Chemometric characterization of soil and plant pollution: Part 1: Multivariate data analysis and geostatistical determination of relationship and spatial structure of inorganic contaminants in soil.

Geostatistical and multivariate methods of data analysis are used to describe patterns of soil pollution with inorganic contaminants in Celje County, Slovenia. Groups of contaminants and polluted sites were identified using cluster analysis and confirmed with multidimensional variance and discriminant analysis. Factor analysis yields an identification of not directly observable relationships between the contaminants. The spatial structure and distribution of contaminants were assessed by applying semivariogram analysis and kriging interpolation method. Zinc, Cd and Cu were identified as a pollutant emitted from the zinc smelter, Pb also from other sources, and Cr and Ni mostly from geological parent material.

Determination of heavy metal concentrations in plants exposed to different degrees of pollution using ICP-AES.

Plant samples (Plantago lanceolata - narrow leaf plantain and Cichorium endiviae - endive) were collected in the surroundings of heavy metal emission sources and in other less contaminated areas. After digestion in a closed microwave system using HNO(3), the concentrations of Cd, Co, Cr, Cu, Fe, Mn, Mo, Ni, Pb, and Zn were determined using ICP-AES. Detection limits for all the elements of interest are given. Differences in heavy metal uptake rate between both plant species were observed. The uptake is more intensive for endive than for narrow leaf plantain. High concentrations of some heavy metals were determined in the unwashed plant samples as a result of exposure to aerosols. Tukey's statistical test was used to confirm the discrepancy of Cr concentration in plant samples from various areas. Washing the leaves with water was found to remove a large amount of water-soluble aerosols.