TSD-1e

CMAQ Model Performance and Assessment

8-Hr OTC Ozone Modeling 

Bureau of Air Quality Analysis and Research

Division of Air Resources

New York State Department of Environmental Conservation

Albany, NY 12233

February 23, 2006

1
Air quality model evaluation and assessment 

One of the tasks that is required as part of demonstrating attainment for the 8-hr

ozone NAAQS is the evaluation and assessment of the air quality modeling system that

has been utilized to predict future air quality over the region of interest. As part of the

attainment demonstration, the SMOKE/CMAQ modeling system was applied to simulate

the pollutant concentration fields for the base year 2002 emissions with the corresponding

meteorological information. The modeling databases for meteorology using MM5 (TSD1a), the emissions using SMOKE (TSD-1b and TSD-1c), and application of CMAQ

(TSD-1d) provides simulated pollutant fields that are compared to measurements, in

order to establish the credibility of the simulation. In the following sections a comparison

between the measured and predicted concentrations is performed and results are

presented, demonstrating on an overall basis the utility of the modeling system in this

application.

The results presented here should serve as an illustration of some of the

evaluation and assessment performed on the base 2002 CMAQ simulation. Additional

information can be made available by request from the New York State Department of

Environmental Conservation.

Summary of measured data

The ambient air quality data, both gaseous and aerosol species, for the simulation

period of May through September 2002 were obtained from the following sources:

• EPA Air Quality System (AQS)

• EPA fine particulate Speciation Trends Network (STN)

• EPA Clean Air Status & Trends Network (CASTNet)

• Interagency Monitoring of PROtected Visual Environments (IMPROVE)

• Pinnacle State Park, NY operated by Atmospheric Science Research Center,

University at Albany, Albany, NY

• Harvard Forest, Petersham, MA operated by Harvard University, Boston, MA

• Atmospheric Investigation, Regional Modeling, Analysis and Prediction

(AIRMAP) operated by University of New Hampshire, Durham, NH

• NorthEast Ozone & Fine Particle Study (NE-OPS), led by Penn State University

and other research groups in Philadelphia, PA

• Aircraft data obtained by the University of Maryland, College Park MD

• Wet deposition data from the National Atmospheric Deposition Program/National

Trends Network (NADP/NTN), Atmospheric Integrated Research Monitoring

Network (AIRMoN), and the New York State Department of Environmental

Conservation (NYSDEC)

Measured data from sites within the Ozone Transport Region (OTR) plus the rest of

Virginia were included here. The model-based data were obtained at the grid-cell

corresponding to the monitor location; no interpolation was performed.

2
Ozone (O3)

Hourly O3 is measured at a large number of State, Local, and National Air

Monitoring Stations (SLAMS/NAMS) across the US on a routine basis, and the data from

208 sites were extracted from the AQS database

(http://www.epa.gov/ttn/airs/airsaqs/aqsweb/aqswebhome.html). Hourly O3

concentrations from the Harvard Forest Environmental Management Site in Petersham,

MA (http://www.as.harvard.edu/data/nigec-data.html); Pinnacle State Park in

Addison, NY (http://www.asrc.cestm.albany.edu); and the four University of New

Hampshire AIRMAP sites (http://airmap.unh.edu) were also included in this database.

The EPA CASTNet program collects hourly O3 at generally rural locations across the US

(http://www.epa.gov/castnet); data from 22 sites, including two from West Virginia,

were used in the model evaluation.

Fine particulate matter (PM2.5)

The 24-hour average Federal Reference Method (FRM) PM2.5 mass data collected

routinely at SLAMS/NAMS sites across the US were extracted from AQS (257 sites).

Hourly PM2.5 mass was also included in this database, primarily extracted from AQS (54

sites). Hourly PM2.5 mass were also taken from the Thompson Farm, NH AIRMAP site,

Pinnacle State Park, and the NE-OPS site in Philadelphia, PA (http://lidar1.ee.psu.edu).

