Pilot Test of the Permeable Reactive Barrier for Removing Uranium from the Flooded Gunnar Pit
Bibliographic record
Abstract
This work reports on applying iron oxide coated sand (IOCS) media in an experimental permeable reactive barrier to remove uranium (U) species from uranium containing water. A field study was conducted at the legacy Gunnar uranium mine & mill site that was abandoned in the 1960s with limited to no decommissioning. The flooded Gunnar mine pit presently contains about 3.2 million m3 of water contaminated by dissolved U (1.2 mg/L), Ra-226 (0.4 Bq/L), and minor concentrations of other contaminants (As, Se, etc.). The water is seeping over the pit rim into Lake Athabasca, posing potential environmental and health concerns. IOCS media can be used to immobilize uranium species through an adsorption process. Herein, the preparation of hydrous ferric oxide sorbents and their supported forms onto silica sands is described. Fourier transform infrared spectroscopy (FTIR) and powder X-ray diffraction (pXRD) were used for structural characterization. The adsorption properties of the IOCS sorbent media were modeled by the Langmuir adsorption isotherm, where a maximum uranium uptake capacity was estimated. Bench-scale adsorption kinetic experiments were also performed before moving to a field trial. Based on these lab results and input on field-scale parameters, a pilot permeable reactive barrier was fabricated and a field test conducted near the Gunnar pit in June 2019. This pilot test provided technical data and information needed for designing a full-scale permeable barrier that employs the IOCS media. This approach can be applied for in-situ water treatment at Gunnar and other legacy uranium sites.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 source (direct Gemma or distilled Codex), 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".