Operational and diagnostic evaluations of ozone 

forecasts by the Eta-CMAQ model suite during the 2002 

new England air quality study (NEAQS)

Shaocai Yu$, Rohit Mathur+, Daiwen Kang$, Kenneth Schere+,

Brian Eder+, Jonathan Pleim+,

Atmospheric Sciences Modeling Division

NERL, U.S. EPA, RTP, NC 27711.

$ On assignment from Science and Technology Corporation 

+ On assignment from Air Resources Laboratory, NOAA
Introduction

Introduction

 O3

forecast

 Necessary 

 O3: a secondary pollutant, 

 produced by pollution from natural and human activities.

 Warn the public: 

 unhealthy air

 voluntarily reduce emission-producing activities

 Forecasting methods (EPA, 1999):

 Persistence, climatology, regression equation etc.

 3-D air quality models

 Advantages of 3-D air quality models

 Spatial and temporal distributions of O3and its precursors

 Understand chemical-physical processes controlling O3formation
CMAQ Community Multiscale Air Quality Model

 Community Model

 Multiscale

– consistent model structures for interaction of urban through 

Continental scales

 Multi-pollutant

– ozone, speciated particulate matter, visibility, acid deposition

and air toxics

Objective

Evaluate 3-D Eta-CMAQ model performance on the 

spatial and temporal variations of O3 with AIRNOW 

Obs over the NE US

Diagnostically examine the ability of Eta-CMAQ in 

representing chemical-physical processes for O3

formation with 2002 NEAQS data 
Model Description

 Eta-CMAQ model suite: (R. Mathur et al. Talk)

 Period: August 6 to August 17, 2002 August 6 to August 17, 2002

 Using results: 12 UTC run and 

target period for next day forecast (04 UTC to 03 UTC)

NE Model domain and site locations

AIRMAP sites
Results

1. O3 episode after 8/11

0

5

10

0 5 10

0.0

0.2

0.4

0.6

0.8

1.0

1.2 (b) SO2

/NOy ratio (CS)

0

2

4

6

8

(a) SO2 (CS) ppb

0

0.7

1.4

0 0.7 1.4

0

12

24

0 12 24

0

1.3

2.6

0 1.3 2.6

Time (EST)

Obs

Model

Obs

Model

50.0

100.0

150.0

200.0

250.0

300.0

350.0 (c) CO (CS) ppb

0

180

360

0 180 360

0

5

10

15

20 ppb (d) SO2

 (TF)

0.0

0.5

1.0

1.5

2.0

2.5 (e) SO2

/NOy ratio (TF)

0

250

500

0.0 0 250 500

100.0

200.0

300.0

400.0

8/6 8/8 8/10 8/12 8/14 8/16 8/18

(f) CO (TF) ppb

Parrish et al., 1991:

•Mobile source: CO, NOx

•Point source (power 

plants): SO2, NOx

•SO2/NOy<1:mobile source

•SO2/NOy>1:point source

Sites were significantly 

influenced by polluted 

plume after 8/11:

mobile and point 

sources

SO2 (CS)

SO2 (TF)

CO (CS)

CO (TF)

8/11
Results

1. O3 episode (8/6-8/17/2002)

Modeled and observed (diamond) O3(ppb)

~45 ppbv O3 ~110 ppbv O3
Results

2. Operational evaluation at AIRNOW sites

Max 8hr

Max 1hr

AQS O3(ppb)

M

o

d

e

l

O

3

NMB (max 8-hr)

-92 -90 -88 -86 -84 -82 -80 -78 -76 -74 -72 -70 -68

34

36

38

40

42

44

46

48

 -33.3 to -20

 -20 to 0

 0 to 25

 25 to 50

 50 to 75
Results

3. Time-series eval. 

Time (EST)

Concentrations (ppb)

0.0

50.0

100.0

150.0

O3(Obs)

O3 (Model)

0

80

160

0 80 160

Harvard Forest

0.0

0.5

1.0

1.5

2.0 NO(Obs)

NO (Model)

0

1

2

0 1 2

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0 NO2(Obs)

NO2 (Model)

0

4

8

0 4 8

0.0

1.0

2.0

3.0 PAN(Obs)

PAN (Model)

0

2.5

5

0 2.5 5

0.0

100.0

200.0

300.0

400.0

500.0 CO(Obs)

CO (Model)

0

300

600

0 300 600

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

8/6 8/8 8/10 8/12 8/14 8/16 8/18

NOy(Obs)

