Lessons Learned:One-Atmosphere Photochemical Modeling

in Southeastern U.S.

Presentation from Southern Appalachian Mountains Initiativeto Meeting of Regional Planning Organizations

December 3, 2002

SAMI Atmospheric Modeling

Unique Contributions: Demonstrated fully-integrated one-atmosphere model

ozone, aerosols, and deposition“performance comparable to or better than recent

applications of CMAQ or REMSAD”

In 1997 selected to use: RAMS-3B meteorological model EMS-95 emissions model Urban to Regional Multi-scale (URM) air quality model

variable grid (12-km over Southern Appalachian Mountains) SAPRC chemical mechanism for gasesISORROPIA for aerosolsReactive Scavenging Module for depositionDecoupled Direct Method for sensitivity to emissions changes

SAMI Atmospheric Model

SAMI Atmospheric Modeling Domain

Georgia Institute of Technology

SAMI Atmospheric Modeling

Unique Contributions: Selected episodes to represent annual and seasonal

air quality measures based on meteorology characterized for 5-year period9 episodes in Feb, Mar, Apr, May, Jun, Jul, Aug

Lesson learned: prioritize computational power: greater spatial resolution or longer time periods?

SAMI Atmospheric Model: Lessons Learned

Emissions Inventory uncertainties: especially NH3, primary OC; non-road, area sources

Meteorological Model performance: clouds and precipitation affect chemistry and deposition wind speed and direction, mixing heights affect transport

SAMI Atmospheric Model: Lessons Learned

Air Quality Observations limited spatially and temporally: PM2.5 data, especially NH4 wet and dry deposition data vertical profiles for initial and boundary conditions

SAMI Atmospheric Model: Lessons Learned

Photochemical Model Performance: SO4 and OC best performance (+/- 50%), largest

components of PM2.5 overpredict NO3, soil, and EC; small components SO4 not fully neutralized by NH4, atmosphere NH4-

limited need better measures: NH3, NH4, primary vs secondary

OC

URM Model Performance - Fine Particle Mass Great Smoky Mtns

2/01/01

SO4 NO3 NH4 ORG EC SOIL

0

10.0

20.0

30.0

Con

cent

ratio

n (

g/m

3)

Class 5Class 4Class 3Class 2Class 1

2/09/94 3/24/93 4/26/95 8/04/93 8/07/93 8/11/93 7/12/95 7/31/91 7/15/95

Modeled (left) IMPROVE (right)

July 1995May 1995May 1993March 1993February 1994July 1991June 1992August 1993April 1995

0.0

5.0

10.0

15.0

20.0

25.0

0.0 5.0 10.0 15.0 20.0 25.0

IMPROVE Measurements (g/m3)

UR

M M

odel

ed C

once

ntra

tion

(g/

m3)

URM Model Performance: Sulfate Fine Particle Mass

+ 50%

- 50%

(based on data from 3-10 IMPROVE sites in 12, 24, and 48 km grids)

July 1995May 1995May 1993March 1993February 1994July 1991June 1992August 1993April 1995

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0

URM Model Performance: PM2.5 MassU

RM

Mod

eled

Con

cent

ratio

n (

g/m

3)

IMPROVE Measurements (g/m3)

+ 50%

- 50%

(based on data from 3-10 IMPROVE sites in 12, 24, and 48 km grids)

Wet Ammonium Deposition Normalized Percent Bias

0

50

100

150

200

250

July 11-18, 1995

May 23-30, 1995

May 11-18, 1993

March 23-30,1993

Feb 8-15, 1994

April 26 - M

ay 3,1995

August 3-11,

1993

June 24-29,1992

July 23-30, 1991

Nor

mal

ized

Per

cent

Bia

s

(based on data from 9-14 NADP wet deposition sites in 12, 24, and 48 km grids)

SAMI Atmospheric Modeling

Unique Contributions: To assess effects, used modeled relative change in

air quality to adjust measured air quality:visibility ozone effects to forestsacid deposition effects to streams and forests

Lesson learned: bound relative reduction factor by model performance

SAMI Atmospheric Modeling

Unique Contributions: Used direct sensitivity analyses to evaluate state

contributions to Class I areasDecoupled Direct Method (DDM-3D) evaluated responses to 10% change in emissions

Lessons learned: trust relative contributions rather than absolute daily source contributions from DDM compare favorably to

daily back trajectories

DDM Sensitivity Performance

GaseousSpecies

Aerosol Species

Wet Deposition

Species

SO2 NOx NH3 VOCsOzone Good Good

SO2 Good

NH3 Good

SO4 Good Good

NO3 Good Poor Good

NH4 Good Good Fair Good

OC Good Good

ECSOIL

PM2.5 Good Good Poor Good

SO4 Good

NO3 Poor Good Poor Good

NH4 Poor Poor Poor Poor

Fair

Annual SO4 Fine Particles Response to 10% Reduction in SO2 Emissions from 2010 A2 strategy

