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This study proposes and constructs a model for a closed-loop farming system (CLFS) for pig manure waste reuse under circular economy principles (CEPs) to optimize economic benefits. Pig farming produces waste that harms the ecological environment in Taiwan. However, few studies have focused on pig farming waste within the context of CEPs, where the resource utilization of pig manure waste and CLFS are the main concerns. This study introduces a CLFS with a farming production plan that enhances systematic efficiency and builds a framework for resource reuse, supporting a local living circle. The resource utilization of pig manure waste is integrated into the CLFS, ensuring that the entire pig raising production process operates within the system, maximizing waste utilization to increase economic benefits. A sensitivity analysis is also presented. The results confirm that all counties and municipalities in Taiwan achieved self-sufficiency in pork production, reaching a 100% satisfaction rate for pork demand, and feed prices did not impact the overall CLFS. [Display omitted] [ABSTRACT FROM AUTHOR]

Incorporating local solar resources into traditional energy systems to meet various building needs has the potential to enhance the adoption of renewable energy sources and address environmental concerns. Departing from conventional approaches that rely solely on solar power or thermal energy, this study proposes a novel energy system driven by full-spectrum solar energy and methanol, leveraging thermal-chemical reactions utilizing both renewable and waste thermal energy. Through device modeling and multi-objective optimization, configurations are optimized considering ecological carbon emissions and costs to assess specific carbon footprints and techno-environmental performance. Findings reveal that indirect carbon emissions, accounting for over 50% of total emissions from an ecological perspective, result in higher environmental and economic burdens compared to conventional methods. The system achieves energy and exergy efficiencies of 90.9% and 62.1%, respectively, under ideal configurations. Sensitivity analysis demonstrates that cities with high cooling demands necessitate larger heat pump capacities, leading to increased specific costs and reliance on the power grid, while higher capacities of solar devices reduce costs at the expense of reduced consumption rates. This research provides valuable insights into maximizing the utilization of local solar resources across the full spectrum to meet diverse production demands. • A full-spectrum solar and methanol driven tri-generation system. • Analysis of the energy-exergy-environmental-economic interplay from an ecological standpoint. • Sensitivity analysis examining environmental and technical parameters. • Attainment of exceptional energy and exergy efficiencies, reaching 90.9% and 62.1% respectively under optimal configurations. [ABSTRACT FROM AUTHOR]

Membrane-based separation is one of the promising next-generation carbon capture technologies. High degrees of freedom in process design for multi-stage membrane networks, make it difficult to fully understand the impact of network configuration on the economics of capture and separation performance. Furthermore, the optimality in process design is heavily influenced by the levels of membrane performance and the characteristics of feed gas. Membrane model utilized for the study is validated and tuned with 183 experimental data measured at various operating conditions, having 2.45 % of overall prediction error. The superstructure-based framework for the optimization of multi-stage membrane networks is used, with which design interactions between network configurations, flue gas characteristics and membrane performance are systematically investigated. Techno-economic analysis is embedded in the optimization framework, which performs rigorous trade-off between capital and operating costs, as well as allows simultaneous determination of optimal process network configuration and operating variables. Flue gas streams emitted from a coal-fired power plant and a steam methane reforming hydrogen production plant are selected as CO 2 capture sources for the analysis of flue gas characteristics. Case study shows capture cost ranged from 30.2 $/tCO 2 to 79.9 $/tCO 2 , depending on the network configuration and design specifications, and clearly improves our techno-economic understanding on the network configuration of membrane capture process. In addition, cryogenic-hybridized membrane capture process is examined and the optimal level of enriched CO 2 stream concentration between membrane capture and cryogenic distillation processes is determined. Study suggests how network configuration of membrane capture process can impact capture cost. [ABSTRACT FROM AUTHOR]

The necessity of making reliable decisions is exceptionally important in the field of sustainable development, particularly when evaluating the management of renewable energy sources. A thorough analysis becomes imperative in complex decision problems where various factors influence outcomes. Multi-Criteria Decision Analysis (MCDA) methods have emerged as valuable tools for addressing such challenges, enabling decision-makers to navigate through conflicting criteria and make informed choices. Combined with sensitivity analysis approaches, comprehensive assessments can be achieved, ensuring the robustness of decision-making processes. To increase the reliability of the results, different aspects of input data fluctuations should be examined to provide a broader view of the stability of the results. This paper proposes a comprehensive multi-dimensional sensitivity analysis approach to assess the robustness of renewable energy source (RES) development in selected European countries. By evaluating RES management in terms of electricity and energy consumption and generation, the study addresses key components of sustainable development. It offers a holistic perspective on result reliability and stability by analyzing five sensitivity dimensions: a comparative analysis of four MCDA methods, varying criteria weights scenarios, probabilistic modifications, criteria relevance identification, and ranking stability. This approach enhances decision-making in sustainable energy development, providing valuable insights for policymakers on prioritizing sustainable technologies. The provided open-source implementation promotes transparency and accessibility in decision support systems. • Novel sensitivity analysis for robust RES in Europe. • Advances decision-making in sustainable energy. • Guides policy with insights & open-source framework. [ABSTRACT FROM AUTHOR]

Floods persist as a recurring and daunting peril in the Brahmaputra plain of Assam. Notwithstanding advancement, Bongaigaon is a highly flood-afflicted district in the lower part of this region, inflicting significant damage to both lives and property almost every consecutive year. Hence, the delineation of precise and reliable flood risk susceptibility zones within the district constitutes the foremost concern of the study. The present work considered a total of sixteen multi-collinearity free parameters integrating with the GIS- based Multi-Criteria Decision Making-Analytical Hierarchy Process (MCDM-AHP) model for identifying potential flood hazard zones (FHZ), flood vulnerability zones (FVZ), and flood risk zones (FRZ) for the region. The result revealed that over 28% of the district's total area falls under the high to very high flood risk zone. Srijangram circle covers the highest flood risk zone with 343.19 sq. km. The FHZ map of the district demonstrated reliability exceeding 90% in ROC-AUC and below 40% in MSE and RMSE. Additionally, sensitivity analyses depict the role indicators in the predictive model, placed as a virgin gap for study in the region. Moreover, a multivariate correlation statistic is used to examine the potential risk zones and temporal flood effects on different Revenue Circles (RC), showing R2 over 0.6 in each category. The robustness of this model manifests sensible findings, aiding in fortifying sustainable flood management strategies to mitigate risks at different levels. Strategies adopted here contain greater potential for current as well as future trends in similar domains of research. This study may provide invaluable insights for decision-makers, thinkers, administrators, and developers working in this region. [Display omitted] • We assessed flood risk in various spatial units in the Lower Brahmaputra Floodplain, Assam. • The performance of the MCDM-AHP model is further enhanced by sensitivity analysis in this study. • More than 90% of the accuracy of the model shows its reliability. • This integrated study would fortify the pace of the flood management strategy in the region. [ABSTRACT FROM AUTHOR]

The building and construction sector is a major contributor to carbon emissions in China. Hence, it is crucial to explore the characteristics and trends of building carbon emissions to achieve the carbon peak and neutrality. While previous studies have made efforts to analyze the influencing factors through different approaches, developing an effective and intelligent regression model based on machine learning algorithms remains challenging in predicting the carbon emission trend. This study analyzed carbon emissions and per capita indicators of the building and construction sector in 30 provincial regions in China from 2005 to 2021. While embodied and operational carbon emissions contribute equally to the total emissions, the results showed a significant spatial-temporal correlation. Considering the emissions as target features, nine alternative machine learning regression models were developed using eight identified explanatory features incorporating scale, economic, technological, and classification factors. Based on performance metrics encompassing root mean squared error, coefficient of determination, and mean absolute percentage error, the stacking ensemble regression model was identified to have superior performance. This model was further employed to conduct a sensitivity analysis of explanatory features on carbon emissions. The results indicated that urbanization rate and population were the most sensitive factors, with varying effects on different target features. These findings can be used to predict carbon emission trends and promote carbon reduction policies in the building industry. • Characteristics and trends analyzed for building carbon emissions during 2005–2021. • Embodied and operational carbon emissions contribute equally to the building sector. • Nine regression models developed for embodied and operational carbon emissions. • Stacking ensemble model shows superior performance with R2 values exceeding 0.910 • Sensitive features exert different influences on varying carbon emission targets. [ABSTRACT FROM AUTHOR]

Before implementing large-scale emerging sludge treatment methods, it is crucial to conduct a comprehensive analysis of their environmental impacts and economic costs at the system level. This study utilizes standardized Life Cycle Assessment (LCA) and Life Cycle Cost (LCC) accounting methods to evaluate four emerging sludge treatment routes: anaerobic fermentation (AF), pyrolysis (PY), hydrothermal carbonization (HTC), and alkaline thermal hydrolysis (ATH). These routes are compared with two traditional sludge treatment routes, anaerobic digestion (AD) and aerobic composting (AC). The results indicate that the conventional route AD is the optimal choice in terms of environmental pollution, carbon emission control, and life cycle cost. The emerging routes AF and ATH have significant environmental benefits from carbon source recovery and protein recovery. However, they require approximately twice the cumulative energy demand of AD and additional consumption of chemicals, which imposes a greater environmental burden. While PY and HTC outperform the conventional sludge treatment routes in terms of the total environmental impact (1.79E-10, 1.72E-10) due to energy recovery and the use of clean energy sources. AF and PY demonstrate better economic performance (842.11 and 712.00 CNY) compared to the traditional route AC (905.06 CNY). However, both HTC and ATH incur costs approximately 1.3 times higher than AC due to their high energy and material demands. Furthermore, sensitivity analysis reveals that emerging treatment routes are highly influenced by energy and resource recovery and consumption. Therefore, reducing the energy and resource inputs for emerging routes could significantly decrease their environmental impact and cost, maximizing their resource recovery advantages. [Display omitted] • Emerging sludge treatment routes evaluated using LCA and LCC. • Optimizing energy/materials use greatly reduce the EI and EC of emerging routes. • AF and ATH benefit from resource recovery on both environment and economy. • AF and PY cost less than traditional AC, while HTC and ATH cost more. [ABSTRACT FROM AUTHOR]

