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Background and Objective: The steel industry is the worldchr('39')s largest consumer of energy. A large amount of iron waste is produced annually, which its use in the steel industry can be economic. The purpose of this study was to investigate the environmental impacts of the steelmaking from iron scrap as a raw material using a life cycle assessment (LCA) method. Materials and Methods: Simapro software and the ecoinvent database were used to conduct LCA. Data on the steel production process (raw materials, waste, and products) were collected by a questionnaire from a steel plant. Environmental burdens were quantified using ReCiPe, Cumulative Energy Demand (CED), IPCC) Intergovernmental Panel on Climate Change) and water footprints methods. Results: The results of the ReCiPe method showed that the terrestrial ecotoxicity with a value of 14392 kg 1,4-Dichlorobenzene (1,4-DCB) eq/ton of steel and global warming with 5289 kg CO2 eq/ton of steel, had the greatest environmental impact, respectively. The lowest environmental impact of this process was obtained for freshwater ecotoxicity and human carcinogenic toxicity. The carbon footprint resulting from steelmaking is 5.24 ton CO2 eq/ton of steel. The most important sector of the greenhouse gas producer is the consumption of electricity with a rate of 2900 of kg CO2 eq/ton of steel. The cumulative energy demand of one ton of steel ingot was 73393 MJ, which is three times the global equivalent. The total water footprint for one t of steel was 19.5 m3 of water, which is almost near to the equivalent in Europe. Conclusion: the use of iron scrap as raw material in the process of steelmaking instead of iron ore has reduced the amount of human toxicity potential and mineral resource consumption.

Life cycle assessment (LCA) is a well-known and accurate methodology for comparison of environmental impacts of activities including different agricultural management systems. Since the used inputs have an important role in environmental pollution and greenhouse gas emissions, LCA have been extensively applied for crop species. This study was conducted to assess the environmental impact of saffron production systems based on field area (1 ha) in the Khorasan-e Razavi province using LCA methodology. The amounts of utilized agricultural inputs from the first year to the sixth year were collected by means of a questionnaire (13 fields from each area). In this regard, four phases, which are goal and scope definition, inventory analysis, impact assessment and interpretation, were designed to assess life cycle index with ISO14044 procedure. Functional unit were considered as one kg of flower. Three main categories as impacts on environment including global warming, acidification and eutrophication (terrestrial and aquatic) were defined. Finally, an index -called environmental index (EcoX) was calculated. Cronbach's alpha was used assessing the reliability of the questionnaire. The results showed that the Cronbach's alpha was computed with α=%84. The average values for global warming, acidification and eutrophication terrestrial and aquatic categories were calculated with115.41±53.41 kg CO2 equiv. / one kg flower yield, 0.35±0.16 kg SO2 equiv./ one kg flower yield, 0.58±0.27 kg NOx equiv./ one kg flower yield and 0.20±0.09 kg PO4 equiv./ one kg flower yield, respectively. The largest share of greenhouse gas emissions in the global warming category was related to CH4. The maximum emission of pollutants in acidification, eutrophication terrestrial and eutrophication aquatic categories was related to NH3. The results revealed that, field area affected the amounts of utilized agricultural inputs and environmental impacts as flower yield. Eutrophication and climate change categories had more sensitivity and affected as intensification based on field area. Therefore, one of the appropriate approaches to mitigate and decline the environmental impacts of agricultural production is achieving higher economical yield per unit of area by increasing resource use efficiency.

Development of renewable energy would help to achieve the goals of economic, social and ecological development which are considered as the most important factors in achieving sustainable development in each country. This article examines the impact of real economic growth per capita on the country's clean energy deals during the period 1967-2012 in Iran. To this end, the pattern Auto Regressive Distributed Lag (ARDL) and Co-Integration method are employed to determine the presence of short and long-term relations among the variables. The results show that the speed of adjustment is relatively high error correction model and the model is able to adjust the 61% of short-term imbalance error, to achieve long-run equilibrium. According to the corresponding estimations, the relationship between real economic growth per capita and renewable energy consumption, combustible renewable and waste consumption and electrical energy consumption in both short-term and long-term is negative. Also Long-term results have showed a significant negative relationship between electrical energy consumption, renewable energy consumption combustible renewable and waste consumption and real economic growth per capita. So, in long- term, increasing one percent consumption of the mentioned variables, cause to decrease the real economic growth per capita to 0.71, 0.72 and 0.79 respectively.

