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In the context of carbon neutrality target, renewable energy sources have been transforming from "supplementary energy" to "main energy", which have promoted the green and low-carbon transition of global energy supply system. In-depth analyzing the spatial patterns and driving mechanisms of renewable energy expansion are of significance for optimizing the spatial layout of clean power, and avoiding the phenomenon of wind and solar power curtailment. In this paper, we proposed an ensemble learning model to examine the nonlinear effects of physical geography, resource endowment, and socio-economic factors on solar photovoltaic (PV) capacity at the prefecture-level city scale in China. Using the city-level multi-sources geospatial big data, we extensively collected a total of 175 related explanatory variables and cumulative installed capacity of solar PV power for 295 prefecture-level cities of China. The recursive feature elimination algorithm (SVM-REF) is firstly used to extract the optimal feature subset of urban PV capacity from multi-dimensional features variables. Furthermore, three advanced machine learning models (random forest, decision tree, extreme gradient boosting) are developed to identify the key influencing factors and nonlinear driving effect of urban solar PV power expansion in China. The results show that China's PV installation capacity is highly concentrated in Northern and Northwest parts of China, with the occupancy over 70% in 2019. Moreover, the XGBoost model has the best prediction accuracy (R2 = 0.97) among three methods. We also found that total amount of urban water resources, average solar radiation, and population density are the most important controlling factors for urban solar PV capacity expansion in China, with contribution of 35.6%, 17.7%, and 13.3%, respectively. We suggested that urban solar PV layout mode in China is recommended to gradually shift from resource orientation to the "resource-environment-demand" comprehensive orientation. The paper provides a replicable, scalable machine learning models for simulating solar PV power capacity at the prefecture-level city scale, and serves as a motivation for decision-making reference of the macro siting optimization and sustainable development of China's green power industry. • This study examines the impact of high-dimensional features variables on urban solar energy development. • Over 70% of solar PV installation capacity is concentrated in Northern and Northwest parts of China. • Water resources, solar radiation, population density have significant impact on solar PV distribution. • Solar PV distribution in China should shift from resource orientation to the comprehensive orientation. [ABSTRACT FROM AUTHOR]

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

In the global context, countries must reduce carbon dioxide emissions to "net zero" by 2050 to limit global warming to 1.5 °C above pre-industrial levels. China's Nationally Determined Contributions (NDCs) are to peak carbon dioxide emissions by 2030 and achieve the carbon neutrality target by 2060. To monitor the achievements of the NDCs, establishing an annual-based accounting mechanism is necessary to record the carbon stocks in China, especially for Blue Carbon. The paper aims to present China's first national-scale systematic Blue Carbon accounting for mangroves, salt marshes, and seagrasses, covering the accounting subjects of physical and monetary assets, as well as relevant indicators for investors. It focuses on the design of the accounting method and system, the selection of data categories applied to this system, and the application of China's Blue Carbon accounting based on this accounting system. Taking Blue Carbon accounting as a starting point, this paper analyses the restoration prospects of these ecosystems and their application potential for NDCs in China compared with the terrestrial ecosystems. The results indicate that mangroves are the most cost-effective type of ecosystem, even compared to terrestrial forests. Thus, the paper provides policymakers with a new perspective on the decision-making of carbon sequestration relevant decisions, aiming to promote the monitoring, restoration, and expansion of China's coastal blue carbon ecosystem through the establishment of a sound Blue Carbon accounting system, and to help achieve the carbon neutrality goal in China's NDCs through regular and systematic monitoring of its national Blue Carbon inventories. • China's coastal blue carbon ecosystems are carbon sources rather than carbon sinks. • Mangroves are the most cost-effective coastal blue carbon ecosystem compared to salt marshes and seagrass beds. • The Blue Carbon of mangroves is more cost-effective than the Green Carbon of terrestrial forests when meeting China's Nationally Determined Contributions target of increasing forest stocks. • Establishing guidelines for Blue Carbon data requirements will lay a scientific foundation for formulating strategies and policies to cope with global climate change. [ABSTRACT FROM AUTHOR]

The proposal of the dual carbon goal and the blue economy in China has sparked a keen interest in carbon emissions reduction from sewage treatment. Carbon accounting in urban sewage plants serves as the foundation for carbon emission reduction in sewage treatment. This paper re-evaluated carbon accounting in the operational processes for urban sewage treatment plants to develop a novel carbon emission evaluation model for anaerobic-anoxic-oxic treatment plants. The results show that the carbon emissions generated by non-carbon dioxide gases far exceed the carbon emissions from carbon dioxide alone. Moreover, the recycling of sewage leads to carbon emissions reduction that offsets the carbon emissions generated during the operation of the sewage plant. Also, the carbon emissions generated by sewage treatment plants are lower than those generated by untreated sewage. The findings and insights provided in this paper provide valuable references for carbon accounting and the implementation of low-carbon practices in urban sewage treatment plants. [Display omitted] • A novel carbon emission evaluation model for AAO treatment plants was proposed. • Mechanical processes generated higher carbon emissions than energy and chemicals. • The determination of direct and indirect emissions of CO 2 from sewage plants. • Sewage recycling can offset carbon emissions from the operation of sewage plants. [ABSTRACT FROM AUTHOR]

