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China's pulp and paper industry (CPPI) has been always the main carbon emission source in recent years. However, the analysis on influencing factors of carbon emissions from this industry is insufficient. To address the issue, the CO2 emissions from CPPI are estimated in the period of 2005–2019, the driving factors of CO2 emissions are investigated by the logarithmic mean Divisia index (LMDI) method, the decoupling state of economic growth and CO2 emissions is determined by Tapio decoupling model, and finally, future CO2 emissions are predicted under four scenarios by the STIRPAT model to explore the potential of carbon peaking. The results show that CPPI exhibits a rapid increase and a fluctuating downward trend in CO2 emissions during the period of 2005–2013 and 2014–2019, respectively. The main promoting and inhibiting factors to the increase of CO2 emission are per capita industrial output value and energy intensity, respectively. There are five decoupling states of CO2 emissions and economic growth during the study period, and the CO2 emissions exhibit a weak decoupling state with the industrial output value growth in most years of the study period. It is very difficult to realize the carbon peaking goal by 2030 under the baseline and fast development scenarios. Therefore, efficient low carbon and strong low-carbon development policies are necessary and urgent for the realization of carbon peaking goal and the sustainable development of CPPI. [ABSTRACT FROM AUTHOR]

Improving carbon emission efficiency is crucial for achieving carbon peak and carbon neutrality. This paper analyzes the carbon emission efficiency of Chinese cities using panel data from 275 prefecture-level cities between 2006 and 2020. The super-efficiency SBM (undesirable slacks-based measurement) model of undesired output, combined with kernel density estimation and exploratory data analysis, is employed. This study finds, firstly, from 2006 to 2020, the average efficiency of carbon emissions in Chinese cities declined from 0.53 to 0.48, indicating a downward trend. Secondly, from a temporal perspective, the level of dispersion in urban carbon emission efficiency has become increasingly distinct over time, coupled with a decrease in polarization. Thirdly, in terms of spatial analysis, urban carbon emission efficiency in China shows a positive correlation in a global context. In terms of local spatial correlation, it primarily exhibits high-high and low-low clusters, with a few instances of low–high and high-low clusters. Finally, based on the research findings, this paper proposes suggestions to improve urban carbon emission efficiency. [ABSTRACT FROM AUTHOR]

Carbon abatement efforts in China are penetrating to sub-national level. Zhejiang province, as the 4th wealthy region in China and important player in global market (e.g., textiles, cloth, petroleum, and chemical products), lacks in-depth study of its climate change mitigation efforts, especially after China's accession to the WTO in 2001. This paper analyzed carbon emissions and intensity in Zhejiang province using most comprehensive and time-series dataset available to date since 2002. Its carbon emissions were growing at a declining speed, and carbon intensity was almost halved. The leading emitters largely agglomerate around Hangzhou Bay, close to Zhoushan Port and Shanghai Port. The growth in absolute emissions primarily arose from higher investment (323.1 Mt) and exports (280.6 Mt), while the slower growth was mainly due to efficiency improvements (− 245.7 Mt) stemming from energy and carbon abatement policies and inflows of emission-intensive products from the rest of China. Similarly, declined carbon intensity was mainly attributed to efficiency improvement. Major contributors were sector S13-Non-metallic minerals, S12-Chemicals, S26-Transport, storage and post, S07-Textiles, and S10-Paper. Economic restructuring played different roles on emissions and intensity during various development stages. Policy implications of the findings are discussed for future developments. [ABSTRACT FROM AUTHOR]

The Web of Science Core Collection platform was used to withdraw the papers included in this study. The studied period comprised from inception till 2018. Trends in research, journals of publication, subject areas of research, keywords most frequently used, countries of publication, international collaboration, and trends of funding research were also analyzed. A total of 3902 articles were published, most of them (52.5%) during the five-year period 2014–2018. The area with the highest number of papers was environmental sciences (41%), followed by energy fuels (16.6%) and engineering environmental (15.7%). "Nitrous oxide emissions" was the most frequent word, followed by "Carbon dioxide emissions" and "Methane emissions". Other words that stood out were "Life cycle assessment", "Climate change" and "Environmental impacts". The United States was the country with the highest productivity (27.9%), followed by China (12.8%) and the United Kingdom (9.6%). There was a concentration of research in recent years, as more than 80% of the papers were published in the last 10 years. The journals that published the largest number of publications were devoted mainly to environmental studies (sciences and engineering), sustainable and green science and technology, energy and fuels, economics, and agriculture. Half of the works were published in Europe and the other half between North America and Asia. Two thirds of the works (67%) were financed compared to a third that were not financed. The percentage of funded works has been increasing over the last decade, which is seen as an indication of the importance of GHGE. [ABSTRACT FROM AUTHOR]

In order to promote the balanced development of regional economy, governments at all levels are constantly introducing regional coordinated development policy (hereinafter referred to as "the Policy"). However, there is an important and interesting issue, namely, with the increasingly severe environmental problems resulted from rapid regional economic growth, what kind of impact will the Policy have on carbon emissions reduction? This is attracting wide attention from relevant stakeholders. Therefore, taking the Beijing–Tianjin–Hebei (BTH) region in China for example and through constructing the difference-in-differences (DID) model, this paper evaluated the effect of the implementation of the Policy on carbon emissions reduction. Results indicated that the Policy significantly reduced the level of regional carbon emissions in the BTH region. After carrying out a series of robustness tests, this paper still found that the above conclusions were reliable. Moreover, the mediation effect test shown that the Policy indirectly lessened carbon emissions by optimizing energy structure and reducing the intensity of carbon emissions, while the expanding of economic scale would lead to an increase in carbon emissions due to the effect from the Policy. Additionally, heterogeneity analysis revealed that the Policy had a more significant effect on carbon emissions reduction in underdeveloped regions with low environmental constraints. Overall, this paper would be beneficial to understanding the environmental effects of the Policy at the urban regional scale, thus providing an important basic theoretical basis for promoting the green and sustainable development of regional economy. [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]

