روح الله میرزایی

Among the various species of mammals, three guilds of the Bovidae and Cervidae family, including red deer – roe deer, goitered gazelle – chinkara, and wild goat – mouflon have always been considered as target species in conservation programs. However the impacts of climate change on the effectivness of the conservation areas (CAs) of Iran is poorly understood. The current research using Speceis Distribution Model (SDM) based on MaxEnt model aims at identifying suitable habitats and hotspot areas for these species in the current time and evaluate the impact of climate changes by 2050. Our results showed that all models obtained AUC > 0.8 revealing proper predictive performances. The comparison of the area of suitable habitats for the current time and 2050 showed that all species, except for chinkara and goitered gazelle, will face a reduction in the area of suitable habitats in the future. Among the speceis roe deer and red deer will experience the greatest habitat loss, 70% and 61%, respectively. The evaluation of the effectiveness of the CAs to cover hotspot areas, Class 4 and Class 5 of speceis richness, revealed that only 12% and 18% of hotspots will be covered by the conservation network in the current time and 2050, respectively. Therfore, the present study by identifying hotspots of these species could be considered as an operative tools for the conservation planning of in the current time and future.

Nowadays, the physical expansion of cities has made citizens dependent on private and public vehicles to move around the city to meet their needs. In recent decades, many cities around the world have made efforts to improve their central texture. One of these measures has been to build turns in some streets into sidewalks, which has proved to improve the quality of the environment by eliminating or reducing car traffic on busy streets. Walking is as natural as breathing. Increased physical activity is one of the biggest health concerns of the 21st century. Encouraging people to walk as a superior way to move them is very important due to its positive effects, and strategies need to be adopted to make it attractive. The purpose of implementing these policies is to increase the environmental quality of walking through the street space which is the right of way for pedestrians. The purpose of this study is to investigate the effects of socio-economic factors on pedestrian acceptance in Kashan. The research is of an applied type.

The research method in the present study is descriptive-analytical.  To obtain and collect up-to-date data, the researcher prepared a questionnaire which, according to the research background and theoretical foundations, included many socio-economic issues affecting the acceptance of walking in Kashan. The statistical population of the present study consisted of the city population of 304487. The sample size was estimated to be 150 people based on the Sample Power software. The data were analyzed by the SPSS and AMOS software programs. The main tool of this research was a questionnaire with 68 items whose content validity was confirmed by experts, and the reliability of the questionnaire was confirmed by completing 30 initial questionnaires and performing Cronbach's alpha test. Cronbach's alpha test was also used to determine compatibility. The reliability of the questionnaire was evaluated using Cronbach's alpha test in the SPSS environment for 44 questionnaire items. A number was obtained to indicate the reliability of the questionnaire.

The results of the analyses indicate that the variables of age, sex, and location contribute for more than 0.5, which is statistically significant. It is also indicated that the underlying factors (i.e. age, gender, and neighborhood) are effective in accepting the walk. The variables of social interaction, happiness, attractiveness, attendance, and enhanced level of awareness are of higher effects than the desired average (3), and the variables of security and satisfaction with services are lower than the average. According to the average values obtained, the sum of the averages of social indicators is equal to 3.28. It can be stated that the total of social variables in this region is at a higher level than the average. This factor indicates the desirability of social indicators in the region. Among the economic factors, the variables rate of business use, the prosperity of use, commercial real estate, residential real estate, willingness to buy, and travel cost have been defined as significant (0.05). Also, according to the upper and lower limits and the significance levels, the variables of business usage, prosperity, commercial and residential real estate, and travel costs are significant and of appropriate evaluation indexes, and the variable of multiple shopping centers is higher than 3; due to the level of significance of 0.257 and the upper and lower limits, it is not significant and, thus, inappropriate. The average of the total economic indexes is found higher than the average level, which indicates the desirability of this index in the region. The findings of the second-order factor model show which variables are ultimately more important. The findings show that the social factor has the highest factor load of 0.89 and is more effective than the other factors. Next to the social factor, there are the health factor with a factor load of 0.6 and the economic variable with a factor load of 0.58. Therefore, it can be said that the social factor has the greatest impact on the acceptance rate of pedestrians.

According to the results of this study, suggestions are viewed reasonable for accepting to walk in Kashan. They are as follows: Creating micro-service applications for easier access, creating public open spaces such as squares, local parks, providing adequate lighting for sidewalks at night, using signs and boards to identify sidewalks and places of interest in Kashan, increasing the width of the sidewalks, and providing access to shops, benches, chairs, kiosks and toilets in the city.

The aim of the present study was to assess the probable heavy metals contamination in topsoil surrounding Venarj mine in Qom province using contamination indices and artificial neural networks method.

  in order to evaluate the contamination status around Venarj mine in Qom province, 70 soil samples were collected in an area of 22 Km2, and  the total average concentration of Mn, Pb, Zn, Cu and Ni was measured. The indices of geoaccumulation (Igeo), contamination factor (CF), pollution load index and human health risk assessment index were applied to quantify the risk of soil contamination with heavy metals. Also multilayer perceptron (MLP) neural networks method was used to determine the spatial pattern of soil contamination with heavy metals.

