Joshua Fu, Yun-Fat Lam* and Yang GaoJoshua Fu, Yun-Fat Lam* and Yang GaoUniversity of TennesseeUniversity of Tennessee

Daniel Jacob , Loretta Mickley and Shiliang Wu Daniel Jacob , Loretta Mickley and Shiliang Wu Harvard UniversityHarvard University

Oct 20, 2009

The effects of Climate Change to the The effects of Climate Change to the Future Air Quality in United StatesFuture Air Quality in United States

Joshua Fu , Yun-Fat Lam, University of TennesseeUniversity of TennesseeDaniel Jacob (PI), Loretta Mickley, Harvard UniversityHarvard University

John Seinfeld, California Institute of TechnologyCalifornia Institute of Technology David Streets, Argonne National LabArgonne National Lab

David Rind, GISS/NASAGISS/NASA

GLOBAL CHANGE AND AIR POLLUTION (GCAP)GLOBAL CHANGE AND AIR POLLUTION (GCAP)

SOURCE: GCAP group

GCAP: How will global change affect U.S. air quality

UT

Effect of Global Warming in Effect of Global Warming in GISS General Circulation ModelGISS General Circulation Model

Goddard Institute for Space Studies GCM: 9 layers, 4ox5o horizontal grid, CO2 + other greenhouse gases increased yearly from 2000 to 2050.

Carbon Monoxide: COsource: present-day anthropogenic

emissionssink: CO + present-day OH fields

Black Carbon: BCsource: present-day anthropogenic

emissionssink: rainout

1950 spin-up (ocean adjusts) 2000 increasing A1 greenhouse gas 2050

Timeline

spin up 1995-2002

2045-2052{

+2o C Temp change

July global mean temperature

Mickley et al., 2004Mickley et al., 2004

SOURCE: GCAP group

Effect of Climate Change on Regional StagnationEffect of Climate Change on Regional Stagnation

Pollution episodes double in duration in 2050 climate due to decreasing frequency of cyclones ventilating the eastern U.S; this decrease is an expected consequence of greenhouse warming.

GISS GCM 2’ simulations for 2050 vs. present-day climate using pollution tracers with constant emissions

Mickley et al. [GRL 2004]

Mid-latitudes cyclones tracking across southern Canada are the main drivers of northern U.S. ventilation

2045-2052

1995-2002

summer

Northeast U.S.CO tracer

SOURCE: GCAP group

Climatological Fact Climatological Fact

Annual number of surface cyclones and anticylones over North America

Cyclone frequency at 30o-60oN

cyclones

anticyclones

1000

100

500

1950 1980

Agee [1991]

McCabe et al. [2001]

SOURCE: GCAP group

DECREASE IN FREQUENCY OF MID-LATITUDE DECREASE IN FREQUENCY OF MID-LATITUDE CYCLONES OVER PAST 50 YEARSCYCLONES OVER PAST 50 YEARS

Global model vs. Regional ModelGlobal model vs. Regional Model

Atmospheric component

Sea Ice component

Ocean component

Land surface model

component

Climate

Air Quality, Heat waves, Flooding, Drought, Human Health

Missing Missing aerosol aerosol

feed back feed back

Global ModelGlobal Model Regional ModelRegional Model

Two-ways coupled climate and chemistry

One-way coupled climate and chemistry

Direct Direct affect solar affect solar radiationradiation

Significant of Regional ModelSignificant of Regional Model

• Resolution : down to 1 x 1 km– Taking advantages of detail geographical

information in meteorology modeling, as well as highly reliable emission inventories for ozone and aerosol modeling

• All the equations in regional model are designed to use in fine resolution conditions– Scalability issue in global model

• Regional/urban climate and air quality conditions can be simulated to provide information for local and regional planning – It has better implication in model outputs

Development of downscaling approachDevelopment of downscaling approach

– Analysis of 2000-2050 trends in air

pollution meteorology

– Development of GISS/GEOS-Chem interface

– Development of GISS/MM5 interface

– Development of future emission inventories for carbonaceous aerosols

– Application of GISS/GEOS-Chem to 2000-2050 trends in ozone and PM (IPCC A1B scenario)

