An inter-method comparison of mercury measurements in Icelandic volcanic gases
Bibliographic record
Abstract
Volcanic systems are challenging environments in which to accurately sample or measure gaseous mercury (Hg) concentrations, as the gas plumes may be hot, acidic and halogen-rich; Hg concentrations may be highly variable; and the environment may not be readily accessible. We conducted an inter-method comparison study of atmospheric Hg measurements at Icelandic volcanic systems using four different methods. These included a passive air sampler (PAS), an active sampler with activated carbon trap (ACT) and two real-time measurement instruments, the Lumex portable mercury analyzer and the Tekran automated mercury analyzer. Good agreement in calculated and time-averaged volcanic plume Hg concentrations (ranging from 2.3 to 7.2 ng m−3) was obtained between the ACT and Lumex methods operated simultaneously at the same sites. In a post-fieldwork intercomparison, ACT and Tekran sampling yielded excellent agreement in measuring background atmospheric Hg concentrations. However, PAS-measured concentrations were significantly lower than the other methods, and in many cases were below the method detection limit, which may be due to the short sampling timeframes and/or adverse meteorological conditions not allowing sufficient Hg to be collected on the samplers. These findings demonstrate that Lumex and ACT methods are suitable for gaseous Hg measurement in volcanic gas plumes.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.001 |
| 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".