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Paper mill sludge (PMS) is featured with a high content of cellulose and hemicellulose, and using its characteristics to make paperboard can achieve a high-value utilization of PMS, which has attracted growing interest. In this study, currently prevalent landfill, incineration technologies (generating heat and electricity by incineration), and three paperboard technologies (medium density fiberboard, pulp board, and corrugated paper) were evaluated and compared via life cycle assessment (LCA) and life cycle costing (LCC) methods. LCA results show that the PMS-to-pulp board outperforms others with an energy conservation and emission reduction (ECER) value of − 2.86 × 10−8, while the landfill exhibits the highest overall environmental impact with an ECER value of 4.80 × 10−9. LCC results reveal that the PMS-to-pulp board delivers the highest economic profit with $257.357, while the landfill is the lowest with $ − 35.63. The PMS paperboard technologies are more economically friendly than the incineration technologies due to additional electricity/steam consumption during the PMS pre-drying process in incineration. In addition, different scenarios were set up to explore national GHG emission reduction potential by increasing paperboard technologies application rate and reducing the proportion of landfill and incineration. The scenario analysis suggests that replacing 90% of landfill and incineration ratio with PMS paperboard technologies could tremendously improve the overall emission reduction performance with − 9.08 × 1010 kg CO2 eq. This result indicates that the PMS treatment technology transformation has a significant favorable impact on the achievement of the "carbon neutrality" target. [ABSTRACT FROM AUTHOR]

The paper by Kiss and Szalay ([12]) titled I Sensitivity of buildings' carbon footprint to electricity decarbonization: a life cycle-based multi-objective optimization approach i examines how changes in electricity mix impacts GHG emissions. The Intergovernmental Panel on Climate Change (IPCC) emphasizes the need to immediately tackle climate change by significantly reducing greenhouse gas (GHG) emissions and capping global warming at 1.5 °C above pre-industrial levels (IPCC, [8]). The study found that total GHG emissions from maize production were on average 429 ± 27 kg CO2-eq/ton grain, with the highest emissions occurring during the dry season. This SI further contributes to raising awareness to the topic of measuring GHG emissions, decarbonization measures as well as climate neutrality. [Extracted from the article]

How the transformation of trade patterns affects carbon emissions is an important topic in the field of trade and the environment. Based on the panel data of Chinese cities from 2000 to 2016, this paper uses fixed effect model, instrumental variable model and threshold estimation model to investigate the impact of the transformation of export trade patterns on carbon emissions and its internal mechanism. We find that during the investigation period, the transformation of export trade pattern has a significant "U"-shaped nonlinear impact on carbon emissions, and the research results still hold after a series of robustness checks and instrumental variable estimation; through the mechanism analysis of the threshold effect, it is found that in the process of the impact of trade patterns transformation on carbon emissions, there are double thresholds for energy structure transition; the nonlinear impact of export trade pattern transformation on carbon emissions has significant heterogeneity in different regions, city categories, and different periods; the mechanism analysis results show that industrial structure upgrading, industrial co-agglomeration, and green technology innovation are the main paths that the transformation of export trade patterns affects carbon emissions. Under the dual goals of fulfilling China's commitment to "carbon peak in 2030 and carbon neutrality in 2060" and implementing corporate social governance to promote green and sustainable development, this paper will provide suggestions for realizing the goal of low-carbon emission reduction from the perspective of the transformation of export trade patterns. [ABSTRACT FROM AUTHOR]

The double-carbon goal proposal has made it imperative for China's power industry to address the urgent issue of reducing greenhouse gas emissions from coal-fired power plants and promoting their clean and efficient use. A new approach to achieving peak-shaving and improving grid stability is the combination of carbon capture and storage (CCS) facilities with coal-fired power plants, which offers a strategic solution for mitigating climate change. Nonetheless, the viability of CCS retrofitting for coal-fired power plants in China hinges on its economic feasibility. The technical characteristics, economic analysis, and policy implications of clean coal-fired power plant equipped with CCS (CCP-CCS) technologies are evaluated in the paper. A comparison of the characteristics of different clean coal power generation technologies, including capacity, efficiency, coal consumption, and environmental performance, is conducted. The paper analyzes the economic feasibility of four typical clean coal power generation technologies, namely Supercritical (SC), Ultra-supercritical (USC), Integrated Gasification Combined Cycle (IGCC), and Circulating Fluidized Bed (CFB), both with and without CCS, using the levelized cost of electricity (LCOE) model. Financial parameters, investment parameters, operation and maintenance parameters, tax parameters, and capacity parameters are all considered in the LCOE model. The results indicate: (1) If CCS is not installed, the LCOE of USC power plants is the lowest at 0.37 yuan/kWh, while the LCOE of IGCC power plants is the highest at 0.44 yuan/kWh. (2) If CCS is installed, the LCOE of CFB units is the highest at 0.74 yuan/kWh, while the LCOE of USC units is the lowest at 0.60 yuan/kWh. (3) In sensitivity analysis, coal prices have the most significant impact on LCOE, followed by expected annual operating hours, while the cost of carbon capture equipment is the least sensitive. (4) The cost of retrofitting CCS on clean coal-fired power plants (CCP) is currently high, with an LCOE increase of around 40 to 70%, which is comparable to that of renewable energy electricity. This paper presents policy recommendations, including preferential loans, tax incentives, and R&D funding, to promote the development of CCP in China based on the economic analysis results and challenges faced by CCP. Additionally, the paper proposes relevant policy implications such as preferential loan policies, a diversified financing system, R&D and innovation, and the establishment of a carbon trading market for CCS in China to provide practical guidance for the promotion of CCP-CCS technologies in China. [ABSTRACT FROM AUTHOR]

A major environmental concern today is the carbon emissions caused by rapid urbanization. As the largest developing country and carbon emitter, China has controlled the urban growth boundary (UGB) as a quasi-experimental policy to achieve carbon neutrality. Therefore, this paper employs the difference in differences (DID) method, for panel data from 2000 to 2019 in China to shed light on the effects on carbon emissions. Results show that the UGB can reduce carbon emissions considerably. After the implementation of the policy, the carbon emissions of the pilot cities decreased by 23.91%. Additionally, a series of robustness tests such as PSM-DID and Placebo tests support the conclusions. Moreover, the greater influence is reflected in the scope of the whole city and the intensity of the permanent plan. The UGB is more susceptible to cities in the central and western areas and cities with weak environmental regulations. Through the mechanism tests, the emission reduction effect of the UGB will be greater in cities with larger vegetation coverage and advanced industry structure. Furthermore, our analysis suggests the UGB needs to be adequately promoted as a policy to achieve carbon neutrality in cities. To make the policy more effective, vegetation cover and industrial structure ought to be taken into consideration. [ABSTRACT FROM AUTHOR]

As a major part of global development governance, G20 countries account for 80% of global carbon emissions. In order to achieve the goal of "carbon neutrality" proposed by the United Nations, it is important to compare and analyze the drivers of carbon emissions in G20 countries and provide recommendations for their carbon emission reduction. Based on the data of 17 G20 countries in the EORA database, this paper compares the drivers of carbon emissions of each country from 1990-2021 using weighted average structural decomposition and K-mean model. This paper focuses on four drivers, including carbon emission intensity, final demand structure, export structure, and production structure. Carbon emission intensity and final demand structure are the main factors of carbon emission reduction, and the other two factors have little influence. Among the G20 countries, the UK is in the first category because it does the best job on the four factors of carbon emissions, yet Italy is in the last category because it does not take full advantage of the four factors. Therefore, improving supply energy efficiency and adjusting demand, export, and industrial structure have become important tools for countries to transform and achieve carbon neutrality. [ABSTRACT FROM AUTHOR]