– Statistical projection of 2000-2050 ozone trends

GISS GCM 31950-2050transient climate

simulation

Interface Developed

Greenhouse gases

GEOS-Chem CTM

global O3-PM-Hgsimulation

MM5 mesoscaledynamics simulation

CMAQO3-PM-Hgsimulation

met. input

boundaryconditions

2050 vs. 2000

climate

IPCC scenarios

and derivedemissions

ozone and PMSMOKE derived

emissions

GISS GCM 31950-2050transient climate

simulation

Interface Developed

Greenhouse gases

GEOS-Chem CTM

global O3-PM-Hgsimulation

MM5 mesoscaledynamics simulation

CMAQO3-PM-Hgsimulation

met. input

boundaryconditions

2050 vs. 2000

climate

IPCC scenarios

and derivedemissions

ozone and PMSMOKE derived

emissions

ObjectiveObjective

Investigate the future air quality in United States for Investigate the future air quality in United States for year 2050 using regional air quality model, CMAQ & year 2050 using regional air quality model, CMAQ & MM5MM5

Study the effect of global warming in regional scale Study the effect of global warming in regional scale for both climate and air qualityfor both climate and air quality

Examine the effect of change of anthropogenic Examine the effect of change of anthropogenic emissions emissions

Determine the emission reduction offsets required Determine the emission reduction offsets required to maintain NAAQSto maintain NAAQS

Models:Models:

Global ModelsGlobal Models

GISS-GCM III (GISS-GCM III (GISS/NASA)GISS/NASA)GEOS-Chem IV (HARVARD UNIVERSITY)GEOS-Chem IV (HARVARD UNIVERSITY)

Regional ModelsRegional Models

MM5 and WRF (NCAR)MM5 and WRF (NCAR) CMAQ 4.6 (EPA and others)CMAQ 4.6 (EPA and others)

Interface Program Development and Regional Interface Program Development and Regional Modeling (UT)Modeling (UT)

GISS2MM5 => MM5 (UT)GISS2MM5 => MM5 (UT) GEOS-Chem => CMAQ (UT)GEOS-Chem => CMAQ (UT)

Model ConfigurationsModel Configurations

GISS general circulation model IIIGISS general circulation model III

Global climate model Provide initial guess

values for MM5 (Both current and future climate conditions - e.g. 2000 and 2050)

4° x 5° horizontal resolution

30 vertical sigma/pressure layers

Global Model ConfigurationsGlobal Model Configurations

Climate ModelClimate Model

GEOS-Chem IVGEOS-Chem IV

Global chemistry model Provide initial and boundary

conditions for CMAQ 2° x 2.5° horizontal resolution 28 vertical sigma/pressure

layers Take into account of volcanic

events, wild fire, lightning and dust storm across the globe

Chemistry ModelChemistry Model

MM5MM5

Regional climate model

Terrain followed sigma

coordination

Resolution: 108km and nest

down to 36km (can be down to 1

km)

43 vertical sigma/pressure layers

Preprocessor: TERRAIN,

REGRID, LITTLE_R, INTERPF and

NESTDOWN

Regional Model ConfigurationsRegional Model Configurations

Climate ModelClimate Model

CMAQ 4.6CMAQ 4.6

14 layers (from the MM5 sigma levels)

36 km horizontal resolution (in this study)

ICON and BCON from GEOS-Chem from 3 hrs to one hour average

GISS/MM5 meteorological Inputs

Input emission is compatible with 2001 EPA National Emission Inventory

Chemistry ModelChemistry Model

Example Results of MM5 Outputs from GISSExample Results of MM5 Outputs from GISS

GISS surface wind and temperature Inputs

Year 2000

Year 2050

• Source:L. Mickley (Harvard) 108 km - CONUS108 km - CONUS 36 km - CONUS36 km - CONUS

GISS

MM5 MM5

GISS Vs. MM5 GISS Vs. MM5 A

vera

ge

d Z

on

al

Te

mp

era

ture

(K

)

288290292294296298300302304

Time (hour)

