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Abstract: This paper presents the method and results of a survey of 27 of the 33 Australian universities teaching engineering education in late 2007, undertaken by The Natural Edge Project (hosted by Griffith University and the Australian National University) and supported by the National Framework for Energy Efficiency. This survey aimed to ascertain the extent of energy efficiency (EE) education, and to identify preferred methods to assist in increasing the extent to which EE education is embedded in engineering curriculum. In this paper the context for the survey is supported by a summary of the key results from a variety of surveys undertaken over the last decade internationally. The paper concludes that EE education across universities and engineering disciplines in Australia is currently highly variable and ad hoc. Based on the results of the survey; this paper highlights a number of preferred options to support educators to embed sustainability within engineering programs, and future opportunities for monitoring EE, within the context of engineering education for sustainable development (EESD). [Copyright &y& Elsevier]

The rapid development of the magnesia refractory industry has caused serious problems of resource and energy waste and environmental pollution. Cleaner Production and Cleaner Production Audit are considered effective tools for energy conservation and emission reduction in the industry. This study presents an application of cleaner production and cleaner production audit in a typical large-scale magnesia raw material production plant in Liaoning, China and the results of their implementation. Through the 7 steps of a cleaner production audit (planning and organization, pre-assessment, assessment, option generation and screening, feasibility analysis, implementation, and maintenance of cleaner production), the resource and energy consumption and environmental emissions of the enterprise are investigated, the key auditing procedures are identified, and the cleaner production opportunities are analyzed. 28 cleaner production options, including raw material and energy substitution, technology improvement, facility maintenance and updates, process optimization and control, waste reutilization, management, and staff training and motivation, have been developed and implemented in a feasible way. After complete implementation of these options, great environmental and economic benefits are expected to be achieved: increased utilization of magnesite tailing powder by 281,000 t per year; annual savings of 25,000 t of magnesite ore; savings of 384,000 kW h of electricity; a 21.7% reduction in magnesite consumption per ton of FM product; improvement of the wastewater utilization rate from 70% to 100%; the removal of dust, SO 2 and NO x emissions produced by burning coal or producer gas; savings of 1.066 million USD per year. The results demonstrate that implementing cleaner production can not only bring huge environmental benefits, but also significant economic gains. Moreover, factory staff have recognized the benefits that cleaner production can bring to the plant, and plan to continue the process. Since there are few studies on the application of cleaner production in the magnesia refractory industry, this paper provides scientific guidelines for its implementation in other similar enterprises, and a theoretical and practical basis for promoting the sustainable development of the industry. [ABSTRACT FROM AUTHOR]

Emerging economies account for a fast-growing share of the global energy market. In particular, energy use in China has become significant from both economic and environmental standpoints. This trend makes it necessary to balance the need for affordable, reliable electricity supply with the need to ensure that the power infrastructure is environmentally sustainable. As such, this paper presents a multi-dimensional pinch analysis (MDPA) of the power generation sector in China; the analysis considers five key indices: carbon footprint, energy return on investment (EROI), water footprint, land footprint, and risk to humans. By simultaneously quantifying five different indices under a common methodological framework, we are able to coherently assess the impact on five different environmental concerns. This approach provides a more complete picture of the true environmental impact of China's power sector. This information can thus help policymakers avoid the problem of shifting environmental impacts to other domains, which can occur when the analytic procedure used focuses on a single environmental dimension. [ABSTRACT FROM AUTHOR]

The need for the development of clean but still profitable processes and the study of low environmental impact and economically convenient management policies for them are two challenges for the years to come. This paper tries to give a first answer to the second of these needs, limited to the area of discontinuous productions. It deals with the development of a robust methodology for the profitable and clean management of (fed-)batch units under uncertainty, which can be referred to as a robust sustainability-oriented model-based optimization & control strategy. This procedure is specifically designed to ensure elevated process performances along with low-cost utilities usage reduction in real-time, simultaneously allowing for the effect of any external perturbation. In this way, conventional offline methods for process sustainable optimization can be easily overcome since the most suitable management policy, aimed at process sustainability, can be dynamically determined and applied in any operating condition. This leads to a significant step forward with respect to the nowadays options in terms of sustainable process management, that drives towards a cleaner and more energy-efficient future. The proposed theoretical framework is validated and tested on a case study based on the well-known fed-batch version of the Williams–Otto process to demonstrate its tangible benefits. The results achieved in this case study are promising and show that the framework is very effective in case of typical process operation while it is partially effective in case of unusual/unlikely critical process disturbances. Future works will go towards the removal of this weakness and further improvement in the algorithm robustness. [ABSTRACT FROM AUTHOR]

Environmental protection is one of the main concerns of the international community. Countries show meticulous attention to environmental issues by considering eco-efficiency. The eco-efficiency evaluation of countries is a complex and multidisciplinary topic. Data envelopment analysis has widely been applied to measure the eco-efficiency of organization for economic co-operation and development countries. In previous studies, energy inputs have not been contemplated. The subject becomes more important when there are non-discretionary factors. In this paper, the eco-efficiency of countries in the organization for economic co-operation and development is assessed given energy inputs, undesirable outputs, and non-discretionary factors. To this end, slack-based and range-adjusted measures are extended. Also, new environmental indices are introduced. The relationship between consumption of energy inputs and production of undesirable outputs can be addressed by two new environmental indices. Spearman correlation test indicates a direct and positive relationship between potential of energy saving and potential of undesirable output abatement. France, Germany, Luxemburg, Norway, Sweden, and the United Kingdom are recognized as eco-efficient countries. South Korea and Italy have the highest and lowest potential for energy saving, respectively. Poland and Iceland are countries with the highest and lowest potential for undesirable output abatement, respectively. It can be concluded that countries producing high undesirable outputs may not operate eco-efficiently and thus have an extreme potential to save the optimum energy. Moreover, countries consuming low energy may operate eco-efficiently and have a low potential to reduce undesirable outputs. [ABSTRACT FROM AUTHOR]