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]

Energy efficiency (EE) plays an important role in achieving the dual-carbon goal, and improving EE is thus indispensable. This paper evaluates the impact of carbon emission trading policy (CETP) on EE based on a difference-in-difference (DID) method, using 16-year data of 30 provinces and cities from 2005 to 2020. Conclusions are as follows: (1) CETP significantly promotes EE, and this conclusion still appears valid after robustness tests. (2) The positive impact of CETP on EE is more effective in regions of high foreign direct investment (FDI) and high government intervention (GOVI). (3) The positive impact of CETP on EE is through impact mechanisms of energy structure adjustment (ESA), green innovation (GI), and industrial structure upgrading (ISU). The findings in this paper may enrich current research in CETP and offer more pragmatic suggestions for policy advancement as well. [ABSTRACT FROM AUTHOR]

The construction of high-speed railways and the smart city pilot (HSR-SCP) demonstrates the synergy of traditional and new infrastructure upgrades, which has a significant influence on the economic transition and green economic growth. However, little study has been conducted on the impact of HSR-SCP synergy on carbon emissions. Applying China's prefecture-level panel data, this paper, therefore, attempts to investigate the effect of HSR-SCP on carbon emissions and uncover its in-depth mechanism through the multi-period difference-in-differences model. Notably, an appropriate instrumental variable for HSR-SCP is introduced to address possible endogeneity. The main conclusions indicate that the construction of HSR-SCP plays an essential role in cutting carbon emissions, which is still valid after adopting the instrumental variable method and some robustness tests. Furthermore, green technology innovation plays a crucial intermediary role in that relationship. Finally, the carbon reduction effect of HSR-SCP is significant in Mid-Eastern China and cities with high population sizes and administrative levels, but not in other cities or regions. The research conclusions demonstrate the significant synergy of traditional and new infrastructure upgrades on carbon reduction and provide an empirical foundation for developing countries to realize low-carbon development through optimizing smart infrastructure and promoting green technology innovation. [ABSTRACT FROM AUTHOR]

The marine ecological compensation (MEC) policy is a scheme for protecting and restoring marine ecology. The previous studies have verified that the policy has improved the marine environment, ignoring the comprehensive performance of the economy and environment. Is the MEC policy actually effective for reducing marine carbon emission considering resource input and economy output? To address the question, this paper evaluates the impact of MEC policy on marine carbon emission efficiency by introducing the multi-stage difference-in-difference with propensity score matching. The results show that the MEC policy significantly improves marine carbon emission efficiency, and the positive effects dynamically enhance over time. Low-carbon technology innovation is confirmed to play a mediating role by which the MEC policy improves marine carbon emission efficiency. Therefore, gradually popularizing the MEC policy and accelerating low-carbon technology innovation are crucial measures to improve marine carbon emission efficiency and achieve sustainable marine development. [ABSTRACT FROM AUTHOR]

A carbon emission factor (CEF) database is required for the basis of carbon emission calculation in construction projects. However, the default values for existing CEF databases cannot cover the complex resources involved in a construction project. Therefore, this paper proposes a three-step method to guide the establishment of an extensible CEF database for the construction industry, including (1) data collection and parser, (2) data extension, and (3) data encoding and storage. The data extension mechanisms provide the supply chain perspective considering temporal issues and the accounting perspective to streamline the process. Aiming to address the lack of a comprehensive CEF database for the construction industry in China, this paper uses this method to establish a carbon emission factor database for the Chinese construction industry (CEFD for CCI). This database is open and free with 646 CEFs, including five parts: energy, human, material, machinery, and greenspace. This paper provides a way for developing and less developed countries to establish an expandable CEF database, which benefits the parser, extension, encoding, and storage of new resources, as well as computer access. [ABSTRACT FROM AUTHOR]

Coordinated efforts to reduce haze and carbon emissions are important in promoting global climate governance and sustainable development. In this paper, based on prefecture-level data of China from 2005 to 2019, we investigate the impact of environmental regulatory intensity on the emissions of the concentration of PM2.5 and carbon dioxide (CO2). The research indicates that environmental regulation facilitates synergistic governance for PM2.5 reduction and carbon mitigation. Green technological advancement emerges as the primary mechanism through which environmental regulation achieves haze reduction and carbon mitigation. This conclusion remains robust after a series of robustness tests. Furthermore, the results from quantile regression reveal that the haze reduction and carbon mitigation effects of environmental regulation are subject to certain conditional dependencies. Environmental regulation exhibits a significant negative impact on carbon emissions across various quantile points. However, their influence on different quantile levels of PM2.5 concentration displays an asymmetric pattern. Finally, threshold regression findings suggest that there is no significant threshold effect of environmental regulation on CO2 emissions, but there are dual threshold effects on the PM2.5 concentration. Therefore, it is recommended that local governments judiciously implement environmental regulatory intensity, establish interregional policies for haze reduction and carbon mitigation, and fully harness the driving force of green technology to promote a comprehensive green transformation of economic and social 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]

