Gaseous mercury emissions from natural sources in Canadian landscapes
Bibliographic record
Abstract
Field measurements of mercury air‐surface exchange from natural settings were made in various Canadian landscapes. Soil and water samples were analyzed for mercury concentrations, and air‐surface exchange fluxes from these substrates were determined using dynamic chamber, micrometeorological, or modeling methods. Environmental variables, including air and soil/water temperature, solar radiation, humidity, and wind speed, were monitored concurrently with the air‐surface exchange to better understand the processes affecting the environmental cycling of mercury. Average mercury fluxes from aquatic landscapes ranged from 0.0 to 5.0 ng m−2 h−1 with total mercury concentration in water ranging from 0.3 to 6.5 ng L−1. A significant correlation (R2 = 0.47) was found between gaseous Hg fluxes and total Hg concentration in water. Mean gaseous Hg fluxes from forest soils varied from −0.4 to 2.2 ng m−2 h−1, while those from agricultural fields ranged from 1.1 to 2.9 ng m−2 h−1. Non‐mineralized bedrock, sand, and till sites yielded fluxes ranging from −0.03 to 5.9 ng m−2 h−1. Mean fluxes from mercuriferous geological substrates at various locations were large compared to non‐mercuriferous sites, ranging from 9.1 to 1760 ng m−2 h−1, and represent natural emissions. The corresponding total mercury substrate concentrations ranged from 0.360 to 180 ppm. A significant correlation (R2 = 0.66) was found between Hg fluxes and total Hg concentrations in mineralized and non‐mineralized substrates. These gaseous Hg flux measurements represent a significant contribution to understanding natural mercury cycling, but there are still insufficient data and knowledge of processes to properly scale up fluxes from natural sources in Canada.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 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".