Atmospheric Concentrations of New Persistent Organic Pollutants and Emerging Chemicals of Concern in the Group of Latin America and Caribbean (GRULAC) Region
Bibliographic record
Abstract
A special initiative was run by the Global Atmospheric Passive Sampling (GAPS) Network to provide atmospheric data on a range of emerging chemicals of concern and candidate and new persistent organic pollutants in the Group of Latin America and Caribbean (GRULAC) region. Regional-scale data for a range of flame retardants (FRs) including polybrominated diphenyl ethers (PBDEs), organophosphate esters (OPEs), and a range of alternative FRs (novel FRs) are reported over 2 years of sampling with low detection frequencies of the novel FRs. Atmospheric concentrations of the OPEs were an order of magnitude higher than all other FRs, with similar profiles at all sites. Regional-scale background concentrations of the poly- and perfluoroalkyl substances (PFAS), including the neutral PFAS (n-PFAS) and perfluoroalkyl acids (PFAAs), and the volatile methyl siloxanes (VMS) are also reported. Ethyl perfluorooctane sulfonamide (EtFOSA) was detected at highly elevated concentrations in Brazil and Colombia, in line with the use of the pesticide sulfluramid in this region. Similar concentrations of the perfluoroalkyl sulfonates (PFAS) were detected throughout the GRULAC region regardless of location type, and the VMS concentrations in air increased with the population density of sampling locations. This is the first report of atmospheric concentrations of the PFAAs and VMS from this region.
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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 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".