ALBERT

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: German Federation of Industrial Research Associations http://dx.doi.org/10.13039/501100002723

Description: Federal Ministry for Economic Affairs and Energy http://dx.doi.org/10.13039/501100006360

Description: In order to advance ongoing efforts in the (still emerging) field of marine restoration, different forms of knowledge must be combined: not only the biological and technical aspects, but also the social and cultural dimensions of marine restoration efforts. This calls for a newly combined array of methods that allows for a bridging of these different knowledge dimensions. Drawing on our experiences from the ongoing knowledge transfer processes of the INTERNAS project (Scientific Transfer of the results of INTERNational Assessments in the field of Earth and Environmental Research into the German policy context), we provide an overview of methods that were used to link global recommendations with localized marine restoration schemes and policy options. Using a mixed methods approach, we were able to capture and understand the pathways of knowledge transfer from globally synthesized scientific knowledge to local realities related to protecting and enhancing marine biodiversity in Germany. With this structured knowledge transfer approach, actionable solutions for marine conservation and restoration activities could be tailored to the specific national and regional circumstances. Using participatory methods, framework conditions like ecological, social, legal, and sectoral value judgment dimensions can be identified. This allows for the development of concerted solutions and creates a common ground for good governance towards marine restoration. When scientists engage not only as experts but also as reflexive facilitators in such participatory processes, it is ensured that more inclusive forms of knowledge are fostered that are necessary to better anticipate the potentials and likely pitfalls that marine restoration efforts may encounter. We conclude that existing knowledge on ecosystems, their goods and services as well as societal expectations need to be understood from the onset in any kind of marine restoration effort.

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.