Reducing carbon emissions is the key to fulfilling the "double carbon commitment" and promoting the green transformation of the economy. The financial sector is the forerunner of change in economic development. The rapid development of digital finance has disrupted the traditional financial operation mode and has had a significant impact on economic development and environmental quality. This paper explores the impact of digital finance development on carbon emissions using carbon emission data from 2011 to 2017 in China's counties and combining it with the Digital Inclusive Finance Index of Peking University. The findings are as follows: (1) The development of digital finance can curb carbon emissions, and this causal relationship still holds through a series of robustness tests. The greater the carbon emissions, the better the carbon suppression effect of the development of digital finance. (2) When regions face strict financial regulation and environmental constraints, the development of digital finance can be more effective in reducing carbon emissions. The existence of a digital divide in general can weaken the disincentive effect of the development of digital finance on carbon emissions. (3) The development of digital finance can promote the development of green finance, enhance the level of green technological innovation, improve green total factor productivity, and transform energy structures, thus curbing carbon emissions. This paper not only enriches the literature on the development of digital finance and the environment but also provides a reference for government departments to improve the development strategy of digital finance and achieve "carbon peaking and carbon neutrality." [ABSTRACT FROM AUTHOR]

This paper aims to encourage power generation enterprises to actively carry out emission reduction activities by studying the impact of carbon emission reduction investment on long-term development. The existing literature mainly studies the interaction between national economic development and energy consumption at the macro level, and the impact of environmental protection investment by enterprises at the micro level on the short- and long-term economic consequences. However, there is still a large space for research on how specific emission reduction measures lead the long-term development of enterprises. Therefore, this paper chooses to introduce enterprise competitiveness, government subsidy, and management shareholding ratio respectively to conduct intermediary test and grouping regression, and empirically studies the mechanism of carbon emission reduction input of Chinese power generation enterprises on the cost of equity capital from 2013 to 2020. The results show that management shareholding can enhance the initiative of enterprises to reduce emissions. At the same time, carbon emission reduction investment can effectively reduce the cost of equity capital by improving the competitiveness of enterprises and forming a reputation mechanism faster. This study reveals the significance of carbon emission reduction investment as an important part of enterprise environmental protection investment, and emphasizes that the government and enterprises can effectively avoid the short-sighted tendency of enterprises and improve the long-term development power of enterprises by adjusting government subsidies, management shareholding ratio and other policies. [ABSTRACT FROM AUTHOR]

Climate policies could improve air quality, thereby generating health benefits and thus increasing labour input for economic growth. Nevertheless, health benefits are usually overlooked in evaluation frameworks of climate policies. In this paper, a dynamic recursive computable general equilibrium (CGE) model is adopted to define how climate policies are related to air pollution, namely PM 2.5 concentrations. Health benefits of climate policies are divided into reduction of PM 2.5 -related morbidity and mortality. The CGE model results show that both carbon tax and emission trading scheme (ETS) decrease morbidity and mortality; therefore, under climate policies, PM 2.5 -related labour loss decreases, and thus increasing labour input triggers an economic boom. Carbon tax generates more health benefits in short term, while health benefits of ETS policy will gradually increase in long term. Hence, we conclude that regarding health benefits, a long-term ETS policy is preferable to a long-term carbon tax. This finding implies that the recently established nationwide ETS market in China is meaningful, as it will generate more health benefits in future. Nevertheless, the quantified health benefits in this paper still cannot compensate GDP loss induced by climate policy implementations, implying that it is a challenging task to unbiasedly model health benefits of climate policies. Hence, we have recommended that the scopes and contents of health benefits should be expanded in evaluations of climate policies. [ABSTRACT FROM AUTHOR]

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

Whether the market-based environmental regulation policy can achieve a win–win situation of economic growth and carbon emission reduction has always been an academic controversial topic. Taking the pilot policy of energy-consuming right trading (ECRT) of China in 2016 as a quasi-natural experiment, this paper uses the difference-in-differences (DID) method to investigate the policy impact of ECRT on the economic performance and carbon emissions of firms. An economy-environment composite index has been conducted for testing double dividend effect of ECRT. The empirical results show that ECRT can improve the economic performance and reduce carbon emissions of firms significantly. The double dividend effect is more significant in high-carbon emission firms, non-state-owned firms and prior to COVID-19 pandemic. ECRT policy has Porter innovation mechanism, in which innovation input is the main contribution of economic dividend effect and green technology innovation is the main contribution of environmental dividend effect. The conclusions of this paper provide empirical evidence and policy implications for realizing the common development of economy and environment, accelerating the process of emission reduction and building a national energy trading market. [ABSTRACT FROM AUTHOR]

Controlling agricultural carbon emissions contributes to achieving peak carbon emissions and carbon neutrality. However, as a conservation management practice of farmland, the impact of No-tillage management (NTM) on agricultural carbon emissions needs to be further discussed. The main purpose of this paper is to assess the direct effect and spatial spillover effect of NTM on agricultural carbon emissions, revealing the regulating mechanism of NTM on agricultural carbon emissions and the combined application of NTM. Results indicate that NTM reduces agricultural carbon emissions, which is significant in the central and western regions, along with the primary grain, corn, and rice production areas, as well as the northern regions of the Huai River. Furthermore, the spatial spillover analysis reveals that the implementation of NTM increases agricultural carbon emissions in neighboring regions, but financial support and cross-regional services can negatively regulate the relationship between NTM and space agricultural carbon emissions. This paper also finds that combining straw-returning technology and NTM reduces agricultural carbon emissions. Building a cross-regional coordination mechanism, an incentive mechanism, and innovating the conservation tillage model is essential for promoting the NTM and achieving agricultural carbon reduction. [ABSTRACT FROM AUTHOR]

