Photo‐induced Hg(II) reduction in snow from the remote and temperate Experimental Lakes Area (Ontario, Canada)
Bibliographic record
Abstract
This paper reports a net snow‐to‐air Hg transfer from the remote and temperate Experimental Lakes area (Ontario, Canada). More than 40% loss of total Hg concentration was observed in surface snow within 24 hours of its deposition on the ground. Stratigraphic profiles of total Hg in various snowpacks demonstrated a systematic decrease in total Hg concentration with snow depth pointing to snow‐to‐air Hg transfer and not snow‐to‐ground transfer. These results confirm observations made in a suburban area (Sainte‐Foy, Quebec, Canada) receiving higher atmospheric deposition of Hg perhaps differently associated chemically. The occurrence of this phenomenon is therefore extended geographically to include snow from pristine regions. It is hypothesized that the loss of Hg is caused by a sunlight‐initiated Hg(II) reduction in snow and subsequent gas transfer of Hg0 to the atmosphere. Polychromatic action spectra demonstrated that Hg(II) reduction in snow was mostly mediated by UV‐B irradiation and not visible, or UV‐A wavelengths. In addition to Hg(II) reduction in snow, we observed Hg0 oxidation in snow samples spiked with Cl−. Hg0 oxidation could limit the potential for Hg loss from snowpacks from coastal polar or subpolar regions (where snow often contains high chloride levels) by competing with Hg(II) reduction and slowing the snow‐to‐air Hg transfer. However, in regions under minimal marine influences, watershed budgets of Hg should consider the possibility of Hg loss from snow with time of deposition on the ground. Also, snow core studies should consider historic sunlight irradiation if extrapolation from snow cores is desired to estimate past ambient Hg levels.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 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".