Data processing was conducted using the Anaconda distribution of Python 3.9 and associated libraries. Jupyter notebooks are available at https://github.com/patlewig/nts_pfas. Datasets supporting the manuscript are accessible at https://doi.org/10.23645/epacomptox.26524327. This dataset is associated with the following publication: Patlewicz, G., R. Judson, A. Williams, T. Butler, S. Barone, K. Carstens, J. Cowden, J. Dawson, S. Degitz, K. Fay, A. Lowit, S. Padilla, K. Friedman, M. Phillips, D. Turk, J. Wambaugh, B. Wetmore, and R. Thomas. Development of chemical categories for per- and polyfluoroalkyl substances (PFAS) and the proof-of-concept approach to the identification of potential candidates for tiered toxicological testing and human health assessment. Computational Toxicology. Elsevier B.V., Amsterdam, NETHERLANDS, 31: 100327, (2024).

Data were collected to develop a comprehensive, generalized approach to predict the retention of per- and polyfluoroalkyl substances (PFAS) from aqueous film forming foam (AFFF) by a soil matrix as a function of PFAS molecular and soil physiochemical properties was developed. An AFFF with 34 major PFAS (12 anions and 22 zwitterions) was added to uncontaminated soil in one-dimensional saturated column experiments and PFAS mass retained was measured. PFAS mass retention was described using an exhaustive statistical approach to generate a poly-parameter quantitative structure-property relationship (ppQSPR). This dataset is not publicly accessible because: The senior author generated the data and has the data. At the time he was a graduate student at Oregon State University. It can be accessed through the following means: By contacting the senior author at: Thomas.Wanzek@Geosyntec.com. Format: Likely in excel spreadsheets. This dataset is associated with the following publication: Wanzek, T., J. Stults, M. Johnson, J. Field, and M. Kleber. Role of Mineral−Organic Interactions in PFAS Retention by AFFF-Impacted Soil. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 57(13): 5231-5242, (2023).

Per- and polyfluoroalkyl substances (PFAS) and related chemical and physical data are presented from shallow soil and groundwater at two sites in New Hampshire. The two sites, the former Brentwood Fire Training Area and White Farm, were selected because materials known to contain PFAS were used at each site. White Farm is an active farm where biosolids have been applied for several years. At the former Brentwood Fire Training Area, PFAS-containing aqueous film-forming foams were applied as part of regular fire training exercises. At each site, soil samples were collected in a gridded pattern over the site. Soil horizons within the sampling intervals were described using the National Soil Survey Center Natural Resources Conservation Service U.S. Department of Agriculture Field Book for Describing and Sampling Soils (Schoeneberger and others, 2012). Analyses included 36 PFAS compounds, 36 PFAS compounds post-total oxidizable precursor assay (TOPA), total organic carbon (TOC), moisture content, pH, autoclaved-citrate extractable protein, grain size, major ions and other physical and physicochemical parameters. Groundwater samples were collected and analyzed for PFAS during two sampling events at each site from temporary wells, existing monitoring wells, and/or pushpoint samplers. Additionally, a lysimeter was installed at the center of each site and a composite sample through the duration of each water sampling event (approximately 7 days) was collected. Quality control samples included source-solution blanks, equipment blanks, and replicates. Reference: Schoeneberger, P.J., Wysocki, D.A., Benham, E.C., and Soil Survey Staff, 2012, Field book for describing and sampling soils, Version 3.0: Natural Resources Conservation Service, National Soil Survey Center, Lincoln, NE.

Supporting information for the NIST Internal Report entitled: Per- and Polyfluoroalkyl Substances - Non-Targeted Analysis Interlaboratory Study Final Report. The files include four comma-separated value (CSV) text files, three of the CSV text files contain summary tables of all per and polyfluoroalkyl substances (PFAS) detected in the three test samples from the interlaboratory report (sample_a_table.csv, sample_b_table.csv, sample_c_table.csv) including the individual laboratory reported identities and their associated identification confidence levels. The final CSV text file, all_pfas_table.csv, contains a summary of all PFAS detected in all of the samples and the highest level of confidence reported in each of the three test samples. These files are meant to supplement the abbreviated tables presented in the Final Report that reported the top 20 PFAS in each of the three test samples. These tables were produced through the analysis of the individual laboratory results and aggregation of the results by the reported PFAS identity.The Microsoft Excel file, PFASNTAILS_Reporting Form.xlsx, is the example form that was used by all participating laboratories to report their results. It is provided to provide readers of the interlaboratory report with context to the information that was provided by each laboratory.

Current studies on nontarget analysis and toxicities of PFASs are disconnected, due to the challenges posed by the large numbers (>1,000) and diverse structures of PFASs. The SECC method provides a high-throughput experimental way to tackle the challenge of prioritizing PFASs according to key proteins, especially when their authentic standards are not available. While this study is focused on hL-FABP due to its critical role in regulating the toxicokinetics of PFASs, the protein-centric method could also be adapted to screen PFASs binding to other key proteins, such as PPARs. Computational toxicology is the predominant strategy for high-throughput predictions of toxicities of chemical contaminants. This dataset is not publicly accessible because: Data generated and owned by external academic lab with chemicals provided by the EPA under an MTA. EPA's contribution was assisting in manuscript writing. It can be accessed through the following means: Contact the Corresponding author: Hui Peng, e-mail: hui.peng@utoronto.ca, Department of Chemistry, University of Toronto, Toronto, Ontario, M5S3H6, Canada. Format: Not available. This dataset is associated with the following publication: Yang, D., J. Han, D. Ross Hall, J. Sun, J. Fu, S. Kutarna, K. Houck, C. LaLone, J. Doering, C. Ng, and H. Peng. Nontarget Screening of Per- and Polyfluoroalkyl Substances Binding to Human Liver Fatty Acid Binding Protein. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 54(9): 5676-5686, (2020).

The file contains raw data measurement conducted by EPA's contractor. The data have the names of the samples and the concentration of 26 PFAS compounds that were analyzed. This dataset is associated with the following publication: Chen, Y., H. Zhang, Y. Liu, J. Bowden, T. Tolaymat, T. Townsend, and H. Solo-Gabriele. Concentrations of perfluoroalkyl and polyfluoroalkyl substances before and after full-scale landfill leachate treatment. WASTE MANAGEMENT. Elsevier Science Ltd, New York, NY, USA, 153: 110-120, (2022).

Dataset includes summary statistics (mean, standard error, sample size) for all endpoints measured and reported from the the experiments described in the published manuscript. This dataset is associated with the following publication: Conley, J., C. Lambright, N. Evans, J. Bangma, J. Ford, D. Jenkins-Hill, E. Medlock Kakaley, and L. Gray. Maternal and neonatal effects of maternal oral exposure to perfluoro-2-methoxyacetic acid (PFMOAA) during pregnancy and early lactation in the Sprague-Dawley rat. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 58(2): 1064-1075, (2024).

PFAS in Landfill Organics. This dataset is associated with the following publication: Saha, B., M. Ateia, T. Tolaymat, S. Fernando, J.R. Varghese, D. Golui, A.N. Bezbaruah, J. Xu, N. Aich, J. Briest, and S.M. Iskander. The unique distribution pattern of PFAS in landfill organics. JOURNAL OF HAZARDOUS MATERIALS. Elsevier Science Ltd, New York, NY, USA, 479: 135678, (2024).