The dataset accompanies the manuscript. The data provided include concentration data for trichloroethene, cis-dichloroethene, vinyl chloride, ethane, and ethane. Stable isotope data are provided for trichloroethene, cis-dichloroethene, vinyl chloride, methane, and dissolved carbon dioxide. Additional data are provided in the supporting information published with the article. This dataset is associated with the following publication: Wilkin, R.T., T.R. Lee, M.R. Sexton, S.D. Acree, R.W. Puls, D.W. Blowes, C. Kalinowski, J.M. Tilton, and L.L. Woods. Geochemical and Isotope Study of Trichloroethene Degradation in a Zero-Valent Iron Permeable Reactive Barrier: A Twenty-Two-Year Performance Evaluation. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 53: 296-306, (2019).

The dataset contains chromatographic traces of samples containing thioarsenic species and solubility data for disordered orpiment (arsenic sulfide). This dataset is associated with the following publication: Wilkin, R.T., R.G. Ford, L.M. Costantino, R.R. Ross, D.G. Beak, and K.G. Scheckel. Thioarsenite Detection and Implications for Arsenic Transport in Groundwater. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 53(20): 11684-11693, (2019).

This dataset includes the elemental composition of 28 hydrant flush solids collected during routine hydrant flushing events in some of the utilities studied. The link to all remaining raw data (publicly accessible through the US EPA's Arsenic Demo website) is also provided. This dataset is associated with the following publication: Triantafyllidou, S., D. Lytle, A. Chen, L. Wang, T. Sorg, and C. Muhlen. Patterns of Arsenic Release in Distribution Systems. AWWA Water Science. John Wiley & Sons, Inc., Hoboken, NJ, USA, 1(4): e1149, (2019).

These data contain concentrations of tetrachloroethylene in groundwater samples collected from 2011 to 2015 by the EPA. These data are a subset of all the groundwater at the site. Samples were collected using direct-push technology. In order to protect personally identifiable information (PII), all data collected by the U.S. Environmental Protection Agency do not contain spatial information. Please contact the U.S. Environmental Protection Agency for permission and access to spatial information for these samples. These data support the following publication: Wilson, J.L., Limmer, M.A., Samaranayake, V.A., Burken, J.G., 2018, Phytoforensics: trees as bioindicators of potential indoor exposure via vapor intrusion: PLoS ONE, v. 13, no. 2. DOI: 10.1371/journal.pone.0193247.

This dataset includes data collected to validate a method of analysis for arsenic species As(III), As(V), dimethylarsinate (DMA), and monomethylarsonate (MMA) in surface water and groundwater samples. It also includes site information and water chemistry for samples used in the validation and used for other studies of arsenic species in groundwater. It includes speciation data measured at multiple time points to establish or verify hold times and stability of As species in surface water and groundwater samples.

This dataset includes data collected to validate a method of analysis for arsenic species As(III), As(V), dimethylarsinate (DMA), and monomethylarsonate (MMA) in surface water and groundwater samples. It also includes site information and water chemistry for samples used in the validation and used for other studies of arsenic species in groundwater. It includes speciation data measured at multiple time points to establish or verify hold times and stability of As species in surface water and groundwater samples.

Contains data related to Arsenate and Arsenite injections into chlorinated distribution system simulator. Contains data related to model to predict arsenate and arsenite aqueous and wall concentrations within a chlorinated water distribution system. This dataset is associated with the following publication: Burkhardt, J., J. Szabo, S. Klosterman, J. Hall, and R. Murray. Modeling Fate and Transport of Arsenic in a Chlorinated Distribution System. ENVIRONMENTAL MODELLING AND SOFTWARE. Elsevier Science Ltd, New York, NY, USA, 93(1): 322-331, (2017).

The spreadsheet contains mineralogical and solubility data for the uranyl minerals: metaschoepite and uranophane. This dataset is associated with the following publication: Stanley, D.M., and R.T. Wilkin. Solution equilibria of uranyl minerals: Role of the common groundwater ions calcium and carbonate. JOURNAL OF HAZARDOUS MATERIALS. Elsevier Science Ltd, New York, NY, USA, 377: 315-320, (2019).

The objective of this research was to evaluate the performance of five arsenic adsorptive media technology of full-scale drinking water treatment systems in the USEPA Arsenic Demonstration Program (ADP) that were found to simultaneously remove other co-occurring inorganic contaminants. The datasets presented here are the figures included in the referenced journal article. This dataset is associated with the following publication: Sorg, T., A. Chen, L. Wang, and D. Lytle. Removing co-occurring contaminants of arsenic and vanadium with full-scale arsenic adsorptive media systems. JOURNAL OF WATER SUPPLY: RESEARCH AND TECHNOLOGY - AQUA. IWA Publishing, London, UK, ( ): 2021148, (2021).

This data release contains data used to develop models and maps that estimate probabilities of exceeding various thresholds of arsenic concentrations in private domestic wells throughout the conterminous United States. Three boosted regression tree (BRT) models were developed separately to estimate the probability of private well arsenic concentrations exceeding 1, 5, and 10 micrograms per liter (µg/L). A random forest (RF) model was developed to estimate the most probable arsenic concentration category (≤5, >5 to ≤10, or >10 µg/L). The models use arsenic concentration data from private domestic wells located throughout the conterminous United States and independent variables that are available as geospatial data. The models were used to produce maps that are included in this data release. The model input data (predictor variables) that were used to make the maps are within a zipped folder (Map_Input_Data.zip) that contains 85 tif-raster files, one for each model predictor variable. The map probability estimates that are outputs from the model are in a zipped folder (Map_Output_Data.zip) that contains 13 tif-raster files, one model estimate map for each of the BRT models and four for the RF model, as well as 2 confidence interval maps for each BRT model.