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As major strategic development areas in China, the provinces around the Yangtze River are facing the pressure of large aggregate CO 2 emissions and high per capita CO 2 emissions. The study on the pathway of reducing CO 2 emissions and increasing carbon sequestration will help China better clarify the ways realize the goals of carbon peak and carbon neutrality as soon as possible. In this paper, the extended STIRPAT model and OLS regression were used to establish a prediction model to estimate the CO 2 emissions during 2010–2060 under different scenarios. Meanwhile, the InVEST model was used to estimate the carbon sequestration, and the comparison with the CO 2 emissions was analyzed. The results show that Qinghai and Yunnan have achieved the goal of carbon neutrality in 2010. Under the low-carbon and energy-saving scenario and the baseline scenario, all provinces within the study area are anticipated to attain their emissions peak by 2030 or earlier, and the CO 2 emissions peak value of the whole study area is 3111 Mt and 3199 Mt, respectively. While under the high emissions scenario, only Chongqing and Qinghai will reach the emissions peak in 2030, and the whole study area will reach the emissions peak in 2040, with peak value of 3470 Mt. Under the three scenarios, the whole study area cannot achieve carbon neutrality before 2060. Only Sichuan and Hubei can achieve carbon neutrality in 2050 and 2060 under the low-carbon and energy-saving scenario. All provinces and municipalities in the lower reaches of the Yangtze River are facing huge pressure of emissions reduction. The research reveals that the goals of carbon peak and carbon neutrality should be achieved by developing clean energy, transforming industrial structure, increasing carbon sequestration and improving carbon emissions trading system. [Display omitted] • The CO 2 emissions showed a pattern of increase during 2010–2020. • The whole study area will achieve carbon peak by 2040 or earlier. • The whole study area cannot achieve carbon neutrality before 2060. • The realization pathway of carbon peak and neutrality was proposed. [ABSTRACT FROM AUTHOR]

Second emission trading market is not active in China so far, and the reason mainly lies in that enterprises do not have strong initiative for transaction. Thus it's meaningful to study related guiding mechanisms from the perspective of enterprises behavior. In this paper, an evolutionary game model and a small-world network model considering stock heterogeneity are constructed based on four given guiding mechanisms, and a simulation study is conducted through China Zhejiang emission trading market. The result shows that: (1) the optimal guiding mechanism is dynamic and changes from reward-punishment for both enterprises with surplus stock and enterprises with insufficient stock to reward-punishment for enterprises with insufficient stock when trading preferential profit coefficient increases to 1. (2) when penalty coefficient changes, the optimal guiding mechanism is the reward-punishment for both enterprises with surplus stock and enterprises with insufficient stock and keeps unchanged. (3) the enterprises with insufficient stock are more sensitive to penalty coefficient and trading preferential profit coefficient, especially to the latter, so it's better to stimulate the emission rights purchasing side and formulate positive reinforcement methods. The study of this paper can provide decision-making suggestions for Chinese government to stimulate the activity of second emission trading market. [Display omitted] • Four guiding mechanisms are given based on implementation objects. • An evolutionary game model is constructed. • A complex network model is constructed considering stock heterogeneity. • The optimal guiding mechanism is simulated and dynamically analyzed. • The policy recommendations are highlighted. [ABSTRACT FROM AUTHOR]

The objective of the traditional dispatching optimization model is to find the most economical scheduling mode, while ignoring the efficient use of renewable energy. To properly arrange thermal power generation and renewable energy power generation, this paper constructs an optimization model of the combined wind–photovoltaic (PV)–thermal dispatching system under a carbon emissions trading (CET) mechanism. The contribution of this paper is twofold. First, a dispatching optimization model is proposed, which not only considers the total cost but also takes into account the impact of the renewable energy spillage rate on the dispatching system. As a factor affecting renewable energy consumption, a carbon emissions trading mechanism has also been introduced into the dispatching system. The second contribution is to develop a model for predicting the output of renewable energy generation. Then, the optimization model is applied to the auxiliary power dispatching system of the Tianzhong ±800 kV UHV DC transmission channel in Xinjiang. The results indicate that under a carbon emissions trading mechanism, thermal power generation will be limited by the carbon emissions cost, thereby reducing the total cost of the system. Optimizing the spillage rate increases the share of renewable energy in the dispatching system, resulting in a 3.5% reduction in the actual spillage rate. The proposed model alleviates the serious problem of electricity being abandoned in the existing scheduling mode and helps to realize economical low-carbon dispatching of the power system. [ABSTRACT FROM AUTHOR]

