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Sustainability pertains to the interplay between environmental, economic, and social systems at varying scales. In transportation systems, vehicles use different fuels to fulfill their energy requirements. However these fuels emit green house gases that pollute the environment. Taking into account this fact, the present paper delves into the investigation of a multi-objective multi-item fixed cost solid transportation problem with various driving styles. Also, three types of fuels are incorporated in the proposed model. The primary focus of this paper is to maximize profit by reducing breakage of the items along with reducing carbon emission and time of transportation. In real-life situations, the parameters of multi-objective multi-item fixed cost solid transportation problem may not be tackled crisply. Hence triangular intuitionistic fuzzy numbers are introduced in the proposed model. The score function is employed to convert intuitionistic fuzzy problem to deterministic one. Thereafter, a methodology is developed to solve the proposed model involving different driving styles and is extended to consider the optimistic, pessimistic, and mixed view of the decision maker. Comparisons are made among the compromise solutions that are derived from different approaches and are shown by various charts and graphs. A case study is included to illustrate the applicability and validity of the proposed methodology. • A sustainable multi-objective 4DTP with multiple items and fixed charge is modeled. • Three types of fuels: diesel, petrol and CNG are incorporated in the proposed model. • Driving style is included to analyze the fuel consumption and breakability of items. • The decision-maker's optimistic, pessimistic, and mixed viewpoints are discussed. [ABSTRACT FROM AUTHOR]

Alternative fuels are the subject of growing interest among both researchers and practitioners. In this aspect, to properly handle the problem of proper evaluating alternative fuels, appropriate methods, and tools are undoubtedly needed. Since the evaluation of sustainable alternative fuels similarly, like most sustainability problems, has a multi-criteria character, multi-criteria methods have the potential to be employed here. Analysis of the alternative fuels domain indicates that classical multi-criteria methods are not exactly suitable for use in cases where, instead of a single matrix for evaluating alternatives, we have a set of them collected for particular periods. Therefore, developing a dedicated approach that considers the specifics of a given problem is necessary. For this purpose, the paper proposes a new Temporal Preference Ranking Organization Method for Enrichment Evaluations II (PROMETHEE II) method for multi-criteria temporal evaluation. Hence, the presented method solves the limitations occurring in previously developed multi-criteria methods. In addition to the classical aspect of evaluating the options under consideration, the proposed method makes it possible to accurately grasp the dynamics of the outcomes and put them into an easy-to-interpret result. A practical contribution of the paper is applying the developed method to a multi-criteria temporal evaluation of sustainable consumption of alternative fuels in road transport. For this purpose, an assessment model was built based on the data for 32 European countries acquired from the European Union's statistical office (Eurostat). Preference imprecision modeling and model sensitivity analysis demonstrated the analytical potential of the developed sustainability assessment model and, simultaneously, the Temporal PROMETHEE method's superiority. The comparative analysis of the Temporal PROMETHEE II method clearly shows that the results are robust and reliable, and the developed method is suitable for evaluating various temporal sustainability problems. The research demonstrated that a model alternative fuel mix and its shape as well as progression is maintained by Scandinavian countries such as Norway and Sweden. [Display omitted] • A new temporal method for multi-criteria sustainability assessment. • Public available algorithm and code of method developed. • An evaluation of sustainable consumption of alternative fuels. [ABSTRACT FROM AUTHOR]

Abstract Currently, wind and solar energy have not been well utilized in China, and the rate of abandoned wind and solar facilities in China is increasing annually. Renewable portfolio standards (RPS) are an effective system for promoting large-scale renewable energy integration and consumption and realizing the goal of renewable energy development. To clarify the interactive relationship between the different levels and multiple actors in RPS, this paper uses policy network theory to analyze the interactive relationship of stakeholders from the three aspects of network subject, network structure and network interaction. The policy network of the RPS consists of the policy community, professional network, intergovernmental network, producer network and issue network. Under the RPS, to meet their own needs, participants affect the formulation and implementation of the RPS through the actions of confrontation, alliance, competition and cooperation. In different stages of developing the RPS, the openness and integration of policy networks change accordingly. This study overcomes the limitations of past simple analyses of the actor relationship in the policy process and thereby offers certain reference significance. Highlights • The actors of RPS policy networks are analyzed. • This paper analyze the game relationship of the stakeholders from three aspects. • This research reveals the network relationship between multiple stakeholders. • This study breaks through the limitations of past analysis of actor relationship. [ABSTRACT FROM AUTHOR]

Abstract Railways are a rather efficient transport mean, and yet there is increasing interest in reducing their energy consumption and making them more sustainable in the current context of climate change. Many studies try to model, analyse and optimise the energy consumed by railways, and there is a wide diversity of methods, techniques and approaches regarding how to formulate and solve this problem. This paper aims to provide insight into this topic by reviewing up to 52 papers related to railways energy consumption. Two main areas are analysed: modelling techniques used to simulate train(s) movement and energy consumption, and optimisation methods used to achieve more efficient train circulations in railway networks. The most used methods in each case are briefly described and the main trends found are analysed. Furthermore, a statistical study has been carried out to recognise relationships between methods and optimisation variables. It was found that deterministic models based on the Davis equation are by far (85% of the papers reviewed) the most common in terms of modelling. As for optimisation, meta-heuristic methods are the preferred choice (57.8%), particularly Genetic Algorithms. Highlights • Modelling and optimisation methods for railways energy efficiency are reviewed. • Modelling methods provide reliable simulations of the trains' energy consumption. • Optimisation methods help obtaining the most efficient solutions for train traffic. • Most used modelling methods are deterministic, based on Davis equation. • Most used optimisation methods are meta-heuristics, mainly genetic algorithms. [ABSTRACT FROM AUTHOR]

Abstract The Chinese government conducted a policy experiment on real estate-led economic growth on such a massive scale, which is unprecedented. This paper empirically analyzes the impact of real estate investment on energy efficiency. Provincial level panel data of China during 2004–2012 was used for the analysis. Two-way Fixed Effect model was applied to test the impact of real estate investment on total-factor energy efficiency (TFEE). The findings in this paper are: a certain degree of the real estate-led model of economic development can improve TFEE of the economy. Developing countries can gain economic development and energy efficiency improvement simultaneously by developing the real estate industry to a certain extent. But the impact of real estate investment on TFEE exhibits a nonlinear characteristic, that is, when the real estate investment proportion exceeds the threshold value, the impact of real estate investment on TFEE will take a reversal; Except Beijing, Shanghai, Hainan and Zhejiang provinces, to some extent, improving real estate investment can be helpful to improve TFEE in most of China's provinces. Highlights • The Chinese government conducted a policy experiment of real estate-led economic growth and the scale is unprecedented. • The impact of real estate investment on TFEE exhibits an "inverted-U shaped" curve. • A certain degree of the real estate-led model of economic development can improve TFEE of the economy. • Except few provinces, most of the Chinese province are lying on the left side of the curve. • Panel data is used to assess the effect of real estate investment on TFEE. [ABSTRACT FROM AUTHOR]

Abstract Green and sustainability issues are being considered extensively in industry and in the literature. Most of the green-related effects in the manufacturing sector can be modeled by the costs associated with the production machines due to their resource consumption and/or pollutant emission, as a part of the operation cost. Accordingly, taking into account the machine processing costs alongside the other production criteria is one of the main approaches to consider green issues in the production management problems. In the same way, scheduling as one of the major operational problems in the factories can benefit this point of view to involve sustainability aspects. In this paper, the aforementioned modeling approach is taken one more time to establish a formulation for a green scheduling problem in uniform parallel machine environments. Here, it is assumed that the machines have different processing cost rates, i.e. they are different with regard to sustainability. The considered problem objectives are the total green cost and the makespan which are minimized simultaneously with the aim of earning Pareto optimal solutions. To this end, the ε -constraint method is first used to convert the problem into single objective problems. Then an existing heuristic is improved to solve these problems and estimate the Pareto solutions that show the trade-offs between the green cost objective and the ordinary time objective. Moreover, having a rigorous analyze in a theorem, some useful upper bounds for the gap of the green cost of the heuristic solution from optimality is derived. Finally, conducting numerical experiments at the end of the paper, the superiority of the improved heuristic to the previous one and its effectiveness in approximating the Pareto optimal solutions is demonstrated. Graphical abstract Image 1096644 Highlights • A green scheduling model in uniform parallel machine environments is developed. • The machines are assumed to have different sustainability costs. • The aim is to minimize both the total costs and the makespan, simultaneously. • The ε-constraint method is first used to convert the problem into single objective problems. • An improved version of an existing heuristic is utilized to solve the problems. [ABSTRACT FROM AUTHOR]

