The Total Oxidizable Precursor (TOP) Assay as a Forensic Tool for Per- and Polyfluoroalkyl Substances (PFAS) Source Apportionment

Abstract

Per-and polyfluoroalkyl substances (PFASs) are a class of synthetic, organic chemicals that contaminate drinking water and natural ecosystems. PFAS source apportionment is challenging because there are many sources, and standard analytical methods quantify fewer than 100 of the thousands of PFASs in commerce. The total oxidizable precursor (TOP) assay augments the number of PFASs that can be quantified and is increasingly incorporated into routine site investigation. Here we examine the ability of the TOP assay to identify PFAS sources, including aqueous film-forming foam (AFFF) impacted sites, municipal wastewater treatment plants (WWTPs), and municipal solid waste landfills in 145 samples from 46 locations and three countries. The bootstrapped mean composition of PFASs from each source was dominated by precursors, particularly in samples from WWTPs where precursors that form short-chain perfluoroalkyl carboxylates during the TOP assay were most common. Compared to when TOP assay data were excluded, inclusion of TOP assay data in dimension-reducing algorithms, such as principal component analysis (PCA), improved separation among sources. We converted the PCA tool into a web application that allows users to initiate PFAS source apportionment efforts on data from sites where contaminant sources are unknown.

Oxidative Transformation of Nafion-Related Fluorinated Ether Sulfonates: Comparison with Legacy PFAS Structures and Opportunities of Acidic Persulfate Digestion for PFAS Precursor Analysis

“…TP2 is another novel indicator for PFESAs with a –O–CF 2 CF 2 –SO 3 – terminal, a common structure shared in Nafion-related (Figure ), F-53B, and other novel structural analogues. ,, Previous studies also identified other PFAS transformation patterns under HO • oxidation, such as the exclusive formation of C 7 F 15 –COO – from C 8 F 17 –SO 2 NH 2 and the dominating formation of – OOC–C n –1 F 2 n –2 –COO – from H–CF 2 –C n –1 F 2 n –2 –COO – (Figure d) . We recommend (i) pretreating the samples with both HO • and SO 4 – • (and sequential treatment, if needed) before target PFAS analysis, (ii) adding more known structures (e.g., – OOC–C n F 2 n –COO – , ether carboxylates/sulfonates, and other commercially available PFAS chemicals) to the target list of TOP assay, (iii) using advanced mass spectrometry methodologies, data processing algorithms, and additional spectroscopy methods (e.g., 19 F NMR) to assist structural determination, and (iv) modifying the existing methodologies with new structural transformation mechanisms. In order to satisfy the imminent need for the detection, monitoring, and treatment of “non-legacy” PFAS pollutants, it is imperative to expand our understanding of structure-transformation relationships for emerging PFAS chemicals. − , The elucidation of additional transformation pathways for SO 4 – • oxidation is equally important and intriguing to environmental chemists.…”

“… 5 , 6 , 36 Previous studies also identified other PFAS transformation patterns under HO • oxidation, such as the exclusive formation of C 7 F 15 –COO – from C 8 F 17 –SO 2 NH 2 15 and the dominating formation of – OOC–C n –1 F 2 n –2 –COO – from H–CF 2 –C n –1 F 2 n –2 –COO – ( Figure 2 d). 18 We recommend (i) pretreating the samples with both HO • and SO 4 – • (and sequential treatment, if needed) before target PFAS analysis, (ii) adding more known structures (e.g., – OOC–C n F 2 n –COO – , ether carboxylates/sulfonates, and other commercially available PFAS chemicals) to the target list of TOP assay, (iii) using advanced mass spectrometry methodologies, 37 data processing algorithms, 38 and additional spectroscopy methods (e.g., 19 F NMR) to assist structural determination, and (iv) modifying the existing methodologies with new structural transformation mechanisms. In order to satisfy the imminent need for the detection, monitoring, and treatment of “non-legacy” PFAS pollutants, it is imperative to expand our understanding of structure-transformation relationships for emerging PFAS chemicals.…”

The Future of Municipal Wastewater Reuse Concentrate Management: Drivers, Challenges, and Opportunities

“…A key challenge with industrial pretreatment programs is that the responsibility of enforcement falls on the wastewater municipality, which may lack the resources and legal authority needed to ensure sufficient compliance, particularly in the case of unregulated or emerging contaminants . To aid municipalities, research is needed to develop forensic methods for tracing the source of micropollutants that are accurate, timely, and affordable …”

“…113 To aid municipalities, research is needed to develop forensic methods for tracing the source of micropollutants that are accurate, timely, and affordable. 114 The third recommendation to reduce the costs for reused municipalities is strengthening relations with the public they serve. Water resources may hold significance for people for a wide range of reasons, including water supply, recreation, wildlife habitat, and cultural.…”

Applications of Artificial Intelligence, Machine Learning, and Data Analytics in Water Environments

“…Other contributions introduce novel methodologies that combine ML with statistical approaches to address various environmental problems, such as sewer overflow pollution abatement, fault detection in water and wastewater treatment, , an assay for source apportionment of per- and polyfluorinated substances (PFAS), detection of freshwater algae, and influent water data . Beyond water quality, ML has been applied to model water quantity, exploring dominant factors influencing urban industrial wastewater discharges, model energy consumption of wastewater treatment, identify endocrine-active pollutants in the organic Unregulated Contaminant Monitoring Rule (UCMR 1–4) and their toxic potentials, and employ quantitative biodescriptors to predict in vivo toxicity …”