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This paper investigates the low-carbon product manufacturer's different decision behavior in the offline traditional retail channel and online e-commerce channel when the carbon trading market has been established. The low-carbon product manufacturer is both in the carbon trading market and product market. In the former market, the manufacturer can gain profits by selling its emission quota. In the latter market, the manufacturer has two sales channel options, the traditional offline retailer and the online e-commerce platform. These two channels make two supply chains, the manufacturer-led offline one and the e-commerce platform-led online one. This paper combines the carbon trading market with the product market, formulates different Stackelberg game models, compares the manufacturer's decision under two channels and the impact of channels on the carbon emission, does sensitivity analysis, and verifies the conclusions with numerical examples. Our findings are (1) the establishment of the carbon market will help the manufacturer reduce its carbon emission, especially for those sensitive to the carbon price and those with too much emissions; (2) whether the manufacturer turns to the online channel depends on the consumers' sensitivity to the sales service, and consumers' attention will guide the way to the online mode; (3) which mode is conducive to carbon emission reduction relies on the product type: the e-commerce platform does well for daily necessities of mass production while the traditional channel is better for experience goods. [ABSTRACT FROM AUTHOR]

As a critical component of the energy sector, the high‐temperature gas‐cooled reactor (HTR) system plays an important role on the road to carbon neutrality. As a flagship of the safety analysis codes, the HTR code package (HCP) has been developed to provide a comprehensive modeling and simulation platform of the HTR system under operational and accidental conditions, especially for pebble bed reactors. A variety of individual legacy HTR computer codes were integrated into a consistent code package using flexible and efficient programing techniques and standards, and the know‐how gained over decades in HTR safety studies was preserved. This paper gives a state‐of‐the‐art overview in HTR studies and presents the new flexible curtain‐based control rod system that has been recently implemented. This method involves flexible manipulation of isotope concentrations and utilizes C++ object‐oriented programing principles while incorporating the legacy codes. Comparative analyses with established codes such as Serpent and ATHLET underscore the precision and reliability of the HCP, thereby enhancing its applicability in HTR design and safety evaluations. Finally, the paper outlines prospective avenues for further advancing the HCP, underscoring its evolving role in shaping the future of HTR development and analysis. [ABSTRACT FROM AUTHOR]

With breakthroughs in big data, communication networks, artificial intelligence, and other next-generation information technologies, intelligent production methods and digital lifestyles have risen rapidly. Digital economy has become a significant force in promoting regional low-carbon development as a new economic form in the important period of the intersection of digitalization and "carbon peaking and carbon neutrality goals." This paper empirically explores the moderating role and threshold role of human capital in digital economy and regional carbon productivity by systematically measuring digital economy indicators. Research shows that China's digital economy development index is rising annually. However, the development of digital economy varies significantly between different regions. The results of moderating effect showed that human capital accumulation could dramatically strengthen the role of digital economy in promoting regional carbon productivity. The results of the threshold effect showed that human capital plays an important threshold role in the relationship between digital economy and regional carbon productivity. This paper provides a practical reference for exploring power sources, policy design, and path selection of low-carbon development. [ABSTRACT FROM AUTHOR]

Driven by the carbon peaking and carbon neutrality target, the large-scale grid-connected of renewable energy such as wind and solar has increased, and the volatility and randomness have posed new challenges to the stability of the power grid frequency. In this case, battery energy storage is a grid auxiliary resource with fast response and adjustable parameters, which can provide frequency support for the grid system in a short period. This paper studies the frequency regulation strategy of large-scale battery energy storage in the power grid system from the perspectives of battery energy storage, battery energy storage station, and battery energy storage system, respectively. First of all, the droop control based on logistic function and the virtual inertia control based on piecewise function are proposed for battery energy storage frequency regulation, which improves the performance of battery energy storage power output effectively. Second, the weighting factor is set according to the current battery charge to achieve the most optimal distribution of frequency regulation power for each battery pack in the battery energy storage station. In the end, a control framework for large-scale battery energy storage systems jointly with thermal power units to participate in system frequency regulation is constructed, and the proposed frequency regulation strategy is studied and analyzed in the EPRI-36 node model. The results of the study show that the proposed battery frequency regulation control strategies can quickly respond to system frequency changes at the beginning of grid system frequency fluctuations, which improves the stability of the new power system frequency including battery energy storage. In addition, this paper also provides a certain reference for the construction of the new power system dispatching that integrates "Generation-Grid-Load-Storage" in the future. [ABSTRACT FROM AUTHOR]

In order to establish the optimal price of low-carbon products and set the optimal target carbon emissions in the production cycle so as to maximize profits, this paper proposes the optimal pricing model of environmental quality index futures from the perspective of green finance. This paper mainly studies the optimal pricing and carbon emission strategy of low-carbon products of a single enterprise under the carbon trading system based on the quota system. When enterprises join the carbon trading system, how to optimally determine their target carbon emissions in the production cycle and the optimal price of their low-carbon products in order to maximize their own profits, based on the carbon emission quotas freely allocated by the government in the face of exogenous carbon trading prices and different consumer preferences for low-carbon products in the market, is discussed in detail. The experimental results show that the low marginal cost of emission reduction will urge enterprises to implement low-emission strategies as much as possible, and the marginal cost of a specific size will enable enterprises to implement low-carbon policies with low emissions, and the optimal emissions will decline with the increase of carbon prices. However, from the perspective of 50–300 carbon trading prices, the profits generated are less than those of the minimum emission strategy, and the difference between the two is generally one order of magnitude. Therefore, if the internal conditions permit and the external carbon trading price is reasonable, enterprises should reduce carbon emissions as much as possible. The properties obtained from the model analysis and the numerical conclusions given in the example part reflect the relationship between the enterprise product pricing, the marginal cost of emission reduction, and the target emission decision-making and draw some valuable information for the enterprise and the government decision-making. [ABSTRACT FROM AUTHOR]

China's rural energy consumption structure has dominated by coal, and carbon dioxide emissions are relatively large. Under the dual historical responsibilities of the carbon peak, the carbon neutral dual-carbon, and the rural revitalization strategy, the rural energy transition is imminent. This paper conducts an in-depth study on the green entrepreneurship of migrant workers returning to their hometowns and carefully analyzes the factors affecting the return of migrant workers to green entrepreneurship. This paper establishes a regression model to clarify that the green entrepreneurial guidance mechanism can effectively increase entrepreneurial opportunities, promote the rational allocation of regional resources, increase the success rate of entrepreneurship, and promote the construction of new rural areas in China with proper healthcare. The implementation of the scientific guidance mechanism for migrant workers' green entrepreneurship should adhere to the scientific development concept, correctly guide farmers to return to their hometowns to start businesses, and provide them with a green channel for fiscal taxation. Green entrepreneurship can improve the entrepreneurial ability of migrant workers in order to effectively increase the success rate of migrant workers in entrepreneurship, ensure the rational use of regional resources, and promote the harmonious and stable development of society. [ABSTRACT FROM AUTHOR]

