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The pilot free trade zone (PFTZ) policy is an important strategic initiative to lead green and high-quality economic development. Based on panel data from 2012 to 2019 of 287 Chinese cities, this study systematically investigates the effect of the PFTZ policy on carbon emissions by building the staggered difference-in-difference (DID) model. The results showed that the PFTZ policy significantly reduced carbon emissions and that this reduction effect increased over time. These findings hold true after robustness tests. Additionally, the heterogeneity analysis showed that the carbon emission reduction effect was more significant in coastal areas. In terms of impact mechanisms, the main driving force of carbon emission reduction from the PFTZ policy is technological progress. Furthermore, the PFTZ policy has a spatial spillover effect, which can drive neighboring cities to reduce their carbon emissions. This study provides useful policy insights for building a green low-carbon trade system and helps achieve carbon peaking and carbon neutrality goals. [ABSTRACT FROM AUTHOR]

Battery storage is critical for integrating variable renewable generation, yet how the location, scale, and timing of storage deployment affect system costs and carbon dioxide (CO2) emissions is uncertain. We improve a power system model, SWITCH-China, to examine three nationally uniform battery deployment strategies (Renewable-connected, Grid-connected, and Demand-side) and a heterogeneous battery deployment strategy where each province is allowed to utilize any of the three battery strategies. Here, we find that the heterogeneous strategy always provides the lowest system costs among all four strategies, where provinces with abundant renewable resources dominantly adopt Renewable-connected batteries while those with limited renewables dominantly adopt Demand-side batteries. However, which strategy achieves the lowest CO2 emissions depends on carbon prices. The Renewable-connected strategy achieves the lowest CO2 emissions when carbon prices are relatively low, and the heterogeneous strategy results in the lowest CO2 emissions only at extremely high carbon prices. Heterogeneous battery strategy, with each province flexibly choosing different battery strategies, achieves the lowest power system costs. However, this non-uniform strategy only achieves the lowest CO2 emissions at extremely high carbon prices. [ABSTRACT FROM AUTHOR]

In this study, we assessed the impacts of the benchmark designs of emissions allowance allocation in China's national carbon emissions trading system with plant-level data and further estimated the marginal clearing price and power supply cost in Guangdong power market under electricity-carbon market coupling with unit commitment and economic dispatch model. We find that the existing allowances benchmark would result in a considerable surplus of allowances at about 222 Mt. But the benchmarking and exemplary levels on the heat rate of power supply would motivate thermal power units to reduce CO2 emissions. Under a tight balance of supply and demand in Guangdong, peaking thermal power plants will become the marginal clearing units and higher clearing prices will add to the revenue of lower cost inframarginal renewable energy power units. However, the combined impact of electricity-carbon market coupling would cause the marginal clearing price fluctuates obviously from 0 to 1159 CNY/MWh. Compared to the baseline scenario with free CO2 allowances allocation, the efficiency of thermal power utilization would decrease by 23%-59% and the net revenue per MWh power supply of coal-fired power units would decrease by 275%-325% under the stress scenario. Our study suggests that setting a more stringent allowances allocation benchmark for carbon price discovery is necessary. As electricity-carbon market coupling changes the role of coal-fired power plants to provide flexibility service and decrease their revenues, it calls for further market designs on proper reimbursement of flexible resources, under which the electricity market can effectively achieve the synergy among accommodating new energy, ensuring resource adequacy, and delivering cost efficiency. In addition, the synergy can be enhanced by formulating a tax program, which can promote renewable energy investment. [ABSTRACT FROM AUTHOR]

As the largest carbon emitter in the world, with its transportation sector contributing the largest shares of its emission, the need for a low-carbon transition economy has become a policy agenda for China because in order to reach carbon neutrality by 2050, lowering the intensity of carbon emissions in the transportation sector will be crucial. In this regard, we used the "bootstrap autoregressive distributed lag model" to explore the impact of clean energy and oil prices on the intensity of carbon emissions in China's transportation sector. The study found that an increase in oil prices decreases the intensity of carbon emissions in the short and long run. Similarly, an increase in the level of renewable energy and economic complexity declines the intensity of carbon emissions in the transportation sector. On the contrary, the research demonstrates that non-renewable energy contributes positively to carbon emission intensity. Therefore, the authorities must promote green technology to neutralize the transportation system's detrimental effects on China's environmental quality. The implications for successfully promoting carbon emission intensity mitigation in the transportation sector are examined in the conclusion. [ABSTRACT FROM AUTHOR]

European energy crisis, triggered by the conflict between Russia and Ukraine, has again drawn attention to the decarbonization of fossil energy sources. However, few studies have objectively considered coal from an integrated life cycle and its position in the energy system. In the present study, we used the integrated life cycle analysis and fixed-effect panel threshold model to reveal that (1) power generation and heating and iron and steel smelting are the highest CO2 emission sectors. In addition, the coal chemical industry and power generation and heating are the two sectors with the highest contribution rate of CO2 emissions. (2) Based on these, underground coal gasification (UCG) and underground coal gasification-integrated gasification combined cycle (UCG-IGCC) technologies were introduced to innovate the coal life cycle (the process cycle of coal production and utilization). The panel threshold model has proved that when the energy intensity falls in the interval 0.363–2.599, UCG-IGCC technology could be the complement in mitigating CO2 emissions. (3) Finally, for the same amount of emission mitigations, the social cost of innovating coal production and utilization processes using UCG-IGCC technology will be lower than phasing out coal-fired power plants using carbon prices. For China, UCG-IGCC and renewable energy should be developed simultaneously. [ABSTRACT FROM AUTHOR]

This paper reviews the incentives for pursuing a low-carbon electricity sector that are embedded in China's regulatory and policy framework. To do so, we first describe the industry structure and the regulatory framework. Second, we explicitly review the policies that were developed to promote energy efficiency and renewable energy. These policies range from the introduction of legal requirements to undertake particular actions to pricing mechanism and financial incentives. Based on this, we tease out the challenges faced by a sector governed by a myriad of complex arrangements, different institutions and agents who face different and often conflicting incentives for pursuing environmental and energy efficiency objectives. Finally, we provide suggestions to scientifically set up low-carbon policies and to achieve the expected goals with minimum social cost. [ABSTRACT FROM AUTHOR]

This paper estimates the potential influence of China's future nationwide carbon market on clean technology innovation. To overcome data limitation issues, the energy price is adopted as a proxy for the carbon price to estimate its impact on clean innovation and R&D. Then, a counter-factual method is introduced in which the potential carbon price is mapped onto the equivalent percentage change of energy price by sector. According to our results, the carbon market shows both a redirection and a crowding-out effect on technology innovation, with the former overwhelming the latter. If the future nationwide carbon market yields a carbon price of 50 Yuan, our findings estimate that it would result in an increase in the quantity and proportion of clean invention patents in ETS-covered sectors of 2.2% and 3%, respectively, and in an increase in the quantity and proportion of clean utility patents of 3.6% and 1.4% respectively. However, the effect on overall R&D is negative, indicating that carbon costs might crowd out some R&D expenditures, but in a limited manner. Generally, the carbon market in China is expected to help redirect technology innovation onto a cleaner path. [ABSTRACT FROM AUTHOR]

