中国碳排放强度影响因素对区域差异的作用分析

根据IPCC方法计算得到1995—2012年中国各省市碳排放数据,表明从1995年开始,我国各省市的碳排放强度整体上呈现南低北高,东低西高的分布格局,并有逐渐下降的趋势.区域间碳排放强度的基尼系数、Theil系数、对数离差均值的计算结果表明碳排放强度在各省市自治区间存在明显差异,并且差异随着时间逐渐增大.为了进一步分析碳排放强度差异的影响因素,我们建立了碳排放强度的回归方程,并采用夏普里值分解法进行影响因素的分解分析.整体上可以看出经济发展水平对碳排放强度差异的贡献值最大,而且随着时间推移其对碳排放强度差异的作用逐渐加强.其次是产业结构和能源结构,贡献值分别为18.91%和26.76%,对碳排放强度差异的贡献值随着时间逐渐减少,作用也逐渐弱化.最后是城市化水平(贡献值为~(-1).65%),仅在一定程度上能够降低碳排放强度的差异.进一步采用第三产业占比表示产业结构,石油占比表示能源结构进行分析,发现它们与碳排放强度变为反向关系.即一个地区的第三产业比重高,在能源结构中油的比重大,煤炭比重小,碳排放强度相比于其他地区则低.由此可见,石油比重的区域差异是影响碳强度差异的一个主要原因.因此,提升碳排放强度高的地区的石油以及低碳能源可以缩减区域间的碳排放差异.本文的研究对合理、公平的碳减排政策的制定,鼓励各省市自治区积极参加碳减排活动有着积极的意义.

Analysis of the determinants of carbon emission intensity on regional differences

Based on the method of IPCC, this paper calculated carbon emissions and emission intensity of 30 provinces of China. The results show that the provincial emission intensity decreased continuously since 1995, with a spatial pattern high in the north and west and low in the south and east. The result of Gini coefficient, Theil index and the mean logarithmic deviation of the carbon emission intensity revealed that there were great differences between provinces and these differences increased with time. In order to further analyze factors that affect carbon emission intensity, a regression equation of emission intensity was developed and the impact factors were decomposed by the Shapley method. Results showed that economic development contributed the most to the differences of carbon intensity, and its effect was gradually strengthened over time. Industrial and energy structure were other two main factors that affected carbon intensity, and their contribution to carbon intensity (18.91% and 26.76%, respectively) decreased over time. Urbanization level (contribution of -1.65%) could only slightly reduce the difference on carbon emission intensity. Furthermore, this study used the proportion of the tertiary industry represented industrial structure and the proportion of oil represented energy structure for further analysis. The result showed negative relationship between carbon intensity with these two factors. In other words, the higher proportion of the tertiary industry, the larger proportion of the oil in the energy structure and the smaller proportion of coal would lead to lower provincial carbon emission intensity. Therefore, the regional difference between the proportions of oil was one of the main reasons that affected carbon intensity difference. Increasing the proportion of oil in energy structure and using low carbon energy would significantly reduce regional carbon intensity differences. This study has great significance for constructing reasonable and fair carbon emission reduction policies and encouraging local government to actively participate in carbon emission reduction activities.