Measurement of mercury species in the atmosphere and the interactions of ozone and particulate matter with mercury over cropped land
Bibliographic record
Abstract
A one year study (July 2006-August 2007) was conducted at Elora, Ontario, Canada to measure gaseous elemental mercury (GEM), reactive gaseous mercury (RGM) and particulate mercury (HgP) as well as GEM fluxes over cropped land through the four seasons. Ozone (O3) and particulate matter (PM) were also measured to investigate their correlation with mercury. The micrometeorological approach was used for GEM flux determination using a continuous two-level sampling system for GEM concentration gradient measurement above soil surface and crop canopy. The turbulent transfer coefficients were derived from meteorological parameters measured on site. The average GEM flux recorded was 6.49±33.98 ng m-2 hr-1 (mean±SD) while the average GEM, RGM and HgP concentrations were 1.2±0.51 ng m -3, 15.10±10.02 pg m-3 and 16.35±9.54 pg m-3 respectively. The average O3 and PM 2.5 concentrations were 26.15±13.72 ppb and 27.2±30.25 g m-3 respectively. Highest mercury species and PM concentrations were recorded in early spring while highest ozone concentrations were observed in winter. GEM concentrations and fluxes as well as ozone and PM exhibited a diurnal pattern while no pattern was observed for RGM and Hg P. GEM flux showed clear seasonal behaviour with highest volatilization rates recorded in spring and summer. Net radiation, temperature and wind direction were the main factors influencing atmospheric pollutants concentrations.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".