Tool and Database for Estimating Potential Longevity of Colloidal Activated Carbon Barriers for PFAS in Groundwater
Bibliographic record
Abstract
ABSTRACT This study presents a planning‐level graphical tool and a regression equation model for estimating the longevity of Colloidal Activated Carbon (CAC) barriers for treating per‐ and polyfluoroalkyl substances (PFAS) in groundwater. The tool development incorporated information from field‐scale CAC barriers, including design data from 17 sites and performance monitoring results from a total of 26 sites. The tool consists of both graphical and mathematical frameworks for estimating barrier longevity based on site‐specific parameters, including barrier dimensions, groundwater Darcy velocity, CAC loading, and influent PFAS concentrations. Application of the tool to 17 field sites yields barrier longevities ranging from 4 to over 100,000 years, with median values of 870, 150, and 180 years for PFOS, PFOA, and PFHxS, respectively. The wide variation in longevities is partly due to the significant variability in PFAS mass flux entering the barriers, as shown by the five‐order‐of‐magnitude difference in PFOA mass flux, ranging from 4 × 10−8 to 1 × 10−3 kg m−2 year−1. The systematic decrease in barrier longevity from PFOS to PFOA/PFHxS aligns with known sorption behavior of these compounds onto CAC media. Key uncertainties in longevity estimation include spatial and temporal variability of PFAS and CAC, hydrogeologic heterogeneity, sorption isotherm selection, competitive sorption effects, and limited long‐term performance data. The tool provides a standardized approach for preliminary barrier design using site‐specific data while emphasizing the importance of applying appropriate safety factors and implementing long‐term monitoring strategies.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".