Data center is a very important infrastructure to support the development of information technology, and its development and increment are very remarkable. However, with the rapid and large-scale development of data centers, the problem of energy consumption turns to be also very prominent. Under the background of global carbon peak and carbon neutrality, developing green and low-carbon data centers has become an inevitable trend. This paper reviews and analyzes the policies and their roles in promoting China's green development of data centers in the past 10 years, summarizes the current situation of the implementation of green data center projects in China and gives the changes of PUE limits of data centers under the policy constraints. Application of green technologies is an important measure for energy-saving and low-carbon development of data centers, so encouraging innovation and application of green technologies in data center is also a priority task in relevant policies. This paper points out the green and low-carbon technology system of data centers, further summarizes energy-saving and carbon-reducing technologies in IT equipment, cooling system, power supply and distribution system, lighting, intelligent operation and maintenance, and provides an outlook on the future green development of data centers. • China's green data center policy in recent 10 years has played an important role in promoting the development of green data centers. • Summarizes the status of green data centers under policy guidance. • Provides energy saving and carbon reduction technology path for data centers. • Prospects for the future development of green data centers. [ABSTRACT FROM AUTHOR]

China's carbon emission trading policy plays a crucial role in achieving both its "3060" dual carbon objectives and the United Nations Sustainable Development Goal 13 (SDG 13) on climate action. The policy's effectiveness in reducing pollution and mitigating carbon emissions holds significant importance. This paper investigated whether China's carbon emission trading policy affects pollution reduction (PM 2.5 and SO 2) and carbon mitigation (CO 2) in pilot regions, using panel data from 30 provinces and municipalities in China from 2005 to 2019 and employing a multi-period difference-in-differences (DID) model. Furthermore, it analyzed the heterogeneity of carbon market mechanisms and regional variations. Finally, it examined the governance pathways for pollution reduction and carbon mitigation from a holistic perspective. The results indicate that: (1) China's carbon emission trading policy has reduced CO 2 emissions by 18% and SO 2 emissions by 36% in pilot areas, with an immediate impact on the "carbon mitigation" effect, while the "pollution reduction" effect exhibits a time lag. (2) Higher carbon trading prices lead to stronger "carbon mitigation" effect, and larger carbon market scales are associated with greater "pollution reduction" effects on PM 2.5. Governance effects on pollution reduction and carbon mitigation vary among pilot regions: Carbon markets of Beijing, Chongqing, Shanghai, and Tianjin show significant governance effects in both "pollution reduction" and "carbon mitigation", whereas Guangdong's carbon market exhibits only a "pollution reduction" effect, and Hubei's carbon market demonstrates only a "carbon mitigation" effect. (3) Currently, China's carbon emission trading policy achieves pollution reduction and carbon mitigation through "process management" and "end-of-pipe treatment". This study could provide empirical insights and policy implications for pollution reduction and carbon mitigation, as well as for the development of China's carbon emission trading market. • China's carbon emission trading (CET) policy promotes pollution reduction and carbon mitigation. • Higher carbon trading prices lead to stronger "carbon mitigation" effect. • Larger carbon market scales bring greater "pollution reduction" effects on PM 2.5. • Regional heterogeneity exists on pollution reduction and carbon mitigation. [ABSTRACT FROM AUTHOR]

China's coastal region is the major geographical unit for the future development of China's industrial sector. The transformation of basic structure to high-class development in China's coastal places is a significant tool for promoting the changes related to quality, power and efficiency in regional economic development. In the 21st century, environmental and energy issues have increased worldwide, and challenges related to environmental pollution, energy crises, and ecological imbalances have emerged. To climate change and energy utilization, the sustainable progress of clean energy is the new route of future energy development. Based on China's non-polluting energy growth process in the last ten years, this article explores China's clean/green energy policies and economic growth development plans. Clean energy utilization is crucial for sustainable development in the context of high-quality economic growth and climate change. However, the monetary evolution and carbon emission are not investigated whole from the clean energy aspects. Using Wind energy sources as the acceptable variable, this paper employs threshold regression and impulse functions to assess the energy consumption and economic growth on carbon emission in 30 Chinese provinces over the 2000 to 2020 period. The Deep Belief Network (DBN) model predicts wind energy utilization and efficiency. The results show that economic development and carbon emissions are connected. Further, growth influences promote the offset of carbon emissions. Green innovation alters the nexus of carbon emissions, and China's economy reduces carbon usage. It provides the decision-making policies for clean energy development. • China's Coastal region is the major geographical unit for the future development of China's industrial. • In high-quality economic growth and climate change, clean energy use is vital for sustainable development. • The utilization of wind energy and it's efficiency is predicted using Deep Belief Network (DBN) model. • Empirical results link economic growth with carbon emissions, showing growth promotes emissions offset. • Green innovation changes the economic growth-carbon link, aiding China's carbon reduction efforts. [ABSTRACT FROM AUTHOR]

Although our knowledge of national carbon emission trading system and green certificate trading system are powerful incentive instruments that can deliver on increasingly ambitious climate targets in China, there remains an uncertainty of systems' structural reforms. This study builds on and extends a well-established dynamic computable general equilibrium (CGE) model to incorporate carbon trading system and green certificate trading system into the modeling framework, simulating a diverse of system development pathways further allows an exploration of the many possible policy effect. Then, using total factor productivity as a comprehensive indicator to asses policy effectiveness, the evolutionary trend of comprehensive effects under different paths are separately evaluated to discover the reforms' optimal range. Our work offers main results: First, these instruments provide a price signal. The introduction of a carbon allowance auction drive up carbon prices, while the implementation of a green certificate punishment and the expansion of the trading scope promote an increase in green certificate prices. Second, all policy scenarios that help reduce carbon emission intensity and optimize the power supply structure. However, in achieving the net-zero goal, the green certificate policy incurs more economic costs than the carbon trading policy. Indeed, the combination of multiple policy tools alleviates the decline of social welfare levels. Third, synergism design among policy tools: the focus should be on carbon trading policy from 2021 to 2030, green certificate trading policy from 2030 to 2050, and strengthened policy from 2050 to 2060. Reform measures within policies may need to be introduced in a timely manner. This study offers specific insights and tailored policy proposals to support policymakers in balancing environmental goals with economic and social needs in light of the aforementioned findings. Fig. 1. Introduction of the research questions Fig. 2. Framework of this paper. [Display omitted] • Carbon emission trading and green certificate trading policies were introduced into a dynamic CGE model. • The comprehensive performance of different scenarios were measured using total factor productivity index. • The policy effects of different scenarios were explored from 2020 to 2060. • The even more effective reform measures were adopt, within a single policy. • A sensible mix were proposed, within different policies. [ABSTRACT FROM AUTHOR]