Fine particulate speciation

The 24-hour average PM2.5 and fine particulate speciation (sulfate (SO4), nitrate

(NO3), elemental carbon (EC), organic carbon/organic mass (OC/OM), and soil/crustal

matter) from Class I areas across the US, collected every 3rd day, were obtained from the

IMPROVE web site (http://vista.cira.colostate.edu/IMPROVE/Default.htm). In

addition to these parameters, the EPA STN

(http://www.epa.gov/ttn/amtic/speciepg.html) also reports ammonium (NH4) to AQS;

data from this network are collected every 3rd or 6th day. Data from 49 STN sites,

generally in urban areas and often collocated with FRM monitors, and 21 IMPROVE

sites (including Dolly Sods, WV) were used in this analysis. Organic mass is assumed to

equal 1.8×OC, and soil/crustal matter is assumed to consist of oxides of Al, Ca, Fe, Si,

and Ti. The STN OC data are blank-corrected by removing a monitor-specific, constant

blank, and these values are available from

http://www.epa.gov/airtrends/aqtrnd03/pdfs/2_chemspec0fpm25.pdf; the IMPROVE

OC blanks are assumed to equal zero.

Criteria gaseous pollutants

Hourly carbon monoxide (CO; 97 sites), nitric oxide (NO; 75 sites), nitrogen

dioxide (NO2; 97 sites) and sulfur dioxide (SO2; 134 sites) are also included in this model

evaluation database. A large majority of these sites are SLAMS/NAMS monitors located

primarily in urban in suburban areas, but data from the Harvard Forest, Pinnacle State

Park, and AIRMAP sites are also included here.

3
Non-methane hydrocarbons

While there are several dozen hydrocarbon species measured routinely, for this

model evaluation database the focus was on Carbon Bond IV species groups that consist

of a single primary species. For this reason only ethene (C2H4), isoprene (C5H8), and

formaldehyde (HCHO) concentrations were extracted from AQS. Hourly C2H4 and C5H8

data from 19 Photochemical Assessment Monitoring Stations (PAMS) sites and 24-hour

average HCHO from 18 air toxics sites are included in this database.

University of Maryland aircraft data

The University of Maryland performed 144 aircraft spirals at 41 regional airport

locations over 26 days from May-August 2002

(http://www.atmos.umd.edu/~RAMMPP). Spirals are approximately 20-45 minutes in

duration, over which time the atmosphere from about 0-3 km is sampled. The

concentrations of O3, CO, and SO2 from these spirals were included in this database, and

help provide a semi-quantitative evaluation of CMAQ performance above the ground

surface. Minute average aircraft data were compared to the nearest instantaneous 3-

dimensional CMAQ output.

Wet deposition

The NADP (http://nadp.sws.uiuc.edu) collects wet deposition samples across the

US, through the NTN and the AIRMoN. Weekly wet deposition samples are collected by

the NTN, while daily or event-based samples were collected by the AIRMoN. The

NYSDEC (http://www.dec.state.ny.us) also collects weekly wet deposition samples

independently from the NADP. The wet deposition of SO4

2-, NO3-

, and NH4

+

 from 43

NADP/NTN sites, 7 NADP/AIRMoN sites, and 19 NYSDEC sites are included in this

model evaluation database. 

Evaluation of CMAQ predictions

The following sections provide model evaluation information for the above

referenced pollutants over the OTR portion of the 12-km modeling domain. The

statistical formulations that have been computed for each species are as follows: Pi and

Oi are the individual (daily maximum 8-hour O3 or daily average for the other species)

predicted and observed concentrations, respectively; P and O are the average

concentrations, respectively, and N is the sample size.

Observed average, in ppb:

O

N

= ∑ Oi

1

Predicted average, in ppb (only use Pi when Oi is valid):

4
P

N

= ∑ Pi

1

Correlation coefficient, R2:

[ ] R

P P O O

P P O O

i i

i i

2

2

2 2

=

− −

− −

∑

∑ ∑

( )( )

( ) ( )

Normalized mean error (NME), in %:

NME

P O

O

i i

i

=

−

× ∑

∑

| |

100%

Root mean square error (RMSE), in ppb:

RMSE

N

Pi Oi = −









 ∑ 

1 2

1 2

( )

/

Fractional error (FE), in %:

FE

N

P O

P O

i i

i i

=

−

+ ∑ ×

2

100%

Mean absolute gross error (MAGE), in ppb:

MAGE

N

Pi Oi = ∑ −

1

Mean normalized gross error (MNGE), in %:

MNGE

N

P O

O

i i

i

=

− ∑ ×

1

100%

Mean bias (MB), in ppb:

MB

N

Pi Oi = ∑ −

1

( )

Mean normalized bias (MNB), in %:

