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Sources of Organic Aerosol: Semivolatile Emissions and Photochemical Aging
Allen Robinson and Peter Adams
Center for Atmospheric Particle StudiesCarnegie Mellon University
Presented at Sources and Atmospheric Formation of Organic Particulate Matter Progress Review Meeting, EPA, RTP, NC, Sept 21, 2010.
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2
A knowledge gap. . .
?HOA
OOA
Average urban OAZhang et al, GRL, 2007
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3
Elemental Carbon
Resovled Particle-Phase
Particle-Phase UCM
Resolved IVOCs & SVOCs
IVOCs & SVOCs UCM
gas-phase volatile organics
87 % of particle-phase & SVOC/IVOC emissions are UCM
Diesel exhaust
UCM
UCM
Complexity of Combustion Emissions
Schauer et al., ES&T 2002
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4
Old conceptual model
C* (g m-3)10-2 100 102 104 106 108 1010
S1 S2Volatile
Products
SOAPrecursor
PrimaryEmissions
POA
1
2
Primary Organic Aerosol
Non-volatile
Non-reactive
Secondary Organic Aerosol
Very volatile precursors
Semivolatile products
• Monoterpenes• Light aromatics
• Diesel exhaust• Wood smoke
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5
Revised conceptual model
C* (g m-3)
10-2 100 102 104 106 108 1010
S1 S2Volatile
Products
SOAPrecursor
P2
PrimaryEmissions
P1 P3 P4 P5
f1 f3f2 f5f4
Semivolatile
Reactive
1 2
(Robinson et al. Science 2007)
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0
2
4
6
8 Traditional SOA IVOC SOA SVOC SOA POA
10-2 100 102 104 106 108 1010
Cum
mul
ativ
e O
A (T
g yr
-1)
C* (g m-3 @ 298 K)
0
5
10
15
20
Emis
sion
s (T
g yr
-1)
Biogenic Anthropogenic
0.25
0.5
0.75
1.0
0
Esti
mat
ed Y
ield
( Donahue et al. AE 2009)
Traditional SOA
Non-Traditional SOA
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Objectives of Research
What is the volatility distribution of fresh emissions?
What is the effect of aging on primary emissions?
What are the implications for urban and regional organic aerosol concentrations?
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Change T or COA
Measure changes in partitioning
Fit data to derive volatility distribution
Lipsky et al., ES&T, 2006An et al., J. Aerosol Sci., 2007
Dilution SamplerThermodenuder
Objective 1. Quantifying volatility distributions
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Combining TD and Dilution Data
9
C10001
f
C1001
f
C101
fX
OA
4
OA
2
OA
1p
Wood Smoke Volatility distribution
10 100 1000 100000.0
0.2
0.4
0.6
0.8
Emis
sion
Fac
tor
(g/k
g-fu
el)
C* (g/m3)
Grieshop et al. EST 2010
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Partitioning and POA Emission Factors
10Robinson et al. JAWMA 2010
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Objective 2. Effects of agingExperiments with increasingly complex mixtures
Diluted exhaust Emission Surrogates
• motor oil (new & used)• diesel fuel • mixtures of fuel & oil
Single components
• n-alkanes • branched alkanes• aromatics • simple mixtures
• diesel exhaust• wood smoke• aircraft exhaust
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Aging of Wood Smoke Experimental Setup
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Wood smoke Aging Rapidly Creates Lots of “SOA”
o
50
40
30
20
10
0
CO
A (µ
g m
-3) Lights off
Measured OA
POA MassModeled Mass
f i 60 0
6543210
Elapsed since lights on (hours)
120
80
40
0Modeled MassPOA Mass
SOA via BC Scaling
Wal
l-los
sC
orre
cted
(g/
m3 )
(Grieshop et al. ACP 2009)
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Data from multiple wood smoke aging experiments
2.5
2.0
1.5
1.0
6543210
Expt. 5
Expt. 3
Expt. 2
Expt. 4 - High NOx
Expt. 6
Expt. 1
6 Yellow Pine, smoldering/dying flame 50 2.18E+07 196
Laurel Oak Expts.Yellow Pine Expts.
