Trends in long-term gaseous mercury observations in the Arctic and effects of temperature and other atmospheric conditions
Bibliographic record
Abstract
Abstract. Gaseous elemental mercury (GEM) measurements at Alert, Canada, from 1995 to 2007 were analyzed for statistical time trends and for correlations with meteorological and climate data. A significant decreasing trend in annual GEM concentration is reported at Alert, with an estimated slope of −0.0086 ng m−3 yr−1 (−0.6% yr−1) over this 13-year period. It is shown that there has been a shift in the month of minimum mean GEM concentration from May to April due to a change in the timing of springtime atmospheric mercury depletion events (AMDEs). These AMDEs are found to decrease with increasing local temperature within each month, both at Alert and at Amderma, Russia. These results support the temperature dependence suggested by previous experimental results and theoretical kinetic calculations on both bromine generation and mercury oxidation and highlight the potential for changes in Arctic mercury chemistry with climate. A correlation between total monthly AMDEs at Alert and the Polar/Eurasian Teleconnection Index was observed only in March, perhaps due to higher GEM inputs in early spring in those years with a weak polar vortex. A correlation of AMDEs at Alert with wind direction supports the origin of mercury depletion events over the Arctic Ocean, in agreement with a previous trajectory study of ozone depletion events. Interannual variability in total monthly depletion event frequency at Alert does not appear to correlate significantly with total or first-year northern hemispheric sea ice area or with other major teleconnection patterns. Nor do AMDEs at either Alert or Amderma correlate with local wind speed, as might be expected if depletion events are sustained by stable, low-turbulence atmospheric conditions. The data presented here – both the change in timing of depletion events and their relationship with temperature – can be used as additional constraints to improve the ability of models to predict the cycling and deposition of mercury in the Arctic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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 teacher head, 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".