Atmospheric Evolution and Chemical Aging of Organic Particulate Matter

Spyros Pandis and Neil Donahue

Center for Atmospheric Particle Studies (CAPS)

Carnegie Mellon University

Some Questions

• Do the biogenic and anthropogenic SOA components get along (mixing)?• Does the biogenic SOA age gracefully (chemical aging)?• Effects of SOA on climate relevant particle like absorption• Can our updated models reproduce the observations of OA and particle number in areas with both biogenic and anthropogenic sources?

Mixing of Different OA Components

OA for Different Mixing Assumptions

PMCAMx-Summer 2001

Mixing Experiments- Donahue

Correlation of the mass spectra of individual particles with the average initial composition of one of the two populations as a function of time.

Chemical Aging of SOA

β-Caryophyllene SOA Formation

1 10 100 1000

0

10

20

30

40

50

60

70

SO

A Y

ield

(%

)

SOA Mass (μg m-3)

Chen et al. (2011)

Winterhalter et al. (2009)

Lee et al. (2006)

Jaoui et al. (2013)

Ng et al. (2006)

Experimental setup

Smog Chamber(Temperature controlled room)

AMS

SMPS

8

Teflon bag12 m3

Ozone+NOx monitors

ozone generator

O2

tank

300 ppb

HONO or H2O2

Air

2-butanol

Air

β-caryophylleneInjection point

Air

3-30 ppb

0 50 100 150 200 250 300

0

10

20

30

40

50

60

wall losses corrected

raw measurement

time (min)

SO

A M

ass (

μg

m-3)

Temperature increase 20oC →40oC

Formation-Evaporation of the SOA

(28 ppb β-caryophyllene + 300 ppb Ozone + 2-butanol)

β-Caryophyllene ozonolysis SOA yield

0.1 1 10 100 1000

0

20

40

60

80

100

120

SO

A y

ield

(%

)

SOA mass ( ìg m-3)

Chen et al. (2012) (excess of ozone)

This study (no seeds)

This study (with seeds)

SOA (mg m-3)

0 20 40 60 80 100 120 140 160 180 200 220 240 260 2800

5

10

15

20

25

30

raw measurement

wall losses corrected

UV light onUV light offHONO

Time (min)

SO

A M

as

s (

mg

m-3)

Aging of β-caryophyllene SOA by OH

(3 ppb β-caryophyllene + 300 ppb ozone)11

0 50 100 150 200 250

0.10

0.12

0.14

0.16

0.18

0.20

0.22

0.24

0.26

0.28

0.30

0.32

0.34

UV light onUV light off

HONO

O

:C

Time (min)

O:C during aging of SOA

12

Aging of a-pinene SOA

PM Mass Concentration

14

-1 0 1 2 3 4 5 6

0

10

20

30

40

50

60

70

802nd HNO

2

A

eroso

l M

ass

Conce

ntr

atio

n (m

g m

-3)

Time (h)

1st HNO2

COA,1 COA,2

MBTCA Production and Aging

(3-methyl-1,2,3-butanetricarboxylic acid)

Ambient Perturbation Experiments

Dual Mobile Chamber System

Dual Mobile Smog Chamber System

Instrumentation in Mobile Laboratory

Mobile Smog Chambers

Baseline Characterization

20x103

15

10

5

0

Nu

mb

er

(# c

m-3

)

14:00 15:00 16:00 17:00

Time (h)

Chamber 1 Chamber 2

a-Pinene Addition to Chamber 1

20000

17500

15000

12500

10000

7500

5000

2500

0

Nu

mb

er

co

nce

ntr

atio

n (

# c

m-3

)

16:00 17:00 18:00 19:00 20:00 21:00 22:00

Time (h)

Chamber 1 Chamber 2

UV 'ON'

OA Mass Concentration(a-pinene addition)

2.50

2.25

2.00

1.75

1.50

1.25

1.00

0.75

0.50

0.25

0.00

ma

ss c

on

ce

ntr

atio

n (

μg

m-3

)

16:00 17:00 18:00 19:00 20:00 21:00 22:00

Time (h)

Chamber 1 Chamber 2

UV 'ON'

Wall-Loss Corrected OA Concentrations

Corrected

Absorption by SOA+BC

The D-toluene SOA - soot particles have core shell morphology and their absorption is consistent with Mie theory predictions.