As the largest energy consumer, China's control of carbon emissions from energy consumption plays a pivotal role in world climate governance. However, few studies have been conducted to explore the emission reduction pathways that promote a high level of synergy between China's economic growth and the " carbon peaking and carbon neutrality " goal from the perspective of energy consumption. Based on the measurement of energy consumption carbon emissions, this paper reveals the spatial and temporal distribution and evolution trends of carbon emissions in China at the national-provincial level. The multi-dimensional socio-economic factors such as R&D and urbanization are taken into account, and the LMDI model is used to decompose the driving effects of energy consumption carbon emissions at the national-provincial levels. Further, this paper combines the Tapio decoupling index with the LMDI model to decompose the decoupling states of China year by year and at the provincial level in four periods to explore the reasons for the change of carbon decoupling states. The results show that: (1) China's energy consumption carbon emissions grew at a high rate before 2013, and slowed down after that. There are significant differences in the scale and growth rate of carbon emissions among provinces, which can be classified into four types accordingly. (2) The R&D scale effect, urbanization effect, and population scale effect are the factors driving the growth of China's carbon emissions; while the energy structure effect, energy consumption industry structure effect, energy intensity effect, and R&D efficiency effect inhibit the growth of China's carbon emissions. (3) Weak decoupling is the most dominant decoupling state in China from 2003 to 2020, and the decoupling state varies significantly among provinces. According to the conclusions, this paper proposes targeted policy recommendations based on China's energy endowment. [ABSTRACT FROM AUTHOR]

This paper constructs a novel stress measurement system of carbon market from the perspective of trading, emission reduction, and external shocks and simulates the stress indices of national and pilot carbon markets of China with the methods of functional data analysis and criteria importance through intercriteria correlation. It concludes that the overall carbon market stress is in the shape of "W" and still at a high level, with frequent fluctuations and an upward trend. In addition, the stress of Hubei, Beijing, and Shanghai carbon market fluctuates and rises, while the stress of Guangdong carbon market decreases. Moreover, carbon market stress mainly comes from trading and emission reduction. Furthermore, stress fluctuation of Guangdong and Beijing carbon market is more prone to "big waves," indicating that the two markets are sensitive to big events. Finally, the pilot carbon markets are divided into stress-driven and stress-release market and the type of which keeps change in different period. [ABSTRACT FROM AUTHOR]

This paper investigates the relationship between digital finance and carbon emissions and explores the ecological effects of digital finance. Based on a panel data of 256 cities in China from 2011 to 2018, this paper investigates the impact of digital finance on carbon emissions and its intrinsic mechanisms. First, digital finance significantly suppresses the intensity of regional carbon emission, and the breadth of coverage, depth of use, and degree of digital support of digital finance together curb regional carbon emissions, with the strongest suppressive effect being the breadth of coverage. In addition, the regression results remain significant after a series of robustness tests. Second, it reveals the potential mechanism of digital finance to curb urban carbon emissions. These mechanisms include the three channels: promoting industrial advancement, green technology innovation, and optimizing labor resource allocation. Third, the heterogeneity test finds that the energy saving and emission reduction effects of digital finance are significantly stronger in non-low-carbon pilot cities with low urbanization rates, confirming the emission reduction utility of digital finance development. Therefore, we should take advantage of digital finance to improve the green development of financial services and adopt diverse policy measures according to local conditions to maximize the ecological effects of digital finance on energy saving and emission reduction. In the context of the development strategy of "carbon peaking and carbon neutral," this study has some implications for management in developing a regional green development system supported by digital finance. [ABSTRACT FROM AUTHOR]

The establishment of the green belt and road is an inevitable choice to conform to and lead the green and low-carbon cycle development and an inherent requirement for sustainable development. Therefore, we establish an evaluation system of green development oriented to carbon neutrality, and calculate the green development level (GDL) of the provinces along the belt and road in China from 2003 to 2018 by using a three-dimensional evaluation model. In addition, this paper employs the Obstacle Degree Model to identify the main obstacle factors that affect GDL, and provides targeted and differentiated countermeasures and suggestions for improving the regional GDL. Our results suggested that the overall GDL has improved, but not obvious, with a low level. The GDL and coordination degree between different regions exist certain differences, and its spatial pattern is characterized by "high in southeast and northeast, low in southwest and northwest". From a regional perspective, innovation capacity is the key factor that affects the green development of the region in southeast, northeast, northwest and southwest China. Driving economic green transformation and promoting industrial energy conservation and emission reduction through technological innovation are the internal driving forces to achieve regional green sustainable development. [ABSTRACT FROM AUTHOR]

With the increase in energy demand and carbon emission requirements, energy management and CO2 emission reduction on the user side are significant for integrated energy system (IES) scheduling. This paper constructs a two-stage optimal dispatching model combining active/passive demand response (DR) and reward and punishment ladder-type carbon trading. In the first stage, the electricity/gas load was optimized by adding a logistics function to the active DR model. A passive DR model is built based on the optimized electric load and the heat/cooling–electricity ratio of the cogeneration unit to optimize the heat/cooling load. In the second stage, a multi-objective IES model based on the optimized load and reward and punishment ladder carbon trading was solved by the golden eagle multi-objective optimization (MOGEO). Analyzing the scheduling results from different scenarios, the active/passive DR model can reduce the load peak-to-valley difference and improve user satisfaction and grid revenue. At the same time, the combination of reward and punishment ladder carbon trading makes the system gain more carbon revenue, reduces system operating costs and carbon emissions, and improves energy utilization. [ABSTRACT FROM AUTHOR]

Many countries have launched the carbon emission trading scheme (ETS), attempting to limit carbon emissions through total amount control, and thus accelerating the improvement of emission reduction technology. However, the role of the ETS in emission reduction technical change (ERTC) is still controversial. To clarify the role of the ETS in ERTC, this paper firstly proposes an endogenous growth equilibrium model to theoretically analyze how the ETS induces ERTC, and extracts the corresponding influencing factors. Then, the emission reduction technology is further decomposed into the source, process and end-of-pipe emission reduction technologies by the whole process decomposition method. Last, taking China's carbon pilot market as a sample, we use the time-varying difference-in-difference method to empirically estimate the impacts of the ETS on ERTC. Results show that: (1) the ETS is conducive to ERTC, but whether the effect is significant is depends on the technology accumulation in the early stage, research efforts, success probability of technology research, and carbon trading effect; (2) China's ETS significantly improved the process emission reduction technology, but has no obvious effects on the source and end-of-pipe emission reduction technology. (3) China's ETS has heterogeneous impacts on technical change concerning different regions. Accordingly, three suggestions are provided, including laying out new technologies for energy conservation and emission reduction, expanding the industry coverage of the ETS, and correcting the distortion of carbon trading price. [ABSTRACT FROM AUTHOR]

