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Introduction: The final energy consumption per capita in Iran in the agricultural sector is 3.4, as well for household sector is 2, besides the commercial and public sectors are 1.6, and transportation and industry are 1.4 times the global average. This is due to low efficiency in operation, high energy consumption, as well as the use of energy goods and services. The use of renewable energy in the agricultural sector, while increasing the security of energy supply, will reduce global warming, stimulate economic growth, create jobs, and increase per capita income and social justice and environmental protection in all areas. The purpose of this study is to investigate farmers' preferences for using solar energy in Sari.Materials and Methods: The Choice Experiment methods allow researchers to focus on valuing final changes as multidimensional features rather than discrete changes. Choosing between options encourages respondents to examine their preferences in detail related to different management programs. The Choice Experiment test approach consists of several steps, which include designing the Choice Experiment test, determining the sample size and method of data collection, estimation process, and modeling the Choice Experiment test. Designing a Choice Experiment test consists of five important steps which are defining attributes, determining the relevant levels, conducting an experimental design, constructing Choice sets, and measuring preferences. After determining the criteria affecting the prioritization of renewable energy, liketechnical, environmental, economic, social, and political criteria, in order to investigate the willingness to Pay of Sari farmers, a test questionnaire was designed. The criteria obtained from the review of prioritization of renewable energy were considered as the attributes of the Choice Experiment and the price attribute was added to the above criteria. A total of six technical, economic, social, political, environmental, and price attributes were considered to investigate farmers' willingness to pay. In the review of the studies and the current situation, the levels of each of the attributes were determined. To determine the levels of price attribute, these points were considered; the price of agricultural electricity per kilowatt-hour is 383 Rials, which was approximately 400 Rials for the current situation.Results and Discussion: To investigate the farmers' preferences for using solar energy, 98 questionnaires of farmers in Sari were completed in September 2019. Each questionnaire included 8 choice set cards and each card included three options, based on which, the number of observations in Sari is equal to 2352 observations. The purpose of this study is to investigate the preferences of farmers in Sari for the use of solar energy. For this purpose, the Multinomial logit, the Random parameter logit, the latent class, and the Random parameter logit latent class are used. Based on the results of the Multinomial logit method, environmental and price attributes at the level of one percent and economic attribute at the level of five percent are statistically significant, but political, social, and technical attributes are not statistically significant. The Alternative-specific Constants (ASC) in the first and second options are not statistically significant. Based on the results of the Random Parameter Logit estimation method, environmental, economic and price attributes are statistically significant at the level of one percent. Technical, political, and social attributes are not statistically significant, which shows that farmers do not make a significant difference between these two attributes. The Alternative-specific Constants (ASC) are significant in the first option at the level of five percent and the second option at the level of one percent. The results of latent class estimation show that in the first class, environmental, economic, political, social, and price attributes are statistically significant at the level of one percent and technical attribute at the level of ten percent. The Alternative-specific Constants (ASC) are statistically significant at the level of one percent in the first class. In the second class, technical attribute at the level of five percent and environmental attribute at the level of ten percent are significant, besides other attributes in the second class are not statistically significant. The most sensitive class is the first class and farmers of the second class are considered the base class. The results obtained from the Bayesian and Akaike criteria of different classes showed that the two classes have the lowest values of BIC and AIC criteria and the class is appropriate. After determining the appropriate class, the model was estimated. The results of model estimation were calculated by the Latent Class Random Parameter logit method. In the first class, environmental attributes and price are significant at the level of one percent and economical attributes at the level of five percent. Also, the Alternative-specific Constants (ASC) is significant at the level of one percent, but, in the second class, the attributes are not statistically significant. Technical, environmental, economic, political, social, and price attributes, as well as the option of status quo or the Alternative-specific Constants (ASC) in the second class, do not affect farmers' utility due to the lack of statistical significance.Conclusion: A comparison of the results obtained from the four methods shows that the highest value of the estimated coefficient for environmental attributes was in the latent class method and the lowest value was in the multinomial logit method; Comparison of fitted methods shows that the highest Log-likelihood is related to the latent class random parameter logit method and the lowest value is related to the multinomial logit method. Accordingly, the highest value of Akaike and Bayesian criteria is related to the multinomial logit method and the lowest value is related to the latent class random parameter logit method which is better than other methods according to the good fit criterion.