Abstract Water pumping systems are widely used in industrial and civil applications. During their operational life, they consume energy and materials (mainly for installation and replacement of components). The aim of this paper is to optimize the pump operations in order to save energy and enlarge the operational life of the pumps and their components. This paper addresses the multi-period (e.g. 24-hours time horizon) optimization of pumping systems. To this end, we have developed a simulation-based optimization approach including novel relevant technical features of a generic but realistic pumping system, namely cavitation and overflow. The proposed multi-period optimization differs further from the classic static optimization (i.e. at the design stage), proposing a new dynamic approach in which pump activation is steered dynamically for an optimal management of the variability of water inflow. Furthermore, the problem includes constraints on the number of pump activations allowed to reduce material strain. The performances of different meta-heuristic optimization algorithms (e.g. genetic algorithm, simulated annealing and particle swarm optimization) for solving the problem are compared. The numerical results show that energy savings are possible with the dynamic approach and that particle swarm optimization and simulated annealing algorithms provide the most suitable solutions for this problem. Highlights • Three algorithms are compared to minimize energy pump consumption. • The pump model includes energy, cavitation, overow and activation frequency. • Static and dynamic optimizations are investigated. • The dynamic optimization can reduce the energy consumption by 6.5%. [ABSTRACT FROM AUTHOR]

Abstract The extensive use of energy-saving appliances can promote household energy conservation, which, to a certain extent, can help to alleviate haze pollution. Based on the Theory of Planned Behavior and Normative Activation Model, a research framework is developed in this paper to explore residents' intention to purchase energy-saving appliances under the influence of severe haze pollution. This paper takes the residents in Xuzhou as the object of survey. Then, the structural equation model and Bootstrap method are used to analyze the valid measurement questionnaires. The results demonstrate that residents had a very strong intention to purchase energy-saving appliances under the influence of haze pollution from the perspective of self-interest and altruism, respectively. Attitude, subjective norm, perceived behavior control and personal norm are the key factors influencing residents' purchasing intention of energy-saving appliances under frequent haze pollution, of which attitude is the most powerful influence. In addition, ascription of responsibility is a partial mediator between the relationship of awareness of consequences and personal norm, and together with awareness of consequences can positively influence personal norm. Finally, based on the empirical results, this paper proposes measures to guide consumers to buy energy-saving appliances. [ABSTRACT FROM AUTHOR]

Abstract As an effective way to reduce power consumption, coasting has been widely used during the operation of high-speed train. However, as a typical electromechanical coupling system, the different speed of inert point may lead to complex dynamic behavior of high-speed train and affect the safety operation. Based on this, this paper proposes an optimization methodology of the coasting point to simultaneously ensure the safety operation and energy saving of the train. A mathematical model of permanent magnet synchronous motor (PMSM) during coasting is established, and the local stability and bifurcation conditions are derived based on Routh-Hurwitz criterion and the bifurcation theory. And the influence of load torque variation on bifurcation characteristics of equilibrium point and stable operation domain of the system is studied. Moreover, detailed numerical simulations are carried out to analyze the effect of load torque on the coasting point, and an optimization methodology is proposed. Experimental platform is set up to verify the correctness and the effectiveness of the proposed optimization methodology. The results show that the variation of the motor parameters may the occurrence of Fold and Hopf bifurcations, and the increase of load torque may change the bifurcation characteristics and lead the system to transit into a chaotic state and lose stability. The experimental results show that the optimization method proposed in this paper can effectively reduce the energy consumption by 7.7 percent. Highlights • A dynamic model of PMSM for high-speed train during coasting is established. • The influence of the change of load torque on the stable operation domain of high-speed is studied. • Under the premise of ensuring the safe operation of high-speed train, an optimization methodology of the coasting point is proposed. [ABSTRACT FROM AUTHOR]

Abstract Environmental issues and cleaner production are getting increasing attentions currently, making the clean production and sustainable consumption with low emissions significant. Traditional energy vehicles are increasingly unsuitable for the development of current society. It's a trend in the current vehicle market to accelerate the substitution of new energy vehicles for traditional energy vehicles. This paper makes a theoretical study on the development of new energy vehicle market supported by the government. First, this paper establishes a Cournot duopoly model which includes domestic and imported new energy vehicle manufacturers. Through the analysis of this model, this paper argues that government support policies such as subsidies and tariffs can effectively expand the market share of domestic new energy vehicles with less technology. Yet this approach is unsustainable, because domestic new energy vehicles with less technology can only survive in the market by shortening the gap with imported brands. Secondly, this paper establishes a Stackelberg model with product price as the decision variable and find that when there is a technical gap, the first mover advantage in the market will no longer exist. Finally, this paper compares two kinds of subsidies for domestic new energy vehicles and shows that the two subsidies are not different from subsidizing consumers or enterprises in expanding market share, and the consumer can obtain higher social welfare level as the subsidy object. Highlights • New energy vehicles boom with obvious substitution effect on traditional ones. • Both subsidies and tariffs can expand the production of domestic new-energy cars. • First move of domestic brands into the market can narrow the price difference. • First mover advantage no longer exists in the Stackelberg game. • Consumer subsidy is superior to enterprise subsidy in new energy auto industry. [ABSTRACT FROM AUTHOR]

Abstract The governance of industrial energy use in recent times has been driven by the quest for greater energy security and sustainable industrial growth. Sustainable use of energy necessitates a rethink in the production, use and governance of energy resources that stimulates and supports transition to a more effective and efficient energy system. However, how do we ensure an effective transition in industrial energy use in the midst of gross energy poverty within a developing country context? This paper explores the motives and drivers of changes in energy use within the industrial sector. Statistical data from published reports, as well as informal interviews of stakeholders in Nigeria's industrial sector were used. Following analysis of data, four important salient phases (eras) of industrial energy transition in Nigeria's manufacturing sector was established. These distinct eras are: (1) Grid-dependent era; (2) Self-generation era; (3) Industrial energy outsourcing era; (4) Industrial energy conservation era. The study reveals that: outsourcing of industrial services; cost reduction; and business realignment motives are key drivers of transitions in Nigeria's industrial sector. This paper concludes by highlighting the implications of these changes for the future of energy and sustainable industrial growth in Nigeria. Highlights • Industrial energy transitions in Nigeria is happening but rather slow. • There is high dependence on biofuels and wastes for certain industrial processes. • Cost reduction and business realignment motives are key drivers of transitions. • Outsourcing industrial energy services is viewed as one way to drive transitions. [ABSTRACT FROM AUTHOR]

Abstract Onshore and offshore wind turbines may have different environmental sustainability due to their own characteristics, and this information is important for future growth of wind power. The paper uses life cycle assessment (LCA) to estimate the life-cycle greenhouse gas (GHG) emissions of onshore and offshore wind turbines with the nominal capacity of 2 MW, to advance our understanding of onshore and offshore wind energy and to inform policy, planning, and investment decisions for future growth of wind power. Results show that the life-cycle GHG emission intensity is 0.082 kg CO 2 -equivalent (eq)/Megajoule (MJ) for onshore wind turbine and is 0.130 kg CO 2 -eq/MJ for offshore wind turbine, respectively. Offshore wind turbine has larger life-cycle GHG emissions than onshore wind turbine, owing to the floating platform fixed in sea. Onshore and offshore wind turbines have much smaller life-cycle GHG emission intensity than coal power plants. If the installed wind turbines in 2014 displace coal, the saved GHG emissions can roughly reach 5.08 × 107 t CO 2 -eq, accounting for 0.09% of global GHG emissions in 2012. The sensitive analysis shows that the lifetime and energy production of wind turbine have large influences on the GHG emission intensity of both onshore and offshore wind turbines, implying that it is an effective way to prolong the lifetime of wind turbine and increase the energy production of wind turbine to reduce the GHG emission intensity of wind turbine. The sensitivity analysis further shows that the distance from wind turbine factory to wind farm site has more significant influence on the life-cycle GHG emission intensities of both onshore and offshore wind turbines than that from wind farm site to the recycling and landfill locations, suggesting that the wind farm site and the wind turbine factory should be as close as possible. Highlights • The paper presents a first attempt to analyse the life-cycle GHG emission of onshore and offshore wind turbines with same capacity size. • Offshore wind turbine has larger life-cycle GHG emissions than onshore wind turbine. • Onshore and offshore wind farms have much smaller life-cycle GHG emission intensity than coal power plants. • Lifetime and energy production have large influences on GHG emission intensity of onshore and offshore wind turbines. • If the installed wind turbines in 2014 displace coal, the saved GHG emissions can roughly reach 5.08 × 107 t CO 2 -eq. [ABSTRACT FROM AUTHOR]

