Search

The paper industry is a high-carbon emission and energy-intensive industry. From the perspective of low-carbon trade and carbon neutrality, its energy conservation and emission reduction are worthy of attention. This study used the input-output model to calculate the embodied carbon emissions of China’s paper industry’s export trade to the United States from 2006 to 2020 and used the logarithmic mean division index (LMDI) method to analyze influencing factors of the change of embodied carbon emissions. The study found that the embodied carbon emissions of China’s paper industry’s export trade to the United States generally shows a stable downward trend after reaching the peak with the increase of export trade scale; scale effect is the main factor that causes the embodied carbon emissions, while technological progress, policy support, and environmental regulations are important driving forces to promote carbon emission reduction. The research results of this paper not only can test and guide China’s paper industry trade policies and industrial policies, but they can also provide decision-making reference for China and the United States to promote the carbon emission reduction of the paper industry. [ABSTRACT FROM AUTHOR]

This paper studies the impact of digital economy development on carbon emissions, which is a hot topic in the field of environmental economics. This topic is within the scope of the Frontiers in Environmental Science and is particularly in line with the theme of Environmental Economics and Management section in the journal. Firstly, this paper constructs the Digital Economy Development Index and its variable indicators to measure the development of the digital economy. Secondly, this paper uses urban panel data to reveal the impact of digital economy development on carbon emissions, and further adopts IV method to deal with endogeneity issues. Thirdly, this paper performs the heterogeneity analyses depending on the characteristics of the city. The results can provide a basis for formulating differentiated policies. Fourthly, this paper further explores the mechanism by which the digital economy affects carbon peaking. The results show that the digital economy may influence carbon peaking through upgrading of the industrial structure, technical innovation, and energy consumption. [ABSTRACT FROM AUTHOR]

There are many important cultural relics in China, including many paper relics. Therefore, it is particularly important to find methods of protecting the handwriting in paper relics. This study focuses on the effects acrylic polyurethane materials have on preserving handwriting in paper relics by examining the color change and diffusion of handwriting before and after reinforcement treatments on handwriting materials, including ink, carbon ink, blue-black ink, pure blue ink, red ink, and pencil. The acrylic polyurethane materials have a certain degree of stability and enhance the handwriting of paper relics. We analyzed the acrylic polyurethane reinforcement material in terms of acid resistance, alkali resistance, oxidation resistance, dry heat aging resistance, and durability. The experimental results show that the optimal reinforcement concentration is within 15% for ink, 10% for carbon ink, 20% for blue-black ink, 15% to 20% for pure blue ink, and 3% for red ink and pencil. Finally, the surface of the reinforced paper and handwriting were observed through laser microscopy, SEM, EDS, and infrared spectroscopy and the protective effect of acrylic polyurethane reinforcement material on handwriting was determined. [ABSTRACT FROM AUTHOR]

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

Sustainable development has become society's focal point. In this context, China's paper industry needs to be more concerned about a low‐carbon strategy. Therefore, a carbon performance evaluation system must be built to guide the low‐carbon enterprise transformation. Based on the carbon value flow analysis, this study takes JX Paper (a paper‐making enterprise) as an example to construct a carbon performance evaluation system consisting of carbon input, transfer, and output indicators. The quantitative and qualitative index weights were determined through a principal component analysis and an analytical hierarchy process. The overall carbon performance increased from 2012 to 2021, but room remains for improvement. These results show that the performance evaluation system provides a helpful reference for enterprises to identify the key factors affecting carbon emissions and evaluate their carbon performance. Moreover, objective criteria should be developed to improve sustainable enterprise carbon performance and low‐carbon competitiveness. [ABSTRACT FROM AUTHOR]

Simultaneously achieving economic development and environmental protection is a shared global challenge. While the positive effect of environmental regulations on protecting the environment has been widely recognized, the attention paid to low-carbon governance and corporate green transformation remains insufficient. Based on the two-stage least square regression model (2SLS) of instrumental variables, this paper utilizes panel data from China to identify the influence mechanism of government low-carbon governance on enterprise green development. It explores the effect of low-carbon governance on enterprise green development from the perspective of fiscal decentralization. The findings show that (1) Low-carbon governance significantly promotes corporate green development, primarily through improving industrial structure and technological innovation; (2) Low-carbon governance notably promotes the green development of private enterprises but has little effect on state-owned enterprises. There are also geographical differences, and the results are better in Eastern China than in the Central and Western parts of China; (3) Fiscal decentralization at both central and local levels inhibits the effect of low-carbon governance on driving corporate green development by causing a mismatch of human resources. Therefore, to promote corporate green development, low-carbon governance must prioritize green development, actively guide industrial structural upgrading and enterprise technological innovation, implement differentiated low-carbon governance measures tailored to different ownership enterprises, and optimize the assessment indicators for fiscal decentralization. This paper helps deepen the understanding of the relationship between government low-carbon governance and enterprise green development in developing countries. It can be used as a reference for government departments to formulate relevant policies. [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]

With the proposal of "Carbon Peak and Carbon Neutrality" goals, China is facing a more serious carbon emissions reduction situation, and how the booming digital economy effectively helps China's carbon emissions reduction is one of the most urgent things that should be solved. To study the impact of the digital economy on carbon emission intensity, this paper is based on the panel data of 30 provinces in China (excluding Tibet, Hong Kong, Macao, and Taiwan) from 2011 to 2021, and applies the double-fixed effect model and the threshold effect model to study the impact of the digital economy on carbon emission intensity and the mechanism of its action, as well as to analyze the mechanism of the digital economy's action on carbon emission intensity from the perspective of technological innovation. The results of the study show that: i) The digital economy can reduce the intensity of regional carbon emissions; ii) The carbon emission reduction effect of the digital economy is non-linear, and its carbon emission reduction effect gradually increases with the level of development of the digital economy; iii) In addition to the direct impact of the digital economy on carbon emission intensity, it also has an indirect impact on carbon emissions through technological innovation; iv) There is regional heterogeneity in the carbon emission reduction effect of the digital economy, and the carbon emission reduction effect is more significant in the central and western parts of the country and regions with a high level of human capital development. Based on the conclusions obtained, this paper suggests: i) The rational integration of the digital economy and regional development should be strengthened; ii) Strong provinces in the digital economy should be encouraged to help weaker provinces, to narrow the "digital divide" between provinces; iii) Differentiated development strategies should be formulated in accordance with local conditions, to give full play to the optimal effect of the digital economy in carbon emission reduction. [ABSTRACT FROM AUTHOR]

