Search

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 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]

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]

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]

Addressing the urgent need for accurate carbon emissions forecasting to support global emissions reduction goals, this paper introduces a novel approach for carbon emissions prediction that dynamically considers the spatial–temporal correlation of carbon emissions across forecasting targets. Traditional statistical and machine learning models have limitations, such as oversimplification and inefficiency in capturing evolving dynamics among multiple forecasting targets, alongside a focus on longer forecasting horizons like monthly or yearly. To tackle these, we propose an innovative Dynamic Spatial–Temporal Graph Convolutional Recurrent Network (DSTGCRN), a blend of graph convolutional and recurrent neural network structures customized for up-to-date multi-regional spatial–temporal predictions at a daily level. Comprehensive empirical analyses on datasets from China, the US, and the EU confirm DSTGCRN's superior performance and robustness across diverse geographical contexts. It outperforms the second-best among 10 baseline models, achieving 40.6%, 24.6%, and 38.5% improvements in MAE, RMSE, and MAPE, respectively, across various horizons. The incorporation of environmental data, including temperature and Air Quality Index, as supplementary predictors in the DSTGCRN model, has demonstrated its efficacy in the context of the China dataset. The DSTGCRN model's improved accuracy and daily multi-regional forecasting deepen emission dynamics understanding, supporting the development of informed and region-specific environmental policies that can respond promptly to changes. [ABSTRACT FROM AUTHOR]

This study delves into the nexus between the efficiency of carbon emission allocation and the efficiency of green development within the context of innovative city construction. Leveraging data from 283 prefecture-level cities and corresponding provincial-level panel data spanning the period from 2005 to 2019 in mainland China, the research employs the zero-sum gain DEA model to compute provincial carbon emission allocation efficiency and allocate allowances. Furthermore, it utilizes the all-factor non-radial directional distance function and the SBM-DEA model to gauge the green development efficiency of prefecture-level cities. The double-difference method is applied to evaluate the impact of innovative city construction on regional green development efficiency. The results indicate that an imbalance between carbon emission allocation efficiency and emission quotas detrimentally affects urban green development. However, technological progress, factor accumulation, and the institutional environment associated with innovative city building mitigate this negative impact. Heterogeneity analysis reveals a differentiated effect of innovative city building on regional green development efficiency. This paper not only explores the concept of achieving an equitable distribution of carbon emission allowances but also examines how innovative city building influences regional green development. By establishing connections between urban policies, the equitable distribution of carbon emission allowances, and regional green development, it introduces a new perspective for promoting high-quality development at the regional level. [ABSTRACT FROM AUTHOR]

Green finance is a financial innovation that directs capital allocation towards green industries. How will this affect regional carbon emissions? Based on the data on green finance and carbon emissions of 30 provinces in China from 2008 to 2019, this paper employs a multivariate linear regression model and a spatial econometric model to empirically study the impact of green finance on carbon emissions. The results find that (1) green finance significantly reduces provincial carbon emissions, specifically through promoting a cleaner energy structure and an advanced industrial structure, as well as improving the quality of green innovation. (2) Heterogeneity exists between regions. In eastern regions and areas characterized by high levels of marketization and minimal fiscal pressure, the role of green finance in promoting provincial carbon emission reduction is more pronounced. (3) Spatial econometric analysis found that green finance has a significant spatial spillover effect on carbon reduction in adjacent regions. Specifically, the flow of green resources and green ideas between provinces facilitates the formation of regional radiation, while green competition generates a siphon effect on neighboring regions. These findings provide some meaningful policy implications to achieve China's dual-carbon goal by promoting green finance. • Green finance has significantly reduced China's provincial carbon emissions. • The upgrading of energy structure and industrial structure is a positive channel to reduce carbon emissions. • Green innovation strengthens the carbon reduction effect of green finance, but reveals the potential "greenwashing". • Green finance has a significant spatial spillover effect on carbon reduction in adjacent regions. • Policymakers should develop flexible, dynamic and coordinated green finance development policies. [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]

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]

This paper aims to study the significance of China's Industrial Structure Rationalization (ISR) in reducing carbon emissions. To this end, this study uses panel data from 30 Chinese province from 2000 to 2019 to measure the Industrial Structure Rationalization of each province by calculating the Thiel index, base on which a nonlinear autoregressive lagged distribution (NARDL-PMG) model is established to explore the impacts of industrial structure rationalization on carbon emissions. The results show that: (1) There still exist significant regional differences between Eastern and Central-Western regions in industrial structure as illustrated by the ISR index. The industrial structure in Eastern region is more rational; (2) In the long run, the carbon emission in China will drop when the industrial structure becomes more rational; (3) However, in the short run, the carbon emission in China will increase when the industrial structure becomes more rational. Besides the findings above, the major difference between this paper and the extant researches is that this paper pays attention to the relationship between industrial structure rationalization and environmental quality by investigating the asymmetric influences of industrial structure rationalization index's positive and negative shocks on carbon emission, which lays solid foundations for government aiming to set more detailed policies. • Focus on the impact of rationalization of industrial structure on CO2 emissions. • Focused on the linear relationship between industrial structure and carbon emissions. • Attempts to analyze three regional pairs from the East, Central and West regions. • Provide a reference for developing countries to achieve sustainable development. [ABSTRACT FROM AUTHOR]

Innovative emission reduction technologies combined with optimized processes can effectively reduce the environmental pressure in the iron and steel industry (ISI). Identifying and comparatively analyzing the carbon emissions (CE) from steel productions is conducive to achieving China's ambitious carbon reduction targets. In this paper, we investigated two innovative routes: the shaft furnace-induction furnace-basic oxygen furnace route (SF-IF-BOF) and shaft furnace-electric smelting furnace-basic oxygen furnace route (SF-ESF-BOF), alongside two traditional routes: the blast furnace-BOF route (BF-BOF) and SF-electric arc furnace route (SF-ESF). The analysis was based on a functional unit of 1000 kg of crude steel (CS). By establishing the mass and energy balance models and decision criteria, 12 typical smelting scenarios for these routes were analyzed and compared in terms of materials consumption and CE. The results showed that increasing the proportion of scrap was beneficial for reducing CE. Under the condition of a 50% scrap ratio, the CE of the SF-IF-BOF, SF-ESF-BOF, BF-BOF, and SF-EAF routes were 768, 823, 946, and 870 kg, respectively. The SF-IF-BOF route displayed the most significant advantage of CE reduction. In addition, by using 100% zero-carbon electricity substitution, the SF-EAF route exhibited the greatest CE reduction effect of 41% (from 870 to 510 kg/t). While deploying 100% biomass fuels to replace coal, the CE of the BF-BOF route reduced by 80%. Finally, after introducing biomass fuels and zero-carbon electricity, the CE of the SF-IF-BOF route was minimized to a significantly low 13 kg/t (from 768), nearing zero CE. This research is expected to provide a novel solution for further CE reduction in the future of ISI, contributing to environmental sustainability and carbon reduction goals. • Suggestions for solutions to reduce CO2 emissions in the steel industry are provided. • Emissions of the SF-IF-BOF and SF-ESF-BOF compared to the BF-BOF and DRI-EAF routes. • DRI is considered to be generated using COG zero reforming process. • Using zero-C electricity and biomass can reduce CO2 emissions for the steel industry. [ABSTRACT FROM AUTHOR]