Abstract With energy shortage and environmental pollution becoming increasingly severe problems, energy-efficient scheduling is attracting much more attention than before. This paper addresses the flexible job shop scheduling problem (FJSP) with the objective of minimizing total energy consumption. Firstly, the total energy consumption of the workshop is discussed and modelled. Then, based on two different modeling ideas namely idle time variable and idle energy variable, six new mixed integer linear programming (MILP) models with turning Off/On strategy are proposed. The original objective function of the model based on idle time variable is nonlinear and linearization is needed. For the linearization, additional decision variables and constraints are added. The objective function of the model based on idle energy variable is originally linear and concise. Lastly, those six proposed models and the existing one are detailedly compared and evaluated under both the size and computational complexities. The correctness and effectiveness of all MILP models are verified by using CPLEX SLOVER to carry out numerical experiments. The results show that the MILP models based on different modeling ideas vary remarkably in both size and computational complexities, and all the six models proposed in this paper outperform the existing model significantly. The proposed models will help the enterprises rationalize production so as to reduce energy consumption and costs. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we adopt a non-radial directional distance function to analyze the efficiency and shadow price of CO 2 emissions of coal-fired power plants. Using a sample of Shanghai's 20 coal-fired power plants, we find that the efficiency performance of power plants remained steady during the period 2007–2010. On average, the carbon abatement costs of Shanghai's power plants increased from 20.58 yuan/ton to 39.67 yuan/ton during 2007–2010. Although the average shadow price of the power plants increased during the period, the price was still well below shadow prices for the energy consumption of the industries, and a little lower than the trading price in the ETS markets. In addition, the paper discusses the implications of the findings. [ABSTRACT FROM AUTHOR]

Abstract A rapid development of building environmental research from the globe is witnessed in recent years to deal with the environmental issues, especially in terms of energy consumption and carbon emissions, due to the substantial environmental burdens associated with the building industry. Thus, numerous scientific efforts have been devoted to buildings through environmental assessment like a life cycle assessment (LCA) and a methodological framework development. Concerning the rapid growth of buildings, LCA is increasingly used for assessing and mitigating the associated environmental impacts from material selection to the whole building systems. This study aims to comprehensively review the LCA implication on buildings by discussing the contemporary issues related to the development of this research field. The study considers a wide range of literature including case studies, reviews and surveys, and these articles are critically examined according to the predefined criteria developed. An in-depth analysis is also conducted on selected studies to unveil the criticality of the assessments and results under different considerations. In addition to demonstrating the research gaps for comprehensive assessment of buildings, the adoption of a circular economy (CE) concept is highlighted by providing a comprehensive framework. The findings show that resource recovery and resource-efficient building construction are seldom considered in prevailing studies. As a result, the framework proposed in this paper should help support a paradigm shift towards a comprehensive research for increasing the accuracy and practicability by introducing the CE principle to the building industry for enhancing its sustainability performance. Highlights • Literature related to building-environmental research was critically analyzed. • LCA implication on buildings was comprehensively reviewed by discussing the contemporary issues. • Selected papers were critically analyzed to unveil the research trends and practices. • Knowledge gaps for comprehensive assessment of buildings under the CE principle are identified. • Comprehensive framework based on the CE principle was proposed for comprehensiveness building LCA. [ABSTRACT FROM AUTHOR]

Abstract Most of the sustainable scheduling research deals with some environmental issues such as electricity consumption or carbon emissions although there are many other environmental and social indicators. Whereas, more and more manufactures are executing many solutions not only via implementation of environmentally-oriented but also socially responsible economically sound and management program. This proposed research has an objective to get a comprehensive view of the state and progress of sustainable scheduling by considering more sustainable indicators to assist many manufacturers to apply environmentally sound technological solutions. To achieve this objective, we, first, create a pool of sustainable manufacturing indicators that refers to some previous research that focus on applicable-proven indicators. Then, we employ an iterative process that is adapted from the general guidelines for literature review. We conceptualize, search, evaluate, analyze, and synthesize all 50 relevant papers resulting a completely new research framework to characterize the research. We use mathematical model components, i.e. manufacturing model, the system of objectives, objective function, constraints, model type, and optimization method, as the dimensions to classify the papers that were included in our analysis. We also apply the triple bottom line pillars – economic, environmental, and social to specify attributes and categories for the objective function and constraints. In literature classification step, the framework seems very sensitive since it can identify 49 different sustainable scheduling configurations from 50 reviewed papers. It means the framework can easily grasp the contributions of each paper. Then, in the analyses phase, we use 'sustainable link' to indicate if one research can be classified as sustainable scheduling research. The results show that energy cost and greenhouse gas indicators become the most frequently used indicators in sustainable scheduling. On the other hand, the mapping shows that some links have been rarely or never included, indicating potential areas for further research. We also list four main directions for future research which are: implementing other optimization methods; adding sustainability indicators; extending the model to a larger scale of manufacturing system; and loosening some assumptions. [ABSTRACT FROM AUTHOR]

Abstract Human activities cause massive CO 2 emission, and the Emission Trading Scheme (ETS) is currently one of the most effective methods of emission reduction. Few studies focus on the impact of different transfer payments in ETS on rural and urban population. This paper establishes a dynamic recursive Computable General Equilibrium (CGE) model and constructs 3 counter-measure scenarios (i.e. payment methods based on income, direct tax and population, respectively), following China's pilot ETS pattern, to analyze and provide insights on the best option for the government to transfer ETS revenues to rural and urban population. The results show that commodity consumption, energy consumption, direct tax, and social welfare will be significantly impacted by ETS transfer payments, while commodity price and household savings will be less affected. For rural population, more transfer payments will lead to an increase in consumption levels in the ETS transfer payments scenario based on population, despite the rise in commodity prices. Moreover, the payments based on population can also reduce by 15.09 billion tons of CO 2 emission during 2017–2030. Therefore, this paper suggests that the ETS transfer payments method should be based on population. Highlights • A dynamic recursive computable general equilibrium model is established. • Fossil energy consumption of households is strongly influenced by transfer payments. • Population-based ETS transfer payments should be adopted. • Consumption elasticity of rural residents is larger than that of urban residents. [ABSTRACT FROM AUTHOR]

Abstract China has encountered the environmental issues and energy pressures in the middle-income stage. Strengthening environmental regulation is a crucial measure to prevent environment deterioration and energy dilemma. This paper investigates the three types of environmental regulations on energy consumption using feasible generalized least squares method during 1997–2015 in direct and indirect path. The main conclusions are as follows. In the direct path, the economical and supervised types of environmental regulations have inhibited energy consumption whilst legal environmental regulation has no significant impact. As for indirect path, the "rebound effect" of energy is greater than the energy conservation generated by technological innovation, which is embodied as an inhibitory effect. The effects of environmental regulation display regional difference. The legal and supervised types of environmental regulations have significant "cost effect" and "rebound effect" on energy consumption in the entire samples. On the contrary, the economical environmental regulation shows the opposite sigh in eastern regions. The counterfactual simulation results show that the net effects of environmental regulations on energy consumption are negative, which is beneficial for relieving energy pressures. Based on the findings, this paper provides pertinent policy implications. Graphical abstract Image 1 Highlights • Environmental regulation can be divided into three types. • Environmental regulation can affect energy consumption in direct and indirect path. • Differernt types of environmental regulation have distinct impacts on energy consumption. • The effect of environmental regulation displays regional difference. • Strengthening environmental regulation can relieve energy pressure. [ABSTRACT FROM AUTHOR]

Abstract Energy efficiency improvement is usually regarded as an effective way to decrease energy consumption and to fight climate change, but it also booms energy consumption through rebound effects. But the improvement of energy efficiency also has rebound effects, which increases energy consumption and emission. So this paper arms to capture the rebound effects of efficiency improvement by considering zero-cost breakthrough of energy efficiency and price jump of energy purchase. First, energy efficiency improvement, measured by zero-cost breakthrough of energy efficiency, stimulates energy consumption, but it may reduce the total emission. Second, both the direct and indirect rebound effects of energy efficiency improvement on energy consumption and environment are captured. Interestingly, jumping energy price decreases both the direct and indirect rebound effect. Finally, the result of the paper shows that restriction of individuals' entry or competition restriction moderates the rebound effects of energy efficiency improvement. Highlights • Effect of competition on energy efficiency rebound effects is developed in theory. • Rebound effects of energy efficiency are captured under zero-cost breakthrough. • Moderate monopoly is proofed to be helpful for reducing energy efficiency rebound effects. • Improvement of energy efficiency has both direct and indirect rebound effects. • Energy price jump has offset effects on rebound effects of efficiency promotion. [ABSTRACT FROM AUTHOR]