In forest ecosystems, forest production, storage and carbon flow are calculated based on biomass measurements. The aim of this study was to compare the biomass and carbon stock of the above-ground, litter and soil in the oak decline and control plots in Chaharmahal and Bakhtiari province. Four one-hectare sample plots were selected in the healthy (control) and declined stands of oak. Then quantitative information of all trees were measured. Allometric equations were used to calculate the above-ground biomass and carbon stock. Ten microplots were established in each sample plot and all litters were collected. Wet and dry weights and carbon content of the litter samples were measured. To measure soil organic carbon, five soil samples were taken in each sample plot. The results showed that above-ground biomass in the control and decline sample plots were 31.4 and 15.8 tons/hectare respectively. Also, the average of the above-ground carbon stock in the control and decline plots were 15.1 and 7.7 tons/hectare, respectively. The mean of litter carbon in the control plots was 1584.1 kg/ha and in the decline plots was 1148.6 kg/ha. The amount of carbon, nitrogen, phosphorus and soil moisture content showed a significant difference between the control and decline plots. The results of this study indicated significant changes in biomass, carbon stock and soil in declined stands of oak which may cause irreparable damage to the Zagros forest ecosystem, in the long term. This issue highlights the need for the attention of managers and decision makers of natural resources, regarding the provision of management solutions to control this phenomenon.

The alarming rate of population growth has increased the demand for food production in third-world countries leading to a yawning gap in demand and supply. This has led to an increase in the number of hungry and chronically malnourished people. This situation has created a demand for the formulation of innovative and alternative proteinaceous food sources. Single cell protein production is a major step in this direction. SCP is the protein extracted from cultivated microbial biomass. Algae, fungi and bacteria are the chief sources of microbial protein that can be utilized as SCP. Produced proteins from these microbes have various nutrition values. SCP is the manufacture of cell mass using microorganisms by culturing on available agriculture, industrial wastes and fisheries by products. Fish wastes due to high protein are the most important substrates for SCP production. In this study, SCP production was done from Silver carp and tuna fish wastes (head, tail and vise versa) and cooked water of canned tuna factories. The used microbes were six genus and species of yeasts include Candida utilis, Saccharomyces cereviceae, Rhodotorula, Khyveromyces marxians, Zygosaccharomyces rouxii and Bacillus subtilis and B.licheniformis. The examination was done in bench scale and CSTR bioreactor (Continuous Stirred Tank Reactor). The effects of various parameters such as pH, temperature, time, supplemented substrates, method of inoculation of microbes, rpm were evaluated. Changes of microbial growth and protein contents were tested by using Optical Density (OD) and Makrokjeldal methods respectively. In end of examination, produced protein were extracted and lyophilized. The results showed that protein percentage in bacterial protein was than yeast protein but wet percentage in bacterial protein was low. Production value produced from tuna fish wastes was higher than (30-45 g/l) to Silver carp wastes (25-29 g/l) and cooked water (10-15 g/l). By adding supplemented substrates, production value has been increased. Candida utilis, in comparison other yeasts, has high activation. B.licheniformis has also had more activation than Bacillus subtilis. The results of the effect some parameters on fermentation showed that yeasts and Bacillus in pH= 5.4 and 32oC and pH=6.9 and 35oC were better than growth pH=6 and 25oC and pH=6.5 and 30oC respectively. Time of fermentation in batch and bioreactor was 54 and 21 hours respectively. High rpm has been caused increasing of microbial growth in bioreactor. The conclusion showed that with optimizing of the growth condition such as some parameters (pH, temperature, substrates and so on) produced SCP with high efficiency. However, produced SCP should be exanimated with other specific tests such as amino acid and fatty acid profiles, minerals, nucleic acids and so on. After full examination, this SCP as probiotic could be used in fish and poultry feed. Iranian Fisheries Science Research Institute Published

Climate change is a serious challenge to human interest by its adverse effect on various sectors, such as water sources, agriculture, and energy. According to IPCC report, the average annual temperature of the earth has been raised between 0.3 to 0.6º because of the spread of the greenhouse gases, and this report predicts this amount will increase between 1 to 3.5º until 2100(Boberg et al ,2010). To study the effect of greenhouse gases in the atmosphere and the oceanic-atmospheric, general circulation model in regional scale is the most efficient vehicle. These models have been developed to simulate the current climate. They also performed well in predicting future changes in the climate and simulating interactions of soil, atmosphere, and oceans (IPCC, 2007). The effect of climate change on water sources is assessed using rainfall-runoff models by simulating hydrological processes. Studying future climate change and its likely events will help planners and water sources administrators to cope with the future challenge. Considering these likely changes will contribute to objective planning toward optional operations. Predicting future runoff value is one of the most important factors about dam construction, water transferring, agricultural growth and industrial activities.  Semenov (2008) assessed LARS-WG performance by data from 20 representative stations. Babaeian et al, (2004) and Khaliliaqdam, et al( 2013), studied the effect of climate change on the hydroelectric reservoir of Jor Dam by the microclimate model LARS-WG and scenarios B1, B2, and A1B. Output results of the model showed that Tmin and Tmax will increase to the amount of o.3-0.6 degrees. As a result, available water reservoirs of behind the dams for hydroelectric generation are affected by the decreased rainfall. BaniHabib et al, (2016), simulated the input flow of Shahcheraghi Dam using the generator LARS-WG, data downscaling, and the function of artificial neural networks on output of LARS. They found that nightly and daily temperatures rise 1.1 and 1.2 degrees from 2015 to 2040, and rainfall will decrease by 9% during January. By simulating artificial neural networks, it was determined that the input flow will experience 2.4-4.1 % decrease based on different scenarios.

