Simulating the Oxygen Content of Organic Aerosol in a Global Model

Qi Chen, Colette L. Heald

Department of Civil and Environmental Engineering, Massachusetts Institute of Technology

AGU Fall Meeting (A52E-06), Dec 7, 2012

Funded by NSF

(Heald et al., ACP, 2011)(Spracklen et al., ACP, 2011)

Average for 37 campaigns in the Northern Hemisphere (Zhang et

al., 2007)OrganicSulfateAmmoniumNitrateChloride

Atmospheric Organic Particles

dry or wet deposition

NR-PM1 chemical composition

Models substantially underestimate the observed concentrations of organic aerosol (OA).

(Jimenez et al., Science, 2009)

Hydrocarbon-like OA

Semi-volatile oxygenated OA

Low-volatility oxygenated OA

Global Modeling of OA: Additional Sources? Aqueous-phase secondary organic aerosol (SOA) production Spracklen et al. (2011) suggests that an additional source of 100 Tg yr-1

anthropogenically controlled SOA can close the measurement-model gap. Mechanism unclear.

Atmospheric aging is not included in the model, which may increase the OA mass.

Can O/C be a useful constraint on the global budget of OA?

Volatile Organic

Compounds

Hydrophilic

Primary OA

Hydrophobic

Primary OA

Gas-phase

Products i

Secondary OA

Standard Model:GEOS-Chem v9-01-03

gas

particle

Simulating O/C: Applying Experimental Data to Model

Absorptive Partitioning Model0.8

0.6

0.4

0.2

0.0

Yie

ld

4

12 4

102 4

1002

Organic Mass Concentration [µg m-3]

HV Product (2, C2)

LV Product (1, C1)

*

*

*

i

iC

α - stoichiometric mass yieldC*- saturation concentration

Example of 2-product fitting of yield and elemental composition: α-pinene dark ozonolysis, low NOx ; other SOA systems are also parameterized in this project.

Adding another dimension of input parameters:

Input O/Ci ranges from 0.2 to 0.9

*

O/C

H/Ci

i

i

i

C

0.6

0.5

0.4

0.3

0.2

O/C

1 10 100Organic Mass Concentration [µg m

-3]

HV Product(O/C2, H/C2)

LV Product(O/C1, H/C1)

POA1

POA1

O/C

H/CPOA2

POA2

O/C

H/C

Global Distribution of O/C: Standard Model Simulation

Surface O/C ranges from 0.3-0.7 with little seasonal difference.

Compared to 2005-2011 Surface O/C data from HR-AMS measurements along with 4 additional Q-AMS data.

(June, 2008)0.10 0.28 0.45 0.62 0.80

How Does the Standard Model Simulation Compare to Observations?

Standard model simulations reproduce the observations of O/C in near-source regions but

underestimate the values in aged locations.

1.0

0.8

0.6

0.4

0.2

O/C

0.01

0.1

1

10

100

OA

[µg

m-3]

Amazon

, Brazil

Born

eo, M

alaysi

a

Southe

rn G

reat

Plains

, US

Whis

tler M

ountain

, Can

ada

Montse

ny, S

pain

Upton

, NY,

US

Kaipi

ng, P

RD, C

hina

Cool, C

A, U

S

Davis,

CA, U

S

Mexico

City

(T0), M

exico

Que

ens C

olleg

e, NYC

, US

Riversid

e, CA,

US

Beijin

g, Chin

a

Shan

ghai, C

hina

Shen

zhen

, Chin

a

Jiaxin

g, PR

D, Chin

a

Fresno

, CA, U

S

Cheju

Islan

d, Ko

rea

Okinaw

a, Jap

an

Finok

alia S

tation

, Greec

e

Jungfr

aujoc

h, Sw

itzerlan

d

Urban Downwind Rural / Remote

Observation (HR-AMS) Derived from Q-AMS data Model: Standard

Does the Addition of 100 Tg/yr Anthropogenically-controlled SOA Source Improve the Comparison?

Addition of anthropogenic SOA leads increased O/C at all locations but has little skill on the spatial

variability.

1.0

0.8

0.6

0.4

0.2

O/C

0.01

0.1

1

10

100

OA

[µg

m-3]