Elapsed Time (hr)
Org
anic
Aer
osol
Enh
ance
men
t
(Grieshop et al. ACP 2009)
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Similarity of Aged Organic MS
MILAGRO OOA1 MILAGRO OOA2 MILAGRO BBOA
Residual 4 hour
example scatter plots
16
12
8
4
0
3020100 1612840 12840
1.00.90.80.70.60.50.4
543210-1Elapsed since lights on (hours)
1.00.90.80.70.60.50.4
Ambient Factors
Lab Diesel Spectra
intercept=0.37slope=0.63r2=0.82
intercept=0.20slope=0.80r2=0.93
intercept=0.30slope=0.70r2=0.52
r2_rel_org_milagro_ooa1 r2_rel_org_milagro_ooa2 r2_rel_org_milagro_bboa r2_nov19_pghOOA
r2_relorg_31janPOA_dies r2_rel_org31jan5hr_dies r2_rel_org31jan5hr_dresid
Diesel POA
Aged Diesel
BBOA
OOA1OOA2
R2
R2
Elapsed Time since UV (hrs)
Wood smoke versus lab diesel
Am
bien
t Fa
ctor
s co
urt
esy
of J
. Jim
enez
CU
Bou
lder
Wood smoke versus ambient
(Grieshop et al. ACP 2009)
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n-alkane high NOx SOA yields
16(Presto et al. EST 2010)
C-12 C-15
C-17
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Yields are “high”
17
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Parameterizing yields based on C*
18(Presto et al. EST 2010)
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SOA from IVOCs can be highly oxygenated
19
OOA-like
AM
S f 4
4 Less oxidized
(Presto et al. EST 2009 & 2010)
Composition C15 SOA
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Objective 3. Regional and global modeling to quantify organic aerosol
Modifications
Update inventory
Added species
Aging
Critical inputs
Volatility distribution
Aging mechanism
IVOC emissions
Activity coefficients
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Aging mechanism
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.00
5
10
15
20
25
SVOCChamber
Data
Aer
osol
Mas
s (u
g m
-3)
Time (hrs)
SVOC + 1.5 IVOC
10-2 10-1 100 101 102 103 1040.0
0.2
0.4 Particle Gas
Nor
mal
ized
EF
C* (g m-3)C* @ 298K (ug/m3)Con
cent
ratio
n (u
g/m
3)
Primary
Time (hrs)
Aer
osol
Mas
s (u
g/m
3 )
DataScheme #2
Scheme #1
Aging Scheme
• Gas-phase Reactions w/ OH
• kOH = 4 x 10-11 cm3 (molec s)-1
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Updating Emission Inventories
RedistributingNon-Volatile POA
Revised Inventory
0.0
0.1
0.2
0.3
2
4
6
8
Emis
sion
s (T
g yr
-1) Redistributed POA
Existing VOC
C* (g m-3)10-2 100 102 104 106 108 1010
0
200
400
1000
C* (ug/m3)
Emis
ssio
ns(k
ton/
yr)
0 10-2 100 101 105
0.0
0.1
0.2
0.3
2
4
6
8
Emis
sion
s (T
g yr
-1) POA
VOC
C* (g m-3)0 10-2 100 102 104 106 108 1010
NEI 2002
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Are there missing emissions?
0100200300400
1000200030004000500060007000
Mas
s (K
tons
/Yr)
C* @ 298K (ug/m3)101110-210-11001011021031041051061071081091010
VOCSVOC
?
MissingEmissions
0
1
2
3
Diesel
Catalyt
ic Gas
Non-Cat
Gas
Wood smoke
Emissions Data
SVO
C V
apor
sPO
A
(Schauer et al. EST 99, 00, 02)
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Summertime OA Predictions
TraditionalNon-volatile POA Semivolatile POA
RevisedSemivolatile + Aging
0 1 2 3 4
OAg m-3
July 2001
Shrivastava et al. JGR 2008
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Ratio of Revised-to-Traditional Predicted OA levels
July 2001 OA
0 2 4 6 8 10 120
2
4
6
8
10
12
0 2 4 6 8 10 120
2
4
6
8
10
12
(a) Nonvolatile STN IMPROVE
(b) Revised
Observed
Pred
icte
d
Traditional
Revised
1.4
1.2
1
0.8
0.6
Shrivastava et al. JGR 2008
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Wintertime OA Predictions
OAg m-3
TraditionalNon-volatile POA Semivolatile POA
RevisedSemivolatile + Aging
0 1 2 3 4
January 2002
Shrivastava et al. JGR 2008
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January 2002
0 2 4 6 8 10 120
2
4
6
8
10
12
0 2 4 6 8 10 120
2
4
6
8
10
12
(c) Nonvolatile
(d) Revised
Observed
Pred
icte
d
Traditional
Revised
1.2
1.0
0.8
0.6
Ratio of Revised-to-Traditional Predicted OA levels
Shrivastava et al. JGR 2008
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Revised model predicts a more regional aerosol
Upwind Rural Site
Urban Site
Model-Measurement Comparison
Shrivastava et al. JGR 2008
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Oxygenated Organics Dominate in Summer
Traditional ModelNon-Volatile POA
Revised modelSemivolatile + Aging
1
0.8
0.6
0.4
0.2
0
July 2001
Traditional SOATotal OA
Traditional SOA + Aged PrimaryTotal OA
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Revised Model and AMS OOA
AMS data Zhang et al. GRL 2007Urban Rural
0.0
0.2
0.4
0.6
0.8
1.0 F
ract
iona
l con
trib
utio
nto
tota
l OA
Aged Primary Traditional SOA
AMS OOA
Pinnacle
state
parkDuke Fores
t
New York
Houston
Pittsburg
h
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Conclusions
Primary emissions are semivolatile
Aging of emissions create substantial SOA
Accounting for aging and partitioning improves predictions of CTMs
Important implications for developing control strategies
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Journal Papers
A.L. Robinson, A.P. Grieshop, N.M. Donahue, S.W. Hunt “Updating our conceptual model for fine particle mass emissions from combustion systems,” Journal of the Air and Waste Management Association, in press.
