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Application of geostatistical approaches to predict the spatio-temporal distribution of summer ozone in Houston, Texas

Journal of Exposure Science & Environmental Epidemiology volume 29, pages 806–820 (2019)Cite this article

Abstract

Mitigation of adverse effects of air pollution requires understanding underlying exposures, such as ambient ozone concentrations. Geostatistical approaches were employed to analyze temporal trends and estimate spatial patterns of summertime ozone concentrations for Houston, Texas, based on hourly ozone observations obtained from the Texas Commission on Environmental Quality. We systematically assess the accuracy of several spatial interpolation methods, comparing inverse distance weighting, simple kriging, ordinary kriging, and universal kriging methods utilizing the hourly ozone observations and meteorological measurements from monitoring sites. Model uncertainty was assessed by leave-one-out cross-validation. Kriging methods performed better, showing greater consistency in the generated surfaces, fewer interpolation errors, and lower biases. Universal kriging did not significantly improve the interpolation results compared to ordinary kriging, and thus ordinary kriging was determined to be the optimal method, striking a balance between accuracy and simplicity. The resulting spatial patterns indicate that the more industrialized areas east and northeast of Houston exhibit the highest summertime ozone concentrations. Estimated daily maximum 8 h ozone concentration fields generated will be used to inform research on population health risks from exposure to surface ozone in Houston.

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Acknowledgements

This research was supported in part by Assistance Agreement No. 83575401 awarded by the US Environmental Protection Agency. It has not been formally reviewed by the EPA. The views expressed in this document are solely those of the authors and do not necessarily reflect those of the Agency.

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Authors and Affiliations

  1. Research Applications Laboratory, National Center for Atmospheric Research, Boulder, CO, USA

    Ryan Michael, Cassandra R. O’Lenick, Andrew Monaghan, Olga Wilhelmi & Mary Hayden

  2. Atmospheric Chemistry Observations and Modeling Laboratory, National Center for Atmospheric Research, Boulder, CO, USA

    Christine Wiedinmyer

  3. Air Modeling and Data Analysis Section, Texas Commission on Environmental Quality, Austin, TX, USA

    Mark Estes

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Michael, R., O’Lenick, C.R., Monaghan, A. et al. Application of geostatistical approaches to predict the spatio-temporal distribution of summer ozone in Houston, Texas. J Expo Sci Environ Epidemiol 29, 806–820 (2019). https://doi.org/10.1038/s41370-018-0091-4

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