Mercury fluxes and speciated concentrations above terrestrial surfaces in Canada during colder periods
Bibliographic record
Abstract
Emission rates (fluxes) of gaseous elemental mercury (GEM) and concentration measurements of GEM, reactive gaseous mercury (RGM) and particle bound mercury (Hgp) were measured from different terrestrial surfaces in Canada in order to provide regional modelers with more reliable information on the behaviour of mercury in the environment during colder months. A micrometeorological flux gradient technique was used to infer the flux of GEM using a continuous two-level sampling system. Fluxes were measured from substrates (soils) containing low concentrations (< 1 [mu]g g-1) of mercury in the substrate but are representative of background levels in North America. In the Arctic, the highest depositional fluxes occurred during polar night and the largest emissions occurred when the tundra was first visible. The flux of GEM was approximately zero during atmospheric depletion events (AMDEs) demonstrating that mercury is not being deposited as GEM to the snow pack during these episodes. In Southern Ontario during the late fall, depositional fluxes of GEM were significantly elevated during a biosolids application event, although fluxes were only slightly increased during substantial rain events due to the surface soil moisture being near field capacity throughout the study. During the winter in Southern Ontario, GEM emission fluxes were 3 times higher during periods of snow cover than without. GEM fluxes were also significantly influenced by soil freezing, resulting in fluxes over 2 times greater when the freezing duration increased from 6 to 20 continuous days. Concentrations of RGM and Hgp in the Arctic were elevated during periods of low wind speeds. As the air temperature and specific humidity increased, higher levels of RGM were noted and colder temperatures with low specific humidities resulted in elevated Hgp concentrations. A biosolids application event during the fall in Southern Ontario resulted in elevated levels of RGM and He while harvesting of corn produced increased concentrations of Hgp and GEM. During the winter, elevated levels of GEM, RGM and Hgp were noted when the winds prevailed from urbanized areas with light industry and known atmospheric releases of mercury. The highest hourly averaged GEM concentrations occurred when the net radiation was highest. The highest concentrations of Hgp and RGM occurred throughout the night with the greatest variations occurring in the evening for He and around mid-day for RGM. On an averaged day, emissions of GEM occurred throughout the night when the soil temperatures were the lowest and deposition occurred around mid-day when the soil temperature was the highest.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".