Passive air sampling of polycyclic aromatic hydrocarbons and polychlorinated naphthalenes across europe
Bibliographic record
Abstract
This study presents concurrently sampled ambient air data for a range of polycyclic aromatic hydrocarbons (PAHs) and polychlorinated naphthalenes (PCNs) at the continental scale. This was achieved with a passive air sampling system, by deploying polyurethane foam disks, which were prepared in one laboratory, sealed to prevent contamination, sent out by courier to volunteers participating in different countries, exposed for six weeks, collected, resealed, and returned to the laboratory for analysis. The study area was Europe, a region with a history of extensive persistent organic pollutants usage and emission, and with marked national differences in population density, the degree of urbanization and industrial and agricultural development. Samplers were deployed at remote, rural, and urban locations in 22 countries. Calculated air concentrations were broadly in line with those obtained by conventional active air sampling techniques, for both compound classes and for compounds existing predominantly in the gas and particle phases. The geographical compound distribution reflected suspected regional emission patterns and highlighted localized source areas. Both PAH and PCN levels varied by more than two orders of magnitude. The implications for sources 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 | 0.001 | 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".