Using panel data for 277 Chinese cities, this paper applies a time-varying difference-in-differences (DID) model to empirically test the impact of China's carbon emissions trading scheme (ETS) on urban air quality, and further explores its heterogeneity and the mechanisms involved. The results show that ETS can improve urban air quality. This conclusion remains robust through a series of robustness tests, including PSM-DID estimation, varying window periods, exclusion of significant events, lag phase, and placebo tests. The dynamic effect test indicates that ETS has a continuous and effective effect on improving urban air quality. Mechanism analysis reveals that the degree of marketization can enhance the improvement effect that ETS has on urban air quality. Meanwhile, industrial structure upgrading and green technology innovation are important mechanisms by which pilot ETS policy improves urban air quality. Regional heterogeneity analysis finds that ETS only improves urban air quality in eastern and central regions. [ABSTRACT FROM AUTHOR]

The impact of the carbon emission trading system (ETS) on firms' market competitiveness has been a controversial issue with no consistent theoretical conclusions. The aim of this paper is to explore the impact of the carbon emission trading system on firms' markups using the latest robust staggered difference-in-difference estimation method. The results show that China's carbon emission trading system greatly contributes to the enhancement of firms' market power, as evidenced by a series of robustness tests. In addition, the analysis of the impact mechanism shows that the carbon emission trading system enhances the market power of firms through the low-carbon innovation effect and the market integration effect, while the impact of the environmental cost effect is not obvious. Moreover, the heterogeneity analysis shows that the impact of China's carbon trading system policy on firms' market power is more pronounced, especially for those firms that are actively involved in low-carbon transformation and upgrading, have a stronger cost-shifting capacity, and are more efficient in production. This study provides empirical evidence on how environmental regulations affect firms' market power and offers theoretical guidance for the construction of China's carbon market. [ABSTRACT FROM AUTHOR]

As the issue of global climate change caused by carbon emissions is of great concern, China has proposed achieving its achieve carbon peak goal by 2030. Building carbon emissions account for approximately 50% of China's total carbon emissions. It is crucial to study the time and values of building carbon peaks. In this paper, based on a system dynamics model, logarithmic mean Divisia index model and Monte Carlo simulation, we predict the building carbon peak in China. The following conclusions are obtained: 1) in the baseline scenario, China's building carbon emissions will peak at 5,427 million tons in 2027. In the high-speed development scenario, China's building carbon emissions will peak at 6,298 million tons in 2032. In the coordinated development scenario, the green development scenario, the low-carbon development scenario, and the low-speed development scenario, the peak occurs in 2030 at 5,972 million tons, 5,991 million tons, 5,657 million tons, and 6,329 million tons, respectively. 2) According to the comprehensive simulation, China's building carbon emissions will reach the peak in 2030, with an 80% probability of reaching 5,729–6,171 million tons. [ABSTRACT FROM AUTHOR]

As the problems of "valuing compliance over trading" and quota over-allocation seriously affect the effectiveness of China's national carbon emission trading (CET) market, the quota auction mechanism will be introduced timely to solve these problems. Since implementing the quota auction means reduced free quotas, regulated enterprises are more motivated to pursue low-carbon technology innovation (L-CTI). On these grounds, by establishing a system dynamics model of the national CET market and designing seven scenarios for simulation analysis, this paper investigates the impact of quota auction and L-CTI on the emission reduction effectiveness and cost effectiveness of the national CET market. The results indicate that for the national CET market, introducing quota auction is conducive to decreasing the CET price and improving its liquidity and emission reduction effectiveness, which is one of the quota allocation mechanisms to improve the CET market effectiveness at present. However, the quota auction will increase the abatement cost and reduce the cost effectiveness. Therefore, to improve the institutional performance of China's CET system, it is necessary to conduct L-CTI to alleviate the increasing abatement cost caused by quota auction, and thus improve the emission reduction effectiveness and cost effectiveness of the national CET market. [ABSTRACT FROM AUTHOR]

Provinces (cities and districts) with identifiable boundaries are under intense pressure to reduce emissions as a fundamental unit and research object of carbon peaking and carbon-neutrality goals. Due to the significant variability of regional development, achieving equilibrium between carbon emissions and carbon absorption is challenging, contributing to the difficulty of developing carbon emission reduction and relevant green strategic initiatives in China. Therefore, this paper explored the spatial effect of carbon balance with carbon pressure as the starting point. First, this paper defined the "carbon pressure index" (CPI) of 30 provinces (cities and districts) in China from 2000 to 2019. Second, this paper validated the CPI agglomeration evolutionary characteristics in global and local aspects based on the Moran's index. Third, this paper identified and decomposed the spatial heterogeneity of CPI using the kernel density estimation method and the Theil index, then extracted typical cities to analyze the specific causes. Finally, this paper classified the seven regions in China into four types according to a comprehensive analysis of CPI. The results indicated that China's ecological carbon cycle system was in a serious "carbon overload" state. Thirty provinces (cities and districts) showed significant spatial agglomeration characteristics. The spatial gap of CPI was gradually decreasing nationwide, and the intra-regional differences were the leading cause of CPI levels in China. This can provide policy basis for the improvement of China's balanced development system of regional carbon emission reduction. [ABSTRACT FROM AUTHOR]

Taking the data of 30 provinces (excluding Hong Kong, Macao, and Taiwan regions and Tibet) at the provincial level from 2010 to 2019 as the research object, this paper analyzes the current situation and characteristics of China's agricultural modernization and response to carbon emissions. Agricultural modernization is decomposed into production modernization, management modernization, and ecological modernization. This study uses the spatial Dobbin model to demonstrate the impact of agricultural modernization on carbon emissions and analyzes the impact of agricultural modernization on carbon emissions in the East. The direct effect and spatial spillover effect of the three western regions are to different degrees. The results show that agricultural carbon emissions are spatially dependent. The development of agricultural modernization and transportation of neighboring provinces and cities will have an impact on agricultural carbon emissions in this region. Therefore, under the background of rural revitalization and low-carbon agriculture, this paper further analyzes the impact of agricultural modernization on the spatial distribution of carbon emissions in the eastern, central, and western regions. Recommendations are proposed with a view to giving better play to the process of agricultural modernization. [ABSTRACT FROM AUTHOR]

