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China is the top emitter of greenhouse gases in the world. Pulp and paper industry is one of eight the strictly regulated industries about carbon emission in China. However, estimates of carbon emissions from China's pulp and paper industry have been suffered from remarkable uncertainty. It is summarized that is aroused by the inaccuracy of factors evaluating energy consumption, and the huge gap between the calculation standards for assessing energy consumption in the production process and the actual level recorded in the factories. This paper re-evaluated the carbon emission of China's pulp and paper industry from the perspective of life cycle assessment, and applied more accurate emission factors, taking account of the actual energy consumption of the production process in factories, to estimate the actual carbon emissions in maximum. It is found that the national standards about the energy consumption quota of China's pulp and paper industry is no longer applicable, and the actual energy consumption regulated in the production process is far better than the advanced level given by the national standards. The greenhouse gas emission have been seriously overestimated approximately 12.00%–56.17% by international organizations. • Life Cycle Analysis of the China's pulp and paper Industry is conducted thoroughly. • The pulp flow of China's pulp and paper Industry is analyzed. • Energy regulated in factory is far better than the national standards' required. • Carbon emissions of China's pulp and paper Industry are overestimated. [ABSTRACT FROM AUTHOR]

With the development of energy technology, hydrogen is gradually becoming widely used. China is also rapidly developing its own hydrogen energy industry in an effort to accomplish the "dual carbon target'. Hydrogen from methane is one of the mainstream sources, of which hydrogen from methane cracking is the decomposition of methane into hydrogen and solid carbon, with the solid carbon also having a high economic value. In particular, this technology does not emit carbon dioxide, which is very friendly to the environment, but it cannot avoid larger energy consumption. In contrast, hydrogen production from methane cracking driven by solar energy not only combines the characteristics of no CO 2 emission, but also greatly reduces the consumption of primary energy, which is the future development trend of hydrogen production from methane. This paper provides a brief overview of the various technological pathways for methane to hydrogen production in the context of China's actual development, focusing on the current status of the development and application of solar methane cracking to hydrogen production technologies at home and abroad. Among them, this paper mainly discusses the characteristics of solar reactors of different sizes and structures, and summarizes the results of related optimization studies. Meanwhile, the application of catalysts in solar reactors and the problem of carbon deposition are analyzed, and the practical application of solar methane cracking hydrogen production system is outlined. Finally, the future development of solar methane cracking hydrogen production technology is prospected from the national situation of China. [Display omitted] • Solar methane cracking for hydrogen can reduce emissions and energy consumption. • The current state of research on solar reactors is summarized. • Solar methane cracking requires higher performing catalysts. • Providing insights into the future development of solar methane cracking in China. [ABSTRACT FROM AUTHOR]

Urbanization and the release of carbon emission are two significant features of contemporary economic and social progress in China. However, there are few studies that consider how urbanization policy goals affect carbon emission. This paper aims to study the nonlinear effects of urbanization policy goals on carbon emission in 13 cities of the Beijing-Tianjin-Hebei region. In this paper, a multi-dimensional spatial disturbance grey model is proposed. Based on matrix perturbation theory, this paper explores the spatial perturbation bounds of the novel model and verifies that the spatial property of the model is consistent with the viewpoint of the First Law of Geography. Then, the novel model is used to predict the urban carbon emission under different urbanization policy goal scenarios. The results showed that the novel model has spatial regional correlation in spatial region prediction. With the development of urbanization level, carbon emissions show a downward trend in more than 50% of cities from 2022 to 2025. In addition, the improvement of urbanization policy goals will promote the carbon peak time of most cities. The carbon emission intensity will exhibit an inverted U-shaped trend distribution in space. The research results are conducive to providing scientific guidance for the formulation of new-type urbanization policies and helping to achieve the dual carbon goals. • A multi-dimensional spatial disturbance grey model is proposed. • The novel grey model is consistent with the viewpoint of the First Law of Geography. • The spatial distribution of carbon intensity showed an inverted U-shaped pattern. [ABSTRACT FROM AUTHOR]

Policy synergy is a unique way for the government to establish a policy network and a crucial way for cities to expand their carbon reduction channels. Using urban data from China, this paper empirically investigates how environmental governance policy synergy (EGPS) affects carbon emissions. In comparison to non-pilot cities, the environmental information disclosure (EID) policy and low-carbon city (LC) policy play an inhibitory role in carbon emissions. Furthermore, EGPS has a stronger effect and is heterogeneous by region. Through the use of technical advancement and industrial structure optimisation, EGPS lowers carbon emissions, and this effect of EGPS grows over time in tandem with the level of environmental pollution in the cities. Our paper proposes policy implications in order to improve the overall effect of environmental governance policy and help achieve the dual carbon targets. [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]

This paper proposes a novel aviation CO 2 emissions reduction method by introducing a market-based incentive mechanism. An aviation carbon emissions prediction model is proposed to characterize both the microscopic flight dynamics and the macroscopic air traffic demand trend. Based on emissions prediction, a linear climate response model is applied to evaluate the environmental impact of the aviation carbon emissions. Finally, a market-based framework for aviation CO 2 emissions reduction is established based on a two-phase carbon trading model, which provides a piecewise charge method through emission taxation and cap-and-trade. A case study is carried out to demonstrate the effectiveness of the proposed framework using a real-world dataset from the Hefei Air Traffic Control Zone in China. Three scenarios are defined to describe the possible development speed of sustainable aviation fuel application in the future: not applied, medium-speed development, and high-speed development. The results show that the carbon peak will be reached in 2025 in the high-speed development scenario, when the emission amount and associated environmental impact will be reduced by 23.7% and 22.3%, respectively. Thus, the market-based framework proposed in this paper can effectively reduce aviation CO 2 emissions and mitigate the effects of global warming. • An aviation CO 2 emissions prediction model is proposed considering both microscopic flight dynamics and macroscopic traffic demand. • A more efficient market-based CO 2 emission reduction framework is developed based on a two-phase carbon trading model by means of taxation and cap-and-trade. • Case study shows that the proposed method has a more optimal incentive for CO 2 emission reduction. [ABSTRACT FROM AUTHOR]