Abstract This study was carried out to study the effect of biopriming using Trichoderma hamatum and Enterobacter sp. as plant growth promoting on some morphological characteristics and grain yield (GY) of wheat (Triticum aestivum L. cv. ‘Milan’). A field experiment was conducted in a split factorial arrengment based on randomized complete block design with three replications in Sari (Soteh village) during 2014-2015. Three levels of triple super phosphate (TSP; zero, 50 and 100 kg.ha-1) were applied as the main plot and both fungal (inoculation with Trichoderma hamatum and uninoculated as control) and phosphate solubilizing bacteria (PSB) inoculations (inoculation with Enterobacter sp. and uninoculated as control), were served as the sub-plots. The results indicate a positive effect of both fungal and PSB inoculations on the most studied traits of wheat. Enterobacter sp. increased GY by 19, 7, and 26% when used with zero, 50 and 100 kg.ha-1 of TSP, respectively. In addition, Trichoderma hamatum increased GY and biological yield (BY) by 13 and 10%, respectively, as compared to the control conditions. Enterobacter sp. inoculation along with Trichoderma hamatum enhanced the values of all studied triats such as panicle length (4%), GY (21%) and (10%) as compared to the control. Therefore, these environmental friendly microorganisms can be used as an effective seed inoculants to improve grain yield of wheat and to decrease over application of P fertilizers and also could be useful tools for soil productivity, particularly when were used along with TSP as compared to the application of TSP alone.

Considering its biological situation, each country has a specific carrying capacities to absorb pollutants. Increased production, population, and direct and indirect fossil energy consumption have increased emissions such as carbon dioxide, resulting in destructive effects on the environment such as imbalanced greenhouse gases, global warming, climate changes, and endangering of humans’ and other creatures’ lives. The extent and dimension of the mentioned effects can vary depending on the consumption modus and technique practiced by households and industries. Ecological carbon footprint is a criterion to measure the humans’ impact on carbon emissions. In an attempt to measure the carbon footprint of households, this research seeks to answer the following questions: How much is the carbon footprint of urban and rural household deciles? What deciles create higher carbon footprints? What is the share of households in the country’s total carbon footprint? How big is the carbon footprint per capita in each decile? For this purpose, the Social Accounting Matrix of the year 2011 is used. The empirical results indicate that in 2011, the total net direct and indirect carbon footprint in Iran was 517 million tons, in which the household consumption accounts for 64% and the remaining 36% belongs to the government’s final consumption, export and others. Moreover, carbon footprint of urban households is more than the rural ones and it is elevated in higher income deciles. Carbon footprint of the tenth urban decile is 11 times greater than the first one. For rural deciles, this ratio is 9. Furthermore, carbon footprint of the tenth urban decile is 4 times greater than that of the tenth rural one. An Iranian’s household carbon footprint per capita was found to be about 4429 kg in 2012. Carbon foot print per capita in the first urban decile, the tenth urban decile, first rural decile, and the tenth rural decile is 1,124, 17,134, 965 and 9,803 kg, respectively. The results indicate that people with higher incomes have a greater carbon footprint.

