Differentiating overlapping sources of per- and polyfluoroalkyl substances (PFAS) remains a central challenge in environmental forensics, particularly where investigations rely on targeted analytical datasets. Here, we present a tiered PFAS fingerprinting framework designed to extract source, process, and transport information using only target analytes. The framework integrates multiple, complementary lines of evidence, including compound-level concentrations, class- and carbon-number-resolved composition, diagnostic ratios, isomer distributions, precursor-product relationships, multivariate clustering, and geospatial pattern analysis, to support defensible source differentiation under data-limited conditions. The framework is demonstrated using groundwater datasets collected at two time points (2018 and 2024) from a complex industrial setting with overlapping PFAS inputs. Application of the framework resolves distinct PFAS mixture archetypes that reflect differences in manufacturing era, formulation chemistry, and hydrologic context. Identified profiles include sulfonate-rich mixtures consistent with electrochemical fluorination-era inputs, telomer-associated industrial mixtures characterized by fluorotelomer sulfonates and carboxylates, and short-chain-enriched profiles influenced by wastewater-related transport and mixing. Temporal evaluation shows changes in precursor abundance and terminal perfluoroalkyl carboxylic acids, between sampling events, while diagnostic ratios and isomer patterns provide additional temporal context where quantifiable. Unsupervised clustering independently corroborates compositional similarity and hydraulic connectivity among site domains. Together, these results indicate that target-only PFAS datasets can support forensic interpretation when multiple, complementary analytical metrics are evaluated in a structured framework. The approach outlines an analytical structure that could assist PFAS investigations where source histories are complex and compound coverage is limited.
Zenobio et al. (Mon,) studied this question.