Applying contamination indices indicated that the soil of the Venarj area was contaminated with Mn and Pb and to some extent with Cu due to mining activities. However, no significant enrichment of Zn and Ni was observed. Human health risk assessment indicated that the highest risk of carcinogenic and non- carcinogenic were associated with Pb, where carcinogenic risk was higher in children than adults. Spatial distribution patterns of the elements demonstrated that the maximum concentration of heavy metals was observed in western (extraction region) and southwestern (crusher region) areas. Distance increasing from mine decreased the concentration of all metals in topsoil samples, indicating their mining source.

The results revealed that the topsoil concentration of Mn and Cu and especially Pb around the Venarj manganese mine was increased due to the mining activities. The most negative environmental and health effects of the mine resulted from higher concentration of Pb in the soil.

Rainfall is one of the most important factors affecting vegetation cover. Fluctuation and year-to-year variation of rainfall always affect vegetation cover patterns. The main aim of this study was to investigate and modeling the effects of rainfall changes on the variation of the vegetation cover in the Meyghan basin in Arak province using MODIS satellite images. NDVI, DVI, RVI and EVI indices were used to manifest vegetation covert variations linear and nonlinear relationship between vegetation cover changes and rainfall investigated simultaneously (May), with one and two month delay (April and March) ) during the statistical period of 2000-2017. The rainfall trend analysis was done using non-parametric Mann-Kendall test. According to the results, the minimum rainfall during the 18-year period was increased. Between vegetation indices, NDVI index showed the maximum and the average incremental trend. Between precipitation and vegetation, third-order non-linear relationship was stronger than linear, quadratic, power, logarithmic and exponential. The maximum correlation between DVI index and rainfall was obtained for synchronous times, while, the maximum correlation was observed between NDVI index and precipitation. The study with two month delay showed that the maximum correlation (0.52) was between the RVI index and precipitation. Vegetation modeling using simultaneous rainfall and delay of up to two months showed that the indices of DVI, RVI and EVI provided the best regression relationship at the same time, while the NDVI index had the best regression relationship with rainfall of two months ago.

Textile industry wastewater in additions toxicity for organisms led to changes as decreased of water transparency and sunlight penetration and increase in chemical oxygen demand. Therefore, this study was carried out with the aim of removal of cationic red 46 dye from aqueous solution. For this purpose, the magnetic polymeric composite of graphite oxide nanoparticles (GO) and magnetic nanoparticles (MNP) in the matrix of polyacrilonitrile fiber (WPAN) at micro size by electroespining method was prepared. The XRD and SEM tests were used to determine the polymeric adsorbent characteristics. Magnetic properties of magnetic nanoparticles and polymeric adsorbent were measured at using vibrating sample magnetometer (VSM) analysis. Batch adsorption tests were optimized using the L16 orthogonal array of Taguchi method. The effects of variables including pH, adsorbent dosage, initial dye concentration and contact time on the dye removal were examined and the most influential factor in the removal of dye was pH. The adsorption isotherm data were well-fitted to Freundlich isothermal model (R^2= 0.99). Furthermor, adsorption kinetics of the dye followed pseudo-second-order model. Basic on these results, the polymeric composites was effective adsorbent for dye removal with efficiency over 96% and with quick separation for dye removal from aquatic solution.

According to Jane Jacobs, the main part of the concept of "street life" lies in its pedestrians. From his point of view, these are busy and vibrant walkways that give meaning to the city center by providing a social interactive environment. The existence of communities to achieve sustainable transport goals is obvious because it improves displacement, reduces the negative environmental impacts, enhances the economy, and improves social sustainability by improving social interaction. Perhaps disassembly can be considered as the amount of capacity and ability to navigate properly in the built environment. The contribution of walking on community safety, access and social participation has emerged as a serious challenge to the design of the urban environment, as pedestrian access has steadily decreased in most cities over the last century. In Iran, population growth, accelerated urbanization and increased personal ownership of urban vehicles, especially in the central part of the cities and the old texture, have increased the density in the city center road network and the occurrence of traffic congestion in them, which are generally for the passage of this type and The volume of traffic was not designed and the lack of road networks and their mismatch with today's needs, as well as the deployment of adsorbent population and productive forces, dense neighborhoods and sometimes incompatibility of the basic problems of these areas, and causing interference between rides and pedestrians. The area is in the city of kashan. Kashan is considered one of the most important historical cities of Iran, which has many monuments and valuable monuments. The protection and protection of these historical monuments requires pollution and traffic congestion of the cabin to pay attention to the issue of pedestrians. Although the city of Kashan has some problems, such as low passageways, narrow pedestrian width, crowded traffic and urban traffic, disturbing street view, floor problems, and other issues. For this purpose, the preliminary research is the answer to the question of what is the priority of the planning indicators for pedestrians and, finally, the appropriate passageways for walking in the city of Kashan

Protecting a representative array of habitats is currently the most effective tool for biodiversity conservation. Hence, identifying the most important areas for conservation is a critical task and a priority. We selected reserves in the Golestan Province based on their importance for avifauna. To achieve this, the distributions of 129 bird species within the province were modeled through ecological niche modelling. Applying simulated annealing algorithm, conservation patches were then selected to cover 5%, 10%, 15%, and 20% of the distribution ranges of the studied species. Two scenarios were considered: 1- reserve selection without considering current protected areas network in Golestan Province to conserve 5, 10, 15 and 20% of the species geographic distributions in Golestan province, 2- supplementation of current protected areas network to conserve different percentages of species’ distributions. Results showed to achieve these conservation goals, 1066 km2 (5.23%), 2161 km2 (10.60%), 2308 km2 (16.23%) and 4562 km2 (22.40%) of the province surface area would be respectively required to be protected. The overlap between the existing protected areas network and the selected conservation patches in this study based on the above-mentioned conservation goals were 14.80%, 21.08%, 31/21% and 43.20% respectively. Among the current protected areas of the province Gomishan and Qazanqayeh protected areas had the most overlap with the proposed conservation networks, while Azizabad and Khosh-Yeylagh protected areas were not selected as conservation important areas. The overlap between the selected conservation netwoks and the existing protected areas of the province was less than 50 percent. Results of second scenario indicated that the expansion of the protected areas network by 5.6, 16.6, 40.1 and 72.7 percent are necessary to meet 5, 10, 15 and 20 percent conservation targets respectively.