Currently, numerous studies are being conducted on various carbon reduction policies, but their synergies have been poorly investigated. This paper examines the synergistic effect of combining emissions trading schemes (ETS) and energy carbon-content taxes (ECT), using China as a case study. A computable general equilibrium model is used to identify the synergistic effect of these two carbon mitigation policies. The results show that the synergistic effect helps to reduce GDP loss by approximately 5.44 billion CNY, which accounts for 2.83% of the overall GDP losses caused by ETS and ECT. Additionally, the synergistic effect reduces an additional 5.25 million tons of CO 2 emissions and decreases the negative impact on social welfare resulting from the two policies. Although these achievements are commendable, there are costs associated with this synergy. The effect on energy security presents mixed results and leads to increased carbon leakage. Therefore, policymakers should take heed of the potential "cocktail effects" that may arise in their pursuit of carbon neutrality. [ABSTRACT FROM AUTHOR]

This paper presents an energy-sharing market coupled with carbon emission trading to quantify peer-to-peer energy-sharing markets' economic and environmental influences. We establish a bi-level peer-to-peer energy sharing market considering the interaction between energy prosumers and the system operator. An interaction algorithm and generalized Nash game are thus applied in this work. With the simulation results, we find that the daily disutility of provincial systems is reduced by about 7 ¥ when time-of-use electricity rates are applied. This pricing strategy can encourage prosumers to participate in energy-sharing transactions. The subsidies of electricity rates, carbon prices, and renewable energy investments can improve the social welfare of the whole system. Considering the development of power generation technology and emission reduction targets, the change of optimization parameters in the next 30 years is analyzed in the example. It can be concluded that the total CO2 emission in 2050 will be reduced to almost half of that in 2020 in the energy-sharing markets. The subsidy of renewable energy generation and stricter CO2 emission constraints may accelerate the reduction of carbon emissions. [Display omitted] • It is the first time to assess the environmental effect of peer-to-peer energy trading with actual data. • We analyze the peer-to-peer energy trading impacts on the carbon emission amount in China. • We compare the market participants' revenue and CO2 emission considering the different scenarios. • We develop a bi-level coupled emission right trading market to verify whether total emission is reduced. • The development of technologies and various energy structures are considered quantitatively. [ABSTRACT FROM AUTHOR]

Carbon emission trading, a market-incentive environmental regulation, plays a critical role in leading China towards the carbon peaking and carbon neutrality. To improve the national carbon emission trading in China, we analyze the effects of the policy in pilot provinces and pilot A-share listed firms from 2008 to 2016. Particularly, to explore the pilot policy's environmental and financial impacts, this paper applies a difference-in-difference method. After the robustness check, the results confirm the carbon emission trading pilot's significantly positive impact at both firm- and province-level regarding carbon emission reduction. Meanwhile, corporate innovation seems to partially mediate the relationship between the policy and corporate carbon emission reduction. Plus, the policy promotes firms' market-based financial performance but such impact on accounting-based financial performance is insignificant. Ultimately, the operational mechanism of the policy is proved to be effective. In this paper, industry- and firm-level carbon emissions databases are established via environmental extended input-output table, which fill the research gap of China's firm-level carbon emissions. To ensure the reliability of results, the list of covered firms is sorted out manually in accordance with the disclosed data of seven carbon trading markets. Our results are meaningful for avoid productivity reduction and mechanism re-design in the context of the national carbon emission trading launched in 2021. Specifically, encouraging firms to further improve their productivity and competitiveness by innovation could eventually achieve a win-win situation between economic performance and environmental merits in the long run. [ABSTRACT FROM AUTHOR]