Numerous studies have discussed the economic impacts of the COVID-19 pandemic in recent years. However, the effectiveness and trade-offs of diverse countermeasures still need to be investigated, particularly under the long-term goal of low-carbon transition, which is crucial for understanding the potential impacts of the future public health emergency (PHE) related economic crisis. Given that China still faces big pressures from the potential PHE and carbon neutrality, this paper assesses the effectiveness of policy instruments in restoring the economy and advancing green development after the PHE using the Dynamic Stochastic General Equilibrium framework. Our findings reveal that the PHE imposes more constraints on the economy because of the decrease in productivity on the supply side and in consumption on the demand side. Compared to the other counterparts, the mixed stimulus can overcome the adverse impacts of the PHE while contributing to carbon reduction. Furthermore, all types of low-carbon policies investigated in this study can contribute to carbon reduction at the expense of economic growth. Meanwhile, the carbon tax realizes the target of reducing emissions with the smallest negative impact on economic growth. Thus, we suggest adopting the carbon tax policy as the most effective low-carbon measure to address uncertainties associated with the PHE. • This study explores pathways for advancing economic recovery and green development after the public health emergency. • We develop a scenario-based dynamic stochastic general equilibrium (DSGE) model. • We characterize public health emergency shocks from a supply and demand perspective. • The model introduces different carbon abatement mechanisms. [ABSTRACT FROM AUTHOR]

Accurately predicting carbon trading prices using deep learning models can help enterprises understand the operational mechanisms and regulations of the carbon market. This is crucial for expanding the industries covered by the carbon market and ensuring its stable and healthy development. To ensure the accuracy and reliability of the predictions in practical applications, it is important to evaluate the model's robustness. In this paper, we built models with different parameters to predict carbon trading prices, and proposed models with high accuracy and robustness. The accuracy of the models was assessed using traditional survey indicators. The robustness of the CNN-LSTM model was compared to that of the LSTM model using Z-scores. The CNN-LSTM model with the best prediction performance was compared to a single LSTM model, resulting in a 9% reduction in MSE and a 0.0133 shortening of the Z-score range. Furthermore, the CNN-LSTM model achieved a level of accuracy comparable to other popular models such as CEEMDAN, Boosting, and GRU. It also demonstrated a training speed improvement of at least 40% compared to the aforementioned methods. These results suggest that the CNN-LSTM enhances model resilience. Moreover, the practicality of using Z-score to evaluate model robustness is confirmed. • Deep learning by combined CNN-LSTM networks for carbon price forecasting. • Hyperparameter tuning of deep learning models for improving forecast accuracy. • CNN-LSTM models outperform single CNN models and single LSTM models. • Performance metric of deep learning for abrupt changes in carbon price variation. [ABSTRACT FROM AUTHOR]

To address global climate change, achieving carbon peak and carbon neutrality has become a global consensus. However, the means to simultaneously achieve carbon reduction and promote green economic development, particularly in developing countries, require further investigation. This study evaluates the impact of e-commerce on CO 2 emissions. Through an examination of the effects of the National E-Commerce Demonstration City (NEDC) policy from 2006 to 2017, this paper reveals that e-commerce growth facilitated by the NEDC policy resulted in a 7.89% reduction in total CO 2 emissions and a per capita reduction of 1.1146 tons in the pilot cities. Mechanism analysis demonstrates that the upgrading of industrial structure, development of digital finance, and the growth of innovation and entrepreneurship serve as primary pathways for this impact. The robustness of the findings is supported by parallel trend tests, placebo tests, and additional sensitivity analyses. Furthermore, the research reveals that the NEDC policy exhibits a more significant reduction in CO 2 emissions in cities with higher levels of economic development and non-resource-based cities. Welfare analyses show that the NEDC policy has significant socio-economic effects. These findings provide new evidence on the environmental effects of the digital economy and offer insights into achieving carbon neutrality. • The National E-commerce Demonstration Cities (NEDC) policy reduced CO 2 emissions. • Optimizing industrial structure, enhancing digital finance, and promoting innovation and entrepreneurship are mechanisms. • The effect is more pronounced in cities with high economic levels and high resource dependence. • The NEDC policy substantially enhanced social welfare by reducing CO 2 emissions. [ABSTRACT FROM AUTHOR]

Digital technology is an effective way to realize the carbon neutrality target in China. Therefore, based on panel data at the city level in China from 2006 to 2016, we take the e-commerce pilot policy as a quasi-natural experiment, using the staggered difference-in-differences (DID) method to explore the effect of digital technology development on carbon emissions and its transmission mechanism. The conclusion of this paper shows that (ⅰ) the e-commerce pilot policy has significantly reduced carbon emissions. After a series of robustness tests, this empirical conclusion is still valid. (ⅱ) The inhibitory effect of different waves of e-commerce pilot cities on carbon emissions sequentially decreases. The e-commerce pilot policy has a greater effect on reducing carbon emissions in non-old industrial based cities and non-resource-based cities. (ⅲ) Implementing the e-commerce pilot city policy mainly reduces urban carbon emissions by optimizing resource allocation, reducing energy consumption and upgrading the industrial structure. (ⅳ) In addition, implementing the e-commerce pilot city policy has a significant positive carbon-reducing linkage effect with the carbon trading pilot policy and the low-carbon city pilot policy. The findings of this paper provide empirical evidence for carbon emission reduction, which has implications for upgrading urban construction patterns and promoting green urban development. • The construction of national e-commerce pilot cities has significantly reduced the carbon emission of cities. • The inhibitory effect of different batches of e-commerce pilot cities on carbon emissions sequentially decreases. • Playing more significant effect in non-old industrial based cities and non-resource-based cities. • Reducing urban carbon emissions by optimizing resource allocation and reducing energy consumption. • Having a significant positive carbon-reducing linkage effect with carbon emissions mitigation policies. [ABSTRACT FROM AUTHOR]