Better digging the sustainable development path of the top five energy consumers (China, the United States, India, Japan and Russia) can serve both domestic economy and global economy to achieve coordinated development with the ever-increasing energy demand. This work has made the following efforts: (1) the Tapio decoupling model was employed to determine the decoupling states between energy consumption and economy; (2) based on the extended Kaya formula and the LMDI method, this work focused on measuring the impact of technological factors and urbanization factor on energy consumption; (3) the LMDI method and the Tapio decoupling model were combined to measure the impact degree of influencing factors on decoupling indicators. The main findings show that from 2001 to 2018: (1) Japan was the country with the most year of strong decoupling, followed by the United States, which indicates that the decoupling status of developed countries was better than that of developing countries. (2) The driving forces behind the energy consumption growth are mainly the effects of R&D scale and urbanization, while the main factors that hinder energy consumption growth were technological factors, including energy intensity effect and R&D efficiency effect. (3) Energy intensity effect was the main driving force for the decoupling process, and the R&D efficiency effect was the biggest obstacle to decoupling energy consumption from economic growth. Finally, this paper proposes that the government can give priority to relying on technological innovation to accelerate the development and promotion of energy-saving and emission-reduction technologies. • Exploring the coordinated development path of energy consumption and economic growth in top five energy consumers. • Extending the traditional LMDI method to measure the impact of technological progress and urbanization on energy consumption. • R&D scale and urbanization promote energy consumption growth, while technological progress inhibits energy consumption growth. • Governments can prioritize technological innovation to speed up energy conservation and emissions reduction. [ABSTRACT FROM AUTHOR]

The paper deals with the reuse of fibers from textile waste for the development of innovative and sustainable materials applied in the construction field. Currently, managing the high volumes of textile waste produced, and reducing the damage this waste does to the ecosystem, involves finding solutions for its reuse. Meanwhile, the construction sector has a great impact on the environment, and there is an urgent need to design innovative, sustainable building materials to reduce energy consumption and prevent the depletion of resources. In this context, the objective of the MOBIOTEX project is to develop new materials to replace the petrochemical-made vapor-barrier (VB) and rain-screen (RS) generally used in timber-frame construction (TFC). For that, nonwoven (NW) fabrics from textile waste were manufactured. Then, measurements based on standards for VB and RS were carried out on untreated and functionalized NW fabrics, to test their sealing and mechanical properties. Lamination of NW gives satisfactory results and some modified materials meet the requirements for both VB and RS applications and have similar properties as commercial products. These first results are quite promising as they show that, with some treatment, nonwoven from textile waste can be as technically efficient as commercial products. The different processes used during the MOBIOTEX project made it possible to build up the system boundary for the production of functionalized nonwoven in order to carry out future Life Cycle Assessment (LCA) and to compare with commercial products' LCA. In a circular economy approach, other characteristics such as durability, fire resistance and recyclability of such materials should be studied and optimized in order to reduce energy consumption and environmental impacts. Still, the main benefit of the developed materials, compared to commercial petrochemical rain-screens and vapor barriers, is on the production of raw materials, because it involves less exploitation of non-renewable resources, as an important part of materials come from waste, and the application in timber-framed construction can be a positive way in which to reuse a non-negligible volume of waste from the textile industry. [ABSTRACT FROM AUTHOR]

A key challenge of the 21st century is to transform society into one that features sustainable patterns of production and consumption. To achieve this, transition processes need to be designed in key areas such as housing, mobility and nutrition. The design and large-scale implementation of sustainable product service systems (PSS) is regarded a promising approach for sustainability transitions. Real-life socio-technical experiments are an important infrastructure for designing PSS in collaboration with stakeholders and users. In this paper, we argue that transdisciplinary and action research methods are required for institutionalising an experimental set-up and developing PSS within such infrastructures. We present the Sustainable LivingLabs (SLL) research infrastructure and its methodology as an example of such experimental settings. It was collaboratively developed with key stakeholders in three consecutive research projects and applied to e.g. heating and space heating. We show new qualities of SLL in relation to existing LivingLabs and approaches for PSS design and present its methodological three-phase model (insight research, prototyping, field testing) of research. Our article contributes to knowledge on a methodological framework and tool-kit for PSS development in SLL with a clear focus on socio-ecological sustainability. Intermediate findings confirm the high influence of user practices on heating energy consumption and show starting points for PSS development: e.g. transformational products, home-automation combined with consulting along value chains. We hypothesise that developing PSS in user- and stakeholder-integrated settings supports acceptance and diffusion and, by taking into account users' social practices of utilising novelties, reduces rebound effects caused by incorrect application. [ABSTRACT FROM AUTHOR]

