School of Statistics and Applied Mathematics, Anhui University of Finance and Economics, Bengbu, 233030, China.
Department of Finance, NEOMA Business School, 1 Rue du Maréchal Juin, 76130, Mont-Saint-Aignan, France.
J Environ Manage. 2024 Jul;364:121445. doi: 10.1016/j.jenvman.2024.121445. Epub 2024 Jun 12.
The Yangtze River Delta (YRD) region plays a crucial role in achieving China's carbon peaking goal. However, due to uncertainties surrounding future economic growth, energy consumption, energy structure, and population, the attainment of carbon peaking in this region remains uncertain. To address this issue, this study utilized the generalized Divisia index method to analyze the driving factors of carbon emissions, including economy, energy, investment, and population. Subsequently, Monte Carlo simulations were combined with scenario analysis to dynamically explore the peak path of regional heterogeneity in the YRD from 2022 to 2035 under uncertain conditions. The findings highlighted that economic uncertainty has the most significant impact on carbon emissions. Furthermore, reducing energy intensity and promoting the transformation of the energy consumption structure contribute to carbon reduction. The study also revealed that the carbon peak in the YRD exhibits regional heterogeneity. According to the baseline scenario, carbon emissions in the YRD will not peak before 2035. However, under the low-carbon development scenario, the carbon emissions of Zhejiang and Shanghai will peak before 2030. Moreover, under the enhanced emission reduction (EE) scenario, carbon emissions in Jiangsu, Zhejiang, and Shanghai will peak before 2025, while Anhui will reach its peak before 2030. Collectively, the entire YRD region is forecasted to attain a carbon emissions peak of 2.29 billion tons by 2025 under the EE scenario. This study provides valuable insights into the carbon emission trajectories of the YRD region under uncertain conditions. The findings can be instrumental in formulating carbon peaking policies that account for regional heterogeneity.
长三角地区在实现中国碳达峰目标中发挥着关键作用。然而,由于未来经济增长、能源消费、能源结构和人口等方面存在不确定性,该地区实现碳达峰仍存在不确定性。为了解决这一问题,本研究利用广义迪氏指数法分析了经济、能源、投资和人口等因素对碳排放的驱动作用。随后,采用蒙特卡罗模拟与情景分析相结合的方法,动态探讨了长三角地区在 2022 年至 2035 年期间在不确定条件下的区域异质性达峰路径。研究结果表明,经济不确定性对碳排放的影响最大。此外,降低能源强度和促进能源消费结构转型有助于减少碳排放。研究还揭示了长三角地区的碳达峰存在区域异质性。根据基准情景,长三角地区的碳排放不会在 2035 年前达到峰值。然而,在低碳发展情景下,浙江和上海的碳排放将在 2030 年前达到峰值。此外,在强化减排情景下,江苏、浙江和上海的碳排放将在 2025 年前达到峰值,而安徽则将在 2030 年前达到峰值。总体而言,在强化减排情景下,长三角地区预计将在 2025 年达到 22.9 亿吨的碳排放峰值。本研究为长三角地区在不确定条件下的碳排放轨迹提供了有价值的见解。研究结果可为制定考虑区域异质性的碳达峰政策提供参考。