Characterizing and Quantifying Controls on Arsenic Solubility over a pH Range of 1−11 in a Uranium Mill-Scale Experiment
Bibliographic record
Abstract
A mill-scale hydrometallurgical experiment (2700 m3 of effluent treated/day) was conducted for three months at the Rabbit Lake uranium mine site located in northern Saskatchewan, Canada, to determine the controls on the solubility of dissolved arsenic over a pH range of 1-11 and to develop a thermodynamic database for the dominant mineralogical controls on arsenic in the mill and the resulting mill tailings. The arsenic concentrations in the mill ranged from 526 mg/L at pH 1.0 (initial) to 1.34 mg/L at pH 10.8 (final discharge). Geochemical modeling of the chemistry data shows that arsenic solubility is controlled by the formation of scorodite (FeAsO4-2H2O) from pH 2.4 to pH 3.1, with 99.8% of dissolved arsenic precipitated as scorodite. Model results show that scorodite is unstable (releasing arsenic back in to solution) above pH 3.1 and arsenic adsorption to the surface of 2-line ferrihydrite is the dominant controlling factor in the solubility of arsenic from pH 3.2 to pH 11.0, with 99.8% of dissolved arsenic removed from solution via this mechanism. Finally, model results show -0.2% of the total dissolved arsenic adsorbs to the surface of amorphous aluminum hydroxide from pH 5.0 to pH 8.0. Minor alterations to the thermodynamic properties of arsenite and arsenate adsorption to 2-line ferrihydrite allowed the fit between measured mill-scale and modeled concentrations for the pH range of 3.2-11.0 to be optimized.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".