The influence of ozone on atmospheric emissions of gaseous elemental mercury and reactive gaseous mercury from substrates
Bibliographic record
Abstract
Experiments were performed to investigate the effect of ozone (O 3 ) on mercury (Hg) emission from a variety of Hg-bearing substrates. Substrates with Hg(II) as the dominant Hg phase exhibited a 1.7 to 51-fold increase in elemental Hg (Hg o ) flux and a 1.3 to 8.6-fold increase in reactive gaseous mercury (RGM) flux in the presence of O 3 -enriched clean (50 ppb O 3 ; 8 substrates) and ambient air (up to ∼70 ppb O 3 ; 6 substrates), relative to clean air (oxidant and Hg free air). In contrast, Hg o fluxes from two artificially Hg o -amended substrates decreased by more than 75% during exposure to O 3 -enriched clean air relative to clean air. Reactive gaseous mercury emissions from Hg o -amended substrates increased immediately after exposure to O 3 but then decreased rapidly. These experimental results demonstrate that O 3 is very important in controlling Hg emissions from substrates. The chemical mechanisms that produced these trends are not known but potentially involve heterogenous reactions between O 3 , the substrate, and Hg. Our experiments suggest they are not homogenous gas-phase reactions. Comparison of the influence of O 3 versus light on increasing Hg o emissions from dry Hg(II)-bearing substrates demonstrated that they have a similar amount of influence although O 3 appeared to be slightly more dominant. Experiments using water-saturated substrates showed that the presence of high-substrate moisture content minimizes reactions between atmospheric O 3 and substrate-bound Hg. Using conservative calculations developed in this paper, we conclude that because O 3 concentrations have roughly doubled in the last 100 years, this could have increased Hg o emissions from terrestrial substrates by 65–72%.
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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 | 0.000 |
| Science and technology studies | 0.000 | 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".