Global warming can be solved with carbon trading. When carbon emissions become a commodity, it can be a powerful motivator for companies to optimize production capacity and innovate technologically. The goal of this paper is to examine the way in which China's carbon emissions trading policy (CET) influences firm technological innovation in seven pilot regions, using a sample of firms in eight high-carbon industries. We employ difference-in-difference (DID) as well as DID-based propensity score matching (PSM-DID) models to investigate the influence of China's carbon emission policy on firms' technological innovation by using 4745 observations of 749 A-share listed firms in eight high-carbon industries in mainland China from 2007 to 2021. According to the findings, China's CET policy significantly boosts firms' technological innovation, and this beneficial effect persists even after a series of robustness tests that change the policy's implementation year and the technological innovation measure. Further analysis shows that this positive effect is heterogeneous across high-carbon industries and firms with different ownership. In addition, based on the external governance perspective, we find that CET policy performs better in firms in high-carbon industries with a sizable portion of ownership held by institutional investors. This study suggests the effectiveness of CET policy in promoting firms' technological innovation, confirms empirical evidence for Porter's hypothesis, and provides a basis for Chinese firms to achieve their emission reduction targets by improving technological innovation. [ABSTRACT FROM AUTHOR]

Under the current technical conditions and power mix in China, flexible modified thermal power units must provide enough flexibility resources for new power system since the potential of flexible resource has not been fully used. In this paper, a bi-level model is proposed to characterize the decision behavior of the generation company in the case of individual rationality and generation-side coordination. The model fully considers the concrete conditions of China and the technical differences between thermal power units in the multi-market (including energy, ancillary services and carbon emission trading market). The bi-level model could be reconstructed into an equivalent MILP model which can be solved directly. The strategic bidding behavior of small capacity units in the energy market show the urgency to enhance the transmission of deep peak regulation price compensation signals. The coupling of multi market is likely to be the most effective policy package to guide large-scale units to play a supporting role and small-scale units to assume the regulating function to play a role in the transition to a low-carbon future. Long-term policy mechanisms should be developed, combining electricity transition with the mechanisms in the carbon emission trading market to achieve the integral maximization of environmental benefit. • A bi-level model coupling energy, ancillary services and CET market is proposed. • A clearing model from the perspective of system integral orientation is proposed. • The technical differences of coal-fired power units are fully considered. • The analysis results provide policy implications tailored to the Chinese context. [ABSTRACT FROM AUTHOR]

Global warming caused by the excessive combustion of fossil fuels has become the focus of the international community. China's carbon emission reduction policy plays a vital role in international climate change, carbon emission neutrality and domestic environmental pollution control. This paper summarises the progress of China's Emission Trading Scheme (ETS) pilots from 2011 to 2021, including trading volume, carbon emissions price, and the effect of carbon emission abatement. By calculating the carbon emissions intensity decrease rate of China's ETS pilot and non-pilot regions, the ETS and carbon emissions tax are compared in terms of emission reduction effectiveness, emission reduction cost and implementation resistance to provide theoretical support for the Chinese government to select and develop carbon emission reduction tools. The development of the Clean Development Mechanism in China is also compared with China Certified Emission Reduction (CCER), and the offsetting rules of CCER are summarised. After the whole analysis and assessment, the results show that from 2013 to 2018, the average carbon emissions intensity decline rate in the ETS pilots was 7.3% and that in non-pilots was 4.29%. Some problems of China's carbon emissions trading market are also concluded. The trading volume is small (only 43.4 × 106 t in 2020) and is discrepant greatly in the different ETS pilots. The carbon emissions price is low (only 33.45 Yuan/t in 2020), with high volatility and large price differences among the ETS pilots. Based on the existing problems, this paper proposes some suggestions for improving China's emission trading market and provides theoretical and decision-making support for promoting carbon emission reduction and neutralisation for China. [Display omitted] [ABSTRACT FROM AUTHOR]

