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The transition to renewable energy is key for sustainable development. Therefore, one of the sustainable development goals (SDG) of United Nations (UN) is to shift towards clean energy. However, in many resource-rich countries several factors can stand as barriers towards the transition process. In this regard, this paper examines the influence of higher oil price, CO 2 emissions, and income on renewable energy consumption in Iran from 1980 to 2019, employing General to Specific (Gets) modeling approach. Estimation results indicated that oil price and CO 2 emissions both have statistically significant and negative impact on renewable energy consumption. The negative influence of higher oil prices on renewable energy consumption may be interpreted as sign of satisfaction coming from higher oil prices, which postpones the transition from traditional energy sources to renewable for Iran. Furthermore, we concluded that income does not have a statistically significant influence on renewable energy use. The paper discusses alternative policies to promote renewable energy consumption. • The effect of higher oil price on renewable energy consumption was studied. • A novel version of General to Specific (Gets) modeling approach was employed. • We found significant, negative impact of oil price on renewable energy use in Iran. • The paper discusses alternative policies for Iran to promote renewable energy use. [ABSTRACT FROM AUTHOR]

This paper investigates the sustainability of Tabriz City focusing on its decarbonization. Statistical, quantitative, and comparative research methods are used to analyze the total energy consumed, conversion of primary energy, final exergy, and losses analysis according to the renewable and carbon-based energies. Then, the renewable resource potentials of the city are simulated using Grasshopper plug-in-Rhino simulator, THERM, PVSyst photovoltaic software, and ArcMap. In terms of the socio-economic assessment, non-oil Per Capita GDP, emissions, and energy intensities are analyzed concerning the B2DS scenario by 2050. The per capita GDP of the city is 71% of the country's average value. Tabriz's real GDP growth averaged −1.11% per year, primary energy demand increased by an average of 6.1%, CO 2 emissions from energy use grew by an average of 6% annually and the emission intensity of the economy increased by a total of 52.02%, in the period from 2011 to 2019. Finally, it is shown that the city consumes 58050 GWh/year of different carbon-based resources that only produced 20110 GWh/year of useful work with 5.63 MT CO 2 emissions, while the same work could locally be supplied by 30000 GWh/year RE with a minimum rate of 0.18 MT CO 2 emissions. The city Landfill receives 1000 tons/day of MSW, but two-thirds of this amount can be recycled. Regarding different sectors, buildings produce half of the CO 2. The cement industry with dual pollutants (17%) is the most polluting factory. Carbon-based electricity (66%) is the most polluting form of energy. In terms of carbon sequestration requirements with trees, shifting from fossil fuels toward green energies, EE, and recycling MSW can plunge required trees from 81.9 to 1.16 million trees. This paper highlights the importance of electrification of transportation based on RE, energy performance of buildings, and all sectors. • Large city decarbonization strategies • Application of RE according to geographic and climatic factors. • Electrification of sectors based on RE locally. • MSW recycling and sequestration by trees for decarbonization regarding the LULC and NDVI analysis. • Conversion and storage efficiencies of carbon-based fuels vs RE. [ABSTRACT FROM AUTHOR]

Although the socio-economic determinants of terrorism are conducted by many researchers using different samples and time spans, the impact of renewable energy consumption on terrorism has been ignored for a long time. To bridge the gap, this paper aims to investigate the impact of renewable energy consumption on terrorism regarding economic growth, non-renewable energy consumption, and income inequality over the period straddling 1990 and 2019 for a panel of the USA, China, India, Iran, Germany, and Russia. We employ the CUP-FM and CUP-BC estimators to reveal the long-run relationship between variables. The empirical findings suggest that renewable energy consumption has a negative impact on terrorism. A 1% increase in renewable energy consumption decreases terrorism by 0.315% and 0.631%, according to the CUP-FM and CUP-BC estimators, respectively. Economic growth also has a negative impact on terrorism, whereas non-renewable energy consumption and income inequality positively affect terrorism. Our empirical findings highlighted that renewable energy consumption and economic growth are crucial for combating terrorism in these countries. Therefore, these countries need to improve comprehensive policies in terms of renewable energy consumption and simultaneously decrease non-renewable energy consumption and income inequality. • Renewable energy consumption helps to lower the terrorism index. • Inequality of income expedites the rise of terrorism. • Terrorism is exacerbated as a result of fossil fuel consumption. [ABSTRACT FROM AUTHOR]

In recent years, permanent outages and lack of access to electricity have been significant problems in most cities of Iran. The increasing growth of fossil fuel consumption made it necessary to change the design of buildings. Designing a net-zero energy building (with natural ventilation and renewable energy systems) is a solution for reducing fossil fuels. In this paper, dynamic energy modeling of the building for the smart operation of the trapezoidal Trombe wall and underground air ducts is performed. In the first step, the Trombe Zones are considered for heating. Then the combination of the Trombe zones with underground air ducts for cooling is simulated. Then the system combination with a solar hot water system to supply hot water energy is evaluated. Finally, the economic analysis of the optimal hybrid system (with a photovoltaic system, wind turbine, battery, and inverter) for supplying the electricity of the building equipped with both passive energy strategies was evaluated by Homer software. The results show that by integrating the Trombe wall, the heating load is reduced by 44 %, and by integrating a coupled geothermal cooling system with the air duct and the Trombe wall, the cooling load is reduced by 39%. Also, the net present cost over the 25-year life of the optimized renewable system is reduced by about 12.5% due to both passive strategies. The average daily electricity energy demand of the base building is equal to 86.37 kWh and for the passive building, it is equal to 67.49 kWh. [ABSTRACT FROM AUTHOR]

