Air‐water gas exchange of mercury in the Bay Saint François wetlands: Observation and model parameterization
Bibliographic record
Abstract
Total gaseous mercury (TGM) air‐water flux measurements were taken using a dynamic flux chamber (DFC) coupled with a gaseous mercury (Hg) analyzer at the Bay St. François (BSF) wetlands (Quebec, Canada) in summer 2003. The measured TGM fluxes over water exhibited a consistent diurnal pattern, with maximum emissions during daytime and minimum fluxes occurring at night. Pearson correlation analysis showed that solar radiation was the most influential environmental parameter in TGM air‐water exchange. Significant correlations were also found between TGM fluxes and 1 hour time‐lagged water temperature, indicating the enhancement of fluxes by bacterial activities or chemical reactions. The concentrations of dissolved gaseous mercury (DGM) in water were measured during the 2003 sampling period and indicated that DGM was always supersaturated, which implied that the water body acted primarily as a source of mercury to the atmosphere. Several empirical models of mercury air‐water gas exchange were developed and evaluated. Compared to the published models, these proposed models were capable of producing good results, leading to a better agreement between the measured and modeled fluxes (improvements by 48–98%). Among these empirical models, the ones linking TGM fluxes with net radiation were superior because of their strong predictive capability. Two preferred models were selected for air‐water TGM flux estimation from Lake St. Pierre's surrounding wetlands. These two models yield a mean emission of 0.19–0.24 kg mercury during May–September each year from 1999 to 2003.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".