2023污染生态学与绿色低碳发展——基于STIRPAT模型的中国碳排放峰值预测与驱动因素分析  

Research on Carbon Emission Peak Prediction in China—Based on STIRPAT Model and Driving Factor Decomposition Analysis

作　　者：于智超 蒙鲁宁 韩欣桐 王诗云 

机构地区：[1]沈阳航空航天大学理学院,辽宁 沈阳

出　　处：《应用数学进展》2024年第7期3442-3455,共14页Advances in Applied Mathematics

摘　　要：中国是碳排放大国,其碳达峰和碳中和实现对全球碳减排至关重要。中国未来碳排放如何变化,其关键驱动因素是什么,一直是人们关注的焦点。本研究通过构建拓展的STIRPAT模型,基于2000~2020年碳排放数据,开展我国未来碳排放变化模拟研究。结合LMDI分解方法,从人口规模、人均GDP、第二产业占比、城镇化率、煤炭消费量占比和能源强度角度阐明我国碳排放变化的驱动因素。研究结果表明,STIRPAT模型能较好模拟我国碳排放量。人口规模,人均GDP和城镇化率是促进我国碳排放的主要驱动因素,平均贡献率分别达30.16%,34.85%和36.02%。通过STIRPAT模型模拟可发现基准情景、绿色发展情景和经济增速放缓情景在2030年前均能实现碳达峰,且绿色发展情景是我国实现碳达峰的最优路径。此情景下,我国在不降低经济增速的前提下,需要积极调整能源结构和产业结构,提高能源利用效率,加大碳减排政策的实施力度,可确保2030年前实现碳达峰目标,碳排放峰值为115.86亿吨。研究成果可为我国碳减排目标实现路径和相应政策制订提供参考依据。China is a major carbon emission country, and its realization of carbon peak and carbon neutralization is crucial to global carbon emission reduction. How China’s carbon emissions will change in the future and what are the key drivers have always been the focus of attention. Based on the carbon emission data from 2000 to 2020, we simulate China’s future carbon emission changes through STIRPAT model. Combined with LMDI decomposition method, the driving factors of China’s carbon emission change are clarified from the perspective of population, per capita GDP, the proportion of secondary industry, urbanization rate, the proportion of coal consumption and energy intensity. The results show that STIRPAT model can accurately simulate China’s carbon emissions. Population, per capita GDP and urbanization rate are the main factors that promote China’s carbon emissions, with contribution rates of 30.16%, 34.85% and 36.02% respectively. Through STIRPAT model simulation, we found that carbon emission under the benchmark scenario, green development scenario and low economic growth scenario can achieve carbon peak before 2030, among which the green development scenario is the best path for China to achieve carbon peak goal. Under the green development scenario, the peak carbon emission would be 11.586 billion tons. It needs to actively adjust the energy structure and industrial structure, improve energy efficiency, and strengthen the implementation of carbon emission reduction policies to ensure carbon peak before 2030 without restricting economic development. Our study can provide a reference for the realization path of China’s carbon emission reduction goals and the corresponding policy-making.

关 键 词：碳排放 峰值预测 驱动因素 STIRPAT模型 LMDI分解方法 

分 类 号：F42[经济管理—产业经济]