As the integrated gas-electricity system (IEGS) grows within the context of carbon abatement, natural gas shippers (NGSs) face a twofold challenge: perceiving the dynamic behavior of the gas system swiftly while considering the revenue and costs of IEGS. To address these challenges, a novel Integrated Electric-Gas Dispatch (IEGD) model is introduced in this paper. Firstly, the Box-Jenkins-based NGPN rapid transient flow model is proposed. Secondly, an IEGD model with optimization targets focusing on IEGS cost and NGSs revenue is introduced. Finally, the proposed natural gas flow model is validated through its application to an inter-provincial natural gas pipeline network and a regional-level network in China's central and western regions. A comparison with commercial software indicates that the proposed model offers additional advantages, with a total relative average error of 0.57% and 0.36%, respectively, and a computation speed of 62.3 times and 72.4 faster. When the IEGD model is applied to an IEGS, promising outcomes are revealed by two distinct scenarios: carbon emissions within the IEGS can be reduced by as much as 32.64% per day, considering carbon taxes. Furthermore, through intensifying the collaborative integration of gas and electricity systems, overall carbon emissions can be lowered by up to 48.19%, and NGSs revenue can be boosted by as much as 11.2%. • A novel rapid natural gas network transient flow model is proposed. • Natural gas transient flow is first converted to the Box-Jenkins system. • The network topology can be established by the proposed model conveniently. • Natural gas shipper revenue and integrated system cost are considered as objective. • Overall carbon emissions can be lowered by up to 48.19%. [ABSTRACT FROM AUTHOR]

Inequality and climate change are major challenges for sustainable development, but a dilemma between the objectives has been widely observed. Based on the panel data of China Household Finance Survey (CHFS), inequality in carbon emissions across income groups is witnessed, which provides basics for the study. From a quasi-natural experiment, an increase of 9.9% in household per capita carbon emissions (HCEs) of the impoverished group is found after the Targeted Poverty Alleviation policies (TPA) in China, providing evidence for the enhancement of poverty alleviation measures on equal right for household carbon emissions. Specifically, dual mechanism of transfer payments and employment assistance acting as direct and indirect strategies to enhance family wealth are examined as the pathways to carbon equality. Further, a decline in household carbon emission intensity in the impoverished group is also observed after the treatment, which implies the accelerating role of TPA in low-carbon lifestyle formulation for the impoverished families. The findings of this paper confirm the positive effect of TPA policies on carbon equality for households, and also refute the "equality-pollution dilemma", which provide insights for policy makers in formulating equitable decarbonization policies and allocating the carbon budget. • Poverty alleviation policies have reduced household carbon emission inequality. • Transfer payments and employment assistance act as mechanisms of policy effect. • Household carbon emission intensity is decreased by the policies. • Policy effect is more prominent in families suffered from special burdens. [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]

This paper delineates the impact of digital infrastructure construction (DIC) on carbon emission efficiency (CEE) within the ambit of China's "Broadband China" pilot policy (BCP). A quasi-natural experimental framework reveals direct effects, indirect influences, non-linear relationships, and spatial heterogeneity of DIC on CEE. The research distills several pivotal insights: (1) DIC exerts a markedly positive impact on CEE, as evidenced by comprehensive robustness analyses. (2) The digital service industry agglomeration and green technology innovation act as key mechanisms through which DIC influences CEE. (3) The intensity of BCP exhibits an "inverted U-shaped" relationship with CEE. As the level of CEE increases, the impact of DIC on CEE gradually rises, demonstrating a marginal increasing effect. (4) The spatial spillover effects of DIC on CEE vary with increasing distance, revealing a dichotomy: an "agglomeration shadow" within 200 km of policy pilot cities and a pronounced stimulative effect on CEE within a 200–300 km radius. (5) The efficacy of DIC in enhancing CEE is augmented by proximity to central cities, with the optimal radius of influence for central cities determined to be 200 km, beyond which a diminishing gradient effect is observed, forming a "core-peripheral" spatial pattern. The findings endorse the strategic augmentation of digital infrastructure as a lever for economic and environmental co-benefits, steering towards carbon neutrality and equitable regional development. [ABSTRACT FROM AUTHOR]

Under the background of "double carbon", ecological water has become one of the significant resources to ensure the healthy and sustainable development of the regional ecological environment. And the ecological water consumption prediction is a prerequisite for optimizing water supply structures. Considering the impact of CO 2 emissions on ecological water consumption, the FGM(1,1) model was firstly used to predict CO 2 emissions considered as an impact factor in this paper. Then, an adjacent accumulative grey multivariate convolution model (AGMC(1,N)) was combined with the Average Weakening Buffer Operator (AWBO) to predict the annual ecological water consumption of 30 provinces (municipalities and autonomous regions) in China. The results show that the AGMC(1,N) model combined with the AWBO has better prediction effect. In addition, in the next decade, only six provinces in the northern region will have a decreasing trend in ecological water consumption. However, the other provinces are showing an upward trend. The ecological water consumption trends deviate from the CO 2 emission trends in 12 provinces. The research results are beneficial for the formulation of the ecological water consumption policies and the achievement of the dual carbon goals. [ABSTRACT FROM AUTHOR]

The accurate prediction of China's CO 2 emissions provides a reference and early warning for the implementation of the government's environmental strategy and has far-reaching significance for the world's environmental protection. The carbon emission system is a nonlinear dynamical system influenced by multiple factors with multiple data features. This paper establishes a novel grey differential dynamic multivariate prediction model with recurrent neural network. It uses the grey differential dynamic multivariate prediction model to describe the dynamic characteristics of the nonlinear system. And it uses recurrent neural network to extract data features. The new model is used to compensate for the shortcomings of the grey prediction model that use the least squares method to solve the model parameters affecting the accuracy of the model. The numerical solution of the whitening equations of the new model visualizes the hidden layer state function of the recurrent neural network. The optimal parameters of the new model are obtained through repeated training to improve the prediction accuracy of the model. Finally, the new model is applied to the prediction of China's CO 2 emissions to verify the validity of the new model from four different perspectives. The results show that the simulation and prediction errors of the new model for data of different lengths are less than 5%. The average simulation error in the optimal scheme is 3.01%, and the average prediction error is 0.78%. The results of the new model are better than the results of the other models. This indicates that the new model has better prediction results. Applying the scenario in forecasting the amount of carbon dioxide in China from 2020 to 2026 yields a forecast that matches the actual trend, further illustrating the validity and feasibility of the model. Finally, the forecast results are analysed, and relevant policy recommendations are provided. • A novel neural network grey prediction model is developed. • The model uses neural networks to deeply explore the time-series type data features. • The dynamic nature of the system is reflected using multiple differential grey models. • Successful prediction of CO2 emissions in China. [ABSTRACT FROM AUTHOR]