The reduction of carbon emissions has become an important climate issue worldwide. However, the diversity of carbon trading systems and the differentiation policy may generate incomparable carbon abatement costs across regions and countries. Based on the nonparametric model, this paper investigates the shadow price of carbon emissions and energy structure in 38 Asian countries from 1991 to 2019. The main findings of this paper are as follows: (1) The annual average shadow price of carbon emissions experienced a fluctuating decline for Asian countries during the period 1991–2000, followed by a continuous rise and then a fluctuating decline. (2) Industrialization may lead to a decline in carbon shadow price, while urbanization may lead to a rise in the opportunity cost of carbon reduction. (3) The carbon shadow price in countries of Asia–Pacific Economic Cooperation (APEC) is lower than that in non-APEC countries. (4) The structure of energy consumption is negatively related to marginal abatement costs, while on the contrary, the coefficients of the level of human resources are significantly positive. We also derive corresponding policy measures to promote intra-regional emission reduction. [ABSTRACT FROM AUTHOR]

Carbon emission trading policy (CETP) is an important tool for energy savings and emission reduction. However, the effect of CETP on carbon emission reduction in power industry is still unknown. This paper uses the difference-in-differences (DID) model and the intermediary effect model to test the impact and mechanism of CETP on power industry carbon emissions. In addition, a spatial difference-in-differences (SDID) model is established to analyze the spatial spillover effect. The results show that CETP has a significant inhibitory effect on power industry carbon emissions and the results are still valid after endogenous and robust tests. The improvement of technology level and power conversion efficiency plays an intermediary role for CETP to reduce power industry carbon emissions. The optimization of power generation structure is likely to become another important way for CETP to play its role in the future. The spatial spillover effect test shows that CETP not only has a significant inhibitory effect on power industry carbon emissions in the pilot areas but also has a negative spatial spillover effect on power industry carbon emissions in the surrounding non-pilot areas. The heterogeneity tests show that CETP has the most significant reduction effect in the central region of China and the strongest spatial spillover inhibiting effect in the eastern region. The purpose of this study is to provide decision-making references for government to achieve China's dual-carbon goal. [ABSTRACT FROM AUTHOR]

As Chi na's shipping industry continues to develop, ship emissions have become a significant source of pollutants. Consequently, it has become imperative to comprehend accurately the nature and attributes of ship pollutant emissions and understand their causation and effect as a crucial aspect of pollution control and legislation. This paper employs high-precision automatic identification system (AIS) dynamic and static data, along with pollutant emission parameters, to estimate the pollutant emissions from a ship's main engine, auxiliary engine, and boiler using a dynamic approach. Additionally, the study considers the sailing state and trajectory of the vessel and analyzes the characteristics of ship carbon emissions. Taking Tianjin Port as an example, this study conducts a multi-dimensional analysis of pollutant emissions to gain insight into the causation and effect of pollutants based on the collected big AIS data. The results show that the pollutant emissions in this region are mainly concentrated in the vicinity of Tianjin Port land port area, Dagusha Channel, and the Main Shipping Channel of Tianjin Xingang Fairway. Carbon emissions peak in September and are lower in June and December. Through accurate analysis of pollutant emission sources and emission characteristics in the region, this paper establishes the regular relationship between pollutant emissions and possible influencing factors and provides data support for China to formulate accurate pollutant emission reduction policies and regulate ship construction technology and carbon trading. [ABSTRACT FROM AUTHOR]

The application of the farm biogas project is a perfect measure to deal with the increasingly nervous global climate problem and energy crisis and can support the accomplishment of urgently needed carbon peaking and carbon neutrality effectively. But the poor economic benefits hinder its better development. Thus, this paper aims to enhance the economics of farm biogas projects and explore a win–win model for economic and environmental benefits by studying the economic impact of participation in carbon trading on three types of farm biogas projects. First, economic analysis of farm biogas projects based on life cycle cost is carried out using case analysis. Second, the greenhouse gas emission reductions are calculated and benefits from carbon trading are considered. Then, the economic robustness was tested. Specifically, the economics of all three types of farm biogas projects is improved after carbon trading. The ecological farm biogas project has the best economic performance, with a net present value of $551,689.11, internal rate of return of 49%, and payback period of 2.39 years. In addition, the emission reductions of 5045.79 t CO2e, 7420.28 t CO2e, and 148.41 t CO2e are very significant. Based on these, suggestions for developing farm biogas projects and introducing biogas projects to carbon trading are put forward for the reference of governments and investors when making investments and reforms. According to the result, participation of farm biogas projects in carbon trading can effectively enhance economic benefits and accelerate the achievement of the greenhouse gas emission reduction target which is of great significance to the urgent goal of global green and low-carbon transformation. [ABSTRACT FROM AUTHOR]

With the gradual increase of international willingness to reach the carbon peak and carbon neutrality, this paper decomposes the influencing factors of China's carbon emission changes from 2008 to 2019 using the Logarithmic Mean Divisia Index model (LMDI), and analyzes the contribution amount and rate of each influencing factor. The results found that: for the whole country, the cumulative growth of carbon emissions during the study period is about 416,484.47 (104 tons), among which the economic growth effect plays a major role in promoting, with a cumulative contribution rate of 284.16%; The increase in regulation intensity and the optimization of industrial structure, however, suppress carbon emissions well, with a cumulative contribution rate of about – 199.21% and − 64.75%, respectively, during the study period. For economic regions, the cumulative influence direction of each driver is the same as that of the whole country, while the population size effect in the northeast economic region and the regulation input effect in the eastern coastal economic region act in the opposite direction from other economic regions, and the carbon emission reduction direction of the energy intensity effect varies from one economic region to another. Accordingly, this paper proposes policy recommendations to enhance regulatory intensity, optimize industrial and energy consumption structure, implement localized emission reduction strategies, and promote synergistic emission reduction in economic zones. [ABSTRACT FROM AUTHOR]

Nowadays environmental issues have been of great concern to the world, among which the problem of global warming caused by greenhouse gas emissions is particularly prominent. All countries in the Kyoto Protocol and the Paris Agreement have committed to control greenhouse gas emissions, and China, as the largest carbon emitter, has assumed a heavier burden. China has been striving to develop low-carbon technologies such as hydrogen, nuclear, wind, and solar energy, but the most attention should be paid to CCUS, which many scholars have high expectations that CCUS can help China reduce emissions to some extent. Therefore, this paper presents a prediction that CCUS can reduce 3.8% of carbon emissions for China in 2040 when CCUS emission reductions increase at a rate of 30%. The power and chemical industries could reduce carbon emissions by 2.3% and 17.3%, respectively. [ABSTRACT FROM AUTHOR]

