Synergisms in the Development of the CMAQ and CAMx PM/Ozone Models

Ralph E. Morris, Greg Yarwood

Chris Emery, Bonyoung Koo

ENVIRON International Corporation

101 Rowland Way

Novato, CA

Presented at

CMAS Models-3 User’s Workshop

October 27-29, 2003

Research Triangle Park, NCPresents:slides/

Introduction

Numerous challenges in particulate matter modeling:> Multiple Components

• SO4, NO3, SOA, POC, EC, Crustal, Coarse, Other

> Multiple Processes• Gas-, Aqueous-. Heterogeneous-, Aerosol-Phase Chemistry• Rainout/washout, dry deposition of Gases and Particles• Advections and Diffusion• Clouds, Canopy, Terrain, etc.

> Numerous Uncertainties• Chemistry (e.g., nitrate, SOA, aromatic, etc.), PM Size

Distribution, Meteorology, Emissions, Measurements

Introduction

> CMAS Workshop Good Forum to Discuss Challenges, Approaches and Potential Solutions for Improving PM Modeling

> CMAS Workshop Theme Emphasizes the Common Challenges of PM Modeling

• One Atmosphere• One Community• One Model

One Atmosphere

One Community

One Model

CMAQ

One Model?

CMAQ

MM5 RAMS WRF

One Model??

CMAQ

MM5 RAMS WRF

SMOKE EMS EPS OPEM

One Model???

CMAQ

MM5 RAMS WRF

SMOKE EMS EPS OPEM

MOBILE NONROAD EDMS EMFAC AP42

One Model????

CMAQ

MM5 RAMS WRF

SMOKE EMS EPS OPEM

MOBILE NONROAD EDMS EMFAC AP42

IMPROVE CASTNET STN AQS/AIRS NADP SuperSites

Multi-Model Intercomparisons> Intercomparing models and alternative formulations is an integral

part of model development> Photochemical grid model development has taught us that much

more can be learned from comparing different models with different formulations – this is even more true for PM models due to more uncertainties in processes

Early 1980s UAM vs. CIT

~ 1990 UAM vs. CALGRID

Early 1990s UAM-V vs. UAM vs. SAQM

Mid 1990s UAM-V vs. CAMx vs. MAQSIP

Early 2000s CMAQ vs. CAMx

Early CMAQ vs. CAMx Comparisons for Ozone

• 1991 Lake Michigan Ozone Study (LMOS) Databases> Tesche ands co-workers (2001) (available at www.crcao.com as

CRC Project A-25)> MM5 and RAMS Meteorology> No one model performing sufficiently better than another> CMAQ and CAMx using MM5 more similar than CAMx using

RAMS> Similar ozone responses to VOC/NOx controls> CMAQ using QSSA and SMVGEAR chemistry solvers takes ~5

and ~8 times longer to run than CAMx

EPA implements faster Hertel/MEBI chemistry solver in CMAQ

Early CMAQ vs. CAMx Comparisons for Ozone

• July 1995 NARSTO-Northeast Ozone Episode> Morris and co-workers (available at www.crcao.com as CRC

Project A-24)> MM5 and RAMS Meteorology

> Layer 1 KV mixing issues

EPA implements 1.0 m2/s minimum KV in MCIP, land use specific lower layers minimum KV used with CAMx

> QSSA chemistry solver accuracy and stability issues

Hertel/MEBI solver implemented in CMAQ> Smolarkiewicz advection solver is overly diffusive.

Smolarkiewicz removed from CAMx (not in CMAQ)

Early CMAQ vs. CAMx Comparisons for Ozone

• July 1995 NARSTO-Northeast Ozone Episode> SAPRC97 chemistry more reactive than CB-IV

Both CMAQ and CAMx implement SAPRC99 chemistry > Different horizontal diffusion (KH) formulations in CMAQ and

CAMx• CMAQ inversely and CAMx proportional to grid spacing

Area of future research and sensitivity tests (e.g., spawned BRAVO sensitivity test)

> MM5 convective activity potentially can produce modeling artifacts MM5 interface an area of continued research for CMAQ and

CAMx

Emerging PM Model Development Issues

• Aqueous-Phase Chemistry> High pH dependency of aqueous-phase O3+SO2 reaction

> Coarse and fine droplets may have different buffering and different pH effects on aqueous-phase sulfate formation

> Test this effect using PMCAMx sectional PM model that incorporates CMU VSRM aqueous-phase chemistry module

• October 17-19, 1995 Southern California PM episode• Two aqueous-phase chemistry modules used