The performance of a manufacturing system is measured by factors such as its productivity and energy efficiency. Current systems lack the required indices to measure its efficiency and highlight the areas of inefficiency in the system. The paper is aimed at improving the overall performance of manufacturing system by suggesting methods for integrated improvement in above two factors. This paper establishes performance indices for measuring energy efficiency and productivity of the system, which uses easily available sensor data from the production line. The energy structure and effects of downtime events on the production line has been analyzed to develop energy and productivity performance indicators. The indices are utilized to identify the machines which is most power inefficient and results in maximum production loss of the system. These indicators are utilized to illustrate our method for improving productivity and concepts of downtime-bottleneck and power-bottleneck. The methods proposed are verified by simulation studies. [ABSTRACT FROM AUTHOR]

This paper offers a combined theoretical and empirical assessment of energy democracy and degrowth in relation to the case study of a city's municipally-owned energy company in Sweden. Energy democracy is a fairly new concept and is a normative proposal that aims at articulating prospects for reduction of consumption, resource efficiency, use of renewable sources of energy and community empowerment. Though degrowth and energy democracy have similar goals and orientation, a combined analysis of both normative proposals remains underdeveloped. The focus on energy democracy serves us to articulate a deeper discussion on how technology, energy use and sustainability challenges interplay with definitions and meanings of degrowth vis-à-vis processes of capital accumulation. Empirically, we use the case of a municipality-based project of energy extraction and distribution in Sweden to discuss degrowth and energy democracy perspectives in this context. Theoretically, we develop insights from critical theories of technology. A main conclusion of the paper is that prospects for energy democracy and degrowth are limited in the energy project approached in the paper as it is based on the use of forest resources-a contested resource in the area - and also because this project assumes the development of economic processes oriented towards economic growth within the framework of capital accumulation. [ABSTRACT FROM AUTHOR]

The domestic sector uses the majority of the energy consumed in Palestine. The Palestinian Central Bureau of statistics (PCBS) performs periodic statistics regarding the average energy consumption of the households, but there is no up to date breakdown of the energy consumption in the residential sector. The Palestinian energy sector main challenges are the high fuel prices, lack of sustainable consumption and energy insecurity. Developing energy policies and studying the potential of shifting towards more independent and sustainable energy sources need a clear understanding of the current energy consumption. A survey was used to collect relevant quantitative and qualitative data. The total number of households in Hebron who responded to the survey was 322 households. The survey covered physical characteristics of the dwellings, socioeconomic features of the households in addition to the pattern of heating the spaces, quantity and type of fuel used for heating. On average the households heated only 9.2% of the total area of their houses during the winter days. The survey revealed that households spend 3.5%–21.6% of their monthly income on space heating during winter. The main contribution to knowledge of this paper is a regression model to estimate energy consumption based on the data collected from the survey. The regression model is developed with an R 2 adjusted 0.606 indicating 60.6% accuracy of the predicted energy consumed for heating. The regression model depends on 14 parameters which include the type of settlement, physical characteristics of the dwelling that are housing typology, level of thermal insulation of the walls, the main building materials and the housing age. It also depends on socioeconomic parameters which are the family monthly income and the occupancy period. Moreover, the type of the heating system used, the number of heated months and the nominal heated area were influential parameters in this model. The significance of this paper stems from the methodology that propose an alternative to the energy audit and simulation methods. The proposed method can be used in contexts where a combination of energy resources is used with no proper metering system and with the absence of accurate data that is needed for simulation. [ABSTRACT FROM AUTHOR]

Most economists focus on how a market system determines the consumption of resources, but the Chinese government controls its energy demand and succeeds to save energy. It is intriguing to ask about how the Chinese government reduces firms' (fossil) fuel consumption. To the best of our knowledge, this paper contributes by offering a first attempt to show how government intervention determines a firm's fuel-saving incentive. With evidence from China, this paper first documents that a firm's fuel intensity significantly constrains its profitability. In particular, the constraint effect is robust to potential endogeneity bias. Moreover, we confirm that the constraint effect of fuel intensity on profitability is larger for firms when the burden, intensity or capacity of a local government to intervene for ambient air quality is great than when the interventional burden, intensity or capacity is small. Thus, these findings offer application for fuel-saving intervention in a developing country. [ABSTRACT FROM AUTHOR]

The effect of the flow of knowledge on sustainable innovation in project-based firms in project-based industries is the subject of in-depth research in this paper. It studies the simultaneous functioning and effects of knowledge flow mechanisms on sustainable innovation in project-based firms in project-based industries; industries like the construction-, film-, game-, consultancy-, and IT-industry. To this end, a retrospective case study, covering 20 years (1989–2008) of sustainable innovation in the Dutch house-building industry, is conducted. This study finds that bundles of knowledge flow mechanisms stimulate both sustainable innovation creation by small networks of innovative firms that cooperate in demonstration projects, as well as stimulates a limited adoption of some of these created sustainable innovations by networks of larger incumbent firms outside these demonstration projects. Based on this finding the paper proposes a model and related propositions. To scholars it can serve as a basis for future research that further explores and tests the effect of the flow of knowledge on the eco-innovativeness of industries that heavily rely on projects. The findings can also be of benefit for policy and business practitioners in and around project-based industries. To them it can provide a route for getting sustainable innovations applied on a larger scale, from demonstration projects to regular projects. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) refers to a group of manufacturing techniques that produce components in a layer-by-layer fashion. By virtue of its capability to produce parts with complex geometry and functionally graded materials, AM has been introduced and used in multiple industrial sectors and is leading the way into the “third industrial revolution”. One of the key considerations in Additively Manufactured Products (AMP) is the issue of sustainability which attracts increasing attention as modern society becomes more aware of environmental concerns. As a response to the growing requirement for sustainability, industries and customers are inclined to assess products and services through the perspective of life cycle sustainability. The integration of life cycle sustainability and AMP is still an open question and is the primary motivation for this study. Since the eventual goal of all advanced technologies is to serve and satisfy human society, social sustainability must be an essential part of all decisions regarding AMP. Limited studies that integrate social sustainability into AMP life cycle analysis is a current research gap in the body of the literature, and thus this paper will address it. The primary merit of this paper is developing a suitable full-dimension sustainability life cycle assessment framework to obtain a fundamental understanding of the performance of AMP life cycle sustainability. The proposed framework applies a more systemic AMP life span including AMP design, AM, usage, and end-of-life (EOL) handling. An AM produced gear is used as an example to illustrate the life cycle sustainability assessment framework. The results show that the AM stage has the highest influence on economic and environmental dimensions of sustainability and the EOL stage has the highest social impact. The results also indicate that AM mass production can significantly reduce the impact of sustainability. [ABSTRACT FROM AUTHOR]

The use of non-imaging collectors has a wide scope in process heat applications based on its performance and economics. An experimental investigation of trapezoidal/concave cavity surface receiver (TSR) for non-imaging solar concentrating collector is carried out in this paper. The implementation of surface/coil receiver instead of tubular receiver for non-imaging collector is presented in this paper. A TSR with helical coil is developed for non – imaging concentrating collector, Elliptical Hyperbolic Collector (EHC). Experiments are carried to estimate the thermal performance of the system under various operating conditions such as two operating modes: series and parallel modes of operation of the collector, two circulation modes: passive and active modes. The stagnation temperature of the trapezoidal/concave cavity surface receiver is measured to be 118 °C on a clear sunny day in October and 102 °C on a cloudy day in February. The daily performance tests are performed under different operating conditions. Based on the experimental study, for the flow rate of 0.03 kg/min and 0.5 kg/min, the fluid outlet temperature is estimated to be 87 °C at 768 W/m 2 and 49 °C at 908 W/m 2 respectively. The corresponding instantaneous efficiency was calculated to be 9% and 40% respectively. The numerical model is developed to predict the temperature of the fluid along the receiver. The pressure drop across a receiver is estimated to be 9.3 kPa for a flow rate of 0.5 kg/min. Exergy analysis of the system is carried out and it ranges between 10 and 20%. The costs involved in fabricating the EHC system are compared to that of a non-imaging concentrating collector (CPC) of same aperture area. An economic analysis of the system is also carried out to study the feasibility of the system based on the life cycle savings method by estimating the annual solar savings from the EHC system. The present system can be a suitable option for low and medium temperature process heat applications. [ABSTRACT FROM AUTHOR]

