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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]

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Typical public institutions such as government offices, hospitals, and schools play important leading and exemplary roles in the green and low-carbon development of the whole society. This paper analyzes the business and energy consumption characteristics of public institutions, as well as the characteristics of personnel travel, and constructs a carbon accounting model for public institutions. It innovatively proposes a methodology for carbon accounting of personnel travel related to public institutions and validates and analyzes it using a comprehensive hospital as an example. The paper analyzes the carbon emission characteristics of various energy types, systems, and types of travelers in hospitals, provides schemes for the transformation of main energy systems, and corresponding emission reduction effects, thereby providing technical support for the full-chain carbon accounting of public institutions. Additionally, this paper explores the carbon reduction pathways for hospitals to support the peak carbon and carbon neutrality goals of public institutions, and promote the high-quality development of public institutions in China. [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]

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]

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]

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]

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 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]

As global climate change becomes increasingly severe, energy technology innovation has become a key means of coping with the climate crisis and realizing green and low-carbon development. However, existing literature rarely examines the effects of carbon emission reduction policies based on the perspective of energy technology progress for both short-term economic fluctuations and long-term equilibrium. This paper introduces the fossil energy technology sector and the renewable energy technology sector into the dynamic stochastic general equilibrium (DSGE) model, and compares the effectiveness of the carbon emission cap policy, the fossil energy technology subsidy policy, and the renewable energy technology subsidy policy under the framework of China's carbon trading market in promoting macroeconomic growth and controlling pollutant emissions. We found that in long-term, the emission reduction effect of the carbon emission cap policy falls short of the other two policies, and subsidizing fossil fuel technologies is more cost-efficient comparatively. The government expenditure shock can all stimulate macroeconomic growth with crowding out of private investment and household consumption, whereas the energy technology research productivity shock leads to a decline in total output and an increase in renewable energy technology demand. In addition, pollutant emissions are pro-cyclical under the impact of total carbon policies and counter-cyclical under the impact of energy technology subsidy policies. This article constructs a multi-technology sectoral dynamic stochastic general equilibrium model, expanding the research perspective and theoretical framework for evaluating carbon emission reduction policies. At the same time, it proves the importance of the government to implement the phased energy technology subsidy policy while implementing the carbon emission cap policy, which provides important enlightenment for the implementation and adjustment of carbon emission reduction policy. [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]

Public institutions, emblematic of public infrastructure, exhibit extensive reach and operational scope, positioning them as vanguards in China's dual carbon initiatives and serving as exemplars. Electricity and natural gas predominantly fuel the operations of public institutions. Notably, the fixed commute routes and consistent procurement patterns of office personnel yield a standardized energy consumption profile within these entities. Researching carbon emissions related to commuting and evaluating procurement strategies for reducing carbon footprints in public institutions demonstrate a precision-tailored approach. This paper, through an analysis of the energy consumption characteristics, utilization structure of public institutions, and the commuting behaviors and procurement practices of office personnel, establishes a bespoke carbon accounting model specifically designed for public institutions, seamlessly embedded within a comprehensive platform. By providing fundamental methodological frameworks and advanced technological foundations for carbon accounting in public institutions across China, this work propels the nation's efforts towards carbon peak and ultimately carbon neutrality. [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]

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]

With the proposal of the carbon neutrality target, China's attention to carbon emissions has been further enhanced. Effective prediction of future carbon emissions is important for the formulation of carbon neutralization target and action plans in the region. Many factors affecting carbon emissions, cause their development trends may be nonlinear. To forecast the carbon emissions of coal and natural gas in the industrial sector more accurately, a new MGM(1,m,N|γ) model considering nonlinear characteristics is proposed in this paper. The new model introduces power function γ as nonlinear parameter, and the γ value is solved by nonlinear constraint function. We further deduce the simulation and prediction formula and then apply the improved model to the carbon emission forecast. The comparisons show that the nonlinear parameters can modify the trend of sequences and improve the prediction accuracy, which verifies the validity of the model. Finally, according to the influencing factors and forecast results, this paper analyzes the causes of high carbon emissions and puts forward reasonable suggestions for China's carbon governance. [ABSTRACT FROM AUTHOR]