The adsorption process is one of the most effective methods for removal of dyes from wastewater. The main aim of the present study was to investigate the efficiency of hydrated cement as an adsorbent for removal of Direct Yellow 12 dye from aqueous solutions.
This study was performed experimentally in laboratory scale and in a batch system. The effects of initial dye concentration, absorbent dosage, contact time and pH on efficiency of dye removal were investigated. SEM, XRD and FT-IR were used to characterize the hydrated cement powder particles. Langmuir and the Freundlich adsorption isotherms were selected to explicate the interaction between the dye and adsorbent. The pseudo-first and the pseudo-second-order kinetic models were used to calculate the adsorption rates.
The results showed that by increasing the adsorbent dose from 0.05 to 2 g/l, dye removal efficiency increased from 31.1 to 97.43%. The highest dye removal efficiency (87.33%) was obtained at pH= 1. By decreasing initial dye concentration from 60 to 5 mg/l, dye removal efficiency increased from 50.79% to 68.94%. The appropriate time period to get maximum dye adsorption was 180 min. The results also showed that the adsorption of dye followed the Freundlich isotherm model (r2= 0.99) and adsorption kinetics of the dye followed a pseudo-second-order model (r2= 0.99).
Compared to other costly methods of dye removal, hydrated cement powder can be used as an efficient and low-cost adsorbent for the removal of dye from aqueous solutions.

Due to the importance of accessibility to updated and timely information regarding land cover changes, it is necessary for researchers and managers to assess such provincial level changes to help the planning process and prevent the damages caused in various regions. To this end, the Chaharmahal and Bakhtiari Province land cover changes from 2015-1994 were developed in six main classes using the hybrid method. Then land cover changes were determined by applying “after-classification comparison” and “landscape metric”. Therefore, MPS, LPI, NP and PLAND metrics were calculated at the class level, and SHDI, LPI, CONTAG SPILIT INDEX metrics were calculated to quantify the landscape patterns at the landscape level. Finally, for each land use type, the destruction rates and the human destruction index were calculated separately. The results indicated a sharp decline of %36.67 in pastures and 6.42% in the forests areas, as well as an increase 39.32% in the barren lands. In such a manner, the landscape is more fragmented, disordered (or unsystematic) and discontinuous plus it has become more diverse for the studied time period coverage. So, if the current trend continues, the a sharp decrease in the ecosystem services and functions is likely to occur.

It is essential to remove dye products from wastewater. The main aim of present study was to investigate the efficiency of marble powder as an adsorbent for removal of BR 46 dye from aqueous solution.This study was performed experimentally in laboratory scale and in a batch system. In this research, the effect of initial dye concentration, absorbent dosage, contact time and pH on efficiency of dye removal were investigated. SEM, XRD and FT-IR were used to characterize the marble powder. Langmuir and the Freundlich adsorption isotherms were selected to explicate the interaction of the dye and adsorbent. Two kinetic models (the pseudo-first-order and the pseudo-second-order) were used to calculate the adsorption rate constants. The results showed that the efficiency of dye removal was increased with increasing adsorbent dosage and by increasing adsorbent dose from 0.05 to 2 g/l, dye removal efficiency was increased from 82.91 to 87.55%. The highest dye removal efficiency (56.9%) was obtained in pH= 9. By decreasing initial dye concentration from 30 to 250 mg/l, dye removal efficiency was increased from 90.84% to 56.7%. The appropriate time period to get the maximum of dye adsorption and equilibrium state was 90 min.The results also showed that the adsorption of Basic Red 46 followed the Langmuir isotherm model (r2= 0.89). Moreover, results indicated that the adsorption kinetics of the dye followed pseudo-second-order model. Compared to the other expensive dye removal methods, the marble powder can be considered as a non-expensive adsorbent for the removal of BR 46 from aqueous solution.

Telomerase is an enzyme, which is overexpressed in 80-90% of cancers. Simultaneous activities of telomerase and NF-κB are required for progression of many cancers. In recent years, researchers have found out a close relationship between telomerase and the transcription factor NF-κB. Increased expression of telomerase is associated with significant increases in the expression level of NF-κB and endogenous genes, such as IL-6 and TNF-α. In recent years, several methods have been proposed to inhibit telomerase in cancer cells. Therefore, If it is possible to inhibit telomerase activity and consequently reduce the expression of inflammatory cytokines, the NF-κB signaling pathway, and the expression of target genes in the multiple myeloma disease. In this study, the effect of MST-312 (a derivative of green tea) with telomerase inhibition activity, was investigated on the treated U266 cell line and the expression of inflammatory cytokines.
In this experimental study, U266 cells, were treated with different dosed of MST-312 for 48 hours, and cellular apoptosis, was assessed by Annexin V Apoptosis Detection Kit. Then, to assess the expression of IL-6 and TNF-α genes, cells were treated with MST-312 (2μM for 48 hours) and the RNA of these cells, was extracted. In the following, real-time PCR method was used to investigate gene expression level.
In this study, an increase in apoptosis and a decrease in the expression of IL-6 and TNF-α genes in U266 cells, was observed after 48 hours of exposure with 2μM MST-312. In addition, no cytotoxic effect was observed on normal blood mononuclear cells.
The results of the present study indicated that inhibition of telomerase activity by MST-312, can be considered as a novel treatment strategy for multiple myeloma.

