Air Quality Data for Health-Related Applications

The data set authors and their affiliations are:

Requia, W. J.^{1, 3}, Y. Wei¹, A. Shtein¹, X. Xing², E Castro¹, Q. Di^{1, 4}, R. Silvern⁵, J. T. Kelly⁶, P. Koutrakis¹, L. J. Mickley⁵, M. P. Sulprizio ⁵, H. Amini⁷, C. Hultquist ^{2, 8}, L. Shi⁹, Y. Daouk², and J. Schwartz^{1, 10}.

¹Department of Environmental Health, Harvard T. H. Chan School of Public Health, Harvard University, Boston, MA, United States
²Center for International Earth Science Information Network (CIESIN), Columbia Climate School, Columbia University, Palisades, NY, United States
³School of Public Policy and Government, Fundação Getúlio Vargas, Brasília, Distrito Federal, Brazil
⁴Vanke School of Public Health, Tsinghua University, Beijing, China
⁵John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, United States
⁶U.S. Environmental Protection Agency (EPA), Office of Air Quality Planning & Standards (OAQPS), Research Triangle Park, NC, United States
⁷Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States
⁸School of Earth and Environment, University of Canterbury, Christchurch, New Zealand
⁹Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, United States
¹⁰Department of Epidemiology, Harvard T. H. Chan School of Public Health, Harvard University, Boston, MA, United States

For more information about the data see this readme text file and this peer reviewed open access article:

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.

Acknowledgements:

This work was supported by U.S. EPA grants RD-834798, RD-835872, and 83587201, and Health Effects Institute (HEI) grant 4953-RFA14-3/16-4 and assistance award CR-83467701. The HEI is an organization jointly funded by the U.S. EPA and certain motor vehicle and engine manufacturers. The computations were run on the Odyssey cluster supported by the Faculty of Arts & Sciences (FAS) Division of Science, Research Computing Group at Harvard University. The data conversion work from RDS to GeoTIFF with QA/QC was supported by the National Institutes of Health, National Institute of Environmental Health Sciences (NIH/NIEHS) grant R01ES032418. The contents are solely the responsibility of the grantees and do not necessarily represent the official views of the U.S. EPA. Further, the U.S. EPA does not endorse the purchase of any commercial products or services mentioned in the data or documents. The authors also thank Gregory Yetman (CIESIN) for his help with the data conversion process.

Potential Use Cases:

It is anticipated for this work to be used for conducting new studies on individual and combined health risks of total O3 concentration, environmental justice analysis, or understanding fine-scale spatiotemporal variabilities of O3. This data can be useful for the environmental health community to estimate the health impacts of O3 more accurately over space and time, especially in health studies at an intra-urban scale.

Select References (for all other references see readme text file):

1. Heo, S., and Bell, M. L. (2023) Investigation on urban greenspace in relation to sociodemographic factors and health inequity based on different greenspace metrics in 3 US urban communities. Journal of Exposure science & Environmental Epidemiology,, 33, 218–228. https://doi.org/10.1038/s41370-022-00468-z.
2. Ma, T., Danesh-Yazdi, M., Schwartz, J., Réquia, W. J., Di, Q., Wei, Y., Chang, H. H., Vaccarino, V., Liu, P., and Shi, L. (2022). Long-term air pollution exposure and incident stroke in American older adults: A national cohort study. Global Epidemiology , 4, 100073. https://doi.org/10.1016/j.gloepi.2022.100073.
3. Qiu, X., Danesh-Yazdi, M., Wei, Y., Di, Q., Just, A., Zanobetti, A., Weisskopf, M., Dominici, F., and Schwartz, J. (2022). Associations of short-term exposure to air pollution and increased ambient temperature with psychiatric hospital admissions in older adults in the USA: A case–crossover study. The Lancet Planetary Health, 6(4), e331-e341. https://doi.org/10.1016/S2542-5196(22)00017-1.
4. Qiu, X., Shi, L., Kubzansky, L. D., Wei, Y., Castro, E., Li, H., Weisskopf, M. G., and Schwartz, J. D. (2023). Association of long-term exposure to air pollution with late-life depression in older adults in the US. JAMA Network Open, 6(2), e2253668. https://doi.org/10.1001/jamanetworkopen.2022.53668.
5. Zhang, H., Shi, L., Ebelt, S. T., D’Souza, R. R., Schwartz, J. D., Scovronick, N., and Chang, H. H. (2023). Short-term associations between ambient air pollution and emergency department visits for Alzheimer’s disease and related dementias. Environmental Epidemiology , 7(1), e237. https://https://doi.org/10.1097/EE9.0000000000000237.