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《Earth and Environment》 2011-04
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The Application of Multivariate Statistical Analysis in the Pollution Source Recognition and Analysis of Heavy Metals in Soils

LIN Yan-ping1,2,ZHAO Yang1,HU Gong-ren1,2,SU Guang-ming1(1.Department of Environmental Science and Engineering,Huaqiao University,Xiamen 361021,China; 2.Key Laboratory of Urban Environment and Health,Chinese Academy of Sciences,Xiamen 361021,China)  
More and more attention has been paid to the pollution and control of heavy metals in soils.It is very important to find the contamination source before effective treatment.The applications of cluster analysis,principal component analysis and factor analysis in research on heavy metal source recognition in soils are summarized in this paper.On the basis of the lack and the existing problems involved in the past studies,the key points of studying heavy metal contamination source recognition and analysis in the future are set forth as follows;(1) combining the GIS technology and multivariate statistical analysis to generate thematic maps of pollution,one can better determine the source of pollutants;(2) using the enrichment factors(EFs),one can determine the source of a single metal,which verifies the results of multivariate statistical analysis;and(3) taking the advantages of some improved methods such as matrix-augmented principal component analysis(MAPCA) and positive matrix factorization(PMF),one can overcome some limitations caused by multivariate statistical analysis.
【Fund】: 国家自然科学基金项目(21077036);; 中国科学院城市环境与健康重点实验室开放基金项目(KLUEH201004)资助
【CateGory Index】: X53
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