The Chinese government has declared a determination at the 75th United Nations General Assembly that China will improve its independent contribution and adopt more powerful measures to peak the carbon emissions before 2030. However, such strict implementation of carbon reduction policies is bound to bring the cost of sacrificing economic development. In such a context, this paper tries to use shadow price to measure the average social cost of emission reduction, marginal abatement cost to depict the pressure to reduce carbon emissions based on non-radial distance function, and provides an optimal scheme for provincial emission reduction to minimize the national cost of emission reduction based on variable-coefficient model. Results show that: First, the average value of shadow price is 15.91 and varies widely among regions, which means on average reducing one unit of carbon emissions will sacrifice 15.914 yuan RMB of economic output, and there exists possibility of carbon transactions across regions; Second, on the one hand, marginal abatement cost of carbon emission for most regions presents an upward tendency over time, which means greater economic costs have to be sacrificed with economic development in the future; On the other hand, marginal abatement cost is much higher in regions with high economic level than that in the economically undeveloped areas, which indicates reducing carbon emissions is becoming increasingly difficult and would pay more economical cost in economically developed regions; Third, the optional allocation scheme of CO2 reduction derived from this research is better than administrative ways of Grandfathering and Benchmarking in terms of minimizing emission reduction cost. Results of this paper indicate that larger carbon trading market can be implemented in China to economically fulfill the commitment of peaking carbon emissions. • This paper provides a scheme to minimize the carbon emission reduction cost. • Shadow price and marginal cost of carbon emission are estimated. • More comprehensive carbon trading market can be implemented in China. [ABSTRACT FROM AUTHOR]

This paper analyzes the overall and time-varying efficiency of China's carbon market, which is crucial for carbon risk management and policymaking. Due to the severe illiquidity problems other pilots face, we first select Shenzhen, Guangdong, and Hubei pilots out of the eight carbon pilots for our study based on the statistical analysis. We then test the overall efficiency of the markets using the LM, CD, and Wild-Bootstrap variance ratio test. The sliding window method is combined with the above three variance ratio test methods to validate the time-varying efficiency. The results prove that the overall efficiency of the three carbon pilots has not yet reached a weak form. And we observe that the short-term efficiency is time-varying and may be weak-form. The study further found Hubei to be the most efficient carbon pilot, followed by Guangdong and Shenzhen. Finally, this paper conducts a qualitative analysis on the low efficiency from five aspects namely carbon trading rules, market liquidity, price volatility, trading volume, and types of trading products. Several conclusions and recommendations are proposed for policymakers and investors. • Sliding window method is combined with a series of variance ratio test methods. • The overall and time-varying efficiency of China's carbon market is tested. • China's carbon market has not reached weak-form efficiency. • Hubei is the most efficient carbon pilot. • Reasons for low efficiency are analyzed. [ABSTRACT FROM AUTHOR]

Green power trading is an institutional innovation proposed by China to promote green and sustainable development. This policy aims to relieve the serious debt pressure of renewable energy generation enterprises, thus laying the foundation for achieving carbon reduction targets. This paper empirically examines the role of green power trading by constructing the difference-in-differences (DID) model. Our findings indicate that green power trading significantly reduces the debt levels of policy-covered generation enterprises. This effect is more pronounced for state-owned enterprises, companies with better ESG performance, companies in regions with higher degree of marketization and companies specializing in renewable energy power generation. Further research discusses the impact mechanism of green power trading in terms of external and internal environmental channels. We find that a strong green development atmosphere, especially the external atmosphere, will significantly reinforce the weakening effect of green power trading on corporate debt. Our research provides empirical evidence for the success of green power trading policy in its pilot phase. • Green power trading significantly alleviates the policy-covered firms' debt burden. • The role of green power trading presents heterogeneity in enterprise characteristics. • A better regional environment for green growth can stimulate the effect of green power trading. [ABSTRACT FROM AUTHOR]

Based on the tightening regulation of carbon emissions, China has launched the pilot carbon emission trading scheme (CETS) since 2013. There is growing empirical evidence of the actual effect of CETS to promote enterprises' productivity which is characterized by total factor productivity (TFP). However, most studies ignored the further analysis of influence mechanisms. This paper aims to explore the impact of CETS on the TFP of enterprises and discuss the mediating role of government participation and carbon trading market efficiency. Using data from A-share listed enterprises from CETS-covered enterprises, this paper employed a combination of the propensity score matching (PSM) and difference-in-differences (DID) strategies and found that the CETS has a statistically significant positive impact on the TFP of enterprises, and the positive effect has been maintained for six years since its inception. The moderation analysis indicated that: (1) two dimensions of government participation in terms of the market incentive and government supervision significantly moderate the positive impact of CETS on TFP of enterprises; (2) two dimensions of carbon trading market efficiency in terms of the market scale and liquidity significantly moderates the positive impact of CETS on TFP of enterprises. In light of Chinese pilots CETS policy, the study highlights the important moderating roles of government participation and high carbon trading market efficiency on enterprise's TFP. [Display omitted] • Chinese pilots CETS significantly improved the TFP of enterprises by 9.48%. • The government participation moderates the positive impact of CETS on enterprises' TFP. • The higher carbon trading market efficiency is, the greater the moderating effect of CETS on TFP is. [ABSTRACT FROM AUTHOR]

