Quantification of Non-refractory Aerosol Nitrate in Ambient Air by Thermal Dissociation Cavity Ring-Down Spectroscopy
Bibliographic record
Abstract
A thermal dissociation cavity ring-down spectrometer (TD-CRDS) for real-time quantification of non-refractory aerosol nitrate in ambient air is described. The instrument uses four parallel detection channels and heated quartz inlets to convert particulate organic nitrate (pON) (at 350 °C) and ammonium nitrate (NH 4 NO 3 ) aerosol (at 540 °C) to nitrogen dioxide (NO 2 ), whose mixing ratio is monitored via its absorption at 405 nm. Concentrations of aerosol nitrate are determined by difference relative to a parallel TD-CRDS channel in which aerosol is removed by in-line filtering. The method was validated by sampling gas streams containing laboratory-generated NH 4 NO 3 aerosol in parallel to a scanning mobility particle sizer (SMPS). Scatter plots of TD-CRDS and SMPS data correlated ( r 2 > 0.9) with slopes near unity, confirming quantitative TD-CRDS response to NH 4 NO 3 aerosol. In contrast, no response was observed when sampling (NH 4 ) 2 SO 4 aerosol. Instrument limits of detection (LOD; 2σ, 10 s) were 120 parts per trillion by volume (10 –12, pptv) for NO 2 and 148 pptv for ammonium nitrate. Partial and unsustained conversion of refractory sodium nitrate (NaNO 3 ) was observed at the inlet temperature used for complete dissociation of HNO 3 and NH 4 NO 3, suggesting that this channel may not constitute a robust measurement of total odd nitrogen (NO y ) in environments where NaNO 3 particles may be present (e.g., the polluted marine boundary layer). A potential application of the TD-CRDS is the calibration of particle counters, for which convenient methods are not currently available. Sample ambient air measurements of pON and total aerosol nitrate in Calgary are presented.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".