, were collected in three replicates. In fields irrigated with Yazdbaf industrial EW water the soil, plant (Cynodon dactylon), and check filed were sampled. In fields irrigated with Selkbaf industrial EW, Haloxylon aphyllum Root and shoot were sampled and in fields irrigated with Afshar industrial EW, Triticum aestivum Root and shoot were sampled.The EW and well-water were analyzed for pH, EC, TDS, TSS, N-NO3, cations, anions, BOD, COD, and the concentration of heavy metals including Cu, Zn, Cd, Pb and Cr. The soil samples were analyzed for pH, EC, texture, organic matter, cations, anions and concentration of heavy metals including Cu, Cd, Zn, Cr and, Pb. The plants samples were analyzed for percent dray matter content and the same heavy metals as soil samples. The results were compared with permissible concentration levels....Results: The comparison of the results with permissible level shows that pH, TDS, TSS, sulfate, chloride, and heavy metal concentration of Zn and Cd, were limited for discharge into surface water and, disposal into absorption wells TDS, sulfate, chloride, and heavy metal concentration of Cd and Zn and for utilization as the irrigation water pH, salinity, TDS, TSS, sulfate, chloride, bicarbonate, and heavy metal concentration of Cu, Zn and Cd are limited.The limiting chemicals properties in well-water for discharge into surface water, disposal into absorption wells and utilization as irrigation water are pH, salinity, TDS, sulfate, chloride and bicarbonate. Concentration of heavy metal in soil samples is higher than control. In addition, the concentration of Cd and Zn heavy metals exceed normal concentration level and are in the critical range and the organic matter, total nitrogen, available phosphorus and potassium of soils were significantly high and are higher than control.Similar results have been reported by numerous researches. The results show the accumulation of heavy metals in soil due to long term application of EW. Comparison of the result with the permissible level show that the concentration of heavy metals Zn and Cu in all of the plants are exceed the permissible level and are in critical range. The Cu concentration in root is higher than the shoot in Cynodon dactylon and Triticum aestivum plants but in Haloxylon aphyllum plant is eversible. The Zn concentration in shoot is higher than the root in Cynodon dactylon and Haloxylon aphyllum plants but in Triticum aestivum plant it is reverse. Plants uptake of heavy metals has increased by long-term utilization of industrial EW in agricultural land. Presently the quality of EW plays an important role in contamination of soil, plant, and water resources. The long-term application of EW may lead to serious contamination and accumulation of heavy metals exceeding the permissible ranges. Conclusion: 1-The contamination of heavy metals in soil can be referred to the heavy metal concentrations in the effluent.2-The result of this research showed that for utilizing the industrial wastewater in agriculture and discharging to the surface water or wells many limitations are involved. Therefore, for any use of the wastewater, including discharge to the environment or use in agriculture, it is needed to refine and meet the characteristic concentration limit.3-lndustrial wastewater plays an important role in agricultural land pollution, groundwater and plants grown on contaminated land and in long term period of time, the underground water source of Yazd will be highly contaminated.4-Utilization of the none-prime water resources especially industrial and municipal effluent water in the arid region for agricultural land is needed. Water has several limitations. However due to chemical and biological limitation of EW, regarding the heavy metal concentration and it's introduction into human food chain, it is recommendedA- To fully treat before discharge into environmentB- To be used for plant with low tendency to accumulate heavy metalsC- To monitor water resources and take the necessary steps to prevent contamination of underground water resources.

