Trace level analysis of polycyclic aromatic hydrocarbons in surface waters by solid phase extraction (SPE) and gas chromatography-ion trap mass spectrometry (GC-ITMS)
Bibliographic record
Abstract
Ontario Provincial Water Quality Objectives for polycyclic aromatic hydrocarbons (PAHs) in surface waters require low parts per trillion (ng L(-1))/high parts per quadrillion (pg L(-1)) detection limits. To meet these monitoring requirements, a solid phase extraction-gas chromatography-ion trap mass spectrometry (SPE-GC-ITMS) method was developed. Seventeen priority PAHs commonly monitored in surface and drinking waters were examined using an external ionization ion trap mass spectrometer operated in selected ion monitoring (SIM) mode. Under 70 eV electron ionization (El) conditions, both the quantitative [M]+* ion and confirmatory [M - 2H]+* ion were formed in classical abundance ratios. Each of these ion species was isolated in the ion trap using a specific scan function. However, to overcome poor levels of confirmatory ion abundance which otherwise restrict PAH method detection limits (MDLs), the abundance of [M - 2H]+* ions was augmented during isolation by causing the dissociation of [M]+* with the broad-band waveform used for high mass ion ejection. Augmenting the [M - 2H]+* signal intensity facilitated the achievement of MDLs of approximately 1 ng L(-1). PAHs in surface water samples that were not detected by current Ontario Ministry of the Environment high-performance liquid chromatography (HPLC)-fluorescence and GC-single-stage quadrupole mass spectrometry methods were detected and quantified using the ion trap mass spectrometry SIM method. The data produced by all three methods on natural water samples fortified at sub-parts per billion (ppb) levels were comparable. When applied to Standards Council of Canada/Canadian Association for Environmental Analytical Laboratories (SCC/CAEAL, www.CAEAL.ca) accreditation audit samples, the SPE-GC-ITMS method results met all performance evaluation criteria.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".