In recent years, repeated droughts have had negative impacts on agricultural products. Farmers can reduce the effects of droughts by using adaptive strategies. The aim of this study was to investigate farmers' strategies in response to drought consequences and to examine the factors affecting the use of these strategies. In terms of purpose, the study is an applied one, and the method is descriptive-analytical. The data gathering tool was a questionnaire and interviews. The statistical population of the research consisted of the rural households in Roshtkhar County (N = 13716). Using the Cochran formula, 373 farmers were selected as the sample. For data analysis, the unlimited exploratory uncertainty test and the binary logistic model (LM-Newton-Marcard-Raphson method) were used. The results showed that decreased water resources (0.882), reduced crop area (0.735) and increased living expenses (0.698) were the most important consequences of drought. Drought-tolerant plants such as saffron, irrigation, and non-agricultural jobs were the most important strategies adopted by the farmers in response to drought consequences. Variables such as age, sex, indigenous knowledge, labor force, income, farmers’ experience, and farm size were significantly associated with the application of strategies. The results of the research can be used for more adaptation of farmers to drought consequences in the villages of the county.

Introduction: Particulate matter refers to the combination of atmospheric pollutants that a portion of this particulate is bioaerosol. The aim of this study was the evaluation of bacteria, fungi and biomass in particulate matter in ambient air of Khorramabad during summer and autumn 2012. Materials and Methods: This study was a cross sectional study that conducted in Khorramabad city during summer and fall 2012. Sampling has been done via high-volume sampler. The special cultures were used for cultivation and determination of fungal and Heterotrophic Plate Count (HPC (and Bradford method were used to determine bacteria and protein as biomass indicator, respectively. Relationship between these variables with metrological parameters was evaluated too. Results: The highest PM10 in July (257.18 µg/m3) and lowest in September (92.45 µg/m3) had been recorded. The highest amount of bacteria and fungi were measured as monthly in November (605 No/m3) and December (120 No/m3), respectively. The highest of protein concentration was measured in August, September and December (27-30 µg/m3). With the increase in PM10, biomass concentration in the air showed a meaningful increase. Conclusion: Biomass concentration in the air increased with increasing PM10 but it had no significant effect on the concentration of bacteria and fungi in the air. Meteorological factors such as temperature, humidity, wind speed, solar radiation and the amount of exposure time had a significant impact on bioaerosol concentrations in the air.

Introduction: The rapid population growth in Iran and the corresponding increases in water demands, including drinking water, industry, agriculture and urban development and existing constraints necessitate optimal scheduling necessity in use of this crucial source. Furthermore, the phenomenon of climate change as a major challenge for humanity can be considered in future periods. Climate change is caused by human activity have also been identified as significant causes of recent climate change, referred to as "global warming". Climate change indicates an unusual change in the Earth's atmosphere and climate consequences of the different parts of planet Earth. Climate change may refer to a change in average weather conditions, or in the time variation of weather around longer-term average conditions. A Warmer climate exacerbates the hydrologic cycle, altering precipitation, magnitude and timing of runoff. The purpose of this study was to evaluate the effect of climate change on water consumption and demand in Bar river basin of Neighbor. Climate change affects precipitation and temperature patterns and hence, may alter on water requirements and demand at three sectors; agriculture, industry and urban water. Materials and Methods: At present, Global coupled atmosphere-ocean general circulation models (AOGCMs) are the most frequently used models for projection of different climatic change scenarios. AOGCMs models represent the pinnacle of complexity in climate models and internalize as many processes as possible. These models are based on physical laws that are provided by mathematical relations. AOGCMs models used for climate studies and climate forecast are run at coarse spatial resolution and are unable to resolve important sub-grid scale features such as clouds and topography. As a result AOGCMs output cannot be used for local impact studies. Therefore, downscaling methods were developed to obtain local-scale weather and climate, particularly at the surface level, from regional-scale atmospheric variables that are provided by AOGCMs. Four different downscaling methods exist: regression methods, weather pattern-based approaches, stochastic weather generators, which are all statistical downscaling methods, and limited-area modeling. For this research, HadCM3 and statistical downscaling model (SDSM), precipitation and temperature variations were simulated under A2 scenario. Then the impacts of these variations on Bar River discharge were analyzed, i.e. water resources at three sectors of agriculture, industrial and potable water under climate change during 2011-2040 using WEAP. Results at first part of simulation showed