Air–Seawater Exchange of Organochlorine Pesticides in the Southern Ocean between Australia and Antarctica
Bibliographic record
Abstract
This study contributes new data on the spatial variability of persistent organic pollutants in the Indian-Pacific sector of the Southern Ocean and represents the first empirical data obtained from this region in 25 years. Paired high-volume atmospheric and seawater samples were collected along a transect between Australia and Antarctica to investigate the latitudinal dependence of the occurrence and distribution of legacy organochlorine pesticides (OCPs) and the current use pesticide chlorpyrifos in the Southern Ocean. Dissolved ΣHCH and dieldrin concentrations decreased linearly with increasing latitude from 7.7 to 3.0 and from 1.0 to 0.6 pg·L(-1), respectively. There was no consistent trend observed in the latitudinal profile of atmospheric samples; however, some compounds (such as dieldrin) showed reduced concentrations from 7.5-3.4 to 2.7-0.65 pg·m(-3) at the highest latitudes south of the Polar Front. Chlorpyrifos was found in samples from this area for the first time. Estimated air-seawater fugacity ratios and fluxes indicate a current net deposition between -3600 and -900, -6400 and -400, and -1400 and -200 (pg·m(-2)·d(-1)) for γ-HCH, dieldrin, and chlorpyrifos, respectively. These findings suggest that, under current climatic conditions, the Southern Ocean reservoir in the Indian-Pacific sector serves as an environmental sink rather than a source of OCPs to the atmosphere.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".