Amazon

, Brazil

Born

eo, M

alaysi

a

Southe

rn G

reat

Plains

, US

Whis

tler M

ountain

, Can

ada

Montse

ny, S

pain

Upton

, NY,

US

Kaipi

ng, P

RD, C

hina

Cool, C

A, U

S

Davis,

CA, U

S

Mexico

City

(T0), M

exico

Que

ens C

olleg

e, NYC

, US

Riversid

e, CA,

US

Beijin

g, Chin

a

Shan

ghai, C

hina

Shen

zhen

, Chin

a

Jiaxin

g, PR

D, Chin

a

Fresno

, CA, U

S

Cheju

Islan

d, Ko

rea

Okinaw

a, Jap

an

Finok

alia S

tation

, Greec

e

Jungfr

aujoc

h, Sw

itzerlan

d

Urban Downwind Rural / Remote

Observation (HR-AMS) Model: Standard Model: ASOA x 30

Volatile Organic

Compounds

Hydrophilic

Primary OA

Hydrophobic

Primary OA

Gas-phase

Products i

Secondary OA

Standard Model:GEOS-Chem v9-01-03

gas

particle

*

O/C

H/Ci

i

i

i

C

POA1 POA1O/C , H/C POA2 POA2O/C , H/C

Volatile Organic

Compounds

Hydrophilic

Primary OA

Hydrophobic

Primary OA:

Anthropogenic

BiofuelBiomass Burning

Gas-phase

Products i

Secondary OA

Standard Model:GEOS-Chem v9-01-03

gas

particle

POA1-1 POA1-1

POA1-2 POA1-2

POA1-3 POA1-3

O/C , H/C

O/C , H/C

O/C , H/C

*

O/C

H/Ci

i

i

i

C

POA2 POA2O/C , H/C

Updated Scheme

Simulating O/C: Adding a Simple Scheme for Oxidative Aging of OA

Volatile Organic

Compounds

Hydrophilic

Primary OA

Hydrophobic

Primary OA:

Anthropogenic

BiofuelBiomass Burning

Gas-phase

Products i

Secondary OA

Standard Model:GEOS-Chem v9-01-03

gas

particle

POA1-1 POA1-1

POA1-2 POA1-2

POA1-3 POA1-3

O/C , H/C

O/C , H/C

O/C , H/C

*

O/ , C

,

C H/i

i

i

i C

POA2 POA2O/C , H/C

Aged OA

Aged OA Aged OAO/C , H/C

kOH, 2kOH, 3

kOH, 1

Elemental ratios and apparent rate constants are constrained by literature values (Turpin and Lim, EST, 2001; Aiken et al., EST, 2008; Mohr et al., EST, 2009; Lambe et al., ACP, 2011)

Updated Scheme

First Look: How Does Global Distribution of O/C Change with Aging?

Simulation with Aging 0.66 ± 0.09 for

60˚S to 60˚N Surface OA in

aged environment is dominated by Aged OA and POA.

(June, 2008)

Standard Simulation 0.43 ± 0.05 for

60˚S to 60˚N Surface OA in

aged environment is dominated by POA.

0.10 0.28 0.45 0.62 0.80

kOH, 1-3 = 1.1 × 10-12 cm3 molec-1 s-1 ~ 7 days exposure (Lambe et al., 2011)

1.0

0.8

0.6

0.4

0.2

O/C

0.01

0.1

1

10

100

OA

[µg

m-3]

Amazon

, Brazil

Born

eo, M

alaysi

a

Southe

rn G

reat

Plains

, US

Whis

tler M

ountain

, Can

ada

Montse

ny, S

pain

Upton

, NY,

US

Kaipi

ng, P

RD, C

hina

Cool, C

A, U

S

Davis,

CA, U

S

Mexico

City

(T0), M

exico

Que

ens C

olleg

e, NYC

, US

Riversid

e, CA,

US

Beijin

g, Chin

a

Shan

ghai, C

hina

Shen

zhen

, Chin

a

Jiaxin

g, PR

D, Chin

a

Fresno

, CA, U

S

Cheju

Islan

d, Ko

rea

Okinaw

a, Jap

an

Finok

alia S

tation

, Greec

e

Jungfr

aujoc

h, Sw

itzerlan

d

Urban Downwind Rural / Remote

Observation (HR-AMS) Model: Standard Model: POA Aging Model: POA + SOA Aging

First Look: Does Aging Improve Simulation of O/C Compared to Observations?kOH, 1-3 = 1.1 × 10-12 cm3 molec-1 s-1 ~ 7 days exposure (Lambe et al., 2011)

The simplified aging scheme shows the potential to improve model simulation at aged locations. On-going project:

sensitivity study on input parameters (e.g., kOH) and model resolution.

Summary

We applied experimental constraints on O/C simulated with the global GEOC-Chem model.

The model simulations are compared to recent surface measurements by HR-AMS. The standard simulation reproduces the observed O/C values in near-source regions. However, the model has little skill in aged locations and underestimates O:C by 0.4-0.5.

We developed a simple model scheme to simulate aging based on recent laboratory observations. Preliminary model simulations with POA and SOA aging show model improvements of O/C at some aged locations. On-going…

Data sharing from Jose Jimenez Group (CU); Qi Zhang Group (UC Davis); Ling-Yan He, Xiao-Feng Huang (PKU, China); Manjula Canagaratna, Douglas Worsnop (Aerodyne); Niall Robinson, Hugh Coe (U. Manchester)

NSF for funding

Acknowledgements