Comment on amt-2022-130
Bibliographic record
Abstract
Total gaseous chlorine (TClg) measurements can improve our understanding of unknown sources of Cl to the atmosphere. Existing techniques for measuring TClg have been limited to offline analysis of extracted filters and do not provide suitable temporal information on fast atmospheric process. We describe high time-resolution in-situ measurements of TClg by combusting ambient air over a heated platinum (Pt) substrate coupled to a cavity ring-down spectrometer (CRDS). The method relies on the complete decomposition of TClg to release Cl atoms that react to form HCl, for which detection by CRDS has been shown to be fast and reliable. The method was validated using custom organochlorine permeation devices (PDs) that generated gas-phase dichloromethane (DCM), 1-chlorobutane (CB), and 1,3-dichloropropene (DCP). The optimal conversion temperature and residence time through the high-temperature furnace was 825 °C and 1.5 seconds, respectively. Complete conversion was indicated by the near unity orthogonal distance regression analysis slope (±σ) of 0.996 ± 0.012, 1.048 ± 0.006, and 1.027 ± 0.061 for DCM, CB, and DCP, respectively. Breaking these strong C-Cl bonds represents a proof of concept for complete conversion of all similar or weaker bonds that characterize all other TClg. We applied this technique to both outdoor and indoor environments and found reasonable comparisons in ambient background mixing ratios with the sum of expected HCl from known Cl species. We measured the converted TClg in an indoor environment during cleaning activities and observed varying levels of TClg comparable to previous studies. The method validated here is capable of measuring in-situ TClg and has a broad range of applications to make routine TClg measurements in a variety of applications.
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.032 | 0.018 |
| Insufficient payload (model declined to judge) | 0.059 | 0.062 |
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".