The shadow price of carbon emissions can measure the marginal output effect under the carbon emission regulation and is also one of the key indicators to construct a low-carbon development path for production units. Currently, international research on shadow price is focused on the industrial and energy sectors. However, in the context of carbon peaking and carbon neutrality targets in China, the use of shadow price to study the cost of reducing emissions from agricultural production, especially forestry fruit industries, is significant. In this paper, we use a parametric approach to construct the quadratic ambient directional distance function. Using the input–output data of peach, we then calculate the environmental technical efficiency and shadow price of carbon emissions from peach production in Guangxi, Jiangsu, Shandong, and Sichuan provinces, and further estimate the values of green output in each province. The results show that (i) the environmental technology efficiency of peach production in Jiangsu province, located in the coastal plain area of eastern China, is the highest among the four provinces, while that in Guangxi province, located in the hilly area of southeast China, is the lowest. (ii) Guangxi province has the smallest carbon shadow price of peach production among the four provinces, while Sichuan province, located in the mountainous area of southwest China, has the largest. (iii) The green output value of the peach production in Jiangsu province is the highest among the four provinces, and that in Guangxi province is the lowest. In order to effectively reduce carbon emissions in peach production without affecting economic benefits, the paper puts forward the following suggestions: for peach-producing areas in the southeast hills of China, it is necessary to increase the application of green environmental technology while reducing the input of production factors in peach production. For peach-producing areas in the northern plains of China, the input of production factors should be reduced. It is not easy for peach-producing areas in the southwest mountains of China to reduce the input of production factors while increasing the application of green technologies. Finally, for peach-producing areas in China's eastern coastal plain, the implementation of environmental regulations for peach production should be gradual. [ABSTRACT FROM AUTHOR]

Collaborative reduction of carbon and air pollutants can more efficiently achieve green technological change, industrial low-carbon transition, and high-quality economic and social development. As a typical environmental policy in China, the pilot carbon Emission Trading Scheme (ETS) has obvious advantages in achieving the collaborative reduction of carbon and air pollutants. Therefore, an evaluation of China's pilot carbon ETS from the perspective of collaborative reduction of carbon and air pollutants is performed in this paper. Compared with previous studies, first, this study innovatively uses the coupled coordination degree (CCD) model to measure the collaborative reduction level of carbon and air pollutants under different scenarios based on the panel data of China's 30 provincial-level regions during 2004–2018. Second, this study uses the DID method to evaluate the impact of China's pilot carbon ETS on the collaborative reduction of carbon and air pollutants and conducts some robustness checks and regional heterogeneity regressions. Third, this study uses the synthetic control method (SCM) further to examine the policy outcomes of the pilot carbon ETS. Scenario analysis shows that attaching importance to reducing air pollution will improve the collaborative reduction effect of carbon and air pollutants. Furthermore, the implementation of China's pilot carbon ETS exerts an effect of roughly 24.7% on reducing carbon, roughly 10.1% on reducing air pollutants, and roughly 22.0% on the collaborative reduction of carbon and air pollutants, ceteris paribus. Regional heterogeneity analysis shows that the impacts of the pilot carbon ETS are significant in all regions, except that the impact on reducing air pollutants in the central region is not significant. In addition, results from SCM indicate that the impacts of the pilot carbon ETS on the collaborative reduction of carbon and air pollutants are significantly efficient in Beijing, Tianjin, Shanghai, Hubei, and Chongqing, while not much efficient in Guangdong and Fujian. The main policy implications include strengthening the top-level design of the ETS in the collaborative reduction of carbon and air pollutants, attaching importance to the governance of air pollution, making the regional governance more targeted, and improving energy efficiency. [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]

Climate change mitigation is a pressing global challenge that requires reducing CO2 emissions without hindering economic growth. Using an extended Kaya identity, Logarithmic Mean Divisia Index (LMDI), and Tapio decoupling indicator, this paper investigates the spatio-temporal variations, drivers, and decoupling of CO2 emissions from economic growth in 150 countries from 1990 to 2019, considering regional disparities and income-based inequalities. The findings reveal increasing CO2 emissions between 1990 and 2019, with notable fluctuations in certain 5-year intervals. CO2 emission growth varied significantly by region, with countries like China, the USA, India, and Japan experiencing rapid increases. Economic growth emerged as the primary driver of CO2 emission growth, and its impact strengthened over time. Population growth also contributed significantly to CO2 emissions, particularly in middle- and low-income countries. The study identifies energy and carbon intensity as crucial mitigating factors that weaken CO2 emissions, offering hope for effective climate change mitigation. Furthermore, the degree of decoupling between economic growth and CO2 emissions varied among countries in the same region, with high-income countries demonstrating stronger decoupling compared to upper-middle-income countries, which accounted for 71% of global CO2 emission increase. These findings underline the imperative of accounting for income levels and regional differences in formulating CO2 emission mitigation strategies. Also, the study emphasizes the pressing necessity for cohesive global coordination to facilitate the transition toward a low-carbon economy. Such collaborative endeavors are paramount in our collective pursuit to combat climate change effectively, safeguarding the well-being and sustenance of our planet for future generations. As policymakers, it is imperative to integrate these insights into decision-making processes to chart a sustainable and resilient course forward. [ABSTRACT FROM AUTHOR]

