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Environmental sustainability has become one of the most common phrases in discussions about climate change. This study examines the impact of clean energy investment and financial development on environmental sustainability and China's economic growth, using manufacturing value-added and urbanization as moderator variables from 1970 to 2016. We used advanced econometric methodologies for empirical estimations, used structural break unit root tests, fully modified least square, dynamic least square, and robust least square multiple regressions for long-run estimates. Overall, the results determine that clean energy investment is negatively associated with CO2 emissions and ecological footprint while positively associated with China's economic growth. Financial development, manufacturing value-added, and urbanization are positively associated with CO2 emissions, ecological footprint, and China's economic growth. Moreover, clean energy investment improves environmental sustainability at the expense of economic growth. Financial development, manufacturing value-added, and urbanization encourage economic growth at the expense of environmental sustainability. We argued that the local governments play a critical role in lifting the outstanding barriers to cleaner energy investment, addressing disincentives, including pricing carbon dioxide emissions, reforming inefficient nonrenewable fossil fuel subsidies, and addressing regulatory and market rigidities that can undesirably affect the attractiveness of clean energy investment. Policymakers are suggested to encourage green finance strategy for the financial sector to broader sustainable development objectives. At the heart of green manufacturing, industrialization policies are needed to integrate diverse intentions, like inclusive growth, environmental protection, and productivity through a wider range of economic, social, and environmental policy frameworks suitable for decoupling growth from social and environmental unsustainability. [ABSTRACT FROM AUTHOR]

This paper focuses on the estimation of carbon shadow price (CSP) by applying the by-production (BP) model within a nonparametric framework. The extended BP model ensures the meaningful shadow price estimation and linkages between the sub-technologies that define production and pollution activities. We focus on the instance of the Fare-Grosskopf-Lovell index that is important for empirical analysis due to its non-radial nature. The model is applied to China's industrial sector, which has undergone considerable development in recent decades. Data from 1998 to 2017 are used for the analysis, and the results suggest that the eastern region performs the best. In general, the CSP has been increasing in all regions, suggesting that cleaner energy has been introduced into the energy mix. Further promotion of the renewables would result in a decline in the CSP. The comparative analysis is carried out to check the effects of the axioms on the resulting estimates of the CSP. [ABSTRACT FROM AUTHOR]

Climate policies that achieve air quality co-benefits can better align developing countries' national interests with global climate mitigation. Since the effects of air pollutants are highly dependent on source locations, spatially nuanced policies are crucial to maximizing the achievement of co-benefits. Using the coal power industry as a case study, this study presents an interdisciplinary approach to assessing facility level co-benefits at every specific source location in China. We find that co-benefits range from US$51-$278 per ton CO2 reduction nationwide and are highly heterogeneous spatially, with "hotspot" regions that should be the priority of emissions reduction policies, and that provinces should use different techno-economic strategies to reduce emissions. The location-specific co-benefit value plus a carbon price serves as a unified environmental indicator that enables policy makers to more accurately understand the social costs of electricity generation from coal burning and provides a scientific framework for geographically nuanced policymaking. Spatially nuanced policies are necessary for maximising co-benefits of carbon-emissions reduction from coal-fired power plants. Here the authors present an approach integrating costs of CO2 and air pollution emissions to better understand social costs of electricity generation from coal burning in China. [ABSTRACT FROM AUTHOR]

Carbon emission right allowance is a double-edged sword, one edge is to reduce emission as its original design intention, another edge has in practice slain many less developed coal-consuming enterprises, especially for those in thermal power industry. Partially governed on the hilt in hands of the authority, body of this sword is the prices of carbon emission right. How should the thermal power plants dance on the blade motivates this research. Considering the impact of price fluctuations of carbon emission right allowance, we investigate the operation of Chinese thermal power plant by modeling the decision-making with optimal stopping problem, which is established on the stochastic environment with carbon emission allowance price process simulated by geometric Brownian motion. Under the overall goal of maximizing the ultimate profitability, the optimal stopping indicates the timing of suspend or halt of production, hence the optimal stopping boundary curve implies the edge of life and death with regard to this enterprise. Applying this methodology, real cases of failure and survival of several Chinese representative thermal power plants were analyzed to explore the industry ecotope, which leads to the findings that: 1) The survival environment of existed thermal power plants becomes severer when facing more pressure from the newborn carbon-finance market. 2) Boundaries of survival environment is mainly drawn by the technical improvements for rising the utilization rate of carbon emission. Based on the same optimal stopping model, outlook of this industry is drawn with a demarcation surface defining the vivosphere of thermal power plants with different levels of profitability. This finding provides benchmarks for those enterprises struggling for survival and policy makers scheming better supervision and necessary intervene, and the methodology developed in this paper provides a research paradigm for enterprise survival analysis. [ABSTRACT FROM AUTHOR]