This paper studies a collection centre location problem for e-waste acquisition from households. The proposed location-allocation model is a bi-objective mixed-integer non-linear model that maximises waste collection and minimises the cost of collection. The model considers that both drop-off and pick-up policies are in place, i.e., people can either drop their e-waste at a collection centre or request doorstep pick-up of their e-waste. The model considers that people's decision to drop off their e-waste at the collection centres depends on the financial incentive offered by the firm and the distance of the collection centre. However, in the case of pick-up, no incentive is provided, and it is considered that the households' willingness to return depends on people's concern for environmental degradation. The proposed model decides the location of the collection centre, the assignment of customer nodes, the incentive offered, and the e-waste collected using both pick-up and drop-off methods. Instances generated using a real case of Delhi, India, demonstrate the feasibility and validity of the proposed model, and the epsilon constraint method is employed to handle its multi-objectivity. Furthermore, sensitivity analysis is used to assess the relative importance of the parameters on the model output. The study offers valuable theoretical and practical implications. • A bi-objective mixed-integer non-linear program model is proposed. • Both pick-up and drop off strategy are simultaneously considered. • Drop off is modelled as a function of incentive and distance. • The ε -constraint method is employed to solve the proposed bi-objective mixed-integer non-linear program model. [ABSTRACT FROM AUTHOR]

The use of pallets is crucial in supply chain and transportation processes, with wood pallets representing the most common packaging type in the US and in Europe. This work focuses on the environmental and economic impact of wood pallet reverse logistics, quantifying the context in which preemptive remanufacturing schedules are useful. Preemptive schedules allow the service provider to reduce transportation emissions and costs by combining multiple pallet components remanufacturing activities. However, this advantage has to be weighed against the losses associated with repairing or replacing a still functional component earlier than required. An integer linear optimization model analyzes this trade-off, first from an environmental then from an economic perspective. This model is applied using the two most common pallet types as case studies: 48- by 40-inch stringer and block pallets. Different handling and loading scenarios are considered. The impact of transportation distance on the efficiency of preemptive policies is explored through a sensitivity analysis. Results show the positive impact of preemptive remanufacturing on costs and CO 2 -equivalent emissions in all scenarios, with larger benefits in good handling or light loading scenarios. • Preemptive remanufacturing policies for block and stringer pallets are compared. • An optimization model analyzes costs and CO2eq emissions of preemptive repair schedules. • Preemptive policies result in costs and CO2eq emissions reduction by 30–40%. • Up to 50% cost and emission reduction with good handling or light loading conditions. • Results for block pallets are sensitive to distance below 200 km. [ABSTRACT FROM AUTHOR]

Recently, social awareness, governmental legislations and competitive business environment have spurred researchers to pay much attention to closed-loop supply chain network design. In order to support the arising trend, this paper presents a comprehensive mathematical model for a multi-period, multi-product, multi-modal and bi-objective green closed-loop supply chain. The objective of the model is to minimize the total cost and environmental emissions through making the best decisions on facility location, transportation amounts and inventory balances. According to the inherent complexity of the problem and considering multi-product, multi-period and multi- modality assumptions makes it hard to handle, and as for the solution approach, an effective accelerated benders decomposition algorithm is implemented. Then, computational results for a set of numerical example are discussed. Besides, the model and solution approach are applied on a wire-and-cable industry. Then, a sensitivity analysis is implemented in an effort to validate the model. Results reveal applicability of the proposed mathematical model and presented solution approach. Following the obtained results, it can be validly concluded that the suggested solution approach leads to more than 13 percent reduction in total cost for the studied case, and can be even employed for larger and more complex real-world industrial applications. • A multi-period, multi-product, multi-modal closed-loop supply chain network design is investigated. • A multi-objective MILP model is developed for the proposed problem context. • LP-metric method is used to deal with the multi-objective mathematical model. • An accelerated bender's decomposition algorithm provides an efficient solution procedure. [ABSTRACT FROM AUTHOR]

Islands are threatened by various natural and anthropogenic factors including climate change, overpopulation, unsustainable use of natural resources and increasing trend in seismic events. Therefore, studies on island in specific aspect (ecological, social and economic) is very essential for sustainable resource management and future development. Mangroves are highly important natural resources of coastal regions in respect to coastal livelihood and natural defense. Although, around 46% of the mangrove forest area has vanished worldwide in the last few decades. In this present research, Future Mangrove Suitability Index (FMSI) using the Analytic Hierarchy Process (AHP) method has been performed for sustainable forest management under the United Nations Sustainable Development Goal no 15. It is a new framework applied on North and Middle Andaman Island to determine the future distribution of mangrove forest. Land-use and land-covers (LULC) are prepared in supervised classification (maximum likelihood algorithm) techniques with 3000 signatures. A total number of fourteen parameters has been used in multi-criteria decision making (MCDM) platform to generate future scenarios. Among them, Representative Concentration Pathways (RCPs) projected climatic data (RCP 6.0 scenario shows the best result comparing to 4.5 and 8.5) and projected population data has been used for the first time in the investigated area. The final results are validated using 556 field sample point. Seven major sensitive parameters have been selected from sensitivity analysis and three statistical correlation analysis has been performed using 300 field points to generate the actual correlation between the parameters. The final outcome shows that major unsuitable zones are located in Diglipur tehsil whereas; highest suitable zones are located in Rangat tehsil region which are the result of the continuous increase of sea surface height (1.5 mm observed during 1980–2009), seismic events with frequent storm surges, anthropogenic influences and impact of climate change. Thus a planned sustainable development practice is essential to control the biodiversity loss and future livelihood management. Moreover, this study will strengthen future planning projects and researches in mangrove ecosystem management of Andaman. • LULC changes of Andaman shows that 47% of mangrove forest degraded during last 30 years. • FMSI has been prepared using AHP method for future mangrove suitable zone mapping to strengthen sustainable development. • Statistical Analysis by 300 field sample points used to identify the actual correlation between sensitive parameters. [ABSTRACT FROM AUTHOR]

Heavy metals could serve as both pollutants and resources. To better understand the cleaner production potential of material flow control for simultaneous pollution reduction and resource conservation at source in zinc hydrometallurgy system, the generation and distribution of the Pb, Cu, and Ag in the process network of a typical zinc hydrometallurgy plant were investigated in this study. Four kinds of hazardous wastes with a total dry weight of 942 kg/tZn were identified as the major system outputs for Pb (12.08 kg/tZn), Cu (5.63 kg/tZn), and Ag (70.5 g/tZn). More than 85% of the target substances were accumulated in the leaching and purification subsystem, which determined the final proportion of the substances in the system outputs. The unsatisfactory distribution of the substances in the present process network contributes 0%, 45.9% and 27.5% of final resource wastage or pollution for Pb, Cu, and Ag of the generated wastes, corresponding to 0, 0.53 kg/tZn, and 13 g/tZn, respectively. Presently the Pb wastage or generation of Pb pollution was mainly due to the lack of recovery process. However, the potential to optimize the flow partitioning for Cu is relatively high. In summary, optimization of the process distribution might slightly increase the total recovery rate of the substances, but could significantly reduce the environmental risk of the disposed wastes generated in the zinc hydrometallurgy system. These results will be helpful to improve the understanding of the mechanisms for heavy metal pollution generation and provide further insight in the control of pollution and resource in process industries, such as nonferrous metals industry. Image 10778 • Substance flows of Pb, Cu and Ag in zinc hydrometallurgy system was studied. • There were 942 kg/tZn wastes containing Pb, Cu and Ag was generated in the system. • Contribution of substance distribution to resource wastage/pollution was evaluated. • Key process units affecting the distribution behavior of system were identified. [ABSTRACT FROM AUTHOR]

