Search

As the global shipping industry experiences rapid expansion, the imperative to address greenhouse gas emissions and environmental impact becomes increasingly paramount. Hydrogen has emerged as a pivotal and eco-friendly energy source, offering a pathway towards carbon neutrality and a complete zero-carbon transition in maritime operations. However, the widespread adoption of hydrogen-powered ships hinges on the establishment of robust regulations and technical standards. This paper conducts a comprehensive examination of hydrogen fuel cell (FC) technology in ships, scrutinizing the role of international classification societies and exploring existing standards and regulations within the maritime industry, specifically centered around hydrogen energy. The study outlines a strategic developmental roadmap for a green shipping hydrogen energy system tailored for hydrogen FC-powered ships in China. Emphasizing the differences in hydrogen application between fuel cell vehicles and ships, the paper elucidates technical challenges unique to hydrogen FC-powered ships. Furthermore, it proposes a visionary framework for future technical standards, advocating for the creation of a ship-based hydrogen energy standard system, the development of core technical standards, and a heightened focus on safety regulations. Through comprehensive analysis and compelling argumentation on hydrogen fuel cell ship technology and standards, this paper underscores the indispensable role that technical standards play in propelling the advancement of environmentally friendly shipping. Beyond serving as an informative resource, the paper aims to provide valuable guidance and direction for the future demonstration, application, and promotion of hydrogen fuel cell ship technology. Ultimately, it underscores the pivotal role of technical standards in advancing sustainable maritime transportation. • Analyze hydrogen energy technical standards from the production, storage, safety. • Comparison of hydrogen energy technical differences between vehicles and ships. • Outline the unique challenges of applying hydrogen technology to ship operations. • Constructed a technical standard framework for future hydrogen energy ships. [ABSTRACT FROM AUTHOR]

Renewable Portfolio Standards (RPS) and carbon emission trading (CET) system are the top-level system design of China's energy low-carbon transformation, which have great strategic significance for realizing the "carbon peak in 2030 and carbon neutrality in 2060". At present, China's tradable green certificates market and CET market are still in the initial stage. The implementation single system may have diverse trials and errors in its initial stage, and the market activity and transaction frequency are low. Therefore, this paper aims to explore whether the synergistic effect between the two systems can effectively promote China's energy low-carbon transformation. This paper establishes the system dynamic model of the synergistic effect between the RPS and CET in China's electricity market to reveal the influence mechanism and the synergistic effect. The results show that: (1) There is a positive synergistic effect between the RPS and CET, which will change with the institutional parameters. (2) The simultaneous implementation of the RPS and CET can effectively stimulate market vitality and promote the development of the renewable energy industry. (3) Higher quota and lower benchmark price can optimize power source structure, and improve social welfare and institutional performance. [ABSTRACT FROM AUTHOR]

Hydrogen is not only an important energy carrier needed to achieve the global goal of carbon neutrality, but also an important way of international energy trade in the future. This research analyzes the advantages and challenges of China's participation in international hydrogen trade in detail, proposes the possible routes of China's international hydrogen trade, and proposes specific measures to enhance China's participation in international hydrogen trade. This paper proposes that China should take green hydrogen as its development direction, and guide the development of China's hydrogen trade with the principle of blue green cooperation and gray hydrogen withdrawal. In the future, China's hydrogen trade forms will be diversified, and the types of trade will cover the entire hydrogen energy industry chain. Therefore, China should accelerate the overall deployment of hydrogen trade and the construction of hydrogen trade infrastructure, and build a more sophisticated hydrogen economy. [Display omitted] • The advantages of China's international hydrogen trade are analyzed. • Discussed China's possible international hydrogen trade routes in the future. • The obstacles affecting China's hydrogen competitiveness are analyzed. • Put forward suggestions to promote China's international hydrogen trade. [ABSTRACT FROM AUTHOR]

With rapid industrialization, rising fossil fuel consumption, and environmental concerns, developing clean and green energy is an inescapable option. Hydrogen has emerged as a significant potential energy carrier and a viable future replacement fuel for fossil fuels due to its renewable and pollution-free properties. Previous review papers have significantly contributed to the body of literature on the various technologies for producing hydrogen by revealing key insights into their working principles and conditions, as well as the economic and environmental aspects. In addition, they also highlighted the potential pathways to enable the application of these technologies in the context of carbon neutrality. However, these studies have not broken down the evolutionary patterns and developmental progress of either fossil fuel-based or renewable energy-based technologies used to produce hydrogen. In addition, the currently available literature does not contain the most recent research that focuses on the evolution and life cycle of each technology category from a chronological point of view. The key drivers, countries/regions, and their contributions to the field's development have received little attention. As a result, it is critical to monitor technological advances in hydrogen energy production and investigate the key enablers of these advancements. Against this backdrop, the current study employs patent analysis tools to achieve four primary goals: (1) to track the development trends in the field of hydrogen production from 2000 to 2019; (2) to identify and compare the recent development trends in the last five years according to the feedstock, i.e., fossil fuel, water, and biomass-based technologies; (3) to predict the technology life cycle of the two main groups of hydrogen production technologies (fossil and renewable); (4) to identify and compare the key drivers of hydrogen production technologies from a statistical standpoint. The findings of the study may aid in identifying technical prospects in the field of fossil and renewable-based hydrogen production, and decision-makers may use them as a reference in developing a strategic plan for future technological growth. • Patent review on hydrogen production technologies from 2000 to 2019. • Japan, US, China are the leading countries in the field. • Recent developments are focused on renewable energy-based technologies especially water. • Technology maturity rate of renewable-based technologies is about 57%. • R&D expenditure strongly promotes hydrogen production innovations. [ABSTRACT FROM AUTHOR]

The ever-increasing challenges related to water security and climate mitigation underscore the pressing need for forward-thinking systems planning tools to drive urban sustainability transitions. In this study, we propose a novel city-level multi-objective planning framework that explores the nexus between carbon trading and water management, with the aim of facilitating water-efficient urban industrial restructuring. The framework integrates cap-and-trade mechanisms into a two-layered optimization model, creating an integrated approach to optimizing carbon emissions and generating economic opportunities for improving water efficiency. To illustrate the potential application of this framework, we conducted a case study focusing on Dongguan City, a water-stressed industrial metropolis in southern China. The results illustrate potential synergies between water planning strategies and carbon trading schemes, which could be harnessed to enable targeted reductions in water usage and carbon emissions. Furthermore, our findings identify the textile, apparel, and paper products manufacturing industries as primary candidates for strategic production scale reduction, emphasizing the importance of sustained support for the development of the computer and electronic manufacturing sector as a catalyst for urban sustainability transitions. By pioneering this new nexus-based perspective, our study offers valuable insights into long-term strategic planning for a low-carbon and resource-efficient urban economy. • Synergizing carbon trading and water management within a novel integrated planning framework. • Implementing resource-efficiency-driven optimization for water- and carbon-intensive manufacturing sectors. • Gaining insights into the specific roles of key manufacturing sectors in water management and carbon trading. • Introducing carbon trading systems may help in promoting water-efficient industrial restructuring. [Display omitted] [ABSTRACT FROM AUTHOR]

