January 2022 Daily 8-Hour Maximum and Annual O3 Concentrations for the Contiguous United States, 1-km Grids, v1 (2000 – 2016) PURPOSE To provide daily 8-hour maximum and annual ground-level Ozone (O3) concentration data in the U.S. at a resolution of 1 km (about 30 arc-seconds) for public health research to respectively estimate short- and long-term effects on human health, and for other related research. DESCRIPTION The Daily 8-Hour Maximum and Annual O3 Concentrations for the Contiguous United States, 1-km Grids, v1 (2000 - 2016) data set contains estimates of ozone concentrations at a high resolution in space (1 km x 1 km grid cells) and time (daily) for the years 2000 to 2016. These predictions incorporated various predictor variables such as Ozone (O3) ground measurements from the U.S. Environmental Protection Agency (EPA) Air Quality System (AQS) monitoring data, land-use variables, meteorological variables, chemical transport models and remote sensing data, along with other data sources. After imputing missing data with machine learning algorithms, a geographically weighted ensemble model was applied that combined estimates from three types of machine learners (neural network, random forest, and gradient boosting). The annual predictions were computed by averaging the daily 8-hour maximum predictions in each year for each grid cell. The results demonstrate high overall model performance with a cross-validated R-squared value against daily observations of 0.90 and 0.86 for annual averages. ACCESSING THE DATA The data may be downloaded at https://sedac.ciesin.columbia.edu/data/set/aqdh-o3-concentrations-contiguous-us-1-km-2000-2016/data-download DATA FORMAT This archive contains data in raster, tabular, and vector formats. The data files are compressed zip files. Downloaded files need to be uncompressed in a single folder using either WinZip (Windows file compression utility) or similar application. Users should expect an increase in the size of downloaded data after decompression. DATA VALUES The unit is parts per billion (ppb). SPATIAL EXTENT Contiguous United States, 1 km (about 30 arc-seconds). DISCLAIMER CIESIN follows procedures designed to ensure that data disseminated by CIESIN are of reasonable quality. If, despite these procedures, users encounter apparent errors or misstatements in the data, they should contact SEDAC User Services at ciesin.info@ciesin.columbia.edu. Neither CIESIN nor NASA verifies or guarantees the accuracy, reliability, or completeness of any data provided. CIESIN provides this data without warranty of any kind whatsoever, either expressed or implied. CIESIN shall not be liable for incidental, consequential, or special damages arising out of the use of any data provided by CIESIN. USE CONSTRAINTS This work is licensed under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0). Users are free to use, copy, distribute, transmit, and adapt the work for commercial and non-commercial purposes, without restriction, as long as clear attribution of the source is provided. RECOMMENDED CITATION(S) Data Set: Requia, Weeberb J.1, Yaguang Wei1, Alexandra Shtein1, Carolynne Hultquist2, Xiaoshi Xing2, Qian Di1, Rachel Silvern3, James T. Kelly4, Petros Koutrakis1, Loretta J. Mickley3, Melissa P. Sulprizio3, Heresh Amini1,5, Liuhua Shi1,6, and Joel Schwartz1. 2021. Daily 8-Hour Maximum and Annual O3 Concentrations for the Contiguous United States, 1-km Grids, v1 (2000 – 2016). Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/a4mb-4t86. Accessed DAY MONTH YEAR. 1 Department of Environmental Health, Harvard T.H. Chan School of Public Heath, Harvard University, Boston, MA, United States 2 Center for International Earth Science Information Network (CIESIN), Earth Institute, Columbia University, Palisades, NY, United States 3 John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, United States 4 U.S. Environmental Protection Agency, Office of Air Quality Planning & Standards, Research Triangle Park, NC, United States 5 Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 1165, Denmark 6 Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, United States Scientific Publication: Requia, W. J., Q. Di, R. Silvern, J. T. Kelly, P. Koutrakis, L. J. Mickley, M. P. Sulprizio, H. Amini, L. Shi, and J. Schwartz. 2020. An ensemble learning approach for estimating high spatiotemporal resolution of ground-level ozone in the contiguous United States. Environmental Science & Technology, 54(18):11037-11047. https://doi.org/10.1021/acs.est.0c01791. ACKNOWLEDGEMENT: The work for journal paper was supported by U.S. EPA grants RD-834798, RD-835872, and 83587201, HEI grant 4953-RFA14-3/16-4, HHS/NIH grant UG3OD023282, NIH grant P50 AG025688, HERCULES Center grant P30ES019776. The computations were run on the Odyssey cluster supported by the FAS Division of Science, Research Computing Group at Harvard University. The data work from RDS to GeoTIFF with QA/QC is supported by NIH/NIEHS grant R01ES032418.