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By purchasing emission reduction equipment or reducing production scale, it is possible to effectively decrease CO 2. Therefore, understanding the marginal abatement cost (MAC) associated with these methods is crucial for making decisions. However, previous studies using the directional distance function (DDF) approach often mis-specified production functions and neglected data noise. They also assumed decision-making units (DMUs) to be on the production frontier and used proportional changes in inputs and outputs as abatement paths. This paper addresses these limitations by developing the convex quantile non-radial directional distance function (CQR-NDDF) method, which estimates the MAC of CO 2 and determines optimal abatement paths for DMUs without assuming a specific production function, employing linear programming techniques. Applying this method to 30 provinces in mainland China from 2011 to 2019, the study finds that China's CO 2 MAC increased from 182 to 247 yuan/ton. The lowest-cost abatement path varies by province and time. The club convergence and ordered probit model are employed to conclude that the second industry and urbanization increase the MAC of CO 2 , while factors such as foreign direct investment, openness level, and human capital decrease the MAC. Moreover, the CQR-NDDF method yields significantly lower MAC estimates than the NDDF method. In conclusion, this paper provides new insights into China's CO 2 MAC, emphasizing the importance of considering inefficiency and data noise in MAC estimation. We anticipate that utilizing CO 2 MAC as a benchmark for carbon trading market prices could lead to an increase in prices within China's carbon trading market. • A novel method for estimating CO 2 MAC has been developed. • Ignoring inefficiency will result in an overestimation of CO 2 MAC. • Three different emission reduction pathways are considered in the estimation. • The heterogeneity of the lowest cost abatement pathways has been identified. [ABSTRACT FROM AUTHOR]

The core of the energy transformation under the carbon-neutral vision is the gradual replacement of high-carbon energy by zero-carbon and low-carbon energy. However, the large-scale deployment of clean energy technology in turn relies on key minerals such as copper, aluminum, zinc, and nickel. Based on this, this paper conducts research on the demand for key minerals in clean energy transition and the role of key minerals in clean energy transition. In particular, this paper calculated the demand for mineral supply for China's carbon neutrality target, and the impact of some mineral resource constraints on the carbon neutrality path. Relevant results can provide a decision-making basis for the future development and utilization of key mineral resources, as well as the implementation of future carbon-neutral goals. • We evaluate the impact of crucial mineral resource on the carbon neutrality path. • Copper's availability greatly affects the adoption of new energy technologies. • Limited resources hinder early carbon capture and storage development. • Negative emission technologies are necessary for China's carbon neutrality. [ABSTRACT FROM AUTHOR]

To attain China's target of carbon neutrality by 2060, the implementation of the Energy Consumption Trading (ECT) system serves as an effective approach to improve energy efficiency and mitigate CO 2 emissions. Nevertheless, it is crucial to consider not only the importance of carbon reduction effect caused by ECT system but also the associated cost. Therefore, this paper applies the spatial difference-in-differences (SDID) model to assess the direct and spillover impacts of the ECT policy on the carbon abatement cost, which is measured by shadow price of CO 2 emissions and calculated using SBM-DEA model. Panel data encompassing 279 Chinese cities from 2010 to 2019 are employed for analysis, with additional insights provided through heterogeneity and mechanism analyses. The results show that ECT policy increases the local carbon abatement cost in pilot cities but decreases the cost of surrounding cities. Meanwhile, such a declination effect in neighboring cities with a spatial attenuation boundary of 1000 km. The heterogeneity analysis suggests that the implementation of ECT policy leads to an increase in the carbon abatement cost in cities located in non-Eastern Coastal regions, cities with abundant natural resources and cities with small populations. The mechanism analysis indicates that the ECT policy implementation facilitates the improvement of green technology in the neighboring cities of the pilot project, consequently lowering the carbon abatement cost. Besides, this policy also results in a decrease in the carbon intensity of the pilot cities. Owing to the U-shaped association between carbon intensity and the carbon abatement cost, the policy implementation stimulates an increase in the cost within the pilot cities. • This paper estimates the carbon abatement cost (MAC) using SBM-DEA method. • The SDID model is used to investigate the impacts of ECT policy on carbon MAC. • We test whether green technology and carbon intensity are mediating variables. • ECT policy increases the carbon MAC in pilot cities through carbon intensity. • ECT policy lowers the carbon MAC of adjacent cities through the green technology. [ABSTRACT FROM AUTHOR]

The carbon neutrality agenda requires that carbon lock-in enters an endgame. A well-developed energy system, which is secure, equitable, and sustainable is paramount to getting rid of carbon lock-in and realizing decarbonization. We carry out systematic research to empirically study the possible carbon lock-in reduction effect of energy trilemma based on the instrumental variable-generalized method of moment (IV-GMM) model. We also detect heterogeneous effects in terms of geographical locations and endowments of capital, as well as the impact mechanisms. Moreover, this paper highlights the mediating and threshold role of environmental regulation. We thus get the following conclusions. (1) The paper's primary findings underscore that the continuous increase of energy trilemma exacerbates carbon lock-in and hampers the process of decarbonization; (2) Energy trilemma has a higher stimulating effect on carbon lock-in in provinces that lie in the central region and that have a comparatively low level of physical, social, and human capital; (3) Energy trilemma can also indirectly aggravate carbon lock-in by inhibiting technology innovation and exacerbating carbon emissions intensity; (4) The interaction of environmental regulation and energy trilemma can alleviate the energy trilemma - carbon lock-in nexus, and environmental regulation also shows a significant threshold effect. • We investigate the impact of the energy trilemma on carbon lock-in. • Energy trilemma eradication is an effective way to realize the carbon lock-in endgame. • The nexus between energy trilemma and carbon lock-in is more prominent in provinces with high capital endowments. • Environmental regulation shows significant mediating and threshold effects. • The exacerbate carbon lock-in effect of energy trilemma depends on technology and intensity effect. [ABSTRACT FROM AUTHOR]

In the background of exhaustion of the traditional fossil energy sources and environmental deterioration, developing renewable energy has become a strategic choice for countries to achieve energy sustainable utilization and carbon neutrality target. Different renewable energy technical plans have different characteristics under multiple criteria. Therefore, before the further exploitation of renewable energy sources, it is of great significance to evaluate the comprehensive performance of different plans and then determine the best renewable energy sources. However, the commonly used weight calculation methods in the existing renewable energy evaluation have obvious shortcomings, such as the randomness of the subjective method is strong and the gap in the weight allocation of the objective method is too large, which affect the reliability and accuracy of the sorting result. In this paper, a novel weight calculation method based on non-dominated sorting genetic algorithm (NSGA-II) is proposed, and is applied to renewable energy evaluation. The study in this paper focuses on methodology. Firstly, for the linear normalized and Zeros normalized evaluation data, the differences between renewable energy plans in the two normalized evaluation data are measured, and the ranking deviations of the two normalized data are calculated. Then, the multi-objective weight solving model is constructed in terms of plans differences minimization and ranking vectors deviations minimization. The NSGA-II algorithm is applied to the optimization of multi-objective functions to find the Pareto non-dominated solution, so as to determine the weight values of each evaluation index. Finally, the TOPSIS method is used to determine the relative closeness value of each plan, and the rankings of renewable energy technical plans are achieved. Based on the actual renewable energy development data of a province in China, experiments were carried out to investigate the effectiveness of the proposed method. Experimental results show that the proposed method performs better than some popular renewable energy evaluation methods. [Display omitted] • Propose a novel evaluation method for renewable energy technical plans. • Apply non-dominated sorting genetic algorithm II to determine the index weights. • Compared with the existing evaluation method, the proposed method performs better. [ABSTRACT FROM AUTHOR]