This paper conducts quasi-experiment design with Chinese listed companies microdata to investigate the effect and mechanism of corporate participation in carbon emission trading market on firm financial performance by using the staggered difference-in-differences method. We show that: a) corporate participation in carbon emission trading market can enhance firm financial performance; b) an increase in green innovation ability and a decrease in strategic choice variance both partially mediate the relationship between carbon emission trading and firm performance; c) executive background heterogeneity and external environmental uncertainty moderate the relationship between carbon emission trading and firm performance in different directions; d) our further study indicates that carbon emission trading pilot policy has a spatial spillover effect on firm financial performance in the neighboring provinces. Therefore, we recommend that the government and enterprises make an effort to further stimulate the vitality of corporate participation in carbon emission trading market. [ABSTRACT FROM AUTHOR]

With intensified urbanization, cities are becoming increasingly important units for addressing air pollution issues. From the perspective of urban agglomeration (UA), in this paper, the influence of functional division on carbon dioxide (CO2) emissions is studied. To explore the spillover effect within UA, a spatial Durbin model is built. The mediating effects of economic growth, industrial structure, and technological progress are examined using the parallel multiple mediation model. An empirical study is carried out on the Yangtze River Delta in China. The results suggest that: at the UA level, functional division and CO2 emissions follows a positive "U-shaped" curve relationship. The level of functional division is located on the left side of this curve. This implies that when the functional division of the Yangtze River Delta improves, current CO2 emission levels will decrease. Within the UA, improving the level of functional division will minimize CO2 emissions of adjacent cities, exerting a significant spillover effect. Functional division imposes a significantly negative influence on CO2 emissions. Moreover, economic growth, industrial structure, and technological progress all exert a significant mediating effect on the influencing mechanism. Functional division within the UA can also significantly reduce CO2 by optimizing these three paths. [ABSTRACT FROM AUTHOR]

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

With the acceleration of urbanization and industrialization, carbon neutrality and peak carbon dioxide emissions have become common sustainability goals worldwide. However, there are few literature statistics and econometric analyses targeting carbon neutrality and peak carbon dioxide emissions, especially the publication trends, geographic distribution, citation literature, and research hotspots. To conduct an in-depth analysis of existing research fields and future perspectives in this research area, 1615 publications from the Web of Science Core Collection, between 2010 and 2020, were evaluated by using three analysis tools, under the framework of the bibliometrics method. These publications are distributed between the start-up (2010–2015) and the stable development (2016–2020) phases. Cluster analysis suggests three areas of ongoing research: energy-related carbon emissions, methane emissions, and energy biomass. Overall, future trends in this field include cumulative carbon emissions, the residential building sector, methane emission measurement, nitrogen fertilization, land degradation neutrality, and sciamachy satellite methane measurement. Finally, this paper further examines the most comprehensive coverage of nitrogen fertilization and the most recent research of the residential building sector. In view of the statistical clusters from 1615 publications, this paper provides new insights and perspectives for climate-environment-related researchers and policymakers. Specifically, countries could apply nitrogen fertilizer to crops according to the conditions of different regions. Additionally, experiences from developed countries could be learned from, including optimizing the energy supply structure of buildings and increasing the use of clean energy to reduce CO2 emissions from buildings. [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]

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

The paper examines the impact of macroeconomic variables on CO2 emissions, very few research studies are available to estimate the asymmetric impact and causality. Because of the significance of asymmetries, this paper examines the asymmetric impact of economic growth, crude oil use, and FDI inflows on CO2 emissions in the India wherein COP (Crude oil price) is comprised as the extra variable. The implicate aggressive growth of selected variables over the period 1990–2020 is also assessed. This study uses the methodology ARDL and NARDL model to determine the macroeconomics variable's effects on CO2 emission over the period 1990-2020. Additionally, also applied the EKC (Environmental Kuznets Curve) hypothesis with an application of ARDL and NARDL model. With help of the ARDL and NARDL model, the study shows the results that a rise in economic growth would reduce CO2 (carbon dioxide) emissions while a decrease in economic growth would raise CO2 emissions which indicates an inverted U-shaped Curved relationship between economic growth and CO2 emissions. The positive and negative shockwaves in COP (crude oil prices) have a satisfactory and substantial impact on CO2 emissions as well. Besides, the crude oil consumption with positive shockwave confirmations has a positive and substantial impact on CO2 emission. In addition, the results of FDI inflows support the pollution heaven hypothesis. In light of these outcomes, this paper also recommended policy implications and future research, the policy implications are where the descending flow of FDI allows limited space to India in FDI selection; however, the existence of emission merging and implementation of carbon pricing may facilitate India in achieving its environmental targets. [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]

In recent years, excessive emissions of carbon dioxide have further intensified global warming, which poses a great threat to human society. The best way to reverse this situation is to take action to equalize the "carbon emissions" with the "carbon absorption," i.e., carbon neutrality (CN). To better understand the evolution and display a broad panorama of CN research, this paper provides a comprehensive bibliometric analysis of publications in the field of CN from 2006 to 2021. We use the Web of Science Core Collection as the data source, and a total of 633 publications have been retrieved. In the paper, we measure the productivity and influence of publications through recognized bibliometric metrics, and visually analyze publications using VOS Viewer and CiteSpace. The analysis results show that China is the most productive country/region. The study illustrates that in order to reach the goal of CN, it is necessary to reduce carbon emissions such as full using renewable energy. Simultaneously, it is also essential to enhance the "negative emissions" of carbon such as taking advantage of carbon sink and carbon capture, utilization, and storage. This paper provides some references for scholars who are interested or research in this field. [ABSTRACT FROM AUTHOR]

