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An in-depth investigation into the effect of embedment in global value chain (GVC) on energy conservation and emissions reduction is of great significance for scientifically assessing the environmental impact of GVC participation, and promoting high-quality development in China. This paper incorporates GVC embedment, energy consumption and carbon emissions into the same analysis framework for the first time. Based on the WIOD database, this paper theoretically and empirically examines the impact and mechanism of global value chain embeddedness on carbon emission reduction from two dimensions: energy consumption intensity and energy consumption structure. The study found that GVC embedment significantly reduced the industry's carbon emission intensity; developing economies' embedment in GVC helped reduce their carbon emission intensity, while the effect was not obvious in developed economies. GVC embedment had a significant inhibitory effect on the carbon emissions in both upstream and downstream industries, but not conducive to carbon reduction of low-tech manufacturing. The mechanism test shows that the GVC embedment not only exhibits the dual effects of energy conservation and emissions reduction, but also has a significant impact on carbon emissions by reducing the energy consumption intensity and improving the energy consumption structure. [ABSTRACT FROM AUTHOR]

With China's rapid industrialization and urbanization in the process of socio-economic development, the extensive use of energy has resulted in a large amount of CO2 emissions, which puts great pressure on China's carbon emission reduction task. Through multivariate socio-economic data, this paper proposes an extraction and screening method of multivariate variables based on land-use types, and the downscaled spatial decomposition of carbon emissions at different scales was carried out by using the spatial lag model (SLM). This paper makes up for the shortcomings of previous studies, such as an insufficient modeling scale, simple modeling variables, limited spatio-temporal span of spatial decomposition, and no consideration of geographical correlation. Based on the results of the spatial decomposition of carbon emissions, this paper explores the spatial and temporal dynamics of carbon emissions at different scales. The results showed that SLM is capable of downscaling the spatialization of carbon emissions with high precision, and the continuity of the decomposition results at the provincial scale is stronger, while the differences of the decomposition results at the municipal scale are more obvious within the municipal units. In terms of the spatial and temporal dynamics of CO2 emissions, carbon emissions at both scales showed a significant positive correlation. The dominant spatial correlation types are "Low–Low" at the provincial level, and "Low–Low" and "High–High" at the municipal level. The smaller spatial scope is more helpful to show the geographic dependence and geographic differences of China's carbon emissions. The findings of this paper will help deepen the understanding of the spatial and temporal changes of carbon emissions in China. They will provide a scientific basis for the formulation of feasible carbon emission reduction policies. [ABSTRACT FROM AUTHOR]

High-energy consumption and high-emission industries contribute a lot to economic development, but their carbon emissions are also huge. In order to achieve the dual-carbon target as early as possible, it is necessary to reduce the carbon emissions of high-energy consumption and high-emission industries. This paper selected five representative factors (population, per capita gross domestic product (GDP), energy intensity, energy structure and carbon emission coefficient) and adopted the logarithmic mean divisia index (LMDI) method to decompose the driving factors of carbon emissions. Therefore, this paper uses Tapio decoupling model to analyze the decoupling relationship between the two factors with the greatest impact on carbon emissions and carbon emissions. The results show that: (i) There is a good decoupling between high-energy consumption and high-emission industries and per capita GDP, and the impact of per capita GDP on carbon emissions will gradually decrease in the future; (ii) The decoupling relationship between carbon emissions and energy intensity is poor. For some industries, the reduction of energy intensity can help reduce carbon emissions. Finally, this paper puts forward some suggestions to promote carbon emission reduction. This paper provides theoretical support for studying how to reduce carbon emissions and formulate relevant emission reduction policies in the high-energy consumption and high-emission industries. [ABSTRACT FROM AUTHOR]

Facing the double constraints of the "double carbon" target and high-quality economic development, carbon trading policy is an important tool for realizing the emission reduction commitment; based on the perspective of microenterprises, the specific mechanism and spatial effect of carbon trading policy still need to be evaluated. Taking China's carbon emissions trading pilot as a quasi-natural experiment, this paper empirically investigates the impact of carbon trading policy on the carbon emission intensity of pilot enterprises and its mechanism of action, and its impact on the carbon emission intensity of neighboring enterprises, based on the multi-temporal double-difference model, moderating effect model, and spatial Durbin model with the A-sharelisted enterprises in the period of 2009-2019 as the samples. It is found that: 1) Carbon trading policy will reduce the carbon emission intensity of enterprises to different degrees, and there are significant differences under different ownership types, degrees of marketization and the level of digitization. 2) Under the influence of environmental uncertainty, ESG disclosure will weaken the effectiveness of carbon emission reduction in the pre-pilot stage of the policy; with the gradual improvement of the carbon trading policy and ESG disclosure mechanism, ESG ratings will positively regulate the inhibitory effect of the carbon trading policy on the carbon emission intensity of enterprises through multiple paths. 3) Carbon trading policy effectively reduces multiple negative spillovers through the demonstration effect and competition effect of neighboring enterprises, driving the carbon emission reduction behavior of non-pilot enterprise. The research in this paper enriches the research paradigm of carbon emission intensity influencing factors, provides reference suggestions for the government to improve its policies, and better contributes to the realization of the "dual-carbon" vision in China as soon as possible. [ABSTRACT FROM AUTHOR]

The power sector is one of the major CO2-emitting industries in China. It is also the first key emissions control industry included in China's national carbon trading market established in 2021. Therefore, based on the data of 30 provinces and cities in China from 2015 to 2022, this study analyzes the impact of the national carbon market policy on the carbon emissions of the power industry based on the generalized Difference-in-Difference (DID) model. Based on the method of text analysis, this paper constructs the carbon market policy intensity index of each region and incorporates it into the DID model. Empirical analysis finds that the national carbon market policy can significantly inhibit the carbon emissions of the power industry. However, the heterogeneity analysis of 30 provinces and cities shows that the national carbon market policy has a significant impact on the regions that already have a carbon pilot, but not on the non-pilot regions. Therefore, this paper demonstrates the effectiveness of the national carbon market policy in the power industry emissions control, and also exposes the heterogeneity between regions, providing an important empirical basis for the inclusion of other energy-intensive industries. [ABSTRACT FROM AUTHOR]

