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As major strategic development areas in China, the provinces around the Yangtze River are facing the pressure of large aggregate CO 2 emissions and high per capita CO 2 emissions. The study on the pathway of reducing CO 2 emissions and increasing carbon sequestration will help China better clarify the ways realize the goals of carbon peak and carbon neutrality as soon as possible. In this paper, the extended STIRPAT model and OLS regression were used to establish a prediction model to estimate the CO 2 emissions during 2010–2060 under different scenarios. Meanwhile, the InVEST model was used to estimate the carbon sequestration, and the comparison with the CO 2 emissions was analyzed. The results show that Qinghai and Yunnan have achieved the goal of carbon neutrality in 2010. Under the low-carbon and energy-saving scenario and the baseline scenario, all provinces within the study area are anticipated to attain their emissions peak by 2030 or earlier, and the CO 2 emissions peak value of the whole study area is 3111 Mt and 3199 Mt, respectively. While under the high emissions scenario, only Chongqing and Qinghai will reach the emissions peak in 2030, and the whole study area will reach the emissions peak in 2040, with peak value of 3470 Mt. Under the three scenarios, the whole study area cannot achieve carbon neutrality before 2060. Only Sichuan and Hubei can achieve carbon neutrality in 2050 and 2060 under the low-carbon and energy-saving scenario. All provinces and municipalities in the lower reaches of the Yangtze River are facing huge pressure of emissions reduction. The research reveals that the goals of carbon peak and carbon neutrality should be achieved by developing clean energy, transforming industrial structure, increasing carbon sequestration and improving carbon emissions trading system. [Display omitted] • The CO 2 emissions showed a pattern of increase during 2010–2020. • The whole study area will achieve carbon peak by 2040 or earlier. • The whole study area cannot achieve carbon neutrality before 2060. • The realization pathway of carbon peak and neutrality was proposed. [ABSTRACT FROM AUTHOR]

Carbon emission trading, a market-incentive environmental regulation, plays a critical role in leading China towards the carbon peaking and carbon neutrality. To improve the national carbon emission trading in China, we analyze the effects of the policy in pilot provinces and pilot A-share listed firms from 2008 to 2016. Particularly, to explore the pilot policy's environmental and financial impacts, this paper applies a difference-in-difference method. After the robustness check, the results confirm the carbon emission trading pilot's significantly positive impact at both firm- and province-level regarding carbon emission reduction. Meanwhile, corporate innovation seems to partially mediate the relationship between the policy and corporate carbon emission reduction. Plus, the policy promotes firms' market-based financial performance but such impact on accounting-based financial performance is insignificant. Ultimately, the operational mechanism of the policy is proved to be effective. In this paper, industry- and firm-level carbon emissions databases are established via environmental extended input-output table, which fill the research gap of China's firm-level carbon emissions. To ensure the reliability of results, the list of covered firms is sorted out manually in accordance with the disclosed data of seven carbon trading markets. Our results are meaningful for avoid productivity reduction and mechanism re-design in the context of the national carbon emission trading launched in 2021. Specifically, encouraging firms to further improve their productivity and competitiveness by innovation could eventually achieve a win-win situation between economic performance and environmental merits in the long run. [ABSTRACT FROM AUTHOR]

Promoting low-carbon development in the iron and steel industry (ISI) is essential for China to achieve the carbon neutrality targets. This paper separately adopts the Logarithmic Mean Divisia Index (LMDI) technique and the Mean Impact Value (MIV) method to analyze the impact of driving factors on the CO 2 emissions of ISI in the historical and future dimensions. Furthermore, this paper establishes the extreme learning machine model optimized by the bat algorithm (BA-BP) to explore the carbon emission reduction pathways of ISI in the business-as-usual (BAU) scenario, the low-speed, medium-speed and high-speed development scenarios considering the constraints of carbon neutrality targets. The results reveal that: (1) Production capacity and energy efficiency are important drivers of CO 2 emissions in ISI; (2) The emission reduction situation is not optimistic under the BAU scenario, and it is difficult to accomplish the carbon neutrality goals by 2060; (3) Under the most ideal emission reduction pathway (corresponding to the high-speed development scenario), ISI will reach its peak in 2022 with the peak value of 2143.42 MtCO 2. Compared to the peak year, the CO 2 emissions will be reduced by 654.69 MtCO 2 and 1558.61 MtCO 2 in 2030 and 2050, respectively. Moreover, the achievement of short-term and long-term emission reduction targets depends on production capacity decline and technological progress, respectively. The optimal emission reduction pathway provides a reference for ISI to formulate periodic emission reduction targets. • The improved extreme learning machine is employed to predict the carbon emissions. • The emission reduction pathways are explored under the carbon neutrality target. • Controlling production capacity is a crucial reduction strategy. • The energy rebound effect is supposed to be weakened. • The application of advanced technologies will greatly promote emission reduction. [ABSTRACT FROM AUTHOR]

Emissions trading system (ETS) is a cost-effective way towards achieving the carbon neutrality goal. Based on the gaps in the research on carbon allowance allocation vis-à-vis the carbon neutrality target, this study examines how to allocate carbon allowances equitably and effectively among Chinese provinces. Different from the previous research that mainly considers responsibility, ability, and potential of equity dimensions, this paper proposes a composite indicator allocation approach based on the equity of history, demand, contribution, and guarantee, and it also employs the entropy method and expert survey method to obtain the indicator weight values in different scenarios. Results show that the carbon allowances of some provinces, such as the forest-rich province of Yunnan, vary significantly in five scenarios, but little differences are observed for some provinces, such as the high historical emissions province of Shanxi. More provinces achieve data envelopment analysis efficiency in the preferred scenario. Compared with the objective scenario, the required emission reduction in the preferred gross domestic product (GDP) scenario is 231 million tonnes less, and the emission reduction cost is 190 billion yuan less. It is suggested that the Chinese government should adopt the allocation scheme in preference for the GDP scenario. [ABSTRACT FROM AUTHOR]