This paper explores the optimization scheme of carbon trading in China based on a novel energy-saving and emission-reduction (ESER) system with carbon price constraints. With the aid of nonlinear dynamics theory, the dynamics behavior of the novel system is discussed. Genetic algorithm and back propagation neural network is used to identify the quantitative coefficients according to the statistical data of the second period in European Union (EU). Taking the actual situation in EU for instance, the variables which are sensitive to carbon trading are detailedly researched. Enlightened by the EU’s experience, an optimal road of China ’ s carbon trading is put forward. The results show that carbon emissions could be controlled by carbon trading. The investment to carbon trading hampers economic growth in the near future, and ESER technical progress is negatively correlated with carbon trading in the long run. Demand and supply relationship is closely related to carbon price, both are the important issues in carbon trading system. Excessive government control and extortionate carbon price will deliver the opposite effect and even fatal influence on carbon trading system. [ABSTRACT FROM AUTHOR]

Recycling plastic can abate the environmental pollution as well as CO2 emissions by saving the carbon-intensive feedstock input. The uncertain carbon price places significant effects on the establishment and operation of the whole supply chain. This study develops a green supply chain model combined with geographic information system (GIS) to account for carbon price uncertainty and evaluate its effects on the closed-loop supply chain (CLSC) of plastic recycling. A two-stage stochastic programming model is constructed, in which the stochastic variable, CO2 price is modelled as a geometric Brownian motion process. Six scenarios are designed with respect to price expectation and volatility. A case study is performed with the GIS information of the plastic supply chain in Zhejiang province, China. The results illustrate that triggering the establishment of reverse logistics requires a carbon price threshold significantly beyond the current level. Lower price volatility would facilitate the decision-making of investment into the reverse logistics. Mechanisms to alleviate the market variation shall be introduced. A sound market condition is desired to obtain the optimal balance that encourages the CLSC without creating extra pressure on the firms. The proposed modelling framework can be easily applied to other sectors with similar characteristics. [ABSTRACT FROM AUTHOR]

The internet has become a valuable tool for people to receive and transmit information, thus having a profound impact on their living habits and values. Based on face‐to‐face interview survey data collected in Central China, taking the biogas CCER scheme as an example, we discuss the effects of internet access on farmers' willingness to participate in the PCT scheme and desired carbon price. Our findings revealed that internet access improved the willingness of farmers to participate in the PCT scheme. We also found that it was likely to further increase the desired carbon price for those willing to participate. Further analysis demonstrated that male, young and middle‐aged, and low‐educated farmers were more likely to show greater motivation for participation in the PCT scheme due to internet access influence compared to other farmers. Additionally, we identified that the longer duration of internet access, the more likely farmers are to show a higher willingness to participate in the PCT scheme and hence the desired carbon price. In summary, the findings from this study imply that rural internet building exhibits a significant role in promoting the spread of PCT scheme and also helps to alleviate rural poverty. [ABSTRACT FROM AUTHOR]

Recently, carbon price forecasting has become critical for financial markets and environmental protection. Due to their dynamic, nonlinear, and high noise characteristics, predicting carbon prices is difficult. Machine learning forecasting often uses stacked ensemble algorithms. As a result, common stacking has many limitations when applied to time series data, as its cross-validation process disrupts the temporal sequentiality of the data. Using a double sliding window scheme, we proposed an improved stacking ensemble algorithm that avoided overfitting risks and maintained temporal sequentiality. We replaced cross-validation with walk-forward validation. Our empirical experiment involved the design of two dynamic forecasting frameworks utilizing the improved algorithm. This incorporated forecasting models from different domains as base learners. We used three popular machine learning models as the meta-model to integrate the predictions of each base learner, further narrowing the gap between the final predictions and the observations. The empirical part of this study used the return of carbon prices from the Shenzhen carbon market in China as the prediction target. This verified the enhanced accuracy of the modified stacking algorithm through the use of five statistical metrics and the model confidence set (MCS). Furthermore, we constructed a portfolio to examine the practical usefulness of the improved stacking algorithm. Empirical results showed that the improved stacking algorithm could significantly and robustly improve model prediction accuracy. Support vector machines (SVR) aggregated results better than the other two meta-models (Random forest and XGBoost) in the aggregation step. In different volatility states, the modified stacking algorithm performed differently. We also found that aggressive investment strategies can help investors achieve higher investment returns with carbon option assets. [ABSTRACT FROM AUTHOR]

Effective prediction of carbon prices matters a great deal for risk management in the carbon financial market. This article designs a blended approach incorporating secondary decomposition and nonlinear error-correction technology to predict the regional carbon price in China. Firstly, the variational mode decomposition (VMD) method is used to decompose the carbon price, and then, the time-varying filter-based empirical mode decomposition (TVFEMD) is introduced to decompose the residual term generated by VMD, and the multiple kernel-based extreme learning machine (MKELM) optimized by the sparrow search algorithm (SSA) is innovatively built to forecast the carbon subsequences. Finally, in order to mine the hidden information contained in the forecasted error, the nonlinear error-correction method based on the SSA-MKELM model is introduced to correct the initial prediction of carbon price. The empirical results show that the proposed model improves the prediction accuracy of carbon prices, with RMSE, MAE, MAPE, and DS up to 0.1363, 0.1160, 0.0015, and 0.9231 in Guangdong, respectively. In the case of the Hubei market, the model also performs best. This research innovatively expands the prediction theory and method of China's regional carbon price. [ABSTRACT FROM AUTHOR]

As a result of the COVID-19 pandemic, production costs have grown, while human and economic resources have been reduced. COVID-19 epidemic costs can be reduced by implementing green financial policies, including carbon pricing, transferable green certificates, and green credit. In addition, China's tourist industry is a significant source of revenue for the government. Coronavirus has been found in 30 Chinese regions, and a study is being conducted to determine its influence on the tourism business and green financial efficiency. Econometric strategies that are capable of dealing with the most complex issues are employed in this study. According to the GMM system, the breakout of Covid-19 had a negative effect on the tourism business and the efficiency of green financing. Aside from that, the effects of gross capital creation, infrastructural expansion, and renewable energy consumption are all good. The influence of per capita income on the tourism industry is beneficial but detrimental to the efficiency of green finance. Due to the current pandemic condition, this report presents a number of critical recommendations for boosting tourism and green financial efficiency. [ABSTRACT FROM AUTHOR]

Carbon trading price (CTP) prediction accuracy is critical for both market participants and policymakers. As things stand, most previous studies have only focused on one or a few carbon trading markets, implying that the models' universality is insufficient to be validated. By employing a case study of all carbon trading markets in China, this study proposes a hybrid point and interval CTP forecasting model. First, the Pearson correlation method is used to identify the key influencing factors of CTP. The original CTP data is then decomposed into multiple series using complete ensemble empirical mode decomposition with adaptive noise. Following that, the sample entropy method is used to reconstruct the series to reduce computational time and avoid overdecomposition. Following that, a long short-term memory method optimized by the Adam algorithm is established to achieve the point forecasting of CTP. Finally, the kernel density estimation method is used to predict CTP intervals. On the one hand, the results demonstrate the proposed model's validity and superiority. The interval prediction model, on the other hand, reflects the uncertainty of market participants' behavior, which is more practical in the operation of carbon trading markets. [ABSTRACT FROM AUTHOR]