Food consumption has resulted in great carbon emissions in recent years. China has been facing the new mitigation challenge of carbon emissions with its emerging middle-income groups, especially in urban areas. This paper analyzes and predicts carbon emissions from food consumption (CEFC) of middle-income groups in the Yangtze River Economic Belt (YREB), which has a higher emerging middle-income group and the highest economic corridor in China. Few studies address CEFC analysis from middle-income groups perspective; thus, this paper calculates urban–rural CEFC of middle-income groups spanning 2010–2018 and predicts them in 2025, 2030 and 2035 using the extended IPAT model. Results are as follows: (1) YREB's urban–rural CEFC of middle-income groups show an upward trend and present a spatial pattern of "low–high–low–high" from the western region to the eastern region. Urban CEFC of middle-income groups are significantly higher than that of rural areas; (2) rural CEFC of middle-income groups in the YREB will first increase in 2025 and then decrease in 2030 and 2035. The growing trend of urban CEFC of middle-income groups will show a significant downward from 2025 to 2035. The growing proportion of urban CEFC of middle-income groups will exhibit an objective growth in 2035. Understanding the changing trend of CEFC of middle-income groups provides governments with differentiated and forward-looking suggestions toward coordinating middle-income groups' expansion and carbon emissions reduction. [ABSTRACT FROM AUTHOR]

The accountability audit of natural resources (AANR) is a major institutional arrangement for advancing the construction of an ecological civilization in China. Based on the panel data of 271 cities in China from 2005 to 2017, this paper investigates the relationship between the AANR and carbon dioxide (CO2) emissions using a multi-period difference-in-differences (DID) model. The results show that AANR significantly increases the CO2 emission reduction rate by 0.009 units at the 5% significance level. The results still hold after a series of robustness tests. Given all else being equal, this significant effect is 0.001. Further analyses show that AANR improves pilot cities' CO2 emission reduction rates mainly by enhancing their green innovation capability. The mediating effect of cities' green technology innovation capability accounts for 96.00%, while the AANR's direct effect only accounts for 4.00%. The AANR has significantly positive effects of 0.017% and 0.029% for western cities and cities with high fiscal pressure at the 5% and 1% significance levels, respectively. Therefore, strengthening AANR implementation by enhancing the mediating efficiency of cities' green technology innovations and implementing dynamically differentiated AANR policies in Chinese meso-cities will contribute to the achievement of China's carbon peaking and carbon neutrality targets. [ABSTRACT FROM AUTHOR]

Integrated energy system is crucial in realizing China's "dual carbon" targets. Considering the carbon capture based electricity to gas and the interaction of multiple markets, this paper proposes a low-carbon operation optimization method of integrated energy system. In terms of market policy, a coupling trading mechanism for carbon trade and green certificates is established. This approach is intended to delve into the profound significance of utilizing green certificates in carbon emission reduction. In terms of equipment models, the coupling model of carbon capture equipment with coal-fired cogeneration unit, as well as power-to-gas equipment with renewable energy, is constructed. In addition, this equipment model is introduced into the operation optimization scheduling of the comprehensive energy systems. A low-carbon economic operational strategy is further proposed to minimize the daily operational costs, by which the integrated energy system is eco-nomically, environmental protection optimized. To verify the effectiveness and feasibility of the proposed model, this paper sets up several comparison scenarios and conducts the simulations using GUROBI solver. The results show that the proposed strategy can effectively improve the uptake rate of renewable energy, reduce the carbon emission, improve the operation economy, and realize the complementary incentive effect between markets. [ABSTRACT FROM AUTHOR]

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To promote sustainable economic development in the Belt and Road region of China, reducing carbon emissions is essential. The construction industry is a major contributor to carbon emissions in China. Therefore, studying the dynamic evolution of carbon emissions from the construction industry in this region and its driving factors is of great significance for effectively controlling emissions and achieving China’s carbon peak and carbon neutrality targets. This paper first employs the Slope model, Moran’s I index, and standard deviation ellipse to reveal the spatial-temporal characteristics of carbon emissions from the construction industry, and then applies the geographical detector model to identify the main driving factors of carbon emissions. The results indicate that: (1) From 2006 to 2021, the total carbon emissions showed a fluctuating growth trend, and there were significant differences in emissions among different regions. (2) Carbon emissions in most provinces exhibited a moderate growth trend, and there was significant spatial correlation and aggregation of inter-provincial emissions. Regional carbon emissions from 2006 to 2021 showed a spatial distribution pattern from northeast to southwest, with a weakening trend, and the center of gravity mainly distributed in the east of the region. (3) Labor input, urbanization rate, total output value of the construction industry, degree of opening up, and energy intensity are the main factors influencing the spatial heterogeneity of carbon emissions from the construction industry, and the majority of the interaction types between factors were bivariate enhancement. This study aims to provide theoretical support for policymakers to formulate appropriate policies for building energy conservation and emission reduction. [ABSTRACT FROM AUTHOR]

With the challenge posed by global warming, accurately estimating and managing carbon emissions becomes a key step for businesses, especially power generation companies, to reduce their environmental impact. Optuna–LightGBM–XGBoost, a novel power and carbon emission relationship model that aims to improve the efficiency of carbon emission monitoring and estimation for power generation companies, is proposed in this paper. Deeply exploring the intrinsic link between power production data and carbon emissions, this model paves a new path for "measuring carbon through electricity", in contrast to the emission factor method commonly used in China. Unit data from power generation companies are processed into structured tabular data, and a parallel processing framework is constructed with LightGBM and XGBoost, and optimized with the Optuna algorithm. The multilayer perceptron (MLP) is used to fuse features to enhance prediction accuracy by capturing characters that the individual models cannot detect. Simulation results show that Optuna–LightGBM–XGBoost can achieve better performance compared to existing methods. The mean absolute error (MAE), mean squared error (MSE), mean absolute percentage error (MAPE), and coefficient of determination (R2) of the model are 0.652, 0.939, 0.136, and 0.994, respectively. This not only helps governments and enterprises to develop more scientific and reasonable emission reduction strategies and policies, but also lays a solid foundation for achieving global carbon neutrality goals. [ABSTRACT FROM AUTHOR]

This paper proposes a temperature-adaptive radiative cooling (TARC) coating with simple preparation, cost effectiveness, and large-scale application based on a thermochromic powder. To determine the energy efficiency of the proposed TARC coating, the heat transfer on the surface of the TARC coating was analyzed. Then, a typical two-story residential building with a roof area of 258.43 m2 was modeled using EnergyPlus. Finally, the energy-saving potential and carbon emission reduction resulting from the application of the proposed TARC roof in buildings under different climates in China were discussed. The results showed that the average solar reflectivity under visible light wavelengths (0.38–0.78 μm) decreases from 0.71 to 0.37 when the TARC coating changes from cooling mode to heating mode. Furthermore, energy consumption can be reduced by approximately 17.8–43.0 MJ/m2 and 2.0–32.6 MJ/m2 for buildings with TARC roofs compared to those with asphalt shingle roofs and passive daytime radiative cooling (PDRC) roofs, respectively. This also leads to reductions in carbon emissions of 9.4–38.0 kgCO2/m2 and 1.0–28.9 kgCO2/m2 for the buildings located in the selected cities. To enhance building energy efficiency, TARC roofs and PDRC roofs are more suitable for use on buildings located in zones with high heating demands and high cooling demands, respectively. [ABSTRACT FROM AUTHOR]

