You are here:
Performance Summary of the 2006 Community Multiscale Air Quality (CMAQ) Simulation for the AQMEII Project: North American Application
Citation:
APPEL, W., S. J. ROSELLE, G. POULIOT, B. K. EDER, T. E. PIERCE, R. MATHUR, K. L. SCHERE, S. T. RAO, AND S. Galmarini. Performance Summary of the 2006 Community Multiscale Air Quality (CMAQ) Simulation for the AQMEII Project: North American Application. Chapter 84, Douw G. Steyjn & Silvia Trini Castelli (ed.), NATO/SPS/ International Technical Meeting on Air Pollution Modeling and its Application. Springer Netherlands, , Netherlands, Series C:505-511, (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:
The CMAQ modeling system has been used to simulate the CONUS using 12-km by 12-km horizontal grid spacing for the entire year of 2006 as part of the Air Quality Model Evaluation International initiative (AQMEII). The operational model performance for O3 and PM2.5 for the simulation was assessed. The model underestimates O3 mixing ratios in the winter, which is likely due to low O3 mixing ratios in the middle and lower troposphere from the lateral boundary conditions. PM2.5 performance varies seasonally and geographically, with PM2.5 overestimated in the winter and fall, while performance in the spring and summer is generally good, especially in the summer. PM2.5 concentrations are systematically higher in the AQMEII CMAQ simulation than in previous CMAQ simulations, primarily due to higher concentrations of TC and unspeciated PM2.5 mass, which may also be due to differences in the lateral boundary conditions.