The process of carbon neutrality does have economic costs; however, few studies have measured the cost and the economic neutral opportunities. This paper uses a dynamic computable general equilibrium (CGE) model to simulate China's carbon neutrality path from 2020 to 2060 and analyzes its economic impact. This paper innovatively adjusts the CGE modeling technology and simulates the boundary of the Porter hypothesis on the premise of economic neutrality. The results show that the carbon neutrality target may reduce the annual GDP growth rate by about 0.8% in 2020–2060. To make the carbon pricing method under the carbon neutrality framework meet the strong version of the Porter hypothesis (or economic neutrality), China must increase its annual total factor productivity by 0.56–0.57% in 2020–2060; this is hard to achieve. In addition, the study finds that China's 2030 carbon target has little impact on the economy, but the achievement of the 2060 carbon neutrality target will have a significant effect. Therefore, the paper believes that the key to carbon neutrality lies in the coexistence of technological innovation and carbon pricing to ensure that we can cope with global warming with the lowest cost and resistance. [ABSTRACT FROM AUTHOR]

This paper investigates how National Eco-industrial Demonstration Parks (NEDP) in China affects carbon emission efficiency. The difference-in-differences (DID) strategy is used for analysis. This paper finds that the construction of NEDP is conducive to the improvement of carbon emission efficiency, and the findings remain robust through placebo tests and propensity score matching. Heterogeneity analysis shows NEDP construction has greater utility on carbon efficiency in non-resource-based cities as well as in environmentally friendly cities. The mechanism analysis found that green technology innovation, industrial restructuring, and the relocation of industrial enterprises are effective ways to improve carbon efficiency in NEDP. Finally, this paper finds that the construction of NEDP has obvious spatial spillover effects on carbon efficiency, which can effectively heighten the carbon efficiency level of this locality and nearby areas. [ABSTRACT FROM AUTHOR]

In the context of rapid advancement in automation and increasing global warming, understanding the impact of artificial intelligence (AI) on carbon emissions (CES) is a cutting-edge research topic. However, there is limited focus in existing research on the nonlinear carbon reduction effect (CRE) of AI. This paper first theoretically elaborates the dual impact mechanisms of AI on CES and illuminates the nonlinear carbon reduction mechanisms of AI. Then, this study employs panel data encompassing 30 Chinese provinces between 1997 and 2019 to empirically test the net effect of AI on CES and the nonlinear carbon reduction effect of AI through econometric models. The results are as follows: first, although AI can both reduce and increase CES, AI primarily helps decrease CES. This conclusion holds true even after considering robustness, endogeneity, and spatial heterogeneity. Secondly, relative to the central and western regions, AI has significant achievement in reducing carbon intensity and per capita CES in the eastern region. However, there is still room for improvement in terms of reducing the total CES in the eastern region. Thirdly, improving the AI development level (AIDL) can magnify the marginal CRE of AI and lead to a nonlinear CRE of AI. Lastly, even if the AIDL remains constant, improving the level of marketization, human capital, digital infrastructure, economic development, openness, and government intervention can also amplify the marginal CRE of AI and lead to a nonlinear CRE of AI. To fully harness the potential of AI for green development, concerted efforts should be directed towards enhancing the innovation and application of AI technologies with carbon reduction potential. [ABSTRACT FROM AUTHOR]

Reducing carbon emission intensity is crucial for achieving sustainable development. Carbon emission intensity is expressively affected by the issuance of green bonds. Thus, it is imperative to assess the influence of green bond issuance on carbon emissions and examine their correlation. Such research holds great potential to expedite the overhaul and modernization of businesses and to construct a circular economy system. This paper uses the spatial Durbin model to draw empirical conclusions by using data from 26 provinces in China between 2016 and 2021. Firstly, under different spatial matrices, it has been analyzed that an increase of 1% in the issuance of green bonds leads to a reduction of 0.306% or 0.331% in carbon emission intensity. It shows that green bonds have the potential to substantially reduce carbon intensity. Additionally, the intensity of emissions in the current period is driven by the intensity of emissions in the previous period. Secondly, the analysis of mediated transmission suggests that green bonds can ultimately reduce carbon emission intensity by changing the energy consumption structure or improving the efficiency of green technology innovation. Thirdly, the analysis of heterogeneity shows that the inhibitory effect of green bond issuance on carbon emissions is stronger in less economically developed regions than in economically developed regions. There is a significant inhibitory effect of green bond issuance in neighboring provinces on local carbon emission intensity. This effect is present only in provinces in less economically developed regions and not in economically developed regions. [ABSTRACT FROM AUTHOR]

The carbon emission trading pilot policy is an important initiative to achieve synergistic economic-environmental development. Based on the data of 268 cities in China from 2006 to 2020, this paper analyzes the impact of carbon emission trading pilot policy on urban innovation capacity by using a time-varying difference-in-difference model. The study shows that, first, the implementation of the CETP improves the innovation capacity of cities, and the robustness test confirms the above findings. Second, the effect of the policy on enhancing urban innovation capacity is heterogeneous between the type of innovation and city type: the promotion of innovation capacity is stronger for utility model patents and non-capital cities. Third, there is a positive spillover effect of the implementation of the CETP on the promotion effect of the urban innovation capacity, which can lead to the improvement of the innovation capacity of neighboring cities. This paper has some reference value for building a unified carbon emission trading market and promoting low-carbon economic development within China. [ABSTRACT FROM AUTHOR]

Resource-based regions support national economic development and are essential sources of basic energy and raw materials. In the post-pandemic era, however, there are practical situations to deal with, such as a fractured industrial chain, a weaker industrial structure, and a sharp reduction in economic benefits. Based on data collected from 68 cities in China, from 2010 to 2021, with 816 observations, this paper explores the industrial development process of resource-based regions in China and the change in the toughness of the industrial structure under the impact of COVID-19. The paper studies and analyzes industrial development trends, industrial structure toughness, and spatial spillover effects. The methods used are the Markov chain model and the Industrial Structure Advancement Index. By building the spatial Dubin model, the paper analyzes the spatial spillover effect of regional industrial development. It decomposes the spillover effect using the partial differential model based on regression. The results show that, during the study period, the comprehensive development level of industries in resource-based regions in China was slowly improving and tended to stabilize after entering the post-pandemic era. The evolution of an advanced industrial structure is significantly heterogeneous among regions, and each region has different toughness. The impact of COVID-19 has reduced the toughness of China's resource-based regions' industrial structure. The spatial spillover effect of regional industrial development is significant. Labor force, technology input, and industrial-structure optimization have different impacts on the industrial development of neighboring regions. In the post-pandemic era, China has used new management methods for more innovation. In order to achieve low-carbon, environmental protection, and sustainable development of resources, realize the rapid recovery of the toughness of industrial structure in China's resource-based cities, and reduce the impact of the COVID-19 pandemic, China proposes to expand the supply of resources, improve the allocation of resources, optimize the direction, promote the rational flow and efficient aggregation of various factors, and enhance the impetus for innovation and development. [ABSTRACT FROM AUTHOR]