PM2.5 particulate matter is one of the major air pollutants in cities of Iran especially Tehran, which threaten health of Iranian people due to numerous health hazards. Risk levels of these particulate depend on spatial-temporal changes in the air. Hence, this study aimed spatial-temporal analysis of PM2.5 concentration in Tehran's air using the Geographic Information System.
Material and Hourly data of PM2.5 concentration was collected in 2016-2017 from 38 air pollution monitoring stations and was analyzed monthly, seasonally and annually. Inverse Distance Weighting interpolation method was used in order to present concentration maps of the PM2.5. Existence of spatial autocorrelation in data was analyzed by Moran's I and data clustering was accomplished by Global and Local Moran's I and finally Getis-Ord-Gi index was used to determine hot spots of this pollutant in Tehran.
Results of concentration maps of PM2.5 and global and local spatial autocorrelation with PM2.5 concentration hot spot analysis showed that the concentration of this pollutant has an incremental mode from the north to the south of Tehran so that areas in south of Tehran especially Ray stations were the most polluted areas in Tehran. In addition, results showed that the concentration of this pollutant was more in the two colder seasons so that most hot spots were identified in these seasons.
Using several spatial analyses simultaneously showed that Tehran can be separated into two parts of non-polluted north and polluted south, which this issue should be considered by urban planners to improve Tehran's air quality.

The environment and development are two major concerns worldwide. The state of being under the influence of human activities and the increase in demands for resources utilization is a factor which prompts researchers to vulnerable areas and take necessary measures where it is required to manage and protect the environment and sustainable development. In this study, environmental vulnerability index EVI of Lorestan province with characteristics of natural impacts (topography, climate, geology, vegetation index NDVI, water density), environmental impacts (erosion, land use, DRASTIC index) and human impacts (road density, population density and waste depot location), have been investigated. For this purpose, two analytic hierarchy process AHP and weighted linear combination WLC , based on the geographic information system, have been used. Environmental vulnerability impact maps of the two methods were categorized in 5 classes of very low, low, moderate, high and extreme vulnerability. Based on the results of the AHP method, 1.76% of the province with an area of 482.1 km2 is located in the category of extreme vulnerability. Also, based on the results of the WLC method, 14.18% with an area of 3998.4 km2 was placed in the category of extreme vulnerability. Hot spots in the province include the center and south of Aleshtar City, the center and east of Khorramabad City, the center and east of Boroujerd City, Doroud center, north and east of Aligoudarz and northern Azna. In the cities of Kouhdasht, Rumeshkan, Doureh and in the west of the city of Poldokhtar and northwest and south west of Nourabad known as hot spots. Finally, the priority of vulnerability to surface and underground water resources, vegetation and soil was determined in the province.
Extended Abstract
1- The environment and development are two major concerns worldwide. The state of being under the influence of human activities and the increase in demands for resources utilization are the factors which prompt researchers to identify vulnerable areas and take necessary measures when it is required to manage and protect the environment and express sustainable development. Therefore, the aim of this study is to determine the spatial pattern of environmental vulnerability in Lorestan Province, through which the critical points of the province and the contribution of natural and human factors to the vulnerability of the regions are identified.
2- Environmental vulnerability index (EVI) of Lorestan Province has been investigated with characteristics of natural impacts (topography, climate, geology, Normalized Difference Vegetation Index (NDVI), and water density), environmental impacts (land use, DRASTIC vulnerability index and erosion) and human impacts (road density, population density and waste depot location). For this purpose, two methods of analytic hierarchy process (AHP) and weighted linear combination (WLC) have been used. To apply AHP, a questionnaire was designed to handle paired comparison between the criteria and their classes. Then, the relative importance of the elements was determined by 15 environmental experts and the weights ware calculated using the Expert Choice software. Subsequently, the vulnerability map was prepared according to this method. Also, for the weighted linear combination method, considering the importance of the classes of criteria and the expert opinion in relation to the terms of the study area, the threshold for the criteria was determined and the maps were standardized using the scale of 0-255 in Idrisi TerrSet software environment. So that, the symmetric fuzzy function was used for height, slope and vegetation index, the decreasing function was used for the average rainfall and waste depot location criteria. Besides, increasing function was used for geology, mean temperature, water density, road density, population density, land use, DRASTIC index and erodibility criteria. Then the vulnerability map was prepared and eventually, maps of the eenvironmental vulnerability index derived from the two methods were categorized into five classes of extremely low, low, moderate, high and severe vulnerability.
3- The results showed that according to the analytic hierarchy process, 15.2 percent of the province's area was very vulnerable, 44.38 percent had a low vulnerability, 42.22 percent had a moderate vulnerability, 9.51 percent was located in the high vulnerable class and 1.76% was placed in severely vulnerable category. Therefore, the most area of the province was located in the low vulnerability category. According to the weighted linear combination method, 1.94 percent of the province's area was very vulnerable, 12.25 percent had a low vulnerability, 30.50 percent had a moderate vulnerability, 41.14 percent was located in the high vulnerable class and 14.18% was placed in severely vulnerable category. Therefore, based on this method the most area of the province was located in the high vulnerability category. Compared to the analytic hierarchy process, the hot spots in the province through weighted linear combination method were more extensive. The size of the environmental vulnerability classes differentiated by elevation categories showed that the altitudes of 191-1000 includes the highest range of hot spots compared to the extent of its province's coverage. After that, the altitudes of 1000-2000 and 2000-3000 were ranked second and third, respectively. The extent of the vulnerability classes differed by the counties of Lorestan Province showed that based on the area of each county, Aleshtar has the highest rate of vulnerability than any county. Subsequently, Boroujerd, Doroud, Khorramabad, Poldokhtar, Aligoudarz, Nourabad, Azna, Roumeshkan, and Kouhdasht are in next categories respectively. Most identified hot spots were distributed in center and south of Aleshtar, center and east of Khorramabad, center and east of Boroujerd, north and east of Aligoudarz and north of Azna. Also these spots can be recognized dispersedly in Kouhdasht, Roumeshkan and Doureh, north of Poldokhtar and northeast and south of Nourabad.
4- The investigation of the vulnerability condition of recognized hot spots in the counties of the province showed that the effective factors in the increasing of environmental vulnerability vary based on the county. This means that in Aleshtar, Khorramabad, Boroujerd, Doroud, Aligoudarz and Azna counties, agricultural and urban land uses had the highest role in the environmental vulnerability, while in Kouhdasht, Roumeshkan and Doureh counties oak forests and in Polodokhtar and Nourabad, agricultural lands and sensitive geological structure have been effective in the increasing of vulnerability and recognition of hot spots. Recognizing the vulnerability hot spots and their most important formation factors in county level can determine the priority of environmental policy and planning for mitigating the environmental vulnerability level.