Sustainabi1ityin Tourism is defined in different ecological, social, psychological and economical levels. Its sustainability depends on the quality of the tourists' experience and residents' benefits. Determining which levels of change could be locally acceptable and leads to the concept of tourist carrying capacity. Tourism carrying capacity is one of the most debated management tools for sustainability, showing the expectation of an objective measure and a tourist-bias for the relatively greater relevance given to the tourist's with respect to the resident's point of view.One of the purposes of ecotourism is to relax and aspirate the natural energy. Sacred and Energetic sites are the locations for experiencing the relaxation. Since 2005, the Energy Tourism or spiritual Tourism has been developed in Iran (Sanaye Goldouz, 2007). There are some places in Iran which have a kind of energy as subtle energy for increasing personal health and awareness. These places have some restrictions in Tourism sustainability, so their carrying capacity must be estimated. Carrying Capacity can be used as an index number for identifying the management policies.Takht-e Soleiman (Azargoshnasb) in Iran is a historical site located in 45 kilometers northeast of the Takab city. It is the heritage remained from the Sassanid era (226-650 AD). Takht-e Soleiman (Throne of Solomon) is the home to one of the three famous Sassanid fire temples. It is also where the kings of the Sassanid dynasty were crowned.The historic monument in Takht-e Soleiman has been built around a lake in the form of an oval structure and is enclosed by a stone wall. In addition to historic monuments, those who travel to Takht-e Soleiman may also see an absolutely eye-catching lake with changing colors. The ancient site is most known for its Sassanid monuments such as: Azargoshnasb Fire Temple, Anahita Temple, Hadaya (Gifts) Museum, Zendan (Jail) Mountain, and Belgheis Castle.Takht-e Soleiman (Throne of Solomon) is an important archeological site in Iran which was not only registered by UNESCO in 2003 as a world heritage, but also was inscribed in the world sacred sites list in 1967. From 2005, many tourists travel to this site to receive its energy each year. In general, there are three types of ecotourist in Takht-e Soleiman. The foreign tourists travel to this site because it is an archeological site. Iranian tourists are the aboriginals and the others from the other cities of Iran. The third type is the energy tourists or spiritual tourists who travel to this site for receiving the natural and subtle energy. These tourists turn around the holy lake and meditate or promenade in silence in Takht-e Soleiman.In this research, psychosocial carrying capacity of the energy tourism in sacred site (Takht-e Soleiman) was surveyed. In order to indentify psychosocial carrying capacity, the management indicators that affect the carrying capacity, were determined. According to these indicators, the questionnaires were provided. 140 of 150 tourists were traveled to Takht-e Soleiman for receiving the energy responded to the questionnaires in a summer vacation in 2007. The travel goal of 36 persons was curiousness and the travel goal of the rest (104 persons) was receiving energy.The contingency tables were provided. In the analysis of the tables, the fisher's test was used. After statistical analysis, with p-value = 0.017£0.05, the number of psychosocial carrying capacity which identified density, crowding levels and encounter preferences was less than 150 persons daily in recreation season (summer) when Takht-e Soleiman was very crowded. The acceptable number of psychosocial carrying capacity has been shown in Table 1.   Table1: Contingency table of travel goals and acceptable density     Travel goals Acceptable Density & Encounter Preferences       Total     Cumulative percent Less than 150 Persons Percent More than 150 Persons Percent Curiousness Receiving Energy Total 31   69   100 86.2   66.3   71.4 5   35   40 13.8   33.7   28.6 36   104   140 100   100   100                         Then the contingency table between the acceptable density and the seating was provided. The number of psychosocial carrying capacity has been shown in Table 2.This number specially identified the acceptable density around the holy lake with p-value = 0.042£0.05.   Table1: Contingency table of travel goals and acceptable density       Seating Acceptable Density & Encounter Preferences       Total     Cumulative percent Less than 150 Persons Percent More than 150 Persons Percent Around the lake in the monuments Total 94   6   100 82.5   54.5   80 20   5   25 17.5   45.5   20 114   11   125 100   100   100                         As it was shown in Table 2, the energy tourists like to meditate and turn around the lake in silence and to meet utmost 150 persons who have the same travel goal. It shows that the holy lake in Takht-e Soleiman is very attractive and eye-catching.The number of psychosocial carrying capacity can be used in management programs as an index number.This number was estimated while in Takht-e Soleiman it was just one guard with unsuitable management and no planning was existed for dividing the three types of tourists. Increasing the number of Energy Tourists day by day in Takht-e Soleiman and bringing again into activity and prominence, the management conditions and planning must be improved to arrange the tourists. Also, training, suitable planning for different kind of tourists, improving facilities, increasing the number of guards and leaders are necessary.

