Atmospheric mercury in the Canadian Arctic. Part I: A review of recent field measurements
Bibliographic record
Abstract
Long-range atmospheric transport and deposition are important sources of mercury (Hg) to Arctic aquatic and terrestrial ecosystems. We review here recent progress made in the study of the transport, transformation, deposition and reemission of atmospheric Hg in the Canadian Arctic, focusing on field measurements (see Dastoor et al., this issue for a review of modeling studies on the same topics). Redox processes control the speciation of atmospheric Hg, and thus impart an important influence on Hg deposition, particularly during atmospheric mercury depletion events (AMDEs). Bromine radicals were identified as the primary oxidant of atmospheric Hg during AMDEs. Since the start of monitoring at Alert (NU) in 1995, the timing of peak AMDE occurrence has shifted to earlier times in the spring (from May to April) in recent years, and while AMDE frequency and GEM concentrations are correlated with local meteorological conditions, the reasons for this timing-shift are not understood. Mercury is subject to various post-depositional processes in snowpacks and a large portion of deposited oxidized Hg can be reemitted following photoreduction; how much Hg is deposited and reemitted depends on geographical location, meteorological, vegetative and sea-ice conditions, as well as snow chemistry. Halide anions in the snow can stabilize Hg, therefore it is expected that a smaller fraction of deposited Hg will be reemitted from coastal snowpacks. Atmospheric gaseous Hg concentrations have decreased in some parts of the Arctic (e.g., Alert) from 2000 to 2009 but at a rate that was less than that at lower latitudes. Despite numerous recent advances, a number of knowledge gaps remain, including uncertainties in the identification of oxidized Hg species in the air (and how this relates to dry vs. wet deposition), physical-chemical processes in air, snow and water-especially over sea ice-and the relationship between these processes and climate change.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".