Perfluorooctanoic acid (PFOA) precursors are a class of compounds that are commonly released into the environment through aqueous film-forming foams (AFFFs) and are known to decompose into PFOA. PFOA is one of the most used per- and polyfluoroalkyl substances (PFAS), a class of highly persistent synthetic chemicals. Exposure to PFOA through environmental contamination has been linked to a variety of health concerns, and precursors from AFFFs are sources of PFOA contamination. Although PFOA precursors are often not considered, studies have demonstrated that they contribute to the overall levels of PFOA contamination, meaning that the ability to detect them is important for removing PFOA from the environment. However, the detection of PFOA precursors is limited to mass spectrometry methods, which are expensive and time-consuming. While higher-throughput methods have been developed for PFOA, no high-throughput sensing platforms have been reported for PFOA precursors. To address this problem, we developed a fluorescent sensor platform for detection and differentiation of three specific PFOA precursors, both from each other and from PFOA itself. We demonstrate that dynamic combinatorial libraries (DCLs) made up of dithiol monomers and templated with a solvatochromic fluorophore can be used to form a sensor array that achieves this detection and differentiation at low nanomolar, environmentally relevant concentrations. We can discriminate individual PFOA precursors from each other and perfluoroalkyl carboxylic acids of varying chain lengths, mixtures of varying ratios of the precursor to PFOA, and use our system in complex samples extracted from soil spiked with the precursors. To our knowledge, this is the first report of a fluorescence-based method for the detection and differentiation of PFOA precursors.
Tripp et al. (Tue,) studied this question.