Tehran is one of the most polluted metropolises in the world. Sink capacity for absorption and assimilation of pollution is reduced generally in Tehran due to failure in incorporation of ecological aspects in the regional land use development plans. The present condition of air and water related issues in Tehran are largely affected by landscape structural alterations at urban level.In this research, the focus is to understand the relationships between land use patterns and ecological processes particularly those air and water related processes, which are affecting the urban environmental quality. We propose measures to harmonize urban growth patterns based on the existing opportunities for increasing the sink capacity for air pollution and waste water.Using Land sat satellite images (dated 1988 & 2002) maps for three classes of green, open and built land cover types were created. A series of landscape metrics, NP (Number of Patch), MPS (Mean Patch Size), MNND (Minimum Nearest Neighbor Distance), and CAP (Class Area Proportion) were used for the analysis of landscape structure (both configuration and composition) at two different scales. Based on Variations in environmental conditions and spatial configuration and composition of Tehran landscape, three distinct homogeneous zones and six subzones with different environmental conditions and ecosystem capabilities for urban development are distinguished within the delimited urban region considered (Figure 1 and Table 1).The following characteristics have been associated to each zone: Zone A: in this zone, the remnant patch mosaic network with the highest MPS value and most appropriate connectedness is found. Conservation and restoration of remnant patch mosaic network will be most cost effective results in landscape type A because of its proximity to mountainous area as the source of valuable services that may be transferred into the city by means of several river valleys which are still remained less altered.Zone B: in this zone despite low class area proportion of urban green space, it has a high class area proportion of open (agricultural land, hills and river valleys) patch type with good connectedness. If treated waste water and urban runoff is appropriately allocated to these patches, an important green patch mosaic as urban forest is expected to be created that function as sink for air and water pollution and will serve as a source of environmental services in addition to improvement of urban regions' remnant patch network connectedness.Zone C: The present urban remnant patch mosaic network has both a low connectedness and a low class area proportion. It is essential to develop urban green spaces to obtain regional connectedness despite the fact that no particular advantageous potential resources are available in this respect.…Final results demonstrate that despite ecological alteration, the remnant patch mosaic network of Tehran may still be restorable. The river valley network provides the basis for development of a conceptual framework referred to in this research as "Refuge Network" in order to integrate all corrective measures at different scales. Natural layouts of river valley networks along with the core open patches of hills may be the basis for implementation of a comprehensive restoration plan based upon the "Aggregate with outlier" model as a spatial design framework at urban level.

Ecosystems provide goods and services that contribute to human welfare, and provide an environment in which ecological process take place. Economic theories predict that ecosystem goods and services for which there are inefficient markets, trend to be underrepresented in management decisions and their supply will be sub-optimal. Ecosystem Degradation not only has many negative impacts on economic condition, but also has many negative effects on future sustainable economic growth. One of the most important reasons for this degradation is lack of market for ecological goods and services.On the other hand, estimating the real value of these functions is an essential need for achieving the appropriate allocation of natural resources. Valuation can be effective in obtaining the social decisions, in the assessment of cost and benefit, accept or reject of the project, or determine appropriate and acceptable level of damages to the environment.Also in national income calculations in macro level, awareness of the value is required, because usually in the process of economic development ecosystem goods and services are not entered in the calculations and often results in wrong patient to provide statistics such as GDP indices.Knowing the values plays an effective role in people's and policy makers' attention to the environment. In fact, the fundamental point is that the value of ecosystem service is not the solely aim but it is a "decision support tool" to a better decision making in environmental filed.Forests as one of the most important terrestrial ecosystems provide the highest number of ecosystem services and there is no market to present their values. Among these non market services, gas regulation is the most important issue. Forests are carbon stores, and they are carbon dioxide sinks because plants absorb co2 and use it in photosynthesis process. This process, in addition to producing plant biomass and releasing o2, has an effective role in reducing the greenhouse effect. In the recent years there are a lot of concerns with this phenomena and it causes global warming with a lot of significant effects. Amongst the world forests, tropical forest stands the highest in carbon absorption.There is not a spatial similarity in co2 absorption because of the difference in plant concentration, tropical situation, kinds of specious and the amount of plant annual growth per hectare. Therefore, spatial valuation can distinguish between these differences and shows the heterogeneity in these areas.In this study we introduce a pattern to achieve spatial distribution of co2 absorption with geographical information system in a part of Caspian forests of Iran.Caspian forest, with an average area of 1.8 million hectare is located on the north of Iran, near the Caspian Sea, and it is divided to many watersheds. Fig 1 shows the study area location.