Comparison of Mie theory with measurements

SOA formation

2 x SOA formation

PMCAMx Evaluation Summer 2012, Italy

25

OA in a Polluted Area

(Po Valley, Italy)

• Central site of the PEGASOS 2012 campaign

• Rural area in Po Valley

• Agricultural sources

• Industrial sources

Extensive AMS measurements

from 6 June until 8 July 2012

Ground measurements

Zeppelin measurements

PMCAMx

Org

an

ics

(μg

m-3

)

Application of PMCAMx over Europe

Europe

5400 × 5832 km2 region

36 × 36 km2 grid resolution

14 vertical layers (up to 6 km)

MeteorologyWRF oo

EmissionsAnthropogenic (TNO – GEMS)

Biogenic (MEGAN)

SAPRC-99

Volatility basis-set27

OA (μg m-3), June – July 2012

Predicted PM2.5 concentrations – Summer

2012

28

OA (μg m-3) Nitrate (μg m-3)

Sulfate (μg m-3) Ammonium (μg m-3)

0

5

10

15

20

25

30

0

5

10

15

20

25

30

11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 1 2 3 4 5 6 7 8

PM

1O

rgan

ics

(μg

m-3

)

Date (2012)

PM1 OA - Bosco Fontana

Mean predicted: 6.07 μg m-3

Mean observed(AMS): 8.10 μg m-3

June July

observedpredicted

PM1 Organics (μg m-3) – Bosco Fontana

Comparisons with zeppelin observations - OA

30

20/6

0

200

400

600

800

1000

1200

0

2

4

6

8

10

12

14

16

18

20

4:33 5:45 6:57 8:09 9:21 10:33 11:45

Org

anic

s (μ

g m

-3)

Time of day (hrs)

Predicted Observed Altitude

Altitu

de

4/7

0

100

200

300

400

500

600

700

800

0

2

4

6

8

10

12

14

5:16 6:28 7:40 8:52 10:04

Org

anic

s (μ

g m

-3)

Time of day (hrs)

Predicted Observed Altitude

Altitu

de

PMCAMx - Evaluation Spring 2013, Finland

31

PM1 Organics (μg m-3) - Finland

32

April May

0

2

4

6

8

10

12

14

0

2

4

6

8

10

12

14

24 25 26 27 28 29 30 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

PM

1O

A (

μg

m-3

)

Date(2013)

Predicted : 1.9 μg m-3

Observed : 2.1 μg m-3

0

1

2

3

4

5

6

7

0

1

2

3

4

5

6

7

0:00 2:24 4:48 7:12 9:36 12:00 14:24 16:48 19:12 21:36

PM

1O

A (

μg

m-3

)

Time of day (hrs)

Predicted

Observed

Predicted

Observed

Diurnal OA Sources - Finland

33

April May

0

1

2

3

4

5

6

Co

nce

ntr

atio

n (

μg

m-3

)

Date (2013)

OPOA bSOA aSOA fresh POA

aSOA mean predicted = 0.3 μg m-3

bSOA mean predicted =1.2 μg m-3

Fresh POA mean predicted = 0.1 μg m-3

Oxygenated POA mean predicted = 0.3 μg m-3

PMCAMx-Evaluation

1-D Trajectory 2-D VBS Version

Homogeneous chemical aging (with OH)

Simple Functionalization- Base case (Murphy et al., ACP, 2011)

+ O

ato

ms

C*C*/10C*/102

0

1

2

Reactant Species

50%

50%

Reaction constants:

• kOH = 1∙10-11 cm3 molec-1s-1 negligible bSOA aging

for aSOA and bSOA

• kOH = 4∙10-11 cm3 molec-1s-1

for SOA-sv, SOA-iv

Average Diurnal O:C

(San Pietro Capofiume, Italy)

Average predicted O:C = 0.62

Average measured O:C = 0.58

Ground AMS Measurements

Average Diurnal OA Concentration

(San Pietro Capofiume, Italy)

Average predicted OA = 3.4 μg m-3

Average measured OA = 2.8 μg m-3

2 4 6 8 10 12 14 16 18 20 22 240

2

4

6

8

10

OA

(mg

m-3

)

Local Time (Hour)

Ground Measurements

Model

Average Vertical O:C Profile

(All Zeppelin flights)

Average measured O:C = 0.58

Average predicted O:C = 0.59

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

200

400

600

800

1000A

ltit

ud

e (

m)

O:C

Model

Zeppelin

Homogeneous chemical aging (with OH)

Functionalization- Fragmentation

+ O

ato

ms

C*C*/10C*/102

0

1

2

Reactant Species

50%

50%

b

SOA Effects on Particle Number

Particle number concentration fields

(June 2012)

N10 N100(cm-3) (cm-3)

Without organic condensation

Changes due to condensation of organic

vapors (no chemical aging)