MNB

N

P O

O

i i

i

=

− ∑ ×

1

100%

( )

Mean fractionalized bias (MFB), in %:

MFB

N

P O

P O

i i

i i

=

−

+









 ∑  ×

2

100%

5
Normalized mean bias (NMB), in %:

NMB

P O

O

i i

i

=

−

× ∑

∑

( )

100%

Daily maximum 8-hour O3 concentrations

Model evaluation statistics, based on daily maximum 8-hour average O3 levels on

those days having (1) at least 18 valid observations, or (2) fewer than 18 valid

observations but the observed daily maximum O3 concentration was at least 85 ppb, are

presented here for all sites across the OTR and all of VA. The data cover the period May

15 through September 29, excluding July 6-9, when many sites across the eastern US

were affected by large forest fires in Quebec. There are 208 SLAMS/NAMS sites and 28

special sites.

These model evaluation statistics were computed using two different threshold

values for observed daily maximum 8-hour O3. First, the statistics were computed using

only those days when the observed daily maximum 8-hour O3 concentration exceeded 40

ppb. Second, the statistics were computed using only those days when the observed daily

maximum 8-hour O3 exceeded 60 ppb. This latter method focuses on the highest O3 days.

Figures 1-4 display time series of observed and predicted daily maximum 8-hour

O3 concentrations averaged over all sites across the OTR, at SLAMS/NAMS and special

sites and for the daily maximum two thresholds. These averages were computed for each

day considering all sites that met the corresponding threshold criteria. In general the

observed and predicted composite average O3 concentrations track each other rather well,

although there was fairly substantial underprediction during the mid-August period.

Also, the model performance tends to be better when the lower cutoff (40 ppb) was

considered.

Figures 5-8 display spatial maps of fractional error and mean fractionalized bias

for the two threshold levels. At each site the statistics were computed over the entire

modeling season. Both the SLAMS/NAMS and special monitors are displayed here. In

general, the model performance was better in the vicinity of urban areas and along the

northeastern corridor, compared to the performance in rural areas where the model tended

to underpredict daily maximum concentrations. The other statistical metrics yielded

similar results to FE and MFB.

Table 1 lists the median and range in fractional error, and the mean fractionalized

bias of daily maximum 8-hour O3 calculated at each site over the season, for both

observed thresholds (40 and 60 ppb), as well as all sites versus just the SLAMS/NAMS

sites. Considering just SLAMS/NAMS sites, FE was always less than 32% for the 40

ppb threshold, and less than 40% for the 60 ppb threshold. Similarly, the MFB at

SLAMS/NAMS sites ranged from -29 to +23% for the 40 ppb threshold, and ranged from

-40 to +22% for the 60 ppb threshold. Adding the special sites did not affect the statistics

substantially.

6
Diurnal variations of gases

Figures 9-17 display the composite diurnal variations of the species reported

hourly – O3 (SLAMS/NAMS and other/special sites, displayed separately), continuous

PM2.5, CO, NO, NO2, SO2, ethene, and isoprene. The average diurnal variations are for

the period of May 15-September 30 – again excluding July 6-9 – considering all sites in

the OTR. Note that the O3 diurnal variations were computed from running 8-hour

averages, with hours denoting the start of the 8-hour block. The number of monitors used

to compute each composite diurnal variation is shown in each figure.

For O3, the composite diurnal pattern predicted by CMAQ is fairly similar to that

observed, especially at the more urban SLAMS/NAMS monitors. However, on average

CMAQ predicts the daily maximum about an hour earlier than observed. For most of the

other species presented here, CMAQ tends to predict two daily peaks, one morning and

one late afternoon. For some species, such as PM2.5 mass the observed concentration on a

composite basis has very little diurnal variation. On the other hand, primary pollutants

like CO, NO, and ethane, CMAQ exhibits qualitative agreement with the observations.

Daily average concentrations of co-pollutant trace gases

Composite daily average predicted and observed concentrations of CO, NO, NO2,

SO2, C2H4, HCHO, and C5H8 across the OTR are displayed in Figures 18-24. Daily

average concentrations of the criteria gases, C2H4 and C5H8 were computed from hourly

averages, and only those days having at least 12 hours of valid observed data were

considered here. The HCHO data shown here are based on 24-hour average values every

6

th day. The criteria gas data cover the period May 15 – September 30, whereas the

NMHC data only cover the June 1 – August 31 period, since these data are predominantly

PAMS data; however, excluded from this analysis is the July 6-9 period when many sites

across the eastern US were affected by large forest fires in Quebec.

