Measurements of hydroxyl and hydroperoxy radicals during CalNex‐LA: Model comparisons and radical budgets
Bibliographic record
Abstract
Abstract Measurements of hydroxyl (OH) and hydroperoxy (HO 2 *) radical concentrations were made at the Pasadena ground site during the CalNex‐LA 2010 campaign using the laser‐induced fluorescence‐fluorescence assay by gas expansion technique. The measured concentrations of OH and HO 2 * exhibited a distinct weekend effect, with higher radical concentrations observed on the weekends corresponding to lower levels of nitrogen oxides (NO x ). The radical measurements were compared to results from a zero‐dimensional model using the Regional Atmospheric Chemical Mechanism‐2 constrained by NO x and other measured trace gases. The chemical model overpredicted measured OH concentrations during the weekends by a factor of approximately 1.4 ± 0.3 (1 σ ), but the agreement was better during the weekdays (ratio of 1.0 ± 0.2). Model predicted HO 2 * concentrations underpredicted by a factor of 1.3 ± 0.2 on the weekends, while measured weekday concentrations were underpredicted by a factor of 3.0 ± 0.5. However, increasing the modeled OH reactivity to match the measured total OH reactivity improved the overall agreement for both OH and HO 2 * on all days. A radical budget analysis suggests that photolysis of carbonyls and formaldehyde together accounted for approximately 40% of radical initiation with photolysis of nitrous acid accounting for 30% at the measurement height and ozone photolysis contributing less than 20%. An analysis of the ozone production sensitivity reveals that during the week, ozone production was limited by volatile organic compounds throughout the day during the campaign but NO x limited during the afternoon on the weekends.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".