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Additive manufacturing (AM) can be used to fabricate products with complex shapes that cannot be realized with traditional manufacturing. However, when manufacturing large metal components, AM is constrained by extended production cycles and reduced efficiency, leading to substantial resource usage and environmental impacts. To clarify the environmental impact and sustainability (EIS) of AM systems and improve their resource utilization and economic benefits, an emergy-based approach was proposed. Initially, the scope and boundary of the approach are defined, and the methodology and preparatory steps are detailed. Subsequently, emergy models for sustainability evaluation are established, including factors such as production time, quality, resource use, costs, and economic performance. A comprehensive evaluation is conducted to determine the relevant indices. The results of the evaluation of three distinct AM processes reveal that resource and energy utilization in AM systems contribute approximately 50% of the environmental impact. To mitigate the environmental impact of AM systems and improve their sustainability, reducing the energy consumption of AM systems is indicated as an effective strategy. Our method quantitatively evaluates the EIS of AM, providing a basis for informed decision-making to reduce environmental impact while enhancing production efficiency and economic benefits. • Emergy-based method to assess sustainability of additive manufacturing (AM) proposed. • It provides a unified model for the integration of quality, cost, time, energy, and materials. • It unifies different performance index measures of AM systems. • A comprehensive evaluation of different AM processes was conducted. • It provides an analytical basis for a circular economy. [ABSTRACT FROM AUTHOR]

Compared to the original product, the quality of remanufactured products has higher uncertainty, resulting in lower customer purchase willingness and market acceptance. It has been considered as a bottleneck for the sustainable development of the remanufacturing industry. In response, this study aims to propose strategies that can enhance the quality of remanufactured goods, thereby stimulating consumer demand and fostering the growth of the remanufacturing sector. To achieve this objective, a two-stage model incorporating the original manufacturer, remanufacturer, and retailer was formulated, with a particular emphasis on carbon -neutral objectives. The study explores the impact of the government's dual policy, encompassing cap-and-trade mechanisms and subsidies, on the quality-linked strategies adopted by remanufacturing enterprises. A comparative analysis was conducted to evaluate the effects of different government subsidy approaches, considering scenarios without subsidies, subsidies to consumers, and subsidies to enterprises, all contingent on carbon emissions from enterprises. The findings of our analysis revealed that, under carbon emission limits, an increase in the government subsidy coefficient linked to carbon emissions effectively heightens consumers' willingness to purchase remanufactured products. This, in turn, leads to an improvement in the overall quality of remanufactured goods and an expansion of the remanufacturing industry. Notably, the impact of combining government subsidies with carbon allowance trading varies, with subsidies proving more advantageous for improving the economic and environmental efficiency of the manufacturing process as well as enhancing consumer surplus and social welfare within the industry under specific conditions of subsidy amounts and carbon emissions. The proposed model's validity and reliability were affirmed through arithmetic simulations. In conclusion, this study presents a novel strategy aimed at improving the quality of remanufactured goods, fostering customer purchase intention, and generating a combination of economic, environmental, and social benefits for enterprises. The findings of this research offer valuable insights for the development of low-carbon legislation, serving as a guide for policymakers in the quest for sustainable manufacturing practices. [Display omitted] • Remanufactured product quality, purchase intention, and carbon emission correlate. • Government policies affect remanufacturing enterprises' economic, environmental, and social benefits. • Government's dual policy of cap-and-trade and subsidies affects willingness to pay, product quality, and industry size. • The study provides a reference to formulate low-carbon policies. [ABSTRACT FROM AUTHOR]