…There are a relationship between land characteristic and the value of ecosystem services. A pattern has been introduced among these two items. To achieve this pattern, First of all the forest type map has been generated. Then the map of annual growth per year has been established according to the average growth of each plant type in a ten year period. By employing the density of each plant type, the growth map of annual produced plant biomass has been introduced. The relationship between plant biomass and CO2 absorption has been calculated by photosynthesis formula. According to this formula plants absorbs 264 gram CO2 and produce 162 gram amylase (plant biomass).Co2(264g)+H2o(108g) ® C6H12O6(180g)+O2(193g) ® Amylase(162g)The map of carbon absorption has been generated according to the relationship between the produced amylase and the absorbed carbon dioxide. This map shows that there is a great difference between different parts of the area in CO2 absorption. Finally the ecosystem function of CO2 absorption has been valued with replacement of the cost method. There are other evaluation methods like carbon marketing, substituting the cost method and carbon tax, for evaluating the CO2 absorption value. Replacement cost method is one of the most important cost based methods in environmental economics. This method is based on the cost of replacing the natural services with a man made services. We use the cost of industrial carbon capture and storage for replacing the natural value of CO2 absorption. Carbon capture and storage (CCS) is a mean to mitigating the contribution of fossil fuel emissions to global warming, based on capturing carbon dioxide (CO2) from large point sources such as fossil fuel power plants, and store it away from atmosphere by different means.The largest CO2 storage project to date has been injecting approximately 1 million tones of CO2per year since 1996 into a saline formation. According to the IPCC report, the average cost of CCS in 2007 was around 63/3 US$ for each ton of carbon dioxide. In this pattern according to kinds of specious, plant concentration and growth per hectare, we achieve the map of spatial distribution of CO2 absorption value.Planners can Use this map, as a decision support tools, for more careful local and regional planning. A comprehensive forestry plan for Caspian forest can help planer to create integrated map of CO2 absorption value in the Caspian forest, but studies show that only 45% of north forest of Iran has a comprehensive forestry plan, that unfortunately in some of these projects many shortcomings are facing.Results show that in the study region with an area of 20582 hectare, the value of CO2 absorption is more than 8 million Dollars per year. It is important to note that this amount is only one of several valuable ecosystem services that forests ecosystems provide. Fig 2 shows the map of carbon dioxide absorption value in the study region.  …This study shows that the economic value of carbon absorption is significant. Also the CO2 absorption value is more than 6 times different from one place to another place in the study region, it shows that the spatial deference plays as important role in evaluation and it is not appropriate to consider the whole area as a similar zone. Accessing the spatial value in ecosystem services can help planners and decision makers to have more accurate evaluations and it may help them for more sustainable management of the forests.

Environmental Impact Assessment (EIA) is a critical appraisal of the likely effects of a policy, program, project, or activity on the environment. To assist the decision making authority, assessments are carried out independently of the proponent that may have prepared an environmental impact statement (EIS). Sometimes impact assessing methods, proposed alternatives, plans and the development of policy are against each other. Although EIA and environmental economical theories are useful facilities to measure the environmental capacities, the results are not always effective because of the measurement of quality. A Decision Support Systems (DSS) is a useful instrument for solving these problems. Degradation Model, as a Decision Support Systems, was first introduced in Iran.In this research, spatial data such as topography, hydrologic network, roads network in 1:25000 scale and land use in the 1:50000 scales are employed. Moreover, the physical landscape metrics are used to execute the human activities intensity.The landscape degradation is:LD=SI/ViWhere LD is equal to degradation coefficient of landscape compartments, SkI is the index of intensity of human activities in landscape working units, (I is the indicator of metrics and k is intensity of them) V stands for habitat vulnerability.According to McGarigal and Marks (1995), the list activities in landscape degradation model is as follow: Number of Patches in landscape (NumP), Median Patch Size (MedPS), Total Edge (TE), Edge Density (ED),  Mean Patch Fractal Dimension (MPFD), Shannon's Diversity index (SDI) and Mean Shape Index (MSI). Landscape ecological metrics are useful instrument to interference ecology in planning and they help to measure the quantity of landscape processes. At first, all the landscape metrics should be determined for each sub watershed and then the scope of each metric in each sub watershed will be categorized based on the median. The median is a number that divides data into equal parts. In other word, it shows which part is the bigger 50%, and which part is the smaller than 50%. To achieve this, Excel program is used. In the next step, the total metrics is considered as collection of landscape degradation activities. Activities are categorized in terms of quality in 4 classes: Code (1) Insignificant degradation, Code (2) Medium degradation, Code (3) Intense degradation, Code (4) high intense degradation.After comparing activities intensity (different metrics) with median scale, the intensity of each activity has been determined in working unit.One method to determine vulnerability is quantitative landscape by extracting, landscape metrics. Based on ecological landscape principals, when number of patches in ecosystem is fewer or when there is equal in land use in an ecosystem or sub watershed, the ecosystem is exposed to much less vulnerability. The number of patches in landscape (Nump) is used to determine the ecological vulnerability. Table I shows the level of vulnerability in Shafarud watershed.   