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The mitigation of climate change requires that agricultural development would proceed in accordance with green and sustainable practices. This implies that economic performance should be improved while minimizing the impact on the environment. One way to assess the underlying costs of sustainable agricultural development, and to model the relationship between the environment and the economy in general, is to use the carbon shadow price (CSP). In this paper, we utilize a by-production model within a non-parametric framework to estimate the agricultural CSP from 1997 to 2020 in 31 provinces of China. The patterns of the agricultural CSP are unveiled through kernel density analysis and convergence tests. Additionally, this paper constructs a comprehensive agricultural informatization indicator using the entropy method. We then empirically investigate its influence on agricultural CSP. The results reveal that China's agricultural CSP has demonstrated consistent growth over the past two decades which suggests serious improvement in environmental performance. Furthermore, the CSP show cross-province variation, albeit with conditional β convergence. Our empirical findings indicate that agricultural information technology contributes to an increase in CSP, thereby indicating its positive role on the green growth of agriculture in China. [ABSTRACT FROM AUTHOR]

The pursuing of inter-regional power transmission to address renewable power curtailment in China has resulted in disappointing gains. This paper evaluates the case of local green ammonia production to address this issue. An improved optimization-based simulation model is applied to simulate lifetime green manufacturing, and the impacts of main institutional incentives and oxygen synergy on investment are analysed. Levelized cost of ammonia is estimated at around 820 USD/t, which is about twice the present price. The operating rate, ammonia price, the electrical efficiency of electrolysers and the electricity price are found to be the key factors in green ammonia investment. Carbon pricing and value-added tax exemption exert obvious influences on the energy transition in China. A subsidy of approximately 450 USD/t will be required according to the present price; however, this can be reduced by 100 USD/t through oxygen synergy. Compared to inter-regional power transmission, green ammonia production shows both economic and environmental advantages. Therefore, we propose an appropriate combination of both options to address renewable power curtailment and the integration of oxygen manufacturing into hydrogen production. We consider the findings and policy implications will contribute to addressing renewable power curtailment and boosting the hydrogen economy in China. [Display omitted] • Local green ammonia production to reduce renewable power curtailment is explored. • The impacts of institutional incentives on green ammonia production are evaluated. • A hybrid model is applied to simulate the lifecycle green production. • Green ammonia investment exhibits both economic and environmental advantages. • The integration of oxygen manufacturing into green hydrogen production is proposed. [ABSTRACT FROM AUTHOR]

Distributed photovoltaic energy storage systems (DPVES) offer a proactive means of harnessing green energy to drive the decarbonization efforts of China's manufacturing sector. Capacity planning for these systems in manufacturing enterprises requires additional consideration such as carbon price and load management. This paper proposed a triple-layer optimization model for DPVES capacity configuration in the manufacturing sector using a chemical fibre manufacturing enterprise for demonstration. Refined photovoltaic generation and energy storage lifetime models were used. Beyond the considerations of electricity prices and meteorological conditions, we further studied the influence of carbon price and user load management on system capacity configuration and associated economic feasibility. Firstly, without considering carbon, minimizing user costs requires maximizing PV capacity up to the area limit while adjusting the ES to its optimal capacity and power. The optimal DPVES annually reduces the grid electricity consumption and carbon emissions, resulting in a 12.73% annual cost reduction. When considering the costs of carbon emissions, the carbon reduction contributed by DPVES can reduce the annual costs, making the whole system more economically feasible. However, the presence of substantial carbon emissions costs diminishes the economic feasibility of the ES, leading to a reduction of 24.51% in the optimal capacity configuration. Finally, user load management can further reduce system costs because it replaces some of the functions of energy storage. This results in a decrease of over 39% in the optimal energy storage capacity and a further reduction in related costs. Additionally, we found that load management by enterprises is more effective during the low carbon price than the high carbon price, implying that companies should implement load management as soon as possible. • Established a triple-layer optimization model for capacity configuration of distributed photovoltaic energy storage systems • The annual cost can be reduced by about 12.73% through capacity and power configuration optimziation • High carbon prices may reduce the economic viability of the energy storage system, causing reduction in its optimal capacity • Load management can further reduce the energy storage capacity demand by 39%, bringing economic benefits especially in low carbon prices [ABSTRACT FROM AUTHOR]