Recycling carbon tax revenue is a significant part of the design of a nation's carbon tax system. The impact of different recycling principles on the socio-economy and carbon emission reduction varies greatly. Under the background of China's goal of reaching peak carbon emissions, this paper designed three carbon tax recycling principles based on the goal of Nationally Determined Contributions (NDCs), including recycling principles based on output ratio, export ratio, and carbon intensity. A recursively dynamic CGE model was developed in this study to evaluate the economic effects of these three carbon tax recycling principles based on tax neutrality under China's goal of reaching peak carbon emissions. Carbon tax recycling measures could mitigate the economic losses caused by carbon tax, and the results could be greatly affected according to different recycling principles. The results showed that: 1 The recycling principle based on output ratio could reduce economic losses and improve households' social welfare. 2 China's carbon intensity in 2030 could be reduced by more than 65% compared with that in 2005, and the proportion of non-fossil energy in primary energy consumption could reach 25% using the recycling principle based on carbon intensity, but the economic loss mitigation effect of the recycling measures based on this principle was small. 3 Adopting the recycling principle based on export ratio would narrow the competitive gap between China and foreign countries, and the exports of high-carbon-intensity goods would not increase under this principle. 4 According to principles based on output ratio and export ratio, the NDC goal of non-fossil energy accounting for about 25% of primary energy consumption by 2030 could not be achieved, and only the NDC goal of reducing carbon emissions per unit of GDP by more than 65% compared with that of 2005 could be achieved. In brief, as an essential policy tool to achieve China's goal of reaching peak carbon emissions, the carbon tax should be implemented as soon as possible. At the same time, according to China's national conditions, a targeted choice of carbon tax recycling principle is needed. The role of the carbon tax in the process of achieving the goal of Nationally Determined Contributions should be fully utilized. [ABSTRACT FROM AUTHOR]

China is actively heeding the call and striving for a low-carbon and environmentally friendly development route as part of the general trend toward a global low-carbon economy. The rapid economic development of our nation has brought to light the issue of carbon emissions resulting from the consumption habits of residents. This paper delves into the topic by conducting a thorough analysis of the carbon emission of residents' consumption using the input-output method. Based on the survey findings, the disparity in carbon emission between urban and rural communities in Shandong Province is evident not only in terms of total emissions but also in different categories and regions. Urban residents generate a total carbon emission of approximately 70.2921 million tons, which is three times higher than that of rural residents at 23.7846 million tons. The carbon emission of both urban and rural residents is primarily attributed to their embodied carbon emission. In examining the composition of the implied carbon emission of residents' consumption in Shandong Province, urban residents' carbon emission is concentrated in three areas, namely, food, culture, education, entertainment, transportation, and communication, accounting for 21.45%, 20.88%, and 15.10%, respectively. Conversely, rural residents' carbon emission is concentrated in four areas, including clothing, food, culture, education, entertainment, transportation, and communication, accounting for 29.01%, 17.45%, 15.43%, and 13.36%, respectively. Finally, according to the characteristics of the consumption carbon emission of urban and rural residents in Shandong Province, we give corresponding emission reduction strategies. [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]

This paper analyzes the spatial and temporal distribution characteristics of carbon emissions in China's construction industry, and studies the key influencing factors of carbon emission intensity in China's construction industry at the spatial level through spatial spillover effects, so as to reveal the inter-regional influence mechanism. The results show that：the total carbon emissions of China's construction industry are generally on the rise, the carbon emission intensity is generally declining first and then stable, and the carbon emission intensity has intra-regional convergence and inter-regional heterogeneity；the proportion of housing construction industry, the scale of construction industry, regional economic level, environmental regulation, and nationalization rate of construction enterprises have a significant inhibitory effect on the carbon emission intensity, while the technological progress, the regional economic level and environmental regulation have a significant negative spatial spillover effect on the carbon emission intensity. Accordingly, relevant measures to promote the effective emission reduction of the construction industry are proposed. [ABSTRACT FROM AUTHOR]

The steel industry is a major source of CO2 emissions, and thus, the mitigation of carbon emissions is the most pressing challenge in this sector. In this paper, international environmental governance in the steel industry is reviewed, and the current state of development of low‐carbon technologies is discussed. Additionally, low‐carbon pathways for the steel industry at the current time are proposed, emphasizing prevention and treatment strategies. Furthermore, the prospects of low‐carbon technologies are explored from the perspective of transitioning the energy structure to a "carbon–electricity–hydrogen" relationship. Overall, steel enterprises should adopt hydrogen‐rich metallurgical technologies that are compatible with current needs and process flows in the short term, based on the carbon substitution with hydrogen (prevention) and the CCU (CO2 capture and utilization) concepts (treatment). Additionally, the capture and utilization of CO2 for steelmaking, which can assist in achieving short‐term emission reduction targets but is not a long‐term solution, is discussed. In conclusion, in the long term, the carbon metallurgical process should be gradually supplanted by a hydrogen–electric synergistic approach, thus transforming the energy structure of existing steelmaking processes and attaining near‐zero carbon emission steelmaking technology. [ABSTRACT FROM AUTHOR]

With the rise of China’s economy and the expansion of China’s foreign trade scale, the carbon emissions generated by China’s trade are attracting extensive attention from political and academic circles. In the context of global ‘decarbonization’, this paper focuses on the new trade model of digital trade and uses China's provincial panel data from 2013 to 2021 to deeply explore the effect of digital trade development on carbon emissions and its transmission mechanism. We find that digital trade development can reduce regional carbon emissions through structural and technological effects; specifically, industrial structure upgrading, consumption upgrading, and green technology innovation play a crucial intermediary role in this process. Subsequent investigation reveals a nonlinear, diminishing trend in the marginal impact of digital trade on emission reduction. Furthermore, once digital trade surpasses the threshold of environmental regulation its marginal effect on emission reduction becomes more pronounced. Additionally, employing a spatial econometric model has revealed that the advancement of digital trade can also contribute to reducing carbon emissions in neighboring regions. Heterogeneity analysis results demonstrate that the eastern region exhibits the most significant emission reduction effect in relation to digital trade, followed by the western and central regions. [ABSTRACT FROM AUTHOR]