Highlights • Performing a comprehensive review and analysis of the energy performance certification. • Developing an operational definition of the energy performance certification. • Illustrating the scope and data of the energy performance certification. • Classifying the energy performance certification. • Analyzing the practicability of the energy performance certification. Abstract The energy performance certification has been recognized as an effective assessment methodology and tool to systematically manage energy consumption and improve energy performance. In the process manufacturing industry and building industry, a large number of energy performance certifications have been applied worldwide with remarkable results achieved in energy saving and emissions mitigation. Mechanical manufacturing industry, which is characterised as a typical discrete manufacturing having a wide distribution in operations with large consumption of energy and low efficiency, has a considerable potential of benefiting from energy saving and emissions mitigation. The objective of this paper is to perform a review and analysis of energy performance certification in the mechanical manufacturing industry for evaluating its potentials and applicability for performance enhancement. We begin with analyzing energy performance certification and research gaps to develop an operational definition of energy performance certification. The scope of energy performance certification and the method for data acquisition are reviewed. Next, we establish the classification of energy performance certification from perspectives of the energy benchmarking, rating and labelling to lay a foundation for its implementation framework and evaluating its practicability. Through the systemic review and analysis, the current state of researching energy performance certification is provided with the methods for developing energy performance certification summarized and analyzed. These findings are useful references for managers to strengthen energy management and monitoring and improve energy performance in the mechanical manufacturing industry. [ABSTRACT FROM AUTHOR]

Highlights • Presenting an emergy-based evaluation and improvement for manufacturing systems. • Constructing an emergy-based sustainable measure model. • Establishing an evaluation index system. • Proposing an improvement benchmarking card for sustainable manufacturing systems. Abstract Sustainable manufacturing, regarded as resource efficient, environment-friendly and customer satisfaction production, is major driving force for sustainable development. With growing demand for decoupling between resources and world economic development, accelerating sustainable manufacturing has become an important strategy. Therefore, a novel method based on emergy theory is proposed to perform the comprehensive evaluation and improvement of manufacturing systems. Firstly, drivers and challenges are analyzed, and the boundary and connotation of manufacturing systems are defined. Then, an emergy-based calculation model of the energy, material, service and waste is presented considering the variety and dimension of the input and output of manufacturing systems. The model expresses the mechanism of the transfer, coupling and conversion of the emergy for manufacturing systems. Besides, some indicator systems are established including functional emergy indicators, structural emergy indicators, eco-efficiency emergy indicators and sustainability indicators of manufacturing systems. The inner link between the economic, environment and social benefits of manufacturing systems is revealed through these indicators. On this basis, an improvement benchmarking card is developed to achieve the excellent quality, high efficiency, energy reduction, resource saving and environmental protection of manufacturing systems. Finally, a case study illustrates the practicability of the proposed method, and results show that the proposed method provides theoretical support for evaluating and improving the sustainability of manufacturing systems to coordinate the resources and development of the manufacturing industry. [ABSTRACT FROM AUTHOR]

How to quantitatively measure the eco-environment loss caused by industrial solid waste (ISW) and how to determine the ecological compensation criterion reasonably have been recognised as a problem of improving the environment performance. To solve this challenge, this study uses emergy theory to calculate emergy loss of ISW with different treatments for quantitatively measuring the eco-environment loss. Then the ecological compensation criterion of ISW is established to compensate for the loss based on sustainability. The pollution tax of ISW is introduced to balance the pollution-control effectiveness and the eco-environment loss, further the government fines for the discarded ISW can be determined. Finally, the case study is performed to analyse and calculate the phosphogypsum emission as the ISW in a city. The results show that the ecological compensation criterion is 37.4 CNY/ton, and its pollution tax should be determined as 44.9 CNY/ton. Therefore, the government fines should be no less than 350.5 CNY/ton for the discard phosphogypsum. Besides, the phosphogypsum pollution tax (30 CNY/ton, National standard) is not satisfied with the pollution of the city's ecologic environment losses. This study gives an effective reference standard for the government decision makers in pollution tax of the industrial waste. [ABSTRACT FROM AUTHOR]