Whether renewable energy consumption is beneficial to reducing CO 2 emission intensity and carbon emissions in the context of the goal of "carbon peak and carbon neutrality" in China. To prove this conjecture, considering the spatial spillover effect of carbon dioxide, this paper adopts the spatial Dubin model for empirical analysis based on the panel data of China's 30 provinces over the period 2002–2019. This study explores the CO 2 intensity mitigation effect of China's renewable energy consumption and further investigates the mediation role of technological innovation, industrial structure upgrading and optimization, and energy efficiency in the nexus between renewable energy consumption and carbon intensity. The main findings present that: (1) China's carbon emission intensity is characterized by significant spatial correlation; (2) Renewable energy consumption can significantly reduce carbon intensity and per capita carbon emissions; (3) The mediation effect of renewable energy consumption in reducing carbon emission intensity is to promote technological innovation and industrial structure upgrading, as well as improve energy efficiency. Based on the conclusions, this paper offers several policy implications for governments to reduce CO 2 emission intensity. • The impact of renewable energy consumption on CO 2 emission intensity is explored. • Renewable energy consumption can reduce carbon emission intensity and per capita carbon emissions. • Renewable energy consumption reduces CO 2 intensity through the spatial mediation effect. [ABSTRACT FROM AUTHOR]

The proposed targets to achieve peak carbon before 2030 and carbon neutrality before 2060 would require China to accelerate the development of natural gas infrastructure. The forecasted future of natural gas consumption in China will not only help learn about the future usage of natural gas but also guide government departments to conduct more scientific planning and management of natural gas production and pipeline channels. Therefore, this paper fully considers the characteristics of natural gas consumption affected by seasonal factors and uses the 2018–2021 quarterly natural gas consumption time-series data to analyze whether natural gas consumption contains trends and seasonality. It is noticeable that seasons impact China's natural gas consumption, so the moving average method is applied to calculate the seasonal index. Based on this, China's natural gas consumption from 2022 to 2035 is forecasted. As results show, China's gas consumption will continue to grow over the next 14 years but at a slower rate. By 2035, it will double from the 2021 level, reaching 765.4 billion cubic meters, but the growth rate will drop to below 4%, entering a period of low growth. Finally, the paper illustrates current situation of natural gas development combined with rationalized suggestions for future natural gas production and energy security in China. • Natural gas consumption is influenced by seasonal factors. • A seasonal forecasting method is applied. • China's gas consumption will continue to grow by 2035. [ABSTRACT FROM AUTHOR]

The essence of industrial chain structure optimization is to strengthen the synergy and division ability among sectors. It is a crucial factor in reducing energy intensity and achieving carbon neutrality goals. This paper completed the China's non-competitive input-output table from 2000 to 2020, constructed industrial synergy and division index using structural path analysis method and examined its development trend. Combining with a two-way fixed effects model, we explored the influence of industrial synergy and division on energy intensity. The research found that China's industrial synergy and division development level shows an upward trend. The proportion of the low-layer industrial chain decreases, and the peak contribution rate moves to the high-layer industrial chain. Secondly, industrial synergy and division significantly reduces sectoral energy intensity, the results are robust after endogeneity test. Finally, heterogeneity analysis showed that industrial synergy and division can reduce the energy consumption intensity of all sectors, and it is more obvious for sectors with high energy dependence. This research can provide targeted policy suggestions for China to optimize its industrial structure. It also has a reference significance for other countries. • The impact of industrial synergy and division on energy intensity is explored. • This paper extracts China's non-competitive IO table from the global MRIO table. • SPA is applied to construct industrial synergy and division index. [ABSTRACT FROM AUTHOR]

Under the background of "carbon neutrality" and "carbon peak" concepts, China desires to develop a new power system based on renewable energy sources (RES), which will be the primary energy support in prospective China. Thus, it is imperative to improve the peak shaving capability of power system to address the problem of random fluctuation and intermittency of RES by developing various energy storage systems. An innovative approach to enhance the flexibility of the conventional thermal power unit (TPU) through the utilization of flywheel energy storage array (FESA) is presented, simulated, and evaluated in this paper. Using the relatively practical and specific model of TPU and FESA, modified frequency modulation and automatic generation control (AGC) instruction tracing operation scenario models are constructed. A comprehensive control strategy of FESA and a well-designed operation coordinated control method for TPU with FESA are proposed and applied. The simulation results are distinctively processed and evaluated by the methods in "two documents", aiming to assess the real-world operation performance of the model proposed in this paper. The comprehensive analysis of the indicators demonstrates that the FESA can improve the flexibility and economy of the units. This research may guide the usage of FESA to improve the operational flexibility of TPU. • Composition and Control Methods of the flywheel energy storage array are provided. • A coordinated control scheme for the thermal power unit with flywheel energy storage array is proposed. • Frequency modulation and AGC instruction tracking scenario models are constructed and simulated. • AGC regulation indicators are conducted and analyzed to evaluate the unit's performance. [ABSTRACT FROM AUTHOR]

Clarifying the relationship between new energy and economic growth is an essential prerequisite for achieving the goal of carbon peaking and carbon neutrality. This paper utilizes a combination of nonlinear analysis methods, including transfer entropy, Bai–Perron (BP) structure point breakpoint detection, and complex network theory, to examine the coupling relationship between China's new energy and economy across different stages and sectors. An analysis of the network's topological properties shows that a complex coupling driving relationship exists between the new energy industry and the other 11 economic sectors. In particular, the agricultural sector exerts a significant driving force on the new energy industry, with the most extended duration of influence. Besides, the IT and construction industries also play a driving role in the new energy industry, and the latter's impact is earlier than that of the IT industry. The empirical results can guide the government and makers to formulate long-term sustainable action plans for different economic sectors. • Transfer entropy, BP structure break point detection and complex network are used. • 33 net transfer entropy symbol mode complex networks are constructed. • The coupling relationship between China's new energy and economy is complicated. • The agriculture industry has a large driving force on new energy industry. [ABSTRACT FROM AUTHOR]

The exploration and promotion of new energy constitute a significant initiative for numerous countries in their pursuit of sustainable development and efforts to alleviate climate change. However, the influence of a multitude of uncertain factors on the evolutionary path of new energy is currently poorly studied. By establishing a dynamic evolution model for new energy under polymorphic uncertainty, this paper analyses the complex interaction between new energy, economic growth, and carbon trading over the period 2020–2060, using China as a case study. We employ numerical simulation and sensitivity analysis to investigate the evolutionary trajectories of the new energy system under various parameter value scenarios. We show that the evolutionary trajectories will undergo substantial fluctuations before 2030, subsequently stabilizing from 2030 onwards. The study highlights that an excessively rapid pace of new energy development is detrimental to new energy systems, whereas energy storage system deployment has the opposite effect. There exists a significant risk of the system collapsing as a result of slow new energy development, over-building energy storage facilities, or over-intervening in carbon trading. We also find that overdevelopment of energy storage system may have greater negative impacts on the economic system than underdevelopment. [Display omitted] • Dynamic evolution model of new energy under polymorphic uncertainty is constructed. • New energy production elasticity and energy ratio are innovatively constructed. • Excessive intervention in carbon market can lead to the collapse of new energy system. • Overdeveloped energy storage hinder the synergy of new energy and economic growth. [ABSTRACT FROM AUTHOR]

Electricity market-oriented reform and carbon emissions trading, as the main policies implemented in China's power sector, have a profound impact on China's green and low-carbon transition by promoting resource allocation efficiency and internalizing external environmental costs, respectively. Therefore, this paper constructed a dynamic recursive CGE model to measure the energy, economic, and environmental impacts of carbon emissions trading and electricity market-oriented reform from electricity market structure and pricing mechanism. The results show that the two policies have a synergistic effect on industrial structure optimization, energy consumption structure optimization, and carbon emission reduction. Specifically, the share of value-added of the tertiary sector, the growth rate of coal consumption, the share of thermal power consumption, and carbon emissions in 2030 are reduced by 5.70 %, 18.29 %, 2.55 %, and 2.838 trillion tons, respectively, compared with the scenario without carbon emissions trading and electricity market-oriented reform. However, imperfectly competitive market structures outperform perfectly competitive market structures in energy consumption structure and carbon emission reduction. Electricity price regulation is also more beneficial to GDP growth and increase in residential disposable income compared to price liberalization. To this end, returning emission trading scheme revenues to residents can effectively mitigate the adverse impacts caused by market-oriented reforms. • EMR is involved in market structure, pricing mechanisms, and market regulation. • EMR and CET have a synergistic effect on carbon reduction. • Energy consumption structure is better in imperfectly competitive market. • Electricity price regulation is more beneficial to GDP growth. • Returning ETS revenue to residents increases per capita disposable income. [ABSTRACT FROM AUTHOR]

