carey jang, pat dolwick, norm possiel, brian timin, joe tikvart u.s. epa

Multi-Scale Applications of Multi-Scale Applications of U.S. EPA’s U.S. EPA’s

Third-Generation Air Quality Modeling System Third-Generation Air Quality Modeling System

(Models-3/CMAQ)(Models-3/CMAQ)

Carey Jang, Pat Dolwick, Norm Possiel, Brian Timin, Joe Tikvart

U.S. EPAOffice of Air Quality Planning

and Standards (OAQPS)

Research Triangle Park, NC , U.S.A.

OUTLINEOUTLINE

Models-3/CMAQ systemModels-3/CMAQ system

• One-Atmosphere perspectiveOne-Atmosphere perspective

Multi-Scale Applications of Models-3/CMAQMulti-Scale Applications of Models-3/CMAQ• Western U.S. ApplicationWestern U.S. Application

• Annual Nationwide U.S. ApplicationAnnual Nationwide U.S. Application

• Eastern U.S. ApplicationEastern U.S. Application

• Hemispheric/Continental Modeling InitiativeHemispheric/Continental Modeling Initiative

Features of Models-3/CMAQFeatures of Models-3/CMAQ

““Open-Access” Community-Based Models :Open-Access” Community-Based Models :• User-friendly, Modular, Common modeling framework for User-friendly, Modular, Common modeling framework for

scientists and policy-makers.scientists and policy-makers.

Advanced Computer Technologies :Advanced Computer Technologies :• High performance hardware and software technologies High performance hardware and software technologies

(Cross-platform, GUI, distributed computing, visualization (Cross-platform, GUI, distributed computing, visualization tools, etc.). tools, etc.).

““One-Atmosphere” Modeling :One-Atmosphere” Modeling :• Multi-pollutant (Ozone, PM, visibility, acid Multi-pollutant (Ozone, PM, visibility, acid

deposition, air toxics, etc.), Multi-scale.deposition, air toxics, etc.), Multi-scale.

Air Toxics

PM

Acid Rain

Visibility

Ozone

Regulating Air Pollution: One-Regulating Air Pollution: One-Atmosphere ApproachAtmosphere Approach

Mobile Mobile SourcesSources

Industrial Industrial SourcesSources

Area Area SourcesSources

(Cars, trucks, airplanes, boats, etc.)

(Power plants, factories, refineries/chemical plants, etc.)

(Homes, small business, farming equipment, etc.)

NOx, VOC,NOx, VOC,ToxicsToxics

NOx, VOC, NOx, VOC, SOx, ToxicsSOx, Toxics

NOx, VOC,NOx, VOC,ToxicsToxics

Chemistry

Meteorology

Atmospheric Deposition

Acid Rain(NO3- deposition)

Water Quality(Nitrogen deposition,

Lake Acidification)

NONOxx

Visibility(Fine PM)

(NOx + VOC + hv) -->

Ozone(NO3-, NH4+)

PM

NONOxx-Related Air Quality Issues-Related Air Quality Issues

Acid Rain(SO42- deposition)

SOSOxx

(Fine PM)

Visibility(SO42-, NH4+)

PM

SOSOxx-Related Air Quality Issues-Related Air Quality Issues

Water Quality(Lake acidification,

Toxics deposition)

Air ToxicsAir Toxics

OzoneOzone

Acid RainAcid Rain

VisibilityVisibility

PMPM2.52.5

Water Water QualityQuality

..OHOH

..OHOH role in pollutants formation : role in pollutants formation : One-AtmosphereOne-Atmosphere

NOx + VOC + OH + hv ---> O3

SOx [or NOx] + NH3 + OH ---> (NH4)2SO4 [or NH4NO3]

SO2 + OH ---> H2SO4

NO2 + OH ---> HNO3

VOC + OH --->Orgainic PM

OH <---> Air Toxics (POPs, Hg(II), etc.)

