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Dual shuttle cranes scheduling problem is an option of Automated Storage and Retrieval System (AS/RS), which has paid marginal academic regard, so it could be extended to advance novel challenges that should be investigated. In this paper, an integrated class-based storage location assignment and dual shuttle cranes scheduling problem is addressed by introducing a novel bi-level optimization model. In the upper-level, the locations of storing and retrieving products under class-based storage policy, multi-period planning and inventory considerations are determined, which its objective functions are included minimization of total cost and energy consumption. The solution of this level is utilized by the lower-level, which is related to the scheduling of dual shuttle cranes. In the lower-level, a broad range of necessities of rewarding scheduling, ranging from workload balance to time windows under multi-period planning is reflected. Since the proposed model is a bi-level and bi-objective, a Modified Cooperative Coevolutionary Algorithm for Bi-Level Optimization (MCoBRA) is presented with the intention of solving the proposed model. Finally, in order to illustrate the validation of the proposed model and solution approach, a broad range of numerical experiments are sketched out, and some comparative analyses concerning two existing algorithms in the literature are provided. Sensitivity analyses show that considering class-based storage policy in the upper-level has significant influences on the whole of the objective functions, which could be offered better planning of operations. [ABSTRACT FROM AUTHOR]

A biomass gasification based multi-generation system integrated with thermoelectric generators is developed and proposed for cleaner applications. The paper presents, analyzes and validates a novel integration of the thermoelectric generators in the proposed biomass gasification based system and discusses the possibility of better efficiency and energy use with reduced carbon emissions. The influences of varying biomass gasification parameters are also studied against the syngas composition. The major subsystems of the integrated system, such as gasification, cryogenic air separation unit, Brayton cycle, heat recovery and domestic hot water production is simulated using Aspen plus while the Engineering Equation Solver (EES) is employed to model thermoelectric generators, proton exchange membrane electrolyzer and organic Rankine cycle. The system operating conditions and their effects on system performance are investigated. The waste heat from the thermoelectric generators is employed to the organic Rankine cycle to produce power and work generated by thermoelectric generators is employed to the proton exchange membrane electrolyzer to produce hydrogen. The amount of hydrogen produced is about 0.13 kg/day, and the amount of heating achieved by the system is 1.4 MW. Likewise, the proposed system is capable of producing 22 kg/s of hot water for the domestic purposes. The overall energy and exergy efficiencies are found to be 58.03% and 32.78%. As compared to conventional systems with thermoelectric generation, the system proposed in this study carries unique and superior characteristics. • A biomass gasification based integrated energy system is uniquely proposed. • Influence of biomass gasification parameters on syngas composition is investigated. • Operating conditions and their effects on system performance are investigated. • Power from thermoelectric generators is employed to the PEM electrolyzer. • The overall energetic and exergetic efficiencies are found to be 58.03% and 32.78%. [ABSTRACT FROM AUTHOR]

Polyurethane-bounded pavement with good road performances is a new pavement form. Whether polyurethane (PU) pavement met the requirements of energy conservation, environmental protection and sustainable development or not, the energy consumption and emission of PU pavement in whole life cycle were analyzed systematically in this paper. Firstly, the life cycle of pavement was divided into six phases: material production, mixture production, transportation, construction, maintenance and recycling according to the construction technology of road in China. Based on the classification of the life cycle environmental impact assessment (LCIA), the effects of six main exhaust gases (CO 2 , CH 4 , N 2 O, CO, SO 2 , NO x) were divided into four categories: Global Warming Potential (GWP), Eutrophication Potential (EP), Photochemical Smog Potential (POCP) and Acidification Potential (AP). Secondly, the energy consumption and emission of each phase are studied, and the main phase with significant environmental impact was selected. Thirdly, the results of inventory would be normalized and weighted to analyze the environmental impact by the life cycle impact assessment (LCIA). The LCIA method was environmental design of industrial product 97 (EDIP 97). Results show that the construction of PU pavement is conducive to energy conservation. Besides, the energy consumption of mixture production phase is the largest in asphalt pavement, and it is material production phase in PU pavement. In terms of emission, the emissions mainly occur in material production and mixture production phases in asphalt pavement, and it is material production phase in PU pavement. Under the same structure, the construction of PU pavement is not conducive to reducing the emission, and will enlarge the GWP, EP and AP. For example, the CO 2 , N 2 O and NOx emissions of PU pavement are 1.98, 5.30 and 2.35 times higher than that of asphalt pavement respectively, but the CO emission of asphalt pavement is 3.86 times higher than that of PU pavement. Furthermore, the results of LCIA show that the score of all environmental impact of PU pavement is little smaller than that of asphalt pavement after normalization and weighting. However, the road performances of PU pavement are much better than that of asphalt pavement. With the same environmental impact, PU pavement has a longer service life. It is summarized that PU pavement meets the requirements of environmental protection and sustainable development in the long run. This is conducive to the promotion and application of PU pavement. • The energy consumption and emission of PU pavement in life cycle were studied. • The goal and scope definition of this study were determined. • The key phases of high energy consumption and emission were identified. • The comprehensive environmental impact assessments of asphalt pavement and PU pavement are conducted. [ABSTRACT FROM AUTHOR]

Understanding which factors influence urban metabolism is a prerequisite for designing policies and plans that effectuate sustainable resource management. A growing number of publications is concerned with these factors. Yet, this emerging field of research lacks a common framework that supports researchers in interpreting their findings, such as generalizability to other cities, and making informed decisions on their research design. Aiming to contribute to building such a framework, we systematically reviewed urban metabolism literature. This review paper presents an overview of factors influencing urban water and energy consumption and their effect on consumption, and it describes the interconnectedness of these factors for six different types of relationships. Results disclose fourteen drivers, changes in societal context that shape consumption patterns, and twenty-one facilitators/constraints. The latter type of factors include consumer, resource and urban landscape characteristics that affect resource consumption by facilitating or constraining specific activities. Findings indicate commonalities between primary studies in terms of prevalent observed effect direction for a given factor. However, the interconnections between different factors can influence the direction and magnitude of effects and thereby result in case-specific variability in consumption patterns. Future research should enhance the understanding of these interconnections, strengthen the evidence for the factors presented here and provide insight in additional factors of influence. It is essential to align these studies in terms of a common terminology, transparent quality assessment and a unified approach to measuring and expressing factors of influence. Connecting with related disciplines working on a common systems approach is key to realize the full potential of urban metabolism research to advance our understanding of cities. • We present an overview of the factors influencing urban water and energy consumption. • Changes in societal context affect consumption as drivers. • Consumer, resource and urban landscape characteristics act as facilitator/constraint. • These factors are interconnected across various spatial and temporal scale levels. • This interconnectedness generates case-specific effects on consumption patterns. [ABSTRACT FROM AUTHOR]

In order to keep pace with the global trend of controlled and proper energy usage, the Korean government has enforced its energy-related regulations. However, the firms under these regulations are of the view that this approach may threaten their financial performance. In response to the growing interest of industry in Korea, this paper investigates whether energy efficiency has a positive relationship with firms' financial performance. For the purpose of accommodating various factors for measuring energy efficiency, we extended an existing two-stage network DEA (Data Envelopment Analysis) model that distinguished pure-energy efficiency and economy efficiency by developing a multi-period model with the aim to identify any change in efficiency during each period. An empirical analysis on Korean firms reveals interesting findings; First, while it is true that energy efficiency has changed over time, there is a difference in the magnitude of changes by industry. Firms in more energy-intensive industry have experienced more changes in their energy efficiency performance. Second, it is impossible to improve both categories of efficiency (i.e., pure-energy and economic efficiencies) at the same time. Thus, a firm should understand its current position in order to determine the extent and direction of efficiency improvements. Third, the energy efficiency has been found to have a significant relationship with financial performance. However, firms whose pure-energy efficiency was found to be relatively high did not always achieve better financial performance. [ABSTRACT FROM AUTHOR]

