Étude de la mobilité du radium-226 en milieu naturel anthropisé par approches expérimentales et modélisation géochimique
Bibliographic record
Abstract
226Ra, a radioactive decay product of 238U and the most prevalent naturally occurring isotope of radium leads to many environmental issues in various industries due to its half-life of 1600 years: hydrothermal energy, seawater desalination and zircon production among others. The most impacted industries are the extractive ones: shale oil and gas production, coal, phosphate and uranium extraction. 226Ra remains in tailings from U mines and its mobility is controlled by retention mechanisms: sorption on mineral surfaces (iron oxy-hydroxydes, phyllosilicates, zeolites) and organic matter, or by the formation of solid solutions (sulfate minerals such as barite and carbonate minerals). The average concentration in lithospheric rocks being 32Bq / kg, or 1ppt, the identification of the retention mechanisms of this radionuclide at the scale of the material sampled in the field is made difficult because it is an ultra-trace element. Sequential extractions are commonly used to assess the retention of trace elements, but this technique is subject to experimental and analytical artefacts which are exacerbated in the case of an ultra-trace element. In this work, geochemical modeling of sequential extractions experiments has indeed shown that this technique leads to biased interpretations, particularly in the case of 226Ra which is remobilized during the different extraction steps. In order to have a better understanding of the retention of 226Ra and its distribution in heterogeneous and fine-grained materials, including mine tailings, a new approach has been developed. This approach combines alpha autoradiography, chemical elemental cartographies and mineralogical characterizations obtained on petrographic thin sections. A direct global analysis of the activity of the sample at the petrographic thin section scale is thus possible. This method was first qualified on model samples containing a single synthetic or natural mineral playing an important role in the retention of 226Ra in the natural environment. It was then tested on an assemblage of three of the main minerals responsible for the retention, namely: barite, clay minerals and iron oxy-hydroxydes. Finally, it was applied to U-mine tailings. A first set of samples comes from the French post-mining storage sites of Bellezane, where the tailings are stored under a solid cover, and from Bois Noirs Limouzat, which uses a liquid cover. A second set of tailings sample comes from the on-going ore processing facility of McClean Lake, Canada, which uses a tailings neutralization process by barite precipitation. The results show that barite is the main trap of 226Ra via the formation of a solid solution (Ba, Ra)SO4 in all these tailings from different sites. Over a few years, with or without neutralization by barite precipitation, it appears that this solid solution tends towards a recrystallization equilibrium which controls the concentration of 226Ra in solution. These results will subsequently be integrated into reactive transport type modeling to predict the long-term behavior of these tailings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".