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<p>As the world’s largest carbon emitter and the second-largest economy, China has committed to reaching peak carbon emissions around 2030, with a 60%-65% reduction in carbon emissions intensity compared to 2005 levels. However, there is significant heterogeneity among Chinese provinces, and a one-size-fits-all approach to achieving peak carbon is not feasible. This paper, from a regional classification perspective and based on the “14th Five-Year Plan” (14th FYP) of each province, designs three development scenarios: low-carbon, baseline, and high-carbon. We utilize a GA-BP neural network integrated with Monte Carlo simulation to forecast China’s carbon emissions during 2021–2030, analyzing regional emission patterns and identifying differentiated decarbonization pathways across China. The main conclusions are as follows: (1) Based on variations among Chinese provinces in terms of economy, population, and energy consumption, they can be categorized into five types of regions: low-carbon demonstration, low-carbon potential, resource-dependent, low-carbon pilot, and those urgently in need of low-carbon development. (2) The primary factors influencing carbon emissions across different regions include GDP, population size, urbanization rate, technological level, energy consumption, and energy structure. Except for the technological level, which exerts a negative impact, all other factors have a positive effect. (3) China can achieve its peak carbon target under both low-carbon and baseline scenarios; however, under the high-carbon scenario, a peak cannot be reached before 2030. (4) A few provinces are projected to peak between 2020 and 2025; the majority are expected to reach their peak between 2025 and 2029, while provinces that are unlikely to peak by 2030 include Xinjiang, Inner Mongolia, Henan, Jiangxi, Fujian, and Guangxi.</p>

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Advancing China’s dual carbon goals: regional classification and customized emission reduction strategies

  • 期刊论文

  • 发表日期：

    2025年8月22日

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  • Junwei Zhao,
  • Huiqin Zhang,
  • Yuxiang Zhang,
  • Anhang Cheng

摘要

As the world’s largest carbon emitter and the second-largest economy, China has committed to reaching peak carbon emissions around 2030, with a 60%-65% reduction in carbon emissions intensity compared to 2005 levels. However, there is significant heterogeneity among Chinese provinces, and a one-size-fits-all approach to achieving peak carbon is not feasible. This paper, from a regional classification perspective and based on the “14th Five-Year Plan” (14th FYP) of each province, designs three development scenarios: low-carbon, baseline, and high-carbon. We utilize a GA-BP neural network integrated with Monte Carlo simulation to forecast China’s carbon emissions during 2021–2030, analyzing regional emission patterns and identifying differentiated decarbonization pathways across China. The main conclusions are as follows: (1) Based on variations among Chinese provinces in terms of economy, population, and energy consumption, they can be categorized into five types of regions: low-carbon demonstration, low-carbon potential, resource-dependent, low-carbon pilot, and those urgently in need of low-carbon development. (2) The primary factors influencing carbon emissions across different regions include GDP, population size, urbanization rate, technological level, energy consumption, and energy structure. Except for the technological level, which exerts a negative impact, all other factors have a positive effect. (3) China can achieve its peak carbon target under both low-carbon and baseline scenarios; however, under the high-carbon scenario, a peak cannot be reached before 2030. (4) A few provinces are projected to peak between 2020 and 2025; the majority are expected to reach their peak between 2025 and 2029, while provinces that are unlikely to peak by 2030 include Xinjiang, Inner Mongolia, Henan, Jiangxi, Fujian, and Guangxi.