Since sustainable scheduling is arousing increasing attention from many manufacturing enterprises and energy consumption is a core problem regarding sustainability, the purpose of this paper is to develop an energy-efficient scheduling method to fulfill material delivery tasks in mixed-model assembly lines. In this research, the objective of minimizing the energy consumption is jointly integrated with the operational criterions when executing material delivery tasks. Owing to the NP-hard nature of the considered problem, a Taboo enhanced Particle Swarm Optimization (TEPSO) algorithm is developed to solve the multi-objective problem. Several improving strategies are applied to enhance the performance of the proposed TEPSO in order to obtain a stronger local search capability and faster search speed. The performance of the proposed TEPSO algorithm is evaluated by comparing with two other high-performing multi-objective optimization methods. Computational experiments are conducted in order to test and verify the effectiveness and efficiency of the proposed TEPSO algorithm. The achievements reported in this paper might be inspiring for further studies on energy-efficient production scheduling. [ABSTRACT FROM AUTHOR]

Quantifying the use of resources in food production and its environmental impact is key to identifying distinctive measures which can be used to develop pathways towards low-carbon food systems. In this paper, a first-principle modelling approach is developed, referred to as gThermaR (Glasshouse-Thermal Requirements). gThermaR is a generic tool that focuses on the energy requirements of protected heated production, by integrating holistic energy, carbon, and cost modelling, food production, data analytics and visualization. The gThermaR tool employs historic data from weather stations, growing schedules and requirements specific to grower and product needs (e.g. set-point temperatures, heating periods, etc.) in order to quantify the heating and cooling requirements of glasshouse food production. In the present paper, a case study is reported that employs a database compiled for the UK. Another relevant feature of the tool is that it can quantify the effects that spatial and annual weather trends can have on these heating and cooling requirements. The main contribution of this work, therefore, concerns the development a tool that can provide a simple integrated approach for performing a wide range of analyses relevant to the thermal requirements of heated glasshouses. The tool is validated through collaborations with industrial partners and showcased in a case study of a heated glasshouse in the UK, offering the capacity to benchmark and compare different glasshouse types and food growth processes. Results from the case study indicate that a significant reduction in the heating requirement and, therefore, carbon footprint, of the facility can be achieved by improving key design and operational parameters. Results indicate savings in the peak daily and annual heating requirements of 44–50% and 51–57% respectively, depending on the region where the glasshouse is located. This improvement is also reflected in the carbon emissions and operating costs for the different energy sources considered. Furthermore, the temporal variability/uncertainty of the annual energy requirements and of the peak daily energy requirements are found to be considerably lowered through improvements to the glasshouse attributes. Overall, gThermaR proves its value in quantifying and identifying key factors that have a significant impact on energy requirements of heated glasshouses. Such valuable outputs are invaluable for stakeholders in the food industry that have an interest in mapping the sustainability and mitigating the carbon footprint of their supply chain processes. [ABSTRACT FROM AUTHOR]

A resident's willingness to pay(WTP) for the environmental improvement of renewable energy source (RES) is supposed to be highly correlated with the information he or she acquires. This paper provides both theoretical proof and empirical evidence of resident's cognitive bias regarding green power. A large-scale field survey was conducted in Shanghai and more than 3000 respondents were selected to examine their WTP for green energy. Applying double-bounded dichotomous contingent valuation method (DBDC), this paper elicits the urban residents' WTP for green power and identifies the information effect. Given all the other factors, our research shows that accurate information provision on the costs and environmental improvement effects compared to thermal power would reduce the residents' WTP for RES. The emission information of thermal power, however, would insignificantly change the residents' WTP for RES. The result indicates that residents in urban China have cognitive bias regarding the costs and environmental benefits of RES. Blind testing or improper way of information provision are essential aspects to be avoided for the purpose of eliciting real WTP from consumption side. [ABSTRACT FROM AUTHOR]

The five major power generation corporations dominate the power industry in China, and play vital roles in China's carbon trading scheme. Under this circumstance, this paper studies the allocation of carbon emission quotas to China's five major power generation corporations based on the fairness and efficiency principles, which proves the primary prerequisite for setting up the national carbon market. Specifically, a bi-level programming model is developed to optimally allocate carbon emission quotas to the corporations, and then a zero sum gains data envelopment analysis (ZSG-DEA) model is adopted to evaluate the efficiency of the allocation so as to adjust towards the optimal solution. The results indicate that power generation has significantly positive influence on the allocation of carbon emission quotas. Moreover, the difference between the sum of optimal carbon emissions and the sum of carbon quotas allocated is 1.431 billion tons, which implies that the emission reduction potential of the five major power generation corporations is tremendous. Finally, the bi-level model in this paper can well capture the context of China's power industry and provide effective results for the allocation of carbon quotas. [ABSTRACT FROM AUTHOR]

This paper presents the outcome of an extensive research that ultimately proposes a dynamic quasi comprehensive model to assess the carbon footprint of fossil fuel electrical energy. The key parameters and their respective effects have been fully considered. Such key parameters include plant type, fuel type, fuel transportation, emissions for fuel extraction and processing, within-facility power consumption at the power plant, degradation rate, site ambient conditions, and losses related to transmission and distribution. The proposed model has two significant features. The first feature considers a framework that generates a dynamic model. The time span in the dynamic framework is flexible and can vary from 1 s to the entire functional life of a power plant. The second feature of the model (representing its comprehensiveness) considers the aforementioned nine key parameters, holistically and simultaneously. Applying the proposed model across a wide range of circumstances leads to the estimation of the quantitative effect of each parameter. This shows the priority of order that the parameters should be given when designing a low-emission fossil-fuel power plant. Among the different standard cases of plant designs discussed in this paper, combined-cycle power plants running on natural gas have the minimum carbon footprint. Hence, the power plant and fuel types have the greatest effect on carbon footprint per unit of generated electrical power. Moreover, other mentioned parameters demonstrate significant effect on the results in this research work. The variation of parameters from least to most can result in a four-fold increase in carbon footprint. [ABSTRACT FROM AUTHOR]

The low price and excellent flexibility of plastic straws make them very popular, yet their short lifespan and improper disposal after use result in major resource waste and environmental burdens. To this end, paper straws and polylactic acid (PLA) straw alternatives have emerged on the market. Aiming to present a comparative sustainability study of drinking straws, this article provides a life cycle assessment of drinking straws made of polypropylene (PP), paper, and polylactic acid (PLA) based on Chinese context, as well as a scenario analysis of the availability of low-carbon electricity (LCE) and its recycling capacity (RC). The functional unit was set as a straw suitable for 500 ml milk tea cups, and the system boundary is from cradle to grave, including raw material preparation process, straw production process, usage process, waste process, transportation and recovery process. The comparative analysis revealed that the plastic straw alternative would not be superior in all indicators, but would lead to environmental problem-shifting, which will provide a basis for decision making and avoid bias caused by subjective choices. Scenario analysis shows that the synergistic effect of LCE and RC can minimize the environmental burden for paper straw, especially in terms of Primary Energy Demand (PED) which reduced by 27.9% with 100% RC and 50% LCE, and this is mainly due to RC. The findings of this work can offer theoretical justification, data references, and fresh perspectives for environmental evaluation of straws. [Display omitted] [ABSTRACT FROM AUTHOR]

Transnational power cooperation contributes to promoting the large-scale use of renewable energies in Asia, but how to develop the structure of power transmission network deserves careful investigation. This paper thoroughly investigates the structure of power investment and transmission network in China and neighbouring countries, aiming to promote the large-scale use of renewable energies around Asia. Various power-generation and power-transmission technologies are considered in detail, and transnational power interconnection risk cost and carbon emission cost are embedded into a bottom-up optimization model. The future power-generation structures and networks installed under various policy scenarios are analysed in detail, and the corresponding economic, carbon emission reduction and renewable energy consumption benefits are evaluated. The results show that power transmission between China's internal regions and neighbouring countries can save $56.7 billion for the entire power system through the large-scale grid integration of renewable energy. The installed capacities of wind power, solar power, and hydropower renewable energy power generation could be increased by 141 GW, 163 GW, and 58 GW, respectively. The construction of transnational transmission lines from Central Asia to Northwest China, Mongolia to North China, the Russian Far East to Northeast China, and Northeast China to South Korea could effectively promote the utilization of renewable energy in the Russian Far East, Mongolia and Central Asia and further reduce carbon emissions in China, Japan and South Korea. • It examines how to construct a power investment and transmission network in Asia. • Various technologies, risks and costs are considered based on bottom-up model. • Huge benefits exist for power transmission between China and neighbouring countries. • Various power-generation structures and networks installed are analysed in detail. • Suggestions about power investment and transmission are given for Asian countries. [ABSTRACT FROM AUTHOR]

