Sampling and Analysis of Airborne Particulate Matter and Aerosols Using In-Needle Trap and SPME Fiber Devices
Why this work is in the frame
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Bibliographic record
Abstract
A needle trap device (NTD) and commercial poly(dimethylsiloxane) (PDMS) 7-microm film thickness solid-phase microextraction (SPME) fibers were used for the sampling and analysis of aerosols and airborne particulate matter (PM) from an inhaler-administered drug, spray insect repellant, and tailpipe diesel exhaust. The NTD consisted of a 0.53-mm o.d. stainless steel needle having 5 mm of quartz wool packing section near the needle tip. Samples were collected by drawing air across the NTD with a Luertip syringe or via direct exposure of the SPME fiber. The mass loading of PM was varied by adjusting the volume of air pulled through the NTD or by varying the sampling time for the SPME fiber. The air volumes ranged from 0.1 to 50 mL, and sampling times varied from 10 s to 16 min. Particulates were either trapped on the needle packing or sorbed onto the SPME fiber. The devices were introduced to a chromatograph/mass spectrometer (GC/MS) injector for 5 min desorption. In the case of the NTD, 10 microL of clean air was delivered by a gas-tight syringe to aid the introduction of desorbed analytes. The compounds sorbed onto particles extracted by the SPME fiber or trapped in the needle device were desorbed in the injector and no carry-over was observed. Both devices performed well in extracting airborne polycyclic aromatic hydrocarbons (PAHs) in diesel exhaust, triamcinolone acetonide in a dose of asthma drug and DEET in a dose of insect repellant spray. Results suggest that the NTDs and PDMS 7-microm fibers can be used for airborne particulate sampling and analysis, providing a simple, fast, reusable, and cost-effective screening tool. The advantage of the SPME fiber is the open-bed geometry allowing spectroscopic investigations of particulates; for example, with Raman microspectroscopy.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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