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This paper addresses the issue of reliable and green routing in a road-rail multimodal transportation network. To enhance network reliability, types of disruptions occurring simultaneously in each node and arc are identified. Additionally, carbon emission is considered a risk caused by transportation process disruptions for achieving green routing. A combination of rating methods such as DEMATEL-based Analytic Network Process (DANP) and the Combined Compromise Solution (COCOSO), along with Failure mode and effects analysis (FMEA) Criticality reliability assignment method, is used to evaluate disruptions and select a safe route from origins to destinations. The DANP method produces a ranking of sub-criteria, and the COCOSO method produces a ranking of criteria in the network. The FMEA Criticality reliability assignment method is used to assign reliability to each option. Next, the route with the highest reliability from each origin to each destination is selected. The presented model investigates a cement road-rail transportation network in Iran. After analyzing the sensitivity of criteria and sub-criteria, the results provide best routes with increased reliability and reduced emissions risk. • Identifying risks in each node and arc in the transportation network. • Prioritizing criteria, sub-criteria, and options using a mix of DANP and COCOSO ranking methods. • Assessing the reliability of each option using the FMEA Criticality method. • Selecting the best path with the highest reliability and the less carbon emission risk in each O-D pair. • Considering a case study in the cement road-rail transportation network in Iran. [ABSTRACT FROM AUTHOR]

This paper focuses on a comprehensive solution for dry municipal solid waste (MSW) management with describes the scenario of the gasification process. For this purpose, the potential of implementing the MSW gasification process in Southeast Asia (Iran) with three agents of air, steam, and air-steam is investigated. In order to manage the MSW gasification process as accurately as possible in the study area, a thermodynamic, exergy, economic, environmental, carbon footprint, water footprint, ecological emergy, and risk assessment for the three mentioned gasification agents were carried out in the most populated cities of Iran. In the capital of Iran (Tehran) with the largest population and as a result of largest MSW production, the potential of the gasification process has been investigated at different times (10 consecutive years and 12 months of a year). Finally, by combining artificial neural networks and genetic programming, comprehensive relationships have been established to predict the thermodynamic conditions of gasification with an air-steam agent. The general results of the survey indicate that gasification with air agents has good potential for most regions. The use of the steam agent has created worse economic, environmental, and risk conditions than the other two agents. Investigating the potential of the gasification process in Tehran shows that this city has a good potential to implement this process compared to other cities in Iran, and the most suitable location for establishing the gasification process is the 4th region of this city. [Display omitted] • Potential of municipal solid waste (MSW) gasification for all Iranian cities. • Comparison of using air, steam, and air-steam agents for MSW gasification. • The payback period of air agent MSW gasification is lower than other agents. • Machine Learning used for prediction of the behavior of MSW gasification. [ABSTRACT FROM AUTHOR]

This paper proposes a novel agent-based model (ABM) to assess actual informal water market (IWM) trade—a highly common form of reallocating water globally, but where analysis is challenging due to data paucity. Because, typically, there is not an integrated or centralized institution coordinating transactions in IWMs, social networks and communications between farmers play a key role. This makes applications of ABMs in the informal space appealing and useful. Survey and interview data are used for the model development via a sample of farmers in Mojen Area, Iran. Also, in the final model, some critical human behaviors (e.g. adaptability and self-interest) are described in the form of parameters and formulas, with optimum values calibrated based on the Mojen sample as well as making possible a detailed assessment of the effects on water transaction and farmers' profit margins. The result of the simulation reveals that IWM trade frees up water for use by other farmers in the Mojen area, especially when stronger social networks are in place where the average number of water transactions will be increased—about 50%. The presence of IWMs also contributes to a more stable cultivation area in dry years, where water trading helps protect perennial crops that have become an increased production system choice in recent years. Further, informal water markets help farmers to optimally use water supply in order to deal with lower rainfall years and fulfil water needs during higher rainfall years due to increasing cultivation areas. [Display omitted] • An agent-based social network model for informal water market (IWM) simulation is developed. • A method of trades and an updating rule for simulating profit margins are proposed. • Experience, prior knowledge, and land area are three factors affecting water exchanges. • IWM can greatly improve the situation of water scarcity. • IWM stimulates farmers to use water in the best way in both trading and irrigation. [ABSTRACT FROM AUTHOR]

There is a growing concern about the pollution of agricultural systems caused by plastic residue and debris. This pollution poses a threat to the quality of food products. To gain a deeper understanding of how to maintain cleaner farmlands and reduce plastic residue and debris pollution, this cross-sectional study investigated the intention and behavior of plastic residue management (BPRM) in farmlands. Using random sampling method, the study surveyed 338 farmers in northwestern Iran. The resulting evidence found that 37.6% of farmers perform the BPRM with a mean score above average. The path analysis cleared that among the conceptualized ecological, economic, and social connotations, only the ecological attitude had a significant and positive impact on the BPRM (β E c o A t t i → B H V = 0.28, p < 0.001). It was found that both fact feedback (β F F B s → Int = 0.76, p < 0.001) and causal feedback (β C F B s → Int = 0.22, p < 0.001) contribute to reducing plastic residue pollution and forecasting the intention to perform the BPRM. The intention, in turn, directly predicts BPRM (β Int → B H V = 0.30, p < 0.001). Using a 2 × 2 cross-tabulation of causal feedback and the scenario of landfilling, derived from perceived action-based life cycle analysis of plastic wastes, the association between the two variables was found to be statistically significant (x 2 (df) = 3.24(1), p < 0.05). The resulting evidence would provide essential information for farm management strategists and governmental authorities to reduce plastic residue pollution in farmlands. This can be achieved by implementing policy initiatives that aim to change farmers' intentions and behaviors. • Paper indicates how to keep farmlands cleaner from plastic residue pollution. • Factual feedback forecasts intention to perform plastic residue management behavior. • Cause feedback predicts intention to perform plastic residue management behavior. • Cause feedback links with scenario of landfilling from action-based life cycle. • Factual and causal feedback should be given to farmers. [ABSTRACT FROM AUTHOR]

The Integrated Solid Waste Management (ISWM) is a recent effective tool to manage with the growing challenge of Municipal Solid Waste (MSW). The ISWM integrates all the system components (i.e. transfer, treatment, recycling and disposal of wastes) to enhance the sustainable waste management whilst reducing operational costs. In this paper, we investigate an integrated framework of the Fleet Size and Mix Vehicle Routing Problem (VRP) to optimize the cost-effective ISWM system. A novel bi-objective Mixed-Integer Linear Programming (MILP) model is developed to concurrently minimize the transportation cost in the entire waste management system and total deviation from the fair load allocation to transfer stations. A complete ISWM system with all interdependent facilities and multiple technologies, is developed to address a tri-echelon Fleet Size and Mix VRP with a heterogeneous fleet of vehicles under multiple technologies and waste compatibility constraints. The model was solved for both the Preemptive and Non-Preemptive conditions using Lexicographic and Goal Programming optimization approaches. The model was tested on a case of ISWM in the Southern part of Tehran, Iran. [ABSTRACT FROM AUTHOR]

Growing demand for electricity has made power grid design and expansion planning one of the main challenges in power industry management. In recent years, reconfiguration of existing power grid along with the adoption of renewable power generation leads to a significant reduction in expansion costs and GHG emissions. This paper offered a novel optimization model to address the design and planning of power grid expansion in a dynamic environment. Besides capacity planning, the model also determines location and time to construct new facilities. This research aims to satisfy demand by considering reduction in net present value of costs and increase in network efficiency. Electricity tariff and cost of load shedding differ according to different power consumers (i.e., residential, commercial, industrial and agricultural). Due to inherent intermittency in renewable energy resources and their subsequent impact on the entire power grid, different scenarios are generated, and the model is solved using the sample average approximation method. Eventually, validation of the proposed model and sensitivity analysis is carried out through a real case study in Iran. Computational results demonstrate the practicality of the stochastic model and show integration of renewable power plants would decrease the transmission and sub-transmission network costs. • A novel optimization model is developed to determine the power grid's design parameters and expansion mode. • Discretization of the electricity demand in different sectors is considered. • Sub-transmission systems alongside with renewable resources are incorporated in the proposed network. • The incentive by the government is considered for private enterprise to invest in renewable energy. [ABSTRACT FROM AUTHOR]

Due to problems such as limited land area for waste disposal and waste-borne diseases, waste management organizations have increasingly been offering technologies for recovering energy from waste. These technologies can help governments, local authorities, developers and investors for mitigating climate change and building sustainable societies. The suitable waste-to-energy production technology selection is a complex issue in waste supply chain management that must not only be assessed in terms of both socioeconomic and environmental criteria. With the purpose of balance between energy trilemma issues in the context of waste-to-energy generation and develop sustainable waste management strategies in the waste chain, energy justice criteria must also be taken into consideration. The paper considers the application of an integrated multi-criteria decision-making model consisting of fuzzy decision-making trail and evaluation laboratory method, the analytic network process and the simple additive weighting approaches. The integrated method can be applied to select the suitable technology in a sustainable manner, taking into account energy justice criteria. The applicability of proposed model is demonstrated by a case study of the technology selection in the city of Behbahan, Iran. It includes various technologies for waste-to-energy generation and ranks technologies from the most to least preferred as: Anaerobic digestion, Gasification, Pyrolysis, and Incineration. Image 10859 • We focused on the case of Iran for waste-to-energy technologies selection. • Anaerobic digestion, Gasification, Pyrolysis and Incineration items are applied. • The criteria of the decision making are the energy justice principles. • The energy justice concept refers to the sustainability criteria. • The combination of decision-making methods is employed. [ABSTRACT FROM AUTHOR]