This paper tries to simulate and discuss the possible solutions that improve the economic and technical performances of a battery-less renewable energy-powered BWRO system according to the real climate conditions. The systems are considered in two capacities (50 and 100 m3/day) and are powered using photovoltaic panels, wind turbines, or both. Four scenarios are considered to couple the RO unit with renewable energy (RE) sources: simple; elevated brackish water tank; variable frequency drive; and a combination of the latter two. First, the simple approach is optimized for the lowest levelized cost of water, and then the other three scenarios are analyzed based on the optimized results of the first scenario. Results indicate that the hybrid system can provide more water (13,500 and 24,900 m3/year). However, due to its homogenous nature and fewer fluctuations, the PV-based system shows better results from several viewpoints, such as specific energy consumption (1.08 kWh/m3 for both capacities) and unused energy ratio (0.32 and 0.28 for 50 and 100 m3/day devices). Also, the suggested scenarios improve the economic performance of the systems. With the modifications of scenario 4, the PV-based system enhances more and shows the lowest value of levelized cost of water (1.09 $/m3). • It is tried to present feasible methods for standalone BWRO units. • Technical and economic analyses are conducted for the systems. • The case study is a water-deprived region in Iran. • A system with an elevated BW tank with VFD-aided pump shows the best result. [ABSTRACT FROM AUTHOR]

• Application of solar energy according to land use/land cover map. • Electrification of transportation sectors based on local renewable energies. • Comparison of conversion and storage efficiencies of different energy forms in transportation. • Reducing transportation and urban environmental impacts. • Multi-criteria decision-making of sustainable transportation based on sustainable development pillars. The main aim of this paper is the decarbonization of the transportation sector in Tabriz City regarding sustainable development aims and beyond-2-degrees-scenario by focusing on electric vehicles, as well as on appropriate infrastructures. Quantitative and simulation research methods are used to analysis of total energy, exergy, and losses analysis according to different resources and vehicles. Next, the solar potential of the city is simulated using the Grasshopper plug-in-Rhino simulator and PVsyst software. A LULC analysis has been done using ArcMap 10.8. With renewable electrification, energy consumption will plunge from 15.5 TWh input-energy content of different carbon-based resources to 3.7 TWh with 0.17 MtonCO 2 /year instead of 2.13 MtonCO 2 /year emissions. In this paper, the overall system efficiency of electric vehicles is around 55% which is significantly higher than internal combustion engines. Fully electrification of the transportation systems based on renewable resources mitigates CO 2 emissions of internal combustion engines 15 times, besides reducing the emissionsa variety of harmful pollutants. In terms of multi-criteria decision-making, the technique for order of preference by similarity to the ideal solution was used to rank 50 popular vehicles according to interconnected sustainable development criteria. This paper highlights that conventional internal combustion engines can be replaced by electric vehicles by applying combination of appropriate taxes, tariffs, and incentives. [ABSTRACT FROM AUTHOR]

[Display omitted] • The effect of EC windows on energy consumption of high-rise buildings was assessed. • EC windows were combined with various glazing types, BIPV and BEMS. • The combination of EC windows with these tools reduced energy up to 35.57%. • Northern cities with more latitude values showed more energy saving potential. Traditional windows cannot adapt to external and internal environmental conditions. Smart windows are the next generation of windows, which can change their thermal and optical properties to control indoor environmental conditions. Electrochromic (EC) windows can control solar energy and provide visual comfort. These windows can be used with other tools such as various glazing types, building integrated photovoltaic (BIPV) and building energy management system (BEMS). This paper aims to evaluate the effect of EC windows, various glazing types, BIPVs and BEMS on energy consumption of high-rise office buildings. A model was created and several inputs were entered into the model. Then, annual simulations evaluated the effect of EC windows and other parameters on energy consumption of the building in four climate conditions of Iran. First, the effect of EC windows and various glazing types on energy consumption of the building were identified separately. Afterward, 12 different scenarios were defined to evaluate the effect of using both EC windows and optimal glazing type on energy consumption of the building. Then, BIPVs were combined with EC windows and photovoltachromic (PVC) windows were modeled using inputs of EC windows and BIPVs. In the end, BEMS was combined with PVC windows and had a positive effect on energy consumption of the building in all climate conditions. Finally, simulation results indicated that energy consumption of the building reduced up to 35.57% using EC windows and other tools. The difference between simulation and actual results is predicted to be at least 1.60% and maximum 6.22%. [ABSTRACT FROM AUTHOR]

• Numerical method is used to find proper cooling tube configuration for a PV/T panel. • The selected configuration was experimentally studied in the northern part of Iran. • The panel had an average electrical efficiency of 13.83% in the non-cooling state. • With the highest water flow rate, electrical efficiency would rise to 14.84%. Solar energy is greatly recommended as a source of renewable energy in wide range of in-house applications to large power plants. Photovoltaic (PV) panels utilized for absorbing solar energy have some limitations: low efficiency, large occupied space and high dependency on environmental conditions. Panel surface temperature is one of the main conditions affecting PV panels. High temperatures would lead to lower panel efficiency. Therefore, researchers have proposed hybrid PV/thermal systems where maintaining panel temperature for higher efficiency is participated in heat production. This benefit made it attractive for household consumption. In this paper, a numerical method is deployed to find an appropriate cooling tube configuration for a specified panel. The selected configuration was prepared for experimental studies on a hybrid PV/thermal system in the northern part of Iran. As this region receives lower irradiation compared to southern parts, People are not persuaded to use photovoltaic systems, so using hybrid systems can motivate them to use solar energy on a small scale. Results showed that serpentine tube configuration would lead to a 7.3% increase in electrical efficiency compared to the no-cooling state, and also thermal efficiency raised to 48.4%. Total efficiency reached 51.76% at the highest performance. Therefore this design provides a possible platform for increasing PV/T systems performance. [ABSTRACT FROM AUTHOR]