• We model China's emission trajectories under the dual goals by scenario analysis. • China's emission trading scheme (ETS) is simulated through a non-linear programming. • Linking the ETS to dual goals saves emission abatement costs (EACs) by 61.41%–80.33%. • Historical responsibility scheme is optimal for its lowest initial EACs without ETS. • Peaking emissions in 2030 generates more room for economic growth in the next decade. China has committed to goals of reducing its carbon intensity by 60%–65% in 2030 above the 2005 levels and peaking its carbon emissions by latest 2030. While a unified national emission trading scheme (ETS) has been recognized as the crucial instrument to fulfill these ambitious dual goals, its potential performance remains underexplored. This paper quantifies China's need for emission reduction under the dual goals in 2030 by setting three scenarios for peak emissions. Four initial allocation schemes of carbon emission allowance (CEA) are compared according to the emission abatement costs (EACs) of China and its 30 provinces. By estimating the provincial marginal abatement cost curves, China's ETS is simulated through a nonlinear programming aimed at minimizing its total EACs. We find that in achieving the dual goals it makes economic sense to operationalize the ETS that would reduce China's EACs by 61.41%–80.33% in 2016–2030, at a carbon price of 394.55–425.75 RMB per ton CO 2. Peaking China's emissions in 2030 is the preferred choice that will trigger the largest GDP in 2016–2030. The historical responsibility scheme is recommended for the CEA allocation because of the lowest initial EACs without ETS. To allow more room for economic growth after China peaks emissions, there is a need for overfulfilling the goal of carbon intensity reduction by 2030, which is consistent with China's latest climate mitigation targets. This research not only highlights the role of ETS in realizing China's dual goals, but provides a scientific framework for evaluating the environmental policies towards multiple goals in a cost-effective manner. [Display omitted] [ABSTRACT FROM AUTHOR]

The switch of coal to gas in power generation enterprises is of great significance for tackling air pollution and mitigating climate change. Under China's emissions trading system, power generation enterprises have incentives to switch to low-carbon clean power, and the cost-benefit of switching is the basis of their decision-making. To this end, this paper studied the impact of changes in carbon and fuel prices on switching prices. The results show that: (1) For per yuan increase in the amount of natural gas, coal, and carbon, the switching price increased 4.768, decreased 5.845 and decreased 0.9994 yuan, respectively. (2) The carbon price is relatively low, and the impact of it on switching price is small. (3) The fluctuation in the carbon price, coal price and the natural gas price has a hysteresis effect on switching price. [Display omitted] • This study assesses the coal-to-gas switch possibility in Guangdong Province. • A new mode of operation of coal-to-gas switch is published. • For per yuan increase of carbon price, the switching price decreased 0.99 yuan. • The impact of carbon price fluctuations on switching price has a lag effect. [ABSTRACT FROM AUTHOR]

Carbon emission trading (CET) is an important mechanism for China to achieve carbon emission reduction targets and sustainable development. The success of its implementation depends on the scientific institutional supply design. At present, China is actively promoting the implementation of electricity marketization reform and Renewable Portfolio Standards (RPS), which would change the institutional environment for manufacturers' decision-making and trading, thus impacting CET. Accordingly, this paper aims to establish an evaluation model using the system dynamics method to simulate and evaluate the impact of RPS on CET under the background of electricity marketization reform by designing and combining different policy scenarios. The results show that: (1) The impact of electricity marketization reform and RPS on carbon trading is mainly reflected in carbon emission rights' demand, trading volume, trading price and power generation of manufacturers. (2) Under the situation of marketed electricity price and the absence of RPS, various indicators of the CET market are superior to other policy combinations. (3) Marketed electricity price can effectively stimulate manufacturers' demand for carbon emission rights, increase trading volume, and have a positive impact on CET. However, the implementation of RPS weakens the demand for emission rights, reduces manufacturers' power generation and profit, and harms CET. • Studied the impact of RPS on CET in the context of electricity marketization reform. • Establish an evaluation model by using the SD method. • Marketed electricity price positively affect CET, while the RPS harms CET. • The policy combination of marketed electricity price without RPS is optimal. [ABSTRACT FROM AUTHOR]

To realize China's low-carbon development, coal needs to be produced and consumed in a clean and efficient way. In this paper, a multi-regional coal supply model is developed to gain insights into China's coal supply system up to 2050. Regional disparity, coal classification, and the development of clean coal technologies are specified in the model. Based on MESSAGEix, this model takes full consideration of coal mining, preparation, transformation, and transportation processes. Moreover, the effects of non-fossil energy development and carbon price are discussed. With the above framework, the future of China's coal supply system is optimized. Results indicate that: 1) China's national raw coal production will peak in 2030 under the business- as -usual scenario, while it has already peaked under the GREEN and carbon price scenarios, 2) The amount of coal used in final consumption and transformed into coke decreases, while coal transformed into liquids and SNG increases from 11 Mt in 2015 to 221 Mt in 2050 under the business- as -usual scenario, 3) both non-fossil fuel development and carbon price strategies have a positive effect on coal supply regulation and coal-related GHG emission reduction, 4) carbon price could facilitate the adoption of CCS technology and can effectively reduce coal-related GHG emissions. • A multi-regional coal supply model with four types of raw coal is developed. • Raw coal production in China will peak in 2030 at 3791 Mt under the BAU scenario. • Coal production will be more concentrated in JSMN region and XJ region. • Raw coal output in the GREEN scenario is 9% lower than the BAU scenario in 2050. • Carbon price scenarios have a significant effect on GHG emissions reduction. [ABSTRACT FROM AUTHOR]