6/1 6/6 6/11 6/16 6/21 6/26 7/1

288290292294296298300302304

GISS MM5-108km MM5-36km

YEAR 2000

YEAR 2050

GISS Vs. MM5-108km: RMSE = 0.18 KGISS Vs. MM5-36km: RMSE = 0.08 K

GISS Vs. MM5-108km: RMSE = 0.27 K

GISS Vs. MM5-36km: RMSE = 0.08 K

GISS Vs. MM5 (JJAS)GISS Vs. MM5 (JJAS)

NE

SE

MidN

297 297300 300 298

302298 298

302 300 299304

297 298300 301 299 303

290

295

300

305

310

315

320

325

330

MidN NE SE MidN NE SE

2000 2050

zona

l tem

pera

ture

(K)

GISS MM5-108km MM5-36km

Average Temperature (K)

Domain GISSMM5-

108kmMM5-36km

MidN 2.5 2.6 3.2NE 1.2 1.1 0.6SE 2.3 2.3 3

2050 - 2000

MAX & AVG Temperature

GISS Vs. MM5 (JJAS)GISS Vs. MM5 (JJAS)

Temperature RMSE is below 0.4 K. And the mean bias is close to 0.1 K << 0.5 (benchmark)

Wind speed RMSE is less than 0.2 m/s << 2 m/s (benchmark). For the mean bias, the value is 0.1 m/s

Wind direction RMSE is less than 20° and mean bias is less than 1 ° << 10 °

MidN NE SE

Win

d S

pee

d R

MS

E

(m/s

)

0.0

0.2

0.4

0.6

0.8

1.0

MidN NE SE

Win

d d

irec

tio

n R

MS

E

(

deg

ree)

0

20

40

60

80

MidN NE SE

MidN NE SE

Tem

per

atu

re R

MS

E

(

K)

0.0

0.2

0.4

0.6

0.8

1.0

MidN NE SE

MidN NE SE

GISS Vs. MM5-108km GISS Vs. MM5-36km

CMAQ Simulations ScenariosCMAQ Simulations Scenarios

2000 climate with 2000 emission

2050 climate with 2000 emission

2000 climate with 2050 emission

2050 climate with 2050 emission

Climate/Emission Climate/Emission ContributionsContributions

Study period: June 1 to September 1 (Ozone season)

IPCC NOx IPCC NOx Emission Emission ScenarioScenario

X

2000 NO2000 NO22

2050 NO2050 NO22Emission ProjectionEmission Projection

Maximum Ozone ConcentrationMaximum Ozone Concentration

2000climate-2000emi 2050climate-2000emi

2000climate-2050emi 2050climate-2050emi

warmer

Fu et al. 2008 Emission has more effect than climate change on pollution events

0

10

20

30

40

50

60

70

80

90

100

MidN NE SE MidN NE SE MidN NE SE MidN NE SE

2001 2001_fut 2050 2050_fut

Ozo

ne

co

nc

en

tra

tio

n (

pp

bv

)

GEOS-Chem CMAQ

175 170

130140

149

125142

203

162

120

177

145

0

50

100

150

200

250

300

MidN NE SE MidN NE SE MidN NE SE MidN NE SE

2001 2001_fut 2050 2050_fut

Ozo

ne c

on

cen

trati

on

(p

pb

v)

GEOS-Chem CMAQ

CMAQ Simulations – Output (JJAS)CMAQ Simulations – Output (JJAS)

MAXIMUM OZONE

AVERAGE OZONE

Source: Harvard University

GEOS-Chem Vs. CMAQ (JJAS)GEOS-Chem Vs. CMAQ (JJAS)

0.1 1 10 30 50 70 90 99 99.999.99

0

20

40

60

80

100

120

140

0.1 1 10 30 50 70 90 99 99.9

0

20

40

60

80

100

120

NE

0.1 1 10 30 50 70 90 99 99.90

20

40

60

80

100

120

0.010.1 1 10 30 50 70 90 99 99.9

0

20

40

60

80

100

120

0.1 1 10 30 50 70 90 99 99.999.990

20

40

60

80

100

120

140

160

180

0.1 1 10 30 50 70 90 99 99.999.99

0

20

40

60

80

100

120

20002000_fut20502050_fut

SEMidN

CM

AQ

GE

OS

-Ch

em

Cumulative Probability (%)

