The contribution of oceanic halocarbons to marine and free tropospheric air over the tropical West Pacific
Bibliographic record
Abstract
Abstract. Emissions of halogenated very-short-lived substances (VSLSs) from the oceans contribute to the atmospheric halogen budget and affect tropospheric and stratospheric ozone. Here, we investigate the contribution of natural oceanic VSLS emissions to the marine atmospheric boundary layer (MABL) and their transport into the free troposphere (FT) over the tropical West Pacific. The study concentrates on bromoform, dibromomethane and methyl iodide measured on ship and aircraft during the SHIVA (Stratospheric Ozone: Halogen Impacts in a Varying Atmosphere) campaign in the South China and Sulu seas in November 2011. Elevated oceanic concentrations for bromoform, dibromomethane and methyl iodide of on average 19.9, 5.0 and 3.8 pmol L−1, in particular close to Singapore and to the coast of Borneo, with high corresponding oceanic emissions of 1486, 405 and 433 pmol m−2 h−1 respectively, characterise this tropical region as a strong source of these compounds. Atmospheric mixing ratios in the MABL were unexpectedly relatively low with 2.08, 1.17 and 0.39 ppt for bromoform, dibromomethane and methyl iodide. We use meteorological and chemical ship and aircraft observations, FLEXPART trajectory calculations and source-loss estimates to identify the oceanic VSLS contribution to the MABL and to the FT. Our results show that the well-ventilated MABL and intense convection led to the low atmospheric mixing ratios in the MABL despite the high oceanic emissions. Up to 45 % of the accumulated bromoform in the FT above the region originates from the local South China Sea area, while dibromomethane is largely advected from distant source regions and the local ocean only contributes 20 %. The accumulated methyl iodide in the FT is higher than can be explained with local contributions. Possible reasons, uncertainties and consequences of our observations and model estimates are discussed.
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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) | 0.001 | 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".