Microgrid is a promising way to integrate renewable distributed generation into the electric power sector, which has received widespread attention. In this paper, a uniform capacity-constrained optimization model under different power purchase and sale price contracts is developed to explore the optimal green investment strategy for grid-connected microgrid (GCM) with three configuration types. The impact of renewable energy source endowment and incentive policy is focused when macrogrid's generators emit more pollution than GCM's non-renewable generators, such as in China and India. The results show that: (1) GCM with renewable generation can only be invested in a site with relatively abundant renewable endowment; (2) carbon tax effectively promotes the deployment of GCM with renewable generation and achieves carbon emission abatement, but excessive carbon tax cannot incentive investment in the most desired GCM type; (3) a subsidy trap is found under feed-in tariff (FIT) subsidy, which implies that the fade-out or exit of FIT subsidy is beneficial for microgrid's healthy development; (4) and the comparisons under different price contracts emphasize the importance of macrogrid providing non-discriminatory access to feed-in and feed-out services to microgrid. • Investment strategy is explored for grid-connected microgrid (GCM) with three types. • Renewable source endowment and incentive policy determine the investment for GCM. • Excessive carbon tax cannot incentive investment in the most desired renewable GCM. • The fade-out or exit of FIT subsidy is beneficial for healthy GCM deployment due to the subsidy trap. • Emphasizing the importance of macrogrid providing non-discriminatory services to GCM. [ABSTRACT FROM AUTHOR]

Combined heat and power is an inevitable trend in the development of waste-to-power industry. Many waste incineration power generation projects that have already put into operation in China are waiting for transition and upgrading to combined heat and power projects. From a growth option perspective, this paper considers the irreversible process and uncertainty in economic benefits, introduces carbon emission trading mechanism and develops the growth option theory to design the expansion decision making model of waste-to-energy combined heat and power projects, so as to obtain the project value and find the optimal expansion timing. In this paper, a case study is carried out on the expansion decision making of a waste-to-energy combined heat and power project in Shandong Province in China. And two scenarios with specific and flexible expansion times are developed from European and American options separately, as European options require investors to expand at a certain time but American options not. The results indicate that 1) real option approach successfully improves the project value through considering uncertainty, and American option can achieve the optimal expansion time, 2) under the carbon emission trading mechanism, the carbon price affects the expansion index, which has a positive effect on the project value, 3) the linear nature of the income and cost expansion index can help investors make judgments on expansion investments. The effectiveness of the case study implies the practicality of the expansion option method for similar projects to reach dual carbon targets in cost and benefit analysis. • Real option approach is applied in energy transition in WTECHP projects. • European and American options are proposed for certain and flexible decision times. • Expansion time and triggers of WTECHP are incorporated into life cycle management. • CCER is introduced as an environmental element to evaluate expansion decision making. [ABSTRACT FROM AUTHOR]

Carbon trading market is a central policy tool for promoting cleaner enterprises' energy consumption and investment behaviors. It is crucial for enterprises to establish a green and low-carbon development model by clarifying carbon trading impact mechanism on enterprise behaviors and the interactive relationship between entities in the carbon market. China's contract-based carbon market is still in the development stage, the impact of the mainstream allowance mechanism and government regulation on enterprises' energy behaviors has yet to be determined. In view of this, this paper describes mathematical mechanisms of the influence of carbon prices and carbon quotas on enterprises' energy consumption and investment, and the evolutionary game model of government-enterprise behaviors is constructed, the evolution process and appropriate strategies of enterprises' energy behaviors in the development of the carbon market are discussed. This paper uses real data of China carbon market to simulate the model, it is found that strategies such as relaxation of carbon quotas and carbon subsidies dynamization are needed during the initial development of the market. In the mature stage of the carbon market, strategies are needed to increase the proportion of government carbon revenue and reduce its regulatory cost. The higher the initial willingness of government-enterprise, the better the effect of strategies and the constraints of public willingness. The model and results have theoretical implications for enterprises' energy transformation and government regulation, and provide a reference for the development of China's carbon market. • Constructed benefit-cost analytical framework for enterprises' energy behaviors. • Described mechanisms of carbon trading affecting enterprises' energy behaviors. • Constructed government-enterprise behaviors model by the evolutionary game theory. • Found new conclusions of enterprises' energy behaviors under the carbon market. [ABSTRACT FROM AUTHOR]

