A portable, robust, stable, and tunable calibration source for gas-phase nitrous acid (HONO)
Bibliographic record
Abstract
Abstract. Atmospheric HONO mixing ratios in indoor and outdoor environments span a range of less than a few parts per trillion by volume (pptv) up to tens of parts per billion by volume (ppbv) in combustion plumes. Previous HONO calibration sources have utilized proton transfer acid displacement from nitrite salts or solutions, with output that ranges from tens to thousands of ppbv. Instrument calibrations have thus required large dilution flows to obtain atmospherically relevant mixing ratios. Here we present a simple universal source to reach very low HONO calibration mixing ratios using a nitrite-coated reaction device with the addition of humid air and/or HCl from a permeation device. The calibration source developed in this work can generate HONO across the atmospherically relevant range and has high purity (> 90 %), reproducibility, and tunability. Mixing ratios at the tens of pptv level are easily reached with reasonable dilution flows. The calibration source can be assembled to start producing stable HONO mixing ratios (relative standard error, RSE ≤ 2 %) within 2 h, with output concentrations varying ≤ 25 % following simulated transport or complete disassembly of the instrument and with ≤ 10 % under ideal conditions. The simplicity of this source makes it highly versatile for field and lab experiments. The platform facilitates a new level of accuracy in established instrumentation, as well as intercomparison studies to identify systematic HONO measurement bias and interferences.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".