Table 2 lists the median and range in mean fractionalized bias calculated at each

site over the season used in this analysis. The values listed in Table 2 were computed at

each site over the entire season. While the range in MFB is rather large for each species

across all sites, the median MFB was below 50% for all species except C2H4, which is

substantially overpredicted by CMAQ. It should be noted that these species can vary

substantially from day to day, and days with very low modeled or observed values can

contribute to high MFB.

PM2.5 mass and speciation

Composite daily average predicted and observed concentrations of PM2.5 mass

(both daily average FRM data and continuous data), as well as major speciation –SO4,

NO3, NH4, EC, OM (defined here operationally as 1.8×blank-corrected organic carbon),

and crustal mass (sum of oxides of Al, Ca, Fe, Si, and Ti) – across the OTR were

7
compared in this analysis. The data cover the period May 15 – September 30, and again

the July 6-9 period was excluded, when numerous sites in the eastern US were affected

by large forest fires in Quebec. The continuous and FRM PM2.5 data are shown every

day, since there are ample daily FRM sites across the OTR. The speciation data included

here are daily averages every third day, and consist of the largely urban EPA STN and

the largely rural IMPROVE network. The two speciation networks collect PM2.5, SO4,

NO3, EC, OM, and crustal mass, while only the STN reports NH4 at a sufficient number

of locations.

Table 3 lists the median and range in mean fractionalized bias calculated at each

site over the season used in this analysis. The values listed in Table 3 were computed at

each site over the entire season. Figures 25-39 display time series of composite average

observed and predicted daily concentrations; in these figures, for each day the statistics

were computed using all monitors with valid data. The best qualitative agreement

between observed and modeled concentrations is exhibited for PM2.5 and SO4. Note that

in the case of crustal mass, the data from July 4 are also not included since this day is

greatly affected by fireworks. On July 4, the composite average observed and predicted

crustal concentrations were 4.59 μg m-3 and 1.74 μg m-3, respectively at the STN

monitors, and 4.46 μg m-3 and 0.99 μg m-3, respectively at the IMPROVE monitors.

As with the gaseous co-pollutant data, there is a substantial spread in MFB across

the sites. However, the median MFB for PM2.5 mass and SO4 was generally small

(<12%) for both urban and rural sites. CMAQ tends to overpredict NO3, more so at the

IMPROVE sites. CMAQ also tends to underpredict OM at both urban and rural sites,

although some of this discrepancy may be attributed to the fact that OM is operationally

defined and is highly dependent on the blank correction and multiplier to account for

other components of OM not directly measured. CMAQ tends to overpredict both EC

and crustal mass, especially at urban sites; similar to OM, the crustal mass overprediction

is related to the fact that this parameter is operationally defined.

Wet deposition of sulfate, nitrate, and ammonium

Observed and predicted wet deposition of SO4, NO3, and NH4 were compared

over the period May 14 – September 30. For this analysis, weekly or event-based wet

deposition amounts from the NADP/NTN (43 sites), NADP/AIRMoN (7 sites), and New

York State DEC (19 sites) covering the entire OTR plus all of VA and WV were

integrated over the four-and-a-half months. Because the observed weekly wet deposition

samples did include July 6-9, the corresponding CMAQ predictions also include this

period. Table 4 lists the model evaluation statistics for integrated wet deposition of SO4,

NO3, and NH4 at each site over the season, while Figures 40-42 compare the observed

and predicted weekly values relative to the 1:1 line.

Overall CMAQ tended to overpredict wet deposition of these ions. On a

percentage basis, the overprediction was least for SO4 and highest for NO3. The NME,

MNGE, MNB, and NMB were less than 50% for the three ions. Given that precipitation

is very difficult to predict, especially during the summer months when rainfall can vary

8
tremendously over a 12 km by 12 km area represented by this model grid, CMAQ did a

rather good job reproducing seasonal wet deposition over the OTR.