NOy (Model)

0

20

40

0 20 40

Obs

Model

O3

NO

NO2

PAN

CO

NOy

Harvard Forest

8/11
Hanna et al. (2001):

•50% uncertainty in JNO2

• 40 ppbv (or 20%) 

uncertainty in max O3

•Model reproduces 

• 64-77% of observed 

JNO2 within a factor of 1.5

Priority: more accurate 

determination of JNO2 in 

model

Results

3. Time-series at AIRMAP sites
Results

3. O3 Lidar vertical profiles

Obs

Model

Extremely tough test:

Temporal and 3-D field 

correctly

•Model reproduced obs at low 

altitude and more uniform

•Over predictions increase 

with altitude Ship Track
Results (diagnostic evaluation)

NOx-sensitive regimes: [O3]/[NOx], Photochemical age: [NOz]/[NOy],

O3 production efficiency: [NOz]/[O3]

Arnold et al., 2003:

•[O3]/[NOx]<14: VOC-sensitive

>46: NOx-sensitive

Both model and obs: three sites are mainly under strongly NOxsensitive conditions (>53%)

NOx-sensitive regimes: [O3]/[NOx]
Results Photochemical age: [NOz]/[NOy]

Arnold et al., 2003:

•[NOz]/[NOy]>0.6: aged NOx plume

0.0

0.2

0.4

0.6

0.8

1.0

Obs

Model

(a) CS

0.0

0.2

0.4

0.6

0.8

(b) TF

N

Oz

/N

Oy

ratio

0.0

0.2

0.4

0.6

0.8

(c) HF

0 2 4 6 8 10 12 14 16 18 20 22

Time (EST)

For daytime (6 to 18 EST) hours: 

NOz/NOy>0.6 CS TF HF

Obs 82% 72% 82%

Model 96% 56% 87%

Model and Obs: accumulating O3

aging the NOx

in the similar way. 

CS

TF

HF
Results O3 production efficiency : O3-NOz

slope

10

20

30

40

50

60

70

80

Obs 

Model 

(a) CS

0

20

40

60

80

100

120

140

160

[O3] (ppb)

(b) TF

0

20

40

60

80

100

120

140

160

02468 10 12 14 16

NO

z

 (ppb)

(c) HF

05

10

05 10

08

16

08 16

Model

Obs

NO

z

 (ppb)

048

048

Parrish et al., 1993 : • O3-NOz

slope: 

upper limit of 

:

•Obs: 8.3 to 10.0 •Model: 4.2 to 5.1

N



N



N



At rural sites in E US NOz (Olszyna et al., 1994):  N : 5 to 10 

NOz

O3

CS

TF

HF
Contacts:

Brian K. Eder

email: eder@hpcc.epa.gov 

www.arl.noaa.gov/

www.epa.gov/asmdnerl

Conclusions

 Model captured the buildup of O3and its episode after August 11 and 

reproduce spatial distr. of O3for the daytime over the NE US very well 

with NMB<20%. 

 For operational evaluation at AIRNOW sites, model reproduced most of 

observed max 8-hr O3 within factor of 1.5 with NMB=9%.

 Model captured 64-77% of observed JNO2 within a factor of 1.5

 Model reproduced the O3 Lidar vertical profiles at low altitude (355 to 

500 m) well but tended to overpredict in high altitude.

 Both model and Obs show the AIRMAP sites are mainly under strongly

NOx-sensitive conditions (>53%) and are accumulating O3 and aging 

the NOx in the similar way in these sites

 The modeled upper limits (4.3 to 5.1) of estimated by O3-NOz 

slopes are about half of the observations (8.3 to 10.0) 

N


Future research needed 

For real time forecast of O3, key is the prognostic 

model forecasts of meteorological fields:

Cold front patterns, 

cloud cover 

wind fields

 Improve photochemical mechanism and emission

 Improve the model performance for JNO2, 

especially during the cloudy periods

 More evaluation with extensive data from the 

2004 NEAQS field campaign is underway
Disclaimer

The research presented here was performed under the Memorandum of Understanding 

between the U.S. Environmental Protection Agency (EPA) and the U.S. Department of 

Commerce's National Oceanic and Atmospheric Administration (NOAA) and under

agreement number DW13921548. Although it has been reviewed by EPA and NOAA and 

approved for publication, it does not necessarily reflect their policies or views.