Monitoring and managing the wildlife populations and habitats required to model the species distribution and habitat suitability. So, Gazella subgutturosa potential distribution in Mishdagh Protected Area was modeled using fuzzy (based on ecological knowledge of local communities) and MaxEnt (based on species occurrence records) approaches; thus, in addition to model the species distribution using maximum entropy algorithm (MaxEnt approach) and fuzzy inference system (fuzzy approach), we can also assess and compare the performance of each approach. In addition, the accuracy of predictive models was tested using jackknife test. Also, we applied threshold of 10%. Based on results of fuzzy and MaxEnt approaches, the most important variables for species potential distribution modelling were land use, distance to farms and distance to water sources. Also, 47.45% and 14.08% of study area predicted as species potential presence area in fuzzy and MaxEnt approaches, respectively. According to results of jackknife test, success rates of fuzzy and MaxEnt approaches were 80.95% and 66.66%, respectively (p

Bushehr Province has been located in the south west of Iran and due to water shortage crisis in this province, the water quality assessment of its rivers is very important. This study was conducted with the aim of the quality assessment of Shapour, Dalaki, Helleh, Baghan, Mond and Bahoosh in Bushehr Province by using NSFWQI and IRWQISC indexes, because of the importance of these rivers in drinking, agricultural and industrial consumption .
In this study, water sampling information were taken from 11 stations along 6 rivers including Shapour, Dalaki, Helleh, Mond, Bahoosh and Baghan during 2011-2013. Then, Tthe quality assessment of above-mentioned rivers was implemented by using NSFWQI and IRWQISC indexes. PO4, NO3, DO, BOD, and COD were the parameters that used for the calculation of IRWQISC whereas DO, NO3, PO4, and BOD were utilized for the measurement of NSFWQI index. One way analysis of variance was applied for the comparison of the mean of water quality parameters among different years. Moreover, ArcGIS 10.1 was applied for spatial analysis of water quality parameters and water quality indexes.
The results of this study indicated that according to IRWQISC index, Baghan and Dalaki rivers with scores of 31.3 and 39.8 were categorized as bad quality rivers while Shapour, Mond, Bahoosh and Helleh with 46 and 53 scores were included in the average quality category. In addition, with respect to NSFWQI index; Baghan River with a water quality index value of 68 was in the average quality group whereas the rest of rivers with values of 73 and 80 were in the good quality rivers.
The findings of this study proved that the of Shapour, Dalaki, Helleh, Mond, Bahoosh and Baghan rivers water were suitable for agricultural purposes while it should be purified for drinking purposes.

