Direct, Isomer-Specific Quantitation of Polycyclic Aromatic Hydrocarbons in Soils Using Membrane Introduction Mass Spectrometry and Chemical Ionization
Bibliographic record
Abstract
Polycyclic aromatic hydrocarbons (PAHs) are routinely screened for in soils, where quantitation of structural isomers is critical due to varying toxicity within PAH isomer classes. While chromatographic methods provide isomer resolution, such strategies are cost and time intensive. To address these challenges, we present condensed phase membrane introduction mass spectrometry using liquid electron ionization/chemical ionization (CP-MIMS-LEI/CI) as a direct mass spectrometry technique that provides rapid, quantitative results for PAH isomer measurements in soil samples. A methanol acceptor phase is flowed through a probe-mounted polydimethylsiloxane hollow fiber membrane directly immersed into a dichloromethane/soil slurry. PAHs and dichloromethane co-permeate the membrane into the acceptor solvent, whereas particulates and charged matrix components remain in the sample. A nanoflow of the membrane permeate is then directly infused into a LEI/CI interfaced triple quadrupole mass spectrometer. Diagnostic PAH adduct ions were formed at either M + 45 ([M + CH2Cl + CH3OH–HCl]+) or M + 47 ([M + CHCl2–HCl]+). This allowed the development of specific MS/MS transitions for individual PAH isomers. These transitions were subsequently used for the direct analyses of PAHs in real soils where CP-MIMS-LEI/CI was shown to be rapid (15 soil samples/h) and sensitive (ng/g level detection limits). CP-MIMS-LEI/CI results compared well to those obtained using GC–MS (average percent difference of −9% across 9 PAHs in 8 soil samples), presenting a compelling argument for direct, quantitative screening of PAHs in soils by CP-MIMS-LEI/CI, particularly given the simple workflow and short analytical duty cycle.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".