Constructing and adopting a county-level panel dataset containing carbon emission (CO 2) and economic information between 2009 and 2017, this paper employs the continuous difference-in-differences (DID) model and is among the first to conduct an evaluation of the CO 2 reduction effect of China's emission trading scheme (ETS) pilot markets from the dual perspectives of price and scale. The empirical results emerge that the increase of transaction price and the expansion of transaction volume in ETS pilots have a persistent and significant influence on CO 2 reduction. Parallel to this, it is found the rising of transaction price in ETS can be effective on CO 2 reduction by improving the energy structure transition, however, optimization of industrial structure and the development of ICT might be the essential channels driven by the expansion of transaction volume. Last, this paper identifies the synergistic effect on different sorts of contaminants and find it is more substantial to those with the gas state. This paper implies that the policymakers should fully excavate the market-oriented environmental regulation tools from transaction price and volume perspective of views for the well achieving the climate ambitions of carbon peak and neutrality. • This article estimates the carbon emission reduction effect in of China's ETS pilots from the dual perspective of price and scale point of view. • The switch of China's carbon ETS regional pilots to national unified one can make the carbon emissions experience a wave of decline about 6.162%. • By estimating the possible synergistic effect on pollution of ETS market pilots, which find it is more significant to pollutants with gas phase. [ABSTRACT FROM AUTHOR]

As an important supplementary mechanism to the Emissions Trading Scheme (ETS), the Chinese Certified Emission Reduction (CCER) scheme is of profound significance for achieving low-cost emission reduction and renewable energy goal. However, limited literature discusses the role of the CCER scheme. To explore to what extent will the CCER scheme save cost for China's carbon trading system, this paper establishes a two-level decision sub-game led by the national government and compares the cost-saving effect before and after introducing the CCER scheme. The empirical results from China confirm the cost-saving effect of the CCER scheme while achieving the homogeneity and equivalence of carbon emission quotas and CCER quotas are the prerequisite for the minimum national aggregate costs. The equilibrium CCER trading price is linked to three factors, including the offset rate of CCER quotas, the total carbon emission quotas and the reciprocal of the declaration cost coefficient. Depending on the actual situation in China, the ceiling offset rate of CCER quotas should not exceed 6%. Even so, the national government still needs to clarify the potential provinces and direction of CCER projects to ensure that the actual offset rate could be as close as possible to the optimal value. These findings can provide guidance for policy makers in the design of the national carbon trading system. • A two-level decision sub-game led by the central government is established. • The cost-saving effect of the CCER scheme is confirmed. • The optimal and ceiling offset rate of CCER quotas is obtained. • The development potential and direction of CCER projects are discussed. [ABSTRACT FROM AUTHOR]

Accurate carbon price projections can serve as valuable investment guides and risk warnings for carbon trading participants. However, the escalation of uncertain factors has brought numerous new hurdles to existing carbon price forecast methods. In this paper, we develop a novel probabilistic forecast model called quantile temporal convolutional network (QTCN) that can precisely describe the uncertain fluctuation of carbon prices. We also investigate the impact of external factors on carbon market prices, including energy prices, economic status, international carbon markets, environmental conditions, public concerns, and especially uncertain factors. Taking China's Hubei carbon emissions exchange as a study case, we verify that our QTCN outperforms other classical benchmark models in terms of prediction errors and actual trading returns. Our findings suggest that coal prices and EU carbon prices have the most significant effect on Hubei carbon price forecasting, while air quality index appears to be the least important. Besides, we demonstrate the great contribution of geopolitical risk and economic policy uncertainty to carbon price projections. The effect of these uncertainties is more pronounced when the carbon price is at a high quantile level. This research can offer valuable guidelines for carbon market risk management and provide new insight into carbon price formation mechanisms in the era of global conflict. • We propose a novel probability forecast model QTCN for carbon prices. • The impact of economic policy uncertainty and geopolitical risks are considered. • The prediction accuracy of QTCN outperforms other competing models. • QTCN-based trading strategies yield higher profits than a point forecast-based one. [ABSTRACT FROM AUTHOR]

Process-related carbon emissions, which cannot be completely eliminated by the improvement of processes and energy structure, are recognized as an enormous challenge for in-depth decarbonization. To accelerate the achievement of carbon neutrality, the concept of 'artificial carbon cycle' is proposed based on the integrated system of process-related carbon emissions from high-emitting industries and CCU technology as a potential pathway towards a sustainable future. This paper conducts a systematic review on the integrated system with the case of China, which is the largest carbon-emitting and manufacturing country, to provide a clearer and more meaningful analysis. Multi-index assessment was used to organize the literature and draw the useful conclusion. Based on literature review, the high-quality carbon sources, reasonable carbon capture approaches and promising chemical products were identified and analyzed. Then the potential and practicability of the integrated system was further summarized and analyzed. Finally, key factors of future development including technology improvement, green hydrogen, clean energy and industrial cooperation were stressed to provide a theoretical reference for future researchers and policy makers. • Demonstration on the rationality and importance of applying CCU technology on process-based carbon emissions. • Multi-index assessment on adoptable carbon sources, possible pathways of carbon capture and carbon conversion. • Analysis on the potential and practicability of the integrated system to accelerate carbon neutrality. [ABSTRACT FROM AUTHOR]

