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• A CGE model elaborately depicting six CCS technologies was developed. • Impacts of four CCS incentive scenarios on decarbonization pathways were simulated. • CCS can sequester 960 ∼ 1,604 MtCO 2 annually in China by 2060 with policy incentives. • CCS incentives can reduce China's future primary energy demand by 7.7 ∼ 17.4 %. • CCS incentives can increase GDP by 5.64 ∼ 6.59 % compared to no policy scenario. Carbon capture and storage (CCS) technology, considered as a pivotal tool in mitigating climate change within the fossil energy system, particularly in China, has experienced slower development than expected. The exploration of direct incentive policies to facilitate its growth remains relatively underdeveloped. This study developed a hybrid dynamic computable general equilibrium (CGE) model to simulate the substantial impacts of CCS incentive policies on China within the context of carbon neutrality target. Two potential incentive policies, carbon emission trading system (ETS) and 45Q tax credit, were simulated, with different sectoral coverage. The results indicate that CCS technologies can reduce carbon emissions by 960 ∼ 1,604 MtCO 2 annually by 2060 through the strategic implementation of these incentive policies. The 45Q tax credit demonstrates its effectiveness in promoting early-stage research and development (R&D) and demonstration of CCS, while the ETS policy facilitates the commercial development of CCS in the later stage of development. By 2060, the implementation of CCS incentive policies could potentially result in 7.7 ∼ 17.4 % reduction in China's primary energy consumption, 71.2 ∼ 82.7 % decrease in the carbon price of ETS and 5.64 ∼ 6.59 % increase in the GDP compared with the no-policy scenario. In addition, the sectoral output in various sectors and the welfare of urban and rural households also increase. This paper provides an important reference for the realization of China's carbon neutrality goal and the model framework can be applied to other countries. [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]

• 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]