To achieve the carbon peaking and carbon neutrality goals, China promoted county-wide photovoltaic projects (CWPVs) in 2021. A large number of distributed photovoltaic (DPV) installations have expanded the scale of prosumer. It also brings the inequity problem of prosumer, distribution network system operator (DSO) and consumer--DSO and consumer bear the costs such as access cost and depreciation of stock investment caused by DPV access. Combined with China's current electricity tariff system and the promotion of photovoltaic scale development, this paper proposes a standby fee model based on the principle of "beneficiary apportionment". In this model, the standby fee mechanism for self-owned power plants is applied to DPV to reduce the implementation cost of the mechanism, and the principle of "beneficiary apportionment" is adopted to ensure the profitability of DPV. This paper takes the CWPV in Hunan Province, China as an example, calculates the standby fee under various electricity metering methods, and determines the most appropriate standby fee by considering factors such as output uncertainty of DPV. Finally, the difficulties in the implementation of standby fee are sorted out. [ABSTRACT FROM AUTHOR]

Global environmental problems are worsening. Among various regulatory measures, market-oriented approaches are most favored by governments worldwide. Using provincial panel data from 2004 to 2020, a multi-period DID model was hereby constructed to empirically study the pollution reduction effects of the pilot policy for carbon emissions trading in China. Findings of this paper could be listed as follows: (1) The pilot policy has achieved notable reductions in waste gas and solid waste, although its effect on wastewater pollutants has been less pronounced; (2) Pollution reduction in the pilot regions can be achieved by optimizing the energy consumption structure; (3) Significant variations in pollution reduction effects are observed between the Northern and Southern pilot regions, with notably stronger policy effects in the north across various pollutants compared to the south. Overall, this paper offers pertinent policy recommendations to aid the Chinese government in enhancing its carbon market. [ABSTRACT FROM AUTHOR]

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]

Compared to cast-in-situ construction, prefabricated construction reduces the generation of construction waste; however, construction waste cannot be entirely eliminated through prefabrication and can be generated at each stage of its life cycle. This paper generates a system dynamics model, comprising two causal-loop diagrams and one stock-flow diagram, to simulate the effectiveness of policies on decarbonizing prefabricated concrete building waste. The model can predict the annual and total construction waste, along with the associated carbon emissions, under different policy scenarios in China by 2030. This paper focuses on prefabricated concrete buildings in China, with specific attention to the wastage of concrete, bricks, mortar, and metal. In single-factor scenario simulations, increasing landfilling fee is the most effective policy for waste decarbonization, potentially reducing carbon emissions by 31%. Increasing prefabrication rate and enhancing regulation degree at the design phase of prefabrication can directly reduce prefabricated building waste generation, subsequently resulting in an 18% and 7% carbon emissions reduction. Multi-factor scenario simulations demonstrate that the simultaneous application of all four policies is most effective, achieving a 44% reduction in carbon emissions. This research establishes a theoretical framework for prefabricated concrete building waste management and provides the Chinese government with practical insights on optimizing policies for waste decarbonization in the dynamic landscape of prefabrication. • This paper develops the prefabricated building waste generation and disposal systems. • The model predicts the construction waste and associated carbon emissions by 2030. • Raising landfill fee is an effective policy for decarbonizing construction waste by 31.06%. • Prefabrication rate reaching 100% can reduce 18.04% of carbon emissions from waste. • Applying all policies is most effective, achieving a 44.34% carbon emissions reduction. [ABSTRACT FROM AUTHOR]

With the growing global energy demand and limited production of conventional crude oil, the extraction of unconventional heavy and extra-heavy oil is receiving unprecedented attention. China is the fourth largest producer of heavy oil. High viscosity and complex formation environments increase the difficulty of exploiting heavy oil. To alleviate the economic cost and environmental pollution pressure brought by heavy oil production, China has achieved significant advancement in the innovation of heavy oil recovery, including accelerating the transformation of thermal technology to non-thermal technology and the use of new energy technology to achieve the goal of low-carbon economy and green environmental protection. Based on the background of heavy oil in China, this paper recharacterizes the high-viscosity mechanism of heavy oil. From different aspects, including basic principles, main characteristics, applicability, limitations, and challenges, this paper comprehensively reviews existing heavy oil recovery technologies, including thermal recovery, in-situ upgrading, cold recovery, and new energy technologies. Currently, in China, the main target of heavy oil recovery is achieving the "carbon peaking and carbon neutrality" goals, which can be described as low energy consumption, low emission, and low pollution. To facilitate the low-carbon transition in the extraction of heavy/extra-heavy oil and attain environmental sustainability goals, it is essential to increase the proportion of non-thermal factors in thermal recovery technologies, develop efficient in-situ catalysts, adopt clean cold extraction techniques, and advance the development of new energy technologies. [ABSTRACT FROM AUTHOR]

The fundamental way for China to achieve carbon peak and carbon neutrality is to continuously improve the penetration of renewable energy (RE) in the power system and establish an electricity mix dominated by RE power. According to China's 14th Five-Year Plan, the proportion of non-fossil energy power generation should reach about 39% by 2025. However, the impact of the increase in share of RE power on carbon emissions of the electricity sector remains to be estimated. To this end, the purpose of this paper is to capture the nonlinear characteristics of RE on electricity-related carbon emissions by using panel smooth transition regression (PSTR) model and provincial panel data covering the period 1991–2020 under the background of provincial RE quota system. The estimation results indicate that, (i) in the four transition variables of PSTR model such as the installed capacity of power generation, substation equipment capacity, total electricity consumption and total power generation, the nexus between RE deployment and electricity-related carbon emissions was detected as nonlinear. (ii) The heterogeneous RE carbon abatement effect is reflected in its increasing penetration in provincial power systems. (iii) Carbon abatement performance of RE generation decreases in the negative range with the increase of transition variables. (iv) The estimation coefficient of RE is positive at the higher value of the transition variable in the PSTR model of carbon emissions per capita. As a result, the RE quota with the best emission abatement performance should be designed based on the provincial power resource endowment and the medium and long-term expected electricity consumption. [ABSTRACT FROM AUTHOR]

China's carbon peaking and carbon neutrality goals present a significant challenge for coal chemical technology, which is critical to securing the energy structure. Combining coal chemical industry technology with new energy is an effective approach to transform the development of the coal chemical industry. This paper proposes and studies a novel coal-to-methanol (CTM) technology of gasification integrated solid oxide electrolysis cell (SOEC). SOEC electrolytic hydrogen production technology is an advanced electrolytic water technology with the advantages of large scale and high efficiency, which is very suitable to be combined with industrial technology and can solve the painful problem of H 2 deficiency in the conventional coal to methanol process. In this study, from mechanistic analysis and model simulations, it is observed that by increasing the SOEC capacity, the novel CTM system can create more methanol at the same coal consumption and simultaneously reduce CO 2 emissions. The novel CTM system can produce up to 2.2 times more methanol and reduce CO 2 emissions by 94% by replacing the water-gas-shift (WGS) process with the SOEC unit. The novel CTM increases energy consumption. In addition, the novel CTM technology will effectively improve the economics of coal to methanol, taking into account the carbon tax. At the methanol price of 2900 RMB/t and SOEC capacity of 250 MW, the economic benefits of novel CTM were 2.1 times greater than CTM technology. • Propose a novel coal-to-methanol technology of gasification integrated electrolysis. • The novel coal-to-methanol technology can produce more methanol and reduce CO 2 emissions. • The novel technology can offer better economics when methanol price is higher than 2900 RMB/t. [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]