[Display omitted] • Energy-Water-Food security nexus of mung bean production in Iran is analyzed. • Non-renewable cumulative energy demand is estimated at 27.4 MJ/kg of beans. • Total water footprint is estimated at 1.55 m3/kg of beans. • On-farm production concentrates the largest environmental impacts (40% to 96%). • Cooking accumulates over 50% of the carbon footprint. Mung bean is a very important crop in Iran in both socio-economic and nutritional terms. However, although discussions on food and food security increasingly include sustainability issues, there are no precedents in academic literature that analyze in depth the nexus between energy, water use and food security in relation to this crop in Iran from an agri-food system approach. Therefore, our main objective is to assess the energy-water-food security (EWFs) nexus and the environmental impact of mung bean production in Iran from a "cradle to fork" approach using different nutritional units (1 kg of beans, 1 kg of proteins, and 1000 kcal) and load allocation criteria. In addition, an economic analysis of the farms is carried out. The results show that the on-farm production of mung beans is the phase where the largest environmental impacts are concentrated (between 40 % and 96 % of them, including those related to water and energy use), while cooking accounts for more than 50 % of the carbon footprint. The non-renewable cumulative energy demand (NR CED) and total water footprint (TWF) per kilogram of beans ("cradle to fork") is estimated at 27.4 MJ and 1.55 m3 and the farm Net Margin (NM) is estimated at 3,677 USD per ha. The paper discusses whether mung bean is a low-impact option for protein production, especially when compared to animal products and the importance of using different functional units and load allocation criteria to address the issue of EWFs and sustainability. In this regard, further research is needed to improve the environmental efficiency of bean production, which is critical for promoting sustainable diets in line with food security goals. [ABSTRACT FROM AUTHOR]

According to reports of Tavanir (power generation organization in Iran) in 2015, the share of wind power generation in Iran compared with other energy sources is less than 0.3%. In this paper, we suggest that despite the local potentials that exist in Iran, these capacities in wind power industry of Iran aren't correctly identified and used, also previous wind power functions have been weakened, all these because of the dynamic inhibitor loops as a result of policies conducted. Inhibitor loops are the results of short-term corrective measures which have brought dynamic risks and costs. These risks and costs make wind power energy sources unprofitable. In this study, using system dynamics approach, we analyze these costs paid for balance of risks and survey the optimal wind power production compared with other energy sources in energy portfolio. In the model used in this study, a dynamic relationship between risk and value is presented to create value in order to use energy sources efficiently and manage generated risks. Finally, the future process of value of wind power in energy portfolio is evaluated by computer simulation. • Develop a model to evaluate risk-value power production by renewable energies. • Identified reinforcing and balancing loops in risk-value of wind power production. • Analysis of the future trend of wind power generation in Iran to declare investment opportunities. • Examined three scenarios to analyzing risk-value creation in wind power production in Iran. [ABSTRACT FROM AUTHOR]

[Display omitted] • A new configuration of HVAC systems for an office as zero energy building. • This model is simulated in six major climate regions in ten cities of Iran. • The evaporating cooler integrated with the ground is used as the main cooling facility. • Cooling energy demand scale in comparison with other systems' energy tends to zero. • PV cells and ground heat pump generate electricity and heating, respectively. • The LCC value for this article model system is lower than the 50 %of value in comparison with usual systems. This paper presents a new configuration of heating and cooling systems for a net zero energy building (NZEB). In this paper, one design for Net Zero Energy Building(NZEB) systems is simulated, which can provide cooling and heating needs in a wide variety of climates. This current model benefits from direct evaporating cooling (DEC) which is coupled with the ground instead of the chiller in order to reduce the consumption of energy, water usage, and humidity of indoor air. The PV cells and heat pump that are connected to the ground generate electricity and heating energy, respectively in the building besides domestic hot water is provided by solar collectors. This model is simulated in ten cities of Iran as a multi climate country with six various major climates. The Life Cycle Cost (LCC)is calculated for all of these cities and the value is compared with the usual systems. The results show the possibility of an NZEB in various dry weather in Iran, furthermore the thermal comfort situation is confirmed. The cooling energy demand proportion to other energy usage tends to be zero. The LCC value will be able to reduce to 50% of the usual systems. [ABSTRACT FROM AUTHOR]

This paper investigates the relationship of two types of renewable energy consumption (total hydropower, wind, solar and nuclear energies, and total combustible renewable and waste) to stock market value and economic growth in Iran. An autoregressive distributive lag (ARDL) model was used for data from 1990 to 2014 and results show that stock market value affects both groups of renewable energies in the long run. Growth rate significantly affects total hydropower, wind, solar, and nuclear energies in both the short and long run, although it is only significant in the short run for combustible renewable and waste energies. Neither type of renewable energy consumption affects growth in either the short or long run. • Studying energy consumptions of wind/hydro/solar/nuclear and combustible/waste. • Using ARDL, results show stock market value affects both groups in the long run. • Growth rate significantly affects total hydro/wind/solar/nuclear energy. • The effect is significant for combustible and waste energies in the short run. • Neither types of renewable energy consumption affect growth. [ABSTRACT FROM AUTHOR]

Iran's energy system is extremely dependent on fossil fuels which, in turn, have led to problems such as fossil fuels depletion, social, economic and environmental damage and territorial imbalance. The country should therefore design a sustainable energy system based on clean energy a s well as renewable energy. Accordingly, and given that Iran's rural areas suffer from the unsustainable energy system, it is necessary to integrate renewable energy into comprehensive development programs in general, and into rural development programs, specifically. This review paper answers the following questions: Why is renewable energy important for Iran at national and rural levels? How is renewable energy related to sustainable rural development? and What are the challenges in the promotion of renewable energy technologies in Iran? The paper concludes that although renewable energy has potential for development in Iran's rural areas due to environmental, social and economic advantages, it could face some infrastructural, managerial, socio-cultural and economic challenges. Accordingly, aggressive and innovative policy making is required to meet these challenges. [ABSTRACT FROM AUTHOR]

Abstract While the empirical literature on energy intensity is focused mainly on reduced energy intensity, this study examines a case where energy intensity is increasing. The paper aims at identifying price and non-price determinants of Iran's energy intensity and analyzing their importance in dynamics of it. In order to answer the research question, LMDI decomposition technique as well as time series econometrics have been used to data analysis. Based on the results, both structural changes in economic activities and inefficiency of energy consumption have led to the increase in Iran's energy intensity, although the latter dominated the former. The elasticity of energy intensity with respect to total factor productivity, real energy prices, and industrial development is negative in the short-run and long-run. Additionally, per capita income has a positive linear relationship with energy intensity that implies a high income elasticity of energy demand. Furthermore, changes in TFP and energy prices contribute more than two-thirds of forecast error variance decomposition of energy intensity, which shows the importance of these factors in energy intensity dynamics. Hence, in order to change the increasing trend of energy intensity, it is important to consider the necessities of improving technology and productivity while realizing energy prices. Highlights • Iran's economy faced an average annual growth of 3.3% in energy intensity between 1974 and 2014. • Both inefficiency and structural effects led to the increase in energy intensity of Iran. • Relative energy price and total factor productivity have key roles in energy intensity dynamics. • Economic growth based on TFP improvement will lead to declining energy intensity. • Industrial development strategy can has a significant role in energy productivity in Iran. [ABSTRACT FROM AUTHOR]

