Fractal modeling of multivariate principal component of contaminating toxic elements in Irankooh Pb-Zn mining area

Abstract

The primary purpose of this investigation is contamination mapping in surrounding areas of Irankuh Pb–Zn mine, located in central Iran, using an integrated approach of principal component analysis (PCA) with the Concentration-Area (C-A) and Power Spectrum-Area (S-A) fractal models. PCA categorized the 45 elements into eight principal components. Component 2, containing the toxic elements of Pb, Zn, As, Mn, Cd, and Ba, was identified as contamination factor. This multivariate contamination factor was modeled using the C-A and S-A fractal methods (in spatial and frequency domains) to delineate pollution areas. Modeling of PCA data using the C-A fractal method showed four main populations for contamination factors. Two populations with higher fractal dimensions are associated with contamination from mining activities or anthropogenic effects. Low fractal dimensions are considered the background population which has not been affected or is less affected by these activities. Five geochemical populations were obtained for contamination factors using the S-A fractal modeling of PCA in the frequency domain. Therefore, various geochemical populations were achieved using geochemical filtering and two-dimensional inverse Fourier transformation. The geochemical populations related to classes 2, 3, and 4 containing intermediate frequency signals showed the pollution anomaly. The spatial distribution of pollutant geochemical signals exhibits excellent conformity with the mining operation limit and tailing dam location as pollutant sources. The results indicate that the elements of Pb, Zn, Cd, and As have significant values in the surrounding soils rather than their concentrations in the earth’s crust. The results demonstrate that the S-A fractal models can more precisely delineate the environmental anomaly than the C-A fractal model, especially in intermediate frequency populations.