The remanufacturing machining has been recognized as an effective technology that helps improving the energy and materials utilization, and resulting environmental emissions and production costs decrease. Due to the intense lack of sustainability evaluation, therefore, this paper presents a novel emergy based evaluation method considering these objects in the remanufacturing machining systems. On basis of analyzing the remanufacturing machining and sustainability, this method comprises data collection, emergy based sustainability evaluation model and development of sustainable evaluation indexes and systems. Meanwhile, this method translates the quality loss function, time loss function, and cost into emergy by the Emdollar value, and calculates the emergy value of the environmental losses caused by the energy and resources used in remanufacturing machining process and its waste. Finally, the results of the remanufacturing crankshaft machining show that the remanufacturing machining system possesses high production efficiency and return with heavy environmental load state, and the sustainability index is less than 0.05. There is considerable potential for utilizing the energy and alloy powders of the remanufacturing technologies. This study contributes to studying sustainability modeling of remanufacturing to evaluate machining process and to optimize remanufacturers and manufacturers. [ABSTRACT FROM AUTHOR]

The online quality control for reassembly (remanufacturing assembly) process is one of the key technologies to ensure the quality of reassembly influenced by uncertain, nonlinear and dynamic environment. According to the characteristics of reassembly process, this paper constructs the state space model which takes assembly operation and part attributes as the input vector, work-in-process as the state vector, and assembly quality as the output vector. Then, a transfer function for assembly quality is established, which is used to characterize the coupling mechanism of assembly error. Furthermore, considering the uncertainty of remanufactured parts, the modified operation index for reassembly workstation is calculated. On the basis of the studies above, the online quality control method of reassembly is put forward by the grading method. Finally, the online quality control method for the axial clearance and gyroscopic moment of remanufactured crankshaft is studied. The results of the case study indicate that the methods can improve the reassembly precision. [ABSTRACT FROM AUTHOR]

To improve the ecological efficiency (eco-efficiency) of industrial production and promote its sustainable development, we present a data-driven method for evaluating and optimizing the eco-efficiency of industrial production system. The data of industrial production system are collected and processed in a unified dimension from the perspective of emergy, then the eco-efficiency evaluation model of industrial production system is constructed to realize the quantitative evaluation, the correlation between various factors and eco-efficiency is analysed, and a date driven eco-efficiency optimization decision is built to improve eco-efficiency and production benefits in industrial production. In the application to an example in a manufacturing enterprise, the method identifies opportunity for reducing resource consumption by 8.3% and waste discharge by 6.7%, enhancing the eco-efficiency by 13.8% and production benefit by 8.1%. This paper provides theoretical and methodological support for the evaluation and optimization of eco-efficiency of industrial production system, and also provides theoretical basis for the sustainable development of industrial production. • Ecological efficiency of industrial production considering the economic, social and environmental benefits. • Constructing a data-driven eco-efficiency model of industrial production system. • Analysing various factors related to the eco-efficiency. • Illustrating the measurable, evaluable and optimized eco-efficiency mechanism of industrial production system. [ABSTRACT FROM AUTHOR]

Optimized control of remanufacturing assembly process in a dynamic and uncertain environment has been recognised as a big challenge for remanufacturer. Therefore, an integrated optimization control method for reassembly system is proposed. The state space model of the remanufacturing assembly process and the transfer matrix of reassembly are constructed to characterize the transfer mechanism of reassembly process. Then, an optimization control model based on dynamic programming is established to realize online guidance of reassembly station. Finally, the method is applied in reassembly line of crankshaft remanufacturing, and the feasibility and effectiveness are verified. The results show that this method can effectively improve the quality of remanufactured products by 5.27%, and reduce the cost of reassembly system by 2.76%. Moreover, the method provides theoretical and methodological support for the core competitiveness of remanufacturing enterprises. [ABSTRACT FROM AUTHOR]

