AQUA-GAPS/MONET-Derived Concentrations and Trends of PAHs and Polycyclic Musks across Global Waters
Bibliographic record
Abstract
Polycyclic aromatic hydrocarbons (PAHs), released from petrogenic, pyrogenic or diagenetic sources (degradation of wood materials), are of global concern due to their adverse effects, and potential for long-range transport. While dissolved PAHs have been frequently reported in the literature, there has been no consistent approach of sampling across water bodies. Passive samplers from the AQUA/GAPS-MONET initiative were deployed at 46 sites (28 marine and 18 freshwater), and analyzed for 28 PAHs and six polycyclic musks (PCMs) centrally. Freely dissolved PAH concentrations were dominated by phenanthrene (mean concentration 1500 pg L –1; median 530 pg L –1 ) and other low molecular weight compounds. Greatest concentrations of phenanthrene, fluoranthene, and pyrene were typically from the same sites, mostly in Europe and North America. Of the PCMs, only galaxolide (72% of samples) and tonalide (61%) were regularly detected, and were significantly cross-correlated. Benchmarking of PAHs relative to penta- and hexachlorobenzene confirmed that the most remote sites (Arctic, Antarctic, and mountain lakes) displayed below average PAH concentrations. Concentrations of 11 of 28 PAHs, galaxolide and tonalide were positively correlated ( P < 0.05) with population density within a radius of 5 km of the sampling site. Characteristic PAH ratios gave conflicting results, likely reflecting multiple PAH sources and postemission changes.
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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 | 0.001 |
| 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".