[Display omitted] • Measure carbon emission inequalities (CEIs) of urban agglomerations under rapid urbanization. • Identify the key factors determining CEIs within the three urban agglomerations. • Account for the differences between adjacent or distant urban agglomerations. • The declining CEI is mainly due to changes in industrial structure and economic development. • CEI in the upper reaches of the YREB increases due to the changes in energy intensity. Increasing countries are articulating ambitious goals of carbon neutrality. However, large inequalities in regional emissions within a country may hinder progress toward a carbon–neutral future, as the unequal distribution of reduction responsibilities among regions could impair just transition and exacerbate uneven development, which necessitates an in-depth understanding of the mechanism of multi-scale carbon inequalities within country, region, and city. Yet, the evolution of carbon inequalities within urban agglomerations and the differences between adjacent or distant urban agglomerations have not been well understood, especially in countries undergoing rapid urbanization. Using the data of 89 cities in China's Yangtze River Economic Belt (YREB) during 2006–2021, this paper quantifies carbon emissions inequality (CEI) at different scales in a systematic regional-urban agglomeration-city hierarchical structure. Then, under the integrated mean logarithmic deviation-logarithmic mean Divisia index (MLD-LMDI) decomposition framework, multi-scale CEIs are perfectly decomposed into six interrelated drivers, i.e., industrial emission structure, energy emission intensity, industrial energy mix, energy intensity, industrial structure, and economic development. The results show that economic development, energy intensity, and industrial energy mix disparities are the main determinants accounting for CEIs at different scales. The decreasing CEI in YREB is mainly due to the changes in industrial structure and economic development, while the energy intensity effect partially hinders the mitigation of CEI. In the upper reaches of the YREB, the energy intensity effect accounts for over 94% growth of CEI during 2006–2021, while the decline in CEIs in middle and lower reaches is primarily caused by the effects of industrial energy mix and industrial structure, respectively. Further spatial decomposition analysis reveals more refined city-level heterogeneous effects and emphasizes the prioritized emission reduction direction for each city. This paper offers implications for reducing carbon inequality and insights into coordinated carbon emissions mitigation at the regional level for a carbon–neutral future. [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]

Carbon lock-in has become a major obstacle to green development in all countries, and carbon unlocking (CUL) is of great significance in accelerating the process of carbon neutrality worldwide. Based on the panel data of 292 prefecture-level cities in China from 2006 to 2020, this paper constructs a PSM-DID model based on machine learning to empirically test the impact of LCCP policy on urban CUL. The regression result shows that the low carbon city pilot (LCCP) policy significantly increases the level of CUL by 1.25 % in the pilot cities, which is still valid after range of robustness tests, and the mechanism analysis shows that green innovation and green habits are important ways for the policy to affect CUL. Based on the generalized random forest (GRF) algorithm, we further find that the policy can increase the CUL level by 0.6 %, and the average treatment effect (ATE) of the sample is concentrated between 0.004 and 0.006, which exhibits obvious heterogeneity. This paper chooses population quality, openness level and industrial structure as heterogeneous factors, which are finally found to have a U-shaped or inverted U-shaped relationship with ATE. This study provides useful insights for China and other countries to break the carbon lock-in and realize green development. • Low-carbon city pilot policy can effectively promote urban carbon unlocking. • Causal forest model is used for causal inference based on generalized random forests algorithm. • The propensity score is calculated by machine learning. • Generalized random forest is used for heterogeneity analysis. • Low-carbon city pilot policy transmits policy effects through green innovation and green habits. [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]

• City level data in China was used to examines the effects and mechanisms of digital finance on residential carbon emissions. • In terms of the structural composition of carbon emissions, digital finance mainly increases residential carbon emissions by affecting electricity consumption and transportation in China. • Digital finance can increase residential carbon emissions through the consumption effect and employment effect. Reducing residential carbon emissions is important for all countries to achieve carbon neutrality. For such task, the impact of digital development of finance on residential carbon emissions cannot be ignored. This paper estimates residential carbon emissions in 186 Chinese cities from 2011 to 2019 and examines the effects and mechanisms of digital finance on residential carbon emissions. The results show that digital finance exacerbates residential carbon emissions in China. In terms of the structural composition of carbon emissions, digital finance mainly increases residential carbon emissions by affecting electricity consumption and transportation in China. Mechanism analysis shows that digital finance can increase residential carbon emissions through the consumption effect and employment effect. [ABSTRACT FROM AUTHOR]

Carbon trading is widely used as a carbon finance instrument to promote green transformation. This paper focuses on carbon trading's impact on the bond spread for high-carbon enterprises. Using variation in carbon trading access due to pilot policies in China, we find that bonds issued by high-carbon enterprises participating in the carbon trading pilots have lower spreads. Furthermore, the results suggest that carbon trading reduces bond spreads by encouraging high-carbon enterprises to improve their environmental performance. Another channel is the information asymmetry between bondholders and enterprises. More active carbon markets provide investors with more information about enterprises' motivations for reducing carbon emissions, leading to a greater reduction in bond spreads. In addition, the impact of carbon trading is more significant in local SOEs, high-innovation enterprises, and longer-term bonds. Our research helps us understand the importance of carbon trading in achieving a low-carbon economy. [ABSTRACT FROM AUTHOR]

• A novel application mode of CSP with HEHP technology is proposed. • The flexible operation benefits of CSP with HEHP technology in the IES are analysed and quantified. • The carbon emission trajectory of the IES containing CSP with an HEHP device is depicted. • CSP with HEHP technology increases the utilization of solar energy. • A rational combination of the hydrogen and thermal energy storage capacities are necessary. The efficient integration of renewable energy with hydrogen storage is an important means for China to achieve carbon neutrality. Concentrated solar power (CSP) is an emerging technology for solar energy utilization that combines the advantages of power generation and energy storage. However, CSP has not been fully exploited because of the high generation cost and an incomplete market mechanism in China. The heat collected by CSP can be utilized for high-temperature electrolytic hydrogen production (HEHP), which is an efficient technology for hydrogen production and storage, and reducing carbon emission. Thus, a low-carbon operating mode for an integrated energy system (IES) consisting of wind, solar and hydrogen energy is proposed in this paper. First, an optimal operation model of electricity-heat-hydrogen coupling for an IES containing CSP and HEHP is established. Second, the effect of CSP with HEHP on the total operation performance of the system is evaluated from the aspects of the system economy, renewable energy utilization, and carbon emission. Finally, the model is validated by a case study of an island IES, and an optimal sizing for hydrogen energy storage and thermal energy storage of CSP is determined. The results show that CSP with HEHP can effectively improve the utilization rate of solar energy and reduce the carbon emissions of the system, offering an approach for carbon reduction planning and the operation of CSP in electric-hydrogen energy systems. [ABSTRACT FROM AUTHOR]

