Statistical characterization of urban CO2 emission signals observed by commercial airliner measurements
Bibliographic record
Abstract
Abstract Cities are responsible for the largest anthropogenic CO2 emissions and are key to effective emission reduction strategies. Urban CO2 emissions estimated from vertical atmospheric measurements can contribute to an independent quantification of the reporting of national emissions and will thus have political implications. We analyzed vertical atmospheric CO2 mole fraction data obtained onboard commercial aircraft in proximity to 36 airports worldwide, as part of the Comprehensive Observation Network for Trace gases by Airliners (CONTRAIL) program. At many airports, we observed significant flight-to-flight variations of CO2 enhancements downwind of neighboring cities, providing advective fingerprints of city CO2 emissions. Observed CO2 variability increased with decreasing altitude, the magnitude of which varied from city to city. We found that the magnitude of CO2 variability near the ground (~1 km altitude) at an airport was correlated with the intensity of CO2 emissions from a nearby city. Our study has demonstrated the usefulness of commercial aircraft data for city-scale anthropogenic CO2 emission studies.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".