The present study aimed to demonstrate that identification of the chemical forms of heavy metals in sewage sludge produced in municipal Wastewater Treatment Plants (WWTPs) is a critical element of ecological risk assessment, especially in terms of its agricultural or natural use. The concentrations of seven heavy metals (Cd, Cr, Cu, Ni, Pb, Zn and Hg) were determined using inductively coupled plasma optical spectrometry (ICP-OES) and cold vapor atomic absorption spectrometry (CV-AAS). The chemical forms of heavy metals were analyzed in accordance with the sequential extraction method proposed by the Community Bureau of Reference (BCR). Sludge samples were collected at the five municipal WWTPs located in the largest industrial area in the country, i.e., the Upper Silesian Industrial Region (southern Poland, central Europe). The ecological risk was assessed by calculating the Potential Ecological Risk Factor (ER), Risk Index (RI), Risk Assessment Code (RAC), Individual Contamination Factor (ICF), Global Risk Index (GRI) as well as the author's indices, i.e., Individual Ecological Risk (IER) and Global Ecological Risk (GER). To demonstrate the differences between the level of ecological risk posed by the different heavy metals, sludge samples were collected at two specific points of the processing line. Considering the chemical forms of heavy metals, the highest ecological risk was posed by Zn, Cd and Ni, while in the case of their total concentrations, by Cd and Hg. The obtained results confirm that quantitative determination of the total content of heavy metals in sewage sludge is not a sufficient criterion in assessment of the ecological risk that these elements pose to the natural environment and living organisms. Moreover, multivariate statistical analysis revealed a significant correlation between the concentrations of heavy metals, which indicates that they plausibly originate from the same source of pollution.
Keywords: chemical forms of heavy metals; ecological risk assessment; environmental pollution; heavy metals; multivariate statistical analysis; risk indices; sequential extraction; sewage sludge.