Abstract This paper aims to develop a novel efficient Feed-In-Tariff (FIT) supportive scheme for diffusing photovoltaic systems in the residential sectors in the presence of multifarious smart net metering mechanisms. In doing so, a comprehensive economic analysis is performed to explore the optimal regional FIT for spreading PV systems and preventing overpayment/underpayment of flat national FIT. In addition, a new scheme of incentives in each region is established to change electricity use from their current consumption patterns in response to changes in the PV generation and the price of electricity. The participation of PV systems during peak demand associated with different potentials of PV self-consumption is the linchpin of the proposed methodology. The proposed model is then applied to investigate the techno-economic analysis in sixteen geographic areas in Iran. Such analysis introduces the most appropriate regions for investment and provides regional FIT. These results also show that at the current FIT as well as retail rate, the combination of FIT incorporating net metering is not beneficial. It can be concluded that by increasing the electricity price, the so-called retail rate or FIT, there is a point at which the PV systems investment will be cost-effective considerably. Highlights • Optimal regional FIT is introduced instead of national FIT. • A planning perspective for association FIT to electricity price is proposed. • A new scheme of incentive is presented for adoption demand with PV generation. • An incentive for long-term is examined from both utility/investor perspective. • Several scenarios are conducted to investigate subsides effect on FIT. [ABSTRACT FROM AUTHOR]

This paper studies forecasting the use of renewable energies in the water and wastewater industry. Different methods have been proposed to show energy recovery techniques and the use of renewable energy in wastewater treatment. The results indicate that increasing the carbon tax to more than 30 USD per ton of CO2 could reduce emissions from all fossil-fuel power plant types by 30%. • Providing a new assessment approach in applying renewable energy in the water and wastewater industry • Measuring the potential of using renewable energy in the water and wastewater industry • Investigating the use of renewable energy to reduce greenhouse gas emissions and air pollution control by wastewater treatment [ABSTRACT FROM AUTHOR]

This paper for the first time systematically examines fuel dual-pricing policy (FDPP) in the context of developing countries. Governments in most of these countries pay a heavy price for subsidizing fossil fuels and thus, most of these countries suffer from adverse economic, social and environmental consequences. In these circumstances, governments cannot take the risk of social unrest and economic shock by quickly removing fuel subsidies. FDPP can be addressed as a transitional policy to liberalize fuel prices. However, the literature fails miserably to address the dynamics of FDPP execution due to the lack of valid empirical data. Accurate analysis making use of long-term valid data could shed light on this dilemma. Through a scenario planning approach, this study evaluates the positive and negative impacts of executing or terminating FDPP. In general, it is concluded that, despite difficulties in formulation and implementation, FDPP has the potential for several positive economic and environmental effects through which fuel-subsidizing economies can employ FDPP as a transition pathway to liberalizing fuel prices. • This paper for the first time examines fuel dual-pricing policy (FDPP). • The FDPP can be addressed to tackle the upward trend of fuel consumption. • FDPP can be addressed as a transitional policy to liberalize fuel prices. • This paper used scenario planning method with real data to assess the FDPP. • The FDPP also could have substantial environmental achievements. [ABSTRACT FROM AUTHOR]

This paper provides an overview of the power sector development in Iran for the period 1984–2014. A retrospective optimization approach is applied to assess economic and environmental benefits that would have been achieved through appropriate long-term planning. MESSAGE, a systems engineering optimization model, is used for this analysis. Two alternative scenarios are defined to explore the impact of supply- and demand-side strategies on the power generation mix, fuel consumption and CO 2 emissions. The focus on the past choice of energy scenarios provides some insights for future scenario design. The results of the cost-optimal scenarios with international fuel prices are compared with the actual historical development. The findings indicate that the demand-side strategies are key drivers in achieving a low-carbon generation mix. Least-cost scenarios would favor much more combined cycle, renewable technologies and distributed electricity generation units, and less gas turbine than the actual transition pathway. Long-term energy planning would have reduced the cumulative total power system costs by $21-$90 billion. [ABSTRACT FROM AUTHOR]

Energy subsidies can incentivise the overconsumption of energy resources and contribute to other economic or social distortions. In this paper, an ex-post analysis is presented that explores the extent to which electricity subsidy reform could have reduced Iran's energy demand during the period 1984–2017. It also quantifies the techno-economic and environmental benefits that could have been achieved through such reforms. A time-varying econometric model is linked to an energy systems optimisation model. The former estimates electricity demand under different subsidy removal scenarios, and the latter identifies the cost-optimal generation mix to meet the demand. The results of cost-optimal transition pathways under subsidy removal scenarios are compared with the real-world energy system development during the study horizon. The comparison reveals that the subsidy reform could have reduced the total cumulative electricity consumption by 22%. Renewable share in power generation could have increased from 5% to 15%. Moreover, the reform combined with a cost-optimal generation pathway would have saved $69 billion and avoided 944 million tons of CO 2 emissions. The analysis also shows that every five-year delay in subsidy removal causes about 100 million tons of additional CO 2 emissions. Finally, the paper presents lessons learnt for future energy modelling. • An ex-post analysis quantifies the benefits of energy subsidy reform in the power sector. • The total cumulative electricity consumption could have been reduced by 22%. • Renewable share in power generation could have tripled. • Subsidy reforms combined with cost-optimal generation could have saved $69 billion. • The paper presents lessons learnt for future energy modelling. [ABSTRACT FROM AUTHOR]

