Statistical models for monitoring and regulating ground-level ozone

The U.S. Environmental Protection Agency (EPA)'s National Ambient Air Quality Standard (NAAQS) for ground-level ozone is now based on the fourth-highest daily maximum 8-h average ozone level (FHDA). Standard geostatistical models may not be appropriate for interpolating such a statistic from a network of monitoring sites. In this article we compare the performance of different statistical models in predicting this standard at locations where monitors are not located. We give special attention to two models: a daily model that uses an 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, we find that the daily model is superior enough to the seasonal model to warrant its added complexity.