Quantifying historical releases and pre-operation levels of metals and radionuclides
Bibliographic record
Abstract
Assessing the recovery of aquatic ecosystems from metal and radionuclide contamination requires knowledge of the concentration of radionuclides and metals before anthropogenic releases. Pre-operational conditions, or baseline, are often unknown for many mining operations initiated decades ago. The objectives of this study were to quantify baseline levels of metals and radionuclides and describe historical releases of an industrialised watershed in Northern Ontario where mining operations were carried out from 1955 to 1996. For this purpose, water and surface sediment samples were collected from this watershed and in an adjacent non-industrialised watershed every 2 km. Using metal and radionuclide concentrations in the non-impacted watershed, we calculated water and sediment baseline concentrations as upper 95th percentile values. Baseline pH, 226Ra and uranium in water of lakes and rivers were similar at pH of 6.8, 10 mBq·l−1, and 2.5 μg·l−1, respectively. For sediments, baseline lake sediment exhibited concentrations of radionuclides that were higher than river sediments. We calculated baseline concentrations in lake sediment at 2,115 Bq·kg−1 210Pb, 535 Bq·kg−1 210Po, 218 Bq·kg−1 226Ra, 235 Bq· kg−1 228Th, 184 Bq·kg−1 230Th, and 223 Bq·kg−1 232Th. Baseline concentrations of metal levels in lakes were at 98 mg kg−1 Ni, 119 mg kg−1 Cu, 2300 mg kg−1 Zn, 112 mg kg−1 Pb and 19 mg kg−1 U. In Lake Huron, we collected two sediment core profiles along with surface sediment to estimate baseline radionuclide activities and metal concentrations and quantify historical releases from the industrialised watershed. The sediment core profiles reflected baseline conditions prior to releases from the uranium mining operation and contamination from its onset in 1955 to its closure in 1996. Concentration of metals in pre-industrial sediment layers were lower than in surface sediment of Lake Huron, suggesting atmospheric depositions. Our study indicates that collecting surface sediment in this non-impacted watershed may yield baseline concentrations for uranium and radionuclides. For metal, collecting surface sediment may yield ambient metal concentrations because of long-range atmospheric transport from remote sources. By comparison, sedimentary profiles can provide baseline concentrations of both metals and radionuclides. In the case of the Serpent River watershed, we report that water quality has recovered downstream of Quirke Lake as of 1993 and that additional sediment cores would better assess sediment recovery.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".