The carbon market has been playing an increasingly important role in mitigating carbon emissions. However, with the tightening of the carbon allowance, where the carbon market will evolve is still unclear. Abstracting three agents—Government, Carbon-supplier('CS'), Carbon-buyer('CB'), this paper intends to investigate the operation mechanism of carbon market from the perspective of the stakeholders. Based on the simulation analysis, it is suggested that: 1) the carbon market in China may become a major "seller's market" when carbon quota experienced dramatic reduction; 2) when the carbon price is constant, CS with excessive carbon productivity will crowd out and exploit CB in the carbon market competition; 3) strict administrative penalties and information disclosure would help promote proactive participation of CS and CB in the carbon market; and 4) the interaction between CS and CB in different strategic scenarios is influenced by the carbon price and the coefficient of demand variation for carbon quota. In contrast with previous studies, this paper has uncovered a dynamic strategic evolution mechanisms of stakeholders in the carbon market at the micro-level, contributing to carbon market governance and providing stakeholders with tailor-made climate policy tools and strategic choices. • The carbon market in China may evolve into a "seller's market" with a scarcer allowance. • We first identify the phenomenon of carbon exploitation in the carbon market. • Improving the carbon price under buyer's market would facilitate positive participation of three agents. • Carbon accounting, carbon disclosure, and strict administrative penalty help regulate non-compliance actions by enterprises. • The equilibrium of agents' strategy are influenced by dual aspects—parameters and other stakeholders' choices. [ABSTRACT FROM AUTHOR]

Equilibrium capacity expansion is an effective tool to help regulators predict the generation evolution of power systems by analyzing the decision-making of generation companies (Gencos). With the development of carbon markets (CMs) and electricity markets (EMs), Gencos' decisions in these two markets (encompassing investment and bidding decisions related to carbon emission allowances and electricity) are deeply intertwined through market clearing results. However, existing studies mainly focus on equilibrium capacity expansion with fixed carbon prices and usually ignore the realistic clearing process of CMs, which cannot simulate Gencos' coupled decision-making and accurately predict generation evolution under the CMs and EMs. This paper proposes a two-level equilibrium capacity expansion model for power systems which considers the coupled decisions of Gencos between CMs and EMs. At the upper level, multiple Gencos' coupled decision models are proposed based on their interaction with market clearing results. At the lower levels, CMs and EMs are respectively cleared to determine the varying carbon and electricity prices. Furthermore, the developed equilibrium capacity expansion model is reformulated as an equilibrium problem with equilibrium constraints (EPEC), which is solved by a diagonalization-based solution procedure. Finally, a provincial power system of southeast China is used to validate the performance of the proposed framework. The results illustrate that under CMs and EMs, non-fossil energy would account for 81.3% of total capacity and 73.88% of total generation in 2050. Compared to the existing model using fixed carbon prices, the consideration of realistic carbon market clearing will promote the installation of renewable energies and improve social welfare. The proposed model can provide beneficial references for regulators to perceive the evolution of power systems in CMs and EMs. • A two-level equilibrium capacity expansion model for power systems is proposed. • A novel coupled decision model for Gencos in CMs and EMs is developed. • The proposed model is solved by a diagonalization based solution procedure. • The results can guide the transition of power systems under the CMs and EMs. [ABSTRACT FROM AUTHOR]

[Display omitted] • It analyzes the feasibility of achieving net zero emission in the Chinese power sector by 2050 and the required policy measures. • It is essential to foster the concurrent development of renewable energy, energy storage, and demand response technologies. • The carbon pricing mechanism with exponential growth is more suitable. • Referring to the European offshore wind power investment model is beneficial for the development of offshore wind power in China. The low-carbon transition in China's power sector plays a crucial role in the mitigation of climate change worldwide, and increasing renewable energy penetration rate is widely recognized as the key approach to decarbonize this sector. This paper proposes a renewable energy penetration model to examine the feasibility for net zero emission by 2050 in China's power sector taking into account of economic and social development. It also evaluates the impacts of carbon pricing and financial incentives on renewable energy penetration and carbon emissions. The results indicate that along with economic development, China's electricity demand will continue to grow, but at a gradually slowing rate. It is possible for the power sector to achieve net zero emission by 2050 while meeting this growing electricity demand, with a renewable energy penetration rate of 75%. To ensure the achievement of the goal, we recommend setting the carbon price with the current market price as the baseline and increasing it annually by a relative increment index of 10%. Furthermore, given the high initial cost and late start of offshore wind power, we suggest incorporating associated grid connection cost into the transmission and distribution price to ensure the comprehensive and healthy development of renewable energy. [ABSTRACT FROM AUTHOR]

