Ernest Vončina,a Darinka Brodnjak Vončina,bNataša Mirkovič,a Marjana Novičc
a
Institute of Public Health Maribor, Institute of Environmental Protection,
Prvomajska 1, 2000 Maribor, Slovenia
b Faculty of Chemistry and Chemical Engineering, University of
Maribor, Smetanova 17, 2000 Maribor, Slovenia.
Tel: +386(2)2294432,
Fax: +386(2)2527774,
E-mail: darinka.brodnjak@uni-mb.si
c National Institute of Chemistry, Hajdrihova 19, 1000 Ljubljana,
Slovenia
Paper based on a
presentation at the 12th International Symposium on Separation
Sciences, Lipica, Slovenia,
September 27–29, 2006.
Abstract
The quality of ground water
as a source of drinking water in Slovenia is regularly monitored. One of the
monitoring programmes is performed on 5 wells for drinking water supply, 3
industrial wells and 2 ground water monitoring wells. Two hundred and fourteen
samples of ground waters were analysed in the time 2003–2004. Samples were
gathered from ten different sampling sites and physical chemical measurements
were performed. The following 13 physical chemical parameters were regularly
controlled: temperature, pH, conductivity, nitrate, AOX (adsorbable organic
halogens), metals such as chromium, pesticides (desethyl atrazine, atrazine and
2,6-dichlorobenzamide), highly-volatile halogenated hydrocarbons (trichlorometane,
1,1,2,2-tetrachloroethene and 1,1,2-trichloroethene). For handling the results
different chemometrics methods were employed, such as basic statistical methods
for the determination of mean and median values, standard deviations, minimal
and maximal values of measured parameters and their mutual correlation
coefficients, cluster analysis (CA), the principal component analysis (PCA), the
clustering method based on Kohonen neural network, and linear discriminant
analysis (LDA). The study gives the opportunity to follow the quality of ground
waters at different sampling sites within the defined time period. Monitoring of
general pollution of ground waters and following measuring can be used to search
the pollution source, to plan prevention measures and to protect from pollution,
as well.
Keywords: ground waters, water quality, chemometrics, principal component analysis, classification, Kohonen neural networks