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As global climate change becomes increasingly severe, energy technology innovation has become a key means of coping with the climate crisis and realizing green and low-carbon development. However, existing literature rarely examines the effects of carbon emission reduction policies based on the perspective of energy technology progress for both short-term economic fluctuations and long-term equilibrium. This paper introduces the fossil energy technology sector and the renewable energy technology sector into the dynamic stochastic general equilibrium (DSGE) model, and compares the effectiveness of the carbon emission cap policy, the fossil energy technology subsidy policy, and the renewable energy technology subsidy policy under the framework of China's carbon trading market in promoting macroeconomic growth and controlling pollutant emissions. We found that in long-term, the emission reduction effect of the carbon emission cap policy falls short of the other two policies, and subsidizing fossil fuel technologies is more cost-efficient comparatively. The government expenditure shock can all stimulate macroeconomic growth with crowding out of private investment and household consumption, whereas the energy technology research productivity shock leads to a decline in total output and an increase in renewable energy technology demand. In addition, pollutant emissions are pro-cyclical under the impact of total carbon policies and counter-cyclical under the impact of energy technology subsidy policies. This article constructs a multi-technology sectoral dynamic stochastic general equilibrium model, expanding the research perspective and theoretical framework for evaluating carbon emission reduction policies. At the same time, it proves the importance of the government to implement the phased energy technology subsidy policy while implementing the carbon emission cap policy, which provides important enlightenment for the implementation and adjustment of carbon emission reduction policy. [ABSTRACT FROM AUTHOR]

In the global context, countries must reduce carbon dioxide emissions to "net zero" by 2050 to limit global warming to 1.5 °C above pre-industrial levels. China's Nationally Determined Contributions (NDCs) are to peak carbon dioxide emissions by 2030 and achieve the carbon neutrality target by 2060. To monitor the achievements of the NDCs, establishing an annual-based accounting mechanism is necessary to record the carbon stocks in China, especially for Blue Carbon. The paper aims to present China's first national-scale systematic Blue Carbon accounting for mangroves, salt marshes, and seagrasses, covering the accounting subjects of physical and monetary assets, as well as relevant indicators for investors. It focuses on the design of the accounting method and system, the selection of data categories applied to this system, and the application of China's Blue Carbon accounting based on this accounting system. Taking Blue Carbon accounting as a starting point, this paper analyses the restoration prospects of these ecosystems and their application potential for NDCs in China compared with the terrestrial ecosystems. The results indicate that mangroves are the most cost-effective type of ecosystem, even compared to terrestrial forests. Thus, the paper provides policymakers with a new perspective on the decision-making of carbon sequestration relevant decisions, aiming to promote the monitoring, restoration, and expansion of China's coastal blue carbon ecosystem through the establishment of a sound Blue Carbon accounting system, and to help achieve the carbon neutrality goal in China's NDCs through regular and systematic monitoring of its national Blue Carbon inventories. • China's coastal blue carbon ecosystems are carbon sources rather than carbon sinks. • Mangroves are the most cost-effective coastal blue carbon ecosystem compared to salt marshes and seagrass beds. • The Blue Carbon of mangroves is more cost-effective than the Green Carbon of terrestrial forests when meeting China's Nationally Determined Contributions target of increasing forest stocks. • Establishing guidelines for Blue Carbon data requirements will lay a scientific foundation for formulating strategies and policies to cope with global climate change. [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]