LED is an extremely important energy-saving lighting products, which has greatly facilitated human life. Meanwhile, it also makes a positive contribution to global carbon neutrality and carbon peaking. Defect detection is a vital part of the production process to control the quality of LED chips. The traditional methods use a microscope for manual visual inspection, which is time-consuming and has inconsistent testing standards, low efficiency, and other deficiencies. To solve these problems, a hybrid algorithm based on geometric computation and a convolutional neural network is proposed for LED chip defect detection. The method takes advantage of the dimensionality reduction of geometric computation to perform coarse detection of defects on preprocessed chip lithography graphs in the form of grid segmentation, which realizes fast coarse screening of large-scale chip samples and reduces postcomputational costs. The convolutional neural network model is used for the secondary fine detection of "suspected defective" chips after geometric coarse screening, and the SPP (spatial pyramid pooling) network model is improved by directly introducing the original feature map into the SPP pooling layer for summation to enhance the global and local feature information of the output feature map. Furthermore, we construct an LED chip image acquisition platform using a high-frequency multimagnification zoom lens, collect training samples of defective chips, and increase the number of samples through image processing techniques. The research introduces the R-CNN, SDD, and YOLO methods to evaluate the superiority of our method in a number of experiments. The experimental results show that our algorithm proposed in this paper has an average precision (AP) of 96.7% for large-scale chip detection with a low defect rate. Compared with other methods, the testing mean average precision (mAP) is 10.39% higher than traditional YOLO v2. The testing mIoU is also 3.63% higher than traditional YOLO v5, the detection speed is also significantly improved, and it has good robustness. [ABSTRACT FROM AUTHOR]

Under the "carbon peak and carbon neutrality" goal, the construction of an efficient, low-carbon, and economical energy supply system is of great significance for advancing a dual carbon strategy. In allusion to the integrated energy systems (IES) with hydrogen energy coupling, a hydrogen energy coupling IES low-carbon optimization operation strategy that took account of green certificate and ladder-type carbon joint trading and dual-incentive demand response was proposed in this paper. First, a hydrogen energy multiuse system composed of an electrolyzer, a hydrogen fuel cell, a methane reactor, and hydrogen energy storage was constructed to make full use of the low-carbon cleaning characteristics of hydrogen energy. Besides, a combined model of hydrogen mixed with natural gas was established to improve the utilization efficiency of hydrogen energy. Second, a dual-incentive demand response model including price incentives and subsidy incentives was constructed to fully use the ability to adjust demand-side resources. Next, in view of the carbon emission reduction mechanism of the green certificate, a green certificate and ladder-type carbon joint trading mechanism was constructed. In addition, a green certificate trading mechanism and a reward and punishment tiered carbon trading mechanism had been introduced separately in the IES optimization operation model to reduce carbon emissions of the system. The calculation simulation sets up different scenarios for comparative analysis. As shown by the results, the proposed model could effectively improve renewable energy consumption capacity and energy utilization efficiency. The effectiveness of hydrogen energy utilization, demand respond, and green certification carbon trading mechanism in improving system economy and low-carbon efficiency is verified. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) power generation is the main aspect of new energy power generation, and it is an important means to achieve the goal of carbon neutrality. When the PV system is connected to the grid, the nonlinear load of the grid will affect the power quality and consume reactive power. This paper proposes a PV power generation grid-connected system to improve power quality, with an active power filter (APF) function. Through the maximum power point tracking (MPPT) method, PV power generation can operate at the maximum power point and play the function of harmonic and reactive power compensation at the load side. To improve the dynamic performance of the grid-connected PV system and harmonic compensation simultaneously, multistep finite control set model predictive control (FCS-MPC) is adopted for the grid-connected module. The whole system does not need additional equipment, as it plays the role of two devices and effectively reduces the input cost. In this paper, the proposed structure and multistep FCS-MPC are verified in MATLAB/Simulink. The results show that the system injects the maximum power into the power grid at the same time when the load changes and compensates the harmonic generated by the nonlinear load of the power grid so that the total harmonic distortion of the power grid can meet the operation standard, and the system has good dynamic performance and steady-state performance. [ABSTRACT FROM AUTHOR]

Summary: Integrated energy system (IES) can improve energy efficiency, reasonable configuration of low‐carbon equipment in IES can effectively reduce carbon emissions and achieve carbon peaking and carbon neutrality. Under the background of carbon peaking and carbon neutrality, this paper proposes a configuration method of low‐carbon equipment in IES considering life cycle carbon emissions and ladder‐type carbon trading cost. Firstly, the IES architecture of animation and cartoon industry parks in Sino‐Singapore Tianjin eco‐city is analyzed, and the models of "electrical/heating/cooling" energy supply equipment and integrated energy storage equipment are built. Secondly, the two‐stage operation of power to gas (P2G) is refined, and P2G is subdivided into equipment combination of electrolyzer, methanation reactor, hydrogen fuel cell to study the various benefits of hydrogen energy. Then, the life cycle carbon emission calculation method of renewable energy power generation and P2G equipment is proposed, the life cycle carbon emission model of IES is established, and the ladder‐type carbon trading mechanism is introduced to restrict IES carbon emission. On this basis, aiming at minimizing carbon emission cost, energy purchased cost, equipment investment, operation and maintenance cost, and renewable energy power generation curtailment cost, a joint optimal configuration model of renewable energy power generation and P2G is established in order to realize the low‐carbon economic operation of IES. Finally, through multi‐scenario comparative analysis, the correctness and effectiveness of the optimal configuration method of low‐carbon equipment in IES are verified, and the influence of carbon trading mechanism and refining two‐stage operation of P2G on the optimal configuration results are discussed. [ABSTRACT FROM AUTHOR]

With the rapid development of the economy, carbon neutral and carbon peak are on the agenda in China, and the reform of intelligent construction and assembly building is in full swing in the Chinese construction industry. In order to further explore and study the relationship between the textural structural issues of the envelope structure and the overall energy consumption situation of the house, and further bridge the gap between the actual energy-saving design scheme and the actual application scheme, therefore, this paper takes a certain place as a research object to study the phenomenon of design assembly energy saving, based on dozens of assembly building enterprises researched, selected samples of envelope components studied, selected BIM technology for premodeling optimization, used neural network algorithm for analysis of influencing factors, and studied the application in the study of energy-saving optimization of assembly building envelope in the western Sichuan plain area, and used OpenStudio was used to build a model to simulate the heating and air conditioning load of the assembled building numerically and to fit the quantitative relationship between the variable factors and the building energy consumption. On this basis, the relationship between multifactor and single-factor variables is identified and evaluated using relevant variables means. [ABSTRACT FROM AUTHOR]

The "carbon peak and carbon neutral" emission target has set new requirements for the supply chain structure, exacerbated by the complexity and vulnerability of the agricultural sector and global supply chains after the COVID-19 outbreak. Under these circumstances, the resilience evaluation of the agricultural supply chain based on green transformation became an important subject. Based on this topic with outstanding problems, this paper evaluates the resilience level of the agricultural supply chain in northeast China with the goal of achieving the "double carbon" objective. By focusing on its resilience, we selected Heilongjiang, Jilin, and Liaoning provinces as research subjects and collected the agricultural supply chain-related data from 2010 to 2019. Based on the relationship between supply chain nodes and the operation system, an evaluation model containing three levels was established. The entropy weight method and TOWA operator were used to carry out secondary weighting on the evaluation system and time levels containing 12 indicators, following the evaluation of the resilience level of the agricultural supply chain in three static and dynamic dimensions using the grey correlation method. The results show that the importance of the evaluation level of "internode resilience level" has always been a priority during the decade. Therefore, it is pointed out that the resilience construction and green transformation of the agricultural supply chain should be strengthened and implemented from the following three aspects: strengthening agricultural modernization, optimizing supply chain operation, and the implementation and promotion of effective policies. [ABSTRACT FROM AUTHOR]