The Belt and Road Initiative proposed by China has significantly increased trade in countries along the Belt and Road (B&R). Since most of these countries are developing and emerging economies, the pressure to reduce carbon emissions poses a leading challenge for them. Carbon productivity has become a key indicator for assessing the degree of low-carbon development, as it can link economic development with CO2 emission reduction. However, few studies have investigated how international trade affects carbon productivity. Based on panel data from 43 countries along the B&R during 2001–2019, this paper uses a system GMM model to explore the impact of international trade on carbon productivity. Then, we divide the 43 countries in the sample into two groups according to their income levels to compare the different effects of international trade on carbon productivity. The results show that, first, the carbon productivity of the examined B&R countries has an overall increasing trend, and there is a significant heterogeneity of carbon productivity among countries with different income levels. Second, the effects of international trade, export, and import on carbon productivity are all significantly positive, and export's effect is higher than import. In the high-income group, carbon productivity is more likely to be improved by trade than in the middle (low)-income group. Third, economic development level, urbanization, and energy productivity are positively associated with carbon productivity, while CO2 per capita and government size inhibit carbon productivity improvement. Insight into the impact of international trade on carbon productivity provides theoretical support for B&R countries to better leverage foreign trade activities to achieve a green economy. [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]

Carbon peaking and carbon neutrality will be important policies to constrain China's economic and social development in the future. Based on the theory of computable general equilibrium, CGE model of carbon emission was constructed in this paper to simulate the influence of different scenarios of carbon emission reduction on economic and social development. The major contribution is to subdivide the energy sector according to primary energy and secondary energy, and construct the macro SAM table and micro SAM table of 21 energy sectors in 2017 to quantitatively simulate the impact of carbon emission reduction policies on China's economy and society, and put forward some policy suggestions based on this. [ABSTRACT FROM AUTHOR]

Industrial land is currently the main carrier and important source of global carbon emissions, and as the world's largest developing country, China's large-scale and diversified industrial land supply has made it the world's largest carbon emitter. Therefore, researching the impact of different supply methods of industrial land on carbon emissions and its impact paths in China can help provide a reference for other countries to reduce carbon emissions from the perspective of urban industrial land management, which is of great significance for effectively promoting global carbon reduction. Based on this, this paper analyses the impact of different supply methods of industrial land on carbon emissions and its urban heterogeneity using the SYS-GMM and chain-mediated effects models for 285 cities in China from 2008 to 2020. The study found that, in general, the impact of different industrial land transfer modes on carbon emission has hysteresis and persistence. Agreement and listing transfer with government intervention can significantly exacerbate carbon emissions, while more market-based bidding and auction transfer can dampen carbon emissions. In terms of intermediary effects, the transfer of industrial land by agreement and listing will inhibit the rationalization and advancement of industrial structure, thus aggravating carbon emissions. The transfer of industrial land by bidding and auction will create barriers to entry and a crowding-out effect, promote the rationalization of industrial structure and the transformation and upgrading of industrial structure and moderate carbon emissions. In terms of city heterogeneity, there is urban heterogeneity in the impact of industrial land transfer on carbon emissions in cities with different economic types. Bidding and auction transfer for industrial land in both economically developed and less developed cities can promote carbon pollution. While the more developed urban economy makes the intermediary effect of industrial structure not significant. In the future, it is necessary to strictly control the scale of industrial land supply; the whole process supervision mechanism of industrial land allocation and differentiated industrial land supply strategies will provide useful experience for many developing countries in allocating industrial land to mitigate carbon emissions, generating effective contributions to global carbon emission reduction. [ABSTRACT FROM AUTHOR]

Digital transformation and green innovation are powerful initiatives to achieve carbon peaking, carbon neutrality targets and high-quality economic development. Using a sample of high energy-consuming listed enterprises from 2012 to 2021, a double fixed-effect model is constructed to verify the effect of green innovation on the carbon emission reduction performance of high energy-consuming enterprises, and digital transformation is used as a moderating variable to analyze the inner mechanism of green innovation affecting the carbon emission reduction performance of high energy-consuming enterprises under the effect of digital transformation. The empirical results show that green innovation can significantly improve the carbon emission reduction performance of energy-consuming enterprises, while digital transformation positively moderates the effect of green innovation on the carbon emission reduction performance of energy-consuming enterprises. When considering the industry heterogeneity, the moderation effect of digital transformation is significant in the chemical raw materials and chemical products manufacturing industry and the electricity and heat production and supply industry, but the petroleum processing and coking and nuclear fuel processing industry, the non-metallic mineral products industry, the ferrous metal smelting and rolling processing industry and the non-ferrous metal smelting and rolling processing industry are not yet significantly affected by green innovation and digital transformation. The findings of the study provide empirical evidence to promote the improvement of carbon emission reduction performance of energy-intensive enterprises in China and to achieve the "double carbon" target. [ABSTRACT FROM AUTHOR]

An accurate evaluation of carbon emission efficiency (CEE) at the city level can provide guidelines for understanding low carbon performance, which is crucial to achieving dual carbon targets. Existing CEE studies focused on national, industrial, and provincial scales while neglecting the city level and failing to consider competing relationships among decision-making units in their measurement models. To fill these gaps, this paper introduces the data envelopment analysis game cross-efficiency model (DEA-GCE) to measure urban CEE performance and compares it with the traditional Super-SBM model using the data from 283 Chinese cities between 2006 and 2019. The results show that (1) the DEA-GCE method provided more intensive and stable results. (2) Overall CEE of Chinese cities declined slightly amidst fluctuations during this period. (3) CEE in cities exhibits spatial clustering characteristics. CEE performance in Northeast China has improved, while CEE in Northwest China continues to lag behind. This study introduced an innovative method for calculating urban CEE and conducted an empirical study of 283 Chinese cities, which has implications for formulation of emission reduction policies. [ABSTRACT FROM AUTHOR]

Considering the opening of high-speed railway (HSR) as a quasi-natural experiment, this paper explores the emission reduction effect of HSR opening and its mechanisms and heterogeneity characteristics based on the panel data of 272 cities in China from 2006 to 2019 by staggered DID model and the mediating effect model. It is found that (1) the opening of HSR significantly reduces the carbon emission level of cities, and the conclusion still holds after controlling the endogeneity issue and a series of robustness tests; (2) Bancon decomposition and negative weight diagnostics both show that the estimated average treatment effect bias is small and the robust estimators are more robust; (3) by reducing production costs and promoting inter-regional industrial division of labor, the opening of HSR promotes intra-industrial structural transformation and inter-industrial structural transformation, respectively, thus reducing urban carbon emissions. At the same time, HSR achieves urban carbon emission reduction by promoting free movement of population and human capital agglomeration; and (4) further study finds that there is regional heterogeneity in the emission reduction effect of HSR opening, and the carbon reduction effect is mainly reflected in large and medium-sized cities, near provincial capitals, non-resource-based cities, and cities with rich educational resources, which indicates that the location of future HSR should be combined with the city's own characteristics and be tailored to the city. [ABSTRACT FROM AUTHOR]