Accurate short-term prediction of bioenergy power generation structure can optimize the bioenergy structure and help achieve carbon neutrality. However, there are currently few related studies, and most of them present long-term predictions on the development potential of bioenergy, which cannot meet the modeling requirements of predicting structure. Hence, the Fractional-order-accumulation grey Compositional data Model with Particle swarm is proposed in this paper (PFCM (1,1)) for forecasting bioenergy power generation structure. The proposed model satisfies the modeling requirements by introducing the fractional accumulation operator to ensure the prediction accuracy, and constructing the spherical mapping space to reduce the data dimension. The empirical studies prove that the newly developed model performs better than other models, which is successfully employed to predict bioenergy power generation structure of China for 2020–2024. The results show that the share of renewable municipal waste in bioenergy power generation will exceed that of solid biofuels by 2023 and the share of biogas power generation has not changed much. Furthermore, although the total amount of bioenergy power generation in China is growing rapidly, unbalanced development and small share of power are two important challenges. [Display omitted] [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]

As major strategic development areas in China, the provinces around the Yangtze River are facing the pressure of large aggregate CO 2 emissions and high per capita CO 2 emissions. The study on the pathway of reducing CO 2 emissions and increasing carbon sequestration will help China better clarify the ways realize the goals of carbon peak and carbon neutrality as soon as possible. In this paper, the extended STIRPAT model and OLS regression were used to establish a prediction model to estimate the CO 2 emissions during 2010–2060 under different scenarios. Meanwhile, the InVEST model was used to estimate the carbon sequestration, and the comparison with the CO 2 emissions was analyzed. The results show that Qinghai and Yunnan have achieved the goal of carbon neutrality in 2010. Under the low-carbon and energy-saving scenario and the baseline scenario, all provinces within the study area are anticipated to attain their emissions peak by 2030 or earlier, and the CO 2 emissions peak value of the whole study area is 3111 Mt and 3199 Mt, respectively. While under the high emissions scenario, only Chongqing and Qinghai will reach the emissions peak in 2030, and the whole study area will reach the emissions peak in 2040, with peak value of 3470 Mt. Under the three scenarios, the whole study area cannot achieve carbon neutrality before 2060. Only Sichuan and Hubei can achieve carbon neutrality in 2050 and 2060 under the low-carbon and energy-saving scenario. All provinces and municipalities in the lower reaches of the Yangtze River are facing huge pressure of emissions reduction. The research reveals that the goals of carbon peak and carbon neutrality should be achieved by developing clean energy, transforming industrial structure, increasing carbon sequestration and improving carbon emissions trading system. [Display omitted] • The CO 2 emissions showed a pattern of increase during 2010–2020. • The whole study area will achieve carbon peak by 2040 or earlier. • The whole study area cannot achieve carbon neutrality before 2060. • The realization pathway of carbon peak and neutrality was proposed. [ABSTRACT FROM AUTHOR]

• Provide an in-depth evolution analysis in the practical development of shore power. • Conduct a systematic bibliometric analysis of pivotal shore power-related publications. • Coordinate practical shore power applications with academic research to highlight the predominant trends. • Divide shore power research into four categories to understand its progress and trends. • Establish well-reasoned remarks, implications, and agenda for future studies. Shore power not only reduces ship emissions and noise in berthing but also has shown practical implications for maritime competitiveness. However, the existing literature and industry reports reveal that a limited number of ships have access to shore power. This highlights the need for research into the constraints faced by the sector and the development of solutions to enhance its adoption. Addressing these issues will enable the port and shipping industries to enjoy the associated benefits. Currently, existing research on shore power remains dispersed, yet it fully addresses such questions and lacks an integrated framework, making it challenging to extract pivotal insights. This paper aims to conduct a state-of-the-art review of shore power by the Web of Science Core Collection and Scopus databases as a pivotal solution to shipping emissions reduction in ports and advancing the maritime sector towards carbon neutrality. This analysis is grounded in a bibliometric analysis of existing literature on this topic, with a focus on the need to devise robust strategies to fully harness the potential of shore power for carbon neutrality. The valuable findings are revealed, including (i) The adoption of shore power by ports is predominantly propelled by regulatory mandates and incentives, inclusive of government subsidies in leading regions such as China, the U.S., and Europe; (ii) Due to the implementation of Emission Control Areas and carbon neutrality regulations, an increasing number of port operators in Europe are turning to shore power to fulfil both the governmental or industrial requirements, especially regarding cruise ships; (iii) The literature on shore power primarily delves into four main research areas: the inherent features of shore power, emission inventory assessments, practical applications of shore power, and energy management strategies; and (iv) Emerging directions in shore power research include cooperative optimisation among stakeholders, integration of new technologies into shore power, a holistic evaluation of the multifaceted advantages of diverse emission reduction strategies, and critical examinations of any unintended consequences stemming from shore power adoption. They offer invaluable insights on enhancing the adaptation and effectiveness of shore power. [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]

Given the phase-out of subsidies, the Chinese government has issued a series of non-subsidized industrial policies to support the development of the power Lithium-ion Battery (PLiB) industry, recognized as pivotal for achieving carbon neutrality in the transportation department. However, existing literature provides limited evidence on the contribution of non-subsidized industrial policies, particularly to the PLiB industry. To bridge this gap, using data of 31 PLiB listed firms and 279 relevant non-subsidized industrial policies, this paper analyzes the effects of non-subsidized industrial policies on the global value chain (GVC) embedding position. The results reveal that non-subsidized industrial policies significantly raise the GVC embedding position of Chinese PLiB firms, and the positive effects are prone to increase over the research period. Further investigation shows that there is heterogeneity among PLiB firms, with the raising effects on the GVC embedding position being more significant in eastern and middle PLiB firms, private PLiB firms and midstream PLiB firms. The mechanism verification shows that non-subsidized industrial policies raise GVC embedding position of PLiB firms through technological innovation effect and scale economy effect, while competitiveness effect does not give full play. These findings provide important recommendations for better design of the industrial policies to improve the international competitiveness of PLiB industry and other strategic emerging industries. • This study investigates the effects of industrial policy from the perspective of non-subsidized industrial policies. • Non-subsidized industrial policies raise global value chain embedding position of China's Power Lithium-ion Battery firms. • Mechanisms of technological innovation effect, scale economy effect and competition effect are verified. [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]