In this paper, the factors causing the change in carbon emissions from direct energy consumption in the construction industry in Beijing–Tianjin–Hebei are decomposed using the logarithmic mean divisia index (LMDI) method to analyze the effect values and contribution rates of each macrofactor. Based on the decomposition results and given relevant national policies, five scenarios are set up for each influencing factor, and a regression stochastic impact on population, affluence, and technology (STIRPAT) with ridge regression analysis is applied to each scenario combination for scenario prediction, forming a scientific and reasonable theoretical system to predict the future time of carbon peaking and carbon neutrality in the construction industry of Beijing–Tianjin–Hebei. The results show that (1) energy intensity and energy structure have a suppressive effect on direct energy consumption carbon emissions in the construction industry in Beijing–Tianjin–Hebei, and the industrial structure, economy, and population will promote an increase in carbon emissions. Energy intensity and the economy have a more significant effect on carbon emissions in the construction industry. (2) The peak year of carbon emissions varies with different scenarios, and the energy efficiency scenario achieves peak carbon in 2028, the earliest peak time, and the lowest peak, as it is the optimal emission reduction projection scenario. [ABSTRACT FROM AUTHOR]

Summary: To limit the increase of the global average temperature in the range of 1.5°C to 2°C above pre‐industrial levels, it is mandatory to reduce anthropogenic CO2 emissions. Aggressive mitigation measures are thus needed to tackle these emissions leading to "net negative CO2 emissions." The present study focuses on direct air capture (DAC) processes among the diverse negative emissions approaches. DAC refers to man‐made technologies that selectively extract CO2 from ambient air and deliver it in a concentrated form for further use or storage. DAC technologies are currently developed at different levels of maturity and performance. They can be classified into three main approaches, the liquid sorbent approach, the solid sorbent approach, and a panel of more innovative technologies combining different approaches. They involve various unit operations and different materials and energy types (electrical and thermal). To better evaluate the status and both the environmental and economic performances, the present paper provides a literature review of the life cycle (LCA) and techno‐economic (TEA) assessments in relation to DAC process chains. It was emphasized that DAC could lead to negative emissions if paired with subsequent storage, while the production of synthetic fuels can at best be carbon neutral when using CO2 from the air. Building large DAC plants has an impact on the amount of energy required to operate them, as well as other environmental impacts with regard to land, water, and material use. Even if the carbon‐negative characteristic of DAC was confirmed, these technologies are still expensive. It was highlighted that large DAC costs ranges are currently provided in the literature, from €80/tCO2 to €1133/tCO2 for the current DAC processes, while estimations from €34 to €260/tCO2 are expected in the future. Different levers were identified to improve the environmental and economic performances of DAC processes, such as the availability of waste heat, the heat integration possibilities, and, among others, the improvement of contactors and sorbents properties. Highlights: The paper entitled "Life cycle and techno‐economic assessments of direct air capture processes: An integrated review," submitted by Dr Remi Chauvy and Dr Lionel Dubois, fills the current gap in terms of comprehensive systematic and impacts assessment research on Direct Air Capture (DAC) technologies.Indeed, to better evaluate the status and both the environmental and economic performances of DAC technologies, the present paper provides an up‐to‐date literature review of the life cycle (LCA) and techno‐economic (TEA) assessments in relation with DAC process chains.The paper goes beyond the literature review as key levers, related to technology developments, to the energy use and to the implementation characteristics, are also identified to improve the environmental and economic performances of DAC processes. [ABSTRACT FROM AUTHOR]

This paper carries out the quasi-natural experiment on China's carbon emissions trading pilot policy to assess the impact of China's carbon emissions trading pilot policy on the export product quality of enterprises in the pilot areas by using the data of listed companies and China Customs, and employing the DDD method. Meanwhile, it analyzes the heterogeneity of the impact under different ownership attributes and energy-intensive attributes of enterprises. The empirical results are as follows. First, due to the implementation of the carbon emissions trading pilot policy, the enterprises in the included industries bear the emission reduction cost. The export product quality of the enterprises in the included industries in the pilot areas is negatively affected compared with that of nonincluded enterprises in the nonpilot areas. Second, the impact of the carbon emissions trading pilot policy on the export product quality of enterprises may be heterogeneous due to the different ownership attributes of enterprises. The carbon emissions trading pilot policy significantly reduces the export product quality of non-state-owned enterprises, but has no significant effect on state-owned enterprises. Third, the impact of the carbon emissions trading pilot policy on the export product quality of enterprises is heterogeneous due to different energy-intensive attributes of enterprises. The carbon emissions trading pilot policy significantly reduces the export product quality of enterprises in energy-intensive industries, but it does not have a significant impact on enterprises in non-energy-intensive industries. [ABSTRACT FROM AUTHOR]

Driven by the emission peak and carbon neutrality targets, traditional cruising taxis are also under pressure to reduce emissions, and reducing taxi vacant time is an effective way to reduce emissions. This paper aims to examine the influence mechanism of built environment characteristics on vacant time of taxi trips from the supply-side perspective. To do so, the study uses a one week of taxi trajectory data of 2019 provided by a taxi company in Chongqing, a megacity in China. We take the divided square grid cell as the study units, calculate the taxi vacant time of 168 (7 × 24) hourly slots for each grid, and then calculate the built environment indicators of the grids with Point of Interest (POI) and vector road network data. A generalized additive model (GAM) based on panel data is constructed to investigate the influence mechanism of built environment on taxi vacant time. The results show that the time-varying trend of taxi vacant time is opposite to the time-varying trend of taxi trips and is similar to taxi trips in spatial distribution with significant spatial dependence. Taxi vacant time is negatively correlated with taxi trips. POI mixture, the number of enterprises, governmental agencies, and shopping services are negatively correlated with vacant time, while the number of sports and leisure services, hotel services, healthcare services, financial and insurance services, and living services are positively correlated with vacant time. An interesting finding is that metro stations significantly increase the vacant taxi time in the region. Average traffic flow speed, road density, the number of bus stops, catering services, residence communities, and motor vehicle services show strong nonlinear relationships with taxi vacant time, and their influence effects are alternately positive and negative. The study provides useful insights for understanding mechanisms of the role of built environment on taxi vacant time and has important implications for driver searching strategy improvement, taxi management measures development, spatial and temporal scheduling of taxi capacity resources, and urban transportation facilities layout planning. [ABSTRACT FROM AUTHOR]

Carbon neutral environmental protection is an important way to effectively control the rapid rise of global temperature, promote the green transformation of energy utilization, and promote green, low-carbon, and other technological progress. It is a new driving force for world economic development and growth. This paper explores the construction of wireless sensor model for carbon neutralization and environmental protection from the perspective of the transformation of energy Internet of things. This paper analyzes the development background and research status of energy Internet of things technology at home and abroad and determines the overall design scheme of environmental monitoring Internet of things system. Then, we design the overall scheme of wireless sensor model under the environment monitoring Internet of things system. An experimental test platform was built to test the performance of the environmental monitoring Internet of things system. The test results show that the wireless sensor can monitor and respond to physical impact, and the generated energy can realize wireless data transmission of about 20 m; the regional coverage and fixed-point Internet of things system can realize the real-time monitoring of environmental parameters such as light, temperature, humidity, and dust, interact with the data and instructions of the cloud platform normally, and work stably. The basic functions of the whole Internet of things system have been realized, including the alarm function of passive wireless impact sensing, the cloud real-time monitoring function of environmental data and the real-time sending function of cloud instructions, and the real-time monitoring of indoor and outdoor environment under two working modes. The task objectives set in the early stage of the whole system are realized. [ABSTRACT FROM AUTHOR]