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]

This paper examines the dynamic linkages among economic policy uncertainty (EPU), the green bond market, the carbon market, and the macroeconomy using the time-varying parameter vector autoregressive (TVP-VAR) model with monthly data spanning from January 2016 to December 2021. Additionally, it assesses the robustness and accuracy of the empirical results through the Bayesian vector autoregressive (BVAR) model. The findings indicate that EPU negatively affects the green bond market in the short term but has a positive impact in the medium and long term. Conversely, EPU has a positive impact on the carbon market in the short term but a negative impact in the medium and long term. Furthermore, the green bond market negatively influences the carbon market in both the short and medium to long term. These results suggest that emerging markets, such as the green bond and carbon markets, are influenced by EPU. The adverse impact of the green bond market on the carbon market, however, contributes to expediting China's attainment of its low-carbon objectives. Appropriate economic policies can play a vital role in accelerating the transition to a low-carbon economy. The study also reveals that the US-China trade war has expedited the development of green capital markets in China, despite its impact on the green economic transition in the country. These findings provide insights for the government and investors to formulate suitable strategies for risk mitigation. [ABSTRACT FROM AUTHOR]

The actual situation of carbon-emission reduction in China's power sector has not yet achieved the expected benefits. The rent-seeking behavior of participants in power construction projects (PCPs) hinders the realization of low-carbon benefits. It is necessary to explore the behavioral strategies of the various participants in the low-carbon transition of PCPs. This paper creatively constructs an evolutionary game model of PCPs' participants from the perspective of MRV (monitoring, reporting, and verification) and introduces the influence of the public to provide a comprehensive analysis of strategic equilibrium points. Through numerical simulations with MATLAB R2021a software, this paper explores the strategic choices of participants in different situations and gives relevant inferences and proofs. The results show that the grid company dominates at the initial stage and promotes participants to regulate behaviors. Under the premise of satisfying the system-stability requirements, setting the growth rate of the grid company's punishments to 100% can enhance the willingness for strict supervision, while the growth rate of the supervision costs to 200% significantly decreases the probability of strict supervision. With the integration of MRV and PCPs, participants spontaneously fulfill the carbon-emission-reduction tasks. Reasonable control of input costs can effectively avoid the occurrence of rent-seeking behavior. In addition, this paper sets the public-influence growth rate at 200% and finds that the public plays a greater role in driving participants to fulfill responsibilities. Based on the results, a low-carbon transition mechanism for PCPs under the MRV system is proposed by considering several dimensions, which provides suggestions for participants to fulfill carbon-reduction responsibilities. [ABSTRACT FROM AUTHOR]

The integration or segmentation of regional carbon prices implies that barriers may hinder prices from adjusting efficiently and impede linkages between regional carbon markets. Past studies have found that crossregional carbon prices in China tend to diverge, indicating unbalanced regional markets and that carbon cap-and-trade policies may be insufficiently effective. China's carbon trading pilots opened in 2013. Is the integration efficient? This is the research question addressed in this study. This paper uses the carbon prices of four carbon-trading pilot regions in China (i.e. Beijing, Shanghai, Tianjin, and Guangdong) over the period of January 1, 2014, to March 23, 2021, to explore whether prices are correlated across three dimensions: long-term convergence, short-term correlation, and volatility transmission by adopting a vector error correction model with heterogeneous variances. And by using longer-term daily data and empirical tests that can account for the multiple-faceted correlations, this paper provides evidence showing that long-term convergence and risk transfer between the four regional carbon prices exist, which indicates significant regional integration. The results indicate that the price behavior of the Beijing pilot is efficient and that the Shanghai pilot has the lowest volatility. The paper also documents an information transfer pattern. For example, the Beijing pilot is shown to be the leading risk transfer market, whereas the Shanghai pilot is shown to be the market where most risk is transferred. Contrary to findings elsewhere, our main results demonstrate that China's carbon markets exhibit integration efficiency and no imbalance between regions. This may be because the efficiency of China's carbon markets has improved over time. The evidence also implies that if a multi-dimensional correlation has not been considered, it may underestimate the efficiency of regional carbon prices' integration. [ABSTRACT FROM AUTHOR]

Carbon emission trading has been actively applied in many countries, and its operational effect has received widespread attention. However, previous studies mostly focused on single environmental effect, and the investigation of the comprehensive environmental effect needs to be further supplemented. Based on this, this paper explores the comprehensive environmental effect of carbon emission trading with eco-efficiency as the starting point. First, this paper measures eco-efficiency using the super-efficient minimum distance to strong efficient frontier (MinDS) model with undesirable outputs. Second, this paper uses the propensity score matching difference in difference (PSM-DID) model to quantify the effect of carbon emission trading on eco-efficiency. Finally, this paper examines the mediating mechanism of the effect of carbon emission trading on eco-efficiency based on the mediating effect model. The results show that carbon emission trading can improve the level of urban eco-efficiency. Energy savings and increased efficiency effectively mediate the promoting effect of carbon emission trading on eco-efficiency. The mediating push effect of R&D innovation and industrial structure restructuring has not yet appeared. This paper can not only provide policy basis for the improvement of carbon emission trading market but also provide reference for the construction of carbon emission trading market in developing countries. [ABSTRACT FROM AUTHOR]

Improving total factor carbon emission efficiency (TCE) is the key to achieving carbon emission reduction targets while ensuring economic growth. In this paper, the global Malmquist index based on the SBM model is used to measure TCE of 283 cities in China from 2011 to 2019. On this basis, this paper uses the spatial econometric model and intermediary effect model to empirically analyze the impact of industrial co-agglomeration on TCE and its transmission mechanism. Furthermore, considering the differences in geographical location and resource endowment among regions, this paper analyzes the heterogeneous effect of industrial collaboration agglomeration on TCE in different regions and cities. The results show that: (1) Industrial co-agglomeration can improve TCE, and its main transmission channel is technological innovation. (2) Industrial co-agglomeration has a positive spatial spillover effect. Industrial co-agglomeration in one region can improve the TCE in the surrounding regions. (3) Industrial co-agglomeration of cities with different geographic locations and resource endowments has a heterogeneous effect on TCE. Regarding geographical heterogeneity, the industrial co-agglomeration in the eastern region has the greatest promoting effect on TCE, followed by the central region. However, the impact of industrial co-agglomeration in the western region on TCE is not significant. Regarding resource endowment heterogeneity, the industrial co-agglomeration in non-resource-based cities has a greater promoting effect on TCE than that in resource-based cities. [ABSTRACT FROM AUTHOR]