Energy and environmental issues have become pertinent to all industries in the globe because of sustainable development issues. However, the ever increasing demand of customers for quality has led to better surface finish and thus more energy consumption. The energy efficiency of machines tools is generally very low particularly during the discrete part manufacturing. This paper provide a multi-objective predictive model for the minimization of power consumption and surface roughness in machining, using grey relational analysis coupled with principal component analysis and response surface methodology, to obtain the optimum machining parameters. The statistical significance of the proposed predictive model has been tested by the analysis of variance (ANOVA) test. The obtained results indicate that feed is the most significant machining parameter followed by depth of cut and cutting speed to reduce power consumption and surface roughness. The constructed response surface contours can be used by the shop floor people to find and use the best combination of machining parameters for the given situation. The reduction of peak load through optimization will results in lowering the power consumption of the machine tools during non-cutting idling time. [ABSTRACT FROM AUTHOR]

As China's economy is transforming into a new normal stage, the energy industry is becoming increasingly innovation-driven, which is shown particularly in renewable energy. Given that the green innovation transformation is crucially critical during China's new normal stage, this paper analyzes the direct impact of energy consumption on energy innovation and innovation transformation, and reveals the net effect of green innovation transformation on economic sustainability and energy consumption. Micro and macro empirical evidence are both provided in this paper by implementing two estimation methodologies: fixed effect model and Generalized Method of Moments (GMM) Vector AutoRegression (VAR) approach, respectively. Estimating Chinese micro 153 listed energy companies' data and macro 30 provincial data from 2009 to 2016, we find that: (1) In terms of energy enterprises' innovation activity behavior, energy consumption could promote total energy innovation, of which renewable energy innovation is stimulated far more significantly. (2) There is an increasing tendency for energy structure to transform into renewables as the energy consumption increases. (3) The green innovation transformation, instead of total innovation counts, can reduce energy consumption and benefit economic sustainability. Therefore, the structure of innovation transformation plays more significant role than total energy innovation in stimulating economic growth, and alleviating the energy consumption antinomy during China's new normal stage. In this regard, in order to stimulate green energy transformation, government should implement financing policy, reduce administrative intervention, upgrade energy legal system and improve energy pricing mechanism to encourage more research and development (R&D) activities at the core of renewable energy. • Provide evidence from both micro- and macro-economic perspectives. • Energy consumption stimulates renewable energy innovations more. • Transformation towards renewables is driven by high energy consumption. • Green innovation transformation decreases energy consumption in the long run. • Green innovation transformation benefits economic sustainability. [ABSTRACT FROM AUTHOR]

Despite the substantial effort on almost all levels during the last decades, the buildings' renovation rate needs to be at least doubled from the current 1% to meet ambitious energy efficiency goals. In the same way, the energy-intensive material replacement did not reach yet the desired grade in terms of sustainability measures and outlined goals heading to a low-carbon economy. This paper summarizes principles of sustainable development together with the current methodological framework relevant to the civil engineering and construction industry. The main part is devoted to the identification and understanding of principal factors preventing faster adoption of energy efficiency measures. High initial financial costs, investment risk over a long-term period, poor acceptance of sustainable measures, lack of information, and limited methodological framework for a reliable evaluation of environmental projects with the intergeneration context or understanding of externalities of human activities are identified as the main barriers to the sustainable building retrofits. These barriers are closely related each other and can be merged into several groups according to the stakeholders or scientific disciplines to amplify their primary impact. Notwithstanding, solution strategies based on narrow boundary conditions and limited multidisciplinary approach prevent substantial advances towards the sustainable building sector. In this regard, the major obstacles preventing the achievement of energy efficiency goals can be remedied by interdisciplinary cooperation. • Lacking multidisciplinary approach hinders sustainable measures adoption. • Limited public acceptance prevents a stronger political commitment. • Methods of social measures need to be studied for decision support. • Sustainable building industry transition is not a technical issue only. [ABSTRACT FROM AUTHOR]

Abstract: Reducing energy usage is an essential consideration in sustainable manufacturing. In the past, metal cutting operations have been mainly optimized based on economical and technological considerations without the environmental dimension. It is essential to improve production rate and cutting quality while simultaneously mitigating the effect of manufacture on the environment. This paper presents a multi-objective optimization method based on weighted grey relational analysis and response surface methodology (RSM), which is applied to optimize the cutting parameters in milling process in order to evaluate trade-offs between sustainability, production rate and cutting quality. Three objectives, such as surface roughness, material removal rate and cutting energy, are simultaneously optimized. The parameters evaluated are spindle speed, feed rate, depth of cut and width of cut. The grey relational grade values for the multiple responses are obtained using weighted grey relational analysis. The weighted grey relational analysis is a quantitative method we proposed to determine the weight factors of multiple responses for grey relational analysis. Based on weighted grey relational analysis and RSM, the optimal milling parameters were identified, and the obtained results indicated that width of cut is the most influential parameter. Experiments using Taguchi design method were performed to verify the proposed optimization method and promising results were achieved. The experimental results indicate that the proposed optimization method is a very useful tool for multi-objective optimization of cutting parameters. Moreover, the results also show that low spindle speed cutting is more energy efficient than cutting at initial speed for milling process and the traditional multi-objective optimization does not satisfy the requirement for sustainable machining. [Copyright &y& Elsevier]