• We study the relationship between GVC embedding and carbon emission density. • A mediation effect model was established to test the mechanism. • There is a U-shaped relationship between urban GVC embedding and carbon emission density. To achieve its carbon peak and neutrality plan, whether China's global value chain (GVC) embedding has a carbon emission reduction effect is a question worthy of attention. This paper measures the GVC embedding degree of 218 Chinese cities from 2000 to 2016, and constructs a panel data model to investigate the impact and its mechanism of GVC embedding on carbon emission intensity. This study finds that there is a significant U-shaped relationship between GVC embedding and carbon emission intensity, and a series of robustness test results support this conclusion. Export scale, energy consumption structure and technological innovation play a mediation role in the impact path of GVC embedding on carbon emission intensity. Based on this, this paper proposes that while participating in GVC, China needs to actively utilize the emission reduction effect of GVC, promote the transformation of export mode to high quality, reduce the use and dependence on high-carbon resources such as coal, and encourage companies to innovate. [ABSTRACT FROM AUTHOR]

Ports are essential and strategic nodes of international trade and economic activities. The integration of port resources helps enhance the optimal division of port functions to further promote economic development. This paper explores the evolutionary trends of port integration policy from 2011 to 2021 in China through a text-mining approach. We first used the Latent Dirichlet Allocation (LDA) topic analysis method to analyze the port integration policies and summarize the evolutionary trends of port policies. In addition, an association analysis was conducted to explore port integration policies' impacts by examining their relationships among the environmental protection, digitalization level, and port development scale. Our findings suggested that China's port integration policy has evolved from specific and simple to abstract and complicated at the managerial level. Port development has enriched from infrastructure construction to the ideology of economic development. Our findings show that China's port integration is gradually improving the port operation. The findings of the study contribute to the extant literature by analyzing the port integration policy evolution in China and can be referred to by other countries. • Text mining method was used to explore the port integration policy evolution. • Port integration policy evolved from specific and simple to abstract and complicated. • Port development enriched from basic infrastructure to the governance model. • The evolution of port integration policy was related to reducing carbon emissions in the port sector. • The evolution of port integration policy made the ports intelligent in association with digital technology such as big data and AI. [ABSTRACT FROM AUTHOR]

Pollution reduction and low-carbon development are two specific but intertwined goals of addressing climate change and sustainable development of the United Nations in 2030, and the effective use of digital financial inclusion is imperative for driving technical innovation, upgrading industrial structure, and addressing climate change. Therefore, this paper investigates the impact of digital financial inclusion on the coupling coordination between pollution reduction and low-carbon development using a panel dataset of 30 China's provinces from 2011 to 2020. The results show that the coupling coordination between pollution reduction and low-carbon development in China improves significantly during the sample period. The synergistic effect of different economic zones and provinces varies greatly in space and time. In addition, digital financial inclusion has a promoting effect on the coupling coordination of pollution and carbon emission reduction. A mechanism analysis also reveals that technological innovation, industrial structure and energy consumption are the core transmission channels through which digital financial inclusion influences the synergistic effect of pollution and carbon emission reduction. This suggests that the need of coordinated governance by policymakers is warranted, and digital financial inclusion is an important way to this coordinated governance. [ABSTRACT FROM AUTHOR]

The Chinese government aims to balance employment stabilization and emissions reduction when it initiates an emissions trading scheme (ETS) to control carbon emissions. However, the policymakers should not neglect the role of imperfectly competitive market structure and market power from incumbent firms. In view of this, classical framework of Berman and Bui's (2001) is extended in this paper to clarify the theoretical mechanism of employment effect of the ETS considering firm-level market power. In addition, based on the firm-level panel data from 2008 to 2019 of China, the employment effect of each pilot ETS is measured with the method of difference-in-difference-in-differences. Then a moderating effect model is established to verify the role of firm-level market power on the heterogeneous employment effect among the pilot ETSs. Moreover, the employment effect is further decomposed to evaluate the influential mechanism from the perspective of firms' strategic behavior. It is found that there is negative employment effect of China's ETS policy, due to the significant moderating role of firm-level market power. This decrease in labor demand is mainly dominated by a negative output effect rather than a positive substitution effect because strategic allowance sellers with stronger market power tend to hire fewer employees to reduce carbon emissions by controlling production scale. However, the heterogeneity of policy effects resulted by market structure is also identified in different pilot regions. Employment dividend has been found in Beijing and Tianjin where strategic allowance buyers manipulate the carbon market and hire more employees to consolidate their market power. Therefore, policymakers should improve the design of the ETS to overcome the adverse employment effect duo to the region-specific market structure. [ABSTRACT FROM AUTHOR]

Fossil-based natural resources are carbon-intensive, and over-reliance on them often leads to persistent high carbon emissions at national or regional levels, resulting in the carbon curse. Based on the panel data of 114 resource-based cities in China from 2007 to 2020, this paper examines the carbon curse and solutions for these cities from the perspectives of total and intensity of carbon emissions. The results show that: Firstly, due to the different stages of urban development, resource endowment, degree of resource dependence, and policy background, there is a heterogeneity of carbon curse in China's resource-based cities. Secondly, the carbon emission trading policy can effectively mitigate the carbon curse in China's resource-based cities, and the robustness tests demonstrate the validity of this finding. Thirdly, under the carbon emission trading policy, industrial structure upgrading and digital transformation can play a secondary moderating role in resolving the carbon curse in resource-based cities, further strengthening the inhibitory effect of the carbon emission trading scheme on the carbon curse. In contrast, green technology innovation exhibits no enhancement in the impact of the policy. These findings contribute to the existing research on the carbon curse, offering valuable insights and policy implications for effectively addressing this challenge. [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]

