灰色关联分析在中国农村家庭碳排放影响因素分析中的应用

Application of gray relational analysis method in the influencing factor analysis of China’s rural household carbon emissions

农村家庭碳排放影响因素分析的研究对于合理发展农村经济,有效制定农村减排政策具有重要的指导意义。根据IPCC参考方法、生活碳排放研究方法和投入产出基本方法,计算了1995—2010年中国大陆31省区农村人均家庭碳排放量。通过因子分析方法,剔除农村人均家庭碳排放量不显著相关的影响因素,利用灰色关联分析方法对影响农村人均家庭碳排放量的显著相关影响因素进行评价,得出不同驱动因子对碳排放的关联度。结果表明,(1)从时间上看,1995至2010年,农村家庭碳排放呈现出逐渐上升趋势,1995年农村的人均家庭排放量为C 0.170 t人-1,增加到2010年的0.504 t人-1,同比增长196.90%。(2)从空间看,东部地区的农村家庭碳排放远远高于中部、东北和西部地区的农村家庭碳排放。(3)从地区差异看,位于东部地区的上海市农村人均家庭碳排放远远高于位于西部地区的内蒙古,1995年上海市农村人均家庭碳排放为C 0.454 t人-1,而内蒙古为0.145 t人-1;2010年上海市农村人均家庭碳排放为C 1.351 t人-1,而内蒙古为0.498 t人-1。(4)利用灰色关联分析,经济水平指标中的农林牧渔总产值与农村人均家庭碳排放的关联度为最大,为0.982 4,因此对农村家庭碳排放的影响最大,而人口指标中的农村人口比例与农村人均家庭碳排放的关联度最小,为0.570 2,因此对农村家庭碳排放的影响最小。

This article analyzed the influence factor of rural household carbon emissions. It is of significance in the sustainable development of rural economy and the policy formulation of rural emission reduction. This paper calculated the rural per capita household carbon emissions of China＇s 31 provinces according to the IPCC reference approach, the household carbon emissions research approach, the input-output method. We eliminated the non-significant correlative factors by using the factor analysis method.We evaluated the significant correlation factors which influence the rural per capita household carbon emissions by using the grey relational analysis method, then we got a correlation which comes from driving factors on carbon emissions. The results show that： （1） In terms of time, the results showed that the per capita household carbon emissions in rural China have constantly increased from 0.170 tons in 1995 to 0.504 tons in 2010, it increased 196.90% year-on-year. （2） From space, the rural per capita household carbon emissions in the eastern region are far above in the central, northeast and western region. （3） From regional difference, the rural per capita household carbon emissions in Shanghai city which lies in the east of China are far above in Inner Mongolia which lies in the western China. In 1995, the per capita household carbon emission is 0.454 tons inShanghai, and is 0.145 tons in Inner Mongolia. In 2010, the per capita household carbon emission is 1.351 tons in Shanghai, and is 0.498 tons in Inner Mongolia. （4） With the grey related analytical method, this thesis showed that the degree of association between the rural per capita household carbon emissions and the value of farming, forestry, husbandry, fishing is largest, and showed that the degree of association between the rural per capita household carbon emissions and the rural population proportion is lowest. The msximum and mlnimum degree of association is 0.9824 and 0.5702 respectively.