Since the 18th National Congress of Chinese Communist Party, ecological civilization construction has been incorporated into Five-sphere Integrated Plan, that is, to promote coordinated progress in the economic, political, cultural, social, and eco-environmental fields. The Chinese government has proposed the goal of "carbon peak" and "carbon neutrality". Low-carbon transportation becomes the mainstream. To achieve carbon peak and carbon neutrality in public transport, this paper takes Beijing's public transport sector as a case study, using system dynamics model with relevant policies and the current situation. It calculates and predicts carbon emissions under electric vehicle substitution scenario, clean energy generation, and carbon capture, utilization and storage scenario for the period of 2020–2060. The following main conclusions are obtained: Direct carbon emissions have peaked and started to decline based on the current measures, while indirect carbon emissions have peaked and started to decline under the suggested intervention. The direct carbon emissions peaked at 2.58005 × 106 tons in 2014. The indirect carbon emissions peaked at 1.59027 × 106 in 2025. They all achieved carbon neutrality under the suggested intervention. Electric vehicle substitution and carbon capture, clean energy generation, utilization and storage are the main factors of carbon emission reduction. The outcomes of this study can provide essential information for policy-makers to advance Beijing's future low-carbon development in public transport. The electric vehicle substitution, clean energy generation and carbon capture, utilization and storage provide a new perspective to research carbon emissions in the transport sector. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to determine the spatial spillover effects of renewable energy on carbon emissions in China's less-developed areas. However, few studies have considered this issue from the perspective of less-developed areas. Based on panel data of 21 provinces in China from 2000 to 2017, this paper analyzes the spatial spillover effects of renewable energy on carbon emissions using Moran's I and Spatial Durbin Model (SDM). The results suggest that, first, Moran's I ranges from 0.378 to 0.519, Moran scatter plot presents that provinces are located in the high–high (HH) and low-low (LL) quadrants, indicating provincial carbon emissions in the study area have a significant spatial correlation and agglomeration. Second, under the three matrices, the direct effect coefficients of renewable energy are -0.2522, -0.2639 and -0.2601, this shows that renewable energy is beneficial to local carbon emissions reduction. In contrast, the indirect effect coefficients of renewable energy are 0.0605, 0.1012 and 0.1125, which means higher renewable energy consumption in a single area is conducive to the improvement of carbon emissions to neighbouring areas. Third, urbanization, industrialization, physical capital and other variables have different impacts on local and nearby carbon emissions. This study provides empirical evidence to achieve carbon emission reduction targets by government policymakers. [ABSTRACT FROM AUTHOR]

It will contribute to ameliorating the national carbon trading system and further benefit the realization of China's carbon peaking and carbon neutrality goals through in-depth study and summarize the effectiveness of carbon trading policy implementation in pilot areas. Based on the multi-phase difference-in-differences approach and synthetic control method, this paper utilizes China's provincial panel data from 2006 to 2020 to comprehensively assess the Porter effect (including the economic and green innovation effects) and carbon mitigation effect of carbon trading policy from the overall and local perspectives. Then the robustness test and mechanism analysis are carried out. The findings show that: (1) from the overall effect, the carbon trading policy brings a noticeable carbon mitigation effect and Porter effect, and the intensity of the impact keeps changing over time; (2) there is significant heterogeneity in the local effects of this policy on the eight pilot provinces and cities, with only Chongqing obtaining both the Porter effect and the carbon mitigation effect, while the rest of the regions do not yield the triple dividend of economic, environmental, and green innovation simultaneously; (3) there are much more prominent environment and green innovation effects in the developed regions, while the underdeveloped ones have better economic development and no green innovation effect; (4) the policy can bring environmental and economic dividends through energy structure optimization. However, due to the carbon rebound effect, stimulating green innovation pathways can only boost the economy while carbon emissions increase instead. The research conclusions can provide the decision support and policy direction for policies related to China's carbon market. [ABSTRACT FROM AUTHOR]

With ecological civilization becoming an increasingly high profile topic, terms such as carbon neutrality and carbon markets have entered the research landscape. Carbon prices are the core of carbon markets. After analyzing the eight carbon trading markets in China, this paper finds that carbon prices are poorly balanced, i.e., they vary widely between pilots. Regional carbon prices show a discrete distribution, and regions with better carbon market development do not have a spatial demonstration effect on neighboring regions. Therefore, in the initial stage of China's unified carbon trading market, the mandatory control threshold amount should be lowered to allow more enterprises can participate in emission reduction. Reliance on nonclean energy should be weakened, investment in environmental protection and emission reduction should be strengthened, the proportion of carbon offset in forestry should be increased, and a carbon tax should be gradually introduced. The paper's overall aim is to bridge regional barriers and narrow differences to achieve a smooth transition from pilot regions to national and global carbon markets. [ABSTRACT FROM AUTHOR]

The carbon emissions of the beer industry have always been a concern. To reduce environmental pollution, this paper systematically calculates the carbon emissions of the beer supply chain and studies the optimization of carbon emissions reduction through scenario simulation. In this study, the boundary of the beer supply chain carbon emissions system is constructed. The scenario simulation and simulation analysis are carried out based on five factors: water recycling utilization rate, power generation mode, weight–volume ratio, recovery ratio, and transportation mode. To obtain the optimal scheme of economic cost and emissions reduction, the cost of the beer supply chain is analyzed under the condition of carbon trading. The results show that the proportion of carbon emissions in each link of the beer supply chain is production, packaging, transportation, and storage, which are 59.58%, 22.27%, 17.67%, and 0.5%, respectively. The improvement of the water recycling utilization rate of manufacturing enterprises can reduce the overall carbon emissions of the supply chain, and the effect is obvious. The highest proportion of carbon emissions in the packaging link is the bottle consumption stage (22.43%). Raw materials transportation accounts for the highest proportion of total carbon emissions in transportation (63.73%). The waterway/railway ratio will be increased to 0.6/0.4, and the carbon emissions in the supply chain will be reduced by 5.7%. In the context of carbon trading, when the carbon trading price is higher than 49.16 yuan/ton, enterprises can achieve a win-win situation in reducing emissions and maintaining positive economic growth by the measures given in the paper. [ABSTRACT FROM AUTHOR]

To accelerate the low-carbon transformation of the power industry, a range of carbon emission reduction policies and technologies have emerged. However, the current China's carbon emissions trading (CET) policy is inadequate in encouraging power generation enterprises to take proactive measures towards emission reduction due to challenges like fixed and low carbon prices. The high proportion of renewable energy in electricity consumption also faces significant challenges due to the unpredictable nature of wind and PV energy. Therefore, this paper applies stepped CET mechanism, energy storage system (ES) system and carbon capture and storage (CCS) mechanism together to hybrid renewable energy system, aiming to study their synergistic carbon emission reduction effect. Firstly, the paper constructs the stepped CET model considering incentives and penalties. Secondly, the stepped CET model, ES system and CCS are jointly introduced into the hybrid renewable energy system. Finally, a scenario analysis is conducted to investigate the synergistic effect of various carbon emissions reduction policies and technologies in the operation of power generation systems. The results show that: i) compared with traditional CET, the stepped CET increases renewable energy consumption by 0.12% and reduces carbon emissions by 0.6%; ii) the introduction of stepped CET and ES equipment together consumes an additional 36.1% of renewable energy and reduces carbon emissions by 32.4%; iii) based on stepped CET model and ES equipment, the introduction of CCS system reduces carbon emissions by 29.4%. [ABSTRACT FROM AUTHOR]

Many developing countries are facing the difficulty of choosing between economic growth and energy conservation and emission reduction (ECER). China has strengthened the implementation of ECER by setting environmental accountability as the development goal of local governments, hoping to have better governance effects. To evaluate the actual intervention effect of this approach, this paper constructs panel data covering 46 countries from 1995 to 2014 and uses the difference-in-differences (DID) method and the composite control method to quantitatively analyse the policy effect. The results show that China can effectively curb energy consumption and carbon emission intensity per unit of GDP by adding ECER targets to the government's five-year plan, which has significant effects on ECER. Furthermore, we use an intermediary mechanism to test and identify low-carbon alternatives and an ECER promotion mechanism for technological advancement. The conclusion shows that economic development is compatible with low carbon and energy consumption. Combined with China's long-term goals for ECER, it can be considered that on the road to achieving carbon peaking and carbon neutrality in the future, the economy and tertiary industry should be rationally developed, the degree of urbanization should receive more attention, and the proportion of thermal power generation should be reduced. [ABSTRACT FROM AUTHOR]