To reflect the future electricity demand variations in the industrial sector of western China under the "carbon peaking" and "carbon neutral" strategies, that the traditional methods of electricity consumption forecasting are no longer effective, this paper proposes a new hierarchy of electricity demand influencing factors based on the transition path of low-carbon and CO 2 emission intensity constraints of the industrial sector. Then, the feedback equations of the influencing factors based on CO 2 emission intensity is constructed, and a long-term electricity forecast model based on system dynamics is established. Finally, taking Ningxia Province as an example, the electricity demand and carbon emissions of the industrial sector are predicted under different policy constraint scenarios. The results show: (1) In the baseline scenario, electricity demand will tend to saturate with about 140.1TWh in 2030, and the CO 2 emission level of electricity demand will peak at 72.52 million tons in 2029. (2) Compared with the system dynamics model without considering CO 2 emission intensity, the mean absolute percentage error is reduced about 3.16 % by inputting the influence factors and regression coefficients designed in this paper. (3) Compared with other forecasting methods, the model proposed in this paper has the lowest mean absolute percentage error of 2.75 %. The model improves the accuracy and provides a reference for planning departments to develop energy transition plans, where the prediction results reflect the reality of the industrial sector in western China. Correspondingly, this model has reference value for relevant institutions in forecasting the electricity demand under the low-carbon development path in industrial sectors of different regions. • Influencing factors are screened according to the low-carbon transition paths. • The distributed power installed capacity and load interaction coefficient are considered. • Multiple regression equations are developed between CO 2 emission targets and influencing factors. • A long-term electricity demand forecast model driven by CO 2 constraints is constructed. • The multi-scenario electricity demand in western China is forecasted in response to carbon peaking and carbon neutral targets. [ABSTRACT FROM AUTHOR]

[Display omitted] Waste-to-Energy (WtE) technology is the most effective solution for managing non-recyclable wastes through mass burning and energy recovery. Owing to the significant volumes of plastics in China's industrial solid wastes (ISW), a large amount of greenhouse gases (GHG) is generated during the incineration process. Therefore, monitoring GHG emissions from WtE facilities is essential. Owing to the lack of suitable accounting models and characterized fossil carbon fraction (FCF) data, current studies use default values provided by the Intergovernmental Panel on Climate Change's (IPCC), which increases calculation inaccuracies. Therefore, this study established an improved method to accurately account for carbon emissions during solid waste incineration by firstly using radiocarbon dating by accelerator mass spectrometry (AMS) technique to determine the FCF of the solid waste components in China. Monte Carlo analysis was employed to perform the sensitivity analysis, and the results indicated that there was a significant deviation between the measured value and IPCC's default values of FCF, 3.2, 32.48, 93.39, 93.76, 90.49, and 93.8 % for paper, cotton, synthetic textiles, artificial rubber, artificial leather, and plastics, respectively. By replacing coal with ISW in a 2 × 110 t/h circulating fluidized bed boilers, 9.251 × 104 t CO 2 -eq emissions were reduced, and the carbon emission factor reached 0.56 t CO 2 -eq/t waste. This study complements the research gap fossil carbon data of wastes in the IPCC guidelines and provides a more accurate and effective way to calculate carbon emissions during ISW incineration treatment. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO 2) emissions and climate change risk have become constraints on global economic sustainable development. Environmental regulation (ER) is a key method for achieving synergy in CO 2 and pollution reduction in China. This paper is the first study to explore the effects of ER on CO 2 emissions by exploiting the National Environmental Protection 11th Five-Year Plan (NEP11-FYP). The implementation of the NEP11-FYP significantly decreases CO 2 emissions by 19.73% in key environmental cities relative to other cities. Heterogeneity analyses suggest that this negative impact is larger in western cities and cities with more pressure to reduce CO 2 emissions. Scale effects, structural effects, and technical effects might be three potential influencing channels through which ER contributes to the CO 2 reduction effect. In addition, the results of the spatial externality of the NEP11-FYP demonstrate a positive spillover effect in neighboring cities within a distance of 300 km and a negative spillover effect in cities more than 500 km away. Our empirical findings provide policy implications for implementing low-carbon transition strategies and reducing CO 2 emissions. [ABSTRACT FROM AUTHOR]

In the context of China's carbon peak and carbon neutrality goals (the "dual carbon" goals), balancing economic development, environmental protection, and low carbon is a high priority. Therefore, exploring the impact of digital finance on carbon dioxide (CO 2) emissions is crucial. In this paper, we select the panel data of 241 cities in China from 2011 to 2020 and use the double logarithm model after verifying model forms to explore the impact of digital finance on urban CO 2 emissions. The results show a significant negative correlation between the level of digital finance and the intensity of CO 2 emissions. Heterogeneity analysis results show that the eastern region exhibits the greatest inhibitory effect, while the western region exhibits the lowest. The three sub-dimensions of digital finance can all reduce carbon emissions, but the usage depth dimension has the greatest reduction effect, while the coverage breadth dimension is slightly lower. Through mediating effect tests from two dimensions, we find that digital finance can achieve CO 2 emission reduction by promoting scientific and technological innovation. These findings have implications for understanding the carbon reduction effectiveness of digital finance and achieving the dual carbon goals. [ABSTRACT FROM AUTHOR]

