Data used for model evaluation were obtained from EPA’s

AIRS database (hourly ozone - >700 stations used, mostly

urban/suburban), from the IMPROVE (Interagency

Monitoring of Protected Visual Environments) network for

daily averages (every third day) of SO2, NO3, PM2.5, OC,

and EC from 50 rural sites, from the STN (Speciated Trends

Network) for 2002 only for daily averages (every third day)

of SO2, NO3, PM2.5, NH4, OC, and EC from 60 urban sites,

and from the SEARCH (Southeast Aerosol Research and

Characterization) research sites for 1999 only for daily and

hourly averages of PM2.5 and its components.

CMAQ model results for maximum daily 8-hr ozone

concentrations are shown in Figure 6 and Table 4 for the 4-

week summer 1999 application period. There were over

23,000 data points in the analysis covering over 700

monitoring stations. While the scatterplot in Figure 6

illustrates considerable variability in the model/observations

intercomparison, correlations are strong (r=0.75) and nearly

all comparisons are within a factor of two. CMAQ model’s

mean bias is 4.3 ppb (or 8.7% as a normalized mean bias).

The frequency distribution in Table 4 indicates that the

model tends to slightly underpredict at the highest ambient

ozone levels and overpredict at the low end of the


Model results for daily average PM2.5 concentrations for

the 4-week summer period are shown in Figure 7 and Table

5. CMAQ model results from PM2.5 are obtained by

summing the simulated aerosol concentrations of sulfates,

nitrates, ammonium, organic and elemental carbon, and

uncategorized aerosol. Results shown on the scatterplot in

Figure 7 indicate that model and observed aerosol

concentrations for the summer period are considerably

higher in the eastern sites than in the west. Most data points

fall within the 2:1 bounds and are correlated (r=0.71), with a

small mean bias (-0.73 :g m-3, or -9.8% as a normalized

mean bias). Among the principal aerosol components (not

shown), sulfate tends to be slightly overpredicted and

organic aerosols are slightly underpredicted during this time




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