that temperature is increasing and precipitation is decreasing resulted in decreasing of Bar discharge. According to the decreasing on Bar discharge, water allocation was simulated under these conditions of agricultural and industrial development and increasing of population with WEAP. Simulation showed that watershed will face increasing of water demand for all three sectors; agriculture, industry and drinking water, so the highest water shortage would be in agricultural demand and then industry and drinking water respectively. IWRM is the basic managerial need to rest the demands especially for drought periods. Current allocation process is based on steady state conditions while allocation pattern would be done under climate change conditions so we need to be reinvestigat the last allocations for all three sectors. Another challenge for this watershed refers to the gardens and steel factory of Khorasan that they need to use new technologies for reduction of their water needs. Results Discussion: In this study, the outputs of General Circulation Models (HadCM3) and statistical downscaling model (SDSM) have been used to investigate the changes of rainfall and temperature under A2 scenario in Bar river basin of Neishaboor and assess the impacts of this changes on the Bar river’s discharge. Finally, using WEAP model under climate change conditions for the period of 2011-2040, the status of basin water resources was evaluated for the three sectors (agricultural, domestic and industrial). The results indicated increased temperature in the Arie station amounting to 16 percent and rainfall reduction in the Arie and Taghan stations amounting to 3.9 and 8.75 percent respectively. Under these conditions, according to the increasing water demands of agricultural and industrial sectors in the future, there will be a shortage of water supply resources in the region. So the agricultural sector with 12 percent will have the highest percentage of water shortage and water scarcity and of the industrial sector will be 2%. However, the drinking water or domestic demand will not face a shortage of supplies. Conclusion: Therefore given that the most part of agriculture sector’s share of basin is allocated to orchards and on the other hand the most shortages are related to agriculture, then while creating an integrated management of water resources, development and use of modern methods of irrigation during the period of 2011 - 2040 would seem to be necessary.

Due to the growing demand for electricity it is inevitable to have new power plants. Given the large share of electricity production in thermal power plants, construction of gas burning power plants have particular importance. Because of the high construction cost of the new plants, it is advisable to start with improvement of the efficiency in the existing and plates. One important index in electricity industry, is the efficiency of power plants which concerns all the powerplants in the world. In order to increase it as much as possible, and reduce the loss of energy to a reasonable degree, this paper examined the performance impact of plant life and obtained 0.07 of electricity coefficient for the variable. We also examined other factors related to efficiency. Among the factors influencing efficiency of this type of power plants, the cost of fuel and average plant life and volume of production of electricity were also important. In this study a panel data from 34 gasplants in Iran was used for a period of 4 years (2008-2011).

Introduction: Forecasting the inflow to the reservoir is important issues due to the limited water resources and the importance of optimal utilization of reservoirs to meet the need for drinking, industry and agriculture in future time periods. In the meantime, ignoring the effects of climate change on meteorological and hydrological parameters and water resources in long-term planning of water resources cause inaccuracy. It is essential to assess the impact of climate change on reservoir operation in arid regions. In this research, climate change impact on hydrological and meteorological variables of the Shahcheragh dam basin, in Semnan Province, was studied using an integrated model of climate change assessment. Materials and Methods: The case study area of this study was located in Damghan Township, Semnan Province, Iran. It is an arid zone. The case study area is a part of the Iran Central Desert. The basin is in 12 km north of the Damghan City and between 53° E to 54° 30’ E longitude and 36° N to 36° 30’ N latitude. The area of the basin is 1,373 km2 with average annual inflow around 17.9 MCM. Total actual evaporation and average annual rainfall are 1,986 mm and 137 mm, respectively. This case study is chosen to test proposed framework for assessment of climate change impact hydrological and meteorological variables of the basin. In the proposed model, LARS-WG and ANN sub-models (7 sub models with a combination of different inputs such as temperature, precipitation and also solar radiation) were used for downscaling daily outputs of CGCM3 model under 3 emission scenarios, A2, B1 and A1B and reservoir inflow simulation, respectively. LARS-WG was tested in 99% confidence level before using it as downscaling model and feed-forward neural network was used as raifall-runoff model. Moreover, the base period data (BPD), 1990-2008, were used for calibration. Finally, reservoir inflow was simulated for future period data (FPD) of 2015-2044 and compared to BPD. The best ANN sub-model has minimum Mean Absolute Relative Error (MARE) index (0.27 in test phases) and maximum