Climate change induced by carbon emissions has received extensive global attention. However, with the ever-increasing environmental attention from governments, whether firms, as main contributors to carbon emissions, have responded to the government's call to achieve carbon abatement target is uncertain. To answer this question, we manually collected urban government work reports from 2007-2016 and extracted environment-related textual content to quantify government environmental attention (GEA). Employing firms' carbon emission data from National Tax Survey Database (NTSD), this paper explores the impact of GEA on firms' carbon emissions governance. We observe that the increase in GEA cuts firms' carbon emissions. The results remain solid after using the instrumental variable method to alleviate endogeneity problems. The mechanism analysis reveals that GEA reduces firms' carbon emissions via three environmental-related decision-making behaviors of government: environmental regulations, fiscal expenditure and subsidy policies, and energy structure transformation strategies. Heterogeneity analysis shows that GEA notably reduces firms' carbon emissions from burning coal and oil energy. Moreover, firms in eastern-north, central, and western regions are more susceptible to GEA, while the impact is insignificant for firms in eastern regions. Furthermore, the carbon reduction performance is more pronounced for enterprises in capital-intensive, technology-intensive, and high polluting industries. This study provides a reference for policymakers to ensure the enforcement of carbon emissions governance of firms and to reach carbon abatement targets. [ABSTRACT FROM AUTHOR]

This paper uses panel data on renewable energy in China. Thus, the current analysis fills the gaps by examining the relationship between green technology innovation and renewable energy and CO 2 emissions from 1990 to 2018. The current study examines all concerns connected to panel data analysis with advanced panel estimators, such as cross-sectional dependence, stationarity, variation in slope parameters, and structural break. Our findings show that test results reveal that green technology innovation and renewable energy have a negative and considerable influence on CO2 emissions in the long run. Moreover, the short-run relationship of green technology innovation, on the other hand, is not significant—as evidenced by the findings of robustness tests such as AMG and CCEMG. Other empirical results revealed that GTI, REN and NEN significantly reduced local CO 2 emission, while POP and PI had no obvious reduction effects on CO 2 emissions. Different GTIs had the same spatial "symbiotic effects" on CO 2 emission reduction in the short term, showing positive spatial spillover reduction effects. Lastly, we conclude that the use of green technology innovation has positive externalities. Some policies to assist green innovation technologies and renewable energy resources have been suggested for the Chinese government to enact. • This paper uses panel data on renewable energy in China. • The current study examines all concerns connected to panel data analysis with advanced panel estimators. • The short-run relationship of green technology innovation is not significant. • We conclude that the use of green technology innovation has positive externalities. [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]

Faced with the difficult but urgent task of reducing carbon emission intensity, considering urban agglomeration as a fundamental spatial unit for this purpose has become increasingly important. However, as a long-standing and pivotal phenomenon in the development of urban agglomerations, the potential role of spatial functional division in urban agglomerations in reducing carbon emission intensity has been largely overlooked. To fill this gap, this paper explores the relationship between spatial functional division in urban agglomerations and carbon emission intensity, relying on a dataset of 19 urban agglomerations in China. The main results reveal an inverted U-shaped relationship between spatial functional division in urban agglomerations and carbon emission intensity. Spatial functional division in urban agglomerations increases carbon emission intensity in the initial stage; once it reaches a turning point, spatial functional division in urban agglomerations can reduce carbon emission intensity. This conclusion remains robust after conducting various robustness checks and addressing endogeneity concerns. This paper identifies productivity enhancement as an underlying mechanism that shapes this relationship. Moreover, the relationship between spatial functional division in urban agglomerations and carbon emission intensity exhibits heterogeneity based on function types and urban types. These findings emphasize that spatial functional division in urban agglomerations plays a unique role in reducing carbon emission intensity, which offers a new strategy for reducing carbon emission intensity from an individual city level to an entire urban agglomeration level. • An inverted U-shaped relationship exists between SFD and CEI. • Productivity enhancement derived from SFD is a crucial influencing mechanism. • Function types and urban types influence the relationship between SFD and CEI. • Improving SFD adds a novel urban agglomeration-level strategy to reduce CEI. [ABSTRACT FROM AUTHOR]

The widespread use of digital technology has driven a huge change in the way payments are made. Based on the micro-data of the China Family Panel Studies (CFPS), this paper explores the relationship between mobile payment and carbon emissions from the consumption side. With the exogenous impact of Alipay's "Collecting Five Blessings" campaign, this paper finds that mobile payment significantly increases household consumption carbon emissions, but the marginal effect is gradually decreasing. Mechanism analysis shows that mobile payment mainly realizes the above impact through promoting the increase of consumption expenditure and upgrading of consumption structure. Further analysis indicates that carbon reduction policies introduced by the Chinese government in the personal consumption sector can mitigate the carbon emissions growth associated with mobile payments. Still, there is a need to strengthen policy measures further to effectively address the issue of rising carbon emissions from household consumption. [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 global climate change posing a major threat to human society, a growing number of countries have taken "carbon-neutral" as a national strategy and proposed a vision of carbon-free future. As an important supplement to traditional fossil energy, renewable energy is the main force to reduce the use of high-carbon energy and carbon dioxide emissions, which will become the trend of social development in the future. Finding the optimal renewable energy source is of particular significance for achieving the net zero emissions. However, the existing evaluation methods of renewable energy sources have obvious shortcomings. In terms of weight calculation methods, such as the randomness of the subjective method is strong and the index weights do not reflect the small changes of the evaluation matrix, which affect the reliability and accuracy of the evaluation result. The existing ranking methods can only achieve the complete ranking of the different objects, but cannot classify the renewable energy technical alternatives into different grades. Given this background, this paper proposes a novel evaluation method for renewable energy plans based on improved sparrow search algorithm and projection pursuit model. Firstly, this paper improves the traditional sparrow search algorithm from three aspects: population initialization, population update and population variation. Then, the projection pursuit model is constructed, and the improved sparrow search algorithm is applied to optimize the projection target to find the optimal projection direction, so as to determine the weight values of each evaluation index. Finally, the weighted rank-sum ratio method is used to select the best renewable energy technical plan, which can not only realize the complete ranking of different plans, but also classify the technical plans into different levels. Based on the actual renewable energy development data from 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 existing evaluation methods of renewable energy technical plans. [ABSTRACT FROM AUTHOR]