The aim of Sustainable Development Goal 7 is to ensure access to affordable, reliable, sustainable and modern energy for all. Increased energy efficiency is particularly important in the construction industry because urban agglomerations currently consume up to 80% of global energy, 40% of which is attributable to buildings. In countries like Italy however, where historical buildings constitute a significant part of the building patrimony, improving energy efficiency is not always straightforward as interventions must take into account the historical materials used as well as the context of the construction. Therefore, the aim of this research was to establish a methodology that would identify the most effective means of achieving energy efficiency taking into account the historical aspects of a building and its cultural context. The methodology proposed and described in this paper involves: preliminary analyses to identify the elements of value and the level of transformability of facades; the selection of different insulating materials; dynamic simulations of building behaviour; analyses of intervention costs in relation to each type of insulation and finally the preparation of a multi-criteria matrix to identify the most effective method of improving energy efficiency of a historical wall with differing degrees of transformability. Each insulating material was analysed in relation to heating and cooling requirements and material cost impact. The methodology was applied to a case study in the Province of L'Aquila, Italy. In the paper a multicriteria framework, for the improvements in the thermal efficiency of a building, it is presented. Specifically the attention is focused on heating requirements, cooling requirements and cost impact. The results indicate that, with respect to historical building, it is possible to adopt strategies finalyzed to improve the energy efficiency of these buidings, contributing in this way, also toward the SDG7. Specifically, the best performance for a wall with a high level of transformability can be obtained using calcium silicate, extruded polystyrene, kenaf and hemp, whilst, in the case of a wall with a low level of transformability, the best materials are calcium silicate, polyurethane and linen fiber. Finally, in the case in which external constraints prevent the application of a thick coat and internally there is limited space, the use of calcium silicate was found to be the best energy efficient measure. [ABSTRACT FROM AUTHOR]

The amount of coal gangue, a by-product of coal mining and washing, is rapidly increasing with the growing trend of energy consumption. The accumulated coal gangue without appropriate utilization has resulted in a squander of resources, waste disposal and environmental pollution issues. Over the past few decades, there has been wide attention in developing strategies for the utilization of coal gangue due to a cultural shift towards sustainable development coupled with increasing demand for disposing the challenge of coal gangue accumulation. However, to our knowledge, there is no thorough and in-depth review on the series address of coal gangue reuse. In spite of some advantages of using coal gangue, it is notable that negative environmental problems cannot be ignored, so the scientific utilization is necessary to control the environmental impacts. Therefore, the main objective of this paper is to provide a comprehensive literature review of coal gangue utilization in building material production, energy generation, soil improvement and other high-added applications, analyze the worldwide dynamics of the studies on coal gangue utilization and identify the potential environmental risks in various pathways. The key focus of the review is on detecting the potential problems and thus giving recommendations for the solution. In addition, based on the progress of previous research, this paper also points the directions for further research within the field. A bibliometric analysis was developed in China National Knowledge Internet and Web of Science and a systematic review was conducted for related 237 articles to understand the physicochemical properties and utilization characteristics of coal gangue as well as corresponding environmental risks. The results indicated that the number of published articles has increased in recent years, and the researches were mainly from China, with the contribution of 78.94% of the total selected publications. Besides, these researches mainly focused on the utilization of coal gangue, while there was a lack of attention to environmental risks. The findings of the present study open up a new gate for the further application in coal gangue, hopefully motivate future relevant studies and guide the policy-making. • Coal gangue has been applied in building material, energy, agriculture and other industries. • Negative environmental problems cannot be ignored in the utilization of coal gangue. • Few researches considered environmental aspects of coal gangue uses. • The problems in the utilization of coal gangue were identified and some suggestions were proposed. [ABSTRACT FROM AUTHOR]

Abstract: With the world’s largest population and consistently rapid rates of economic growth, China faces a choice of whether it will move towards a more sustainable development trajectory. This paper identifies the different factors driving innovation in the fields of green chemistry and green engineering in China, which we find to be largely driven by energy efficiency policy, increasingly strict enforcement of pollution regulations, and national attention to cleaner production concepts, such as “circular economy.” We also identify seven key barriers to the development and implementation of green chemistry and engineering in China. They are (1) competition between economic growth and environmental agendas, (2) regulatory and bureaucratic barriers, (3) availability of research funding, (4) technical barriers, (5) workforce training, (6) industrial engineering capacity, and (7) economic and financial barriers. Our analysis reveals that the most crucial barriers to green chemistry and engineering innovations in China appear to be those that arise from competing priorities of economic growth and environmental protection as well as the technical challenges that arise from possessing a smaller base of experienced human capital. We find that there is a great deal of potential for both the development of the underlying science, as well as its implementation throughout the chemical enterprise, especially if investment occurs before problems of technological lock-in and sunk costs emerge. [Copyright &y& Elsevier]

Abstract: China has now the largest annual outputs of galvanized steel and the most amount of galvanizing plants in the world. However, with obsolete technology, the hot dip galvanizing industry has been proved as one of the industries, which consume large amounts of raw materials and energy, produce numerous pollutants and causes serious contamination in China. Cleaner Production in the hot dip galvanizing industry is now the only way to achieve the sustainable development of hot dip galvanizing industry. The implementation of the Common Fund for Commodities (CFC) project: The Transfer of Technology and Promotion of demand: Batch hot dip galvanizing in China launched by International Zinc Association (IZA) is introduced in this paper, The Best Available Technologies of operation, energy and environmental management in the world are also introduced. With the implementation of the project, an assessment system of Cleaner Production and a training system have been developed and implementation of technical updating to the demonstration plant shows that the reduction of zinc loss, and water and fuel cost savings can be achieved. It is believed that the methodology of the project can be applied throughout China as the galvanizers see the cost benefits. [Copyright &y& Elsevier]