Forests provide wood biomass to produce various wood products while sequestering CO2 from the atmosphere. The joint benefits of wood production and carbon sequestration should be considered when making forest management decisions such as those related to optimal rotation periods. In this study, we extend the Faustmann model to consider the effects of timber value and the dynamics of forests' multiple carbon pools (biomass, dead organic matter and long-period forest products) on the optimal rotation and the corresponding net present value (NPV). The theoretical framework also takes account of dynamic carbon prices and potential effects of carbon cap policies. We showcase our approach using Populus × euramericana " Nanlin895" as an example. This tree species is an important species for the planted forests in East China. The results show that: (1) multiple carbon pools increase the optimal rotation period by 4.76 per cent and the NPV by 45.66 per cent under the static carbon price scenario, (2) the tightening carbon cap facilitates carbon price variation and results in a significant increase in the NPV, while the optimal rotation period fluctuates between 8 and 10 years and (3) frequent cap policy adjustments shorten the optimal rotation period and lower the NPV even if the cap reduction target is achieved. Although the effect of carbon benefits on the optimal rotation period is small, the forest carbon trade mechanism could effectively enhance landowners' income through the tightening carbon cap. These findings have significant policy implications for forest management. Highlights   • We analyze the effects of multiple carbon pools on the optimal rotation period and the net present value. • We examine how carbon trade affects the management decision of Populus plantations. • Tightening the carbon cap promotes dynamic carbon price variation, benefiting landowners. [ABSTRACT FROM AUTHOR]

As a major carbon-emitting country, China has considerable potential for carbon capture and storage (CCS) applications, but economics is critical for CCS deployment. In this study, the levelized cost of electricity (LCOE) at province level was calculated for operational coal-fired power plants after post-combustion carbon capture (CC) retrofitting. The costs of captured CO2 and avoided CO2 were then compared. The economics of CC-retrofitted coal-fired power plants co-firing with biomass (BECC) were also analyzed. CC retrofitting is economical in North and Northwest China (except Qinghai) where coal prices are low. However, BECC retrofit is more suitable for coal-fired power plants in Central China where biomass prices are low. Therefore, the variation in the resource conditions among provinces should be considered when promoting CC and BECC retrofits. Compared with other power sources, coal-fired power generation becomes much more expensive after retrofits. We calculated the carbon price and capacity subsidy intensity that could support the retrofit of coal units. Effective carbon price should be 142.44–406.06 CNY/t for retrofits, and the capacity subsidy intensity ranges from 175.14–721.52 CNY/kW. The current carbon market and capacity market are not sufficiently developed to support retrofitting. The development of the carbon market with effective carbon price signals and proper power market mechanisms is critical to the rollout of CCS in China. [ABSTRACT FROM AUTHOR]

The conservation and efficient use of water resources are directly related to the sustainable and high-quality development in China. This paper regards the pilot policy of water-saving society construction as a quasi-natural experiment, and employs a differences-in-differences approach to evaluate the effectiveness of urban water-saving policies and exploit its drive mechanism by using the panel data of 263 cities in China from 2001 to 2016. Findings show that the pilot policy of water-saving society construction can achieve better water-saving effects, which can not only promote the reduction of urban water consumption in intensity and total amount, but also improve the efficiency of water resources utilization. And this policy has brought long-term dynamic effects on the urban water resources conservation. Heterogeneous effects exist in different types of cities, that is, the water-saving performance is more significant in cities with sufficient water resources and in central China. Besides, this paper finds that the impact of this water-saving policy on urban water resource conservation is mainly through two channels such as water resources infrastructure investment and water resources pricing. These findings provide useful inspirations for local governments to take effective economic measures to manage water resources. • Regard the pilot policy of water-saving society construction as a quasi-natural experiment. • Employ a differences-in-differences approach with the panel data of 263 cities in China from 2001 to 2016. • Evaluate the effectiveness of urban water-saving policies and exploit its drive mechanism. • Water-saving society construction can achieve better water-saving effects. • Water infrastructure investment and water pricing are important mechanisms. [ABSTRACT FROM AUTHOR]

In order to achieve the power supply change from traditional energy to clean energy in China, improving the grid parity rate of photovoltaic (PV) power is a key problem to be addressed. To establish a harmonious grid price between PV power and coal-fired power, this paper investigates the impact of carbon emission quota (CEQ) price on both PV power revenue and efficiency by constructing the carbon-electricity linkage mode with following innovative works. First, we set a trading mechanism that involves PV power plants and links carbon-electricity markets, and then propose market clearing rules for both CEQ and PV power prices. Second, we integrate market factors into the framework of power cost structure of different power sources based on the Life Cycle Cost (LCC) Theory. Third, we characterize the volatility of CEQ prices by offsetting the reduced fiscal subsidy of PV power and balancing grid price of different power sources. Our key findings show that the plan of improving current trading linkage of carbon-electricity market and grid parity scheme of PV power will be brought forward to 2023 that is 2 years ahead of schedule. What's more, in the case of completely cancelling subsidy, CEQ price should be tripled by using this linkage to accelerate PV grid parity. By showing the possible trading benefit of carbon markets, this paper will help reduce the generation cost of PV power grid connection. • We link carbon-electricity market to offset the negative impact of photovoltaic (PV) subsidy cancelling on grid parity. • The market clearing rules of carbon-electricity linkage is illustrated and expressed by formulas. • The price model of PV grid parity under the carbon-electricity linkage is constructed. • We simulate the grid parity schedule for PV power generation under the carbon-electricity linkage. [ABSTRACT FROM AUTHOR]

As China's economy is transforming into a new normal stage, the energy industry is becoming increasingly innovation-driven, which is shown particularly in renewable energy. Given that the green innovation transformation is crucially critical during China's new normal stage, this paper analyzes the direct impact of energy consumption on energy innovation and innovation transformation, and reveals the net effect of green innovation transformation on economic sustainability and energy consumption. Micro and macro empirical evidence are both provided in this paper by implementing two estimation methodologies: fixed effect model and Generalized Method of Moments (GMM) Vector AutoRegression (VAR) approach, respectively. Estimating Chinese micro 153 listed energy companies' data and macro 30 provincial data from 2009 to 2016, we find that: (1) In terms of energy enterprises' innovation activity behavior, energy consumption could promote total energy innovation, of which renewable energy innovation is stimulated far more significantly. (2) There is an increasing tendency for energy structure to transform into renewables as the energy consumption increases. (3) The green innovation transformation, instead of total innovation counts, can reduce energy consumption and benefit economic sustainability. Therefore, the structure of innovation transformation plays more significant role than total energy innovation in stimulating economic growth, and alleviating the energy consumption antinomy during China's new normal stage. In this regard, in order to stimulate green energy transformation, government should implement financing policy, reduce administrative intervention, upgrade energy legal system and improve energy pricing mechanism to encourage more research and development (R&D) activities at the core of renewable energy. • Provide evidence from both micro- and macro-economic perspectives. • Energy consumption stimulates renewable energy innovations more. • Transformation towards renewables is driven by high energy consumption. • Green innovation transformation decreases energy consumption in the long run. • Green innovation transformation benefits economic sustainability. [ABSTRACT FROM AUTHOR]