Emissions trading schemes have been widely implemented by many countries to enforce the "cap and trade" concept for mitigating CO2 emissions. Thus, the carbon price influences the manufacturing costs in all stages of production, recycling, and disposal. Consideration of the carbon price is especially important for the economic efficiency of the downstream manufacturing sectors, such as in plastic product manufacturing, to substantially reduce their costs through the design and management of networked supply chains, which results in purchasing feedstocks from different technological routes, as well as choosing plants, warehouses and various transportation modes with diverse CO2 emission intensities. Supporting the decision-making in such situations requires the integration of life cycle analysis and networked supply chain management methodologies with an analysis of the carbon-market uncertainties. Such approaches have not been sufficiently quantified in the existing literature. This study presents a stochastic mixed-integer linear programming model developed for polyvinyl chloride pipe manufacturing in China, which is used to evaluate the effects of the life cycle emissions of procurement on the whole supply chain under carbon market uncertainty. Our results illustrate that the carbon market uncertainty would not only significantly influence the carbon-intensive production sectors but also the downstream manufacturing sectors. The five scenarios with carbon price variation exhibit distinctively different choices in procurement and supply chain configurations, as well as in their performances regarding total emissions and associated costs. [ABSTRACT FROM AUTHOR]

The growing energy consumption and associated carbon emission of Bitcoin mining could potentially undermine global sustainable efforts. By investigating carbon emission flows of Bitcoin blockchain operation in China with a simulation-based Bitcoin blockchain carbon emission model, we find that without any policy interventions, the annual energy consumption of the Bitcoin blockchain in China is expected to peak in 2024 at 296.59 Twh and generate 130.50 million metric tons of carbon emission correspondingly. Internationally, this emission output would exceed the total annualized greenhouse gas emission output of the Czech Republic and Qatar. Domestically, it ranks in the top 10 among 182 cities and 42 industrial sectors in China. In this work, we show that moving away from the current punitive carbon tax policy to a site regulation policy which induces changes in the energy consumption structure of the mining activities is more effective in limiting carbon emission of Bitcoin blockchain operation. The growing energy consumption and carbon emissions of Bitcoin mining could potentially undermine global sustainability efforts. Here, the authors show the annual energy consumption of the Bitcoin blockchain in China is expected to peak in 2024 at 296.59 Twh and generate 130.50 million metric tons of carbon emissions. [ABSTRACT FROM AUTHOR]

Water Saving Management Contract (WSMC) is believed as an efficient water-saving model and developed in recent years. However, because the high upfront investment cost and great uncertainty of WSMC, the static evaluation methods have defects in evaluating the return on investment of WSMC projects. Real option theory makes up for these defects and is applied in this paper with the expectation to evaluate the uncertainty of a Shared WSMC project and the economic feasibility of investing in the project. First, a new expression of volatility is presented based on the characteristics of Shared WSMC projects. The volatility contains uncertainties in water price, the amount of water-saving, waterborne fee, and operating & maintenance cost simultaneously. Then, it is assumed that the water saving service company is entitled options to abandon and expand the Shared WSMC project during the contract period. Based on the existing model, the exercise prices of the two options are improved. Furthermore, the real option value (ROV) of a Shared WSMC project is solved using the binomial tree option pricing model, and the economic feasibility of the project is comprehensively evaluated by combining with the static net present value and ROV organically. Finally, the Shared WSMC project of the Hebei University of Engineering in China is studied to verify the validity of the proposed method. The obtained results indicate that the economic value of the Shared WSMC project is expanded by the ROV, which means that additional value can be gained through flexible strategies and management in the context of uncertainty. Besides, the additional economic benefits of the two options vary significantly for different Shared WSMC projects. Expand option is particularly essential when Shared WSMC projects with a considerable return on investment. Conversely, the abandon option should be taken seriously. Especially when both options are considered together, the additional economic benefits are sub-additive. • Based on Monte Carlo simulation, the volatility of project value is measured synthetically by several key factors. • The time value of the fund is emphasized according to different discount rates, and then the exercise price is determined. • The model of option pricing with modified volatility and exercise price is applied to the Shared WSMC project firstly. [ABSTRACT FROM AUTHOR]

