Comparison of Airborne Reactive Nitrogen Measurements During WINTER
Bibliographic record
Abstract
Abstract We present a comparison of instruments measuring nitrogen oxide species from an aircraft during the 2015 Wintertime INvestigation of Transport, Emissions, and Reactivity (WINTER) campaign over the northeast United States. Instrument techniques compared here include chemiluminescence (CL), thermal dissociation laser‐induced fluorescence (TD‐LIF), cavity ring‐down spectroscopy (CRDS), high‐resolution time of flight, iodide‐adduct chemical ionization mass spectrometry (I‐CIMS), and aerosol mass spectrometry. Species investigated include NO2, NO, total nitrogen oxides (NOy), N2O5, ClNO2, and HNO3. Particulate‐phase nitrate is also included for comparisons of HNO3 and NOy. Instruments generally agreed within reported uncertainties, with individual flights sometimes showing much better agreement than the data set taken as a whole, due to flight‐to‐flight slope changes. NO measured by CRDS and CL showed an average relative slope of 1.16 ± 0.01 across all flights, which is outside of combined uncertainties. The source of the error was not identified. For NO2 measured by CRDS and TD‐LIF the average was 1.02 ± 0.00; for NOy measured by CRDS and CL the average was 1.01 ± 0.00; and for N2O5 measured by CRDS and I‐CIMS the average was 0.89 ± 0.01. NOy budget closure to within 20% is demonstrated. We observe nonlinearity in NO2 and NOy correlations at concentrations above ~30 ppbv that may be related to the NO discrepancy noted above. For ClNO2 there were significant differences between I‐CIMS and TD‐LIF, potentially due in part to the temperature used for thermal dissociation. Although the fraction of particulate nitrate measured by the TD‐LIF is not well characterized, it improves comparisons to include particulate measurements.
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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) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".