Per‐ and polyfluoroalkyl substances in untreated and treated sludge/biosolids from 27 water resource recovery facilities across the United States and Canada
Bibliographic record
Abstract
Per- and polyfluoroalkyl substances (PFAS) are being studied in all environmental matrices because of their ubiquitous presence and adverse human health impacts. This study conducted a surveillance of 27 water resource recovery facilities throughout the United States and Canada to screen the range of PFAS concentrations in pre-stabilized sludge and post-stabilized product. Among the 27 water resource recovery facilities, 82% use anaerobic digestion and the rest use chemical stabilization and/or incineration for sludge stabilization. Forty PFAS compounds were evaluated by US Environmental Protection Agency Method SW846/537.1, and four and nine compounds were reported in the pre-stabilized sludge and post-stabilized product, respectively. Concentrations of reported compounds in pre-stabilized sludge and post-stabilized product varied from 5 to 33 ng/g dry basis and 2 to 220 ng/g dry basis, respectively. 3-Perfluoropentylpropanoic acid (5:3 FTCA) and perfluorooctanesulfonic acid (PFOS) were the most frequently observed compounds, and PFAS concentrations in the post-stabilized products were generally higher than the corresponding pre-stabilized sludge. PRACTITIONER POINTS: Among the 40 target PFAS, four were above reporting limit in the pre-stabilized sludge and nine in the post-stabilized product. Incineration ash (post-stabilized product) samples did not have any reportable PFAS. 5:3 FTCA and PFOS were the two frequently observed compounds; concentrations were higher in the post-stabilized product compared to the pre-stabilized sludge. PFPeA and PFHxA were the only two short chain perfluoroalkyl carboxylic acids reported. PFOA was reported in only one of the 54 samples evaluated.
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.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".