Environmetric modeling and interpretation of river water monitoring data

被引:108
作者
Simeonov, V
Einax, JW
Stanimirova, I
Kraft, J
机构
[1] Univ Jena, Inst Inorgan & Analyt Chem, D-07743 Jena, Germany
[2] Univ Sofia St Kl Okhridski, Fac Chem, Dept Analyt Chem, Sofia 1164, Bulgaria
关键词
data analysis; river water data; cluster analysis; principal components analysis; source apportioning model;
D O I
10.1007/s00216-002-1559-5
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
This environmetric study deals with modeling and interpretation of river water monitoring data from the basin of the Saale river and its tributaries the Ilm and the Unstrut. For a period of one year of observation between September 1993 and August 1994 a data set from twelve campaigns at twenty-nine sampling sites from the Saale river and six campaigns from the river Ilm at seven sampling sites and from river Unstrut at ten sampling sites was collected. Twenty-seven chemical and physicochemical properties were measured to estimate the water quality. The application of cluster analysis, principal components analysis, and apportioning modeling on absolute principal components scores revealed important information about the ecological status of the region of interest: identification of two separate patterns of pollution (upper and lower stream of the rivers); identification of six latent factors responsible for the data structure with different content for the two identified pollution patterns; and determination of the contribution of each latent factor (source of emission) to the formation of the total concentration of the chemical burden of the river water. As a result more objective ecological policy and decision making is possible.
引用
收藏
页码:898 / 905
页数:8
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