China, as the world's largest emitter, intends to achieve the peaking of carbon dioxide (CO) emissions around 2030 and to make best efforts to peak early to mitigate global change. Under this strategy, a dynamic, recursive computable general equilibrium (CGE) model is used to analyze the economy, energy, and environment impact of CO emission reduction policy based on 17 scenarios in China: carbon tax, emission trading scheme (ETS), and the mixed policy in different price level, in order to find out which kind of emission reduction strategy is more feasible. The results show that CO emission in 2030 will be reduced with the implementation of tax, ETS and mixed policy, by 10-13 %, 12-14 %, and 18-28 %, respectively. From 2016 to 2030, China can reduce 18,338-24,156 Mt CO through the implementation of mixed policy. Furthermore, relative to single policy, mixed policy has stronger effects on primary energy consumption cut, by 738-1124 Mtoe or 18-28 %, which will make CO emissions reach a peak before 2030 and the peak emission is not greater than 12 billion tons which is in line with the reduction demand in China. Thus, the mixed policy is the most effective strategy so that mixed policy is recommended to parties included in Annex I in United Nations Framework Convention on Climate Change Kyoto Protocol and other countries with large potential of emission reduction, while ETS is suggested to countries with low carbon emissions per capita which can balance economic development and CO mitigation. [ABSTRACT FROM AUTHOR]

This study estimates the effect of carbon pricing for CO 2 mitigation in China’s cement industry. The statistics and prediction show that cement production initially experienced accelerated growth and is now expected to plateau out over the next few years. The energy saving and carbon mitigation technologies considered in this estimation are at different adoption stages. Full technology diffusion is expected within 10–20 years, and the remaining technology mitigation potential stands at about 8.8% by 2025 and 10.2% by 2030. Nevertheless, attaching a price to carbon would have a limited effect. Reductions of 9.9 and 12.9 Mt-CO 2 might have been realised in 2015 under respective prices of 60 and 100 Yuan/t-CO 2 , compared to a non-pricing scenario. The reduction attributed to carbon pricing would be around 4.9 Mt-CO 2 in 2020 at both price levels, and around 70% of the mitigation may be at a marginal cost of 50 Yuan/t-CO 2 by 2020. The marginal cost for nearly 90% of the policy mitigation would be below 100 Yuan/t-CO 2 by 2030. This paper confirms the effectiveness of a command-and-control approach so far for energy saving in China’s cement industry and advises early introduction of a carbon pricing regime with consideration of policy interactions. [ABSTRACT FROM AUTHOR]

This paper analyzed the coupling relationship between the carbon market and power market and constructed a threshold regression model of carbon cost pass-through to electricity prices. Furthermore, a system dynamics model was built based on "electricity-carbon" market. The results show that first, the carbon market and power market operate independently but are interrelated. The two markets will work when Chinese emission allowances and carbon prices are effectively connected with carbon emissions and electricity prices. Second, because the electricity price formation mechanism is mainly regulated by China's government, the carbon price has a significant negative effect on the electricity price since the operation of the national carbon trading system. There is no obvious linkage effect between the CO 2 cost and electricity price. Third, under the current policies and market mechanism, the carbon price will experience the process of "remain low-rapid rise-remain high". The carbon price will drive the on-grid price and sales price up. The allowance auction mechanism and carbon cost direct pass-through can effectively reflect CO 2 cost in the electricity price. In the long term, introducing auctioning in the carbon market and reforming electricity price formation in the power sector will tap the emission reduction potential. [Display omitted] • Design of coupling relationship between China's electricity market and national ETS. • Measure the carbon cost pass-through rates in electricity market. • Build the system dynamics model of national ETS and electricity market. • Explore the factors that affect the effectiveness of CO 2 cost pass-through. [ABSTRACT FROM AUTHOR]

Promoting electrical transition in vehicle industry has become one of the main objectives for transportation sectors nowadays. However, no consensus has been reached as to whether the penetration of electric vehicles (EVs) have superiority in energy conservation and carbon reduction with life-cycle thinking. Consequently, this paper applies network evolutionary game theory to investigate the evolution trend of industry energy conservation and carbon reduction with promoting electrification in China. To fit the real decision-making environment faced by manufacturers, the greenness competition interactions, competitive strategy invasion, and market uncertainty are further considered under the impact of dual credit policy. Results show that implementing dual credit policy makes electrical transition an irreversible trend for manufacturers, but it does not mean that internal combustion engine vehicle will disappear, rather, it coexists with EVs in a certain proportion, which is negatively related to consumer's acceptance toward EVs. Meanwhile, to address energy conservation and carbon reduction, manufacturers should be encouraged to choose a fuel reduction strategy to decelerate the industry electrification trend, thus acquiring better energy conservation performances. And before increasing consumer's acceptance toward EVs, increasing the proportion of renewable source in primary energy warrants greater urgency and effectiveness to achieve life-cycle emission reduction advantage of EVs. • It is an irreversible trend for all manufacturers to choose electrical transition. • Internal combustion engine vehicles will coexist with electric vehicles eventually. • High invasion ratio of fuel reduction strategy initially is suggested. • Promoting the clean energy supply is of more urgency and effectiveness. • Optimal new energy credit price exists for fuel and carbon reduction objectives. [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]

With the continuous development of the global economy, the rapid deterioration of the global ecological environment has caused a huge impact on the future development of the world. In order to solve the problem of global warming and enhance the self-development capacity of all countries, based on the concept of sustainable development, China has set the ambitious goal of dual carbon. To this end, China is actively promoting the establishment of a national carbon emissions trading system. In response to low price competitiveness, such as nonstandard trading system, the influence of the development of the carbon emissions trading system in the future, should not only attach importance to enrich and strengthen the basic function of the carbon market, also continue to carbon pricing system and in-depth reform of the fiscal and taxation system, clear up the thoughts to the carbon market trading rules, is on its relevant rights and obligations, firmly adhere to steadily promote carbon market links between countries. Currently, China’s carbon emission trading is still in its infancy, and its effect is still limited in specific practice. Meanwhile, carbon emission trading markets in developed countries such as the United States and the United Kingdom have begun to implement carbon tariffs and other means to maintain their carbon borders. Therefore, the construction of carbon emission trading is necessary for development, but also for the sustainable development of the country. The lag of China’s carbon emission market leads to the worsening of the problem of carbon excess emissions of industries in the regions not covered, and the increased economic burden caused by the carbon barriers of other countries in foreign trade. Of course, this requires China take the path of sustainable development to continue to strengthen the system construction of carbon emission rights and promote the further optimization of their functions. [ABSTRACT FROM AUTHOR]