Carbon market is the most effective market tool for carbon emission reduction. China, the largest carbon emitter in the world, established the national carbon market in 2021, covering over 2000 key units in the power sector. Therefore, the forecasting of carbon price has profound implications for environmental and energy policies. In this paper, two traditional econometric model and three kinds of machine learning (ML) algorithms are used to predict carbon returns in the Chinese carbon trading market based on carefully selected predictors. Among all forecasting models, the Random Forest (RF) has the best forecasting performance, followed by some GARCH models using various factors. Compared with the traditional benchmark of ARMA model, the BP neural network (BP) and the GA improved BP method (GA-BP) are less competitive in predicting carbon returns in China because of their large forecasting errors. According to the optimal model, social attention to the carbon market, the international crude oil returns and the overall performance of the stock market are the most important predictors. The findings are robust to the change in the sample set. Overall, the ML approach shows an advantage in forecasting carbon returns, but the selection of predictors is also important. • Machine learning and econometric models are used to forecast carbon returns in China. • The selection of predictors is based on economic analysis. • The Random Forest (RF) outperforms the other ML and econometric methods. • The energy market is extremely important for predicting carbon returns. • Social concerns and stock market performance improve forecasting accuracy. [ABSTRACT FROM AUTHOR]

In order to probe collaborative environmental governance (CEG) in China's "1 + N" policy framework for carbon peak and carbon neutrality, this paper applies the Actor-network theory (ANT) as an analytical framework to explore carbon reduction policy coordination. We then model ANT's relations with an evolutionary game theory (EGT) model to examine the evolutionarily stable strategies in CO 2 emission reduction by various actors including the central government, local governments, commercial banks, and polluting enterprises. Our objective is to examine policy coordination as the key enabler for governing success via an ANT-based mechanism design in China's institutional context. Combining the strength of ANT with a four-party EGT model, we investigate how to improve policy coordination to mobilize the actor-network for promoting CEG. Simulations are conducted to examine the effectiveness of policy coordination involving multiple policy instruments for controlling carbon emissions. The central government fulfills leadership in translating the interests of other actors and shaping the desired collaborative network. Without proper coordination, environmental policies may counteract each other. Government transfers and subsidies have direct impacts, but in the long run enhanced competitiveness and profitability of enterprises represent the intrinsic key to CEG success. From a methodology perspective, policy simulation in an EGT framework represents a novel addition to the research toolbox that expands ANT. [ABSTRACT FROM AUTHOR]

Hydrogen produced from renewables-fuelled electrolysis has the potential to provide deep decarbonisation for sectors that are the most difficult to decarbonise, but the intermittency of renewable sources may result in low electrolyser utilisation and, consequently, high costs. This study determines the greenhouse gas (GHG) emissions and levelised cost of hydrogen (LCOH) associated with blending wind electricity with the grid to increase electrolyser utilisation. A novel cost model was developed to determine the production performance, costs and embodied CO 2 emissions of an electrolyser with hybrid fuel supply (wind and grid) considering dynamic load constraints of alkaline (ALK) and Proton exchange membrane (PEM) electrolysers and using high-resolution historical weather data to determine wind production profiles in two case study regions: northern (Bayannur) and southern (Pingtan) China. The results show that using 52% of grid electricity in an ALK electrolyser in Bayannur reduces LCOH by 11%, increasing hydrogen production by 74% but with 17.4 kg CO 2 / kg H 2 generated in CO 2 emissions. When a carbon price is accounted for, the optimal electrolyser utilisation is reduced to 40%, with the LCE 44% reduced. Emissions of 9.8 kg CO 2 /kg H 2 are lower than for stream methane reforming with carbon capture. In Southern China (Pingtan), LCOH is higher than Bayanur because of the high electricity cost. The economic benefits of increasing grid power depend primarily on the total CAPEX cost, grid power cost, and carbon tax. By altering the carbon tax, the optimal blend of wind/ grid differs. The grid contribution to the optimal blend diminishes as a carbon tax approaches 35 USD/ t CO 2. • This paper analyses the value of adding grid electricity to a pure wind-powered H 2 production plant. • The LCOH and CO 2 life-cycle emissions are obtained for Alkaline and PEM electrolysers. • We are introducing the novel ICOH metric to optimise the trade-off of LCOH and CO 2 emission on H 2 production. • Using only 52% of grid electricity in an ALK electrolyser, H 2 production can increase by 75%. [ABSTRACT FROM AUTHOR]

