Three recent IARC Working Groups pioneered inclusion of the US Environmental Protection Agency (EPA) ToxCast program high-throughput screening (HTS) data to supplement other mechanistic evidence. In Monograph V110, HTS profiles were compared between perfluorooctanoic acid (PFOA) and prototypical activators across multiple nuclear receptors. For Monograph V112-113, HTS assays were mapped to 10 key characteristics of carcinogens identified by an IARC expert group, and systematically considered as an additional mechanistic data stream. This dataset is not publicly accessible because: The data is generated by external authors from existing public data sources. It can be accessed through the following means: Data is available in existing public data sources. Format: N/A. This dataset is associated with the following publication: Chiu, W., K. Guyton, M. Martin, D. Reif, and I. Rusyn. (ALTEX) Use of High-throughput in vitro toxicity screening data in cancer hazard evaluations by the IARC Monograph Working Groups. ALTEX. Society ALTEX Edition, Kuesnacht, SWITZERLAND, 35(1): 51-64, (2018).
This study evaluated two anti-angiogenic agents, 5HPP-33 and TNP-470, across the ToxCastDB HTS assay platform and anchored the results to complex in vitro functional assays: the rat aortic explant assay (AEA), rat whole embryo culture (WEC), and the zebrafish embryotoxicity (ZET) assay. This dataset is not publicly accessible because: no EPA data; all the data generated by external organizations; EPA coauthors. It can be accessed through the following means: Data generated by external organizations. Format: N/A. This dataset is associated with the following publication: Ellis-Hutchings, R., R. Settivari, A. McCoy, N. Kleinstreuer, J. Franzosa, T. Knudsen, and E. Carney. (REPRODUCTIVE TOXICOLOGY) EMBRYONIC VASCULAR DISRUPTION ADVERSE OUTCOMES: LINKING HIGH THROUGHPUT SIGNALING SIGNATURES WITH FUNCTIONAL CONSEQUENCES. REPRODUCTIVE TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 70: 82-96, (2017).
The paper has data generated by NIH and the EPA coauthors provided input into the preparation of the manuscript. This dataset is not publicly accessible because: Data was not collected in EPA labs or paid for by EPA. It can be accessed through the following means: Data generated by NIH. Format: N/A. This dataset is associated with the following publication: Lynch, C., S. Sakamuru, R. Huang, D.A. Stavea, L. Varticovski, G.L. Hagar, R.S. Judson, K.A. Houck, N.C. Kleinstreuer, W. Casey, R.S. Paules, A. Simeonov, and M. Xia. (Toxicology) Identifying Environmental Chemicals as Agonists of the Androgen Receptor by Applying a Quantitative High-throughput Screening Platform. TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 385: 48-58, (2017).
THIS DATA ASSET NO LONGER ACTIVE: This is metadata documentation for the Region 7 Air Compliance Complaint Database (ACCD) which logs all air pollution complaints received by Region 7. It contains information about the complaint along with how the complaint was addressed. The Air and Waste Management Division is the primary managing entity for this database. This work falls under objectives for EPA's 2003-2008 Strategic Plan (Goal 1) for Clean Air & Global Climate Change, which are to achieve healthier outdoor air.
The tool summarises the relevant climate-related risks and opportunities for banks, insurers and asset managers based on the business activities, products, or risks of the firm and the materiality of different lending exposure types, underwriting classes, asset classes, and economic sectors for the firm. The tool can generate two types of report: an Institutional Report which gives a report tailored to your institution a Sector Report which allows users to see the content for an individual sector
The Climate Financial Risk Forum (CFRF) list of data and tools providers is a collection of currently-available climate risk data, tools and products for financial institutions. It has been created to serve as an illustrative list of current climate risk offerings, highlighting the variety and scope of what is currently available in the marketplace. This is to ultimately support research and decision making around climate risk product procurement. The database has been designed to provide practitioners with relevant information in a digestible and searchable format.
