Development & Application of

Advanced Plume-in-Grid (PiG)

Multi-Pollutant Models

Prakash Karamchandani, Krish Vijayarag

Shu-Yun Chen & Christian Seigneu

AER, Inc., San Ramon, CA

9th Conference on Air Quality Model

October 9 & 10, 2008

EPA, RTP, NC
Why Use Plume-in-Grid Appr

Plume Size vs Grid Size (from Godowitch, 2004)

• Artificial dilutio

emissions 

• Unrealistic nea

plume concent

• Incorrect repres

plume chemistr

• Incorrect repres

plume transpor

Limitations o

Grid-Based A

Subgrid-scale reof plumes addreslimitations
Plume Chemistry & Releva

Ozone & PM Modelin

Early Plume Dispersion

NO/NO

2/O

3

chemistry

1

2

Mid-range Plume Dispersion

Reduced VOC/NO

x/O

3

chemistry —acid formation from OH and NO

3/N

2

O

5

chemistry

Long-raDispers

Full VOchemisacid an
PiG Modeling

• PiG model consists of a reactive plume m

embedded within a 3-D grid model

– Plume model captures local variability 

concentrations near sources with full treatment of chemistry

– Grid model provides continuously evo

background concentrations

– Grid model concentrations are adjuste

large downwind distances when the psize is commensurate with the grid sizmaterial is “handed over” to grid mode
History of PiG Modelin

• Began in the 1980s, focusing on ozone (PiG 

of UAM was called PARIS - Plume-Airshed RInteracting System)-Seigneur et al., 1983, AEnviron.

• Early models were overly simplified

– No treatment of wind shear or plume ove– No treatment of effect of atmospheric tur

on chemical kinetics

– Simplified treatment of chemistry in some 

• The development of a state-of-the-science P

model for ozone was initiated in 1997 under sponsorship
Advanced PiG Mode

• Embedded Plume Model: SCICHEM (state-of-

science treatment of stack plumes at the suscale)-developed by L-3 Communications/TitAER (Karamchandani et al., 2000, ES&T).

– SCICHEM is based on SCIPUFF, an alterna

model recommended by EPA on a case-bybasis for regulatory applications (also useDTRA and referred to as HPAC)

– Three-dimensional puff-based model, with 

order closure approach for plume dispersitreatment of puff splitting and merging

– SCICHEM adds full chemistry mechanism 

CBM-IV) to SCIPUFF
Advanced PiG Model

• SCICHEM was first embedded in MAQSIP

precursor to the U.S. EPA Model, CMAQ

• In 2000, AER incorporated SCICHEM into 

(Karamchandani et al., 2002, JGR) 

• The model is called CMAQ-APT (Advance

Treatment)
CMAQ-APT Applications for 

• Eastern United States with two neste

domains (12 and 4 km resolution), Jul(Karamchandani et al., 2002, JGR)

• Central California (4 km resolution), J

August 2000 (Vijayaraghavan et al., 2Atmos. Environ.)

• Key conclusion from Eastern U.S. 

application: for isolated point sourcesCMAQ-APT predicts lower O

3 and HNO

formation compared to the base mode
Addition of PM Treatment 

PiG Model

• PM and aqueous-phase chemistry treatm

were added in 2004-2005 (Karamchanda2006, Atmos. Environ.)

• Two versions:

– EPA treatment of PM (CMAQ-AERO3-A– MADRID treatment of PM (CMAQ-MAD

developed by AER

MADRID: Model of Aerosol Dynamics, ReIonization and Dissolution (Zhang et al., JGR)
Model Components

CMAQ v. 4.6

MADRID PM Treat

CMAQ-MADRI

SCICHEM-AERO3

PM Treatment based on EPA CMAQ 

SCICHEM-MADR

PM Treatment based on C

CMAQ-AERO3-APT CMAQ-MADRID
Application to Southeaste

• Study designed to supplement RPO modelin

conducted by the Visibility Improvement StTribal Association of the Southeast (VISTA