As global warming intensifies, the reduction of carbon emissions is imminent. Carbon price is directly related to whether carbon can be effectively reduced. Therefore, accurately forecasting carbon price has important practical significance. Aiming at the nonstationary and nonlinear characteristics of carbon price, this paper proposes a novel hybrid model for forecasting carbon price, which is based on improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), multiscale fuzzy entropy (MFE), complete ensemble empirical mode decomposition (CEEMD), improved random forest by salp swarm algorithm (SSARF), improved back propagation by cuckoo search (CSBP), improved extreme learning machine by whale optimization algorithm (WOAELM) and error correction (EC), named ICEEMDAN-MFE-CEEMD-SSARF-CSBP-WOAELM-EC. Firstly, carbon price is decomposed by ICEEMDAN, divided into high-, medium-, and low-complexity components by MFE. Secondly, high-complexity components are merged and secondarily decomposed by CEEMD, which are still recorded as high-complexity components. Then, SSARF, CSBP and WOAELM are used to forecast high-, medium-, and low-complexity components, respectively, and forecasting results are reconstructed. Finally, EC is carried out using an extreme learning machine to obtain the final forecasting results, and the Diebold-Mariano test is introduced for a comprehensive evaluation of the model. Taking carbon price in the pilot cities of Shenzhen and Hubei as examples, after 6 aspects and 20 comparative experiments, the results show that the proposed model has higher forecast accuracy, with MAPE, MAE and RMSE up to 0.03131, 0.00089 and 4.02e-06 in Hubei, and its forecasting ability is better than other commonly used international carbon financial price forecasting models, providing a theoretical and data basis for carbon pricing and formulating carbon reduction policies in China. The main contributions of this paper are the improved primary decomposition, the use of secondary decomposition, and the innovative combination of three optimal models to forecast carbon price, but it still needs to be optimized for practice. [Display omitted] • Propose improve CEEMDAN by using Hermite interpolation and calculating residuals first. • High complexity components are secondarily decomposed to reduce its complexity. • Improved RF by SSA, named SSARF, is proposed to solve the dilemmas of RF. • Propose a high-accuracy hybrid model for carbon price forecasting. • Compare multi-faceted experiments to prove the validity of the proposed model. [ABSTRACT FROM AUTHOR]

With the development of low-carbon energy, the use of thermal and hydropower units for regulation in the power system dominated by new energy (PSDNE) is decreasing. Electric buses (EBs) are expected to become the primary dispatching objects in this context. Accurately evaluation EB's response capability (RC) is vital for the scheduling operation of the PSDNE. However, current evaluation methods for EB's RC are relatively crude, lacking detailed and quantifiable measures. This paper proposes a novel multi-dimensional evaluation method to provide the aforementioned RCs. The EB operational schedule revise model considering traffic and temperature is proposed to obtain more accurate EB charging load by revise arrival charging time and remaining battery energy. The proposed EB charging model considering carbon emissions contributes to revealing the impact of various charging modes, such as low-carbon and electricity price, on the Eb's RC. The EB multi-dimensional evaluation model is established to obtain quantified and detailed RCs to support the operation of NEDPS. These capabilities include fast response within various periods, sustained response over extended durations, and remaining RC after executing scheduling instructions. Finally, using the actual data from an EB station of a city in China, the effectiveness of the proposed evaluation model is verified. [Display omitted] • The impact mechanisms of traffic and temperature on the EB's RC are revealed. • The accuracy of the revised EB's operating schedule is greatly enhanced. • The impact mechanisms of carbon emissions reduction on the EB's RC are revealed. • The EB's RC under different charging modes is quantitatively evaluated. • The fast RC, sustained RC, and remaining RC of the EB are quantitatively evaluated. [ABSTRACT FROM AUTHOR]

Under the background that China will achieve the goal of carbon neutrality by 2060, analyzing the impact of carbon neutral target constraints on the welfare of urban and rural residents is an important part of the design of a carbon emission reduction policy mechanism, in this paper, the dynamic recursive CGE(Computable general equilibrium) model is used to simulate the changes in welfare level, income consumption, and CO2 emissions of residents and their urban-rural heterogeneity under the policy of imposing a carbon tax on the fossil energy industry from 2022 to 2060. The results show that: compared with the BAU scenario, by 2060, first the income and consumption of residents will decrease slightly. Second, the target constraint of carbon neutrality makes the equivalent variation and compensate variation of urban and rural residents' welfare decrease slightly, and the equivalent variation and compensate variation of urban residents decrease more than those of rural residents. The following conclusions are drawn: first, the carbon-neutral target constraint makes the welfare of urban and rural residents decline slightly, but it will not have a strong impact on residents' income and consumption. Second, this constraint has a greater impact on the income, consumption and savings of urban residents than those of rural residents. [Display omitted] • A five-layer nested dynamic recursive CGE model is established to analyze residents' welfare. • Carbon taxes are incorporated into production decisions as a policy cost for energy companies. • The heterogeneity of the impact of carbon tax policy constraints on the welfare of urban and rural residents was analyzed. • The government needs to improve the intensive and diversified energy supply in rural areas to reduce the urban-rural gap. [ABSTRACT FROM AUTHOR]