• Cross-subsidy and price inversion are severe in China's natural gas industry. • We use price-gap method to estimate the subsidy rate and scale. • The natural gas pricing reform provides a quasi-natural experiment. • Estimation results show that the pricing reform is effective. • The government should establish a more market-oriented pricing mechanism. China's natural gas consumption has grown rapidly over the years, but the price mechanism was distorted by cross-subsidy and price inversion for a long time. In June 2013, nationwide pricing reform was implemented in the non-residential sector. To explore the effect of the reform on price distortion, this paper uses monthly data from 27 key cities to estimate the scale and rate of natural gas price subsidy from 2008 to 2017. The results show that the natural gas subsidy remains a large scale, but varies across sectors. The time interval in the implementation of the policy provides a quasi-natural experiment for studying the reform. The difference-in-difference-in-difference estimations prove that the natural gas pricing reform has significantly eliminated the subsidy rate in the non-residential sector, and an effective terminal pricing mechanism has been conducted. Considering that energy subsidy is a global issue, the experience of the pricing reform in China may be extended to emerging and developing countries. [ABSTRACT FROM AUTHOR]

This study simulates the short-run effects of an Emissions Trading Scheme (ETS) and two auxiliary policies on the Chinese tourism industry. The results show that the ETS alone will increases energy prices and have significant adverse impacts on China's economy. The adverse impacts are relatively stronger on the energy sectors than they are on tourism. Two auxiliary policies—a tourism subsidy and a reduced goods and services tax (GST)—are examined as policy options to soften the negative impacts of the ETS. Results show that the tourism-subsidy policy is more effective than the GST reduction policy. [ABSTRACT FROM AUTHOR]

In the past two decades, both housing prices and carbon emissions have risen dramatically in China. However, it is unclear whether there is a nexus between them. This study employs a dynamic panel threshold regression model using residents' income levels as the threshold variable to investigate the relationship between housing prices and per capita carbon emissions. By considering 60 Chinese housing price-monitored cities, a threshold effect of income on carbon emissions was identified with a threshold value of 2.448, which divided the full sample into two regimes to further analyse the impacts of housing prices on per capita carbon emissions at each income level. The empirical results show that housing prices have a slight but positive effect on per capita carbon emissions both at two income levels. Specifically, a 10% change in housing prices can lead to a change in the same direction in per capita carbon emissions by 0.7% and 0.2% at lower and higher average income levels, respectively. However, in small cities, limited population may contribute to the negative impact of housing prices on carbon emissions. Furthermore, the results also confirm that the urbanization rate is an important factor of per capita carbon emissions. [ABSTRACT FROM AUTHOR]

Decisions related to pricing production-use water are a critical issue that local governments in China are facing. Its significance has increased in recent years, as a serious corporate water-supply shortage has surfaced with rapid economic development and urbanization. Different from developed countries, the pricing of production-use water is a complex issue in China that involves the distribution of benefits among local governments, water-supply companies, and water-consuming companies, where the overall balance is affected by every slight adjustment. Based on the evolutionary game theory, this study constructs an evolutionary game model involving water-supply companies and water-consuming companies with a systematic analysis of the interaction process between the policy formulation related to water pricing by water-supply companies and the decision making related to water consumption by water-consuming companies. The research finds that the difficulty of balancing corporate financial benefits and public water conservation benefits has led to the complexity of water pricing. Moreover, raising water prices will not necessarily cause companies to save water, but it will increase the production cost of the entire economy. This is the direct cause of low water prices, implemented by water-supply companies, in many regions of China. [ABSTRACT FROM AUTHOR]

To investigate the impacts of regulatory announcements on China's pilot carbon markets, as well as test the semi-strong form of market efficiency, a multivariate regression model with GARCH effects combined with multiple bilaterally modified dummy variables is established which allows us to investigate the potential overlapping influence from two timely adjacent events. The Shanghai, Guangdong and Hubei pilot carbon markets are taken as case studies. Based on the ADF test and the runs test, the results show that the China's pilot carbon markets have achieved the weak form of efficiency but not the semi-strong form of efficiency. With the regression model the results show that the release of the allowance allocation plan will affect the carbon price trend, and the allowance auction can only play an auxiliary role as its impact on the carbon price is not decisive. In addition, ubiquitous ex-ante impact proves that the information leakage exists in each pilot carbon market. The model established in this paper is suitable for analyzing the impacts of overlapping events in different markets, which can effectively assist decision makers to distinguish the effects caused by overlapping events. [ABSTRACT FROM AUTHOR]