We created a consensus, meta-model using the Systematic Empirical Evaluation of Models framework in which the predictors of exposure were combined by pathway and weighted according to predictive ability for chemical intake rates inferred from human biomonitoring data for 114 chemicals. This dataset is associated with the following publication: Ring, C., J. Arnot, D. Bennett, P. Egeghy, P. Fantke, L. Huang, K. Isaacs, O. Jolliet, K. Phillips, P. Price, H. Shin, J. Westgate, R. Setzer, and J. Wambaugh. Consensus Modeling of Median Chemical Intake for the U.S. Population Based on Predictions of Exposure Pathways. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 53(2): 719-732, (2019).
All data is generated by the external authors or taken from public data sources. This dataset is not publicly accessible because: Data was not collected in EPA labs or paid for by EPA. It can be accessed through the following means: All data is generated by the external authors or taken from public data sources. Format: N/A. This dataset is associated with the following publication: Mahapatra, D., J.A. Franzosa, K. Roell, M.A. Kuenemann, K.A. Houck, D.M. Reif, D. Fourches, and S.W. Kullman. Confirmation of High-Throughput screening data and novel mechanistic insights into VDR-xenobiotic interactions by orthogonal assays. Scientific Reports. Nature Publishing Group, London, UK, 8(8883): 1-16, (2018).
The data contained in this worksheet provides the Median Fluorescence Intensity (MFI) readings from saliva samples serially collected during the BoquerĂłn Beach, Puerto Rico study. Samples were analyzed using the bead-based multiplex immunoassay to assess immunoconversions in the beachgoers to multiple waterborne pathogens. In the study, we collected an initial sample (S1) at the beach and the remaining samples (S2 and S3) were self-collected by participants 10 -14 and 30 - 40 days later, respectively. This dataset is associated with the following publication: Simmons, K.J., T. Eason, C.L. Curioso, S. Griffin, M.K.D. Ramudit, K. Oshima, E. Sams, T. Wade, A. Grimm, A. Dufour, and S. Augustine. Visitors to a Tropical Marine Beach Show Evidence of Immunoconversions to Multiple Waterborne Pathogens. Frontiers in Public Health. Frontiers, Lausanne, SWITZERLAND, issue}: 231, (2019).
Data for publication Turley et al. "Applying the RISK21 approach to assess predictivity of new approach methodologies in toxicity testing and exposure assessment: a case study on food contact chemicals". Includes food concentration predictions from the model of Biryol et al. (2017) and SHEDS-HT exposure predictions. This dataset is associated with the following publication: Turley, A., K. Isaacs, B. Wetmore, A. Karmaus, M. Embry, and M. Krishan. Incorporating new approach methodologies in toxicity testing and exposure assessment for tiered risk assessment using the RISK21 approach: Case studies on food contact chemicals. FOOD AND CHEMICAL TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 134: 110819, (2019).
THIS DATA ASSET NO LONGER ACTIVE: This is metadata documentation for the Region 7 Drycleaner Database (R7DryClnDB) which tracks all Region7 drycleaners who notify Region 7 subject to Maximum Achievable Control Technologiy (MACT) standards. The Air and Waste Management Division is the primary managing entity for this database. This work falls under objectives for EPA's 2003-2008 Strategic Plan (Goal 4) for Healthy Communities & Ecosystems, which are to reduce chemical and/or pesticide risks at facilities.
This dataset is the raw Luminex antibody responses to six common waterborne pathogens reported in MFI (Median Fluorescence Intensity) units. This dataset is associated with the following publication: Augustine , S., T. Eason , K. Simmons, C. Curioso, S. Griffin , M. Ramudit, and T. Plunkett. Developing a Salivary Antibody Multiplex Immunoassay to Measure Human Exposure to Environmental Pathogens. Journal of Visualized Experiments. JoVE, Somerville, MA, USA, 115: e54415, (2016).
data for figures 1-8 in journal article "Assessment of port-related air quality impacts: geographic analysis of population", International Journal of Environment and Pollution, 58, 231-250, (2015). This dataset is associated with the following publication: Arunachalam , S., H. Brantley , T. Barzyk , G. Hagler , V. Isakov , S. Kimbrough , B. Naess, N. Rice, M. Snyder, K. Talgo, and A. Venkatram. Assessment of port-related air quality impacts: geographic analysis of population. INTERNATIONAL JOURNAL OF ENVIRONMENT AND POLLUTION. Inderscience Enterprises Limited, Geneva, SWITZERLAND, 58(4): 231 - 250, (2015).