With the rapid developm the application of digital ent of the new generation of information and communication technologies (ICT), the state-level governance model has undergone profound changes. It is worth pondering whether this change will have an impact on the carbon peak and carbon neutrality goals. Therefore, we collected data from 51 global economies that have proposed carbon neutrality targets from 2003 to 2020 to build a series of spatial measurement models and explored the impact of e-government construction on carbon emission intensity (CEI). Then, we further considered regional heterogeneity factors, grouped the selected countries into Asian, European, and American countries, and verified the differences between e-government construction and CEI in different regions. Additionally, on the basis of the spatial mediation effect model, this paper analyzed the industrial structure which played an intermediary role in achieving target for reducing CEI through e-government construction. The main findings are as follows. (1) A higher level of e-government construction will result in lower-carbon emissions intensity. (2) Spatial spillover effect regression results showed that the construction of e-government in neighboring countries also significantly inhibits the carbon emission intensity of the host country. (3) There was significant regional heterogeneity in the impact of e-governments on CEI; in Asia, the construction of e-governments significantly reduced CEI, but no significant reductions were observed in Europe and America. (4) E-governments influenced CEI by optimizing the industrial structure. The construction of e-governments was effective in Asia and Europe, while intermediary effect test was failed to pass in the Americas. This study mainly focused on the environmental benefits brought by the construction of e-governments, and the obtained results would provide an important reference for the achievement of the dual-carbon goals in countries worldwide. [ABSTRACT FROM AUTHOR]

As a powerful engine for economic reform and curbing carbon emissions, digital inclusive finance provides solid support for achieving the goal of digital carbon neutrality. This study reveals the positive effect of digital inclusive finance on carbon emission reduction and the deeper reasons behind it by digging deeper into the panel data of 213 cities in China. The study adopts advanced empirical analysis methods to rigorously test the association between digital inclusive finance and carbon emissions. The results show that there is a strong positive correlation between the booming development of digital inclusive finance and the significant decline in carbon emissions. This finding remains solid after several rounds of robustness tests, which fully proves the reliability of the research results. Further mechanism analysis reveals the multiple paths of digital financial inclusion on carbon emission reduction. First, it promotes the optimization and upgrading of industrial structure by optimizing the allocation of financial resources, thus reducing the proportion of high-carbon emission industries. Second, digital inclusive finance attracts more foreign capital inflows and introduces advanced low-carbon technologies and management experience, further promoting the development of low-carbon economy. In addition, the study also found that the differences between different cities in terms of geographic location and city size have a significant impact on the carbon emission reduction effect of digital inclusive finance. In particular, the carbon emission reduction effect of digital inclusive finance is particularly significant in western regions, central cities, and first-tier cities. In response to these findings, this paper proposes a series of targeted policy recommendations. First, the financial service system should be further optimized to increase the coverage and penetration of digital inclusive finance, especially in less developed regions and small- and medium-sized cities. Second, regional policy synergies should be strengthened to form a strong synergy to promote the development of a low-carbon economy. In addition, it should guide capital flows to low-carbon industries and encourage enterprises to increase green technology research and development and application, while actively promoting low-carbon consumption concepts and guiding consumers to form green consumption habits. Through the implementation of these measures, it is expected that the potential of digital inclusive finance in the development of a low-carbon economy will be further stimulated, making a greater contribution to the realization of the goals of carbon peaking and carbon neutrality. [ABSTRACT FROM AUTHOR]

To ensure the realization of carbon neutrality and emission peak, the Chinese government promulgated the pilot policy for an emissions trading scheme (ETS) in 2011 and gradually expanded the range of the pilot program. However, it has not been systematically studied whether this policy can achieve double dividend and its transmission mechanism. Based on the Porter hypothesis, this paper explores the impacts of an ETS on macro emission reduction and microeconomic performance, verifies the influence of an ETS on double dividend, and analyzes its transmission mechanism using a difference in difference (DID) model and mediation model. The results indicate that an ETS can reduce CO2 emissions and remarkably improve the economic performance of the enterprises in the areas it is enacted. A double dividend has been realized, which verifies Porter's hypothesis. The mechanism test shows that from the macro perspective, the emission reduction effect of an ETS is mainly achieved by adjusting the energy structure and through local government regulations. In contrast, the mediation effect on the industrial structure is not apparent. From a micro perspective, an ETS mainly affects the economic situation of enterprises through cash flow and technological innovation. Moreover, the transmission effect of enterprises' low-carbon behavior is not apparent. Heterogeneity analysis shows that compared with Midwestern China, an ETS could reduce emissions by adjusting the energy structure in Eastern China. Also, compared with state-owned or large enterprises, an ETS helps improve the economic performance of small or non-state-owned enterprises through technological innovation. This paper provides empirical evidence from macro- and microperspective for evaluating an ETS, conducive to improving the top-level framework of China's future carbon market operation. [ABSTRACT FROM AUTHOR]

With the introduction of national carbon neutrality targets, carbon emission reduction actions in developed countries have become a hot topic as part of the international community's drive to take action to mitigate climate change. Carbon emission efficiency is an important indicator that can be used to measure progress toward carbon emission reduction targets. The relationship between green technology innovation and carbon emission efficiency has not been adequately studied, and the transmission mechanism is not yet clear. Based on the above research gaps, taking 32 developed countries that have proposed carbon neutral targets as research samples, this paper used spatial econometric models to explore the impact of green technology innovation on carbon emission efficiency and adopted spatial mediation model and spatial moderation model to analyze the transmission effects of economic development, urbanization, and financial development on environment-related green technology and carbon emission efficiency. This paper aimed to provide a policy basis for developed countries to mitigate carbon emissions and achieve carbon neutrality goals as soon as possible. The following results were obtained: (1) Luxembourg, Norway, and Switzerland were found to be efficient in terms of carbon emissions, while most developed countries were in an inefficient state. (2) Environment-related green technology innovation significantly improved carbon emission efficiency. (3) Economic development and urbanization had a mediating role on green technology innovation and carbon emission efficiency. In other words, green technology innovation could have an indirect impact on carbon emission efficiency by influencing economic development and urbanization. (4) Financial development could positively moderate the sensitivity of carbon emission efficiency to green technology innovation. Improving the level of green technology innovation is one way to improve carbon emission efficiency, and the mediating effect of economic development and urbanization can be used as a focus point to improve carbon emission efficiency. The pressure of carbon emission reduction can be moderated by finance development. The results of this study provide theoretical support that will assist developed countries in achieving their carbon neutrality targets. [ABSTRACT FROM AUTHOR]

