Using Regionalized Air Quality Model Performance and Bayesian Maximum Entropy data fusion to map global surface ozone concentration
Author:
Becker Jacob S.1, DeLang Marissa N.1, Chang Kai-Lan23, Serre Marc L.1, Cooper Owen R.23, Wang Hantao1, Schultz Martin G.4, Schröder Sabine4, Lu Xiao5, Zhang Lin6, Deushi Makoto7, Josse Beatrice8, Keller Christoph A.910, Lamarque Jean-François11, Lin Meiyun1213, Liu Junhua910, Marécal Virginie8, Strode Sarah A.910, Sudo Kengo1415, Tilmes Simone11, Zhang Li121316, Brauer Michael1718, West J. Jason1ORCID
Affiliation:
1. 1Department of Environmental Sciences and Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA 2. 2Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA 3. 3NOAA Chemical Sciences Laboratory, Boulder, CO, USA 4. 4Jülich Supercomputing Centre (JSC), Forschungszentrum Jülich, Jülich, Germany 5. 5School of Atmospheric Sciences, Sun Yat-Sen University, Zhuhai, Guangdong, China 6. 6Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, China 7. 7Meteorological Research Institute (MRI), Tsukuba, Japan 8. 8Centre National de Recherches Météorologiques, Université de Toulouse, Météo-France, CNRS, Toulouse, France 9. 9NASA Goddard Space Flight Center, Greenbelt, MD, USA 10. 10Universities Space Research Association, Columbia, MD, USA 11. 11National Center for Atmospheric Research, Boulder, CO, USA 12. 12NOAA Geophysical Fluid Dynamics Laboratory, Princeton, NJ, USA 13. 13Program in Atmospheric and Oceanic Sciences, Princeton University, Princeton, NJ, USA 14. 14Graduate School of Environmental Studies, Nagoya University, Nagoya, Japan 15. 15Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokosuka, Japan 16. 16Department of Meteorology and Atmospheric Science, Pennsylvania State University, University Park, PA, USA 17. 17Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA 18. 18School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada
Abstract
Estimates of ground-level ozone concentrations have been improved through data fusion of observations and atmospheric chemistry models. Our previous global ozone estimates for the Global Burden of Disease study corrected for bias uniformly across continents and then corrected near monitoring stations using the Bayesian Maximum Entropy (BME) framework for data fusion. Here, we use the Regionalized Air Quality Model Performance (RAMP) framework to correct model bias over a much larger spatial range than BME can, accounting for the spatial inhomogeneity of bias and nonlinearity as a function of modeled ozone. RAMP bias correction is applied to a composite of 9 global chemistry-climate models, based on the nearest set of monitors. These estimates are then fused with observations using BME, which matches observations at measurement stations, with the influence of observations declining with distance in space and time. We create global ozone maps for each year from 1990 to 2017 at fine spatial resolution. RAMP is shown to create unrealistic discontinuities due to the spatial clustering of ozone monitors, which we overcome by applying a weighting for RAMP based on the number of monitors nearby. Incorporating RAMP before BME has little effect on model performance near stations, but strongly increases R2 by 0.15 at locations farther from stations, shown through a checkerboard cross-validation. Corrections to estimates differ based on location in space and time, confirming heterogeneity. We quantify the likelihood of exceeding selected ozone levels, finding that parts of the Middle East, India, and China are most likely to exceed 55 parts per billion (ppb) in 2017. About 96% of the global population was exposed to ozone levels above the World Health Organization guideline of 60 µg m−3 (30 ppb) in 2017. Our annual fine-resolution ozone estimates may be useful for several applications including epidemiology and assessments of impacts on health, agriculture, and ecosystems.
Publisher
University of California Press
Subject
Atmospheric Science,Geology,Geotechnical Engineering and Engineering Geology,Ecology,Environmental Engineering,Oceanography
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