Long‐term variation of atmospheric methyl iodide and its link to global environmental change
Bibliographic record
Abstract
It has been suggested that the emissions of volatile organic compounds (VOCs) from the ocean could be affected by global warming, with feedback effects on the climate. In order to detect changes in their emissions as a response to global environmental change, long‐term observations are required. Here we report for the first time long‐term variations of atmospheric methyl iodide (CH3I), the most abundant iodine‐containing compound predominantly emitted from the ocean. We monitored its concentration periodically at five remote sites covering 82.5°N–40.4°S and over the western and northern Pacific Ocean from the late 1990s to 2011. At most observation sites, CH3I increased from 2003/2004 to 2009/2010 by several tens of per cent, with a decreasing trend before 2003. The inter‐annual variation pattern is well approximated by a sine curve with a period of 11 years and showed a good correlation with the Pacific Decadal Oscillation (PDO), suggesting that CH3I emissions are affected by global‐scale, sea surface temperature (SST)‐related, decadal anomalies. The influence of natural oscillations or environmental change on trace gas emissions from the ocean may be greater than has been thought previously, and these emissions may thus be sensitive to future climate change.
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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 | 0.000 | 0.001 |
| 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) | 0.000 | 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 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".