This paper proposes a new Vehicle Routing Problem (VRP) with fair Carrier Collaboration (CC) which split multi-pickup and delivery services are considered for serving customers. This study has focused on VRP and serving customers with several commodity requirements from different geographically scattered suppliers subject to constraints on the vehicle capacity. A Mixed Integer Programming (MIP) model to maximize the total profit and the fair sharing of profit among the carriers by considering the travel time minimization is developed. Each carrier with its limited capacity can have reserved requests which must be served by itself and selective requests which can be served by itself or other vehicles or not served at all. There are various applications of the proposed model in the environment which can help reducing number of vehicles serving to the customers and eliminating empty back hauls. A Genetic Algorithm (GA) is proposed to solve this problem due to its Non-deterministic Polynomial-time hard (NP-hard) nature. In addition, Variable Neighbourhood Search (VNS) method is developed for improving the quality of initial solutions. Some instances are generated at different scales to evaluate the algorithm's performance by comparing the results of an exact optimal solution with that of the proposed algorithm. The obtained results demonstrate the efficiency of the proposed algorithm in providing reasonable solutions within an acceptable computational time. The algorithm is also tested for an online shopping website in Tehran, Iran. The test outcome shows that the proposed model returns a better benefit compared to the manual methods. The results of sensitivity analysis suggest that increasing the fairness coefficient among carries can led to a decrease in the total obtained profit. • Develop a novel carrier collaboration routing problem model with multi-commodity service and sharing fair profit. • Extend the carrier collaboration to general problems with in many-to-one problem pickup and delivery category. • Solve the problem with genetic algorithm with a new specific chromosome representation. • Result of implementation of the model in the real-world and sample instances. • Sensitivity analysis of the model based on fair distribution between participants is conducted. [ABSTRACT FROM AUTHOR]

Abstract In this paper, the full repowering of a steam Power Plant with a capacity of 320 MW in Iran was evaluated technically and economically. Implementation of this plan for the target power plant was selected because of its over 30 years of age. Due to the presence of steam flash feed water preheaters and the possibility of preheating feed water entirely or partially prior to entering heat recovery steam generator, the effect of using or not using these low and high pressure equipment was evaluated in different cases. To do this, five different cases were proposed and reviewed. Considering the available gas turbines in Iran, the gas turbines models Siemens V94.2 and V94.3A were selected. In each case, the optimum point is obtained in terms of the lowest cost of electricity generation. Finally, after reviewing the results of all cases, full repowering plan with parallel feed water heating was selected as the best alternative in terms of energy and exergy efficiencies and the price of generating electricity. If two heat recovery steam generators and two V94.3A gas turbines are used, the net exergy and energy efficiencies for the cycle can reach 54.49% and 52.98%, respectively. Moreover, the power capacity of a repowered unit is equal to 700.44 MW with electricity generation price of 0.05986 $/kWh. Graphical abstract Image 1057 Highlights • In the present study, a real power plant has been studied (A Case Study). • The five different arrangements of feed water heaters for proposed scenarios have been considered. • The merging of water-gas heat exchangers with existing preheaters has been investigated. • Optimum techno-economic case for repowering has been presented. [ABSTRACT FROM AUTHOR]

Abstract This paper designs a novel biogas fueled combined cooling, fresh water and power (CCWP) generation system, and investigates its performance under extremely-hot summer days. In this tri-generation system, biogas is used as clean resource to reduce emissions and consumption of fossil fuels. Six electrical chillers are used for cooling demand supply of a benchmark building located in Ahwaz, Iran. In addition, expected required power of chillers and building is supplied either by gas turbine cycle or by main grid (If total power consumed by chillers and electrical equipment is larger than output power of gas turbine, building owner pays for purchasing electricity from local power system to satisfy not-supplied demand). A low-grade waste heat is extracted from the flue gases for preheating purpose and closed-air open-water humidification dehumidification (HDH) desalination process. In addition, a mixed integer non-linear programming problem is solved to minimize an objective function composed of daily electricity cost, total capital investment, operation and maintenance cost of CCWP generation system considering all operational limitations of gas turbine cycle, chillers, HDH process, and strategic cooling and electrical demand response programs (DRPs). If ambient air decreases, gas turbine power and mas flow rate of potable water will be increased due to lower compressor power and higher absolute humidity of air, respectively. Application of DRPs reduces total electricity cost from 31.2$ to 16.4$. Utilization of biogas and waste heat recovery of flue gases with no need to combustion of fossil fuels results in emission reduction. Hence, this tri-generation plant is called a net-zero emission system. [ABSTRACT FROM AUTHOR]

Due to the adverse impacts of severe droughts on various aspects of human life and ecosystem services (ESs), the spatio-temporal assessment of the resilience of ESs under droughts is essential. In this paper, we propose a new methodology for assessing ESs-based resilience, taking into account the seven resilience principles: a) redundancy and diversity, b) managing connectivity, c) managing slow variables and their feedback, d) complex adaptive system (CAS) thinking, e) experimentation and learning, f) broadening participation, and g) polycentric governance. These principles enable us to consider the main social, political, hydrological, economic, and environmental aspects concerning resilience which have been overlooked in previous studies. The methodology is evaluated by applying it to Zarrinehroud River Basin (ZRB) in north-western Iran. A set of qualitative and quantitative criteria and their sub-criteria are proposed for quantifying the ES-based resilience and generating time series of resilience against severe droughts in several sub-basins in the study area. To evaluate the criteria and sub-criteria, the required data are derived from calibrated SWAT and MODSIM models as well as experts' judjments. The time series of ES-based resilience under 128 Water and Environmental Resources Management (WERM) scenarios (for enhancing agricultural practices, altering and modernizing irrigation methods, improving irrigation network and drainage facilities) and Climate Change (CC) scenarios (RCP 4.5, RCP6.0, and RCP 8.5) are derived for each sub-basin based on short-term (2020–2049) and long-term (2020–2098) periods. The low resilience values (0.53–0.6) of all sub-basins under the base management scenario (the status quo scenario (SC 0)) illustrate the need for implementing some projects to enhance the ESs in the study area. The results show that the WERM scenario SC 12346 can improve the values of the resilience criterion in sub-basins up to 0.85 and reduce the vulnerability of the study area to droughts. By evaluating all management scenarios, scenario SC 12346 is reported as the best scenario, since it can significantly increase the resilience of all sub-basins against extreme droughts with an acceptable cost of 636 million US dollars compared to other scenarios. Under this WERM scenario, the resilience values of sub-basins increase up to 40%. This scenario suggests implementing a set of projects such as improving irrigation networks and drainage facilities. [Display omitted] • A new methodology is proposed to assess basin-wide spatio-temporal resilience. • 128 scenarios are evaluated using a novel two-point evidential reasoning approach. • The best management scenario enhances the resilience value from 0.53 up to 0.85. • The selected scenario suggests improving irrigation networks and drainage facilities. • The seven resilience principles decrease the width of uncertainty band by 0.44%. [ABSTRACT FROM AUTHOR]

The purpose of this study is to present a framework to identify consumer's behavior towards green products by measuring the gaps between expectations and perceptions of consumers. The previous studies have mainly used SERVQUAL method in service quality to measure the gaps, but this paper introduces new approach of this methodology. It is modified using Grey system where the ambiguity and poor information existed in consumer opinions are consider. Unlike the previous studies, our model is applied to goods rather than services. In order to identify the quality of products, the main characteristics of green products have been identified based on last researches and according to interviews with dozens of experts in the field in which eleven components are selected. For collecting data, an instrument based on characteristics of products is designed and distributed among 387 consumers of LED bulbs as a case study of green products which is a common green product among Iranians. The results show that the highest positive gap is in terms of durability and performance, but the most negative gap is the price and serviceability of the products. Finally, the importance-performance analysis is made based on the results. [ABSTRACT FROM AUTHOR]

