Multivariate statistical interpretation of coastal sediment monitoring data

被引:12
作者
Simeonov, V [1 ]
Stanimirova, I [1 ]
Tsakovski, S [1 ]
机构
[1] Univ Sofia St Kl Okhridski, Fac Chem, Chair Analyt Chem, Sofia 1164, Bulgaria
来源
FRESENIUS JOURNAL OF ANALYTICAL CHEMISTRY | 2001年 / 370卷 / 06期
关键词
D O I
10.1007/s002160100863
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Multivariate statistical analysis of sediment data (input matrix 122 x 15) collected from 122 sampling sites from the western coastline of the USA and analyzed for 15 analytes indicates that the data structure could be explained by four latent factors. These factors are conditionally named "anthropogenic", "organic", "natural", and "hot spots". They explain over 85% of the total variance of the data system, which is an acceptable value for the PCA model. The receptor models obtained after regression of the mass on the absolute principal components scores ensures reliable estimation of the contribution of each possible natural or anthropogenic source to the mass of each chemical component. It can be concluded that the region of interest reveals a different pattern of pollution compared with the eastern coastline treated statistically in a previous study.
引用
收藏
页码:719 / 722
页数:4
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