Quantifying H <sub>2</sub> S with a Picarro CRDS G2201-i and the effect of H <sub>2</sub> S on carbon isotopes
Bibliographic record
Abstract
Abstract. Cavity Ring-Down Spectroscopy (CRDS) is a popular analytical method with important applications in earth sciences including volcanology. A main disadvantage of using CRDS in volcanology is that the presence of H2S distorts some spectral lines causing errors in the measurements. In this study, we investigated the effects of H2S on measurements using a Picarro G2201-i instrument. We defined the interferences caused by H2S on CO2, CH4, and their carbon isotopic compositions. We found that 30 ppb H2S in 1000 ppm CO2 causes a difference of ~1.0 ± 0.2 ‰ on the δ13C-CO2 measurement, while 1 ppm H2S in 1 ppm CH4 per causes a difference of < 0.2 ‰ on the δ13C-CH4 measurement; this agrees with the results from previous studies using other models of Picarro instruments. Characterizing how H2S produces these interferences as a function of concentration, we further developed a series of equations to quantify H2S in gas mixtures in a concentration range of 1 to 270 ppm. We validated our method by analyzing a natural dry gas sample and comparing our results with those of two other independent analytical techniques, namely a CH4-MultiGAS and a “Giggenbach bottle”. When comparing the results between the CH4-MultiGAS and the Picarro G2201-i, we measured differences of ~ 4 %, while when comparing the results between the Giggenbach bottle and the Picarro G2201-i, we measured differences of ~ 9 %. The results of these three techniques show excellent agreement within error of each other. Our study demonstrates that the Picarro G2201-i instrument can accurately and precisely measure CO2, CH4, and H2S concentrations in the gas phase.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".