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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 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]

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 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]

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]

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]

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]

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]