Outsourcing has become an effective production and management measure to increase the resource utilization and production efficiency. However, performing a sustainability evaluation of the outsourcing faces some difficulties in constructing a unified dimensional evaluation model for integration of the quality, time, logistics cost and resources consumption. This paper proposes an emergy-based sustainability evaluation method for the outsourcing machining resources for improving resource utilization efficiency. Firstly, the scope and boundary are defined, and the processes of the method and preparation are illustrated. Then, emergy models for the sustainability evaluation that comprise production quality emergy, production time emergy, production logistics cost emergy and production resources consumption emergy models are established. An integrated assessment is performed to acquire a best plan of outsourcing machining, and the corresponding evaluation indicators can be determined. Finally, a case illustrates the practicability of the proposed method laying a foundation for sustainability evaluation and selection of the outsourcing machining resources. • Proposing a sustainability evaluation method for outsourcing machining resources. • Considering the quality, time, logistics cost and resources in outsourcing machining. • Establishing a unified dimensional emergy model. • Presenting an integrated assessment method. • Illustrating the practicability of the proposed method in real application. [ABSTRACT FROM AUTHOR]

• BN-QCG is developed to model the cause–effect relationship between process variables. • Information entropy is introduced to quantify the uncertainty of diagnostic systems. • ISFLA is proposed to deal with the multi-objective optimization problem. This paper presents a sensor deployment strategy based on a Bayesian network (BN) and information entropy to diagnose multi-station assembly processes. A station-indexed state space model is employed to analyze the influence of fixture faults and part reorientation faults on the process fault. Based on the matrix transformation of the state space model, the inherent rules of process fault propagation in various stations are revealed and the system detectability is quantified by the process fault-detectability index. Subsequently, a BN-based quantified causal graph is developed to model the causal relationship between process faults and sensor measurements, and information entropy is introduced to quantify the uncertainty of process fault diagnosis. Finally, sensor–fault matching algorithms are proposed to minimize information entropy of unit cost and process fault unobservability, under the constraints of detectability, thus achieving optimum sensor placement. An example involving assembly of automobile differential illustrates the methodology. [ABSTRACT FROM AUTHOR]

The service stability of industrial robots (IRs) is considered the basis for ensuring intelligent manufacturing operations. Knowledge-based work plays a central role in the practical application of intelligent manufacturing because the staff have professional knowledge of production and manufacturing after learning, undergoing training, and thinking. They can use their knowledge to analyze complex states, assess them accurately, and make innovative decisions. Therefore, expressing and constructing IR data and knowledge is a key issue in the application of knowledge to the predictive maintenance (PdM) of IRs. Considering the intelligent management of IRs as the research objective of this study, a PdM method based on data and knowledge was developed. A running-state feature-recognition model based on a long short-term memory network was first established to recognize future running states using the history and real-time running data of IRs. Furthermore, the k-nearest neighbor algorithm was used to analyze the correlation between the running-state feature data and faults to predict possible faults. The prediction results were then input into the knowledge graphs (KGs) of IRs for reasoning. PdM strategies were automatically formulated based on the KGs. Finally, a PdM system for IRs was designed and developed. The effectiveness of the proposed method and system were verified by applying them to the welding robots in a new energy automotive welding workshop. The findings of this study provide new concepts and tools for the PdM of IRs, as well as theoretical and methodological support for the production stability of intelligent manufacturing. 1 1 Industrial robot (IR), predictive maintenance (PdM), knowledge graph (KG), industrial Internet of Things (IIoT), intelligent manufacturing (IM), intelligent manufacturing systems (IMS), k-nearest neighbor (KNN), long short-term memory (LSTM), process control (OPC), programmable logic controller (PLC), factory automation system (FAS), manufacturing execution system (MES), recipe cluster management system (RCMS), recurrent neural network (RNN), support vector machine (SVM), knowledge ontology (KO), physical production system (PPS), physical modeling modules (PMM), application management modules (AMM), system management module (SMM), fault information management (FIM), knowledge graph management (KGM), maintenance plan management (MPM), information push management (IPM), statistical analysis management (SAM), user interface (UI). [ABSTRACT FROM AUTHOR]

