Loss of isoprene and sources of nighttime OH radicals at a rural site in the United States: Results from photochemical models
Bibliographic record
Abstract
A one‐dimensional Lagrangian model for atmospheric transport and photochemistry has been developed and used to interpret measurements made at Pellston, Michigan, during the summer of 1998. The model represents a moving vertical column of air with vertical resolution of 25 m near the ground. Calculations have been performed for a series of trajectories, with representation of emissions, vertical mixing, and photochemistry for a 3‐day period ending with the arrival of the air column at Pellston. Results have been used to identify causes of the observed decrease in isoprene at night, to investigate causes of high nighttime OH. Significant OH can be generated at night by terpenes if it is assumed that some fast‐reacting monoterpenes are emitted at rates comparable to inventory emissions for terpenes. However, this nighttime OH is confined to a shallow surface layer (0–25 m) and has little impact on nighttime chemistry. The observed decrease in isoprene at night can be reproduced in models with low OH, and is attributed primarily to vertical dilution. There is also evidence that transport from Lake Michigan contributes to low nighttime isoprene at Pellston. Model results compare well with measured isoprene, NOx, and with isoprene vertical profiles. Significant model‐measurement discrepancies are found for OH, HO2, methylvinylketone, and formaldehyde.
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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".