Elevated levels of OH observed in haze events during wintertime in central Beijing
Bibliographic record
Abstract
Abstract. Wintertime in situ measurements of OH, HO2 and RO2 radicals and OH reactivity were made in central Beijing during November and December 2016. Exceptionally elevated NO was observed on occasions, up to ~ 250 ppbv, believed to be the highest mole fraction for which there have then co-located radical observations. The daily maximum mixing ratios for radical species varied significantly day-to-day over the range 1–8 × 106 cm−3 (OH), 0.2–1.5 × 108 cm−3 (HO2) and 0.3–2.5 × 108 cm−3 (RO2). Averaged over the full observation period, the mean daytime peak in radicals was 2.7 × 106 cm−3, 0.39 × 108 cm−3 and 0.88 × 108 cm−3 for OH, HO2 and total RO2, respectively. The main daytime source of new radicals via initiation processes (primary production) was the photolysis of HONO (~ 83 %), and the dominant termination pathways were the reactions of OH with NO and NO2, particularly under polluted, haze conditions. The Master Chemical Mechanism (MCM) v3.3.1 operating within a box model was used to simulate the concentrations of OH, HO2 and RO2. The model underpredicted OH, HO2 and RO2, especially when NO mixing ratios were high (above 6 ppbv). The observation-to-model ratio of OH, HO2 and RO2 increased from ~ 1 (for all radicals) at 3 ppbv of NO to a factor of ~ 3, ~ 20 and ~ 91 for OH, HO2 and RO2, respectively, at ~ 200 ppbv of NO. The significant underprediction of radical concentrations by the MCM suggests a deficiency in the representation of gas-phase chemistry at high NOx. The OH concentrations were surprisingly similar (within 20 % during the day) inside and outside of haze events, despite j(O1D) decreasing by 50 % during haze periods. These observations provide strong evidence that gas-phase oxidation by OH can continue to generate secondary pollutants even under high pollution episodes, despite the reduction in photolysis rates within haze.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".