Assessment of seasonal and polluting effects on the quality of river water by exploratory data analysis

被引:997
|
作者
Vega, M [1 ]
Pardo, R [1 ]
Barrado, E [1 ]
Debán, L [1 ]
机构
[1] Univ Valladolid, Fac Ciencias, Dept Quim Analit, E-47005 Valladolid, Spain
关键词
water quality; surface water; hydrochemistry; exploratory data analysis; ANOVA; box plot; principal component analysis; pattern recognition; cluster analysis;
D O I
10.1016/S0043-1354(98)00138-9
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
22 Physico-chemical variables have been analyzed in water samples collected every three months for two and a half years from three sampling stations located along a section of 25 km of a river affected by man-made and seasonal influences. Exploratory analysis of experimental data have been carried out by box plots, ANOVA, display methods (principal component analysis) and unsupervised pattern recognition (cluster analysis) in an attempt to discriminate sources of variation of water quality. PCA has allowed the identification of a reduced number of "latent" factors with a hydrochemical meaning: mineral contents, man-made pollution and water temperature. Spatial (pollution from anthropogenic origin) and temporal (seasonal and climatic) sources of variation affecting quality and hydrochemistry of river water have been differentiated and assigned to polluting sources. An ANOVA of the rotated principal components has demonstrated that (i) mineral contents are seasonal and climate dependent, thus pointing to a natural origin for this polluting form and (ii) pollution by organic matter and nutrients originates from anthropogenic sources, mainly as municipal wastewater. The application of PCA and cluster analysis has achieved a meaningful classification of river water samples based on seasonal and spatial criteria. (C) 1998 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:3581 / 3592
页数:12
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