yang zhang, betty k. pun, krish vijayaraghavan, shiang-yuh wu and christian seigneur

21
Incorporation of the Model of Aerosol Dynamics, Reaction, Ionization and Dissolution (MADRID) into CMAQ Yang Zhang, Betty K. Pun, Krish Vijayaraghavan, Shiang-Yuh Wu and Christian Seigneur AER, San Ramon, CA CMAQ Workshop, October 2002

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Incorporation of the Model of Aerosol Dynamics, Reaction, Ionization and Dissolution (MADRID) into CMAQ. Yang Zhang, Betty K. Pun, Krish Vijayaraghavan, Shiang-Yuh Wu and Christian Seigneur AER, San Ramon, CA CMAQ Workshop, October 2002. - PowerPoint PPT Presentation

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Page 1: Yang Zhang, Betty K. Pun, Krish Vijayaraghavan,  Shiang-Yuh Wu and Christian Seigneur

Incorporation of the Model of Aerosol Dynamics, Reaction, Ionization and Dissolution (MADRID)

into CMAQ

Yang Zhang, Betty K. Pun, Krish Vijayaraghavan, Shiang-Yuh Wu and Christian Seigneur

AER, San Ramon, CA

CMAQ Workshop, October 2002

Page 2: Yang Zhang, Betty K. Pun, Krish Vijayaraghavan,  Shiang-Yuh Wu and Christian Seigneur

MADRIDModel of Aerosol Dynamics, Reaction, Ionization,

and Dissolution

Gas/particle mass transfer

• Hybrid algorithm

• Full equilibrium algorithm

Coagulation not important under polluted conditions

Condensable gases

ExistingParticles

Nucleation

Condensation

Coagulation

Page 3: Yang Zhang, Betty K. Pun, Krish Vijayaraghavan,  Shiang-Yuh Wu and Christian Seigneur

Gas-to-Particle Conversion Processes in MADRID

• Nucleation (McMurry and Friedlander,1979)• Thermodynamic equilibrium for inorganic species

– ISORROPIA (SO4=, NO3

-, NH4+, Na+, Cl-, water)

• Equilibrium for organic species– Absorption based on empirical data– Dissolution and absorption from first principles

• Diffusion-limited condensation/volatilization– Hybrid mass transfer from Calpado & Pandis or from

Meng et al.– Moving-center algorithm of Jacobson

Page 4: Yang Zhang, Betty K. Pun, Krish Vijayaraghavan,  Shiang-Yuh Wu and Christian Seigneur

Major Differences between MADRID and Original CMAQ Module

CMAQ• Modal size distribution

• NH4+, SO4

=, NO3-, Na+, Cl-

• Coagulation• Nucleation• Full equilibrium approach to

simulate mass transfer• Standard dry deposition• Absorption (irreversible) of 6

SOA using chamber data

MADRID• Sectional representation• Same species • Not treated• New particle formation• Hybrid or full equilibrium

approach• Revised flux approach• Two SOA modules

available

Page 5: Yang Zhang, Betty K. Pun, Krish Vijayaraghavan,  Shiang-Yuh Wu and Christian Seigneur

SOA Modules in MADRID

MADRID 1• Modified CBM-IV &

RADM2• 4 anthropogenic SOA

(aromatics)• 34 biogenic SOA

(monoterpenes)• Absorption based on

smog chamber data (Odum et al., 1997; Griffin et al., 1999)

MADRID 2• CACM(1)

– 42 condensable products– hydrophobic surrogate SOA

• 4 anthropogenic, 1 biogenic– hydrophilic surrogate SOA

• 3 anthropogenic, 2 biogenic

• Absorption based on estimated properties

• Dissolution into existing aqueous particles

(1) Caltech atmospheric chemistry mechanism

Page 6: Yang Zhang, Betty K. Pun, Krish Vijayaraghavan,  Shiang-Yuh Wu and Christian Seigneur

Meteorology

Sectional Modal

CBM-IV / RADM2 + 19 biogenic

reactions or CACM

Sectional PM module

PM concentrations

Sectional

PM chemicalconcentrationsby size section

PM depositionflux by chemical

Pre-Processors

ChemicalTransportModel

Output

Conversion from modal to sectional

PM concentrations

Gas-phase: CBM-IV + 3 biogenic

reactions

Modal PM module

PM chemicalconcentrations

by mode

Dry Deposition(sectional Vdep)

Dry Deposition(modal Vdep)

Emissions, initial conditions, boundary conditions (modal)

ModalSectional

Modal

Incorporation of MADRID into Models-3

Page 7: Yang Zhang, Betty K. Pun, Krish Vijayaraghavan,  Shiang-Yuh Wu and Christian Seigneur

Los Angeles Application

• SCAQS episode of 27-28 August 1987

• Simulation using MM5 and CMAQ-MADRID 1

Page 8: Yang Zhang, Betty K. Pun, Krish Vijayaraghavan,  Shiang-Yuh Wu and Christian Seigneur

