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This study aims to explore the direct and indirect impacts of the Carbon Emission Trading System (CETS) on the green transition development (GTD) of Chinese cities. This paper constructs a GTD evaluation system from the perspective of prevention and governance at the source, in terms of carbon reduction, pollution reduction, green expansion and growth, and measures the GTD performance of 281 cities based on the EW-TOPSIS model. It is found that the average increase in GTD of the sample cities from 2006 to 2020 is 3.40 %, the GTD progress of the 281 cities has a considerable positive spatial autocorrelation, with the GTD progress of the CETS pilot cities being significantly bigger than that of the non-pilot cities. Further this paper adopts the spatial difference model (S-DID) to scientifically identify the influence mechanism and heterogeneity of the direct and spatial effects of CETS on city GTD, and the results show that CETS has a positive effect on the GTD of both local and neighboring cities. Propensity score matching (PSM) is used to further corroborate these findings. The study also shows that CETS improves local GTD by promoting green innovation, rationalizing industrial structures, and enhancing energy efficiency in cities. Nevertheless, the ensuing siphon effect hinders nearby cities' levels of energy efficiency, industrial structure rationalization, and green innovation. The policy effects of CETS are more significant in large cities, eastern cities, old industrial areas, and non-resource-based cities. CETS can work in synergy with smart city construction, low-carbon city pilot policies, and emission trading policies to accelerate the process of GTD. [ABSTRACT FROM AUTHOR]

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

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]

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]

Accurately predicting carbon price can promote the rational allocation of carbon resources, reducing carbon emissions and contributing to green development. The decomposition integration framework is widely applied for carbon price forecasting, but several problems remain. Thus, this paper innovatively proposes an enhanced decomposition integration model for deterministic and probabilistic carbon price forecasting, which combines two-stage feature extraction and intelligent weight optimization. In order to decrease the complexity of the data and fully extract the characteristics, two decomposition approaches are utilized. For reconstruction, fuzzy entropy is applied to balance model complexity and computing efficiency. Next, the combination forecasting model based on two deep learning models is built to circumvent the constraints of the single forecasting model, and the cuckoo search optimization method (CS) is utilized to find the weight of the combination model adaptively. Considering the differences in the contributions of each component, the optimal weighting strategy based on CS is then used to derive the final forecast. Ultimately, considering the probability interval can provide more helpful information, the decomposition integration framework is supplemented with Gaussian process regression relying on the mixed kernel function for interval prediction. In an empirical study of five carbon trading markets, the hybrid model developed in this paper exceeded all baseline models regarding prediction stability, proving that the developed model can make effective forecasting for the carbon trading business. • An enhanced decomposition integration model is developed for carbon price prediction. • Both deterministic and uncertainty carbon price prediction are performed. • The two-stage feature extraction technique well balances model complexity and computational efficiency. • Intelligent weight prediction integrated model greatly improves the accuracy of prediction results. • The proposed model has excellent performance in carbon price prediction. [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]

Under the goal of "carbon peaking" and "carbon neutrality" in China, it is significant to explore whether green finance contributes to carbon emission reduction. Therefore, based on the panel data of 30 provinces in China from 2005 to 2020, this paper empirically examines the impact of green finance on carbon emissions and its mechanism using the FE model, GMM model, DID, and the mediating effect model. Results find that green finance can significantly promote carbon emissions reduction, and this promotion remains still after robustness tests. The heterogeneity analysis shows that green finance's carbon emission reduction effect is more significant in developed and western regions. Moreover, the results of policy intervention effects confirm that green finance reform and innovation pilot zones (GFRIs) for carbon emission reduction are more pronounced than in other regions. Finally, the mediating effects reveal that industrial structure and green innovation are the core transmission channels through which green finance influences carbon emission reduction. These findings offer meaningful implications for formulating reasonable carbon emission reduction plans and determining the future development direction of green finance. [ABSTRACT FROM AUTHOR]

