All relevant data are within the manuscript, its Supporting Information files, and the httk R software package v1.9.2. This dataset is associated with the following publication: Honda, G., R. Pearce, L. Pham, R. Setzer, B. Wetmore, N. Sipes, J. Gilbert, B. Franz, R. Thomas, and J. Wambaugh. Using the Concordance of In Vitro and In Vivo Data to Evaluate Extrapolation Assumptions. PLoS ONE. Public Library of Science, San Francisco, CA, USA, 14(5): 1-33, (2019).

This record describes Bio-Optics data collected from the Marine National Facility (MNF) RV Investigator voyage: IN2016_V05, titled: "The Great Barrier Reef as a significant source of climatically relevant aerosol particles." The data were collected as part of the supplementary project titled: "Biogeochemical and optical properties of the Coral Sea and Queensland Shelf." The voyage, departing from and returning to Brisbane, QLD, took place between September 26 to October 24, 2016. The data can be used for Ocean Colour sensor validation. Parameters measured are the concentration of chlorophyll and carotenoid pigments, total suspended solids, and absorption coefficients.

EPA Draft Method C QPCR cycle threshold (Ct) measurements of standardized reference materials and blinded test samples as described in D-EMMD-MEB-025-QAPP-01 and Journal article. This dataset is associated with the following publication: Aw, T., M. Sivaganesan, S. Briggs, E. Dreelin, A. Aslan, S. Dorevitch, A. Shrestha, N. Isaacs, J. Kinzelman, G. Kleinheinz, R. Noble, R. Rediske, B. Scull, S. Rosenberg, B. Weberman, T. Sivy, B. Southwell, S. Siefring, K. Oshima, and R. Haugland. Evaluation of multiple laboratory performance and variability in analysis of recreational freshwaters by a rapid Escherichia coli qPCR method (Draft Method C). WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 156: 465-474, (2019).

Files are an overview of all data acquired in the study examining source and treated drinking water. This dataset is associated with the following publication: Glassmeyer , S., E. Furlong, D. Kolpin, A. Batt , B. Benson , S. Boone , O. Conerly , M. Donohue , D. King , M. Kostich , H. Mash , S. Pfaller , K. Schenck , J.E. Simmons , E. Varughese , S. Vesper , E. Villegas , and V. Wilson. Nationwide reconnaissance of contaminants of emerging concern in source and treated drinking waters of the United States. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 581582: 909-922, (2017).

The NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Bidirectional Reflectance Distribution Function (BRDF) and Albedo Nadir BRDF-Adjusted Reflectance Daily Global 0.05 Degree Climate Modeling Grid (CMG) Version 1 product (VNP43C4) is derived from the 30 arc second CMG VNP43D Version 1 product suite. VNP43C3 is generated daily from all available high-quality reflectance data over a 16-day moving window emphasizing the ninth day of the retrieval period, which is reflected in the Julian date in the filename. The VNP43 algorithm uses the RossThick/Li-Sparse-Reciprocal (RTLSR) semi-empirical kernel-driven BRDF model, with the three kernel weights from VNP43C1 to compute NBAR values for the VIIRS Day/Night band (DNB), and moderate resolution bands M1 through M5, M7, M8, M10, and M11. The algorithm removes view angle effects from directional reflectances to model the values as if they were collected from a nadir view at local solar noon. The quality and inversion status of the majority of the underlying 30 arc second pixels is provided as well as the percentage of the underlying pixels that were present or were snow covered. Users are encouraged to assess the quality information before using the BRDF/Albedo data. This 0.05 degree (5,600 meters at the equator) CMG product covers the entire globe for use in climate simulation models. The VNP43C3 product includes 10 layers containing NBAR values for VIIRS DNB and moderate resolution bands M1 through M5, M7, M8, M10, and M11. Along with the NBAR data for the 10 bands are five ancillary layers for uncertainty, quality, local solar noon, percent finer resolution inputs, and snow cover. A low-resolution browse image is also available showing NBAR bands M5, M4, and M3 as a red, green, blue (RGB) image in JPEG format.

Data from pharmaceutical paper. This dataset is associated with the following publication: Furlong, E., A. Batt, S. Glassmeyer, M. Noriega, D. Kolpin, H. Mash, and K. Schenck. Nationwide reconnaissance of contaminants of emerging concern in source and treated drinking waters of the United States: Pharmaceuticals. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 579: 1629–1642, (2017).

Measurements of gamma-BHC (Lindane) collected at Coalinga Canal. Currently collected twice a year, previously collected quarterly. Access further information for this data set by contacting Bureau of Reclamation, California-Great Basin Region, Environmental Affairs Division (CGB-157). See ResultAttributes for STAFF_GAUGE, SMPL_DEPTH, SMPL_CATEGORY_NAME, METHOD_CODE, RESULT_RL, RESULT_RL-UNIT_STD_NAME, RESULT_MDL, RESULT_MDL-UNIT_STD_NAME, USBR_QA_SUBTYPE_NAME, USBR_QULFR_DESCRIPTION. STAFF_GAUGE is the water height in decimal feet measured by gauge (e.g., 15.2). SMPL_DEPTH is the vertical depth at which sample is collected (e.g., 0 - 15 cm). For water samples: depth below water/air interface. For sediment and soil samples: depth below water/solid or air/solid interface. SMPL_CATEGORY_NAME is the category type of sample (e.g., Composite). METHOD_CODE is the name of method used to obtain result (e.g., EPA 200.8). RESULT_RL is the result reporting limit (accounting for dilution) (e.g., 0.02). RESULT_RL-UNIT_STD_NAME is the unit associated with RESULT_RL (e.g., mg/L). RESULT_MDL is the result method detection limit (e.g., 0.007). RESULT_MDL-UNIT_STD_NAME is the unit associated with RESULT_MDL (e.g., mg/L). USBR_QA_SUBTYPE_NAME is the quality control type of the sample (e.g., USBR_BLANK_SPIKE). USBR_QULFR_DESCRIPTION is the quality assurance description (if any) (e.g., Result may have a high bias.).