This paper explores the spatial impact effects and spatio-temporal heterogeneity of the digital economy on urban carbon emissions (CO2). Specifically, firstly, the Digital Economy Index (DEI) system of 285 cities in China was constructed and the Global Principal Component Analysis (GPCA) was applied to evaluate the digital economy level of Chinese cities. Based on spatial correlation and spatial heterogeneity, the paper explores the global spatial impact and spatio-temporal heterogeneity of the impact of digital economy on CO2 using spatial Durbin model (SDM) and geographic time-weighted regression (GTWR), respectively. And the mechanism variables are used to further demonstrate the mechanism effect and nonlinear characteristics of the impact of digital economy on CO2. The findings indicate that (1) the advancement of the digital economy is beneficial for achieving carbon abatement goals, and the impact of the digital economy on CO2 mitigation remains stable across several robustness tests. (2) The spatial spillover effect of the digital economy on the impact of carbon reduction is not significant. And there is significant temporal and spatial heterogeneity in the impact of the digital economy on carbon emissions. (3) According to the mechanism analysis, the digital economy reduces carbon emissions by encouraging the development of green technologies and promoting the modernization of industrial structures. And there are non-linear characteristics of this effect. This study concludes that the digital economy can support China's goal of achieving "carbon peak and carbon neutrality." However, it is important to consider the differences in urban development over time and space. Leveraging the city's strengths to develop a digital economy in a unique way that will help achieve China's carbon reduction goals. [ABSTRACT FROM AUTHOR]

As the digital economy grows rapidly around the world, how would it impact carbon emissions? This paper discusses this issue from the perspective of heterogeneous innovation. Based on the panel data of 284 cities in China from 2011 to 2020, this paper empirically examines the impact of the digital economy on carbon emissions as well as the mediating and threshold effects of different innovation modes. The study finds that the digital economy can significantly reduce carbon emissions; this conclusion holds after a series of robustness tests. Independent innovation and imitative innovation are important channels through which the digital economy affects carbon emissions, but technological introduction is not an effective way. For regions with high levels of financial investment in science and innovative talents, the reduction in carbon emissions from the digital economy is more significant. Further research shows that the effect of the digital economy on carbon emissions has a threshold feature, with an inverted U-shaped relationship between the two, and that an increase in autonomous innovation and imitation innovation can enhance the digital economy's carbon reduction effect. Therefore, it is necessary to strengthen the capacity of independent innovation and imitation innovation to exploit the carbon-cutting effect of the digital economy. [ABSTRACT FROM AUTHOR]

In the context of carbon neutralization and carbon peak, carbon reduction in key industries has become a central topic in our country. As an important part of technological progress, it is necessary to study the effect of technology import on carbon emission reduction in key industries. Based on the panel data of 30 provinces. from 2011 to 2020, this paper used the fixed-effect model to analyze the emission reduction effect in key industries on the development status of technology import. The spatial econometric model was used to analyze the spatial characteristics of carbon emissions of technology import and key industries. Then, the mediating effect model was used to bring industrial technological innovations into the research category to analyze the mediating role of technology imports on the carbon emissions of key industries. Finally, a robustness test proved the reliability of the model. The findings were as follows: (1) Technology import significantly promoted carbon emission reduction in key industries; (2) In terms of the spatial relationship, technology import and carbon dioxide emissions had significant spillover effects, and there were trends of high and high aggregation and low and low aggregation, with the impact of technology import on carbon dioxide emissions having a siphon effect; (3) Industrial technological innovation played an intermediary role in this path, but it was a negative role, which was not, in general, conducive to the reduction of carbon emissions of key industries. On this basis, the paper puts forward several policy suggestions. [ABSTRACT FROM AUTHOR]

Developing electric vehicle (EV) energy storage technology is a strategic position from which the automotive industry can achieve low-carbon growth, thereby promoting the green transformation of the energy industry in China. This paper will reveal the opportunities, challenges, and strategies in relation to developing EV energy storage. First, this paper clarifies the strategic value and potential of developing EV energy storage under the carbon neutrality goal. Second, this paper demonstrates strategic opportunities and challenges during the development. Third, this paper proposes methods for creating a good market environment and business models. Finally, this paper suggests that relevant policies and regulations should be formulated and charts the course of technology development. The results show that EV energy storage technology has potential in terms of technology, the scale of development, and the user economy. The proposal of the carbon neutrality goal, the increasing market share of EVs, lower-cost and higher-efficiency batteries, etc., have all further accelerated the development of EV energy storage. The EV energy storage field should focus on developing battery technology, make advancements toward delivering longer cycle lives and improving the safety and availability of battery materials, and ramp up the R&D efforts with respect to developing vehicle-to-grid (V2G) management technologies. Simultaneously, it is necessary to create a business ecosystem centered on V2G operating platforms, constituting a process to which various players can contribute and achieve mutually beneficial results. It is also essential to formulate top-level strategic plans across industries and organizations, develop an electricity-trading mechanism as soon as possible, and promote the implementation of technical standards related to EV energy storage. [ABSTRACT FROM AUTHOR]

The serious consequences of climate warming have increasingly become a globe agenda in recent decades. China has been actively participating in various initiatives to address global climate change and has made commitments to reduce carbon emissions. Although the logistics industry is regarded as the "new driving force of national economic development", its carbon intensity is relatively high. Therefore, whether the logistics industry can develop in a green and low-carbon way is very crucial. This paper takes the green logistics efficiency of China's provincial logistics industry as the research object. The Super-SBM model is used to measure the China's green logistics efficiency, then the general dynamic characteristics is depicted by kernel density analysis. With the GML (Global Malmquist-Luenberger) index model, the reasons for the changes in green logistics efficiency are explained. Finally, Moran's I index is used to analyze the spatial correlation of green logistics efficiency in each province. The results show that the green logistics efficiency in China is at a low level, but with an upward trend. China's green logistics efficiency has a significant positive spatial correlation, showing a zonal pattern of high in the east and low in the west, and a polarization phenomenon. In addition, the bottleneck of the overall development of green logistics efficiency in China depends on the level of green technology. Furthermore, the results also imply that green technology advancement is an inherent key factor for green logistics efficiency to achieve growth. [ABSTRACT FROM AUTHOR]