Table1: Vulnerability level in shafarud landscape   Vulnerability scope (NumP) Vulnerability level 6.9>I1 6.9>12³8.5 8.5>13³17.75 I4³17.75 Resistant Semi-critical Critical Vulnerable   To apply the landscape degradation model we considered Shafarud watershed that is located in Gilan. Figure 1 Show the study area. … Table 1 shows degradation scope in Shafarud watershed based on development & protection ratio according to the fuzzy logic classification. In chart 1 the Hierarchy of degradation in each sub watershed shown.It aims to show those classes to which LD belongs and to show the degradation which belongs to that special class. …After computation of landscape degradation model, subwatershed 25, 26 and 27 are the maximum number of degradation. In this study, the satellite data, length of road, slope and number of patches are correlated and the data is extracted from landscape degradation model. These correlation illustrated that the red class in imaging data is accomplished the highest correlation with degradation (R2=0.61).

The economic and market value of environmental goods and services is latent, at least in the appearance. Among the conventional methods of evaluation and economic pricing of environment the hedonic pricing method (HPM) is based on this assumption that usually people show their demand level on the quality of environment through their settlement purchase.Therefore, in making decision for buying a house, there is a hidden price in which the environmental quality is also evaluated, and the amount of demand for the consumption and/or the use of non-market goods and services such as the presence or absence of air or noise pollution is specified. HPM evaluates the economic value of places in environmental point of view using the quantitative and statistical methods. This article uses the HPM method for the analysis of the prices and the residential values in selected areas of Tabriz. Results of the analysis indicate significant correlation between variables, and emphasizing the hidden price of houses in peoples' willingness to pay for living in a better and pollution free environment.The first step in HPM is the estimation of hidden price function as follows:P=f(x1, ………., xn)  (1)In which P is the given price of the good, x1 up to xn is the characteristics of that good. The market price of any unit of product or good (p) is determined through the demand and supply therefore, we used a regression analysis method for estimation of equation (I): Ph=a+b1+b2x2+b3x3+b4x4+b5Uh   (2)We also specified the amount of effects of variables x1 to xn in order to estimate the independent variables' influence on prices.The following diagram shows how (P) is affected by two different situation of place, namely, the pollution free and polluted aspects.D1 stands for housing demand in a polluted environment, and D2 shows the demand for a house in pollution free area. The difference in prices for both locations is shown by dP which in fact specifies the amount of willingness to pay (WTP) for a better environment.…Aims of the research: The main questions for carrying out this research were as follows:I) Do the property owners give importance for the relationship between the environmental services such as clean air, or the concentration of atmospheric particles and the house prices?2) Is it possible to price the environmental value of houses within the framework of real estate prices?3) What types of data and information are needed for applying the HPM and the determination of variables?4) How can we extract the demand curve for environment through the WTP of people?Data and methods: Alongside the application of regression model, we used the following model for determining the WTP: P=a+Sb+Lg+Gt+eThe definitions relating to the above equation are explained within the paper.We referred to various real estate agents in Tabriz to gather the necessary information. 220 questionnaires were filled in randomly among property buyers in real estates. 40 questionnaires were put aside due to their uncertainty of answers. Map (1) shows the estimation of average house prices of identical physical conditions (the number of floors, the quality and area). The map was derived using ArcGIS software to study the area. The basis information for the house prices was the referral to 60 real estate agents in Tabriz. Although the perfect accuracy of announced house prices was not clear, the standard for approximate pollution levels were the data derived from pollution measurement stations, and the extent of green space in the areas.Findings and discussion: About 50% of those respondents seeking to buy houses were university graduated. The average house price during the study period (2006-2007) was 70-90 Million Tomans (Approx. US$ 80.000). The priority of environmental quality promotion in the questionnaire was the most imperative factor in selecting the house. Also green space took a vantage point in the respondents' views....The step-wise regression analysis results designated positive significant correlation in 95% confidence level between the independent variables of environmental quality, green space, and the access to services and dependent variable of house price. The null hypothesis thereby was rejected and the amount of was 68%. Final conclusion is that people "do" include the quality of environment in their choices of buying house or property and they allocate hidden prices to the environmental values and amenities for their purchase. This study showed that HPM can be a reliable method for appraisal and estimation of the effects of non-market environmental goods and services, on house prices and other amenities. Further research can focus on deeper aspects of environmental pricing in other similar areas of developing countries where the shortage of data and lack of a serious look and impression on environmental issues, especially among the decision makers and planners impose irreversible effects on the living environment.