Studies have demonstrated the energy savings potential of mixed-mode ventilated office buildings. Yet, it is important to widen the knowledge about how those buildings have been designed and built in practice, and which design parameters have greater influence on its energy performance. The aim of this paper was to evaluate how building envelope design parameters influence the energy performance of cellular mixed-mode office buildings, in order to identify key design variables. The analysis presents a comparison among literature research studies and typical construction practices from a sample of buildings located in the city of Sao Paulo, Brazil. According to a base case model, established based on the real buildings sample, three sensitivity analysis techniques were performed to obtain relative parameter sensitivity to thermal loads: OFAT, Morris and Monte Carlo. Results showed the importance of the window opening effective area and the reduced impact of the window-to-wall ratio on the energy performance of mixed-mode office buildings. By applying a multivariate regression model, it showed significant in predicting 78.1% of the variance in annual thermal loads. The accurate determination of annual thermal loads into mixed-mode office buildings can be used to optimize the envelope characteristics based on a combination of input data and the building geometry. Findings from this study could also be applied to other locations, provided that similar climatic environment and urban context are taken into account. • We evaluate the energy performance of mixed-mode office buildings. • A base case and its characteristics were defined based on a sample. • Typical construction practices versus theoretical studies were compared. • Three sensitivity analysis methods were applied and compared. • Multivariate regression model predicted 78% of the variance in annual thermal loads. [ABSTRACT FROM AUTHOR]

A submerged combustion vaporizer (SCV) is normally used at a liquefied natural gas (LNG) terminal to vaporize LNG and supply natural gas to domestic and industrial markets. In this study, a new methodology was developed to reduce NO x efficiently in the flue gas of the SCV. The experimental setting of the SCV was prepared, and the impact of various process variables (e. g., excess O 2 concentration, temperature, pH of water, and H 2 O 2 concentration) on NO x reduction was investigated. For this, a surrogate model was developed by using an artificial neural network (ANN) algorithm based on the experimental data. The contributions of the input variables on NO x removal were assessed using sensitivity analysis. A genetic algorithm (GA) was integrated with the model to optimize the variables to maximize the removal of NO x in the flue gas. Finally, the ANN-GA model was validated through experimental verification, performed under the identified optimum condition. Image 1 • A new method was develped to reduce released amounts of NO in flue gas. • Experiments were conducted to model a submerged combustion vaporizer. • A surrogate model was developed by using an artificial neural network algorithm. • The model was integrated with genetic algorithm to search optimal operating points. • The optimization results were verified with additional experiment results. [ABSTRACT FROM AUTHOR]

The study of waste management strategies is increasing worldwide due to the necessity of a more sustainable environment. In this framework, guaranteeing cleaner energy is the key parameter for cleaner production, especially for reducing the emissions of greenhouse gases and other pollutants to the environment, which are directly related to the types of the energy sources used. Through the methodology of LCA it can help in the study of the environmental part. This study is based on the methodologies ISO 14040 and 14044 for obtaining quantitative results on the environmental impact, from cradle to grave, of different waste collection systems. A sensitive study of the influence of the energy source on the life cycle assessment (LCA) is analysed for six different waste collection systems (trucks - electric, gas, diesel, diesel-electric, gas-electric - and stationary pneumatic waste collection) and five energy sources (Spanish energy mix 2008, hydropower, photovoltaic, wind, and a renewable energy mix). The results show that the energy source has a big impact in the results of the LCA with variations up to 80%. The environmental impact of each collection system depends strongly on the source of the energy used and thus, decision-makers should consider the energy source and the expected evolution of energy mix when considering the best waste collection systems from an environmental point of view. In a framework with a majority of fossil-sourced energy, the truck collection shows lesser environmental impact, due to its lower electricity use, whereas in a renewable energy environment, the stationary pneumatic waste collection shows better performance. • Life cycle assessment of two different systems of urban waste collection was studied. • Ecoinvent v3.0 database was used to obtain the environmental impacts. • Different scenarios were studied, for the collection and for the energy mix. • The electricity has a very high impact in the LCA of all the scenarios studied. • When the RES use increases the impact of electricity production decreases. [ABSTRACT FROM AUTHOR]

Energy performance contracting (EPC) was developed and had ever been believed as an effective energy-saving method. Despite that a variety of schemes, Guaranteed Saving, Shared Saving, and First-Out schemes, are created to be applied in various conditions, it has not been widely adopted as expected, due to the complexity of its profit allocation, high uncertainty and investment-assessing deficiency. In order to promote the wide applications of EPC projects, Real option analysis (ROA) is applied in this paper with the attempt of seeking the optimal scheme, which could be feasible and profitable for both stakeholders. ROA is studied to be an effective tool capable of considering the uncertainty and the managerial flexibility, and of assessing the investment value. A ROA-enabled methodology is proposed and expected to (1) identify feasible options for both the energy service company and the owner, (2) evaluate the investment value using the binomial tree pricing model, (3) develop new metrics for the optimal EPC scheme, and finally (4) single out the optimal scheme that is feasible and attractive for both sides. A real EPC project is studied to test the effectiveness and applicability of the proposed approach. The Shared Saving scheme is identified as the optimal scheme for the EPC project, striking a more ideal profit difference between participants than the other two schemes. This demonstrates the capability and effectiveness of the proposed approach in optimizing the scheme into a new balance. The sensitivity of the sharing proportion on the optimal EPC scheme is discussed, and it is found that the sharing proportion of realized energy cost savings by the energy service company is positively correlated with the total investment value. The novelty of this research lies in (a) the incorporation of contractual flexibility by means of the real option into the EPC project for optimal design, and (b) new metrics for the selection of the optimal EPC scheme. The proposed model and suggestions based on the case study are supposed to help decision-makers optimize the scheme under different scenarios. A feasible and attractive EPC scheme can further prompt wide application of energy-saving projects, which in turn contributes to the improvement of energy-consuming efficiency and then to realize the environmental sustainability. • Real option analysis is incorporated to manage the uncertainty and flexibility in EPC. • Investment value of EPC projects increases due to the consideration of managerial flexibility. • New metrics are proposed for the selection of the optimal EPC scheme. • The shared saving scheme is identified to be the optimal scheme in the case study. • The sensitivity of the sharing proportion on the optimal EPC scheme is discussed. [ABSTRACT FROM AUTHOR]

Utilizing bentonite in composites such as concrete mixture is one of the practical approaches for adsorption of heavy metals. The mixture of bentonite and normal concrete is known as bentonite plastic concrete (BPC). This type of concrete is commonly utilized as the material of cutoff walls under earth dams with the aim of minimizing or preventing water seepage. Plastic concrete should possess high workability and consistency since it is poured into trenches by tremie pipe; this fact highlights the importance of predicting the slump of BPC. Different strength parameters of BPC such as compressive strength and elastic modulus can be predicted by utilizing prediction models. This information is exceedingly useful for modifying mixing design of BPC which results in reducing the cost and time of constructing a project. Consequently, it is vital to propose models that can predict the parameters of BPC with high precision. In this research, 158, 169, and 119 data records respectively for slump, compressive strength of cubic samples (f' c,cube), and elastic modulus (E c) of BPC were collected from literature in order to propose prediction models. Three soft computing methods of artificial neural network (ANN), Multivariate adaptive regression splines (MARS), and M5 model tree (M5Tree) were utilized and compared in this paper. Then, parametric studies were conducted to study the effect of different variables such as silty clay addition, bentonite dosage, water content, and curing time on the outputs (i.e., slump, f' c,cube , and E c). Results indicate that ANN models are more accurate than the other models for prediction of all three parameters. The water variable produces the greatest effect on the slump of BPC while the sand variable has the least influence. In addition, both for f' c,cube and E c models, variables of cement and curing time have the maximum and minimum impact on the outputs, respectively. • Three datasets of Slump, f' c,cube , and E c of BPC were gathered from the literature. • Three methods of ANN, MARS, and M5Tree were compared. • ANN models were more precise than the other models. • The parametric studies were performed to investigate the behavior of ANN models. • The sensitivitsy analysis showed the influence of input parameters on models output. [ABSTRACT FROM AUTHOR]

Energy consumption is constantly improving due to the increasing development of community economy and material living standards. Solar energy is the first green energy, and its unique advantage is of great importance in solving the energy crisis and environmental degradation. Furthermore, selecting appropriate locations is necessary to take full advantages of solar energy. This study intends to set up a multistage decision support framework for sites selection of solar power plants with probabilistic linguistic (PL) information. The proposed framework considers not only the disposal of linguistic information but also the interrelationships among criteria. A probabilistic linguistic term set (PLTS) is used to deal with a large volume of linguistic evaluation information. Then, probabilistic linguistic normal cloud (PLNC) is proposed to transform qualitative concepts into quantitative values so as to handle PLTS effectively and reduce information loss and distortion. A new distance measure that connects a Heronian mean (HM) operator with distance measure is also presented. An improved maximizing deviation method is introduced on the basis of this new model to deal with the interrelationships among criteria. In addition, a ranking method VlseKriterijumska optimizacija I Kompromisno (VIKOR) which considers the maximum utility of a group and the minimum regret value of individuals is proposed. Next, the proposed framework is successfully implemented in a case study. Results show that Gansu and Xinjiang are more suitable locations for building solar power plants. Sensitivity analysis is carried out to explore the change in ranking order due to variations in parameters. The proposed assessment model is then compared with the extant methods to deal with PL information and thereby certify its effectiveness, feasibility and advantages. Ultimately, the policy recommendations and contributions of this article are laid out. [ABSTRACT FROM AUTHOR]