This study aims to examine how carbon trading policies impact total factor carbon productivity and subsequently provide recommendations for sustainable regional development. Through analyzing the trends in total factor carbon productivity and its mechanisms, this paper suggests that carbon trading policies can significantly enhance total factor carbon productivity. Additional mechanistic tests reveal that carbon trading can promote technological progress, factor accumulation, scale allocation and energy substitution effects; all contributing towards a low-carbon economic transition. These four effects serve to both promote economic growth and contribute towards carbon reduction targets. Therefore, to encourage low-carbon and high-quality development of the region's economy, policymakers must focus not only on constructing and expanding carbon markets, but also emphasize the synergies between these different effects. [ABSTRACT FROM AUTHOR]

The construction industry is one of the most energy-intensive industries in China, which contributes to high carbon emissions and hinders efforts to reduce the emissions. The high energy consumption and emission have seriously constrained the growth of low carbon economy in China's construction industry. And reducing the carbon emission from construction industry (CECI) has become the key to sustainable development and the achievement of "double carbon target". The paper firstly decomposes the main influencing factors and calculates their effects by LMDI model. Then, the Tapio decoupling index is used to explore the decoupling relationship between carbon emissions and economic output. Finally, the spatial-temporal evolution of carbon emissions is analyzed through spatial autocorrelation theory. The results show that the carbon emissions from construction industry are highly increased by the construction employment rate (EM), and may be reduced by the energy intensity (EI) and carbon emission efficiency (CI). And the regions with better decoupling status are the eastern and central regions, which have relatively developed construction industry. Moreover, the spatial-temporal characteristic of carbon emissions is "high in the east and low in the west, high in the south and low in the north," showing obviously regional differences. [Display omitted] • Factors about production technology are taken into account, reflecting the characteristics of the construction industry. • Developed regions have better decoupling potential and more responsibility for CO 2. • The spatial distribution is "high in the east and low in the west, high in the south and low in the north". • The provinces in a region have similar decoupling status and carbon emission distribution. [ABSTRACT FROM AUTHOR]

Under the background of the gradual scarcity of terrestrial resources and the increasingly fierce competition for global marine resources, the task of green development of marine economy and green transformation of marine industry is imminent. Carbon finance is a product of low-carbon economic development and a derivative of green finance. It is an effective way to alleviate the global climate crisis and promote the transformation of the global economy to a low-carbon economy to achieve sustainable development. Studying the mechanism of carbon finance on the development of marine economy will help to grasp the influencing factors of the green transformation of the marine industry in an all-round way, better promote the sustainable development of China's marine economy, and realize the strategy of marine power at an early date. Based on this, this paper selects China's data from 2006 to 2020, and uses the AHP-entropy method to select 26 indicators from five levels: economic growth, energy conservation and emission reduction, marine ecology, structural adjustment and scientific and technological innovation to construct a comprehensive evaluation index system for the green transformation of China's marine industry. Based on the PLSR model, the impact of carbon finance on the green transformation of China's marine industry is empirically analyzed, and the results show that: (1) The comprehensive score of China's marine industry green transformation from 2006 to 2020 fluctuates and rises: from 2006 to 2009, the comprehensive score of China's marine industry green transformation is low, and the transformation effect is not obvious. From 2009 to 2012, the comprehensive score of green transformation of the marine industry improved significantly. From 2012 to 2018, the comprehensive score of China's marine industry green transformation fluctuated little and showed a slow growth trend, while China's marine economic transformation grew steadily at a low speed. In 2019–2020, due to the impact of the epidemic, the speed of transformation has decreased again. (2) The carbon ratio and the green credit balance of commercial banks have a role in promoting the green transformation of China's marine industry, while the carbon trading volume and carbon intensity have a restraining effect on the green transformation of China's marine industry. From the perspective of effect, carbon intensity has the strongest effect, followed by carbon ratio, carbon trading volume is slightly weaker, and the role of green credit balance of commercial banks is the weakest. Based on the research conclusions, relevant policy recommendations were put forward. [ABSTRACT FROM AUTHOR]