Given the importance of environment and sustainable development, environmental issues are very important. Investigating environment quality and economic growth relation plays an important role in optimizing economic development perspective in the country. For this purpose, this study surveys the aforementioned relationship in the various Country Development Programs. Variables of the model are carbon dioxide emissions per capita (as an indicator of pollution), Iran GDP per capita, the number of cars produced and imported, the degree of openness of an economy (ratio of total exports and imports to GDP), the country population, and the dummy variables of development programs. The results of this study showed that in the variables classes, the Chi-square test represent that the emissions of carbon dioxide and air pollution have significant relationship. The estimated logarithmic Grossman and Krueger model showed that the domestic gross incomes, the number of vehicles, and the rate of population have direct relationship with carbon dioxide gas emissions. The highest correlation is related to gross domestic income. So that one percent increase in gross income, these gas emissions 5.539 percent will increase. The relationship between the degree of openness of economy and these gas emissions was negative, with one percent increase in this index; these gas emissions 0.3372 percent will be reduced. Finally, results showed that the third Development Program compared with the other programs was successful in controlling pollution. It indicated less annual increase in carbon dioxide emissions and pollution that is caused by the implementation of programs like Comprehensive Program of Pollution Reduction in the eight largest cities. Therefore, this study suggests that these programs should be continued with emphasis on the control of all effective variables.Summery of Article: Estimated annual losses of mortality due to urban air pollution are 640 million dollars (i.e. 5100 billion Rials) that is equivalent to 0.57 percent of GDP. The disease caused by urban air pollution creates 260 million- dollar or 2100 billion- Rials cost (0.023 percent of GDP) for the economy of Iran. (World Bank, 2005) This study surveys relationship between air pollution and economic growth. Also, evaluation of Economical and Social Development Programs in the field of air pollution reduction is carried out. For this purpose, the study used data for the years 1979-2005 from the Balance Sheet Energy (2009), Iran Department of Environment (2009), Central Bank of Iran (2009) and Wood Development Reports (2008) has been collected. Calculation and estimates is done by SHAZAM and SPSS packages. The estimation of relationship between economic growth and environmental destruction has done by the use of Grossman and Krueger model with some adjustments (Eq.)(1).L N P=a0+a1 L N G D P+a3 L N G D P2+ a4 L N c a r + a5 L O+ a6 L N U                        (1)+ a7 D1+ a8 D2+ a9 D3+eWhere LNP :the logarithm of pollution variable (carbon dioxide emissions per capita in thousand tons), LNGDP: the logarithm of GDP per capita in Iran (billion Rials), LNGDP2: the square logarithm of GDP  per capita in Iran, LNCAR: the logarithmic number of cars produced and imported, LN( the logarithm of the degree of openness of an economy (ratio of total exports and imports to GDP), LNG: logarithm of population (thousands), D1: dummy variable for the function of first Development Program, D2: dummy variable for the function of second Development Program, D3: dummy variable for the function of third Development Program (in each dummy variables, the number 1 is related to the program years and the number 0 for the other years). For each of the variables some classes are considered, and then the effect of them is investigated through the calculated results from SPSS package. Many studies have been done in the field of air pollution considered carbon dioxide emissions as an index of the air pollution and this gas is one of the most important gases leading to climate change and global warming. Additionally, about 72 percent of greenhouse is related to carbon dioxide, so in this study carbon dioxide emission is a criterion for air pollution. Study data are time series, so stationary test is done and the result is available in Table (1) that shows two lags are optimal and whereas calculated value is more than critical value the model is stationary. Table 1: Generalized Dickey - Fuller Unit root test results Error term Data level -5.835 2 3.5573* -2.57 Description Variable AIC criteria Lag lengthCalculated valueCritical value (Source: research findings)* 10% significance levelTable 2: Estimated effects of different factors on carbon dioxide emissions…Table 3: Estimated logarithmic model…Chi-square test shows that there are significant differences in carbon dioxide per capita for various variable levels. Considering the fifth column table (2), when the population is over 60 million people, 100 percent of pollution will be more than five ton. Significant differences exist in different classes of the export and import at one percent level of and when imports increase the level of pollution also increases. It is obvious that the highest pollution level in import and export class is in 40 to 50 billion-dollar level. The emissions of CO2 during various Development Programs are different (Table 3). In first and second Development Programs, the pollution emissions are almost equal, while during the third Development Program pollution has significantly decreased. The highest effect on pollution is related to economic growth variable. Since the increase in economic growth is as an important goal for every government, it is necessary to accomplish this goal taking into consideration the sustainable development and minimum environmental damage.

