Mean errors (NMB) (and correlation coefficient, R).

• Ozone is fairly unbiased and accurate (NMB<10%) and NME=~20%); sulfate

performance is quite well, even for STN. NO3 was the worst in the winter (NME

~67% for STN and ~96% for IMPROVE)

14. Frank, N.,”Use of National PM2.5 and Speciation Network Measurements for Model

Evaluation ”, PM Model Performance Workshop, RTP, NC, 2004.

• Compared correlated speciated monitoring sites (e.g., IMPROVE, CASTNet, STN) for

ambient PM species measurements.

• The sulfate agrees very well, but nitrate has both positive & negative bias site-by-site.

• OM is more uncertain than other species, but is still somewhat robust for model

evaluation (ie., uncertainty is relatively small compared to current range of uncertainty

in modeling). OM is about 50%-80% of urban excess of PM2.5.

15. Hu, Y.,, “Evaluation of CMAQ with FAQS Episode of August 11th-20th”, 2000,

CMAS Annual workshop, RTP, NC, 2003.

• Conducted CMAQ (36/12/4 km nesting) performance evaluation for O3 based on Fall

Line Air Quality Study (FAQS) 8/11-20.

• Indicated that CMAQ had a good O3 performance, but has a nighttime problem, which

could be due to min Kz used. Analysis suggested that an optimal of min Kz may lie

between 0.1~1 m2/s.

• The Isoprene emissions may be overestimated in the rural area and CO emissions may

be underestimated.

16. Tonnesen, G., et al., “Prelim Preliminary Results CMAQ and CMAQ-AIM with

SAPRC99”, National RPO Modeling Meeting, 2004b.

• Compared CMAQ and CMAQ-AIM with SAPRC99 based on 2001 VISTAS modeling

study. CMAQ-AIM with SAPRC99 has larger negative bias and lower predictions of

Sulfate PM than standard released CMAQ.

• Conducted model & chemistry inter-comparisons: CMAQ with CB4, CB4-2002,


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