Introduction: Greenhouse gases absorb the radiation reflected from the earth surface which would otherwise be sent back into space. The composition and mixture of these gases make life on earth possible. In recent years, human activity has affected both the composition and mixture of the atmosphere, modifying the climate. When climate changes, crop production is affected. There are many studies that consider the type and amount of production changes for particular crops, places and scenarios. Others attempt to expand knowledge about production changes and their impacts on economy and regional welfare. Climate change affects agriculture through direct and indirect affects i.e. temperature, and precipitation changes in the biological and physical environment. Restriction in water availability is one of the most dramatic consequences of climate change for the agricultural sector. Water availability is expected to be even more limited in the future. Scarcity of water is due to potential evapotranspiration increase. It is related to increase in air and earth surface temperatures. This phenomenon is important in low-precipitation seasons, and is even more severe in dry areas. The number of regions with loss of soil moisture is expected to increase, resulting in direct economic consequences on the production capacity. Considering the above decisions, the main objective of this paper is to integrate climate change into agricultural decision-making by using an Economic Modeling System to identify the impacts of climate change induced by greenhouse gas emissions on agricultural sector productions and available water resources in the down lands of the Taleghan Dam. Materials and Methods: In this study, the effects of greenhouse gases on climate variables of temperature and precipitation under emission scenarios A1B, A2 and B1 were evaluated using time series data from 1981- 2008 and General Circulation Models (GCM). Then Ordinary Least Squares (OLS) was used to survey the impacts of climate variables on the selected products yield. Changes in agricultural production, farmer’s gross profit and economic value of irrigation water were analyzed and compared with the base year by the regression analysis results in the Positive Mathematical Programming (PMP) model. This methodology that was developed by Howitt (1995) to calibrate agricultural supply models has been used to link biophysical and economic information in an integrated biophysical and economic modeling framework and to assess the impacts of agricultural policies and scenarios. These models are also accepted for analyzing the impact of climate change and water resources management policies and scenarios. The PMP model used in this paper is a three-step procedure in which a non-linear cost function is calibrated to observe values of inputs usage in agricultural production. In the basic formulation, the first step is a linear program providing marginal values that are used in the second step to estimate the parameters for a non-linear cost function and a production function. In the third step, the calibrated production and cost functions are used in a non-linear optimization program. The solution to this non-linear program calibrates to observed values of production inputs and output. The required data in this paper were collected from meteorological stations and the relevant agencies in the Qazvin province. Regression functions estimated in Eviews software package and the PMP model were solved in GAMS (General Algebraic Modeling System) software. Results and Discussion: The results obtained in this paper showed that with emissions of greenhouse gases under the studied scenarios (A1B, A2 and B1), the average annual climate variables of temperature and precipitation changes from 1.64 to 2.28 °C and from20.92 to 1.1 mm, respectively. With these change, the yield of the most selected products decreases in the down lands of Taleghan Dam. Moreover, the obtained results showed that with emissions of greenhouse gases under the scenarios A1B, A2 and B1, the total acreage of the selected products changes from 2.18 to 4.09 percent. Total used water also decreases from 1.67 to 5.18 percent. Moreover, with emissions of greenhouse gas under the above scenarios total farmer’s gross profit decreases from 1.93 to 3.72 percent. However, the economic value of water increases from 4.27 to 13.6 percent in comparison with the base year. Conclusion: In this study finally, in order to reduce greenhouse gas emissions in the vicinity of the down lands of the Taleghan Dam, it is recommended that the government should use punitive tools (green complications) for polluting units and serve the private sectors in forestry projects in the vicinity of the industrial towns. Keywords: Agricultural productions, Climate change, Greenhouse Gases, Positive Mathematical Programming, Taleghan Dam

Abstract Background and Aim: Increasing energy consumption has created an energy crisis in the world. Fossil fuels are limited and depleting. Biogas is considered a fuel that has attracted the attention of researchers. To increase biogas production, different pretreatments have been utilized. The purpose of this study was to investigate the optimal mixing ratio of Municipal Solid Waste (MSW) and Sewage Sludge (SS), as well as the effects of various conditions of alkaline pretreatment on biodegradability of wastes and the amount of biomethane production. Materials and Methods: This study was done in a laboratory digester with 1 L volume at 37 °C with different concentrations of NaOH in a completely randomized design. Biogas volume, methane volume, and changes in pH were measured daily. Measurement parameters in the anaerobic digestion including total solids, volatile solids, and carbon and nitrogen content in the feedstock were determined according to the APHA standard methods. Results: The optimal mixing ratio of MSW to SS was 60:40 with the highest methane yield of 254.87 mL/g VS. Next, the effects of 2, 6, and 10% NaOH concentrations were evaluated on the amount of gas produced, indicating that 6% NaOH concentration significantly improved waste decomposition. Methane production, VS, and TS removal were compared to the control treatment, and there were increases of 30, 27.94, and 27.25%, respectively. Conclusion:The results showed that the mixing ratio of MSW to SS at 60:40 with 6% NaOH improves the decomposition of organic wastes and increases biomethane production. Keywords: Alkaline Pretreatment; Anaerobic Digestion; Biogas; Municipal Solid Waste; Sewage Sludge