Semiquantification of PFAS in nontarget analysis via ionization efficiency: A critical review of evidence and
Xin Xin1, Huijiao Wang2, Zhenyu Wang3
1School of Chemical and Environmental Engineering, China University of Mining and Technology-Beijing, Beijing, 100083, China; State Key Laboratory of Regional Environment and Sustainability, Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China.
Abstract:
Semiquantitative PFAS estimates can support local screening, but their use across new PFAS structures, sample matrices, or analytical platforms requires direct validation. This need is acute in quantitative nontarget analysis (qNTA), where PFAS diversity far exceeds the availability of authentic and isotopically labelled standards. Ionization-efficiency/response-factor (IE/RF)-based approaches help bridge this standards gap, yet existing reviews have rarely linked validation design to the concentration-use claims it can support. We therefore propose a dimension-aware L0-L4 evidence-to-claim framework that evaluates structural, matrix, and platform transfer independently and records transfer outcome separately from validation scope. We applied the framework to 83 study/workflow settings from 52 articles. Across these settings, 77 supported only local or same-context use (L0), while only six supported matrix and/or platform transfer (L2, L3, or L2+L3); none supported structural transfer (L1) or fully integrated deployment (L4). Even where point performance was reported, empirical coverage, explicit applicability-domain/out-of-domain (AD/OOD) handling, and predefined action rules were rare, limiting confidence in use beyond the tested context. By showing whether the available evidence supports the intended comparison, the framework distinguishes defensible use from cases requiring recalibration and re-evaluation, a narrower claim, or withholding. It thereby makes clear which qNTA results can inform cross-matrix monitoring, interlaboratory comparison, or risk prioritization and which should not.
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