Nexus approaches, aiming at the complex connections among the correlative systems, provide an effective method for analyzing coevolution processes. In the context of urbanization, water, energy, and environment (W-E-E) systems are increasingly connected thus can be profiled as a W-E-E nexus. However, research on urban water-energy interactions and their impact on the environment is still in its infancy. In addition, a generic framework for modeling W-E-E nexus that includes dynamic feedbacks between human and natural systems remains elusive. In an attempt to fill this gap, this paper proposes a sensitivity-based framework consisting of four components: the water balance model, the energy balance model, the environmental response model, and the urbanization model. Community sensitivity serves as the missing link, tying together two feedback loops driven by economy and environment respectively. To demonstrate how such a framework could be applied, Wuhan city was selected as a case study and analyzed for its coevolution under three scenarios: extensive development, common development, and sustainable development. The results show that the proposed framework is competent in modeling the W-E-E nexus in Wuhan. The coevolution process is broadly divided into four cyclic stages (expansion, degeneration, convalescence, and stabilization) and environmental recovery consumes decades or more regardless of the development pattern. However, development patterns exert a salient effect on community sensitivity, with +294.4%, +5.5%, and −17.4% for extensive, common, and sustainable development patterns during the simulation period respectively. And only under sustainable development, can Wuhan anticipate achieving the goal of carbon neutrality by the 2060s. It is hoped that this framework will aid our understanding of the fundamental interactions in this complex relationship and allow researchers to improve W-E-E nexus modeling through better capture of the key elements in the feedback loops. • Present a sensitivity-based framework for the water-energy-environment nexus. • Build the missing link that connects 2 key loops driven by economics and environment. • Provide urban development pattern decisions for achieving resource sustainability. • Assess Wuhan's development trajectory over the next 2 centuries quantitatively. • Propose a development pattern to achieve carbon neutrality in Wuhan in 2060s. [ABSTRACT FROM AUTHOR]

With the goal of pursuing carbon neutrality, this study is aimed to investigate effectively managing distributed renewable energy. Considering the uncertainty of wind power (WP), photovoltaic power (PV), and load, a two-stage robust optimization model for virtual power plant (VPP) is proposed, with a focus on calculating the available capacity of electric vehicle (EV) aggregated virtual energy storage (VES). Time–space distribution characteristics of EVs and the responsiveness of EV users are analyzed and the available capacity calculation model is constructed. In the first stage, the bidding strategy and unit combination of the VPP are determined based on the predicted values of WP, PV, and load. Combining with the pre-decided decision from the first stage, the output of each unit is determined by considering an uncertainty set in the second stage, for achieving the best operational benefit under worst-case scenarios. Robust control parameters are introduced into the model and used to adjust conservativeness. The model is solved by applying the C&CG algorithm. Additionally, a carbon trading mechanism is leveraged to balance the system economy and environmental friendliness. The results show that the optimal scheduling solution helps to reduce fluctuations caused by uncertainties, balancing the economic benefits and operational risks of the VPP. Besides, guidance is provided for VPP operators to formulate reasonable incentives for EV users and the construction of energy storage systems. When the carbon trading price of the VPP proposed in the paper is set at 160 ¥ /ton, economic and environmental sustainability can be effectively balanced. [Display omitted] • Virtual power plant structure featuring electric vehicle virtual energy storage. • Electric vehicle user responsiveness-based available capacity calculation model. • Two-stage robust scheduling model for virtual power plant with electric vehicles. • Scheduling under varied risk achieved by modifying robust coefficients. • Balancing economic and environmental properties via suitable carbon trade parameters. [ABSTRACT FROM AUTHOR]

As the climate is warming up and climate disasters occur more frequently, China's carbon peak and carbon neutrality targets are gaining attention, with provinces starting to set carbon peak targets and constantly exploring low carbon economic development opportunities. However, the existing evaluation index system mainly focuses on low carbon cities and green cities, and there is no evaluation index system for carbon peak and carbon neutrality. This study adopts a combination of theoretical and empirical research and draws on domestic and international research results to construct the first index system for evaluating China's provincial carbon peak and carbon neutrality. The evaluation index system includes 18 indicators from three dimensions: climate ambition, low carbon status, and emissions trends. Using this index system, we calculated the carbon peak and carbon neutrality indices of 30 Chinese provinces. Further, the 30 provinces were classified into six categories, and corresponding policy recommendations for achieving the "Dual carbon" targets were put forward. The evaluation index system constructed in this paper can provide a reference for future carbon peak and carbon neutrality assessments. By disclosing the integrated index of each province, we hope to effectively curb the increasing local carbon emissions; avert inaction in areas with good natural endowments; and motivate the advancement of the latter, to boost the implementation of the "Dual carbon" targets coherently for the whole country. [Display omitted] • An integrated evaluation system on China's Provincial "Dual carbon" was proposed. • 30 provinces in mainland China were ranked based on the integrated index. • 6 groups were classified to show provincial differences on dual carbon performance. • Policy recommendations to fulfill China's climate commitment were put forward. [ABSTRACT FROM AUTHOR]

