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China's energy transformation has been accompanied by potential energy security issues. However, the influence degree and driving mechanism behind this phenomenon remain unclear. In this paper, we developed a complex network-based technical resilience assessment framework and quantified both the historical trajectory and the prospective pathway of energy technical resilience in China. We proposed to reveal the relationship between cleaner energy supply and technical resilience by defining three energy technology resilience indicators: energy robustness, energy recovery rate, and energy performance loss. The results showed a consistent decline in energy technical resilience within China, predominantly characterized by an average diminution of 6.83% in energy robustness from 2010 to 2018. Taking carbon neutrality as a target, China's energy system transformation, characterized by increasing clean energy supply, leads to a significant improvement of 7.73% in energy robustness from 2020 to 2060. Conversely, the nationally determined contribution scenario exhibited negligible changes (±0.57%) in energy robustness, while a decline of 2.21% was noted under the business as usual scenario. Furthermore, energy robustness exhibited increments of 12.07%, 2.3%, and 4.17% for every 10% rise in the share of clean energy supply during 2020–2060, demonstrating greater resilience for cleaner energy systems against disruptions, including energy import interruptions, malicious attacks, and random failures. It has been concluded that enhancing the supply of clean energy can significantly contribute to bolstering China's energy technical resilience, while simultaneously addressing climate change concerns. • Network analysis is used to assess China's energy technical resilience. • Energy technical resilience is evaluated regarding robustness, recovery rate, and performance loss. • Energy system robustness significantly increases under carbon neutrality scenario. • Increasing clean energy supply strengthens resilience against shocks. [ABSTRACT FROM AUTHOR]

The intensification of global climate change has led to a widespread consensus on carbon reduction, with the power industry being the principal contributor to carbon emissions necessitating an inevitable transition of its energy structure. Concomitantly, the escalating frequency of natural disasters caused by extreme weather presents formidable challenges to both secure power supply and the low-carbon transition of the power system. To fulfill the developmental requirements of a low-carbon power system and address the carbon emission risks imposed by natural disasters, this paper proposes a bi-level model for generation expansion planning (GEP) that incorporates constraints on the carbon emission trajectory and the influence of natural disasters. The planning-level model optimizes investment costs of various generation technologies and energy storage (ES), as well as the overall operational expenses over the planning period, with an objective to minimize them. It incorporates carbon emission trajectory constraints and policy constraints, such as carbon peaking, carbon neutrality and renewable energy (RE) penetration rates, in order to optimize the planning installed capacity of power sources. The operational-level model aims to minimize typical daily operating costs while also simulating power unit outputs in routine and disaster scenarios. A case study is conducted in a disaster-prone province in southern China to analyze the power generation expansion planning and the trajectory of carbon emissions from 2020 to 2060 under different scenarios. The simulation results show that compared to thermal power, the planning scheme mainly focused on RE with ES is better suited to achieve the goal of a low-carbon transition of the power grid. Moreover, after considering natural disasters, the cost and carbon emissions of power system planning are higher, and the risk of carbon emissions increases with the severity of disasters. • A multi-time scale bi-level low-carbon GEP model is proposed. • Natural disaster scenarios and low-carbon policy constraints are considered in the GEP model. • Carbon emission trajectory of the planned power system is estimated and introduced as a constraint into the GEP model. • Evaluation indicators that comprehensively consider low-carbon performance and economic feasibility are proposed. [ABSTRACT FROM AUTHOR]

