摘要
利用空间变差函数和探索性空间数据分析(ESDA)方法分析了中国省域人均碳排放的空间异质性和空间自相关性,综合考虑碳排放的各影响因素,利用地理加权回归模型分析了影响碳排放的主要因素。结果表明:①中匡l省域人均碳排放存在显著的空间异质性和空间自相关性,在空间上表现出明显的集聚特征,形成了典型的中心一外围结构,中心区主要分布于内蒙古、吉林、辽宁、河北、山西和宁夏等地。②各因素对人均碳排放的影响具有显著的空间异质性,表现为同一因素对人均碳排放的影响,在不同省域存在明显差异。③影响中国省域人均碳排放的重要因素是碳排放强度、人均GDP(2010年不变价)和人均全社会固定资产投资。最后,提出了减少碳排放的对策。
In the severe situation of global warming, the research of carbon influence factor has become research hotspot. Spatial variation function and Exploratory Spatial Data Analysis (ESDA) were employed to analyze the spatial heterogeneity and spatial autocorrelation of China' s per capita carbon emissions in the province level, comprehensive consideration of various carbon influencing factors, Geographical Weighted Regression (GWR) was employed to analyses the main influencing factors of carbon emission. The results were shown as the follows: 1)There was significant spatial heterogeneity and spatial autocorrelation of China' s per capita carbon emissions in the province level, which showed significant agglomeration characteristics and formed a typical center-periphery structure in space, the center areas mainly distributed in Inner Mongolia, Jilin, Liaoning, Hebei, Shanxi and Ningxia; 2)It has significant spatial heterogeneity in various factors impacting on per capita carbon emissions, which showed that the same influence factors had an obvious regional difference between different provinces; 3)The important factors influencing the per capita carbon emissions are carbon emission intensity, per capita GDP (2010 constant prices) and per capita total social investment in fixed assets. Finally, some countermeasures were proposed for reducing carbon emissions.
出处
《经济地理》
CSSCI
北大核心
2015年第11期21-28,共8页
Economic Geography
基金
中国清洁发展机制基金赠款项目(1214073
2012065)
关键词
碳排放
空间异质性
空间自相关性
地理加权回归模型
中国
carbon emissions
spatial heterogeneity
spatial autocorrelation
Geographically Weighted Regression Model
China