Whether grid upgrading in China, centered on building trans -regional transmission lines, can promote a low-carbon transition in the power sector is controversial. Since there is no precedent to follow, various countries are interested in learning from China's experience. This paper adopts a two-way fixed effects model based on panel data for 30 Chinese provinces from 2007 to 2019 to reveal the nonlinear relationship between grid upgrading and renewable energy generation. The research finds that: (1) A U-shaped relationship exists between grid upgrading and renewable energy generation, which is robust to a series of robustness checks. (2) When the ratio of transmission lines over Extra High Voltage (EHV) exceeds 0.152, grid upgrading has a scale effect in promoting renewable energy generation to achieve a low-carbon transition in the power sector. (3) Building the EHV grid has made a significant contribution to renewable energy generation, particularly in resource-intensive areas. Conversely, building Ultra High Voltage (UHV) grids has not observed such a positive impact. Finally, targeted policy recommendations are put forward for the low-carbon transition of China's power sector. • A U-shaped relationship exists between grid upgrading and renewable energy generation. • Scale effect occurs when trans -regional transmission lines' ratio exceeds 0.152 • Extra High Voltage has made a significant contribution to renewable energy generation. • Ultra High Voltage has not shown a significant impact on renewable energy generation. • The contribution of grid upgrading increases with the installed capacity. [ABSTRACT FROM AUTHOR]

Towards the target of carbon neutrality, the need for deep decarbonization in iron and steel industry is increasingly recognized. Existing studies rarely mention the effects of collaboration with its source industries for carbon emission reduction in ISI. Furthermore, the fundamental laws of CO 2 emission reduction capacity with cost change of source substitutions for various steel production routes under market economics are unclear. To avoid the blind substitution of clean sources for meeting the urgent requirements for decarbonization in China's steel industry, which may result in increased carbon emissions and uneconomical carbon reduction from a lifecycle perspective. This paper integrates the production and utilization processes of source resources into the steel production process, establishes coupling models of carbon and value flows for four main types of steel production routes, and aims to quantitatively analyze the specific CO 2 emission reduction potential and costs. Three economic market development scenarios from 2021 to 2060 are set, and the marginal carbon prices of various source substitutions are determined. Subsequently, decarbonization pathways with the goal of minimizing production costs are developed. Finally. The future resource demand and the carbon emission reduction contributions of source industries collaborated are predicted. The results show that (1) about 81.7–89.9 % of CO 2 emissions could be reduced in the scenarios; (2) the demands of electric power and hydrogen energy will reach 54.48–511.90 BkWh and 7.47–10.31 Gt in 2060, respectively; and (3) collaboration with source industries could make 18.3–18.3% of CO 2 emission reduction contributions. All in all, this study could provide scientific support for the low-carbon transformation of China's steel industry. • Carbon and value flows of BF-BOF, Scrap-EAF, DRI-EAF, MOE-EAF routes are analyzed. • CO 2 emission reduction potential with marginal carbon price is determined. • Decarbonization paths during 2021–2060 for China's steel industry are developed. • Quantify the contribution of collaborative carbon reduction with source industries. [ABSTRACT FROM AUTHOR]