Fine PM(Nitrate, Sulfate, Organic PM)

NOx + SOx + OH (Lake Acidification,

Eutrophication)

Example of “One-Atmosphere” ModelingExample of “One-Atmosphere” Modeling

Impact of Impact of

50 % NOx 50 % NOx

Emission ReductionEmission Reduction

on PM 2.5on PM 2.5

Impact of 50% NOx emission reductionImpact of 50% NOx emission reduction

Nitrate PM decreaseNitrate PM decrease Sulfate PM decreaseSulfate PM decrease

Impact of 50% NOx emission reductionImpact of 50% NOx emission reduction

OO33 decrease decrease HOx decreaseHOx decrease

Models-3/CMAQ Applications at Models-3/CMAQ Applications at OAQPSOAQPS

Western U.S. ApplicationWestern U.S. Application• New domain, episodic ONew domain, episodic O33

Annual Nationwide U.S. ApplicationAnnual Nationwide U.S. Application • Annual PM & visibilityAnnual PM & visibility

Eastern U.S. ApplicationEastern U.S. Application• Urban & SIP applications Urban & SIP applications

Hemispheric/continental Modeling InitiativeHemispheric/continental Modeling Initiative• Linkage of climate change and air pollutionLinkage of climate change and air pollution

Purpose: To evaluate Models-3/CMAQ feasibility as a regulatory tool

Western U.S. Western U.S.

ApplicationApplication

Objectives :Objectives :• New M3/CMAQ DomainNew M3/CMAQ Domain• New Episode (July 1996)New Episode (July 1996)

Model Setup :Model Setup :• Episodic OEpisodic O33 modeling modeling

• Meteorology : MM5Meteorology : MM5• Emissions : Tier-2 regriddedEmissions : Tier-2 regridded• 36km/12km, 12 layers36km/12km, 12 layers• Compare against observations and UAM-VCompare against observations and UAM-V

177

153

Annual Nationwide U.S. Annual Nationwide U.S. ApplicationApplication

Objectives :Objectives :• Annual CMAQ RunAnnual CMAQ Run

• Nationwide CMAQ DomainNationwide CMAQ Domain

Model Setup :Model Setup :• Annual Annual PMPM and O and O3 3 (1996)(1996)

• 36-km, 8 vertical layers36-km, 8 vertical layers

• Meteorology : MM5Meteorology : MM5

• Emissions Processing: SMOKEEmissions Processing: SMOKE

• Model Evaluation: Compared against observed Model Evaluation: Compared against observed data (IMPROVE & CASTNET) & REMSADdata (IMPROVE & CASTNET) & REMSAD

Models-3/CMAQ Simulation: Annual Average

PM 2.5 Sulfate PM

Organic PMNitrate PM

National 1996 CMAQ Modeling:National 1996 CMAQ Modeling:

O3 (July Max) Visibility (1996 avg.)

National 1996 CMAQ Modeling National 1996 CMAQ Modeling (January (January average)average)Sulfur Wet Deposition Nitrogen Wet Deposition

CMAQ Sensitivity CMAQ Sensitivity Studies Studies

CB4 vs. RADM2CB4 vs. RADM2• Is RADM2 a better mechanism than CB4 for PM Is RADM2 a better mechanism than CB4 for PM

modeling?modeling?• Run CMAQ w/ both CB4 and RADM2 for January and Run CMAQ w/ both CB4 and RADM2 for January and

July, 1996July, 1996

NHNH33 sensitivity sensitivity• Are NHAre NH33 emissions the culprit of nitrate PM over- emissions the culprit of nitrate PM over-

prediction? prediction? • Run CMAQ w/ 50% reduction of NHRun CMAQ w/ 50% reduction of NH33 emissions for emissions for

January and July, 1996January and July, 1996

Boundary conditions sensitivityBoundary conditions sensitivity• Run CMAQ w/ 10 ppb O3 increase along the western Run CMAQ w/ 10 ppb O3 increase along the western

boundary for January and July, 1996boundary for January and July, 1996

PM 2.5 (January Avg.)PM 2.5 (January Avg.)

RADM2 Original CB4

PM_SO4 (Jan. Avg.)

Orig. CB4 RADM2 Fixed CB4

NHNH33 Sensitivity Modeling Sensitivity Modeling

Nitrate PM : Nitrate PM : (January Avg.)(January Avg.)