Wheat is a strategic crop for Iran with respect to food security and environmental impact. In the northeastern Golestan Province irrigated and rainfed wheat production systems co-exist. In the light of climate change the comparative assessment of the two systems regarding productivity and sustainability is of urgent importance. This paper aims to contribute to a more informed debate on the viability of irrigation in marginal crop production regions. For this purpose, the present study investigates productivity and environmental impact of 540 wheat producing farm households (259 irrigated; 281 rainfed) in Golestan by partial life cycle assessment (LCA) methodology using greenhouse gas (GHG) emissions and product carbon footprint (PCF) as environmental sustainability indicators. The study finds huge heterogeneity among wheat producers with regard to yield, GHG emissions and PCF. Comparing irrigated and rainfed production showed that irrigation in average leads to 22% higher yields. However, the environmental impact of irrigated production is disproportionally high leading to 110% higher GHG emissions and 62% higher PCF, which highlights the trade-off between productivity and environmental sustainability. The major contributors to total GHG emissions of wheat production are energy for irrigation (only in irrigated production), N 2 O emissions related to fertilization and residue handling, diesel for machinery, and emissions related to fertilizer production and transport. Increased GHG emissions and PCF in irrigated compared to rainfed production are not only attributed to the energy required for irrigation, but also to increased fertilizer and other production inputs. Splitting the farmers into high, medium and low yield groups indicates the potential for increasing yields through increased input intensity without negative effects on PCF. The study's results demonstrate the potential of better balancing the trade-offs between productivity and sustainability of wheat production in marginal wheat production regions of the world. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) Panels, one of the more promising renewable energy technologies, are growing rapidly nowadays, especially in developed countries. However, these systems have not achieved public acceptance in some countries due to low energy efficiency and poor economic performance, especially in countries which are subsidized in energy tariffs. In this paper, the energy and economic performance of fourteen rooftop PV systems with the power of 5 kW in the hot and dry climate of Iran are assessed by monitoring the total annual energy production and simulation. The monitored data is used to analyze systems’ economic performance via Pay-Back Period (PBP), Net Present Value (NPV), Return of Investment (ROI) and Levelized Cost of Energy (LCOE). Results show that single array configuration systems have the maximum energy production while dividing the system decreases the production. Economic analysis shows that the average PBP is 11.6 years under actual price of electricity (0.21$), however it is 46.9–50.5 years under subsidized average tariffs. ROI values range from 2.6 to 3.2 with the average of 2.9 for actual prices. Under subsidized prices, the cash generated by investment cannot even offset the costs that the investment requires during its lifetime with NCF and NPV being both negative. Overall, the systems are not economically beneficial under subsidized average tariffs in Iran, which discourages private and public sectors to investment on these systems. Environmentally, each PV system can averagely reduce 500 kg CO 2 emission in the first year of installation and fourteen of them can approximately reduce 1,613,900 kg of CO 2 emission during life time of PV panels. [ABSTRACT FROM AUTHOR]

The aim of this paper is to provide a solution to decrease water consumption in the slab-cooling unit of Mobarakeh Steel Complex in Iran. The plan should give an hourly decline in water consumption during a one-year operation period to calculate the annual reduction in water consumption of the proposed process. Recommended solutions for the conversion scheme of an existing wet cooling tower to a dry or hybrid cooling system require modeling of the slab cooling process. The curves of temperature drop in slabs are extracted in this paper by modeling the transient heat transfer of the slabs in the cooling process. This will reduce the computational volume. Then, the design and optimization of the hybrid cooling system done by the Genetic Algorithm (GA) is investigated. Accordingly, the objective function (reducing the costs of construction, operation, waste of water during the year) is chosen by single-objective method, and the modeling of the series hybrid system is done for the off-design mode during one year. The present design is for different scenarios and various savings of water consumption. The results demonstrate that if the control system is fitted with the sensitivities of the ambient temperature and also is based on the water consumption reduction and equipment design according to reliable standards, then the annual water consumption will be reduced by 88.3% (1.89 million m3). The payback period will be 3.63 years for the proposed system. • Numerical modeling of slab cooling process in transient cooling. • Extraction of the outlet water performance map to model the hybrid in off-design. • Modeling of off design air cooler control system and wet cooling tower. • An overview of hybrid system during the year based on an optimized design. [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]

The optimal siting of wind farms is a multi-attribute problem, and different objectives and constraints like economic, environmental, social, and technical should be taken into account. The widely-used category of site selection methods, multi-criteria decision making (MCDM), suffers from local scoring despite its numerous advantages. In this paper, support vector regression (SVR) is implemented to add the global scoring capability to MCDM by using a global-scale span of decision criteria. Here, the weighting of the decision criteria is obtained by the analytic hierarchy process (AHP), and then an SVR is utilized to appoint a score to any candidate site location. The proposed procedure has been used to study potential wind sites in Iran. In this regard, the study was conducted through three scenarios based on the natural and artificial potential of candidate sites. This study reveals that there are several vast areas, especially in eastern Iran, having high wind power density and flat terrain that are ready to be utilized as an endless source of clean energy provided that proper investment is made in power transmission lines and road networks. [Display omitted] [ABSTRACT FROM AUTHOR]

Iran's energy consumption is constantly and rapidly increasing. Due to the country's geographical placement on the Sun Belt of the Earth, there is a great potential for photovoltaic (PV) energy to be used; however, it necessitates an evidence-based selection of appropriate locations to develop solar farms. In this paper, we used a new approach to prioritize potential PV plant sites employing geographical information system (GIS)-based Fermatean Fuzzy (FF) TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution). We considered economic, geographic, climatic, infrastructures, and demographic criteria in GIS-based FF-TOPSIS and compared outputs with earlier versions of the TOPSIS method (crisp and triangular fuzzy numbers (TFN)). Although all three versions indicated high correlations of >0.89, 20.88% of pixels' priority differed depending on the chosen method's logic. Regarding the sensitivity analysis, the GIS-based FF-TOPSIS in terms of criteria's weight was substantially more resistant to uncertainty than the TNF-TOPSIS. Besides, the GIS-based FF-TOPSIS has rational sensitivity (i.e., tolerance) to the accuracy of input data. The GIS-based FF-TOPSIS method demonstrated sensitivity or robustness depending on the degree of uncertainty in the numbers, which can be altered depending on the expertise and mastery of experts. Our findings indicated that approximately 13.81% of the entire country has the potential for solar power plants. According to the results of the GIS-based FF-TOPSIS approach, the provinces of Sistan and Baluchestan, Hormozgan, Fars, and Khuzestan have the largest potential for solar power farms in Iran. • Prioritizing potential areas to localize solar farms on a national scale. • Evaluating GIS-based TOPSIS with and without considering fuzzy principles. • Integrating Fermatean fuzzy sets (FFs) concept with spatial data and GIS concepts. • Proposing a GIS-based FF-TOPSIS as a practical method for uncertainty conditions. [ABSTRACT FROM AUTHOR]

The aim of this study is to perform a life cycle and energy flow assessments of Municipal Solid Waste (MSW). These latter are modeled using Artificial Neural Network (ANN) for integrated waste management system in Tehran Municipality, Iran. The initial data used in this study have been obtained from Waste Management Organization of Tehran Municipality, while the required data related to the background system were extracted from the EcoInvent 2.2 database. Based on the obtained results from the energy cycle analysis, energy consumptions for transportation and processing plus recycling were calculated as 227.02 and 155.95 Gigajoules (GJ), respectively for 8500 t MSW. This energy consumption has led to the production of 18,884.03 GJ energy output (recycled materials) with an energy ratio of 121.56. A high energy ratio demonstrated that recycling of municipal solid is a new gateway against energy challenges. By optimizing energy consumption, especially energy related to transportation, this ratio could increase more than before. The results obtained from Life Cycle Assessment (LCA) indicate that transportation is considered the most important hot spot in the recycling of MSW while recycling papers is the main contributor to the redaction of environmental indicators in the recycling system. More intensity is observed for indicators related to toxicity due to the lack of waste disposal and to the entry of undesirable substances in natural resources. The 5-7-7-11 structure is the best topology to predict the amount of recycled materials and the impacts of environmental emissions from MSW recycling process developed by feed-forward back-propagation ANN models which are based on Levenberg-Marquardt (LM) training algorithm. Coefficient of determination values for train are in the ranges of 0.926–0.978 and have excellent performance in predicting all the output parameters based on the input parameters. [ABSTRACT FROM AUTHOR]

This paper develops a theoretical background of the inverse DEA with pollution generating technology that is capable of dealing with undesirable outputs. Interaction between input, desirable output, undesirable output and environmental efficiency is investigated for industrial sector of Iranian provinces. Five scenarios are designed to perform this aim and construct a gradual planning scheme for short to long run CO 2 reduction. The following results are found. There exit a high potential of saving capital in short and mid and long-run from 80% to 150% in total. Province P8 and P5 are found as the most effective provinces in terms of saving inputs (labor and capital) in proposed scenarios. No labor reduction is suggested for a short run or for a long run in total, approximately 7%–160% extra labor is needed in the planning period. Some provinces face with infeasibility problem in the planning scheme especially in period on CO 2 reduction. The tightest scenario in terms of CO 2 reduction requires both extra labor and capital while reducing undesirable output and expanding desirable output. [ABSTRACT FROM AUTHOR]

In recent years, society and many organizations have been paying increasing attention to the social responsibilities of organizations towards various stakeholder groups. To ensure the fulfillment of social responsibilities of organizations towards society, corporate social responsibility should be embedded in day-to-day operations and managerial decision-making. Total quality management is also a commonly used managerial tool that takes into considerations the interests of various stakeholder groups. This paper investigates how the relationship between corporate social responsibility and total quality management affect the organizational performance measured by the Balanced Scorecard (BSC). The results of the analysis, using structural equation modeling on 933 completed questionnaires sent to the pharmaceutical companies in Iran, suggest that social responsibility is significantly associated with the integration of this responsibility into quality management programs. Quality management, in turn, has a significant and positive effect on organizational performance. The results provide contribution to the earlier studies that have found inconsistent results on the direct association between social responsibility and organizational performance by demonstrating that quality management mediates the relationship between social responsibility and organizational performance. In practice, Managers can strengthen their relationships with stakeholders and, ultimately, improve organizational performance if social responsibility towards stakeholders is embedded in operational routines and processes. [ABSTRACT FROM AUTHOR]

