Emissions of CH<sub>4</sub> and N<sub>2</sub>O over the United States and Canada based on a receptor‐oriented modeling framework and COBRA‐NA atmospheric observations
Bibliographic record
Abstract
We present top‐down emission constraints for two non‐CO 2 greenhouse gases in large areas of the U.S. and southern Canada during early summer. Collocated airborne measurements of methane and nitrous oxide acquired during the COBRA‐NA campaign in May–June 2003, analyzed using a receptor‐oriented Lagrangian particle dispersion model, provide robust validation of independent bottom‐up emission estimates from the EDGAR and GEIA inventories. We find that the EDGAR CH 4 emission rates are slightly low by a factor of 1.08 ± 0.15 (2 σ ), while both EDGAR and GEIA N 2 O emissions are significantly too low, by factors of 2.62 ± 0.50 and 3.05 ± 0.61, respectively, for this region. Potential footprint bias may expand the statistically retrieved uncertainties. Seasonality of agricultural N 2 O emissions may help explain the discrepancy. Total anthropogenic U.S. and Canadian emissions would be 49 Tg CH 4 and 4.3 Tg N 2 O annually, if these inventory scaling factors applied to all of North America.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".