Per- and Polyfluoroalkyl Substances in Contaminated Soil and Groundwater at Airports: A Canadian Case Study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The occurrence of 93 classes of per- and polyfluoroalkyl substances (PFASs) was investigated at aqueous film-forming foam (AFFF)-impacted sites of four Canadian airports. Surface/subsurface soil and groundwater samples were characterized using high-resolution mass spectrometry (HRMS) and an improved total oxidizable precursor (TOP) assay. PFAS profiles, loads, and spatial trends were highly site-specific, influenced by the AFFF use history, variations in sorption, transport, and in situ transformation potential of PFASs. All sites have been impacted by more than one AFFF chemistry, with the active firefighter training area exhibiting a greater PFAS variety and total PFAS burden than decommissioned sites. Zwitterionic and cationic compounds composed a large percentage (34.5–85.5%) of the total PFAS mass in most surface soil samples in the source zone but a relatively low percentage (<20%) in groundwater samples. Background soils surrounding the source zone contained predominantly unidentified precursors attributed to atmospheric deposition, while in AFFF-impacted soils, precursors originating from AFFFs can be largely captured by HRMS using available suspect lists. Horizontal transfer of PFASs in surface soils was limited, but vertical migration down the soil column occurred even in locations of low permeability. This study provides a critical data set to support developing new priority analyte lists and integrating TOP assay for comprehensive PFAS monitoring at AFFF-impacted sites.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it