Mitigating greenhouse gas emissions is a significant global challenge, and precise prediction of carbon emissions holds the utmost importance for China to attain its dual carbon goal. To overcome the limitations of existing studies using a single forecasting method, based on quadratic exponential smoothing, multiple linear regression, and Gaussian process regression models, this paper constructs a carbon emission combination forecasting model with the generalized induced ordered weighted average (GIOWA) operator and analyzes carbon emission reduction performance. Empirical testing utilizing China's carbon emission data from 1980 to 2020 reveals the following findings: (1) The GIOWA combination forecasting model significantly enhances the accuracy of carbon emission forecasts, with an average accuracy exceeding 99.5% over the sample period, surpassing various single forecasting methods. (2) The carbon emission reduction target can be achieved under three different scenarios of low, average, and high GDP growth rates. Specifically, under the low growth rate scenario, China can achieve a 60% reduction in carbon intensity by 2025 and a 65% reduction by 2030. This study offers valuable decision support for the development of effective carbon reduction policies. [ABSTRACT FROM AUTHOR]

Given the worsening environmental pollution and China's carbon peak and carbon neutrality goals, it is imperative to study the low-carbon travel behavior of urban residents. Previous research has mainly focused on objective environmental factors, subjective behavioral factors, and low-carbon travel behavior. However, the evolving decision-making of local governments, community residents, and individuals within the low-carbon travel system still needs to be explored. Tripartite evolutionary game theory is an effective method for studying the dynamic changes in strategies among limited rationality multiple actors in long-term repeated games, making it applicable to this study. Therefore, this paper simulates participants' behavior using evolutionary game theory, conducts stability analysis of equilibrium points of the replicator dynamic system using the Lyapunov first method, derives evolutionarily stable strategy combinations under different conditions, and finally performs simulation analysis using Matlab. The simulation results indicate: (1) By implementing reasonable incentive mechanisms, Local governments can encourage citizens to adopt low-carbon travel and community transformation. They should pay attention to their expenditures and subsidies, manage their spending to reduce consumption, maximize efficiency, and strive to achieve carbon emission reduction goals. (2) The likelihood of residents choosing low-carbon travel is mainly influenced by direct advantages such as health and economy in the initial stages, and later, it is more affected by the indirect benefits brought about by subsequent objective environmental changes. (3) The cost of renovation significantly affects the built environment of communities, leading to a reduction in renovation costs and the adoption of uniform standards and, consequently, stimulating enthusiasm for community transformation. The research findings suggest that the government can collaborate with the public to reduce carbon emissions by implementing specific environmental changes and providing incentives to encourage citizens to participate in low-carbon transportation. Simultaneously, the government can cooperate with the public, considering the quality of environmentally friendly transportation for citizens, formulating uniform regulations, reducing renovation costs, and achieving the highest low-carbon goals with minimal financial expenditure. [ABSTRACT FROM AUTHOR]

In order to probe collaborative environmental governance (CEG) in China's "1 + N" policy framework for carbon peak and carbon neutrality, this paper applies the Actor-network theory (ANT) as an analytical framework to explore carbon reduction policy coordination. We then model ANT's relations with an evolutionary game theory (EGT) model to examine the evolutionarily stable strategies in CO 2 emission reduction by various actors including the central government, local governments, commercial banks, and polluting enterprises. Our objective is to examine policy coordination as the key enabler for governing success via an ANT-based mechanism design in China's institutional context. Combining the strength of ANT with a four-party EGT model, we investigate how to improve policy coordination to mobilize the actor-network for promoting CEG. Simulations are conducted to examine the effectiveness of policy coordination involving multiple policy instruments for controlling carbon emissions. The central government fulfills leadership in translating the interests of other actors and shaping the desired collaborative network. Without proper coordination, environmental policies may counteract each other. Government transfers and subsidies have direct impacts, but in the long run enhanced competitiveness and profitability of enterprises represent the intrinsic key to CEG success. From a methodology perspective, policy simulation in an EGT framework represents a novel addition to the research toolbox that expands ANT. [ABSTRACT FROM AUTHOR]

The aim of the paper is to evaluate empirically the main implications of digital technology (DT) on carbon emissions (CE). Our sample focuses on 283 cities of China over the period from 2003 to 2019, and the effect of DT on CE is examined with a threshold spatial effect model. Empirical results show that DT has a negative impact on carbon emissions and the transmission mechanism contains both a direct impact on local region and a spillover effect across regions. There is empirical evidence of a threshold effect in the relationship between DT and CE, with stronger carbon reduction effect for DT values larger than the established threshold. Moreover, CE reduction effect of DT appear to be amplified by the level of marketization. Regions with a higher level of marketization thus show a more significant manifestation of CE reduction effect attributed to DT. Our results provide empirical evidence that DT development may contribute to achieving carbon neutrality at least partially. [ABSTRACT FROM AUTHOR]

Being one of the significant conduits linking international and domestic markets, agricultural trade is an area of study that commands attention. While it may bring about transnational carbon emission transfers, it begs the question: does it promote carbon reduction in a country's agricultural sector? Such an inquiry holds profound implications for optimizing agricultural trade and promoting low-carbon agricultural advancement. Utilizing two-way fixed effect model, mediating effect model and dual-fixed spatial Durbin model, this paper examines the impact effects, mechanisms and spatial characteristics of agricultural trade openness (ATO) on agricultural carbon reduction using panel data from Chinese provinces spanning 2000 to 2021. The main findings include: (1) ATO markedly and positively influences the reduction of agricultural carbon emissions (ACE), this conclusion maintains its validity under endogeneity treatment and robustness tests. (2) ATO contributes to reducing ACE through three intermediary channels: scale effect, technological effect, and structural effect. (3) From a spatial perspective, a notable positive spatial spillover effect is observed from agricultural trade openness to agricultural carbon reduction, with the spatial carbon reduction effect being more apparent. (4) The spatial carbon reduction effect of agricultural trade liberalization exhibits heterogeneity across different natural geographical locations and levels of ATO. The study confirms the vital role of ATO in promoting agricultural carbon reduction in typical countries, underscoring the urgency and importance of bolstering cross-border agricultural trade cooperation and domestic agricultural product circulation in the domain of climate change. • The impact of agricultural trade openness (ATO) on agricultural carbon reduction is investigated in China. • The scale, technological, and structural effect of ATO serve as intermediary channels in reducing carbon emissions. • ATO engenders positive spatial spillover effects on agricultural carbon reduction. • Bolstering cross-border agricultural trade cooperation are of importance and urgency in the domain of climate change. [ABSTRACT FROM AUTHOR]