Environmental information disclosure (EID) is an important measure to promote multiple subjects' collaborative management of pollution emissions. In this paper, we first measure the carbon dioxide (CO2) emissions of 282 cities in China from 2006 to 2020, and clarify the theoretical mechanisms and transmission channels of EID affecting CO2. Subsequently, the Time-varying difference-in-differences (DID) and the mediation effect model are used to assess the impact of EID on CO2 and its transmission mechanism, respectively. The study shows that although EID is a voluntary environmental regulation, the policy significantly reduces CO2, and this reduction effect has regional and low-carbon policy intensity heterogeneity. The study also shows that green technology innovation and energy intensity mediate the carbon reduction effect of EID. This study has important reference significance for reducing greenhouse gas emissions and improving the quality of economic development. [ABSTRACT FROM AUTHOR]

Fujian Province, China was chosen as the study area for estimating the marginal agricultural abatement costs within the province based on data for 2010-2020. The study employed these estimations as a pivotal factor affecting the efficiency of carbon emissions reduction, constructed an index model to gauge the potential of agricultural carbon emissions reduction, and delved into the urban agricultural carbon emissions reduction potential from the perspectives of economic development rights (equity) and carbon emissions reduction difficulty (efficiency). Our findings indicated a marked regional disparity in the marginal abatement costs of agriculture across Fujian Province, with the highest recorded at EUR 1.3771 × 108 per 104 tonnes and the lowest at EUR 0.6526 × 108 per 104 tonnes, albeit demonstrating general upward inter-annual trends. Furthermore, the assessment of agricultural carbon emissions reduction potential, grounded in the principles of equity and efficiency, revealed four distinct developmental tiers. Resource allocation pathways for carbon emissions reduction were subsequently delineated, informed by the stratification of high- and low-carbon emissions reduction potential indices alongside typological characteristics. The outcomes of this study offer strategic guidance to the government of Fujian Province in crafting suitable carbon emissions reduction strategies and in devising targeted action plans aimed at achieving the twin goals of 'carbon peaking' and 'carbon neutrality'. [ABSTRACT FROM AUTHOR]

The formulation of long-term step-by-step emission reduction plan is an important step for effective scientific emission reduction. This paper takes Shanghai as the research object, constructs PSO-LSTM model on the basis of STIRPAT model, and further constructs three dynamic policy scenarios combined with China's actual situation and makes short-, medium-, and long-term multivariate predictions for them. The study finds that only the improvement of energy consumption structure has a promotion effect on carbon emission reduction, and urbanization, industrial structure, technology level, population, and economic level all have an increasing effect, and secondly, the carbon emission reduction path of Shanghai basically achieves the core objective of steady decrease under the three scenarios. Secondly, under the three scenarios, Shanghai's carbon emission reduction path basically achieves the core objective of steady decline, but the decline in the GU scenario is more significant. It is recommended that Shanghai further adjusts its industrial structure, optimizes its energy consumption structure, promotes technological innovation and progress, and promotes the development of the circular economy model. [ABSTRACT FROM AUTHOR]

China faces the dual pressure of haze pollution control and carbon emission reduction. The goals of national key ecological functional areas (NKEFAs) are to improve ecological quality and enhance ecological supply. In this paper, a time-varying difference-in-differences model is used to assess the impact of NKEFAs on PM2.5 and CO2 by the panel data of prefecture-level cities of China and then investigate the synergistic reduction effect. This quasi-natural experiment reveals that NKEFAs can effectively reduce both PM2.5 and CO2 and then achieve the synergistic emission reduction effect. Land use pattern optimization and productivity enhancement are identified as key drivers for promoting this synergistic effect. This effect is observed in NKEFAs of water conservation and soil conservation types, as well as in the northern region, middle and lower reaches of the Yangtze River, and southeast coastal areas of the southern region. This study provides valuable theoretical references and empirical insights for realizing a synergistic status of environmental improvement and low-carbon transformation. [ABSTRACT FROM AUTHOR]

The carbon mitigation response encompasses a variety of strategies aimed at mitigating greenhouse gas emissions resulting from human activities. These measures are crafted to address the challenges posed by climate change and facilitate the transition of businesses towards a low-carbon paradigm. Leveraging the analytical outcomes of the extended STIRPAT model and the PSO-BP prediction model, this paper suggests countermeasures for reducing carbon emissions in China's metal smelting industry. The overarching objective is to contribute to China's attainment of the "dual carbon objectives." The study identifies key factors influencing carbon emissions in the metal smelting industry, ranked in descending order of sensitivity: population, coal consumption, urbanization rate, total metal production, carbon intensity, proportion of secondary industry, and GDP per capita. Results from three established scenarios—namely, low carbon, standard, and high carbon—indicate a consistent decline in carbon emissions from China's metal smelting industry over the next 15 years. This research not only enhances the findings of existing studies on carbon emissions in the metal smelting sector but also introduces an innovative approach to carbon emission reduction within China's metal smelting industry. [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]

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

In the context of global low-carbon emission reduction, how to achieve green and high-quality development has become a major issue for the Communist Party of China (CPC) and the Chinese government recently. Based on the data of China's listed companies from 2013 to 2020, this paper uses Python to implement text analysis of annual reports, and explores the relationship between political acuity and carbon-efficiency synergies (CES) from the perspective of enterprise initiative. We found that (1) political acuity positively affects carbon-efficiency synergies. (2) Increased political acuity can reduce carbon emissions, but the effect on economic efficiency is not obvious. That is, low carbon takes the lead in raising the level of carbon-efficiency synergies. (3) Environmental regulations can positively regulate the relationship between political acuity and carbon-efficiency synergies. (4) Political acuity in southern China, carbon neutral and non-state-owned enterprises (NSOEs) will have a more pronounced effect on carbon-efficiency synergies. From the perspective of the root causes of political linkages, we find the synergies between formal and informal institutions, and the key factors for policy implementation. This paper is helpful for enterprises to improve the synergies of emission reduction and efficiency promotion, and has practical implications for the government to promote green and high-quality development. • Assess the value of the low-carbon economy from its political roots. • We build a carbon-efficiency synergy evaluation system. • Political acuity and formal institutions are synergistic. • The influence of political acuity on CES can be replicated. • This paper expands the technical approach to low-carbon research. [ABSTRACT FROM AUTHOR]

