Shan Bao-Guo, Yao Li, Zhang Cheng-Long, Tan Xian-Dong
State Grid Energy Research Institute Co., Ltd., Beijing 102209, China.
Huan Jing Ke Xue. 2025 Jul 8;46(7):4052-4064. doi: 10.13227/j.hjkx.202406016.
Achieving carbon peak before 2030 and carbon neutrality in 2060 is the solemn commitment of the Chinese government to the international community. It is important to scientifically identify the key influencing factors and accurately predict carbon peak value and time for achieving the dual carbon targets in China. On the basis of the economic and energy consumption data from 1980 to 2022， a STIRPAT extended multivariate-nonlinear model was built， which was fitted by a ridge regression to examine the relationships between carbon emissions of energy consumption and seven influencing factors， including population， GDP per capita， energy intensity， secondary industry proportion， fossil energy proportion， electrification rate， and urbanization rate. Based on the proposed STIRPAT extended model， predictions of carbon emissions of energy consumption were made for the period from 2023-2035 under three different scenarios. The results showed that： ① There were five factors that increased the carbon emissions including population， urbanization rate， secondary industry proportion， GDP per capita， and electrification rate. The degree of influence decreased in turn. Fossil energy proportion and energy intensity were the two factors that restrained the carbon emissions. The influencing degree of fossil energy proportion was the biggest， and that of energy intensity was the smallest. ② During different stages of economic development， the roles and contributions of the seven factors changed significantly. In particular， the effects of energy intensity， secondary industry proportion， and fossil energy proportion resulted in the turning changes， which reflected the periodical characteristics of carbon emissions in different stages. ③ Carbon emissions of energy consumption will achieve a peak during 2028-2032 in China. The peak was 11.66-12.75 billion tons. Under the baseline scenario， the peak was 12.04 billion tons， which will be fulfilled in 2030. The peak of the low-carbon scenario was 11.66 billion tons in 2028， which was 3.16% lower than that of the baseline scenario. The peak of the high-carbon scenario was 12.75 billion tons in 2032， which was 5.90% higher than that of the baseline scenario. Based on the research results， reasonable suggestions such as accelerating renewable energy development， increasing the electrification rate， optimizing the economic structure， and improving energy efficiency are put forward to ensure that China will achieve its carbon peak target before 2030.
2030年前实现碳达峰、2060年前实现碳中和，是中国政府向国际社会作出的庄严承诺。科学识别关键影响因素，准确预测我国实现“双碳”目标的碳峰值和时间至关重要。基于1980—2022年经济与能源消费数据，构建了STIRPAT扩展多元非线性模型，并采用岭回归进行拟合，以考察能源消费碳排放与人口、人均GDP、能源强度、第二产业比重、化石能源占比、电气化率、城镇化率7个影响因素之间的关系。基于所构建的STIRPAT扩展模型，对2023—2035年3种不同情景下的能源消费碳排放进行了预测。结果表明：①人口、城镇化率、第二产业比重、人均GDP、电气化率5个因素增加碳排放，影响程度依次递减；化石能源占比和能源强度是抑制碳排放的2个因素，其中化石能源占比影响程度最大，能源强度影响程度最小。②在经济发展的不同阶段，7个因素的作用和贡献变化显著，特别是能源强度、第二产业比重、化石能源占比的作用出现转折性变化，体现了不同阶段碳排放的阶段性特征。③我国能源消费碳排放将在2028—2032年达峰，峰值为116.6亿—127.5亿吨。基准情景下峰值为120.4亿吨，将于2030年实现；低碳情景下2028年峰值为116.6亿吨，比基准情景低3.16%；高碳情景下2032年峰值为127.5亿吨，比基准情景高5.90%。基于研究结果，提出加快可再生能源发展、提高电气化率、优化经济结构、提升能源效率等合理建议，以确保我国在2030年前实现碳达峰目标。
