Per- and polyfluoroalkyl substances and volatile methyl siloxanes in global air: Spatial and temporal trends
Bibliographic record
Abstract
The study reports on the atmospheric concentrations of per- and polyfluoroalkyl substances (PFAS) and volatile methyl siloxanes (VMS) measured using sorbent-impregnated polyurethane foam disks (SIPs) passive air samplers. New results are reported for samples collected in 2017, which extends temporal trend information to the period 2009–2017, for 21 sites where SIPs have been deployed since 2009. Among neutral PFAS, fluorotelomer alcohols (FTOHs) had higher concentrations than perfluoroalkane sulfonamides (FOSAs) and perfluoroalkane sulfonamido ethanols (FOSEs) with levels of ND‒228, ND‒15.8, ND‒10.4 pg/m3, respectively. Among ionizable PFAS, the sum of perfluoroalkyl carboxylic acids (PFCAs) and perfluoroalkyl sulfonic acids (PFSAs) in air were 0.128–781 and 6.85–124 pg/m3, respectively. Longer-chain i.e. C9–C14 PFAS, which are relevant to the recent proposal by Canada for a listing of long-chain (C9–C21) PFCAs to the Stockholm Convention, were also detected in the environment at all site categories including Arctic sites. Cyclic and linear VMS ranged between 1.34‒452 and 0.01–12.1 ng/m3, respectively, showing dominance in urban areas. Despite the wide range of levels observed across different site categories, geometric means of the PFAS and VMS groups were fairly similar when grouped according to the five United Nations regions. Variable temporal trends in air (2009–2017) were observed for both PFAS and VMS. PFOS, which has been listed in the Stockholm Convention since 2009, is still showing increasing tendencies at several sites, indicating constant input from direct and/or indirect sources. These new data inform international chemicals management for PFAS and VMS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".