Ozone production efficiency and loss of NO<sub><i>x</i></sub> in power plant plumes: Photochemical model and interpretation of measurements in Tennessee
Bibliographic record
Abstract
A model for photochemical evolution in power plants has been developed and used in combination with measurements to investigate ozone production efficiency (OPE) per NOx and the rate of photochemical removal of NOx. The model is a two‐dimensional (2‐D) Lagrangian model with 1 km horizontal resolution and vertical resolution ranging from 25 m to 300 m, nested within a larger 3‐D regional model. These results are compared with measured O3, Nox, and SO2 along aircraft transects through power plant plumes (Ryerson et al., 1998). Measured flux of NOx and SO2 in plume transects is 33%–50% lower than plume emission rates, suggesting that a fraction of plume emissions remained above the top of the convective mixed layer. The measured loss rate of SO2 is greater than expected from photochemistry and surface deposition, suggesting the possibility of cumulus venting of the boundary layer. If model parameters are adjusted to reflect this hypothesized transport of plume air above the boundary layer, then the model NOx removal rate agrees with measurements. OPE is derived from measured fluxes of O3, NOx and SO2 in the plume. The resulting OPE (1.2–2.5) is somewhat higher than the previous estimate by Ryerson et al. OPE in models is slightly higher than measurements (2–3). Higher OPE (3–4) is predicted for power plant plumes 18 hours downwind of the emission source. OPE for these far downwind plumes is comparable to OPE for other emission sources of NOx. OPE and NOx lifetime are both correlated with plume NOx concentrations. Model results suggest that OPE inferred from statistical correlations between O3 and tracers such as SO2 underestimate the true OPE in situations where the correlation between O3 and SO2 is nonlinear.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 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".