China's energy transformation has been accompanied by potential energy security issues. However, the influence degree and driving mechanism behind this phenomenon remain unclear. In this paper, we developed a complex network-based technical resilience assessment framework and quantified both the historical trajectory and the prospective pathway of energy technical resilience in China. We proposed to reveal the relationship between cleaner energy supply and technical resilience by defining three energy technology resilience indicators: energy robustness, energy recovery rate, and energy performance loss. The results showed a consistent decline in energy technical resilience within China, predominantly characterized by an average diminution of 6.83% in energy robustness from 2010 to 2018. Taking carbon neutrality as a target, China's energy system transformation, characterized by increasing clean energy supply, leads to a significant improvement of 7.73% in energy robustness from 2020 to 2060. Conversely, the nationally determined contribution scenario exhibited negligible changes (±0.57%) in energy robustness, while a decline of 2.21% was noted under the business as usual scenario. Furthermore, energy robustness exhibited increments of 12.07%, 2.3%, and 4.17% for every 10% rise in the share of clean energy supply during 2020–2060, demonstrating greater resilience for cleaner energy systems against disruptions, including energy import interruptions, malicious attacks, and random failures. It has been concluded that enhancing the supply of clean energy can significantly contribute to bolstering China's energy technical resilience, while simultaneously addressing climate change concerns. • Network analysis is used to assess China's energy technical resilience. • Energy technical resilience is evaluated regarding robustness, recovery rate, and performance loss. • Energy system robustness significantly increases under carbon neutrality scenario. • Increasing clean energy supply strengthens resilience against shocks. [ABSTRACT FROM AUTHOR]

Wind and solar power are expected to play important roles in many countries to achieve carbon neutrality; however, their inherent instabilities pose significant threats to existing power grids. Because hydropower has been recognized as a viable compensatory resource for solar and wind energy uncertainties, many studies have sought to determine optimal scheduling strategies for hydro-PV, hydro-wind, and hydro-PV-wind systems. However, few studies have simultaneously considered the sizing and scheduling of large-scale hydro-PV-wind hybrid systems connected to long-distance transmission lines. Therefore, this paper develops a mathematical metric to measure the wind and solar output complementarity and incorporates it into a multi-objective sizing and scheduling model for a hybrid hydro-PV-wind system, in which resource complementarity, profit generation, system reliability, and power curtailment trade-offs are concurrently considered. The ɛ -constraint method is employed and decision makers' attitude parameters are introduced to transform the proposed model into its equivalent single objective form. A case study in China reveals that the maximum wind and solar power output complementarity rate can be at least 0.19 for the studied hybrid hydro-PV-wind system. The incorporation of wind enables the hybrid hydro-PV-wind system to provide 4.11% more load than a hydro-PV system. In addition, if 2% of power curtailment is permitted, 1.53% more load can be served and 14.9% higher profits can be earned. To better explore the application of hybrid systems, management recommendations are provided for system operators, the power industry, and management administrations. • Multi-objective sizing and scheduling method for the hybrid renewable system is proposed. • Mathematical metrics to measure wind and solar power complementarity is provided. • A complementarity rate of 0.19 can be reached with 100% reliable service and no curtailment. • Integrating wind power into the hydro-PV system can reliably serve 4.11% more load. • An optimal rather than minimal level of the renewable power curtailment is more efficient. [ABSTRACT FROM AUTHOR]

• Integration of blockchain characteristics into the collaborative carbon emission reduction game model of both the supply and demand sides of electricity is proposed to encompass source control and terminal suppression. • Blockchain is utilized to trace electricity types within the electricity market and to quantify the carbon emissions generated by the demand side of electricity. • By incorporating blockchain, users can actively engage in individual-level carbon trading to control and reduce carbon emissions. • Blockchain facilitates enhanced carbon emission reduction efforts by the power supply side. The task of carbon emission reduction is severe in the power industry in China under the national goal of "carbon peaking and carbon neutrality". The current carbon reduction is mainly based on supply side, but the effect is limited. To solve this problem, this paper proposed a coordinated supply–demand carbon emission reduction strategy based on blockchain technology. Based on the carbon emission reduction of complementary thermal power and renewable energy under the carbon trading mechanism of power supply side, users are made to participate in the individual level carbon trading mechanism with the help of blockchain technology, and the carbon emission reduction in power demand side is guided through the market mechanism, thus forming a supply–demand collaborative carbon emission reduction strategy of source side control and terminal inhibition. By analyzing the decision changes of both the supply and demand sides of electricity before and after the introduction of blockchain, quantifying the influence of blockchain on electricity quantity, electricity price and users' utility in turn, and establishing the personal carbon trading mechanism supported by blockchain, a game model of two-side interaction between supply and demand was constructed. The simulation results show that the collaborative carbon emission reduction strategy based on blockchain gives full play to the potential of carbon reduction in power demand side, and the personal carbon trading mechanism can better inhibit terminal carbon emissions, which is conducive to the deep carbon emission reduction of the power industry. [ABSTRACT FROM AUTHOR]

China has committed to peak carbon emissions by 2030 and become carbon neutral by 2060. Hebei, as a major energy province in China, has more challenging carbon peaking and carbon neutrality targets. Based on the extended STIRPAT model, this paper evaluates the time to peak carbon and post-peak carbon trend changes in Hebei province under different scenarios from 2020 to 2060. Based on the support vector machine model with particle swarm optimization, this paper evaluates the carbon neutral pathways under different scenarios in Hebei province from 2020 to 2060 in terms of forests, croplands, wetlands, grasslands and Carbon Capture, Utilization and Storage (CCUS). The results show that a monotonically flat trend without inflection point, a single-inflection-point plateau-period trend and a multi-inflection-point inverted U-wave trend occur after carbon peaks. Hebei Province can achieve carbon neutrality by 2060 under the policy scenario and the enhanced scenario, and the enhanced scenario is better. Comparing with existing studies, the innovation of this paper is to design different trends of changes after carbon peak, combining carbon absorption and carbon emission, and providing more diversified development paths for carbon neutral strategies through a more integrated perspective and multi-scenario comprehensive analysis. Therefore, In the future, Hebei Province should establish a platform for carbon emissions monitoring and carbon footprint assessment, and set up an early warning and assessment mechanism for carbon peaking, so as to prevent a rebound trend in carbon emissions after peaking. At the same time, it should introduce and develop carbon capture and conversion technologies and promote the low-carbon transformation of the industrial and energy sectors, thereby forcing the early realization of peak carbon. Pay attention to the role of forestry resources in carbon neutrality, increase carbon sink resources such as forests and wetlands, promote the development of CCUS, and enhance the implementation of the policy. [ABSTRACT FROM AUTHOR]