Big data industry development and carbon dioxide emissions reduction are the crucial driver and objective functions of economic growth, respectively. Whether the two types of corresponding policies can achieve the "win-win" effect is the key to green development transformation in the future. However, little attention has been paid to the influence of big data industry development on carbon dioxide emissions. Based on the quasi-natural experiment in China's national big data comprehensive experimental area, the paper identifies the causal effect between big data industry development and carbon dioxide emissions. Specifically, the panel data of 282 cities in China spanning from 2010 to 2019 are used in regression analysis. The study reveals that the big data industry development has a substantial impact in reducing carbon dioxide emissions. Meanwhile, the findings are confirmed by a set of rigorous robustness checks. The heterogeneity analyses suggest that the effect of inhibiting carbon dioxide emissions due to the big data industry development is more significant in eastern & central China, and large-sized cities. In addition, the big data industry reduces carbon dioxide emissions through the effects of industrial structure optimization, technological innovation, and resource allocation. Our findings contribute to the nexus between big data industry development and carbon dioxide emissions. In light of these findings, the paper recommends that governments integrate economic growth and environmental protection policies by promoting big data industry development. • The paper provides a novel insight into the CO 2 emission from the perspective of big data industry. • Based on quasi-natural experiment, the paper has identified the causal effect between the big data industry development and CO 2 emissions with the Difference-in-Difference (DID) methodology. • Big data industry development effectively stimulate the reduction of CO 2 emissions. [ABSTRACT FROM AUTHOR]

China's industry is facing a carbon lock-in (CLI) dilemma. Based on the complexity and dynamics of CLI, exploring diversified unlocking paths is an important way to achieve emission reduction goals. This paper innovatively applies system dynamics (SD) to the study of CLI prediction and unlocking path, and systematically constructs an industrial CLI SD model, trying to break the positive feedback mechanism of CLI through multiple causality and feedback chains. This paper simulates and predicts the changing trend of the CLI level of China's industry and 8 major subsectors from 2020 to 2050. At the same time, the random forest algorithm is used to select the regulatory variables of policy analysis. Compared with the previous research methods, the accuracy and objectivity of the selection of regulatory variables are improved, so as to test the effectiveness of the unlocking path under each scenario. The results show that (1) the whole industry faces a serious CLI problem and is still in a deep lock-in state. From the perspective of subsectors, the light, electromechanical, and textile industries have achieved unlocking; the oil and extractive industries are in a moderately lock-in state; the chemical, steel, and power industries are in a deep lock-in state; and the CLI situation is serious. (2) The results of the random forest algorithm show that R&D investment, the proportion of fixed asset investments in the energy industry, car sales, energy structure, and carbon emission industry structure are the most significant factors affecting CLI in each subsystem. (3) Compared with the existing economic development model, the technological, institutional, social, and comprehensive unlocking scenarios can all enable industry to achieve carbon peak and carbon unlocking in advance. However, the effect of each scenario is as follows: comprehensive unlocking scenario > technological unlocking scenario > institutional unlocking scenario > social unlocking scenario. (4) The unlocking times of the oil, chemical, steel, and power industries are relatively late in each scenario. To realize carbon unlocking in industry, these four areas should be focused on in the future. This study helps policymakers formulate reasonable policies to accelerate industrial carbon unlocking and promote the implementation of the "dual carbon" strategy. • The whole industry faces a serious carbon lock-in problem. • The technological, institutional, social and comprehensive unlocking scenarios can all achieve carbon unlocking in advance. • The comprehensive unlocking scenario has the best effect, and the social unlocking scenario has the worst effect. • The oil, chemical, steel and power industries should be focused on in the future. [ABSTRACT FROM AUTHOR]

The failure of the global food system to produce food in a sustainable way needs to change urgently, and a solid push to harmonize low-carbon food production with stable supply security is the right direction in which modern agriculture must evolve, but it is more difficult for large food-producing countries, and finding the right practices or systems to help policymakers or producers address this dilemma is critical. This requires political will, increased financing and top-level design. Digital inclusive finance (DIFI) embodies the financial concept of a community of human destiny, and it is worth examining whether this more inclusive and comprehensive financial service can shoulder the "responsibility" of "ensuring food security and reducing carbon emissions" in agriculture. This paper takes China's grain production system as an example, measures the coordinated development level of food production ensuring supply and reducing carbon emissions, and then analyzes the overall and regional characteristics of it. It is found that the coordinated development trend of China's food production ensuring supply and reducing carbon emissions is relatively stable during 2011–2020, fluctuating slightly above and below 0.9, and the central region has the highest level of coordinated development. The empirical results show that DIFI has led to a 4.3 percentage point increase in the level of coordinated development of food production ensuring supply and reducing carbon emissions during the decade, showing a stronger spatial spillover effect on neighboring regions than the local effect. At the same time, in the research of regional division in China, the impact of DIFI on the level of coordinated development of food production ensuring supply and reducing carbon emissions varies across regions, with typical uneven characteristics, and the promotion effect is more significant in the central and northern regions of China. Overall, this paper provides a simple tool for policy makers or producers to understand the balance between guaranteed output and low-carbon development of agricultural production activities. This paper will provide a methodological basis for assessing and standardizing low-carbon agricultural practices, innovating financial development models and systems, and promoting sustainable agriculture. [Display omitted] • Measuring coordinated development level of ensuring food supply and low-carbon. • Digital inclusive finance had increased the coordinated development level by 4.3%. • Digital inclusive finance also had a significant spatial spillover effect. • The role of digital inclusive finance showed a typical non-equilibrium feature. • The study's results could help to sustainable agriculture in agricultural country. [ABSTRACT FROM AUTHOR]

Carbon emission policy aims to restrict carbon emissions from energy-intensive companies. It encourages target companies to take green innovation but brings fulfillment pressure. Policy prospects for a low-carbon economy are widely discussed in current studies while insufficient attention has been paid to the effect of the policy on the operating activities of target companies. Using the data of Chinese A-share listed companies from 2007 to 2020, this paper explores the effect of carbon emission policy on the financial performance of target companies. The main empirical results prove the significant positive effect of the policy on the financial performance of target companies and reject the interference of earnings management and survivor bias. Further analysis indicates that target companies significantly reduce the selling, general and administrative (SG&A) expenses and non-operating expenses. The trade of carbon quotas between target companies is allowed and it is regarded as non-operating activity. Results of non-operating revenues and expenses prove that target companies tend to actively reduce carbon emissions but the action does not exceed the policy expectation. The increasing efficiency of asset utilization represents that target companies have taken relevant measures to deal with overcapacity. This paper confirms the positive policy responses of target companies. Policy implications are proposed from the perspective of coverage expansion and market incentive mechanisms to realize the full potential of target companies for carbon emission reduction. [ABSTRACT FROM AUTHOR]

Abstract With the development of China's economy, the use of fossil energy has become more and more, resulting in increasing carbon emissions. CO 2 emissions have caused global warming, threatening humans and creatures on Earth. In order to effectively suppress the growth of carbon emissions, it is necessary to analyze the influencing factors of carbon emissions and apply them to predict carbon emissions. This paper presents sixteen potential influencing factors and uses grey relational analysis to identify the factors that have a strong correlation with carbon emissions. The principal component analysis (PCA) is used to extract the four principal components, which reduce the redundancy of the input data. The long short-term memory (LSTM) method is established to predict carbon emissions in China. We use back propagation neural network (BPNN) and Gaussian process regression (GPR) to compare LSTM method. The simulation results show that the prediction accuracy of carbon emissions based on LSTM is better than that of BPNN and GPR, indicating the effectiveness of PCA and LSTM in prediction of carbon emissions. Finally, this paper provides the theoretical basis for China to reduce carbon emissions by studying prediction of carbon emissions. Highlights • Grey correlation analysis is applied to identify factors associated with carbon emissions. • Principal components analysis is used to simplify input variables and obtain the main factors affecting carbon emissions. • The long short-term memory model is used for the first time to predict carbon emissions. • The direction of reducing carbon emissions in China is given by analyzing the prediction results. [ABSTRACT FROM AUTHOR]

