Interpreting the information in ozone observations and model predictions relevant to regulatory policies in the Eastern United States

To study the underlying forcing mechanisms that distinguish the days with h igh ozone concentrations from average or nonepisodic days, the observed and model-predicted ozone time series are spectrally decomposed into different temporal components; the modeled values are based on the results of a thre e-month simulation with the Urban Airshed Model-Variable Grid Version photo chemical modeling system. The ozone power spectrum is represented as the su m of four temporal components, ranging from the intraday timescale to the m ultiweek timescale. The results reveal that only those components that cont ain fluctuations with periods equal to or greater than one day carry the in formation that distinguishes ozone episode days from nonepisodic days. Whic h of the longer-term fluctuations is dominant in a particular episode varie s from episode to episode, However, the magnitude of the intraday fluctuati ons is nearly invariant in time. The promulgation of the 8-h standard for o zone further emphasizes the importance of longer-term fluctuations embedded in ozone time series data. Furthermore, the results indicate that the regi onal photochemical modeling system is able to capture these features. This paper also examines the effect of simulation length on the predicted ozone reductions stemming from emission reductions. The results demonstrate that for regulatory purposes, model simulations need to cover longer time period s than just the duration of a single ozone episode; this is necessary not o nly to perform a meaningful model performance evaluation, but also to quant ify the variability in the efficacy of an emission control strategy.