Functions and data tables for simulation and statistical analysis of chemical toxicokinetics ("TK") as in Pearce et al. (2017) . Chemical-specific in vitro data have been obtained from relatively high throughput experiments. Both physiologically-based ("PBTK") and empirical (e.g., one compartment) "TK" models can be parameterized for several hundred chemicals and multiple species. These models are solved efficiently, often using compiled (C-based) code. This dataset is associated with the following publication: Pearce , R., C. Strope , W. Setzer , N. Sipes , and J. Wambaugh. (Journal of Statistical Software) HTTK: R Package for High-Throughput Toxicokinetics. Journal of Statistical Software. American Statistical Association, Alexandria, VA, USA, 79(4): 1-26, (2017).
Technical papers detailing the development of harsh environment sensors for geothermal applications. Principle Investigator is Prof. Albert P. Pisano (University of California, Berkeley). Submission includes a paper about geothermal environmental exposure testing on encapsulant and device materials in addition to a paper pertaining to MEMS Sensors for downhole monitoring of geothermal systems.
The High Production Volume Information System (HPVIS) provides access to select health and environmental effect information on chemicals that are manufactured in exceptionally large amounts.
Under the ExpoCast program, United States Environmental Protection Agency (EPA) researchers have developed a high-throughput (HT) framework for estimating aggregate exposures to chemicals from multiple pathways to support rapid prioritization of chemicals. Here, we present methods to estimate HT exposures to chemicals migrating into food from food contact substances (FCS). These methods consisted of combining an empirical model of chemical migration with estimates of daily population food intakes derived from food diaries from the National Health and Nutrition Examination Survey (NHANES). A linear regression model for migration at equilibrium was developed by fitting available migration measurements as a function of temperature, food type (i.e., fatty, aqueous, acidic, alcoholic), initial chemical concentration in the FCS (C0) and chemical properties. The most predictive variables in the resulting model were C0, molecular weight, log Kow, and food type (R2=0.71, p<0.0001). Migration-based concentrations for 1009 chemicals identified via publicly-available data sources as being present in polymer FCSs were predicted for 12 food groups (combinations of 3 storage temperatures and food type). The model was parameterized with screening-level estimates of C0 based on the functional role of chemical in FCS. By combining these concentrations with daily intakes for food groups derived from NHANES, population ingestion exposures of chemical in mg/kg-bodyweight/day (mg/kg-BW/day) were estimated. Calibrated aggregate exposures were estimated for 1931 chemicals by fitting HT FCS and consumer product exposures to exposures inferred from NHANES biomonitoring (R2=0.61, p<0.001); both FCS and consumer product pathway exposures were significantly predictive of inferred exposures. Including the FCS pathway significantly impacted the ratio of predicted exposures to those estimated to produce steady-state blood concentrations equal to in-vitro bioactive concentrations. While these HT methods have large uncertainties (and thus may not be appropriate for assessments of single chemicals), they can provide critical refinement to aggregate exposure predictions used in risk-based chemical priority–setting. This dataset is associated with the following publication: Biryol, D., C. Nicolas, J. Wambaugh, K. Phillips, and K. Isaacs. High-throughput dietary exposure predictions for chemical migrants from food contact substances for use in chemical prioritization. ENVIRONMENT INTERNATIONAL. Elsevier Science Ltd, New York, NY, USA, 108: 185-194, (2017).
The Human Exposure Database System (HEDS) provides public access to data sets, documents, and metadata from EPA on human exposure. It is primarily intended for scientists involved in human exposure studies or work requiring such data.