We try to expand the political promotion tournaments in Chinese local governments from raising GDP to the level of increasing fiscal revenues. From the vantage point of officials' performance appraisal, we investigate the impact of local government officials' political ambitions, represented by the ex-ante commitment level of fiscal revenue targets, on carbon emission intensity (CEI). Utilizing a sample of 209 prefecture-level cities in China spanning 2006 to 2019, this paper empirically scrutinizes the influence of local government political ambition on CEI. The findings reveal that the greater the political ambition of local government officials, the more pronounced the reduction in CEI. Furthermore, our study demonstrates that political ambition contributes to the decline of CEI by elevating the levels of environmental attention and green innovation. This research not only aids in comprehending the rationale and necessity of the political promotion tournaments implemented by the Chinese central government but also offers valuable insights for other developing countries seeking to mitigate CEI. [ABSTRACT FROM AUTHOR]

The carbon emission trading scheme (CETS) has been gradually introduced in China to control carbon emissions and boost economic and social development. The existing literature has evaluated the market potential of pilot CETSs or a certain industry, yet no study has focused on the industrial sectors to be covered in the national CETS to analyze trading flexibility and the sector inclusion sequence. This study presents an analytical framework for estimating market potential (i.e., potential gains and carbon emission reduction potential) and industrial sector inclusion sequences for China's national CETS using by-production models. Three simulation scenarios (i.e., no-trading scenario, power sector trading scenario, and multiple-industry trading scenario) and two trading modes (i.e., contemporary and intertemporal trading mode) are simultaneously considered. The novel evidences are: (i) There would be 39.93% (27.7 trillion CNY), 65.26% (273.0 trillion CNY) and 159.42% (666.7 trillion CNY) national aggregated potential gains of CETS in intertemporal power sector trading scenario, contemporary multiple-industry trading scenario and intertemporal multiple-industry trading scenario, and they would help save 3.60%, 5.18% and 6.05% of CO 2 emissions reduction, respectively. (ii) CO 2 emission permits would transfer from nonmetal minerals, ferrous metals, and electricity, to paper making, non-ferrous metals, petrochemicals, and chemicals under the intertemporal multiple-industry trading simulation. (iii) Based on the principle of potential gain maximization, it is recommended that the sector of smelting and processing of non-ferrous metals should to be included as the next sector in national CETS. The results show that national CETS has great market potential for achieving China's joint carbon control and economic growth goals. [ABSTRACT FROM AUTHOR]

Under the background that China will achieve the goal of carbon neutrality by 2060, analyzing the impact of carbon neutral target constraints on the welfare of urban and rural residents is an important part of the design of a carbon emission reduction policy mechanism, in this paper, the dynamic recursive CGE(Computable general equilibrium) model is used to simulate the changes in welfare level, income consumption, and CO2 emissions of residents and their urban-rural heterogeneity under the policy of imposing a carbon tax on the fossil energy industry from 2022 to 2060. The results show that: compared with the BAU scenario, by 2060, first the income and consumption of residents will decrease slightly. Second, the target constraint of carbon neutrality makes the equivalent variation and compensate variation of urban and rural residents' welfare decrease slightly, and the equivalent variation and compensate variation of urban residents decrease more than those of rural residents. The following conclusions are drawn: first, the carbon-neutral target constraint makes the welfare of urban and rural residents decline slightly, but it will not have a strong impact on residents' income and consumption. Second, this constraint has a greater impact on the income, consumption and savings of urban residents than those of rural residents. [Display omitted] • A five-layer nested dynamic recursive CGE model is established to analyze residents' welfare. • Carbon taxes are incorporated into production decisions as a policy cost for energy companies. • The heterogeneity of the impact of carbon tax policy constraints on the welfare of urban and rural residents was analyzed. • The government needs to improve the intensive and diversified energy supply in rural areas to reduce the urban-rural gap. [ABSTRACT FROM AUTHOR]

Clarifying the clean energy (CE) development path is significant for realizing energy system transformation, coping with climate risks, and ensuring energy and ecological security. This paper uses national data from China from 1978 to 2021 as a sample. It considers the year-by-year dynamic indicators of changes in technology, population, industry, and economic factors in the short term. It takes the mandatory carbon emission reduction targets set by the country as the basis for carbon constraints. The Markov chain model was introduced to construct a power demand structure prediction model under scenarios to more accurately quantify the energy-saving and emission-reduction paths under different carbon constraints and economic development scenarios. The results show that China's electricity demand will rapidly grow in the short term. The upper limit constraint of thermal power generation under the high and normal economic growth models still has room to grow in the short term under the target carbon emission constraint scenario. During 2025–2030, the overall lower limit growth rate of the CE power generation structure under the target emission reduction scenario must exceed 8%, and the overall growth rate under the high-efficiency emission reduction scenario must exceed 12%. By 2030, the proportion of hydropower in CE generation is estimated to decrease to 33.7%, while nuclear power, wind power, and photovoltaic power generation will increase to 16.3%, 30.5% and 19.5%, respectively. These results provide a reference for the government to formulate a CE development path against the background of carbon constraints. [Display omitted] • Clarified China's short-term energy development path under carbon constraints. • Thermal power will not exit the market quickly in 2030. • Constructed an energy and power prediction model under carbon constraints. • Wind energy and photovoltaic energy will become the main development energy sources. • Support low-carbon power sector transformation under carbon policies. [ABSTRACT FROM AUTHOR]

Digital technologies are a key driver of carbon peaking and carbon neutrality. However, as the physical foundation supporting digital technology, how digital infrastructure affects carbon emissions is unclear. Based on the panel data from 2008 to 2019, this paper examines the impact of the Broadband China Policy on carbon emissions by adopting a multi-period difference-in-differences (DID) method. The empirical findings indicate that, first, digital infrastructure development plays a significant role in reducing carbon emissions in China. Second, the Broadband China Policy significantly reduces carbon emissions especially in China's low-carbon emission regions, high-level digitization regions, and non-resource-cursed regions. Third, the implementation of the Broadband China Policy facilitates carbon emissions reduction through the promotion of green technology progress, optimization of industrial structures, green transformation of residents' lifestyles, and electrification of energy mix. Finally, the Broadband China Policy has a positive spatial spillover effect on the carbon intensity in the surrounding regions of pilot cities, but it has no significant effect on the total carbon emissions and per capita carbon emissions in the surrounding regions. The results provide important insights for digital infrastructure construction to achieve a win-win situation for economic development and emission reduction. • It explores the impact of Broadband China Policy on carbon emissions reduction. • Digital infrastructure development has positive impact on reducing carbon emissions. • The reduction effect is heterogeneous in regions with different characteristics. • Carbon emissions can be reduced at both industrial and individual levels. [ABSTRACT FROM AUTHOR]

