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Influence of Boundary Conditions on Simulated U.S. Air Quality
Citation:
Hogrefe, C., G. Pouliot, J. Xing, W. Appel, S. Roselle, AND R. Mathur. Influence of Boundary Conditions on Simulated U.S. Air Quality. Air & Waste Management Annual Conference and Exhibition, Raleigh, NC, June 22 - 25, 2015.
Impact/Purpose:
The National Exposure Research Laboratory’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:
One of the key inputs to regional-scale photochemical models frequently used in air quality planning and forecasting applications are chemical boundary conditions representing background pollutant concentrations originating outside the regional modeling domain. A number of studies have investigated the effects of boundary conditions on the results of the regional-scale simulations. In this study, we build upon the existing body of work by analyzing two annual simulations for the year 2010 over the continental U.S. driven by boundary conditions derived from three different global or hemispheric scale models. Daily maximum 8-hr (DM8HR) ozone and 24-hr PM2.5 concentrations from these simulations are then compared to determine the magnitude of model-to-model differences and their impact on model performance. The results show that different boundary conditions can have a substantial impact on CMAQ model performance for DM8HR ozone and 24-hr PM2.5 concentrations. Moreover, the differences in CMAQ simulations attributable to differences in boundary conditions vary across seasons as well as across space.