Rapid changes and evolution in technological innovation have spilled over many industries and compelled firms to release new products periodically. The advent of new products intensifies the importance of analyzing sales data trends and finding the most profitable portfolio that can no longer be ignored in production planning. The topic of diffusion processes has evoked considerable interest from academics and practitioners to forecast sales patterns of two or three competitive generations. However, there is still a lack of in-depth discussion on the effects of core determinants on customers' preferences and choices. This paper bridges the gaps in the literature by conceptualizing the interaction effects among current and new products on diffusion processes that could affect supply chain operations. Specifically, the Bass diffusion model (BDM) is modified to estimate market volume, advertisement effects, and sales data trends, then combined with a choice model to examine how consumers' propensities affect the choice probability of alternatives. The proposed choice-based diffusion model is incorporated into a supply chain problem for joint planning on a production-location-inventory problem concerning the economic and social aspects of designing multi-generation production lines. The model formulation is a bi-objective mixed-integer nonlinear problem with a computation burden. Thus an outer approximation-based algorithm is proposed to reduce computational complexity and combined with an augmented ε -constraint to generate efficient Pareto sets. The model is validated by conducting a case study in Iran and compared to other established models. The computational results demonstrate the proposed model outperforms the expert forecasts, and there are no significant differences between the total sales estimated by the proposed model and the actual sales. The manager is advised to adopt a conscious policy for adoption engagement under supply constraints. It should price the products in a way be more tightly aligned with customers' desirability and overcome the supply constraints by increasing production or storage capacities. • A bi-objective optimization approach is applied to design and plan multi-generational products. • A novel choice-based diffusion model is proposed for demand forecasting. • The proposed non-convex model is transformed into a convex problem and solved by an outer approximation-based algorithm. • Model verification is done by conducting a case study in Iran. [ABSTRACT FROM AUTHOR]

Recently, the closed-loop supply chain (CLSC) domain has garnered considerable attention from scholars and practitioners. The increasing number of publications makes it necessary to study this domain comprehensively. To achieve this goal, this paper makes the first attempt to investigate the knowledge base and knowledge diffusion paths of the whole area systematically from both static and dynamic perspectives. Based on 1041 papers published in 2001–2020 from Web of Science, the characteristics of publications, productive authors, institutions, countries/territories and journals, as well as the co-authorship relationships are investigated by using bibliometrics. In addition, the evolution of hot topics and the historical development of CLSC domain are vividly described by keyword analysis and main path analysis respectively. The results show that: (1) Van Wassenhove, LN, Guide, VDR and Govindan, K play an important role in this domain and in addition Govindan, K has established extensive cooperative relationships; (2) INSEAD and Penn State Univ are more influential and they cooperate closely; (3) Several countries such as Italy, UK, Iran and China have begun to pay more attention to CLSC research in the past five years; (4) the hot topics revolve around the three aspects of network design, coordination and circular economy, and the trajectories of knowledge diffusion of this domain show that the focus has shifted to the green and sustainable CLSC recently. This study is able for researchers to grasp the general information, identify hot topics and capture history, development status and possible directions for the future research in the CLSC domain. • 1041 papers from Web of Science in closed loop supply chain (CLSC) domain are analyzed. • Bibliometrics and main path analysis are adopted to study the overall development of the CLSC domain. • The hot topics revolve around network design, coordination and circular economy. • The network design of CLSC is the main concern in the process of knowledge dissemination. • The influence of government policies on the CLSC in the e-commerce environment is attractive recently. [ABSTRACT FROM AUTHOR]

Globally, most industrial parks that have not gone through a proper site selection process have been neglected or underutilised and such active sites tend to burn a lot of fuels and generate greenhouse gases. Technology must be used to conduct on-site investigations of the spatial and non-spatial factors of industrial parks, especially the emerging Eco-Industrial Park (EIP). The paper seeks to appraise the global application, capability and acceptability of Geographic Information System (GIS) and Multi-Criteria Decision-Making (MCDM) tools in the EIP sites selection and planning. Also, to identify the benefits of mixing MCDM tools when integrating with GIS. There have been some reviews on the use of GIS and MCDM methods, but so far, there is none on the role of GIS and MCDM methods in EIP site selection. Geospatial and MCDM tools can be used to carefully select EIP sites, where materials and energy can be shared to achieve cleaner production, reduce environmental pollution and promote sustainable development. To understand the usage of these tools and their role in the EIP site selection process, a critical review of twenty-two papers published from 2007 to 2020 indexed by Google Scholar, Springer, IEEE Xplore and Web of Science have been developed for the first time. The articles are classified based on country/region, journal of publication, year and citations of publication, the authors and technologies applied. The results show that most studies on EIP site selection come from Iran and China. The Journal of Environmental Monitoring and Assessment has the highest number of articles published at 28%. The highest number of articles was published in 2014 with 312 citations. GIS and Analytic Hierarchy Process (AHP) topped the technologies used, accounting for 42% and 24% respectively, and hybrid tools 34%. As categorised by criteria content, there was an overlap of criteria in most journals. Though, water bodies, utilities, infrastructure, and natural characteristics were prominent. Renewable energy resources were not given attention by most researchers, and risk assessment was absent from the site selection literature. A blend of traditional MCDM tools constitutes the state-of-the-art tools, and when these are combined with GIS in EIP site surveys, they execute to obtain actual results. Future EIP site selection that is integrated with risk assessment is envisioned to be industry 4.0 (4IR)-driven through a combination of GIS and artificial intelligence, and the recently developed MCDM hybrid modules. [Display omitted] • Poor site selection has led to industrial park being neglected or underutilised. • Abandoned/underutilised active industrial parks can burn fuels to cause GHG. • First time of critical review of role of GIS and MCDM tools in EIP site selection. • GIS and AHP currently mainly used for large-scale EIP site criteria selection. • EIP site choice risk study using GIS, AI and MCDM hybrid can sustain industry 4.0 [ABSTRACT FROM AUTHOR]

In recent years, research has shown a growing interest in the use of hybrid wind photovoltaic (PV) systems that provide better performance compared to the use of a single component due to complementarity in meeting electricity demand. Over the past twenty-five years, hundreds of articles have addressed the topic of hybrid systems considering different configurations and final uses and, over the past decades, many reviews have made a comprehensive summary of various results obtained. However, some reviews deal with the research in a too general and qualitative way, without providing quantitative data, and other reviews are too focused on a specific topic aspect. To provide a qualitative-quantitative prospect of the research trend in the last twenty-five years, the present work is aimed at carrying out a literature review and statistical analysis starting from data extracted from the 550 most relevant and recent articles concerning hybrid systems, published between 1995 and 2020. The review aim was to produce an upgradable matrix literature database that schematizes the content of all articles in terms of different categories, such as the geographical distribution, their component configurations, operating mode and the auxiliary components used to support it, their intended uses and study methodologies (simulation, experimental, economic, energy, environmental and social analysis etc.) and software used. In addition, all the optimization algorithm, energy, economic, environmental and social indicators available in the literature were extracted and elaborated to identify the most used. The 550 articles were analysed, compared, and classified into several categories to provide an overall framework of the state of the art. The objective is to clearly and appropriately show important trends and findings in the development of hybrid wind and solar PV experimental, simulation and optimization projects. Data are elaborated to obtain a statistical analysis for each category or a combination of categories. In particular, the analysis highlighted that research is more focused on testing systems in warm or temperate localities, with the Köppen climate groups B and C prevalent over the others. From the geographical point of view, Asia is the continent most involved in world research (with China, India and Iran the first three countries for total publications produced). However, also in other parts of the world, a growing interest was noticed in this technology. The prevalent tested system configuration mode is the stand-alone hybrid systems, in a wide variety of climates and especially for residential uses. Simulations are mostly implemented in the analysed publications, mainly through HOMER and MATLAB software. Parametric analysis is widely used for optimal system design with a large variety of techniques. In particular, the system performance is examined mostly from an energy point of view. Economic analysis is also very common, alone or in combination with energy analysis. The most frequently used optimization algorithms are the particle swarm optimization (PSO) and genetic algorithm (GA), while the loss of power supply probability (LPSP) and renewable fraction (RE) for the energy analysis, the net present cost (NPC) and cost of energy (COE) for the economic analysis and the emissions (E) of CO 2 for the environmental analysis are most widespread indicators. Finally, an analysis on the size of the system components is performed to study which renewable source is more preferred at low and high installed power, for stand-alone, grid-connected systems and overall, considering different intended uses. The analysis highlights that PV systems are preferred at low installed powers, especially for residential use and stand-alone mode, while wind systems, in addition to being extensively used for low installed powers, demonstrates higher employment compared to PV systems as the power increases. The paper findings and upgradable matrix literature database are proposed as a valuable tool for engineers, experts and national and international policymakers. • 550 relevant papers were reviewed and used to create an upgradable matrix literature database. • Asia is the continent most involved in world research with Iran, India, and China. • The dry and temperate climate zones of Köppen climate group BWh are the most investigated. • Stand-alone hybrid systems and residential use are the most explored applications. • The use of photovoltaic system is preferred for low installed powers, while wind systems also for high installed powers. [ABSTRACT FROM AUTHOR]