In zebrafish, 161 compounds were screened and 34 were identified by visual inspection as VDCs, of which 28 were confirmed as VDCs by quantitative image analysis. Testing of the zebrafish VDCs for their capacity to inhibit endothelial tube formation in the murine yolk-sac-derived endothelial cell line C166 identified 22 compounds that both disrupted zebrafish vascular development and murine endothelial in vitro tubulogenesis. This dataset is associated with the following publication: McCollum, C., J. Conde Vancells, C. Hans, M. Vazquez-Chantada, N. Kleinstreuer, T. Tal , T. Knudsen, S. Shah, F. Merchant, R. Finnell, J. Gustafsson, R. Cabrera, and M. Bondesson. (Reproductive Toxicology) Identification of vascular disruptor compounds by a tiered analysis in zebrafish embryos and mouse embryonic endothelial cells. REPRODUCTIVE TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 70: 60-69, (2017).
Insecticide Netting In this study, we focused on two types of long-lasting insecticide netting (LLIN) that have been found to be effective for managing various stored product insect pests. One is an LLIN consisting of a polyethylene netting (2 × 2 mm mesh, D-Terrence, Vestergaard, Inc., Lausanne, Switzerland) with 0.4% deltamethrin active ingredient (a.i.), while the second one is Carifend® net (40 deniers with mesh size 97 knots/cm2; BASF AG, Ludwigshafen, Germany) containing 0.34% α-cypermethrin (a.i.). Foundational Model We used a standard Lefkovitch matrix model to project population growth for Tribolium castaneum, with four life stages (e.g., egg, larva, pupa, and adult;(Lefkovitch,1965). In equation (1), the Leftkovitch matrix L matrix (4 × 4) represents the life-stage structure of T. castaneum which has an egg, larvae, pupae, and an adult, where only the adults contribute to the fecundity, F. By multiplying L with the population vector ni(t), where t is time step (e.g., generation) and i is a life stage, we obtain the resultant vector ni(t + 1), which reveals the distribution of individuals across different life stages in the subsequent time period. In equation (1), P1 represents the probability of staying in the egg stage and G1 is the probability of moving from the egg to the larval stage, P2 is the probability of staying in the larval stage, G2 is probability of moving from the larval stage to pupal stage, P3 is the probability of staying in the pupal stage, G3 is probability of moving from the pupal stage to adult, while P4 is the probability of staying in the adult stage (Figure 1). Model Parameterization and Scenarios We simulated population outcomes for up to 15 generations by using the life table data for T. castaneum using the R package popbio. Survivorship, fecundity, and transition information for each stage were derived from the literature (summarized in Table 1). The developmental duration of eggs, larvae, and pupae were 3.82 ± 0.005, 22.81 ± 0.67, and 6.24 ± 0.071 days (Kollros,1944). The average life duration of the adult used in this study was 221.16 days (Park et al., 1961). We used 94 offspring for fertility from the study Park et al.,(1965) and 99% rate of eclosion from pupae to adult. In order to explore the sensitivity of the base model to changes in mortality and fecundity, both of these parameters were systematically varied from near zero to their maximum value given in the base model (e.g., F = 94, P4 = 0.871). The parameters were varied alone or in combination and the resulting population growth was plotted. All plots were created using ggplot2 (Wickham, 2016) in R software (R Core Team, 2022). Three empirical scenarios from the literature were modeled containing estimates of fecundity reduction only, survivorship reduction only, or both fecundity and survivorship reduction when using LLIN (R.V. Wilkins et al., 2021; Gerken et al., 2021;Scheff et al., 2021, Scheff et al., 2023; Table 2). An individual projection matrix was constructed for each of the three scenarios and combinations of the reductions in fecundity, survivorship, or both. Population growth and proportion in each life stage was projected for 15 generations for each case, including the base model. Overall variation and oscillation were calculated to compare trends among proportion of life stages in each case. In order to compare differences in population sizes between cases for all generations and for generation 15 only, population sizes for each generation were bootstrapped 1000 times to provide iterative replication. The bootstrapped data were then compared one case to another using proc ttest in SAS (Version 9.4) for all generations and for generation 15 only. In addition, a sensitivity analysis was performed to determine which stage should be targeted to most greatly affect the population growth after exposure to the netting. Moreover, a mortality function based on empirical data with LLIN exposure collected in the laboratory on T. castaneum was implemented. The three scenarios are derived from: Gerken, A. R., J. F. Campbell, S. R. Abts, F. Arthur, W. R. Morrison, and D. S. Scheff. 