According to China's 14th Five-Year Development Plan, China aims to peak its carbon emissions by 2030 and achieve carbon neutral by 2060, which will be a major strategy for China to implement in the coming period of time. All kinds of industries need to take the industry characteristics into account and gradually form relative carbon reduction targets according to the National Carbon Summit Action Program. Under the constraints of carbon emission reduction, enterprises face trade-off when making emission reduction decisions. How to systematically optimize the profitable and environmentally friendly decisions, under the consideration of carbon emission production, is gradually becoming a main concern of regulated enterprises. In this paper, a Cournot game model is constructed to explore optimal production carbon abatement decisions for two oligopolistic firms, under the governance of a cap-and-trade mechanism. Real case data collected from China's airlines is an example to test the validity of our model. The qualitative analysis shows that, through a reasonable output and emission reduction investment, companies are capable of efficiently minimizing the negative impact brought about by the carbon trading system. A numerical experiment indicates that the companies on one side can reach a decision equilibrium in some circumstances, but on the other side, there exists a lack of incentive to reduce their emissions. Additional government incentives or increased investment in technological improvements will be needed to encourage companies to further reduce carbon emissions. In this paper, while analyzing the choice of emission reduction strategy for enterprises under the carbon trading system, it also provides effective emission reduction approaches for the government and industry managers, hoping to provide some references for the establishment of emission reduction system and policy formulation. [ABSTRACT FROM AUTHOR]

China's rapid economic growth is accompanied by industrial agglomeration (IA) and environmental pollution. Although IA has played an important role in reducing environmental pollution, its effect on carbon emissions is still debatable and deserves further study. In this context, this paper constructs a two-sector general equilibrium model including households and firms to explore the mechanisms of IA on carbon emissions and finds that IA mainly affects carbon emissions through the agglomeration effect and congestion effect. Then, based on the balanced panel data for 30 Chinese provinces from 2003 to 2019, this study employs the dynamic spatial panel model to investigate the nexus between different types of IA and carbon emissions. The empirical results reveal that a significant positive spatial dependence is verified in the regional carbon emissions of China, indicating that carbon emissions exhibit a remarkably spatial spillover effect. Meanwhile, there are significant variations in the influence of different types of IA on carbon emissions. Specifically, specialized agglomeration (SA) positively affects carbon emissions, while the impact of diversified agglomeration (DA) on carbon emissions is negative, implying that China's DA may contribute to carbon emission control. In addition, there is regional heterogeneity in the effect of IA on carbon emissions, with the western region having a significantly greater effect than the eastern and central regions. Therefore, the Chinese government should follow the notion of integrating territory administration and interregional communication and formulate regionally differentiated environmental governance policies to promote carbon emission reduction in the future. [ABSTRACT FROM AUTHOR]

Although government subsidies provide some financial support for firms to invest in low-carbon technologies, carbon price fluctuations bring greater uncertainty risks to firms' investment. The paper constructs a real option model to analyze the timing of low-carbon technology adoption between upstream dominant high energy consuming firms and downstream retailers in case of collaborative decision-making and Stackelberg game, and a numerical simulation is conducted to analyze factors affecting the timing for low-carbon investment. We find that the proportion of cost subsidies, carbon price volatility, carbon emission reduction rate, and cost-sharing ratio will affect firms to choose the optimal investment opportunity. [ABSTRACT FROM AUTHOR]

Carbon emissions reduction in supply chain is an effective method to reduce the greenhouse effect. The paper investigates the impacts of carbon trading price and consumers’ environmental awareness on carbon emissions in supply chain under the cap-and-trade system. Firstly, it analyzes the centralized decision structure and obtains the requirements to coordinate carbon emissions reduction and order quantity in supply chain. Secondly, it proposes the supply chain coordination mechanism with revenue-sharing contract based on quantity discount policy, and the requirements that the contract parameters need to satisfy are also given. Thirdly, assuming the market demand is affected by consumer’s environmental awareness in addition form, the paper proposes the methods to determine the optimal order quantity and the optimal level of carbon emissions through model optimization. Finally, it investigates the impacts of carbon trading price on carbon emissions in supply chain. The results show that clean manufacturer’s optimal per-unit carbon emissions increase as the carbon trading price increases, while nongreen manufacturer’s optimal per-unit carbon emissions decrease as the carbon trading price increases. For the middle emissions manufacturer, the optimal per-unit carbon emissions depend on the relationship between the carbon trading price and the carbon reduction coefficient. [ABSTRACT FROM AUTHOR]

With the increase in tightening of carbon neutral policies, electric new energy vehicles have become a top priority in the development of the automotive industry. The integrated electric vehicle wheel (hub motor) can effectively optimize the vehicle structure and reduce the weight of the vehicle and reduce the energy consumption. At the same time, the feature that four tires can be driven separately is also conducive to the application of various new control algorithms. In this paper, a generalized adaptive PID control is experimented with the speed control of the hub motor, and a fuzzy control-based variable step method is proposed for the overshoot or even runaway problem caused by the inertia of the hub motor in the process of adaptive PID control. Experiments have demonstrated that this method can effectively reduce the amount of overshoot triggered by adaptive control and shorten the regulation time into a steady state. [ABSTRACT FROM AUTHOR]

At a new stage of "carbon peak" and "carbon neutral," we need to strengthen the internal impetus of institutions and policies to promote ecological civilization construction. The initiative implementation of voluntary environmental behavior (VEB) is an effective way for enterprises to achieve high quality sustainable development. The VEB of enterprises include but are not limited to compliance with voluntary environmental regulations (VER). Different from the existing literature on enterprise VER, most of which are just the verification of ISO14001, the study conducts a comprehensive exploratory research on the theoretical framework of what is driving the VEB of Chinese textile enterprises. First, based on grounded theory, the paper coded the hand-collected environmental text information of Chinese listed textile enterprises from 2004 to 2018 and constructed a complete theoretical analysis framework from motivation to performance evaluation of enterprise VEB. Second, PSM method is taken to verify the conceptual model. As a result, we find the following: (1) in addition to ISO14001, the textile enterprises involve many industry-specific VER. (2) The VEB and VER of Chinese textile enterprises promote each other. (3) Either following VER or implementing VEB can effectively increase the innovation input and then actively improve the innovation quality of Chinese textile enterprises. In this way, the conclusion not only provides analysis ideas for future empirical research, but also offers practical suggestions to Chinese textile enterprises and policy makers for environmental management. [ABSTRACT FROM AUTHOR]