Energy subsidies can incentivise the overconsumption of energy resources and contribute to other economic or social distortions. In this paper, an ex-post analysis is presented that explores the extent to which electricity subsidy reform could have reduced Iran's energy demand during the period 1984–2017. It also quantifies the techno-economic and environmental benefits that could have been achieved through such reforms. A time-varying econometric model is linked to an energy systems optimisation model. The former estimates electricity demand under different subsidy removal scenarios, and the latter identifies the cost-optimal generation mix to meet the demand. The results of cost-optimal transition pathways under subsidy removal scenarios are compared with the real-world energy system development during the study horizon. The comparison reveals that the subsidy reform could have reduced the total cumulative electricity consumption by 22%. Renewable share in power generation could have increased from 5% to 15%. Moreover, the reform combined with a cost-optimal generation pathway would have saved $69 billion and avoided 944 million tons of CO 2 emissions. The analysis also shows that every five-year delay in subsidy removal causes about 100 million tons of additional CO 2 emissions. Finally, the paper presents lessons learnt for future energy modelling. • An ex-post analysis quantifies the benefits of energy subsidy reform in the power sector. • The total cumulative electricity consumption could have been reduced by 22%. • Renewable share in power generation could have tripled. • Subsidy reforms combined with cost-optimal generation could have saved $69 billion. • The paper presents lessons learnt for future energy modelling. [ABSTRACT FROM AUTHOR]

Energy is essential for socio-economic development and due to the increase in energy consumption it is necessary to look for renewable and clean energy over the coming decades. Wind energy has received more attention than other sources due to better economic conditions as well as lack of environmental pollution and unlimited wind resources. This paper describes a practical method for measuring the potential of wind resources with the ability to generate electricity, using the geographic information system and considering the selection criteria of wind farms. The present study analyzed a multi-criteria decision support system to define wind energy resources in western Iran. In the method of calculating wind potential in this paper, the desired items are considered with equal importance and these criteria include technical, environmental, economic and geographical factors. The aims of this research are measuring the potential of areas suitable for generating electricity from wind energy for large turbines according to international standards, stating the standards and criteria for measuring the potential of wind resources and finally implementing the items mentioned in regional electricity. The results show that assuming the use of Gamesa G58 turbine, a maximum of 1897 MW of wind power can be generated in the study area, which is 26% of the region's electricity supply in 2025 horizon. The method used in this study can be applied for future wind potential measurements and it is recommended to be integrated with fuzzy AHP method to enhance the accuracy of the results. • Describing a practical method for measuring the potential of wind resources with the ability to generate electricity, using the geographic information system and considering the selection criteria of wind farms. • Measuring the potential of areas suitable for generating electricity from wind energy for large turbines according to international standards. • Obtaining the necessary factors to select suitable locations for wind farms in Iran's Western Regional Electricity in order to provide criteria based on GIS and evaluating their impact. [ABSTRACT FROM AUTHOR]

Energy drives national economies with a positive correlation. Global environmental concerns, growth of the world population, and emerging of developing economies with more need for energy resources, would change the future of energy markets and human lives. To manage energy shortage and energy-related environmental threats, decision-makers have to decide between three potential solutions [1], to develop supply value [2], to suppress energy (all types) demands, or [3] to adopt a hybrid strategy. This paper is aimed to uncover potential saving capacities to fill the supply-demand gap based on efficiency improvements for the case of Iran as a developing economy with increasing energy needs. The methodology has been designed based on energy balance calculations which have been evaluated and validated through 47 expert panels under 9 major themes. Then, policy sets have been determined and to map how defined policies were interacting in the living energy, a system interpretive structural model was performed to determine direct and indirect relationships among policies. As a result, policymakers can prioritize and set a roadmap to approach the desired future. Findings showed for the case of supply-side Iranian energy management [1] maximizing electricity transmission and distribution efficiency [2], upgrading the consumption standard in equipment and processes (in the terms of energy production, conversion, and transmission), and [3] online monitoring of distribution networks are most basic and top priority policies. While for the case of demand-side "targeting energy subsidies" is the most crucial policy to support the Iranian energy efficiency improvement targets. • Iran's potential saving capacities to fill the supply-demand gap based on efficiency improvements are studied. • Policy sets have been proposed through 47 expert panels containing 9 main themes. • An interpretive structural model was performed to map policy relationships and dedicate a macro-level action plan. [ABSTRACT FROM AUTHOR]

Population growth and technological advancement mean that human activities now consume increasingly higher levels of energy. This causes major problems such as depletion of fossil fuel resources and environmental pollution. Energy managers and planners are therefore trying to develop options to meet these increasing demands for energy while maintaining low environmental impact. Application of advanced energy saving techniques and renewable energy resources and technologies present a good solution to these problems. Bio-energy is a widely available resource so it presents an attractive type of renewable energy. Biomass is abundant and easily accessible, making it a low cost resource with great flexibility in terms of potential application. This paper reports on biogas production from livestock manure and considers evaluations made for the different provinces in Iran. Data for calculations were sourced from available databases relating to Iranian cattle farms. This study reports on calculations made using statistical data on number of cows, amount of manure produced and volume of created biogas per kilogram of animal waste. The total amount of biogas production from livestock waste was calculated for each province using theoretical and experimental methods. Outcomes showed that production of biogas from livestock waste could potentially supply a proportion of the country׳s natural gas demand. The outcomes were tabulated and a GIS database was generated. Volumes of produced biogas from livestock manure were compared with those of natural gas consumption and outcomes were plotted on a classified map showing data for natural gas consumption and biogas energy. Outcomes revealed that the provinces of Sistan-Baluchestan and Ilam had the highest priority in production of biogas from livestock waste with annual gas consumption levels of 33.3% and 9% respectively. [ABSTRACT FROM AUTHOR]

