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With the acceleration of the global response to climate change, increasing attention has been paid to the risks associated with climate change mitigation, such as regulation uncertainties and market interactions. As the country with the greatest CO2 emissions globally, China has launched a national carbon market to speed up its climate mitigation. While the national carbon market provides a platform for regional coalitions to reduce emissions, its incomplete sectoral coverage might allow for the strategic behavior of industries in different regions and ultimately affect the efficiency of the carbon market. This paper explores how the sectoral expansion of the national carbon market affects regional emission reductions in China when emissions trading sectors engage in strategic behavior in the output market. From the sectoral perspective, our numerical results show that the strategic effect in the electricity and steel sectors is more significant than in other sectors. From a regional perspective, the western regions of China, which are mostly permit sale regions, have less strategic power than the eastern regions in the output and carbon markets. Finally, this paper suggests that measures, such as the dynamic adjustment of emission allowance allocation, should be considered by policy makers to prevent the widening of regional economic disparities when extending the sectoral coverage of the carbon market in China. [ABSTRACT FROM AUTHOR]

This paper introduces a novel methodology for estimating carbon total factor productivity based on the Cobb–Douglas production function. The research method introduced in this article expands upon the framework for assessing total factor productivity through the Solow residual method. It unifies the conceptual and methodological aspects of carbon total factor productivity with those of single factor productivity. Utilizing panel data from various provinces between 2010 and 2021, we computed carbon total factor productivity to understand its implications for China in combating global climate change. We demonstrate that (i) we have introduced a method to handle negative coefficients in the Cobb–Douglas production function by incorporating productivity in lieu of input factors during calculations. (ii) Carbon total factor productivity, encapsulating the geometric weighted mean of labor, capital, and carbon productivity, holds notable economic relevance. Further, it serves as an integrative metric comprising carbon productivity intertwined with the mean labor and capital carbon factors. And (iii) the influence of carbon total factor productivity growth on economic progression remains relatively subdued, with escalating labor force growth posing detrimental effects on several provincial economies. Enhancing carbon total factor productivity emerges as an imperative to harmonize robust economic growth with strategic carbon curtailment. Our analytical framework provides nuanced perspectives on productivity determinants, accentuating the thrust towards sustainable evolution amidst climatic challenges. This investigation bears profound significance for policymakers endeavoring to sculpt a carbon-conscious economic paradigm in consonance with global climatic ambitions. [ABSTRACT FROM AUTHOR]

Carbon intensity is one of the key indexes in the process of decarbonizing development. Therefore, our paper investigates possible pathways of China's carbon intensity to 2050 depending on China's development stage and trends. We first investigate the major influence factors of carbon intensity based on the Kaya identity, and then forecast China's future carbon intensity with a generalized regression neural network model coupled with a scenario analysis with official data from 1978 to 2020. Our results show that: (1) China's carbon intensity will decrease under the benchmark growth, high growth, and low growth scenarios but vary by amounts and rates of decrease due to the settings of the influences factors; (2) China is able to achieve the reduction targets of 2025 under the benchmark growth and low growth scenario, but cannot achieve the target under the high grow scenario. However, China can meet its reduction target by 2030 in all scenarios. (3) The Chinese government should aim to reduce carbon intensity by 23–25%, 40–44% and 64–70% by 2035, 2040 and 2050 as compared to the level in 2030. Therefore, China should keep promoting the deep low-carbon transformation of economic development model, and realize high-quality economic development in order to achieve these objectives. [ABSTRACT FROM AUTHOR]

How to achieve the "double carbon" goal in energy systems has been the concern of governments. Integrated energy system (IES) is affected by climate change during his operation, in order to study the impact of climate change on IES and achieve the "double carbon" goal in energy systems, this paper proposes an integrated machine learning(IML) to forecast the long-term load, then investigates IES costs and carbon emissions in relation to climate, followed by the establishment of carbon peak energy system(CPES) and carbon neutral energy system(CNES), finally the honey badger algorithm is used to optimize the configuration of CPES and CNES. The results show that: IML can accurately make load forecasts. Under climate change, changes in load reduce the cost and carbon emissions of IES, and changes in equipment efficiency increase the cost and carbon emissions of IES. When both are considered, the cost and carbon emissions of IES increase by 1.18% and 0.92% per decade respectively. The costs of CPES and CNES increase by 0.93% and 1% respectively for every 10 years earlier than the year of achievement. To meet China's "double carbon" goal, CPES and CNES need to increase their costs by 1.97% and 2% respectively. • Integrated machine learning proposed for long-term load forecasting. • Studied the impact of system equipment efficiency and load with climate change. • Proposing carbon peaking energy system to achieve the carbon peak goal. • Proposed carbon-neutral energy system to achieve carbon neutrality goal. • The increased costs of achieving carbon peak and carbon neutral were studied. [ABSTRACT FROM AUTHOR]