• Constructed an operation architecture of the coupling of energy supply and demand. • Established the comprehensive demand response mechanism based on time-sharing energy prices. • Established the minimum carbon emission cost economic scheduling model as an objective function. • The scheduling method could achieve the goal of low-carbon economic dispatch. Aiming at the problems of low energy utilization and environmental pollution in China's livestock and poultry breeding industry under the carbon peaking and carbon neutralization goals, this paper proposes an optimal scheduling model for multi-energy coupling integrated energy system with ladder-type carbon trading mechanism and demand response. First, based on the construction of a reward and punishment model with ladder-type carbon trading mechanism, this paper explores the potential interaction between the coupling ability of multiple heterogeneous energy sources and carbon emissions in consideration of the impact of carbon capture equipment on carbon emissions. Second, in view of the diversity and complexity of demands for agricultural energy supply, the energy supply side equipment model and the comprehensive demand response model of electricity, heat, and gas are established, and a low-carbon economic scheduling model of integrated agricultural energy system is proposed, aiming at minimizing the total operation cost of the system. Finally, the model is solved by CPLEX, and the coupling system of a 6-node power distribution network, a 6-node gas network, and a 4-node heat supply network is used to verify the effectiveness of the proposed model and method and optimize the operation of the integrated agricultural energy system. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of China's environmental regulations, with a focus on the green credit policy, on green innovation in pursuit of the "carbon peak and carbon neutrality" goal. Given the implementation of the 2012 Green Credit Guidelines, this paper employs the Difference-in-Difference Method (DID) and conducts a quasi-natural experiment to empirically examine the interactions among the central government, local governments, and high-pollution and high-emission enterprises by exploring the impact of green credit policies on green innovation of these enterprises. Relying on 4503 samples of 237 high-pollution and high-emission enterprises listed in the main board in China from 2003 to 2021, this study reveals that the green credit policy can improve green innovation of these enterprises. Specifically, this study explores the detailed mechanism through which the green credit policy enables these enterprises to increase their market concentration and then the monopoly profits, which in turn promotes their green innovative productivity. In addition, this paper also reveals how local governments' political and financial incentives may serve as positive and negative moderating factors, respectively, within the impact mechanism. This study has valuable implications for how to effectively formulate and implement environmental regulations by balancing the interests of the central government, local governments and enterprises. [ABSTRACT FROM AUTHOR]

Carbon trading market is a central policy tool for promoting cleaner enterprises' energy consumption and investment behaviors. It is crucial for enterprises to establish a green and low-carbon development model by clarifying carbon trading impact mechanism on enterprise behaviors and the interactive relationship between entities in the carbon market. China's contract-based carbon market is still in the development stage, the impact of the mainstream allowance mechanism and government regulation on enterprises' energy behaviors has yet to be determined. In view of this, this paper describes mathematical mechanisms of the influence of carbon prices and carbon quotas on enterprises' energy consumption and investment, and the evolutionary game model of government-enterprise behaviors is constructed, the evolution process and appropriate strategies of enterprises' energy behaviors in the development of the carbon market are discussed. This paper uses real data of China carbon market to simulate the model, it is found that strategies such as relaxation of carbon quotas and carbon subsidies dynamization are needed during the initial development of the market. In the mature stage of the carbon market, strategies are needed to increase the proportion of government carbon revenue and reduce its regulatory cost. The higher the initial willingness of government-enterprise, the better the effect of strategies and the constraints of public willingness. The model and results have theoretical implications for enterprises' energy transformation and government regulation, and provide a reference for the development of China's carbon market. • Constructed benefit-cost analytical framework for enterprises' energy behaviors. • Described mechanisms of carbon trading affecting enterprises' energy behaviors. • Constructed government-enterprise behaviors model by the evolutionary game theory. • Found new conclusions of enterprises' energy behaviors under the carbon market. [ABSTRACT FROM AUTHOR]

• Net carbon sink efficiency is used to measure carbon neutral performance. • A spatial spillover effect existed between urbanization and net carbon sink efficiency across counties. • Being surrounded by highly urbanized units resulted in positive effects on a unit's net carbon sink efficiency. • The impact of socioeconomic factors on net carbon sink efficiency is heterogeneous. Reducing carbon emissions and improving vegetation carbon sequestration (VCS) have long been recognized as the key ways to address the aim of carbon neutrality, requiring global effort and typical regional experiences. This paper develops an assessment framework for measuring the net carbon sink efficiency (NCSE) based on the concept of net-zero carbon sink to depict both carbon emission and VCS simultaneously. This paper primarily runs a spatial autocorrelation analysis to explore spatial characteristics of urbanization and NCSE of Yangtze River Delta urban agglomeration (YRD) in China from 2000 to 2020, followed by employs a spatial econometric model to investigate the spatial spillover effect of urbanization on NCSE. The results show that NCSE in YRD exhibits clear spatial disparities, descending from the southern part dominated by mountainous hills to the flatter northern region. The spatial evolutionary trend of urbanization and NCSE has a significant positive correlation, manifested as H-H and L-L agglomeration, covering most counties in southeast coastal areas and northern plains, respectively. The NCSE can improve even during the continued urbanization in YRD. Specifically, for every 1% increase in urbanization, NCSE will increase by 0.164%, of which 0.118% in direct and 0.046% in indirect growth, respectively. In addition, GDP per capita, industrial structure, technological progress, road area and direct foreign investment are benefit for NCSE. In contrast, population density, environmental regulation, and built-up area tend to decline NCSE. These findings may help to formulate the urban sustainable development planning and differentiated carbon neutrality policies. [ABSTRACT FROM AUTHOR]

Under the goal of "carbon peaking" and "carbon neutrality" in China, it is significant to explore whether emission reduction commitments contribute to carbon risk premium. Therefore, based on a sample of Chinese listed companies that publicly disclosed questionnaires in the CDP from 2009 to 2021, this paper empirically examines the relationship between emission reduction commitments and carbon risk premium and their formation mechanism. The results show that emission reduction commitments can effectively hedge the carbon risk premium, which pass several robustness tests. Specifically, the more comprehensive and ambitious the commitment is, the greater the suppression of the carbon risk premium. The mechanism test shows that disclosing emission reduction commitment information can reduce carbon risk by improving investor confidence and attracting political resources. Differences in enterprise emission levels, regional environmental regulation intensity and green financial development result in different risk-hedging effects of emission reduction commitments. Moreover, the greater the substantial pressure from stakeholders, the greater the tendency for firms to set up emission reduction commitments. Finally, the heterogeneity analysis reveals that confidence level of commitments has a significant impact on risk premium. Specifically, enterprises with SBTi validation, higher CDP ratings and higher target completion are more helpful in curbing carbon risk premium. Our findings contribute to corporate commitment to climate change and complement the carbon risk premium hypothesis. [Display omitted] The possible highlights of this study are as follows. • With the help of forward-looking information on emission reduction commitments, we re-examine the conclusion of the carbon risk premium and find that emission reduction commitments can effectively hedge the risk premium, enriching and developing the carbon risk premium hypothesis • This paper brings commitment levels and carbon emission levels into a unified analytical framework to study the correspondence between emission reduction commitments made under pressure to reduce emissions and the carbon risk premium, providing micro evidence for solving the mystery of the carbon risk premium. • Measure emission reduction commitment indicators from various angles, making the data on emission reduction commitments more objective and scientific. [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]

