ALBERT

Description: The main objectives of this study were to evaluate the Cu, Zn, Pb, Cr and Ni mobility using modified Tessier sequential extraction procedure and to study the functional group changes affected by each extraction step using FTIR analysis in the soil of a former sewage farm sedimentation basin. Tessier extraction revealed element dependent fractionation of studied metals: Pb was mostly discovered in the residual fraction (77%) followed by Cr (53%), Cu (8%), and Zn (5%), while Ni was not extracted in this fraction. The organic matter-bound was the dominant species of Cu (77%). Zn and Ni exhibited the highest affinity for Fe/Mn oxides fraction (55% and 39%, respectively). The average recovery rate was 62–111%, whereas the lowest rate was obtained for Ni (62%) and the highest for Cu/Pb (110–111%). Results indicated elevated concentrations of studied elements, with the following order of mobility factor: Ni 〉 Zn 〉 Cu 〉 Pbdouble bondCr. The preliminary interpretation of the sequential extraction FTIR spectral response revealed that DRIFT is applicable to interpret the sequential metal extraction and revealed three most profound changes correlated to the carbonate, Fe/Mn oxides, and OM fraction.

Description: Sewage disposal onto agricultural land may result in the high accumulation of organic wastes, which questions the applicability of typical elemental analysis used for the soil components. To monitor the contamination status of agricultural soils at a former sedimentation basin, after the long-term cessation of wastewater irrigation, 110 locations (15–20 cm depth) and 4 boreholes (up to 100 cm depth) were sampled to determine pH, loss on ignition, and concentration of Ni, Cu, Pb, Zn, and Cr. Additionally, the applicability of portable X-ray fluorescence (pXRF) for the soil samples highly influenced by the organic wastes was evaluated. The study revealed the presence of a relatively homogenous sewage waste layer (depth of 20 cm), characterized by slightly acidic to neutral pH (6.3–7.5), high organic matter (OM) accumulation (up to 49%), and elevated concentration (mg kg −1) ranges between: Pb (5–321), Cu (31–2828), Ni (10–193), Cr (14–966), and Zn (76–6639). The pXRF analysis revealed metal concentration increase in mineral samples (up to 50%). The regression models and correction factors demonstrated high correlation and significance of pXRF measurement with response to increasing OM content, with the lowest r 2 = 0.86 obtained for Ni. Correlation of pXRF and AES measurement illustrated element-dependent response for soils high in organics. Zn, Cu, and Cr pXRF analysis led to a slight underestimation in lower values, but overall good correlations (0.87; 0.89; and 0.88 respectively). Pb and Ni pXRF measurement revealed higher deviation from the reference in both lower and higher concentrations (0.74 and 0.70, respectively).

Description: Reflectance spectroscopy in the visible-infrared and shortwave infrared (450–2500 nm) wavelength region is a rapid, cost-effective and non-destructive method that can be used to monitor heavy metal (PTE, potential toxic elements) contaminated areas. Due to the PTE pollution that has accumulated in the course of wastewater treatment, the existence of Technosols presents an environmental problem, a potential source for PTE uptake by vegetation, or even the release of PTEs into groundwater. In this study, multivariate procedures using Partial Least Squares Regression (PLSR) and Random Forest Regression (RFR) are applied to quantify relationships between soil heavy metal concentration (Cr, Cu, Ni, Zn) and reflectance data of highly contaminated Technosols from a former sewage farm near Berlin, Germany. Laboratory measurements of 110 soil samples in four different preparation steps were acquired with HySpex hyperspectral cameras. The impact of the different preparation steps, namely “oven-dried”, “sieved”, “ground”, “LOI”, was evaluated for its potential to enhance the method performance or to reduce the time-consuming soil sample preparation. Furthermore, different spectral pre-processing methods were evaluated regarding improvements of spectral modelling performance and their ability to minimise noise and multiple scattering effects. Considering the optimal coefficient of determination (R2), PLSR shows an improving performance and accuracy with increasing preparation steps such as ground or LOI for all metals of interest (R2_Cr: 0.52–0.78; R2_Cu: 0.36–0.73; R2_Ni: 0.19–0.42 and R2_Zn: 0.41–0.74). RFR shows a weaker estimation performance for all metals, even when using higher sample preparation levels (R2_Cr: 0.36–0.62; R2_Cu: 0.17–0.72; R2_Ni: 0.20–0.35 and R2_Zn: 0.26–0.67). The results show that an application of methods such as PLSR for the prediction of PTE concentration in Technosols is still a challenge but provides more robust estimations than the user-friendly RFR method. Additionally, this study shows that PTE estimation performance in heterogeneous soil samples can be improved by increased laboratory soil preparation steps and further spectral pre-processing steps.