The focus of this paper is on achieving a win-win situation regarding the economic, environmental, and social impacts of the cold chain logistics terminal distribution system. This paper proposes three multi-objective models to investigate the above effects by incorporating soft time windows, heterogeneous fleets, and path flexibility, with defining the objectives of examining logistics costs, fuel consumption, carbon emissions, quality damage to perishable commodities, and customer satisfaction using six evaluation functions. To solve the proposed models, an efficient optimization framework is developed by combining domain operators with versatile multi-objective evolutionary algorithms (MOEA) to obtain Pareto solutions. Extensive experiments are conducted to test the validity of the concerned model and algorithms. The results demonstrate that: (1) the proposed algorithm is effective in solving the proposed model; (2) the proposed multi-path strategy can effectively improve the performance of cold-chain logistics systems compared to single-path strategies; (3) evaluation functions that assess customer satisfaction greatly affect the performance of cold-chain logistics systems; and (4) the trade-off relationship between the objectives should be investigated to define the model. The paper also provides valuable managerial insights for improving the efficiency and sustainability of cold-chain logistics operations. [ABSTRACT FROM AUTHOR]

To identify the influence of digital transformation on energy consumption, this paper introduces digitalization and energy elements into the multi-sector energy efficiency analysis model. Furthermore, this paper empirically tests the influence of digital transformation on energy efficiency from the micro level. The results show that the digital transformation indeed improves the enterprises energy efficiency, in which enterprises with higher energy efficiency are more affected. The improvement effect of digital transformation on enterprise energy efficiency continues to increase over time. In comparison, digital transformation shows more effective improvement effect on energy efficiency in enterprises that substantive transformation priority, with same group and maturity stage. Mechanism analysis shows that digital transformation can improve the energy efficiency of enterprises by reducing costs, increasing income, improving production efficiency and promoting technological innovation. In addition, the digital inclusive finance, government subsidies, intellectual property protection and service industry opening show positive regulatory effects. This paper proposes that, with the goal of peak carbon dioxide emissions and carbon neutrality, enterprises should actively increase digital investment and strengthen digital management of energy utilization. [Display omitted] • Digital transformation indeed improves the enterprises energy efficiency. • The promotion effect of digital transformation increases over time. • Digital transformation drives efficiency improvement and technological innovation. • Digital transformation contributes to cost reduction and benefit increase. [ABSTRACT FROM AUTHOR]

Carbon emission flow is an effective tool to obtain carbon emission distribution in power systems, which can guide the active carbon reductions of consumers through proper incentive schemes. With the increasing penetration of renewable energy, the existing single-valued carbon emission flow model based on deterministic forecasted power outputs cannot describe the impacts of renewable energy uncertainties on carbon flows. Therefore, this paper mainly focuses on the assessment of the probabilistic carbon emission flow through the power systems considering the impacts of load and renewable energy uncertainties. In this paper, the probabilistic carbon emission flow (PCEF) is innovatively proposed. With the PCEF, consumers can make better energy use plans considering their own risk appetites for carbon emission payment. Firstly, the impact factors of the PCEF are modeled, including load and renewable energy uncertainties and integrated carbon intensity of thermal plants. The uncertainties of load, wind power and photovoltaics are modeled based on a p-box method while the uncertainty of hydropower is modeled based on the multi-state model. Besides, the integrated carbon intensity model of thermal plants are proposed considering the carbon intensity variations during the operating, start-up, and shut-down stages. Furthermore, the probabilistic carbon emission evaluation framework is proposed to assess the probabilistic carbon distribution. In this framework, novel probabilistic carbon indices are defined to precisely characterize the carbon emission situation with probabilistic representations. A solution method based on an adaptive interval point estimation (AIPEM) algorithm is proposed to efficiently solve the developed evaluation problem. Tests on an IEEE-30 node system, and a real provincial power system in China validate the effectiveness and application of the proposed model. The results showed that the PCEF can be a useful tool for obtaining the probabilistic representation of carbon emission flow and guiding the consumers' active carbon reduction in power systems. • Probabilistic carbon emission flow is proposed considering multiple uncertainties. • Integrated carbon intensity model for thermal plants is developed. • A p-box model is used to describe the uncertainties of load and renewable energy. • PCEF can help consumers balance the cost and carbon risk when making decisions. [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]

Single-rate pipeline prices have resulted in low competitive flexibility and have led to high costs and consumption in China's refined oil logistics system. This study aims to propose a framework for multi-product pipelines supplementary pricing strategy that creates a win-win situation for both shippers and pipeline carriers while quantifying economic, energy and environmental performance. Based on the objective of cost minimization, a lower limit constraint on pipeline transportation quantity is added, and a discount coefficient is introduced for pipeline prices, thus improving the transportation optimization model. Moreover, this paper develops an implementation approach for a supplementary pricing strategy that can ensure that the discounted price is not lower than the sum of cost and minimum profit. This framework usability is confirmed using a Chinese oil company as an example. The results show that the optimal scheme can increase pipeline revenue by ¥79.8 million while reduce shipper's logistics costs by ¥1.68 million during the practice cycle. Meanwhile, this work reduces energy consumption by 1.37 tce, CO 2 emission by 444 tons, SO 2 emission by 5.65 tons, and NO X emission by 7.07 million tons for the logistics system. Compared with past studies, this study is more economical or more in line with market-oriented behavior. • A framework for 3E performance improvement of multi-product pipelines is proposed. • The improved transportation optimization model is used as a pricing tool. • A supplementary strategy implementation approach is defined. • Total economic benefit to shippers and pipeline carriers is ¥9.66 million. • The energy and environmental benefits of the logistics system are quantified. [ABSTRACT FROM AUTHOR]