correlation coefficient (ρ) (0.82 in test phases). Results and Discussion: The tested climate change scenarios revealed that climate change has more impact on rainfall and temperature than solar radiation. The utmost growth of monthly rainfall occurred in May under all the three tested climate change scenarios. But, rainfall under A1B scenario had the maximum growth (52%) whereas the most decrease occurred (–21.5%) during January under the A2 climate change scenario. Rainfall dropped over the period of June to October under the three tested climate change scenarios. Furthermore, in all three scenarios, the maximum temperature increased about 2.2 to 2.6°C in May but the lowest increase of temperature occurred in January under A2 and B1 scenarios as 0.3 and 0.5°C, respectively. The maximum temperature usually increased in all months compared to the baseline period. Minimum and maximum temperatures enlarged likewise in all months, with 2.05°C in September under A2 climate change scenario. Conversely, solar radiation change was comparatively low and the most decreases occurred in February under A1B and A2 climate change scenarios as –4.2% and –4.3% , respectively, and in August under the B1 scenario as –4.2%. The greatest increase of solar radiation occurs in April, November, and March by 3.1%, 3.2%, and 4.9% for A1B, A2, and B1 scenarios, respectively. The impact of climate change on rainfall and temperature can origin changes on reservoir inflow and need new strategies to adapt reservoir operation for change inflows. Therefore, first, reservoir inflow in future period (after climate change impact) should be anticipated for the adaptation of the reservoir. A Feed-Forward (FF) Multilayer-Perceptron (MLP) Artificial Neural Network (ANN) model was nominated for the seven tested ANN models based on minimization of error function. The selected model had 12 neurons in the hidden layer, and two delays. The comparison of forecasted flow hydrograph by selecting an ANN model and observed one proved that forecasted flow hydrograph can follow observed one closely. By comparison with the IHACRES model, this model displayed a 54% and 46% lower error functions for validation data. The selected model was used to forecast flow for the climate change scenarios of the future period. Conclusions: The results show a reduction of monthly flow in most months and annual flow in all studied scenarios. The following main points can be concluded: • By climate change, flow growths in dry years and it declines in wet and normal years. • The studied climate change scenarios showed that climate change has more impact on rainfall and temperature than solar radiation.

Introduction: Water when harvested is commonly stored in dams, but approximately up to half of it may be lost due to evaporation leading to a huge waste of our resources. Estimating evaporation from lakes and reservoirs is not a simple task as there are a number of factors that can affect the evaporation rate, notably the climate and physiography of the water body and its surroundings. Several methods are currently used to predict evaporation from meteorological data in open water reservoirs. Based on the accuracy and simplicity of the application, each of these methods has advantages and disadvantages. Although evaporation pan method is well known to have significant uncertainties both in magnitude and timing, it is extensively used in Iran because of its simplicity. Evaporation pan provides a measurement of the combined effect of temperature, humidity, wind speed and solar radiation on the evaporation. However, they may not be adequate for the reservoir operations/development and water accounting strategies for managing drinking water in arid and semi-arid conditions which require accurate evaporation estimates. However, there has not been a consensus on which methods were better to employ due to the lack of important long-term measured data such as temperature profile, radiation and heat fluxes in most lakes and reservoirs in Iran. Consequently, we initiated this research to find the best cost−effective evaporation method with possibly fewer data requirements in our study area, i.e. the Doosti dam reservoir which is located in a semi-arid region of Iran. Materials and Methods: Our study site was the Doosti dam reservoir located between Iran and Turkmenistan borders, which was constructed by the Ministry of Water and Land Reclamation of the Republic of Turkmenistan and the Khorasan Razavi Regional Water Board of the Islamic Republic of Iran. Meteorological data including maximum and minimum air temperature and evaporation from class A pan were acquired from the Doosti Dam weather station. Relative humidity, wind speed, atmospheric pressure and precipitation were acquired from the Pol−Khatoon weather station. Dew point temperature and sunshine data were collected from the Sarakhs weather station. Lake area was estimated from hypsometric curve in relation to lake level data. Temperature measurements were often performed in 16−day periods or biweekly from September 2011 to September 2012. Temperature profile of the lake (required for lake evaporation estimation) was measured at different points of the reservoir using a portable multi−meter. The eighteen existing methods were compared and ranked based on Bowen ratio energy balance method (BREB). Results and Discussion: The estimated annual evaporation values by all of the applied methods in this study, ranged from 21 to 113mcm (million cubic meters). BREB annual evaporation obtained value was equal to 69.86mcm and evaporation rate averaged 5.47mm d-1 during