Mercury Distribution and Deposition in Glacier Snow over Western China
Bibliographic record
Abstract
Western China is home to the largest aggregate of glaciers outside the polar regions, yet little is known about how the glaciers in this area affect the transport and cycling of mercury (Hg) regionally and globally. From 2005 to 2010, extensive glacier snow sampling campaigns were carried out in 14 snowpits from 9 glaciers over western China, and the vertical distribution profiles of Hg were obtained. The Total Hg (THg) concentrations in the glacier snow ranged from <1 to 43.6 ng L(-1), and exhibited clear seasonal variations with lower values in summer than in winter. Spatially, higher THg concentrations were typically observed in glacier snows from the northern region where atmospheric particulate loading is comparably high. Glacier snowpit Hg was largely dependent on particulate matters and was associated with particulate Hg, which is less prone to postdepositional changes, thus providing a valuable record of atmospheric Hg deposition. Estimated atmospheric Hg depositional fluxes ranged from 0.74 to 7.89 μg m(-2) yr(-1), agreeing very well with the global natural values, but are one to two orders of magnitude lower than that of the neighboring East Asia. Elevated Hg concentrations were observed in refrozen ice layers in several snowpits subjected to intense melt, indicating that Hg can be potentially released to meltwater.
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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 | 0.000 | 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) | 0.000 | 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 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".