Impacts of anthropogenic and natural sources on free tropospheric ozone over the Middle East
Bibliographic record
Abstract
Abstract. Significant progress has been made in identifying the influence of different processes and emissions on the summertime enhancements of free tropospheric ozone (O3) at northern midlatitude regions. However, the exact contribution of regional emissions, chemical and transport processes to these summertime enhancements is still not well quantified. Here we focus on quantifying the influence of regional emissions on the summertime O3 enhancements over the Middle East, using updated reactive nitrogen (NOx) emissions. We then use the adjoint of the GEOS-Chem model with these updated NOx emissions to show that the global total contribution of lightning NOx on middle free tropospheric O3 over the Middle East is about 2 times larger than that from global anthropogenic sources. The summertime middle free tropospheric O3 enhancement is primarily due to Asian NOx emissions, with approximately equivalent contributions from Asian anthropogenic activities and lightning. In the Middle Eastern lower free troposphere, lightning NOx from Europe and North America and anthropogenic NOx from Middle Eastern local emissions are the primary sources of O3. This work highlights the critical role of lightning NOx on northern midlatitude free tropospheric O3 and the important effect of the Asian summer monsoon on the export of Asian pollutants.
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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".