Studying the comprehensive performance of industrial carbon emission has profound significance for improving carbon allowance allocation scheme and achieving the carbon neutrality target. The paper selects 181 enterprises in Zhengzhou as the case, a comprehensive carbon emission performance indicator system and a carbon allowance allocation model were established, and compared with other allocation schemes (historical/baseline method). The results showed that the overall differences in the comprehensive performance evaluation indicator of carbon emissions in typical industries in Zhengzhou were obvious, and there was a correlation with the characteristics of industrial production activities. The overall emission reduction of Zhengzhou was 244.33×103t, and the emission reduction ratio was 7.94% by simulating carbon allowance allocation under the comprehensive performance. The carbon allowance allocation method based on the comprehensive performance has the strongest restraint on the "high emission, low performance" industry, which is more equitable and more conducive to carbon emission reduction. In the future, it will be recommended to give full play to the leading role of the government, implement industrial carbon allowance allocation based on the comprehensive performance evaluation of carbon emissions, to achieve multi–objectives of resource conservation, environmental pollution abatement, and carbon reduction. [ABSTRACT FROM AUTHOR]

Under the guidance of carbon peak and carbon neutral targets, the industrial structure transformation is vital for carbon emissions reduction in China. However, there is a rebound effect of carbon emissions during the industrial structure transformation. Resource dependence and technological progress have significant impacts on industrial structure transformation and its carbon reduction effect. This paper explores how industrial structure transformation under resource dependence causes the rebound effect from a technological progress perspective. The key results indicate that (1) resource dependence distorts the carbon emissions reduction effect of industrial structure transformation; (2) with the development of technology, the industrial structure upgrading under resource dependence could cause an increase on carbon emissions at the beginning, but the increase would be weakened subsequently, displaying a two-stage feature; (3) the industrial structure rationalization under resource dependence reduces carbon emissions at first, but the reduction would be weakened as the technology develops, then industrial structure's rationalization shows an insignificant impact on carbon emissions, and finally reduces carbon emissions again, presenting a four-stage characteristic; (4) environmental protection technology can correct the distortion effect of resource dependence on the industrial structure rationalization and amplify the industrial structure rationalization's reduction effects on carbon emissions; (5) with the development of energy-saving technology, industrial structure rationalization has a paradoxical impact on carbon emissions, the industrial structure rationalization first reduces, then increases, and finally reduces carbon emissions, indicating an inverted "N" relationship. Finally, policy recommendations for carbon emissions reduction are proposed from the perspective of industrial structure transformation and technological progress. [ABSTRACT FROM AUTHOR]

Low-carbon development of China's power sector is the key to achieving carbon peaking and carbon neutrality goals. Based on the logarithmic mean divisor index (LMDI) model, considering the carbon transfer caused by inter-provincial electricity trading, this paper analyzes the influencing factors of CO2 emissions in the provincial power sector and uses K-means clustering method to divide 30 provinces into four categories to analyze the differences in regional carbon emission characteristics. In addition, by establishing different development scenarios, the carbon emission trends and emission reduction potentials of each cluster under different emission reduction measures from 2020 to 2040 are studied, in order to explore the differentiated emission reduction paths of each cluster. The results show that the contribution of influencing factors shows great differences in different provinces. Trends in CO2 emissions vary widely across scenarios. In the reference scenario, the CO2 emissions of each cluster will continue to increase; in the existing policy scenario, the total power industry will peak at 6.1Gt in 2030; in the advance peak scenario that puts more emphasis on the development of advanced technologies and renewable energy under the clean development model, the carbon emission peak will be brought forward to 2025, and the peak will be reduced to 5.2Gt. Finally, differentiated emission reduction paths and measures are proposed for the future low-carbon development of different cluster power industries, providing theoretical reference for the deployment of provincial-level emission reduction work, which is of great significance to the global green and low-carbon transformation. [ABSTRACT FROM AUTHOR]

This paper considers a supply chain formed by a manufacturer with constrained capital and a retailer with sufficient capital. By using the Stackelberg game theory, we discuss the manufacturer's and retailer's optimization decisions for bank financing, zero-interest early payment financing, and in-house factoring financing under both normal and carbon neutrality scenarios. In the carbon neutrality scenario, numerical analysis shows that improving the efficiency of emission reduction drives manufacturers to switch from external to internal financing methods. The impact degree of green sensitivity on the supply chain's profit depends on the carbon emission trading prices. In the framework of green sensitivity of products and emission reduction efficiency, manufacturers' financing decisions are affected by carbon emission trading prices rather than by whether emissions exceed the standards or not. When the price is higher, internal financing is easier to obtain, whereas the space for external financing is constrained. [ABSTRACT FROM AUTHOR]

With the official national unified carbon market launch on July 16, 2021, the allocation and trading of initial carbon quotas between regions will become the focus of research in the future. Based on a reasonable regional initial carbon quota allocation, introducing the concept of carbon ecological compensation and formulating differentiated emission reduction strategies according to the characteristics of different provinces can better guarantee the realization of China's carbon emission reduction goals. Based on this, this paper first analyzes the distribution effects under different distribution principles from the perspective of fairness and efficiency. Secondly, the Pareto optimal multi-objective particle swarm optimization (Pareto-MOPSO) algorithm is used to build the initial carbon quota allocation optimization configuration model to optimize the allocation results. The optimal initial carbon quota allocation scheme is determined through the comparative analysis of the allocation results. Finally, we explore the combination of carbon quota allocation and the concept of carbon ecological compensation and formulate the corresponding carbon compensation scheme. This study not only reduces the relative sense of exploitation of carbon quota allocation in different provinces but also contributes to the realization of a carbon peak in 2030 and carbon neutrality in 2060 (the "30.60" double carbon target). [ABSTRACT FROM AUTHOR]

With the rapid development of distributed energy resources and natural gas power generation, multi-energy microgrid (MEMG) is considered as a critical technology to increase the penetration of renewable energy and achieve the target of carbon emission reduction. Therefore, this paper proposes a low-carbon economic dispatch model for MEMG to minimize the daily operation cost by considering integrated demand response (IDR) and multistep carbon trading. Specifically, IDR operation includes shifting of shiftable electric load, adjusting of flexible thermal load and cooling load, and it is employed to decrease operation cost. Besides, the multistep carbon trading means that different carbon trading prices correspond to different carbon trading volumes, which is applied to stringently restrict carbon emission. The simulation results show that the proposed model can effectively reduce the carbon emission while greatly decrease the operation cost. [ABSTRACT FROM AUTHOR]

China is committed to achieving the goals of "peak carbon and carbon neutrality," and the carbon dioxide emissions generated in the energy utilization process mainly come from industrial and energy systems. This paper used structural decomposition analysis (SDA) and input-output analysis to study the structural emission reductions in China's industrial and energy systems in 2007–2015. The results revealed that the final demand effect was the main factor promoting the growth of energy-related CO2 emissions and that the energy intensity effect played a weak role in promoting the growth of energy-related CO2 emissions. However, the energy structure effect and input structure effect reduced energy-related carbon emission growth. We found that for energy systems, the emission reduction effects of blast furnace gas, raw coal, refinery dry gas, and natural gas were obvious, while those of crude oil, gasoline, fuel oil, and kerosene were not obvious. For industrial systems, the tertiary industry played a major role in the final demand effect, followed by the secondary industry, and the primary industry in turn. This paper provides a theoretical basis and practical guidance for the carbon peak and carbon neutrality goals of China's energy systems and industrial systems. [ABSTRACT FROM AUTHOR]

