Assessing the Influence of Meteorological Parameters on the Performance of Polyurethane Foam-Based Passive Air Samplers
Bibliographic record
Abstract
Polyurethane foam (PUF) disk passive air samplers were evaluated under field conditionsto assessthe effect of temperature and wind speed on the sampling rate for polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), and organochlorine pesticides (OCPs). Passive samples integrated over 28-day periods were compared to high-volume air samples collected for 24 h, every 7 days. This provided a large data set of 42 passive sampling events and 168 high-volume samples over a 3-year period, starting in October 2003. Average PUF disk sampling rates for gas-phase chemicals was approximately 7 m3 d(-1) and comparable to previous reports. The high molecular weight PAHs, which are mainly particle-bound, experienced much lower sampling rates of approximately 0.7 m3 d(-1). This small rate was attributed to the ability of the sampling chamber to filter out coarse particles with only the fine/ultrafine fraction capable of penetration and collection on the PUF disk. Passive sampler-derived data were converted to equivalent air volumes (V(EQ), m3) using the high-volume air measurement results. Correlations of V(EQ) against meteorological data collected on-site yielded different behavior for gas- and particle-associated compounds. For gas-phase chemicals, sampling rates varied by about a factor of 2 with temperature and wind speed. The higher sampling rates at colder temperatures were explained bythe wind effecton sampling rates. Temperature and wind were strongly correlated with the greatest winds at coldertemperatures. Mainly particle-phase compounds (namely, the high molecular weight PAHs) had more variable sampling rates. Sampling rates increased greatly atwarmertemperatures as the high molecular weight PAH burden was shifted toward the gas phase and subject to higher gas-phase sampling rates. At colder temperatures, sampling rates were reduced as the partitioning of the high molecular weight PAHs was shifted toward the particle phase. The observed wind effect on sampling for the particle-phase compounds is believed to be tied to this strong temperature dependence on phase partitioning and hence sampling rate. For purposes of comparing passive sampler derived data for persistent organic pollutants, the factor of 2 variability observed for mainly gas-phase compounds is deemed to be acceptable in many instances for semiquantitative analysis. Depuration compounds may be used to improve accuracy and provide site-specific sampling rates, although this adds a level of complexity to the analysis. More research is needed to develop and test passive air samplers for particle-associated chemicals.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".