Emission trading scheme (ETS) is considered as a tool to reduce emissions at a low cost, which can effectively promote the carbon peak and carbon neutrality. As the main participants in the carbon emission trading (CET) market, the behavior and strategies for governments and different types of enterprises affect the final emission reduction performance. Taking the national carbon market as an example, this paper constructs a tripartite evolutionary game model including governments and power generation enterprises with different emission reduction capacity to analyze the possible game situations in the development process of the CET market. The results show that with the development of the CET market, the governments and power generation enterprises will have different game results. In order to achieve the optimal stable equilibrium and maximize carbon emission reduction, governments should improve regulatory efficiency and formulate appropriate incentive strategies for excess emission reduction and punishment strategies for insufficient emission reduction. In addition, the initial willingness will not affect the final strategy choice of the three parties. Reasonable free carbon quota ratio, lower technology emission reduction cost and higher carbon price can stimulate the enthusiasm of governments and enterprises to reduce emissions. The above results provide a reference for coordinating the relationships between governments and power generation enterprises with different emission reduction capacity in the construction of the CET market in the future. [ABSTRACT FROM AUTHOR]

To fulfill the goals of sustainable development and emission reduction, China has established the consumption side renewable portfolio standards (RPS) and domestic nationwide carbon emission trading (CET) scheme. However, there are intricate interrelationships between the two mechanisms as they overlap in policy goals and implementation measures, which might lead to policy synergy or policy ineffectiveness. Therefore, investigating the coupling effects in the context of policy coexistence is imperative for policy optimization and realization of the policy objectives. In this study, a simulation model cooperating the electricity market, the excess consumption trading market, the tradeable green certificates (TGC) market and the CET market, based on the system dynamics (SD) methodology is proposed. The paper comprehensively investigated the complex relationship between the four markets and conducted experiments with different scenario settings in RPS quota goal and carbon quota goal. The results illustrate that: (1) Both mechanisms can facilitate the expansion of renewable electricity and improve the power supply structure. (2) The quota goals of the two policies should be reasonably set as they contain both the abovementioned overlapping effects, as well as conflicts in the effects on the total electricity supply and electricity price. (3) The consumption side RPS is conductive for market absorption of renewable electricity with a proper higher RPS quota goal. (4) The TGC market is oversupplied, and the price keep decreasing under the consumption side RPS, more demand incentive mechanisms are required for TGC market. • Implementation mechanism and effects of the consumption side RPS are investigated. • Policy coordination between the consumption side RPS and CET in China are examined. • The effects of consumption side RPS and CET have both overlaps and conflicts. • Ratio of renewable electricity consumption is positively correlated with RPS quota goal. [ABSTRACT FROM AUTHOR]

To fulfill the goals of sustainable development and emission reduction, China has established the consumption side renewable portfolio standards (RPS) and domestic nationwide carbon emission trading (CET) scheme. However, there are intricate interrelationships between the two mechanisms as they overlap in policy goals and implementation measures, which might lead to policy synergy or policy ineffectiveness. Therefore, investigating the coupling effects in the context of policy coexistence is imperative for policy optimization and realization of the policy objectives. In this study, a simulation model cooperating the electricity market, the excess consumption trading market, the tradeable green certificates (TGC) market and the CET market, based on the system dynamics (SD) methodology is proposed. The paper comprehensively investigated the complex relationship between the four markets and conducted experiments with different scenario settings in RPS quota goal and carbon quota goal. The results illustrate that: (1) Both mechanisms can facilitate the expansion of renewable electricity and improve the power supply structure. (2) The quota goals of the two policies should be reasonably set as they contain both the abovementioned overlapping effects, as well as conflicts in the effects on the total electricity supply and electricity price. (3) The consumption side RPS is conductive for market absorption of renewable electricity with a proper higher RPS quota goal. (4) The TGC market is oversupplied, and the price keep decreasing under the consumption side RPS, more demand incentive mechanisms are required for TGC market. • Implementation mechanism and effects of the consumption side RPS are investigated. • Policy coordination between the consumption side RPS and CET in China are examined. • The effects of consumption side RPS and CET have both overlaps and conflicts. • Ratio of renewable electricity consumption is positively correlated with RPS quota goal. [ABSTRACT FROM AUTHOR]