Phosphorus is an essential element in sustaining modern day farming practices and is expected to deplete within the next 100 years. However, phosphorus utilisation efficiencies in most countries are below 20%, making the implementation of suitable phosphorus recovering technologies urgent and necessary. In spite of intensive research and development, there are only a few commercial recovery facilities being implemented. Therefore, there is a need to identify potential roadblocks/hurdles in a systematic manner. To this end, technology readiness level, process economics and sensitivity analyses were novelly integrated and employed to evaluate the opportunities and hurdles during the implementation of current phosphorus recovery technologies. The enhanced methodology is demonstrated via a case study, revealing that only struvite crystallization is sufficiently mature to be industrially implemented. Under most scenarios evaluated, struvite crystallization can be profitable or break-even if financial assistance is provided from policy-makers. Sensitivity analysis showed that overall profitability is highly sensitive to raw materials cost and product sale price, while phosphorus concentration in waste streams has less effect. Such an assessment could be extended to identify barriers in other resource recovery technologies. [ABSTRACT FROM AUTHOR]

With increasing environmental concerns with respect to the petroleum-based adhesive production process, bio-based adhesive has been explored as a promising replacement. The purpose of this paper was to explore the economic feasibility of structural bio-adhesives made from glycerol, a byproduct of biodiesel production. SuperPro Designer software was employed to perform the techno-economic analysis. Several key parameters were analyzed, such as total capital investment, annual operating costs and revenues. It was found that the unit production cost of structural bio-adhesives ($2.45/kg) was compatible with that in the current market. Three different scenarios were built to investigate the worst-case scenario and the best-case scenario associated with this production process. Sensitivity analysis was also performed to evaluate the key parameters significantly influencing the economic result. In this study, material cost was determined to be the most significant factor throughout the production process. Discounted cash flow analysis was conducted to explore the influence of the time value of money. The minimum selling price obtained was $3.11/kg for this bioadhesive production process. Underlying issues and areas needed for improvement were also discussed in this study. Image 10624 • A techno-economic analysis was conducted on glycerol-based structural bioadhesive. • Material cost was determined as the most sensitive parameter in the process. • Minimum selling price of the structural bioadhesive was determined to be $3.11/kg. [ABSTRACT FROM AUTHOR]

To face up abiotic resource depletion and other environmental issues as climate change due to usual fossil-based chemical production technologies, some alternative strategies have been developed using renewable resources. To produce such bio-based chemicals, renewable raw materials such as cereal crops or vegetables are currently used. To promote an environmental responsible practice, organic waste could be a relevant alternative to these dedicated crops. BIORARE technology is an innovative concept based on coupling an anaerobic digestion plant processing with bioelectrosynthesis in order to produce a range of chemicals from organic waste. Even if bioelectrosynthesis processes are not yet technologically mature; it is appropriate to consider the credibility of this emerging technology in environmental terms thanks to an eco-design approach. This eco-design approach is based on the life cycle assessment (LCA) methodology. A LCA of biosuccinic acid production thanks to BIORARE technology has been carried out and has been combined with sensitivity analysis. The aim of this strategy is to ensure that sensitive parameters are identified and adjusted in order to make the technology the more eco-friendly possible whilst maintaining good economy efficiency. The present study describes the identification and optimisation of key parameters of the BIORARE technology applied for succinic acid production. These key parameters and their range of variation are chosen according to a realistic strategy allowing the control of the BIORARE technology on an industrial scale. The results show that the current density applied during the bioelectrosynthesis and the hydrolysis yield during the pre-treatment of the waste stream are key variables in the optimisation between production efficiency and the environmental footprint. The environmental efficiency of the process was studied by applying the eco-efficiency ratio. When the production of biosuccinic acid using the BIORARE technology was compared to a reference scenario, better overall eco-efficiency was shown despite some environmental penalties. In parallel, when the same study was performed for bioethanol production a low efficiency was revealed without environmental penalties. Image 1 • Environmental biorefinery can produce bio-succinic acid from organic wastes. • Eco-design through life cycle assessment helps identifying sensitive parameters. • Trade-offs exist between production efficiency and environmental burdens. [ABSTRACT FROM AUTHOR]

Transportation infrastructure and operations are greatly impacted by ice and snow, adding enormous costs to the American economy. Because of their sustainability benefits, heated-pavement systems (HPS) continue to gain attention as a potential alternative to conventional snow removal operations, and the main goal of this paper is to assess the economic feasibility of hydronically-heated pavements systems (HHPS), one type of heated pavements, for use at apron areas of commercial airports. Both benefits and expenses associated with use of HHPS for snow and ice removal were identified and quantified in monetary terms using a stochastic economic analysis method, and a sensitivity analysis approach was used to determine particular variables that significantly influence overall economic viability of HHPS. The findings suggest that, despite high capital costs, HHPS use at airports might be economically feasible. The results from the sensitivity analysis indicate that airport size, in the context of number of aircraft operations, strongly affects the benefit-cost ratio of HHPS use. [ABSTRACT FROM AUTHOR]

This paper addresses the issue of pricing, product greenness, and coordination in a dual channel supply chain under channel disruption. It is assumed that one type of green product is being sold through a dual supply system. Also the movement of customers between channels in cases that only one of the channels is disrupted is surveyed. The decisions and profits of the supply chain and the members in the centralized and decentralized decision structures are extracted. In order to coordinate the supply chain, a transshipment contract is proposed and its application and usefulness is examined through a series of numerical examples and sensitivity analyses. The results illustrate that the proposed contract is capable of coordinating the supply chain and also guaranteeing the members' profitability. • Coordination of pricing and product greenness in a dual channel supply chain is analyzed. • Possible scenarios for channel disruption in both channels are investigated. • Developed model considers customer movement between channels if disruption occurs. • A transshipment contract is proposed to coordinate pricing and greening decisions in both channels. • The proposed coordination model results in more green products. [ABSTRACT FROM AUTHOR]

Abstract In this study, the sulfur recovery unit based on the modified Claus process with the split flow is simulated and the results are validated with South Pars gas refinery data. Since optimum energy consumption is essential for community development, exergoeconomic and sensitivity analyses are conducted to prevent waste production and increase energy efficiency in this unit. Energy and exergy analyses are performed to identify the equipment with low exergy efficiency and calculate their exergy destruction extent. Reaction furnace with 4178.8 kW exergy destruction has the highest rate, and then waste heat boiler and P-7 pump are placed. After the pumps, the heat exchangers have the lowest exergy efficiency so that the acid gas preheater with the value of 60% has the lowest one. All equipment investment and operating and maintenance cost calculations are carried out so that the largest cost is related to the hydrolyzing Claus bed that followed by waste heat boiler and P-7 pump. Then equipment exergoeconomic parameters such as exergoeconomic factor, cost rate of exergy destruction and relative cost difference are obtained. The lowest exergoeconomic factor among the process equipment is related to reaction furnace and second condenser with the values of 0.26% and 0.86%, respectively. The maximum exergoeconomic factor is 94% which is attributed to compressors. The reaction furnace with 4706.16 ($/h) and waste heat boiler with 4629.89 ($/h) have the highest cost rate of exergy destruction and CMPR-5 compressor with 0.2451 ($/h) has the lowest cost rate. Finally, considering some of the functional and economic parameters in the sensitivity analysis procedure, the influence of changing these variables on exergoeconomic parameters have been investigated. Highlights • The gas refinery sulfur recovery unit is simulated. • The exergoeconomic analysis is performed on a sulfur recovery unit. • Products cost rates including sulfur streams, LP and MP steams are calculated. • All equipments in terms of exergoeconomic variables are ranked. • Sensitivity analyses on the operational and economic parameters are conducted. [ABSTRACT FROM AUTHOR]

Abstract Building envelopes can highly impact the building energy demand and indoor environmental quality, so that the application of novel façade systems such as photovoltaics has been widely investigated. However, few study has addressed the interactive effect between photovoltaic (PV) application and traditional passive architectural design strategies, which is thoroughly discussed in this comparative study using a holistic design optimization process. The holistic design optimization approach combines screening-based and variance-based sensitivity analyses with the non-dominated sorting genetic algorithm-II (NSGA-II) and hybrid generalized pattern search particle swarm optimization (HGPSPSO). The impact of the light-to-solar gain ratio (LSG) is evaluated as one of the key factor to combine the passive design and PV glazing based on a comprehensive glazing database. Through an exhaustive sensitivity analysis (SA), the Morris method is proved to be efficient and robust in factor prioritizing only when the required minimum sampling size is satisfied. The window to ground ratio showed much greater impact on the net building energy demand when PV applications are coupled with all available vertical façades. Furthermore, the necessary particles for specified design input dimensions are determined for the optimal performance of HGPSPSO. With the optimum design configuration, the net building demand can be reduced by up to 71.36% under the hot summer and warm winter condition of Hong Kong. Research findings from this study can be used to develop low-energy building guidelines and building integrated PV applications in early planning stages. Highlights • Impact of light-to-solar gain ratio is evaluated for integrated PV and passive design. • A holistic design optimization based on robust sensitivity analysis is developed. • Minimum required sample size for the Morris method is determined. • Required particle swarm size is determined for different design input dimensions. • The energy saving potential with optimized PV envelope is estimated up to 71.36%. [ABSTRACT FROM AUTHOR]

