Passive Air Sampling of PCBs, PBDEs, and Organochlorine Pesticides Across Europe
Bibliographic record
Abstract
This study presents concurrently sampled ambient air data for a range of persistent organic pollutants at the continental scale. This was achieved using a passive air sampling system, deploying polyurethane foam disks, which was prepared in one laboratory, sealed to prevent contamination, sent out by courier to volunteers participating in different countries, exposed for 6 weeks, collected, resealed, and returned to the laboratory for analysis. Europe was the study area--a region with a history of extensive POPs usage and emission and with marked national differences in population density, the degree of urbanization and industrial/agricultural development. Samplers were deployed at remote/rural/urban locations in 22 countries and analyzed for PCBs, a range of organochlorine pesticides (HCB, alpha-HCH, gamma-HCH, ppDDT, ppDDE), and PBDEs. Calculated air concentrations were in line with those obtained by conventional active air sampling techniques. The geographical pattern of all compounds reflected suspected regional emission patterns and highlighted localized hotspots. PCB and PBDE levels varied by over 2 orders of magnitude; the highest values were detected in areas of high usage and were linked to urbanized areas. HCB was relatively uniformly distributed, reflecting its persistence and high degree of mixing in air. Higher gamma-HCH, ppDDT, and ppDDE levels generally occurred in South and East Europe.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".