The carbon emission trading scheme (ETS) is an important market-based tool for achieving carbon neutrality. The existing research on the policy effect of ETS focuses on emission reduction effect and economic effect respectively. In view of this, based on the connotations of green development, we embed fairness toward the environment into the green development system to construct a balanced green development index to measure two dimensions, namely, efficiency and fairness. Theoretically understand the synergistic development effect of economic growth and ecological environment quality produced by the implementation of ETS, and analyze the impact of carbon market on balanced green development. A multiperiod difference-in-differences (DID) model explores the impact of China's carbon ETS on the green equilibrium level by using Chinese provincial panel data for the period 2008–2018. First, the results demonstrate that China's balanced green development level is weakly coordinated overall and there is a global spatial agglomeration effect. Second, the carbon ETS has significantly improved the level of balanced green development which promotes the degree of coordination between green economic growth and environmental fairness, offering an effective path that includes efficiency and fairness for green development. Third, there are regional differences in the impact of the carbon ETS on green equilibrium levels. The effect on the western region of China was significantly higher than that of the central and eastern regions of China. Compared with the existing research, the study breaks the single research perspective. From the perspective of efficiency and fairness, we propose improvements in the construction of a national unified carbon emissions trading market to strengthen the balanced green development. This paper provides a theoretical basis and policy reference for deepening China's green and high-quality development under the "carbon peaking and carbon neutrality" goal. [Display omitted] • Evaluation system of Balanced Green Development Index is constructed. • The system was applied to balance green economic growth with environmental equity. • Emission trading scheme has significantly improved the level of balanced green development. • The promotion effect is more obvious in western China. [ABSTRACT FROM AUTHOR]

This paper examines the risk spillover effect between the carbon market and the stock market in China and the role of corporate social responsibility (CSR) on this effect. Employing Beijing, Hubei, and Guangdong carbon markets, we apply time-domain and frequency-domain spillover approaches and find that during the Chinese stock market crisis in 2015, risk spillovers from the stock market to the carbon market were more pronounced. Additionally, CSR firms are more dominant as information transmitters than those non-CSR (NCSR) firms in the carbon market. However, plausibly, due to the infancy of carbon trading, our results show that the level of connectedness between the carbon market and the stock market in China is relatively low. [ABSTRACT FROM AUTHOR]

With the gradual strengthening of environmental supervision, how to coordinate the relationship between environmental protection and full employment has become an urgent problem. This paper takes China's carbon emission trading policy as the research subject, and evaluates the employment effect of carbon emission trading policy from the perspective of micro enterprises under the premise of considering the spatial spillover effect. This paper aims to verify and evaluate the spatial spillover effect of China's carbon emission trading pilot policy on labor demand of enterprises, and study the effect of environmental policies on the employment market in China. Firstly, from the theoretical point of view, comparisons among the differences of the average employment effect, spillover effect and total effect coefficient of carbon trading right policy are conducted under the condition of spillover effect or not. Secondly, from the empirical perspective and relaxing the STUVA conditions, a Triple Difference Model is constructed to evaluate the impact of carbon emission trading policy on the labor demand of enterprises by using the panel data of China A-share listed companies in Shanghai and Shenzhen from 2008 to 2017. Thirdly, this paper further uses the synthetic control method to analyze the employment effect differences of carbon emission trading policies in different pilot areas of China. The results show that the carbon emission trading policy in China has an about 10 percent positive spillover effect on the neighboring provinces in pilot areas. Moreover, the results indicate that China's carbon emission trading policy has generated some employment dividend, and the total effect is about 11.5 percent when the ratio of individual sample is considered. In addition, the impact of carbon emission trading policy on employment is gradually increasing, and the employment effect of carbon trading policies in different pilot areas of China is quite dissimilar. The findings of this paper confirm the positive employment effect of China's carbon emission trading policy, and have important policy implications for the further promotion of the national carbon emission trading market. At the same time, it helps to clarify the relationship between environmental protection and full employment. • Verifies and evaluates the spatial spillover effect of carbon trading policy. • Constructs a Triple Difference Model for evaluating the impact of carbon trading policies on the labor demand of enterprises. • Finds about 10% positive spillover effect of the carbon emission rights trading policy in China. • Shows about 11.5% total employment effect of carbon emission trading policy when the individual sample ratio was considered. [ABSTRACT FROM AUTHOR]