Abstract: Life Cycle Assessment (LCA) is a well-known tool for analyzing environmental impacts on a wide perspective with reference to a product system and the related environmental and economic impacts. The need for a novel approach that complements environmental and financial considerations is addressed in this study with the introduction of a new graphical representation: the Environmental Performance Strategy Map. This graphical map allows one to combine the main environmental indicators (footprints) with the additional dimension of cost. The paper defines the Sustainable Environmental Performance Indicator as a single measure for sustainability of a given option. Comparison of different options for strategic decision-making purposes can be enhanced and facilitated by the use of this indicator. [Copyright &y& Elsevier]

The stamping industry is critical in the automotive and aerospace industries, and the environmental impacts and sustainability of stamping systems have attracted considerable attention. To analyze the environmental impact and sustainability of stamping systems quantitatively, this paper presents an emergy-based evaluation method considering all the associated environmental impact factors of a pressing workshop including material and energy consumption, waste flows, time and mass losses, and processing costs. On the basis of analyzing the stamping processes and sustainability, this method comprises data collection, emergy based sustainability evaluation model and the development of sustainable evaluation indexes and systems. Based on the proposed method, the environmental impact of an industrial vehicle stamping workshop was evaluated. The results show that the net emergy yield ratio of the stamping system was greater than 2, and the waste emergy output ratio was very low, indicating that the system had high productivity levels, high yields, and low pollution discharge rates. However, its sustainability index was less than one owing to its high energy and material consumption during the production processes. To reduce the environmental impact of this stamping system and improve its sustainability, we investigated the potential improvements that could be achieved in energy consumption, productivity, and environmental impact by implementing energy-saving scheduling in the stamping workshop. The results show that the corresponding net emergy yield ratio and sustainability index of the system were both improved. The proposed emergy-based method could be used to quantitatively evaluate the environmental impacts and sustainability of stamping systems and facilitate efforts to reduce the environmental impacts of pressing workshops while improving their productivity and economic profitability. [ABSTRACT FROM AUTHOR]

Among the main components of a smart city, the energy system plays a vital and core role in the transition towards a sustainable urban life. Furthermore, the utilization of renewable energy sources has been demonstrated as a significant contribution to reducing pollutant emissions and enhancing the quality of the living environment. Therefore, designing the energy systems based on clean and renewable criteria is considered a sustainable solution for smart cities. Indeed, the deep and rapid penetration of renewable energy-based technologies have been believed to very well fit into a smart city under various scales, this could supply a secure basis for a modern society with a low-carbon economy. In this review paper, the main components and roles of renewable energy resources (such as solar, wind, geothermal, hydropower, ocean, and biofuels) for the smart city were fully introduced. Besides, integrating the renewable sources form into the energy systems of smart cities was thoroughly analyzed on the basis of technical and economic criteria. Finally, existing challenges and future scenarios were also discussed in detail to clarify the progress and perspective of smart renewable energy systems for the smart city. In general, the integration of renewables into energy systems of the smart city is a sagacious perspective and solution aiming to achieve cleaner process and more sustainable development. However, the optimization issues of the energy system for integrating of renewable components, ensuring good stability, maximizing the operating range, and minimizing the investment costs should be critically evaluated in the future works. • Designing tools and key criteria for smart renewable energy systems. • Efficiency and prospect of integrating renewables into energy system for smart city. • Existing problems and challenges for renewable-based energy system in smart city. • Future scenarios for the sustainable development of energy system in smart city. [ABSTRACT FROM AUTHOR]

The main objective of this review paper is to present the historical development, current utilization, practices and opportunities of geothermal energy in Algeria. Algeria has relatively abundant geothermal resources of low-enthalpy type that could form part of the total energy network of the country. Algeria is the leading country of the direct use of geothermal energy in Africa with a total amount reaching 54.64 MW t installed thermal power, and also among the first five countries in the world in air conditioning application. The main utilization field of geothermal energy in Algeria is balneology, which accounts for about 82% of the total geothermal power utilization, the remaining 18% of the energy is consumed for other purposes such as space heating, heat pumps and fish farming. In this study, the existing literature and current practices of the Algeria's geothermal resources are reviewed and it is revealed that geothermal energy development remained almost stagnant over the past two decades in Algeria although there is a large potential and resources available in the country. Furthermore, geothermal energy use and latest technologies around the world have been summarized. This study elucidates the influencing factors in the development of geothermal energy in Algeria and suggests the development roadmap and a number of measures that can enhance the development of this significant energy source. • Previous researches on geothermal energy in Algeria are reviewed. • Geothermal energy utilization and advanced technologies around the globe are summarized. • Current geothermal energy utilization in Algeria is discussed. • Exploitation opportunities of geothermal energy in Algeria are addressed. • Countermeasures to promote geothermal energy development in Algeria are proposed. [ABSTRACT FROM AUTHOR]

Renewable energy is one of the fastest growing segments of energy consumption and wind energy is one of the most widely used sources of renewable energy. There is, however, much less known about the main drivers of wind energy consumption at the country level. This paper uses the logarithmic mean Divisia index (LMDI) method to study the driving factors in wind energy consumption for a group of 17 countries (Australia, Canada, China, Denmark, France, Germany, Greece, India, Ireland, Italy, Japan, Netherlands, Portugal, Spain, Sweden, United Kingdom, and the United States) that are major consumers of wind energy. The renewable energy share component has the largest impact on wind energy consumption. Improvements in energy intensity are the largest driver of reductions in wind energy consumption. Wind energy consumption forecasts for each country in the business as usual (BAU) scenario for the years 2018–2025 show that compound annual growth rates (CAGRs) for wind energy consumption are highest for Canada, Sweden, China, and Germany. Countries that have high shares of renewable energy like Spain, Portugal, and Denmark have low forecast values of CAGRs. Wind energy forecasts are also calculated for a high growth rate scenario and a low growth rate scenario. Future increases in wind energy consumption are going to depend upon the continued increase in renewable energy share which in turn is affected by energy policy designed to promote fuel switching from fossil fuels to renewables. [ABSTRACT FROM AUTHOR]