– CMU 1-section bulk module– CMU 2-section VSRM module

Southern California Modeling Domain

VSRM (Multi-Section) vs. Bulk Aqueous ChemistryPercent Increase in Sulfate (%)

By second day, VRSM estimates ~15-30% more sulfate across the SoCAB with > 50% increase offshore and around Long Beach

VSRM (Multi-Section) vs. Bulk Aqueous Chemistry

PM10 Sulfate - Long Beach - Oct. 18, 1995

0

5

10

15

20

25

30

1 6 11 16 21

Time (hr)

Sulfa

te (

m g/m

3) VSRM

Bulk

No Aqueous-PhaseChem.

> 6 mg/m3 difference

> 16% difference in daily avg

PM10 Sulfate - (18,15) - Oct. 18, 1995

0

5

10

15

20

1 6 11 16 21

Time (hr)Su

lfate

(m g

/m3

) > 10 mg/m3 difference

> 31% difference in daily avg

VRSM can form significantly more sulfate than the bulk 1-section aqueous-phase chemistry module

Emerging PM Model Development Issues• Conclusions on Bulk vs. Multi-Section Aqueous-Phase

Chemistry Tests> Multi-section aqueous-phase chemistry module made significantly

more sulfate in the Southern California test case> Due to low sulfate in Southern California, differences were not

significant enough to appreciably affect sulfate model performance> Need further testing for eastern US where higher sulfate

concentrations occur> Merging of CAMx4 and PMCAMx models provides platform for

testing RADM and CMU 1-section bulk aqueous-phase chemistry modules against the CMU VSRM multi-section module

> CMU VSR multi-section module requires ~5 times more CPU time than CMU 1-section module (Further optimization warranted)

Emerging PM Model Development Issues• Aerosol Thermodynamics Gas/Particle Partitioning

> Gas/Particle equilibrium usually assumed> ISORROPIA equilibrium scheme widely used

• Fast and reliable• CMAQ, CAMx, URM, etc.

> Equilibrium assumption may not always be correct, especially for coarse particles

> PMCAMx sectional PM model includes three options for Gas/Particle partitioning:

• Equilibrium (ISORROPIA)• Dynamic (MADM)• Hybrid (equilibrium for fine/dynamic for coarse particles)

> Testing using October 1995 Southern California Database

Equilibrium vs. Dynamic vs. Hybrid

0 5 10 150

2

4

6

8

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14

16

Measured concentration (ug/m)

Pre

dic

ted

con

cen

tra

tion

(mg

/m3)

0 50 100 1500

50

100

150

Measured concentration (mg/m3)

Pre

dic

ted

con

cen

tra

tion

(mg

/m3)

+30%

0 5 100

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4

6

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12

14

Measured concentration (ug/m)

Pre

dic

ted

con

cen

tra

tion

(mg

/m3)

0 20 40 60 80 1000

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20

30

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80

90

100

Measured concentration (mg/m3)

Pre

dic

ted

con

cen

tra

tion

(mg

/m3)

PM2.5 SO4 PM10 SO4

PM2.5 Mass PM10 Mass

EQUIHYBRMADM

Equilibrium vs. Dynamic vs. Hybrid

0 5 10 150

2

4

6

8

10

12

14

16

18

Measured concentration (mg/m3)

Pre

dic

ted

con

cen

tra

tion

(mg

/m3)

0 10 20 30 40 500

10

20

30

40

50

Measured concentration (ug/m3)

Pre

dic

ted

con

cen

tra

tion

(mg

/m3)

PM2.5 NO3

0 10 20 30 40 500

10

20

30

40

50

Pre

dict

ed c

once

ntra

tion

(mg/

m3)

0 5 10 150

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16

Measured concentration (mg/m3)

Pre

dic

ted

con

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tion

(mg

/m3)

PM10 NO3

PM2.5 NH4 PM10 NH4

+30%

EQUIHYBRMADM

Emerging PM Model Development Issues

• Conclusions on use of equilibrium approach for gas/particle partitioning> For Southern California application:

• dynamic and hybrid modules produce nearly identical results• most of the time equilibrium approach produces results very

close to dynamic and hybrid approaches, but differences as high as 30% did occur

• dynamic (MADM) approach requires approximately 10 times the CPU time as equilibrium approach