• An improved singular spectrum decomposition is proposed. • High complexity components are secondarily decomposed to reduce its complexity. • An improved prediction model of optimization algorithm is proposed. • Intelligent weighting strategy is introduced to overcome traditional weighting problem. • A combined prediction model for carbon emission is proposed. Accurate prediction of carbon emission is critical for the development of low-carbon economy. However, most carbon emission prediction studies use a single model with low prediction accuracy, and do not consider the instability of carbon emission. Therefore, this paper proposes a combined prediction model of carbon emission. Firstly, the original data is decomposed by singular spectrum decomposition to obtain a limited amount of singular spectrum components. Secondly, high complexity components are secondarily decomposed by variational mode decomposition. Then, chameleon swarm algorithm and carnivorous plant algorithm are used to train the regularization coefficients and kernel parameters of kernel extreme learning machine and least squares support vector machine respectively, and the trained model is used to predict the decomposition components. Finally, induced ordered weighted averaging operator is used to calculate the weight of single model, and error correction is introduced to further promote the prediction accuracy. The carbon emission data of China and the United States is used to make a prediction experiment. The results indicate that the proposed model is superior to other comparative models in different indexes, which provides a new idea for carbon emission prediction. [ABSTRACT FROM AUTHOR]

Changes in international markets and strict environmental regulations have challenged Chinese energy companies to reconcile sustainable and low-carbon development. Therefore, this paper focuses on 296 energy firms in China from 2011 to 2021 and uses the Difference-in-Differences (DID) method to explore the impact of China's environmental protection tax (EPT) reform on the dual dividend of energy firms from the perspective of resilience and CO 2 emissions, and fully discusses the role of government subsidies and corporate social financing. This research finds that China's EPT reform can improve the resilience of energy firms while reducing CO 2 emissions, and thus bringing a double dividend to energy firms. At the same time, government subsidies can enhance the decarbonization effect of EPT reform, but excessive subsidies can reduce the resilience of firms. In addition, the EPT reform can expand the scale of social financing for energy firms, helping them to realize a double dividend. The study's findings have important implications for the long-term low-carbon development of energy firms and provide a theoretical reference for China's EPT reform. [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]

Population aging has indeed emerged as a significant challenge for China. Using data from four waves of the China Family Panel Studies, this paper explores the impact of population aging on household carbon emissions and its underlying mechanisms. Results show that population aging significantly decreases per capita household carbon emissions, and this conclusion is robust with respect to sample selection, measurement of primary independent variable, and data selection. Population aging influences household carbon emissions through negative consumption effects and positive composition effects, with the former playing a dominant role. Notably, population aging increases per capita household carbon emissions in items such as medicine, heating, and healthcare, while decreasing emissions in most other items. Furthermore, empirical evidence suggests impact heterogeneity across hukou, income level, and the health status of household head. The insights presented in this paper are crucial for advancing our understanding of sustainable development. • Population aging decreases per capita household carbon emissions. • It is achieved through negative consumption effects and positive composition effects. • The consumption effects play a dominant role. • Evidence indicates impact heterogeneity across, hukou, income level, and the health status of household head. [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]

With the increasing severity of global warming, the goal of carbon sequestration and emission reduction in various industries has become an important responsibility for sustainable development. As an important part of carbon sink, the improvement of net carbon efficiency in the plantations industry will make a great contribution to the realization of the "double carbon" target in agriculture. However, there are large spatial and temporal differences in the net carbon efficiency of the plantations sector in various provinces, and there is still a large scope for increasing carbon sink and reducing carbon emission. In this paper, we have analyzed spatial and temporal trends in the net carbon sink efficiency of the plantations' production processes in 31 provinces in China (excluding Hong Kong, Macao and Taiwan) from 2000 to 2020. On this basis, we have analyzed the influencing factors of net carbon efficiency in the plantations' production process through an extended Kaya constant equation. Through the geographically and temporally weighted regression model, we explore the spatio-temporal heterogeneity of the influencing factors, and further analyze the driving and restraining factors of net carbon efficiency in plantations' production process, in order to propose appropriate countermeasures. The study shows that: (1) The net carbon efficiency of plantations sector in China increase between 2000 and 2020, and the development of net carbon efficiency is uneven across regions. (2) The geographic center of net carbon efficiency of China's plantations industry shift from the northeast to the southwest and is consistent with the migration direction of agricultural inputs. (3) The influencing factors of net carbon efficiency in the plantations sector show large regional differences, and can be specifically divided into four major types of zones. In this regard, this paper provides more appropriate countermeasure suggestions for increasing carbon sink and reducing carbon emission in each zone, with a view to achieving the goal of double carbon in agriculture with practical significance. • Net carbon efficiency is a new objective indicator to measure the carbon sink level of cropland. • Cultivated land carbon sink capacity is closely related to agricultural inputs. • Regional differences in the factors influencing net carbon efficiency. [ABSTRACT FROM AUTHOR]

Urban residents' travel is an important component of carbon emissions and is becoming a hot topic in discussions on how to achieve carbon neutrality by 2060. Existing studies mainly focus on low-carbon travel behaviours and intentions independently, ignoring the inconsistency between the two. This paper uses a bivariate probit model based on questionnaire survey data to explore the consistency between urban residents' intentions and behaviour. The results show that sociodemographic factors, TPB (theory of planned behaviour) factors, and situational factors all significantly impact the inconsistency. This paper provides careful analysis, and based on the results and analysis, proposes targeted suggestions to enhance the public intention of low-carbon travel and proper policies to improve low-carbon travel in cities. [ABSTRACT FROM AUTHOR]

The map of radiative cooling potential shows that the radiative cooling power can reach up to 100 W/m2 for its application in different climatic zones. However, the effect of building deployment on the city-scale application of radiative cooling is generally ignored in majority of existing studies, which overestimates the cooling benefit. This paper investigates the cooling benefit of implementing radiative cooling on a city-scale by considering building deployment. To determine the effect of building deployment on the radiative cooling potential, the city of Xi'an in China is modeled using COMSOL and verified with real weather data. Then, the thermal response of buildings with radiative cooling envelopes is discussed in detail. Finally, carbon emission reduction is derived at the city-scale by applying radiative cooling considering building deployment. The results show that the estimated radiative cooling power is approximately decreased by 14.7% for the ideal broadband surface and 47.1% for the ideal selective surface on the selected day by considering building deployment on a city-scale. Furthermore, carbon emission reductions of 0.52 gCO 2 /(m2⋅h) and 0.16 gCO 2 /(m2⋅h) can be achieved from the roof and walls on the selected day by applying radiative cooling material on both the roof and walls. This study can provide guiding significance for the large-scale application of radiative cooling in cities. [ABSTRACT FROM AUTHOR]

