• PFAS quantified with diffusive gradients in thin-films passive samplers in water • Gel diffusion coefficients determined with non-steady state finite difference model • FDM used to determine D Gel error and goodness of fit • D Gel error propagated into time-weighted average DGT concentrations • DGTs accurately quantified TWA PFAS at ∼1, 10, 100, 200 ng L −1 Diffusive gradients in thin-films (DGT) passive samplers are used to quantify analytes in water, but their capabilities for capturing time-weighted average concentrations (C DGT ) of per- and polyfluoroalkyl substances (PFAS) at low ng L −1 levels are unknown. For 32 PFAS, DGT passive sampler gel layer diffusion coefficients (D Gel ) ± 95% confidence intervals (CIs) were determined using two-compartment diffusion cell tests analyzed with a non-steady-state finite difference model (FDM), which was previously shown to produce D Gel estimates with less error than traditional methods relying on a pseudo-steady-state flux assumption. For each PFAS, the FDM also determined the normalized weighted sum of square errors (WSSE × n −1 ), a goodness of fit measure. Eleven PFAS had adequate FDM fits (WSSE × n −1 < 0.03) and D Gel ± 95% CIs decreased with increasing molecular weight (MW) from 7.1–5.1 (± 0.1–0.6) × 10 −6 cm 2 s −1 . For the other 21 PFAS, linear regression models (D Gel vs. MW; R 2 ≥ 0.967) were used to estimate D Gel ± 95% CIs from 3.4–7.6 (± 0.2–1.0) × 10 −6 cm 2 s −1 . Compared to their free water diffusivities, D Gel values differed by a median of 6.5 % and first and third quartiles of 4.5 and 8.7 %, respectively. Error in D Gel was propagated into C DGT for 5–36-day laboratory-scale DGT deployments, in which C DGT ± 95% CIs for 20–31 of the 32 PFAS were indistinguishable from grab samples (sign test; α = 0.05). DGTs accurately captured time-weighted average PFAS aqueous phase concentrations at ∼1, 10, 100, and 200 ng L −1 . This study demonstrates the utility of DGTs for PFAS quantitation at low ng L −1 levels and establishes methods for PFAS D Gel determinations, error propagation into C DGT , and comparisons with grab sampling.
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Harris et al. (Wed,) studied this question.
www.synapsesocial.com/papers/69df2a4be4eeef8a2a6af875 — DOI: https://doi.org/10.1016/j.watres.2026.125918
Brianna Harris
Samuel D. Hodges
David G. Wahman
Water Research
Environmental Protection Agency
University of Arkansas at Fayetteville
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