On-line measurement of oxidative degradation kinetics for trace gasoline contaminants in aqueous solutions and natural water by membrane introduction tandem mass spectrometry
Bibliographic record
Abstract
Membrane introduction mass spectrometry (MIMS) was used to directly monitor the loss of trace gasoline contaminants (benzene, toluene, 2-methylthiophene and methylcyclohexane) in nanomolar (ppb) aqueous solutions under a variety of UV-induced advanced oxidation processes (AOP). The decay kinetics of these contaminants were followed simultaneously in "real-time" via tandem mass spectrometric techniques by re-circulating the reaction mixture in a closed loop over a semi-permeable membrane interface. The photocatalyzed degradations were observed to follow pseudo-first-order kinetics with rate constants ranging from 0.006 to 0.2 min⁻¹ depending on the reaction conditions. We report rate enhancements for several UV-based advanced oxidative processes using physiosorbed titanium dioxide (TiO₂/UV, TiO₂/UV/O₂, TiO₂/UV/H₂O₂) and compare these to the direct photolysis of H₂O₂ under otherwise identical conditions. The relative degradation rates of 4 trace contaminants are reported for reactions carried out in the same solution. The degradation kinetics were also monitored directly in a natural surface water spiked with the same contaminant suite. The observed decay kinetics in the presence of TiO₂ in air-saturated natural water were similar to those carried out in deionized water. However, when the photo-oxidation was enhanced by the addition of H₂O₂, the degradation was markedly slower in natural water relative to deionized water due to competition for photons by dissolved organic matter. This work further demonstrates the use of MIMS as a sensitive on-line measurement technique for "in-situ" reaction monitoring of organic contaminants at environmentally relevant concentrations in complex solutions and reactive media.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".