The most significant global challenge is global climate change; carbon emission reduction and carbon neutralization are the last way to solve global climate change. Achieving carbon neutrality will significantly impact the global economy and the national economy. The "dual carbon goals" proposed by China will also substantially impact the global economy and regional economic development. Focusing on regional economic development, achieving carbon neutrality is not only an opportunity for regional economic development but also a challenge. To achieve the goal of carbon neutrality, there must be institutional innovation and management innovation, which will provide new opportunities for balanced development among regions. With the development of inclusive finance, financial services for many disadvantaged groups and small and medium-sized enterprises have been further developed, thereby promoting economic development. With the development of Internet finance, big data, cloud computing, and other technologies, the development of inclusive finance, etc., the concept has also emerged. However, due to the short time of digital financial inclusion, the imperfect regulatory system, and the low degree of public participation, it is worth investigating whether the development of digital financial inclusion has a catalytic effect on the improvement of economic growth. Using the data of 31 provinces to build a panel regression model, this paper studies the market development, the development degree of digital financial inclusion, and the impact of digital financial inclusion on the relationship between factor markets and product markets and regions from the perspective of factor markets and product markets. [ABSTRACT FROM AUTHOR]

According to the proposal of Kyoto protocol, carbon dioxide emission rights are traded as a commodity, and carbon emission trading market emerges as the times require. As the world's largest carbon emitter, China has established eight pilot markets for carbon emission trading. Selecting the closing price of eight carbon trading markets from the establishment to June 23, 2020, this paper analyzes the daily, weekly, and monthly return series data, using the first-order autoregressive process to adjust the daily income series to eliminate the weak trading market effect and then comprehensively uses the traditional variance ratio test and multiple variance ratio test to analyze the weak-form market efficiency of the eight carbon trading markets. The empirical results show that most of the carbon trading markets are non-weak-form market efficiency, and only Tianjin, Shanghai, and Hubei markets are weak-form market efficiency under the daily trading data. However, with the increase of carbon holding period, the weak-form market efficiency continues to strengthen. It shows that liquidity, quantity, and information transparency are important factors that affect the market efficiency. [ABSTRACT FROM AUTHOR]

Since China's reform and opening up, the social economy has achieved rapid development, followed by a sharp increase in carbon dioxide (CO2) emissions. Therefore, at the 75th United Nations General Assembly, China proposed to achieve carbon peaking by 2030 and carbon neutrality by 2060. The research work on advance forecasting of CO2 emissions is essential to achieve the above-mentioned carbon peaking and carbon neutrality goals in China. In order to achieve accurate prediction of CO2 emissions, this study establishes a hybrid intelligent algorithm model suitable for CO2 emissions prediction based on China's CO2 emissions and related socioeconomic indicator data from 1971 to 2017. The hyperparameters of Least Squares Support Vector Regression (LSSVR) are optimized by the Adaptive Artificial Bee Colony (AABC) algorithm to build a high-performance hybrid intelligence model. The research results show that the hybrid intelligent algorithm model designed in this paper has stronger robustness and accuracy with relative error almost within ±5% in the advance prediction of CO2 emissions. The modeling scheme proposed in this study can not only provide strong support for the Chinese government and industry departments to formulate policies related to the carbon peaking and carbon neutrality goals, but also can be extended to the research of other socioeconomic-related issues. [ABSTRACT FROM AUTHOR]

This review proposes a performance evaluation system of low-carbon economic development based on multiobjective analysis in low-carbon environment. This is a modeling method combining super efficiency and relaxation-based measurement model (super-SBM model), which can effectively measure green innovation efficiency with unexpected outputs and traditional innovation efficiency without unexpected outputs. Using the Malmquist–Luenberger index method to dynamically analyze the efficiency of green innovation, a multiobjective model is obtained, including economic scheduling target considering wind power cost and low-carbon scheduling target considering carbon trading. The efficiency of green innovation considering unexpected output is obviously lower than that of traditional innovation without considering unexpected output. This phenomenon is more pronounced in some areas of central and western China. Technical efficiency improves the innovation level of environmental protection economy in China and the impact of technological progress is greater than that of technical efficiency. In this review, the output super SBM model is used to study the development of China's low-carbon industry, and the correlation between the prediction model and the performance change of low-carbon economic development is analyzed. The Malmquist–Luenberger (ML) index of environmental protection product development efficiency in China is not less than 1. Due to the improvement of the efficiency of scientific and technological development, the combination of the two will eventually lead to the improvement of the development of green products and environmental economic products in China. Combining with the empirical analysis, this paper puts forward some methods to promote the low-carbon economy in the economic zone. [ABSTRACT FROM AUTHOR]

The Olympic Games is a comprehensive social and cultural activity with the most complicated system and the largest scale. With the development of the Olympic Games, the ecological problems brought by the Olympic Games have attracted increasing attention, and the sustainable development of the Olympic Games has been put on the agenda. Based on the comprehensive index of Ecological Carrying Capacity (ECC), Environmental Kuznets Curve, and carbon footprint analysis of the Olympic Games host city competition cycle, this study analyzes three modes of ECC of the host city: light urban ecological burden mode, heavy urban ecological burden mode, and overload urban ecological burden mode. Based on the temperature sensor and GPS positioning, the land surface temperature change map of Tokyo, Japan, from 1990 to 2015 is obtained, and the heat island effect of Tokyo is obtained. This paper analyzes the case of using sensors for intelligent event management such as venue detection in the sustainable development plan of the 2020 Tokyo Olympics; the idea and practice of thrifty hosting of 2022 Beijing Winter Olympics and 2022 Hangzhou Asian Games holds that in most cases, the ECC of the host city of the Olympic Games is under great pressure, so it is necessary to pay attention to the ECC of the host city. The sustainable development of the Olympic Games is an important issue in the development of the Olympics, but the sustainable development plan of the Olympics is still being explored. It is suggested that the sustainable development of the Olympic Games needs to evaluate the ECC of the host city in the whole cycle, establish the principle of ecological priority to avoid the overload mode of ecological burden, strive to achieve carbon neutrality in the competition, and practice the idea of scientific frugality in running the competition. [ABSTRACT FROM AUTHOR]

Today, cities account for the majority of global energy consumption and CO2 emissions. The interaction between cities is critical for regional low-carbon development. At this time, China has turned to the full opening of the carbon trading market as an important policy tool for achieving its ambitious emission reduction goals. This paper attempts to explore the spatial relationships among cities from the perspective of carbon trading. A "multiscenarios across different spatial scales" analysis framework applied to the allocation and trading of CO2 emission quotas among cities in China is proposed. Based on this framework, the carbon trading networks of 182 cities in China are specifically simulated under four different scenarios, with a comparative analysis of the networks' complexity made from different perspectives. The results of the study are as follows: firstly, significant spatial network correlations exist between the cities' carbon trading under each scenario. Secondly, on a national scale, there are more inner connections in carbon trading networks, with stronger correlations and robustness, while the degree of connection of intercity carbon trading is higher overall on a regional scale. Thirdly, on a national scale, no obvious core nodes exist in the network, while core nodes do exist in the overall network and in each region under the regional scale. Fourthly, cities in the central region have the highest core position overall. Finally, based on the research results, practical guidance in using the framework for achieving carbon reduction, promoting economic growth, and balancing regional development, as well as the important inspiration for policy formulation, is further discussed. [ABSTRACT FROM AUTHOR]