China has issued a series of biodiesel-related policies to alleviate energy shortage anxiety and reduce carbon emissions. However, no other provinces or cities in China widely utilize biodiesel except Shanghai. This article firstly conducted a comprehensive estimation of the potential botanical biodiesel capacity in China. Then, we examined why biodiesel advancement in China was stagnated by comparing biodiesel-related policies in pioneer countries such as Malaysia and Indonesia. We found the highest mix ratio will be ∼13 % if all potential botanical oils are added to petrochemical diesel and an addition of 3 % blending ratio can be achieved if waste cooking oils are effectively utilized. We concluded that despite the encouragement from policies, insufficient materials and lack of downstream consumptions may be the major reasons for the sluggish development of biodiesel in China. If microalgae biodiesel production technology is overcome in the future, China can compulsorily mix biodiesel on a large scale. This paper provided a comprehensive review of biodiesel-related policies in Malaysia, Indonesia and China, and figured out the key problems that hinder the promotion of biodiesel, helping to understand the dilemma and drive the potential development of biodiesel in China. • Potential biodiesel capacities were estimated among various provinces in China. • The highest biodiesel mix ratio will be ∼13 % if adding all potential botanical oils. • The southern China is more likely to prioritize blending biodiesel than the north. • Biodiesel-related policies in Malaysia, Indonesia and China were fully reviewed. • Inadequate materials and lacking downstream consumption hindered biodiesel growth. [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]

Co-combustion of semi-coke and coal is a prospective technique for large-scale disposal or utilization of the solid waste. In this paper, the co-combustion behaviors and kinetics of semi-coke and coal were studied by thermogravimetric analysis with a focus on the influence of blending method and synergy. The results indicated that the semi-coke combustion was improved by blending with coal, and the interaction between fuels tended to promote the co-combustion. The ignition and burnout temperatures were positively correlated with the carbon content of the mixture, while the comprehensive combustion index and stability index were negatively correlated with it. The layer blending and partition blending method seemed to show stronger promotion than uniform blending method, and the layer blending method with coal in the upper layer was recommended due to the better combustion behavior. The promotion of coal on semi-coke combustion was less affected in devolatilization stage but weakened by the decrease of O 2 concentration in char burnout stage. The apparent activation energy (E a) of the mixture decreased with the increasing faction of coal. The layer blending method with coal in the upper layer had the lowest E a in devolatilization stage and relatively high E a in char burnout stage. The work can give some new insights into waste co-disposal strategy and carbon emission reduction in China. [Display omitted] [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]

Industrial chain structure optimization and digital transformation are crucial factors for achieving carbon emission reduction goals. Based on China's non-competitive input-output tables, this paper constructed industrial chain panel data using the structural path analysis method. We explored the influence of industrial chain division (ICD) on CO 2 emission intensity through panel fixed effects model, and examined the moderating effect of digitization. The research found that: (1) The ICD can significantly reduce CO 2 emission intensity, the results are robust after some endogeneity tests. (2) The emission reduction effect brought by ICD will be more obvious in high-stage, high-energy consumption, and high-intelligence industrial chains. There is still room to improve the emission reduction brought by the division network effect. (3) Digitization plays a positive moderating role on this effect. Furthermore, digital manufacturing and digital services exhibit heterogeneity in various types of industrial chains. (4) The ICD can reduce carbon emission intensity through pathways such as intelligent transformation, technological innovation, and energy efficiency, and digitization has positively moderated these impact pathways. Based on research results, targeted policy suggestions are provided for optimizing industrial chain structure and promoting digital transformation. • This paper constructed industrial chain carbon emission intensity panel data. • This paper assessed the industrial chain digitization by digital intermediate input. • This paper constructed industrial chain synergistic division (ICSD) index. • This paper explored the influence of ICSD on CO 2 emission intensity. • Digitization plays a positive moderating role on carbon emission reduction effect. [ABSTRACT FROM AUTHOR]

Combined heat and power is an inevitable trend in the development of waste-to-power industry. Many waste incineration power generation projects that have already put into operation in China are waiting for transition and upgrading to combined heat and power projects. From a growth option perspective, this paper considers the irreversible process and uncertainty in economic benefits, introduces carbon emission trading mechanism and develops the growth option theory to design the expansion decision making model of waste-to-energy combined heat and power projects, so as to obtain the project value and find the optimal expansion timing. In this paper, a case study is carried out on the expansion decision making of a waste-to-energy combined heat and power project in Shandong Province in China. And two scenarios with specific and flexible expansion times are developed from European and American options separately, as European options require investors to expand at a certain time but American options not. The results indicate that 1) real option approach successfully improves the project value through considering uncertainty, and American option can achieve the optimal expansion time, 2) under the carbon emission trading mechanism, the carbon price affects the expansion index, which has a positive effect on the project value, 3) the linear nature of the income and cost expansion index can help investors make judgments on expansion investments. The effectiveness of the case study implies the practicality of the expansion option method for similar projects to reach dual carbon targets in cost and benefit analysis. • Real option approach is applied in energy transition in WTECHP projects. • European and American options are proposed for certain and flexible decision times. • Expansion time and triggers of WTECHP are incorporated into life cycle management. • CCER is introduced as an environmental element to evaluate expansion decision making. [ABSTRACT FROM AUTHOR]