This paper takes 30 provinces in China as the research subjects and constructs a real options model to explore the impact of carbon emissions trading market, energy storage subsidies, and their synergy on the optimal investment decision of household PV-ESS projects. The results show that a single factor has a catalytic effect on project investment, and both together have a better effect. And, project investment benefits are better in areas with abundant light resources and higher than average electricity prices. In addition, a sensitivity analysis is conducted on the initial investment cost, CO 2 price, and energy storage subsidies. The results show that immediate investment in all provincial projects can be achieved when the initial investment cost is reduced by 50%, or the CO 2 price is increased by about 33 times, indicating that the current environment is insufficient to attract investors. The results provide a reference framework for investment in household PV-ESS projects. • Use real options methods to assess investment decisions for household PV-ESS projects. • Explore the role of carbon trading market and energy storage subsidies on investment. • Research the impact of different regional power grids on investment value. [ABSTRACT FROM AUTHOR]

Carbon Capture, Utilization, and Storage (CCUS) is an indispensable technology to achieve carbon neutrality in China, but confined by technology and economy, the offshore CCUS in China is still in the planning stage and has not yet reached the desired scale. Offshore source-sink matching and cost analysis of CCUS is the premise and basis of offshore CCUS deployment. Thus, based on the CO 2 storage potential of offshore sedimentary basins in China, this paper conducts the offshore source-sink matching and cost analysis of CCUS in China under different constraints. The result showed that: ⅰ) the CO 2 storage capacity of China's offshore sedimentary basins is estimated to be 767.3 Gt, which is enough to meet approximately 200 years of coal power CO 2 emissions in China. ⅱ) the CO 2 storage potential could reach 721.9 Mt/a by source-sink matching under different constraints. ⅲ) early opportunities for offshore CCUS would be in the Bohai Bay and Pearl River Mouth Basin, considering the compensation effect of CO 2 -EOR. ⅳ) combined with the CCUS cost and emission reduction in China under different time nodes, it is inferred that deploying offshore CCUS in China between 2030 and 2040 commercially will be advantageous. • The CO 2 storage potential in China's offshore sedimentary basin was evaluated. • The cost of offshore CCUS was analyzed under different technology combinations. • Bohai Bay and Pearl River Mouth Basin would be early opportunities for offshore CCUS. • 2030–2040 would be the favorable time to deploy the large-scale offshore CCUS. [ABSTRACT FROM AUTHOR]

Public low-carbon travel is of great significance for achieving carbon neutrality and mitigating climate change. Therefore, taking the Chinese public as the research object, this paper discusses the impact of public awareness of climate policy on low-carbon travel. First, based on stimulus-organism response (SOR) theory, this paper constructs a theoretical model to study the impact of public perception of climate policy on low-carbon travel. Then, environmental emotion is used as a mediating variable in the model. Finally, 419 respondents were selected for a questionnaire survey to collect data. It is found that public awareness of climate policy affects low-carbon travel by triggering environmental emotions. Positive environmental emotions have a significant positive impact on low-carbon travel, while negative environmental emotions have a significant negative impact on low-carbon travel. In addition, positive environmental emotions have a greater impact on low-carbon travel than negative environmental emotions. Based on the above conclusions, this paper puts forward the following specific suggestions: in-depth publicity of climate policy, cultivation of positive environmental sentiment, strengthening the public's responsibility to respond to climate change concerns, etc. • The effect of climate policy cognition on low-carbon travel is explored. • Offers solutions by identifying the mediating role of environmental emotion. • Positive environmental emotion is more influential than negative environmental emotion on low-carbon travel. [ABSTRACT FROM AUTHOR]

With the development of low-carbon energy, the use of thermal and hydropower units for regulation in the power system dominated by new energy (PSDNE) is decreasing. Electric buses (EBs) are expected to become the primary dispatching objects in this context. Accurately evaluation EB's response capability (RC) is vital for the scheduling operation of the PSDNE. However, current evaluation methods for EB's RC are relatively crude, lacking detailed and quantifiable measures. This paper proposes a novel multi-dimensional evaluation method to provide the aforementioned RCs. The EB operational schedule revise model considering traffic and temperature is proposed to obtain more accurate EB charging load by revise arrival charging time and remaining battery energy. The proposed EB charging model considering carbon emissions contributes to revealing the impact of various charging modes, such as low-carbon and electricity price, on the Eb's RC. The EB multi-dimensional evaluation model is established to obtain quantified and detailed RCs to support the operation of NEDPS. These capabilities include fast response within various periods, sustained response over extended durations, and remaining RC after executing scheduling instructions. Finally, using the actual data from an EB station of a city in China, the effectiveness of the proposed evaluation model is verified. [Display omitted] • The impact mechanisms of traffic and temperature on the EB's RC are revealed. • The accuracy of the revised EB's operating schedule is greatly enhanced. • The impact mechanisms of carbon emissions reduction on the EB's RC are revealed. • The EB's RC under different charging modes is quantitatively evaluated. • The fast RC, sustained RC, and remaining RC of the EB are quantitatively evaluated. [ABSTRACT FROM AUTHOR]

China has set a goal of carbon neutrality by 2060 and is determined to increase wind and solar power to 1200 GW by 2030, even though it already has the world's largest installed capacity of renewables. However, the lack of flexibility in the power system will limit the development of a higher proportion of renewable energy. This paper evaluates the applicability of different types of flexible power sources in China for the first time. Above all, it describes the current situation of China's power industry and the necessity of increasing flexible power sources, establishes an evaluation system from the perspectives of benefit, opportunity, cost & risk, then determines 19 evaluation criteria. The BOCR-ANP-TOPSIS method was used to evaluate the system, where the ANP method determines the weights and the TOPSIS method ranks the alternatives. The result shows that pumped storage hydropower has the highest overall ranking, followed by the flexibility transformation of coal-fired power. Coupled with sensitivity and comparative analysis, valuable findings that will help future energy policymakers are reported. • Evaluating the applicability of different flexible power sources in China for the first time. • The identification of criteria for the selection of flexible power sources was given. • Making recommendations for China's flexible power source development policy. • The BOCR-ANP-TOPSIS method adopted can be extended to select flexible power sources in different regions meticulously. [ABSTRACT FROM AUTHOR]

Transferring energy-intensive industries to regions with abundant clean energy is crucial for achieving low-carbon transformation of energy-intensive sectors during carbon neutrality. By manually collecting the project data from energy-intensive enterprises in China, we construct a three-dimensional panel data with 1.86 million observations to empirically examines the impact of the carbon intensity constraint policy (CICP) on the transfer of high energy-intensive projects (HEP). Our findings indicate that the CICP accelerates the transfer of HEP. The transfer direction shows that the HEP transferred from the eastern region to the western region have increased, but the HEP transferred from the western region to the eastern region have not decreased. To explain the above phenomena, we further discuss the underlying mechanism from the perspective of energy structure and industrial agglomeration. From the standpoint of transfer-out regions, the higher the proportion of thermal power in the energy consumption structure, the more HEP will be transferred out. From the standpoint of transfer-in regions, the industrial agglomeration will attract the transfer of the HEP. However, we do not find evidence that wind power and photovoltaics can attract the HEP. This paper provides project-level empirical evidence for promoting the low-carbon transformation of energy-intensive industries. • The carbon intensity constraint accelerates the transfer of energy-intensive projects. • The dynamic effect shows a fluctuating and decreasing trend. • The transfer direction is the net transfer from the east to the west. • The more thermal power, the more energy-intensive projects will be transferred out. • We don't find the attraction of the clean energy for the energy-intensive projects. [ABSTRACT FROM AUTHOR]

