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EPA’s 8 th Conference on Air Quality Modeling Comments on Model Evaluation

EPA’s 8 th Conference on Air Quality Modeling Comments on Model Evaluation. By Bob Paine, ENSR (Peer reviewed by the A&WMA AB-3 Committee). Comment Areas. A new approach for model evaluations (ASTM guide 6589) Other approaches that should also be considered. Comments on ASTM guide 6589.

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EPA’s 8 th Conference on Air Quality Modeling Comments on Model Evaluation

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  1. EPA’s 8th Conference on Air Quality Modeling Comments on Model Evaluation By Bob Paine, ENSR (Peer reviewed by the A&WMA AB-3 Committee)

  2. Comment Areas • A new approach for model evaluations (ASTM guide 6589) • Other approaches that should also be considered

  3. Comments on ASTM guide 6589 • ASTM Guide 6589 applies to tracer field studies having intensive surface networks of receptors • It provides best fit to arc of observed concentrations rather than picking the peak value • It conducts resampling of predicted and observed concentrations to give confidence intervals to results

  4. Consideration of Non-tracer Databases • Entire class of databases consisting of long-term (e.g., 1 year), but spatially sparse networks of monitors not addressed by this guide • Does this new standard exclude other techniques, or simply augment them? • Does it imply that other procedures (e.g., by Cox and Tikvart) are sufficiently well-developed to deal with such databases?

  5. Advantages of Long-Term Databases • More extensive set of databases is available for long-term studies than tracer studies, due to extremely high cost of short-term studies • EPA has conducted studies involving such databases (i.e., for rural, urban, and complex terrain models) • EPA has developed software (Model Evaluation Methodology, or MEM) for such databases

  6. Advantages of Long-Term Databases, cont. • Regulatory standards in the US (e.g., number of peak concentrations above threshold value during a year) are best addressed by long-term studies • Annual averages, especially important for risk assessment studies, can only be assessed with long-term databases • Large range of meteorological conditions expected at a given site over all times of day and seasons can only be accomplished with long-term databases • Statistics that rely upon pairing in space (but unpaired in time) work quite well with such databases

  7. Disadvantages of Long-Term Datasets • For any given time period, it is difficult to determine where the plume centerline is • These databases do not work well for statistics that rely upon events paired in time (not necessarily paired in space) • These databases do not lend themselves well to intensive analyses of given short-term events • It is evident that both types of evaluation databases (long-term, spatially sparse and short-term, spatially dense) have their useful features.

  8. Recommendations • EPA can incorporate ASTM Guide 6589 for short-term tracer databases • EPA should also provide a mechanism for evaluating long-term databases and having common statistical measures for an overall model performance assessment

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