Following India's efforts to mitigate the emission of greenhouse gases, there has been a transition from fossil fuels to clean energy sources, such as solar and wind, in the energy portfolio. The renewable energy sector is widely acknowledged as a fertile ground for employment creation, as it is labour-intensive. Against this backdrop, the main objective of this paper is to provide an empirical explanation of how the growth of renewable energy sources, particularly solar photovoltaic (PV) technology, affects employment creation in India. The findings reveal that, despite a substantial investment in India's solar PV technology, the number of jobs created by the sector declined marginally from 164000 in 2017–114000 in 2018. India's estimated employment elasticity is just 0.004, implying that the level of employment does not show a significant positive response to changes in installed capacity. Almost 60 per cent of the global solar PV workforce is in China, which has become the leading country both in terms of installed capacity of global solar PV technology and manufacturing of solar PV cells and modules. The wide disparity in solar PV employment between India and China is explained by the former's excessive dependence on China for solar PV cells. Alongside climate conservation, India should, therefore, place more emphasis on revitalising the domestic solar manufacturing industry to bring about efficient use of the nation's untapped resources. [ABSTRACT FROM AUTHOR]

Governments design energy-efficiency programs (EEPs) to reduce the energy consumption of the energy-intensive sectors. In this paper, we propose a comprehensive EEP for the industrial and household sectors as a multi-agent problem. A sustainable supply chain consisting of an energy supplier, an energy-efficient manufacturer, and a conventional manufacturer is considered on this matter in a duopoly. Some energy policies under direct, indirect, and combined intervention are applied by the government to improve the cost-effectiveness of the program. In addition, the authors investigate the rebound effects of energy consumption in both sectors, under the consumer behavioral intentions i.e., the efficiency-related awareness, loyalty, and income level as a novel contribution. A multi-stage model is extended based on Cournot model to formulate the problem. The scenarios' comparison and sensitivity analysis of the equilibrium decisions indicate that energy financial policies (e.g., energy tariff) encourage the manufacturers to follow the energy-efficiency path upon their high-energy-consuming products and processes. The combined intervention is more effective than the unilateral policies to reduce energy intensity and increase the energy-saving and social welfare of the industrial and household sectors, respectively. The industrial tariff also seems to be more powerful policy than consumer tariff and energy-efficiency awareness to satisfy the investigated energy-related targets. Finally, the present study provides a management point of view of a sustainable supply chain for energy policy-makers. • A Cournot model with consumer loyalty is proposed for an energy-efficiency program. • Consumer features and energy intensity as a novel utility function are considered. • Government policies encourage manufacturers to follow efficiency programs. • Combined energy policies are the best ways to promote energy efficiency approach. • Industrial tariff is more powerful than the other tools to satisfy energy targets. [ABSTRACT FROM AUTHOR]

This study is meant to investigate the main driving factors of energy consumption structure (ECS) in China and construct a hybrid prediction model with higher accuracy. In this paper, Logarithmic Mean Divisia Index (LMDI) is applied to study the factors of energy consumption structure of China covering 1980 to 2016 and calculate the contribution of each factor. The factors that have large contribution rate are selected as the main factors of energy consumption structure to simplify prediction model. And then, the original data series of energy consumption structure and main factors are decomposed into different components by empirical mode decomposition (EMD) model to deal with the intrinsic complexity and irregularity of sequences. Finally, the components are used as input data to construct the prediction model, least square support vector machine (LSSVM), the coefficients of which are optimized by the particle swarm optimization (PSO) algorithm. The results show that prediction error of EMD-PSOLSSVM model is significantly lower than benchmark models of grey model neural network and PSOLSSVM model. The constructed model fully exploits the advantages of each algorithm of the hybrid model and improves the prediction accuracy of energy consumption structure. Image 1 • The energy consumption structure in China is decomposed for 1980–2016. • The empirical mode decomposition is applied to decompose factors. • A hybrid prediction model is constructed to forecast energy consumption structure. • Income is dominant force of energy consumption structure. • The accuracy of hybrid model is far higher than benchmark models. [ABSTRACT FROM AUTHOR]

Through dynamic analysis of the train-track-bridge (TTB) system, vehicle induced vibration responses of a rail transit continuous rigid bridge on Guangzhou Metro Line 14 are obtained. Aiming to expand the frequency bandwidth and harvest vehicle-induced vibration energy efficiently from different vibration peaks, 3 types of multi-frequency electromagnetic vibration energy harvesters (EM-VEHs) with 4 submodules are designed in this paper. Based on this, energy harvesting and conversion performance of the proposed multi-frequency EM-VEHs are fully investigated. Energy harvesting analysis show that the harvested vibration energy of each type is up to 90% in the first 50 s during the 5-min train running period. Average power output for 24 h of the 3 types of EM-VEHs are 0.91 W, 1.41 W and 0.84 W in sequence, each of which could meet the normal working requirements of the above sensor unit. Compared with SDOF EM-VEH, all the 3 types of MDOF devices win perfectly in harvesting vibration energy efficiency from different vibration peaks, energy conversion stability with no decrease in power output. Due to the unneglectable mass of the lead blocks in the 4 submodules, the EM-VEHs perform an additional function of being tuned mass damper. Proper matching between the gross mass and vibration energy harvesting efficiency is significant during the design procedure of multi-frequency EM-VEH. • Proposed 3 types of multi-frequency EM-VEHs to harvest vehicle induced vibration energy at different frequency peaks. • Stable and continuous vibration excitation is critical for the working efficiency of EM-VEHs. • The proposed EM-VEHs are improved by orders of magnitude in energy harvesting efficiency than most exsiting EM-VEHs. • Proper matching between the gross mass and energy harvesting efficiency is considerable while proposing an MDOF EM-VEH. [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]

Nowadays the manufacturing enterprises are driven towards significant energy improvements by increasing energy costs and sustainability awareness, and energy consumption and energy efficiency are taking a more and more dominating position in the decision-making process of manufacturing enterprises. However, in the process of production, existing researches rarely integrate energy management with conducting preventive maintenance at the strategic level, ignoring energy-saving opportunities that may arise during machines' downtime. This paper considers a serial production system with intermediate finite buffers. Based on the concept of "energy-saving opportunity window" and the modelling of the continuous deterioration process of each machine, the window of energy-saving opportunity of the production system is regarded as a window of opportunity for the preventive maintenance, thus a proactive preventive maintenance strategy is proposed. The serial production system is modeled and the impact of different maintenance thresholds on the energy efficiency is explored by means of Monte Carlo simulation. For purpose of maximizing the energy efficiency of the entire production system, an iterative algorithm for solving the optimal preventive maintenance thresholds is presented as well. The numerical analysis with other maintenance strategies shows that the proposed strategy is more competitive in improving the effective throughput while reducing the overall energy consumption. • A proactive condition-based preventive maintenance policy was proposed. • Integrating the concept of energy-saving window (ESW) and the quality loss into an optimization production model. • An energy-related objective function, effective energy efficiency (EEE), was developed. [ABSTRACT FROM AUTHOR]

Coarse coke particles, thick combustion zone, and poor thermal permeability during sintering have been widely reported to lead to incomplete solid fuel combustion and low oxygen potential, which induces the formation of harmful gas and decreases the energy efficiency. To solve these problems, stand-support sintering with an ultrathick 1000 mm bed was first proposed in this paper. The influences of the stand height and coke size on the process parameters and sinter quality were studied through a series of experiments. The results showed that the average gas flow velocity increased from 0.24 m/s to 0.32 m/s and the maximum combustion zone thickness decreased from 202 mm to 140 mm, which indicated that stand-support sintering could substantially improve the thermal permeability and enhance the oxidizing atmosphere. The fuel consumption was reduced by 1.28 kg/t (2.25%), the generated CO in exhaust gas was reduced, and the production efficiency increased by 17.4% when the stand height increased from 0 to 500 mm. Moreover, a 3D high-energy X-ray computerized tomography (CT) scanner was first used to quantitatively confirm the effect of the stand on the distribution and size of the pores in the whole sinter cake. Research findings showed that the porosity increased by 7.1% when the height of the stand increased from 0 to 500 mm, which further illustrated the effect of stand-support sintering. The present study provided an effective way to optimize the energy efficiency and reduce the CO content in exhaust gas. Image 107820 • Fuel consumption and generated CO in exhaust gas reduced. • The production efficiency increased by 17.4% when the stand height was 500 mm. • Stand-support sintering has good adaptability to coarse coke (>3 mm, 20–40%). • Decreases in TCZ and MTCZ are desirable for coke combustion and sinter quality. • 3D pores distribution feature of sinter cake was firstly proposed through CT. [ABSTRACT FROM AUTHOR]