The significant carbon emissions generated by China's sludge treatment industry cannot be ignored. However, with only a few recent well-executed studies on carbon emission reduction in the sludge treatment field, the literature awaits a more comprehensive assessment and prediction whether the sludge treatment industry can achieve the dual-carbon target. This article aims to fill this gap, holistically examining the carbon emission reduction potential in the industry. Using the moving average method and IPCC method, the projected carbon emission value of sludge treatment in China from 2021 to 2030 indicates a total net carbon emission of 0.3 million tons by 2030. This suggests that the sludge treatment industry is on track to meet the carbon peak target, leaving surplus carbon quotas or credits available to assist other industries for carbon emissions reductions. The study also finds that only incineration and composting demonstrate the potential to be able to partially offset carbon emissions through resource utilization in certain stages or processes. Therefore, the current sludge treatment methods do not yield comprehensive emission reduction effects and cannot provide sufficient contribution to China's dual carbon goals. To address this issue, the paper explores a new scheme that focuses on improving the sludge treatment process. The scheme comparative analysis reveals that, even with all sludge treatment methods optimized, the total net carbon emissions of the industry could only be reduced to 0.058 million tons. This reduction falls short of significantly mitigating carbon emissions to achieve the carbon neutrality goal. Therefore, industries unable to achieve substantial net carbon reduction may need to explore alternative measures, such as carbon sinks, to ultimately attain carbon neutrality. [ABSTRACT FROM AUTHOR]

Food loss and waste become the sever problem in the modern society. This paper studies the carbon emissions related to different circulation forms of lychee，which is a typical perishable fruit in China. First, we construct a kinetic model of lychee by using the Arrhenius equation. And then, we propose a carbon emission measurement with the unit effective carbon emission and the comprehensive carbon emission utility by using life cycle assessment. With this measurement, we measure the rate of loss and life cycle carbon emissions of four lychee's circulation scenarios, including: cold chain, room temperature, cold chain broken at the beginning and cold chain broken at the end. The results show that with the traditional carbon emission measurement, the carbon emissions generated by the cold chain circulation scenario are the highest in total carbon emissions under the four scenarios. But using the unit effective carbon emissions measurement, the total carbon emissions under the cold chain circulation situation is 34.84 % less than those of the room temperature circulation. Under the cold chain circulation scenario, the unit effective carbon emission and comprehensive carbon emission utility are 0.38 kgCO 2 /kg and 85.33 %, respectively. Improving the rate of cold chain circulation can improve the comprehensive carbon emission utility and achieve land-saving. Comparing with the cold chain circulation rate in China in today, when it increases to 95 %, the comprehensive carbon emission utility of lychee supply chain increases to 81.65 %, and the required land is reduced by 54.84 %. • The unit effective carbon emission and the comprehensive carbon emission utility are proposed. • A kinetic model of lychee is developed to measure the loss rate of lychee. • A life-cycle carbon emissions model is developed to estimate lychee carbon emissions with different scenarios. [ABSTRACT FROM AUTHOR]

The comprehensive cohesion of the digital economy, structural deviation adjustment, and green development is a crucial step towards promoting high-quality economic growth and realizing carbon peak and carbon neutrality. This paper probes the impact of intra- and inter-regional digital economy on carbon emissions, considering the mediating effect of structural deviation, utilizing panel data from 267 prefecture-level cities in China spanning the years 2011–2019. The findings reveal the following key insights. First, the connection between the digital economy and carbon emissions within cities follows an inverted "U" shape. In the early stages, the digital economy leads to an average increase in carbon emissions of 0.069%. However, in the later stages, the digitized economy markedly decrease emissions. Second, both the digital economy and carbon emissions exhibit spatial spillover effects. Within the region, DE has a significant nonlinear spillover effect on CO 2 emissions in the neighboring regions, with the spatial decay boundary of this effect extending up to 380 km. Third, analysis of the impact mechanism reveals that the digital economy mitigates local and neighboring carbon dioxide emissions by adjusting structural deviation. Heterogeneity analysis indicates that the digital economy is more likely to have a carbon emission reduction effect in cities that are not involved in the industrial transfer and those that do not belong to the old industrial base. These findings provide a rationale and policy reference for China to harness the opportunities presented by digital economy development and to achieve the "dual-carbon" goal. [ABSTRACT FROM AUTHOR]

China has implemented the coal-to-clean-energy shift policy in rural areas of northern China to improve air quality, optimize energy structure and reduce greenhouse gas emissions, resulting in a significant increase in natural gas and electricity consumption. The policies shifts can reduce CO 2 emissions, but methane emissions from switching processes may contribute to short-term climate impacts. The climate impact during the policy transition is still unclear. Thus, this paper developed a lifecycle greenhouse gas (GHG) emissions framework for coal-to-clean-energy policies in rural northern China. The GHG emissions for heating and cooking, the two most energy intensive activities, were calculated. Four scenarios were designed based on energy types and equipment. Uncertainties in estimating lifecycle GHG emissions under different scenarios were analyzed. The technology warming potential values were calculated for the conversion of scenarios. Besides, the environmental benefits of natural gas versus electricity under emission reduction targets were compared. According to our findings, the total GHG emissions reduction of coal-to-clean-energy shift policies in rural northern China under global warming potential on a 100-year scale (GWP 100) is 1.83 million metric ton CO 2 equivalent (MMT CO 2 eq) in 2018. Since the climate benefits of policy shifts are driven by chosen technical routes, replacing coal with natural gas should be prioritized; heating with natural gas boilers can maximize GHG emissions reduction and climate benefits. By 2038, the climate benefits of electricity will be far superior to those of natural gas, based on emission reduction targets and electrical mix. There are numerous opportunities to reduce GHG emissions in China's energy sector, and there is a need for the energy industry to obtain better emissions data as well as to increase efforts to reduce GHG emissions. [Display omitted] • The coal-to-clean-energy policy in rural areas has a positive climate benefit. • Priority should be given to replacing coal with natural gas in policy execution. • Heating and cooking with electricity will maximize climate benefits from 2038. • Climate impact caused by CH 4 emission during the energy lifecycle can't be ignored. [ABSTRACT FROM AUTHOR]

