ISAMO (Iron Salt Atmospheric Methane Oxidation)
Bibliographic record
Abstract
Methane is a well-mixed greenhouse gas responsible for >1/3 of global warming since pre-industrial times whose atmospheric burden continues to increase with a new record set in 2022. Active chlorine in the atmosphere is poorly constrained and so is its role in the oxidation of methane. This uncertainty propagates into methane source budgets through isotope-constrained topdown models, in which the observed abundance of 13C in tropospheric methane (commonly expressed as δ13C-CH4) is used to constrain the sources of methane using their characteristic δ13C-CH4 values. These models need to account for the change in the observed δ13C-CH4 by the Cl and OH sinks, which shift the observed isotope towards higher δ13CCH4 values of fossil fuel sources, and away from 13C depleted biological sources. The ISAMO project focuses on the hypothesis that Cl atoms are produced naturally by the action of sunlight on particles containing iron and chloride and these chlorine atoms oxidize atmospheric methane. To study this, we use the sensitive and selective indirect quantification of the concentration of atomic Cl through the strong carbon kinetic isotope effect (KIE) in the CH4 + Cl reaction, which leaves the remaining CH4 enriched in 13C, and producing extremely 13C-depleted CO. We will present field and laboratory observations and global modelling, including CO isotope measurement from flasks samples across the North Atlantic. We show how this mechanism affects 13C depletion in atmospheric CO and how the corresponding 13C enrichment in CH4 affects global methane emission estimates
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".