Balancing the ecological and economic benefits of energy consumption is an essential requirement and a key part of achieving the task of high-quality economic development and the goal of carbon neutrality. This paper analyses the energy efficiency and spatial and temporal evolution characteristics of thirty Chinese provinces and cities from 2006 to 2019 based on the DSBM model. The results show that, firstly, environmental factors have a significant impact on the evaluation of energy efficiency, with the national energy efficiency showing phase fluctuations and a decreasing trend from the east to the center and then to the west during the sample period. Secondly, the country and the three major regions did not show a σ convergence. Thirdly, there is significant absolute and conditional convergence in overall energy efficiency after considering spatial spillover effects, and with a turning point. Fourthly, energy efficiency in the three major regions also shows a clubbing phenomenon, with different regions tending to their own steady state of energy efficiency. Finally, we put forward suggestions for improving energy efficiency. The results of the study help to understand the changing trends and influencing factors of inter-regional energy efficiency in China, which can provide a reference for achieving the transformation of energy structure and has important practical significance. [Display omitted] • The DSBM model to evaluate energy efficiency relaxes the assumptions of DEA models. • The DSBM model includes environmental and relaxation variables in EE assessment. • The spatio-temporal characteristic of EE is analyzed from multifaceted perspectives. • We analyze the club characteristic and key turning points of EE convergence in China. [ABSTRACT FROM AUTHOR]

The realization of carbon neutral goal is inseparable from the development of new energy industry, and scientific and effective policy support can accelerate the progress of the goal. In this paper, the policy driven ability of China's photovoltaic industry in the background of carbon neutral is evaluated. Firstly, the evaluation system is established by the improved diamond model. Then, the policy evaluation standard is formulated according to the Interval Type-2 Fuzzy sets (IT2FS). Finally, the weight of each index is determined by using the fuzzy OWA operator weighting method (F-OWA). Then, the policy driving ability of China's photovoltaic industry is evaluated by fuzzy matter-element extension method (F-MEEM), and the effectiveness of the evaluation results is further verified by weight sensitivity analysis. According to the evaluation results, policy support plays an important role in the development of photovoltaic industry. This paper also gives policy suggestions for the development of China's photovoltaic industry under the background of carbon neutral from the macro, meso and micro perspectives. • China's PV industry evaluation system is established by the improved diamond model. •IT2FS and F-OWA are used to process indicators. •The policy driving ability of China's PV industry is evaluated by F-MEEM. •The effectiveness of the evaluation results is further verified by weight sensitivity analysis. •The results are analyzed in detail, and corresponding suggestions are put forward. [ABSTRACT FROM AUTHOR]

How to achieve the "double carbon" goal in energy systems has been the concern of governments. Integrated energy system (IES) is affected by climate change during his operation, in order to study the impact of climate change on IES and achieve the "double carbon" goal in energy systems, this paper proposes an integrated machine learning(IML) to forecast the long-term load, then investigates IES costs and carbon emissions in relation to climate, followed by the establishment of carbon peak energy system(CPES) and carbon neutral energy system(CNES), finally the honey badger algorithm is used to optimize the configuration of CPES and CNES. The results show that: IML can accurately make load forecasts. Under climate change, changes in load reduce the cost and carbon emissions of IES, and changes in equipment efficiency increase the cost and carbon emissions of IES. When both are considered, the cost and carbon emissions of IES increase by 1.18% and 0.92% per decade respectively. The costs of CPES and CNES increase by 0.93% and 1% respectively for every 10 years earlier than the year of achievement. To meet China's "double carbon" goal, CPES and CNES need to increase their costs by 1.97% and 2% respectively. • Integrated machine learning proposed for long-term load forecasting. • Studied the impact of system equipment efficiency and load with climate change. • Proposing carbon peaking energy system to achieve the carbon peak goal. • Proposed carbon-neutral energy system to achieve carbon neutrality goal. • The increased costs of achieving carbon peak and carbon neutral were studied. [ABSTRACT FROM AUTHOR]

Banning gasoline vehicle sales policy (BGVSP) is considered a potentially important drivers for achieving carbon peak. This study, therefore, analyzed public support for such policies from the perspective of consumers. Using a grounded-theory approach, we developed a public-support model for BGVSP, on that basis, revealed the effects of the key elements and the theoretical logic. The results revealed: 1) Individual and psychological factors are important internal motivations, while the external driving factors include contextual factors and product factors. 2) The depth of individual perception is key to filling gaps in attitudes and behavior, and it plays an important role in improving public support. 3) The external contextual factors that affect consumer support mainly include external incentives, social influences, and urban contextual variables, which also play a moderating role in the integration model. The results show that the prohibition policy is easy to bring negative emotions, thereby causing public resistance, so the design of BGVSP should be based on the understanding of individual cognition, attitude and emotions. This paper constructs a model of the motivation of public support for China's localized BGVSP, and clarifies the core influencing factors and mechanisms, which provides fresh ideas for the realization of carbon peaking and carbon neutrality goals. • Banning gasoline vehicles increase the speed of carbon peaks in the transportation sector. • The public support for banning gasoline vehicle sales policy has been explored. • Developed a public support model with four core categories, namely, individual, psychological, contextual, and product. [ABSTRACT FROM AUTHOR]

COVID-19 brings new challenges to addressing climate change and achieving the goal of environmental sustainability. This paper examines how the COVID-19 pandemic affects transmission of returns spillovers among green finance, carbon market and renewable & non-renewable energy in China. We evaluate the dynamic and directional risk connectedness across time and at various frequency bands using Diebold and Yilmaz and Baruník and Křehlík approaches. First, the total spillover effects increase significantly when the COVID-19 outbreak. Second, the carbon price fluctuations are mainly influenced by non-renewable energy. Third, the spillover effect is mainly acted in the short term, meaning that it is strongly influenced by investor sentiment in the short term. Fourth, non-renewable energy and carbon markets are the main net recipients and can be used as hedge assets. Finally, the total spillover is time-varying that is affected by the unexpected crisis. The findings will help policymakers and environmental investors to develop policy measures and portfolios that are appropriate for different frequency domains. • Time-frequency connectedness among green finance, carbon and energy is tested. • Spillovers increase at the onset of the COVID-19 and mainly acted in the short-term. • The carbon price fluctuations are mainly influenced by non-renewable energy. • Non-renewable energy and carbon markets are the major net recipients. • The total spillover is time-varying affected by the unexpected crisis. [ABSTRACT FROM AUTHOR]

Intermittent renewable energy sources have been transformed from supplementary energy to dominant incremental alternative energy sources in the context of carbon neutrality target worldwide. For coastal countries, it is urgent to integrate abundant offshore energy into regional onshore renewable power sources economically and reliably considering the scarcity of land resources and negative environmental impacts. However, limited knowledge on the complex spatiotemporally synergy relationships between energy potential (onshore and offshore) is a barrier in making reasonable policies to promote collaborative development of onshore and offshore energies. This study presents a spatiotemporally explicit modelling framework for assessing the synergy potential characteristics of onshore and offshore renewable energy sources. The framework firstly estimates the technical potential of solar PV and wind energy across the country by using 40 years of hourly meteorological reanalysis data (1980–2020), and then investigates the long-term changes trend, stability, and complementarity of solar-wind energy potential spatiotemporally at both onshore and offshore sub-regions. We find that a considerable amount of solar PV and wind energy sources could be harnessed in China, and onshore potential across the country (178 PWh/yr) is approximate 20 times higher than offshore energy potential (8.9 PWh/yr). Overall, onshore solar-wind energy potentials exhibit statistically insignificant but slightly increasing trend over the past 40 years, while offshore wind potentials observe an opposite change trend for solar PV and wind energy production. Complementarity assessment showed the northeast and offshore parts of China present high complementarity effects for hourly and daily power production of solar-wind systems. Furthermore, inter-regional combination between offshore and onshore northwest regions also exhibits promising synergy effect for renewable energy power output. The results on resources dynamic and complementarity highlight the advantage of interregional resources cooperative configuration and electric power grid interconnections. The analysis performed in this paper could provide a global picture for the integration planning and collaborative development strategies formulation of on-/offshore renewable energy across the country. • Synergy potential of onshore and offshore renewable energy was evaluated. • Trend, stability, and complementarity of solar and wind potential were examined. • Onshore energy potential in China is 20 times higher than offshore potential. • Synergy development strategies of onshore and offshore energy were proposed. [ABSTRACT FROM AUTHOR]