The manufacturing sector consumes a significant amount of energy and their outputs, like solid and gaseous waste streams, can result in substantial stress on the environment. This paper aims to analyze and compare the electrical energy and material efficiency of machining, additive and hybrid manufacturing. The analysis of the manufacturing processes is based on machine tool data from a sample process. To get a generalized statement about the energy consumption of the investigated processes the electrical energy demand was extrapolated as a function of the material removal ratio. The results indicate that hybrid manufacturing becomes beneficial from an environmental point of view compared to milling, when the material removal ratio exceeds 55%. The electrical break-even point for selective laser melting is approximated to 82% material removal ratio from data extrapolation. Subsequently, opportunities for electrical energy and material efficiency improvements are presented for these technologies to gain an understanding of how each can contribute to a more sustainable manufacturing landscape. • Additive processes show a smaller amount of wasted material. • For material removal ratios over 55% additive processes show less demand of energy. • For material removal ratios over 75% additive processes show less processing time. [ABSTRACT FROM AUTHOR]

Energy Consumption monitoring technology (ECMT) can effectively reduce the energy consumption of public buildings (PB) in the operational phase, but it is not used widely in China. The main reason for this is that the existing policies have a poor effect on diffusing ECMT; thus, studying the impact of different policy instruments on ECMT in PB is of great significance to the widespread use of ECMT and its role in decreasing the energy consumption of PB. This paper systematically reviews the policy related to ECMT in China from 1990 to 2018, and, on this basis, divides the promotion stage of China's ECMT into three stages: the concept stage, the demonstration stage and the gradual promotion stage. A questionnaire survey and semi-structured interview of 313 stakeholders (ECMT suppliers, government officials, and scholars) was used to study the influence of command-and-control instruments (CAC), economic incentive instruments (EI) and exhortatory instruments (EXI) on the diffusion of ECMT in PB. The empirical results show that CAC and EXI contribute to the diffusion of ECMT in PB, whereas EI do not. In more detail, laws and regulations, energy consumption quotes, education and information programs, and energy audits and disclosure also have a significant impact on diffusing ECMT, whereas technical standards, subsidies for adopting ECMT, energy performance contracting, and carbon trading do not. Finally, relevant policies and suggestions are put forward based on the results. [ABSTRACT FROM AUTHOR]

With the economy development and rapid urbanization, the residential usage of energy has been increasing in China, leading to more CO 2 emissions in resident sector. To predict the trend of residential energy-related CO 2 emissions accurately, it is significant to analyze the influential factors. In this paper, 18 preliminary indicators are identified by grey relational analysis to prove their correlation with CO 2 emissions firstly. To reduce the redundancy of data, 4 main components are extracted by principal component analysis as predicting input data of support vector machine (SVM). By adding chaotic mutation and nonlinear weight index, the improved chicken swarm optimization (ICSO) algorithm is proposed to optimize the parameters of SVM, hereafter referred as ICSO-SVM. Finally, the new hybrid model is applied to predict residential energy-related CO 2 emissions in Shanghai, China. The simulation results in the forecasting accuracy demonstrate that the ICSO-SVM model outperforms the compared original chicken swarm optimization model (CSO-SVM), particle swarm optimization model (PSO-SVM), genetic algorithm optimization model (GA-SVM) and basic SVM. The rigorous influencing factors analysis and the outstanding performance in predicting CO 2 emissions of ICSO-SVM model can offer relevant scholars and policy makers more breakthrough points of residential CO 2 emissions abatement. [ABSTRACT FROM AUTHOR]

This paper proposes a robust co-state predictive model for Pontryagin's Minimum Principle (PMP)-based energy management of plug-in hybrid electric bus (PHEB). The main innovation is that the robust co-state predictive model is only expressed by a simplified formula. Moreover, it is exclusively designed by the Design For Six Sigma (DFSS) method in consideration of noises of driving cycles and stochastic vehicle mass. Because the DFSS strives to minimize the weighted sum of mean and standard deviation of fuel consumption, the proposed strategy can simultaneously improve the fuel economy of the PHEB and its robustness. The DFSS results show that the coefficients of the robust co-state predictive model can be found; the simulation results demonstrate that the proposed strategy has similar fuel economy to dynamic programming (DP); the hardware-in-loop (HIL) results demonstrate that the proposed strategy has good real-time control performance, and can averagely improve the fuel economy by 35.19% compared to a rule-based control strategy. Image 1052 • A robust co-state predictive model is designed by the Design For Six Sigma method. • The predictive model can counter the noises of driving cycles and stochastic vehicle mass. • The predictive model can simultaneously minimize the mean and standard deviation of the fuel consumption. • The robust and real-time control performances of the strategy are verified by hardware-in-loop test. [ABSTRACT FROM AUTHOR]

The variation in BEV energy consumption and driving range under different weather and driving conditions can affect the usefulness and consumer acceptance of these vehicles. Thus, there is a need to better understand and quantify seasonal factors that affect consumption and range under real-world driving conditions. In this paper, a dataset representing the real-world driving activity of 197 BEVs of the same model recorded over 12 months at a polling frequency of 0.1 Hz is analyzed to estimate BEV performance across different driving applications (personal driving, taxi operation, and ridesharing) and seasons (spring/autumn, summer, and winter). The results show that the electricity consumption, travel patterns, and charging patterns of BEVs vary significantly by both vehicle application and season. For example, BEV models with a range of 160 km, recharged every 1.6 days on average, can meet most trip demands of personal vehicles. However, the same BEV model when used for ridesharing or taxi purposes, is driven much more and recharged more frequently. The results also show that actual BEV electricity consumption (EC) differs significantly from the consumption predicted by the New European Driving Cycle (NEDC) test, with real-world EC being 7%–10% higher than predicted by the NEDC test cycle. Furthermore, the real-world range of personal-use BEVs in winter is only 64% of the NEDC-estimated range. The study found that, when the ambient temperature is lower than 10 °C, electricity consumption increases 2.4 kWh/100 km for every 5 °C decrease in temperature. When it is higher than 28 °C, EC increases 2.3 kWh/100 km for every 5 °C increase in temperature. These findings imply that manufacturers should design BEVs with application-appropriate driving ranges and make R&D investments for improving battery performance in cold environments. [ABSTRACT FROM AUTHOR]

Brazil, an emerging economy with more than 208 million inhabitants, is currently one of the biggest consumers of disposable diapers worldwide, generating huge waste streams to sanitary landfills or dumps. This take-make-dispose system causes high material and fuel consumption and serious environmental impacts. The concept of the Circular Economy, promoting that material flows should be circular, material and energy efficiency should be maximized and residues, as far as possible, designed out, has continuously gained attention over the last decade. For a Circular Economy, technological innovation, new business models and changes in consumer behavior are needed. The present study compares the use of modern cloth diapers and disposable diapers via a screening Life Cycle Assessment, checking conventional and innovative circular business models for the application of modern cloth diapers, such as the leasing or pay-per-service models, while focusing on the regional context of Brazil. Results indicate that cloth diapers show generally a better environmental performance than disposable diapers, whose poor performance is mainly due to their end-of-life treatment in sanitary or unsanitary landfill, provoking high greenhouse gas emissions. For cloth diapers, the most advantageous product system consists in a diaper-as-service model at large scale, using efficient continuous batch washers for sanitizing the diapers. Diaper-as-service models at smaller scale in so-called on-premise laundries show poorer environmental performance, due to higher water and energy needs. Domestic laundering of diapers is a good alternative regarding its environmental performance, because of its low energy consumption. However, consumers accustomed with disposable diapers might be reluctant to engage with this additional domestic labor. Image 1 • Disposable diapers hold bad environmental performance due to disposal in landfills. • Average conditions in Brazil lead to lower environmental impacts for cloth diapers. • Product-as-service-models should be used only with highly efficient batch washers. • The cotton used in absorbents of cloth diapers has significant influence on impacts. • Cloth diapers may be a bad choice or Brazil's regions with water scarcity. [ABSTRACT FROM AUTHOR]