Corporate social responsibility (CSR) is becoming increasingly important in the field of corporate sustainability. However, little literature has focused on the relationship between CSR and corporate carbon emissions in developing countries. This paper aims to fill this gap by exploring the relationship between CSR and corporate carbon intensity from the perspective of financing constraints. We examine the mediating effects of financing constraints using a mediating effects model by using Chinese listed companies data from 2011 to 2019. The analysis results of this paper are as follows: (1) CSR can reduce corporate carbon intensity. (2) Financing constraints have a positive mediating role between the two. Namely, CSR can reduce the financing difficulties of enterprises, and enhance carbon–neutral capacity. (3) The carbon emission reduction effect of CSR is different in different life cycles. (4) CSR has a greater impact on the carbon intensity of state-owned enterprises, high-tech enterprises, and heavy polluting enterprises. These facts provide meaningful references for developing countries such as China to promote CSR and carbon governance. [ABSTRACT FROM AUTHOR]

More and more emphasis is placed on the common development of economy and ecological environment in China's development strategy, and one of the key solution is green technology innovation of enterprises. This paper takes the carbon emission trading scheme carried out in China in 2013 as a quasi-natural experiment and uses the data of China's A-share non-financial listed companies and the DID method to empirically test the impact of the scheme on enterprise green technology innovation from the micro level. The results suggest that the carbon emission trading scheme has a significant role in promoting enterprise green technology innovation, mainly through the innovation of green practical patents and alternative energy-based patent. Using a series of robustness tests such as dynamic effect test, placebo test, and PSM-DID, it is found that the results are still valid. Further analysis finds that debt financing will weaken the role of carbon emission trading scheme in promoting enterprise green technology innovation. And the carbon emission trading scheme plays a greater role in promoting green technology innovation in state-owned enterprises, enterprises belonging to areas with strong pollution control intensity and high pollution industry. [ABSTRACT FROM AUTHOR]

There is a broad consensus that information and communication technology (ICT) development contributes to economic growth, but its environmental benefits have not been thoroughly studied. This paper explores the impact and mechanisms of ICT development on manufacturing carbon emissions. We first conducted empirical tests based on panel data from 18 manufacturing sectors in 42 countries from 2000 to 2014. The results show that domestic ICT development reduces manufacturing carbon emissions, but the effect is only significant in sectors with high ICT embedded. Second, technological progress, industrial internal structure upgrading, energy consumption intensification, and low carbonization are the main channels for ICT development and embedding to reduce manufacturing carbon emissions. Third, the carbon emissions from manufacturing, which are deeply embedded by ICT, will decrease as the position of ICT forward GVCs improves, and increase as the position of backward GVCs increases. In addition, ICT development has a more significant impact on reducing carbon emissions in high-tech manufacturing. This paper has enriched research on the environmental benefits of ICT development and has been informative and insightful for countries in formulating industrial development policies and implementing the Paris Agreement. [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]

Global warming has endangered the natural ecosystem's balance, as well as human existence and development, and it is mostly caused by carbon dioxide. Identifying carbon emission characteristics and predicting carbon emission reasonably is helpful to provide indication for the effective design of emission reduction path. The most literature use a single prediction model; this paper predicts carbon emission using a number of strategies based on previous research. Considering the prediction accuracy, advantages, and disadvantages of each method, a new method combining autoregressive integrated moving average (ARIMA) model and NAR neural network (NAR-NN) is proposed; in addition, this paper attempts to explain the carbon emission characteristics and emission reduction paths of each region from the new perspective of clustering. First, the results show that China's carbon emission features can be divided into four categories: low-carbon demonstrative type, low-carbon potential type, high-carbon developed type, and high-carbon traditional type. Moreover, low-carbon demonstrative type includes merely Beijing and Shanghai, low-carbon potential type is distributed in the southeast coastal areas of China, the high-carbon developed type is mainly distributed in Northeast China, and the western region basically belongs to high-carbon traditional type. Second, ARIMA model and NAR-NN are the two best methods in terms of prediction effect, and the combined model has better prediction effect than the single model. Third, carbon emissions in most regions of China will increase in the next few years; the time of carbon peak in the east is earlier than that in the west regions of China. Beijing will probably be the first region in China to complete the carbon peak. Besides, there is a certain correlation between the carbon peak time and the type of carbon emission in each region. [ABSTRACT FROM AUTHOR]

In the context of the "peak carbon dioxide emissions" and "carbon neutrality" strategic goals, how green finance can prompt private enterprises to achieve green upgrading has become an important issue to be solved. This paper empirically examines the effect mechanism of green credit policy on private enterprises' green innovation by using the difference-in-differences model based on the manually collected green patent data and matching financial data of Chinese listed private enterprises from 2009 to 2019. It is found that the implementation of green credit policy has a significant negative impact on the quality of green innovation of heavy-polluting private firms relative to non-heavy-polluting private firms, and this conclusion is still valid after replacing the explanatory variables, expanding the sample range, changing the model setting, and excluding the interference of other policies during the sample period. The results of the mechanism suggest that green credit policy negatively affects the quality of green innovation of heavy-polluting private firms by limiting their access to financing for loans and the capital market. Further study finds that commercial banks can reduce their non-performing loan ratio and increase their revenue growth rate by extending green credit funds to improve their business performance. It provides insights for better implementation of green credit policy and promotion of green economy development. [ABSTRACT FROM AUTHOR]

