FluorineID · FluorineID: Bridging identity and quantity – Unraveling the unknown fluorine content in environmental samples via quantitative non-target screening (qNTS)

Per- and polyfluoroalkyl substances (PFAS) encompass potentially millions of synthetic compounds that are widely used in modern society. These “forever chemicals” are extremely persistent, harmful to health, and are widespread globally. Despite advancements in their analysis, high levels of unknown fluorine—termed “PFAS dark matter”—persist in the environment, indicating that most fluorinated compounds remain unidentified. ""PFAS dark matter"" can originate not only from PFAS but also from many other emerging fluorinated compounds, including ionic liquids. Cutting-edge non-target screening (NTS) with high-resolution mass spectrometry (HRMS) can detect thousands of chemicals like PFAS but is typically only qualitative and limited in scope. FluorineID aims to address this gap and to unravel the “PFAS dark matter” by developing computational quantitative NTS (qNTS) methods that (1) integrate key chromatographic separation platforms for broader chemical space coverage, (2) prioritize the millions of fluorinated compounds in the online database PubChem for efficient and comprehensive identification, and (3) apply machine learning to quantify fluorinated compounds. The combination of individually identified and quantified fluorinated compounds with total fluorine measurements will allow verification via fluorine mass balance approaches. FluorineID will advance the identification and quantification of unknown fluorinated compounds, support identifying the origin of unknown fluorine in the environment, and offer open source qNTS workflows to accelerate future community-wide identification and risk assessment of “PFAS dark matter”.""