S1. Additional details on model input data, parameter estimation, and model development (PDF) S2. Model input data and supplemental results (XLSX) S3. Model parameters assembled for the study (XLSX) Link: The portable workflow developed for this work. This dataset is associated with the following publication: Dawson, D., H. Fisher, A. Noble, Q. Meng, A. Doherty, Y. Sakano, D. Vallero, R. Tornero-Velez, and E. Cohen-Hubal. Assessment of Non-Occupational 1,4-Dioxane Exposure Pathways from Drinking Water and Product Use. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 56(8): 5266-5275, (2022).

Model input data in InputData.xls. Table and figure data in stored_results.xls. This dataset is associated with the following publication: Burkhardt, J., B. Burkhart, and F. Shang. Modeling Nicotine-Induced Chlorine Loss in Drinking Water Using Updated EPANET-MSX. JOURNAL OF ENVIRONMENTAL ENGINEERING. American Society of Civil Engineers (ASCE), Reston, VA, USA, 149(12): 04023086, (2023).

We used exposure data collected for a previous study of DBPs to evaluate how different sources of information impact trihalomethane (THM) exposure estimates, Specifically, we compared gestational exposure estimates to THMs based on water utility monitoring data alone, statistical imputation of daily concentrations to incorporate temporal variability, and personal water consumption and use (bathing and showering). We used Spearman correlation coefficients and ranked kappa statistics to compare exposure classifications. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Data that CDC collects or holds must be available for data sharing within a year after the data are evaluated for quality and shared with any partners in data collection activity. Because NBDPS data contain PII, NBDPS data are not released publicly. Instead, they are available via a special use agreement. Qualified researchers can be granted access to NBDPS data for analysis through collaboration with one of the Centers for Birth Defects Research and Prevention. The procedure for applying for access to NBDPS data can be found on the NBDPS Public Access Procedures web site: https://www.cdc.gov/ncbddd/birthdefects/nbdps-public-access-procedures.html. Format: This research was conducted with data collected by the CDC-sponsored National Birth Defects Prevention Study (NBDPS). These data include birth data and geocoded residential addresses before and during pregnancy. This dataset is associated with the following publication: Luben, T., R. Shaffer, E. Kenyon, W. Nembhard, K. Weber, J. Nuckols, and J. Wright. Comparison of trihalomethane exposure assessment metrics in epidemiologic analyses of reproductive and developmental outcomes. Journal of Exposure Science and Environmental Epidemiology. Nature Publishing Group, London, UK, 34: 115-125, (2024).

Dataset summarizes the results of a study to examine de facto reuse of contaminants of emerging concern

Underlying modeling outputs used to generate Figures in the manuscript and supplemental figures. This dataset is associated with the following publication: Stanek, L., J. Xue, C. Lay, E. Helm, T. Speth, D. Lytle, M. Schock, and V. Zartarian. Modeled Impacts of Drinking Water Lead Reduction Scenarios on Children’s Exposures and Blood Lead Levels. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 54(15): 9474-9482, (2020).

Simulation results for one dimensional advection-dispersion-reaction modeling withing drinking water distribution system. Analytical solutions are provided when possible.

This dataset compared the de facto reuse percentage modeled for the 22 surface water sites sampled in Phase II of the drinking water project and the organic chemical data generated as part of the project. This dataset is associated with the following publication: Nguyen , T., P. Westerhoff , E. Furlong, D. Kolpin, A. Batt, H. Mash, K. Schenck, J.S. Boone, J. Rice, and S. Glassmeyer. Modeled De Facto Reuse and Contaminants of Emerging Concern in Drinking Water Source Waters. JOURNAL OF THE AMERICAN WATER WORKS ASSOCIATION. American Water Works Association, Denver, CO, USA, 110(4): E2-E18, (2018).

This dataset compared the de facto reuse percentage modeled for the 22 surface water sites sampled in Phase II of the drinking water project and the organic chemical data generated as part of the project. This dataset is associated with the following publication: Nguyen , T., P. Westerhoff , E. Furlong, D. Kolpin, A. Batt, H. Mash, K. Schenck, J.S. Boone, J. Rice, and S. Glassmeyer. Modeled De Facto Reuse and Contaminants of Emerging Concern in Drinking Water Source Waters. JOURNAL OF THE AMERICAN WATER WORKS ASSOCIATION. American Water Works Association, Denver, CO, USA, 110(4): E2-E18, (2018).

The initial analysis set was downloaded from https://www.waterqualitydata.us/ using queries described in the file load_water_data.py, hosted at https://github.com/USEPA/EcoSEEM-Consensus-Model-for-Chemicals-in-Surface-Water/tree/master/observation_data. The representative concentration ranges and bioactivity:exposure ratio results are available at the same GitHub repo in the file all_chem_res.csv. This dataset is associated with the following publication: Sayre, R., R. Setzer, M. Serre, and J. Wambaugh. Characterizing surface water concentrations of hundreds of organic chemicals in United States for environmental risk prioritization. Journal of Exposure Science and Environmental Epidemiology. Nature Publishing Group, London, UK, 33: 610-619, (2023).