High-Resolution WRF-LES-Chem Simulations to Investigate Ozone Formation Regimes in Houston
Bibliographic record
Abstract
Despite decades of ongoing mitigation efforts, ozone (O 3 ) levels remain persistently high in Houston, TX. For a high O 3 episode observed during the NASA Tracking Aerosol Convection Interactions ExpeRiment-Air Quality (TRACER-AQ) campaign, we use a high-resolution large-eddy simulation (LES) within the Weather Research and Forecasting model coupled with Chemistry (WRF-LES-Chem) to investigate temporal and spatial variations in O 3 formation regimes over the region. By leveraging improved simulations of O 3 and its precursors by LES, compared to the mesoscale WRF model, we derive and compare two O 3 sensitivity indicators: the formaldehyde-to-nitrogen dioxide ratio (FNR) and the ratio of radical loss via NO X reactions to total primary radical production (L N /Q). Specifically, we use L N /Q to inform the threshold for FNR, the latter being a more commonly used and accessible indicator, although it is subject to significant uncertainties. We demonstrate that O 3 production in the Houston urban area transitions from a nearly homogeneous early morning VOC-limited regime to a NO X -limited regime by midday. Using the L N /Q indicator, we identify that a range of 0.6 < FNR < 1.8 falls in the transition zone of O 3 formation regime. The high-resolution modeling of O 3 formation and the FNR range developed in this LES study offers valuable insight for assessing future air quality and improving the understanding of atmospheric chemistry that underpins pollution control in Houston.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".