Constructing a new energy-based power system is not only an important direction for the transformation and upgrade of China's power system, but also a key to achieving peak carbon and carbon neutrality. How to fully utilize situation awareness technology to adapt to diverse and differentiated scenarios has become a crucial breakthrough point for ensuring the reliable, safe, high-quality, low-carbon, and economical operation of the new power system. Starting from the distribution network demand resources, this paper proposes a dynamic aggregation method for load aggregators considering the user deviation quantity, to deal with the current situation that the adjustable load-side resource points are multi-faceted and wide, and the operating subjects are complex and difficult to participate directly in the grid dispatch. First, considering there is subjectivity in the electricity behavior of users under the jurisdiction of the load aggregator, a deviation amount may be generated during the actual aggregation process, which reduces the profit of the load aggregator. Therefore, a load aggregator-level user deviation dynamic volume forecasting method based on the Markov chain is proposed, which is used to predict the deviation quantity of users during the dispatch cycle and achieve a dynamic status estimate on the load side of the new power system. On this basis, a dynamic aggregation model for load aggregators based on the deviation volume was constructed with the objective of maximizing the revenue of load aggregators. The examples, by comparing the aggregation results of users under three scenarios, show the proposed method can effectively guarantee the income of load aggregators, verify the effectiveness of the proposed dynamic aggregation strategy, and provide technical support for the operation situation awareness of the load side of the new power system. [ABSTRACT FROM AUTHOR]

Carbon price prediction is of great importance to regulators and participants in the carbon trading market. It is the basis for developing policies related to the carbon trading market and stabilizing that market. Considering the numerous factors that influence carbon prices in China, dimensionality reduction is needed to improve the prediction accuracy and efficiency. However, the traditional dimensionality reduction methods fail to fully consider the role of influencing factors, which has certain limitations. In this paper, a new dimensionality reduction method, namely scaled principal component analysis (s-PCA), is employed to improve the prediction accuracy of carbon prices. Firstly, a factor library that influence carbon prices is constructed from three perspectives: technical indicators, financial indicators and commodities indicators. Then, the s-PCA method is used to reduce the dimensionality of factors influencing carbon price. Next, two different methods are used to predict carbon prices, including traditional regression method and Long Short-Term Memory (LSTM) method. Finally, the economic value of the s-PCA method is examined by constructing investment portfolios. The empirical results of the Hubei Emissions Exchange show that the s-PCA model outperforms other competing models both in- and out-of-sample. In addition, the LSTM model could improve the performance of the s-PCA model in carbon price prediction. From a market timing perspective, investors can achieve a greater return and a larger Sharpe ratio using the s-PCA method than using other comparative methods and buy-and-hold strategy. Therefore, the s-PCA method is effective and robust in predicting carbon price. [ABSTRACT FROM AUTHOR]

Against the backdrop of global climate change, corporate carbon emissions have increasingly become a focal point, making carbon reduction by companies a pivotal issue. Based on data from Chinese listed manufacturing companies from 2010 to 2020, this paper explores the impact of ESG performance on carbon reduction. The results indicate that ESG performance significantly reduce corporate carbon emissions. Green technology innovation, corporate efficiency, and managerial shortsightedness are vital channels through which ESG promotes corporate carbon reduction. For companies with different environmental regulations, industry competition intensities, and capital intensities, the relationship between ESG performance and carbon reduction varies significantly. Notably, we found that in companies with strict environmental regulations, intense industry competition, and high capital intensity, the carbon-reducing effect of ESG performance is more pronounced. Furthermore, digital transformation positively moderates the relationship between ESG performance and carbon reduction. This study not only provides new empirical evidence for understanding the impact of ESG performance on carbon reduction but also offers valuable insights for businesses and policymakers to promote corporate efforts in carbon reduction and achieve China's "Dual Carbon" goals. [ABSTRACT FROM AUTHOR]

Carbon neutrality is the only way for green low-carbon development. Technological progress is an important starting point for improving energy efficiency. Through scientific and technological innovation, improving energy efficiency is a practical way to achieve the goal of carbon neutralization. Due to the limitation of data and index selection, there is no qualitative analysis of carbon neutrality in this paper. Compared with previous studies, the paper has the following contributions: Firstly, the energy efficiency score of China's provincial level is measured with the DEA method and it is found that the average energy efficiency score of the eastern region is the highest, followed by the western region, and finally the central region. The results also show that the energy efficiency is not in accordance with the economic growth. The regions with higher energy efficiency scores are not always economically developed because of huge energy consumption supporting the economic development. Secondly, the Tobit method is used to study the impact of the reverse technology spillover effect of OFDI on China's energy efficiency. The results show that the spillover effect has a significant positive effect on the improvement of China's energy efficiency, and has a positive impact on the eastern and western regions, but has no significant impact on the western region. Finally, we put forward some policy recommendations to increase energy efficiency to approach carbon neutrality and thus promote green economic development. This paper enriches the content of energy economy, the research method is innovative, and the conclusion is more scientific. [ABSTRACT FROM AUTHOR]

The interactive behaviors, such as competition and learning between local and neighboring cities, can lead to spatial spillover effects in policy implementation. Estimating the direct, indirect, and total effects of the carbon emission trading scheme (CETS) on green innovation is crucial to clarify its role and mechanisms. This paper applies the spatial difference-in-differences model to estimate these effects using data from 278 cities in China from 2009 to 2019. The results demonstrate that the CETS implementation catalyzes green innovation in pilot cities, which supports the Porter hypothesis. However, it has a negative impact on green innovation in neighboring cities of pilot cities, with this negative impact diminishing as distance increases. Notably, the total effect of the CETS is significantly negative, indicating that the CETS's average impact on green innovation in all cities is negative. Mechanism analysis reveals that the direct and indirect effects of the CETS on green innovation are strengthened in cities with higher levels of financial development, lower financial pressure, and easier economic growth targets. Notably, in cities with high-level industrial structures, the CETS not only enhances its contribution to green innovation but also mitigates its negative impact on neighboring cities. Furthermore, this paper explores the heterogeneous effects of the CETS from the perspective of its implementation measures. [ABSTRACT FROM AUTHOR]

The new development pattern has identified two key avenues for the sustained advancement of high-quality agricultural and rural development: digitalisation and low-carbon development. The measurement of the digital economy and the agricultural carbon emission performance, and their spatial and temporal heterogeneity, is a crucial step in promoting the spatial coordination and sustainable development of digitalisation and low-carbon agriculture. This paper employs the entropy value method, SBM model, and coupling coordination degree model to investigate the coupling coordination measurement and spatial-temporal heterogeneity of the performance of the digital economy and agricultural carbon emissions. The data used are provincial panel data from 2013 to 2021. The simulation results demonstrate that, between 2013 and 2021, the digital economy of all provinces exhibited varying degrees of growth, yet the development of the digital economy between provinces exhibited a more pronounced tendency to diverge. Concurrently, the agricultural carbon emission efficiency in China exhibited a fluctuating upward trend. The development of the digital economy and the efficiency of agricultural carbon emission were found to be highly coupled. Their coupling and coordination relationship showed a downward trend followed by an upward trend. In general, it is suggested that we should increase investment in digital economy infrastructure and technology, promote digital agricultural applications, strengthen policy guidance and financial support, establish a coupling coordination mechanism and strengthen farmers' digital literacy and environmental awareness. [ABSTRACT FROM AUTHOR]

