Global Pilot Study of Legacy and Emerging Persistent Organic Pollutants using Sorbent-Impregnated Polyurethane Foam Disk Passive Air Samplers
Bibliographic record
Abstract
Sorbent-impregnated polyurethane foam (SIP) disk passive air samplers were deployed alongside polyurethane foam (PUF) disk samplers at 20 sites during the 2009 spring sampling period of the Global Atmospheric Passive Sampling (GAPS) Network. The SIP disk samplers consisted of PUF disks impregnated with finely ground XAD-4 resin. The addition of XAD-4 greatly improves the sorptive capacity of the PUF disk samplers for more volatile and polar chemicals, and allows for linear-phase sampling over several weeks for these compounds. The SIP and PUF disks were analyzed for polychlorinated biphenyls (PCBs), neutral polyfluoroalkyl compounds (PFCs), and ionic PFCs. Correlations between sampler-derived air concentrations for PCBs in the PUF and SIP disks samplers were significant (p < 0.05). The SIP disks effectively captured 4-50% more of the low molecular weight PCBs than the PUF disks samplers, and the PUF disks also had limitations for time-weighted passive sampling of neutral PFCs in air. Theoretical uptake curves for PUF disks showed rapid equilibration occurring in just hours for 8:2 FTOH and in a few days for MeFOSE, while theoretical curves for SIP disks showed superior sampling profiles for the neutral PFCs. PFCs were measured on SIP disks at all sites with 8:2 FTOH being the dominant compound detected and urban centers (n = 3) having the highest total neutral PFC concentrations ranging from 51.7 to 248 pg/m(3). A positive correlation was found between the FTOHs and FOSAs/FOSEs (p < 0.001, Pearson correlation) indicating similar contamination sources. The SIP disk appears to be a promising passive air sampler for measuring both emerging and legacy POPs on a global scale. They can also be used as a complement to the PUF disk sampler for capturing broader classes of compounds, or as a replacement for PUF disks entirely, especially when longer than quarterly deployment periods are desired.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 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".