Temporal features in observed and simulated meteorology and air quality over the Eastern United States

Abstract

Over the next several years, grid-based photochemical models such as the community multiscale air quality (CMAQ) model, the regional modeling system for aerosols and deposition (REMSAD), the comprehensive air quality model with extensions (CAMx), and other regional models will be used by regulatory agencies in the United States for designing emission control strategies to meet and maintain the National Ambient Air Quality Standards (NAAQS) for O 3, PM 2.5, and regional haze. In this study, temporal scale analysis is applied as a technique to evaluate an annual simulation of meteorology, O 3, and PM 2.5 and its chemical components over the continental US utilizing two modeling systems. The spectral decomposition of total PM 2.5 mass from hourly observations and CMAQ and REMSAD model predictions revealed that days of high PM 2.5 concentrations are generally characterized by positive forcing from fluctuations having periods equal to or greater than a day (i.e., the diurnal, synoptic, and longer-term components) while the magnitude of intra-day fluctuations showed only small differences between average and episodic conditions. Both modeling systems did not capture most of the variability of the high-frequency, intra-day component for all variables for which hourly measurements were available. Furthermore, it is illustrated that correlations were insignificant on the intra-day time scale for all variables, suggesting that these models in the setup used for this study were not skillful in simulating the higher-frequency variations in meteorological variables and the levels of all pollutants. The models exhibited greatest skills at capturing longer-term (seasonal) fluctuations for temperature, wind speed, O 3, sulfate and nitrate. Correlations for total PM 2.5, ammonium, elemental carbon (EC), organic carbon (OC) and crustal PM 2.5 correlations were highest for the synoptic time scale implying problems with factors other than meteorology, such as emissions or lateral chemical boundary conditions, in capturing the baseline fluctuations.