Multivariate statistical assessment of polluted soils

This study deals with the application of several multivariate statistical methods (cluster analysis, principal components analysis, multiple regression on absolute principal components scores) for assessment of soil pollution by heavy metals. The sampling was performed in a heavily polluted region and the chemometric analysis revealed four latent factors, which describe 84.5 % of the total variance of the system, responsible for the data structure. These factors, whose identity was proved also by cluster analysis, were conditionally named ore specific, metal industrial, cement industrial, and steel production factors. Further, the contribution of each identified factor to the total pollution of the soil by each metal pollutant in consideration was determined. (C) Central European Science Journals. All rights reserved.