Theory and Validation of Solid-Phase Microextraction and Needle Trap Devices for Aerosol Sample
Bibliographic record
Abstract
Previous aerosol studies utilizing solid-phase microextraction (SPME) predominantly focused on volatile and semivolatile compounds in the gaseous phase. Difficulties were associated with quantitative analysis of these compounds when they were associated with atmospheric particles. The present study combines SPME technology with that of carboxen packed needles (needle trap, NT) for analysis of gaseous and particle-bound compounds in atmospheric samples. The NT device is constructed as a micro trap by placing some small sorbents in a needle. Aerosol samples are collected by drawing air through the NT device with a pump. The trapped components contain both gaseous chemical compounds as well as particulate matter present in the sample. The total concentration of analytes in an aerosol sample can be obtained on the basis of the exhaustive sampling mode of the NT device. Direct SPME is simultaneously used to determine gaseous compound in the aerosol sample. As a result, the SPME and NT devices, when used together, can provide a complete solution to highly efficient and accurate aerosol studies. The theoretical considerations of SPME and NT devices for aerosol sampling are validated by sampling seasalt aerosol, barbecue, and cigarette smoke. The concentrations of PAHs in the different phases of the samples are few ng/L. Result analysis shows that SPME and the NT device demonstrate several important advantages such as simplicity, convenience, and low costs under laboratory and on-site field sampling conditions.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".