Quantitative passive soil vapor sampling for VOCs- part 2: laboratory experiments
Why this work is in the frame
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Bibliographic record
Abstract
Controlled laboratory experiments were conducted to demonstrate the use of passive samplers for soil vapor concentration monitoring. Five different passive samplers were studied (Radiello, SKC Ultra, Waterloo Membrane Sampler, ATD tubes and 3M OVM 3500). Ten different volatile organic compounds were used of varying classes (chlorinated ethanes, ethanes, and methanes, aliphatics and aromatics) and physical properties (vapor pressure, solubility and sorption). Samplers were exposed in randomized triplicates to concentrations of 1, 10 and 100 ppmv, with a relative humidity of ∼80%, a temperature of ∼24 °C, and a duration of 30 minutes in a chamber with a face velocity of about 5 cm min(-1). Passive samplers are more commonly used for longer sample durations (e.g., 8 hour workday) and higher face velocities (>600 cm min(-1)), so testing to verify the performance for these conditions was needed. Summa canister samples were collected and analyzed by EPA Method TO-15 to establish a baseline for comparison for all the passive samplers. Low-uptake rate varieties of four of the samplers were also tested at 10 ppmv under two conditions; with 5 cm min(-1) face velocity and stagnant conditions to assess whether low or near-zero face velocities would result in a low bias from the starvation effect. The results indicate that passive samplers can provide concentration measurements with accuracy (mostly within a factor of 2) and precision (RSD < 15%) comparable to conventional Summa canister samples and EPA Method TO-15 analysis. Some compounds are challenging for some passive samplers because of uncertainties in the uptake rates, or challenges with retention or recovery.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 it