Upper-air O3, CO, and SO2 data

The University of Maryland operated an instrumented light aircraft during the

summer of 2002. On 26 days from May-August meteorological, trace gas, and particle

scattering/absorption data were collected during ascent or descent spirals over 41 regional

airports. In all, 144 spirals were performed from near the surface to about 3 km above

ground level. For this analysis, composite average profiles of O3, CO, and SO2 were

created over three time periods: “morning” (08-11 EST), “afternoon” (12-16 EST), and

“evening” (17-19 EST). The minute average observed concentrations were aggregated

into layer averages, which correspond to the lowest 15 model layers. Model layers are

increasingly thick away from the surface; the surface layer is about 20 m thick while the

15th layer is about 500 m thick (and centered about 2.8 km above the ground).

Figures 43-51 display the observed and predicted composite vertical profiles of O3, CO,

and SO2 for the three time periods. In terms of profile shape, CMAQ was in good

qualitative agreement for all three species above the surface during the afternoon hours.

For CO, the model tends to greatly underpredict observed levels near the surface,

whereas the predicted O3 and SO2 concentrations are closer to the respective observed

values.

Summary

Various model evaluation statistics are presented here for a variety of gaseous and

aerosol species in addition to O3. In general, the CMAQ results were best for daily

maximum O3 and daily average PM2.5 and SO4 mass. Many other species vary

tremendously over the course of a day, or from day to day, and small model over- or

underprediction at low concentrations can lead to large biases on a composite basis. It is

important to demonstrate that the model performs reasonably over the diurnal cycle, not

just in terms of daily maximum or average values. Also, it is important to demonstrate

that the model can reproduce concentrations above the ground level.

9
Table 1. Median and range in fractional error (FE, %) and mean fractionalized bias

(MFB, %) for daily maximum 8-hour O3 using the 40 ppb and 60 ppb observed

thresholds. The values using only SLAMS/NAMS sites are boldfaced, the values using

all sites are in regular font.

Metric, threshold Range (%) Median (%)

FE, 40 ppb +10 to +34%

+10 to +32%

+15%

+15%

MFB, 40 ppb -34 to +23%

-29 to +23%

-6%

-6%

FE, 60 ppb +9 to +40%

+9 to +40%

+15%

+15%

MFB, 60 ppb -40 to +22%

-40 to +22%

-12%

-11%

Table 2. Median and range in mean fractionalized bias (%) for daily average CO, NO,

NO2, SO2, C2H4, HCHO, and C5H8.

Pollutant Range in MFB (%) Median MFB (%)

CO (97 sites) -128 to +144% -10%

NO (75 sites) -182 to +116% -46%

NO2 (97 sites) -125 to +107% +13%

SO2 (134 sites) -139 to 140% +3%

C2H4 (19 sites) +28 to +168% +86%

HCHO (18 sites) -66 to +96% -13%

C5H8 (19 sites) -54 to +165% +43%

10
Table 3. Median and range in mean fractionalized bias (%) for daily average PM2.5, SO4,

NO3, NH4, EC, and OM.

Pollutant Range in MFB (%) Median MFB (%)

PM2.5 (FRM; 257 sites) -59 to +119% -4%

PM2.5 (continuous; 57 sites) -39 to +85% +5%

STN PM2.5 (49 sites) -45 to +102% -9%

IMPROVE PM2.5 (21 sites) -36 to +19% -10%

STN SO4 (49 sites) -21 to +60% +12%

IMPROVE SO4 (21 sites) -26 to +16% -7%

STN NO3 (49 sites) -73 to +406% +25%

IMPROVE NO3 (21 sites) -57 to +358% +64%

STN NH4 (49 sites) -36 to +112% +16%

STN EC (49 sites) -42 to +269% +34%

IMPROVE EC (21 sites) -60 to +146% -27%

STN OM (49 sites) -82 to -25% -58%

IMPROVE OM (21 sites) -60 to +7% -40%

STN crustal (49 sites) +2 to +546% +182%

IMPROVE crustal (21 sites) -18 to +163% +38%

Table 4. Model evaluation statistics for integrated wet deposition of SO4, NO3, and NH4

.

Parameter SO4 NO3 NH4

Observed average, mg m-2 1063 704 185

Predicted average, mg m-2 946 367 117

Correlation coefficient, R20.17 0.22 0.12

NME, % 34 49 48

RMSE, mg m-2 490 417 109

FE, % 36 62 57

MAGE, mg m-2 365 344 89

MNGE, % 36 45 46

MB, mg m-2 -118 -337 -68

MNB, % -3 -44 -28

MFB, % -13 -61 -44

NMB, % -11 -48 -37

11
Figure 1.

Observed and Predicted averages

208 SLAMS/NAMS sites; 40 ppb threshold

0

10

20

30

40

50

60

70

80

90

100

200205152002052320020531200206082002061620020624200207022002071020020718200207262002080320020811200208192002082720020904200209122002092020020928

p

p

b

obs avg, ppb

CMAQ avg, ppb

Figure 2.

