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Representing the Effects of Long-Range Transport and Lateral Boundary Conditions in Regional Air Pollution Models
Citation:
Mathur, R., S. Roselle, Jeff Young, AND D. Kang. Representing the Effects of Long-Range Transport and Lateral Boundary Conditions in Regional Air Pollution Models. Chapter 51, Air Pollution Modeling and its Application XXII. Springer, Heidelburg, Germany, 2014:303-308, (2013).
Impact/Purpose:
The National Exposure Research Laboratory′s (NERL′s)Atmospheric Modeling Division (AMAD) conducts research in support of EPA′s mission to protect human health and the environment. AMAD′s research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the Nation′s air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air pollution problem, but also in developing emission control policies and regulations for air quality improvements.
Description:
The Community Multiscale Air Quality (CMAQ) modeling system was applied to a domain covering the northern hemisphere; meteorological information was derived from the Weather Research and Forecasting (WRF) model run on identical grid and projection configuration, while the emission inputs were derived from global inventories. The ability of the model to represent long-range transport of pollutants is analyzed through comparisons with aircraft measurements from the 2006 INTEX-B field campaign, ozonesonde profiles, and remotely sensed observations of aerosol optical depth. Time varying lateral boundary conditions from these hemispheric scale calculations were used to drive regional-scale air quality simulations over a finer resolution domain covering the continental United States. Comparison of model predictions with surface O3 and PM2.5 measurements indicate comparable or better performance relative to other approaches (e.g., other global models, static profiles). The successful expansion of CMAQ to the hemispheric scales now provides a conceptual framework to examine interactions between atmospheric processes occurring at various spatial and temporal scales in a consistent manner.