Evaluating the effects of China's carbon emission trading scheme (ETS) is crucial for the coordinated development of Chinese cities. Therefore, based on the panel data of 242 cities in China from 2008 to 2019, this paper uses the multi-period difference-in-difference (DID) model to comprehensively evaluate the impact of carbon market on the coordinated development of cities from the perspectives of carbon market policy and carbon market efficiency, and then analyzes the mechanism and heterogeneity of the effect of carbon market efficiency. The results show that both carbon market policy and carbon market efficiency can promote the coordinated development of cities. Science and education expenditure plays a significant intermediary role in the impact of carbon market efficiency on the coordinated development of cities. The heterogeneity test finds that the stricter the performance penalty system, the higher the level of urban coordinated development, and the stronger the effect of carbon market efficiency. The findings of this paper provide policy recommendations for further improving the construction of China's pilot and national ETS and enhancing the coordinated development of Chinese cities. [ABSTRACT FROM AUTHOR]

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

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

This paper focuses on the spatiotemporal evolution characteristics, as well as the driving factors, of carbon emissions in the prefecture-level cities in the Yellow River Basin (YB). The paper's findings will aid in promoting ecological conservation and high-quality development in the region. The initiatives undertaken in the YB are a significant national strategy towards achieving carbon peaking and carbon neutrality. To fully investigate the spatiotemporal evolution process, as well as the typical characteristics of their carbon emissions, conventional, and spatial Markov transition probability matrices were developed utilizing YB's panel data for 55 prefecture-level cities from 2003 to 2019. The generalized Divisia index decomposition method (GDIM) cleverly uses this data to conduct a complete analysis of the dynamics and driving processes influencing the change in carbon emissions in these cities. However, the evolution of carbon emissions in prefecture-level cities has reached a point of stability that maintains the original state, making it challenging to make meaningful short-term progress. The data indicates that prefecture-level cities in the YB are emitting more carbon dioxide on average. Neighborhood types in these cities significantly influence the transformation of carbon emissions. Low-emission areas can encourage a reduction in carbon emissions, whereas high-emission areas can encourage an increase. The spatial organisation of carbon emissions exhibits a "high-high convergence, low-low convergence, high-pulling low, low-inhibiting high" club convergence phenomenon. Carbon emissions rise with per capita carbon emissions, energy consumed, technology, and output scale, whereas it falls with carbon technology intensity and output carbon intensity. Hence, instead of enhancing the role of increase-oriented variables, prefecture-level cities in the YB should actively engage these reduction-oriented forces. The YB's key pathways for lowering carbon emissions include boosting research and development, promoting and applying carbon emission reduction technologies, lowering output carbon intensity and energy intensity, and improving energy use effectiveness. [ABSTRACT FROM AUTHOR]

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

Industry is a core area to achieve the carbon neutrality target for most developing countries including China. Hence, it is of great practical significance to study the spatio-temporal characteristics of China's industrial carbon intensity and its evolution. The exploratory spatial data analysis methods were adopted to conduct global and local spatial correlation analysis in this paper. The result shows that (1) the industrial carbon emission intensity decreases year by year, with high industrial carbon emission intensity in the West and low in the East. (2) There is a correlation in the spatial distribution of industrial carbon intensity, with the Moran index experiencing the stage of descending first and then ascending. (3) The local spatial clustering of industrial carbon intensity is obvious. (4) Half of the provinces have experienced a leap, with the majority located in the western part of China. Based on these findings, it is concluded that industrial emission reduction policy synergy between provinces is particularly important, such as low-carbon industrial production policy and green industry development policy. [ABSTRACT FROM AUTHOR]

To reduce industrial carbon emissions, various industries have been seeking ways to reduce their own emissions. Implementing carbon trading system measures is one way to effectively control industrial carbon emissions. However, in different industrial sectors, carbon trading systems have different impact. The 14-year provincial panel data (2005–2019) were analyzed by using the propensity score matching and the difference-in-difference model to evaluate the role of the emission trading system (ETS) in reducing emissions from different industries. According to the study, ETS has reduced carbon emissions from the agricultural production sector by 1.6876%. Secondly, it also had a significant inhibitory effect on the manufacturing sector, about 24.0489. Mining, electricity production, wholesale and other industrial sectors are insignificant disincentives, and construction and transportation are insignificant facilitators. China's ETS, therefore, mainly acts as an inhibitory force for different industries, which can effectively reduce their carbon emissions. [ABSTRACT FROM AUTHOR]