The establishment of carbon emissions trading (CET) and tradable green certificate (TGC) markets in China will cause great alterations in the bidding behavior for generation companies (GENCOs) and affect the low-carbon transformation of power industry. In this paper, a Nash bargaining game model is constructed to assess the synergy of power, CET and TGC markets on decision behavior of non-renewable energy GENCOs, renewable energy GENCOs and power purchasers. The simulation results show that there is transition incentive effect, price interaction effect and profit blocking effect between three markets. With the introduction of emissions trading scheme and renewable portfolio standard (RPS), the scheduled power of renewable energy GENCOs will increase by 21.43%, and transaction prices will reduce to 449.58 CNY/MWh; while the scheduled power of non-renewable energy GENCOs will reduce by 4.66%, and transaction prices will increase to 443.71 CNY/MWh, which make all power generation types compete at equivalent price level. Under the current installed capacity distribution and load demand, it is the critical point when RPS is 18.7% and the benchmark value of free carbon quota for units above and below 300 MW are 0.857 tCO 2 /MWh and 0.959 tCO 2 /MWh. Once exceeded, it will affect social benefits and emission reduction efficiency. • Policy synergy among power, CET and TGC market mechanisms is investigated. • Transaction behavior of different GENCOs and power purchasers is discussed. • A power-CET-TGC market transaction model is constructed. • Dynamic CET, CCER and TGC prices are considered. • The critical points of RPS and free carbon quota are found. [ABSTRACT FROM AUTHOR]

The carbon trading market is an effective way to mitigate the threat of climate warming. In the context of carbon neutrality, what is the carbon emission trading scheme's carbon reduction effect? This paper answers the question by examining the carbon efficiency of China's iron and steel industry. This study first constructs CO 2 emission efficiency by employing the data envelopment approach. It then uses the synthetic control method to identify the impact of the carbon emission trading scheme on the CO 2 efficiency of the iron and steel industry. The results show that CO 2 emission efficiency in pilot provinces increased at a 5% significance level compared with the counterfactual scenario. The carbon trading market plays a vital role in industrial CO 2 emission efficiency improvement in Guangdong, Shanghai, Tianjin, Hubei, and Chongqing. From a dynamic perspective, the policy effect of enhancing CO 2 efficiency becomes more prominent over time. Moreover, the effectiveness degree of the carbon emission trading scheme varies across pilot provinces, caused of regional policy differences. Based on the findings, we put forward targeted suggestions for improving the newly-established national carbon trading market. • The DEA model and the synthetic control method are employed in the study. • Impact of carbon market on CO 2 efficiency of iron and steel industry is verified. • The heterogeneity of carbon market effects is explored from regional perspective. • Carbon market significantly promotes industrial CO 2 efficiency in pilot provinces. • China should develop the national carbon market to achieve carbon neutrality. [ABSTRACT FROM AUTHOR]

Carbon neutrality goal puts forward new requirements for the energy structure of the power industry in China. The impact of electricity marketization reform on energy transition is one key issue that we need to consider. This paper constructs a system framework for the internal connection of the four primary energy sources and two system dynamics (SD) models to analyze the impact of the marketed on-grid price on the energy transition in the power industry. The results show that: (1) Compared with the benchmark on-grid price, the marketed on-grid price can promote the realization of the energy transition goal in the power industry to a certain extent. In 2060, the marketed on-grid price will be stable at about 0.1 yuan/kWh. (2) The energy transition goal can be achieved if the degree of market openness exceeds 60%. However, if coal-based power fully enters the marketization stage, the proportion of renewable energy can even reach more than 90% in 2060. (3) It is difficult to achieve the carbon neutrality goal only by increasing the proportion of renewable energy. Finally, we put forward corresponding policy recommendations. • The electricity marketization reform has an impact on the energy transition. • Driving mechanism of the marketed on-grid price is investigated in the power industry. • Two system dynamics models are built. • The energy transition goal can be achieved if the market openness exceeds 60%. [ABSTRACT FROM AUTHOR]

As an important path to realizing carbon neutrality in China, digital development may also lead to the growth and rebound of energy demand. Investigation of digital rebound effect is important to evaluate whether digital development can effectively conserve energy. Thus, this paper examines the impact of digital development on electricity consumption and its heterogeneity among Chinese cities, and further evaluates the sizes of energy rebound effect triggered by digital development. The results show that, first, electricity consumption in Chinese 285 cities increases by 7%–20% due to digital development, and this positive influence tends to increase with the increase in electricity consumption. Second, in the eastern, high-income, and high-tertiary industry share regions, digital development has a greater role in promoting electricity consumption. Third, the digital development of Chinese cities induces the rebound effect of electricity consumption, and even induces the backfire effect in the early stages of digital development. Finally, the energy rebound effect tended to decrease over time, with a partial rebound in electricity consumption, and the minimum rebound effect was 22%. The results highlight the necessary attention on digital rebound effect, and the importance of low-carbon digital development. • Electricity consumption increased 7%–20% due to digital development in China • The positive influence tends to increase with the increase in electricity consumption • Digital development in Chinese cities leads to energy rebound effect • The energy rebound effect tended to decrease over time, with a partial rebound [ABSTRACT FROM AUTHOR]

In the coming four-decade, China will face serious challenge while shifting to carbon neutral. Photovoltaic (PV) power, as one of the most promising clean energies, is seen as an important focus for decarbonization of the power sector in China. The novelty of this study is to use life cycle assessment (LCA) methods to analyze the CO 2 emission reduction of the PV generation industry before 2060 base on the amount of energy and resources consumed and PV generation's CO 2 reduction benefits during the whole industrial chain. This paper aims to examine CO 2 emission reduction contribution, we firstly compute the historical emissions and predict future PV waste and new power capacity from 2010 to 2060. Then, considering the change of industrial structure and technological evolution, the yearly life cycle CO 2 emission from producing stage to recycling stage is calculated. The key results show that the unit CO 2 emission of PV system producing will reduce 88.07% from 2010 to 2060. PV generation industry's total CO 2 emission has reached its neutrality between 2014 and 2015, and will reduce 33.03 Giga tons CO 2 -eq till 2060. The findings can offer relevant insights to low-carbon development of China's PV industry and will provide suggestions for policy-making. [Display omitted] • In the context of Carbon Neutrality target of China. • Explores the CO 2 emission reduction effect of photovoltaic industry in China. • Takes energy structure, technology and products structure into consideration. • Photovoltaic industry will help to reduce 33.03 Bt CO 2 till 2060. [ABSTRACT FROM AUTHOR]

The green transformation of the building industry plays a key role in China's goal of carbon neutrality. This paper creatively brings the green transformation behavior of the buildings industry into the Dynamic Stochastic General Equilibrium (DSGE) model and widens the application to simulate the impact of green building subsidies and carbon emission tax on the green transformation of China's building industry. The DSGE model observes the changing trend of China's output, consumption, investment, and social welfare and provides references for policy-makers to realize sustainable economic development. The results show that the steady-state values of most main variables present an inverted U-shaped trend in the transformation. At the initial stage of the transformation, tax aggravation is good for carbon emission reduction but not for economic growth, while technical achievement and subsidies are contrary. Meanwhile, technical achievement brings the highest social welfare while subsidies bring the least. Urban analysis suggests that the large city shows more vitality and potential in consumption while there is a large growth room for capital investment in the small city in the future. When the transformation enters the middle and late stages, none of the above policies can further promote economic growth except technical achievement. • We introduce green transformation of the buildings industry into the DSGE model. • The carbon tax will reduce carbon emissions and economies in the early stage. • Technical progress and subsidies grow economies and emissions in the early stage. • Only technical progress can rise economies in the late stage of transformation. • Technical progress brings the highest welfare while subsidies bring the least. [ABSTRACT FROM AUTHOR]

