Geogenic arsenic (As) contamination poses a major environmental concern, yet mapping its Natural Background Levels (NBLs) remains challenging in data-scarce, human-impacted regions within heterogeneous sedimentary aquifers. NBLs are essential for distinguishing natural from anthropogenic contributions and for establishing threshold values in environmental policy and groundwater management. This study applies a Random Forest (RF) algorithm to predict arsenic NBL exceedance of the WHO guideline (10 μg/L) in shallow groundwater of the Ferrara province (Po Plain, Italy). Three model configurations were tested using: (i) in-situ hydrochemical variables (hydrochemical model), (ii) spatially continuous variables (geospatial model), and (iii) a combination of both (mixed model). The mixed model achieved the highest performance (AUC = 0.88), followed by the hydrochemical model (AUC = 0.86). The geospatial model performed slightly lower (AUC = 0.83) but enabled the generation of a continuous 50 m-resolution probability map, identifying 17% of the area as potentially exceeding 10 μg/L. Iron, redox potential and dissolved oxygen were the dominant hydrochemical predictors, while organic carbon, clay content, and surficial geology were the dominant spatial variables, reflecting geochemical and sedimentary controls on As mobilization through reductive dissolution processes. Elevated exceedance probabilities are identified in the northeastern sector, proximal to the Po River Delta, and in peat-rich central areas. This study demonstrates that spatially continuous variables can effectively complement hydrochemical data for continuous NBL mapping, capturing meso-scale heterogeneity that single, groundwater body-scale values conventionally adopted in European NBL frameworks are unable to resolve, thus offering a useful tool for contamination assessment and groundwater management.
In situ recovery (ISR) is a worldwide mining technique which accounts for more than 52% (in 2024) of global U production, thanks to its cost-effectiveness. However, where an ISR process uses sulfuric acid (H2SO4), local underground exploited aquifers' water quality can be affected by low pH and high concentrations of SO4. Hydrogeochemical processes controlling this groundwater changes are studied here in the context of the planned exploitation of the Zoovch Ovoo deposit in Mongolia, using a multi-scale approach comparing real data with models. At the laboratory scale, experimental data combined with a 1D reactive transport model (RTM) demonstrate that ion-exchange reactions on clay minerals surface are the main geochemical mechanism governing groundwater chemistry (pH and major ions). To consider system heterogeneity and the spatial impact of the ISR process, field data from two pilot cells were combined with a 3D reactive transport model. The model successfully reproduced the field data by considering both ion-exchange and dissolution-precipitation reactions of the mineral phases, especially calcite and gypsum, necessary to explain the water chemistry at larger scale. Vertical and lateral fluid excursions out of the pilot cells were observed depending on the system heterogeneity. This study demonstrated that the relative importance of the various processes investigated depends on the time and distance scales probed. For the short term and U production, heterogeneities and ion-exchange are crucial for explaining the changes in groundwater chemistry. A better understanding and quantification of these processes will help operators optimize production and long-term environmental remediation strategies.
Herbicide contamination in aquatic systems is commonly assessed through changes in water concentrations, potentially overlooking redistribution among environmental compartments and metabolite formation. Here, we investigated the environmental fate of diuron in aquatic microcosms with and without Pistia stratiotes, integrating diuron partitioning among water, sediment, and plant tissues with DCPMU formation, bacterial abundance, and plant physiological responses under environmentally relevant and elevated exposure levels (2.5, 10.0, and 25.0 μg L−1). In non-vegetated systems, diuron rapidly partitioned into sediment, which represented the main reservoir and was associated with progressive DCPMU formation. In contrast, the presence of P. stratiotes substantially altered diuron partitioning, reducing sediment retention and increasing accumulation in plant tissues, particularly roots, while bacterial abundance increased in water and sediment. These findings indicate that macrophytes can modify contaminant distribution and create alternative compartments for diuron retention and associated transformation processes. Despite physiological stress, P. stratiotes maintained diuron accumulation with limited translocation to shoots. Overall, reductions in water concentrations did not necessarily indicate contaminant attenuation, as diuron was redistributed among sediment and plant compartments and remained associated with metabolite formation. These findings highlight the importance of considering contaminant partitioning, plant accumulation, and transformation processes when assessing herbicide fate and persistence in vegetated aquatic systems.