"Carbon peaking and carbon neutralization" is an important measure to promote China's ecological and environmental protection and high-quality economic development, and the innovation and application of green technology are critical factors in achieving the "double carbon" goal. Based on the number of citations of green patents of listed enterprises in 30 provinces in China from 2011 to 2020, this paper uses GGDP to replace traditional GDP and calculate carbon emission intensity. Based on the relevant panel data at the provincial level, this paper constructs a spatial Durbin model to analyze the impact mechanism of whether the promotion and application of green technologies promote regional carbon emission reduction. The specific research results are as follows: (1) Through regression of the core explanatory variables with a one-stage lag, it is verified that the promotion and application of green technology has a significant positive promoting effect on regional carbon emission reduction, and there are significant spatial spillover effects and "learning by doing" effects. (2) In the part of heterogeneity test, the impact of green technology promotion and application on carbon emission reduction presents apparent regional heterogeneity and factor endowment heterogeneity. (3) The mediating effect test verifies the mediating effect of energy structure and industrial structure on the influence of green technology promotion and application on regional carbon emission reduction. (4) In the part moderating effect test, it is verified that marketization level and new infrastructure construction have a positive moderating effect in their influencing process, financial development, and government support will weaken the influence of green technology promotion and application on carbon emission reduction effect, and human capital level has a nonlinear regulating effect. The research conclusions of this paper provide necessary enlightenment for the coordination and unification of China's economic transition to innovation-driven and green and low-carbon development. • The impact of GTPA on reduction in China was analyzed from a macro perspective. • The GS and FDL plays a negative moderating role in the influence process. • The HCL plays a nonlinear moderating role in the influence process. • The GTPA can significantly reduce regional CEI except in Western China. • Regions with high EDL and high GTI have better carbon reduction effects of GTPA. [ABSTRACT FROM AUTHOR]

High carbon emissions and population aging are two obstacles to China's development as an emerging economy. It is urgent to scientifically examine the impacts of population aging on carbon emissions to discover new pathways for urban carbon emission reduction. However, existing studies face challenges in terms of focusing on and methodology for accurately capturing the role of industrial production and energy consumption in the environmental effects of population aging. This paper constructs a chain mediation analytical framework and systematically examines the intrinsic linkages between population aging and carbon emissions in Chinese cities from 2000 to 2020 using a two-way fixed effects model. This paper has three main findings. (1) The positive correlation between urban population aging and carbon emissions development is generally low, with coupling coordination degree values of 0.4233, 0.4458, 0.4220, 0.4715, and 0.4665 for each yearly cross-section. (2) For every 1% increase in the population aging rate, carbon emissions decrease by 0.3478% on average. The carbon reduction effect of population aging is significantly greater in low-emissions cities and high-income cities than in other cities. (3) The industrial upgrading (IU) path, energy conservation (EC) path and chain mediation (CM) path account for 72.43%, 7.23% and 20.34%, respectively, of the indirect effects. If the causal link between IU and EC is not considered, the EC effect will be overestimated by 281.16%. The results of the study suggest that properly coping with population aging and reducing carbon emissions are not completely opposed to each other, a conclusion that passes both endogeneity exclusion and robustness check. This paper advocates replacing the one-size-fits-all approach in carbon emissions management and investing more in policy preferences to support carbon emission reduction in both high-emissions and low-income cities. [Display omitted] •The synergistic trends of carbon emissions and population aging are not apparent. •Population aging significantly reduces carbon emissions at the city scale. •Linkage effect of industrial upgrading and energy conservation on carbon emission reduction. •Energy conservation effect of population aging amplified by industrial upgrading. [ABSTRACT FROM AUTHOR]

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

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

Can the information technology revolution lead to carbon emission reduction for firms? This study extends the limited evidence in the literature and investigate the role and mechanism of digital inclusive finance on enterprises' carbon emissions using panel data of 247 prefectural-level cities and 6019 industrial enterprises in China. Our findings indicate that digital inclusive finance can promote enterprise carbon emission reduction, and this effect remains significant after the instrumental variable estimation test. The effect has regional heterogeneity and the development of digital inclusive finance in the area east of Hu Huanyong line has a significant impact on reducing enterprise carbon emission. The role of digital inclusive finance is heterogeneous in enterprise ownership, with a remarkable effect in non-state-owned enterprises. Sub-dimension analysis indicates that the breadth of coverage, depth of use, and degree of digitalization of digital inclusive finance have differential effects on reducing enterprise carbon emissions. The stepwise regression method shows that the impact of digital inclusive finance on enterprise carbon emissions can be passed through effect of technological progress, environmental protection investment and financing constrain. This study has significant reference value for evaluating the impact of financial inclusion and policy implications in formulating differentiated strategies for achieving carbon emission reduction efficiency in enterprises. [ABSTRACT FROM AUTHOR]

Carbon emission reduction (CER) in the construction industry can aid in achieving the international community's carbon neutrality target. However, the low motivation of construction enterprises to reduce carbon emissions and the unsatisfactory effect of CER are still unresolved issues. This study aims to address these issues by constructing a building supply chain (BSC) consisting of a developer and a contractor using government subsidies and cost-sharing contracts. The optimal government subsidy and feedback equilibrium strategies of the BSC are examined using a combination of differential game theory and numerical simulations. The findings demonstrate that (1) cost-sharing contracts may enhance developer and contractor profits and building CER, goodwill, and demand without relying on government subsidies; (2) when subsidized by the government, each equilibrium strategy meets or exceeds the performance of the centralized model, with the cost-sharing contract having a negligible effect on the enhancement of each equilibrium strategy; and (3) both the game structure and the positioning of construction enterprises in the BSC are connected to the number of government subsidies. The city of Shenzhen, one of China's first low-carbon pilot cities, provides a realistic environment for the simulation analysis, with the Block K residential building in Nanshan District serving as a case study. Furthermore, this work contributes to the body of knowledge by proposing a novel CER model for the BSC using differential game theory. The research provides new insights into the role of government subsidies in shaping profit distribution, game structure, and enterprise positioning. Findings demonstrate the value of cost-sharing contracts in improving CER, goodwill, demand, and profits when implemented collaboratively. This advances the theoretical understanding of incentives and strategies for promoting CER in construction. This research highlights the importance of collaborative efforts between the government and the building supply chain (BSC) to promote sustainable construction and carbon emission reduction (CER). The study found that government subsidies can be an effective tool to encourage developers and contractors to adopt CER practices. However, relying solely on subsidies is insufficient—collaboration through mechanisms such as cost-sharing contracts can further enhance sustainability outcomes when enterprises work together. To facilitate low-carbon construction, the government could provide subsidies for developers' promotional and marketing activities as well as funding for contractors' research and development of sustainable materials and technologies. Financial incentives such as tax breaks and preferential lending for potential homebuyers can also accelerate consumer demand. Ultimately, creating a supportive environment where enterprises proactively pursue CER creates a win–win situation where the BSC becomes more sustainable while firms improve their branding and profitability. The insights from this research highlight the need for a multipronged approach. Governments play a key role through policy and financial support. Realizing the full potential of sustainable construction also requires active participation from developers, contractors, and consumers. By outlining optimal strategies and incentives, this study provides valuable guidance to construction industry stakeholders seeking to implement CER collaboratively. [ABSTRACT FROM AUTHOR]