Social innovations for sustainable consumption have attracted policymakers' attention internationally as a possible means to reach sustainability and climate change goals. So far, most of the research on the emergence and potential of social innovations has been carried out in the Global North. Consequentially, some theoretical approaches and concepts have not been reviewed critically for their applicability in other contexts. This paper explores similarities and differences in the emergence and development process of social innovations for sustainable consumption in different cultural and geographical contexts to fill this gap. The objective is to enrich current concepts with more context-sensitive categories. On this account, the paper undertakes an explorative qualitative cross-country analysis of innovations for sustainable consumption in diverse sectors, using a sample of 87 cases collected by desk research in Brazil, Germany, and Iran. The analysis is based on a procedural perspective on innovation and refers to the three phases problematization, experimentation, and restabilization. The research shows that, in the problematization phase, the initiatives differ in taking up "globalized" challenges affecting most countries worldwide versus "locally emerged" ones, more connected to socio-economic, cultural, or political specifics. Experimentation with possible solutions differentiates between "imported" versus "locally" invented or appropriated context-specific approaches. Forms and degrees of restabilization depend mainly on framings for start-ups or non-governmental organizations and the local government's openness for innovative approaches. Based on the manifestation of these characteristics, the analyses result in four different qualitative types. The identified categories complement existing typologies, which so far neglect the geopolitical scope of the addressed problems and the tested solutions. Further empirical analyses in different countries will show whether the identified categories and types are helpful for a better understanding of the emergence and development of social innovations for sustainable consumption in different socio-economic, geopolitical, and cultural contexts. • The analytical framework combines the phenomena of sustainable consumption with the three phases of the innovation process. • Social innovations for sustainable consumption differ in their reaction to global or local challenges. • The solutions to global and local challenges can be imported, locally invented, or appropriated context-specific approaches. [ABSTRACT FROM AUTHOR]

In this study, the efficiency of air cleaners in removal of chemical components of PM 2.5 (PAHs, heavy metals, and ions) in the indoor air of dormitories of Tehran University of Medical Sciences, Iran were assessed. 12 rooms were selected and randomly divided into two groups: sham air purifier system deployed room (SR) vs. true air purifier system deployed room (TR). 24-h PM 2.5 samples were simultaneously collected in both TR and SR on PTFE filter papers at a flow rate of 5 L/min. The results showed overall removal efficiency of 76.5 ± 15.5%, 63.1 ± 22.5%, and 66.2 ± 24.8% for PAHs, heavy metals and ions, respectively. Moreover, the fraction of positive ions decreased when air purifiers were used in the rooms. The results showed that the smoking is an important influencing factor on the indoor air quality; smoking can leads to reduction in removal efficiency of PAHs, heavy metals and ions by 26%, 40%, and 51%, respectively. An air purifier could decreased the PM 2.5 even lower than the WHO annual guideline level in non-smoker rooms. The present study revealed that use of indoor air purifiers can significantly reduce the risk of carcinogenicity and non-carcinogenicity attributed to heavy metals and PAHs, especially in places without a smoker. [Display omitted] • Efficiency of air purifiers (AP) in removal of components of PM 2.5 was investigated. • The results showed removal of 76.5%, 63.1%, and 66.2% for PAHs, metals and ions, respectively. • Smoking leads to efficiency reduction of PAHs, metals and ions by 26%, 40%, and 51%, respectively. • AP could decline the PM 2.5 even lower than the WHO guideline in non-smoker rooms. • AP can significantly reduce the health risks attributed to metals and PAHs. [ABSTRACT FROM AUTHOR]

The concentration on producing clean energy such as biofuels in recent years has had an impact on some of the natural resources that humans use, such as water, food, and land. In this paper, a two-phase approach to design and optimize a biofuel supply chain based on Jatropha Curcas L. oil and used cooking oil (UCO) is presented by considering the nexus between energy, water, food, waste, and land (EWFWL) in order to protect natural resources and create environmental security. In the first phase, the most appropriate sites for Jatropha cultivation are determined by considering the accessibility, geological, environmental and climatic criteria, using the Geographic Information System (GIS). In the second phase, a novel multi-objective model is designed considering the EWFWL nexus and solved using the Torabi-Hassini method. The model is validated using real data from Fars province, Iran, as well as a sensitivity analysis. In this study, some of main contributions are identifying suitable Jatropha cultivation sites in Fars province, Iran; development an innovative optimization model regarding EWFWL nexus; and considering financial parameters and global distribution along with EWFWL nexus. According to the results, the sale of biofuel to local and foreign consumers accounts for the largest proportion of network revenues, contributing for 59.25% of total revenue. Furthermore, increasing the use of UCOs for biofuel production will reduce Jatropha output, and consequently reduce water, land use, and increase food security. If UCO shortage occurs, more lands will be dedicated to Jatropha farms and food-loss and water consumption increase. By focusing on biofuel production over UCO, policymakers can produce less Jatropha and decrease the use of land for Jatropha cultivation. Furthermore, effluent-based irrigation can be more widely used to save fresh water by irrigating Jatropha farms. [ABSTRACT FROM AUTHOR]

Nowadays, one of the growing and remarkable branches of tourism is ecotourism. Ecotourism has a great impact on the development of a region from different perspectives. Hence, by improving and developing sustainable ecotourism in a region, it will be possible to develop and improve its economic, social, and environmental situation. The Lafour region is one of the potential hubs for ecotourism activities in Iran. Despite the high potential of this region for ecotourism activities, it has not yet achieved its suitable position in this domain. Hence, the main goal of this study is to develop sustainable goals for ecotourism in the region. To meet the target, first, the Strengths, Weaknesses, Opportunities, and Threats (SWOT factors) are identified through interviews with tourists, local residents, and the experts, filed observation, and considering similar works in the literature review. Then, some practical and useful strategies are determined based on SWOT analysis and consulting with the experts. The important point of the study is proposing an applicable heuristic clustering method based on SWOT analysis to classify the strategies into different clusters. To prioritize the strategies in each cluster, the commonly used Multi-Criteria Decision Making (MCDM) method called the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is applied. This paper concludes and reveals that the three strategies including ST6 "Encouraging investors and entrepreneurs to establish ecotourism centers in the region", ST5 "Establishing and improving the hygiene units and the medical clinics in the region", and ST3 "Improving and diversifying tourism services and products to attract tourists and increase their satisfaction" have the greatest impact on accomplishing sustainable development goals in the region. • The main goal of this study is to develop sustainable ecotourism in Lafour region, Iran. • The SWOT are identified by the help of interviews with tourists, tourism experts, ecotourism activists, local residents and academic experts. • Eight strategies are determined based on SWOT analysis and consulting with tourism experts. • A heuristic clustering method based on SWOT analysis is proposed and the strategies are ranked to different clusters. • The strategies in each cluster are prioritized by TOPSIS method. [ABSTRACT FROM AUTHOR]

Water plays a quintessential role in the lives of individuals and communities. In recent decades, population growth, migration from rural to urban areas, industrialization, and climate change have increasingly jeopardized the sustainability of cities, especially in developing countries, including Iran. The purpose of this study is to assess recent and future perspectives for urban water security in Iran. To do so, the paper extends previous water security studies within the region by collecting data on urban water security from a cohort of cities rather than a single location. To assess the state of water security in the recent past, from 2013 to 2019, we introduce a dedicated framework comprised of five dimensions and twelve indicators. In estimating future water resources for Iran in the period up to 2100, ensemble-based hydro-climatic regional climate model projections for RCPs 4.5 and 8.5 were analyzed in time and space. The results show that four of the five dimensions of present-day urban water security, including accessibility, availability, water health and sanitation, and the economic value of water, all demonstrate general improvements in water-related urban infrastructure, whereas the environmental indicator depicts a decreasing trend. Future projected trends for Iran's hydro-climate show a general decline in its net availability from already scarce conditions and also increased variability due to climate change. In general, the study indicates both advances in Iran's urban water security recently and severe implications for future water availability in certain regions and periods in the decades to come. The study also advises policymakers to seek to mitigate the water crisis in so far, as also enforced by climate change, by increasing the appropriate infrastructure and using new technologies in the water and wastewater industry. [Display omitted] • A new and recent data set on urban water security indicators in Iran was analyzed. • Twelve indicators formed the novel and combined urban water security index. • Four out of five water security dimensions showed progress during 2013–2019. • The urban water environment dimension showed a declining trend. • Projected future water recourses in Iran is under increasing pressure towards 2100. [ABSTRACT FROM AUTHOR]

