Air–surface exchange of mercury in natural and anthropogenically impacted landscapes in Atlantic Canada
Bibliographic record
Abstract
Understanding the relative importance of various sources of mercury within ecosystems and their subsequent impact on biota requires a thorough understanding of the biogeochemical cycling of mercury. An important component of the biogeochemical mercury cycle involves the exchange of gas-phase mercury between the atmosphere and various landscape surfaces. This study examines air–surface exchange (flux) of gaseous elemental mercury in selected undisturbed and anthropogenically impacted aquatic and terrestrial landscape settings. The objective of this study was to quantify air–surface mercury exchange rates in these contrasting landscape settings, to put constraints on these rates and provide insight into physical processes controlling mercury flux. Mean daily mercury flux was typically low over natural forest soils varying from −0.4 (net deposition) to 2.2 ng m −2 h −1 (net evasion). Minimum and maximum flux rates measured at these sites over the diurnal cycle ranged from a minimum of −1.3 to a maximum of 5.7 ng m −2 h −1 . Low flux rates from forest soils was partially due to poor light penetration through the forest canopy. Average daily mercury flux over undisturbed glacial till soil at an open field site with full sun exposure was also low (0.9 ng m −2 h −1 ) compared to the same soil mixed over a depth of 2 m (8.0 ng m −2 h −1 ). Mean daily mercury flux rates measured over pristine freshwater lake surfaces were also low (0.7–6.5 ng m −2 h −1 ), although the overall range in flux varied more widely (−0.3 to 44 ng m −2 h −1 ). Total mercury concentrations in marine water at a moderately polluted coastal harbour site (mean c. 0.8 ng l −1 ) and mean daily mercury flux rates over salt water (0.7 ng m −2 h −1 ) were similar to those measured over freshwater lakes. The highest daily average and diurnal range in mercury flux rates were measured at two abandoned gold mine tailings sites (130 and 237 ng m −2 h −1 ). The abandoned mine sites comprised tailings high in mercury content due to the past use of the mercury amalgamation process in gold extraction from the ore. Flux rates from tailings were two orders of magnitude higher than those observed over undisturbed native soils of similar parent material. Higher flux rates at the mine tailings sites were accompanied by ambient air concentrations 5–10 times background levels at 20 cm above the tailings. Mercury flux from vegetation has not been widely considered. A preliminary study of mercury flux from a white pine tree ( Pinus strobus ) indicated that actively growing trees might play a role in the atmospheric mercury cycle.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".