Abstract The energy-saving and emission reduction (ESER) strategy is a crucial measure for promoting the sustainability of manufacturing industry in green transition. Analyzing current practices and limitations of the ESER in the manufacturing industry, this paper proposes a new concept entitled lean energy-saving and emission-reduction (LESER) and an approach to effectively improve the energy efficiency and reduce waste emissions. This paper illustrates the definition of the LESER and establishes an implementation framework for LESER to improve the manufacturing process. To quantify and evaluate performance of LESER, the state space model of the carbon footprint for energy consumption and waste discharge is established. A method for implementing the LESER strategy is constructed in the following steps: (i) clarification of the current situation; (ii) analysis of the root cause; (iii) improvement; (iv) evaluation of the carbon emissions; (v) sustaining and standardizing. Finally, the LESER strategy is applied to the Zcrubber Group Co. Ltd., which is characterized with high pollution, high energy consumption, and high emission in green transition. Results demonstrate practicability of the proposed strategy to offer an effective measure for promoting sustainability of manufacturing industry. Graphical abstract Unlabelled Image Highlights • Proposing the LESER for promoting sustainability of manufacturing industry • Illustrating the concept and connotation of the LESER • Describing the carbon footprint for manufacturing process by state space model • Presenting the implementation processes of the LESER [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) has been a vital element of smart manufacturing. The high energy intensity or environmental sustainability issue of AM, however, has posed a great challenge to the future massive application, particularly laser-based direct energy deposition (L-DED). This study aims to determine the optimal processing parameters for energy-saving without compromising the geometrical appearance. A quantification model for energy efficiency at the process level was established, with two energy efficiency indicators of AM process. Then, a meta-heuristic Mayfly algorithm, augmented with Bayesian technique and mutation strategies, was proposed to improve hyperparameters in a typical machine learning model (XGBoost). Based on the full factorial L-DED experiments, this study compared the improved XGBoost with four types of XGBoost derivatives via four algorithm evaluation metrics. Non-dominated sorting genetic algorithm II was adopted to optimize the processing parameters subject to the constraints of geometrical appearance. Results indicated that the proposed algorithm outperformed other XGBoost derivatives in terms of prediction accuracy and convergence rate. The energy efficiency could be improved by 76.35 J/g or 6.78 % on average while ensuring the geometry of the deposited layers. This study could help enhance energy-efficient additive manufacturing via proper processing parameters selection and facilitate the sustainability in AM domain. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) has significant advantages, including design freedom, mass customization, and complex-structure manufacturing capabilities. As reducing the manufacturing energy is challenging in terms of the industrial sustainability, the AM energy consumption must be further explored. Existing energy consumption quantitation methods for AM require complex models that considering the energy characteristics of equipment. Therefore, we propose a feature-based energy consumption quantitation method for complex AM parts using simple models and suitable for different AM technologies. First, a feature segmentation method is proposed to divide complex AM parts into typical AM features. Then, the energy consumption model for each AMF is developed for energy consumption quantification during part fabrication. Finally, the energy consumption of a typical mechanical part manufactured via three different AM processes is investigated using the proposed method and measured experimentally. The results show that the proposed method can effectively and rapidly predict the energy consumption of AM processes with an accuracy of more than 95 %. Furthermore, the efficiency of the three AM processes is compared and discussed to address suitable efficiency improvement methods. In general, the proposed method can be integrated into three-dimensional AM models, providing a reference for the structural optimization of AM parts and sustainable manufacturing. • A feature-based energy consumption method for complex AM parts is proposed • The proposed method uses simple models and is suitable for various AM technologies • Feature dissection is employed to divide AM parts into typical AM features • The proposed method predicts energy consumed in AM parts effectively and accurately [ABSTRACT FROM AUTHOR]

