The Use of MIMS-MS-MS in Field Locations as an On-Line Quantitative Environmental Monitoring Technique for Trace Contaminants in Air and Water
Bibliographic record
Abstract
Membrane introduction mass spectrometry (MIMS) is emerging as an important technique for on-line, real-time environmental monitoring. Because MIMS interfaces are simple and robust, they are ideally suited for operation in MS instrumentation used for in-field applications. We report the use of an on-line permeation tube to continuously infuse an isotopically labeled internal standard for continuous quantitative determinations in atmospheric and aqueous samples without the need for off-line calibration. This approach also provides important information on the operational performance of the analytical system during multi-day deployments. We report measured signal stability during on-line deployments in air and water of 7% based on variation of the internal standard response and have used this technique to quantify BTEX (benzene, toluene, ethylbenzenes, and xylenes), pinenes, naphthalene and 2-methoxyphenol (guaiacol) in urban air plumes at parts-per-billion by volume levels. Presented are several recent applications of MIMS-MS-MS for on-line environmental monitoring in atmospheric and aqueous environmental samples demonstrating laboratory, remote and mobile deployments. We also present the use of a thermally assisted MIMS interface for the direct measurement of polyaromatic hydrocarbons, alkylphenols, and other SVOCs in the low ppb range in aqueous environmental samples and discuss improvements in both the sensitivity and response times for selected SVOCs. The work presented in this paper represents significant improvements in field deployable mass spectrometric techniques, which can be applied to direct on-site analytical measurements of VOC and SVOCs in environmental 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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".