2021. “Long-Lasting Insecticide-Treated Netting Affects Reproductive Output and Mating Behavior in Tribolium castaneum (Coleoptera: Tenebrionidae) and Trogoderma variabile (Coleoptera: Dermestidae).” Edited by Rizana Mahroof. Journal of Economic Entomology 114 (6): 2598–2609. https://doi.org/10.1093/jee/toab204. Scheff, D. S., A. R. Gerken, W. R. Morrison, J. F. Campbell, F. H. Arthur, and K. Y. Zhu. 2021. “Assessing Repellency, Movement, and Mortality of Three Species of Stored Product Insects after Exposure to Deltamethrin-Incorporated Long-Lasting Polyethylene Netting.” Journal of Pest Science 94 (3): 885–98. https://doi.org/10.1007/s10340-020-01326-3. Wilkins, R.V., J.F. Campbell, K.Y. Zhu, L.A. Starkus, T. McKay, and W.R. Morrison. 2021. “Long-Lasting Insecticide-Incorporated Netting and Interception Traps at Pilot-Scale Warehouses and Commercial Facilities Prevents Infestation by Stored Product Beetles.” Frontiers in Sustainable Food Systems 4: https://doi.org/10.3389/fsufs.2020.561820. Resources in this dataset: Resource Title: Script for Modeling of LLIN effects on T. castaneum MS File Name: ranabhat_etal_modeling_MS_r_script_final_agdata_commons.R
Annual air trends report in the form of an interactive web application. The report features a suite of visualization tools that allow the user to: -Learn about air pollution and how it can affect our health and environment. -Compare key air emissions to gross domestic product, vehicle miles traveled, population, and energy consumption back to 1970. -Take a closer look at how the number of days with unhealthy air has dropped since 2000 in 35 major US cities. -Explore how air quality and emissions have changed through time and space for each of the common air pollutants. -Check out air trends where you live. Users will also be able to share this content across social media, with one-click access to Facebook, Twitter, Pinterest, and other major social media sites.
The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.
The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.
The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.
The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.
The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.
The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.
The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.
The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.
The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.
The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.
The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.
The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.
The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.
The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.
The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.
The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.
The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.
The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.
The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.
The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.
The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.
The USDA Pesticide Data Program (PDP) database provides national data on pesticide residues in food and water, with an emphasis on foods consumed by infants and children. PDP data are used primarily by EPA to prepare realistic pesticide dietary exposures for pesticide registration activities. Data for each calendar-year survey are stored in a separate dataset.
Pyrethroid exposures and intake doses. 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: No contains PII, but all raw data have been provided in the paper (without PII). Format: Contains PII; however all raw data are provided in the paper (without PII). This dataset is associated with the following publication: Morgan, M. Dietary Pyrethroid Exposures and Intake Doses for 188 Duplicate-Single Solid Food Items Consumed by North Carolina Adults. Toxics. MDPI AG, Basel, SWITZERLAND, 8(1): 6, (2020).
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).
The Toxicity Reference Database (ToxRefDB) contains approximately 30 years and $2 billion worth of animal studies. ToxRefDB allows scientists and the interested public to search and download thousands of animal toxicity testing results for hundreds of chemicals that were previously found only in paper documents. Currently, there are 474 chemicals in ToxRefDB, primarily the data rich pesticide active ingredients, but the number will continue to expand.