Condensed Phase Membrane Introduction Mass Spectrometry with Direct Electron Ionization: On-line Measurement of PAHs in Complex Aqueous Samples
Bibliographic record
Abstract
Polycyclic aromatic hydrocarbons (PAHs) are USEPA regulated priority pollutants. Their low aqueous solubility requires very sensitive analytical methods for their detection, typically involving preconcentration steps. Presented is the first demonstrated ‘proof of concept’ use of condensed phase membrane introduction mass spectrometry (CP-MIMS) coupled with direct liquid electron ionization (DEI) for the direct, on-line measurement of PAHs in aqueous samples. DEI is very well suited for the ionization of PAHs and other nonpolar compounds, and is not significantly influenced by the co-elution of matrix components. Linear calibration data for low ppb levels of aqueous naphthalene, anthracene, and pyrene is demonstrated, with measured detection limits of 4 ppb. Analytical response times (t10%–90% signal rise) ranged from 2.8 min for naphthalene to 4.7 min for pyrene. Both intra- and interday reproducibility has been assessed (<3% and 5% RSD, respectively). Direct measurements of ppb level PAHs spiked in a variety of real, complex environmental sample matrices is examined, including natural waters, sea waters, and a hydrocarbon extraction production waste water sample. For these spiked, complex samples, direct PAH measurement by CP-MIMS-DEI yielded minimal signal suppression from sample matrix effects (81%–104%). We demonstrate the use of this analytical approach to directly monitor real-time changes in aqueous PAH concentrations with potential applications for continuous on-line monitoring strategies and binding/adsorption studies in heterogeneous samples.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".