Investigating the impact of carbon emissions trading policy and elucidating the underlying mechanisms are crucial for enhancing policy effectiveness and refining related systems. This study examines the impact of carbon emissions trading policy by constructing a difference-in-difference model utilizing unbalanced panel data from China's provinces spanning the period from 2005 to 2019. Additionally, a mediating effect model is employed to delve into the underlying mechanisms. The key findings are as follows: Firstly, the implementation of carbon emissions trading policy has a notable inhibitory impact on carbon emissions. Secondly, both the upgrading of industrial structure and the reduction of energy intensity play mediating roles in carbon emissions reduction. However, the development of clean energy industries does not exhibit a significant mediating effect. In conclusion, this study offers policy recommendations aimed at facilitating carbon reduction. These include enhancing the market-based trading mechanism for carbon emissions, optimizing and upgrading industrial structures, fostering innovation in green and low-carbon technologies, and promoting the development and utilization of clean energy. [ABSTRACT FROM AUTHOR]

In the context of the continued advancement of the green economy transition, the proactive pursuit of carbon emissions reduction and the early attainment of carbon neutrality goals have emerged as essential components in promoting high-quality economic development. Not only does it contribute to the creation of a community of human destiny, but it is also vital to the realization of sustainable development for human civilization. A dynamic evolutionary game model, which encompasses the interactions among government, enterprises, and the public, was constructed to examine the inherent impact mechanisms of the behavior of three players on the development of a green economy under the context of energy saving and emission reduction subsidies. The results showed that the incentive and punishment mechanisms served as effective tools for harmonizing the interests of system members. Within the mechanisms, the public demonstrated a higher sensitivity to rewards, while enterprises exhibited greater responsiveness to fines. Consequently, the government could influence the behavior of enterprises by incentivizing the public to serve as a third-party inquiry and oversight body. Simultaneously, the government could encourage enterprises to expedite green technology innovation by employing a combination of incentive and punishment mechanisms. [ABSTRACT FROM AUTHOR]

Efficient carbon emission reduction technologies in buildings are necessary for achieving the "Dual carbon" goal in China. In this study, a comprehensive evaluation model is proposed to assess the effect of carbon emission reduction based on the analytic hierarchy process–entropy weight–coefficient of variation model which takes newly built residential buildings in Zhuzhou City as the research object. The results show that the preferred materials for the roof and exterior walls of the building's envelope structure were flame-retardant extruded polystyrene boards, and porous shale bricks were preferred as the main materials for the exterior walls. In addition, the rooftop solar photovoltaic system and energy-saving air conditioning technology were suitable in terms of being renewable and were better utilized. In the end, carbon emissions were significantly reduced when using the building decarbonization technologies. This study provides a new reference for choosing materials and technologies for the design of residential buildings in Hunan Province and even other regions with hot summers and cold winters. [ABSTRACT FROM AUTHOR]

In the pursuit of carbon neutrality, state-owned forests are prime candidates for carbon offset projects due to their unique tenure and management characteristics. Employing methodologies endorsed by the International Panel on Climate Change and logistic growth curves, this study assesses the carbon stocks and sequestration potential of established state-owned plantation forests across 31 Chinese provinces from 2023 to 2060, encompassing seven forestry industry groups. This study projects that by 2060, these forests will amass a carbon stock of 558.25 MtC, with the highest stock in Northeast China (122.09 MtC) and the lowest in Northwest China (32.27 MtC), notably showing the highest growth rate at 91.15%. Over the forecast period, they are expected to accumulate a carbon sink of 637.07 MtCO2e, translating to an average annual carbon sink of 17.22 MtCO2e and an average annual carbon sink per unit of 1.41 tons of CO2 per hectare per year. Additionally, state-owned forests have the potential to offset approximately 0.15%–0.17% of annual carbon emissions, aligning with international climate goals. However, it is essential to note that the conversion of these carbon sinks into tradable carbon credits is subject to specific methodology requirements. Therefore, the future development of carbon offset projects in China's state-owned forests should consider the advancement of carbon market mechanisms, including the Chinese Certified Emission Reduction and the introduction of a carbon inclusion mechanism and natural forest methodology, to fully realize their potential contributions to carbon neutrality. In summary, these findings offer valuable insights for shaping the future of carbon offset initiatives within China's state-owned forests. [ABSTRACT FROM AUTHOR]

• The spatiotemporal interactions of carbon emission efficiency(CEE) were explored. • A MGWR model was used to estimate the scale effects of factors influencing CEE. • The evolution of the spatial pattern of CEE had strong spatial integration. • CEE agglomeration changes had path dependence and spatial locking. • The factors influencing CEE exhibit obvious scale heterogeneity. Exploring the spatiotemporal evolution and influencing factors of carbon emission efficiency (CEE) is crucial for achieving the goal of urban carbon neutrality. However, most of the existing studies ignore the temporal dependence of the spatial pattern evolution of CEE and the scale variability of the factors influencing CEE. With the help of an exploratory spatiotemporal data analysis framework, this paper examined the spatiotemporal interactions of CEE across 110 cities in the Yangtze River Economic Belt (YREB). In addition, a multiscale geographically weighted regression model was employed to reveal the scale effects of influencing factors on CEE. The main conclusions are as follows: first, the CEE of cities in the YREB shows a fluctuating upward trend, but the overall level is still low, and a certain polarization phenomenon exists. Second, the spatial pattern of the CEE of cities in the YREB is generally relatively stable, with strong spatial integration and path dependence. Finally, the factors influencing CEE exhibit obvious scale variability and spatial heterogeneity. Our findings can provide a basis for localized and differentiated carbon emission reduction decision-making at the city level, as well as new insights for the formulation of sustainable urban spatial planning and low-carbon development strategies. [ABSTRACT FROM AUTHOR]