The carbon trading policy seeks to control carbon emissions by putting a price on carbon emissions and establishing a corresponding carbon market for trading. It is a significant move by China to address climate issues and achieve its Carbon Neutrality target. Therefore, assessing the policy effects of carbon trading is fundamental to its implementation nationwide. Based on the panel data of 30 provinces and cities in China from 2008 to 2018, this paper uses the Synthetic Control Method and Differences-in-Differences method to assess the effects of carbon trading policy on achieving Carbon Neutrality. By measuring the net carbon emissions, this research explores the level of Carbon Neutrality in each region. Based on the Five-sphere Integrated Plan (which covers the economy, politics, culture, social and ecological civilization), this research further verifies the impact paths of carbon trading policy on Carbon Neutrality. The results show that: First, carbon trading policy has a significant and sustainable effect on Carbon Neutrality. Second, from the perspective of the Five-sphere Integrated Plan, the carbon trading policy can help to reduce carbon sources and increase carbon sinks by adjusting the industrial structure, coordinating low-carbon policies, promoting cultural dissemination, increasing green space construction, and reducing energy intensity to achieve Carbon Neutrality. Third, cultural construction plays the most significant role in mediating carbon trading and Carbon Neutrality, followed by political construction. • This paper examines the effectiveness of carbon trading policy for Carbon Neutrality. • We use the Synthetic Control Method and Difference-in-Differences method. • The impact paths of carbon trading policy are examined from the Five-sphere Integrated Plan perspective. • Carbon Neutrality should be incorporated into the Five-sphere Integrated Plan. • A cross-perspective study of the Five-sphere Integrated Plan, carbon trading with Chinese characteristics has been formed. [ABSTRACT FROM AUTHOR]

Thermal power industry is one of China's leading sources of carbon emissions. China has launched a national carbon emissions trading scheme (ETS) and renewable energy incentive programs to achieve its peak emission target by 2030. However, since 2021, China no longer provides a central feed-in tariff (FIT) for new centrally located solar photovoltaic (PV) power plants, commercial and industrially distributed PV projects, and newly approved onshore wind power projects. This change in policy may threaten China's carbon reduction targets and economic development. Using a dynamic computable general equilibrium (CGE) model, we assess the combined effects of carbon ETS and FIT on China's electricity sector, carbon emission peak target, renewable energy and economic development. In terms of policy overlap and integration, we analyze the impact of these policies and estimate how to coordinate FIT and carbon ETS policies to ensure their effectiveness. Results show that the overall effects of FIT subsidies are superior to phasing-out FIT scenarios. The fiscal pressure caused by FIT is lower than its actual expenditure because it stimulates economic activity and boosts government revenue. However, considering the multiplier effect of the FIT on promoting government revenue growth and GDP growth, the most effective FIT should be terminated in 2025, followed by subsidies ending in 2030 and 2035. • Using the dynamic CGE model, the combined effect of Feed-in tariffs and carbon ETS is simulated. • This paper found that the overall effects of continuous FIT subsidies are superior to phasing-out FIT scenarios. • The fiscal pressure caused by continuous FIT is lower than its actual expenditure. • Considering the multiplier effect of the FIT, the most effective subsidy policy should be terminated in 2025. [ABSTRACT FROM AUTHOR]

China pushed for the unification of markets for natural resources and emissions, wherein initial allocation mechanisms have a significant impact on how well the market functions. To identify how the market works well, this paper builds an integrated framework, comprised of permits initialization and reallocation processes. Additionally, we simulate variables by 2030 through scenario analysis and machine learning methods. At the unified energy-carbon market, GDP could increase by more than 49%, while the total energy consumption and the total carbon emission increase by around 410 million tons and 711 million tons, respectively, in China. This illustrates how joint trading markets favor economic growth and emission reduction simultaneously. Besides, most of China's provinces obtain improved energy consumption and carbon emission intensities, which proves the effectiveness and importance of the unified market. However, two rebound effects are found, one is that the increased investment is not always promoting positive effects, and the other is that provinces with higher GDPs have less incentive to cut their energy use. Further, the accumulated per capita initialization type favors energy conservation, while per GDP initialization benefits economic growth and carbon reduction. It's needed that simultaneously constructing an economic and efficient incentive mechanism while effectively playing up the government's role. [Display omitted] • Energy and carbon joint markets have economic and environmental co-benefits. • A novel framework is designed enabling the exchange of energy and carbon permits. • The influence of socio-economic and climate change scenarios in the future is considered. • The influence of initial permits allocation modes on market performance is identified. • Promotion measures are needed especially for provinces with higher economic outputs. [ABSTRACT FROM AUTHOR]

Green credit policy (GCP) can achieve economic growth and environmental conservation, notably by lowering air pollutants (PM2.5). Green credit is a significant component of China's green financing for environmental regulation and achieving carbon neutrality. In this paper, to understand the causal relationship between GCP and PM2.5, we apply a bootstrap full-sample Granger causality test, parameter stability test, and quantile-on-quantile test for the period between 2003:M01 to 2019:M12. The result shows a bidirectional relationship and reveals that GCP has varied environmental implications in its early and mature stages because of a low percentage of green credit and a lack of motivation for financial institutions. In the long run, GCP and PM2.5 interaction confirm the favorable effects of GCP on PM2.5 as the green credit system improves. For robustness, we used quantile-based granger causality to evaluate the causative link between GCP and PM2.5. In light of the findings, this research advises legislative reforms and stresses the relevance of green credit in improving air quality. This study adds additional evidence that air pollution affects green credit policies. Air quality being a leading indicator helps firms anticipate changes in bank credit preferences and alter financing techniques. • The study explores the causal relationship between GCP and PM2.5 • The study used advanced econometrics methods for the period 2003:M01 to 2019:M12. • The result shows a bidirectional relationship between GCP and PM2.5. • GCP has a positive influence on PM2.5 as the green credit system improves. • This study adds further evidence that air pollution affects green credit policies. [ABSTRACT FROM AUTHOR]