SCAQS 1987 Episode

• 25-29 August 1987• Domain: 63 x 28 grid cells, consistent with previous

modeling exercises• Grid Resolution: 5 km• MM5 used to generate input meteorology• Emission inventory developed from previous

simulations

Page 9: Yang Zhang, Betty K. Pun, Krish Vijayaraghavan,  Shiang-Yuh Wu and Christian Seigneur

H AW T

C ELAR IVR

Ventura Los Angeles S an B ernard ino

R ivers ide

S an D iego

Orange

SCAQS Modeling Domain

HAWT

CELARIVR

Page 10: Yang Zhang, Betty K. Pun, Krish Vijayaraghavan,  Shiang-Yuh Wu and Christian Seigneur

Model Performance Ozone and PM2.5

Species Error Bias

O3 34% 9%

PM2.5 44% 14%

Page 11: Yang Zhang, Betty K. Pun, Krish Vijayaraghavan,  Shiang-Yuh Wu and Christian Seigneur

Model Performance PM2.5 Components

Species Error Bias

Sulfate 38% 11%

Nitrate 45% -38%

EC 54% -20%

OC 49% -22%

Page 12: Yang Zhang, Betty K. Pun, Krish Vijayaraghavan,  Shiang-Yuh Wu and Christian Seigneur

Observed and Simulated PM2.5 Composition

27 August 28 August

Sulfate

Nitrate

Ammonium

EC

OC

Others

Observations

MADRID 1

11%

42%

17%

2%

8%

20% 13%

37%

16%

2%

9%

23%

10%

42%

13%

4%

16%

15%9%

42%

13%

4%

15%

17%

Page 13: Yang Zhang, Betty K. Pun, Krish Vijayaraghavan,  Shiang-Yuh Wu and Christian Seigneur

Nashville, Tennessee Application

• SOS episode of 15-18 July 1995

• Simulation using MM5 and CMAQ-MADRID 2

Page 14: Yang Zhang, Betty K. Pun, Krish Vijayaraghavan,  Shiang-Yuh Wu and Christian Seigneur

Model Performance Ozone, PM2.5 and Sulfate

Species Error Bias

O3 17% 4%

PM2.5 17% -15%

Sulfate 13% -11%

Page 15: Yang Zhang, Betty K. Pun, Krish Vijayaraghavan,  Shiang-Yuh Wu and Christian Seigneur

Formation of Condensable Organics

0

2

4

6

8

10

12

14

16

18

20

0 4 8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68

Time (hr)

Gases

Particles

Condensable products in Nashville

Time (hour)

Con

cent

rati

ons

(g/

m3 )

Page 16: Yang Zhang, Betty K. Pun, Krish Vijayaraghavan,  Shiang-Yuh Wu and Christian Seigneur

Formation of Particulate Organics

AEC

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

0 4 8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68

SO

A (

g/m

3 )

Biogenic

Anthropogenic

Nashville

Time (hour)

SO

A (g

/m3 )

Page 17: Yang Zhang, Betty K. Pun, Krish Vijayaraghavan,  Shiang-Yuh Wu and Christian Seigneur

Hydrophobic vs. Hydrophilic Organics

NAS

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

0 4 8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68

SO

A (

g/m

3 )

Hydrophilic SOA

Hydrophobic SOA

Nashville

Time (hour)

SO

A (g

/m3 )

Page 18: Yang Zhang, Betty K. Pun, Krish Vijayaraghavan,  Shiang-Yuh Wu and Christian Seigneur

0

2

4

6

8

10

12

14

0 24 48 72

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Sensitivity of Hydrophilic Organics to Henry’s Law Constant

Nashville

Time (hour)

Hyd

roph

ilic

SO

A (g

/m3 )

RH

Base case; H = 1.6 x 106 M/atm Sensitivity case; H = 109 M/atm

RH

Page 19: Yang Zhang, Betty K. Pun, Krish Vijayaraghavan,  Shiang-Yuh Wu and Christian Seigneur

Other Applications of MADRID

• Nashville– comparison of three SOA modules

• BRAVO– regional simulation with RADM2 and MADRID 1

• Southeast– applications of MADRID 1 and MADRID 2

• Eastern United States– application of MADRID 1 for one year for nitrogen

deposition

Page 20: Yang Zhang, Betty K. Pun, Krish Vijayaraghavan,  Shiang-Yuh Wu and Christian Seigneur

Lessons from PM Simulations

• Accurate PM emission inventories are critical • Secondary organic aerosols remain a major source of

uncertainty• Boundary conditions can have significant effects on

O3 and PM predictions

• Effects of clouds on sulfate need to be simulated for regional haze

• Models yet to be tested for wintertime conditions

Page 21: Yang Zhang, Betty K. Pun, Krish Vijayaraghavan,  Shiang-Yuh Wu and Christian Seigneur

Acknowledgments

• Funding for this work was provided by EPRI and CARB

• We would like to thank – J.H. Seinfeld, S. Pandis, M. Jacobson, R. Griffin,

and A. Nenes for providing source codes used in MADRID

– S. Leduc and F. Binkowski for discussions regarding CMAQ