Emissions trading system (ETS) is a cost-effective way towards achieving the carbon neutrality goal. Based on the gaps in the research on carbon allowance allocation vis-à-vis the carbon neutrality target, this study examines how to allocate carbon allowances equitably and effectively among Chinese provinces. Different from the previous research that mainly considers responsibility, ability, and potential of equity dimensions, this paper proposes a composite indicator allocation approach based on the equity of history, demand, contribution, and guarantee, and it also employs the entropy method and expert survey method to obtain the indicator weight values in different scenarios. Results show that the carbon allowances of some provinces, such as the forest-rich province of Yunnan, vary significantly in five scenarios, but little differences are observed for some provinces, such as the high historical emissions province of Shanxi. More provinces achieve data envelopment analysis efficiency in the preferred scenario. Compared with the objective scenario, the required emission reduction in the preferred gross domestic product (GDP) scenario is 231 million tonnes less, and the emission reduction cost is 190 billion yuan less. It is suggested that the Chinese government should adopt the allocation scheme in preference for the GDP scenario. [ABSTRACT FROM AUTHOR]

The coverage of Emission Trading Scheme (ETS) has been widely discussed. Based on the plans of the various stages of the National Development and Reform Commission in China, we explore the different impacts of different plans by applying recursive dynamic computable general equilibrium. What we found is different. Covering more industries, carbon prices will be lower so that the emission reduction motivation of each covering enterprises will be reduced. However, the resource attributes of carbon emission allowance will gradually emerge. In general, we found that the changes in the sectoral coverage will bring about the changes in the two effects in ETS market: carbon price effect and the allocation effect. The interaction of the two effects has led to a positive impact of both low-coverage and high-coverage on reducing emissions and improving the energy efficiency. This paper suggests that just covering three enterprises that are easy-to-MRV (monitoring, reporting, and verification) is enough for emissions reduction: cement, chemical and electric power, which can also achieve high emission reduction efficiency and can effectively reduce supervision cost. • A dynamic recursive CGE model is established in this paper. • There are two effects in ETS market: carbon price effect and the allocation effect. • Reduction efficiency is an inverted U-shaped curve to the changes of coverage. • Cement, chemical and electricity are encouraged to participate in ETS. [ABSTRACT FROM AUTHOR]

The implementation of market-based climate policies represented by the emission trading system (ETS) is an important path for countries to participate in global climate governance and achieve the goals of carbon emission peaking and carbon neutrality. Whether the covered firms can improve financial performance through bearing responsibility for cutting emissions, a "win-win" of environmental and economic achievement, is an important way to evaluate the effectiveness of ETS. Based on the Chinese A-share listed firms in industrial sector during the period of 2010–2017, this paper employs PSM-DID method to investigate the impact of China's pilot ETS on financial performance of the covered firms. The results show that the covered firm's financial performance is improved by the implementation of pilot ETS, which can increase firm's ROA by 0.01 unit. Specifically, the pilot ETS can significantly improve the financial performance of non-state-owned firms, without affecting state-owned firms. Similarly, the financial performance improvement is more significant for firms in non-energy industries. Furthermore, the pilot ETS can motivate the covered firms to gain financial profit through cutting carbon emission as a mediation path, and the mediation effect size of carbon emission intensity is 0.001. Besides, firm's innovation ability weakens this mediation path, and the well-developed institutions in pilot area, proxied by high degree of marketization, only weaken the first part of the path, namely, carbon emission reduction led by ETS. • ETS achieves a win-win of carbon emission reduction and financial performance improvement. • The improvements by ETS are heterogeneous in ownership and industry. • Firm's carbon emission intensity plays a mediation role. • Firms can gain more benefit under the ETS regulation if the market monopoly is strong. [ABSTRACT FROM AUTHOR]