This paper analyzed the coupling relationship between the carbon market and power market and constructed a threshold regression model of carbon cost pass-through to electricity prices. Furthermore, a system dynamics model was built based on "electricity-carbon" market. The results show that first, the carbon market and power market operate independently but are interrelated. The two markets will work when Chinese emission allowances and carbon prices are effectively connected with carbon emissions and electricity prices. Second, because the electricity price formation mechanism is mainly regulated by China's government, the carbon price has a significant negative effect on the electricity price since the operation of the national carbon trading system. There is no obvious linkage effect between the CO 2 cost and electricity price. Third, under the current policies and market mechanism, the carbon price will experience the process of "remain low-rapid rise-remain high". The carbon price will drive the on-grid price and sales price up. The allowance auction mechanism and carbon cost direct pass-through can effectively reflect CO 2 cost in the electricity price. In the long term, introducing auctioning in the carbon market and reforming electricity price formation in the power sector will tap the emission reduction potential. [Display omitted] • Design of coupling relationship between China's electricity market and national ETS. • Measure the carbon cost pass-through rates in electricity market. • Build the system dynamics model of national ETS and electricity market. • Explore the factors that affect the effectiveness of CO 2 cost pass-through. [ABSTRACT FROM AUTHOR]

The proposed policy targets of "2030 carbon peaking" and "2060 carbon neutrality" further accelerate the substitution of natural gas for oil and coal. In this paper, we systematically considered the growth trend of natural gas demand from both the total amount and the structure of energy.On the basis of 60-year sample data, we built the HMM model innovatively to simulate the complementary and alternative structural effects between different energy. In addition, according to the different policy intensity, we simulated the history of energy demand and forecast the future trend in three scenarios. The empirical results show that the share of natural gas in primary energy consumption in China in 2035 is 16.5%, 17.3%, and 13.6%, respectively, translating into natural gas demand of 6975, 7316, and 5748 bcm. Therefore, policymakers should promote energy transformation in a steady and orderly manner based on national conditions and strengthen gas demand-side management on the premise of ensuring reasonable demand. Our prediction of natural gas demand from a new perspective can assist policymakers to formulate the natural gas demand-side policy and import plan, and also provide a reference for studies of achieving the goal of energy transition and "2060 carbon neutrality". • The overall and structural effects of gas demand growth. • The evolution trend of energy demand structure is predicted through three ideas. • Structure model is used to simulate the substitution of energy sources. • The prediction results of hidden Markov model are more reasonable. [ABSTRACT FROM AUTHOR]

The proposal of carbon peak and carbon neutrality goals will inevitably promote the large-scale development of renewable energy, and the market mechanism is also being pushed forward to absorb more renewable energy in China. Considering electricity-carbon integrated market mechanism, this paper constructs a hybrid game model to study the evolutionary process of renewable energy generation companies (GENCOs) in market trading by setting up three renewable energy bidding modes. Among them, the leader-follow relationship between GENCOs and the day-ahead electricity market is reflected by the Stackelberg game model, and the bidding behavior of different GENCOs is described by cooperative and non-cooperative game models. The role of different stages for the carbon emissions trading (CET) market on the electricity market is discussed based on the sensitivity analysis. The simulation results show that the bundled sales between wind, photovoltaic and thermal power GENCOs could improve the expected profits of each GENCO and reduce the total carbon emissions. As the proportion of renewable energy in the electricity market increases, the clearing prices will decrease. Meanwhile, the peak-shaving times of thermal power units will raise, and thermal power GENCOs are more willing to participate in the auxiliary service market. Besides, the complete marketization of renewable energy GENCOs will affect the recovery of the initial investment. Moreover, it can be found that lower free carbon quota, higher CET and Chinese certified emission reduction (CCER) prices can effectively guide the electricity market to be cleaner. • Propose effective bidding modes for renewable energy. • Consider the impact of electricity-carbon integration mechanism on renewable energy. • Determine the optimal alliance of different types GENCOs for bundling electricity. • Set dynamic CET and CCER prices to better reflect market supply and demand. [ABSTRACT FROM AUTHOR]

To reach carbon neutrality, renewable energy development will gradually accelerate. Tidal current energy, with high energy density, long-term predictability and potentially large reserves, is an important research direction. As the prerequisite for tidal current energy development, Tidal Current Power Plant Site Selection (TCPPSS) affects its future benefits. Although some studies have been conducted on TCPPSS, further work is still needed on criteria system, research scales and methods. In this paper, a three-stage decision framework is proposed based on Geographic Information System (GIS) and Multi-Criteria Decision Making (MCDM) to determine potential marine areas, extract and evaluate site alternatives. In this framework, a scientific criteria system with exclusion and evaluation criteria is established. To reduce subjective deviations in Analytic Hierarchy Process (AHP), a combinative weighting method based on Fuzzy Group decision making AHP (FGAHP) and CRiteria Importance Through Intercriteria Correlation (CRITIC) is developed to calculate the criteria weights. Considering the maximum group utility and minimum individual regret, VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), a compromise method, is used to rank the alternatives. The proposed framework is applied to a case of Shandong Province, Eastern China. The results are verified through sensitivity analysis and can provide a direct reference for decision-makers. • A three-stage decision framework for Tidal Current Power Plant Site Selection is proposed. • The framework based on a novel method includes both large-scale site selection and small-scale site selection. • A scientific criteria system including exclusion and evaluation criteria is established. • A combinative weighting method is developed to calculate criteria weights. • A case study is carried out in Shandong Province, Eastern China. [ABSTRACT FROM AUTHOR]

China has played an active and constructive role in the global combat against climate change. Municipalities play a leading role in tackling global climate change. However, despite the global efforts to push for carbon neutrality, the pathway is not yet clear. Using the municipality of Bengbu as a case, this paper explores pathways for achieving carbon emission peak and carbon neutrality in order to reach a CO 2 emission peak before 2030 in four Scenarios and develops a low emission framework taking into consideration the local economy, population, renewable resources, as well as the transport and energy sectors based on the Low Emissions Analysis Platform (LEAP) model. Meanwhile, the energy demand, the structure of the electric power generation, the CO 2 emission, and the total cost in different Scenarios are simulated respectively. The result of this study provides insight on options for energy transformation for the period of 2020–2060. The results show that the industrial sector is the largest energy consumer. The growth rate of energy demand in the primary industry and industrial sector shows downward trends. The increasement of industrial electrification rate and coal generation phasing out are crucial to CO 2 emission reduction. The large-scale deployment of renewable energy and the deployment of thermal power generation with CCUS are important for the electric power industry to achieve carbon reduction goals. Last but not the least, recommendations on energy planning for municipals to realize carbon emission peak and achieve carbon neutrality are provided. • Pathways for achieving carbon reduction targets of the municipality based on the LEAP model are explored. • The coal generation phasing out is prerequisite to CO 2 emission reduction. • The large-scale deployment of renewable energy is crucial for the electric power industry to achieve carbon reduction goals. • The deployment of thermal power with CCUS is necessary for the electric power industry to achieve carbon reduction goals. • Restructuring of industrial energy consumption and increasing the electrification rate are significant. [ABSTRACT FROM AUTHOR]

As a carbon reduction technology, CCUS (Carbon Capture, Utilization and Storage) is an important way to achieve the goal of "carbon peak and carbon neutrality" in China. In order to change the situation of slow commercialization and large-scale development of CCUS, this paper proposes to establish a CCUS cooperative alliance. Taking alliance organizers, institutional investors, upstream operators and downstream operators as research objects, the evolutionary game model is developed to reveal the dynamic evolution mechanism of CCUS cooperative alliance and analyze the impact of exogenous variables on the strategic choices of alliance members. The results show that: (1) establishing a strong market-oriented alliance can promote the large-scale deployment and commercialization of CCUS, (2) when return on investment is greater than or equal to 6%, it can effectively promote the investment of institutional investors in CCUS field, (3) when the government subsidy rate is greater than or equal to 75%, the willingness of downstream operators to operate independently is significantly enhanced. This study reveals the operation mechanism of the alliance, provides theoretical and methodological support for the operation and management of the alliance, and is of great significance to promote the cooperative operation and development of the alliance. • A CCUS cooperative alliance with commercial characteristics is proposed. • An evolutionary game model is developed to reveal evolution mechanism of alliance. • ROI of 6% or more can promote institutional investors' investment in CCUS. • Subsidy rate of 75% or more can urge downstream operators to operate independently. [ABSTRACT FROM AUTHOR]

