Atmospheric mercury over sea ice during the OASIS-2009 campaign
Bibliographic record
Abstract
Abstract. Measurements of gaseous elemental mercury (GEM), reactive gaseous mercury (RGM) and particulate mercury (PHg) were collected on the Beaufort Sea ice near Barrow, Alaska, in March 2009 as part of the Ocean-Atmosphere-Sea Ice-Snowpack (OASIS) and OASIS-Canada International Polar Year programmes. These results represent the first atmospheric mercury speciation measurements collected on the sea ice. Concentrations of PHg averaged 393.5 pg m−3 (range 47.1–900.1 pg m−3) and RGM concentrations averaged 30.1 pg m−3 (range 3.5–105.4 pg m−3) during the two-week-long study. The mean concentration of GEM during the study was 0.59 ng m−3 (range 0.01–1.51 ng m−3) and was depleted compared to annual Arctic ambient boundary layer concentrations. It is shown that when ozone (O3) and bromine oxide (BrO) chemistry were active there is a positive linear relationship between GEM and O3, a negative one between PHg and O3, a positive correlation between RGM and BrO, and none between RGM and O3. For the first time, GEM was measured simultaneously over the tundra and the sea ice. The results show a significant difference in the magnitude of the emission of GEM from the two locations, with significantly higher emission over the tundra. Elevated chloride levels in snow over sea ice are proposed to be the cause of lower GEM emissions over the sea ice because chloride has been shown to suppress photoreduction processes of RGM to GEM in snow. Since the snowpack on sea ice retains more mercury than inland snow, current models of the Arctic mercury cycle may greatly underestimate atmospheric deposition fluxes because they are based predominantly on land-based measurements. Land-based measurements of atmospheric mercury deposition may also underestimate the impacts of sea ice changes on the mercury cycle in the Arctic. The predicted changes in sea ice conditions and a more saline future snowpack in the Arctic could enhance retention of atmospherically deposited mercury and increase the amount of mercury entering the Arctic Ocean and coastal 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".