• 2 months simulated (January and July 2002

Base CMAQ v 4.4 and CMAQ-APT-PM

• 14 power plant plumes explicitly simulated 

plume-in-grid approach

• Model performance: Base CMAQ vs. CMAQ-• Power plant contributions to PM2.5 compon

calculated and compared for Base CMAQ aCMAQ-APT-PM
Modeling Domain and Loca

of PiG sources
Power-Plant Contributions to Ave

PM2.5 Sulfate Concentratio

Base CMAQ CMAQ-AERO3
Change in Power-Plant Contribution

Sulfate Concentrations When a Plu

Approach is Used

%

Predicted plant contto sulfate when a Pitreatment 
Conclusions from CMA

AERO3-APT Applicatio

• Using a purely gridded approach will typic

overestimate power plant contributions to because SO

2 to sulfate and NO

x to nitrate 

conversion rates are overestimated

• Plume-in-grid PM modeling provides a bett

representation of the near-source transporchemistry of point source emissions and tcontributions to PM2.5 concentrations

• CMAQ-AERO3-APT predicts lower power p

contributions than base CMAQ to local and regional sulfate and total nitrate, particulasummer
Addition of Mercury 

Treatment in the PiG Mo

• Implementation of mercury modules in C

MADRID-APT was completed in 2006 (Karamchandani et al., 2006, 5th Annual C

Conference)

• Application of CMAQ-MADRID-APT (with 

the southeastern U.S. (12 km grid resolu2002

• Application of CMAQ-MADRID-APT (with 

continental U.S. (36 km grid resolution) f(Vijayaraghavan et al., 2008, JGR)
Continental U.S. Applica

2001

• 30 p

witHg

• 36 
Mercury Wet Depositio

in Aug-Sep. 2001

Grid Model % Change du

The model over-predicts 

wet deposition in 

Pennsylvania

The advanced plum

corrects some of the 
Sub-Grid Scale Modeling of A

Concentrations Near Road

• Population exposure to hazardous air pollut

(HAPs) is an important health concern

• Exposure levels near roadways are factors 

larger than in the background–models need capture spatial variability in exposure level

• Many of the species of interest are chemica

reactive–e.g., formaldehyde, 1,3-butadiene, acetaldehyde–models need to treat the chethese species

• Traditional modeling approaches are inadeq

provide both chemistry treatment and fine sresolution
PiG Modeling for Roadw

Emissions

• Based on CMAQ-APT • Prototype version developed in 2007 (Karam

et al., 2008, Env. Fluid Mech.):

– simulates near-source CO and benzene 

concentrations from roadway emissions

– chemistry is switched off– roadway emissions treated as series of ar

sources along the roadway with initial siz

the roadway width

• Concentrations calculated at discrete recep

locations by combining incremental puff concentrations with the grid-cell average baconcentration
Model Applicatio

• Busy interstate highway in 

New York City (I278)

• July 11-15, 1999 period of 

NARSTO/Northeast Program

• Grid model domain
Qualitative Evaluation o

Concentrations

• Result

with Cconcenmeasu

Angele

(2002)Enviro
PiG Modeling Constrain

• Can be computationally expensive if a large 

of point sources are treated with the puff mcomputational requirements increase by a ftwo to three for 50 to 100 sources

• Point sources have to be selected carefully 

the number of sources treated

• To obtain results in a reasonable amount of 

annual simulations are usually conducted bdividing the calendar year into quarters andsimulating each quarter on different procesmachines

• Parallel version of code can address these 

constraints
Parallelization of PiG M

• Development of parallel version of CMAQ-MA

APT completed in late 2007

• On a 4-processor machine, the parallel vers

about 2.5 times faster than the single-proceversion

• On-going project to apply the model to the c

and eastern United States at 12 km resolutievaluate it with available data

– Over 150 point sources explicitly treated – Annual actual and typical simulations for – Future year emission scenarios– Other emission sensitivity scenarios
Ongoing Application of P

PiG Model

• 12 km grid res• 243 x 246 x 19 • Over 150 PiG s
Acknowledgments

• Funding:

– Electric Power Research Institute (EPRI)– Southern Company– California Energy Commission (CEC)– Atmospheric & Environmental Research, I

• Collaboration in Model Development: L-3 CO• Parallelization Insights: David Wong, EPA• Data Sources:

– VISTAS– Atmospheric Research & Analysis, Inc. (A– Georgia Environmental Protection Division