Characterization and Comparison of Three Passive Air Samplers for Persistent Organic Pollutants
Bibliographic record
Abstract
The accumulation of persistent organic pollutants by three passive sampling media--semipermeable membrane devices (SPMDs), polyurethane foam (PUF) disks, and an organic-rich soil--was investigated. The media were exposed to contaminated indoor air over a period of 450 days, and concentrations in the air and in the media were monitored for individual polychlorinated biphenyl (PCB) congeners and polychlorinated naphthalene homologue groups. Uptake was initially linear and governed by the surface area of the sampler and the boundary layer airside mass transfer coefficient (MTC). Mean values of the MTC were 0.13, 0.11, and 0.26 cm s-1 for SPMD, PUF, and soil, respectively. As the study progressed, equilibrium was established between ambient air and the passive sampling media for the lower molecular weight PCB congeners. This information was used to calculate passive sampler-air partition coefficients, KPSM-A. These were correlated to the octanol-air partition coefficient, and the resulting regressions were used to predict KPSM-A for the full suite of PCBs. Information on MTC, KPSM-A, surface area, and effective thickness of each sampler was used to estimate times to equilibrium for each medium. These ranged from tens of days for the lower molecular weight congeners to tens of years for the higher molecular weight PCBs. Expressions were also developed to relate the amount of chemical accumulated by the passive sampling media to average ambient air concentrations over the integration period of the sample.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".