High specific energy consumption (SEC) and its high cost of manufacturing are among the main problems in the hydrogen liquefaction industry. In this paper, an integrated structure for liquid hydrogen production using liquid air energy recycling, fuel cells, carbon dioxide power generation cycle, and photovoltaic (PV) panels is developed and exergetically assessed. To liquefy the hydrogen gas are utilized six compression refrigeration cycles with hydrogen and helium refrigerants. The compressed liquid air is used for the precooling of the hydrogen liquefaction process. After the cold energy recovery from liquid air, it is heated by the waste heat load of the refrigeration cycle and solid oxide fuel cell (SOFC) and then enters the gas turbine and fuel cell, respectively. The fuel cell output hot stream is used to supply heat to the power generation cycle and preheat the fuel cell inlet stream. This integrated structure generates 1,028 kg/h liquid hydrogen by receiving 60.79 kg/h natural gas and 5.559 MW power from solar panels under the climatic conditions of Yazd, Iran. The specific energy consumption of the hydrogen liquefaction process, SOFC efficiency, and carbon dioxide power generation cycle efficiency are obtained as 5.955 kWh/kgLH 2 , 62.96%, and 44.06%, respectively. Integrating the refrigeration structure with the process core is performed in the form of hot and cold composite diagrams. The exergy assessment indicates that the highest exergy destruction occurs in solar panels (81.37%), heat exchangers (7.60%), and turbines (4.73%), respectively. The sensitivity analysis demonstrates that the integrated structure exergy and SOFC efficiencies decrease to 52.9% and 62.3%, respectively when the inlet liquid air mass flow rate increases from 7,400 kg/h to 10,200 kg/h. The power supplied by solar panels and SEC of hydrogen liquefaction process increase up to 5,599 kW and 6.1 kWh/kg LH 2 , respectively with a decrease of pumped liquid air pressure from 80 bar to 40 bar. [Display omitted] • A novel integrated structure for the generation of liquid hydrogen was developed. • Integrated liquid hydrogen, liquid air cold energy recovery, fuel cells & CO 2 power cycles. • Solar panels under the climatic conditions of Yazd city in Iran were used. • System produced 1028 kg/h LH 2 by receiving 60.79 kg/h natural gas & 5.559 MW power. • SEC and exergy efficiency of the system were 5.955 kWh/kgLH 2 & 0.5322, respectively. [ABSTRACT FROM AUTHOR]

Water scarcity is increasing worldwide due to population growth and climate variability/change. As a supplementary water resource, Rainwater harvesting (RWH) is a possible solution for dealing with water scarcity, particularly in arid and semi-arid regions with considerable water demand and high variability in precipitation and unexpected extreme events (floods and droughts). The success of RWH systems significantly depends on the location of RWH structures and usually selecting suitable sites is challenging for decision-makers and managers. This paper presents an approach for mapping suitable sites for RWH structures using socio-environmental variables and artificial intelligence algorithms (AIAs). Based on FAO recommendations, the most important conditioning variables for RWH systems are elevation, slope, aspect, precipitation, temperature, distance from the river, curve number (CN), land use, geology, soil type, population density, distance from road, and distance from lakes. An ensemble model was developed based on AIAs, socio-environmental variables, and existing RWH projects, and used for RWH suitability mapping in the large Maharloo-Bakhtegan basin, Iran. Model performance was evaluated using receiver operating characteristic (ROC) and Kappa index. Using the best-performing model, threshold values for conditioning variables were determined from probability curves (PC). The results showed that land use, precipitation, soil type, CN and slope were the most important variables for RHW sites, with the lowest correlation and autocorrelation. The suitability map indicated that 9.7% (3070 km2) of Maharloo-Bakhtegan basin had very high suitability for RWH systems. Thus, in RWH suitability mapping for large area, climate, hydrological, geological, agricultural, topographical, human and socio-economic parameters should be considered to enable efficient RWH planning. Probability curves revealed that the optimum parameter range (α) in Maharloo-Bakhtegan basin was precipitation 357–428 mm, temperature 12.80–15.16 °C, slope 3–6%, elevation 1612–1975 m asl, distance from lake 32–45 km, distance from river 11.4–15.9 km, distance from road 2.59–4.80 km. The RWH suitability map presented can assist decision-makers, hydrologists, and natural resources planners in finding suitable locations for constructing RWH systems. [Display omitted] • Large-scale rainwater harvesting (RWH) was planned using socio-environmental data. • An ensemble model was developed based on AIAs in RWH planning. • Land use and precipitation were major factors in RWH planning. • New probability curves and optimum variable ranges are presented for RWH systems. • RWH suitability mapping confirmed data reliability without expensive field surveys. [ABSTRACT FROM AUTHOR]

Carbon dioxide utilization (CDU) is one of the most critical approaches in climate change control. CDU's future depends on the future demand for carbon-derived products; among them, formic acid is an excellent candidate due to its distinctive characteristics as a hydrogen carrier in liquid form. It is non-toxic that can be used in hydrogen fuel cells, and its significant potential in the heavy oil and biofuel refining process as a hydrogen-carrier substance. This research aims to use Energy, Exergy, Exergoeconomic, and exergoenvironmental (4E) analysis to evaluate the impact of anolyte material on the efficiency of the electrochemical reduction process to synthesis formic acid (in the term of six new anolyte materials). Results show that the second scenario (IrO 2 single circulation mode) is the best option for the power plant. Implementing this CDU system reduces the carbon capture of about 75.20 kg/s or about 89% of the power plant's overall carbon emission. This process's energy penalty can be adequately provided by the PV, which causes greater exergy efficiency and decreases the power plant's energy performance rate. Moreover, the use of IrO 2 anolyte is decreased the exergy rate cost and the flow rate cost to the 0.21 $/kWh and 2.280×10-2 $/s. The CDU's investment cost using the DSA/O 2 anolyte is 28% decreased compared to the KOH anolyte and reached 7.2 million USD for the CO 2 utilization plant. [Display omitted] • Iran is the 8th Carbon dioxide producer in the world with great potential for carbon capture. • CDU is an option to be combined with the carbon capture process to reuse the Carbon emission. • In this paper, six anolyte for the ER process are compared, and the IrO 2 is selected as the best option. • Implementing the IrO 2 on the ER process results in 89% of emission reduction and also producing 79.7 kg/s formic acid. • Considering the capability of the FA as a hydrogen carrier and Heavy oil refining material, this product can be used in the petrochemical refineries. [ABSTRACT FROM AUTHOR]

Sustainable development programs rely on implementing energy policies in different sectors of a society. As far as agriculture sector is concerned, this paper intends to evaluate the current energy consumption and the potential for renewable energy programs' deployment in regional scale. The candidate region is Iran's Caspian Sea coastline. The assessment is modeled by recent multi-criteria decision analysis approaches, i.e. Level Based Weight Assessment (LBWA) with Weighted Aggregated Sum Product Assessment (WASPAS). The proposed index was designed so as to cover conventional and non-conventional energy resources subjects simultaneously, for instance: (1) biomass production, and (2) natural gas and diesel fuel at state level. From methodology point of view, the traditional WASPAS method is enhanced by the integration of the Weighted Power Heronian (WPHA) and Weight Geometric Power Heronian (WGPHA) functions. Application of these functions enables the elimination of the influence of extreme and unreasonable arguments in initial decision-making matrix. In addition, the interrelations between attributes is considered in the proposed model, that is particualrely appropriate for decision making in dynamic systems. The model capability in decision making has been investigated by comprehensive sensitivity analysis that implies in Iran's Caspian Sea coastline, Mazandaran state ranks first, followed by Guilan and Golestan. The result is suitable for policy makers and regional managers to define proper plans and actions in sustainable development of Caspian Sea coastline based on both agriculture-based energy efficiency as well as bio-based energy potential. [ABSTRACT FROM AUTHOR]

Direct reduction of iron process in steel industry has special production conditions. Low quality cooling water, low cold and high hot cooling water temperature, space limitation for new equipment installation, high value-added of product and severe effect of cooling water temperature on production rate are of these conditions. Considering technical and economic constraints and limitations, this situation makes this process an attractive case study for converting the existing wet cooling tower to hybrid cooling system. In this paper, based on integration of process, dry and wet cooling system and ambient conditions profiles, a new method for designing hybrid cooling system has been proposed. The calculation program has been developed as a MATLAB code and resulted: 1) Calculation of annual water saving and energy consumption with reasonable accuracy, 2) Control system of dry and wet cooling blocks to maximize water saving under various ambient conditions, 3) Closed loop simulation of cooling system considering thermal feedback of process to cooling system and 4) Obtaining optimum values for 16 design parameters of dry block cooling (consisting air cooled heat exchanger and plate heat exchanger). The optimization has been done via genetic algorithm, considering annual response of each design under various ambient temperature and relative humidity. Considering design standards for new equipment and operational and technical constraints, made the optimization model reliable as well as checking the design parameters with process equipment constructors. In optimum point, converting existing wet cooling tower to hybrid cooling system in direct reduction of iron plant of Mobarakeh Steel Complex located in Isfahan province in Iran, will decrease the annual water consumption by 70.15% and production loss by 98% with payback period of 1 years and 10 months. [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]

Industrial Symbiosis (IS) is a means for sustainable cluster development. The first consideration for implementing IS in a cluster is to identify technical opportunities for exchanging waste material and or energy. However, the definition and methods for assessing the technical potential of IS are not elaborated in the literature. This research proposes a method to evaluate IS potential that considers different system boundaries. The method allows for explicitly reflecting current and expected developments at plant and cluster level. The suggested method was applied to the Persian Gulf Mining and Metals Special Economic Zone (PGSEZ) in Iran. The case study shows that expanding the system boundaries to include the waste flows inside steelmaking and direct reduction plants could result in an 8% increase in available waste heat. Heat recovery possibilities outside the cluster boundaries offered 118 MW cooling plus 368 MW heating potential compared to 158 MW demand for electricity in the cluster. Furthermore, less than 20% of generated by-products could currently be reused in the cluster, while theoretically all by-products could be utilized today in other industries such as cement and ceramic. These findings support the use of IS as a way to open new perspectives for EIC development policies. • This paper proposes a method to assess the technical potential for IS. • This study adds value to the IS field by addressing the overlap between IS and process integration. • Examining the waste flows before processing for disposal could reveal higher energy exchange sources. • IS approach could open further potentialities for cluster development. [ABSTRACT FROM AUTHOR]