N10 N100

Comparison with field observations

• Ground stations:

BIRkenes - Norway

MACe Head - Ireland

HYYtiala - Finland

K-PUszta - Hungary

CORsica - France

ASPvreten

VAVhill

ISPra

San Pietro Capofiume

BOLogna

PATra

FINokalia

THEssaloniki

DREsden

HOHenpeissenberg

MELpitz

SCHneefernerhaus

WALdhof

- Sweden

- Italy

- Germany

- Greece

Evaluation of PMCAMx-UF

Measured With organics and aging

Nucleation Frequency (June 2012)

Location

Measured Organics/Aging

Conclusions

• Rapid mixing of aromatic and biogenic SOA for RH exceeding 20%• Reductions of anthropogenic SOA will help reduce biogenic SOA

• Small change in biogenic SOA produced under low NOx

conditions as it keeps reacting with OH

• Significant later generation production of SOA if the first generation of reactions has taken place under high NOx

conditions.

• Results of MBTCA oxidation by OH and ambient perturbation experiments consistent with the above conclusions.

• Condensation of SOA on BC containing particles increases absorption by as much as a factor of two.• Core-shell Mie theory model reproduces this effect

Conclusions

• Updated PMCAMx predictions for a polluted area with both anthropogenic and biogenic influences consistent with the simple VBS parameterizations of SOA formation and chemical aging.

• A number of 2-D VBS schemes can explain OA and O:C observations.

• Additional constraining expected from ongoing application of PMCAMx to the SOAS campaign.

• SOA condensation leads often to reduction of particle number but to increases of the CCN concentrations.• Significant progress in simulating particle number concentrations

• Future work: Estimation of effects of controls of anthropogenic emissions on biogenic and anthropogenic OA in the Eastern US.

Acknowledgements

Graduate Students and Post-docs

M. Day, L. Hildebrandt, C. Kaltsonoudis, E. Karnezi, E. Kostenidou, B. Murphy, D. Patoulias, E. Robinson, A. Tasoglou, N. Wang, Q. Ye.

Colleagues

I. Riipinen, R. Subramanian, PEGASOS team.

Financial Support

EPA STAR and EU FP7 PEGASOS.

Publications Donahue N. M., W. Chuang, S. A. Epstein, J. H. Kroll, D. R. Worsnop, A. L. Robinson, P. J. Adams,

and S. N. Pandis (2014) Why do organic aerosols exist? Understanding aerosol lifetimes using the 2D VBS, Environ. Chem., 10, 151-157.

Murphy B. N., N. M. Donahue, A. L. Robinson, and S. N. Pandis (2014) A naming convention for atmospheric organic aerosol, Atmos. Chem. Phys., 14, 5825-5839.

Tasoglou A. and S. N. Pandis (2014) Formation and chemical aging of secondary organic aerosol during the b-caryophyllene oxidation, Atmos. Chem. Phys., 15, 6035-6046.

Hildebrandt-Ruiz L., A. Paciga, K. Cerully, A. Nenes, N. M. Donahue, and S. N. Pandis (2014) Formation and aging of secondary organic aerosol from toluene: changes in chemical composition, volatility, and hygroscopicity, Atmos. Chem. Phys., 15, 8301-8313.

Day M. C., M. Zhang, and S. N. Pandis (2015) Evaluation of the ability of the EC tracer method to estimate secondary organic aerosol carbon, Atmos. Environ., 112, 317-325.

Pandis S. N., K. Skyllakou, K. Florou, E. Kostenidou, E. Hasa, and A. A. Presto (2015) Urban particulate matter pollution: A tale of five cities, Faraday Discussions, in press.

Ye Q., E. S. Robinson, X. Ding, P. Ye, R. C. Sullivan, and N. M. Donahue (2016) Secondary organic aerosols are crunchy when dry but runny when wet, submitted.

Tasoglou A., G. Saliba, R. Subramanian, and S. N. Pandis (2016) Absorption of chemically aging biomass burning carbonaceous aerosol, to be submitted.

Wang N., E. Kostenidou, N. M. Donahue, and S. N. Pandis (2015) Chemical aging of a-pinene first-generation ozonolysis products by reactions with OH: I: Low NOx conditions, in prep.

Kaltsonoudis C., E. Kostenidou, E and S. N. Pandis (2015) Development and evaluation of a mobile dual two-chamber system for atmospheric field perturbation experiments, in prep.

Karnezi E. and S. N. Pandis (2015) Simulation of organic aerosol formation in a polluted area with the 2-D Volatility Basis Set, in preparation.