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This talk will be webcast and recorded
By the Clean Air Act, the U.S. Environmental Protection Agency (US EPA) is required to monitor, regulate and set national ambient air quality standards (NAAQS) for ozone along with other pollutants considered to be harmful to public health and the environment. To investigate ozone exposure, the EPA utilizes monitoring devices sparsely located across the United States along with estimates of gridded ground-level ozone concentration produced by a deterministic numerical air quality model, Models-3/Community Mesoscale Air Quality Model, CMAQ CMAQ. To investigate about the exceedance behavior of ozone relative to the NAAQS which is given in terms of the level of the annual fourth highest ozone concentration, we propose a downscaling modeling approach that employs a spatial fourth highest extreme value (FHEV) model to assimilate both data sources. In particular, the FHEV incorporates spatially-varying parameters that depend on a smoothed CMAQ output. We apply our approach to the annual fourth highest ozone concentration in the Eastern United States during years 2001-2008 and obtain an improved predictive performance compared to that of other downscaler models.