Due to the significant effects of CO 2 emissions on climate change and global warming, as well as its serious hazards to human health, the prediction of CO 2 emission is a vital issue. The main aim of this paper is to evaluate the power of the Inclusive Multiple Model (IMM) as a novel approach to predict CO 2 emission in the agriculture sector of Iran. For the same, we implemented the environmental Kuznets curve (EKC) specification and data from 2003 to 2017 for 28 provinces of Iran. In the first level, various specifications were implemented for each of the Multiple Regression (MLR), Gaussian Process Regression (GPR), and Artificial Neural Network (ANN) models. In the second level, an IMM model was implemented for treating the outputs of the best specification out of the MLR, GPR, and ANN models as inputs to an ANN model. The performance of the models was compared with the Taylor diagram and innovation and unique graphs. Findings indicated that the IMM model with C C = 0.81 , RMSE = 0.69, the highest residuals between −5 and 5 (37.84%), and the lowest distance from observation points (1.857) estimated CO 2 emission values more precisely. These improvements indicate that there are possible directions for future research activities. Due to the most accuracy of the IMM, it is recommended to use this method to predict CO 2 emission to adopt appropriate policies for reducing air pollution. Image 1 • We developed Inclusive Multiple Model (IMM) as a novel approach to predict CO 2 emission in the agriculture sector of Iran. • We utilized Environmental Kuznets Curve (EKC) hypothesis literature to predict CO 2 emission. • We used the Taylor diagram with distance and new graphs to determine the most accurate model. • A measure of income inequality could improve results in investigating EKC. • The IMM was the most accurate model according to all of performance metrics and diagnostic graphs. [ABSTRACT FROM AUTHOR]

In this paper, a solar site selection problem motivated by a real-world case study to determine sustainable locations for establishing solar sites in the east of Iran is addressed. For this purpose, a hybrid multi-criteria decision-making (MCDM) approach is proposed that adopts best-worst method (BWM) to weight criteria and sub-criteria extracted from literature and applies grey relational analysis (GRA) and VIKOR to rank potential locations. Moreover, an innovative Monte Carlo simulation-based (MCSB) approach is applied to analyze sensitivity of GRA and VIKOR. In this approach, two functional measures of robustness are introduced in order to compare performance of the methods. Based on the obtained results, some criteria, including construction cost (0.125), initial investment (0.166), ecosystem destruction (0.103), solar radiation intensity (0.085), and distance to catchment basins (0.084) have considerable importance because their weight is more than the average amount of global weights (0.0625). Furthermore, Birjand, Sarbisheh, and Khezri are the best locations for establishment of solar sites. Based on the proposed MCSB approach, VIKOR has higher robustness than GRA in the both functional measures. From the perspective of renewable energy development in Iran, the proposed approach can be recommended to be applied in other provinces of Iran for finding the best locations for solar sites. [ABSTRACT FROM AUTHOR]

In this paper optimal and cost-effective design of a photovoltaic/wind turbine/fuel cell (PV/WT/FC), the renewable energy system is proposed with the objective of lifespan cost of hybrid system (LSCS) minimisation and considering reliability constraint as a maximum of load interruption probability (LIP) as LIPmax to supply the demand of residential-commercial centres (RCC) located in Iran based on real data of irradiance and wind speed of this region. A new hybrid meta-heuristic algorithm named hybrid grey wolf optimiser-sine cosine algorithm (HGWOSCA) based on the exponential decreasing function (EDF) with high accuracy and speed of optimisation in achieving to the global solution is applied to determine the optimal size of system components. The superiority of the proposed HGWOSCA is compared with SCA, GWO and particle swarm optimisation (PSO) methods in designing of different combinations of the hybrid system and under varying reliability constraint. The results showed that the PV/WT/FC combination is the best combination in view of LSCS and LIPmax for supplying the RCC as a cost-effective and reliable combination. The superiority of the HGWOSCA in designing different combinations of the hybrid system is proved with fewer LSCS and LIP than the other methods with more convergence speed and accuracy. The results clearly showed that the use of hydrogen storage as a reserve power has well compensated the fluctuations in renewable sources production for meeting the RCC load to achieve optimal reliability. The results cleared that the cost of per kW of RCC supply for LIPmax = 1% and LIPmax = 5% is 0.853 and 0.764 $. The results indicated that increasing the failure rate of the components increases the system cost and weakens the reliability. In addition, the results showed that increased FC efficiency has reduced the level of reserve hydrogen, reduced the LSCS, and improved reliability. [ABSTRACT FROM AUTHOR]

Economic, social, and demographic development has globally led to an increased demand for water, consequently forcing some countries to face the shortage of water resources. In Iran, the problem of water scarcity is such a serious challenge that the sustainable allocation of water resources is sought after so as to help deal with this crisis. To this aim, the present paper proposes a new Robust Fuzzy Stochastic Programming model for the allocation of water resources. For the first time in the literature of stochastic water allocation problem, we applied the sustainability index to the optimization model and considered different levels of groundwater in an allocation system. Another feature of this model is its capability in considering a hybrid uncertainty in the parameters of the model, i.e. fuzzy stochastic scenarios, in a robust fuzzy stochastic programming model. Our proposed model considers three objective functions, namely maximizing the profits of different consumption sectors, minimizing the loss of different sectors caused by water shortage in different scenarios, and minimizing the allocation of salt water from ground water. The model has been applied in Mashhad city, northeastern Iran, which has long had water scarcity as an issue. We studied the allocation of water from surface, ground, and recycled wastewater resources to the three sectors of agricultural, municipal, and industrial; the results indicated that water allocation patterns and water shortages were affected by different scenarios. In fact, the municipal and agricultural sectors did not face water shortage in all scenarios, whereas the industrial sector encountered water scarcity in a drought year. Moreover, the assessment of optimality and feasibility robustness of the model indicated that the proposed model is robust. [ABSTRACT FROM AUTHOR]

Cross-docking practice plays an important role in improving the efficiency of distribution networks, especially, for optimizing supply chain operations. Moreover, transportation route planning, controlling the Greenhouse Gas (GHG) emissions and customer satisfaction constitute the major parts of the supply chain that need to be taken into account integratedly within a common framework. For this purpose, this paper tries to introduce the reliable Pollution-Routing Problem with Cross-dock Selection (PRP-CDS) where the products are processed and transported through at least one cross-dock. To formulate the problem, a Bi-Objective Mixed-Integer Linear Programming (BOMILP) model is developed, where the first objective is to minimize total cost including pollution and routing costs and the second is to maximize supply reliability. Accordingly, sustainable development of the supply chain is addressed. Due to the high complexity of the problem, two well-known meta-heuristic algorithms including Multi-Objective Simulated-annealing Algorithm (MOSA) and Non-dominated Sorting Genetic Algorithm II (NSGA-II) are designed to provide efficient Pareto solutions. Furthermore, the ε-constraint method is applied to the model to test its applicability in small-sized problems. The efficiency of the suggested solution techniques is evaluated using different measures and a statistical test. To validate the performance of the proposed methodology, a real case study problem is conducted using the sensitivity analysis of demand parameter. Based on the main findings of the study, it is concluded that the solution techniques can yield high-quality solutions and NSGA-II is considered as the most efficient solution tool, the optimal route planning of the case study problem in delivery and pick-up phases is attained using the best-found Pareto solution and the highest change in the objective function occurs for the total cost value by applying a 20% increase in the demand parameter. • Developing a novel bi-objective MILP model to integrate reliable PRP and CDS. • Studying the effects of traffic conditions in transportation and pollution emission. • Designing high-quality algorithms including NSGA-II and MOSA to solve the problem. • Applying the Taguchi design method to enhance the performance of the algorithms. • Evaluating the applicability of the proposed methodology using a case study in Iran. [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]

This paper brings together the benefits of a membrane-thermal desalination plant with an integrated system containing parabolic trough collectors and wind turbines in collaboration with the electrical network to produce power and freshwater. This proposed cogeneration system was employed for providing power and freshwater in Chabahar in Iran by three types of desalination system consist of the Reverse Osmosis (RO), Multi-effect distillation (MED), and Thermal Vapor Compression (TVC). Through this novel system, the heat generated in the parabolic trough collector is transferred into the organic Rankine cycle (ORC) to produce power. So, the generated power of the organic Rankine cycle and an auxiliary wind turbine can employ by the Reverse Osmosis unit, and the surplus amount of the electricity can sell to the electrical network. This configuration is enabled to increase the stability of the system, and it ultimately reduces the cost of water production by 23%. Besides, the integration of Multi-effect distillation (MED) and Thermal Vapor Compression (TVC) systems enjoys the rejected waste heat from the condenser to increase the produced freshwater. The obtained results from exergy analysis demonstrated that the exergy destruction of the solar collectors and wind turbines contributed by 39.5% and 22.2%, respectively. The results of multi-objective particle swarm optimization reveal that the exergy efficiency and the cost of freshwater production reach to 26.2% and 3.08 US$/m3, each. The environmental assessments of this system demonstrate that this hybrid system prevents the amount of 52164 tons of CO 2 emission per year. [ABSTRACT FROM AUTHOR]

