A comparison of Arctic BrO measurements by chemical ionization mass spectrometry and long path-differential optical absorption spectroscopy
Bibliographic record
Abstract
[1] A measurement intensive was carried out in Barrow, Alaska, in spring 2009 as part of the Ocean-Atmosphere-Sea-Ice–Snowpack (OASIS) program. The central focus of this campaign was the role of halogen chemistry in the Arctic. A chemical ionization mass spectrometer (CIMS) performed in situ bromine oxide (BrO) measurements. In addition, a long path-differential optical absorption spectrometer (LP-DOAS) measured the average concentration of BrO along light paths of either 7.2 or 2.1 km. A comparison of the 1 min observations from both instruments is presented in this work. The two measurements were highly correlated and agreed within their uncertainties (R2 = 0.74, slope = 1.10, and intercept = −0.15 pptv). Better correlation was found (R2 = 0.85, slope = 1.04, and intercept = −0.11 pptv) for BrO observations at moderate wind speeds (>3 m s−1 and <8 m s−1) and low nitric oxide (NO) mixing ratios (<100 pptv). The improved agreement is likely due to the elimination of periods when the spatial distribution of BrO is inhomogeneous. The detection limit obtained for the CIMS was 2.6 pptv (3σ) for a 4 s integration period, and the estimated uncertainty was ∼30%. The detection limits for the LP-DOAS ranged from 0.7 to 5 pptv (3σ) depending on the level of ambient light and the chosen light path, and the estimated systematic error was 10%. The agreement between the CIMS and LP-DOAS is excellent and demonstrates the capability of both instruments to selectively and accurately measure BrO with high sensitivity.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".