Energy modeling and visualization of machining have been recognized as effective and powerful ways to explore energy-saving potential and to improve energy efficiency. However, energy modeling and visualization of the drilling process have not been investigated adequately. To address this challenge, sub-power models-based energy modeling and multi-angle energy visualization analysis methods of drilling process were proposed in this study. More specifically, three tasks were carried out: (1) detailed sub-power models of drilling were established; (2) sub-power models-based energy modeling method of drilling was proposed; (3) based on the detailed sub-power models and energy data, multi-angle energy visualization analysis was conducted. Application of the proposed drilling energy model in common drilling processes indicated that its average prediction accuracy of the proposed drilling energy model was 96.2%. The results also showed that 7417.8 J energy saving and 12.6% energy efficiency improvement were achieved with the visualization analysis. The proposed method contributed to energy-saving activities for the drilling process, including providing high accuracy energy model, analyzing energy saving potential and improving energy efficiency. We believe that the outcomes of this research can help engineers and managers to better understand and manage the energy characteristics of drilling. • Proposing a new, sub-power-based energy modeling method of drilling. • Average prediction accuracy of drilling energy is improved to 96.2%. • A novel multi-angle energy visualization analysis method is proposed. • 7417.8 J energy saving potential is identified by energy visualization analyzing. • Energy efficiency is improved by 12.6% through implementing the proposed method. [ABSTRACT FROM AUTHOR]

• Presents a data-driven measurement, evaluation, and identification method. • Uses a coupling coordination degree model for three regional agriculture subsystems. • Suggests ways to reduce costs, increase social support, and enhance competitiveness. This study aims to evaluate the relationship between the agriculture economy environment, and society from the perspective of system theory and then put forward targeted suggestions for sustainable development of Anhui's agriculture in China. Based on the collection of relevant data and the objective weighting of indicators, the entropy weight method is used to measure the comprehensive development level of regional agriculture. The coupling coordination degree model is employed to evaluate the coupling coordination level among the three subsystems of regional agriculture. The obstacle degree model is used to identify the key obstacle factors. The case study results show that the main obstacles of the coordination system are the use of pesticides, the number of agricultural scientific and technological achievements, the application of agricultural plastic film, the number of farmers' technical training schools, and the proportion of animal husbandry. Accordingly, the paper posits suggestions, such as reducing the input of pesticides and agricultural plastic films in agricultural production, improving the social support level of agricultural science, technology, and education, and enhancing the competitiveness of animal husbandry in the Anhui Province. This study provides theoretical and methodological support for the coupled and coordinated development of regional agricultural economy, ecology and society(EES). [ABSTRACT FROM AUTHOR]

Remanufacturing is becoming a strategic emerging industry in China. However, there are many uncertain factors such as remanufacturing rate of recycling products, reprocessing costs, quantity of recycling products during a remanufacturing process. Hence, it is difficult to make an accurate production planning. This paper aims at studying a new remanufacturing production planning model in view of some possible uncertain factors in a remanufacturing enterprise according to the features and characteristics of remanufacturing. Considering the production capacity constraint of recycling, reprocessing and reassembly under the condition of uncertain reprocessing amount, unpredictable reprocessing cost, unknown purchase volume of new parts, and uncertain customer demand, this paper develops a two-stage, multi-period hybrid programming model with compensation function based on uncertainty theory to minimize the total remanufacturing cost. A hybrid intelligent algorithm is designed combined with compensation function approximation, neural network training, and virus particle algorithm to optimize this two-stage uncertain remanufacturing production planning. By use of compensation function approximation method, it is to convert an infinite optimization problem in this algorithm into that of a finite one. Finally, one remanufacturing simulation case is studied to validate the efficiency and rationality of the proposed approach. [ABSTRACT FROM AUTHOR]