Faced with the challenges posed by the Paris Agreement targets, biomass co-firing offers an efficient measure to decarbonize coal-fired power generation. Although economic burden of biomass co-firing has severely limited the large-scale application, effective CO 2 emission trading system has the capability to subsidize and incentivize. Existing studies related to biomass co-firing under CO 2 emission trading system fail to consider multiple decision makers and uncertain decision-making environment. To address these limitations, this paper proposes a bi-level model for coal power decarbonization via biomass co-firing considering CO 2 emission trading system in an uncertain decision-making environment. It considers the interactive relationship between multiple decision makers. The upper-level model focuses on the formulation of CO 2 emission trading system, and the lower-level model decides biomass co-firing and emission reduction. Fuzzy set theory is employed to describe the uncertain parameters and convert them into exact values. To calculate the model, a bi-level interactive method based on satisfactory solution is developed. A case study is conducted to illustrate the effectiveness and practicality of the proposed model. Results show that the price of initial quotas fluctuates between 38.01 and 48.7 CNY/tonne, and the lowest carbon intensity is 0.741 kg/kWh. Management recommendations are provided to support CO 2 emission reduction. • A bi-level model for biomass co-firing under carbon emission trading is developed. • The hierarchical decision process between multiple stakeholders is considered. • Fuzzy set theory is employed to effectively handle real-world uncertain information. • A case study in China is conducted to demonstrate the practicality of the method. • The method effectively achieves carbon reduction and reaches Stackelberg equilibrium. [ABSTRACT FROM AUTHOR]

Achieving an efficient, modern, and sustainable energy transition towards carbon neutrality has attracted worldwide attentions. Composite statistical indices are increasingly recognized as valuable tools for policymakers, offering enhanced understanding of the present condition and anticipated direction of energy transition. In this research, we constructed a comprehensive index to track provincial energy transition in China. With this index, we monitored the energy transition progress of 30 provinces in China. The Provincial energy transition index (PETI) scores exhibited considerable heterogeneity across provinces and throughout different time periods, with eastern provinces having the highest scores, and some northwestern and large coal provinces, like Shanxi, having the lowest scores. These findings indicated that provincial energy transition policies should be tailored to the local energy status and economic structures. The paper delineated conclusions and policy implications derived from the study's extensive evaluation. Specifically, effective ways to further improve a region's sustainable energy transition path include advancing the use of clean energy, vigorously promoting power grid construction, and investing in new energy sectors. The implementation of these strategies is expected to reduce energy consumption and carbon intensity, thereby decreasing carbon emissions, then ultimately accelerating the realization of the dual carbon targets. • We present a provincial energy transition index to track regional energy transition process. • There was significant heterogeneity in PETI scores across different provinces. • There were disparities among the performances in the three dimensions of the PETI. • Energy transition policies ought to give precedence to regions that are lagging in their energy transition. [ABSTRACT FROM AUTHOR]

Innovation is crucial for countries to achieve their carbon peak and carbon neutrality goals. To explore how and to what extent innovation contributes to low-carbon development, this study utilizes data from 272 Chinese cities, applying both staggered difference-in-differences and spatial econometric approaches to comprehensively assess the direct and spatial spillover effects of China's innovative city pilot policy on urban low-carbon development. The findings are as follows: First, the innovative city pilot policy has reduced urban carbon intensity by 4.62 % and increased carbon total factor productivity by 3.03 %, with the effect being more significant in larger cities. Second, mechanism analysis indicates that the innovative city pilot policy primarily promotes urban low-carbon development through innovation financing and talent attraction, rather than optimizing industrial structures Third, spatial analysis reveals that the innovative city pilot policy has a low-carbon spillover effect, indicating it can promote low-carbon development in neighboring cities. Finally, this paper proposes policy recommendations for combining innovative city pilot policies with climate policies, focusing on the underlying mechanisms, and exploring cross-regional linkages. [Display omitted] • The direct and indirect effects of China's Innovative City Pilot Policy on low-carbon development are investigated. • The ICPP leads to reduce carbon intensity by 4.62% and increase carbon TFP by 3.03%. • Both mechanisms and heterogeneous effects of ICPP on carbon intensity and carbon TFP are examined. • The ICPP has the potential to propagate the low-carbon development effect to neighboring cities. [ABSTRACT FROM AUTHOR]

Given the current state of global carbon emissions, China has proposed the objectives of achieving carbon peaking by 2030 and carbon neutrality by 2060. To meet the requirement of zero-carbon and achieve the application of pure ammonia fuel in low-speed two-stroke marine engines, this paper proposes the Groove Diversion-Assist Ignition (GDAI) combustion system, which can effectively control the temperature, fuel distribution, and flow rate in the spark plug region near the top dead center and finally achieve the spark ignition of pure ammonia without any change in compression ratio and scavenging temperature. At the same time, the boundary conditions for the ignition of ammonia fuel have also been studied. The results show that enhancing the initial temperature can alleviate the requirement for spark ignition energy, and a minimum energy level of 75 mJ remains necessary for effective spark ignition of ammonia. Furthermore, the utilization of spark ignition of ammonia fuel can achieve a maximum thermal efficiency of 51.32%, representing a 2.8% increase in overall thermal efficiency compared to the diesel mode. Additionally, the application of ammonia fuel can relief the NOx emissions compare to diesel fuel, which provides a new and effective utilization way for the application of ammonia fuel on the marine engine. • The Groove Diversion-Assist Ignition combustion system was proposed. • A minimum energy of 75 mJ is necessary for effective spark ignition of ammonia. • The ammonia engine can provide a 2.8% enhancement in thermal efficiency. • The use of ammonia fuel can relief the NOx emissions compare to diesel fuel. [ABSTRACT FROM AUTHOR]

The intensification of global climate change has led to a widespread consensus on carbon reduction, with the power industry being the principal contributor to carbon emissions necessitating an inevitable transition of its energy structure. Concomitantly, the escalating frequency of natural disasters caused by extreme weather presents formidable challenges to both secure power supply and the low-carbon transition of the power system. To fulfill the developmental requirements of a low-carbon power system and address the carbon emission risks imposed by natural disasters, this paper proposes a bi-level model for generation expansion planning (GEP) that incorporates constraints on the carbon emission trajectory and the influence of natural disasters. The planning-level model optimizes investment costs of various generation technologies and energy storage (ES), as well as the overall operational expenses over the planning period, with an objective to minimize them. It incorporates carbon emission trajectory constraints and policy constraints, such as carbon peaking, carbon neutrality and renewable energy (RE) penetration rates, in order to optimize the planning installed capacity of power sources. The operational-level model aims to minimize typical daily operating costs while also simulating power unit outputs in routine and disaster scenarios. A case study is conducted in a disaster-prone province in southern China to analyze the power generation expansion planning and the trajectory of carbon emissions from 2020 to 2060 under different scenarios. The simulation results show that compared to thermal power, the planning scheme mainly focused on RE with ES is better suited to achieve the goal of a low-carbon transition of the power grid. Moreover, after considering natural disasters, the cost and carbon emissions of power system planning are higher, and the risk of carbon emissions increases with the severity of disasters. • A multi-time scale bi-level low-carbon GEP model is proposed. • Natural disaster scenarios and low-carbon policy constraints are considered in the GEP model. • Carbon emission trajectory of the planned power system is estimated and introduced as a constraint into the GEP model. • Evaluation indicators that comprehensively consider low-carbon performance and economic feasibility are proposed. [ABSTRACT FROM AUTHOR]

