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Simulation of atmospheric oxidation capacity in Houston, Texas
Citation:
Sarwar, G., S. Chen, B. Henderson, K. Fahey, R. Gilliam, G. Pouliot, B. Czader, AND B. Rappenglueck. Simulation of atmospheric oxidation capacity in Houston, Texas. Chapter 81, Air Pollution Modeling and its Application XXII. Springer, Heidelburg, Germany, 2014:481-486, (2013).
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:
Air quality model simulations are performed and evaluated for Houston using the Community Multiscale Air Quality (CMAQ) model. The simulations use two different emissions estimates: the EPA 2005 National Emissions Inventory (NEI) and the Texas Commission on Environmental Quality (TCEQ) Emissions Inventory. A comparison of predictions with observed data from the 2006 TexAQS-II Radical and Aerosol Measurement Project (TRAMP) suggest that while the predicted oxides of nitrogen are greater than observations, predicted volatile organics (e.g., ethane, acetone) are substantially lower than the observations. Predicted hydroxyl radical predictions are in good agreement with the observations. Hydroperoxy radical predictions, however, are substantially lower than the observations.