我国农村居民生活能源碳排放的时空特征分析

随着生活质量的提高,我国农村居民生活能源消费呈现大幅增长的趋势,成为碳排放增长的新源泉。估算了我国30个省区2001—2013年的农村居民生活能源碳排放,采用碳基尼系数、Arc GIS技术分析了中国省级尺度农村居民生活能源碳排放的时空特征,并利用STIRPAT模型辨明了农村居民生活能源碳排放的主要影响因素。结果表明:(1)2001—2013年农村居民直接生活能源碳排放量和间接生活能源碳排放量分别增长了7.65%、9.16%。(2)东部、中部、西部地区的碳基尼系数呈下降趋势,说明各区域农村居民人均生活能源碳排放量的区域差异总体均呈缩小趋势。(3)2001—2013年间,处于我国农村居民人均直接生活能源碳排放高水平地区的空间格局分布相对较为稳定,而对于人均间接生活能源碳排放来说,处于低水平地区的空间格局分布较为稳定。(4)农村人口规模、农民人均纯收入、农村居民生活消费支出、青壮年人口比重对农村居民生活能源碳排放量具有促进作用,而农村居民能源消费结构对其具有减缓作用,且北方农村居民生活能源碳排放量明显高于南方。(5)从环境Kuznets曲线假说出发,经济发展是促使我国农村居民生活能源碳排放Kuznets曲线存在拐点的重要因素。

Analysis of spatio-temporal patterns of carbon emission from energy consumption by rural residents in China

With the development of economy and improvement in the living standard of people, life energy consumption has been increasing with each passing year. The life energy consumption of residents is expected to become a new growth point for carbon emissions. Using GiNi index, a method for spatial autocorrelation analysis, the characteristics, regional disparity, and spatio-temporal pattern of carbon emissions from life energy consumption were analyzed on regional and provincial levels from 2001 to 2013, in China. We used the STIRPAT model to simulate the impact of factors such as population, affluence level, age structure of population, and the proportion of use of electric energy, on carbon emissions. We observed that for the life of rural residents, the direct and indirect energy carbon emissions increased by 7.65% and 9.16%, respectively. The GiNi index analysis indicated that the difference in carbon emissions was shrinking among the three zones of eastern, central, and western regions. The distribution of rural residents'' life energy per capita carbon emissions in provincial China was not completely random. The areas with low levels of direct carbon emissions were mainly distributed in the eastern and western regions, whereas areas with the high levels of direct carbon emissions were relatively stable, and were mainly distributed in Sichuan, Hebei, and Anhui. Population, affluence level, and age structure of population were the main driving factors for the carbon emissions from the life energy consumption of residents, and the change in the rate of carbon emissions from residents'' life energy caused by them exceeded that of themselves. Moreover, the rural residents'' life energy carbon emissions were higher in the north than that in the south. However, the areas with low levels of indirect carbon emissions were relatively stable with respect to their carbon emissions. Within the range of calculated data, the results of the present analysis support the Environmental Kuznets Curve hypothesis, and the economic development has been the important factor for prompting the turning point of the Environmental Kuznets Curve hypothesis.