The realisation of global carbon neutrality is crucial for combating climate change. As the largest emitter, China declared to achieve carbon neutrality by 2060. However, substantial changes in the energy structure are far from being achieved. Using time series data from 2001 to 2019 and the ARDL-ECM method, this paper explored the effectiveness of climate policies in controlling China's carbon emissions. The results show that economic and technical factors such as economic growth and energy structure are the determinants of carbon emissions. A green paradox is shown since increasing climate policy density does not significantly reduce carbon emissions. The main regulatory gaps in China's climate governance include weaknesses in the rule of law, lack of accountability, and insufficient arrangements for equitable energy transitions. A binding legal system is necessary to realise absolute reduction and secure carbon neutrality, especially one including specific climate change legislation, binding reduction targets, and combining energy justice with regulatory efficiency. [ABSTRACT FROM AUTHOR]

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

Carbon emissions have risen in line with China's economic expansion. The key to sustainable development is finding a way to strike a balance between economic expansion and environmental protection, so improving carbon emission efficiency is vital. This paper uses provincial data from 2010 to 2020 to account for total carbon emissions using the emission factor method and obtains carbon emission efficiency data on this basis. A dynamic spatial Durbin model is then used to empirically test the possible influencing factors. The results show that, firstly, the growth rate of total carbon emissions is generally in line with the growth rate of GDP, indicating that there is no 'decoupling' in the economic system. Second, regional carbon emissions and carbon emission efficiency are not necessarily related. Thirdly, there is a clear spatial effect on carbon emission efficiency. The eastern region has the highest carbon emission efficiency, the western region has the lowest, and the northeastern and central regions have little difference in carbon emission efficiency. Further spatial and temporal migration analysis reveals that five provinces have made the migration between 2010 and 2020. Fourthly, in the short term, the direct and indirect effects of the factors affecting carbon emission efficiency are insignificant, but in the long term, most of the factors have significant direct and indirect effects on carbon emission efficiency. Finally, based on the above research findings, this paper makes policy recommendations. [ABSTRACT FROM AUTHOR]

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

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

As a noteworthy initiative of financial supply-side reform to precisely support the green development system, can green finance (GF) help achieve the dual goals of "carbon peaking" and "carbon neutrality"? Using data from China's provincial panel between 2007 and 2019, this paper measured the green finance index by the entropy method and the carbon emission efficiency (CEE) with carbon emission as the non-desired output by the Super-SBM model. Then, the influence of GF on CEE was empirically investigated by the dynamic panel model and the spatial Durbin model. The findings show that GF can significantly improve CEE and has a positive spillover impact on CEE in provinces with close economic ties; the upgrading of the industrial structure is a key mediator in the transmission of GF to CEE; and regional heterogeneity analysis finds that GF notably improves CEE in eastern, high development levels of economic and GF regions. The research can offer some theoretical and empirical references for green finance to contribute to low-carbon economic growth. [ABSTRACT FROM AUTHOR]

This paper explores the effect mechanism of population aging on carbon dioxide emissions using provincial panel data in China from 2005 to 2019 and examines how aging affects carbon dioxide emissions through stepwise regression test and Sobel test respectively by constructing a multiple mediating effect model. The following conclusions have been drawn: (1) the results of the baseline regression show that population aging has a significant inhibitory effect on carbon emissions. (2) The results of intermediary effect test show that the intermediary effect of population aging through technological progress, industrial structure, consumption level, and consumption structure is significant. (3) The results of heterogeneity test show that the mediating effect of technological progress is not significant in the eastern region, central region, and western region, and the mediating effect of industrial structure and consumption structure is significant in the eastern region and central region, and the mediating effect of consumption level is significant in the eastern region and western region. (4) The results of the robustness test also verify the mediating effect conclusion once again and prove the robustness of the results. Overall, as an aging society country, China should take the impact of aging into consideration more in the process of achieving emission peak and carbon neutrality. [ABSTRACT FROM AUTHOR]

