基于PCA-聚类分析的终端二氧化碳排放量分布特征综合评价
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Comprehensive Evaluation on Distribution Characteristics of Terminal Carbon Dioxide Emission Based on PCAcluster Analysis
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    摘要:

    针对高能源需求带来环境与减排压力这一问题,提出了对于终端控制二氧化碳排放量的评价方法;利用省际二氧化碳核算法得出30个省份终端二氧化碳排放量,并采用PCA聚类分析法对终端二氧化碳排放分布特征进行分析。聚类分析在不知先验知识的情况下对指标变量进行分类,结合主成分分析综合得分进行人工判别分析,能更好地对终端二氧化碳的分布特征进行分析,两方法结合归纳总结了各省终端二氧化碳排放污染程度。研究结论表明:空气质量最差的省份是隶属华北地区的河北省,其次是整个华中地区以及华东、华南、华北地区的一些省份,空气质量最好的为西南、西北地区,加大对重大污染区域整改力度,对未来的能源结构调整和低碳环保具有一定借鉴意义和参考价值。

    Abstract:

    According to the problem in environment and emission reduction brought by high energy demand, an evaluation method for terminal control of carbon dioxide emission is proposed.By using interprovincial carbon dioxide calculation method to obtain the terminal carbon dioxide emissions in 30 provinces and by using PCAcluster analysis method, the distribution characteristics of terminal carbon dioxide emissions are analyzed. Cluster analysis analyzes the index variables without knowing the prior knowledge and combines principal component analysis and comprehensive scores for manual discriminant analysis, which can better analyze the distribution characteristics of terminal carbon dioxide. The terminal carbon dioxide pollution degree of each province is generalized and summarized. Research conclusions show that the province with the worst air quality is Hebei Province of North China, followed by entire Central China region and some provinces in East China, South China and North China, and the provinces with the best air quality are in southwest region and in northwest region. The intensification of the pollution treatment in polluted areas is of certain reference significance and reference value to energy structure adjustment and low carbon environment protection.

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吴凤华,胡澄, 江泽标,田娟.基于PCA-聚类分析的终端二氧化碳排放量分布特征综合评价[J].重庆工商大学学报(自然科学版),2020,37(4):111-117
WU Feng-hua, HU Cheng, JIANG Ze-biao, TIAN Juan. Comprehensive Evaluation on Distribution Characteristics of Terminal Carbon Dioxide Emission Based on PCAcluster Analysis[J]. Journal of Chongqing Technology and Business University(Natural Science Edition),2020,37(4):111-117

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  • 在线发布日期: 2020-07-14
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