Electric arc furnace (EAF) steelmaking process is an environmentally friendly, energy saving, and low-carbon route to produce steel, but its further development is restricted by extensive electricity consumption in China. In this paper, the EAF steelmaking processes driven by solar energy system (EAF-SES) was developed, which supplies electricity for the whole process, and reduce the dependence on traditional energy sources. Life cycle assessment and techno-economic analysis of EAF steelmaking processes integrated with traditional energy system (EAF-TES) and EAF-SES was conducted according to the data of 1536 heats based on the function unit of 1000 kg of molten steel (MS). EAF-SES and EAF-TES were studied and compared from perspectives of life cycle carbon footprint (LCCF), production cost (PC), raw materials cost (RMC), solar energy price (SEP), and carbon tax (CT). The results indicated that EAF-SES enjoyed lower LCCF but higher PC than EAF-TES. The LCCF of EAF-SES was 220 kg lower than that of EAF-TES. Besides, compared to the PC of 478 $ per ton of MS in EAF-TES, the PC in EAF-SES increased by 9.13%. While the electricity price was lower than 0.041 $/kWh or CT higher than 217 $/t CO 2 , respectively, EAF-SES had both significant advantages of economic and environmental benefits. Vigorously employing clean energy power generation, cutting down hot metal supply, and adopting full scrap melting mode in EAF steelmaking processes achieve better environmental performance. This research is expected to supply a technical idea for energy conservation, emission reduction, and cleaner production in future iron and steel industry. [Display omitted] • EAF steelmaking process integrated with solar energy system (EAF-SES) was developed. • Comparative life cycle assessment and techno-economic analysis of EAF-SES was conducted. • Life cycle inventories of 1536 heats in EAF steelmaking process in China were converged. • Some methods of energy conservation and emission reduction in EAF steelmaking process were brought out. [ABSTRACT FROM AUTHOR]

• More reliable modeling assumptions and methods are proposed. • Price regulation may increase industrial output in China. • The reform can lead to a cleaner power mix and better economic structure. • The reform can be of great help to alleviate the fiscal deficit. • Impact mechanisms through cost linkages in different situations are put forward. China promised to achieve carbon neutrality in 2060. However, electricity prices are still regulated, which may affect the effect of carbon neutrality, especially in China, because 70% of China's electricity comes from thermal power generation. In this paper, a dynamic recursive computable general equilibrium model (CEEEA/CGE model) is applied to simulate the electricity market-oriented reform under the target of carbon neutrality from 2020 to 2060. The results show that the target may increase the demand for labor and capital to cope with increasing energy costs, and the reform may reduce GDP. However, power reform can significantly optimize the energy and economic structures and alleviate the fiscal deficit. Moreover, this paper finds and concludes the mechanism causing these effects (such as factor substitution, price advantage, government revenue, and structure), which provides policymakers with a new perspective of power reform. [ABSTRACT FROM AUTHOR]

COVID-19 brings new challenges to addressing climate change and achieving the goal of environmental sustainability. This paper examines how the COVID-19 pandemic affects transmission of returns spillovers among green finance, carbon market and renewable & non-renewable energy in China. We evaluate the dynamic and directional risk connectedness across time and at various frequency bands using Diebold and Yilmaz and Baruník and Křehlík approaches. First, the total spillover effects increase significantly when the COVID-19 outbreak. Second, the carbon price fluctuations are mainly influenced by non-renewable energy. Third, the spillover effect is mainly acted in the short term, meaning that it is strongly influenced by investor sentiment in the short term. Fourth, non-renewable energy and carbon markets are the main net recipients and can be used as hedge assets. Finally, the total spillover is time-varying that is affected by the unexpected crisis. The findings will help policymakers and environmental investors to develop policy measures and portfolios that are appropriate for different frequency domains. • Time-frequency connectedness among green finance, carbon and energy is tested. • Spillovers increase at the onset of the COVID-19 and mainly acted in the short-term. • The carbon price fluctuations are mainly influenced by non-renewable energy. • Non-renewable energy and carbon markets are the major net recipients. • The total spillover is time-varying affected by the unexpected crisis. [ABSTRACT FROM AUTHOR]

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

This is the first study utilizing carbon tax revenue to the renewable energy generation with Learning-by-doing (LBD) in the CGE model. This investigation demonstrates how induced technologically change (ITC) in the power sector offsets negative impacts on economic growth caused by the carbon tax in China. Business-as-usual scenario (without carbon tax) shows a significant impact of LBD on GDP growth and CO 2 emission reduction. Under a policy scenario with carbon tax, the results show that the negative impact on economic growth can be alleviated to less than 0.12%. If total carbon tax revenue was used for the subsidy to wind and solar power, even a positive impact on GDP growth will occur in the long-term. Therefore, the results verified and demonstrated the synergic effect of carbon pricing and the LBD process that economic loss caused by carbon tax could be offset by ITC in the renewable energy power sector. GDP decomposition shows that unexpensive electricity affected by ITC is beneficial to drive development of low-carbon energy, which can mitigate shock of carbon tax on heavy dependence on fossil fuel. This paper also provides policy implications that the LBD process will positively play a key role in energy structural shift under climate policy, making a great effort to climate mitigation. [Display omitted] • Combining bottom-up CGE model with top-down module Learning-by-Doing. • Utilizing carbon tax revenue to subsidy to renewable energy generation. • Providing optimistic impacts of carbon tax and subsidy on economic growth and reduction of carbon emission. • Learning-by-doing describes pathway of improved renewable energy. • Giving implication that Learning-by-doing can be boosted by environmental policies. [ABSTRACT FROM AUTHOR]