SO4

Fine

Par

ticle

Res

pons

e (%

)

-8.0

-6.0

-4.0

-2.0

0.0

Sip

sey,

AL

Co

hu

tta,

GA

Joyc

e K

ilm

er,

NC

Gre

at S

mo

kyM

tn,

TN

Sh

inin

gR

ock

, N

C

Lin

vill

eG

org

e, N

C

Jam

es R

iver

F

ace,

VA

Sh

enan

ho

ah,

VA

Ott

er C

reek

, W

V

Do

lly

So

ds,

WV

Non-SAMI states

SAMI states

Appendix

Sulfate Aerosol Normalized Percent Bias

-100

-50

0

50

100

150

7/12/19957/15/19957/19/19995/24/19955/27/19955/12/19935/15/19933/24/19933/27/19933/31/19932/9/19942/12/19944/26/19954/29/19955/3/19956/24/19926/27/19928/4/19938/7/19938/11/19937/24/19917/27/19917/31/1991

Nor

mal

ized

Per

cent

Bia

s

(based on data from 3-10 IMPROVE sites in 12, 24, and 48 km grids)

Ammonium Aerosol Normalized Percent Bias

-60

-40

-20

0

20

40

60

80

100

120

7/12/1995

7/15/1995

7/19/1999

5/24/1995

5/27/1995

5/12/1993

5/15/1993

3/24/1993

3/27/1993

3/31/1993

2/9/1994

2/12/1994

4/26/1995

4/29/1995

5/3/1995

6/24/1992

6/27/1992

8/4/1993

8/7/1993

8/11/1993

7/24/1991

7/27/1991

7/31/1991N

orm

aliz

ed M

ean

Bia

s

(based on data from 3-10 IMPROVE sites in 12, 24, and 48 km grids)

Organic Aerosol Normalized Percent Bias

-60

-40

-20

0

20

40

60

80

100

120

7/12/1995

7/15/1995

7/19/1999

5/24/1995

5/27/1995

5/12/1993

5/15/1993

3/24/1993

3/27/1993

3/31/1993

2/9/1994

2/12/1994

4/26/1995

4/29/1995

5/3/1995

6/24/1992

6/27/1992

8/4/1993

8/7/1993

8/11/1993

7/24/1991

7/27/1991

7/31/1991N

orm

aliz

ed P

erce

nt B

ias

(based on data from 3-10 IMPROVE sites in 12, 24, and 48 km grids)

Nitrate Aerosol Normalized Percent Bias

-50

0

50

100

150

200

250

7/12/1995

7/15/19957/19/19995/24/19955/27/19955/12/19935/15/19933/24/19933/27/19933/31/19932/9/19942/12/19944/26/19954/29/19955/3/19956/24/19926/27/19928/4/19938/7/19938/11/19937/24/19917/27/19917/31/1991

Nor

mal

ized

Per

cent

Bia

s

(based on data from 3-10 IMPROVE sites in 12, 24, and 48 km grids)

PM 2.5 Normalized Percent Bias

-100

-50

0

50

100

150

200

2/9/94

3/24/93

3/31/93

4/29/95

5/15/93

5/24/95

6/24/92

7/24/91

7/31/91

7/15/95

8/4/93

8/11/93N

orm

aliz

ed B

ias

(%)

Normalized Bias of +/- 50% is potential criteria for aerosol model performance

(based on data from 3-10 IMPROVE aerosol sites in 12, 24, and 48 km grids)

2/12/94

3/27/93

4/26/95

5/12/93

5/21/95

5/27/95

6/27/92

7/27/91

7/12/95

7/19/95

8/7/93

Modeled on Left, IMPROVE On Right

URM Model Results vs. Observations for July 15, 1995

PM 2

.5 (

g/m

3)

0.0

10.0

20.0

30.0

40.0

Aerosol Model Performance

Sipsey,AL

GreatSmoky

Mtns.,TN

Shining Rock,

NC

James River

Face, VA

Shenandoah,VA

Dolly Sods, WV

2/01/01

SO4 NO3 NH4 ORG EC SOIL

Wet Sulfate Deposition Normalized Percent Bias

-30

-25

-20

-15

-10

-5

0

5

10

July 11-18,1995

May 23-30,1995

May 11-18,1993

March 23-

30, 1993

Feb 8-15,1994

April 26 -M

ay 3,1995

August 3-

11, 1993

June 24-29,1992

July 23-30,1991

Nor

mal

ized

Per

cent

Bia

s

(based on data from 9-14 NADP wet deposition sites in 12, 24, and 48 km grids)

Confidence Levels in SAMI 1990 Base Year inventory

Utility Industry HighwayVehicles

NonroadEngines

Area

SO2 +++++ ++++ +++ ++ ++

NOx +++++ ++++ +++ ++ ++

VOC +++ +++ +++ ++ ++

NH3 +++ +++ ++ + +

PM2.5 +++ +++ ++ + +