As a major carbon dioxide-emitting country, China set carbon trading market to reduce enterprise carbon emissions through the rational allocation of carbon quotas among different enterprises and regions. The market has also conducted a preliminary exploration for the country to achieve carbon dioxide emissions peak in 2030 and carbon neutrality in 2060 while actively addressing the challenges of global climate change. This study analysed the emission reduction effect of China's carbon trading pilot policy, especially the role of carbon quota and carbon trading price. The analysis used county-level panel data from 1997 to 2017, regarded the implementation of the carbon trading pilot policy as a quasi-natural experiment, and used the difference-in-differences method. The results showed that, first, the policy implementation not only reduced regional carbon emissions but also inhibited carbon dioxide emissions per capita, with long-term effects. Second, the carbon emission reduction effect brought by the carbon pilot policy showed significant heterogeneous results with the different degrees of regional carbon emissions and environmental supervision. The effect was greater in areas with higher carbon emission density and stronger legal supervision. Third, the difference in carbon quota allocations resulted in different emission reduction effects, among which the historical method had the strongest effect. The carbon quota price and number of enterprises participating carbon trading market were the key factors affecting carbon emission reduction. • This paper investigates the impact of carbon emission trading market on the carbon reduction. • China provides an excellent "Quasi-natural Experiment" for assessing the role of carbon emission trading market in environmental management. • It is found that policy implementation has significantly reduced various types of carbon emissions, and this reduction effect is long-term. • Stimulating the vitality of the carbon market and expanding the supply and demand of carbon quotas are the main ways to achieve carbon emission reduction. [ABSTRACT FROM AUTHOR]

The expansion of road networks in emerging economies such as China causes significant greenhouse gas (GHG) emissions. This development is conflicting with China's commitment to achieve carbon neutrality. Thus, there is a need to better understand life cycle emissions of road infrastructure and opportunities to mitigate these emissions. Existing impact studies of roads in developing countries do not address recycled materials, improved pavement maintenance, or pavement-vehicle interaction and electric vehicle (EV) adoption. Combining firsthand information from Chinese road construction engineers with publicly available data, this paper estimates a comprehensive account of GHG emissions of the road pavement network to be constructed in the next ten years in the Shandong province in Northern China. Further, we estimate the potential of GHG emission reductions achievable under three scenario sets: maintenance optimization, alternative pavement material replacement, and EV adoption. Results show that the life cycle GHG emissions of highways and Class 1–4 roads to be constructed in the next 10 years amount to 147 Mt CO2-eq. Considering the use phase in our model reveals that it is the dominant stage in terms of emissions, largely due to pavement-vehicle interaction. Vehicle electrification can only moderately mitigate these emissions. Other stages, such as materials production and road maintenance and rehabilitation, contribute substantially to GHG emissions as well, highlighting the importance of optimizing the management of these stages. Surprisingly, longer, not shorter maintenance intervals, yield significant emission reductions. Another counter-intuitive finding is that thicker and more material-intensive pavement surfaces cause lower emissions overall. Taken together, optimal maintenance and rehabilitation schedules, alternative material use, and vehicle electrification provide GHG reduction potentials of 11%, 4%–16% and 2%–6%, respectively. • Road construction implies significant amounts of GHG emissions. • China's road expansion plans are at odds with its target of GHG neutrality. • We assess GHG emissions of Shandong's roads to be constructed through 2030. • We combine life cycle assessment based on primary data with a new optimization model. • Individual mitigation measures can reduce life cycle GHG emissions by up to 16%. [ABSTRACT FROM AUTHOR]

Although there are some review papers on carbon capture, utilization and storage (CCUS), hardly any of these reviews are focused on the role of CO 2 enhanced oil recovery (EOR) in accelerating carbon neutrality in China. In this review, strategies to achieve carbon neutrality is briefly but critically discussed, followed by a review of CO 2 -EOR as a promising technology. Especially, data analysis, including the number of publications on China's carbon neutrality, per capita CO 2 emissions, China's power generation, and the crude oil production of China's large oilfields, is carried out to make the discussion more comprehensive. Given the large amount of coal consumed in China, the high percent of electricity generated with coal, and the slow penetration of renewables already observed, it seems unlikely that 2060 targets will be met without CCUS. In order to achieve carbon neutrality, both reduction in carbon emissions and increase in carbon sequestration are inevitable. Furthermore, it is concluded that CO 2 storage through EOR is likely to have a bright future. However, there are some critical issues to be solved, including the technical issues, leakage and safety issues, cost issues, policy issues, etc. In order to turn CO 2 -EOR into a reliable and more favorable technology, more research and efforts are needed to solve these issues, including advancing carbon capture technologies, improving storage technologies, developing effective monitoring technologies, deploying government support and incentive policies, etc. • CO 2 emission reduction and sequestration are needed to achieve carbon neutrality. • Carbon capture and storage without utilization is not suitable for China. • CO 2 -enhanced oil recovery (EOR) is more viable as a cost-effective CCUS technology. • CO 2 -EOR is likely to make great contributions to China's carbon neutrality target. • CO 2 leakage risk exists and more research is needed to ensure CO 2 is safely stored. [ABSTRACT FROM AUTHOR]

In this paper, we identify the causal effects of the industrial transfer policy (ITP) on carbon emissions. Specifically, we treat the demonstration zones of undertaking industrial transfer in China as a quasi-natural experiment and evaluation its carbon mitigation effects using the difference-in-differences (DID) and matching DID strategies. Our findings suggest that the ITP exerts a significant negative impact on carbon emissions. In particular, both the DID and matching DID estimates indicate that the ITP leads to mitigate carbon emissions by approximately 4.9 and 4.7 million tons, respectively. We also investigate the heterogeneous carbon mitigation effects of the ITP. Moreover, various checks and falsification tests are also presented to confirm the causal effects, including the placebo test, concurrent events test, alternative measures of the ITP and carbon emissions, alternative estimation method and matching technique. The results indicate that our key conclusion, the carbon mitigation effect of the ITP is robust. These results indicate that policymakers should seize the carbon mitigation dividend of the ITP to achieve the goal of carbon neutrality. Policymakers should also reduce the regional development differences, improve the level of opening to the outside world, strengthen the construction of green demonstration zones for industrial transfer to mitigate carbon emissions. • The carbon mitigation effects of the demonstration zones of undertaking industrial transfer in China are investigated. • The industrial transfer policy leads to mitigate carbon emissions by approximately 4.7 million tons. • The heterogeneous carbon mitigation effects of the industrial transfer policy are examined. • The results are supported by robustness and falsification checks. [ABSTRACT FROM AUTHOR]

