Extreme levels of fallout radionuclides and other contaminants in glacial sediment (cryoconite) and implications for downstream aquatic ecosystems
Bibliographic record
Abstract
Abstract Glaciers in most parts of the world are retreating, releasing water and sediments to downstream rivers. Studies have found elevated levels of fallout radionuclides (FRNs) and other contaminants in glacial sediments, especially cryoconite, in European glaciers and Greenland. However, there are no equivalent studies for glaciers in North America. We report concentrations of FRNs (i.e. 137Cs, 210Pbun and 241Am) and other contaminants (i.e. metal(loids), phosphorus) in cryoconite and proglacial sediments from a glacier in British Columbia, Canada, and compare values to suspended sediments from the downstream river. The mean concentrations of 137Cs, 210Pbun and 241Am in cryoconite were 2,123 ± 74, 7,535 ± 224 and 11.5 ± 3.0 Bq kg−1, respectively, which are an order of magnitude greater than those for most soils and surficial materials. FRNs were much lower in suspended sediments and decreased with distance away from the glacier. Geochemical elements were enriched in cryoconite relative to local clastic materials and upper continental crust. Concentrations of FRNs in cryoconite were correlated with organic matter, which suggests this is important in controlling the scavenging of hydrophobic contaminants in glacial meltwater. Low concentrations of FRNs and contaminants in suspended sediments suggest that glacial meltwater and the delivery of cryoconite have limited impact on downstream aquatic ecosystems.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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 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".