Localizing water resource management with optimum waste allocation approach in rivers is one of the strategies for reducing the pollution. In this regard, a water quality trading program among pollution sources can fulfill this issue. This program is achieved through a tradable discharge permits system which is based on the river self purification capacity and creates an economical incentive to reduce the pollutants. Water quality trading emerges from the concept of hydrology and economy based on the transfer coefficient which is the fraction of pollution load that is transferred from the upstream to the downstream. Transfer coefficient is obtained from the water quality model. In this paper, execution of a tradable discharge permit program for the index pollutants has been assessed. Finally the results are analyzed for evaluating the cost effectiveness.Materials and methods: Generally, a water quality trading program is executed through a five step procedure as follows:1. Zoning the study area: Based on morphological, pollutants and dispersion characteristics of the river, the study area along the river is divided to a number of zones.2. Determination of permissible load of each zone and the primary allocation of pollutant load: Allowable BOD load of each zone is determined by applying the Streeter Phelps model3. Transfer coefficient among the pollutant sources and defined zones.Transfer coefficient (aij) as in Equation (1) is the share of discharger (zone) j (Li) in the pollution of zone j (Lj)aij=Lj/Li            (1)The coefficient is determined using the water quality model.4. Calculation of Tradable discharge Permit (TDP) for each zone According to the Equation 2, TDP for each zone is calculated: TDPj=Ej=Sj-1k=1 akj.TDPk                , k<j   (2)where:TDPj= Tradable discharge Permit (TDP) for zone jEj= allowable load out of zone jakj=transfer coefficient of zone k at upstream of zone j5. Cost of pollution control: To evaluate the cost effectiveness, the cost of pollution control is calculated for technological and non- technologic control measures. In this study, the cost of treatment of one cubic meter wastewater is assumed 500 and 300 Dollars for industrial and municipal wastewater treatment respectively. The treatment plant lifetime is assumed 25 years old. Cost of trading plan implementation is composed of two sections: implementation and monitoring. These costs are estimated annually based on the type and the importance of the study area.Case Study: The study area is a part of Dez river watershed between Dez dam and Ghir dam with the length of 153 kilometers.Results and discussion: Based on the pollution sources and monitoring stations Dez River is divided to three zones as follows:Zone 1: From Dez dam to downstream of Dezfool Ghand Company with the length of 44 kmZone 2: From Dezfool Ghand Company to Abe shirin station with a 39 kilometer length.Zone 3: from Abe shirin station to Ghir dam. The length is 15 kilometers.The model of the river water quality has been developed based on the water quality variation and pollution sources along the study line. The river length is divided to seven regions and the model is calibrated according to the observed data. BOD and DO variation along the river is illustrated in Figure 2.Fill. 2: BOD - DO variation based on Streeter Phelps model…According to the results, matrix of transfer coefficients between zones and pollution sources is demonstrated in Table 1.Table 1: Matrix of transfer coefficients between zones and pollution sources Zone 1 2 3 1 1 0.64 0.52 2 . 1   3 0 0 1 According to the water quality standard, the allowable load of each zone is determined according to the results of water quality model. The TDP for each zone is calculated based on Eq 2. The results are presented in Table 2.Table 2: Calculation of TDPs based on the allowable load of each zoneA comparison between technological (treatment plant construction) and non- technological (take part in the trading plan) cost of pollution reduction is compared in Table 3. The cost effectiveness of water quality trading plan is the ratio of technological to non technological cost of pollution reduction which is calculated and presented in Table 3.Table 3: Calculation of TDPs based on the allowable load of each zoneConclusion: In this study the application of water quality trading has been demonstrated for the Dez River and the cost effectiveness of this method in pollution control has been assessed. The results show that implementation of water quality trading program is a cost effective method for municipal pollutants as buyer and industrial pollutants as seller. Also according to the cost reduction of supervision and monitoring and delay in satisfying the allowable load, this method is very beneficial and cost effective for the environmental authority. Generally the efficiency of this method is dependent on the number and amount of transactions in each zone of the study area. The most deals occur between the large pollutant as seller and small pollutants as buyer.