The low-carbon transition is a systemic economic and social change that will inevitably have an impact on many areas of the urban system. Has China's ongoing low-carbon transition impacted urban resilience (UR) systems while achieving urban energy saving and carbon emission reduction goals? This paper uses the implementation of the carbon emissions trading pilot policy (CETPP) as a "quasi-natural experiment." It evaluates the impact of the policy on UR using a difference-in-differences model based on the data of prefecture-level cities from 2008 to 2020. The study shows that pilot carbon trading policies favor UR, and the market mechanism of carbon emissions has a heterogeneous cause influence on UR. The impact of pilot carbon trading policies on UR varies according to the respective moderating effects of institutional factors, green technology innovation, industrial structure rationalization, and output effects. [ABSTRACT FROM AUTHOR]

Regarding the goal of "carbon peaking and carbon neutrality," an urgent practical problem is how green finance decreases carbon emissions. This paper uses the dynamic spatial Durbin model and China's provincial panel data to empirically test the impact of green credit on carbon emissions. The results show that green credit effectively curbs carbon emissions, and has significant spatial spillover effects on the carbon emissions. In the short run, the spillover effects of green credit on carbon emissions are greater than the direct effects, but in the long run, the direct effects of green credit on carbon emissions are greater than the spillover effects. The mechanism test finds that upgrading industrial structure is an important transmission channel for green credit to affect carbon emissions, and energy consumption only plays a part of the intermediary role in the direct impact of green credit on carbon emissions. However, green credit has not achieved the goal of carbon emission reduction by promoting low-carbon technology innovation. [ABSTRACT FROM AUTHOR]

Carbon emissions embodied in anthropogenic activities represent the major cause of global warming. Countries, regions, and cities have implemented comprehensive, multi-level and multi-scale measures to reduce emissions and move towards carbon neutrality. The demand for carbon emission reduction (CER) is made more challenging by different geographical locations, country-owned natural resources, and economic development stages. The main objectives of this paper are to conduct a bibliometric analysis to map the frontiers and directions of CER and to explore the paths and development models of CER from the perspective of spatio-temporal, multi-scale, multi-sectoral, and multi-responsible subjects. This study reveals that carbon emission evaluation and prediction, correlation and causal relationship analysis, and CER-related policy simulation and optimization are the most critical hotspots. Additionally, we point out the shortcomings of and future developments for the three study dimensions above. The bibliometric analysis also highlights the fact that a cooperative global value chain as well as amendable policies and mechanisms for CER will help with climate change mitigation and adaptation through the use of advanced carbon capture and storage technologies. We review the technical measures for and policy responses to CER adopted by different countries and industries at the theoretical and practical levels and provide new recommendations. Our work provides important information for climate actions in different countries and sectors and for developing more effective CER strategies and policies. [ABSTRACT FROM AUTHOR]

Land intensive use is important for sustainable land use while carbon emission is a constraint to achieve carbon neutrality; they are closely related and committed to sustainable socioeconomic development. The spatial interactions and complex mechanisms between them make it difficult to clarify their relationship precisely. This paper combines the spatial Durbin model and mediating effect model to describe the effects of urban land intensive use (ULIU) on carbon emissions (CEs) for 30 provinces in China during 1995–2018. An inverse U-shaped relationship between ULIU and CEs is proved while considering the spatial interaction. All the provincial observed values of ULIU are less than the inflection point of the curve, which means that the improvement of the ULIU will cause more CEs. Meanwhile, ULIU has multi-indirect effects on CEs, with urbanization and industrial structure upgrading playing mediating roles in the mechanism. The spatial spillover effects of CEs per unit area on the neighboring provinces are negative, indicating that the interregional influence cannot be ignored. These findings have theoretical and practical significance as they reveal the multi-effects of ULIU on CEs. To realize carbon emission reduction effectively, more attention should be paid to improving the intensity of the urban land and strengthening the regional cooperation. [ABSTRACT FROM AUTHOR]

This paper investigates the effects of Emission Trading Scheme (ETS) adoption on the country-level reduction rate of carbon emission. We first used Environmental Kuznets Curve (EKC) tests to group countries into three categories: inverse U-shaped and gamma-shaped EKC for decoupled countries, and a positive linear EKC for non-decoupled countries. We then examined the effectiveness of ETS adoption. We found ETS was effective for both post-industrial and pre-industrial economies. Compared to countries that have not adopted ETS, the carbon emission reduction (increment) rate of decoupled (non-decoupled) countries that have adopted ETS is faster (slower). Furthermore, ETS adoption significantly reduces overall carbon emissions per capita compared to other global events, such as oil crises. The results imply that a market-based mechanism is an effective strategy for achieving sustainable development, thus, providing insights for policymakers and governments to design effective carbon neutrality policies to achieve sustainable development. [ABSTRACT FROM AUTHOR]

One of the key issues facing the government in achieving carbon neutrality is what methods can be used to effectively reduce carbon emissions. Taking manufacturing enterprises as an example, this paper studies the carbon emission reduction effects of green technology innovation subsidy (GIS), carbon tax (CT), and carbon emission trading (CET). Under the background of social welfare and carbon emission reduction efficiency, we get the results of optimal carbon emission reduction measures in different environments. The results are as follows: (1) In the initial and mature stage of green technology innovation, GIS is the best choice to improve the degree of green manufacturing and maximize social welfare. CT and CET are the best choice to obtain the highest SE (carbon emission reduction efficiency). (2) In the transitional stage, CET and CT can promote the maturity of green technology. However, with the maturity of green technology, the promotion of green technology has weakened. CT is the best choice to achieve the highest SE. (3) When the carbon tax or carbon trading price is at a high or low level, raising the tax rate or carbon trading price can increase the income of enterprises. Therefore, the government should take measures according to the objectives of different stages. When the goal is to maximize social benefits, GIS is the best choice in the initial stage and transition stage, and CET or CT is the best choice in the transition stage. In the initial stage and fertilization stage, when the highest SE, CT, or CET is the best choice, while in the transition stage, CT is the best choice. [ABSTRACT FROM AUTHOR]

Does regional corruption exacerbate regional carbon emissions? To answer this, based on the spatial Durbin model, this study empirically examines the impact of regional corruption on carbon emission, using panel data from 30 provinces in China during the period 2002–2017. The results show that: (1) there is an indistinctive N-shaped relationship between regional corruption and carbon emissions at the national level. Regional corruption tends to initially aggravate carbon emissions, then contributes to emission reduction, and then finally boosts carbon emissions. However, this effect is not statistically significant. The results suggest that the role of regional corruption on carbon emissions is twofold. Corruption can exacerbate and can also inhibit regional carbon emissions. (2) Pronounced regional heterogeneity exists with regard to the influence of corruption on carbon emissions. Regional corruption and carbon emissions show a significant N-shaped dynamic relationship in China's central region, while the relationship is not significant in the eastern and western regions. (3) The impact of regional corruption on carbon emissions varies with time. For 2002–2009, regional corruption did not have a significant effect on carbon emissions. For 2010–2017, the direct effect became significant, and an apparent N-shaped relationship formed between regional corruption and carbon emissions. Based on the empirical results, this paper proposes several policy recommendations regarding corruption and carbon governance. [ABSTRACT FROM AUTHOR]

Based on mainland China's provincial OFDI and carbon emissions data from 2003 to 2018, this paper applied a panel fixed-effects model and spatial econometric model to empirically test whether China's OFDI can be a powerful tool to achieve the "carbon neutrality" target. The empirical results indicate that China's OFDI significantly increases carbon emissions, but this effect has temporal and spatial differences. After incorporating spatial factors into the analysis, the impact of OFDI on carbon emissions differs when modelled by different spatial weight matrices. The green effect of OFDI has the problem of poor channels. It is impossible to achieve energy savings and emission reduction by promoting green technology innovation, improving the rationalization of the industrial structure or reducing energy consumption. The test results of the moderating effect indicate that the development of green finance can weaken the positive effect of OFDI on emissions. [ABSTRACT FROM AUTHOR]