The importance of energy demand estimation stems from energy planning, formulating strategies and recommending energy policies. Most often, energy demand is mathematically formulated by socio-economic indicators. The challenging problem is to determine the optimal or near optimal weighting factors. Inspired by social behavior of bird flocking or fish schooling, PSO (particle swarm optimization) is a population-based search technique which has attracted significant attention to tackle the complexity of difficult optimization problems. This paper studies the performance of different PSO variants for estimating Iran's electricity demand. Seven PSO variants namely, original PSO, PSO-w (PSO with weighting factor), PSO-cf (PSO with constriction factor), PSO-rf (PSO with repulsion factor), PSO-vc (PSO with velocity control), CLPSO (comprehensive learning PSO) and a MPSO (modified PSO), are used to find the unknown weighting factors based on the data from 1982 to 2003. The validation process is then conducted by testing the optimized models by using the data from 2004 to 2009. It is seen that PSO-vc produces more promising results than the other variants, HS (harmony search) and ABSO (artificial bee swarm optimization) algorithms in terms of MAPE (mean absolute percentage error). This value is obtained 2.47 and 2.50 for the exponential and quadratic models, respectively. [ABSTRACT FROM AUTHOR]

The ever increasing rate of energy consumption, limited fossil fuels and pollution have made the expansion of renewable resources essential. Due to the suitable solar potential available in Iran, the use of solar energy has been developed more than other renewable resources. In this paper, photovoltaic (PV) panels are hybridized with battery banks and the power grid to provide electricity for 100 residential units and by performing a techno-economic-environmental analysis on the use of different solar tracking systems PV power generation is maximized. The final aim of this paper is to find the optimum scenario for reaching the highest efficiency along with emissions that are within the standard range. Also, the effect of grid sell back on the results is estimated and a sensitivity analysis is performed to generalize the results for other economic and climate conditions. Results show that the use of the solar tracking system significantly reduces the number of needed panels, but this size reduction is not always cost-effective due to the high cost of tracking units. The vertical tracking system indicated the best cost-efficiency with 0.241 $/kWh cost of energy and an average of 23% improvement on the output power. Although the dual-axis tracker improved power production by 32%, it was less cost-efficient. Sensitivity analysis indicated that with 33% renewable fraction and slightly different initial costs, the optimum cost of energy will vary from 0.227 to 0.255 $/kWh. • A grid-connected photovoltaic-battery system is optimized in different climates. • Techno-enviro-economic comparison of different solar tracking systems is done. • Residential demand at a standard level of CO 2 production is provided. • Vertical tracker is the most cost-effective system with 0.241 $/kWh cost of energy. • Power production is improved by 23%, compared to the without tracking scenario. [ABSTRACT FROM AUTHOR]

• Proposing an EH based on CCHP-ORC equipped by SWD, hydrogen electrolyser and EVs. • Assessing the effects of installation of WST on optimal operation of EH and other storage devices. • Modeling EVs uncertainties using scenario generation. • Presenting a Robust stochastic optimization using IGDT. • Considering two objective functions simultaneously as operational costs and emission. With the development of human societies, new industries and needs are being formed which supplying their power and energy consumption, requires the development of equipment and infrastructure in the field of power generation and transmission. An example of these industries are seawater desalination (SWD) units. In addition, increasing attention to air pollution has led to the proliferation of electric vehicles (EVs) or the use of hydrogen as a zero emission fuel. Energy hubs (EHs) can benefit from advantages such as optimal use of installation capacity and environmental potential by accepting to provide other needs along with common requirements such as electricity, cooling, and heating. In this case, EH is able to increase its flexibility by converting energy into the desired product and storing it in a different form as of electrical or thermal energy. In this paper, EH utilizes a SWD with Reverse Osmosis (RO) technology as a flexible load and an Organic Rankine Cycle (ORC) as a new technology for generating electrical power by means of thermal power. In addition, for better interact with available EVs, one parking lot and a Battery Swapping Station (BSS) are introduced. The Electrolyser uses the electrical power to supply the required amount of hydrogen, and the hydrogen tank in addition to fuel cell (FC) help to balance the production and consumption of hydrogen. In order to model the existing uncertainties, scenario generation method as well as information gap decision theory (IGDT) method have been used. The efficacy of the proposed model is evaluated on a smart commercial building in Qeshm Island, which is located a few kilometers off the southern coast of Iran. [ABSTRACT FROM AUTHOR]

Biofuels are considered renewable sources of energy which can replace fossil fuels using naturally extracted fuels from the environment to fulfil growing demands for energy in developing countries. This paper aims to select a suitable province for producing biodiesel from Jatropha plants in new climate conditions of Iran using the additive ratio assessment method (ARAS). Previous feasibility studies lack the environmental factor when considering the cultivation of Jatropha plants in Iran. In this work, the relevant main selecting criteria were identified through using a literature review. Then, the most effective criteria were chosen and categorised as environmental, social and economical factors. The weighting of the criteria was determined by Shannon entropy method and using expert opinions. Next, the ARAS method was used for prioritizing the provinces in Iran. From the results, it is observed that the environmental factor is the key parameter for selecting biodiesel plant location. Furthermore, Golestan province was selected as the best candidate location in Iran for establishing a biodiesel plant using Jatropha plants. Using the semi-arid pastures of Golestan province (about 402,000 Hectares), 1,930,000 tons biodiesel can be produced annually for supplying the fuel to 600,000 diesel cars. • Biodiesel fuel from Jatropha Curcas in Iran was investigated. • Suitable locations were evaluated and ranked accordingly. • Multi-criteria decision-making methods (MCDM) were used for ranking. • Golestan province in north of Iran was selected as the best candidate. • 1,929,057 tons of biodiesel can be produced annually to run 598,976 diesel cars. [ABSTRACT FROM AUTHOR]

Undesirable environmental impacts caused by fossil fuel consumption have motivated governments to focus on biofuels production. Therefore, in our paper, we design a multi-objective biodiesel supply chain from Jatropha, which includes biomass cultivation center, pretreatment, and oil extraction center, biorefinery, and demand zone. In our study, a two-stage approach presented, which first specifies candidate locations for biomass cultivation with a common weight data envelopment analysis (CWDEA) method and then strategic and tactical decisions were made by a mathematical model. The presented multi-objective model focuses on cost minimization, besides social benefits and environmental impacts maximization while a life cycle assessment approach is used to model social indicators. The capability of the model is validated by proposing a case study of Iran and the augmented ε-constraint method is employed to reach a trade-off between three pillars of sustainability while managerial insights are provided by employing a Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method for the optimal solution selection. Model's results and sensitivity analysis on key parameters, specify the best locations for Jatropha Curcas L. (JCL) cultivation and facility construction as well as an optimal value of supply chain variables, which finally proves that Iran has a high potential for biodiesel production from JCL that leads improving balanced socio-economic development in this country. • Presenting a two-stage approach for designing sustainable biodiesel supply chain. • Quantifying social criteria in a multi-objective biodiesel supply chain. • Cost optimization by specifying the best locations for feed stock cultivation. • Presenting the trade-off between three pillars of sustainability. • Considering decision-makers' preferences for selecting the optimum solution. [ABSTRACT FROM AUTHOR]

