基于LMDI模型的能源系统碳排放影响因素分析

Analysis of Factors Influencing Carbon Emissions ofEnergy Systems Based on LMDI Model

在“双碳”目标的背景下,作为全社会碳排放最主要的排放源,能源活动的碳减排尤为关键。为明确电力系统碳排放量、能源消费强度、产业结构等因素对能源系统碳排放的影响作用及贡献程度,基于灰色GM(1,1)模型对我国的能源消费总量进行预测,并进行模型检验以保证可行性。根据联合国政府间气候变化专门委员会(intergovernmental panel on climate change,IPCC)碳排放系数法,根据我国能源平衡表的数据对2015—2019年各行业碳排放量进行测算。在此基础上,利用对数平均迪氏指数法(logarithmic mean Divisia index,LMDI)构建碳排放分析模型,对结果标准化处理后分析各效应对能源系统碳排放量的影响程度。计算结果表明能源消费强度、人口数量、城镇化水平及电力碳排放量会促进能源系统碳排放增长,而能源消费强度、农村人口比重及产业结构起到了抑制作用。

In the context of the “carbon peaking and carbon neutrality” goals, as the main source of carbon emissions in the whole society, carbon reduction in energy activities is particularly critical. In order to clarify the role and contribution of power system carbon emissions, energy consumption intensity, industrial structure and other factors to the carbon emissions of energy system. Firstly, the total energy consumption in China is predicted based on the gray GM(1,1) model, and the model is tested to ensure the feasibility. Secondly, based on the intergovernmental panel on climate change(IPCC) carbon emission factor method, the carbon emissions of each industry from 2015-2019 are measured based on the data of China’s energy balance sheet. On this basis, a carbon emission analysis model is constructed using the logarithmic mean Divisia index(LMDI) method, and the results are standardized to analyze the degree of influence of each effect on the carbon emission of the energy system. The calculation results prove that energy consumption intensity, population size, urbanization level and carbon emission of electricity promote the growth of carbon emission of energy system, while energy consumption intensity, rural population share and industrial structure play a suppressing role.