• This paper compares the price effects of two influential airline mergers taking place in China. • We offer the first comparative analysis of two different types of airline mergers in the Chinese airline market. • A complementary merger could also confer an increase in market power. • The negative impact of high-speed rail on fares gradually weakened after the mergers. This paper compares the price effects of two influential airline mergers taking place in China in 2010. We offer the first comparative analysis of two different types of airline mergers in the Chinese airline market: a parallel merger and a complementary merger. With a difference-in-differences approach, we found that the two types of mergers resulted in similar pricing patterns for the airlines involved in the mergers, suggesting that complementary mergers could also confer an increase in market power. It has been found that the negative impact of high-speed rail on fares gradually weakened after the mergers. [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]

Motivated by reducing carbon emissions, carbon trading market have been opened to promote environmental protection. Accurate carbon trading volume and price forecasts have far-reaching implications for environmental and energy policy formulation. As the country with the most massive carbon emissions in the world, China's carbon price trends, carbon trading volume trends, and policy orientation are of great significance. As matters stand, there are few studies on carbon price and trading volume forecasts, and no research paper has covered carbon price and trading volume forecasts for all carbon trading markets in China. In order to provide a relatively complete reference for the carbon price and trading volume in China, this paper uses six machine learning models to predict the daily carbon price and trading volume of eight carbon markets in China, including Beijing, Shenzhen, Guangdong, Hubei, Shanghai, Fujian, Tianjin, Chongqing. The prediction models include extreme gradient boosting, random forest, kernel-based nonlinear extension of the Arps decline model optimized by grey wolf optimizer (GWO-KNEA), support vector machine optimized by particle swarm optimizer, support vector machine optimized by fruit fly optimizer and simulated annealing algorithm, and radial basis function neural network (RBFNN). Moreover, an advanced data denoising method, i.e., complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), is used in the models to smooth the raw data. Because the eight carbon trading markets have different carbon price and trading volume distribution characteristics in time series, by comparing the prediction results, more suitable models for the specific carbon market can be obtained. The prediction results show that CEEMDAN-GWO-KNEA and CEEMDAN-RBFNN are more competitive in predicting carbon prices and trading volume in China because of their best performance in many datasets. The average accuracy of CEEMDAN-RBFNN and CEMDAN-GWO-KNEA in carbon price prediction is 98.40% and 97.89%, respectively. The predictive stability of each model in different application scenarios is also discussed. The results show that high prediction accuracy does not mean better prediction stability, but CEEMDAN-RBFNN and CEMDAN-GWO-KNEA can still guarantee high stability in most datasets. [ABSTRACT FROM AUTHOR]

China is pursuing aggressive action to reduce greenhouse gas emissions from its coal-dominated electric power system. Two key strategies are power market reform and carbon pricing. This paper investigates the combined effects of these two strategies in reducing CO 2 emissions from power system operations. We develop an economic dispatch model to simulate hourly power supply system operation in China Southern Power Grid in 2018 under fifteen carbon pricing scenarios; these reflect a wide range of policy ambition, from today's carbon prices to much higher ones that aim to instigate aggressive emission mitigation. Our results show that moderate carbon pricing alone is insufficient to effectively reduce CO 2 emissions without concurrent power market reform. With power market reform and as carbon prices increase, large coal units supplemented by energy storage witness higher use rates as they supplant smaller coal-fired generators, until a carbon price of 300 RMB/TCO 2 phases out coal use in favor of natural gas. Only at carbon prices higher than 300 RMB/TCO 2 do emissions begin to decrease appreciably. Geographic disparities emerge among the five provinces that comprise the Southern Power Grid, with Guangdong witnessing the most CO 2 emission reduction at high carbon prices, while emission reductions in other provinces are negligible. Carbon pricing also dramatically increases total power system costs, even at low carbon prices. Our results show the necessity of introducing power market reform and carbon pricing policies concurrently if the goal is to reduce CO 2 emissions, with the ultimate goal being a carbon price significantly greater than 300 RMB/TCO 2. Because both options will be necessary, our research maps a path to deep emission reductions in China Southern Power Grid for investors, analysts, and policy makers as discussions regarding both reforms accelerate. • We assess combined effects of carbon pricing and power market reform in China. • Carbon pricing cannot reduce CO 2 emissions without power market reform. • CO 2 reductions from carbon pricing are negligible until prices of 300 RMB/TCO 2. • Even with low carbon prices, power supply system cost increase appreciably. • Existing system can only achieve shallow decarbonization, even at 1000RMB/TCO 2. [ABSTRACT FROM AUTHOR]

• The influencing factors of carbon prices in China's carbon market are analysed. • The influencing factors and historical data are combined to predict the carbon price. • The EEMD-BP-ELM model and the CHINAGEM-E model are constructed and combined. Carbon price is one of the core indicators of the carbon market. Making accurate predictions of carbon prices based on insight into the volatility characteristics of the carbon market will not only provide a scientific basis for investors and regulators to make decisions and greatly promote emission reduction, but also effectively promote the healthy development of the carbon financial market. Based on the historical carbon price data of the national carbon market, this paper constructs the EEMD-BP-ELM model to predict the high and low frequency components of China's future carbon price. On this basis, according to China's goal of peaking carbon emissions before 2030 and achieving carbon neutrality before 2060, the CHINAGEM-E model is used to predict the trend component of the carbon price under the baseline and the 2060 carbon neutral scenarios. Finally, the trend component is combined with the high and low frequency components to obtain the price range from 2022 to 2060. We find that under the baseline scenario, China's carbon price range in 2060 is [343, 785] CNY/tCO2, while under the 2060 carbon neutral scenario, this price range is [1543, 3531] CNY/tCO2. [ABSTRACT FROM AUTHOR]

We aim to document the impact of cryptocurrencies on China's carbon price variation using some quantile techniques during COVID-19 with the daily data spanning from August 7, 2015 to April 30, 2021. In this paper, we show that cryptocurrencies have a very strong explanation power for carbon market with the non-parametric causality-in-quantiles method. In addition, cryptocurrencies can work as a good hedging candidate for carbon market at different investment horizons with the quantile coherency approach. Using hedging effectiveness measure, we further show that COVID-19 can reverse the optimal hedging ratios in our portfolio specification in cryptocurrencies‑carbon emission trading pairs while this pandemic does not have effects on the trading effectiveness. Finally, the heterogeneity and asymmetry features in the dynamic quantile-on-quantile effects are detected and the effects on carbon efficient index show relatively strong fluctuation while on carbon emission trading market are relatively strong in magnitude. Our empirical results conclude with many potential applications for policymakers and investors. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO2) Capture, Utilization and Storage (CCUS) is an indispensable part of the carbon removal technologies to achieve carbon neutrality for China. Our study focuses on China's CCUS pathways, and draws out three key conclusions: (1) in terms of the greenhouse gases emission reductions required to achieve carbon neutrality and based on current technology projections, the CO2 emission reductions to be achieved by CCUS are 0.6 ∼ 1.4 billion tonnes and 1 ∼ 1.8 billion tonnes in 2050 and 2060, respectively; (2) from the perspective of source-sink matching in China, the emission reduction potential provided by CCUS can basically meet the demand of carbon neutrality target (0.6 ∼ 2.1 billion tonnes of CO2); (3) with the development of technologies, the cost of CCUS in China has a great potential to be reduced in the future. It is expected that by 2030, the technical cost of the whole CCUS process (according to 250 kilometers transportation) in China will be 310 ∼ 770 Chinese Yuan per tonne of CO2, and by 2060, it will gradually drop to 140 ∼ 410 Chinese Yuan per tonne of CO2. [ABSTRACT FROM AUTHOR]