This paper presents a parametric study on the impact of solar cells at the building envelope on the generated power, energy consumption, comfort conditions (interior temperature, relative humidity, discomfort hours, and lighting), and CO 2 emissions within a building. It considers the cell position on the facade (cell inside window, two cells outside the window), orientation direction (north, east, south, west), and location (wall, roof). The study is performed under the meteorological conditions in the city of New Borg El Arab, Alexandria, Egypt. The numerical solution of the physical model is solved using the Design-Builder software and is validated through an experiment. The results reveal that solar cells on the facade and roof decrease the annual energy consumption inside the facility by approximately 15% and 40%, respectively, compared to a facility without cells. A cell installed on the roof facing south has the highest annual generated power. For a solar cell on the wall, a cell facing south produces the highest annual generated power and a cell facing north produces the lowest. The temperature inside the facility is lower when the solar cells are installed, and a cell facing south provides comfortable interior conditions in all the investigated cases. A cell located inside the window produces the lowest light intensity and a cell facing north produces the lowest CO 2 emissions. • Solar cell at south wall produces maximum annual cell power generation while north produces the minimum. • Installed solar cell in the facade decreases the annual energy consumption inside the building by 15%. • Solar cell locates inside the window has the minimum light intensity compared to other positions. • Temperature inside building for all cell cases is lower than the temperature in case of not use cell. • Building with cell oriented to north produces minimum annual CO 2 emission in the building. [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]

Under the situation of unmanned driving, the energy consumption in an electric vehicle's acceleration process can be reduced by controlling the driving behavior. So in this paper, a pedal control strategy which could optimize the energy consumption of electric vehicle's acceleration process is proposed. The strategy is generated by the training results of reinforcement learning framework and the specific method of building such framework is discussed in details. Based on the training results of Q-learning-based algorithm, the relationship between the proportion of energy consumption reduction and vehicle's acceleration time is analyzed, which illustrates the energy-saving potential of the algorithm. In order to improve the control effect of the strategy, an updated algorithm framework based on Deep Q-learning (DQN) is proposed and an improved pedal's control strategy is obtained. Compared with the strategy obtained by Q-learning-based algorithm, the improved strategy not only achieves the same energy-saving effect, but also guarantees the stability of control effect, which is more suitable for actual use. [ABSTRACT FROM AUTHOR]

This paper investigates an order acceptance and scheduling problem with an energy consumption budget, a machine launch budget, and the order release time in a green manufacturing system. The phenomenon of deteriorating jobs is considered in the production of the accepted orders. The objective of the study is to maximize the net revenue and a modified variable neighborhood search (MVNS) Algorithm that combines a novel encoding and decoding procedure as well as a dynamic programming algorithm is developed to solve it. To show the effectiveness and efficiency of the proposed algorithm, we first employ the MVNS algorithm and seven VNS-based algorithms to solve the problems with different configurations of orders and machines. The results show that the MVNS algorithm obtains better solutions than existing VNS-based algorithms. Then, the proposed algorithm is compared with three meta-heuristic algorithms. The experimental results show that the proposed algorithm has significant advantages in terms of solution optimality. [ABSTRACT FROM AUTHOR]

Energy sustainability has great importance in the development of the economy and society since energy is a necessary driving force for economic growth. The construction sector accounts for a greater percentage of global energy consumption than most other sectors. The structure of exports in the current trade pattern has affected the transmission of sectoral embodied energy through changes in regional economies. This paper uncovers the composition of productions for gross exports and examines embodied energy from the viewpoint of value added through a case study in the construction sector. Multi-regional input–output tables have been used to process the data relevant to economic trade and energy input, while the production of gross exports in 40 countries has been decomposed into the exports of value-added trade and the exports of vertical specialisation trade based on data from world input–output tables. The decomposition and reorganisation clearly show the pathways and composition in the trade activities of gross exports. The embodied energy of value-added exports accounted for 60–90% of gross exports in the construction sectors of 37 countries. The framework for sharing production in the construction sector still dominated the connections among many countries, especially the trade relationships between large economies. In the process of vertical specialisation trade, the foreign value added of the construction sector was still limited by significant events such as the global financial crisis. The construction sectors were ranked between 5 and 11 in all 35 domestic sectors in 34 countries as measured by the total export of embodied energy. So, the creation of high value added is enhanced by improvement in energy efficiency in the construction sector. However, the reduction of energy consumption in the construction sector may indirectly increase energy consumption in its upstream sectors because of the connection between exports and related production. The balance between energy consumption and creation of value added in exports is an important consideration for government supervision and sectoral development. Local construction markets need to strengthen their ability in the supply of intermediate goods, which benefits value-added exports and domestic demand. Moreover, developing national and international supply chains can positively offset the impact of the imbalanced distribution of globalised production. • Decomposition reveals the pathways of energy flows embodied in vertical specialisation and value-added trade. • The development of technology-intensive products is encouraged in countries with high embodied energy intensity. • The creation of value added is mainly driven by the direct requirements in export trade. • The construction sector is located in high positions in 35 domestic sectors when measured by the exports of embodied energy. [ABSTRACT FROM AUTHOR]

An indoor corner may provide a relatively comfortable environment for bioaerosol growth and propagation, resulting in an increase in health risks for the resident. This paper presents a feasibility analysis for control of bioaerosol concentration at an indoor corner, defined as the area around ceiling edges, through airflow from ventilation outlet with optimized energy consumption. For the proposed approach, a gas-particle flow model with a chaotic moving vortex is developed to simulate the bioaerosol movement at an indoor corner via the Eulerian-Lagrangian method. In this model, the flowrate of the inlet fresh or air-conditioned air is tuned by a flowrate controller, which is installed at ventilation outlet or inside ventilation duct, in order to control the vortex trajectory. A residual concentration is defined as the ratio of the residual number of densely released particles at the corner to the area of the corner, in order to indicate the probability of bioaerosol movement, which is released sparsely and randomly by a microorganism in a real-world situation. The control strategies are then developed to optimize residual bioaerosol concentration and energy consumption by the orthogonal scheme. Based on the simulation results, a small variation of the airflow rate from the ventilation outlet contributes to reducing the residual concentration of bioaerosols that are originally released from the corner, or to increasing the residual concentration of detergents that are released from the ventilation outlet. It is thus concluded that a Pulse Width Modulation controller, with low amplitude, proper duty factor, period and time delay, is more energy efficient to improve the local indoor air quality. [ABSTRACT FROM AUTHOR]

The role of cities and their stakeholders in creating a sustainable low carbon society is becoming increasingly critical. Cities and their supply chains are responsible for almost 80% of the global energy consumption and over 60% of greenhouse gas emissions (GHG). It is expected that 70% of the global population will be living in urban areas by 2050. However, in general cities still quantify and report only their production-based GHG emissions and fail to account for their supply chains. There has been much less focus on the GHG emissions associated with consumption in cities, including household and government consumption. This paper compares the production-based GHG accounting method with the consumption-based method for ten European cities. This is performed for a base year (2010) and two divergent future scenarios for 2050, a business-as-usual (BAU) scenario and a post carbon (PC 2050) scenario. The PC2050 scenario was created by city stakeholders in the framework of the European research project POCACITO in (2014–2016). Consumption-based emissions are calculated using the EXIOBASE multi-regional input-output model. Compared to 2010, both BAU and PC2050 scenarios show significant decreases for production-based emissions, falling 31% and 68% respectively. However, during this period consumption-based emissions increase for eight cities, rising 33% and 35% respectively. This occurs despite the modelled improvements in global production efficiency for 2050 and the significant production-based reductions under the PC2050 scenarios. The increase in consumption-based emissions is primarily linked to rising GDP and a corresponding increase in spending and consumption, which override the local and global efficiency improvements. Hence the results highlight a notable disparity between the traditional focus on production-based accounting and consumption-based accounting. This suggests that future city actions should extend their focus on addressing the impact of consumption in addition to local energy production and emissions. It also suggests that city stakeholders are generally underestimating the impact of consumption and the responses required. [ABSTRACT FROM AUTHOR]