To achieve China's "double carbon" goal, it is necessary to make quantitative evaluation of the power grid enterprises' contribution to carbon emission reduction. This paper analyzes the contribution of power grid enterprises to carbon emission reduction from three points: power generation side, power grid side, and user side. Then, PLS-VIP method is used to screen the key influencing factors of carbon emission reduction contribution of power grid enterprises from three aspects: consumption of clean energy emission reduction, reduction of line loss emission reduction, and substitution of electric energy. Based on GA-ELM combined machine learning algorithm, we establish an intelligent evaluation model of power grid enterprises' carbon emission reduction contribution. Furthermore, according to the distribution law of key influencing factors, this paper uses Monte Carlo simulation method to calculate the contribution of power grid enterprises to carbon emission reduction by scenario, so as to evaluate the contribution of power grid enterprises to carbon emission reduction. Finally, combined with the relevant data of power grid enterprises from 2003 to 2019, this paper makes an empirical study on the completion of carbon emission reduction contribution and the promotion path. [ABSTRACT FROM AUTHOR]

To cope with climate change, China commits that it will strive to achieve carbon peaking by 2030. Using the Cointegration model and the Markov Chain model, this paper forecasts China's carbon emissions during 2019–2030 in six scenarios, and assesses the contribution of optimizing the energy mix to China's carbon peaking. The research obtains three main conclusions. Firstly, optimizing the energy mix will contribute to achieving China's carbon peaking. In the economic slow-growth scenario, taking China's planned target of energy mix (PTEM) into account, the carbon peaking year will be brought forward from 2028 to 2023. In the economic medium-speed-growth scenario, optimizing the energy mix will make China achieve carbon peaking in 2028. Without considering the PTEM, however, the carbon emissions will not peak before 2030. In the economic fast-growth scenario, the peaking year will not occur whether considering the PTEM or not, but the growth rate of carbon emissions with the PTEM will be far lower than that without considering the PTEM. Secondly, in all three economic growth scenarios, optimizing the energy mix will largely reduce the growth rate of carbon emissions, and thus significantly reduce the peak value of carbon emissions. Thirdly, optimizing the energy mix has a negative adjusting effect on the impact of economic growth on the growth rate of carbon emissions, and the negative effect rise as the economic growth rate increases. [ABSTRACT FROM AUTHOR]

In-depth research on the spatiotemporal patterns and evolution trend of urban land use carbon emission intensity (ULUCEI) can reveal the internal relationship between urban land use and carbon emissions, which is crucial for achieving carbon emission reduction and "double carbon" targets. This paper proposed a conceptual framework of ULUCEI; the methods of kernel density estimation (KDE), exploratory spatial data analysis (ESDA), and spatial Markov chains were adopted for exploring the spatiotemporal patterns and evolution trend of China's ULUCEI from 2000 to 2017. The following conclusions are drawn through research. (1) There was an increasing trend in ULUCEI in China from 0.102 in 2000 to 0.283 in 2017. From the regional perspective, the ULUCEI in the eastern region is markedly higher than that in the central and western regions. Moreover, the results of nuclear density estimation indicate that China's ULUCEI shows an obvious upward and polarized trend. (2) China's ULUCEI shows a positive spatial autocorrelation. The types of spatial agglomeration include "high-high" agglomeration, "high-low" polarization, "low-high" collapse, and "low-low" homogeneity, and there are obvious disparities in the distribution rules of cities with different spatial agglomeration forms. (3) China's ULUCEI presents strong stability and "club convergence" trend. Moreover, spatial factors significantly affect the dynamic transition of China's ULUCEI, and its effect on the shifting upwards gradually enhances with increasing lag type. This paper therefore suggests that policymakers should formulate differentiated urban land low-carbon use models and carbon emission reduction policies to reduce ULUCEI. [ABSTRACT FROM AUTHOR]

This paper analyzes the impacts of the per capita income, the per capita energy consumption, and the trade openness on the level of per capita carbon emissions in the panel dataset of 35 Organization for Economic Cooperation and Development (OECD) countries over the period 1960-2013. Along with the nominal trade openness, the paper uses a different trade openness measure, so called as the 'trade potential index' (TPI). To the best of our knowledge, this is the first paper that uses the TPI in the empirical environmental Kuznets curve (EKC) hypothesis literature. The paper finds that the EKC hypothesis is valid and there is an 'inverted-U' relationship between the income and the carbon emissions. In addition, the paper observes that there is a positive effect of the energy consumption on the carbon emissions. Furthermore, the results indicate that both trade openness measures are negatively associated with the carbon emissions in the OECD countries in the long run. [ABSTRACT FROM AUTHOR]

Current studies do not provide a consensus on whether digital technology innovation can reduce enterprise carbon intensity despite the rise of the digital economy. This paper examines the role and influence pathway of digital technology innovation on enterprise carbon intensity using data from A-share listed enterprises in China's manufacturing industry from 2012 to 2021. The findings indicate that (1) digital technology innovation has been found to significantly reduce enterprise carbon intensity, as confirmed by numerous robustness and endogeneity tests. However, its inhibitory effect on carbon intensity shows a marginal decreasing trend. (2) In the heterogeneity analysis, it was found that digital technology innovation significantly reduces the carbon intensity of consuming coal, coke, kerosene, and diesel. From various perspectives, including enterprise, industry, and external environment, there are significant differences in the carbon reduction effects of digital technology innovation. (3) The analysis of impact paths reveals that digital technology innovation can affect enterprise carbon intensity through three paths: improving productivity, enhancing green innovation efficiency, and adjusting energy consumption. (4) Upon further analysis, it was discovered that the spillover effect of digital technology innovation is more pronounced in the industry cohort of enterprises. Additionally, digital technology innovation plays a positive role in enhancing enterprise ESG performance. The paper's findings offer empirical evidence and decision-making references for the government to develop reasonable policies for reducing carbon emissions, promoting green and low-carbon enterprise transformation, and actively and steadily achieving the goal of carbon peaking and carbon neutrality. [ABSTRACT FROM AUTHOR]