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Record W7161785669 · doi:10.82308/17488

The development and evaluation of a novel personal air sampling canister for the collection of gases and vapors /

2002· dissertation· en· W7161785669 on OpenAlexaboutno aff
Alan Rossner

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicIndoor Air Quality and Microbial Exposure
Canadian institutionsnot available
Fundersnot available
KeywordsVolumetric flow rateOccupational hygieneAirflowFlow (mathematics)Sample (material)Sampling (signal processing)Ventilation (architecture)

Abstract

fetched live from OpenAlex

A continuing challenge in occupational hygiene is that of estimating exposure to the multitude of airborne chemicals found in the workplace and surrounding community. Occupational exposure limits (OELs) have been established to prescribe the acceptable time weighted average for many different chemicals. Comparing the OELs to the measured workplace concentration allows occupational hygienists to assess the health risks and the need for control measures. Hence, methods to more effectively sample contaminants in the workplace are necessary to ensure that accurate exposure characterizations are completed. Evacuated canisters have been used for many years to collect ambient air samples for gases and vapors. Recently, increased interest has arisen in using evacuated canisters for personal breathing zone sampling as an alternative to sorbent samplers. A capillary flow control device was designed at McGill University mid 1990s. The flow control device was designed to provide a very low flow rate to allow a passive sample to be collected over an extended period of time. This research focused on the development and evaluation of a methodology to use a small canister coupled with the capillary flow controllers to collect long term time weighted air samples for gases and vapors. A series of flow rate experiments were done to test the capillary flow capabilities with a 300 mL canister for sampling times ranging from a few minutes to over 40 hours. Flow rates ranging from 0.05 to 1.0 mL/min were experimentally tested and empirical formulae were developed to predict flow rates for given capillary geometries. The low flow rates allow for the collection of a long term air sample in a small personal canister. Studies to examine the collection of air contaminants were conducted in laboratory and in field tests. Air samples for six volatile organic compounds were collected from a small exposure chamber using the capillary-canisters, charcoal tubes and diffusive badges at varied concentrations. The results from the three sampling devices were compared to each other and to concentration values obtained by an on-line gas chromatography. The results indicate that the capillary-canister compares quite favorably to the sorbent methods and to the on line GC values for the six compounds evaluated. Personal air monitoring was conducted in a large exposure chamber to assess the effectiveness of the capillary-canister method to evaluate breathing zone samples. In addition, field testing was performed at a manufacturing facility to assess the long term monitoring capabilities of the capillary-canister. Precision and accuracy were found to parallel that of sorbent sampling methods. The capillary-canister device displayed many positive attributes for occupational and community air sampling. Extended sampling times, greater capabilities to sample a broad range of chemicals simultaneously, ease of use, ease of analysis and the low relative cost of the flow controller should allow for improvements in exposure assessment.

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)0.005
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 score0.005
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.065
GPT teacher head0.303
Teacher spread0.238 · 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

Citations0
Published2002
Admission routes1
Has abstractyes

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