Reasonable design of the tradable green certificate (TGC) system quasi-parameters (benchmark price and technical conversion coefficient) can effectively induce the mutually beneficial cooperation of the TGC market players. However, almost no literature quantitatively estimates the quasi-parameters of TGC system. This paper uses the cooperative game theory to construct the TGC bilateral trade model between renewable energy power generators and distribution power suppliers, and then quantitatively calculates the quasi-parameters of TGC system for social welfare maximization. The results show that: (1) The constructed TGC bilateral trading model guides the mutually beneficial cooperation among market players effectively by realizing benefit expansion and redistribution; (2) The TGC benchmark price and the conversion coefficients can be quantitatively calculated based on the Nash bargaining model. Taking China for example, the benchmark price is 333 yuan/MWh, and the technical conversion coefficients of hydropower, wind power and photovoltaic power are 1, 1.2, and 1.5, respectively. • A tradable green certificate (TGC) bilateral trading model is established. • The benchmark price of TGC in China is 333 yuan/MWh. • The technical conversion coefficients of TGC in China are calculated. • The superiority of Nash bargaining in the quasi-parameters design is validated. [ABSTRACT FROM AUTHOR]

Cargo transportation is one of the major sources of carbon emissions. To reduce carbon emissions from inland freight, one way is to encourage rail transportation instead of truck transportation. In this paper, a new approach combining railway operation management, revenue management, and policy formulation is proposed to increase the market share of railway freight and reduce carbon emissions. Through the integrated optimization of operation planning and pricing, the competitiveness of railway freight services is improved. The carbon tax policy acting on the demand-side can affect consigners' choice behavior. The low-carbon subsidy policy acting on the supply-side can encourage rail transport. Then a bi-level multi-objective model is proposed to achieve the trade-off among the three stakeholders (the government, rail service operators, and consigners). The complexity of the bi-level multi-objective problem motivates the development of a hybrid optimization algorithm that combines the Non-dominated sorting genetic algorithm III (NSGA-III) and the Descent algorithm based on sensitivity analysis (SAB). Through a real case based on a rail service network with nine nodes in China, the rationality of the proposed methodology is verified. The results show that the approach proposed can achieve a 39.27% modal shift (MS) from road to rail, as well as a 37.09% carbon emission reduction. [ABSTRACT FROM AUTHOR]

China is the world's largest developing country and a carbon dioxide emitter. A functional carbon market can effectively reduce carbon emissions. This paper uses the Markov chain Monte Carlo-stochastic volatility model and the wavelet multi-resolution model to analyze the volatility of price returns and the dynamic characteristics of price fluctuations in the carbon pilot markets in Hubei, Shanghai, and Shenzhen. The price movements in these markets are compared to the emissions trading system of the European Union (EU-ETS). The results show that there is a volatility clustering in the price of carbon trading in Hubei, Shanghai, Shenzhen and the EU-ETS. China's carbon pilot markets have a deficiency in terms of volatility stability, as does the EU-ETS. From a long-term perspective, China's carbon market lacks a detailed development plan, which is vital because the construction of the market system is not yet optimal. From a short-term view, China's carbon market is not active and the participants' attitude toward risk is extremely sensitive. • MCMC-SV and wavelet multi-resolution model applied to carbon price volatility. • Three major Chinese markets are compared to the EU-ETS. • All markets evidence volatility clustering. • China's carbon market lacks a detailed development plan for the long term. • Short-term, China's carbon market must become more active and offer more products. [ABSTRACT FROM AUTHOR]

• Optimal configuration of the two representative district MESs in southern and northern China. • Up to 80% of CO 2 can be reduced and more than 40% renewable penetration can be achieved by the MES. • The average cost of reducing CO 2 rises from 491 CNY/tCO 2 to 880 CNY/tCO 2 for the Tongli system. • The cost of reducing CO 2 is higher in southern China than in northern China under the same target level. Multiple energy systems (MES) can exploit synergies among different energy sectors to optimize overall efficiency. They can accommodate renewable energy sources and reduce carbon emissions more economically than in systems where each energy sector is planned and operated separately. This paper describes the optimal planning of two real-world district MESs in China: Tongli new energy town and Tongzhou subsidiary administrative center. In addition to the conventional economy objective, two kinds of low-carbon targets, including the carbon emission target and renewable penetration target, are taken into account. The results show that investment decisions on coal-fired units, combined heat and power plants and renewable energy sources are significantly influenced by the choices of different targets. Reducing carbon emissions and increasing renewable energy integration generally work in tandem, but result in a higher planning cost. The average cost of reducing carbon emissions by 40% is 528 CNY/tCO 2 in Tongli and 327 CNY/tCO 2 in Tongzhou. Meanwhile, the average cost of achieving a 25% penetration of renewable energy is 468 CNY/MWh in Tongli and 363 CNY/MWh in Tongzhou. As expected, the cost of carbon reduction and renewable energy integration gradually rises as the targets tighten. Only a small fraction of the available renewable energy is curtailed (2.9% in Tongli and 8.3% in Tongzhou) even when the renewable penetration reaches 40% in both two systems. Finally, a sensitivity analysis illustrates the effect of planning parameters, including the carbon price, the capital cost of energy components and the fuel prices, on the planning results. [ABSTRACT FROM AUTHOR]

