Assessing the atmosphere-surface exchange of gaseous elemental mercury using passive air samplers
Bibliographic record
Abstract
The specific properties of gaseous elemental mercury (GEM) allow it to undergo bidirectional exchange between the atmosphere and the Earth’s surface. Determining the direction and the magnitude of GEM’s atmosphere-surface flux is possible and has been accomplished using micrometeorological and chamber techniques, but (i) is complex and labor-intensive, and (ii) often only yields fluxes over relatively short time scales. A recently developed passive air sampler for GEM has the precision required for identifying and quantifying vertical concentration gradients above the Earth’s surface. The feasibility and performance of this approach is currently being tested in a number of field studies aimed at the: (i) measurement of GEM concentration gradients above both mercury-contaminated and background forest soils, (ii) quantification of vertical concentration gradients on a tower through a temperate deciduous forest canopy, and (iii) measurement of mercury concentration gradients over stable and thawing permafrost to determine the effect of permafrost degradation on GEM evasion. Contrasting with earlier flux studies, these investigations cover long time periods (up to 1.5 years) and have coarse temporal resolution (monthly to seasonally). Significant gradients of GEM air concentrations, both increasing and decreasing with height above ground, were observed, implying that at a minimum, the method is able to identify the flux direction of GEM. Under the right circumstances, this method can also be used to estimate the approximate magnitude of the GEM air-surface exchange flux. The measured gradients also reveal the impact of factors such as temperature, solar irradiance, and snow cover on air-surface exchange. The method holds promise for establishing the direction and size of exchange fluxes at long time scales of months to a year, especially in study areas where access, effort and cost are prohibitive to longer duration studies with existing approaches.
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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 | 0.000 | 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".