Industrial structure low-carbon restructuring is an essential channel to accelerate China's economic growth and fulfilling carbon emission reduction goals. Whether carbon emission trading pilot policy, as an influential carbon reduction instrument, fosters industrial structure low-carbon restructuring is of major significance to green economic development. This paper empirically investigates the shock of the carbon emission trading pilot policy on industrial structure low-carbon restructuring using the differences-in-differences (DID) and synthetic control method (SCM). Statistics reveal that sectors with low carbon productivity, such as electricity, steam, and hot water production and supply, ferrous metal smelting and pressing, etc., and sectors with high carbon productivity, such as electrical equipment and machinery, electronics and telecommunication equipment, etc. The industrial structure did not develop a stable trend of change before the 12th Five-Year Plan, but a stable trend of low-carbon restructuring emerged after such a period. Carbon emission trading pilot policy significantly facilitates industrial structural low-carbon restructuring. Carbon emission trading pilot policy inhibits energy-intensive industries in the industrial sector significantly, which promotes industrial structure low-carbon restructuring. Therefore, policymakers need to develop a nationwide carbon emission trading market that includes more industries to guide production factors to industrial sectors with high carbon productivity for industrial restructuring and dual carbon goals. [ABSTRACT FROM AUTHOR]

The China government focuses on changes in carbon emission efficiency with establishing carbon emission trade exchange (CETE). It is meaningful to study whether the pilot CETEs can facilitate the betterment of carbon emission efficiency. Using the data of 283 cities in China within 2006–2019, this article gauges the carbon emission efficiency with the SBM-DEA model. This paper analyzes the impact of China's pilot CETEs, which was gradually launched from 2013 to 2014, on carbon emission efficiency through the time-varying difference-in-difference (DID) model. Finally, the mediating effect model is further used to analyze the impact mechanism of the pilot CETEs on carbon emission efficiency from the perspectives of innovation investment and pollution control investment. The results reveal that the carbon emission efficiency of each city from 2006 to 2019 is not very ideal. All cities have some room to facilitate the carbon emission efficiency. The pilot CETEs have increased the carbon emission efficiency and reduced carbon dioxide emission. The policy influences the carbon emission efficiency through innovation investment and pollution control investment, which represent long-run and short-run mechanism respectively. [ABSTRACT FROM AUTHOR]

As more attention is given to climate change and sustainable development in China, enterprises start to care about carbon emissions related to their supply chains. One important issue faced by an enterprise is to select a logistics provider who can provide a high-quality service with low carbon levels. To solve this issue, this paper proposes a selection criterion from the perspective of low carbon levels based on previous studies. The selection criterion consists of comprehensive strength, financial status, market competitiveness, development potential and low carbon level. Next, this paper applies a combined method of information entropy and grey correlation vlsekriterijumska optimizacija i kompromisno resenje (VIKOR) model to evaluate the proposed selection criterion. Subsequently, this paper took company S and its four logistics providers as a case study to check the applicability of our proposed selection method and to illustrate how to use it. Sensitivity analysis and comparative analysis are also conducted. Related managerial insights are also proposed based on the evaluation results. One finding of this paper is to establish a decision-making framework to evaluate logistics suppliers under the new background of 'emission peak and carbon neutrality'. [ABSTRACT FROM AUTHOR]

China states to build new power system dominated by new energy power to promote the targets for peaking carbon emissions by 2030 and achieve carbon neutrality by 2060. Peaking regulation ancillary services provided by coal-fired power units is an essential solution to mitigate the volatility and instability of large-scale renewable energy for China's specific power mix. However, when the coal-fired power units operate at a low power output, the intensity of both coal consumption and carbon emissions gradually rises with the falling output rate. Moreover, cutting down the power output of coal-fired units frequently will damage the technical life. Given the impacts of power market reform and carbon mitigation targets, whether to participate in the energy market or the peaking regulation ancillary service market is an urgent issue for coal-fired power units. Considering the discrepancy in costs and benefits of various units at different output rate, this paper proposes a multi-objective optimization model to solve the issue from the perspective of the coal-fired power generators, in which both economic profit and carbon reduction goals are coordinated. Sequential quadratic programming is adopted to solve the nonlinear optimization problem. In order to study the difference in the decisions made by varied technical units, 7 different types of units are analyzed in the case study. The scenarios analysis indicates that large-capacity and new coal-fired power units are better to participate in energy market since it can give full play to the advantage of higher generation efficiency, while the small-capacity ones are suitable to provide flexible service in the peaking regulation ancillary service market. Besides, simple low-carbon objective will burden the cost of coal-fired power units and challenge the sustainable transition of power system. Hence, the power system should balance both economic profit of generators and national carbon mitigation targets during the low-carbon transition. [ABSTRACT FROM AUTHOR]

