"十四五"时期是中国实现碳达峰的关键时期,也是推动经济高质量发展和生态环境质量持续改善的重要阶段.可拓展的随机性环境影响评估(Stochastic Impacts by Regression on Population,Affluence,and Technology,STIRPAT)模型可以根据研究需要增加自变量,更好地分析相关因素对因变量的影响.以北京市为研究区,通过构建扩展的STIRPAT模型,分析人均地区生产总值(Gross Domestic Product,GDP)、人均汽车保有量、城市化率、第三产业GDP占比、能源消费强度与人均碳排放量的关系,并采用对数平均迪氏指数(Logarithmic Mean Divisia Index,LMDI)分解法分解能源消费强度.结果表明,产业结构和能源消费强度对人均碳排放量均有显著的正向影响.总体来看,要平衡经济发展与碳排放的关系,提高能源利用效率,推广可再生能源,降低能源消耗,减少碳排放.
Analysis on Influencing Factors of Carbon Emissions in Beijing City
The 14th Five-Year Plan period is a crucial period for China to achieve carbon peak,as well as an important stage for promoting high-quality economic development and continuous improvement of ecological environment quality.The Stochastic Impacts by Regression on Population,Affluence,and Technology(STIRPAT)model can add independent variables according to research needs to better analyze the impact of relevant factors on the dependent variable.Using Beijing city as the research area,an extended STIRPAT model is constructed to analyze the relationship between per capita Gross Domestic Product(GDP),per capita car ownership,urbanization rate,proportion of tertiary industry GDP,energy consumption intensity,and per capita carbon emissions,and the Logarithmic Mean Divisia Index(LMDI)decomposition method is used to decompose energy consumption intensity.The results indicate that both industrial structure and energy consumption intensity have a significant positive impact on per capita carbon emissions.Overall,it is necessary to balance the relationship between economic development and carbon emissions,improve energy utilization efficiency,promote renewable energy,reduce energy consumption,and reduce carbon emissions.
carbon emissionsinfluencing factorsStochastic Impacts by Regression on Population,Affluence,and Technology(STIRPAT)modelLogarithmic Mean Divisia Index(LMDI)decomposition methodBeijing city
万方数据
维普