Carbon emission intensity is an important index reflecting an entity's low-carbon competitiveness. This paper presents an extended logarithmic mean divisia index (LMDI) model to dissect carbon intensity within China's civil aviation from 1998 to 2019, revealing a significant reduction in CO2 emissions per air transport revenue. It attributes this decrease to technological advancements, optimized fleet structures, and improved operational efficiencies, highlighting the impact of larger, more efficient aircraft and enhanced load factors. The study also explores economic factors influencing carbon efficiency, suggesting a comprehensive approach encompassing technological innovation and strategic operational improvements for sustainable aviation development. [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 intelligent city pilot policy is a major measure in China to promote urban development from factor driven and investment driven to innovation driven. Intelligent city construction can effectively coordinate specialized production factors and information sharing mechanism, promote digital information technology innovation, promote smart industry cluster, and expand ecological scenarios of clean industry application, so as to reduce carbon emissions. This paper reveals the internal mechanism of intelligent city construction to promote carbon emission reduction. Based on the quasi-natural experiments carried out in three batches of pilot construction of intelligent cities since 2012, the difference-in-difference model (DID) is used to identify its impact on urban carbon emissions. The research results show that the pilot construction of intelligent cities is conducive to reducing carbon emissions, which is still robust under multiple scenarios such as placebo test and endogenous test. Heterogeneity analysis shows that the pilot policies have a more significant carbon emission reduction effect on the Beijing-Tianjin-Hebei urban agglomeration, non-resource-based cities, and non-old industrial bases. After further quantitative analysis of 917 pilot policy texts based on Simhash algorithm, Jieba word segmentation, and word frequency statistics, it is found that intelligent industry policies reduce carbon emissions by driving data elements agglomeration and optimizing industrial structure, while intelligent government and intelligent people's livelihood policies improve energy efficiency and reduce carbon emissions through green technological innovation. Counterfactual tests using machine learning algorithms show that the later the pilot batch, the better the sustainable carbon emission reduction effect of intelligent city pilot policies. [ABSTRACT FROM AUTHOR]

Identifying the relationship between carbon neutrality initiatives and its economic impact is crucial in evaluating the cost of low-carbon transition for policy makers. In this paper, a theoretical model is built to discuss the effects of the low-carbon pilot policy in China on urban economic resilience and an empirical test is conducted to examine the relationship using the Heckman two stage model and a panel data of 277 cities from 2004 to 2020. The results show that low-carbon pilot policy significantly enhanced urban economic resilience and the stimulating effect is mainly achieved by motivating technology innovations. In addition, further analysis indicates that low-carbon pilot policy has a more pronounced effect on improving urban economic resilience of cities in the central and western regions than eastern regions. The effect is also more prominent in non-first-tier cities than first-tier cities. The results are robust to placebo test, the Propensity Score Matching Difference-in-Difference test and the test for alternative measure of urban economic resilience. The findings show that the low-carbon pilot policy is consistent with the goal of improving urban economic resilience and technology innovation is the essential pillar of sustainable development. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to quantify the level of new-type urbanization and unravel the spatial and nonlinear effects of new-type urbanization and technological innovation on industrial carbon emissions. Although the impact of traditional urbanization levels on carbon emissions has been widely studied, there is still a huge room for optimization, and the impact of new-type urbanization on carbon emissions has not yet been clarified. Selecting 37 cities in the Yangtze River Delta as a research sample, this paper measures the new-type urbanization based on an evaluation system we build. Consequently, we assess the spatial and nonlinear effects of new-type urbanization and technological innovation on carbon emissions by the spatial Durbin model and non-parameter addictive model, respectively. The results indicate that the new-type urbanization and low-carbon city pilot policy have significant spatial spillover effects on reducing carbon dioxide emissions, while the economic growth plays a positive role in increasing carbon emission. As for nonlinear effects, there is a significant inverted "N"-shaped relationship between the level of new-type urbanization and carbon dioxide emissions, while the nexus between technological innovation and carbon emissions is an inverted "U"-shaped relationship. This paper provides a new perspective for confirming the mechanism of the new-type urbanization on carbon emissions. Meanwhile, these findings are of significance for the relevant authorities in China to develop appropriate policy in carbon dioxide emission reduction. [ABSTRACT FROM AUTHOR]

The development of green finance and the promotion of green transformation and upgrading of high energy-consuming enterprises are of great significance for China to achieve the "double carbon" goal. This paper employs a dual fixed-effects model to examine the profound ramifications and intrinsic mechanisms of green finance development on the transformative innovation of high-energy-consumption enterprises, using a sample of 462 publicly traded high-energy-consuming corporations from the period spanning 2016 to 2020. The results show that the development of green finance promotes the transformation and innovation of energy-intensive enterprises and that market-incentivized environmental regulation plays a partially mediating role; the results of heterogeneity analysis show that green finance promotes the transformation and innovation of high energy-consuming enterprises with significant differences in different low-carbon pilot regions, company ownership, and enterprise size; the mechanism analysis shows that the development of green finance can increase government subsidies and alleviate financing constraints to promote the transformation and innovation of high energy-consuming enterprises; it is also found that the development of green finance can significantly improve the financial performance of enterprises. The research findings of this paper hold significant implications for promoting the sustainable development of green finance and high-energy consumption enterprises in China. They provide valuable insights and references for facilitating the green transformation and innovation of high-energy-consuming enterprises in China as well as other developing countries. [ABSTRACT FROM AUTHOR]

The rapid development of China's manufacturing industry has brought about environmental problems that have aroused people's attention to improving carbon emission efficiency and reducing carbon emissions. In this paper, 13 prefecture-level cities in Hunan Province from 2010 to 2020 were selected as research samples, and the coupling coordination degree model and super-efficiency slacks-based measure (SBM) model were used to calculate the level of integration of "two industries" (manufacturing and producer services, short for "TI") and the efficiency of carbon emissions. Then, hypotheses are established: The integration of TI can promote the improvement of carbon emission efficiency; The integration of TI promotes technological innovation; Technological innovation can promote carbon emission efficiency; Technological innovation is an intermediary in integrating TI affecting carbon emission efficiency. By using the fixed effect model and the mediation effect test method, we empirically analyze the influence of the integration of TI on carbon emission efficiency and the mediating role of technological innovation in this process. The conclusions are as follows: the integration of TI has a significant promoting effect on carbon emission efficiency; The integration of TI improves carbon emission efficiency by promoting technological innovation, and technological innovation bears part of the intermediary effect in the process of the impact of the integration of TI on carbon emission efficiency. The policy implications for improving carbon emission efficiency are proposed based on the research results. [ABSTRACT FROM AUTHOR]

