Quantifying historical releases of radium-226 from Canadian mining operations to freshwaters
Bibliographic record
Abstract
A common misconception is that radium-226 (Ra-226) is released into receiving waters exclusively by uranium mines and mills. In fact, Ra-226 is routinely analyzed in mining effluent across various sectors. Using data reported under the Canadian Metal and Diamond Mining Effluent Regulations , Ra-226 releases from mine effluent were evaluated for the period of 2014–2022. Final treated effluent concentrations ranged from 0.2 to 7800 mBq/L. Data were grouped by mining sector as being either precious metals, base metals, ferrous metal, non-ferrous metals, uranium ore, or diamonds. Mean Ra-226 concentrations were highest for non-ferrous metal mines (51.9 mBq/L), followed by base metal (31.6 mBq/L), diamond (23.8 mBq/L), uranium (22.0 mBq/L), precious metal (15.0 mBq/L), and ferrous metal mines (11.0 mBq/L). Mean concentrations for non-ferrous, base metal, diamond, and uranium mining sectors exceeded the upper tolerance limit (UTL) for natural background concentrations (21.7 mBq/L), calculated using reference data from Northern Saskatchewan. Median concentrations, however, were below the UTL for all sectors, indicating episodic high Ra-226 releases likely influenced by variations in the uranium content of the ore bodies. This study demonstrates that Ra-226 activity concentrations in final treated effluent from uranium mining operations are lower than those from other mining sectors, challenging the perception that uranium operations are the primary source of Ra-226 releases. • Demonstrated that mining operations from various sectors contribute Ra-226 to receiving environments. • Natural background activity levels for Ra-226 estimated to be around 21.7 mBq/L. • Each mining sector produced final treated effluent concentrations of Ra-226 that exceeded natural background levels.
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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 | 0.000 |
| 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".