As the world's largest producer and consumer of coal, coal phaseout is critical for China to achieve carbon neutrality and contribute to global decarbonization. Here, utilizing the Global Change Assessment Model, this paper simulates China's coal phaseout pathways at the sectoral level between 2015 and 2060, considering the deployment of carbon capture and storage (CCS). The results show that China's coal consumption peaks at 96.4 Exajoules (EJ) in approximately 2020 and needs to decrease to 10.9 EJ by 2060 to achieve carbon neutrality. Specifically, the power sector bears the most significant proportion of responsibility, as its coal consumption must fall to 1.4 EJ by 2060, which is approximately 97.2% lower than the peak in 2020. The industrial sector is next and needs to decrease consumption to 9.2 EJ of coal in 2060, which is a reduction of 32.3 EJ below the 2020 level. Electricity will replace coal as the dominant energy source in the industrial sector after 2040. However, a portion of feed coal will remain in the industry for a long time. Among the industrial subsectors, the steel sector needs to put significant pressure on efforts to phase out coal, followed by the cement and nitrogen fertilizer sectors. In 2060, these three sectors will consume 5.7 EJ of coal, accounting for 64.1% of the total coal consumption in the industrial sector. The deployment of coal-CCS is one of the alternatives to achieve carbon neutrality and ensure smooth coal phaseout. Under the carbon neutrality scenario, the annual deployment of coal-CCS needs to exceed 0.13 EJ from 2025 to 2045, with a peak at 3.3 EJ in 2045. • China's coal phaseout pathway is assessed in the carbon neutrality scenario (CNS). • Coal consumption needs to drop to 10.9 EJ in 2060 to achieve carbon neutrality. • The power sector's coal will decrease to 97.2% below the peak by 2060 in the CNS. • The industry will pass the power sector as the top coal consumer by 2045 in the CNS. • The deployment of coal-CCS will peak at 3.3 EJ after 2045 in the CNS. [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]

• We provide the most up-to-date CO 2 emission inventory for China's cement industry. • We construct the G-LEAP model to project the CO 2 emissions of China's cement industry. • The CO 2 emissions could be reduced maximum by 70 percent in 2060, while the remainder will need to come from technological innovation and new growth horizons. This paper aims to assess the emission reduction potential of combined mitigation technologies in China's cement industry, thus transitioning towards carbon neutrality through a suitable technology portfolio and exploring a low-carbon pathway. The G-LEAP model is constructed for future carbon emission projection, incorporating the cement demand projection and technology application. The pathways based on different technology portfolios are developed to estimate the CO 2 emission trajectory of China's cement industry. We maximize the utilization of currently available technologies and assume a high level of innovative technology diffusion rate in the integrated mitigation pathway to explore the maximum abatement potential of the cement industry. The result shows that short-term mitigation mainly relies on improving energy efficiency and alternative low-carbon fuels, which would contribute 9–12% and 17–22% of the cumulative emissions reduction in the integrated mitigation pathway compared to a frozen scenario. Alternative clinkers can significantly reduce process-related emissions, but the potential is determined by the availability of raw materials, which would contribute 30–39% of the cumulative emission reduction. Post- and oxygen-combustion capture is expected to be deployed by 2030 and contribute about 28–44% to cumulative emission reduction. The technology portfolio in the integrated mitigation pathway would reduce China's cement CO 2 emissions by 63–73% compared to the frozen scenario, and the remainder of CO 2 emission would be 300–400 Mt in 2060, which will need the technological innovation and new growth horizons, such as carbon sink approaches or carbon trading. [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]

• Constructing a new welfare function considering economy, equity and ecology. • Optimizing carbon emission pathways from multiple perspectives. • Focusing on the emission pathways in China achieving the ambitious targets. With the increasing climate warming, reducing carbon emissions has gradually become a consensus around the world. However, the process of carbon emission reduction will inevitably lead to the transformation of economic structure, industrial structure and energy structure, which will bring huge changes in economic output, employment and other aspects, thus affecting the overall social welfare and equity. Therefore, it is particularly important for each country to determine a scientific and effective carbon emission pathway which take into account both social development and climate targets. As the largest carbon emitter, China has put forward the targets of carbon peak and carbon neutrality. In this regard, the corresponding carbon emission reduction scenarios are designed according to the new situation of China's emission reduction in this paper, firstly. Furthermore, under the premise of maximizing social welfare, an optimization model which integrating economic growth-equity-environment is developed to determine China's emission pathways under different scenarios from 2020 to 2050. Besides quantitatively showing the future total amount and peak value of carbon emissions under different scenarios, the results can also identify its evolution pathway over time. Therein, the peak under most scenarios will concentrate in 2025–2030, which is about 10.7 to 11.8 billion tons. With the increasingly stringent constraints on carbon emission reduction, the cost of emission reduction will increase correspondingly, but the overall social welfare will increase slightly. Finally, our findings provide practical guidance on achieving carbon emission reduction and enlightenments on policymaking. [ABSTRACT FROM AUTHOR]