With the "carbon neutrality" target proposal, China is facing severe pressure on carbon reduction. Industrial economic activities form an essential emission source of carbon dioxide. Therefore, it is necessary to promote industrial sectors' coordinated emission reduction work. This paper uses non-competitive input-output model and structural path decomposition method to analyze the carbon emission changes from three levels of total, production layer and industrial chains, identifying the main paths and driving factors of carbon emission changes in China from 2017 to 2018. The results show that: (1) The first layer presents obvious low-carbon characteristics as a direct emission level, but the change in its carbon emissions accounted for 41.8%. (2) The increased emission of industrial chains is mainly caused by consumer spending and fixed capital formation, and emission reduction is mainly triggered by consumer spending. (3) Demand scale is an essential driving factor of carbon emission increase. The contribution rate of demand structure to emission increase and reduction industry chains is 55.1% and −16.5%, respectively, which is the biggest reason for the difference between them. Finally, targeted policy recommendations are put forward from the perspective of the emission transmission path and driving factors in the industrial chain. • The non-competitive IO model of China's CO 2 emissions is established. • SPD is applied to identify the emission increase and reduction industrial chains. • The driving factors of CO 2 emission changes in industrial chain are explored. • The comparative analysis of increase and reduction industrial chains is conducted. [ABSTRACT FROM AUTHOR]

Energy internet is an effective way to fulfill carbon neutrality, since it has the advantages of high-efficiency energy utilization. As an important part in energy internet market, multi-energy transaction reflects complementarity of multi-energy sources and provides guidance for future development. However, there still lacks an effective index system for multi-energy transaction evaluation and a reliable method to flexibly handle the subjectivity and vagueness during the evaluation process. In this paper, an effective index system and its extraction method and a comprehensive evaluation approach are proposed to reliably assess the multi-energy transaction performance of the energy internet market. Firstly, an interval type-2 fuzzy decision-making trial and evaluation laboratory (IT2F DEMATEL) method and λ-adversarial interpretive structural modelling (λAISM) approach are combined to extract a 14-indicator index system, the proposed method not only investigates the interrelationship between the indicators but also calculates the influence degree between them. Secondly, to control the vagueness and uncertainty involved in expert judgement, a novel non-deterministic method, combining fuzzy comprehensive evaluation and credibility-based analytic hierarchy process (AHP) with variable rough precision theory, is developed to evaluate the multi-energy transaction performance. Finally, two real-world demonstration projects in northern and southern China are investigated for case studies. The evaluation score of the multi-energy transaction in DZZ town has improved by 25.77 from 2018 to 2021, reaching a "good" performance of 78.09; while the score of XB town has improved by 19.34, reaching an "excellent" performance of 84.32 in 2021. Comparative analysis shows that the extracted index system contains the minimum required information, and the proposed evaluation method can effectively handle the linguistic imprecision and cognition vagueness caused by expert judgements. [Display omitted] • A 25-indicator comprehensive index system is established for the multi-energy transaction evaluation of energy internet market. • An IT2F DEMATEL-λAISM method is proposed, and 14 key indicators are extracted considering causality and influences between the multi-energy transaction evaluation indicators. • A novel integrated fuzzy performance evaluation approach is proposed for multi-energy transaction evaluation. • Judgement credibility and variable rough precision theory are considered to deal with the subjectivity and uncertainty of evaluation through flexible fuzzy boundaries. [ABSTRACT FROM AUTHOR]

It is critical for China to promote the substitution of coal with natural gas (NG), and the development of carbon sequestration (CS) technology to achieve its carbon neutrality goal by 2060. Underground gas storage (UGS) employing CS technology is an important choice suitable for NG development in large scale and carbon neutral goal requirements. Unfortunately, to date China's UGS has not yet adopted CS technology. This paper focuses on the operation optimization scheme of UGS with CS technology as well as the economic benefits and carbon emission reduction effects of this technology. Firstly, a proxy model with consideration of CS is constructed to improve the operation mode of UGS, and then the operation parameters concerning the dual objective function of maximizing revenue and CS volume is optimized. Based on the range of geological parameters in China, Monte Carlo simulation is used to simulate 100,000 scenarios. The results show that by 2050 the total UGS revenue in China would reach 22.013 billion to 39.423 billion US dollars, and the total CS volume would reach 26.374 million to 54.018 million tons, approximately the total carbon emissions of China's Qinghai Province in 2018. Finally, policy recommendations are provided. • A new carbon storage operation method is presented for underground gas storage. • A proxy model is built to optimize the profit of underground gas storage. • The potential of carbon sequestration is estimated for underground gas storage. [ABSTRACT FROM AUTHOR]

Long-haul heavy-duty freight sector has always been relying on diesel fuel and hard to decarbonize. Hydrogen fuel-cell trucks (HFCTs) can play a critical role in substituting the diesel trucks and achieving carbon neutrality in freight sector. However, the extremely high cost has impeded their penetration. This paper proposed that government could harness freight platform to promote HFCTs by issuing the platform licenses with strings attached that priority dispatch and commission discount have to be provided to HFCT drivers. To simulate the effects of the proposed policy instruments, an optimization model was developed and applied. The results validated the ability of both priority dispatch and commission discount to promote HFCTs' penetration. And combining the two mechanisms together can at most decrease the need for subsidy by 79%. Then the environmental effects were evaluated and the obtained emissions abatement cost ranges from 584 to 3712 RMB/t, which significantly exceeds the current carbon price in China. Besides, sensitivity analyses of key parameters have been conducted. It is found that the effects on promoting HFCT penetration of increasing subsidy is marginal diminishing. Business model innovation as well as further cost reduction of trucks and hydrogen fuels through technology progress are still in need. • The platform-based policies are proposed to develop hydrogen trucks. • Priority dispatch and commission discount can promote hydrogen trucks' penetration. • The CO 2 abatement cost of the proposed policies ranges from 584 to 3712 RMB/t. • The effect of subsidy on hydrogen trucks promotion is marginal diminishing. [ABSTRACT FROM AUTHOR]

A dual-carbon target (i.e., carbon peak and carbon neutrality) has been a critical external factor for the usage of China's fossil energy in the future. As the lowest-carbon fossil energy source, the uncertainty of China's natural gas usage is much higher than that of coal and oil. Thus, a detailed analysis of China's future natural gas consumption (NGC) under the dual-carbon target has attracted great attention from academia. This paper constructs a system dynamics-based forecasting model for China's NGC, and predicts the trends of China's primary energy demand, natural gas demand, and carbon emissions under four scenarios of high-, medium-, low-, and business-as-usual transitions. The low transition scenario, which is in line with the actual situation of China, shows that: (1) primary energy consumption peaks around 2040 at approximately 7 billion tons of standard coal equivalent. (2) Carbon dioxide emissions peak in 2030 at approximately 10.6 billion tons of carbon dioxide, and "net zero" carbon emissions will be achieved in 2057 and 2059 under high and low carbon sinks, respectively. (3) NGC is expected to peak in 2038 at approximately 630 billion cubic meters. (4) Industrial gas is expected to peak around 2035 at approximately 450 billion cubic meters. • We predict medium- and long-term natural gas consumption in China. • We construct a system dynamics model considering the bind of dual-carbon target. • We apply scenario analysis to quantify the intensity of low-carbon transition. • We get results of prediction the peak natural gas consumption in China. [ABSTRACT FROM AUTHOR]

