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Record W2030005855 · doi:10.1021/ac1022265

Theory and Validation of Solid-Phase Microextraction and Needle Trap Devices for Aerosol Sample

2010· article· en· W2030005855 on OpenAlexaff
Xiang Li, Gangfeng Ouyang, Heather Lord, Janusz Pawliszyn

Bibliographic record

VenueAnalytical Chemistry · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAerosolSolid-phase microextractionChemistryParticulatesAnalyteAnalytical Chemistry (journal)ChromatographyParticle (ecology)Sample preparationEnvironmental chemistryMass spectrometryGas chromatography–mass spectrometry

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.003
Open science0.0030.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.033
GPT teacher head0.371
Teacher spread0.338 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations29
Published2010
Admission routes1
Has abstractyes

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