Promoting environmental regulation and the reduction of carbon emissions is of great significance for sustainable development. China plans to achieve the following two major goals by 2030: to experience the peak of carbon dioxide emissions, and to be at the forefront of innovative countries in the world. The realization of these goals not only depends on the environmental regulation policy regarding carbon emissions, but also on the development imbalance among Chinese provinces. The Porter hypothesis theory holds that environmental regulation can produce the Porter effect and promote enterprise innovation; but few studies focused on the causal relationship between environmental regulation and the regional Porter effect. Under this framework, this paper uses propensity score matching - difference in difference (PSM-DID) to construct a quasi-experiment on China's carbon emissions trading pilot policy. Dynamic panel data models are used to double test whether environmental regulation can stimulate the regional Porter effect. The empirical results show that: (1) Under the premise of multiple robustness tests (whether quasi-experimental or dynamic panel data models), no evidence was found in support that environmental regulation can stimulate the regional Porter effect. (2) The reason why the regional Porter effect does not been stimulated is that the pollution heaven effect, induced by the carbon emissions trading pilot policy, counteracts the Porter effect to a certain extent. (3) There is no non-linear relationship between environmental regulation and the regional Porter effect. (4) The analysis of spatial heterogeneity shows that environmental regulation cannot stimulate the Porter effect in the eastern, central, and western regions of China. This suggests that it is very important to establish appropriate provincial environmental regulation objectives and to conduct appropriate environmental regulation in combination with local resource endowments. This study provides quantitative evidence toward an in-depth understanding of the relationship between environmental regulation and the regional Porter effect as represented by the pilot policy of carbon emissions trading. A certain degree of reference is provided for the practice of environmental regulation in other developing countries. • Environmental regulation cannot stimulate the regional Porter effect. • The pollution heaven effect explains why regional Porter effect is not stimulated. • No nonlinearity exists between environmental regulation and regional Porter effect. • Environmental regulation cannot stimulate the Porter effect in all Chinese regions. • The government should appropriately strengthen environmental regulation. [ABSTRACT FROM AUTHOR]

The power sector accounted for almost 40% of China's carbon emissions in 2017 and is the first industry that is included in the national carbon emission trading system, so the current paper carries out a study on allocating carbon emission allowances for the power sector. Different from previous studies, this article assigns carbon emission allowances to 30 provinces according to the principles of equality, efficiency, and sustainability rather than just using the principles of equality and efficiency. We first apply the entropy method to initially distribute emission allowances to 30 provinces. Then, a zero-sum gains data envelopment analysis (ZSG-DEA) model is used to test the efficiency of quota allocation and redistribute the carbon quotas across 30 provinces continuously until the quotas are optimally distributed. The results show that in 2030, Guangxi, Hainan and Shandong have the most emission quotas, while Heilongjiang, Jilin and Qinghai have the least emission quotas. By comparing the quota share of each province in 2017 with 2030, it is found that Hainan, Guangxi and Qinghai located in western China have small emission reduction challenges, while there are great difficulties for provinces Jiangsu, Shanxi and Shandong situated in the central and eastern China to cut down the emissions. • Multiple criteria were used to allocate carbon quotas of China's electricity sector. • We used the entropy method to initially allocate emission quotas to 30 provinces. • A ZSG-DEA model was used to redistribute the carbon quotas across 30 provinces. • Provinces located in central and eastern China have more challenges in decarbonizing. [ABSTRACT FROM AUTHOR]

This paper proposed a model-based framework to optimize the energy-water-emissions nexus (EWEN) for regional electric power system (EPS) planning. The framework integrated the superiority of bi-level programming (BLP), two-stage stochastic programming (TSP), mix-integer programming (MIP), interval parameter programming (IPP) models and carbon emission trading (CET) mechanism, which could effectively deal with the planning problems in the EWEN optimization process. BLP helped decision makers make leader-follower choices when they have conflicting preferences. TSP with IPP could validly address the uncertain information expressed as interval values with unknown distribution. MIP was introduced as an efficacious tool to evaluate the capacity expansion potential in EPS. CET mechanism was applied to reinforce the CO 2 mitigation effect during the EWEN optimization process. Then the proposed framework was applied into a case study in Shanxi Province, a main thermal power base in China to optimize the EWEN. Results indicated that the power supply structure was inclined to show a low-carbon transition trend in the planning periods. Meanwhile, coupled with the strict water conservation policy, every 5% reduction in carbon emission density would lead to an average decreasing rate of 8% for SO 2 , 3% for NOx and 12% for PM. This study may help provide an effective way to deal with planning problems with conflicting and sequential goals under uncertainty and make better tradeoff strategies in EWEN optimization in EPS. • Propose a stochastic leader-follower framework for energy-water-emission nexus. • Control uncertainty by the combination of TSP and with IPP. • Interactions of CO 2 emissions and air pollution emissions are revealed. • Introduce CET mechanism to help improve the CO 2 mitigation effect. • The empirical results demonstrate the excellent performance of the framework. [ABSTRACT FROM AUTHOR]