Circular economy plays an important role in carbon emissions reduction. To understand how the development of circular economy in China improve the carbon productivity is of great significance to realize China's carbon peak and carbon neutrality goals. Due to the late introduction of the concept of carbon productivity, only a few studies have preliminarily analyzed the impact of the overall development of circular economy on carbon productivity at the macro level, but they ignored the different impact of different dimensions of the circular economy indicator system on carbon productivity at the micro level. In this context, this paper analyzes the impact of circular economy on carbon productivity by constructing an index evaluation system for the carbon reduction effect of circular economy through the two dimensions of resource efficiency and economic benefits and using the total factor carbon productivity measured by the DEA-Malmquist model and also analyzes the untapped potential of circular economy in different regions, which is expected to provide policy reference for how to achieve green and sustainable development in China under low-carbon constraints. Results show that first, the development of circular economy positively affects carbon productivity, and such promotion effect gradually strengthens with time. Meanwhile, the proposed indices demonstrate varying effects, with the resource efficiency indices outperforming the economic efficiency indices. Second, the varying degrees of circular economy development across regions lead to variations in the carbon reduction effect of circular economy on carbon productivity. Specifically, compared with the eastern and central regions, the western region shows the greater untapped potential of the circular economy. Identifying priorities for circular economy development, developing a circular economy in accordance with the local conditions, developing and utilizing advanced carbon emissions reduction technologies, and opening up further to the outside world have important theoretical value and practical significance for exploring the carbon emission reduction effect of circular economy. [ABSTRACT FROM AUTHOR]

The essential to achieving the 2060 carbon neutrality target in China lies in the performance of the construction industry. Decoupling economic development from CO2 emissions is the main strategy for reducing emissions in the construction industry. This paper is based on panel data for China and its 30 provinces during 2009–2019. A Tapio decoupling model is constructed to analyze the decoupling state of economic development and CO2 emissions in the construction industry. The logarithmic mean Divisia index model is constructed to continue the decomposition of the drivers of the decoupling state and CO2 emissions. The results show that (1) the economic development level of most provinces is positively correlated with their CO2 emissions; (2) Beijing and Jiangsu reach the ideal strong decoupling state, and Heilongjiang has the worst decoupling state. The same type of decoupling state shows a certain aggregation phenomenon in space; (3) economic output plays a critical role in promoting CO2 emissions and decoupling of the construction industry in China and the provinces. The main driver of decoupling is indirect carbon intensity; (4) energy intensity has a greater impact on CO2 emissions reduction in regions with more developed economic levels. Understanding the drivers of the decoupling state in China's construction industry provides a valuable basis for energy efficiency and emission reduction efforts in China and other countries. [ABSTRACT FROM AUTHOR]

Establishing an efficient carbon emissions trading market is a priority to achieve the goal of carbon peaking and carbon neutrality. In the context of income inequality and emissions inequality, this study examined the efficiency of carbon trading in China from the perspective of resident income. First, this paper used the Cobb–Douglas (C-D) production function to incorporate carbon intensity into the production network model and obtained the expression of household income by solving the Walras equilibrium. Secondly, this study put forward a theory that Carbon trading affects the income level of individuals. Finally, in order to test the theory, the study used the differences-in-differences (DID) method, provincial panel data from 2005 to 2019, and the quasi-natural experiment of China's carbon emissions trading pilot. The results indicated that this policy could reduce the per capita disposable income level. Further heterogeneity research showed that although the emission reduction effect was significant, the pilot policy failed to save emission reduction costs and improve residents' welfare. The low efficiency of the carbon market was mainly attributed to the insufficient liquidity of the pilot carbon market. Therefore, it not only failed to achieve efficiency but also increased unnecessary costs, which had a negative impact on income. In addition, the consumption patterns of residents and the industrial-oriented economic structure exacerbated the decline in income. [ABSTRACT FROM AUTHOR]

Carbon emissions are a critical concern in the realm of energy consumption, with many nations committed to curbing them and striving for carbon neutrality. This research addresses a specific gap in the literature by focusing on carbon emission reduction in the industrial sector through the application of supply chain management (SCM) principles under a monopolistic competition context and by utilizing carbon neutral indicators. Specifically, we develop a mathematical model integrated into an agent-based simulation framework and employ experimental design methods to determine the most optimal decision-making processes for incorporating supply chain carbon neutral indicators. Our findings highlight the effectiveness of two specific carbon neutral indicators within SCM: green-credit policies and the promotion of green products. These measures contribute significantly toward reducing global carbon emissions. This paper offers insights for government decision-makers regarding ideal implementation levels and strategies for green credit policies and the promotion of green products within supply chain environments. It also provides guidance to manufacturers on how to achieve profit maximization while progressing towards carbon neutrality. [ABSTRACT FROM AUTHOR]

Though interfirm collaboration on carbon emission reduction, the cross-enterprise flow of emission reduction resources and improved efficiency in greenhouse gas reduction can be realized. Especially in the context of big data, enterprises can find suitable partners for emission reduction faster and more accurately through interfirm collaboration. However, similar to other cooperative modes, revenue allocation is the key to ensuring the stability of the collaborative emission reduction system. Based on the premise of carbon trading, this paper discusses revenue allocation among enterprises participating in the collaborative emission reduction process under complete information in a big data context. Specifically, we constructed a Shapley value analysis model of revenue allocation for interfirm collaboration on carbon emission reduction, and amended this model with investment cost and risk-bearing. Consequently, this research provides not only a theoretical basis for solving the problem of revenue distribution in the process of collaborative emission reductions among enterprises but also a theoretical guide for enterprises countermeasures following the completion of China's future carbon trading mechanism. [ABSTRACT FROM AUTHOR]

With the statement of Chinese government on energy saving in 2020 at the United Nations General Assembly, carbon neutral was widely spread as a new concept. As a big country, China has the responsibility and obligation to make its own contribution to global climate change. This paper aims to explore and find effective ways for China to achieve carbon neutrality by 2060. We identify the main factors affecting carbon emissions by STIRPAT model; combined with the scenario analysis, we divide the year 2020 to 2060 into three stages: year 2020–2030 is carbon peak stage, year 2030–2050 is rapid emission reduction stage, and year 2050–2060 is complete carbon neutralization stage. At each stage, three development models, high, medium, and low level, were established. There are a total of 27 different scenarios in three stages. A system dynamics model was established to simulate the effects of carbon emission factors and changes in carbon sinks in different scenarios. Finally, 8 paths were found which in line with Chinese current goal of achieving carbon neutrality with treating reach carbon peak in 2030 as an additional filter condition. Comparing per capita GDP levels in different scenarios, we eventually find that keeping economic development at a low level in the first stage, a high level in the second stage, and a medium level in the finally stage, the point where net carbon emissions are less than zero for the first time will appear between year 2056 and 2057. By then, the per capita GDP will reach 144,500 yuan (based on year 2000), nearly four times 2000's. In all, these findings are helpful for policymakers to implement reasonable policies to achieve carbon emission peaking and carbon neutral in China. [ABSTRACT FROM AUTHOR]