Abstract As the number of scrap cars increases rapidly, the management of their reverse logistics (RL) process has become an urgent issue for decision-makers in contemporary China. The process, capable of generating profits as well as minimizing negative environmental effects, mainly includes products acquisition, collection, inspection and disposition. Although the selection of take-back patterns is an essential part in the process, it is not well addressed by existing studies. Involving numerous related factors, the evaluation and selection of the take-back patterns of scrap cars are a comprehensive problem that can be formulated as a multi-criteria decision making (MCDM) problem. In this paper, we propose a complete method to solve it systematically. Three patterns quite suitable for China are presented and a novel criteria system is developed for choosing the best one. The unavoidable uncertainty in practical situation is also considered in this work. We integrate the grey method and Decision-making and Trial Evaluation Laboratory (grey DEMATEL) to determine the weights of nine criteria, and a fuzzy method and Vlse Kriterijumska Optimizacija I Kompromisno Resenje (fuzzy VIKOR) are adopted to rank the three patterns based on expert evaluations. Sensitivity analysis is also used to test and verify the robustness of the proposed method. Finally, we draw a conclusion that the Producer Responsibility Organization Take-back pattern whose main body is formed by manufacturer union organization is most suitable for China. The study results could provide a theoretical guideline for decision-makers in China as well as other developing countries. [ABSTRACT FROM AUTHOR]

Abstract Given the high variability of both quantity and condition of the returns, closed-loop supply chains depend on a mix of remanufactured and new components. Effectively managing the combined flow of returned and new components is imperative to minimize total system costs. This paper proposes a model that helps manage the flow of returns by determining the incentives to offer returners, while simultaneously determining a capacity contract with the supplier of new components. The model considers returns from multiple sources, where each source has different characteristics in terms of the quantity and condition of its returns. The model also accounts for uncertainties from the return sources, as well as the new components supplier. Such uncertainties result in a failure to meet the demand for components, incurring loss costs. Sensitivity analyses of a numerical example were conducted to illustrate the model and gain further insights. The results demonstrate noteworthy relationships between supplier-related costs and those associated with not meeting the required demand, as well as their influence on the incentives to offer and the supplier's capacity contract. Highlights • Components can be sourced new or remanufactured from multiple return sources. • Model determines the capacity to contract from the new component supplier. • Model determines the optimal incentive for each return source. • Costs include losses due to a lack of remanufactured components. • Major interactions exist among incentives, contract capacity and loss costs. [ABSTRACT FROM AUTHOR]

Abstract Modeling life-cycle sustainability assessment (LCSA) for pavement alternatives is still in infant stage. This paper proposes a comprehensive pavement LCSA methodology that integrated life-cycle cost analysis (C-LCA), environmental life-cycle assessment (E-LCA), and social life-cycle assessment (S-LCA). A four-step structure was developed for the proposed methodology, including system definition, modeling, unifying, and interpretation. First, the goal and scope were defined and pavement alternatives were identified during the four main life-cycle phases, including raw materials and production, construction, use, and maintenance. Second, pavement C-LCA, E-LCA, and S-LCA were measured in the modeling process, where the foreground project and background inventory data were collected, and the various impact assessment models were proposed. Third, a multi-criteria decision-making model was applied to unify the three sustainability dimensions, and select the appropriated sustainable pavement alternative. Finally, the results were discussed and highlighted in interpretation step, and a sensitivity analysis on weights was carried out. A case study was applied to illustrate the proposed methodology, including thin hot mix asphalt concrete layer (THMACO), hot mix asphalt with warm mix additive Sasobit (HMAW), and hot mix asphalt with reclaimed asphalt pavement (HMAR) in Southeast of China. The results show that the recycling-based HMAR contributed the best economic and social performance, while HMAW achieved the best environmental performance. A combined AHP-VIKOR model was applied, and HMAR was selected as the optimal alternative. In addition, a sensitivity analysis on weights was conducted using 21 cases. Highlights • Pavement life-cycle sustainability assessment was proposed including economic, environmental, and social factors. • AHP-VIKOR model was applied to select a sustainable pavement alternative, along with a sensitivity analysis. • A case study in China was conducted, including traditional and environment-friendly alternatives. [ABSTRACT FROM AUTHOR]

Abstract Reducing the total CO2 emissions intensity (TCEI) in the Chinese construction industry is an important strategy to cut its CO2 emissions, which share a considerable proportion of sectoral CO2 emissions in China. However, there is lack of an in-depth analysis of the effect of production structure on the TCEI. This study comprehensively investigates the effect of production structure on the TCEI in the Chinese construction industry by using structural decomposition analysis and sensitivity analysis methods collectively. The results show that the TCEI in the Chinese construction industry declined by 0.3505 tons CO2/104 RMB between 2007 and 2012, and the effect of production structure contributed 110.66% to such decline. Over 95% of the effect was contributed by the electricity, steam and hot water production and supply industry and the refined petroleum, coke products, and nuclear fuel industry. The results also demonstrate that the three most critical technical coefficients were for the nonmetallic mineral products industry consumed by the construction industry, the metal smelting and pressing industry consumed by the construction industry, and the metal smelting and pressing industry consumed by itself in 2012. Besides the first two coefficients, the coefficient for the electricity industry consumed by itself was also critical in 2007. The production chains of the construction industry itself and the metal smelting and pressing industry included over half of the twenty most critical technical coefficients. This study can provide valuable reference for Chinese policy makers to take proper strategies to adjust the production structure in order to reduce the TCEI. Highlights • The effect of production structure on TCEI in construction industry was analyzed. • The TCEI in the Chinese construction industry declined by 19% between 2007 and 2012. • The three most critical technical coefficients were identified. • The production chains of construction industry and metal industry were most critical. [ABSTRACT FROM AUTHOR]

Abstract The vehicular emission modelling software COPERT is extensively used in generating emission levels for National Emissions Inventory in Europe and in some other countries internationally. This paper aims to study the uncertainties associated with emission estimates generated from COPERT(v5.1) outputs through sensitivity analysis of the model input parameters. The input parameters considered in this study are temperature, speed, relative humidity, trip length, and driving style (mileage share). Many of these parameters are not directly measured or country-wide average values are investigated in this study. The uncertainties of the emission estimates were obtained through varying the parameter values, within realistic limits, either individually or considering factor interactions by varying two or more parameters simultaneously. The uncertainties of the emission estimates of certain pollutants (CO, VOC and NMVOC) can be significant from −58% to +76%. Some gases, such as CO 2 show almost no sensitivity to input parameter variations. The results indicate that the COPERT outputs are most sensitive to variations in trip length and speed, both of which are not directly measured. Considering the percentage of urban driving share has a huge effect on the national emission estimates, inventories were separately prepared for the Greater Dublin Area (GDA), the largest urban area of Ireland with highest population and vehicle densities. GDA has 48% and 50.37% shares of CO 2 and NOx emissions respectively, compared to the national levels. The consequence of over- or underestimation of emission inventories for Ireland was calculated to be approximately +/− €45million. Considering the major implications of NEI for climate change and other related impacts it is crucial to report the pollutant emission levels appropriately stating uncertainty levels. The findings of this study provide national experts with a methodology to estimate uncertainties of COPERT outputs and to identify the key sources of these uncertainties where policy and emission reduction strategies should be targeted. Graphical abstract Image 100836 Highlights • Vehicular emission levels modelled using COPERT varies significantly based on assumptions. • Sensitivity modelling of COPERT input parameters, values of which are not widely measured. • Individual & interactive effects of temperature, speed, driving style etc. on emission variations. • Uncertainties of CO, VOC, NMVOC, N 2 O levels are greater than uncertainties of CO 2 , NOx, & PM levels. • Damage costs of pollutants under/overestimated by approximately 43.9 mil€. [ABSTRACT FROM AUTHOR]

Abstract Uncertainties in remanufacturing systems add difficulties to the carbon footprint analysis of remanufacturing systems. Traditional probabilistic method requires a large amount of historical data to speculate the distribution types of uncertain variables. This study, based on interval analysis, applies a non-probabilistic method to the environmental assessment on remanufacturing systems in the form of carbon equivalent emissions. Considering four types of uncertainties, we establish the relationship among the quality loss of returned end of use products and environmental indexes. The results of sensitivity analysis indicate that the uncertain variables present different environmental benefits even at the same uncertainty level; however, it is interesting that when all the uncertainties are used as interval variables, the uncertainty level of their comprehensive impacts on environment does not enlarge accordingly, because the uncertain intervals of the variables are counteracted by each other. This model provides a novel method for practitioners in remanufacturing systems to quantify the impacts of uncertainties on the environment and subsequently make the optimal decision in production. [ABSTRACT FROM AUTHOR]

Abstract The aim of this study was to assess the sustainability of three different poultry production systems, in order to evaluate their suitability to address human food need, as well as their environmental sustainability, economic feasibility and animal welfare. The three systems compared were: a conventional intensive indoor system, a free range system and a free range system combined with an olive orchard (where chickens grazed in an orchard instead of in an area used solely for the grazing). A model based on multicriteria decision analysis was developed, using environmental, social and economic criteria. Environmental criteria were estimated using a life cycle assessment, while economic and social criteria were both collected on farms and from the literature. The analysis considered the preferences of different stakeholders involved in the production i.e. farmers, consumers, and scientists. The combined system ranked at the top position according to all three groups of stakeholders, followed by the free range and then the intensive systems. The stability of results was verified by performing a sensitivity analysis, in particular a weight stability analysis. The results showed that the final ranking was quite stable, as only four out of the 20 criteria considered had rank reversal (i.e. the ability to change the relative positions of two cases in a ranking). For these four criteria (i.e. Mortality Rate, Feed Conversion, Fossil Fuels and Land Use), rank reversal was easier between the free-range and the intensive systems, than between the combined and the intensive systems. Highlights • Sustainability of three poultry systems was compared with a multicriteria approach. • Three groups of stakeholders (farmers, consumers, scientists) were involved. • Rearing free range chickens in an olive orchard was preferred by all stakeholders. • A sensitivity analysis indicated that results were stable. [ABSTRACT FROM AUTHOR]

