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STATISTICAL MODELS FOR QUANTIFYING THE SPATIAL DISTRIBUTION OF SEASONALLY DERIVED OZONE STANDARDS

By  and Eric GillelandTor Of Philosophy and Eric Gilleland

Abstract

The U.S. Environmental Protection Agency’s (EPA) National Ambient Air Quality Standard (NAAQS) for ground-level ozone is now based on the fourthhighest daily maximum 8-hour average ozone level (FHDA). Standard geostatistical models may not be appropriate for interpolating such a statistic off of a network of monitoring sites. The performance of different statistical models in predicting this standard at locations where monitors are not located is compared. Special attention is given to two models: a daily model that uses a spatial autoregression to account for spatial and temporal dependence, and a seasonal model that assumes the FHDA field is Gaussian and employs spatial statistical techniques. Based on five seasons of ozone data collected in and around North Carolina, cross-validation shows a preference to the daily model over the seasonal model. In addition to the above models, a spatial extreme value model is also compared to the daily model. Results show that the two vastly different methods give remarkably similar results

Year: 2004
OAI identifier: oai:CiteSeerX.psu:10.1.1.172.5119
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