Sustainable development is very important especially in environmental issues. In this paper, sustainable development is studied in Iran through fuzzy logic for iron and steel production and the results are compared to the global values. Fuzzy logic is expressed by continuous value between zero and one. The following steps were taken in turn:1- Obtaining the related data from internal resources.2- Defining membership functions according to the data and the nature of features.3- Calculating and determining the degree of sustainable development well-being for iron and steel production in Iran by fuzzy rules.The present study is an analytical study which was carried out in 2007 at Islamic Azad University Ayatollah Amoli branch. The data was obtained from the literatures (29 papers and 3 books). Unruly data were excluded from the study.Sustainable development in environmental issues was discussed through six features. The first is soil and water pollution in agriculture, the second is air pollution, the third is forest, then is ecosystems, next is energy and the last is fresh water. The membership functions of that features were defined according to fuzzy conjunction and disjunction rules and presented in Eq. 1 to 11. Fuzzy conjunction and disjunction rules were selected because of the nature of features and the data. The variables of the present study were presented in Table 1 to Table 5.The degree of soil/wastewater well-being = The minimum value measured/ The maximum value measured                    (1)The degree of agriculture well-being= Min (degrees of soil/wastewater well-being)                                   (2)Table 1: Heavy metal measured in soil and wastewater of agriculture…The degree of air pollution well-being= Max (0, (1- The average of produced CO2 in Iran/ The average of produced CO2 in global))  (3)Table 2: The minimum, maximum and average of CO2 produced by iron and steel making (Ton CO2produced per one ton Iron and steel production)…The degree of forest well-being= The number of tree increasing per year/ 3(trees per one ton pig iron) x iron and steel making increasing(ton pig iron per year)      (4)The degree of consumable resources well-being1 = Min (1. The amount of benefit or global consumable / The amount of consumable resource)               (5)The degree of consumable resources well-being2 = Min (1. The amount of consumable scrap in Iran/ The amount of benefit consumable of scrap)        (6)The final degree of consumable resources well-being = Min (the degrees of consumable resources well-being)                          (7)table3: the data of iron and steel making consumable resources per one ton pig iron production…The degree of consumable energy well-being= Min (1. The amount of consumable energy in Germany/ The amount of consumable energy in Iran)             (8)Table 4: the data of consumable energy for one tone pig iron production…The degree of Sulphur content well-being=Min (1, The benefit of Sulphur content/The macimum amount of Sulphut content in coal (cock) or iron ore)     (9)The final degree of fresh water well-being=Min(the degrees of Sulphur contents well-being)      (10)Table5: The data of Sulphur conten in coal/cock or iron oreThe degree of sustainable Development in environment of Iran for iron and steel production = Min (The degree of agriculture well-being,The degree of air pollution well-being,The degree of forest well-being,The final degree of consumable resources well-being,The degree of consumable energy well-beingThe final degree of fresh water well-being)Few variables were indicated in this paper because of the lack of data. The results indicated sustainable development in environment of Iran for Iron and steel production isn't completely well-being at 2005 (The degree of well-being is 0).The topic results are taken in turn: 1-The main reason is air pollution (CO2 content in air). The degree of sustainable development well-being can increase by planting trees and decreasing the produced CO2 simultaneously. Also it is very important because it is overdose.2-The second reason is soil pollution in agriculture as Pb content (The degree of well-being is 0.012).3-The third reason is ecology problem as waste content (The degree of well-being is 0.0525).The importance of six features were defined and determined. Then the effect on the degrees of features well-being was illustrated. More researches on this topic are needed to study the economical approach and define the special training in industry.