Comparison of per- and polyfluoroalkyl substance (PFAS) soil extractions and instrumental analysis: large-volume injection liquid chromatography-mass spectrometry, EPA Method 1633, and commercial lab results for 40 PFAS in various soils
Bibliographic record
Abstract
Quantifying per- and polyfluoroalkyl substances (PFAS) in soil is a crucial part of site evaluations. Several methods are currently used in commercial and academic labs to evaluate PFAS-affected soils, with differences in extraction solvent, extraction method, cleanup procedure, and instrumental analysis among laboratories. This study aims to compare the accuracy and efficiency of a legacy in-house soil extraction method for PFAS with EPA Method 1633 for sample extraction and analysis using liquid chromatography tandem mass spectrometry (LC-MS/MS). An aqueous film-forming foam (AFFF)-impacted field soil (Soil A), a "clean soil" (Ottawa sand), and a certified reference soil were subjected to both extraction methods. Subsamples of these soils were also submitted to an accredited commercial lab. The commercial lab analyzed samples in accordance with EPA Method 1633 both for extraction and analysis. For comparison, our lab extracted the samples with both EPA Method 1633 and the in-house legacy soil extraction method, followed by a large-volume injection (LVI) adaptation of EPA Method 1633 instrumental analysis method. The EPA Method 1633 followed by LVI analysis quantified slightly more compounds without quality control flags than the legacy extraction method followed by LVI analysis for Soil A and the certified reference soil. Both in-house extractions had 76% of reportable compound concentrations within ± 15% relative standard deviation. The commercial small-volume injection results returned the least number of quality control flags, but quantified fewer compounds at low concentrations. Considering the time and cost of EPA Method 1633 and commercial analysis, this study supports the suitability of the legacy soil extraction method with LVI LC-MS/MS analysis for in-house soil analysis with comparable results to EPA Method 1633 as well as commercial analysis.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".