A distributed energy system (DES) can integrate renewable resources and achieve efficient energy utilization, and it is a common form of energy system for isolated systems. However, a multienergy complementary energy supply scheme makes operating a DES complicated. To ensure the system operates efficiently, it is necessary to study its operation strategy. However, currently, the research on DES operation optimization mostly is in the optimization result itself, hence lacking the transferring of the optimized operation strategy to engineering applications, which is difficult to apply to the actual energy saving operation. Therefore, this paper takes the DES of a scientific research station in Antarctica as an example when it comes to the optimization of its operation strategy, extracting the control logic for engineering applications from the optimized operation strategy. Aiming for the lowest primary energy consumption of the DES across an entire year, a model for optimal operation is presented and formulated as a Mixed Integer Linear Program (MILP), and further solved by the General Algebraic Modeling System (GAMS). The operation strategy of the DES is optimized and the energy saving space is analyzed. Furthermore, through strategy interpretation, the available control logic of the project is extracted from the optimized strategy, and the extraction effect is verified. The results show that the primary energy consumption of the optimized operation strategy can be reduced by 11.8% when compared with the original operation strategy. By using the engineering control logic extracted from the optimized operation strategy to adjust the original operation strategy, the primary energy consumption of the system can be reduced by 9.6%. The current study can provide a scientific and reasonable scheduling strategy for the actual operation of a DES and provide guidance and reference for the optimal operation of an existing DES. [ABSTRACT FROM AUTHOR]

With the increase of energy price and environment problem, the energy consumption of machine tool is attracting more attention. The moving components of machine tools consume a large amount of energy in the operating stage. Structure optimization of moving components is a key strategy for energy saving in machine tools design. Traditionally, structural optimization of machine tools is carried out for reducing energy consumption or improving static and dynamic performance. Given that these factors are important to the structure optimization in machine tools design, this paper presents a structural design optimization method for comprehensively considering energy consumption, static and dynamic performance of machine tool. Firstly, the energy consumption model of the moving components is proposed, and the structural performance indicators of the moving components are analyzed. Then, based on the experiment data obtained by uniform design method, five structure parameters that have great influence on performance indicators are selected as decision variables through sensitivity analysis. To improve the computation efficiency, approximation functional relationship between the five decision variables and the four performance indicators are built through response surface method (RSM). After that, an optimization objective is formulated by combining the four performance indicators through principal component analysis (PCA). Finally, a new hybrid algorithm which integrates Simulated Annealing (SA) and Particle Swarm Optimization (PSO) algorithm is developed to solve the structure optimization problem. Through calculation and analysis, it is found that there is a linear relationship between the moving part mass and energy consumption. The results show that the energy consumption of optimized structure is reduced while ensuring the static and dynamic performance. [ABSTRACT FROM AUTHOR]

Energy efficiency analysis and production efficiency improvement are effective ways to promote the sustainable and stable development of ethylene industries. Therefore, this paper proposes novel data envelopment analysis cross-model integrated interpretative structural model and analytic hierarchy process for energy efficiency evaluation and optimization modeling. The interpretative structural model integrating analytic hierarchy process is used to fuse the multidimensional production data to reduce the dimension and obtain comprehensive evaluation indicators, thus reducing the multidimensional indicators influence on the data envelopment analysis model. Then these several fusion results are used as the input indicators of the improved data envelopment analysis cross-model. And the ethylene yield is used as the output index to build the energy efficiency evaluation and optimization model of ethylene production plants. Finally, according to cross-efficiency values and slack variables, the energy efficiency levels of ethylene plants in each month and year are analyzed. The experimental results show that the distinction of the efficiency values is more obvious and accurate. Moreover, the proposed method can optimize production efficiency and improve the proportion of the efficiency value greater than 0.8 increased by 66.6% of ineffective production plants. Image 10547 • A novel DEACM integrated ISM-AHP method is proposed. • Energy efficiency evaluation and optimization model is obtained. • The distinction of the efficiency values is more obvious and accurate. • The proportion of ineffective production plants is increased by 66.6%. [ABSTRACT FROM AUTHOR]

The burnishing process is an efficient finishing operation which is widely used to enhance the surface properties of the machined components. The published works mainly focused on the parameters optimization of the burnishing process in which objective functions are relative to burnished surface qualities. Because of natural resource exhaustion and the rising energy prices, the reduction in energy consumption is an urgent demand in the manufacturing industry. This paper presented an efficient optimization to simultaneously decrease energy consumption as well as the mean roughness depth and improve the Brinell hardness for the burnished surface of H13 steel. The burnishing speed, feed rate, depth of penetration, and the number of rollers were the input parameters. The burnishing processes were carried out on a CNC milling machine. The mathematical relations between inputs and outputs were developed using the radius basis function models. The multi-objective particle swarm optimization and the technique for order of preference by similarity to ideal solution were used to generate the Pareto fronts and to determine the best solution. The results show that energy consumption and surface roughness are reduced by 39.50% and 7.83%, respectively. The Brinell hardness is improved by 29.61% compared to the initial values. The radial basis function models can be effectively used to render the approximations and to predict the response's values. The proposed method can be considered as a sufficient approach for modeling and optimizing the burnishing process. Image 1 • Optimizing processing conditions for the roller burnishing of H13 steel.. • Considering energy consumed, mean roughness depth, and Brinell hardness. • Development of the correlations using radius basic function (RBF) models. • Evaluating alternative solutions using the multi-performance index (MPI). • Determination of optimal factors using RBF-MOPSO-TOPSIS. [ABSTRACT FROM AUTHOR]

Reduction of waiting time and waste directly improves the quality of supply chain and its sequence. The cost and energy consumption vary thereby resulting in an evolving sustainability. This paper investigates the policy that proves the optimum in reduction of such time and the condition, under which the said policies can be feasible. A mathematical model has been developed to analyse two approaches of the replenishment cycles with respect to the waste management. A closed-structured supply chain model has been considered with a primary and secondary market concepts having overlapped and in sequence manufacturing/remanufacturing policies. Through an analytical model, the minimization of total cost has been achieved. Some solutions of the decision variables are obtained in quasi-closed form. The way to use the used or waste from primary supply chain is found very useful for the secondary supply chain. Numerical study finds that the waiting time for the primary market is reduced by 84.62% and the cost is decreased by 1.38% by adopting the right policy such that the waste is reduced remarkably. [ABSTRACT FROM AUTHOR]

The Beijing-Tianjin-Hebei (BTH) Coordinated Development Strategy marks the beginning of China's endeavor to build a world-class Capital Circle. Facing a slew of challenges, the BTH Region has an urgent need for identifying a green, low-carbon and circular development path and building a clean, low-carbon, safe and efficient modern energy system. The Region's coal-dominated energy consumption style has brought about serious environmental and ecological impacts on itself. Vigorous efforts to develop renewable energy have resulted in an explosive growth of wind and solar power in the BTH region and huge integration challenges to the power networks as well. Sufficient operational flexibility is crucial for promoting the renewable penetration into the power system. However, there is still a lack of effective means to systematically evaluate the flexibility performance. In this paper, we conducted a first-of-kind in-depth renewable integration study for the BTH Region. First, we summarized the challenges of renewable power generation in the BTH region from the perspective of "source-grid-load". Second, we proposed a balanced renewable energy integration analytical framework, which can systematically evaluate the technical and economic performance of various flexible resources. Then we conducted a detailed evaluation of the technical and economic performance of main flexible resources with the analytical framework. Finally, we explored the medium- and long-term flexibility development pathways and proposed policy recommendations for the BTH Region to enhance the flexibility of power system and thereby promote the integration of renewable energy. Based on the proposed development pathways for improving the Region's flexibility of "source-grid-load", the BTH Region is expected to have a significant flexibility to support the accommodation of 125.93 GW of wind power and 44.30 GW of PV power by 2035. • Development challenges of renewable energy in the BTH Region from the perspective of "source-grid-load". • A balanced renewable energy integration analytical framework. • Detailed evaluation of the technical and economic performance of main flexible resources. • Development pathways and policy recommendations for the region to enhance the flexibility of power system. • The BTH Region' flexibility would support the accommodation of 125.93 GW of wind power and 44.30 GW of PV power by 2035. [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]

Improving energy efficiency is important to ensure economic growth while conserving energy and reducing emissions. Based on the total factor energy efficiency of China's textile industry, this paper constructs a simultaneous equation model that includes the Tobit model, and empirically analyzes whether foreign trade affects energy efficiency in the textile industry as well as the mechanism of any such influence. The empirical results demonstrate positive feedback between foreign trade and energy efficiency in the textile industry, with imports impacting energy efficiency more than do exports. The foreign trade of textile industry is divided into import trade and export trade, which have different impacts on energy efficiency. Simultaneously, the results also confirm that R&D input, ownership structure and energy price significantly impact the energy efficiency of China's textile industry. • The foreign trade of textile industry significantly affects its energy efficiency. • The import trade impacts energy efficiency more than does the export trade. • Ownership structure significantly impact energy efficiency of textile industry. • Energy efficiency of textile industry has significant positive effect on foreign trade. [ABSTRACT FROM AUTHOR]