Sharing resources and curbing emissions are critical for promoting the adoption of cleaner logistics technologies and improving environmental sustainability. However, little research has examined reducing the impact of carbon emissions on the environment by considering transfer between depots. Hence, this study investigated the impact of carbon emissions on a multi-depot collaborative pickup and delivery network with time windows and transfers (MDCPDPTW-Ts) and proposed a carbon emissions measurement to describe the relationship between fuel consumption and carbon emissions. Then, a two-stage heuristic framework was proposed to simplify MDCPDPTW-Ts and generate high-quality delivery routes. Finally, a case study from Dalian, China, was used to verify the effectiveness of the research methodology. The results demonstrated the following: (1) The multi-depot transfer network constructed in this paper is significantly better than the traditional no-transfer scheme, reducing the cost by 26.64%. (2) Sharing transfer facilities among different depots is the most attractive mode of realizing clean logistics, reducing the emission cost by 59.2% compared with the traditional depot-based transfer scheme. (3) Reasonable carbon prices and carbon quotas are highly significant to establishing a sustainable carbon trading market. As carbon prices increase, carbon emissions first show a sharp reduction trend and then gradually tend to remain unchanged. Therefore, this work can provide practical and theoretical implications for the sustainable development of multi-depot collaborative logistics. [Display omitted] • Transfer locations reduce complexity of the multi-depot collaboration system. • Adaptive iterated local search improves quality of solutions. • Minimizing transportation cost simultaneously reduces fuel and carbon emissions. • The proposed transfer scheme has lower emissions than the traditional scheme. • Carbon quotas and prices to conserve energy and curb emissions are discussed. [ABSTRACT FROM AUTHOR]

"Carbon Peaking and Carbon Neutrality" is one of the important tasks of China's current and future economic construction and development, but the carbon emission reduction effect of High-speed rail (HSR) has not yet been fully studied. In this paper, based on the panel data of 274 cities in China from 2003 to 2016, we take the opening of HSR in the cities as a "Quasi-natural Experiment", and construct the Multi-period Difference-in-Difference Model to explore whether the opening of HSR can reduce carbon emissions of cities along the route, and use the mediating effect model and moderating effect model to further analyze its internal mechanisms. We find that:①The opening of HSR can significantly reduce the carbon emissions of cities along the route, and the opening of HSR in a city will reduce the carbon emissions of the city by about 2.4% on average, and this carbon emission reduction effect usually manifests significantly in the first year after the opening of HSR, and increases year by year thereafter.②The mechanism test shows that the traffic substitution effect, the optimization of the industrial structure and the promotion of economic agglomeration have partial mediating effect on the influence between the opening of HSR and urban carbon emissions. In addition, the increase in the intensity of government environmental regulations can strengthen the effect of the opening of HSR on reducing urban carbon emissions.③The regional heterogeneity research shows that the opening of HSR has a more significant impact on the carbon emissions of cities in the eastern coastal region and western region of China. Moreover, in the western region, the reduction effect of the opening of HSR on carbon emissions is only reflected in the key cities rather than ordinary prefecture-level cities. This paper provides certain reference significance for promoting low-carbon and green economy and helping China to achieve the "Carbon Neutrality" climate action goal. [ABSTRACT FROM AUTHOR]