The increasing carbon emissions have been a major concern for most countries around the world. And as a result, every country is concerned about developing appropriate strategies to curtail it. As a major economy and the largest carbon emitter in the world, China has pledged to reduce the carbon intensity by 60–65% by 2030, compared with 2005 levels, and achieve carbon neutrality before 2060. Therefore, the analysis of the impact of China's carbon intensity is becoming an increasing important topic. Due to the spatial heterogeneity of carbon intensity, various spatial econometric models have been applied in this field. However, the existing literatures failed to consider the cross-products of relevant factors. This paper constructs our dynamic general nesting spatial panel model (GNS) with common factors to deal with the dilemma, and examines the direct and spatial–temporal spillover effects of industrial structure, GDP per capita, investment in anti-pollution projects as percentage of GDP and energy price on carbon intensity in China over the period 2003–2017. Our analysis shows that: (1) China's carbon intensity showed the spatial agglomeration and temporal "inertia" from 2003 to 2017. (2) From the time dimension, the long-term effect of industrial structure first increased and then gradually decreased. (3) From the spatial dimension, industrial structure and investment in anti-pollution projects as percentage of GDP accounted for the main spatial heterogeneity. Furthermore, this paper attempts to provide policy implications to help reduce carbon intensity and achieve carbon neutrality in 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 carbon emissions of the beer industry have always been a concern. To reduce environmental pollution, this paper systematically calculates the carbon emissions of the beer supply chain and studies the optimization of carbon emissions reduction through scenario simulation. In this study, the boundary of the beer supply chain carbon emissions system is constructed. The scenario simulation and simulation analysis are carried out based on five factors: water recycling utilization rate, power generation mode, weight–volume ratio, recovery ratio, and transportation mode. To obtain the optimal scheme of economic cost and emissions reduction, the cost of the beer supply chain is analyzed under the condition of carbon trading. The results show that the proportion of carbon emissions in each link of the beer supply chain is production, packaging, transportation, and storage, which are 59.58%, 22.27%, 17.67%, and 0.5%, respectively. The improvement of the water recycling utilization rate of manufacturing enterprises can reduce the overall carbon emissions of the supply chain, and the effect is obvious. The highest proportion of carbon emissions in the packaging link is the bottle consumption stage (22.43%). Raw materials transportation accounts for the highest proportion of total carbon emissions in transportation (63.73%). The waterway/railway ratio will be increased to 0.6/0.4, and the carbon emissions in the supply chain will be reduced by 5.7%. In the context of carbon trading, when the carbon trading price is higher than 49.16 yuan/ton, enterprises can achieve a win-win situation in reducing emissions and maintaining positive economic growth by the measures given in the paper. [ABSTRACT FROM AUTHOR]

A significant industrial transformation in China's tourism sector is currently taking place in response to carbon peak and carbon neutrality targets. This paper applies the data envelopment analysis (DEA) model to calculate the efficiency of the tourism industry under carbon emission constraints and further investigates its influencing factors through the Tobit regression. The results are as follows: (1) The tourism efficiency under carbon emission constraints of China from 2000 to 2019 showed a trend of first rising and then declining, and there were obvious regional differences; (2) from 2000 to 2019, the total factor productivity of tourism in China increased significantly, while the contributions of technical progress, pure technical efficiency, and scale efficiency decreased sequentially; (3) the factors of industrial structure, transportation convenience, economic development level, degree of opening to the outside world, and the level of scientific and technological development have varying degrees of influence on tourism efficiency. Based on the analysis results, this paper puts forward several policy suggestions on tourism efficiency and low-carbon development. The findings of this paper have some bearing on developing nations' efforts to boost tourism efficiency and realize high-quality industry growth within the framework of sustainable development. [ABSTRACT FROM AUTHOR]