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

Due to environmental and social issues caused by unauthorized processing of recyclables, waste merchants, key informal collectors with the door-step collection in China have been integrated into formal collectors. However, how to achieve effective integration is still underexamined. This study puts forward two strategies for integrating a waste merchant from a formal collector's perspective, namely, contract strategy (CS) and recruitment strategy (RS). A leader-follower game model is developed to explore and compare the suggested integration strategies considering the minimum profit constraint of a waste merchant. On this basis, the feasible boundary for the selection of a reasonable strategy by the formal collector is identified. The results show that the formal collector remains reluctant to integrate the waste merchant through RS or CS if the created value by the recyclables is low. The likelihood of selecting RS increases with the higher reclaimed value. Reduced hassle costs for residents can expand the boundary of selection for RS. Besides, it is observed that CS has a greater chance when the ratio of the collection cost coefficient under RS to CS increases. In particular situations, the formal collector may gain a higher profit using RS, although it may not definitely result in higher collection quantity compared to the situations where CS is applied. Overall, this study provides insights for formal collectors for the selection of an effective integration strategy. • A game model is developed to integrate a waste merchant into a formal collector. • Recruitment and contract integration strategies are compared for a formal collector. • Optimized profit and recycling quantity differ between two strategies. • Collection cost differences and residents' hassle cost reduction have an impact. [ABSTRACT FROM AUTHOR]

The shortage of resources and environmental pollution have become the social issues of world concern, they have seriously affected the sustainable development. Remanufacturing has been recognized as an effective technology helps to improve the energy and materials utilization, and reduce environmental emissions with a low cost. we performed a comprehensive literature review of assessing energy, environment, and economy in remanufacturing based on life cycle assessment method to summarize the development of remanufacturing technologies, conclude new progress of remanufacturing in energy, environment and economy and review the remanufacturing trend. Firstly, we reviewed the life cycle assessment (LCA) method and its application in remanufacturing assessment. Some remanufacturing assessment methods based on LCA were analyzed here. Secondly, a framework of assessing energy, environment, and economy in remanufacturing based on LCA was built. Corresponding assessment methods in remanufacturing were studied and summarized in dimensions of energy, environment and economy respectively. Then following the integrated studies of energy-environment-economic assessment in remanufacturing was also described. In this paper, the remanufacturing and assessment about energy, environment, economy based on LCA were described systematically, so as to better understand and apply LCA and promote remanufacturing. Finally, the limitations of the LCA method were discussed, furthermore, in order to catch up with the trend of the manufacturing industry, the integration of remanufacturing and emerging technologies was proposed at the end of the paper, which will be conducive to the continuous innovation of remanufacturing. • Reviewing the life cycle assessment method and its application in remanufacturing assessment. • Illustrating energy, environment and economic assessment methods in remanufacturing. • Performing integrated studies of energy-environment-economic assessment in remanufacturing. • Discussing the emerging technologies or methods of remanufacturing from the energy, environment and economic perspectives. [ABSTRACT FROM AUTHOR]

• Analyzing driving forces of China's CO2 emissions from energy consumption based on Kaya-LMDI methods. • Economic activity being the greatest driving force for CO 2 emissions growth of China. • Reducing the proportion of coal consumption mainly through vigorous development of natural gas currently. • Electricity trading can serve as a valid temporary means for reducing CO 2 emissions. Anthropogenic carbon emission gives rise to a situation where global warming is becoming serious. China is paying for reducing carbon emissions. The concept of carbon curse suggests that countries rich in fossil fuels tend to be closely linked to high carbon emissions, but this is not absolute, which reminds policymakers that the policies implemented are positively correlates with carbon emission reduction. This study is also aimed at this, hoping to provide some proposals about reducing CO 2 emissions to policy-makers by decomposing and analyzing the important factors. To achieve this target, this paper employs the extended the Kaya identity, combines the LMDI method to analyze the impact factors of carbon emissions in China from 1996 to 2016 and discusses the effects and causes of each factor according to the actual situation. It is found that the economic activity is the greatest driving force to promote carbon emissions, while on the contrary, energy intensity is the biggest suppressor. Optimizing industrial structure, improving the structure of energy and export-import trade and intensifying the development of clean energy can effectively restrain the growth of carbon emissions. In addition, the relative innovation point in this study is to analyze carbon emissions with the combination of electricity trading and discusses that increasing imported electricity is also a strategy to reduce carbon emissions. [ABSTRACT FROM AUTHOR]