Neutral polyfluoroalkyl substances in the global Atmosphere
Bibliographic record
Abstract
Concentrations of neutral per- and polyfluoroalkyl substances (nPFAS) in the atmosphere are of interest because nPFAS are highly mobile percursors for perfluoroalkyl acids. Two calibration studies in Ontario, Canada and Costa Rica established the feasibility of using XAD 2-resin based passive air samplers (XAD-PAS) to reliably determine long term average air concentrations of nPFAS under temperate and tropical climatic conditions. The temporal and spatial distribution of nPFAS was investigated by analyzing XAD-PAS deployed for one year at between 17 and 46 sites on six continents between 2006 and 2011 as part of the Global Atmospheric Passive Sampling (GAPS) study. Higher levels of fluorotelomer alcohols (FTOHs) compared to fluorinated sulfonamides (FOSAs), and fluorinated sulfonamidoethanols (FOSEs) were observed at all sites. Urban sites had the highest levels of nPFAS compared to rural and remote sites, which is also apparent in a positive correlation of nPFAS levels with the proximity of a sampling site to areas of high population density. Levels of FOSAs and FOSEs tended to decrease during the six years of measurements, whereas an initial decline in the concentrations of FTOHs from 2006 to 2008 did not continue in 2009 to 2011. A comparison of nPFAS levels measured in national XAD-PAS networks in Costa Rica and Botswana revealed that the GAPS sites in Tapanti and the Kalahari are representative of the more remote regions in those countries. XAD-PAS derived absolute nPFAS levels at GAPS sites are lower than those measured using another PAS, but are within the range of levels measured with active air samplers. Agreement of relative nPFAS composition is better between samplers, suggesting that the discrepancy is due to uncertain sampling rates.
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 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 | 0.001 | 0.001 |
| 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".