1999～2007年中国能源消费碳排放强度空间演变特征

采用Theil指数和空间自相关分析方法,研究1999～2007年国家、区域和省际层面能源碳排放强度特征、区域差异水平和空间格局演变.结果表明,①1999～2007年,全国能源碳排放总量从0.91 Gt逐年上升至1.83 Gt,碳排放强度从0.83t.万元-1震荡下降至0.79 t.万元-1;②八大经济区域碳排放强度呈现...

Spatial Pattern Evolution of Carbon Emission Intensity from Energy Consumption in China

Using Theil index and spatial autocorrelation analysis methods, the characteristics, regional disparity and spatial pattern evolution of carbon emission intensity from energy consumption were analyzed on national, regional and provincial level from 1999 to 2007 in China. The results indicate that: (1) total energy carbon emission in China has increased from 0.91Gt in 1999 to 1.83Gt in 2007, while carbon emission intensity has decreased from 0.83 t x (10(4) yuan) (-1) to 0.79 t x (10(4) yuan) (-1); (2) carbon emission intensity of eight major economic blocks showed the trend of three-level differentiation, with that of northeast regions, the middle reaches of Yellow River regions and northwest regions above 1.0 t x (10(4) yuan)(-1); northern coastal regions, the middle reaches of Yangtze River regions and southwest regions 0.7-1.0 t x (10(4) yuan) (-1); eastern and northern regions 0.32-0.51 t x (10(4) yuan) (-1); (3) Theil index analysis indicates that the within-region carbon emission intensities were similar, and the expanding total disparity of carbon emission intensity was primarily due to between-region inequalities. (4) spatial autocorrelation analysis shows that Global Moran's I has increased from 0.19 to 0.25, indicating that there were positive spatial correlations among provincial regions in China, and regions of similar carbon emission intensity agglomerated in space. The "cold spot" areas of carbon emission intensity were relatively stable, while the "hot spot" areas has gradually shifted from northwest regions to the middle reaches of Yellow River regions and northeast regions. (5) spatial disparity of carbon emission intensity is closely related to factors such as regional resources endowment, economic development, industrial structure and energy utilization efficiency. The study of regional disparity and spatial autocorrelation provides insight into spatial heterogeneity and spatial pattern evolution of carbon emission intensity in China, and also provides references for the development of differential regional objectives of carbon emission reduction and related regulation policies.