the study period. According to the results, there is a relatively large difference between the obtained evaporation values from the adopted methods. The sensitivity analysis of evaporation methods for some input parameters indicated that the Hamon method (Eq. 16) was the most sensitive to the input parameters followed by the Brutsaert−Stricker and BREB, and radiation−temperature methods (Makkink, Jensen−Haise and Stephen−Stewart) had the least sensitivity to input data. Besides, the air temperature, solar radiation (sunshine data), water surface temperature and wind speed data had the most effect on lake evaporation estimations, respectively. Finally, all evaporation estimation methods in this study have been ranked based on RMSD values. On a daily basis, the Jensen−Haise and the Makkink (solar radiation, temperature group), Penman (Combination group) and Hamon (temperature, day length group) methods had a relatively reasonable performance. As the results on a monthly scale, the Jensen−Haise and Makkink produced the most accurate evaporation estimations even by the limited measurements of the input data. Conclusion: This study was carried out with the objective of estimating evaporation from the Doosti dam reservoir, and comparison and evaluation of conventional method to find the most accurate method(s) for limited data conditions. These examinations recognized the Jensen−Haise, Makkink, Hamon (Eq. 17), Penman and deBruin methods as the most consistent methods with the monthly rate of BREB evaporation estimates. The results showed that radiation−temperature methods (Jensen−Haise and Makkink) have appropriate accuracy especially on a monthly basis. Also deBruin, Penman (combination group), Hamon and Papadakis (temperature group) methods produced relatively accurate results. The results revealed that it is necessary to calibrate and adjust some evaporation estimation methods for the Doosti dam reservoir. According to the required input data, sensitivity and accuracy of these methods, it can be concluded that Jensen−Haise and Makkink were the most appropriate methods for estimating the lake evaporation in this region especially when measured data were not available.

Background and aims: Fossil fuels Emission and their limited resources make to use renewable energy with more sustainable energy sources and less minimal environmental impacts. One of the most appropriate renewable energies considered lots of advantages including being renewable and environmentally friendly and containing social and economical interests, is Biomass. “Biomass” means a power source that is comprised of, but not limited to, combustible residues or gases from forest products manufacturing, waste, byproducts, or products from agricultural and orchard crops, waste or co-products products from livestock and poultry operations, waste or byproducts from and food processing, urban wood waste, municipal solid waste, municipal liquid waste treatment operations, and landfill gas. Due to the wide availability of biomass worldwide, mainly because it can be obtained as a by-product of many industrial and agricultural processes, biomass represents a growing renewable energy source with high growth potential. Biomass helps reduce the amount of GHG that give more impact to global warming and climate change. The biomass emissions level is far smaller compared to fossil fuels. The basic difference between biomass and fossil fuels when it comes to amount of carbon emissions is: all the CO2 which has been absorbed by plant for its growth is going back in the atmosphere during its burning for the production of biomass energy. While the CO2 produced from fossil fuels is going to atmosphere where it increases greenhouse effect. Another great advantage of biomass energy is that it is an indigenous fuel. The fuels from biomass materials can be produced locally and no high technology is required. Producing fuel from biomass materials reduces the dependence of a country on foreign resources for their fuel requirements. Moreover, since this indigenous fuel is labor intensive, it can contribute to the generation of new jobs, particularly in rural and farming communities. The number of employed workers required is 3-6 times greater than the fossil energy production in the associated processes. This study was aimed to identification and green grading of environmental management in that’s jobs. Some other socio-economic benefits can be counted such as slowing down the migration from the rural areas to cities, decreasing the issues associated with rapid urbanization, and developing a biodiesel production industry. Among its great benefits is the forest use of the territory, which would also serve to clean the forest and thus prevent forest fires, and the ability to generate jobs. Biomass generates continuous employment such as the extraction of raw materials from the countryside and the bush. This study was aimed to identification and green grading of environmental management in that’s jobs. The research questions are: 1. What are green job indicators? and 2. has renewable energy biomass business indicators of green jobs? Methods: This study was qualitative – quantitative, first according to the grounded theory qualitative method semi-deep interviewed with 50 environmental experts in the Environmental Protection Agency, the municipality, faculty members of the universities, the natural resources and watershed management, agriculture ministry and NGOs active in the environment conducted a with purposeful sampling (snowball). Regarding qualitative data validation were used constant data