With technological transformations such as big data, blockchain, artificial intelligence, and cloud computing, digital techniques are infiltrating the field of finance. Digital finance (DF) is a resource-saving and environmentally friendly innovative financial service. It shows great green attributes and can drive the flow of financial resources towards environmentally-friendly enterprises, thereby promoting green low-carbon circular development (GLCD). However, few studies have explored the coupling mechanism between DF and GLCD. To fill this gap, this paper explores the effect of DF on GLCD, and established a mediating effect model to investigate the mechanism of DF in promoting GLCD. Additionally, this paper established a random forest model and a CatBoost model based on machine learning to examine the relative importance of DF and the factors affecting GLCD. The results show that DF has significant positive effects on GLCD, and technological innovation plays a key role in the effect of DF on GLCD; meanwhile, the effect of DF on GLCD shows nonlinear features with an increasing "marginal effect"; moreover, both DF and conventional factors have significant impacts on GLCD. Our study highlights the effect of DF on GLCD and underscores the importance of developing policies for DF and GLCD. This study provides an empirical basis and path reference for DF to achieve "carbon peak, carbon neutralization" in China. [ABSTRACT FROM AUTHOR]

Under the "two-carbon" goal, the green and low-carbon development of agriculture is a critical way to consummate agricultural modernization and high-quality economic establishment. Digital inclusive finance eases credit restrictions. It enhances the availability of funds for farmers. It promotes the integration of agricultural industries and talent gathering through digitalization, improves the standard of agricultural production and promotes the development of green and low-carbon agricultural modernization in China. This paper uses panel data for 2011–2021, which includes 31 provinces in China. Green and low-carbon development indicators of agriculture were constructed and calculated, and the comprehensive horizontal spatial differentiation map of GIS technology was used for analysis. A spatial panel model was set up at the same time, to explore the impact and mechanism test of digital financial inclusion on the green and low-carbon development of agriculture, and regional heterogeneity was analyzed. (1) Digital financial inclusion can promote the green and low-carbon development of agriculture, and its influence has a positive spatial spillover effect. (2) The education level of the labor force plays an intermediary role and is the transmission mechanism of digital financial inclusion and the green and low-carbon development of agriculture. (3) The impact of digital financial inclusion on green and low-carbon agricultural development has regional heterogeneity. [ABSTRACT FROM AUTHOR]

Low-carbon pilot policies are an important way to achieve the goal of "peak carbon neutrality" and are of great significance to China's international commitments. Based on a sample of 282 prefecture-level cities from 2006 to 2020, this paper investigates the impact of low-carbon pilot policies on urban carbon efficiency using a quasi-natural experiment with three batches of low-carbon pilot cities in 2010, 2012, and 2017, respectively. It is found that: (1) low-carbon pilot cities can improve urban carbon emission efficiency, which is still valid after a series of robustness tests such as the parallel trend test, placebo test, PSM-DID, and counterfactual test; (2) low-carbon pilot cities can enhance urban carbon emission efficiency by promoting the level of urban innovation and advanced urban industrial structure; and (3) the impact of low-carbon pilot policies on urban carbon emission efficiency is heterogeneous across cities with different geographical locations, population sizes, and resource endowment types. The findings provide policy insights for the promotion of low-carbon pilot policies and strengthening the construction of low-carbon pilot cities. [ABSTRACT FROM AUTHOR]

China needs to achieve its carbon peaking target with minimal economic costs. This paper proposes a framework for achieving the carbon peaking target that emphasizes economic effects. Based on the prediction, the parametric directional distance function (DDF) is adopted to calculate the total factor carbon emission efficiency and marginal carbon abatement cost in each region of China before 2030, and the allocation scheme of the abatement tasks necessary for carbon peaking is optimized from the perspective of least cost. The empirical results show the following: (1) The predicted rapid growth of China's economy from 2020 to 2030 will lead to a rapid increase in marginal abatement costs, with the average marginal carbon abatement cost increasing from 8,833 yuan/ton to 15,077 yuan/ton. The cost of carbon emission reduction in the future is very expensive. (2) The measured marginal abatement costs in China are positively correlated with carbon emission efficiency. In order to ensure economic development, developed regions should try to maintain the development trend, while the central and western regions take on more emission reduction tasks. (3) The emission efficiency is improved by optimizing the allocation scheme of the abatement tasks required to reach the peak, and the scientific and orderly path to reach the peak of each province and the corresponding lowest economic cost are obtained. This paper are of great theoretical and practical significance for the initial quota allocation in carbon trading market and ensuring the achievement of carbon peaking target under economic effect. [ABSTRACT FROM AUTHOR]

Taking 30 provinces in China from 2011 to 2020 as a research sample, this paper empirically tests the impact of digital village construction on carbon emissions. This study found that there is an "inverted U" curve relationship between digital rural construction and rural carbon emissions. Agricultural planting structure and agricultural technology efficiency are important ways for digital village construction to reduce agricultural carbon emissions. The study also found that the higher the level of economic development, the stronger the carbon emission reduction effect of digital village construction. In addition, there are also significant differences in the carbon emission reduction effect of digital village construction in regions with different environmental regulation intensities. Finally, in terms of the relationship between digital economic activities and carbon emission reduction, the research conclusions of this paper have important implications. [ABSTRACT FROM AUTHOR]

Strengthening the synergistic management of carbon and haze is an important means to realize China's "carbon peaking and carbon neutrality goals" and green development. In this paper, the entropy method is used to measure the key core technology innovation level of 30 provinces in China from 2011 to 2021, and the fixed-effect model is used to empirically test the impact of key core technology innovation on carbon haze synergistic governance and the internal mechanism. The study found that (1) key core technological innovation helps to promote carbon haze synergistic governance. (2) The mechanism test shows that key core technology innovation promotes the synergistic management of carbon haze by improving the clean energy structure. (3) The moderating effect shows that both market incentives and government environmental regulations will strengthen the positive relationship between key core technology innovation and carbon haze synergistic governance. The main contribution of this paper is to reveal the influence mechanism of key core technology innovation on carbon haze synergistic governance, and also to provide theoretical basis for the mechanism and law of carbon haze synergistic governance. [ABSTRACT FROM AUTHOR]

