基于LMDI及STIRPAT模型的中国工业能源消费碳排放峰值预测研究

Prediction of Peak Carbon Emissions from Industrial Energy Consumption in China based on LMDI and STIRPAT Model

工业是能源消费碳排放的主要领域,文章以中国工业部门作为主要研究对象,运用LMDI方法将影响中国工业能源消费碳排放量的因素分解为经济增长、能源强度、能源结构、工业产业结构等四个方面,在测算2005—2019年中国工业部门碳排放量的基础上,运用岭回归方法构建扩展STIRPAT模型,与情景分析法相结合,对中国工业部门的碳达峰年份及峰值进行预测。结果显示,经济增长是影响碳排放最主要的因素,能源强度对碳排放有较强的负影响。在基准情景下,工业部门在2035年才出现碳达峰,为实现2030年前碳达峰的目标,文章从转变经济增长方式、优化产业结构、提高能源效率等方面进行路径优化,在低碳情境下,中国工业部门预计将于2028年实现碳达峰。

Industry is the main field of carbon emissions from energy consumption,this paper takes China's industrial sector as the main research object,decomposes the factors affecting China's industrial energy consumption carbon emis-sions into four aspects such as economic growth,energy intensity,energy structure,and industrial structure by using LM-DI method,and constructs an extended Ridge regression method based on measuring China's industrial sector carbon emis-sions from 2005-2019 STIRPAT model,combined with the scenario analysis method,to predict the carbon peak year and peak value of China's industrial sector.The results show that economic growth is the most important factor affecting car-bon emissions,and energy intensity has a strong negative impact on carbon emissions.Under the baseline scenario,the in-dustrial sector peaks in 2035.In order to achieve the goal of peaking by 2030,this paper optimizes the pathway in terms of changing the economic growth mode,optimizing the industrial structure,and improving energy efficiency,so that the peak year of China's industrial sector is advanced to 2028.