湖南省能源消费碳排放驱动因素及趋势预测实证分析

EMPIRICAL ANALYSIS ON CARBON EMISSION DRIVING FACTORS AND TREND PREDICTION OF ENERGY CONSUMPTION IN HUNAN

基于灰色系统理论,建立STIRPAT多变量非线性模型定量研究了湖南省6个角度11个指标对能源消费碳排放的影响。将缓冲算子理论与灰色预测分析相结合,在构建灰色Verhulst模型的同时,采用幂平均弱化缓冲算子对能源消费碳排放量原始数据作优化修正处理并预测未来5年碳排放量。结果表明:产业结构对碳排放关联程度最高、能源结构因素边际贡献率最大,弹性系数为-0.2055,经过幂平均弱化缓冲算子处理的模型具有更高的预测精度。通过定性分析湖南省能源消费碳排放量变化特征,定量计算碳排放驱动因素的边际贡献度,结合其发展趋势和预测结果,可为湖南省节能减排政策的制定提供参考。

Based on the grey system theory, this paper established the STIRPAT multivariable nonlinear model, and quantitatively studied the impact of 6 indicators and 11 indicators on the carbon emissions of energy consumption in Hunan province. The buffer operator theory was combined with grey prediction analysis,when constructing grey Verhulst model simultaneously,the raw data of energy consumption was optimal corrected by the average power weakening buffer operator on carbon emissions and the carbon emissions was forecasted for the next five years. The results showed that the industrial structure on carbon emissions was highest,and correlation energy structure factor marginal contribution rate was largest. The elasticity coefficient was-0. 2055,and model had higher prediction accuracy by the average power weakening buffer operator processing. Through the qualitative analysis of variations characteristics of carbon emissions in Hunan province energy consumption,and quantitative calculation of driving factors of carbon emissions contribution degree,combined with the development trend and the prediction results,the results could provide a scientific basis for Hunan province to develop energysaving emission reduction policies.