One of the critical challenges facing China is environmental pollution caused by insufficient use of clean energy. This paper empirically investigates the impact of rural labor mobility on household clean energy use using data from the China Family Panel Studies (CFPS). The results indicate that labor mobility significantly promotes the adoption of clean energy by rural households, with income effects and information channel effects serving as the underlying mechanisms. The study also finds that health risks, as an important consideration for household energy use choices, enhance this positive effect. Furthermore, heterogeneity analysis reveals that labor mobility has a greater impact on households with lower levels of education, lack of social security, and those located in central and western regions. Therefore, the government should take measures to increase the income of the rural migrant population and continuously widen the information channels for rural households to promote clean energy use. The findings of this study provide a new perspective and evidence for understanding household energy use behavior in China, offering valuable insights for policymakers aiming to expand the use of clean energy. • Labour mobility significantly contributes to clean energy use in rural households. • Income effects and information channel effects are the main mechanisms of action. • Health risks faced by households play a moderating role. • Heterogeneity in region, educational attainment, social security status will influence the effect of labour mobility. [ABSTRACT FROM AUTHOR]

The increasing contribution of refrigeration systems to global warming has led to widespread demand for low global warming potential (GWP) refrigerants as alternatives. This paper proposed a comprehensive environmental assessment method for evaluating the carbon footprint of units charged with low-GWP refrigeration. Experimental and numerical studies were used to investigate the carbon footprint impact of using alternative refrigerants at different ambient temperatures in China. Initially, the model was validated through experimental case studies on the use stage of cold storage units. Subsequently, a comparison was made between the cooling capacity (CC) and energy efficiency ratio (EER) of cold storage units charged with different refrigerants. Additionally, the impact of alternative refrigerants in the use stage was analyzed by numerical calculations, and the adaptability of the cold storage unit to the ambient temperature and the national energy structure was also studied. The results indicate that among the four stages of the cold storage unit, the use stage is the hotspot of carbon footprint due to the large amount of energy consumption and the existence of refrigerant leakage and other behaviors. Utilizing low-GWP alternative refrigerants could significantly reduce the carbon footprint of the cold storage units' use stage by 10.56%–16.39%, thereby lowering the whole stage carbon footprint. Furthermore, the ambient temperature and national energy structure could also effectively reduce the carbon footprint of cold storage units' whole stage by 1%–27.17%. Furthermore, after adopting low GWP refrigerants, the life-cycle cost (LCC) of the units have also decreased by 6.1%–12%. Taking into account both environmental impact and economic considerations, it is recommended to directly replace R404A with R448A in the units in regions where the average ambient temperature is above 15 °C. • A carbon footprint evaluation model for the units was established. • Influencing factors of carbon footprint are studied numerically and experimentally. • By GHG assessments, the optimal refrigerant and external conditions were determined. • Alternative refrigerants reduce carbon emissions for cold storage units by 8.8%–24.92%. [ABSTRACT FROM AUTHOR]

Ocean wave energy is a kind of renewable energy with huge reserves, which can play an important role in the future construction of smart oceans. The low capture efficiency and narrow bandwidth of traditional wave energy capture devices seriously restrict the large-scale application of wave energy. To address these issues, a rack-pinion-lever-spring (RPLS) adaptive bistable Power Take-Off (PTO) mechanism with a time-varying potential barrier is proposed and applied to a point absorber wave energy converter (WEC). In the proposed nonlinear PTO system, a rack-pinion-lever (RPL) mechanism, as a displacement amplifier, has an effect on enhancing the poor amplitude sensitivity issue of the negative stiffness mechanism. Based on linear wave theory, a special nonlinear one-and-half-degree of freedom dynamic model is developed to describe the adaptive bistable wave energy converter (AB WEC). In comparison with the traditional bistable WEC (TB WEC) and equivalent linear WEC, the numerical results show that the AB WEC can greatly enhance the capture efficiency of lower frequency energy, especially at small wave excitations. The energy capture efficiency of the AB WEC is close to that of the TB WEC even at large wave amplitudes and is higher than that of the equivalent linear WEC. Finally, the wave energy capture characteristics of the three kinds of systems are studied based on the wave distribution diagram of a certain sea area in the South China Sea. The results show that the AB WEC has a large wave height adaptability in the low frequency region. The AB PTO mechanism with a displacement amplifier proposed in this paper can provide a technical reserve for the highly efficient and wide bandwidth capture of low frequency ocean wave energy. [ABSTRACT FROM AUTHOR]

During iron ore processing, accurately predicting the total iron (TFe) content in the ore is important for highly efficient and accurate sorting, which can reduce dust pollution, energy consumption, and economic losses, and promote waste utilization. Traditional techniques have limitations in accurately predicting the TFe content of individual iron ores, whereas hyperspectral imaging (HSI) has the potential to fulfill this task. Therefore, this paper explored it. For the experimental materials, 150 high-grade and 150 low-grade ore samples with particle sizes ranging from 20 to 40 mm were prepared. Subsequently, hyperspectral images of these samples were acquired within the range of 953–2517 nm, and the TFe content of each ore sample was measured. After preprocessing, the spectral features were extracted from the mean spectra of the iron ore, based on the analysis of the ore samples using variational mode decomposition (VMD). Subsequently, a random forest (RF) model based on these features was proposed to predict TFe content of the ores, and further sorted each individual piece of iron ore. Based on the evaluations, the prediction coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE) and classification accuracy of the proposed model, VMD Feature-random forest (VMD-RF), were 0.94, 0.07, 0.03, and 0.91, respectively. The results proved the feasibility of accurately sorting each individual iron ore based on its predicted TFe content using HSI. This methodology offers technical support for a cleaner iron ore production. Ore sorting based on Hyperspectral Imaging. [Display omitted] • Predicting total iron (TFe) content of iron ores and sorting them by hyperspectral imaging for cleaner production. • For iron ores, this sorting method can help save energy approximately up to 7.632 billion kWh. • Prediction R2, RMSE, MAE and classification accuracy were 0.94, 0.07, 0.03, and 0.91, respectively. • Reflectance level, 2124 nm peak, and amplitude of the spectra are crucial for predicting TFe content of iron ores. [ABSTRACT FROM AUTHOR]

The increase in energy demand makes it urgent to explore green energy sources. And wind energy is one of the most promising renewable energy sources. In this paper, a rotating hybrid nanogenerator with a combination of a direct-current triboelectric nanogenerator (DC-TENG) and an electromagnetic generator (EMG) is designed; the design concept is to harvest wind energy. First, an optimized ternary DC-TENG is designed based on the ternary dielectric triboelectrification effect. A soft contact structure is designed, which can effectively increase the frictional area as well as reduce the frictional resistance. Then, by introducing the EMG unit, the output power of the device and the speed of charging the capacitor are increased. The high output voltage of the DC-TENG and the high output current of the EMG complement each other to produce excellent power output. At 180 rpm/min, the output power of DC-TENG and EMG can reach 1.78 mW and 215 mW, respectively. With a simple power management circuit design, the device is successfully implemented to power small electronic devices. By charging a suitable capacitor, the device can be used as a power supply to power the sensor. Together with the sensor and power management circuit, it forms a self-powered sensing system that can drive the sensor for continuous operation. This work provides a simple, convenient, and reliable design that offers new insights into energy harvesting in nature. • A ternary dielectric triboelectrification effect triboelectric nanogenerator. • A soft contact structure is designed to minimize frictional resistance. • Introduction of an electromagnetic generator to reduce the capacitor charging time. • Energy supply for the continuous operation of the self-powered sensing systems. [ABSTRACT FROM AUTHOR]

The regional impact of climate change on heating and cooling demand is important to consider when designing optimal long-term energy policies. Several studies have addressed this issue, but either at a very aggregated level or without optimizing the whole energy system. The aims of this paper are to fill this gap in a generic way and to assess the impact of climate change on heating and cooling energy demands for residential and commercial sectors at the regional and nodal levels in the context of Chile's energy transition. We propose a methodology based on high resolution climate simulations for the Representative Concentration Pathways (RCP) RCP 2.6 and RCP 8.5 scenarios. First, a statistical analysis is performed to estimate the long-term trends of so-called heating and cooling degree-days and their impact on final regional energy demands. Then, demand pathways in the energy transition are assessed using a multi-sectoral energy planning model. Numerical experiments using data from Chile show an overall positive economic impact of climate change (limited to heating and cooling demands) for the energy system, with a significant decrease in heating demand compared to a limited increase in cooling requirements. For the RCP 8.5 scenario, cost reductions reach 2.1% of the total discounted system cost on the 2020-2050 period mainly due to a significant decrease of gas consumption for heating. This research highlights the importance for policymakers to consider climate change in efficient energy policies. [Display omitted] • Climate change impact on heating/cooling is assessed for Chile's energy transition. • Significant heating demand decrease and low cooling demand increase are observed. • A global positive economic impact for the energy system is estimated. • For the RCP 8.5 scenario, cost reductions reach 2.1% of the total discounted system cost. [ABSTRACT FROM AUTHOR]