This paper presents an energy efficient optimization method for ecological 3D printing based on Adaptive Multi-Layer Customization (AMC). With the widespread application in end-use fields, the 3D printing (3DP) has already attracted great ecological attentions in energy efficiency, material saving and emissions reduction for better sustainability. Firstly, the energy and material consumption model of 3DP is built by decomposing 3DP into three sub-systems: thermal, mechanical, and auxiliary. The potential impacts on the ecological environment can be further evaluated by correlated degree using covariance analysis. The customized parameters of 3DP such as adaptive layer thickness, infill patterns, infill trajectories are sequentially and deeply investigated to form customization schemes for higher success rate by parameter combination. Considering the implicit non-linear relationships between energy efficiency and the customized parameters, adaptive Generative Adversarial Network (GAN) is built to improve calculation accuracy and prevent premature convergence inspired by Game Theory. To determine the best customization scheme according to the requirements, the mathematical model of AMC is built using multi-objective optimization (MOO). The physical experiment of energy efficiency is implemented by testing energy consumption, temperature, emissions and scanning electron micrograph (SEM). The energy efficiency is improved by maximum ratio of 11.51% and the maximum total carbon emission is reduced by 49.91% for ecological 3DP. The experiment proves that the AMC method can improve energy efficiency of complex functional specimens in highly customized fields such as medical healthcare and astronautics manufacturing industry. • Energy efficiency optimization is proposed for ecological 3D printing (3DP) via adaptive multi-layer customization (AMC). • AMC slices various 3D objects into multi-layer using customized parameters such as infill patterns, trajectories planning. • Represent the relationships between energy efficiency and customized parameters via Generative Adversarial Network (GAN). • Energy efficiency is improved by maximum ratio of 11.51% and total carbon emission is reduced by 49.91% for ecological 3DP. • Physical experiment involves energy consumption, temperature, emissions and scanning electron micrograph (SEM). [ABSTRACT FROM AUTHOR]

Water and energy resource are inextricably linked. Rapid industrialization has led to severe water and energy shortage as well as environmental issues in China. In industrial sector, industrial production and wastewater treatment are two interdependent subsystems. Accordingly, understanding the internal operation performance of the two subsystems as well as assessing their coordination level are of great importance for sustainable water and energy usage. From the perspective of production efficiency, this paper aims to explore industrial water-energy nexus in China by proposing an interactive meta-frontier network DEA approach. The proposed approach is applied to assess the industrial water and energy utilization efficiency in the processes of industrial production and wastewater treatment from 2011 to 2015 in China. The results show that although eastern and central regions have high industrial production efficiency, most regions have relatively low wastewater treatment efficiency. In addition, the nexus degree of eastern region maintains a relatively high level and shows a stable improvement, while the rest two regions perform relatively worse. Comparing the central and western region, the industrial production technology of central region is better yet the wastewater treatment efficiencies of western region are higher, which results in higher nexus degree of western region. Based on the empirical results, policy implications are given in terms of national level, regional level and provincial level, respectively. [ABSTRACT FROM AUTHOR]

Accurately forecasting energy consumption in a building is an important strategy for achieving the goal of reducing energy demand and improving energy efficiency. University campuses represent specific groups of diverse buildings with significant energy consumption. Therefore, they provide an excellent testbed to characterize and understand the energy consumption of a group of mixed-use buildings. This paper presents a novel methodology that considers the recommendations of ISO 50001: 2011 and ISO 50006: 2014 for establishing energy baselines and energy performance indicators in higher education institution buildings to identify electrical energy consumption reduction potentials in buildings and establish energy management strategies related to electricity use. The study was implemented in three buildings at the Federal University of Itajubá (José Rodrigues Seabra Campus). Several methods and indicators were evaluated to monitor and measure energy performance in buildings. A wide range of factors that influence operating system energy consumption in the buildings were studied and taken into account, such as the types of activities carried out in the building, weather conditions, building materials, air conditioning system and occupancy, since these contribute directly and indirectly to the difficulty of accurately measuring the building's energy consumption. The results showed that potential annual savings in electric energy consumption for the campus could be around 9.6%, which translates into a R$ 93,647.2 economic value and a 20.3 tCO 2eq emissions reduction without economic investment. It was concluded that the methodology proposed for establishing and monitoring an energy efficiency indicator can be applied to any institute of higher education because it is flexible and adaptable since each institute can define the period of analysis for the indicator. This research is expected to provide theoretical guidance and a practical data reference for relevant evaluations of building energy efficiency. Image 1 • Energetic characterization of buildings was based on constructive particulars, location and use. • ISO 50001 standard was applied for estimate baseline energy use. • The variables that have a greater influence on the electrical consumption of a building were identified. • Linear regression method applied for the analysis of the variables. • Potential savings in energy consumption and reduction of the carbon footprint were quantified. [ABSTRACT FROM AUTHOR]

To evaluate the energy-saving and emission reduction potential of China's tobacco industry, this paper introduces RAM-DEA models to evaluate the energy and CO 2 emission efficiencies of 18 cigarette companies in China, compared with four of the leading multinational cigarette companies from 2009 to 2016. The results show the following: (1) The average energy and environmental efficiency of Chinese cigarette enterprises is only 0.373, the gap of the comprehensive efficiency between Chinese cigarette manufactures and the technological frontier of the world is big, but it is gradually shrinking. (2) The energy-saving and CO 2 emission reduction potential of Chinese cigarette companies are 57.2% and 68.1%, respectively, and the annual average comprehensive energy-saving and emission reduction quantities are 3.466 million MWH and 1.744 million tons. The energy-saving and emission reduction potential based on a scale efficiency improvement is relatively large. (3) The CO 2 emission efficiency gap of Chinese cigarette companies at domestic and foreign production levels is 25.5%, and it is larger than the energy efficiency gap, 14.1%, due to the high proportion of electric energy consumption. (4) Scale efficiency improvements and energy structure optimization are the main ways to save energy and reduce CO 2 emissions in the future. • New RAM-DEA models for evaluating the energy and emission efficiency are proposed. • Performance between tobacco companies at home and abroad are compared. • Regional differences in the performance of tobacco companies are analyzed. • The influence of production scale on efficiency performance are discussed. • Performance improving policies and strategies for different regions are proposed. [ABSTRACT FROM AUTHOR]

Future developments of energy conversion systems are expected to be based on second and third generation technology. One of the most innovative designs involves the integration of hard coal or lignite gasification technology with a gas turbine (GT) combined cycle, which is known as an Integrated Gasification Combined Cycle. This may constitute an advantageous future energy option, especially for the use of lignite. Gasification also provides one of the most efficient ways to produce clean fuel for the next electrical energy generating fuel cells and cars, as it permits the additional production of syngas with low levels of CO 2 emissions. However, the performance of lignite (brown coal) fired IGCC is degraded by the very high content of moisture in the lignite. The most appropriate approach in order to fully utilise the potential of this type of fuel is the use of a drying system. In the present paper, an Integrated Gasification Combined Cycle for electricity production, coupled with a fuel preparation unit and a coal superheated steam drying system, is analysed. The novelty of the proposed system is its uniqueness in being equipped with a superheated coal drying system, which constitutes a potentially advantageous method of raising the calorific value of lignite and enhancing its use as a fuel. The proposed system permits lignite to become a valuable resource. The combined system is able to generate electricity with a thermal efficiency higher than for conventional systems and it decreases air pollution and fuel consumption. The system consists of seven dependent subsystems: fuel preparation (lignite drying), air separation unit (ASU), coal gasification, gas cleaning system, regeneration system heat recovery steam generator system, steam turbine and gas turbine. The present analysis demonstrates that lignite consists of more than 50 wt % (wet basis) moisture content before the drying process. In the analysed system, the process of drying coal takes place using steam at a pressure 1.2 bar and a temperature of 133.84 °C, which allows brown coal to be dried to 20 wt % (wet basis) of moisture content. The results show that with the coal drying system it is possible to increase significantly the efficiency of the system of the Integrated Gasification Combined Cycle up to 48%–56%, depending on the thermodynamic parameters of the process. The selected thermodynamic parameters are validated and compared with experimental data. • Thermodynamic analysis of the advanced IGCC-CD system with superheated coal drying system. • Advanced combined cycle with additional production of syngas, low CO2 emission & pollution. • Efficient and clean method of raising the value of lignite and enhancing its use as a fuel. • The system exhibits an efficiency of any modern traditional coal-fired power plants. [ABSTRACT FROM AUTHOR]

