Sources of Volatile Organic Compounds in Industrial, Coastal and Urban Regions
Bibliographic record
Abstract
This thesis describes the application of gas chromatography using direct air injection for the measurement and analysis of volatile organic compounds (VOCs) during three campaigns in unique environments (i.e., industrial, marine and urban). A Griffin 450 gas chromatograph equipped with a cylindrical ion trap mass spectrometer and electron impact ionization (GC-ITMS) and a Varian 3380CP equipped with an electron capture detector (GC-ECD) were used to acquire speciated measurements of select VOCs (monoterpenes, alkanes and aromatics) and peroxyacyl nitrates (PANs), respectively, which were analyzed to investigate air mass sources. In the first campaign, principal component analysis (PCA) was used on a dataset collected in the Alberta oil sands to elucidate possible sources of analytically unresolved intermediate volatility organic compounds (IVOCs) that were observed in the GC-ITMS chromatograms. A spectrally similar analytically unresolved peak of IVOCs was observed in the lab from vapours in the headspace of a bitumen sample collected near the measurement site. In the second campaign, previously-reported nocturnal ozone-depletion events were investigated off the West coast of Vancouver Island. Monoterpenes and their oxidation products were measured to explore the role of biogenic VOCs (BVOC) as a possible chemical loss pathway for ozone in this region. The analysis showed that monoterpenes play a minor role in ozone depletion in this environment and that dry deposition is likely the dominant pathway. During this campaign, the headspace vapours of several local kelp species were measured to probe possible BVOC sources in the region. Limonene was found to be enhanced above background concentrations by two species (Nereocystis luetkeana and Alaria marginata) making them a previously unrecognized source of a highly reactive monoterpene in this environment. In the third campaign, two PAN species (i.e., peroxyacetyl nitrate (PAN) and peroxypropionic nitrate (PPN)) were measured by GC-ECD during a period when wildfire smoke was transported from California and British Columbia to Calgary, Alberta. The PPN/PAN ratio was calculated and ranged from 0.05 to 0.17 (a typical background value is 0.10) in biomass burning plumes. Gas chromatography with direct air injection continues to yield new and useful information and should be a component of any comprehensive analysis.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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 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".