The support of digital technology is urgently needed to promote low-carbon development and green economic and social transformation and to realize the goal of "carbon neutrality" early. This paper utilizes the "Golden Tax III" project for the digital transformation of China's tax collection and administration and empirically confirms that digital tax collection and administration significantly reduces carbon emissions based on the panel data of 30 provinces (municipalities directly under the central government and autonomous regions) in China from 2010 to 2020, i.e., digital technology plays a positive role in carbon emission reduction. The mechanism test shows that digital technology indirectly affects carbon emissions through industrial structure, technological innovation, and tax structure. Heterogeneity analysis shows that digital technology has a significant inhibitory effect on carbon emissions in the northern region, non-Yangtze River region, provincial administrative areas with heavy local government debt, and a large proportion of tax revenue from the secondary industry and tax revenue from state-owned enterprises. Under the requirement of high-quality and green development of the economy, this paper is of great theoretical and practical significance for using digital technology to ensure the governance functions of tax, help low-carbon development, and reach the goal of "carbon neutrality" at an early date. • This study assesses the impact of digital technology on carbon emissions from the government's perspective. • This study enriches the mechanism by which digital technology affects carbon emissions. • This study provides suggestions to promote the digitization of government affairs and carbon emission reduction. [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]

Electricity cross-subsidy policies have long been criticized for they involve subsidizing households by charging above-cost prices in industrial sectors. This paper examines the environmental and economic impacts of phasing out cross-subsidy in electricity prices in the context of China's Carbon Peaking and Neutrality goals by exploiting a large panel data from 2012 to 2020. We first adopt a price-gap approach to calculate the scale of negative cross-subsidy in China and different sectors. Next, we estimate the electricity demand price elasticity of high-, medium-, and low-emission industries to evaluate how the cross-subsidy affects electricity consumption, carbon emissions, and the output value. Finally, with the 2020 scenario as our baseline, we simulate three distinct policy change Schemes and evaluate the environmental and economic effects of phasing out electricity cross-subsidy in China. We find that if policy makers do not consider the emission levels of different industries when implementing cross-subsidy removal, great environmental harm will be caused. We also find that the potential burden on households of electricity cross-subsidy removal is likely to be relatively small at all implementation stages. This study provides timely policy implications for the ongoing electricity system reform in China. • This paper examines the environmental and economic impacts of phasing out cross-subsidy in electricity prices in the context of China's Carbon Peaking and Neutrality goals. • We find that if policymakers do not consider the emission levels of different industries in cross-subsidy removal, it will lead to large carbon emissions but small output in average. • If the cross-subsidy is fully borne by high-emission industries, the optimal Scheme is to reduce the cross-subsidy by approximately 50%–70% to obtain more economic output and less carbon emissions. • If high-emission bear twice as much cross-subsidy as the medium-emission industries, the carbon reduction and economic output will be maximised at 10%–30% of cross-subsidy removal. • We also find that the potential burden on households is relatively small at all implementation stages. [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]

Existing studies on emission accounting in global value chains (GVCs) have not focused on the relational nature of GVC activities manifested as the interaction of intermediate goods between enterprises. This paper proposes a relational GVC emissions accounting framework based on an inter-country input-output (ICIO) model distinguishing between domestic-owned enterprises (DOEs) and foreign-invested enterprises (FIEs), which is classified as trade-based, investment-based and hybrid-based emissions. Using AMNE-ICIO tables from 2005 to 2016, this paper traces emissions and carbon intensity in relational GVC activities at the global, economic, and industry levels. We find the following: (1) Investment-based emissions accounted for about 94.15% of the increase in relational GVC emissions, of which more than half comes from the interactive activities between DOEs and FIEs. (2) For the United States, high-income economies, and high-tech manufacturing, investment-based emissions were higher than trade-based emissions, and the reverse was true for upper-middle and lower-middle income economies and China. (3) Although relational GVC carbon intensity was high, the trend of decline was significant. (4) Compared to trade activities, investment-based activities were less carbon intensity in China and upper-middle income economies due to the interaction of production between FIEs and DOEs. The findings add new insights into the coordination of global emissions reductions and the allocation of emissions responsibility. • Emphasize the interdependence between enterprises in cross-border production. • Combine GVC linkages with carbon emissions and carbon intensity. • Investment-based emissions are the main factor of relational GVC emissions growth. • The carbon intensity of relational GVC decreased significantly. • Developing countries can access green spillover through investment-based GVC links. [ABSTRACT FROM AUTHOR]

• The influences of the geometric parameters of the reactor on the SCPP-HPCR are investigated. • A formula is proposed to calculate the CO 2 emissions reduction of the system. • The optimal operating conditions of the SCPP-HPCR is analyzed. • 2.38 kg of CH 4 is degraded and 375.52 kg of CO 2 is reduced through the system one day. The increase of 1.09 °C in global temperature resulted in significant catastrophes because of the extreme climate. The climate change rate can be slowed down by reducing the levels of CH 4 and CO 2 in the atmosphere. The solar chimney power plant integrated with a honeycomb photocatalytic reactor (SCPP-HPCR) uses the photocatalytic technology to remove atmospheric CH 4. In addition, CO 2 emissions can be reduced from coal fired power plant due to the generating capacity of the system. In this paper, the influence of the geometric parameters of the reactor and turbine on the overall performance of the SCPP-HPCR is studied by numerical simulation. The obtained results showed that the flow resistance inside the system was mostly caused by the HPCR at low turbine speed, and primarily by the turbine at high turbine speed. Reducing the pore diameter of the reactor could improve the photocatalytic performance of the SCPP-HPCR more than increasing the turbine speed. The SCPP-HPCR having a pore diameter of 3 mm, porosity of 0.85, and constant turbine speed of 180 rpm, built in Qianyanzhou, China, could remove 2.38 kg of CH 4 and reduce 375.52 kg of CO 2 in one day. [ABSTRACT FROM AUTHOR]