Environmental regulation is of great concern to international academics and policy makers. Previous studies often regarded environmental regulation as an influencing factor when calculating eco-efficiency or energy efficiency. More attention should be given to the efficiency of environmental regulation, especially in industrial field. According to exiting studies, industrial environmental regulation efficiency (IERE) may be influenced by external environmental factors, to explore the influence and obtain an actual efficiency, this paper calculated IERE in China by using the panel data of 30 regions from 2011 to 2015 (the 12th Five-Year Plan period) through the three-stage data envelopment analysis approach. Firstly, the Undesirable-slacks-based model method was used to calculate the original IERE. Secondly, the economic base, industrial structure, urbanization level, and education level were taken as external environmental variables, and the effect of external environmental factors and stochastic disturbance were excluded. Thirdly, the actual IERE can be calculated after adjusting input values. The results showed that China's IERE was underestimated due to the impact from external environmental factors. Moreover, the IERE was more influenced by pure technical efficiency than scale efficiency. The IERE of each region varied, thus, targeted policies should be formulated according to local conditions. This research provided a new analytical method for calculating environmental regulation efficiency. The method can be applied either in other countries or in other sectors. • The environmental regulation efficiency in the industrial field of China was evaluated. • The three-stage DEA method was utilized, the role of environmental variables could be considered. • Industrial environmental regulation efficiency was more influenced by pure technical efficiency. • Three kinds of efficiencies were all underestimated due to the influence of external environmental factors. [ABSTRACT FROM AUTHOR]

Despite the global context, only 6% of Australia's total energy consumption was derived from renewables, while 86.3% of electricity was generated from fossil fuels. However, this trend has been disrupted by the recent decommissioning and closure of a fleet of ageing coal power plants, along with the country's international commitments to reduce fossil fuel emissions. Currently, Australia is at a crucial stage of its transition to renewable energy adoption. With the purpose of providing an updated depiction of renewable energy, related policy and the way ahead in the Australian context, this research paper presents a systematic review of contemporary literature from the perspectives of energy potential, utilisation and policy incentives. The research analysed a total of 118 documents using an interpretivist epistemological lens; emergent findings offer an evidence-based, lucid account of advancements in the renewable energy market. Polynomial regression analysis is also conducted on secondary data obtained from the literature to predict trends in the electricity generated by different sources of renewable energy. The work also identifies several areas that require attention, including: (1) the most recent time-varying feed-in tariffs (TV FiTs) which offer the innate potential to alter consumer attitudes toward power usage at peak times, thereby improving grid security; (2) the increasingly popular integration of waste-to-energy with other sources of renewable energy emerges as a viable complementary solution to meet energy demands; (3) the increasing utilisation of subsidised geothermal energy installations which are set to rise exponentially in the future; and (4) the use of Public Private Partnerships (PPP) for developing renewable energy generation infrastructure and how this investment may facilitate the national transition to renewable energy adoption. This research contributes to the existing body of knowledge by raising awareness of the current state of renewable energy in Australia, along with proposing pragmatic recommendations for overcoming any challenges posed. As a comprehensive reference, this study provides practitioners and policymakers with thorough, reliable and collated information on Australia's current renewable energy position. [ABSTRACT FROM AUTHOR]

Due to high consumption of energy, its associated concerns such as energy security and demand, wastage of resources, and material-energy recovery are leading to the importance of sustainable energy system development. This is a high time to assess the sustainability in energy systems for meeting the requirements of energy with an enhanced economic, ecological, and social performance from a nation context. The energy system plays a significant role in deciding the economic progress of emerging economies such as India, China, Brazil, and Africa. In this paper, an original attempt has been made to list and evaluate important indicators for sustainability assessment of energy systems development and management in an emerging economy especially India. Firstly, based on the analysis of the extant literature and then followed by expert opinion, potential key sustainability assessment indicators for energy systems development and management were identified. Further, grey based Decision-Making Trial and Evaluation Laboratory technique to understand the causal interactions amongst indicators and segregate them into cause and effect groups, is used. This work can provide useful aids to decision making bodies, sustainability practitioners and business organisations in selective implementation, monitoring and control of sustainable strategies in energy systems development and management and meeting sustainable development goals of clean energy in a nation context. Image 1 • Clean energy is a major challenge for sustainable development. • The energy system contributes to a significant extent to a nation economy. • This work evaluated the indicators for sustainability of energy systems in an emerging economy. • Grey-DEMATEL is applied to understand the causal interactions amongst indicators. • 'Adoption of energy management systems (ISO 50001:2011) and 'Developing system capabilities' are significant indicators. [ABSTRACT FROM AUTHOR]

The main purpose of this paper is to explore the impact of institutional quality on growth-emissions nexus in a panel of three East Asian countries over the period from 1990 to 2016. We also incorporated energy consumption and trade openness as important indicators in the model to avoid variable bias. The results of unit root tests show that the variables are stationary at first difference. The panel cointegration test confirmed that all the variables are cointegrated. We employed Fully Modified Ordinary Least Squares and Dynamic Ordinary Least Squares methods to estimate the long-run effects of explanatory variables on economic growth. The main findings are: (i) a positive significant interaction variable between carbon emission and institutional quality indicates that efficient and impartial domestic institutions are very important to increase economic growth and decrease carbon emissions, simultaneously. (ii) Institutional quality, energy use and trade openness stimulate economic growth. (iii) The VECM granger causality test results show that there is a one-way causality runs from institutional quality to economic growth, carbon emission and energy consumption, from trade openness to carbon emissions in both short-run and long-run, from energy use to trade openness, from energy use to carbon emission in both short-run and long-run. Moreover, feedback effect is present between economic growth and carbon emission, and between economic growth and energy use in both short-run and long-run. It is therefore, necessary to regulate and strengthen the role and effectiveness of local institutions with the aim of lowering carbon emissions in the course of economic development. Image 1 • Impartial and effective domestic institutions are very important to reduce carbon emissions in the course of economic growth. • Energy consumption and trade openness do contribute to enhance economic growth. • Feedback effect is present between economic growth, carbon emissions and energy consumption in both short run and long run. [ABSTRACT FROM AUTHOR]

Manufacturing industry accounts for about one-third of the world's total energy consumption (TEC). This study aims to develop a novel mixed-integer mathematical model to represent the direct energy consumption of machines and indirect energy consumption on a shop floor. In comparison with traditional modeling methods, this paper proposes an effective gene expression programming-based rule mining (GEP-RM) algorithm to generate dispatching rules automatically. This method consists of three attributes that have significant impacts on the TEC of a manufacturing process. In addition, diversified rule mining operators with self-learning are designed to ensure population diversity and convergence. Moreover, a perturbation trigger mechanism for reconstructing rules is introduced to avoid being trapped into a local optimum. An unsupervised learning algorithm is achieved by setting the evolution direction with global best and current worst in order to mine the value of the substantial historical data. Experimental results have shown that the proposed multi-attribute rule mining approach outperforms other dispatching rules in terms of energy saving and production efficiency. [ABSTRACT FROM AUTHOR]

