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High resolution LA-ICP-MS mapping for the determination of partition coefficients using the example of natural barite

In deep geological repository systems, containers for highly radioactive waste may encounter groundwater, which ultimately leads to the release of radionuclides. For the exploration of new atomic waste repositories, the retention of these radionuclides in hydrothermally grown barite and calcite has drawn much attention recently. Here, partition coefficients are important parameters as they are helpful to evaluate the immobilization potential. To derive meaningful partition coefficients, only parts of the crystals in equilibrium with their host fluid should be considered. Differences in partition coefficients between synthetic and natural calcite have been observed and might at least partially stem from such analytical complications. This study presents a method which combines both, the advantages of visualizing growth structures at the µm scale and element sensitivity down to the ppm level via LA-ICP-MS. Objects of investigation are natural barites from a borehole in the Äspö Hard Rock Laboratory, Sweden, that have been sampled together with their host fluid. High-resolution mappings with a spot size of 2 µm allow us to define discrete growth zones and calculate equilibrium partition coefficients based on pixel clusters that represent the latest crystallization events. Additional LA-ICP-MS spot analyses substantiate the lower error values of our method and provide partition coefficients for twelve elements. La and Sr are assumed to behave like radionuclides, due to similar chemical properties. Preliminary barite partition coefficients for La and Sr are 3-4 orders of magnitude below calcite values of the same sampling location, indicating a much lower immobilization potential of barite compared to calcite.


Ferdinand Kirchner1, Martin Kutzschbach1, Thomas Neumann1, Henrik Drake2
1Department of Applied Geochemistry, Technische Universität Berlin, 10589 Berlin, Germany; 2Department of Biology and Environmental Science, Linnaeus University, 39231 Kalmar, Sweden
GeoMinKöln 2022