Due to the importance of water consumptions, this study aims to investigate the spatial trend of surface water quality along Kan and Karaj Rivers using three quality indices: NSFWQI, IRWQIsc and WQI.
The information of water quality parameters of 20 monitoring stations was collected to investigate water quality parameters along two mentioned rivers during 2012-2013, and water quality of two rivers were calculated using mentioned three quality indices. The parameters of TDS, FC, EC, nitrate and turbidity were used to measure the NSFWQI and IRWQIsc indices, and TDS, nitrate, and sulfate were used to calculate the WQI index. The measured parameters were compared with standards of drinking. The monitoring stations were grouped by cluster analysis and finally, the pattern of changes in water quality parameters and relevant quality indices were analyzed spatially using ArcGIS software.
The water quality of Kan and Karaj Rivers based on NSFWQI index were in the range of bad and average quality, respectively. According to IRWQISC index, water quality were in the range of very bad and relatively good, respectively and according to the WQI index water quality was in the range of good quality. The quality of upstream was acceptable for drinking and irrigation, on the basis of medium and good conditions of NSFWQI and IRWQISC, respectively. However, the downstream of both rivers are heavily polluted. The results of the clustering analysis stated that moving towards upstream-downstream the quality of water decreases along both rivers.
The spatial trend analysis of water quality parameters along the rivers plays a crucial role for identifying the spatial variation of water quality. Also, availability of clean water depends on the geographical locations and topological situation across the basin.

Nowadays, increasing the urban population, followed increasing in waste production has attracted the attention of environmental researchers towards the sanitary waste disposal. It is estimated that in Khorramabad city with a population of over than 348,216 people, about 458 tones of urban waste are daily produced which are dumped in open lands. Therefore, finding a suitable site for waste disposal is necessary. The purpose of this study is to identify and introduce suitable locations for the sanitary waste disposal across the city using Electre as a Multi Criteria Decision Analysis.
Material and For this purpose, 14 criteria including soil erosion, geology, land use, distance to roads, distance to rivers, springs and kanats, distance to faults, distance to cities and villages, slope, elevation, groundwater depth, distance to protected areas and climate were used. Three common methods including Boolean, Analytic Hierarchy Process (AHP) and Linear Combination Weighted (WLC) were used to combine the criteria maps. Considering the minimum area required for landfill sitting for a period of 20 years, five candidate sites were ultimately extracted from the final resulting map of WLC in order to introduce the best site for urban landfill. Then, these five candidates were ranked using Electre model.
Results of weighting process showed that the groundwater depth, distance to faults and cities had the highest weights whereas elevation and slope criteria had the lowest weights. The consistency ratio for the weighting process was 0.08, which was less than 0.1, presenting the consistency and credibility of the weighting process. According to the WLC method, major parts of north-west, west and north of the area under study were identified as optimal sites. According to the results of Electre model, a site with an area of 694 hectares located in the west of city was identified as the best alternative.
The results showed that the Electre method along with multi-criteria evaluation methods can have high performance in locating sanitary municipal solid waste disposal.

Several modelling techniques have been developed for habitat suitability modelling. In the meantime, the Fuzzy Inference System (FIS) with ability to model uncertainty of input variables is an effective method to model wildlife species habitat suitability. So, Persian Leopard habitat suitability was predicted in Shimbar Protected Area using FIS. Therefore, the effective environmental variables were determined. We also defined and determined the linguistic variables, linguistic values, and range of them. Then, we designed the membership functions of the fuzzy sets of the input and output variables. Also, the definition of the fuzzy rules in the system was performed. Finally, the defuzzification of output was carried out. The accuracy of the predictive model was tested using AUC. Also, 11 FISs were developed to determine sensitivity of the models and important variables in modelling. The results showed that the predictive model was more efficient than the random model (AUC=0.960). In addition, the ‘distance to capra’ was the most important predictor. According to the success of FIS in Persian Leopard habitat suitability modelling, we suggest this method to improve and complete the existing spatial information of wildlife habitats in Iran, especially about regions and species that have been less studied.

