Composition and river export of per- and polyfluoroalkyl substances (PFAS) upstream and downstream of a manufacturing plant in the Cape Fear River basin (North Carolina, USA)
Bibliographic record
Abstract
Presented by: Marie-Amélie Pétré – Postdoctoral Research Scholar at North Carolina State University \n \nCo-authors: Salk-Gundersen K, Knappe DRU, Ferguson PL, Obenour DR, Stapleton HM, Genereux DP \n \nAbstract: The Cape Fear River and its upstream Haw River tributary are important sources of drinking water in North Carolina, and many drinking water intakes in the watershed are impacted by per- and polyfluoroalkyl substances (PFAS). \n \nWe quantified river export of PFAS and determined the PFAS composition of river water upstream and downstream of a plant that has been producing PFAS since 1980. \n \nRiver samples collected between September 2018 and April 2020 were analyzed for 13 PFAS in the Haw River near Bynum and 42 PFAS downstream in the Cape Fear River near Wilmington. At Bynum, Σ13PFAS (PFAS concentrations summed for the 13 analytes) and river export of PFAS averaged 194 ng/L (range 26-742 ng/L) and 256 g/day, respectively. Near Wilmington, Σ42PFAS and river export averaged 143 ng/L (range 40-377) and 4033 g/day, respectively. Perfluoroalkyl acids dominated at Bynum: Σ13PFAS consisted of 77% perfluoroalkylcarboxylic acids and 20% perfluoroalkylsulfonic acids, and fluoroethers associated with the plant were an important contributor to the PFAS signature near Wilmington. Considering only the 13 PFAS detected in Bynum, average river export near Wilmington (1118 g/day) was 4x higher than at Bynum, suggesting significant input of both legacy PFAS and fluoroethers between Bynum and Wilmington. \n \nBiography: Marie-Amélie Pétré received a Ph.D. degree in Hydrogeology from the Institut national de la recherche scientifique (Québec, Canada) and Mines ParisTech (France) in 2016. She was then a postdoctoral fellow in hydrogeochemistry at HydroSciences Montpellier (CNRS, France) in 2017-2019. She is currently a Postdoctoral Research Scholar at North Carolina State University, where she studies the transport of PFAS from groundwater to streams near a manufacturing plant.
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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 | 0.000 | 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 | 0.001 |
| 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".