Are melting alpine glaciers a source of legacy priority contaminants to downstream environments? A high-frequency analysis of water chemistry in the Canadian Rockies.
Bibliographic record
Abstract
Glaciers are retreating across the Canadian Cordillera. As this ice melts trace elements and other contaminants, accumulated from millennia of atmospheric deposition, are subject to release with uncertain consequences for downstream water quality. It is therefore imperative to constrain the rate and magnitude of contaminant input to river systems from glacierized watersheds. Meltwater chemistry was monitored and modelled at a high temporal frequency using a combination of grab-sampling and sondes for physical, chemical, and hydrological parameters at the outlet of proglacial Sunwapta Lake, Athabasca Glacier, Canada. Principal component analysis revealed that chemical parameters could be split into two groups with distinct seasonal trends. Group A encompasses solutes and endogenic bedrock weathering associated elements. Group B includes particulate, and exogenic dust-associated elements. Group A element concentrations were highest during low flow conditions and were correlated positively with conductivity. Group B element concentrations were highest during high flow conditions and had a moderate positive correlation with turbidity. Concentrations of potentially hazardous trace elements remained below Canadian Environmental Quality Guidelines throughout the hydrological season (THg < 2.7 ng/L; TPb < 1.7 µg/L; TAs < 0.34 µg/L; TCr < 1.9 µg/L). Trace element fluxes (kg/year) and yields (kg/year/watershed area) were modelled at a high temporal-resolution by pairing grab sampling results with corresponding strongly correlated high-frequency physical parameters: conductivity or turbidity. Annual fluxes and yields were comparable or lower than fluxes and yields from other glacial meltwater streams globally. Annual fluxes and yields were THg: 95 kg/yr and 3.2 g/yr/km2; TPb: 34 kg/yr and 1.2 kg/yr/km2; TCr 39.5 kg/yr and 1.4 kg/yr/km2; TAs: 7.3 kg/yr and 0.25 kg/yr/km2. Numerous studies have suggested that glaciers are a significant source of high concentrations, fluxes, and yields of contaminants, including: pesticides; PAHs; PCBs; and toxic trace elements. In contrast, we found low concentrations, fluxes, and yields of trace elements in meltwater from the rapidly retreating Athabasca Glacier. Grab-sampling complemented by high-frequency monitoring of physical and chemical water parameters allowed a high-resolution view of water chemistry variation in meltwater from the Athabasca Glacier.
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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 | 0.000 |
| 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".