In the pursuit of carbon neutrality, state-owned forests are prime candidates for carbon offset projects due to their unique tenure and management characteristics. Employing methodologies endorsed by the International Panel on Climate Change and logistic growth curves, this study assesses the carbon stocks and sequestration potential of established state-owned plantation forests across 31 Chinese provinces from 2023 to 2060, encompassing seven forestry industry groups. This study projects that by 2060, these forests will amass a carbon stock of 558.25 MtC, with the highest stock in Northeast China (122.09 MtC) and the lowest in Northwest China (32.27 MtC), notably showing the highest growth rate at 91.15%. Over the forecast period, they are expected to accumulate a carbon sink of 637.07 MtCO2e, translating to an average annual carbon sink of 17.22 MtCO2e and an average annual carbon sink per unit of 1.41 tons of CO2 per hectare per year. Additionally, state-owned forests have the potential to offset approximately 0.15%–0.17% of annual carbon emissions, aligning with international climate goals. However, it is essential to note that the conversion of these carbon sinks into tradable carbon credits is subject to specific methodology requirements. Therefore, the future development of carbon offset projects in China's state-owned forests should consider the advancement of carbon market mechanisms, including the Chinese Certified Emission Reduction and the introduction of a carbon inclusion mechanism and natural forest methodology, to fully realize their potential contributions to carbon neutrality. In summary, these findings offer valuable insights for shaping the future of carbon offset initiatives within China's state-owned forests. [ABSTRACT FROM AUTHOR]

• Forecasting-test framework for long-term power system planning. • Coal-fired generators can be completely withdrawn from the power system by 2060. • China's power capacity mix will transition to wind and solar generators dominated. • Biomass and gas-fired generators will take on the role of reserved generators. • The timing of achieving China's zero-coal power system may be advanced or delayed. Facing the challenges of climate deterioration, environmental pollution, and energy shortages, China has put forward the goals of "carbon dioxide peaking and carbon neutrality", and the electricity sector will be the key area and the main direction of carbon emissions reduction. To prospect China's power system and explore the potential for establishing China's zero-coal power system in the future, this paper proposes a forecasting-test framework for long-term power system planning. We predict, evaluate, and analyze China's power system from 2025 to 2060 using the proposed forecasting-test framework. During this process, the power capacity mix and the electricity generation mix of China's power system will gradually transition from coal-fired generators dominated to wind and solar generators dominated. Moreover, the roles of different generators and energy storages are illustrated through the seasonal comparison and sensitivity analysis of the installed capacity of generators. The results indicate that coal-fired generators can be completely withdrawn from the power system, confirming the feasibility and possibility of achieving China's zero-coal power system by 2060. Although the timing may be advanced or delayed in different scenarios, achieving China's zero-coal power system will require exercising nationwide planning and making joint efforts of various sectors from now on. [ABSTRACT FROM AUTHOR]

This study explores the impact of political uncertainty on sustainable urban development by examining carbon emission trading systems (ETS) in four major markets in China (Beijing, Shanghai, Guangdong, and Hubei) from 2014 to 2022. As an alternative to carbon taxes, carbon ETS markets have become increasingly popular due to their success in reducing greenhouse gas emissions. However, their effectiveness is often hindered by political instability and uncertainty. Utilising logistic regression and AR(1)-GARCH estimations, we identify a negative relationship between political uncertainty and carbon trading volume. Our study also reveals significant variations in the responses of these markets to political uncertainty. The paper contributes to the understanding of how ETS markets operate in a complex and constantly changing political environment. We suggest that policymakers need to consider the impact of political uncertainty on carbon trading when designing and implementing urban policies that promote sustainable development. Additionally, our research contributes to the development of urban policies that can be effectively implemented in both developed and developing regions. • Local government official turnovers are used as the measurement of political uncertainty. • Daily transaction data from four carbon ETS markets (Beijing, Shanghai, Hubei and Guangdong) in China • Considered the probability and proportion of zero transaction day • Logistic regression and AR(1)-GARCH estimations • A negative relationship between political uncertainty and carbon transaction volume [ABSTRACT FROM AUTHOR]

To achieve the goals of carbon peaking and carbon neutrality, China is actively promoting carbon reduction in many areas. Agriculture is one of the main sources of greenhouse gas emissions, and promoting the development of low-carbon agriculture is a critical way to achieve carbon reduction targets. Taking Chongming District in Shanghai as an example, this study summarizes the experience of low-carbon agricultural development in Chongming and analyzes the problems and challenges faced during its development. Finally, based on the system dynamics method, the causal relationship of carbon emission in Chongming's agricultural development is constructed, and feasible loop optimization suggestions are put forward. [ABSTRACT FROM AUTHOR]