Abstract :
The Dust REgional Atmospheric Model (DREAM) predicts concentrations of mineral dust aerosols in time and space, but validation is challenging with current in situ particulate matter (PM) concentration measurements. Measured levels of ambient PM often contain anthropogenic components as well as windblown mineral dust. In this study, two approaches to model validation were performed with data from preexisting air quality monitoring networks: using hourly concentrations of total PM with aerodynamic diameter less than 2.5 μm (PM2.5); and using a daily averaged speciation-derived soil component. Validation analyses were performed for point locations within the cities of El Paso (TX), Austin (TX), Phoenix (AZ), Salt Lake City (UT) and Bakersfield (CA) for most of 2006. Hourly modeled PM2.5 did not validate at all with hourly observations among the sites (combined R < 0.00, N = 24,302 hourly values). Aerosol chemical speciation data distinguished between mineral (soil) dust from anthropogenic ambient PM. As expected, statistically significant improvements in correlation among all stations (combined R = 0.16, N = 343 daily values) were found when the soil component alone was used to validate DREAM. The validation biases that result from anthropogenic aerosols were also reduced using the soil component. This is seen in the reduction of the root mean square error between hourly in situ versus hourly modeled (RMSEhourly = 18.6 μg m−3) and 24-h in situ speciation values versus daily averaged observed (RMSEsoil = 12.0 μg m−3). However, the lack of a total reduction in RMSE indicates there is still room for improvement in the model. While the soil component is the theoretical proxy of choice for a dust transport model, the current sparse and infrequent sampling is not ideal for routine hourly air quality forecast validation.
