simulating the oxygen content of organic aerosol in a global model qi chen, colette l. heald...
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![Page 1: Simulating the Oxygen Content of Organic Aerosol in a Global Model Qi Chen, Colette L. Heald Department of Civil and Environmental Engineering, Massachusetts](https://reader035.vdocument.in/reader035/viewer/2022081504/5697c0121a28abf838ccc541/html5/thumbnails/1.jpg)
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
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(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).
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(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?
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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
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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
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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
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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
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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
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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)
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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.
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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