Observed and Predicted averages

208 SLAMS/NAMS sites; 60 ppb threshold

0

10

20

30

40

50

60

70

80

90

100

200205152002052320020531200206082002061620020624200207022002071020020718200207262002080320020811200208192002082720020904200209122002092020020928

p

p

b

obs avg, ppb

CMAQ avg, ppb

12
Figure 3.

Observed and Predicted averages

28 special monitors; 40 ppb threshold

0

10

20

30

40

50

60

70

80

90

100

200205152002052320020531200206082002061620020624200207022002071020020718200207262002080320020811200208192002082720020904200209122002092020020928

p

p

b

obs avg, ppb

CMAQ avg, ppb

Figure 4.

Observed and Predicted averages

28 special sites; 60 ppb threshold

0

10

20

30

40

50

60

70

80

90

100

200205152002052320020531200206082002061620020624200207022002071020020718200207262002080320020811200208192002082720020904200209122002092020020928

p

p

b

obs avg, ppb

CMAQ avg, ppb

13
Figure 5.

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300 0 300 600 Miles

N

W E

S

FE, 40 ppb cutoff

# 10-15%

# 15-20%

# 20-25%

# 25-30%

# 30-35%

Figure 6.

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# 7-14%

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# 21-28%

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# 35-42%

300 0 300 600 Miles

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# -35 - -25%

# -25 - -15%

# -15 - -5%

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# 5-15%

# 15-25%

300 0 300 600 Miles

N

W E

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300 0 300 600 Miles

N

W E

S

MFB, 60 ppb cutoff

# -42 - -30%

# -30 - -18%

# -18 - -6%

# -6 - 6%

# 6-18%

# 18-30%

15
Figure 9.

Ozone (SLAMS/NAMS) - 208 sites

0.0

10.0

20.0

30.0

40.0

50.0

60.0

0 4 8 12 16 20 24

O3 (p

p

b)

Observed

Predicted

Figure 10.

Ozone (CASTNet & others) - 28 sites

0.0

10.0

20.0

30.0

40.0

50.0

60.0

0 4 8 12 16 20 24

O3 (p

p

b)

Observed

Predicted

16
Figure 11.

Continuous PM2.5 mass - 57 sites

0.00

5.00

10.00

15.00

20.00

25.00

30.00

0 4 8 12 16 20 24

P

M 2.5 (ug/m3)

Observed

Predicted

Figure 12.

Carbon monoxide - 97 sites

0.0

100.0

200.0

300.0

400.0

500.0

600.0

0 4 8 12 16 20 24

CO (p

p

b)

Observed

Predicted

17
Figure 13.

Nitric oxide - 75 sites

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

16.00

0 4 8 12 16 20 24

NO (p

p

b)

Observed

Predicted

Figure 14.

Nitrogen dioxide - 97 sites

0.00

5.00

10.00

15.00

20.00

25.00

30.00

0 4 8 12 16 20 24

N

O2 (p

p

b)

Observed

Predicted

18
Figure 15.

Sulfur dioxide - 134 sites

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

0 5 10 15 20 25

S

O2 (p

p

b)

Observed

Predicted

Figure 16.

Ethene - 19 sites

0.00

0.50

1.00

1.50

2.00

2.50

3.00

0 4 8 12 16 20 24

ethene (p

p

b)

Observed

Predicted

19
Figure 17.

Isoprene - 19 sites

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

0 4 8 12 16 20 24

iso

prene (p

p

b)

Observed

Predicted

Figure 18.

Observed and Predicted average CO (97 sites)

0

100

200

300

400

500

600

700

800

200205152002052320020531200206082002061620020624200207022002071020020718200207262002080320020811200208192002082720020904200209122002092020020928

p

p

b

obs avg, ppb

CMAQ avg, ppb

20
Figure 19.

Observed and Predicted average NO (75 sites)

0

2

4

6

8

10

12

14

16

18

200205152002052320020531200206082002061620020624200207022002071020020718200207262002080320020811200208192002082720020904200209122002092020020928

p

p

b

obs avg, ppb

CMAQ avg, ppb

Figure 20.

