This paper describes the characteristic space and time scales in time series of ambient ozone data. The authors discuss the need and a methodology for cleanly separating the various scales of motion embedded in ozone time series data, namely, short-term (weather related) variations, seasonal (solar induced) variations, and long-term (climate-policy related) trends, in order to provide a better understanding of the underlying physical processes that affect ambient ozone levels. Spatial and temporal information in ozone time series data, obscure prior to separation, is clearly displayed by simple laws afterward. In addition, process changes due to policy or climate changes may be very small and invisible unless they are separated from weather and seasonality. Successful analysis of the ozone problem, therefore, requires a careful separation of seasonal and synoptic components.The authors show that baseline ozone retains global information on the scale of more than 2 months in time and about 300 km in space. The short-term ozone component, attributable to short-term weather and precursor emission fluctuations, is highly correlated in space, retaining 50% of the short-term information at distances ranging from 350 to 400 km; in time, short-term ozone resembles a Markov process with 1-day lag correlations ranging from 0.2 to 0.5. The correlation structure of short-term ozone permits highly accurate predictions of ozone concentrations up to distances of about 600 km from a given monitor. These results clearly demonstrate that ozone is a regional-scale problem.

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The updated regulatory framework for demonstrating that future 8-hr ozone (O 3 ) design values will be at or below the National Ambient Air Quality Standards (NAAQS) provides guidelines for the development of a State Implementation Plan (SIP) that includes methods based on photochemical modeling and analytical techniques. One of the suggested approaches is the relative reduction factor (RRF) for estimating the efficacy of emission reductions.In this study, the sensitivity of model-predicted responses towards emission reductions to the choice of meteorology and chemical mechanisms was examined. While the different modeling simulations generally were found to be in agreement on whether predicted futureyear design values would be above or below the NAAQS for 8-hr O 3 at a majority of the monitoring locations in the eastern United States, differences existed for a small percentage of monitors (ϳ6.4%).Another issue investigated was the ability of the attainment demonstration procedure to predict changes in monitored O 3 design values. A retrospective analysis was performed by comparing predicted O 3 design values from model simulations using emission estimates for 1996 and 2001 with monitored O 3 design values for 2001. Results indicated that an average gross error of ϳ5 ppb was present between modeled and observed design values and that, at ϳ27% of all sites, model-predicted and observed design values disagreed as to whether the design value was above or below the NAAQS. Retrospective analyses such as the one presented in this study can provide valuable insights into the strengths and limitations of modeling and analysis techniques used to predict future design values over time periods of a decade or more for the purpose of developing SIPs. Furthermore, such analyses could provide avenues for improvement and added confidence in the use of the RRF approach for addressing attainment of the NAAQS.

The U.S. Environmental Protection Agency in 1997 revised the 1-hr ozone (O 3 ) National Ambient Air Quality Standard (NAAQS) to one based on an 8-hr average, resulting in potential nonattainment status for substantial portions of the eastern United States. The regulatory process provides for the development of a state implementation plan that includes a demonstration that the projected future O 3 concentrations will be at or below the NAAQS based on photochemical modeling and analytical techniques.In this study, four photochemical modeling systems, based on two photochemical models, Community Model for Air Quality and the Comprehensive Air Quality Model with extensions, and two emissions processing models, Sparse Matrix Optimization Kernel for Emissions and Emissions Modeling System, were applied to the eastern United States, with emphasis on the northeastern Ozone Transport Region in terms of their response to oxides of nitrogen and volatile organic carbon-focused controls on the estimated design values. With the 8-hr O 3 NAAQS set as a bright-line test, it was found that a given area could be termed as being in or out of attainment of the NAAQS depending upon the modeling system. This suggests the need to provide an estimate of model-to-model uncertainty in the relative reduction factor (RRF) for a better understanding of the uncertainty in projecting the status of an area's attainment. Results indicate that the modelto-model differences considered in this study introduce an uncertainty of the future estimated design value of ϳ3-5 ppb.