Catalytic efficiencies for atmospheric methane removal in the high-chlorine regime
Bibliographic record
Abstract
Catalytic production of chlorine atoms from iron salt aerosols (ISA) has been suggested as a means of achieving atmospheric methane reduction (AMR). The feasibility of this approach its efficiency and the optimum conditions for deployment must be determined. Success is not obvious because it depends on nonlinear atmospheric free radical chain reactions; under some conditions added chlorine is known to increase methane lifetime. Here we evaluate the catalytic efficiency of atmospheric methane oxidation, initiated by the photocatalytic conversion of chloride to chlorine by iron chlorides Fe(III)Cl(3−n)n , using a OD box model. While HOx and high NOx behaviours are well known, a new regime is characterized by high ClOx conditions ypified by CH3O2 reacting with ClO rather than NO or HO2. We find that at NOx mixing ratios below 50 ppt or above 390 ppt, methane removal per iron atom is always net positive regardless of the Cl2 addition rate. However, between these NOx mixing ratios and for a chlorine production rate below 1×10^6 Cl2 /(cm3 s) the net effect is negative, increasing CH4 concentrations. The efficiencies seen in the model range from -0.26 to 2.63 CH4/Cl.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".