• Propose a methodology for measuring of regional synergistic emission reduction. • Regional synergistic emission reduction networks have a multilevel nested structure. • Explained the evolution characteristics of regional synergistic emission reduction. • Identified driving factors of regional synergistic emission reduction networks. Synergistic regional emission reduction (SRER) is an important part of the strategy to achieve carbon neutrality. In this paper, a system efficiency value-added model is proposed to measure the strength of SRER network relationships for 40,186 sets of city pairs and the SRER levels of 284 cities in China from 2011 to 2021. Subsequently, the evolution characteristics of the SRER network, the spatial and temporal characteristics of urban SRER levels, and the driving factors of the SRER network evolution are further analyzed. The results are as follows: SRER network is shifting from a fan-shaped network pattern of "three-region clustering and sporadic coverage" to a shuttle-shaped nested network pattern of "east-west linkage and multi-region support". Time series analysis found that urban SRER level in China showed fluctuating growth characteristics during the study period. Spatial analysis reveals that the spatial autocorrelation of urban SRER level is decreasing, and the spatial distribution range is expanding towards the southwest. Emission reduction comparative advantages (CAER), green innovation division of labor (GIDL) and urban economic linkages (LCEL) are driver factors of SRER network evolution. This study proposes an evaluation method for the urban SRER level from network relationships perspective. Subsequently, network evolution characterization, spatial and temporal characterization, and driving factor analysis were conducted. The results of the study provide important theoretical guidance and inspiration for grasping the current status and enhancement paths of China's urban SRER level. [ABSTRACT FROM AUTHOR]

With the establishment of carbon peaking and carbon neutrality goals in China, developing low-carbon cities has become crucial. Previous studies primarily focus on the quantitative structure of land use to achieve low carbon optimization, while ignoring the spatial integration between urban form and carbon emissions. To fulfill this gap, this paper proposed a dual-scale low carbon oriented multi-objective land use allocation (DOLA) optimization model, utilizing idea-point multi-objective linear programming (IMLP) and non-dominated sorting genetic algorithm II (NSGA-II) to optimize the low-carbon-emission pattern of the city at both the structural and spatial scales respectively. By innovatively linking the urban shape index with carbon emissions, this model aims to minimize urban carbon emissions, while maximizing economic development, urban development suitability, and the compactness of city. The proposed method is applied to Wuhan's main urban area in China, the DOLA model shows significant improvements in target values across all scenarios. Among them, the scenario that prioritized low carbon emissions at both the structural and spatial scales achieved the most significant reduction of 6.43 % in carbon emissions. The DOLA effectively contributes to achieving multiple spatial targets, thereby aiding in reducing carbon emissions. It offers technical support for developing pathways towards China's "dual carbon" target. • A dual-scale low carbon oriented multi-objective land use allocation (DOLA) optimization model is proposed. • The DOLA model innovatively incorporates urban form indices to carbon emissions. • The DOLA model achieves spatial aggregation targets, thereby facilitating significant reductions in carbon emissions. • The DOLA model generates a series of land use optimization scenarios, offering a valuable reference for land use planning. [ABSTRACT FROM AUTHOR]

Given the urgency of the transition to renewable energy, this study examines the challenges and opportunities associated with the electrification of heavy-duty vehicles, particularly new energy construction dump trucks, in China. Through a combination of policy analysis and empirical research, it investigates drivers' purchase intentions towards these alternative energy vehicles in a designated study area. The findings reveal that while policies aimed at encouraging adoption are in place, drivers' purchase intentions remain low due to factors such as high costs, technical concerns, inadequate infrastructure, and satisfaction with existing trucks. Specifically, the study identifies key technical challenges, including battery performance and range limitations, and advocates for a shift in policy support towards product development to address these issues. Overall, the paper highlights the need for a comprehensive approach that combines policy incentives with technological advancements to promote the widespread adoption of new energy construction dump trucks in China and achieve sustainability and carbon neutrality goals in the transportation sector. [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]

Technical lignin (TL) is a solid waste generated in industrial activities including pulp and paper mills and second-generation (2G) biorefineries. After isolation processes, TL is available in large quantities and has favorable compositional characteristics to produce high-performance activated carbons (ACs), such as low amount of residual carbohydrates, high reactivity due to the presence of different functional groups, and high aromatic carbon content. The value of the AC market is projected to reach US$ 7 billion by 2028, led by the water treatment sector. This work provides a brief overview of the status quo in the production of new adsorbents from TL, focusing on biorefineries, together with a bibliometric and patentometric survey. This evidenced a scarcity of publications on this topic, with the primary focus being on chemical modification of TL. A notable increase was observed in the production of ACs for electrochemical applications. Only a few patents were found on the subject, with China predominating technological development in this area. The findings revealed a technical-scientific-economic potential that has been largely unexplored, as no TL-derived AC from 2G biorefineries has yet been produced and applied in water treatment. Hence, there is excellent potential for the wider commercialization of AC produced from TL, representing an excellent opportunity to recycle TL and support the bio-based circular carbon economy, while also contributing to carbon emission neutrality. The marketing of high-performance ACs produced from TL could make biorefineries more profitable and less sensitive to market price fluctuations, while becoming carbon-neutral multiproduct platforms. [Display omitted] • Technical lignin (TL) has untapped technical-scientific-economic potential. • Production of activated carbon is a technological way to add value to TL. • Bibliometrics and patentometrics indicate a scarcity of value-added TL products. • Biorefineries as key contributors to carbon neutral emissions in the energy sector. • New opportunities and challenges identified for excess TL in 2G ethanol plant. [ABSTRACT FROM AUTHOR]

Accurate photovoltaic (PV) power forecast is crucial for carbon neutrality. Current researches on PV power forecast mainly focus on using temporal information from single PV station, and the spatial information in multiple PV power stations are often neglected. To address this problem, this paper introduces Moran index to verify the spatial autocorrelation of PV power for the first time, uses Granger causality test and transfer entropy to reveal the spatial information gain in PV power forecast for the first time, and proposes a novel spatial–temporal probabilistic PV forecast method using deep Graph Gated Recurrent Unit (GraphGRU) network-based spatial–temporal multi-task learning and Kernel Density Estimation (KDE). Deep GraphGRU combines the advantages of Graph Convolutional Network (GCN) in spatial feature extraction and the advantages of Gated Recurrent Unit (GRU) network in temporal feature extraction, and thus has strong ability to extract spatial–temporal information in historical data of multiple different PV power stations. Through GraphGRU, temporal dependency information extracted from historical data of multiple PV stations can promote each other to improve the forecast accuracy of each PV stations. KDE is used for estimating the joint probabilistic density function and giving the spatial–temporal probabilistic confidence interval of PV power. Experiments were performed in the five-year actual PV power data from 11 provinces of Belgium and the three-year solar irradiation data from 12 places in China to verify the superiorities of the proposed method. Comparison with conventional spatial–temporal and temporal forecast methods show that the proposed GraphGRU-based spatial–temporal forecast method can extract the spatial–temporal information from multiple PV power stations well and significantly outperform conventional temporal forecast methods. [ABSTRACT FROM AUTHOR]