This paper aims to provide a comprehensive look at the potential price effects of a carbon tax at the sectoral level in Chinese economy. From a production perspective, the sectors subjected to the levy are discussed based on sectoral linkage characteristics, and then the tax-induced repercussions of output prices are simulated using an extended I–O price model. The results, based on the Chinese economy for the year 2012, show that levying a carbon tax on sectors with above-average CO 2 emission linkages and non-significant production linkages will increase their output prices by an average of 1.93%, while induce relatively slight price increases in the encouraged group (0.30%) and the other group (0.34%); the household is the least affected sector (0.28%) in the economy. This means that an appropriate tax design tends to shift intermediate inputs and expenditure toward less CO 2 -intensive goods and services by its uneven cost-push impacts on production sectors, and the entire economy will ultimately get affected. By establishing techniques for policy evaluation, our analysis highlights the value of linkage analysis in the design of a carbon tax and brings more clarity to price transmission after the imposition of a carbon tax in the economy; consequently, the indirect effect of carbon tax on household can be better understood. Image 1 • Special attention should be given to the price transmission caused by a carbon tax. • Sectors subjected to the levy should be identified based on linkage characteristics. • The tax-induced price changes are captured by an extended I-O price model. • The proposed tax design tends to shift the production structure toward low-carbon. • The proposed method is a useful tool for value options aimed at pricing carbon. [ABSTRACT FROM AUTHOR]

China's carbon market has become increasingly active in recent years, and thus it is of great significance to study the characteristics of the carbon allowance price fluctuation for the healthy and steady development of this market. As leverage is common in asset prices in general financial markets, this paper adopts the leverage stochastic volatility (SV-L) model to characterize the price volatility of the five pilot carbon markets in China. We first make a Bayesian inference for the SV model, then construct a Monte Carlo calculation process based on Gibbs sampling for empirical analysis, and finally compare the SV-L model with the normal stochastic volatility (SV–N) model. The results show that the carbon price fluctuations of the five pilot markets are quite different. Among them, Shenzhen, Guangdong, Shanghai, and Beijing have a "positive leverage effect", and Hubei has an "anti-leverage effect". Through comparative analysis, we find that the SV-L model is superior to the SV-N model in terms of the degree of data fitting and simulation ability. Finally, we offer suggestions on the development of China's unified carbon market. • We explore the characteristics of carbon price fluctuation in different pilot markets in China. • The SV-L model indicates that the carbon price fluctuation of each pilot province or city shows great difference. • Five pilot carbon markets show different degree of leverage effect. • The SV-L model is superior to the SV-N model for characterizing the carbon price of pilot markets in China. [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]

Through a series of policies release, the trading system of China's carbon market is being improved, but its current liquidity is still low. To improve market liquidity, this paper analyzes the relation between the release of policy related to carbon market operations and the volatility of carbon price, thus arranging an optimal adjustment scheme for government's policy-making. Through the jump test and Logit regression, we investigate historical policies and prices of 7 Emission Trading Scheme pilots in China to explore the impact of policy release on carbon price, and then quantify the effectiveness of these policies. Empirical results indicate that in the short-term, new policies can rapidly lead to a large volatility of carbon price, but it can also reduce the abnormal volatility with the spread of price information. Further, the demand-stimulus policies promote a positive volatility of carbon price. In the long-term, the insufficient demands for carbon emissions quota raise the disappearance of market dividends caused by the policy release and lead to an excessive call-back of carbon price, thus increasing mid-and long-term risks in carbon markets. Additionally, China's macro environment policy can stabilize carbon price, and thus an effective tool for improving the liquidity of carbon markets is developing demand-stimulus policies. • We analyze the origin of liquidity in China's carbon market from the perspective of policy release. • We obtain the price effect of carbon policy under different policy categories. • We judge the influence cycle of different policies on carbon price based on price jumps after policy release. • We propose a policy tool to improve the liquidity of China's carbon market based on the feedback of policy to carbon price. [ABSTRACT FROM AUTHOR]

Carbon price forecasting is significant to both policy makers and market participants. However, since the complex characteristics of carbon prices are affected by many factors, it may be hard for a single prediction model to obtain high-precision results. As a consequence, a new hybrid model based on multi-resolution singular value decomposition (MRSVD) and the extreme learning machine (ELM) optimized by moth–flame optimization (MFO) is proposed for carbon price prediction. First, through the augmented Dickey–Fuller test (ADF), cointegration test and Granger causality test, the external factors of the carbon price, which includes energy and economic factors, are selected in turn. To select the internal factors of the carbon price, the carbon price series are decomposed by MRSVD, and the lags are determined by partial autocorrelation function (PACF). MFO is then used for the optimization of ELM parameters, and external and internal factors are input to the MFO-ELM. Finally, to test the capability and effectiveness of the proposed model, MRSVD-MFO-ELM and its comparison models are used for carbon price forecast in the European Union (EU) and China, respectively. The results show that the performance of the model is significantly better than other models. [ABSTRACT FROM AUTHOR]