Bioenergy with carbon capture and storage (BECCS) is a key negative emission technology in response to climate change. The industrial chain of BECCS is composed of multi-agent participants: farmers, middlemen, enterprises. This paper fills a gap in BECCS research by establishing a tripartite evolutionary game model and conducting system dynamics simulation to analyze the participants' interaction and strategy choices on system equilibrium in supply chain of BECCS under vertical integration operation model, and further discussing the influence of policy incentives on BECCS. The results show that the willingness of both enterprises and middlemen participate in the cooperation is very low under current scenario. Therefore, appropriate incentives must be taken to promote commercial deployment of BECCS. From sensitivity analysis, the following useful references for practical applications of BECCS in the future are obtained: Compared with other factors, costs of carbon storage have a more significant impact on the evolutionary trajectories and are highly sensitive to evolutionary equilibrium. The government should subsidize carbon utilization and electricity tariffs, but could not provide an initial investment subsidy for BECCS retrofit. Vigorously developing middlemen and promoting the improvement of carbon trading market and carbon tax policies are also of great significance to implementation of BECCS. • We analyze Bioenergy with carbon capture and storage in vertical integration model. • The industrial chain of BECCS is composed of farmers, middlemen, enterprises. • A tripartite evolutionary game model is built to analyze multi-agent interaction. • Willingness of players participate in cooperation is low under current scenario. • Appropriate incentives must be taken to promote the deployment of BECCS. [ABSTRACT FROM AUTHOR]

To estimate the comprehensive impact of China's carbon trading policy launched in 2013 on carbon emissions, this paper conducts a quasi-natural experiment with the combination of difference-in-differences method (DID) and spatial DURBIN model (SDM), further analyzes the mechanism from the perspective of energy use, energy structure and energy efficiency. The empirical results show that, (1) The CET has reduced the carbon emissions in pilots since 2013 significantly. Carbon emissions in neighbouring regions of pilots are also reduced, which proves the existence of spatial spillover effects from CET. Compared with the direct part, the spatial spillover effect accounts for smaller proportion. Both the results of robustness and endogenous analysis support above conclusion. (2) The effect of CET on carbon emissions continues to increase over the long term, while the spatial spillover effect gradually decreases as distance increases. (3) The CET also contributes to the decline of carbon intensity. (4) The decline of fossil energy use is the main path to reduce carbon emissions, while the transformation of energy structure seriously hinders the CET to achieve carbon emission reduction in the long term. • The CET has spatial spillover effect on carbon emissions. • The spatial spillover effect of CET decays with distance. • The decline of fossil energy use driven by CET reduces carbon emissions. • The energy structure driven by CET hinders the carbon emission reduction. [ABSTRACT FROM AUTHOR]

Large-scale clean energy deployment and energy consumption electrification are important measures for China to respond to severe climate challenges and achieve carbon neutrality goals, and the development of lithium-ion battery storage technology is essential to enable clean energy transition. Using three-stage DEA and Tobit model, this paper evaluated the real technological innovation efficiency (TIE) of China's lithium-ion battery listed enterprises (CLBLEs) during 2009–2018, and explored how external environment and enterprise management factors influence the TIE. The results demonstrate that there exist inefficiency problems of the TIE of CLBLEs due to the diseconomies of scale. The average TIE of CLBLEs is low, at 0.39. The stated-owned enterprises, large-scale enterprises, and downstream enterprises have the highest TIE, and mainly concentrated in eastern region. For external environmental factors, regional economic level and government subsidy promote TIE. While for internal enterprise management factors, firm size, financial leverage, profitability, and employee quality significantly promote TIE. Thus, for policy makers, strengthening the implementation of industrial support policies, enhancing industrial agglomeration, and promoting the sharing of innovative resources are conducive to improving the scale efficiency of CLBLEs. In addition, improving management capabilities and personnel composition is also an important direction to promote the TIE of CLBLEs. • A three-stage DEA model was used to evaluate the real TIE of CLBLEs. • Using the SFA model to examine the impact of external environmental factors on TIE. • Using the Tobit model to analyze the impact of internal management factors on TIE. • The average TIE of CLBLEs is relatively low at 0.39 caused by diseconomies of scale. • REL, SUB, SIZ, LEV, ROE and EDU can effectively improve the real TIE of CLBLEs. [ABSTRACT FROM AUTHOR]

China is committed to seeing its peak carbon dioxide emissions before 2030 and then its carbon neutrality before 2060, which further highlights the importance of China's energy transition. On the basis of clarifying the logic of analysis, this paper clearly defines the objectives of both the low-carbon pathway and the green pathway, scientifically identifies the incentives when choosing the green & low-carbon pathway in China's energy transition, tentatively constructs an "Incentive-Driven Analysis Model for Green & Low-carbon Transition", and quantitatively studies the driving effects of five-dimensional incentives. The econometric methodology is applied for empirical analysis using data from 2000 to 2019 for some reason, and the variable values are measured. The results show that: (1) In terms of structure, the institutional incentives are stronger than others, while the "Dual Circulation" incentives are becoming more and more important; (2) In terms of mode, judged by the vector characteristics, obvious differences in "process continuity" and "functional consistency" can be seen among different incentives; (3) In terms of effect, even the same driving force will have different functional attributes in different stages, especially in the "gear shift period" and the "gear shift acceleration period". The main contributions can be summarized as follows: Theoretically, the "low carbon transition" and the "green transition" are clearly distinguished, while a framework with five dimensions for energy transition analysis is introduced for the first time. Practically, the effectiveness of different incentives for given periods is clearly explained from the perspectives of direction, intensity and timeliness, which provides reference for government decision-making. • A novel analysis framework with five-dimensional incentives is built. • Driving forces are analyzed by econometric methodology. • Incentive-Driven Analysis Model for Green & Low-carbon Transition is constructed. • Empirical analysis for China's energy transition is studies within two different periods. [ABSTRACT FROM AUTHOR]

Nowadays, coal consumption is still dominated in China's energy structure, while China aggressively wants to achieve the goal of carbon neutrality in 2060. The substitution of coal consumption will be the first step to the goal. This paper simulates the scenarios of coal resource tax and investment in renewables by applying China Energy-Environment-Economy Analysis (CEEEA/CGE) model. The simulation results show the different mechanisms between the tax and the investment. In general, the impact of coal resource tax comes relatively early and is an effective way to reduce coal consumption in the short term. Renewable energy investment is a long-term, slow, and fundamental way to substitute coal consumption. However, for a long time, renewable energy should be the main driving force of carbon emission reduction. Consequently, we suggest that the process of coal substitution can be carried out through the way of "tax priority in the early stage and investment in the later stage". • Two kinds of policies are simulated: resource tax and renewable investment. • The impact mechanism of resource tax and renewable investment is different. • Tax is a quick re-act way for coal substitution, but lack of long-term capacity. • China should applies multiply ways to substitute coal consumption effectively. [ABSTRACT FROM AUTHOR]

Energy conservation was crucial for operating one industrial power device unit, because the better energy management was beneficial for decreasing the cost during the operation. On the other hand, in a carbon-neutral context, decreasing the Greenhouse gas (GHG) emission was as important as the energy conservation. In this paper, the direct method of the evaluation on the fuel consumption for the energy management was investigated. The fuel consumption factor for the energy conservation was studied in terms of ten different types of the single fuel consumption factor, the average value of the single fuel consumption factor, and the total fuel consumption factor. The result showed that the maximum of the fuel consumption factor was from the backpressure in the turbine part. The fuel consumption factor decreased from 12.65 g/kWh to 9.23 g/kWh after the optimization during the operation. The effect for the energy conservation could reach over 80%, and the cost saving for the optimization could be over 4.65 million US dollars for one year on one power station in China. the goal on the analysis of the fuel consumption factor was controlling the use of the coal, and thus also controlling the CO2 emission. • The fuel consumption factor was proposed and studied. • The optimization for the energy conservation was investigated. • The carbon neutral context for the carbon emission was discussed. [ABSTRACT FROM AUTHOR]