A.A. Presto, M.A. Miracolo, N.M. Donahue, A.L. Robinson “Secondary Organic Aerosol Formation from High- NOx Photo-Oxidation of Low-Volatility Precursors: n-Alkanes” Environmental Science & Technology, 44 (6), 2029–2034, 2010.
M.A. Miracolo, A.A. Presto, A.T. Lambe, C.J. Hennigan, N.M. Donahue, J.H. Kroll, D.R. Worsnop, A.L. Robinson “Photo-Oxidation of Low-Volatility Organics found in Motor Vehicle Emissions: Production and Chemical Evolution of Organic Aerosol Mass,” Environmental Science & Technology, 44(6), 2029–2034, 2010.
J.L. Jimenez, M.R. Canagaratna, N.M. Donahue, A.S.H. Prevot, Q. Zhang, J.H. Kroll, P.F. DeCarlo, J.D. Allan, H. Coe, N.L. Ng, A.C. Aiken, K.D. Docherty, I.M. Ulbrich, A.P. Grieshop, A.L. Robinson, J. Duplissy, J. D. Smith, K.R. Wilson, V.A. Lanz, C. Hueglin, Y.L. Sun, A. Laaksonen, T. Raatikainen, J. Rautiainen, P. Vaattovaara, M. Ehn, M. Kulmala, J.M. Tomlinson, D.R. Collins, M.J. Cubison, E.J. Dunlea, J.A. Huffman, T.B. Onasch, M.R. Alfarra, P.I. Williams, K. Bower, Y. Kondo, J. Schneider, F. Drewnick, S. Borrmann, S. Weimer, K. Demerjian, D. Salcedo, L. Cottrell, R. Griffin, A. Takami, T. Miyoshi, S. Hatakeyama, A. Shimono, J.Y Sun, Y.M. Zhang, K. Dzepina, J.R. Kimmel, D. Sueper, J.T. Jayne, S.C. Herndon, A.M. Trimborn, L.R. Williams, E.C. Wood, C.E. Kolb, U. Baltensperger, and D.R. Worsnop, “Evolution of Organic Aerosols in the Atmosphere,” Science, 326, 1525-1529, 2009.
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Journal Papers
A. Asa-Awuku, M. A. Miracolo, J. H. Kroll, A. L. Robinson, N. M. Donahue “Mixing and phase partitioning of primary and secondary organic aerosols,” Geophysical Research Letters, 36, L15827, doi:10.1029/2009GL039301, 2009.
A.P. Grieshop, M.A. Miracolo, N.M. Donahue, and A.L. Robinson, “Constraining the Volatility Distribution and Gas-Particle Partitioning of Combustion Aerosols Using Isothermal Dilution and Thermodenuder Measurements,” Environmental Science & Technology, 43(13), 4750-4756.
A.A. Presto, M.A. Miracolo, J.H. Kroll, D.R. Worsnop, A.L. Robinson, and N.M. Donahue, “Intermediate- Volatility Organic Compounds: A Potential Source of Ambient Oxidized Organic Aerosol,” Environmental Science & Technology, 43(13), 4744–4749.
A.P. Grieshop, N.M. Donahue, and A.L. Robinson, “Laboratory Investigation of Photochemical Oxidation of Organic Aerosol from Wood Fires 2: Analysis of Aerosol Mass Spectrometer Data,” Atmospheric Chemistry and Physics, 9, 2227-2240, 2009.
A.P. Grieshop, J.M. Logue, N.M. Donahue, and A.L. Robinson, “Laboratory Investigation of Photochemical Oxidation of Organic Aerosol from Wood Fires 1: Measurement and Simulation of Organic Aerosol Evolution,” Atmospheric Chemistry and Physics, 9, 1263-1277, 2009.
N.M. Donahue, A.L. Robinson, and S.N. Pandis, “Atmospheric Organic Particulate Matter: From Smoke to Secondary Organic Aerosol,” Atmospheric Environment, 43(1) 97–109, 2009.
M.K. Shrivastava, T.E. Lane, N.M. Donahue, S.N. Pandis, and A.L. Robinson, “Effects of Gas-Particle Partitioning and Aging of Primary Emissions on Urban and Regional Organic Aerosol Concentrations,” Journal of Geophysical Research, 113, D18301, doi:10.1029/2007JD009735, 2008.
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Acknowledgements
Neil Donahue, Spyros Pandis
Marissa Miracolo, Andy Grieshop, Jennifer Logue, David Lee, Kristina Wagstrom, Manish Shrivastava, David Lee, Jeff Pierce, Chris Hennigan, Ngoc Nguyen, Emily Weitkamp, Amy Sage, Tim Lane, Eric Lipsky
Funding: US EPA STAR
Center for AtmosphericParticle Studies