The aim of the present study was to compare the oxygen transfer efficiency in a conventional activated sludge and a membrane bioreactor system. The oxygen transfer was evaluated by means of the oxygen transfer coefficient and α-factor calculation, under different total suspended solids concentration, extracellular polymeric substances, sludge apparent viscosity and size of the flocs. The oxygen transfer coefficient and α-factor showed an exponential decreasing trend with total suspended solid, with a stronger oxygen transfer coefficient dependence in the conventional activated sludge compared to the membrane bioreactor. It was noted that the oxygen transfer coefficient in the conventional activated sludge become comparable to that in membrane bioreactor when the total suspended solid concentration in the conventional activated sludge was higher than 5 g L−1. Operating under high carbon to nitrogen ratio, the oxygen transfer coefficient increased in both conventional activated sludge and membrane bioreactor because of sludge deflocculation and it was noticed a weaker dependence of the oxygen transfer coefficient with total suspended solid. The results indicated that the most important parameters on the oxygen transfer efficiency were in order: the total suspended solid concentration, flocs size, sludge apparent viscosity and extracellular polymeric substances content. Based on the influence of the main biomass features affecting the oxygen transfer coefficient and considering the typical operating conditions in both systems, those of membrane bioreactor appeared to be more favorable to oxygen transfer efficiency. The paper provides a useful insight about some peculiarities of oxygen transfer in a conventional activated sludge and a membrane reactor system, highlighting new and useful information in the light of a more sustainable management of these systems. Image 1 • A comparison between the oxygen transfer in CAS and MBR bench plant was carried out. • (k L a) 20 and α-factor showed exponential trends with TSS for both CAS and MBR. • (k L a) 20 values higher in MBR within a TSS range between 4 gTSS L−1 and 6 gTSS L−1. • Under similar conditions features of sludge in MBR more favorable to oxygen transfer. • TSS, EPS and viscosity should be controlled to optimize aeration efficiency. [ABSTRACT FROM AUTHOR]

Coal direct chemical looping hydrogen generation (CDCLHG) is a promising technology to convert coal into high purity hydrogen. Cradle-to-grave life cycle greenhouse gas (GHG) emissions and primary fossil energy consumption (PFEC) analysis are developed to study the CDCLHG process in this paper. The results show that the total GHG emissions and PFEC of the CDCLHG process are 9.54 kg eq. CO 2 /kg H 2 and 312.02 MJ/kg H 2 , respectively. The CDCLHG stage is the largest GHG emissions stage and the largest PFEC stage. The total GHG emissions of the CDCLHG process is larger than the ash agglomerating fluidized bed (AFB) gasification process, whereas the total PFEC of the CDCLHG process is smaller than the AFB gasification process. In addition, the sensitivity analysis demonstrates that GHG emissions of the CDCLHG stage are sensitive to reducer temperature, reducer pressure and n F e 2 O 3 to n C . • Cradle-to-grave life cycle analysis is carried out to the CDCLHG process. • The total GHG emissions of the CDCLHG process are 9.54 kg eq. CO 2 /kg H 2. • The PFEC of the CDCLHG stage is 283.61 MJ/kg H 2. • The PFEC of the CDCLHG process is smaller than the AFB gasification process. [ABSTRACT FROM AUTHOR]

The energy, economic and environmental performance of remanufacturing process are complex and diverse. In order to improve the comprehensive benefits, a sustainability evaluation method for multi-objective remanufacturing system synthesis based on energy, economy and environment is proposed in this paper. Starting from the remanufacturing process, the prediction model of each evaluation index is established and verified, and the technique for order performance by similarity to ideal solution (TOPSIS) based on entropy weight is used for analysis and calculation. The established quantitative prediction model is of high accuracy and innovative and practical application value. The example analysis shows that this method can be successfully applied to the remanufacturing of lathe spindle, and the optimal remanufacturing scheme with comprehensive energy, economic and environmental benefits is selected. This study is not only conducive to enterprises to obtain greater comprehensive benefits of remanufacturing, but also can provide a reference for the government to formulate more perfect laws and policies. Image 10109 • Evaluation of remanufacturing sustainability considering energy, economic and environmental benefits. • The analysis and calculation models of energy consumption, cost and carbon emissions are established. • Using TOPSIS based on entropy weight to make comprehensive decision, eliminating the interference of human factors. • It is of positive significance for the development of enterprises and the formulation of government policies. [ABSTRACT FROM AUTHOR]

Aimed at enhancing economic prosperity through unimpeded trade, the Belt and Road Initiative (BRI) is controversial as large-scale infrastructure construction may accelerate energy consumption and deteriorate environment of BRI countries. Against this background, from the perspective of energy intensity gap evolution of BRI countries, this paper combines the panel smooth transition model with β -convergence model to investigate the role of China-BRI trade in energy intensity convergence of 59 BRI countries during 1996–2015, including the trade scale effect, technology effect and composite effect, as well as the tempo-spatial differences of energy intensity convergence rates. The empirical results show that, first, in the premise of reducing energy intensity, the scale of China-BRI trade facilitates energy intensity convergence rate by about 13% of BRI countries when exceeding the trade threshold value. Second, the technology effect accelerates the energy intensity convergence rate in the context of reducing energy intensity; in particular, the high-skill and low-medium skill technology spillover effect increase the energy intensity convergence rate by 12% and 15%, respectively. Third, the composite effect appears insignificant on the energy intensity convergence of BRI countries. Finally, BRI countries with larger bilateral trade scale or more shares of technology-intensive imports with China tend to have greater energy intensity convergence rates than other counterparts. • It detects the convergence of energy intensity in BRI countries. • It explores the role of China-BRI trade in the energy intensity convergence. • Scale effect facilitates energy intensity convergence of BRI countries. • Technology effect contributes to increasing energy intensity convergence rate. • Composite effect has no significant impact on energy intensity convergence. [ABSTRACT FROM AUTHOR]

Because China's statistical system differs from other countries, the reported energy data of its transport sector cannot be used for worldwide comparison, representing an obstacle for scientific research and policy making. A practical methodology to evaluate internationally consistent energy data for China's transport sector is presented in this paper. A calibration process was used to combine the results from top-down and bottom-up methods. The results indicate that the total energy consumption related to all transport activities is about one-third higher than the officially reported data. Gasoline and diesel used by non-operating vehicles in the road sector represent the greatest difference. Total energy demand in China's transport sector was 327 million tons of coal equivalent (Mtce) in 2010, 411 Mtce in 2013, and 452 Mtce in 2015. After adjustment, the transport sector accounted for 13% of the total final energy demand in 2010 and 2013, 14% in 2015, and 10% of national CO 2 emissions in 2015. During 2010–2013 and 2013–2015, total energy demand in China's transport sector increased by 84 Mtce and 41 Mtce, respectively, and 88% and 85% of the growth came from the road sector. Without calibration, bottom-up methods often resulted in an overestimation of energy consumption for gasoline and diesel, sometimes exceeding the total national consumption level. The proposed method and estimated results not only support the development of energy consumption and CO 2 emission inventories for China but also lay the foundation for further research on low-carbon strategies for China's transport sector and associated policies. Uncertainties in the estimations and suggestions for improvement are also discussed. • Official data underestimated the energy demand in China's transport sector. • A methodology to evaluate energy data for China's transport sector was introduced. • Energy demand and CO 2 emissions in transport in 2010, 2013 and 2015 were evaluated. • Total energy demand of transport sector was one-third higher than official data. • The reliability of evaluation result was substantially improved by this method. [ABSTRACT FROM AUTHOR]

Buildings account for more than one-third of the global primary energy consumption and are responsible for most of the global greenhouse gas emission. As one of the infrastructures of buildings, energy systems are crucial to control overall energy consumption and associated emissions. Despite much consideration on improving the efficiency of buildings energy system and the utilization of renewable energy, there has been little discussion on the carbon footprint quantification of building distributed energy systems as well as the reduction potentiality. In such a context, this paper proposed a life cycle economic and carbon emissions assessment framework by dividing the building distributed energy system into five stages. Subsequently, a multi-objective mathematical model is developed with minimal life cycle cost and carbon footprint, while respecting energy balance and technical constraints, and the optimal energy system and the carbon footprint distribution are obtained by solving the model. Finally, a case study is conducted on the building energy system design in a district in Xuzhou to test the effectiveness of this method. The correlation between optimal energy system carbon footprint by facility attributes, and the distribution of energy system carbon footprint by stage and source are investigated. It's found that the carbon emissions in the operation and maintenance stage accounts for the largest share in the entire life cycle. In addition, the proportion of carbon emissions from natural gas is the highest, accounting for 65–73% under environmental optimization and 85–88% under economic optimization. Followed by electricity, with a share of 26–34% and 10–14% under environmental and economic optimization, respectively. Finally, a sensitivity analysis is carried out to analyze the impact of energy carbon emission factors. [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]