Energy is a main factor for sustainable and economic development of many countries in the world. The objective of this paper is to investigate barriers facing solar energy development in Iran through a case study conducted on the Alborz Province. A questionnaire was designed and then submitted to the professionals in the field of solar energy. First, the identified barriers are classified into five categories of technical, legal, economic, sociocultural, and support by help of experts. Then, the fuzzy Best-Worst method is used to determine importance of the identified criteria and sub-criteria for development of the solar energy sector in the region. The findings indicate that the primary barriers to solar energy development are economic factors which are related to the adverse impact of the uncertain economic conditions including the sanctions against Iran. Because of the high risk of new business, domestic people do not have enough ambition and interest in starting new renewable energy projects. The low price of fossil fuels (in the economic category as sub-criteria), has the most significant impact on the stagnation of this sector, which is related to the ease of access to energy in Iran and its effect on the interest in renewable energy use. Supporting the private sectors by receiving financial incentives can help development of the renewable energy sector in the province. By using similar research for other regions, decision makers can accurately identify challenges for development of solar energy. [ABSTRACT FROM AUTHOR]

The methods to collect and transport various types of medical waste are vital to the management of healthcare waste. The lack of a safe plan for the timely collection and transportation of such wastes may have an undesirable impact on the environment and public health. The present research addresses a real-life healthcare waste collection vehicle routing problem (HWCVRP) for small medical centers in Iran that produce minor amounts of waste and lack on-site facilities to treat wastes of various kinds. This problem involves social, environmental, and economic objective functions, aiming to achieve sustainable development. The social objective function is optimized based on a novel definition of risk in medical waste collection and designed to reduce public health risk by minimizing the time of waste collection from centers that produce a larger volume of more hazardous waste. Furthermore, the present paper provides a comprehensive estimate of fuel consumption in vehicles to be accurately minimized to diminish the environmental hazards involved in sustainable transportation. Also, the economic objective function is set to minimize the variable and fixed costs of transportation. A self-adaptive multi-objective evolutionary algorithm is generated with numerous effective operators to solve the model. Specific metrics are employed to compare the performance of the proposed meta-heuristic algorithm with those of multiple other evolutionary algorithms. The results reveal the effectiveness of the proposed method in reaching high-quality non-dominated solutions. Ultimately, a real-life case study is used to implement the proposed approach and to evaluate its performance. Image 1 • A real perspective to the triple bottom line of health-care waste collection. • A new social aspect of sustainability based on the risk of different medical waste. • A new multi-objective self-adaptive evolutionary algorithm (MOSAEA). • The results show that MOSAEA dominates recently competitive approaches. [ABSTRACT FROM AUTHOR]

• Developing novel multi-level benchmarks. • Identifying benchmarks for electricity and thermal energy for office buildings. • Presentation a base for short/long-term energy efficiency plans. • Analyzing energy efficiency and consumption in details. • Creating a dataset, including building and energy information. Energy benchmarking is an accurate tool to measure, monitor, and reduce end-use energy consumption in the building sector using comparison scenarios. Various studies have applied Bottom-Up energy consumption assessment to compare the energy performance of a group of buildings with a benchmark. The Bottom-Up method mostly relies on simulating an ideal building to develop a benchmark. However, this study has developed a Top-Down energy benchmarking methodology based on the actual energy consumption within a cluster of governmental office buildings. The method presents multi-level benchmarks to provide a detailed policy for improving the energy efficiency of buildings in the short or long-term. In an exploratory study, 26 office buildings in a cold climate region were investigated to identify the multi-level benchmarks. Four general benchmark levels were developed, including the 'Best Practice, 'Good Practice', 'Benchmark', and 'Poor Practice'. In addition, 15 energy efficiency classes were also introduced and applied as a base for developing the 'Energy Performance Certificate' method. The results indicate that the benchmark values for electricity and natural gas are 40 and 252 kWh/m2/yr, respectively, while the total energy benchmark is 292 kWh/m2/yr. According to the benchmarking results, 69% of the case studies were inefficient, 23% were labeled 'C', and no cases were labeled 'A' or 'B'. The multi-level benchmarking system can provide quick and clear guidance for building designers, operators, and government regulation/enforcement agencies; thus, it can apply at local, regional, and international levels. These benchmark levels establish reference points for measuring and rewarding good performance, on the other hand, it recognizes poor-performance buildings and prioritizes them for energy efficiency improvement. The method can be replicated in various climates and urban scales. [ABSTRACT FROM AUTHOR]

In this paper, a comprehensive model of indirect water heater for a pressure reduction station of natural gas has been presented. Effiiency and fuel consumption of heater have been estimated by applying energy and mass conservation equations. Three terms of energy including heat absorbed by natural gas, heat transferred to environment from stack and heat loses to environment from heater body have been evaluated. Thermal properties of natural gas has been calcualated using AGA8 state equation. Therefore, the model is a function of climate, heater geometry and natural gas characteristics including temperature, pressure and its composition. The results are compared with data recorded from real station in Iran (Arak, Kheriabad and Malekabad stations) and very good agreement has been observed. Reducing temperature and increasing pressure of inlet gas, thickening glass wool insulation and rising fire tube radius led to an increase in heater's thermal efficiency from 20 to 60% and consequently fuel consumption of heater was reduced. Finally, choosing the sutible geometery yeilded a higher heater efficincy with a raise from 44% to 70%. • Comprehensive thermal model of CGS indirect water heater has been presented. • Ambient temperature has notable effect on annual fuel consumption. • Efficiency could be improved by change of gas and fire tube radius and passes. • Geometry optimization could increase the heater efficiency from 44% to 70%. [ABSTRACT FROM AUTHOR]