Inorganic contaminants, such as heavy metals enter into terrestrial and aquatic ecosystems from different paths such as erosion and weathering of rock, agricultural and industrial activities, automobile exhaust, sewage and atmospheric subsidence. These heavy metals because of their bioaccumulation potential, toxicity, ubiquitous, and resistance degradation, can be a serious threat to ecological systems and human health. According to Amin et al (2009), more than 90% of heavy metals loading in aquatic ecosystems found in sediments; so, the quality of sediments can be a good indicator of water pollution. In these ecosystems, sediments play an important role as a sink for organic and inorganic contaminants (heavy metals) and provide a history of human-origin emission of pollutants and environmental changes.
To address the sediment contamination by heavy metals, different approaches such as hazard quotients; crop uptake and transformation; concentrations of weakly extractable metal and total heavy metal concentration can be used.
sediment contamination is often assessed by comparing heavy metal concentrations with the relevant environmental references or by quantifying an accumulation factor in comparison to the related background concentrations. Up to now, numerous different indices such as the index of geoaccumulation (Igeo), the enrichment factor, the pollution index (PI) and the integrated pollution index (IPI), the individual element polluted index, the contamination factor and degree of contamination, the contamination factor (CF), the pollution load index (PLI) and the total contamination index (Zs) has introduced to estimate the degree of heavy metal contamination.
Up to now, numerous studies have documented the distribution, origin and extent of heavy metals contamination in sediments of various wetlands. However, wetland sediment contamination has sparsely been investigated in Iran in general and no information is available for the Choghakhor wetland. Choghakhor wetland is one of the most important wetland for waterfowl in Iran which has been exposed to different non-point pollution sources and different contaminants such as heavy metals due to surrounding agricultural and recreational activities and discharge of domestic effluents without treatment. Therefore, the aim of this study was to quantify the concentrations of Ni, Zn, Cu and Fe in surface sediments of Choghakhor wetland. Also assessment of heavy metals contamination using different contamination indices was another purpose of this study.
A total of 52 surface sediment samples were collected randomly from different parts of the Choghakhor wetland; then the samples were placed in clean plastic bags and were transferred to the laboratory for further analysis. 1 gram of sieved sediment sample was digested by using the combination of the three acids: HF, HNO3 and HClO4 whit the ratio of 3:5:7. After cooling the samples, 2 ml of boric acid 7% was added to remove the fluoride residual and with distilled water was reached to volume of 25 cc. The concentration of metals in sediments was measured by flame atomic absorption. For quality control and assurance, standard reference materials and blank samples were used.
Various types of direct (Earth Chemical) and indirect methods (statistical) are commonly used to calculate the contamination of heavy metals in the environment. However, statistical methods are more common than chemical methods because the earth is not alone useful for determining the concentration of background samples, also statistical methods have lower lab work and cost. In this study, a statistical method introduced by Ismailia et al (2014) was used for calculating of the background concentrations. Contamination assessment was carried out using several different indices including Enrichment factor (EF), Geo-accumulation index (Igeo), Contamination factor (CF) and pollution load index (PLI).
Sediment quality assessment guidelines (SQGs) can be very useful in determining the amount of sediment pollution compared with the corresponding guides. In this paper, two sets of guidelines including National Oceanic and Atmospheric Administration USA (NOAA) and the Interim Sediment Quality Guidelines Canada (ISQG) were used. These guidelines express the quality level and degree of contamination of sediments which may have an adverse effect on aquatic organisms. The Correlation and PCA analysis were used to determine the source of heavy metals in sediment samples. Inverse distance weighting method was used for mapping of heavy metals distribution in surface sediments of wetland.
Discussion of The mean total concentrations of Cu, Fe, Mn, Ni and Zn in surface sediments in the whole study area were 15.75, 6076.86, 297.74, 30.07 and 29.87 mg/kg, respectively. Average metal concentrations followed the order Fe> Mn> Ni> Zn> Cu. With the exception of Fe, the concentrations of other heavy metals in the surface sediments of Choghakhor wetland were all lower than the background values.
Mean EF values of heavy metals followed the order: Ni> Zn> Cu> Mn. Average EF values for Ni, Cu, Zn and Mn were 1.34, 2.47, 1.75 and 2.54 respectively suggesting a minor enrichment of these metals. Considering background values, enrichment of heavy metals in this study showed that heavy metals concentrations in sediment samples were mostly controlled by natural and partly anthropogenic sources. Average Igeo values for Ni, Cu, Zn, Mn and Fe were 0.014, 0.032, 0.018, 0.005 and 0.0001 respectively indicating no pollution in wetland sediment samples. However, Igeo is not readily comparable to the other indices of metal contamination due to the nature of the Igeo calculation, which involves a log function, and a background multiplication of 1.5. Mean CF values for Ni, Cu, Zn, Mn and Fe were 0.48, 0.65, 0.59, 0.68 and 0.48 respectively indicating low contamination of heavy metals in wetland sediment samples.
Results of correlation analysis showed that the heavy metals concentrations of sediment samples were significantly correlated with each other at level %1. From this, it could be said that their source was almost the same and which may be derived from the natural sources. Considering PCA analysis, all the heavy metals were well represented by the first principal component, which accounted for over 64.79% of the total variance. The results of PCA agreed well with that of the correlation analysis. As mentioned before, the concentrations of most heavy metals were lower than the background values. Therefore, it could be said that the distribution of heavy metals in sediment samples was mainly controlled by natural sources.
In this study, we analyzed the spatial distributions of heavy metals in the whole area of Choghakhor wetland. The spatial distribution patterns of most of heavy metals, especially Cu, Fe and Ni were generally similar, with increasing concentrations from the north of the wetland to the south nearby villages and residential areas. In other words, the high concentrations or hotspots for the three heavy metals mainly existed in southern parts of the area under study. In addition, the spatial distribution of Mn and Zn concentrations showed decreasing trends from the west of the area to the east.
Therefore, from the above discussion can be concluded that although entire wetland is non-polluted and the heavy metals concentrations in sediment were mostly controlled by geomorphological sources but high concentrations of heavy metals in specific areas or hot spots could be related to human activities especially agricultural activity. In particular, these hot spots are located in environmental guard station, tourist area and residential areas especially villages of Kheder Abad, Saki Abad, Seyf Abad and Khani Abad in the vicinity of wetland.
Results indicated that the average concentrations of heavy metals were all lower than background values. According to the results of Contamination Factor, Geoaccumulation Index and Enrichment Factor, considerable and intense contamination of heavy metals in sediments of study area was not observed. Based on the sediments quality guidelines, the concentration of Ni at whole study area has frequently adverse biological effect on aquatic organisms. Although, the results of the PCA revealed that all heavy metals were mainly originated from natural sources, their spatial distribution maps showed that there were several hotspots located in different parts of the area under study.

Land degradation and desertification has intensified by the interaction of climatic factors, land use change and human pressure in recent decades. Awareness that desertification is taking place in which ecosystems, the most important step to control and deal with this phenomenon. The aim of this study was to determine sensitivity to desertification Lorestan province ecoregions using life cycle assessment. For this purpose, the study area was classified into six ecoregions in terms of climate and dominant type of vegetation. Then selected indicators of drought, water erosion and excessive extraction of groundwater as the evaluation criteria. Indicators were prepared using geographic information systems. Finally, combined with variable selection and ecoregion map. Calculation of the characterization factors for each of these factors using geographic information systems, and characterization factors were obtained from the sum of the factors, a total characterization factor. Results indicated that there is the greatest sensitivity 5 ecoregion (dry/Astragalus adscendens Boiss) with characterization factors 1.29 and the lowest sensitivity to desertification 1 ecoregion (dry sub humid/Quercus brantii) with characterization factors 0.29. The results showed that aridity with 2.69 value, is the most effective factors to increasing the sensitivity of the area to desertification. Therefore, should pay attention serious to this problem in planning, managing and Combating desertification.