BaseBase 50% NH 50% NH33 reduction reduction

CMAQ Sensitivity : Boundary ConditionsCMAQ Sensitivity : Boundary Conditions

Effect of a 10 ppb ozone increase along the western boundary

Eastern U.S. ApplicationEastern U.S. Application

Objectives :Objectives :• SIP and urban applicationsSIP and urban applications• Emission growth & controlEmission growth & control• Nested MM5 runsNested MM5 runs

Features :Features :• OO33 and PM, July 95 and PM, July 95• OTAG-like 36/12-km domain, OTAG-like 36/12-km domain,

nested with 4-km (NE, LM, AT, TX)nested with 4-km (NE, LM, AT, TX)• SMOKE : Emissions processingSMOKE : Emissions processing

Climate Change/Air Pollution Modeling Climate Change/Air Pollution Modeling InitiativeInitiative

ProposalProposal : : Global and Regional

Modeling of Ozone and PM

GoalGoal : : Establish linkages

between climate change and air pollution

BackgroundBackground : : O3 and PM are not only key air pollutants, but also major climate-forcing

substances;

Reduction of non-CO2 substances (e.g., O3 and PM, especially black carbon)

could be a viable alternative to CO2 reduction to curb global warming. A key

strategy suggested was to focus on air pollution to benefit regional and local

air quality and global climate simultaneously (Hansen et al., PNAS, 2000);

Black carbon could be the second largest heating component after CO2

contributing to global warming; Control of fossil-fuel black carbon could be

the most effective method of slowing glabal warming (Jacobson, Nature,

2001);


(Hansen et al., PNAS2001)


O3 (0.3+0.1) Black (0.8)Carbon

BackgroundBackground (continued): (continued): There is also mounting evidence that criteria pollutants originating from some developing

countries, especially those in Asia such as China and India, could impact U.S. domestic air

quality as well as contribute to the global background of climate-forcing substances. This

intercontinental transport issue is expected to worsen with the rapid growth in emissions

in these regions.

For example, recent modeling studies showed that by 2020 Asian emissions could

contribute as much as 2 ~ 6 ppb of O3 in the western U.S., offsetting the Clean Air Act

efforts up to 25% in that region (Jacob et al., Geophys. Res. Letts., 1999) and increase

global mean O3 level up to 10% (Collins et al., Atmos. Env., 2000); Asian and Sahara dust

could contribute a significant amount of PM in the western and southeastern U.S. (Husar,

http://capita.wustl.edu/CAPITA/).

– !


http://capita.wustl.edu/CAPITA/

Ozone (ppm) 1998 April 11: 1200 UTC

Models-3/CMAQ Run Example

(Byun and Uno, 2000)


ObjectivesObjectives : : To evaluate available approaches for establishing the

linkages between air pollution and climate change and enhancing modeling capacity within EPA to address these linkage issues.

To explore the impacts of intercontinental transport of O3 and PM as well as their implications for domestic and regional air quality and global climate change

To design integrated emissions control strategies to benefit global climate and regional and local air quality simultaneously


Work PlanWork Plan : :

Phase I : Short-Term (~6 months) Establish a better scientific foundation in linking climate

change and air pollution by leveraging current studies

1. Global Modeling of O3 and PM

2. Global Radiative Forcing of Aerosols

3. Emission Inventories for Climate-Forcing Pollutants

Develop a conceptual model and modeling protocol under

the guidance of an expert advisory panel


Work PlanWork Plan : :

Phase II : Long-Term (1 ½~2 years)Based on Phase I effort, a series of modeling efforts that will be conductedto address the linkages between air pollution and climate change.

These efforts may include:– Enhancement of modeling capability and emission inventories to better represent the

linkages to global air quality and climate.– Development of nesting capability between global chemistry/climate models and

regional air quality models.– Simulation of hemispheric or regional air quality under a variety of scenarios about

future global and regional emissions and air quality.– Evaluation of global and regional air quality models using a diverse set of observational

data sets, including data from satellites, surface networks, intensive field studies, etc.– Assessment of the potential radiative forcing and climate benefits resulting from

planned and alternative non-CO2 control strategies


Thank youThank you

The End

carey jang, pat dolwick, norm possiel, brian timin, joe tikvart u.s. epa

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