In the reforms pertaining to the energy structure in the automotive industry, new energy vehicles (NEVs) have long been the focus of government attention, as an effective means to reduce air pollution. Therefore, this paper employs the rolling-window Granger causality test, in order to discuss the environmental benefits of new energy vehicles, so as to explore the active role of the transportation sector in reducing air pollution. By studying the interactions between NEVs and particulate matter (PM 2.5) from the time period spanning from 2013:M1 to 2020:M9, we have found that the positive influences from NEVs to PM 2.5 ascertain that NEVs cannot be considered as an efficient measure to mitigate air pollution. Moreover, these results are not supported by the energy and environment interaction model, which essentially indicates that replacing traditional energy with renewable energy is an effective measure for controlling environmental pollution. In fact, PM 2.5 tends to have a negative impact on NEVs, which underlines that the air quality index is a leading indicator, particularly when it comes to analyzing the development of the NEVs market. This essentially highlights that in China, NEVs still do not account for a high proportion of car sales, and therefore, its environmental protection effect is not obvious. At the same time, the factor of public awareness regarding environmental protection will thus occupy a considerable proportion in the transmission of NEVs sales. These revelations will help the government to formulate environmental governance policies, and expand the new energy vehicle market to achieve carbon neutrality targets in China. • The impact of NEVs on particulate matter (PM2.5) to investigate the role of the transport sector in mitigating air pollution. • NEVs can not be considered as an efficient measure to mitigate air pollution. • Not supported by the energy and environment interaction model. • The public's awareness of environmental protection will occupy a considerable proportion in the transmission of NEVs sales. • Help the government to formulate environmental governance policies and expand the new energy vehicle market. [ABSTRACT FROM AUTHOR]

The promotion of carbon-neutral investments is among the primary constituents of developing a carbon-neutral economy. This is even more important for emerging economies that have constrained financial markets. In this paper, using monthly data between 2011 and 2019, we study 6519 actively managed mutual funds in BRICS after sorting them into black, brown, and green categories based on their investment holdings. Our comparative performance shows that green funds outperform their counterparts for the entire sample and within-country assessment. We also document the volatility and market timing ability of green funds, mainly absent in high emission funds. The results remained robust for various definitions of performance. Our findings also indicate Chinese green funds perform better than those of other countries. This is attributed to the multiple ecologically friendly economic policies that China has adopted over the years. Based on the results, we propose various interventions that could foster the adaptability of a carbon-neutral investment landscape. [Display omitted] • We assess the performance of BRIC funds after segregating on carbon profiles. • The Green funds show better risk-adjusted performance than brown & black funds. • The low carbon funds exhibit market timing ability during the sample period. • We report strong evidence of volatility timing for green equity funds. • The results are encouraging for promoting a zero-carbon investment paradigm. [ABSTRACT FROM AUTHOR]

In the context of carbon neutrality, the paper uses Super Efficiency Data Envelopment Analysis (DEA) to evaluate the level of regional energy efficiency in China, then selects Theil index to analyze the difference and change of regional energy efficiency. The results are as follows: (1) The overall level of energy efficiency in China is relatively low, and the average efficiency level from 2007 to 2019 is 0.568. Among them, Beijing is the highest, at 1.261, and Xinjiang is the lowest, at only 0.205. The energy efficiency of the eastern region is the highest in China: the average is 0.812. The central region is lower than the national average, with the value of 0.534. The lowest energy efficiency is in the western region, which is only 0.349. It can be seen that there are significant differences in regional energy efficiency, and from west to east has increased. (2) The Theil coefficient increased before 2012 and began to show a downward trend in 2013. The difference in the eastern region maintained the smallest downward trend among the three regions. The difference in the central region fluctuated and increased before 2011, and dropped sharply after 2012. In the western region, the coefficient is relatively stable and has not changed significantly. (3) Differences within and between regions in China show an overall downward trend. From the perspective of contribution rate, the difference between regions contributes the most to the overall difference. • We use super-efficiency DEA to measure China's regional energy efficiency. • We use Theil Index to illustrate regional differences in energy efficiency. • We have reached a conclusion that can provide a theoretical reference for policy making. • We compared the magnitude and trend of energy efficiency in various regions. [ABSTRACT FROM AUTHOR]

As an important new tool for ecological poverty alleviation, carbon trading compensation is combining ecological protection with rural poverty alleviation. This paper evaluates the poverty alleviation impact of China's pilot carbon emissions trading schemes (ETS) at the provincial level before and after the program, which was implemented from 2007 to 2017. Specifically, we measure poverty alleviation in terms of rural residential income growth and rural job creation. By exploiting the quasi-experimental variation in whether provinces were affected by this pilot ETS policy, our analysis finds that the ETS policy resulted in increases in rural residential income and employment. We find the estimated effects correspond to an increase of approximately 752.6 yuan in annual rural residential income and 2.35% in the ratio of rural employed population to the total employed population, accounting for 9.5% of the rural residents' income and 7.11% of the rural employment, specifically. The results imply that the implementation of ETS is beneficial to income growth and job creation for rural areas of China, which mean the ETS policy may be conducive to poverty alleviation in affected provinces. • The effect of China's pilot carbon emissions trading schemes on poverty alleviation is tested. • Difference-in-Differences model is used. • The effect is an increase of approximately 752.6 yuan. [ABSTRACT FROM AUTHOR]