With the general recognition of the awareness of carbon neutrality, economic development growth momentum for carbon neutrality scenario has become research focus. This paper introduces the carbon neutrality double input level based on the perspective of the initiative, consciousness, and self-discipline of firms and residents to practice green low-carbon behavior. By constructing a balanced economic system of green low-carbon behavior, this paper explores the new endogenous growth power in production and consumption, and finds that there exists a carbon neutrality realization regulation of green low-carbon behavior in the new system. Based on the penetration capacity of green low-carbon behavior, this paper studies the endogenous growth law of economic system driven by the evolution of carbon neutrality double input level. The production and consumption processes are considered in the new economic system in this paper, the production of green low-carbon goods is considered in the production sector and the technical equation under carbon neutrality double input level is studied, the consumption process of green goods affected by environment and carbon emissions is considered in the household, then the household utility function is constructed, and the new growth rate is obtained. Using carbon emissions growth rate of green low-carbon goods and its relationship with absorption rate derive the carbon neutrality realization regulation. Then the general equilibrium solution and growth rate under endogenous growth driven by carbon neutrality double input level are also obtained. Furthermore, the carbon neutrality effects which are the endogenous effect of carbon neutrality double input level and the effect of carbon neutrality realization regulation are obtained by numerical simulation and empirical analysis. [ABSTRACT FROM AUTHOR]

The carbon emission trading scheme (ETS) is an important market-based tool for achieving carbon neutrality. The existing research on the policy effect of ETS focuses on emission reduction effect and economic effect respectively. In view of this, based on the connotations of green development, we embed fairness toward the environment into the green development system to construct a balanced green development index to measure two dimensions, namely, efficiency and fairness. Theoretically understand the synergistic development effect of economic growth and ecological environment quality produced by the implementation of ETS, and analyze the impact of carbon market on balanced green development. A multiperiod difference-in-differences (DID) model explores the impact of China's carbon ETS on the green equilibrium level by using Chinese provincial panel data for the period 2008–2018. First, the results demonstrate that China's balanced green development level is weakly coordinated overall and there is a global spatial agglomeration effect. Second, the carbon ETS has significantly improved the level of balanced green development which promotes the degree of coordination between green economic growth and environmental fairness, offering an effective path that includes efficiency and fairness for green development. Third, there are regional differences in the impact of the carbon ETS on green equilibrium levels. The effect on the western region of China was significantly higher than that of the central and eastern regions of China. Compared with the existing research, the study breaks the single research perspective. From the perspective of efficiency and fairness, we propose improvements in the construction of a national unified carbon emissions trading market to strengthen the balanced green development. This paper provides a theoretical basis and policy reference for deepening China's green and high-quality development under the "carbon peaking and carbon neutrality" goal. [Display omitted] • Evaluation system of Balanced Green Development Index is constructed. • The system was applied to balance green economic growth with environmental equity. • Emission trading scheme has significantly improved the level of balanced green development. • The promotion effect is more obvious in western China. [ABSTRACT FROM AUTHOR]

The implementation of the carbon trading system has a great impact on all aspects of the economy and society. Agriculture, which accounts for 34% of global carbon emissions, has also been hit hard as a high carbon emitting industry (Crippa M, 2021). This study uses agricultural green total factor productivity as an important indicator of agricultural green sustainable development, and analyzes the impact of China's carbon trading system on agricultural green total factor productivity, which can provide a reference for other countries that want to improve agricultural sustainable development and implement carbon trading. In this paper, the producer theory is used to build the basic model, and the differences-in-differences (DID) method is used to analyze the provincial data samples in China from 2000 to 2020. It is found that: the implementation of carbon trading pilot policy has a significant promotion effect on agricultural green total factor productivity; and after the implementation of carbon trading policy, with the advancement of time, under the constraint of reducing carbon quota, the promotion effect of agricultural green total factor productivity becomes stronger and stronger. Even in the regions without carbon trading pilot program, the policy spillover effect will also be obvious and promote the development of green total factor productivity of agriculture in this area. [ABSTRACT FROM AUTHOR]

