Characterization of Polymer-Coated Glass as a Passive Air Sampler for Persistent Organic Pollutants
Bibliographic record
Abstract
The use of thin-film polymer-coated glass surfaces or POGs as passive air samplers was investigated during an uptake experiment in an indoor environment with high levels of gas-phase polychlorinated biphenyls (PCBs). POGs consisted of a micron thick layer of ethylene vinyl acetate (EVA) coated onto glass cylinders. The uptake was initially linear with time and governed by the air-side mass transfer coefficient and surface area of the sampler. This was followed by a curvilinear region and finally a constant phase when equilibrium was established between air and EVA. The high surface area-to-volume ratio of the POGs allowed rapid equilibrium with gas-phase PCBs; equilibration times were on the order of hours for the low molecular weight congeners. The equilibrium concentration was dependent on the EVA-air partition coefficient, K(EVA-A), which was shown to be very well correlated to the octanol-air partition coefficient, K(OA). When POGs of varying thickness were equilibrated with air, the amount of PCB accumulated increased with increasing thickness of the EVA, indicating that uptake was by absorption into the entire polymer matrix. A wind field of 4 m s(-1) resulted in an increased uptake rate by a factor of approximately six compared to uptake in relatively still air. This wind speed effect was diminished, however, when POGs were housed in deployment chambers consisting of inverted stainless steel bowls. Relationships based on the air-side mass transfer coefficient and K(EVA-A) were developed for PCBs that describe the entire uptake profile and allow air concentrations to be determined from the amount of chemical accumulated in the POG. It is believed that these relationships are also valid when POGs are used to detect other classes of persistent organic pollutants.
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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 | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".