Handling left-censored PFAS data in surface-water reconnaissance: A reproducible workflow applied to ten sites in the Trinity River headwaters, Texas

Abstract

Analyzing surface-water PFAS datasets using EPA Method 1633 often yields many results below reporting limits and fewer qualified low-level detections, making post-processing choices important for site comparisons. In this pilot study, we used a single synoptic survey of 10 sites in Trinity River headwater tributaries near Fort Worth, Texas, to demonstrate a transparent workflow for summarizing such data. Samples were collected on 21 December 2025 and analyzed for 40 target PFAS using isotope-dilution LC-MS/MS at a commercial laboratory accredited to ISO/IEC 17025. Of the 400 site-analyte results, 82 (20.5%) were detected, and 318 (79.5%) were left-censored. We distinguished detect-only ΣPFAS40, defined as the sum of quantified detections, with non-detects set to zero, from median-imputed ΣPFAS40, a model-based total generated using 5,000 censoring-aware imputations per site. Median imputed ΣPFAS40 ranged from 55.5 to 685.2 ng/L. One high-total site (TW08; 95% conditional imputation-uncertainty interval: 673.2–696.8 ng/L) clearly exceeded the other nine sites. Imputation increased ΣPFAS40 by 32–38 ng/L at lower-total sites relative to detect-only sums, demonstrating that non-detect handling materially affects low-end site comparison. Site rankings were stable across distributional assumptions, substitution methods, and qualifier reclassification. River-network distance, catchment land-cover metrics, and multi-year national pollutant discharge records were retained only as screening-level context. Overall, this pilot case study shows that the main value of the dataset lies in a reproducible, qualifier-transparent, and censoring-aware workflow for PFAS reconnaissance, rather than in any definitive assessment of temporal conditions or causal source attribution.