Under the dual policy targets of carbon emission peaking (CEP) and industrial green transformation (IGT) in China, where a top-down policy implementation is usually adopted, a more integrative planning mode needs to be constructed for greening industrial development. This paper proposes a technical framework to tackle the weakness faced when integrating IGT-associated issues with CEP factors during the development of IGT options, with an application in the Hohhot–Baotou–Ordos–Yulin (HBOY) city cluster. A CEP-IGT model was built to portray the effects of seven selected indicators on industrial carbon emissions, and help develop six options by defining the transformation strengths of HBOY's energy-intensive industrial system. Particularly, the CEP times and volumes were employed as the criteria for evaluating the IGT options. We found that the regional CEP goal will not be accomplished by even 2035 under the business-as-usual scenario. To halt the emission growth trend will rely much on the structural factors of energy mix and industrial output, which were also determinants of the IGT performance. Option 3, representing a moderate level transformation, was the preferred IGT plan, reaching a peak volume of 255.27 MtCO 2 eq·a−1 in 2026. The preferred plan will result in the replacement of at least 14% of the coal used in thermal power by renewable energy, and an increase in industrial coal-use efficiency by 32.02%. Policy measures need to be implemented to cap the total industrial coal consumption to no more than 2494 Mt and sustain an industrial growth by developing lower-energy or carbon-intensive industries. By 2030, the intensity and volume of industrial carbon emissions will reach 1.89 tCO 2 eq·10,000 CNY−1 and 224.85 MtCO 2 eq·a−1, respectively. This CEP-IGT progress will benefit the goal of being carbon neutral. As such, we concluded that this new framework will aid the IGT planning process, not only improving our understanding of the relationships between carbon emission control and industrial updating levels, but also presenting an integrative path for China's city clusters to promote green, low-carbon industrial development. • A technical framework is raised to tackle the weakness of integrating the CEP factors into IGT planning. • The peaking time and volumes of carbon emissions are used as the criteria for determining the preferred plan. • Both industrial updating and carbon emission control rely on the structural factors. • The preferred Option 3 can achieve the peaking goal in 2026 with a moderate transformation strength. • The new framework presents an integrative path to promote the transformation to green, low-carbon industrial growth. [ABSTRACT FROM AUTHOR]

Green development is a common goal pursued globally for carbon neutrality, and whether environmental regulatory system drives it in pollution-intensive industries (PIIs) is puzzled. Using provincial panel data of Chinese PIIs during 2005–2017, this paper applied entropy method to integrate existing environmental regulatory system into three types of environmental regulations, and then explored non-linear effects of them on green total factor productivity (GTFP). Several conclusions are generated. The annual growth rate of GTFP is 10.61% and it presents industrial differences. Technical change is the driving factor, while technical efficiency shows inhibiting effect. The effect of command-and-control environmental regulation on GTFP is a significant inverted U-shape curve, which is currently the primary driving role in green development, but it is too strict and increasingly less effective. Both market incentive and voluntary environmental regulations appear as positive U-shape curves, and their proper enhancement is breakthrough for future green development. Besides, market incentive environmental regulation is more effective in PIIs with relatively low pollution, while voluntary environmental regulation is sensitive to PIIs with relatively serious pollution. The Chinese government should allow environmental regulatory system more marketability and voluntariness, and production characteristics and pollution density of targeted industries should be considered. • The green development grows rapidly but shows technical inefficiency. • Command-and-control environmental regulation drives green development effectively. • Market incentive and voluntary environmental regulations can be enhanced properly. • Market incentive environmental regulation is sensitive to slight-polluted industries. • Voluntary environmental regulation works in heavy-polluted industries. [ABSTRACT FROM AUTHOR]

Enterprises are essential to the realization of sustainable development in human society. However, there is still a lack of simulation models that can dynamically explain, predict and evaluate the complexity of enterprise sustainable development. Therefore, this paper adopts the method of system dynamics to construct a low-carbon sustainable development level model of enterprise. The four indicators of low-carbon economic benefits, low-carbon technology stock, low-carbon human resources, and CO 2 emissions reflect the level of low-carbon sustainable development of enterprises. The results show that the level of low-carbon sustainable development of enterprises is not high (<0.6); low-carbon human resources have two stages of decline and rise; government supervision and low-carbon technology can significantly reduce CO 2 emissions. However, multi-scenario simulation results show that in the early stage of low-carbon sustainable development of enterprise, excessive government supervision will reduce the low-carbon economic benefits of enterprise. Within 10 years, policy supervision can reduce CO 2 emissions by up to 67% and increase low-carbon benefits by 17%; low-carbon technology can reduce CO 2 emissions by up to 60% and increase low-carbon benefits 33%. The government and enterprises should formulate appropriate policies and strategies based on the level of low-carbon sustainable development of enterprises. [Display omitted] [ABSTRACT FROM AUTHOR]