Many countries have taken stringent climate policies to minimize the risks by climate change. But these policies could burden households and the poor with the extra costs and threaten their wellbeing. However, the consequences of climate policies on poverty and welfare loss are seldom presented in stringent long-term climate change mitigation projections. Carbon pricing is a cost-effective approach; how it affects households varies among countries. This study investigated the distributional effects and poverty implications of carbon pricing in China during the transition towards carbon neutrality and the Paris Agreement's long-term goals. We assessed multiple poverty and equity standards in future scenarios with a newly developed integrated assessment model. It was found that climate change mitigation efforts would not greatly hinder poverty alleviation in China, with the poverty headcount under the $3.2/cap/day-threshold being less than 0.3 million people in 2050 in most scenarios. A carbon tax became a regressive factor mainly due to price increases in food and energy goods. This indicates that the distributional effects on carbon pricing should be considered. For example, supplementary policies that compensate for price changes, such as subsidies and early mitigation actions, that lead to modest price increases in the long term are worthy of consideration as valid instruments for the just transition towards the 2 °C or even 1.5 °C pathway. [ABSTRACT FROM AUTHOR]

This article undertakes a systematic study of press articles on climate change in the rich West (Norway), the emerging East (China) and the developing South (Ghana) to explore the cognitive basis for collective climate policy action. Newspapers depict Ghana moving out of a climate-victimhood towards a more active climate policy for development; China figures as spearheading energy efficiency and clean technologies for growth; while Norway is described as exporting its climate action. Our analysis finds little common ground for climate mitigation through binding climate emission limits and carbon pricing. A pluralistic 'green growth' strategy would have greater chances of success. The article also highlights differences in sources and story types: Norway features much enterprising journalism, and academics are the dominant source. In China and Ghana most articles are routinized, with politicians and public officials dominating in China, whilst the press makes heavy use of international sources in Ghana. [ABSTRACT FROM AUTHOR]

Long-haul heavy-duty freight sector has always been relying on diesel fuel and hard to decarbonize. Hydrogen fuel-cell trucks (HFCTs) can play a critical role in substituting the diesel trucks and achieving carbon neutrality in freight sector. However, the extremely high cost has impeded their penetration. This paper proposed that government could harness freight platform to promote HFCTs by issuing the platform licenses with strings attached that priority dispatch and commission discount have to be provided to HFCT drivers. To simulate the effects of the proposed policy instruments, an optimization model was developed and applied. The results validated the ability of both priority dispatch and commission discount to promote HFCTs' penetration. And combining the two mechanisms together can at most decrease the need for subsidy by 79%. Then the environmental effects were evaluated and the obtained emissions abatement cost ranges from 584 to 3712 RMB/t, which significantly exceeds the current carbon price in China. Besides, sensitivity analyses of key parameters have been conducted. It is found that the effects on promoting HFCT penetration of increasing subsidy is marginal diminishing. Business model innovation as well as further cost reduction of trucks and hydrogen fuels through technology progress are still in need. • The platform-based policies are proposed to develop hydrogen trucks. • Priority dispatch and commission discount can promote hydrogen trucks' penetration. • The CO 2 abatement cost of the proposed policies ranges from 584 to 3712 RMB/t. • The effect of subsidy on hydrogen trucks promotion is marginal diminishing. [ABSTRACT FROM AUTHOR]

Carbon emissions in air travel have attracted widespread attention with the fast development of the aviation sector. Currently, biofuel usage has the potential to curb these emissions due to the bottleneck of other aircraft emission reduction technologies. This paper studies carbon tax policy-induced air travel carbon emission reduction and biofuel usage in China considering the interactive relationship between an authority and multiple airlines by a bi-level model and an interactive solution approach. Then a case study based on airlines from southern China's Sichuan Province is conducted to explore useful insights, with scenario analyses being performed. The computational results indicate that the policy could be useful for air travel carbon emission reduction and biofuel usage improvement in China. These results and analyses provide insights to the authority for the tradeoffs between policy equity and carbon emissions reduction effectiveness, and airlines for profitability. • Carbon tax policy-induced air travel carbon emission reduction in China is studied. • A bi-level model considering interaction of an authority and airlines is developed. • Trade-off between the effectiveness and equity of the carbon tax policy is analyzed. • A case study based on airlines in China is provided to explore useful insights. • The policy plays a vital role in carbon emission reduction and biofuel usage. [ABSTRACT FROM AUTHOR]

Emissions trading system (ETS) is an effective approach to achieve China's "double carbon" targets. An accurate measurement of carbon MAC (marginal abatement cost) serves as the basic evidence for the stability of ETS and market validity. This paper constructs a comprehensive analytical framework, including four parametric and two non-parametric methods, to analyze the efficiency and carbon MAC of 92 large coal-fired power plants in China. Results show that the average technical efficiency and shadow price were 0.92 and 13.63 RMB/ton, respectively. As verified by Monte Carlo simulations, each method has its cons and pros, while the MAC calculated by the parametric stochastic frontier analysis (SFA) is the closest to the real carbon market price. Additional analyses show that the MAC is positively related with plant scale and negatively related to the provincial carbon intensity targets. This result suggests power plants' technological progress and the asymmetric government subsidies. [ABSTRACT FROM AUTHOR]

Two emerging policy instruments, carbon pricing and green investments, highlight a complementary relationship between climate mitigation and economic growth. As such, they both advance climate policy differently from command-and-control methods. The central government in China has announced a vision of promoting the two emerging instruments; however, there may be a gap between the central government's vision and local governments' practice. This study measured the application of the three instruments (command-and-control, carbon pricing, and green investments) at the city-level, and described the trends in instrument use from 2011 to 2019. The overall evolution was as follows. Local governments adopted diversified instruments, including rapid but not widely developed carbon pricing, and maintained the command-and-control method. The evolution was different in cities that emphasized the co-benefits of climate and air pollution control; this reflected a binary instrument approach that included the development of both command-and-control and green investment methods. The results identified notable gaps in the application of the green investment method between central and local governments; however, in cities that emphasize co-benefits, the efforts to bridge central–local gaps should mainly focus on the carbon pricing method. [ABSTRACT FROM AUTHOR]