China launched seven emissions trading scheme (ETS) pilots in 2011, and a national ETS, at the end of 2017 in an attempt to reduce its greenhouse gas emissions (GHGs) and drive its extensive energy transition in a cost-effective way. The Hubei province pilot ETS has operated since 2014, and an analysis of its effectiveness can provide lessons for the nascent national system. This paper disaggregates Hubei's industrial carbon dioxide (CO 2) emissions from 2005 to 2018 into economic scale, economic structure, energy efficiency, and energy structure effects using the logarithmic mean Divisia index (LMDI). Difference-in-difference (DID) models then assess the implementation effectiveness of this ETS, and its impact on the main influencing factors of the LMDI. Ten cities each in the Hubei and Hunan provinces are selected as treatment and control groups, respectively, in the DID models. Results show that the change in industrial CO 2 emissions is mainly due to the economic scale and energy efficiency effects. After the ETS implementation, the energy structure effect has a limited impact on emissions, while the economic structure effect makes a negligible contribution. Moreover, the implementation of the ETS has had little demonstrable impact on industrial CO 2 emissions, gross domestic product (GDP), energy consumption intensity, and CO 2 emission intensity. This lacking of impact is caused by the GHG monitoring capacity deficits of the local Development and Reform Commission, and irrational quota allocations. Effective supervision and quota allocation should be developed to increase the impacts of the ETS. [ABSTRACT FROM AUTHOR]

Facing the huge pressure of emission reduction, China officially launched a national carbon emission trading system at the end of 2017. The power industry is an important breakthrough in the construction of China's carbon emission trading system. To push the optimization of the power structure through carbon constraint is the necessary path to promote the transformation of the power industry from fossil energy to clean and low-carbon energy. From the perspective of power consumption, this paper constructs the linkage mechanism model of China's carbon emission trading market, energy market and capital market and applies the DCC-MVGARCH model to analyze the dynamic linkage mechanism of the three markets. The results show that the price fluctuation of the yield series of products in each market has clustering characteristics, and the dynamic correlation has significant time-varying characteristics and persistent characteristics. The dynamic conditional correlation between the carbon emission trading market and the oil market and between the carbon emission trading market and the natural gas market are basically consistent. The dynamic correlation coefficient between the carbon emission trading market and the capital market is negative, which is related to the unreasonable quota setting in China's carbon emission market. On the basis of empirical analysis, the optimal balance weight and the optimal hedging ratio of each asset are determined. [ABSTRACT FROM AUTHOR]

Carbon price forecasting plays a vital role in establishing a reasonable and stable carbon market. A number of carbon price forecasting models have been developed to improve the effectiveness of the predictions. However, most of the previous studies failed to focus on the role of choosing the appropriate input features and only aimed to improve the forecasting accuracy. In this paper, a novel hybrid model based on feature selection and a multi-objective optimization algorithm is proposed for carbon price forecasting. More specifically, the main novel contributions of this study are as follows. A two-stage feature selection method is developed to obtain the appropriate input variables to enhance the forecasting ability. In addition, the weighted regularized extreme learning machine is optimized using a multi-objective optimization algorithm, named the multi-objective grasshopper optimization algorithm, which can obtain better forecasting results. To demonstrate the effectiveness of the developed carbon price forecasting model, two daily carbon price datasets that were collected from the China and European Union Emissions Trading Scheme, are used in this study. The results revealed that the mean absolute percentage errors of the proposed model utilizing data from the China and European Union Emissions Trading Scheme are 2.4923% and 0.8418%, respectively, which are lower than those of other compared models. In addition, the variances of the forecasting errors of the developed model are 1.1419 and 0.0038 for the data from the China and European Union Emissions Trading Scheme, respectively. These results reflect the superior forecasting ability of this method compared to other methods. Therefore, the proposed method is more effective than other models in carbon price forecasting. • A novel hybrid forecasting architecture is proposed for carbon price forecasting. • A two-stage feature selection method is proposed to gain optimal input variables. • A multi-objective optimization algorithm is used to improve the prediction results. • The developed model can perform better using both EU ETS and China data. [ABSTRACT FROM AUTHOR]