Selecting a suitable interpolation method is a main factor of surface analysis and it is a difficult task in geostatistical analysis since different methods of interpolation can result in different surfaces and ultimately different results. Hence, the aim of this study is to evaluate the performance of different interpolation methods in determining the spatial concentration of Cd, Zn and Cu in the Surface soil of Aran-O-Bidgol City.
A total of 135 surface soil (0-20 cm) samples were collected in the study area and the soil heavy metals concentrations were determined. The spatial distribution of heavy metals concentration in Surface Soil of Aran-O-Bidgol was evaluated using different interpolation methods including ordinary Kriging, CoKriging, Inverse Distance Weighting, Local Polynomials and Radial Basis Function. Cross validation and MSE, MBE, RMSE, NSE, PBIAS were applied to estimate their accuracy.
Findings: According to the results Ordinary Kriging (spherical model) had the best efficiency for estimating Cd and Cu concentrations and Ordinary Kriging (exponential model) had the best efficiency for estimating distribution pattern of Zn concentration in the soil of this region. The weight parameter has a significant influence on the accuracy of interpolation. The higher the order of local polynomial, the larger the accuracy of cross validation, whereas, the greater the weighting power of IDW for Cd and Zn, the greater error and larger accuracy of the interpolation will be for Cu.
Discussion and Although all of the considered interpolation methods had a high prediction accuracy of the mean content for soil heavy metals, but taking all cross validation indicators into consideration, Ordinary Kriging (OK) method shows a generally better performance than other methods.

Finding a low-cost adsorbent as well as discovering a simple modification technique to increase the efficiency of adsorbent for the removal of environmental pollutants is always important. Therefore, this study aimed to evaluate the effectiveness of the calcination to increase the efficiency of raw marble powder in the removal of Acid Orange 7 dye from aqueous solution.
In this laboratory study, the effects of different parameters including contact time, pH, initial dye concentration, and adsorbent dose on efficiency of dye removal were investigated. SEM, XRD, and FT-IR were used to characterize the Raw Powder Marble Waste (RPMW) and Calcined Powder Marble Waste (CPMW). The experimental data were analyzed using Langmuir and Freundlich isotherm models and kinetic studies. Liner regression and R2 were used to analyze the data.
The highest dye removal efficiency was achieved in pH= 12 for RPMW and pH= 7 for CPMW. With increasing contact time from 5 to 180 minutes, the efficiency of dye removal increased for two adsorbents. The highest amounts of dye removal for RPMW and CPMW within the initial dye concentrations of 5 and 300 mg/L were 53.54% and 94.45%, respectively. By increasing the absorbents dosage, dye removal efficiency increased. The results showed that the dye adsorption using two adsorbents followed the Freundlich isotherm model (R2= 0.99%) and the adsorption kinetics of the dye followed pseudo-second-order model (R2= 0.99%).
Calcination process increased 40-fold in dye adsorption capacity and hence, CPMW could be used as a relatively efficient and low-cost adsorbent in dye removal from aqueous solution.

Street dust is consisting of solid particles with complex compositions which can be an appropriate indicator to determine urban environmental contamination. Therefore, the purpose of this study was to determine spatial patterns and heavy metals contamination in the street dusts of Kashan.
A total of 48 urban street dust samples were collected and total concentrations of Pb, Cu, Zn, Fe, Cr, Ni, and Cd were determined in the dust samples. The geoaccumulation index was applied to assess heavy metals contamination. In addition, the spatial patterns of heavy metals concentrations in the street dust were determined using GIS.
The results showed that the average concentrations of Zn, Cd, Cr, Fe, Ni, Pb and Cu in the street dust samples were 237.21, 0.43, 37.12, 16589.77, 13.62, 45.18 and 45.58 mg/kg, respectively. The average concentrations of Pb, Cu, Zn, and Fe were higher than their local background values. Based on geoaccumulation index, the heavy metals in the street dust were in the following decreasing order: Pb > Zn > Cu > Ni > Cd > Cr. According to the spatial analysis results, higher concentrations of heavy metals were observed in the city center and Kashan-Qom highway; whereas, lower concentrations were found in the residential regions.
Based on the obtained results, it seems the high concentrations of Pb, Zn and Cu and to a lesser extent Fe and Cd concentrations in the dust samples was derived from anthropogenic activities; whereas the concentration of Cr and Ni has been mostly affected by natural sources. The high concentrations of heavy metals in the street dusts of Kashan could be attributed to vehicle emissions and industrial activities.

Status determination of wildlife habitats is very important in conservation programs and management of wildlife. So, in this study Ursus arctos habitat suitability was modeled using maximum entropy algorithm (MaxEnt) in Shimbar protected area. In order to model the habitat suitability, after investigating and resolving the spatial autocorrelation of occurrence records, spatially independent localities were divided into the calibration and evaluation sets and then were combined with 10 environmental variables (VIF