Analyzing the effect of local government decision‐making competition on regional carbon emissions is important for reducing carbon emissions in rapidly urbanizing areas. Taking the energy rebound effect into account, this study analyzes the effect on carbon emissions of competition between local governments in decision making. Focusing on China's three urban agglomerations, this study further discusses how to avoid this influence. The results show that local government decision‐making competition is one of the main causes of the regional "green paradox"; the effect of local government decision‐making competition on carbon emissions has significant regional heterogeneity and spatial dependence, and the short‐term energy rebound effect is greater than the long‐term energy rebound effect; and local government decision‐making competition has three effects on carbon emissions that also have interaction and substitution effects between them: factor market distortion, investment bias, and the "race to the bottom" of environmental policies. However, four measures can reduce the effect of local government decision‐making competition on carbon emissions: one, improving the performance evaluation system of local governments; two, promoting the marketization of factor prices; three, improving both the energy efficiency and upgrading of industrial structures; and four, introducing macro emission reduction policies that allow the central government to intervene directly. [ABSTRACT FROM AUTHOR]

Carbon policies can be expected to increase the price of fossil fuel, either directly through a cap-and-trade system or carbon tax, or indirectly by regulations that place an implicit tax on fossil fuel. We construct a theoretical model to decompose the effect on employment in a specific industry caused by an increase in the price of fossil fuel. We find that the total effect is determined by the market's responsiveness to the changes of the prices of fossil fuel and final product. We verify the theoretical model by an empirical analysis of China's thermal power industry. Because China is the largest carbon emitter in the world and thermal power industry is the biggest carbon emitter industry in China, the empirical model has strong reference value for other countries and industries. Policy makers should be prepared to mitigate any adverse effects on employment that a carbon policy might cause. [ABSTRACT FROM AUTHOR]

The questions of how to mitigate climate change and its impact on human health are currently high on the Chinese agenda for future development. The emission trading scheme (ETS) has become one of China's most important instruments to address climate change through a market mechanism. In the wake of the evolution from regional pilots to a nationwide scheme, it is inevitable to be confronted with tremendous political–economic–institutional challenges. To facilitate a smooth start-up of the upcoming nationwide ETS, this study provides a systematic overview of seven ETS pilots, involving the detailed comparison of ETS design and the in-depth evaluation of market performance, both internal and external performance, based on trading data. Then, the achievements and deficiencies of seven ETS pilots are summarized, several challenges for the current time are discussed, and policy proposals for China's national-level ETS are navigated further coupled with international experience. This study finds that China's ETS pilots, from the short-term perspective, are successful, especially in the reinforcement of China's capacity to develop a market-based scheme in an economy that still cherishes many non-market endowments. However, deficiencies lie in both the internal and external market performance, such as the carbon price lacking a signal function, insufficient incentives for compliance, too low market liquidity, and much too high market fragmentation. Moreover, the retrospective examination of China's ETS pilots suggests that a nationwide ETS should at least be based on an extension of the cap duration from single year to several years, uniform rules on monitoring/reporting/verification and allowance allocation, and the improvement of institutional foundation. [ABSTRACT FROM AUTHOR]

In the past decade, the deterioration in atmospheric quality caused by emissions of ambient particulate matter with an aerodynamic diameter of less than 2.5 µm (PM2.5) has become an urgent problem in China. As this problem can be mainly attributed to the large amount of coal consumption, a strategy to promote electric power substitution was initiated, and in this case, cutting the price of electricity is considered useful. However, since it was announced that the price of electric power used in the service industry will be reduced by 10%, the proper target to cut the price of electric power used in the secondary industry was under debate. By using the computable general equilibrium (CGE) model, the policy to cut the price of electric power used in the secondary industry was simulated and the effects of the policy on the economy and the environment were explored. The results show that the policy to cut electric power prices will contribute to promoting the strategy of electricity substitution, and further contribute to environmental improvement. This policy can result in positive effects on the systems of the economy and the environment at the same time, and when the target to cut the price of electric power used in the secondary industry is -3%, the maximum positive effects will be obtained: gross domestic product (GDP) growth will be accelerated by 0.015‰, while PM2.5 emissions will be abated by 394.2 tons. Moreover, based on the unique cross-subsidy mechanism in China's electric power industry, although residents' consumption welfare can be fully compensated, less cross-subsidy will have a negative effect on the agriculture industry. [ABSTRACT FROM AUTHOR]