Observed and Predicted average NO2 (97 sites)

0

5

10

15

20

25

30

35

200205152002052320020531200206082002061620020624200207022002071020020718200207262002080320020811200208192002082720020904200209122002092020020928

p

p

b

obs avg, ppb

CMAQ avg, ppb

21
Figure 21.

Observed and Predicted average SO2 (134 sites)

0

1

2

3

4

5

6

7

8

200205152002052320020531200206082002061620020624200207022002071020020718200207262002080320020811200208192002082720020904200209122002092020020928

p

p

b

obs avg, ppb

CMAQ avg, ppb

Figure 22.

Observed and Predicted C2H4 (19 sites)

0

0.5

1

1.5

2

2.5

20020601200206062002061120020616200206212002062620020701200207062002071120020716200207212002072620020731200208052002081020020815200208202002082520020830

ppb

obs avg, ppb

CMAQ avg, ppb

22
Figure 23.

Observed and Predicted HCHO (18 sites)

0

1

2

3

4

5

6

7

8

9

20020601200206072002061320020619200206252002070120020707200207132002071920020725200207312002080620020812200208182002082420020830

ppb

obs avg, ppb

CMAQ avg, ppb

Figure 24.

Observed and Predicted C5H8 (19 sites)

0

0.5

1

1.5

2

2.5

3

20020601200206062002061120020616200206212002062620020701200207062002071120020716200207212002072620020731200208052002081020020815200208202002082520020830

ppb

obs avg, ppb

CMAQ avg, ppb

23
Figure 25.

Observed and Predicted PM2.5 (FRM; 257 sites)

0

5

10

15

20

25

30

35

40

45

200205152002052320020531200206082002061620020624200207022002071020020718200207262002080320020811200208192002082720020904200209122002092020020928

μ g m -3

obs avg, ug/m3

CMAQ avg, ug/m3

Figure 26.

Observed and Predicted PM2.5 (continuous; 57 sites)

0

5

10

15

20

25

30

35

40

45

200205152002052320020531200206082002061620020624200207022002071020020718200207262002080320020811200208192002082720020904200209122002092020020928

μ g m -3

obs avg, ug/m3

CMAQ avg, ug/m3

24
Figure 27.

Observed and Predicted PM2.5 (STN; 49 sites)

0

5

10

15

20

25

30

35

40

20020517200205262002060420020613200206222002070120020710200207192002072820020806200208152002082420020902200209112002092020020929

μ g m -3

obs avg, ug/m3

CMAQ avg, ug/m3

Figure 28.

Observed and Predicted PM2.5 (IMPROVE; 21 sites)

0

5

10

15

20

25

30

20020517200205262002060420020613200206222002070120020710200207192002072820020806200208152002082420020902200209112002092020020929

μ g m -3

obs avg, ug/m3

CMAQ avg, ug/m3

25
Figure 29.

Observed and Predicted SO4 (STN; 49 sites)

0

5

10

15

20

25

20020517200205262002060420020613200206222002070120020710200207192002072820020806200208152002082420020902200209112002092020020929

μ g m -3

obs avg, ug/m3

CMAQ avg, ug/m3

Figure 30.

Observed and Predicted SO4 (IMPROVE; 21 sites)

0

2

4

6

8

10

12

14

16

18

20020517200205262002060420020613200206222002070120020710200207192002072820020806200208152002082420020902200209112002092020020929

mg m -3

obs avg, ug/m3

CMAQ avg, ug/m3

26
Figure 31.

Observed and Predicted NO3 (STN; 49 sites)

0

0.5

1

1.5

2

2.5

3

3.5

20020517200205262002060420020613200206222002070120020710200207192002072820020806200208152002082420020902200209112002092020020929

μ g m -3

obs avg, ug/m3

CMAQ avg, ug/m3

Figure 32.

Observed and Predicted NO3 (IMPROVE; 21 sites)

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

20020517200205262002060420020613200206222002070120020710200207192002072820020806200208152002082420020902200209112002092020020929

μ g m -3

obs avg, ug/m3

CMAQ avg, ug/m3

27
Figure 33.

Observed and Predicted NH4 (STN; 49 sites)

0

1

2

3

4

5

6

7

20020517200205262002060420020613200206222002070120020710200207192002072820020806200208152002082420020902200209112002092020020929

μ g m -3

obs avg, ug/m3

CMAQ avg, ug/m3

Figure 34.