Low carbonization is an inevitable pathway toward the sustainable development of gear machining. Reliable and reasonable prediction of hobbing parameters can effectively reduce energy consumption and carbon emissions. The initial value of process parameters is often generated in a large range, which has a negative effect on the subsequent parameter prediction and the improvement of carbon emission, cutting time and cost. In this paper, a three-stage parameter prediction approach is proposed based on the similarity retrieval method, ε-support vector regression (ε-SVR) and an improved Harris hawks optimization for reducing the cutting time, cost and carbon emissions under data-driven conditions. The first stage is responsible for searching past machining cases similar to hobbing process problems. The ε-SVR and Harris hawks optimization hybrid approach (SVR-HHO) is applied to predict the hobbing parameters in the second stage. Finally, the hobbing process parameters obtained in the second stage are revised using the improved multi-objective Harris hawks optimization for reducing carbon emissions, cutting time and cost. Compared with several well-established algorithms, SVR-HHO is evaluated against 9 benchmark datasets, performing better than 7 of them. A practical case of hobbing prediction is used to perform the feasibility verification and comparison study for the entire approach. The proposed approach achieved a relative carbon emission reduction of 9.3%, when compared to multi-objective HHO. The proposed approach obtained the optimum carbon emission, cutting time and cost compared with other approaches; therefore, it can adequately resolve the problem of the low-carbon hobbing parameter prediction. The performance of prediction stability and running time is slightly weak. Therefore, improving it is a major challenge for future research. Image 1 • Harris hawks optimization is applied to improve the parameters of ε-SVR and hobbing. • Prediction accuracy of ε-SVR is greatly improved with Harris hawks optimization. • Multi-objective Harris hawks optimization is realized using Pareto optimization. • Hobbing parameters are revised for carbon emissions, cutting time and cost. • The proposed method achieved a relative carbon emission reduction of 9.3%. [ABSTRACT FROM AUTHOR]

Passive design strategies such as orientation, shading, sealing, glazing, and insulation can significantly reduce the necessity of an artificial heating-cooling system, accounting for 40% of total energy usage in the residential building. However, none of the previous studies have quantified the energy reduction and their environmental impacts simultaneously for these passive design parameters to achieve the national standard requirements for house rating. Hence, this study focuses on the use of Building Information Modeling (BIM- Autodesk Revit), energy rating tool (FirstRate5), and BIM-enabled life cycle assessment (LCA- Tally) to quantify, compare, and improve the building design options to reduce carbon footprint and energy consumptions in residential dwellings. Sensitivity analysis has been performed with the @ Risk Palisade decision tool for optimizing operational energy efficiency. The sensitivity indices show the ceiling (0.84–0.96) and the wall (0.22–0.37) are the most influential predictors for passive design strategies to reduce energy consumption. A moderate correlation exists with windows, floors, and orientations (0.13–0.29), where the relationship with eave projection, air infiltrations is relatively weak. BIM has been used as a platform of interconnectivity between optimized operational energy of @ Risk optimizer and consequent embodied phases. A comparative study of insulation performance identifies that 95% of the ceiling's total operational energy consumption can be minimized using R3 rather than R6 of the national thermal code. For the wall, 90% of energy minimization can occur using R2 rather than R4 of the national thermal code. The study reveals that while insulation is only 1% of the total building mass, and the corresponding carbon footprint and primary energy demand are 4% and 7%, respectively, LCA explains a significant amount of energy, about 76% reduction at its operational stage. In this paper, an evidence-based analytical framework provides a BIM-based optimization platform to validate and justify the impact categories of environment-friendly, energy-efficient design of houses. Image 1 • Energy rating tool (FirstRate5) is used to incorporate passive design strategies to estimate operational energies. • A BIM-based framework is proposed to integrate FirstRate5 and LCA (Tally) to optimize design scenarios. • Monte Carlo simulation is conducted to obtain the sensitivity indices for design optimization. • In the BIM platform, energy and emissions from the operation and embodied phases are linked to select the best design. [ABSTRACT FROM AUTHOR]

