Persistent Organic Pollutants in the East Antarctic Atmosphere: Inter-Annual Observations from 2010 to 2015 Using High-Flow-Through Passive Sampling
Bibliographic record
Abstract
In the first multiyear sampling effort for POPs in the eastern Antarctic atmosphere, 32 PCBs and 38 organochlorine pesticides were targeted in air collected with a high-flow-through passive sampler. Agricultural chemicals were found to dominate atmospheric profiles, in particular HCB and endosulfan-I, with average concentrations of 12 600 and 550 fg/m 3, respectively. HCB showed higher concentrations in the austral summer, indicative of local, temperature-dependent volatilisation, while endosulfan-I appeared to show fresh, late-austral-summer input followed by temporally decreasing levels throughout the year. The current-use herbicide, trifluralin, and the legacy pesticides mirex and toxaphene, were detected in Antarctic air for the first time. Trifluralin was observed at low but increasing levels over the five-year period. Its detection in the Antarctic atmosphere provides evidence of its persistence and long-range environmental transport capability. While a time frame of five years exceeds the duration of most Antarctic air monitoring efforts, it is projected that continuous monitoring at the decadal scale is required to detect an annual 10% change in atmospheric concentrations of key analytes. This finding emphasizes the importance of continuous, long-term monitoring efforts in polar regions, that serve a special role as sentinel environments of hemispheric chemical usage trends.
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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 | 0.000 | 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".