This dataset contains information on the cluster characteristics, health effect estimates, and the meta-regression results. This dataset is associated with the following publication: Baxter, L., J. Crooks, and J. Sacks. Influence of exposure differences on city-to-city heterogeneity in PM2.5-mortality associations in US cities. ENVIRONMENTAL HEALTH. Academic Press Incorporated, Orlando, FL, USA, 16(1): 1-8, (2017).

measured air pollution exposure metrics. This dataset is associated with the following publication: Breen , M., T. Long , B. Schultz, R. Williams , J. Richmond-Bryant , M. Breen, J. Langstaff , R. Devlin , A. Schneider, J. Burke , S.A. Batterman, and Q.Y. Meng. Air Pollution Exposure Model for Individuals (EMI) in Health Studies: Evaluation for Ambient PM2.5 in Central North Carolina. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 49(24): 14184-14194, (2015).

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).

The data files correspond to the figures in the manuscript and can be read into the open-source R software using standard commands (e.g., data <- readRDS('filename.rds') ). Citation information for this dataset can be found in the EDG's Metadata Reference Information section and Data.gov's References section.

input data for air pollution exposure models. This dataset is associated with the following publication: Breen, M., S.Y. Chang, M. Breen, Y. Xu, V. Isakov, S. Arunachalam, M.S. Carraway, and R. Devlin. Fine-Scale Modeling of Individual Exposures to Ambient PM2.5, EC, NOx, CO for the Coronary Artery Disease and Environmental Exposure (CADEE) Study. ATMOSPHERE. MDPI AG, Basel, SWITZERLAND, 11(1): 65, (2020).

Chemical concentration, exposure, and health risk data for U.S. census tracts from National Scale Air Toxics Assessment (NATA). This dataset is associated with the following publication: Huang, H., R. Tornero-Velez, and T. Barzyk. Associations between socio-demographic characteristics and chemical concentrations contributing to cumulative exposures in the United States. Journal of Exposure Science and Environmental Epidemiology. Nature Publishing Group, London, UK, 27(6): 544-550, (2017).

Data used for manuscript available at https://www.sciencedirect.com/science/article/pii/S1352231023005575. Includes a 'README' file briefly explaining how to combine this data with BenMAP-CE to reproduce the results. Citation information for this dataset can be found in Data.gov's References section.

Chemical concentrations, exposures, health risks by census tract for the United States from National Scale Air Toxics Assessment (NATA). This dataset is associated with the following publication: Huang, H., and T. Barzyk. Connecting the Dots: Linking Environmental Justice Indicators to Daily Dose Model Estimates. International Journal of Environmental Research and Public Health. Molecular Diversity Preservation International, Basel, SWITZERLAND, 14(1): 1-15, (2017).

The dataset contains information on medical history, residential information and demographic information on CATHGEN participants as well as modeled PM2.5 values at participants' residence. This dataset is not publicly accessible because: The data are human subjects data containing potential identifiable information (PII) and therefore access is restricted to the study investigators. Because base data are owned by other entities, these data need to be requested directly from Duke University. It can be accessed through the following means: These data can accessed upon request to the CATHGEN steering committee at Duke University. Format: Data are stored as SAS files on secure EPA drives. This dataset is associated with the following publication: Weaver, A., L. McGuinn, L. Neas, J. Mirowsky, R. Devlin, R. Dhingra, C. Ward-Caviness, W. Cascio, W. Kraus, E. Hauser, Q. Di, J. Schwartz, and D. Diaz-Sanchez. Neighborhood sociodemographic effects on the associations between long-term PM2.5 exposure and cardiovascular outcomes and diabetes. Journal of Exposure Science and Environmental Epidemiology. Nature Publishing Group, London, UK, 3(1): e038, (2019).