Dynamic evaluation of regional air quality models:: Assessing changes in O3 stemming from changes in emissions and meteorology

Regional-scale air quality models are used to estimate the response of air pollutants to potential emission control strategies as part of the decision-making process. Traditionally, the model-predicted pollutant concentrations are evaluated for the base case to assess a model's ability to reproduce past observations. Dynamic evaluation approaches, which evaluate a model's ability to accurately simulate air quality changes from given changes in emissions, are critically important to regulatory applications. Here, we investigate approaches to evaluate the Community Multiscale Air Quality (CMAQ) model's predicted ozone (O-3) response to large NO, emission reductions associated with the NO, State Implementation Plan (SIP) Call and on-road mobile emissions. This case has the advantages that emission changes associated with the NO, SIP Call can be well characterized and substantial changes are observed in O-3 levels. To consider the modeled response to emission changes in light of the strong meteorological influences on O-3, two time periods after the NO, SIP Call are included with very different meteorological conditions. The sensitivity to chemical mechanisms is also considered by including simulations with the CB4, SAPRC, and CB05 chemical mechanisms. The evaluation results suggest that the air quality model predictions underestimate the 03 reductions observed after the NO, SIP Call was implemented. While the emission estimate uncertainties may also be a factor, the results suggest that the contribution of long-range transport Of O-3 and precursors is underpredicted, especially when using the CB4 chemical mechanism. Further investigation of the chemical mechanisms' ability to characterize tropospheric chemistry aloft is recommended. Results based on the most recent CMAQ version 4.6 with CB05 and updated emission inventories show incremental improvements to the modeled O-3 response to NO, emission reductions. (c) 2008 Elsevier Ltd. All rights reserved.