You are here:
Dynamic Evaluation of Long-Term Air Quality Model Simulations Over the Northeastern U.S.
Citation:
Hogrefe, C., K. Civerolo, W. Hao, E. E. Zalewsky, J. Y. Ku, P. S. Porter, S. T. RAO, AND G. Sistla. Dynamic Evaluation of Long-Term Air Quality Model Simulations Over the Northeastern U.S. Chapter 86, Douw G. Steyn & Silvia Trini Castelli (ed.), NATO/ITM Air Pollution Modeling and its Application XXI. Springer Netherlands, , Netherlands, Series C:519-524, (2011).
Impact/Purpose:
The National Exposure Research Laboratory′s (NERL′s) Atmospheric Modeling and Analysis 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:
Dynamic model evaluation assesses a modeling system's ability to reproduce changes in air quality induced by changes in meteorology and/or emissions. In this paper, we illustrate various approaches to dynamic mode evaluation utilizing 18 years of air quality simulations performed with the regional-scale MM5/SMOKEICMAQ modeling system over the Northeastern U.S. for the time period 1988 - 2005. A comparison of observed and simulated weekly cycles in elemental carbon (EC) and organic carbon (OC) concentrations shows significant differences, indicating potential problems with the magnitude and temporal allocation of traffic-related emissions and the split between primary and secondary organic aerosols. A comparison of the observed and simulated interrelationships between temperature and ozone over the 18-year simulation period reveals that the high end of the modeled ozone concentration distribution is less influenced by interannual variability in the high end of the temperature distribution as compared to the observations.