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

This study explores the impact of political uncertainty on sustainable urban development by examining carbon emission trading systems (ETS) in four major markets in China (Beijing, Shanghai, Guangdong, and Hubei) from 2014 to 2022. As an alternative to carbon taxes, carbon ETS markets have become increasingly popular due to their success in reducing greenhouse gas emissions. However, their effectiveness is often hindered by political instability and uncertainty. Utilising logistic regression and AR(1)-GARCH estimations, we identify a negative relationship between political uncertainty and carbon trading volume. Our study also reveals significant variations in the responses of these markets to political uncertainty. The paper contributes to the understanding of how ETS markets operate in a complex and constantly changing political environment. We suggest that policymakers need to consider the impact of political uncertainty on carbon trading when designing and implementing urban policies that promote sustainable development. Additionally, our research contributes to the development of urban policies that can be effectively implemented in both developed and developing regions. • Local government official turnovers are used as the measurement of political uncertainty. • Daily transaction data from four carbon ETS markets (Beijing, Shanghai, Hubei and Guangdong) in China • Considered the probability and proportion of zero transaction day • Logistic regression and AR(1)-GARCH estimations • A negative relationship between political uncertainty and carbon transaction volume [ABSTRACT FROM AUTHOR]

• The mechanisms of SE on CE in SC were explored from single and holistic perspectives. • Quantified the effect of SE on CE in SC. • Providing a reference for SE construction in SC in developing countries. • Synthetic DID and spatial DID models are used to estimate the impact of SE on CE in SC. • SE in SC has a significant reduction in CE and spatial spillover effects. Smart energy, as an important component of smart cities and directly related to carbon emissions, plays a crucial role in smart cities to achieve carbon neutrality, but the theoretical research and empirical evidence on the impact of smart energy on carbon emissions in smart cities are limited. This paper investigates, from single and holistic perspectives, the effect of smart energy on smart city carbon emissions and potential mechanisms. Based on the panel data of 100 smart cities in China from 2014–2019, it uses synthetic difference-in-difference mode and spatial difference-in-difference mode to estimate the carbon emission reduction effect and test the potential mechanisms. The results show that: (1) Smart energy reduces carbon emissions in smart cities by an average of 5.65 %. (2) Smart energy reduces smart city carbon emissions mainly through mechanisms including optimizing energy structure and improving energy efficiency. (3) Smart energy in smart cities has a significant spatial carbon emission reduction effect. (4) Smart energy in smart cities influences holistic regional carbon emissions through spatial mechanisms including technology spillover, peer effect, and scale effect. Finally, this study provides quantitative evidence and valuable insights for cities in developing countries with similar backgrounds to China to design emission reduction paths and adjust smart city strategies. [ABSTRACT FROM AUTHOR]

With greater industrialization and urbanization, the amount of carbon dioxide (CO2) in the atmosphere has increased rapidly, and global warming has become a great challenge for humankind. Land is an important resource for human survival and development. The analysis of CO2 emissions from various land uses is crucial for controlling the level of land CO2 emissions and increasing the effectiveness of land use. This study develops a methodological framework to explore the spatiotemporal spillover effect and efficiency in regional land use carbon emissions (LUCE) and the change of land use structure efficiency (LUSE). The CO2 emissions of various land use types and the amount of indirect CO2 emissions of related industries from 1995 to 2015 were calculated. Based on CO2 emission measurement and spatial autocorrelation test, a spatial Durbin model is constructed to explore the spatial spillover effect (SSE) of LUCE. A Super-slack-based DEA model with undesirable outputs is proposed to measure the LUSE and the LUCE of various provinces from 1990 to 2015. Results show that the LUCE in China show an increasing trend overall, with emissions increasing nearly four times from 1990 to 2015. This increase is caused mainly by indirect CO2 emissions, that is, energy consumption generated by human activities. The local Moran's I showed a downward trend with the increase in years, indicating that regions with similar LUCE were gradually dispersed and that regional differences existed. The LUSE in China presents a mainly decreasing trend from 0.96 in 1990 to 0.69 in 2015. The spatial distribution of CO2 emissions is negatively correlated with land use efficiency. Economic growth, technological input and energy intensity are the core factors affecting regional LUCE and have significant spatial spillover characteristics. The 30 provinces are separated into three subareas by a comparison of the LUSE and the LUCE, and recommendations are made for how to improve the LUSE and CO2 emission reduction control of each subarea. [ABSTRACT FROM AUTHOR]

With the active promotion of the "carbon peaking and carbon neutrality" goals, science and technology finance (STF) is the important driving force of low-carbon development, and financial networks facilitate the aggregation and transformation of resources in space, so it is of great theoretical and practical significance to investigate the impact of science and technology finance networks (STFN) on carbon emissions (CE). Based on the 30 provinces of China from 2011 to 2019, this article used the STF development level in each province as the main indicator to construct the STFN. The complex network analysis and econometric models are combined, with the weighted degree values and betweenness centrality selected as typical network structure indicators incorporating into the econometric model to explore their impact on CE. Then, the Geographically and Temporally Weighted Regression (GTWR) model is applied to analyse the spatio-temporal heterogeneity of influencing factors. The results show the following: (1) From 2011 to 2019, the spatial structure of China's STFN has changed significantly, and the status of the triangle structure consisting of Beijing–Tianjin–Hebei (BTH)–Yangtze River Delta (YRD)–Pearl River Delta (PRD) is gradually consolidated in the overall network, and the network structure tends to be stable. (2) The results of the benchmark regression show that the weighted degree value of the STFN has a significant inhibitory effect on CE, while betweenness centrality shows a certain positive effect on CE. (3) The weighted degree value has a more significant effect on CE reduction in the eastern region, while the betweenness centrality has a more significant effect on CE reduction in the central and western regions, but shows a significant promotion effect in the eastern region. (4) There is spatio-temporal heterogeneity in the effects of residents' affluence, energy consumption, industrial structure, and environmental pollution on CE. [ABSTRACT FROM AUTHOR]

Driven by global targets to reduce greenhouse gas emissions, energy systems are expected to undergo fundamental changes. In light of carbon neutrality policies, China is expected to significantly increase the proportion of hydrogen and electricity in its energy system in the future. Nevertheless, the future trajectory remains shrouded in uncertainty. To explore the potential ramifications of varying growth scenarios pertaining to hydrogen and electricity on the energy landscape, this study employs a meticulously designed bottom-up model. Through comprehensive scenario calculations, the research aims to unravel the implications of such expansions and provide a nuanced analysis of their effects on the energy system. Results show that with an increase in electrification rates, cumulative carbon dioxide emissions over a certain planning horizon could be reduced, at the price of increased unit reduction costs. By increasing the share of end-use electricity and hydrogen from 71% to 80% in 2060, the unit carbon reduction cost will rise by 17%. Increasing shares of hydrogen could shorten the carbon emission peak time by approximately five years, but it also brings an increase in peak shaving demand. [ABSTRACT FROM AUTHOR]