It is of great significance to reduce carbon emissions from electric power generation for green development. In addition to technical measures, two trading mechanisms are built to optimize China’s electric power generation: generation rights trading, and carbon emission rights trading. However, as the carbon emission rights trading are initiated, the issues of how to choose the right trading mechanism, and determining the appropriate strategy under the corresponding trading mechanism continue to confuse generation enterprises. In order to clarify these issues, the game theory was used to identify the proper trading strategies for generation enterprises under the two highly similar trade mechanisms. Results show that the two trading mechanisms are complementary to each other to some extent, and the generation enterprises should choose a proper trade strategy according to the endowment of generation prices, the technical abilities, the grid-loss price and the ratio of carbon-electricity conversion. The equilibrium solutions of trading scales and prices for the two trading mechanisms are mostly related to the endowments of generation prices. Generally, the buyers with higher endowments of generation prices should choose the carbon emission rights trading, and the buyers with lower endowments of generation prices can only benefit in generation rights trading. The bigger gaps between the endowments of generation prices of buyers and sellers are, the more likely the trade can be made and further result in a better environmental consequence. The conclusions provide suggestions to the government that, the grid-loss pricing and the ratio of carbon-electricity conversion could be used as key tools to regulate the market for both of the trade mechanisms. [ABSTRACT FROM AUTHOR]

China has realised that for its own sake and from the international community's perspective, it cannot afford to continue on the conventional path of encouraging economic growth at the expense of the environment. Accordingly, the country has placed ecological goals at the same level of priority as policies on economic, political, cultural and social development. Specifically, meeting the grand goal involves not only capping China's nationwide coal consumption to let it peak before 2020 and carbon emissions peak around 2030, but also putting in place a variety of flagship programs and policies. This article argues that the 2030 carbon emissions peak goal is ambitious but achievable and concludes by arguing why there is reason to be optimistic about China's 'green push'. [ABSTRACT FROM AUTHOR]

Emissions trading schemes (ETSs) are effective measures that facilitate economic growth and carbon mitigation, especially for developing countries such as China. These schemes can further affect the cash flow, production, and investment decisions of regulated companies. However, few empirical studies have explored how ETSs promote companies' market value. We systematically evaluate the influence of the carbon emission trading (CET) policy on companies' market value and explore the influential mechanism. We use the data of listed companies from the Chinese stock "A" markets and employ the difference-in-difference method to account for the unobserved cause of the CET policy regarding companies' market value. Robust benchmark regression results reveal that the CET policy promotes companies' market value significantly. The mechanism analysis reveals that the CET policy can improve the market value of listed companies by influencing the carbon price, innovative activities, and carbon disclosure. The results of the heterogeneity analysis show that the CET policy's impact on companies' market value is heterogeneous in terms of marketization degree, industry, firm ownership, and different regions. We suggest that the carbon pricing mechanism, degree of market perfection, carbon disclosure policy, and carbon finance should be optimized to improve the efficiency of ETSs. [ABSTRACT FROM AUTHOR]

This study investigated the potential financial benefits that private forest famers can derive when participating in a larch carbon sink plantation project in the northwestern Chinese province of Gansu. A decision matrix was developed to help forest farmers justify participation in forest carbon sink projects relative to the traditional land-use goal of timber production under various carbon trading prices, site conditions, and contract terms. The results showed that when the carbon trading price is at the theoretically optimal carbon price (CNY 110/tCO2e, equivalent to USD 17/tCO2e), Chinese business entities are willing to pay for forest carbon credits under the current global carbon emissions level, and forest farmers who participate in a 25-year forest carbon sink plantation project on high-productivity sites would generate the greatest financial benefit compared with the net income from pure timber production forests. Thus, the government does not need to provide a carbon sink subsidy for participating tree farmers. However, at the current average carbon trading price (CNY 19.8/tCO2e or USD 3/tCO2e) in the domestic market, a minimum additional subsidy of CNY 735/ha (USD 113/ha) is required upfront to motivate forest farmers to convert timber production forests into carbon sink forests. The results of this study can help policymakers and forest managers formulate optimal eco-compensation strategies for enrollment in forest-based carbon sequestration programs. [ABSTRACT FROM AUTHOR]

Carbon leakage features prominently in the climate policy debate in economies implementing climate policies, especially in the EU. The imposition of carbon pricing impacts negatively the competitiveness of energy-intensive industries, inducing their relocation to countries with weaker environmental regulation. Unilateral climate policy may complement domestic emissions pricing with border carbon adjustment to reduce leakage and protect the competitiveness of domestic manufacturing. Here, we use an enhanced version of GEM-E3-FIT model to assess the macro-economic impacts when the EU unilaterally implements the EU Green Deal goals, leading to a leakage of 25% over 2020–2050. The size and composition, in terms of GHG and energy intensities, of the countries undertaking emission reductions matter for carbon leakage, which is significantly reduced when China joins the mitigation effort, as a result of its large market size and the high carbon intensity of its production. Chemicals and metals face the stronger risks for relocation to non-abating countries. The Border Carbon Adjustment can largely reduce leakage and the negative activity impacts on energy-intensive and trade-exposed industries of regulating countries, by shifting the emission reduction to non-abating countries through implicit changes in product prices. [ABSTRACT FROM AUTHOR]