Understanding the sorption of radium and lanthanides in soils and biochars for predictive modelling and remediation purposes
[eng] The exponential increase in the demand for certain metals across various technological sectors has intensified mining and industrial activities. A consequence of these processes is the unintentional enrichment of lanthanides (Ln) and naturally occurring radionuclides (NOR), such as radium (Ra)...
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| Tipo de recurso: | tesis doctoral |
| Estado: | Versión publicada |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universidad de Barcelona |
| Repositorio: | Dipòsit Digital de la UB |
| OAI Identifier: | oai:diposit.ub.edu:2445/223641 |
| Acceso en línea: | https://hdl.handle.net/2445/223641 http://hdl.handle.net/10803/695492 |
| Access Level: | acceso abierto |
| Palabra clave: | Radioquímica Eliminació de residus radioactius Radioactive waste disposa Metalls de terres rares Biocarbó Radiochemistry Radi (Metall) Radium Rare earth metals Biochar |
| Sumario: | [eng] The exponential increase in the demand for certain metals across various technological sectors has intensified mining and industrial activities. A consequence of these processes is the unintentional enrichment of lanthanides (Ln) and naturally occurring radionuclides (NOR), such as radium (Ra), in the resulting waste. The accumulation of these contaminants in aquatic and terrestrial environments, with soils acting as receptors of leachates, raises concerns about ecosystem integrity and human health. Therefore, environmental risk assessment studies are essential to evaluate potential exposure scenarios and risks. A key input parameter in risk assessment models is the solid-liquid distribution coefficient (Kd), which reflects a contaminant’s affinity to bind to soil and provides information on its mobility across environmental compartments. Understanding how Kd values vary with the physicochemical properties of the soil’s solid and liquid phases is fundamental for predicting contaminant behaviour. Both parametric and probabilistic modelling approaches are appropriate for deriving new Kd values. When contaminant concentrations and mobility into the food chain represent an unacceptable risk, remediation actions are recommended. In such cases, the use of sorbent materials, either as soil amendments or water filters, can be an effective strategy for immobilising or removing contaminants. For this reason, there is a growing need to conduct comprehensive studies evaluating the sorption capacity of candidate materials for removing target contaminants. Currently, knowledge regarding the interaction of Ra with soils remains scarce, and no unequivocal conclusions have been established concerning the physicochemical parameters of the soil’s solid and water phases that govern Ra sorption and desorption. The lack of understanding is mainly due to the absence of systematic studies addressing this issue, insufficient physicochemical characterisation of affected compartments, and the lack of a critically reviewed, up-to-date compilation of Kd values enabling consistent statistical analyses. As a result, the development of robust, validated models capable of reliably predicting Kd (Ra) values in soils, as well as the derivation of probabilistic functions describing Kd values distributions grouped according to physicochemical properties, or other relevant criteria, remains a significant challenge. Complementarily, one approach to help address the data gap is identifying chemical analogues from which equivalent interaction data may be derived. Additionally, no systematic studies have yet been performed to evaluate sorbent candidates such as biochars, a carbon-rich material that could offer a sustainable alternative to activated carbon for removing Ln from contaminated waters. In the present thesis, the factors influencing Ra sorption in soils have been identified through the acquisition of new sets of sorption and desorption Kd values across a collection of soils with contrasting properties. Several predictive models have been developed and validated, based on parametric equations that require only a few physicochemical parameters of the solid and liquid phases as input data, such as Kd (Ca + Mg), pH, amorphous Mn content in the soil, or specific surface area. Additionally, an alternative probabilistic approach has been applied, allowing for the estimation of the most probable Kd (Ra) values with minimal characterisation of the environmental matrices involved, requiring only the pH or its soluble Ca and Mg content. To support this approach, both experimentally obtained in the laboratory and critically reviewed literature data, together with available characterisation data, have been compiled to create a Kd (Ra) database with the highest number of entries collected to date. Furthermore, barium has been demonstrated to be a suitable, stable chemical analogue for deriving Ra sorption and desorption Kd data. Through the establishment of correction factors, this approach could help to fill existing data gaps without the need to use Ra radioisotopes, thereby avoiding the generation of radioactive wastes. A systematic study involving various untreated biochars and different experimental sorption approaches has demonstrated the suitability of these materials for remediating sites contaminated with Ln. The maximum sorption capacities and Kd values for Ln have been determined and evaluated under a range of contamination scenarios, from simpler cases, such as those containing only Sm, to more complex ones, involving multiple stressors, such as mixtures of Ln or simulated acid mine drainage containing Ln. The key physicochemical properties of biochar responsible for the effective removal of Ln in complex contamination contexts have been identified. In addition, the main mechanisms involved in the Ln sorption process have been elucidated through the integration of sorption studies with spectroscopic and imaging techniques. Finally, the sorption analogy between different elements of the Ln series has been demonstrated in environmentally relevant matrices, such as carbon-rich sorbent materials, clay minerals, and soils, thus helping to simplify the risk assessment in areas contaminated with Ln. |
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