基于ESDA-GWR的1997—2012年中国省域能源消费碳排放时空演变特征

发布时间：2018-06-06 15:00

本文选题：能源消费碳排放 + ESDA　；参考：《环境科学学报》2015年06期

【摘要】：利用1997—2012年《中国能源统计年鉴》和《中国统计年鉴》相关数据,结合重心转移、ESDA及GWR等模型和方法,分析了近16年间中国省域能源消费碳排放量的空间相关性、异质性及影响因素,根据碳排放量划分标准将各省份划分为不同的碳排放区.结果表明:16年间碳排放量的重心向西迁移;我国省域碳排放量存在较为显著的空间正相关,自相关性在整体上表现出先增大后减小的趋势.2001年全局Moran's I指数达到最高值,为0.3012;能源消费碳排放量的冷热点格局表现出冷点扩张、热点被压缩的趋势;影响碳排放量的6个因素的影响程度由大到小依次为:总人口人均GDP煤炭消耗比重全社会固定资产投资第二产业比重人口老龄化率,只有人口老龄化率这一指标表现出负相关性;近16年我国省域碳排放量的空间格局发生了显著变化,2012年已有13个省份属于超重型碳排放区,表明我国要加强碳减排的力度.
[Abstract]:Based on the data of China Energy Statistics Yearbook and China Statistical Yearbook from 1997 to 2012, combined with the models and methods such as shift of gravity and GWR, the spatial correlation of carbon emissions from provincial energy consumption in China during the past 16 years is analyzed. According to the standard of carbon emission, each province is divided into different carbon emission areas. The results show that the center of gravity of carbon emissions moves westward in the past 16 years, and that there is a significant spatial positive correlation in China's provincial carbon emissions, and the autocorrelation shows a trend of first increasing and then decreasing as a whole. The global Moran's I index reached the highest value in 2001. The cold hot spot pattern of carbon emissions from energy consumption shows the trend of expansion of cold point and compression of hot spot. The influence degree of the six factors influencing carbon emissions is as follows: the per capita GDP coal consumption of the total population, the proportion of the whole society's fixed assets investment, the secondary industry proportion, the population aging rate, In recent 16 years, the spatial pattern of provincial carbon emissions in China has changed significantly. In 2012, 13 provinces belong to super heavy carbon emission zones, indicating that China should strengthen carbon emission reduction.
【作者单位】：西北师范大学地理与环境科学学院;
【基金】：国家自然科学基金(No.41361040) 西北师范大学青年教师科研能力提升计划项目(No.SKQNYB1202)~~
【分类号】：F426.2;X24

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