In China, driven by the national "3060" double carbon targets (i.e., reaching peak carbon emissions by 2030 and carbon neutrality by 2060), green housing has become one of the major fields to reduce carbon emissions, facilitating the achievement of the double carbon targets. Promoting the growth of green housing is an important way for the real estate industry to achieve low-carbon transformation and improve the quality of housing. Meanwhile, the construction industry also can benefit from green housing to achieve its energy conservation and emission reduction targets. Therefore, it is critical to boost and maintain the sustainable growth of the green housing market in China. However, the literature has not focused attention on the market behavior of the green housing market in China. This study proposes a tripartite evolutionary game model to investigate the subject behavior of the green housing market in China. This model consists of three major subjects in a green housing market: developers, consumers, and governments. Based on this model, this study analyzes the stability of the strategy options for each stakeholder and identifies the stable conditions of strategy portfolios to reach the equilibrium points of the game system. The validity of the proposed tripartite evolutionary game model is tested through the simulation of the impacts from various factors on system evolution. According to the impacts of factors and the stable conditions of strategies, this paper puts forward relevant policy suggestions for the healthy and sustainable growth of China's green housing market. [ABSTRACT FROM AUTHOR]

Summary: Numerous emerging market organizations have entered the energy market as a result of the gradual expansion in energy market reforms, resulting in fierce competition among them. Meanwhile, the deterioration of environmental contamination and rising energy demands have steadily gained prominence. Therefore, to solve the problems of environmental pollution and conflict of interests among multiple stakeholders in the integrated energy system (IES), this paper proposes a novel collaborative optimization strategy for a low‐carbon economy in the IES based on carbon trading mechanism and Stackelberg game theory. First, a novel multistakeholder low‐carbon transaction mechanism is proposed, which takes into account the initiative and decision‐making capacities in the three‐party stakeholders of energy supply, demand, and storage. Second, a reward and punishment ladder‐type carbon trading mechanism and an integrated demand response strategy based on the price information and carbon compensation are proposed to improve the system economy and environmental benefits. Finally, the mathematical models of each stakeholder are established and are solved by a two‐stage optimization algorithm. The simulation results verify that in a carbon‐constrained environment, all stakeholders can benefit from the proposed transaction mechanism, resulting in an economical and environmentally friendly optimal scheduling of the IES. Novelty Statement: A novel low‐carbon transaction mechanism based on the carbon trading mechanism and the Stackelberg game theory is established.A reward and punishment ladder‐type carbon trading mechanism is introduced.A novel integrated demand response strategy based on the price information and carbon compensation is proposed.A multistakeholder mathematical optimization model is established and solved using a two‐stage algorithm. [ABSTRACT FROM AUTHOR]

Aiming at the problem of insufficient peak shaving capacity of the power system after large-scale renewable energy such as wind power and photovoltaics is connected to the grid, a new energy-pumped storage combined system low-carbon economic operation strategy is proposed. First, the energy storage characteristics of pumped storage are studied; wind power and photovoltaic output are shifted in time and space; and a new energy-pumped storage combined system model with photovoltaics, wind power, and pumped storage as the main body is established. Second, the carbon trading mechanism was introduced, and the reward and punishment ladder carbon trading cost model was established. Then, via the new energy-pumped storage combined system, the upper optimization target with the smallest investment cost and the lower optimization target with the largest system benefit are established, and a two-layer optimization model solution method based on linearly decreasing inertia weight particle swarm optimization and sequential quadratic programming algorithm is proposed. Finally, via the operating data of a pumped storage power station on an island in northern China, the new energy-pumped storage combined system low-carbon economic operation strategy was simulated and verified. The simulation results show that the low-carbon economic operation strategy of the new energy-pumped storage combined system proposed in this paper can effectively suppress load fluctuations, reduce the impact of wind and wind anti-peak regulation characteristics on the power grid, increase the utilization rate of renewable energy, and improve system economy. [ABSTRACT FROM AUTHOR]

The Electricity-Heat-Gas Integrated Energy System (EHG-IES) is important for achieving carbon neutrality. However, the uncertainty of wind power and photovoltaic (PV) output has a large impact on EHG-IES scheduling optimization. In order to solve this problem, a robust scheduling optimization method considering the uncertainty of wind power and PV output and the coupling relationship of each device in EHG-IES is proposed. In the proposed optimization method, the uncertainty of wind power and PV output is described by an additive maximum uncertainty set. Then, the day-ahead scheduling optimization model is proposed based on the coupling relationship of each equipment and electric vehicle (EV) traveling demand. Also, the proposed model is introduced in detail. The simulation is verified by a park calculation example. The economy and accuracy of the proposed method in this paper are verified by comparing the robust optimization results under different uncertainties with stochastic optimization. For robust parameters of 20% and 10%, the economic cost is 1.016% and 1.041% lower than that of the stochastic optimization. Meanwhile, the proposed method can improve the economy of the EHG-IES and realize the economic and safe operation of the EHG-IES under the consideration of EVs and heating storage equipment. [ABSTRACT FROM AUTHOR]

In this paper, we use wireless sensing technology to conduct an in-depth study and analysis of data-driven power energy equipment in the context of carbon neutrality. For the high-order uncertainty of renewable energy power generation and the nonlinearity of the tidal equation, a set of orthogonal bases under arbitrary probability space can be constructed by itself using the high-order information of renewable energy power generation statistics, and then, polynomials fit the state variables such as voltage in the tidal equation using the orthogonal bases and calculate the fitting parameters using the stochastic Gallatin integration method. Based on the analysis of the online monitoring project of the main power equipment in the substation, a substation power equipment condition monitoring system is designed to realize the real-time monitoring of the temperature status of power equipment, substation smoke and temperature, and humidity environment, and the feasibility and advanced of the system are verified by elaborating the analysis. Using wireless transmission to send real-time temperature information to the monitoring background, the infrared thermal imaging online monitoring system is designed around the front-end data acquisition system, transmission network, background data processing, and display module. Saving-investment equilibrium means that total investment equals total savings; government budget balance can be achieved through government savings or deficits. When both supply chain approaches enter into the same environmental competition, the added value that consumers value the product because of the carbon-neutral approach becomes smaller in the coefficient constraint of green effort investment cost due to the competition between the two supply chains, which in turn increases the green investment cost of the supply chain with the green effort carbon-neutral approach, indicating that in the case of competition, consumers, when faced with two products produced by two supply chains, are interested in the product with the carbon-neutral approach has less value-added, and some of the demand is shifted to the product not produced with the carbon-neutral approach. [ABSTRACT FROM AUTHOR]

As the traditional grid produces a large amount of greenhouse gas and cannot adapt to such new demands as dynamic electricity prices, data analysis, and early warning, smart grid with high efficiency and reliability is increasingly valued. It plays a key role in achieving carbon neutrality. Nonetheless, smart grid requires the collection of real-time power data, and personal privacy may be leaked through the frequent electricity measurement reports. With the requirements of data analysis and prediction while preserving users' personal privacy, data aggregation schemes have emerged. However, existing schemes cannot resolve all the troubles well. Some schemes do not consider the failures for smart meters, and most of the schemes have expensive computation cost. In view of this, an efficient privacy-preserving data aggregation scheme with fault tolerance in smart grid is put forward in this paper. To be specific, the proposed scheme is lightweight due to the application of the symmetric homomorphic encryption technology and the elliptic curve cryptography. Even if some smart meters are destroyed, the proposed scheme can still successfully obtain aggregated data. Moreover, the proposed data aggregation scheme is proved to be secure, and all security requirements can be satisfied. Performance evaluation illustrates the relatively low computation cost and communication overhead of the proposed scheme compared to other related schemes. [ABSTRACT FROM AUTHOR]