The development of renewable energy is the key to tackling climate changes and ensuring energy security. Meanwhile, the process is usually associated with a huge investment and financing gap, especially for transitional countries like China. Hence, developing and innovating the traditional financial system is urgent. However, existing studies have mainly focused on traditional financial perspectives, and few papers have critically examined how digital financial inclusion affects the growth of renewable energy industries. To this end, using Chinese provincial data from 2011 to 2020 and applying Feasible Generalized Least Squares (FGLS) method, this study explores the effect of financial inclusion on renewable energy and its underlying mechanisms from the production and consumption perspectives. It is found that the impact of financial inclusion on the production side of the renewable energy industry is significantly better than on the consumption side, and there is heterogeneity effect in different energy resource varieties, different regional locations, and different financial regulation intensities. The financial inclusion on renewable energy has a significant pulling effect in photovoltaic and wind provinces, but not in large hydropower provinces. Then, its driving effect is particularly pronounced in the northern region. Nonetheless, it is not significant for renewable energy consumption in the southern region. Besides, this positive effect cannot be achieved without stronger financial regulation. The mechanism of action assessment finds that optimizes the consumption pattern, increase the competition of commercial banks, and improve technological innovation all contribute to the positive effect whereas, FDI shows the negative effect. This study provides new evidence on China's achievement of the energy transition, suggesting the need to further improve incentives for FDI firms and to strengthen consumption-side guidance. [ABSTRACT FROM AUTHOR]

A hybrid renewable energy system (HRES) utilizes the coaction of diverse energy to enhance energy efficiency while improving economic benefit. Under the paradigm of the electricity market, the HRES decomposes bilateral contract (BC) signed in the medium to long-term market and bids in the spot market are a promising way to get more revenue while ensuring basic profits by exploiting the synergy of different markets. However, the scheme of BC decomposition and the uncertainties of renewable energy affect the revenue of HRES scheduling. This paper proposes an optimal scheduling model for HRES to perform the BC flexible decomposition while bidding in the day-ahead energy market to maximize total revenue. The HRES is a real system located in Southwest China, and its constituent units are a pumped storage, two hydropower, and two solar stations. The Wasserstein metric ambiguity set is adopted to portray the uncertainty of available solar power and the forecasted market price error. Then, the proposed model is formulated as a distributionally robust chance-constrained scheduling model. Finally, the conditional value-at-risk approximation and strong duality are employed to reformulate this model into a tractable problem. The numerical results show that the proposed model can increase the total profit of HRES by 2.26 % (i.e., 2.56 × 104 DKK) compared to the case of fixed BC decomposition and bidding. Moreover, the impact analysis related to the ambiguity set and risk tolerance of uncertainty on total revenue of the proposed model is also presented, which provides the measure for the HRES to trade-off the robustness and economy of the solution. • The dispatch of the hybrid renewable energy system in the power market is studied. • A distributionally robust chance-constrained model is proposed accordingly. • The bilateral contract flexible decomposition is more profitable for the system. • The model can balance the economy and conservativeness of the solution. [ABSTRACT FROM AUTHOR]

During the operation of a power press, the movement of moving parts consumes large amounts of energy. Minimizing the mass of moving parts through lightweight design is considered an effective strategy to reduce this energy consumption. The slider has the largest mass among moving parts and is the best object for lightweight design. Therefore, this paper proposes a lightweight design and structural optimization method for the slider to reduce the energy consumption of the power press. The reduction in mass of the slider is achieved through the application of a novel steel-aluminum composite (steel face sheets, high-strength aluminum alloy core) bionic sandwich structure (SACBSS). Afterward, the performance of the SACBSS is evaluated, and the SACBSS slider is designed. The energy consumption model and the finite element model of the slider are established, respectively. Finally, the response surface method is used to establish the optimization model by comprehensively considering energy consumption and structural performance. The results show that compared to the referenced steel slider, the optimized SACBSS slider reduces the mass by 18.9% and the energy consumption by 6.1%. The proposed design and optimization method of the slider can effectively reduce energy consumption while ensuring performance, which is important for the realization of green production in factories. [Display omitted] • A slider of steel-aluminum composite bionic sandwich structure (SACBSS) is proposed. • An energy model is built for analyzing energy saving potential of the SACBSS slider. • Effect of structural parameters on energy consumption and performance is analyzed. • The SACBSS slider reduces mass by 18.6% and energy consumption by 6.1%. [ABSTRACT FROM AUTHOR]

This paper reviews the published research pertaining to the use of superheated steam for carbon fibre reinforced polymer (CFRP) composite reclamation. Superheated steam has been used for this purpose for around a decade and was initially investigated to prevent the degradation of reclaimed fibres, which occurs during the oxidative char removal step of most pyrolysis-based reclamation techniques. The review evaluates the various methodologies employed with particular focus on the physical, mechanical, and chemical properties of the reclaimed fibres, and the environmental impact of using superheated steam for carbon fibre reclamation as determined by life cycle assessment. Superheated steam studies report recovering carbon fibres with retained tensile moduli of around 90%–100% and tensile strengths of 65%–100% when compared to virgin carbon fibres, however, when optimised it is shown that carbon fibres can be recovered with no loss in stiffness and strength. Most studies are still at laboratory- or pilot-scale, however, several companies are collaborating with researchers to investigate the potential of this reclamation method on a larger scale. Early analysis on the energy use of carbon fibre reclamation using superheated steam shows that energy savings of 25% could be made by recycling CFRP waste using superheated steam and using the recovered carbon fibres to displace virgin carbon fibres rather than landfilling and incinerating this waste. • Review of the developments pertaining to superheated steam use for carbon fibre reinforced polymer reclamation. • Superheated steam reclaimed carbon fibres retain tensile strengths of 65%–100% and tensile moduli of around 90%–100%. • Review of the life cycle assessment of superheated steam-based carbon fibre reinforced polymer reclamation. • Examples of superheated steam reclamation processes entering the pilot-plant/industrial phase. [ABSTRACT FROM AUTHOR]

Carbon peaking and carbon neutrality goals are proposed by the Chinese government, which aims to reach the highest level of CO 2 emissions by 2030 and achieve carbon neutrality by 2060. It is of great significance to accelerate green production and lead high-quality development. Energy carbon emissions account for 88% of total CO 2 emissions, while forest carbon sequestration account for 80% of China's terrestrial ecosystems. In this paper, we analyzed the spatial and temporal evolutions of industrial energy consumption carbon emissions and forest carbon sequestration of Hubei Province, then demonstrated the offsetting effect of forest carbon sequestration on the industrial CO 2 emissions. Our results documented energy carbon emissions and forest carbon sequestration in Hubei Province both increased from 2000 to 2020, with the growth rates of 4.9423 Mt/yr and 0.28015 Mt/yr. Forest carbon sequestration could offset energy carbon emissions before 2005, while the offsetting effect was weak due to the continuous increase in industrial energy consumption after 2005. Significant spatial heterogeneity was observed in both energy carbon emissions and forest carbon sequestration. Wuhan had the biggest carbon emission with annual average carbon emission of about 20.046 Mt, while Enshi had the biggest carbon sequestration with annual average forest carbon sequestration of about 14.411 Mt. Spatial autocorrelation between energy carbon emissions and forest carbon sequestration was significant in Hubei Province in the past two decades. Our findings provided evidence that local-scale forest carbon sequestration could offset carbon emissions caused by industrial energy consumption at a certain extent, helping to draw up the scientific energy-saving and emissions-reducing measures. [Display omitted] [ABSTRACT FROM AUTHOR]

