基于STIRPAT模型的江苏省能源消费碳排放影响因素分析及趋势预测

定量分析碳排放的影响因素,对降低区域碳排放具有重要的指导意义。利用STIRPAT模型,定量分析江苏省能源消费碳排放量与人口、富裕度（以人均GDP表示）、技术进步（以能源强度表示）和城镇化水平之间的关系,通过岭回归拟合后发现,人口数量、人均GDP、能源强度、城市化水平每变化1%,江苏省能源消费碳排放量将分别发生3.467%、(0.242+0.024 lnA)%、0.313%和0.151%的变化。在以上研究的基础上,设置8种不同的发展情景,分析了江苏省未来能源消费碳排放量的发展趋势。结果表明,当人口、经济保持低速增长,并保持高技术增长率时,有利于控制江苏省的能源消费碳排放量,2020年江苏省的能源消费碳排放量预测值为202.81 MtC。

Trend prediction and analysis of influencing factors of carbon emissions from energy consumption in Jiangsu province based on STIRPAT model

Quantitative analysis of influencing factors of carbon emissions has an important guiding effect on reducing regional carbon emissions. This article, based on STIRPAT model, made an analysis of several factors influencing carbon emissions from energy consumption in Jiangsu province, respectively population, affluence (in form of per capita GDP), techonology (in form of energy intensity) and urbanization. The results of Ridge regression showed that for 1% change in population, per capita GDP, energy intensity and the level of urbanization, there was 3.467%, \begin{array}{c}(0.242+0.024\mathit{lnA})\end{array}%, 0.313%, and 0.151% change in energy carbon emissions in Jiangsu, respectively. Based on this study, the paper set eight scenarios to furthur analyze and predict the future trend of carbon emission in Jiangsu. It is found that low growth rate of population, low growth rate of per capita GDP and high technology progress rate would help to control carbon emissions, and the carbon emissions in 2020 would be 202.81 MtC in that case. To control Jiangsu's future carbon emissions, it is essential to not only improve the technology progress rate and control the population quantity, but also to reduce the growth rate of per capita GDP, which indicates the government should slow down economic development and transform the economic growth mode to New Normal.