China has already committed to peaking carbon dioxide emissions by 2030 and achieving carbon neutrality by 2060 (referred to as the 30·60 Target), which has brought both daunting challenges and great opportunities to the automobile industry in China. However, there is still a lack of comprehensive and in-depth studies on the challenges, paths, and strategies for reducing carbon emissions to fulfill the 30·60 Target in automobile industries. Therefore, this paper proposes low-carbon development strategies for China's automobile industry. This study's method is to integrate the results from different literature to summarize the status, challenges, opportunities, and refine the coping strategies for carbon emission of the automobile industry. The results indicated that the paths for achieving the 30·60 Target include joint carbon emission reduction by upstream and downstream enterprises inside the industry. It also needs cross-industry and cross-sector coordinated decarbonization outside the industry. Meanwhile, the low-carbon policy and regulation system should be established to provide a direct driving force and fundamental guarantee for the low-carbon development of China's automobile industry. [ABSTRACT FROM AUTHOR]

With the continuous expansion scale of carbon market and the development of carbon trading mechanism, carbon emission right, as a new financial asset, is being brought into the category of asset allocation by more and more investors. As the burning of coal is the major source of carbon dioxide, China is facing serious ecological and environmental problems, which restrict the development of low-carbon economy. In order to reach the carbon dioxide emission reduction targets and promote the development of green investment market, the carbon market should be a good emission reduction measure. The correlation and dynamic volatility spillover among coal, carbon, and green investing markets are becoming a hot topic for current research. The paper applies both VAR-GARCH-DCC and VAR-GARCH-BEKK models to draw some significant conclusions. (1) The green investment market, coal market, and Shenzhen carbon market show obvious time-varying correlation, and the volatility of the green investment market is higher. (2) There is a bidirectional Granger causality between green investing and coal markets. (3) The investment portfolio and hedging mechanism of the market are established to reduce the risk and help investors obtain higher returns. [ABSTRACT FROM AUTHOR]

With the development of carbon market, the complex dynamic relationship between electricity and carbon market has become the focus of energy research area. In this paper, we applied a new developed multifractal detrended cross-correlation analysis method to investigate the cross-correlation and multifractality between electricity and carbon markets. We analyze the daily return of electricity and carbon prices over a period of 6 years to do the research. The results show that, firstly, we find that there is a strong negative correlation between domestic carbon price and electricity price and a significant cross-correlation between the return series of electricity and carbon markets. Secondly, through multifractal detrended fluctuation analysis, it is proven that there are obvious multifractal characteristics in the return series of electricity and carbon markets, and the results of traditional linear analysis are unreliable. We also find that, based on multifractal detrended cross-correlation analysis, the law cross-correlation between electricity and carbon markets exists significantly. The long-range correlation of small fluctuations and large fluctuations and the fat tail distribution of return series are the reasons for the formation of multifractality. [ABSTRACT FROM AUTHOR]

This paper studies the complexity of the pricing system for the production of low-carbon and nonlow-carbon products in a market composed of duopoly manufacturers under the cap-and-trade policies. Through nonlinear system theory and numerical derivation and simulation, it considers the influence of different market power structures, carbon trading prices, consumer environmental awareness, and other factors on price decisions, carbon emission decisions, profits, and system stability. The influence of price adjustment parameters and unit product carbon emission decision adjustment parameters on the complexity of the pricing system under different market power structures is analyzed. And, it was found that compared with the variable feedback chaos control method, the parameter adjustment chaos control method is more effective in controlling the pricing system in this paper. Our research provides management implications for market competition and operational decision-making for low-carbon and nonlow-carbon products. [ABSTRACT FROM AUTHOR]

Due to excessive greenhouse gas emissions, carbon emission-reducing measures are urgently needed. Important emission-reduction measures mainly include carbon trading and low-carbon cost subsidies. Comprehensive consideration of these two policies is a research hotspot in the field of low-carbon technology investment. Based on this background, this paper considers the impact of consumer low-carbon preferences on market demand and the impact of uncertainty in carbon emission-reduction behaviour. We construct a stochastic differential game model with upstream and downstream enterprises based on cost-sharing coordination under a cost subsidy. From a dynamic perspective, this paper researches the optimal equilibrium strategy and evolution characteristics of the joint emission-reduction mechanism in a supply chain. This paper discusses the sensitivity of the parameters and uses numerical simulation to verify the impact of each parameter on the emission-reduction decision-making activities of stakeholders after introducing the cost subsidy. The results show that a cost subsidy policy can promote carbon emission-reduction investment and supply chain profit. Thus, it is important to strengthen technical cooperation and exchange among enterprises. [ABSTRACT FROM AUTHOR]

To achieve the goal of carbon dioxide emission reduction in 2030 promised to the United Nations, China unified the Carbon Trading System (CTS) in 2017 since carbon dioxide quota allocation is one of the core issues of carbon trading. It is imperative to establish a flexible carbon quota allocation system based on the unbalanced characteristics of resource endowment and economic development in different regions. Unlike previous distribution research, this paper considers five principles, which are fairness principle, efficiency principle, feasibility principle, development principle, and innovation principle. The maximum deviation method is used to research the carbon emission quota allocation in 30 provinces of China, and the results are compared with those under the single principle and the information entropy method. The results reveal that the distribution under the single principle is severely unbalanced, making the region have a strong sense of relative deprivation. The maximum deviation method is better than the information entropy method to achieve carbon intensity by 2030. It is also conducive to promote the coordinated development of the regional economy, narrow the poverty gap, and achieve sustainable development. [ABSTRACT FROM AUTHOR]

This paper investigates how the government can develop subsidies or tax policies to incent power plants to effectively carry out carbon capture to reduce carbon emissions. According to the government's incentive model for carbon capture power plants, the regulation mechanism is developed when government controls carbon emission. When regional or national carbon emission quota is tense, significant effect can be obtained when regulators make regulations to take off low efficiency power plants. In addition, it is verified that the regulators should not blindly pursue a reduction in carbon emissions regardless of the cost. Therefore, regulators need to pay more attention to control the costs of carbon capture equipment and technology. Finally, by parametric and numerical analyses, the conditions of the power plant to maximize corporate surplus are further studied. [ABSTRACT FROM AUTHOR]

In recent years, low-carbon supply chain network design has been the focus of studies as the development of low-carbon economy. The location-routing problem with full truckloads (LRPFT) is investigated in this paper, which extends the existing studies on the LRP to full truckloads problem within the regional many-to-many raw material supply network. A mathematical model with dual objectives of minimizing total cost and environmental effects simultaneously is developed to determine the number and locations of facilities and optimize the flows among different kinds of nodes and routes of trucks as well. A novel multiobjective hybrid approach named NSGA-II-TS is proposed by combining a known multiobjective algorithm, NSGA-II, and a known heuristics, Tabu Search (TS). A chromosome presentation based on natural number and modified partially mapping crossover operator for the LRPFT are designed. Finally, the computational effectiveness of the hybrid approach is validated by the numerical results and a practical case study is applied to demonstrate the tradeoff between total cost and CO2 emission in the LRPFT. [ABSTRACT FROM AUTHOR]