Clarifying the time-varying spillovers among pilot carbon emission permit trading markets in China is an important foundation for building the national carbon emission trading market. We calculate the dynamic spillover of carbon price return among the pilot carbon emission permit trading markets in China with the time-varying connectedness approach. The dataset is constructed from transaction data from seven pilot carbon markets in China during the period of June 23, 2014, to December 31, 2020. The quantitative analysis suggests that (i) Beijing and Chongqing carbon emission trading markets are the main spillover markets of carbon price returns, with strong pricing power, while the Guangdong and Tianjin markets are the main receivers of the price return spillover in other pilot carbon emission trading markets. (ii) The spillover effect among China's carbon markets has a strong policy orientation. The improvement and development of the carbon market driven by macroeconomic regulation and control policies can effectively improve the spillover ability of the carbon market, and the market trading activity, namely the volatility of the carbon price return rate, can amplify the spillover ability of the carbon market in the short term. (iii) There exist three types of price return spillover among China's pilot carbon emission trading markets, including central divergence, one-way chain transmission, and circular spillover. Along with the improvement of market operation efficiency, the central divergent type of spillover shifts to the pattern of circular spillover. It is necessary for the government to improve market efficiency and ensure the coordinated development of China's pilot carbon emission trading market and national carbon emission trading market. [ABSTRACT FROM AUTHOR]

The scientific judgement of the structural abrupt transition characteristics of the carbon market price is an important means to comprehensively analyze its fluctuation law and effectively prevent carbon market risks. However, the existing methods for identifying structural changes of the carbon market based on carbon price data mostly regard the carbon price series as a deterministic time series and pay less attention to the uncertainty implied by the carbon price series. We propose a framework for identifying abrupt transitions in the carbon market from the perspective of a complex network by considering the influence of random factors on the carbon price series, expressing the carbon price series as a sequence of probability density functions, using the distribution of probability density to reveal the uncertainty information implied by carbon price series and constructing a recurrence network of carbon price probability density. Based on the community structure, the break index and statistical test method are defined. The simulation verifies the effectiveness and superiority of the method compared with traditional methods. An empirical analysis uses the carbon price data of the European Union carbon market and seven pilot carbon markets in China. The results show many abrupt transitions in the carbon price series of the two markets, whose occurrence period is closely related to major events. [ABSTRACT FROM AUTHOR]

• Carbon emissions trading inhibits green technology innovation in the short run. • Carbon emissions trading will reduce the carbon emissions and carbon intensity greatly at this stage. • Carbon emissions trading has a crowding-out effect on R&D investment and increases the carbon trading price, which inhibited green technology innovation. • It is necessary to control the scale of carbon emission quota and diversify the subjects of carbon trading. Carbon emissions trading is an important measure to promote high-quality economic development. Based on the panel data of 30 provincial administrative regions in China from 2008 to 2017, this paper uses the difference-in-differences method to analyze the impact of carbon emissions trading on green technology innovation. The results show that: (1) Carbon emissions trading inhibits green technology innovation in the current stage, but greatly reduces carbon emissions and carbon intensity; (2) Carbon price and R&D investment are the mainly working channels, carbon emissions trading has a crowding-out effect on corporates' R&D investment and increases the carbon trading price, which in turn inhibits green technology innovation; (3) Carbon emissions trading has a stronger inhibitory effect on green technology innovation in eastern regions and regions with low emission intensity. Local government competition positively moderates the green technology innovation effect of carbon emissions trading. However, the command-controlled environmental regulations and the scale of the carbon emission quota have opposite effects, with the compatibility of environmental regulation tools remaining to be resolved. Therefore, it is necessary to control the scale of carbon emission quota to diversify the subjects of carbon trading and strengthen the impact of market-incentive environmental regulation tools. [ABSTRACT FROM AUTHOR]

• Pricing carbon without recycling revenue decreases GDP and increases inequality. • Recycling carbon revenue with a uniform tax return rate widens the income gap. • Recycling revenue with a progressive one-step tax return narrows the income gap. • Two-step schemes via general transfer payment distort the primary distribution. • Progressively recycling enhances redistributive effects mainly via vertical effect. Carbon pricing policies are effective tools for mitigating carbon emissions; however, they also alter income distributions. Progressive individual income tax systems help redistribute income and reduce inequality. This paper evaluates the effects of carbon pricing policies and revenue recycling schemes on inequality and assesses the redistributive effects of individual income tax. We adopt a dynamic multi-regional CGE model and extend it in terms of the labor supply, tax revenue, and government expenditures. We obtain several key findings. Carbon pricing without revenue recycling increased income inequality, and the Gini coefficient was 0.59% and 1.88% higher than the benchmark in 2030 and 2040, respectively. When the revenue was recycled via individual income tax returns, the proportional recycling scheme, i.e., all income groups had the same tax return rate, continued to widen the income gap. The progressive recycling scheme, i.e., lower income groups received higher tax return rates, narrowed the income gap by reducing distortions in the economy and enhancing the redistributive effects of individual income taxes. The Gini coefficient was 0.34% and 0.71% lower than the benchmark in 2030 and 2040, respectively. If the central government allocated the carbon revenue to the local governments via general transfer payments, the redistributive effect was magnified, but a pronounced economic distortion widened the income gap. If the tax return rates were categorized by labor groups, the pronounced vertical effect of the redistributive effect benefited income equality most, while the reranking effect weakened that benefit. [ABSTRACT FROM AUTHOR]

This paper studies static and dynamic connectedness among carbon, traditional (oil and coal)/new energy and material (iron, aluminum, cement, and plastic) markets based on the Diebold Yilmaz (2012) method and the Barunik and Krehlik (2018) method. First, total connectedness is larger in the short term and enhanced after the COVID-19 outbreak. Second, material markets exhibit higher explanatory power; plastic prices, for example, have played a leading role during the pandemic crisis according to the networks. Third, the spillover of China's carbon markets post-outbreak is about twice as large as pre-outbreak, showing positive net connectedness in the medium and long term. Carbon markets' spillover is relatively small and mainly contributes to new energy. Finally, time-varying analysis demonstrate that the positive and negative values of time-varying connectedness peak due to economic shocks or global emergencies. High connectedness with longer duration may be caused by a sudden emergency rather than anticipated events. These findings can offer significant benefits to policymakers, high-carbon businesses and investors in crafting appropriate strategies with heterogeneous frequency horizons. • Spillovers among carbon, traditional/new energy and material markets are examined before and during the COVID-19. • Spillover effects of materials are strongest. • China's carbon market's spillover is small, and carbon prices have positive net connectedness in the medium and long term. • New energy has become the main net transmitter during the COVID-19 pandemic. • Spillovers with longer duration are brought by unexpected crisis rather than anticipated events. [ABSTRACT FROM AUTHOR]

This study aims to examine the green innovation effect of the carbon emissions pilot policy in China. First, using the difference-in-differences method and regressions of instrumental variables using the data from Chinese listed firms, we verify that the policy promotes green innovation among regulated firms and is more pronounced among state-owned enterprises, firms in the eastern region, and those with lower financing constraints. Furthermore, this positive effect spreads downstream relative to the regulated firms through input–output linkages, but reduces green innovation to upstream firms. Accordingly, such diffusion of innovation is achieved through the price mechanism. The results necessitate the introduction of various derivatives to mobilize the market to reduce the speculative volatility of carbon prices. In addition, relevant supporting policies must be established to encourage corporate innovation to reduce the crowding-out effect owing to emission reduction and the nonmarket factors. [ABSTRACT FROM AUTHOR]

