A Post‐Phaseout Retrospective Reassessment of the Global Methyl Bromide Budget
Bibliographic record
Abstract
Abstract Methyl bromide is a stratospheric ozone‐depleting substance with both natural and anthropogenic sources. The global budget of methyl bromide has never been fully understood as evidenced by the significant budget gap between the bottom‐up source estimates and calculated atmospheric losses. Atmospheric methyl bromide levels have declined significantly since Phase‐out under the Montreal Protocol began in 1999, and the atmosphere appears to have reached a new steady state during the past five years. Here, we reassess the global methyl bromide budget utilizing the 25‐year record of atmospheric methyl bromide measurements from the National Oceanic and Atmospheric Administration Global Monitoring Laboratory global flask network and a zonal 6‐box coupled global ocean/atmosphere model. Model inversions were used to estimate the total emissions required to account for the observed atmospheric methyl bromide levels. From 1995 to 2019, global land‐based emissions (natural and anthropogenic) declined from about 120 to 85 Gg y−1 and net ocean emissions increased from −5 to +5 Gg y−1. There remains an imbalance between the bottom‐up estimates of terrestrial sources and the inversion result. Based on the timing, magnitude, and spatial distribution of the imbalance we partition it into (a) a persistent or time invariant source located primarily in the tropics, and (b) a smaller time‐varying component that scales with the anthropogenic source during phase‐out. We hypothesize that the persistent source is likely natural and the time variant component is an artifact resulting from a slight underestimation of anthropogenic emissions.
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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 | 0.001 | 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 | 0.001 |
| 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".