Abstract In this study, a conventional hydrogen liquefaction process is comprehensively analyzed. The studied hydrogen liquefaction process is consisted of two independent MR (Mixed Refrigerants) refrigeration cycles. In order to evaluate the liquefaction process and obtain valuable and noteworthy results, the process is examined through a comprehensive exergy based analyses. The exergy based analyses includes conventional exergy analysis to examine the performance of the liquefaction process, exergoeconomic analysis to obtain the effect of cost and economy on the performance, and exergoenvironmental analysis to provide beneficial information about the mutual effect of system's performance and environmental conditions. In addition, a sensitivity analysis is provided to assess and determine the mutual interaction among costs, environmental effects of each component, and the amount of exergy destruction. From the results, it is shown that the first refrigeration cycle exergy efficiency is obtained about 67.53% and the second refrigeration stage exergy efficiency is calculated about 52.24%. The whole hydrogen liquefaction process is exergy efficiency is 55.47%. The specific energy consumption (SEC) of this process is equal to 1.102 kWh/kg LH2. The total performance coefficient of the total process is 0.1797 which is higher than other reported articles. It is recommended from the Exergoeconomic and Exergoenvironmental analyses that the employed turbo-expanders and compressors are in priority for possible modification of the total process in the future. Highlights • A new hydrogen liquefaction process is investigated by exergy based analysis methods. • Two independent mixed refrigerant cycles are used for hydrogen liquefaction. • The process is evaluated by a 3E (exergy/exergoeconomic/exergoenvironmental) analysis. [ABSTRACT FROM AUTHOR]

Abstract The whopping increase in solid waste generation all over the world calls for the development of waste management strategies for a sustainable environment. By the quantification of environmental impacts, life cycle assessment (LCA) tool can help in answering the call. It evaluates the environmental performance of municipal solid waste management (MSWM) system which helps decision-maker in selecting the best management strategy with minimum impacts on the environment. But, up to what extent the LCA methodology can be applied to MSWM systems? To address this question, the present study analyzed the 153 LCA studies published till date since 2013 all over the world. The present study analyzed the time evolution, geographical distribution, and methodology applied in LCA studies. It summarized the use of the functional unit, LCA model, Life Cycle Impact Assessment (LCIA) method, MSWM options, and the critical findings of the selected LCAs, along with MSW composition, income group, and the gaps in the application of the studies. For evaluating the dependence of publication of studies and country's economic condition, the countries in which LCA studies were conducted are classified into four groups on the basis of income level viz., lower income, lower middle income, upper middle income, and higher income countries. In terms of technological coverage, 1 ton of MSW was the most used functional unit. SimaPro was the majorly used LCA model while 56 of the total studies didn't mention about the use of LCA model, only 66 of the total studies included sensitivity analysis in the assessment. Integrated solid waste management was found to be the most preferred waste management option. Also, a very limited number of studies have included life cycle costing and social aspects of MSWM system. The results indicated that the majority of the LCA studies are based in Europe and Asia. Shockingly, 178 out of the total countries in the world have not published a single LCA study on MSWM since 2013. Also, it was found that the effect of increasing Gross Domestic Product (GDP) on the publication of LCA studies is irrelevant, possible reasons being the lack of data, time and economic constraints. Establishment of environment-friendly policies and initiatives by the Government along with the participation of public, non-government and private organizations through training courses and seminars might help in improving the LCA applicability in the field of MSWM. Highlights • Critical review of LCA studies of MSWM all over the world published since 2013. • Adoption of LCA methodology evaluated. • Comparison of LCA studies on the basis of income level of the respective countries. • Gaps identified in application of LCA all over the world. [ABSTRACT FROM AUTHOR]

The concept of NZEB (Nearly Zero Energy Building) has a promising share to fulfill the future of sustainable development goals. However, exploiting renewable-based THESs (Trigeneration Hybrid Energy Systems) for providing the energetic demands of the building sector needs further attention. In this regard, the present paper proposes a sustainable THES driven by a biogas-fueled gas engine. The bottoming systems comprise absorption/electrical chillers (AC and EC), organic Rankine cycle (ORC), solar collector (PTC), and an auxiliary boiler. A detailed sustainability evaluation framework (technical and eco-environment) is derived to approve the performance of the THES. Within this procedure, the best working fluid of the ORC is firstly selected and then the sensitivity of the system performance to the design variables is assessed by a comprehensive parametric study. To make the derived framework more applicable, a case study building is considered and the proposed THES is sized to meet its electricity, heating, and cooling energies. The analyses proved that R123 shows the best techno-economic performance among six investigated ORC working fluids. The parametric study illustrated that the highest and lowest sensitivity of the THES's performance is related to the outlet temperatures of EC condenser and AC evaporator. Furthermore, the energy, exergy, and economic efficiencies of the THES for the case study building are 61.78%, 25.24%, and 44.77%. In this condition, discounted payback period is 7 years, demonstrating the feasibility of this proposal. The maximum CO 2 emission is released in November, with a total electricity generation of 320 MWh. [Display omitted] • Renewable-based hybrid system is introduced to produce cold, heat, and power. • Comprehensive sensitivity analysis is done to assess impact of some decision variables. • A case study building is considered to boost NZEB concept based on the proposed system. • Energy efficiency and payback period is 61.78% and 7 years for the case study building. • Using renewables in energy systems to reduce fossil fuel share has great significance. [ABSTRACT FROM AUTHOR]

The multi-physics coupling process during the heat extraction from enhanced geothermal system, encompassing thermo(T)-hydro(H)-mechanical(M)-chemical(C) interactions, plays a pivotal role in changing geothermal reservoir characteristics. However, a comprehensive quantitative assessment of these multi-physics behaviors has been lacking. In this study, a novel approach was proposed to calculate the magnitude of mechanical, chemical, strong mechanical-chemical coupling, and weak mechanical-chemical coupling effects on the variations of reservoir characteristics. In particular, mechanical-chemical coupling effects are quantified for the first time. They are obtained by the fracture aperture difference results across five distinct coupling models (thermo-hydro, thermo-hydro-chemical, thermo-hydro-mechanical, partially-coupled four-field, and fully-coupled four-field models). The findings indicate that mechanical effects lead to an increase in fracture aperture, while chemical effects contribute to its reduction under underbalanced injection conditions. Strong mechanical-chemical coupling effects, exhibiting a negative correlation with chemical effects, conversely result in a diminished fracture aperture. The influences of these effects are investigated from the temporal and spatial perspectives. Temporally, mechanical effects dominate early production while chemical effects become prominent in later stages. Spatially, there mainly exists two zones when stable production: a mechanical-controlled region surrounding injection wells, and a chemical-controlled area distant from the injection wells. Furthermore, sensitivity analysis of injection concentration indicates its alternation changes the reservoir traits and production performance by modifying the magnitudes of chemical and mechanical-chemical coupling effects. This quantification of multi-physics effects offers insights into optimizing injection strategies for better geothermal development. The approach could hold promising potential in other geo-energy scenarios like carbon and hydrogen storage in reservoirs. [Display omitted] • Multi-physics distributions in EGS are presented with the THMC coupling model. • Mechanical, chemical, strong and weak MC coupling effects are quantified. • Strong MC coupling exhibits a negative correlation with chemical effects. • Reservoir features mechanical- and chemical-driven zones when stable production. • Injection concentration affects production via chemical and strong MC coupling. [ABSTRACT FROM AUTHOR]

Proton exchange membrane electrolytic cells (PEMECs) are considered cleaner energy-conversion devices with potential commercial applications in hydrogen production. However, the heat- and mass-transfer characteristics inside the cell remain unclear, and its performance should be optimized to achieve future commercial applications. A three-dimensional multi-physical field-coupling model is developed for the PEMEC. Subsequently, a multi-objective optimization design is used to optimize the structural and operational parameters of the cell based on a neural-network regression model. The results of the sensitivity and response-surface analyses indicate that the initial working temperature has the most significant impact on the reaction temperature, the current density is increased by up to 65.22% under the coupling effects of temperature and flow rate. The cell performance is also enhanced by the increased channel width and depth, although this is accompanied by limitations. Under the combined effects of increasing the working temperature and channel width or height, the current density can be increased by a maximum of 65.22% and 38.61%, respectively. The improvement in cell performance requires a trade-off between improved mass and heat transfer and larger pressure drop, and the optimal design achieves this trade-off. In optimal design, the current density is improved by up to 16.56%, the oxygen mass fraction of the catalytic layer is reduced by 40.90% compared with the original design, accompanied by a reasonable pressure drop and uniform temperature distribution. This study provides a novel perspective for the optimization of the PEMEC to promote its commercial application, offering a reference for further advanced optimization of cell performance and reducing trial-and-error costs. It is also expected to have practical applications in energy conservation and sustainable development. [Display omitted] • A two-phase multi-physical field coupling model is developed for PEMEC. • A sensitivity analysis is conducted to evaluate the impact of design parameters. • Response-surface analyses is conducted to study the combined effects of parameters. • Intelligent optimization algorithm is used in multi-objective optimization design. [ABSTRACT FROM AUTHOR]