As an important way for China to achieve its dual-carbon goal, green finance has become the foundation for promoting high-quality economic development in China. In order to clarify the mechanism of green finance on carbon emissions, this paper puts green finance into the economic model and deduces the relationship between green finance and carbon emission reduction. This paper is based on the panel data of 30 provinces in China (excluding Tibet, Hong Kong, Macao, and Taiwan) from 2008 to 2019, using the individual fixed effect model, dynamical model, mediator model, and SDM model to study the impact of green finance on carbon emissions and its impact path of upgrading of the industrial structure and the development of science and technology based on the measurement of the green finance development index of each province by the entropy method. The findings show that the development of green finance can reduce carbon emission significantly, which can be sustained until at least the third phase and generates spatial spillover effects; regional heterogeneity analysis finds that the development of green finance shows geographical discrepancies: compared with the eastern and western regions, the development of green finance in central region can reduce carbon emissions more significantly; not only can the development of green finance directly reduce carbon emission, but also through the upgrading of industrial structure and technological innovation. The research not only provides a new perspective and supplementary empirical evidence for understanding the carbon emission reduction effect of green finance, but also offers some useful references for green finance to contribute to carbon emission reduction. [ABSTRACT FROM AUTHOR]

Digitalization and greening are key themes in global development, the manufacturing industry, as a major sector of energy consumption and carbon emissions, is in urgent need of transformation to realize energy conservation and emission reduction, digital transformation provides an opportunity for its green development. However, whether digital transformation can restrain the carbon emission intensity (CEI) of enterprises is still controversial. Based on the data of China's A‐share manufacturing listed companies from 2013 to 2020, this paper uses fixed effect model and intermediary effect model to explore the relationship between digital transformation and enterprise CEI and the influence path. the results show that: (1) Digital transformation has significantly reduced the CEI of manufacturing enterprises. (2) Mechanism analysis indicates that green technological innovation and resource allocation efficiency play a chain mediating role in this relationship. (3) Heterogeneity analysis shows that the carbon emission reduction effect of digital transformation is more significant when enterprises belong to an energy‐intensive manufacturing industry or face strong environmental regulations and industry competition. The analysis of this paper not only deepens enterprises' understanding of digital transformation and green development but also provides a policy basis for China to advocate the coordinated development of the digital economy and green economy. [ABSTRACT FROM AUTHOR]

Amid China's pursuit of a green and low-carbon transition, corporate social responsibility (CSR) is facing new challenges. Our research delves into the influencing factors and mechanisms for CSR reputation under green and low-carbon transition and provides practical enlightenment for enterprises to achieve sustainable development. This paper constructs a comprehensive index system of CSR from five dimensions (innovation, coordination, sustainability, openness, and sharing), and CSR reputation of China's A-share listed companies is comprehensively estimated by using an entropy method and data from 2013 to 2021. Then, from the perspective of external supervision and internal governance, we discuss the influence factors of CSR reputation, with an emphasis on the impact of public environmental concerns. Finally, the realization mechanism of CSR is further revealed. It is found that public environmental concern and the expansion of the enterprise scale boost the enhancement of CSR reputation. However, a higher proportion of female managers tends to hinder CSR reputation. Furthermore, public environmental concern plays a more prominent role in improving CSR reputation of non-state-owned and eastern enterprises. Additionally, public environmental concern significantly enhances CSR reputation through green technology innovation and executive environmental awareness. This research provides valuable insights for improving CSR reputation and optimizing regulatory compliance and governance practices. [ABSTRACT FROM AUTHOR]

In the context of increasingly severe global climate change, finding effective carbon emission reduction strategies has become key to mitigating climate change. Environmental Protection Tax (EPT), as a widely recognized method, effectively promotes climate change mitigation by encouraging emission reduction behaviors and promoting the application of clean technologies. Based on data from 282 cities in China, this paper takes the official implementation of the EPT in 2018 as the policy impact and the cities with increased tax rates for air taxable pollutants as the treatment group and uses DID model to systematically demonstrate the relationship between the implementation of the EPT and carbon intensity (CI) and further explores the possible pollutant emissions and green innovation mediating effects. The findings show that (1) the implementation of EPT can effectively reduce CI by about 4.75%, and this conclusion still holds after considering the robustness of variable selection bias, elimination of other normal effects, policy setting time bias, and self-selection bias. (2) The implementation of EPT can reduce CI by reducing pollutant emissions and improving the level of green innovation. (3) There is obvious regional heterogeneity in the carbon reduction effect of EPT, and the implementation of EPT has a more significant effect on CI in medium-tax areas, low environmental concern areas, general cities, and eastern regions. This paper not only provides a new analytical perspective for systematically understanding the carbon emission reduction effect of EPT but also provides policy insights for promoting regional green transformation and advancing carbon peak carbon neutralization. [ABSTRACT FROM AUTHOR]

The severe global warming issue currently threatens humans' existence and development. Countries and international organizations have effectively implemented policies to reduce carbon emissions and investigate low-carbon growth strategies. Reducing carbon emissions is a hot topic that academics and government policy-making departments are concerned about.Through necessary condition analysis (NCA) and fuzzy set qualitative comparative analysis(fsQCA), this paper investigates local governments' configuration linkage effect and path choice to improve carbon emission performance from six dimensions: energy consumption, industrial structure, technological innovation, government support, economic development, and demographic factors. The research findings include the following: (1) Individual condition does not represent necessary conditions for the government's carbon performance. Among the two sets of second-order equivalence configurations(S and Q) (five high-level carbon performance configurations), those dominated by economic development or low energy consumption can produce high-level carbon performance. Therefore, the six antecedent conditions dimensions work together to explain how the government can create high levels of carbon performance. (2)According to the regional comparison, China's eastern, central, and western regions exhibit similarities and differences in the driving forces behind high carbon emission performance. All three regions can demonstrate carbon emission performance when all the factors are combined. However, when constrained by the conditions of each region's resource endowment, the eastern region emphasizes the advantage of economic and technological innovation, the central region favors government support and demographic factors, and the western region prefers upgrading industrial structure based on a specific level of economic development. [ABSTRACT FROM AUTHOR]

In 2023, China's crude steel production amount reached 1.019 billion tons, and the energy consumption of China's steel industry amount reached 561 million tons of coal. China's steel industry, with its dominant reliance on coal for energy and the primary use of blast furnaces and converters in production processes, as well as its massive output, has become the main field for achieving China's "carbon peaking" and "carbon neutrality" goals. Firstly, this article summarizes the current production status of the steel industry and the situation of carbon emissions in the steel industry. Secondly, it discusses the dual-carbon policies based on the national and steel industry levels and outlines the future directions for China's steel industry. Subsequently, it analyzes the current state of research and application of mature and emerging low-carbon technology in China's steel industry and details the low-carbon plans of China's steel companies using the low-carbon technology roadmaps of two representative steel companies as examples. Finally, the article gives policy suggestions for the further carbon reduction of China's steel industry. The purpose of this paper is to show the efforts and contributions of China's steel industry to the early realization of its "carbon peaking" and "carbon neutrality" goals. [ABSTRACT FROM AUTHOR]