MD

A8

Ozo

ne C

once

ntra

tion

(ppb

)

92 94 96 98 100

60

65

70

75

80

85

90

40 60 80 100

40

50

60

70

80

90

NE

40 50 60 70 80 90 10040

50

60

70

80

90

40 50 60 70 80 90 100

40

50

60

70

80

90

92 94 96 98 10060

65

70

75

80

85

90

92 94 96 98 100

60

65

70

75

80

85

90

20002000_fut20502050_fut

SEMidN

CM

AQ

GE

OS

-Ch

em

Cumulative Probability (%)

GEOS-Chem Vs. CMAQ (JJAS)GEOS-Chem Vs. CMAQ (JJAS)

GEOS-Chem Vs. CMAQ (JJAS) – MidNGEOS-Chem Vs. CMAQ (JJAS) – MidN

92 94 96 98 100

60

65

70

75

80

85

90

0 20 40 60 80 1002

3

4

5

6

7

8

MidN

Daily Maximum avg 8-hr O3 (ppb) Temperature (K) Wind Speed (m/s)

0 20 40 60 80 100300

305

310

315

320

20002050

Large difference in temperature

Small difference in wind speed

The CMAQ’s trend is similar as GEOS-Chem’s trend (Temperature dominated case)

20002000_fut20502050_fut

0 20 40 60 80 100300

305

310

315

320

NE

92 94 96 98 10060

65

70

75

80

85

90

Daily Maximum avg 8-hr O3 (ppb) Temperature (K) Wind Speed (m/s)

0 20 40 60 80 1002

3

4

5

6

7

8

2050 wind speed

2000 wind speed

GEOS-Chem Vs. CMAQ (JJAS) - NEGEOS-Chem Vs. CMAQ (JJAS) - NE

Small difference in temperature

Small difference in wind speed

The CMAQ’s trend is not similar as GEOS-Chem’s trend (Emission domination case)

20002000_fut20502050_fut

Daily Maximum avg 8-hr O3 (ppb) Temperature (K) Wind Speed (m/s)

92 94 96 98 100

60

65

70

75

80

85

90

20002000_fut20502050_fut

0 20 40 60 80 100300

305

310

315

320

0 20 40 60 80 1002

3

4

5

6

7

8

2000 wind speed

2050 wind speed

GEOS-Chem Vs. CMAQ (JJAS) – SEGEOS-Chem Vs. CMAQ (JJAS) – SE

Large difference in temperature

Large difference in wind speed

The CMAQ’s trend is not similar as GEOS-Chem’s trend (Cloud dominated case)

?? Why different from NE ??

• Global downscaling of GISS and GEOS-Chem have successfully performed with high confidence.

• The ozone trend (2050 – 2000) of GEOS-Chem and CMAQ are found to be quite difference, where GEOS-Chem is much more temperature driven (may due to the coarse resolution of meteorological data)

• In GEOS-Chem, climate change is a stronger factor than emission change for MidN and NE, but not showing in SE

• In CMAQ, only MidN have shown stronge climate change effect.

• Overall, the maximum zonal ozone concentration in 2050 is much higher than 2000. However, the probability of getting higher ozone may not higher. The convection and cloud cover have played important role on this issue.

RemarksRemarks

THANK YOU!

Average Aerosol (PMAverage Aerosol (PM2.52.5) Concentration) Concentration

BLACK CARBONBLACK CARBON SULFATE AEROSOLSULFATE AEROSOL

BLACK CARBON - AVERAGE (ug/m3)

0.0

0.1

0.1

0.2

0.2

0.3

0.3

0.4

0.4

0.5

Mid-West North-East South-East

2001met - 2001emi

2001met - 2050emi

2050met - 2001emi

2050met - 2050emi

SULFATE AEROSOL - AVERAGE (ug/m3)

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

Mid-West North-East South-East

2001met - 2001emi

2001met - 2050emi

2050met - 2001emi

2050met - 2050emi

Climate Effect

Emission Effect

Emission has more effect than climate change on pollution events ?

Climate change doesn’t effect South-East ?

USUS USUS