In order to achieve very efficient heat recovery, this study presents an innovative, environmentally friendly multigeneration process that is incorporated into a natural gas combined cycle system. A water electrolyzer, an enhanced absorption refrigeration cycle, a water desalination unit, and methanol production are only a few of the subsystems that must be used in this process. The simulation methods are carried out using the Aspen HYSYS program, which allows for a comprehensive study about the thermo-economic-environmental component. The feasibility analysis results show that the system can produce 111 MW of electricity, 175.6 kg/s of chilled water, 334.9 kg/s of domestic hot water, 7.54 kg/s of oxygen, 18.8 kg/s of fresh water, and 4.59 kg/s of methanol. Consequently, it is found that the energy and energy efficiencies are, respectively, 55.58% and 62.36%. It is shown that 344.3 MW is the overall irreversibility related to the suggested construction. Notably, the combustion chamber contributes the most of all the components, making up a significant 42.94% of the total. The primary cause of irreversibility among the subsystems is the natural gas combined cycle, which accounts for 76% of the total. Furthermore, from an economic standpoint, the entire product cost is 0.0566 $/kWh, but the total unit cost of the goods is 3.59 $/GJ. Additionally, 807.98 M$ is the determined number for the net present value. Furthermore, the suggested system has a carbon dioxide footprint of 0.286 kgCO2/kWh. This variable is 8.88% and 8.13% less than those of stand-alone power plants powered by natural gas and oil, respectively. • Proposal and process development based on a natural gas-def combine power plant. • Generating cooling, heat, electricity, fresh water, oxygen, and methanol simultaneously. • Using Aspen HYSYS for simulation and performing 4 E study. • Exergy efficiency and CO 2 footprint are equal to 62.36% and 0.286 kg CO2 /kWh. • Increasing the H 2 -to-CO 2 ratio results in an increase in methanol production. [ABSTRACT FROM AUTHOR]

The application of solar energy technology to solve the freshwater scarcity problem of society will contribute to the sustainable development goal of the United Nations. It will also recede the dependency on fossil fuels. This paper deals with the investigation of conical passive solar still (CPSS) by incorporating energy metrics, efficiency, and sensitivity analyses. Fundamental equations have been obtained from the thermal modelling of CPSS followed by experimental validation. The coefficient of correlation for water temperature is about 0.96, for condensing surface temperature is about 0.99 and for freshwater yield is also 0.99. The present work involves diverse monthly weather conditions for the performance analysis of CPSS. In the present work, a MATLAB-based computational code is used to compute hourly freshwater output, exergy, and energy assessment for their yearly results. Afterward, energy metrics and different efficiencies were computed, and the outcomes were compared with recent investigations. Finally, the energy payback time has been lowered by 161.40%. The energy production factor and life cycle conversion efficiency for CPSS were improved by 61.71% and 28.20%, respectively, compared with the conventional solar still. The comparative study of daily thermal efficiency reveals that the efficiency of CPSS is higher by 51.47% than V-type solar still. • Characteristic equations for conical passive solar still has been developed. • Energy metrics, efficiency, and sensitivity analyses for CPSS have been carried out. • Energy payback time for CPSS is lower by 161.40% than single slope passive solar still. • Life cycle conversion efficiency for CPSS is 28.20% higher over conventional solar still. • The daily thermal efficiency for CPSS is higher by 51.47% higher than V type solar still. [ABSTRACT FROM AUTHOR]

This study investigates a wind power-photovoltaic-concentrated solar power (WP-PV-CSP) system that incorporates different supercritical CO 2 (S-CO 2) Brayton cycle layouts to address grid-connected safety issues associated with solar and wind energy. Additionally, it aims to enhance the system's techno-economic performance. Notably, prior research has not explored the optimal capacity configuration of the WP-PV-CSP system or identified the most effective S-CO 2 Brayton cycle layout for system optimization. Reasonable capacity allocation can guarantee the system's reliability and feasibility, while an appropriate operation schedule can better handle the problem of mismatch between output and demand, and capacity and operation interact with each other. Consequently, this paper proposes a bi-level capacity-operation collaborative optimization approach to optimize the system's main components' capacity and operation scheduling with the optimization objectives of levelized cost of energy (LCOE) and CO 2 emissions. Moreover, it seeks to pinpoint the most advantageous S-CO 2 Brayton cycle layout. The results demonstrate that employing the S-CO 2 intercooling Brayton cycle as the CSP system's power cycle yields the WP-PV-CSP system's best techno-economic performance. Compared with the WP-PV-CSP system integrating the steam Rankine cycle, the LCOE, CO 2 emissions, and power discard are reduced by 13.81%, 40.36%, and 37.06%, respectively, and the system efficiency experiences a noteworthy 36.36% increase. These findings comprehensively highlight the substantial techno-economic and environmental advantages of adopting the S-CO 2 Brayton cycle. In summary, this research contributes valuable insights into optimizing WP-PV-CSP systems, explicitly addressing capacity and operational challenges, and underscores the potential benefits of selecting the S-CO 2 Brayton cycle in advancing renewable energy solutions. • A renewable energy system integrating S-CO 2 Brayton cycle is studied. • A bi-level model is proposed for simultaneous capacity and operation optimization. • Optimal power cycle layout for WP-PV-CSP system with LCOE and CO 2 as objectives. • Sensitivity analysis of main equipment capacity and meteorological data. [ABSTRACT FROM AUTHOR]

Limiting the global temperatures to +1.5 °C from pre-industrial levels requires achieving net-zero greenhouse gas emissions by 2050. This should be achieved across all sectors, and for electrical and electronic equipment (EEE) the promotion of repair, lifetime extension and other Circular Economy (CE) strategies are often proposed as the main areas for intervention. However, few studies have quantified and compared the effectiveness of different CE strategies at reducing emissions at a national level and into the future. To fill this gap, an extended dynamic stock model was combined with a device energy consumption model to anticipate the embodied, operational, and repair energy requirements arising from the stocks and flows of seven devices up to 2050 in the United Kingdom (UK). To understand the relative influence of all model inputs on device energy demand in 2050, a variance-based sensitivity analysis was performed using the Sobol method. The results show that device size is the most significant variable for six out of the seven devices. Whereas substantial increases in device lifetime and repair rates were shown not to be significant in reducing energy demand. A reduction of 30% of energy demand by 2050 is possible for almost all EEE devices, except laptops and TVs. However, delivering these savings requires significant changes to consumption behaviours such as decreasing device size by about 40% or decreasing ownership rates by approximately two thirds through shared ownership. This analysis prioritises the most impactful strategies to reduce the total energy demand of EEE in the UK. • Impacts of various strategies are tested for seven household electronics. • The influence of these strategies on future energy demand is quantified. • Device size is a significant lever across most devices to reduce energy demand. • Operational efficiency should be prioritised for white goods. [ABSTRACT FROM AUTHOR]

As the importance of achieving carbon neutrality continues to grow, green hydrogen energy has emerged as a promising solution as a clean and sustainable energy source. One of the environmentally friendly methods of producing hydrogen is through offshore wind energy, which generates no pollutants during the process. While there have been economic analyses conducted on this production process, the subsequent life cycle study of hydrogen transport scenarios is often overlooked. To bridge this gap, this study focuses on conducting a comprehensive life cycle cost analysis of two hydrogen transport scenarios that utilize ammonia as the carrier. The analysis encompasses various aspects, including life cycle cost analysis, net present value, and the calculation of the levelized cost of hydrogen. Comprehensive sensitivity analysis is performed, considering indicators such as boil-off gas leakage rate and annual transportation mass. Furthermore, this study analyzes the operational risk rate and payback period of the two transportation scenarios. The findings reveal that for transportation distances within 100 km, the life cycle construction cost for the pipeline transport scenario amounts to 761 M$, whereas for ship transportation, it is 201 M$. The annual transport mass for the pipeline is estimated to be 12,000 metric tons, while for the ship, it is 8600 metric tons. The levelized cost of hydrogen is calculated to be 14.62 $/kg for pipeline transportation and 15.54 $/kg for ship transportation. Notably, the annual transport mass emerges as a significant factor impacting the levelized cost of hydrogen in both scenarios. Furthermore, by achieving an annual transport mass of 18,000 metric tons, the levelized cost of hydrogen can be reduced to 10.42 $/kg when the transportation distance extends to 450 km. This highlights the importance of considering the annual transport mass to optimize the cost-efficiency of hydrogen transportation. [Display omitted] • Life cycle cost analysis is conducted for ammonia-based hydrogen transport. • Two typical offshore hydrogen transport scenarios are studied comparatively. • Net present value, leveling cost of hydrogen, and contribution rate are considered. • Annual transport mass is a vital factor affecting levelized cost of hydrogen. [ABSTRACT FROM AUTHOR]