The large-scale integration of non-dispatchable renewable energy must be carefully planned, especially in poorly robust electrical energy systems. Tenerife is the most populated of the islands in the Canary Archipelago (Spain) and has an isolated electrical system. It is envisaged for the horizon of 2040 that the island will have a high contribution of non-dispatchable renewable energies (fundamentally wind and solar photovoltaic). Tenerife also has exploitable high enthalpy geothermal resources. An energy planning model is implemented in this paper based on which different scenarios with high non-dispatchable renewable energy penetration in the island's electrical system are simulated. Geothermal energy is also incorporated in the simulations as a dispatchable renewable energy source, with the power required sized according to the hypotheses of each scenario. The results are compared according to different technical and economic parameters. An evaluation is also made of the influence that the capacity of the electrical system to take on higher non-dispatchable renewable power and the presence of energy accumulation systems might have on the minimization of losses in the non-dispatchable renewable energy capacity factor. The results of the simulated scenarios show that geothermal energy could meet up to 28.8% of the island's electrical energy demand, increasing the stability, flexibility and supply guarantee of system. A 100% renewable system could be possible through the incorporation of this energy source and the planning of energy accumulation systems. In the case study, the economic saving for Spain's electrical system could exceed 400 €million per year. • Sustainable electricity generation in poorly robust insular electrical systems. • Large-scale integration management of non-dispatchable renewable energies (NDREs). • Exploitation of geothermal energy in 100% renewable electrical systems. • Importance of energy accumulation systems in NDRE integration. • LCOE decrease through exploitation of renewable energies. [ABSTRACT FROM AUTHOR]

Meeting energy needs and ensuring ecological sustainability are important tasks for policymakers. In particular, changing the energy mix used in daily electricity generation can have a major effect on ecological conditions, and this is a previously neglected research topic. Therefore, this paper aims to investigate the influence of daily electricity generation from nuclear power and renewables on the achievement of carbon neutrality targets in the four largest nuclear power countries (i.e., the U.S., China, France, and Russia). The study applies the wavelet-transform coherence (WTC), quantile-on-quantile regression (QQR), and Granger causality in quantiles (GCQ) approaches for the period from January 2, 2019 to December 29, 2022. The outcomes present that electricity generation from nuclear energy reduces carbon (CO 2) emissions only in Russia, while hydropower generation does not contribute to CO 2 emission reduction in any country. Solar electricity generation decreases CO 2 emissions in different quantiles in the U.S. and Russia, while electricity generation from wind power reduces CO 2 emissions in the U.S. and France. The empirical outcomes also reveal that expanding solar, wind, and nuclear power in the energy mix can enhance the potential of the U.S., France, and Russia to achieve carbon neutrality and secure a sustainable future. However, China is using nuclear and renewables inefficiently regarding carbon neutrality. Therefore, the empirical evidence for China is highly controversial compared to former studies. [Display omitted] • The study examines renewable and nuclear electricity effect on carbon neutrality. • The study focuses on top four major nuclear power countries. • The study applies nonlinear approaches by using high-frequency (daily) data. • Renewable and nuclear electricity have time, frequency, & quantile-varying effect. • The best electricity source change according to each country. [ABSTRACT FROM AUTHOR]

At present, some piezoelectric energy harvesters (PEH) have been widely used in various small wireless electronic devices and micro intelligent sensing devices for self-power supply, but PEH still needs to be further improved in the effective acquisition of road vibration energy at low frequency (<10 Hz), especially at ultra-low frequency (<5 Hz) and broadening the capture energy band. Based on this, this paper proposes a hybrid piezo-electromagnetic road vibration energy harvesting device -TPEH (Triple piezoelectric energy harvester) suitable for road deceleration belts. Spring is introduced as the key to improve the efficiency of energy harvesting. Firstly, the vibration environment of the deceleration belts is surveyed, and then the influence of different K , frequencies, vehicle types and impedance on the energy capture effect is observed in the experiment. The experimental results show that: first of all, K = 20 N/kg main spring has the best resilience; Secondly, with the increase of excitation frequency from 0 Hz to 10 Hz, the maximum peak voltage of TPEH increases from 5.7V to 31.2V, and reaches the full bandwidth in the low frequency range of 0–10 Hz, especially the frequency band widening in the range of 0–1 Hz has ma de a breakthrough. Then, the total output power of TPEH reaches a maximum of 10.29 mW under the optimal load condition of 10 kΩ. Finally, TPEH is applied to the speed strip of a local road section. Through reasonable distribution of vibration signals, TPEH could accurately wireless communication module. [Display omitted] • Adopt hybrid dual harvest mechanism to improve performance. • Use vibration superposition mechanism to amplify power. • Full bandwidth in the low frequency range 0–10Hz. • Break through 0–1Hz ultra-low frequency range. • Complete vehicle detection by combining signal transmission technology. [ABSTRACT FROM AUTHOR]

The fossil energy and the carbon market are closely connected, but few articles have applied the Granger causality method on quantiles to explore the bi-directional causality between carbon prices and fossil fuels. Most articles use conditional mean regression models to test linear Granger causality, but are unable to assess tail causality or nonlinear causality. In order to accomplish the objective of studying the interaction of carbon and fossil energy markets at different quartiles, we use the method of Granger causality at quartiles, which allows us to assess median and tail causality and to gain insights into how carbon and traditional fossil energy markets interact under different market conditions. This paper analyzes the causal relationships between carbon prices and coal, oil, and gas from June 1, 2015 to October 31, 2022 across all quantiles. We find no indication of Granger-causality from carbon to oil and gas at the middle quantile. However, at the lower and upper quantiles, we discover the causal relationship between changes in carbon prices and traditional energy prices. The asymmetric two-way causal relationship between the carbon market and the fossil energy market has prompted the government to carry out differentiated management, as well as to improve energy efficiency. • We study the bi-causality between coal, oil, gas markets and carbon market. • We test for Granger-causality for each quantile of the distribution. • The negative correlation between carbon prices and fossil energy prices under mean reversion analysis is unreliable. • The impact of carbon taxes on oil prices varies widely across different quantiles. • We make demands on governments to develop energy policies. [ABSTRACT FROM AUTHOR]

Excessive energy-related carbon emission intensity will lead to deterioration of environmental quality and hinder green economic growth. This paper proposes a novel self-adaptive fractional order grey generalized Verhulst model (SAFGGVM) to predict energy-related carbon emission intensity in China, America, India, Russia, and Japan with nonlinear and complex characteristics effectively. Firstly, self-adaptive fractional order and dynamic background value coefficient are introduced to capture the nonlinear evolutionary trends. Subsequently, the optimal nonlinear parameters are determined using Grey Wolf Optimization algorithm through comprehensive comparison. Furthermore, the flexibility of SAFGGVM is verified by presenting its relevance to existing models. Finally, the validity, applicability, and robustness of SAFGGVM are confirmed by comparing with two machine learning models and four grey prediction models. The empirical results exhibit that the overall precision of SAFGGVM model significantly prevails over the others in five cases, with MAPE values less than 6% in both the simulation and prediction intervals. The out-of-sample forecast results indicate that the energy-related carbon emission intensity of five countries will fall into 5.7024, 1.6030, 7.3668, 8.1633, 2.0399 tons/10,000 USD by 2025, and the decreasing rate of developing countries tends to catch up with, or even exceed, developed countries. Projection results can serve as a reference point for countries to achieve green and sustainable development. • A novel self-adaptive grey generalized Verhulst model is proposed. • Energy-related carbon emission intensity (ECEI) of five countries is predicted. • Optimal nonlinear parameters are determined by Grey Wolf Optimization algorithm. • The novel model is superior to other competing models in accuracy and roubutness. • Decline rate of ECEI in developing countries will catch up with developed countries. [ABSTRACT FROM AUTHOR]

Policies targeting energy efficiency and renewable energy are sometimes viewed as more politically feasible than carbon pricing in pursuit of emission reduction goals. This paper assesses underlying drivers of energy policy development. These factors include economic, social, environmental, and institutional variables. The between estimator for panel data is an appropriate method for our focus on some exogenous variables that vary more across countries than over time. We find that larger oil reserves per capita have a negative relationship with renewable energy policy development. Education and political globalisation have strong positive relationships with both energy-efficiency and renewable-energy policy development. These results suggest that greater participation in global political groups can be an indirect approach toward energy policy development, in cases where direct and immediate policies are hard to implement. OECD countries have higher policy scores by 33 and 25 points in energy efficiency and renewable energy respectively. Blinder-Oaxaca decomposition analysis shows that these higher scores are primarily due to social and political institution predictors rather than economics and physical endowments. • Large-n cross country international sample on continuous policy score measurement. • Political globalisation is positively linked with renewables and energy efficiency policies. • Education is positively linked to energy policy development, especially for efficiency. • Higher OECD countries' policy scores are primarily due to social and political predictors. • Higher incomes are unlikely to lead to automatic improvements in energy policies. [ABSTRACT FROM AUTHOR]