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

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

Electric power industry, as one of the main industries leading to the increase of China's carbon emissions, accounts for about 40% of the total carbon emissions. It is of great practical significance to study the influencing factors of carbon emission decoupling index in power industry and put forward relevant policy suggestions. Based on the decoupling index of China's electric power industry from 1995 to 2018, this paper explores the influence of each index on the decoupling index through the autoregressive- distributed lag model. It turns out that the policy will significantly change the rate of change of carbon emissions and the rate of economic growth, but the impact of the policy is extremely short-lived; power generation structure, environmental regulations, and total lighting value at night play a positive role in promoting the decoupling index, while thermal power fuel efficiency and power generation conversion ratio play a negative role in inhibiting the decoupling index. In addition, the influence of power generation structure, environmental regulations, and the total value of night light on decoupling index also has a lagging and cumulative effect. Therefore, we propose targeted policy recommendations for policy formulation, green development, and low carbon construction in China's power industry from different perspectives based on the findings of the study. [ABSTRACT FROM AUTHOR]

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

This paper uses green innovation and environmental pollution as the mediating variables to construct a mediating effect model to investigate whether China's carbon emission trading policy can improve regional eco-efficiency by reducing regional environmental pollution and stimulating green innovation. This study is based on panel data from 30 provinces and municipalities directly under China's central government and autonomous regions from 2003 to 2019. The eco-efficiency of these provinces is measured using the super-efficiency DEA model and the difference-in-difference method (DID). The results show that (1) China's emission trading policy significantly improves regional ecological efficiency and the per capita GDP. The improvement can effectively improve regional ecological efficiency. (2) The mediating effect of green innovation and environmental pollution is significant. That is, China's carbon emission trading policy further improves regional ecological efficiency by stimulating more green innovation and reducing the synergy brought by environmental pollution. (3) There are differences in the feedback of this impact mechanism between different regions: It shows the characteristics of the western region being more significant than the eastern region. The central region has no significant effect. The research conclusion can provide a policy reference for the subsequent unified promotion of the construction of a carbon emission trading market nationwide and a theoretical basis for helping to achieve the "dual carbon" goal. [ABSTRACT FROM AUTHOR]

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

To achieve carbon peak targets, realize carbon neutrality vision, and tackle global climate change, China must improve the carbon emission performance at the city level. Based on the carbon emission performance of 191 prefecture-level cities in China from 1997 to 2017, this paper analyses the evolution characteristics of urban carbon emission performance from three aspects: the overall spatial and temporal evolution, the differences according to both region and city size, and the differences among clusters categorized by carbon emission performance at the city level. This paper also reveals the impact of the social and economic transition on China's carbon emission performance. The results show that: (1) The overall level of carbon emission performance of Chinese cities is low, and there is a downward trend during the study period. The differences in carbon emission performance among cities are convergent, but there is a wide gap between high and low values. (2) The carbon emission performance of cities in eastern coastal areas is higher than that in non-coastal areas cities. Large urban agglomerations and economically developed regions, such as provincial capitals, are the agglomeration areas of high urban carbon emission performance values. (3) The carbon emission performance level of cities with similar sizes will converge. At the same time, such changes will enhance the differences among carbon emission performances at the city level within the same region. (4) Cities that belong to high urban carbon emission performance clusters are mainly distributed in the eastern region. Such cities are classified into large cities, supercities, and megacities. Compared with low urban carbon emission performance clusters, cities in high urban carbon emission performance clusters show a higher proportion in the medium-high level and high level of carbon emission performance. Moreover, cities in high urban carbon emission performance clusters are more likely to improve theirurban carbon emission performance. (5) The economic agglomeration effect, industrial structure adjustment and carbon intensity reduction have a significant impact on improving urban carbon emission performance. Population agglomeration has an incremental effect, and the anticipated benefits of environmental regulation have yet to be fully realized. The impacts of different clusters and different regions are variable. Finally, this paper advances policy enlightenment according to its research findings. [ABSTRACT FROM AUTHOR]

Climate change intensifies, so does the need to reduce carbon emissions to achieve the goal of being "carbon neutral" for China. This paper focuses on carbon emission prediction and constructs a comprehensive model integrating least absolute shrinkage and selection operator (LASSO), principal component analysis (PCA), support vector regression (SVR), and differential evolution-gray wolf optimization (DE-GWO). Firstly, LASSO is used for feature selection, and important information is extracted from various influencing factors to find out what have a great impact on carbon emission. Principal component analysis is used to extract the features of the remaining variables to avoid missing information caused by feature selection. Secondly, DE-GWO algorithm is used to optimize the parameters of SVR to improve the prediction accuracy. The scenario analysis and prediction algorithm are combined to predict China's carbon emissions. The results show that (1) coal and oil consumption, plate glass, pig iron, and crude steel production are important factors affecting carbon emissions; (2) the use of PCA to comprehensively consider the impact of remaining factors on carbon emissions has a positive influence on carbon emissions prediction; and (3) DE-GWO optimized SVR has higher prediction accuracy than other algorithms. [ABSTRACT FROM AUTHOR]