Flexible options are expected to be adopted in climate change mitigation strategies due to the high uncertainty of climate change. Real options analysis (ROA) matches the feature of filling flexibility under climate change but is seldom leveraged in the decision-making of strategy investment at the building scale. This study proposes a ROA-based decision-making framework to bridge this research gap. First, the future energy consumption is simulated, and the expected yearly future energy loss caused by climate change is calculated. Then, individual and sequential investment analyses are made based on ROA and three strategies (i.e., "shading", "photovoltaic panels", and "shading + photovoltaic panels"). Finally, a sensitivity analysis for optimal investment time, investment sequence, etc., is performed, and regression analysis is used to prove and extend the sensitivity analysis results. The results show that climate change uncertainty does not alter the optimal individual and sequential investment strategies. However, increasing the discount rate advances the optimal investment time and shows an exponential relationship with the premium. The enhancement of forcing has a "marginal effect" on project return and it advances the optimal investment year for individual investment. Additionally, the forcing positively correlates with the benefit of deferring the option under shared socioeconomic pathways SSP1-2.6 and SSP2-4.5 but it negatively correlates with the benefit of deferring the option under SSP3-7.0 and SSP5-8.5. The unit dry bulb temperature under certain forcing yields a range of benefits from 0.47 × 106 to 0.90 × 106 USD when deferring the option. This proposed decision-making framework guides the development of mitigation strategies and provides more managerial flexibility for investors. [Display omitted] • A ROA-based mitigation strategies investment decision-making model is proposed. • Climate change uncertainty does not alter the optimal investment strategies. • Enhancement of forcing scenario has a "marginal effect" on project return. • Enhancement of forcing scenario advances the optimal investment year. • ROA method yields benefits from 0.47 × 106 to 0.90 × 106 USD/oC when deferring option. [ABSTRACT FROM AUTHOR]

The study focused on groundwater evaluation of the trans-Himalayan region using a novel concept of Hybrid Analytic Network Process (ANP) - entropy and Holt's exponential smoothing model for short-term prediction of groundwater quality. Hierarchy cluster analysis of groundwater was performed to identify the sources and spatial distribution of water quality. The PCA coupled with multivariate analysis dictated a high correlation of various ions i.e., NO 3 −, K+, F−, Cl−, SO 4 2−, PO 4 2−, and Na+ with the lithology of the area and helped in identification of various polluting sources i.e., excessive use of fertilizers, wastewater discharges and agrochemicals. The hybrid ANP-entropy technique offered a holistic approach to provide a more accurate and complete understanding of groundwater quality and revealed that groundwater quality in 21.43% (in winter) and 42.86% (in summer) of the locations fall into the poor category. The non-carcinogenic health risk analysis revealed that fluoride poses a major potential health risk followed by nitrate, primarily via the oral pathway while it was negligible through the dermal pathway. The total hazard index was observed highest in children (1.99) followed by infants (1.64). 95th percentile of the probable risk obtained through Monte Carlo simulation also dictated highest risk to infants than child. The predicted values of the Holt's exponential smoothing model for the year 2021 and 2022 was varied within ±5 % of the observed values. The proposed model effectively treats uncertainties in groundwater quality assessment and considers average and incremental increase both hence, can be used for short-term prediction and trend analysis of groundwater quality. [Display omitted] • A hybrid indexing system (ANP-entropy) proposed for assessment of groundwater quality. • Holt's exponential smoothing model was efficient in short term time series prediction. • Monte Carlo simulation provided most reliable estimates of the probable health risk. • Sensitivity analysis dictated NO 3 − being the most dominant pollutants followed by F−. [ABSTRACT FROM AUTHOR]

This study investigates a multi-echelon closed-loop supply chain model integrating learning impact with a single producer, single retailer, and single collector. Retail pricing, green innovation, and marketing efforts are assumed to have a linear relationship with end-user demand. The return of rejected goods occurs at random and is subject to an imperfect inspection procedure that is vulnerable to two different types of classification error. An S-shaped learning curve is considered to soothe the inspection process which is subject to inaccuracy. Numerical examples are used to illustrate the implications of the suggested model in order to achieve a goal that benefits both the consignor and the consignee. It is investigated whether the learning effect can outweigh the loss even when the inspection error has a detrimental effect on supply chain earnings. To identify the crucial parameters that can spark some truly exceptional managerial ideas, a sensitivity analysis is carried out. [ABSTRACT FROM AUTHOR]

It is critical to arrange appropriate charging infrastructure in advance to decarbonise heavy freight through electrification. Based on the same service level, this study conducted a techno-economic comparison of charging modes for battery heavy-duty vehicles in short-haul delivery, covering the broadest range of charging modes, including slow, fast (150 kW), fast (350 kW), swap, and overhead catenary. The techno-economic performance is obtained by a model composed of five evaluation indicators, in which the ratio of service capacity to cost and the average financial net present value are specific. The factors influencing the techno-economic performance of charging modes are further explored based on case analysis. Results show that the charging modes of slow, fast (150 kW), fast (350 kW), swap, and overhead catenary are not profitable under the corresponding facility utilisation rates of 40%, 20%, 20%, 30%, and 70%, or under operating years of 5, 3, 2, 4, and 12 years. Fast charging, at both 150 and 350 kW, has a better advantage in profitability based on the highest average financial net present value. Swap charging is best regarding energy supplement efficiency, but it is not profitable when the battery swapping price is less than 0.8 CNY/kWh. Overhead catenary charging is the most effective system per unit cost due to the highest ratio of service capacity to cost. The insights, the precise prediction of the charging demand, the focus on the charging price, and the comprehensive improvement in the facility utilisation rate are crucial for the success of charging service providers. • Techno-economic comparison of all mainstream and potential charging modes was done. • The facility utilisation rate is the key to profit for all charging modes. • Fast charging has a better profitability advantage for short-haul battery trucks. • Swap charging is best in the aspect of energy supplement efficiency. • Overhead catenary charging has the largest service capacity at the unit cost. [ABSTRACT FROM AUTHOR]

Nanocellulose is a promising biopolymer compound which is produced from pulp. However, the traditional approaches do not produce it in an energy efficient and sustainable way. The production of nanocellulose through moderate refining and froth flotation has the potential to reduce the traditional nanocellulose production cost. This technoeconomic analysis explores the financial profitability of using moderate refining followed by enhanced froth flotation technology at pilot scale (best case scenario) to produce nanocellulose in an affordable and sustainable way. With a 100% nanocellulose yield, the yearly the operational cost was $7312 AUD/ton nanocellulose for the best-case scenario. The 25-year NPV coming from discounted cumulative cash flow rate for best case scenario is approximately 9.5 million AUD (profit). From the sensitivity analysis it was revealed that the key driver behind profitability of nanocellulose production is Capital Cost and Labour cost. Lastly four different case scenarios are explored to examine the economic viability for commercial scale nanocellulose production. For a similar level of nanocellulose pulp quality development, there is an energy savings of approximately 5000 kWh/t (aspect ratio), 2000 kWh/t (fines) and 15,000 kWh/t (volumetric specific surface) in moderate refining combined with enhanced flotation at bench scale, when compared with extensive refining stand alone. There is minimal or no energy savings when flotation is used at a laboratory scale. Technoeconomic assessment for nanocellulose production at pilot scale was evaluated and compared with that of bench scale and it was revealed that moderate refining followed with flotation at pilot scale is most economical. The high ROI of 175.3% and NPV of $9.5 million for moderate refining along with flotation at pilot scale demonstrates flotation technology is worth investing for nanocellulose production at pilot scale. [Display omitted] • Bench vs pilot scale comparison for nanocellulose production. • Harnessing the energy saving and financial profitability of flotation technology. • Capital expenditure and Labour Operating cost are major economic factors. • Enhanced bench scale flotation is energy efficient. [ABSTRACT FROM AUTHOR]

Abstract In many developing countries, the lack of electricity in rural areas is still a key issue for millions of people. The reuse of discarded components in renewable energy systems, based on the frugal innovation concept, has been identified as a solution for rural electrification in countries where renewable resource is plentiful. Specific emphasis is paid in this work to the application of reuse from an engineering viewpoint for a Renewable Energy System, including a "solar" element, composed of solar Photovoltaic (PV) panels and of modified Power Supply Units (PSUs), a "hydro" part and an energy storage system with used car batteries. The scientific objective of this work is to evaluate the environmental impact of this solution, considering only the solar element, as compared to a conventional system consisting of photovoltaic panels, lead-acid batteries, a charge controller and an inverter for small village consumption. For this purpose, Life Cycle Assessment (LCA) has been selected as a methodological framework and both solutions have been described and sized. The results have shown that in the reuse scenario, the impact of PSUs, Uninterruptable Power Supply Units (UPSs) and a microcontroller kit remains very low (0.12% of total impact) while PV modules contribute significantly (66% of total impact). Nevertheless, the consequences of reusing lead-acid batteries are still significant due to the combination of several effects: their weight, reduced efficiency and the need for frequent replacement. A 40% reduction of the environmental burden obtained by the reuse solution is clearly due to the absence of battery production impacts in the case of reuse. A sensitivity analysis has been performed to determine the impact of parameters such as component efficiency, lifetime and transportation distance on environmental impacts. The efficiency of repurposed PSUs and UPSs is the most significant parameter on the environmental impact categories in the reuse solution. [ABSTRACT FROM AUTHOR]