Characterization of Two Passive Air Samplers for Per- and Polyfluoroalkyl Substances
Bibliographic record
Abstract
Two passive air sampler (PAS) media were characterized under field conditions for the measurement of per- and polyfluoroalkyl substances (PFASs) in the atmosphere. The PASs, consisting of polyurethane foam (PUF) and sorbent-impregnated PUF (SIP) disks, were deployed for over one year in parallel with high volume active air samplers (HV-AAS) and low volume active air samplers (LV-AAS). Samples were analyzed for perfluoroalkyl carboxylic acids (PFCAs), perfluoroalkane sulfonic acids (PFSAs), fluorotelomer alcohols (FTOHs), fluorotelomer methacrylates (FTMACs), fluorotelomer acrylates (FTACs), perfluorooctane sulfonamides (FOSAs), and perfluorooctane sulfonamidoethanols (FOSEs). Sampling rates and the passive sampler medium (PSM)-air partition coefficient (KPSM-A) were calculated for individual PFASs. Sampling rates were similar for PFASs present in the gas phase and particle phase, and the linear sampling rate of 4 m(-3) d(-1) is recommended for calculating effective air sample volumes in the SIP-PAS and PUF-PAS for PFASs except for the FOSAs and FOSEs in the PUF-PAS. SIP disks showed very good performance for all tested PFASs while PUF disks were suitable only for the PFSAs and their precursors. Experiments evaluating the suitability of different isotopically labeled fluorinated depuration compounds (DCs) revealed that (13)C8-perfluorooctanoic acid (PFOA) was suitable for the calculation of site-specific sampling rates. Ambient temperature was the dominant factor influencing the seasonal trend of PFASs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".