The industrial sector has significantly contributed to global climate change and urban air pollution while driving economic development. This paper takes the synergistic CO2 and SO2 emission reduction in China's industrial sector as an entry point quantifies the synergistic CO2 and SO2 emission reduction effect using the Kaya extension model and analyzes the synergistic emission reduction expansion mechanism in depth. It is found that the synergistic effect of CO2 and SO2 in the industrial sector is prevalent in most provinces in China. Every 10,000 tons of CO2 emission reduction leads to 1600 tons of SO2 emission reduction. Regional heterogeneity also clarifies that there are differences in synergistic emission reduction among different provinces, with most regions having a significant positive effect of synergistic emission reduction, while a small number of regions have an inverse effect, and direct SO2 reduction measures should be considered separately. The interaction effect analysis found that energy efficiency improvement in the industrial sector is the critical path to synergistic effect enhancement. At the same time, R&D expenditure and fixed asset investment have a weak effect on synergistic emission reduction. The interaction of the three factors can synergize the emission reduction effect by more than twice. The study's findings can be used as a reference for China's industrial sector to achieve the goal of reducing pollution and carbon emissions and for the practice of regional synergistic emission reduction, as well as for the formulation of international synergistic emission reduction policies. [ABSTRACT FROM AUTHOR]

Transnational power cooperation contributes to promoting the large-scale use of renewable energies in Asia, but how to develop the structure of power transmission network deserves careful investigation. This paper thoroughly investigates the structure of power investment and transmission network in China and neighbouring countries, aiming to promote the large-scale use of renewable energies around Asia. Various power-generation and power-transmission technologies are considered in detail, and transnational power interconnection risk cost and carbon emission cost are embedded into a bottom-up optimization model. The future power-generation structures and networks installed under various policy scenarios are analysed in detail, and the corresponding economic, carbon emission reduction and renewable energy consumption benefits are evaluated. The results show that power transmission between China's internal regions and neighbouring countries can save $56.7 billion for the entire power system through the large-scale grid integration of renewable energy. The installed capacities of wind power, solar power, and hydropower renewable energy power generation could be increased by 141 GW, 163 GW, and 58 GW, respectively. The construction of transnational transmission lines from Central Asia to Northwest China, Mongolia to North China, the Russian Far East to Northeast China, and Northeast China to South Korea could effectively promote the utilization of renewable energy in the Russian Far East, Mongolia and Central Asia and further reduce carbon emissions in China, Japan and South Korea. • It examines how to construct a power investment and transmission network in Asia. • Various technologies, risks and costs are considered based on bottom-up model. • Huge benefits exist for power transmission between China and neighbouring countries. • Various power-generation structures and networks installed are analysed in detail. • Suggestions about power investment and transmission are given for Asian countries. [ABSTRACT FROM AUTHOR]

Currently, numerous studies are being conducted on various carbon reduction policies, but their synergies have been poorly investigated. This paper examines the synergistic effect of combining emissions trading schemes (ETS) and energy carbon-content taxes (ECT), using China as a case study. A computable general equilibrium model is used to identify the synergistic effect of these two carbon mitigation policies. The results show that the synergistic effect helps to reduce GDP loss by approximately 5.44 billion CNY, which accounts for 2.83% of the overall GDP losses caused by ETS and ECT. Additionally, the synergistic effect reduces an additional 5.25 million tons of CO 2 emissions and decreases the negative impact on social welfare resulting from the two policies. Although these achievements are commendable, there are costs associated with this synergy. The effect on energy security presents mixed results and leads to increased carbon leakage. Therefore, policymakers should take heed of the potential "cocktail effects" that may arise in their pursuit of carbon neutrality. [ABSTRACT FROM AUTHOR]

The increasing contribution of refrigeration systems to global warming has led to widespread demand for low global warming potential (GWP) refrigerants as alternatives. This paper proposed a comprehensive environmental assessment method for evaluating the carbon footprint of units charged with low-GWP refrigeration. Experimental and numerical studies were used to investigate the carbon footprint impact of using alternative refrigerants at different ambient temperatures in China. Initially, the model was validated through experimental case studies on the use stage of cold storage units. Subsequently, a comparison was made between the cooling capacity (CC) and energy efficiency ratio (EER) of cold storage units charged with different refrigerants. Additionally, the impact of alternative refrigerants in the use stage was analyzed by numerical calculations, and the adaptability of the cold storage unit to the ambient temperature and the national energy structure was also studied. The results indicate that among the four stages of the cold storage unit, the use stage is the hotspot of carbon footprint due to the large amount of energy consumption and the existence of refrigerant leakage and other behaviors. Utilizing low-GWP alternative refrigerants could significantly reduce the carbon footprint of the cold storage units' use stage by 10.56%–16.39%, thereby lowering the whole stage carbon footprint. Furthermore, the ambient temperature and national energy structure could also effectively reduce the carbon footprint of cold storage units' whole stage by 1%–27.17%. Furthermore, after adopting low GWP refrigerants, the life-cycle cost (LCC) of the units have also decreased by 6.1%–12%. Taking into account both environmental impact and economic considerations, it is recommended to directly replace R404A with R448A in the units in regions where the average ambient temperature is above 15 °C. • A carbon footprint evaluation model for the units was established. • Influencing factors of carbon footprint are studied numerically and experimentally. • By GHG assessments, the optimal refrigerant and external conditions were determined. • Alternative refrigerants reduce carbon emissions for cold storage units by 8.8%–24.92%. [ABSTRACT FROM AUTHOR]

Towards the target of carbon neutrality, the need for deep decarbonization in iron and steel industry is increasingly recognized. Existing studies rarely mention the effects of collaboration with its source industries for carbon emission reduction in ISI. Furthermore, the fundamental laws of CO 2 emission reduction capacity with cost change of source substitutions for various steel production routes under market economics are unclear. To avoid the blind substitution of clean sources for meeting the urgent requirements for decarbonization in China's steel industry, which may result in increased carbon emissions and uneconomical carbon reduction from a lifecycle perspective. This paper integrates the production and utilization processes of source resources into the steel production process, establishes coupling models of carbon and value flows for four main types of steel production routes, and aims to quantitatively analyze the specific CO 2 emission reduction potential and costs. Three economic market development scenarios from 2021 to 2060 are set, and the marginal carbon prices of various source substitutions are determined. Subsequently, decarbonization pathways with the goal of minimizing production costs are developed. Finally. The future resource demand and the carbon emission reduction contributions of source industries collaborated are predicted. The results show that (1) about 81.7–89.9 % of CO 2 emissions could be reduced in the scenarios; (2) the demands of electric power and hydrogen energy will reach 54.48–511.90 BkWh and 7.47–10.31 Gt in 2060, respectively; and (3) collaboration with source industries could make 18.3–18.3% of CO 2 emission reduction contributions. All in all, this study could provide scientific support for the low-carbon transformation of China's steel industry. • Carbon and value flows of BF-BOF, Scrap-EAF, DRI-EAF, MOE-EAF routes are analyzed. • CO 2 emission reduction potential with marginal carbon price is determined. • Decarbonization paths during 2021–2060 for China's steel industry are developed. • Quantify the contribution of collaborative carbon reduction with source industries. [ABSTRACT FROM AUTHOR]