comparison, reviewing the observers and handwriting by participants and use of foreign and expert researchers familiar with qualitative research as an observer. Then, data was analyzed using the grounded theory of open, axial and selective coding analyzed in MAXQDA software. Once coding categories emerge, the next step is to link them together in theoretical models around a central category that hold everything together. In order to explain the grounded theory, green jobs are considered as the central variable, and the main line of research is defined using reminders and diagrams around it, and finally the green indicators derived from it are developed. Based on them, researcher-made questionnaire was designed in a combination, closed response with 5-rate likert scale. In order to determine the validity of the questionnaire, the content validity was used with the lawshe model and with reviewing previous studies was determined, the scope of the questionnaire in greenness of the job, and the reliability of the questionnaire was obtained using Cronbachchr('39')s alpha coefficient for internal consistency. Cronbachchr('39')s alpha value for each research question was more than 0.7, the reliability of the questionnaire was approved. Also, the Cronbachchr('39')s alpha coefficient of the questionnaire was 0.890. In order to estimate the repeatability, the retest method and the ICC index were used that index was 0.996 (p <0.001), indicating its high repeatability. For estimating the results of greenness and its degree in the jobs of renewable energy biomass, were used statistical analysis of Kolmogrov-Smirnov test, single-sample t-test and Friedman test in SPSS software. Result: Findings of the qualitative research on the structure of green job identification and prioritization were discussed in six categories including establishment in accordance with the legal and technological infrastructure of the green job as context, green job as a phenomenon, environmental pollution elimination and the health risks reduction of the community as causal conditions, green management as operational strategies, environmental empowerment of jobs as an intermediary conditions and economic and environmental benefits as a consequence. The results of quantitative to showed that jobs studied are considered green jobs and their green grading are as follows: 1. Maintenance (mean=5/61), 2. System Design (mean=4/83), 3. Training (mean=4/22), 4. Quality Monitoring and Quality (mean=4/03), 5. Collection (mean=3/64), 6. Manufacturer (mean=3/61) and 7. Worker and System Administrator (mean=2/06). According to the results, components of green jobs are defined including: (1. explaining Green Jobs, Productivity of Occupations, 2. environmental Protection and Health, 3. Green potentials and incentives, 4. environmental Standards and Indices of Health and Green Management, 5. environmental and health challenges and solving energy crisis with the help of green jobs, 6. environmental education and green culture, 7.environmental empowerment through a variety of environmental and health education, informing and accompanying NGOs, 8. economic-ecological profitability and the optimistic approach to economic interests (green economy) and impact of economic issues, profitability, financial support, market regulation, and return on investment in the process of greening and green expanding businesses). Results show that green indices of occupations are 1- environmental and health of profile occupational, 2- strengths and weaknesses, threats and opportunities green jobs, 3- green supply chain management of businesses, 4- impact of green jobs on sustainable development and community health, 5- effect of environmental education on the green performance of occupations, the impact of environmental advertising on green performance and 6- reduce employee costs and increase business profits through environmental management. These green jobs literature extols the virtues of generating energy using “wood waste and other byproducts, including agricultural byproducts, ethanol, paper pellets, used railroad ties, sludge wood, solid byproducts, and old utility poles. Several waste products are also used in biomass, including landfill gas, digester gas, municipal solid waste, and methane. Conclusion: The green features of the biomass business are included solving the problem of fossil fuels, caused by fossil energy and renewable energy sources. identification and green grading jobs diversifying energy sources, sustainable development, securing energy, removing environmental and health problems would help to managers and policy makers for identifying and providing executive solutions and identifying multifaceted priorities for green management. Despite the high potential of bio-economy in renewable energy (biomass) and high amounts of raw materials in the agricultural waste and sewage has not been fully realized. To achieve of developing a competitive economy, low-carbon resources with efficient resources, global economic markets have shifted strategy towards renewable energies, so as to create green jobs in order to reduce environmental problems (waste and climate change). For performance of macroeconomic policy in notification Supreme Leader on the restructuring of the countrychr('39')s economic structure has proposed policies to change reducing dependencies on fossil fuels and external resources towards the creation and development of green jobs in the field of renewable energy, especially biomass, because there are a lot of raw materials in the country, especially in the villages and without