The recent historical increase in energy-related CO 2 emissions globally have put the United States of America's (USA) transportation sector in the spotlight, courtesy of the significantly high pollutant emissions from this particular sector. Taking a cue from this, this paper follows sustainable development goals of the United Nations, and investigates the impact of biomass energy consumption, fossil fuel energy consumption, and economic growth (GDP) on carbon dioxide (CO 2) emissions in the transportation sector of the USA. In doing so, this study also employs the Gregory-Hansen cointegration, Hatemi-J cointegration, cointegration regression (FMOLS, DOLS, and CCR), and Spectral Breitung-Candelon causality test for the period between 1981Q1 and 2019Q4. The findings reveal that (i) a significant nonlinear cointegration among the environmental quality determinants is observed, using the threshold cointegration test. This test determines the structural breaks endogenously and combines two cointegration tests, namely the Gregory-Hansen Cointegration and Hatemi-J Cointegration tests; (ii) while the use of biomass energy consumption and real GDP have a negative effect on CO 2 emissions in the transportation sector, the rising fossil fuel energy consumption is associated with increasing the CO 2 emissions that are stemming from the transportation sector; (iii) in the long-run, biomass energy consumption, fossil fuel energy consumption, and real GDP cause CO 2 emissions to stem from the transportation sector in the USA at different frequency levels. In general, the current study offers policy insights for the transportation sector of the USA and other similar economies that replicate the same conditions. Image 1 • We explore the driving forces of CO 2 emissions in the transport sector for the USA. • We employ advanced time series econometric techniques for empirical analysis. • Biomass energy and real GDP help to mitigate CO 2 emissions in the transport sector. • Fossil fuel energy has a positive impact on CO 2 emissions in the transport sector. • All variables have a causative relationship with CO 2 emissions in the long-run. [ABSTRACT FROM AUTHOR]

The traditional synthesis gas (syngas) production process in the coal chemical field encounters the problems of high cold energy consumption and difficulty in effectively capturing CO 2. This limits the clean production and sustainable development of coal chemical industry. To solve this problem, this paper proposes a novel process for capturing and separating CO 2 from syngas using [bmim][Tf 2 N]. This process can effectively reduce the cold energy consumption and improve the CO 2 capture efficiency, which will help relieve the global concerns over CO 2 emissions. Energy, economic, and environmental analyses of the process were conducted based on accurate modeling and simulation results. To balance the conflict between the economic and environmental performances, the non-dominated sorting genetic algorithm II method was used for the multi-objective optimization of the process. The CO 2 escape flow rate and total annual cost were the objective functions of the multi-objective optimization scheme and had values that were 5.9% and 1.5% higher than their minimum values, respectively. Moreover, the multi-objective optimization scheme for this process was compared with the Rectisol process and CO 2 capture from syngas using [emim][Tf 2 N]. This work provided new ideas for clean production of coal chemical industry, and also provided reference for the green sustainable development of relevant work. • A novel [bmim][Tf 2 N]-based CO 2 capture and separation process at 25 °C is proposed. • Energy, economic, environmental comprehensive analyses are used to study the process. • Multi-objective optimization balances the conflicting objectives of this process. • The multi-objective optimization process has feasible CO 2 capture ratio (96.34%). [ABSTRACT FROM AUTHOR]

With the increase in awareness of energy conservation and emission reduction in the manufacturing sector, the energy efficiency optimization of the production process is considered an effective way to promote cleaner production and environmentally sustainable development. Moreover, the transportation process and its energy consumption are non-negligible during the entire workshop production process. In practice, cutting tool degradation during operation is inevitable, which causes the actual processing time of work to be extended, so it is necessary to consider the degradation effects and imperfect maintenance. To reduce the total energy consumption in the manufacturing workshop with degradation effects and imperfect maintenance, this paper constructs a novel integrated optimization model including the flexible job-shop scheduling problem (FJSP), forklift transportation and imperfect cutting tool maintenance. First, an imperfect cutting tool maintenance with degradation effect strategy is presented, which makes the actual processing time of each operation more closely approximate the real-world processing situation. Second, an integrated multi-objective optimization model is formulated to simultaneously minimize the makespan, total tardiness, total production cost and total energy consumption. Third, a hybrid multi-objective evolutionary algorithm with Pareto elite storage strategy (HMOEA/P) is proposed to address the model. More precisely, three improved operations are presented: hybrid dominance principle, local search algorithms and Pareto elite preservation strategy. The effectiveness and feasibility of the parameter setting, improved operations and the proposed algorithm are separately demonstrated by the comparative experiments. Last, the superiority of the integrated multi-objective optimization model is proven by comparing different maintenance strategies and energy consumption models. [ABSTRACT FROM AUTHOR]

Considering the current national conditions of China, developing coal-to-liquid process is an attractive way to alleviate the domestic oil crisis. Coal-to-liquid process mainly includes six subsystems and the most essential unit of the system is the gasification unit. This paper aims to provide suggestions for the cleaner production and sustainable development of coal-to-liquid technology. Lurgi, Texaco, and Shell coal-to-liquid process are modelled and simulated. The techno-economic analysis is conducted to investigate their performance using simulation-based results. Results showed that the greenhouse gas emissions of Lurgi, Texaco, and Shell coal-to-liquid process are 5.26 t/t fuel, 4.86 t/t fuel, and 3.49 t/t fuel. Lurgi coal-to-liquid has better performance on reducing oxygen cost and total investment; Texaco coal-to-liquid is advantageous in saving steam cost and production cost; Shell coal-to-liquid shows better performance in terms of energy efficiency, reducing the consumption of coal and water, and greenhouse gas emission. Shell gasifier is recommended in water-deficient areas. Texaco gasifier is recommended when access to water and coal is sufficient. Lurgi gasifier is recommended in pilot-scale projects. In the view of sustainable development, Shell gasifier is prior to Texaco gasifier and Lurgi gasifier because of the low greenhouse gas emission and well resistance to high coal price and high carbon taxes. Gasification unit occupies the largest proportion of total capital investment of coal-to-liquid processes and significantly affects the syngas composition. Coal gasification technology is potentially limiting the overall acceptance and practice of coal-to-liquid process in the future. Image 1 • Techno-economic analysis of coal-to-liquid processes are conducted. • Lurgi coal-to-liquid has a better performance on oxygen cost and total investment. • Texaco coal-to-liquid is shown to have a better performance on steam cost and production cost. • Shell coal-to-liquid has a better performance on energy efficiency, coal and water consumption. • Suggestions for cleaner production and future development of coal-to-liquid are provided. [ABSTRACT FROM AUTHOR]

