Halocarbon Emissions from the United States and Mexico and Their Global Warming Potential
Bibliographic record
Abstract
We use recent aircraft measurements of a comprehensive suite of anthropogenic halocarbons, carbon monoxide (CO), and related tracers to place new constraints on North American halocarbon emissions and quantify their global warming potential. Using a chemical transport model (GEOS-Chem) we find that the ensemble of observations are consistent with our prior best estimate of the U.S. anthropogenic CO source, but suggest a 30% underestimate of Mexican emissions. We develop an optimized CO emission inventory on this basis and quantify halocarbon emissions from their measured enhancements relative to CO. Emissions continue for many compounds restricted under the Montreal Protocol, and we show that halocarbons make up an important fraction of the total greenhouse gas source for both countries: our best estimate is 9% (uncertainty range 6-12%) and 32% (21-52%) of equivalent CO2 emissions for the U.S. and Mexico, respectively, on a 20 year time scale. Performance of bottom-up emission inventories is variable, with underestimates for some compounds and overestimates for others. Ongoing methylchloroform emissions are significant in the U.S. (2.8 Gg/y in 2004-2006), in contrast to bottom-up estimates (< 0.05 Gg), with implications for tropospheric OH calculations. Mexican methylchloroform emissions are minor.
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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 | 0.001 | 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".