The vigorous development of the digital economy (DIEC) offers a substantial potential for China and global economies to realize the goal of "double carbon". This study attempts to analyze the heterogeneous effect of DIEC on carbon emission reduction (CERE), in order to extend a valuable reference for effectively achieving the dual-carbon goal. Accordingly, the effect of DIEC on carbon emission scale (CESC) and carbon emission intensity (CEIN) are examined in this paper by using dual fixed effect model and intermediate effect model, respectively. The study findings show that, at first, DIEC significantly supports the CERE while significantly constraining the uplift in CESC and CEIN. Simultaneously, the CERE effect of DIEC contains digital economy dimensional heterogeneity, industry heterogeneity, production and life heterogeneity, and urban-rural heterogeneity. Finally, the DIEC boosts the technological innovation (TEIN) and residents' income (REIN) levels, in order to heighten the CERE. Further, improving invention technology innovation and TEIN is more conducive to catalyzing the reduction of carbon emission in the whole society and the production field. Conversely, the improvement of non-invention technology innovation and rural- and urban residents' income impedes CERE in the field of life. Thus, the implications of this study are of vital significance for China and the rest of the world to foster CERE and achieve the "dual carbon" goal through DIEC development. [ABSTRACT FROM AUTHOR]

Digital economy development (DED) empowers rural habitat (RH) improvement and promotes the construction of harmonious villages. Based on a panel data of 30 provinces in China from 2013 to 2019, this paper empirically tests the impact of DED on RH and its endogenous mechanism in multiple dimensions using panel fixed effects model and spatial Durbin model. The results show that DED significantly improves RH, which remains robust after a series of robustness tests and dealing with endogeneity issues. The mechanism analysis shows that DED helps to bring into play the rural resource allocation effect, the innovation and entrepreneurship effect, and the carbon emission reduction effect, and improves the RH through these three effects. Further study finds that the digital application divide and regional divide are the main barriers to digital technology enabling RH improvement, there is a spatial spillover effect of DED, which helps to promote the improvement of RH in neighboring areas. The results of the study can provide theoretical support and decision-making reference for the construction of digital villages and the balanced regional development of RH in China. • Indicator system of digital economy and rural habitat was constructed. • Digital economy development significantly boosts rural habitat. • Resource allocation, rural entrepreneurship, and carbon reduction are effective transmission mechanisms. • Digital application divide has a heterogeneity impact. • The spatial spillover effect of the digital economy is significant. [ABSTRACT FROM AUTHOR]

Meeting energy needs and ensuring ecological sustainability are important tasks for policymakers. In particular, changing the energy mix used in daily electricity generation can have a major effect on ecological conditions, and this is a previously neglected research topic. Therefore, this paper aims to investigate the influence of daily electricity generation from nuclear power and renewables on the achievement of carbon neutrality targets in the four largest nuclear power countries (i.e., the U.S., China, France, and Russia). The study applies the wavelet-transform coherence (WTC), quantile-on-quantile regression (QQR), and Granger causality in quantiles (GCQ) approaches for the period from January 2, 2019 to December 29, 2022. The outcomes present that electricity generation from nuclear energy reduces carbon (CO 2) emissions only in Russia, while hydropower generation does not contribute to CO 2 emission reduction in any country. Solar electricity generation decreases CO 2 emissions in different quantiles in the U.S. and Russia, while electricity generation from wind power reduces CO 2 emissions in the U.S. and France. The empirical outcomes also reveal that expanding solar, wind, and nuclear power in the energy mix can enhance the potential of the U.S., France, and Russia to achieve carbon neutrality and secure a sustainable future. However, China is using nuclear and renewables inefficiently regarding carbon neutrality. Therefore, the empirical evidence for China is highly controversial compared to former studies. [Display omitted] • The study examines renewable and nuclear electricity effect on carbon neutrality. • The study focuses on top four major nuclear power countries. • The study applies nonlinear approaches by using high-frequency (daily) data. • Renewable and nuclear electricity have time, frequency, & quantile-varying effect. • The best electricity source change according to each country. [ABSTRACT FROM AUTHOR]

The metallurgy industry plays a very important role in China's economic growth. Due to its energy concentration, the energy consumption of the industry accounts for a large proportion of China's total energy consumption, and thus contributes to carbon emissions. Whether the metallurgy industry can successfully reduce emissions is related to the future of China's carbon emissions targets. In this paper, the logarithmic mean Divisia index model is used to analyze the change in China's carbon dioxide emissions from 1991 to 2014. The empirical results show that there are three main factors affecting the carbon dioxide emissions of China's metallurgy industry. The three factors are labor productivity, energy intensity and industry size. In addition, we further analyzed the deep motivation of carbon dioxide emissions in the industry, and calculated the future emission reduction potentials. Lastly, according to the empirical results, the paper proposes policy recommendations for the future emission reduction of China's metallurgy industry. [ABSTRACT FROM AUTHOR]

A carbon reduction labelling scheme is an effective policy tool for motivating enterprises or organizations to reduce their life-cycle-based carbon emissions to benefit the environment. This paper uses system dynamics to model enterprises' compliance with a combined government policy instrument for a carbon reduction labelling scheme, that is, government subsidies and economic sanctions. A case study of paper enterprises in China is provided to demonstrate the application of the proposed model in which two optional technological plans to reduce the enterprises' carbon emissions are examined. The technological plans are categorized as a low-cost and high-cost plan. The simulation results show that both the technological plans are vulnerable to the combined policy making, and the high-cost plan shows superior environmental performance for carbon emissions reduction. However, the enterprises are more inclined to choose the low-cost plan because of superior economic performance. The study offers insights to help enterprises select optimal actions on carbon emissions reduction and to inform government of possible sustainable policy design to promote low-carbon development. The model limitations are discussed as a basis for further improvements in low-carbon development. [ABSTRACT FROM AUTHOR]

E-commerce has emerged through digital platforms and Internet construction as an important way to achieve low-carbon development in China. To evaluate the mitigation effect of e-commerce, this paper conducts a quasi-natural experiment in terms of the pilot policy of national e-commerce demonstration cities (NEDC) to explore the changes in CO 2 emissions of 270 cities from 2004 to 2017 in China. We also check the asymmetry, mechanism effects and heterogeneity. The results show that the treated cities reduce CO 2 emissions by 4.1% due to the NEDC pilot policy compared to the untreated cities. The estimated results pass the parallel trend test, robustness tests, and the Goodman-Bacon decomposition. Moreover, the NEDC pilot policy increases the CO 2 emissions of treated cities by promoting economic growth (scale effect), and decreases the carbon emissions of treated cities by upgrading the industrial structure (structural effect) and increasing the technological innovation level (technical effect). Furthermore, the CO 2 mitigation effects of the NEDC pilot policy are significantly concentrated in the higher quantiles. Finally, the NEDC pilot policy has significantly negative effects on CO 2 emissions in "postage-free regions," southern China, and cities with large e-commerce sales. The results of this paper provide theoretical and practical references for China to achieve low-carbon development. • Evaluating the impact of pilot policies of national e-commerce demonstration cities (NEDC) on carbon emissions in China. • The NEDC pilot policy reduces carbon emissions of treated cities by 4.1%. • The NEDC pilot policy reduces carbon emissions through structural and technical effects. • The emission-reduction effects are significant at the higher quantiles. • The impact of the NEDC pilot policy on carbon emissions is obviously heterogeneous. [ABSTRACT FROM AUTHOR]