In liquefied natural gas (LNG) power plants, a significant amount of heat and cold energy is consumed to capture and store carbon dioxide (CO2) emitted during the combustion of fossil fuels. The proposed system addresses this problem by utilizing the temperature difference between waste heat and cold energy as a power source to generate electricity. In this study, a novel waste heat and cold energy recovery system for a postcombustion LNG power plant was developed using an organic Rankine cycle (ORC). To design the proposed system, a process model was developed with the following five parts: (i) LNG vaporization, (ii) natural gas combined cycle (NGCC), (iii) amine scrubbing, (iv) CO2 liquefaction, and (v) CO2 injection. In the proposed system, waste LNG cold energy is used for lean amine cooling and CO2 liquefaction. The liquefied CO2 was pressurized to meet the injection pressure requirements. The ORC uses high-temperature exhaust gas from the NGCC as the heat source and high-pressure liquefied CO2 as the heat sink. The economic feasibility of the proposed system was demonstrated by an economic assessment, with the net profit evaluated by a sensitivity analysis considering variations in water, electricity, and equipment costs. Consequently, the proposed system exhibited an 18.6% increase in net power production compared to the conventional system. In addition, the net profit of the proposed system exhibited a 76.7% increase compared to the conventional system, confirming its economic feasibility. [ABSTRACT FROM AUTHOR]

Due to the increasing awareness of global warming and environmental protection, many practitioners and researchers have paid much attention to the low-carbon supply chain management in recent years. Green supplier selection is one of the most critical activities in the low-carbon supply chain management, so it is important to establish the comprehensive criteria and develop a method for green supplier selection in low-carbon supply chain. The paper proposes a fuzz-grey multicriteria decision making approach to deal with these problems. First, the paper establishes 4 main criteria and 22 subcriteria for green supplier selection. Then, a method integrating fuzzy set theory and grey relational analysis is proposed. It uses the membership function of normal distribution to compare each supplier and uses grey relation analysis to calculate the weight of each criterion and improves fuzzy comprehensive evaluation. The proposed method can make the localization of individual green supplier more objectively and more accurately in the same trade. Finally, a case study in the steel industry is presented to demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Green vehicles, such as electric vehicles (EVs), are getting noteworthy popularity among consumers worldwide. The purpose of this paper is to establish EVs as a feasible long-term solution for the future of technology in the vehicle industry, which can decrease the current dependency on fossil fuels and also decrease greenhouse gas (GHG) emissions. As a part of long-term benefits, the adoption of EVs gives environmentally friendly innovation to society. Despite positive environmental implications, the total number of EVs in usage is still inadequate. One of the major causes of this insubstantial adoption of EVs is largely dependent on the perceptions of consumers regarding EVs. However, this particular research study offers an inclusive outline on the existing hurdles for consumer adoption of EVs as well as a framework of the theoretical standpoints that were developed for the adoption behaviour, in addition to considering consumer intentions in the direction of EVs. In this particular study, the researcher found that the literature regarding EV adoption tried to address only the diffusion method of EVs. Whereas this study highlights consumer innovations, which provides a wide insight on consumer emotions to overlook the major aspect in consumer EVs' adoption research. The theme of this particular literature can be implemented in order to better understand the consumers' emotions and behaviour towards the adoption of EVs. The scholars further stated that there is a possible cause for more recent developments within the technological adoption part that can assist to be a standard for upcoming developments. For the last few years, knowledge regarding the problems surrounding the adoption and diffusion of EVs has gained less attention. This study expands this line of research by focusing on making a chance for developing the theoretical frameworks in terms of adding emotions in a psychological perspective where consumer behaviour and ethics are considered. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Energy transformation requires energy producers to pursue energy conservation and emission reduction, control greenhouse gas (GHG) emissions, and produce and supply clean low-carbon energy. Based on the principle of balanced scorecard, this paper selects the data on China Shenhua Energy Company Limited (China Shenhua) of 2015–2019, systematically analyzes the influence of energy transformation on environmental protection effect of energy enterprises, and measures the environmental responsibility level (ERL). The results show that, in the context of energy transformation, Chine Shenhua always attaches great importance to ecoenvironment protection, vigorously develops clean, safe, and efficient energy, implements key tasks like green mine construction and ultra-low emission upgrading, promotes pollution control and ecoenvironment governance, takes measures of energy conservation and emission reduction, and continuously steps up the level of carbon emissions control, thereby steadily improving ecological civilization. [ABSTRACT FROM AUTHOR]

This paper investigates the long-term dynamic cross-correlation evolution between US economic policy uncertainty index (USEPU) and Guangdong carbon emission trading price (GDCP) from the multifractal detrended cross-correlation analysis (MF-DCCA) perspective. With the calculation of correlation statistics and fluctuation function, the beginning procedures of MF-DCCA, we find that the cross-correlation between USEPU and GDCP is significant and presents power law property. Also, with the Hurst exponent, we find that the long-horizon correlations between series are persistent. Moreover, we perform Rényi exponent and spectrum singularity check. The empirical findings reveal that the all the correlations are of multifractality and the correlation of GDCP holds the highest degree. [ABSTRACT FROM AUTHOR]

To achieve the emission reduction target in 2020, China plans to establish a nationwide carbon trading market during 2016–2019. It is therefore an important but difficult task for policymakers to set emission allowances and allocate them among entities. There are three alternative allocation rules, which vary from free of charge to full auctioning. For business managers, the question is whether one of these rules meets the emission cap at the minimum cost. Based on China’s emission-abatement target, this paper examines the optimal investment and analyzes its implementation in different allocation rules. A new model is developed to formulate enterprises’ emission reduction pathways and the cost-minimization problem with the emission cap. The results show that the magnitude of enterprises’ emission reduction is positively related to their innovation potential; neither auctioning nor being free of charge can make enterprise’s individual emission-abatement investment in accordance with the optimal level; enterprise’s individual emission-abatement investment is sensitive to efficiency, budget cap, and environmental benefit. This paper discusses simultaneously their policy implications for China. [ABSTRACT FROM AUTHOR]

Extensive research has been carried out on the "Belt and Road" initiative, most of it focusing on geographical economy and international trade. However, there is a lack of research on the carbon emissions efficiency of the countries along the "Belt and Road," especially regarding the impact of freight trade. To address this research gap, this paper first employs a metafrontier nonradial directional distance function to measure the carbon emission efficiency of 32 countries along the "Belt and Road" from 1990 to 2014. It then examines the role of freight trade. Our main research findings are as follows. Firstly, the carbon emission efficiency of the countries along the "Belt and Road" is generally low. Among them, Russia and Central Asia are mainly due to the large between-group gap in carbon emission efficiency, while Southeast Asia, Western Asia and North Africa, East Asia, South Asia, and Central and Eastern Europe are mainly due to the large within-group gap. Secondly, freight trade promotes carbon emission efficiency, but it will aggravate the gap between the contemporaneous technology and the group technology. Freight trade mainly promotes the contemporaneous carbon emission efficiency (CTCEI) and group-frontier carbon emission efficiency (ITCEI) of low fossil energy dependent countries, and the metafrontier carbon emission efficiency (GTCEI) of high fossil energy dependent countries. Thirdly, foreign direct investment (FDI) has a significant negative effect on a host country's ITCEI and GTCEI, and it will decrease the gap between the group technology and the metafrontier technology. However, freight trade can effectively prevent the entry of FDI, thereby indirectly improving carbon emission efficiency and reducing carbon emission gap. [ABSTRACT FROM AUTHOR]