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

Carbon emissions and energy consumption have serious impacts on humans and ecosystems. This paper investigates the effects of industrial reconstructuring on energy conservation and emission reduction. A multi-objective optimization model was established. The model classifies industrial sectors into four groups according to their carbon emission levels and contributions to economic growth, then non dominated sorting genetic algorithm is applied to solve the model and the Pareto frontier is obtained. The best solution is selected from the Pareto frontier by using a super data envelopment analysis model which measures the degree of coordination between economy and environment. The model is used to analyze the effects of industrial reconstructuring in Beijing during 2018–2020. The results show that industrial reconstructuring enabled economic growth to reach the government's planned rate while the carbon intensity and energy intensity surpassed the goal of the 13th Five-Year Plan. This case can provide decision-making basis for the sustainable development of ecology and economy in other regions. Fig. 6. Pareto front in Beijing region in 2020 The optimal Pareto solution for carbon emissions, energy consumptions and GDP targets after industrial structure reconstructuring. Image 1 • Classifying industrial sectors into four groups according to carbon emission levels and economic growth contributions. • A multi-objective optimization model was established and solved by the genetic algorithm. • A super DEA model evaluates the final plan which reflects the coordination of the economy and environment. • The analysis of each group can help achieving maximum benefits of economic and environment. [ABSTRACT FROM AUTHOR]

Sanitary ware industry consumes vast amounts of energy and materials; however, little is known about the environmental impacts and economic costs associated with the production of sanitary ware. Selecting a factory of a leading Chinese sanitary ware company, Huida Co. Ltd., this paper employs a combined "cradle-to-gate" life cycle assessment (LCA) and life cycle costing (LCC) methodology to evaluate the environmental impacts and economic costs related to the production of one tonne of sanitary ware. The LCA results indicate firing and drying are the processes with the greatest environmental impacts, attributing to the combustion of coke oven gas. The LCC results show that casting, body preparation and firing are the greatest contributors to the total equipment, material and energy costs, respectively. The results of sensitivity analysis confirm that increasing fuel efficiency, natural gas usage and recycling rates can reduce the overall environmental impacts, but the total costs would be increased by 13.8% if coke oven gas is fully replaced by natural gas, even considering carbon tax. Based on the findings, recommendations such as using green materials and improving energy efficiency, are provided to promote both the environmental and economic sustainability of sanitary ware production. Image 1 • Environmental impacts and economic costs of sanitary ware production are evaluated. • Firing and drying have the greatest environmental impacts due to fuel consumption. • Casting and body preparation contribute most to the equipment and material costs. • Using natural gas as fuel reduces environmental impacts while rises costs. • Recommendations are provided to foster the sustainable production of sanitary ware. [ABSTRACT FROM AUTHOR]

The CO 2 emission that accompanies significant consumption of energy raises concern as for whether economies that require such path like Ghana can also achieve sustainable economic development. In this paper, the driving factors of energy-related CO 2 emissions and its future trend for Ghana is studied using a time series data spanning from 1980 to 2016 in an Autoregressive Distributed Lag Model with Extended Kaya Identity framework. First Kaya identity was adopted and extended to decomposed CO 2 emission driving factors into carbon intensity, energy intensity, economic activity, and substitution effect. The estimates were further used to forecast CO 2 emissions through to 2030. The results indicate the major driver for historical CO 2 emissions increase in Ghana has been the transition from biomass to petroleum fuel consumption. This is followed by the energy intensity of economic output, carbon intensity changes and overall economic activity. Carbon-free energy consumption currently does not lead to a reduction of CO 2 in Ghana. The forecasting results show the current trend of energy consumption and economic development path have the potential for CO 2 emissions reduction. Some targeted policy suggestions in relation to the estimate results are also provided. • Energy consumption structure in Ghana favour CO 2 emissions increase towards 2030. • Major driver of CO 2 emissions in Ghana is a transition from biomass to petroleum. • The energy intensity for Ghana does not offer low CO 2 emission path. • Economic development path in Ghana leads to CO 2 emissions increase. • CO 2 emissions reduction potential exist for Ghana towards 2030. [ABSTRACT FROM AUTHOR]

With the deepening understanding of the concept of sustainable development in the world, the roasting method of concentrated sulphuric acid with high pollution and energy consumption adopted by Bayan Obo rare earth ore has become a technical bottleneck and pollution source that seriously restricts the development of rare earth production enterprises. This paper proposes a new clean smelting technology for Bayan Obo rare earth ore, which mainly includes oxidative roasting, NaOH roasting, water washing and acid dissolution. The experimental results show that under the optimum experimental conditions, the washing rate of F and P can reach 63.21% and 17.24%, and the extraction of rare earth can reach 88%. Compared with the existing technology, the new smelting technology has greatly reduced the pollution of three wastes, which can not only realize the recovery of P and F, but also fundamentally alleviate the damage of P and F to the subsequent extraction process. Moreover, the amount of NaOH is less and Th resources are relatively concentrated. Both of them can be recovered economically and reasonably. The new smelting technology has the advantages of short process flow, simple operation and predictable environmental protection. [ABSTRACT FROM AUTHOR]