necessary to high technologies. Biomass development increase energy efficiency, the use of renewable energy resources and the creation of a favourable environment for investment in energy efficiency measures and the generation of ‘green’ jobs. The rural development prospects for green job growth are mixed. Rural areas contain biomass feedstocks which will be increasingly relied upon to offset fossil fuel dependencies. The distribution of those feedstocks, however, is not uniform across rural areas. Furthermore, the technologies to convert those feedstocks into fuels and other uses are yet to be demonstrated at commercially successful scales. Both policy development and research activities should be focused on the efficient utilization of rural natural resources, human capital, and rural infrastructure in achieving national green policies. The green economy appears to be fertile ground for unbiased, academic research to examine some of the regional consequences of green jobs growth and green jobs policies, to include an examination of rural opportunities, but going well beyond that dimension to include the integration of statewide and multi-state regional development opportunities as well as consequences. This study was not about raw materials (waste and sewage) to produce renewable energy biomass, and it is possible that this section may also be effective in the creation and development of green jobs, then there may be restrictions on the generalized findings, interpretations, and attributes of the causation of variables. Therefore, it is suggested that future research into this part of the process of producing renewable energy biomass should be considered.

Introduction Among the economical sectors of the country, residential sector is the largest final consumer of energy and unlike the other sectors, its energy intensity is upward. In this regard, targeted subsidies law is a basic measure by the ninth government which began by the president’s command since 2010 despite the opposition of a number of economists and MPs with the way of its implementation that was a price reform (rising) plan to energy carriers with a focus to reduce energy consumption in all consumer sectors, especially residential sector. The residential sector consists of different groups regarding economic, social and cultural features and it seems that identical changes of prices of gas and electricity for all these groups as result of targeted subsidies law implementation have different effects on the level of energy consumption in these groups. Therefore, after nearly three years of implementation of the law and on the verge of implementation of the second phase, the study is to investigate the effects of social (Social-Economical Status) and cultural (environmental culture) features on the level of change in gas and electricity consumption of households in Esfahan city after the implementation of targeted subsidies law. Materials & Methods Regarding the purpose, the study is practical and regarding the nature and methods, it is descriptive-analysis and casual-comparative (post-event). The data for investigating the research hypotheses are collected by field method. The study population of the research is all the households living in all fourteen districts of Esfahan municipality and 145 households were selected from the 492767 households living in Esfahan city in 2011 by the use of Cochran formula (confidence level of 90 percent) and the data were collected by referring to them using simple random sampling. In order to analyze the effects of the variables, namely Social-Economical Status and environmental culture of the households, on the level of change in gas and electricity consumption after the implementation of targeted subsidies law, we used multivariate regression model of binomial logistics. SPSS software was also used to do the calculation and achieving the results. Discussion of Results & Conclusions The results of the research showed that: 1- Social-Economical Status of Esfahan households did not have a significant effect on reducing the consumption of gas and electricity after the implementation of targeted subsidies law. 2- The effects of environmental culture of Esfahan households on the possibility of gas and electricity energy saving on both levels (low and average) have been negative. In order to justify the lack of any significant relationship between Social-Economical Status Esfahan households and reducing gas and electricity consumption, the reasons are presented as follows in two divisions of sociological and economic fields: A) Sociological analysis: For many years, Social-Economical Status has been a powerful and significant variable in the area of social sciences which is used to explain a host of social attitudes and behaviors. But the lack of relationship between this variable and dependent variables of the research, despite the research hypothesis on the relationship between these two variables, is theoretically very important for the society that is studied; Therefore, it is likely that the views of some sociologists such as Veblen, Weber and Bourdieu who believe in social class life and also believe that socio-economic class factor affects the formation of lifestyle, have been fading away and lack explanatory ability. On the other hand, the approach of intellectuals such as Anthony Giddens, Mike Featherstone and Ulrich Beck is able to analyze the case in a better way. According to the views of these sociologists, social classes do not determine the selective consumption patterns of people so that it is not possible to separate the