Observed and Predicted EC (STN; 49 sites)

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

20020517200205262002060420020613200206222002070120020710200207192002072820020806200208152002082420020902200209112002092020020929

μ g m -3

obs avg, ug/m3

CMAQ avg, ug/m3

28
Figure 35.

Observed and Predicted EC (IMPROVE; 21 sites)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

20020517200205262002060420020613200206222002070120020710200207192002072820020806200208152002082420020902200209112002092020020929

μ g m -3

obs avg, ug/m3

CMAQ avg, ug/m3

Figure 36.

Observed and Predicted OM (STN; 49 sites)

0

2

4

6

8

10

12

14

20020517200205262002060420020613200206222002070120020710200207192002072820020806200208152002082420020902200209112002092020020929

μ g m -3

obs avg, ug/m3

CMAQ avg, ug/m3

29
Figure 37.

Observed and Predicted OM (IMPROVE; 21 sites)

0

1

2

3

4

5

6

7

8

9

10

20020517200205262002060420020613200206222002070120020710200207192002072820020806200208152002082420020902200209112002092020020929

μ g m -3

obs avg, ug/m3

CMAQ avg, ug/m3

Figure 38.

Observed and Predicted crustal (STN; 49 sites)

0

0.5

1

1.5

2

2.5

3

20020517200205262002060420020613200206222002070120020710200207192002072820020806200208152002082420020902200209112002092020020929

μ g m -3

obs avg, ug/m3

CMAQ avg, ug/m3

30
Figure 39.

Observed and Predicted crustal (IMPROVE; 21 sites)

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

20020517200205262002060420020613200206222002070120020710200207192002072820020806200208152002082420020902200209112002092020020929

μ g m -3

obs avg, ug/m3

CMAQ avg, ug/m3

Figure 40.

Wet SO4 Deposition

0

500

1000

1500

2000

2500

0 500 1000 1500 2000 2500

Observed (mg/m2)

Predicted (mg/m 2

)

31
Figure 41.

Wet NO3 Deposition

0

200

400

600

800

1000

1200

1400

1600

0 200 400 600 800 1000 1200 1400 1600

Observed (mg/m2)

Predicted (mg/m 2

)

Figure 42.

Wet NH4 Deposition

0

50

100

150

200

250

300

350

400

450

500

0 50 100 150 200 250 300 350 400 450 500

Observed (mg/m2)

Predicted (mg/m 2

)

32
Figure 43.

Figure 44.

33

M orning (08-11 EST)

0

500

1000

1500

2000

2500

3000

40 45 50 55 60 65 70

O3 (ppb)

Z (m)

observed CMAQ

Afternoon (12-16 EST)

0

500

1000

1500

2000

2500

3000

50 60 70 80 90

O3 (ppb)

Z (m)

observed CMAQ
Figure 45.

Figure 46.

34

Evening (17-19 EST)

0

500

1000

1500

2000

2500

3000

40 50 60 70 80 90

O3 (ppb)

Z (m)

observed CMAQ

M orning (08-11 EST)

0

500

1000

1500

2000

2500

3000

0 100 200 300 400 500

CO (ppb)

Z (m)

observed CMAQ
Figure 47.

Figure 48.

35

Afternoon (12-16 EST)

0

500

1000

1500

2000

2500

3000

0 100 200 300 400 500

CO (ppb)

Z (m)

observed CMAQ

Evening (17-19 EST)

0

500

1000

1500

2000

2500

3000

0 100 200 300 400 500 600

CO (ppb)

Z (m)

observed CMAQ
Figure 49.

Figure 50.

36

M orning (08-11 EST)

0

500

1000

1500

2000

2500

3000

0 1 2 3 4 5 6

SO2 (ppb)

Z (m)

observed CMAQ

Afternooon (12-16 EST)

0

500

1000

1500

2000

2500

3000

0 1 2 3 4 5 6

SO2 (ppb)

Z (m)

observed CMAQ
Figure 51.

37

Evening (17-19 EST)

0

500

1000

1500

2000

2500

3000

0 1 2 3 4 5

SO2 (ppb)

Z (m)

observed CMAQ