Livestock production systems, such as dairy farming, are one of the most important contributors to resource use and if not managed well, it can be environmentally detrimental. Iranian livestock sector faces a variety of the challenges such as high costs of energy and environmental legislations as well as an increasing demand for dairy products to respond the growing population. This paper aims to contribute to the discussion on technical efficiency as a key indicator of energy use within dairy farming systems. A Window Data Envelopment Analysis (W-DEA) with energy use as inputs and milk production as output was modelled with data from 25 provinces during the last 22 years (1994–2016) in Iran. In addition, the Slack-Based Model (SBM) was used to compare the radial DEA model with non-radial SBM, both in a dynamic environment (window analysis). The average efficiency score of Iranian dairy farming production system was estimated at approximately 0.85. Through the years, three provinces including Zanjan, Ardabil and Hormozgan had the highest technical efficiencies. Window analysis represented that provinces are distinctive in terms of their technical efficiencies and energy consumption over the years. Applying the SBM model improved the accuracy of the estimated efficiency scores compared to the radial (DEA) model. Further analysis represented a significant difference between the technical efficiency of different milk production levels. Provinces that produced higher volumes of milk had lower technical efficiencies. Based on the results it can be concluded that there is a substantial space for upgrading the technical efficiency of dairy farming in Iran by improving resource use efficiency which leads to an optimized energy consumption. It is recommended to reform Iranian livestock farming policies by applying mechanized systems, optimal strategies for water, electricity and fossil fuel consumption, use of renewable energy and better feed management while enhancing milk productivity and technical efficiency. In this respect, it is suggested that policy makers consider different indicators such as energy use efficiency and environmental impacts when allocating subsidies and resources to different provinces and farms. • Iranian dairy farming was assessed for the technical efficiency over 22 years. • Efficiency of 25 provinces were identified using window data envelopment analysis. • The average efficiency score of dairy farming was approximately 0.85. • We propose improvement of resource management in order to minimize energy use. • Milk production was found as an effective factor on efficiency of provinces. [ABSTRACT FROM AUTHOR]

The general policy of the European Union in reducing greenhouse gas emissions is such that the increased average global temperature is kept below 2 °C. Many countries are looking for more effective solutions and methods to reduce carbon emissions. There are effective factors in the scheduling passenger and freight trains in the inter-city rail transport industry such as number of trains requested at the station, the number of stops, delays and waiting times for trains at the station which lead to increased fossil fuel consumption and carbon emission. In this paper, we want to present a new mixed integer non-linear model that can choose the best schedule for movement of passenger and freight shuttle trains on a single-line route of the railway network with the least environmental pollution. In this model, the carbon emission factor is based on the weight and prioritization of passenger and freight trains. Also, the average number of demands for using trains at a station and the number of planned or non-planned stops and delays at the middle stations are considered. Also, the proposed model selects the best plan for moving trains with the lowest carbon emissions caused by fuel consumption. To validate the proposed model, a case study of a crowded passenger and freight route of an inter-city railway network in Iran will be solved. We solve the real studied problem using the GAMS v24.9.1 optimization software with BARON solver. Finally, after sensitivity analysis of the results, we demonstrate the convenient and efficient performance of the same model in solving the raised problems in an applied manner. Image 10162 • A new model for reducing Carbon emissions through optimal scheduling of trains is developed. • We apply the carbon emission factor based on the weight and prioritization of passenger and freight trains. • We consider the number of planned and non-planned stops, delays, and waiting times of trains. • A real case study is applied for validating the proposed model. [ABSTRACT FROM AUTHOR]

Particleboard is one of the non-structural wood-based composites developed in the late 1950s in Iran to utilize agricultural and industrial wood residues. Since there was no published document about its Life Cycle Inventory in Iran, the aim of this study was to document the life cycle inventory data from the particleboard manufacturing in the second hand lines in Iran. The study covers the energy consumption and environmental impacts of raw materials and processes during particleboard production. In order to identify the main hotspots and characterize the production process, impact categories were considered using CML methodology and cumulative exergy demand (CExD) indicator. The results revealed that the board shaping subsystem was the main contributor to the most of impact categories. The main hotspot for resin production was known as Urea-formaldehyde (UF). Electricity was the main hotspot in acidification (AC) and ozone layer depletion (OLD) impact categories, while transportation and production process were the main hotspots in marine aquatic ecotoxicity (ME) and photochemical oxidation (PO) impact categories, respectively. Moreover, rotary dryer, hot press, flaker and hammer mill, vacuum pump and diesel fuel were the most effective sectors in the emissions of the production process. Results for substitution of natural gas showed that, except some impact categories, the use of alternative source of thermal energy such as wood residues could improve emissions from the manufacturing process. [ABSTRACT FROM AUTHOR]

This study deals with the interface between energy consumption and its related emissions in the manufacturing of one cubic meter medium density fiberboard (MDF) in Iran and provides a comprehensive life cycle inventory (LCI) data for production process. The study was developed following the methodological guidelines of ISO 14040. Inventories data for a gate-to-gate assessment of MDF manufacturing were collected by on-site surveys. Ten impact categories including of: Abiotic depletion (AD), Acidification (AC), Eutrophication (EP), Global warming (GW), Ozone layer depletion (OLD), Fresh water aquatic ecotoxicity (FE), Marine aquatic ecotoxicity (ME), Human toxicity (HT), Terrestrial ecotoxicity (TE) and Photochemical oxidation (PO) in three subsystem of manufacturing process were assessed. The subsystem of fiber preparation was the major contributor to the environmental impacts. Urea-formaldehyde (UF) resin production was identified as the main hotspot, except in AD, AC, OLD and PO impacts that natural gas, electricity, transport and production process were the main hotspots, respectively. Moreover, Tube dryer, MDF saw and hogger were the most effective sectors in the emissions of production process. Results for substitution of natural gas showed that except in some impacts categories, use of alternative source of thermal energy such as wood residue could improve emissions from manufacturing. [ABSTRACT FROM AUTHOR]