lifestyles according to the social classes and the lifestyles break boundaries of social class differentiations. In fact, lifestyle is neither a social class concept nor a tool for distinction, but it is offered as a new concept against the social class. From such a viewpoint, in modern societies similar consumption behaviors are observed among people from different social classes which show the class integration of lifestyles. In other words, we deal with a lifestyle which does not particularly belong to a group or a class, but it is only significant in the cultural changes of modernity and the growth of consumerism culture. B) Economic Analysis: According to economic studies on this subject, justifications for the lack of relationship can be outlined as follows: 1- Inelasticity of energy demand (consumption) for residential sector against the price changes - even in long term - and the necessity of energy commodity in the households carts. 2- Limitations to find alternatives for energy consumption such as gas and electricity for the households: the reason is the different technologies for using gas, electricity and other types of energy in household appliances. Even if the alternatives are technically possible, it is not economical for the consumers to change their consumption patterns and their energy appliances for slight fluctuations in energy prices (especially knowing that the fluctuations are very slight on the basis of real prices). 3- Since gas and electricity are necessary commodities for residential sector, this sector at least has to use them for heat, light, cooking, etc. In most cases, reducing the consumption of these two energy carriers leads to nothing but lowering the level of well-being and as a result causing numerous social, cultural and sanitary abnormalities and increasing discontent in the society. Therefore, it is natural that energy consumption in household sector is not a function of its price. 4- Energy consumption in residential sector is a function of its previous patterns which means that the consumers of this sector act according to their consumption habits. 5- Regarding the electricity, it can be said that refrigerators, freezers, coolers and TV sets share the greater part of electricity consumption in households which includes 60% of the total energy consumption by the households. It seems that despite rising electricity price after implementation of the law, the household consumer still uses the same electrical appliances; because most families - especially in inflation condition after implementation of the law - can not afford to buy energy-saving modern appliances. 6- For wealthy households who can afford to buy energy-saving appliances it is not economical to change their consumption patterns and appliances for the slight fluctuations in the price of gas and electricity (especially in inflation condition after implementation of the law). 7- Although at the beginning of targeted subsidies law implementation, the government attempted to increase the nominal prices of gas and electricity of the residential sector, only after two months the real price of electricity and after four months the real price of gas have been declining due to fixing the nominal prices of these two energy carriers after the beginning of the plan and ignoring the consumer price index while pricing these two energy carriers. In order to explain the negative effect of households environmental culture on energy consumption reduction it can be argued that households with higher cultures before the implementation of targeted subsidies law had more thrifty behaviors comparing to households from lower cultures; therefore, there is less possibility for them to save energy under the law implementation. It seems that price changing of gas and electricity is not an appropriate leverage to reform energy consumption pattern (gas and electricity) of residential sector; but energy saving in this sector by logical use of energy through creating the consumption culture alongside price changing of energy carriers can have a significant effect on consumption control in this section.

Introduction: Identifying the effect of energy consumption, economic growth and foreign trade on CO2 emissions have been studied at both national and international levels. However, there have been very few researches on the effect of financial and banking development on the CO2 emissions, especially in Iran. So, this study aimed to cover this research gap. Methods: This study was a time-series analyses over the period of 1971-2011. In order to investigate about existence of a long-run co-integration relationship between CO2 emissions and banking development indicators in Iran, long-run coefficients were estimated by Autoregressive Distributed Lag (ARDL) and Dynamic Ordinary Least Squares (DOLS) approaches. Moreover, to carry out the econometric tests Microfit (5.0) and Eviews (9.0) software were used. Results: Findings showed that the ratio of domestic credit to private sector by banks to GDP (Banking Development Indicator) reduces CO2 emissions in Iran. In addition, results confirm with theories and other empirical studies showed that energy consumption has positive and significant effect on CO2 emissions in long-run. Conclusion: The government can help to improve environment quality by establishing a strong policy making on credit to firms by banking system. Because in this framework firms to receive credit from banking system are required codified programs to reduce negative outcomes of energy consumption and this lead to a less CO2 emissions in long-run.