基于空间聚类分析的中国省域能源消费碳排放分布特征研究  

DISTRIBUTION CHARACTERISTICS OF CARBON EMISSION BY ENERGY CONSUMPTION IN CHINA AS JUDGED BY SPATIAL CLUSTERING ANALYSIS

作　　者：李丹丹[1,2] 刘锐[1,3] 陈动[1,4] 

机构地区：[1]北京师范大学地理学与遥感科学学院,北京100875 [2]北京城市学院信息学部,北京100083 [3]中科宇图资源环境科学研究院,北京100101 [4]南京林业大学土木工程学院,南京210037

出　　处：《北京师范大学学报（自然科学版）》2013年第5期529-533,共5页Journal of Beijing Normal University(Natural Science)

基　　金：北京师范大学海外人才引进基金资助

摘　　要：根据2007年的中国能源统计年鉴的数据,采用灰色关联度模型综合考虑影响碳排放的各种因素,选取了GDP、城市化率、第二产业比例、能源利用效率和碳排放强度5个影响碳排放的指标,利用基于空间邻接关系的空间聚类方法分析了中国31个省市、自治区的碳排放情况,运用主成分分析方法确定了聚类后的每个区域的碳排放指标的权重.研究结果表明:1)能源消费碳排放指标值相似的省份,其空间分布具有相邻的特点;2)中国能源消费碳排放总体上呈现出北部地区高于东部沿海地区,中西部地区最低的空间分布格局;3)聚类后的每个区域影响碳排放的主要驱动因素有所不同.上述分析为有效分区管理和合理制定节能减排政策提供了科学依据.Distribution of carbon emission in 31 Chinese provinces has been analyzed by spatial clustering method and grey correlation. This latter method used GDP features, ratio of second industry, urbanization rate, energy utilization rate and intensity of carbon emission and took adjacency relationship into account. Weight of each clustered region was determined by PCA （principal component analysis） method. It was found that provinces with similar carbon emissions had adjacent characteristics in geographical space regions. In northern China, carbon emission was higher than eastern areas, while the middle and the eastern areas had the lowest carbon erffission value. Primary driving factors for carbon emission are different for each clustered regions. These data will help to provide reasonable partition management and provide efficient carbon emission reduction.

关 键 词：能源消费的碳排放 空间聚类 区域差异 主成分分析 灰色关联度 

分 类 号：TK018[动力工程及工程热物理]