China is the largest energy consumer and CO2 emitter in the world. Industrial ecologicalization (IE) as an effective way to reduce carbon emission and achieve green growth is vital for China to strive to peak carbon dioxide emissions before 2030 and achieve carbon neutrality before 2060. Thus, it is necessary and urgent to evaluate the industrial ecologicalization level (IEL) in China. Based on the connotation and characteristics of IE and PSR model, this paper first establishes a comprehensive evaluation index system of the IEL and then uses the global entropy method (OEM) and spatial data analysis (ESDA) to analyze the dynamic evaluation, regional disparity, and spatial correlation of IEL in China. The results show that: (1) The innovation support and the structure optimization are the main stimulus in improving the IEL in China, whose weights of indexes have reached 0.263 and 0.268. (2) The overall IEL has improved steadily in China but differs significantly among provinces during the research period. (3) The regional disparity of IEL presents the Eastern region is leading, whereas the Middle and Western regions are lagging from a geographical perspective; the Northern Coast and Eastern Coast have ranked the top two compared with other six economic regions. (4) The five provinces, namely Beijing, Tianjin, Shanghai, Jiangsu, and Zhejiang, constitute the main agglomeration areas of IEL in China based on the spatial correlation features. The findings of this paper cannot only provide a theoretical basis and practice reference for IEL evaluation but also benefit more focused policy-making of the sustainable development in China. [ABSTRACT FROM AUTHOR]

In recent years, China had released various environmental regulations in order to respond climate change and corresponding environmental issues. However, due to imbalanced economic development and industrial structure, different Chinese regions had different enforcement levels on environmental regulations, which led to the regional transfer of pollution-intensive industries. To study the regional disparities on carbon emission transfer, this paper used the propensity score matching–difference in differences method (hereinafter abbreviated as "PSM-DID") to evaluate the mechanism between carbon trading pilot policies and the transfer of pollution-intensive industries. Panel data on 30 Chinese provinces were used to test the validity of the "pollution haven hypothesis," covering the period of 2010–2018. The empirical results showed that under the constraints of established environmental regulation, the pilot policy promoted the transfer of pollution-intensive industries to a certain extent and verified the "pollution haven hypothesis"; the proportion of the secondary sector and energy industry in the pilot areas had been reduced after the pilot policy; on the contrary, the technical level and the economic development level of the pilot provinces and cities had been further improved. [ABSTRACT FROM AUTHOR]

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

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

In 2020, China promised to achieve carbon peaking by 2030 and carbon neutrality by 2060, and these targets are famous as "Goal 3060" in China. Chinese resource-based cities are concerned about the realization of Goal 3060 to practice national action against environmental change. In this paper, this study evaluates the impact of population, economic growth, energy intensity, industrial structure, fixed asset investment, and urbanization level on carbon emissions in Chinese cities. To do so, the paper divides 36 Chinese cities into four types (growing city, mature city, recessionary city, and regenerative city) from 2003 to 2017 by factor investigation according to the diverse development stages. The extended STIRPAT model is used to assess the impact of various factors on CO2 emissions in the Yellow River basin and diverse city levels. The panel regression analysis was conducted for the basin as a whole and cities at different development stages through a fixed-effects model and a linear regression model with Driscoll-Kraay standard errors. The results show that (1) the total carbon emissions in the Yellow River basin continued to climb during the study period. However, the growth rate slowed down significantly after 2012. In addition, there are differences in the total carbon emissions and growth rate of different cities. (2) Population, real GDP, energy intensity, industrial structure, and fixed asset investment all have a significant positive impact on carbon emissions in the overall basin except the urbanization level which has a significant negative influence on carbon emissions. (3) There is heterogeneity in the influencing factors of carbon emissions in resource-based cities at various development stages. Based on these results, corresponding policies are proposed for different types of cities to help resource-based cities achieve the 3060 dual carbon goal. [ABSTRACT FROM AUTHOR]