Strict climate goals require a rapid reduction of carbon emissions across society. It is a considerable challenge to design decarbonization pathways considering co-operation in energy and carbon emissions across multiple sectors simultaneously. In order to obtain the decarbonization pathway for the whole society, this paper establishes a long-term multi-sector low-carbon transition pathway planning model. Besides inter-sectoral energy supply and demand, this study fully considers the allocation of carbon emissions quotas among different sectors by modified-grandfathering method, which takes into account both equity and efficiency principles. The decarbonization targets of different sectors, corresponding mitigation pathways and energy consumption can be calculated. China is taken as a case study. Results show that China's total energy consumption peaks at 5 billion tces around 2030, then falls below 4 billion in 2060, with the proportion of primary electricity and other clean energy reaching over 50 percent. Besides, the realisation of carbon neutralisation in China depends heavily on the improvement of carbon capture and storage (CCS) and end-use electrification rate. Moreover, the study of different quota allocation ways shows that the increase in the contribution rate of power system mitigation leads to the reduction of the total low-carbon transition costs, which also aggravates administrative difficulties. • A multi-sector model is set up to plan the long-term low-carbon transition pathway. • Modified-grandfathering allocation method can consider multiple indicator factors. • The clean energy consumption of China accounts for about 55% in 2060. • The end-use electrification rate in China is close to 70% in 2060. • The transition pathway with lower cost increases administrative difficulties. [ABSTRACT FROM AUTHOR]

Balancing environmental protection and economic development is critical in climate policy-making. The carbon trading policy is an important market-based climate strategy that aids in achieving the national carbon neutrality goals. However, empirical evidence at the industry level has not yet demonstrated whether there is an employment dividend. In this study, we constructed a theoretical framework to analyze the employment effects of carbon trading policies. We quantitatively evaluated the employment effects of policies in the pilot region using the differences-in-differences model. And we considered and explained the adjustment paths of employment dividends from the industry-level onwards. We found a "two-eight split" phenomenon in the employment effects of the carbon trading policy in China—the overall employment level of the region increases while employment in some regulated industries is inspired and it is hindered in others, shifting to other regulated industries and non-regulated regions. The empirical results revealed the following points. (1) After controlling economic and demographic factors, carbon trading policies can bring significant employment dividends to pilot areas. (2) While implementing such policies can improve the employment level of the paper industry, they can also seriously impact the employment development of the petrochemical and building materials industries. (3) Both energy consumption and technology levels effectively dampen the policy's negative employment effects and promote employment in the pilot areas. (4) The high carbon price levels within the range of carbon price fluctuation have inhibited the employment levels of the pilot industries. However, it still promoted the overall employment levels of the pilot areas through the employment transfer effect. As future carbon prices increase, the policy's regional employment dividend may decrease or disappear. Our findings illustrate the employment effect of industry-level carbon trading policies and provide a reference for improving carbon market construction. [ABSTRACT FROM AUTHOR]

Carbon neutrality goal puts forward new requirements for the energy structure of the power industry in China. The impact of electricity marketization reform on energy transition is one key issue that we need to consider. This paper constructs a system framework for the internal connection of the four primary energy sources and two system dynamics (SD) models to analyze the impact of the marketed on-grid price on the energy transition in the power industry. The results show that: (1) Compared with the benchmark on-grid price, the marketed on-grid price can promote the realization of the energy transition goal in the power industry to a certain extent. In 2060, the marketed on-grid price will be stable at about 0.1 yuan/kWh. (2) The energy transition goal can be achieved if the degree of market openness exceeds 60%. However, if coal-based power fully enters the marketization stage, the proportion of renewable energy can even reach more than 90% in 2060. (3) It is difficult to achieve the carbon neutrality goal only by increasing the proportion of renewable energy. Finally, we put forward corresponding policy recommendations. • The electricity marketization reform has an impact on the energy transition. • Driving mechanism of the marketed on-grid price is investigated in the power industry. • Two system dynamics models are built. • The energy transition goal can be achieved if the market openness exceeds 60%. [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]

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]

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]

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]

• 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]

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]

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]

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]