Due to global warming and energy conservation, the importance of forests should be seriously considered. Forest could not only produce bioenergy by harvest to substitute fossil fuels, but also sequestrate carbon dioxide from the air without harvest. How to measure the trade-off between forests as bioenergy production and carbon sinks is the aim of this paper. The forest management for the trade-offs is modelled theoretically based on two perspectives of carbon reductions and benefits. The magnitude of trade-offs is calculated considering carbon reduction, ecological benefit, and economic benefit by empirical analysis based on the forestry database of 180 countries. The empirical results reveal that the magnitude of trade-offs is lowest in Iran both between carbon sinks and carbon flow from the perspective of carbon reductions and that between economic benefit and ecological benefit based on forest income. It implied the coordinated development of wood fuel and carbon sinks in Iran's forest management. Meanwhile, the magnitude of trade-offs is highest in Ecuador between carbon sinks and carbon flow, and it is highest in Tongo between economic benefit and ecological benefit. It showed that forest management should be improved. Furthermore, energy and environment policy implications could be proposed based on forest management. Effective forest management should be considered to help fully realize energy conservation and environment protection. Image 1 • The trade-off is explored which forest is as bioenergy production or carbon sink. • Trade-offs are modelled theoretically based on carbon reductions and benefits. • The magnitudes of trade-offs in 180 countries are compared. • Energy and environment policy implications could be proposed by forest management. [ABSTRACT FROM AUTHOR]

Climate change, increasing energy demand, and fossil fuel constraints have led to many plights regarding sustainable food and agricultural production. The purpose of this paper is to assess of exergoenvironmental aspects across different paddy production systems, including conventional (CS), low external input (LEI), and organic systems (OS) in Iran. Also, life cycle cost (LCC) and the emissions costs have been considered as a novelty for these scenarios. Data were collected through interviews from 213 paddy producers. Environmental life cycle damages were assessed by IMPACT 2002+ based on 1 ton of paddy yield as the functional unit. The findings revealed that diesel fuel followed by nitrogen had the most substantial role in the resource damage category of CS and LEI, while most values of OS belonged to diesel fuel followed by electricity. Furthermore, On-Farm emissions claimed almost the largest share among the other impacts categories in the surveyed systems. The cumulative exergy demand (CExD) analysis indicated that Non-renewable, fossil fuel was the main energy consumer. In this regard, diesel fuel was the most substantial part of energy forms for all three systems reducing the total CExD. The economic analysis showed that the lowest LCC was associated with OS; accordingly, the highest net profit belonged to OS, followed by CS. Overall, it can be concluded that the advantage of the OS scenario is evident for long-term management and planning in different environmental-exergy-economic indices of production systems. Image 1 • CS, LEI, and OS of paddy scenarios surveyed from LCA, CExD, and LCC viewpoint. • Emissions cost is considered in LCC analysis for mentioned scenarios as a novelty. • Hotspots environmental impacts were attributed to On-Farm emission and diesel fuel. • The lowest LCC and highest net profit belonged to OS. • OS was the exergoenvironmental-economical friendly amongst paddy systems. [ABSTRACT FROM AUTHOR]

As the destructive impacts of unbridled use of fossil fuels threaten the quality of life, moving towards renewable energy like solar power has precipitated. While such movements are commendable, environmental impacts of its infrastructure development should not be overlooked. In this sense, this paper addresses a multi-objective robust mathematical model to study an environmentally conscious solar photovoltaic supply chain under correlated uncertainty. The proposed model aims at minimizing the environmental impacts of included activities in the concerned supply chain in addition to minimizing the conventional cost objective. To quantify and assess the relevant environmental impacts, a life cycle assessment-based model is accomplished employing the ReCiPe 2008‏ approach embedded in the SimaPro software tool. The augmented ϵ -constraint procedure is deployed to optimize the proposed multi-objective model, which is able to attain compromise solutions from the Pareto-optimal set. Correlated uncertainty whose importance is underlined in the real-life situations of the photovoltaic industry is also tackled exploiting a robust optimization method. Ultimately, the validity of the presented model is vindicated through discussing a case study. The acquired results endorse the effectiveness and usefulness of the model and offer prominent practical and managerial insights. • An optimization model to study an environmentally conscious solar photovoltaic supply chain is presented. • To quantify the environmental impacts, a life cycle assessment-based model is performed. • The augmented ϵ -constraint procedure is deployed to optimize the proposed model. • The model is able to consider the correlated uncertainty of data. • The validity of the model is vindicated througha case study. [ABSTRACT FROM AUTHOR]

The use of energy from the sea wave to produce electricity via wave converters is one of the most interesting methods to meet the electrical demand in coastal cities. Hybridization of wave energy with other renewable resources, such as solar, wind, or storage systems, is a reliable way to generate and provide electricity for remote cities. Considering high solar and wind potential and accessibility to three marine areas, including the Persian Gulf, the Gulf of Oman, and the Caspian Sea, Iran is an appropriate place to exploit hybrid energy systems. In this paper, for the first time, a techno-economic and environmental analysis for a hybrid renewable energy system consisting of Wave Energy Converter/PV/Wind Turbine/Battery is performed aiming to provide electricity for 3000 households in three different locations of Iran (Jask, Genaveh, and Anzali cities). The results indicate that the PV/Wind Turbine/Battery system (with the energy cost of 0.219, 0.233 and 0.242 dollars per kWh for Jask, Genaveh, and Anzali, respectively) is the best option for supplying electricity for 3000 households. Furthermore, according to the sensitivity analysis, Anzali demonstrates a higher potential to employ Pelamis in the optimum system, owing to the higher potential of waves in the Caspian Sea. The cost of energy in the hybrid system with a Pelamis converter is obtained 0.233 $/kWh to 0.348 $/kWh. This indicates greater economic profit and higher power capabilities for off-grid systems, compared to the global cost of wave energy converter systems. Image 1 • Study of the hybrid system of Pelamis, PV, Wind turbine and battery in Iranian seas. • By reaching to 0.67 of current price, Pelamis can be an attractive solution in Iran. • Pelamis is a cost-effective unit for stand-alone hybrid power systems in the world. • The cost of energy for the Pelamis hybrid system is 0.233 $/kWh to 0.348 $/kWh. [ABSTRACT FROM AUTHOR]

In many inventory deterioration problems of real world, deterioration rate of some items may be affected by other adjacent items. Accordingly, the effect of deteriorated items on other items could be declined by removing them through inspection. In this sense, an inventory model for deteriorating items is introduced in this paper, considering the effect of inspection times during the replenishment period on average deterioration rate. Also, supplier is considered to impose some prepayments to the retailer. In the proposed model, the average deterioration rate is related to the number of inspections at each period. Likewise, to illustrate the uniqueness of the solution, the convexity of the model is proved. Moreover, the proposed model is validated by discussing and analyzing a case study in Iran through which noticeable results are achieved. The findings indicate that compared to previous models, the proposed model is superior in cost management. • The effect of deteriorated items on deterioration rate of adjacent items is studied. • A relationship between number of inspections and deterioration rate is established. • A distinct modeling of the holding costs of defective items is introduced. • The optimal cycle length and number of inspections is determined. [ABSTRACT FROM AUTHOR]

Sustainable development requires decision-making systems based on sustainability criteria and overpassing just economic and financial criteria. Integration of life-cycle cost analysis (LCCA) and life-cycle assessment (LCA) to select pavement alternative is a solution to address economic and environmental issues simultaneously. While most of current methods related to sustainable design of pavements consider environmental parameters as economic factors i.e. cost, this paper takes the two criteria of carbon emissions and energy consumption into account. Moreover the presented method considers the embedded managerial flexibilities which are available due to existing uncertainties in pavement project valuation procedure. Agency costs, user costs, carbon emissions, and energy consumption are considered as the main criteria, and Monte Carlo simulation (MCS) technique is used with a recursive procedure for analyzing flexibility in each time step of pavement life-cycle. For making the best decision in each time step and the best overall alternative, technique for order of preference by similarity to ideal solution (TOPSIS) is used, and the best alternatives are reported. The model is applied in a highway project in Iran to demonstrate its capabilities to analyze the sustainability of different asphalt and concrete alternatives for pavement projects. Various alternatives of the two pavement types are compared and it is clarified that the best asphalt alternative has lower life-cycle costs but more carbon emissions and much more energy consumption. Selection of concrete pavement instead of asphalt pavement in last decade in Iran, will approximately 35% increase related costs but it will result in about 2,000,000 tons of carbon emissions reduction and 700,000 GJ reduction in energy consumption annually. • An integrating LCA and LCCA model is proposed for sustainable pavement selection. • Recursive dynamic programming method is used for consideration of managerial flexibilities. • TOPSIS is used for multi criteria decision-making with preferred weights. • Cement pavements have 12% less environmental effects than Asphalt pavements. • Cement pavement have 55% less energy consumption than Asphalt pavements. [ABSTRACT FROM AUTHOR]