Carbon market, which is capable of scientific quantifying and marked-based pricing of carbon emission, is an important way for countries to achieve the target of carbon emission reduction. The global carbon market, after more than ten years of development, has developed a mature mechanism. China started the trial of carbon market in 2011. After ten years of exploration, the national carbon trading market was officially launched in mid-July 2021. Against the backdrop of carbon neutrality, the national carbon market will shoulder a greater mission of carbon emission reduction and speed up its financialization and internationalization. However, it should take a dialectical attitude toward the opportunities and risks of carbon market financialization. In the future, China can promote the development of carbon market through efforts to develop market participants, clarify the attributes of carbon finance, prevent potential risks of carbon finance, improve the connection mechanism with the international carbon market, and innovate carbon finance services. [ABSTRACT FROM AUTHOR]

The environmental consequences of economic policy uncertainty (EPU) and oil price changes have attracted much attention in recent years, but few studies have estimated the asymmetric impact. This research investigates the symmetric and asymmetric effects of EPU and oil prices on carbon emissions in the USA and China. Based on monthly data from 1995:1 to 2019:12, we address this issue by applying the ARDL and non-linear ARDL cointegration methodology. The symmetric results show that the change in EPU has no evident impact on carbon emissions in the short and long run for the USA and China, and oil prices have a lag effect in this regard. The non-linear ARDL estimation documents significant asymmetric effects of EPU and oil prices. Specifically, the negative change in EPU facilitates emissions in the USA in the long and short run, and a unit increase in EPU increases emissions by 2.24% and 4.95%, respectively, whereas its positive change does not produce any significant effect. Carbon emissions in China are significantly and positively affected by the positive change in EPU only over the long run, and an increase in EPU increases emissions by 0.04%. Furthermore, the positive shock of oil prices significantly and positively influences emissions in the long run, and a unit increase in this factor increases emissions by 15.73% and 0.44% in the USA and China, respectively. Moreover, the short-term effect of the negative shock of oil prices exhibits a lag effect. The empirical results provide a practical reference for the USA and China to craft robust policies on emission cutting. [ABSTRACT FROM AUTHOR]

Climate change and increased greenhouse gas emissions boost the global average temperature to less than 2°C, which is the estimated breakeven point. The globe is moving into blue pollution economies as the environmental sustainability objective becomes more distorted. The study looked at three United Nations Sustainable Development Goals, namely (i) affordable and clean energy; (ii) industry, innovation, and infrastructure; and (iii) climate change, to see how far the Chinese economy has progressed toward green and clean development strategy. In the context of China, the "pollution damage function" was intended to refer to carbon damages related to carbon pricing, technological variables, sustained economic growth, incoming foreign investment, and green energy. The data was collected between 1975 and 2019 and analyzed using various statistical approaches. The results of the autoregressive distributed lag model suggest that carbon taxes on industrial emissions reduce carbon damages in the short and long run. Furthermore, a rise in inbound foreign investment and renewable energy demand reduces carbon damages in the short term, proving the "pollution halo" and "green energy" hypotheses; nonetheless, the results are insufficient to explain the stated results in the long run. In the long run, technology transfers and continued economic growth are beneficial in reducing carbon damages and confirming the potential of cleaner solutions in pollution mitigation. The causal inferences show the one-way relationship running from carbon pricing and technology transfer to carbon damages, and green energy to high-technology exports in a country. The impulse response estimates suggested that carbon tax, inbound foreign investment, and technology transfers likely decrease carbon damages for the next 10 years. On the other hand, continued economic growth and inadequate green energy sources are likely to increase carbon pollution in a country. The variance decomposition analysis suggested that carbon pricing and information and communication technology exports would likely significantly influence carbon damages over time. To keep the earth's temperature within the set threshold, the true motivation to shift from a blue to a green economy required strict environmental legislation, the use of green energy sources, and the export of cleaner technologies. Source: Authors' self-extract [ABSTRACT FROM AUTHOR]

Carbon capture and storage (CCS) technology is an attractive technique to help power enterprises with carbon emission reduction. In this paper, a two-stage CCS retrofit investment in an existing coal-fired power plant in China including the first stage (demonstration project) and second stage (commercial operation) is taken as a case to decide when and whether to invest. Distinguished from previous models, a binomial lattice compound real options model including the options to defer and expand is established. Further, the accounting approaches to certified emission reductions (CERs) based on the thermodynamics principle are first proposed concerning this model. We find the total invest value under compound options model is less than zero, although greater than that by NPV method. The results indicate carbon prices and subsidy policy, respectively, play a dominating role in initiating the CCS investment at the first and second stage. The growth in government subsidy at the first stage has obviously greater effects on decreasing critical carbon trading prices. Besides, the minimum critical carbon price is 87.09 RMB/ton with full subsidy, greater than the current price (56 RMB/ton). This also illustrates it is not the optimal occasion to invest in a CCS retrofit project for power enterprises. [ABSTRACT FROM AUTHOR]

Planning a portfolio that includes different power generation technologies is an important method to ensure expected value and to reduce risks for the project investment of electric-power enterprises. This paper evaluates the optimal investment portfolio strategies implemented by electric power enterprises by using real option and portfolio optimization methods. The real options method is used to generate investment values and their distribution. These serve as the input variables of the portfolio optimization model. The portfolio optimization model is built based on the conditional value at risk. The optimal investment is analyzed by considering four policy scenarios: different expected investment values, the phase-out of subsidies, tightened carbon reduction standards, and different initial renewable energy certificate prices. A case study is conducted to analyze the investment decision of an electric power enterprise in China. The results show the optimal investment portfolio strategy, the investment value, and the conditional value at risk. The optimal decision for ensuring a relatively high expected value while reducing risks is to increase the share of solar PV power generation and wind power generation in current conditions. Tightened carbon reduction standards and higher renewable energy certificates prices are conductive to increase the investment value, reduce the risk of loss and increase the share of renewable energy power generation. In contrast, the phase-out of the subsidies had the opposite effect. The methodology and results can provide a reference for investors to guide the formulation of the optimal investment decision and for the government to optimize the policy effect. • Evaluate the investment portfolio strategies of power enterprises under multiple-policy scenarios of renewable energy. • Use the real option and portfolio optimization method. • Show the optimal investment portfolio strategy, the investment value, and the conditional value at risk. [ABSTRACT FROM AUTHOR]

Sectoral coverage is a chief challenge in the design of carbon mitigation policies, this paper addresses such a concern within a hybrid regulation setting in which a carbon tax is adopted for complementary regulation of emission sources outside the Emission Trading System (ETS) in China. With a focus on the efficiency of the hybrid system, the regulated sectors are identified by linkage analysis and the resulting price changes is captured by the input-output (I-O) price model. The simulation shows that, in terms of the price incentives, the proposed carbon tax is a necessary complement to the ETS, in respect of both magnitude and structure. As a result, a mixed policy setting can be expected to have an efficiency advantage over the ETS alone. Understanding of the joint determination of the sectoral coverage and the corresponding price incentive effect is a new contribution to the theoretical literature on designing market-based carbon policies, which has substantial policy implication for the future design of instruments targeted at achieving China's post-2020 mitigation commitments. [ABSTRACT FROM AUTHOR]