> Further tests of equilibrium assumption warranted> Given sufficient accuracy, uncertainties and computational

requirements, equilibrium approach appears adequate for annual modeling

Emerging PM Model Development Issues

• Particle Size Distribution> Different representations of particle size distribution in difference

models• CMAQ modal approach using 3 modes and assumes all

secondary PM is fine

• CAMx4, REMSAD and MADRID1 assume fine and coarse PM (all secondary PM is fine)

• PMCAMx, CMAQ-AIM and MADRID2 are fully sectional models where PM10 is divided up into N sections (e.g., N=10)

Emerging PM Model Development Issues

• Particle Size Distribution> Testing of assumptions of particle size distribution using

new merged CAMx4/PMCAMX code• M4 = CAMx4 2 section plus RADM aqueous• EQUI = N sections equilibrium + VRSM aqueous• MADM = 10 sections dynamic + VRSM aqueous• RADM/EQ = 10 sections equil. + RADM aqueous• RADM/EQ4 = 4 sections equil. + RADM aqueous

> October 17-18, 1995 Southern California Episode

M4

EQUI

24-Hour Sulfate (g/m3)

October 18, 1995

• M4 peak SO4 39 g/m3

• EQUI peak SO4 51 g/m3

• ~ Long Beach Area

• Differences due to more sulfate production in CMU VRSM than RADM aqueous-phase chemistry

• Further downwind (Riverside) M4 produces more sulfate than EQUI

24-Hour Nitrate (g/m3)

October 18, 1995

• M4 peak NO3 83 g/m3

• EQUI peak NO3 54 g/m3

• Observed NO3 peak at Riverside ~40 g/m3

• Differences partly due to assuming all nitrate is fine vs. PM nitrate represented by 10 size sections (EQUI)

• Differences in M4 RADM and EQU VSRM also contribute

M4

EQUI

24-Hour Nitrate (g/m3)

October 18, 1995

• M4 peak NO3 83 g/m3

• EQUI peak NO3 54 g/m3

• EQUI 10-Section grows PM NO3 into coarser sections where it dry deposits faster than M4 NO3 that is assumed to be fine

• Result is less NO3 in downwind Riverside area that agrees better with observations

M4

M4 - EQUI

0

10

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30

40

50

60

70

80

90

0.01 0.1 1 10

M4

EQUI

MADM

RADM/EQ

Diameter [mm]

dM

/dL

og

(D)

[mg

/m3]

Sensitivity to Number of Size Sections (10 vs. 4) @ (34,16)

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0.01 0.1 1 10

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0.01 0.1 1 10

RADM/EQ4

RADM/EQ

Diameter [mm]

dM/d

Log(

D)

[mg/

m3]

Computational Efficiency Model ConfigurationsCPU hours per simulation day

(based on Athlon 1600 CPU)

0.1

1

10

100

M4 RADM/EQ4 RADM/EQ EQUI MADM

0.42 0.52

1.2

5.8

63

Emerging PM Model Development Issues

• Nighttime Nitrate Chemistry> September 2003 CMAQ release

• Zero N2O5+H2O gas-phase reaction rate

• 0.02 and 0.002 probability for heterogeneous rate> April 2003 CAMx4 release

• Keep gas-phase N2O5+H2O reaction rate

– German smog tests provide upper bound rate, but is real gas-phase reaction

• Current research suggests part of overestimation tendency may be due in part to assuming all nitrate is fine

> More updates in future

Emerging PM Model Development Issues• Interface with Meteorological Model (MM5/RAMS)

> Mass Conservations and Mass Consistency> Clouds and Precipitation (resolved and unresolved)> Instantaneous meteorological data (convective down bursts)> MM5 PBL heights – what to do when collapsed from clouds/snow

Conclusions on Model Development Synergisms• CMAQ and CAMx offer two completely different

platforms to test alternative PM modules and formulations> provides an “independent” test of the assumptions> identifies potential for introducing compensatory errors

• Numerous common challenges in PM modeling, the more ways of looking at the problem the better> nitrate formation, size sections and deposition> aqueous-phase chemistry> PM size distribution> meteorology> computational efficiency

Toola to Facilitate Model Intercomparisons

• MM5 Interface Software> MCIP 2.2> MM5CAMx + kvpatch

• CMAQ-to-CAMx conversion software> Emissions> IC/BC

• CAMx-to-CMAQ conversion software> Emissions> IC/BC

Current CMAQ/CAMx Comparisons

• 1996 Western USA> WRAP and CRC

• Jan 2002, July 2001, July 1991Eastern USA> VISTAS

• August – September 1997 Southern CalEfornia> CRC

• Midwest US/Supersites> MRPO