Hourly In-Situ Quantification of

Organic Aerosol Marker Compounds

Allen Goldstein

University of California at Berkeley

ARB Chair’s Seminar Series July 1, 2008

Brent Williams, Angie Miller, UC Berkeley

Nathan Kreisberg, Susanne Hering, Aerosol Dynamics Inc.

Photo by Mike Cubison (U.Colorado-Boulder)

ACKNOWLEDGEMENTS

Funding California Air Resources Board (ARB award 03-324)

ARB Staff Support Nehzat Motallebi, William Vance, Eileen McCauley, Chris Jakober

SOAR Host Paul Ziemann (UC Riverside)

SOAR Coordinator Ken Docherty (University of Colorado Boulder)

Operation of Goldstein mobile lab Angela Miller, Megan McKay (UC Berkeley)

SOAR Participants Ziemann et al., Prather et al., Jimenez et al., Worsnop et al., Schauer et al.,

Hannigan et al., Eatough et al., Weber et al., Arey et al., Fitz et al., Paulson et al., etc.

Overview Quantification of organic marker compounds • Motivation- importance of organic aerosols • Organic aerosol measurement approaches • New in situ instrument

– Thermal desorption Aerosol GC/MS – TAG

• Study of Organic Aerosol in Riverside (SOAR) • TAG in action: hourly measurements of marker

compounds and resolution of source contributions

Further TAG developments (if time allows) • Semi-volatile phase partitioning (SV-TAG) • Introduction of multidimensional GC (2D-TAG)

ObjectiveHourly measurements of organic marker compounds in

ambient aerosols.

Science QuestionsWhat are the major sources for organic aerosols?

How important is secondary organic aerosol (SOA), andwhat are its composition and transformation pathways?

Motivation Regulatory efforts to attain fine particulate matter (PM2.5)

standards require improvements in our knowledge of the factors controlling PM concentration, size, and chemical composition. Organics are typically the largest and least understood fraction of PM.

Objective Hourly measurements of organic marker compounds in

ambient aerosols.

Science Questions What are the major sources for organic aerosols?

How important is secondary organic aerosol (SOA), and what are its composition and transformation pathways?

Aerosols impact climate and health

Ganges River, IndiaGanges River, India

““Asian Forecast: Hazy, WarmerAsian Forecast: Hazy, Warmer—— Clouds of pollution heat lowerClouds of pollution heat lower atmosphereatmosphere””

L.T. M

olina, MIT

N. Marley, Univ. of Arkansas

J. A

llen/

NA

SA

Mexico CityMexico CityLos Angeles, CALos Angeles, CA

Long~lived greenhouse gases

I Halo carbons

Climate efficacy

1'.0

1.0 - 1.2

(see caption)

- 10 -100 yrs

Ozone Stra ospheric Tropospheric 0.5 - 2 .0 Weeks ·to

"1 00 yrs

Stratospheric water vapour from CH4

Surface albedo

{

Direct effect

Total Aerosol Cloud a.lbedo

ef1ect

Linear contrai!s

Solar irradiance

J (-0.05) I I

Land use I

Black carbon on snow

(0.01 }

-2 -1 0 Radiative Forcing

~1.0 10 years

10 -100 yrs

0.7 - 1.1 Days

1.0 - 2 .0 Hours -Days

~ 0.6 Hours

0.7 - 1.0 10 -100 yrs

2 Timescale

Global High

Global High

Continental Med

to global

Global Low

Local to Med continental - Low

Continental Med togloba.l - Low

ConUnen al Low to global

Continental Low

Global Low

Scientific understanding

Radiative forcing of climate between 1750 and 2005

Intergovernmental Panel on Climate Change (2007) Working Group I: The Physical Science Basis of Climate Change

Long~lived greenhouse gases

Ozone

Stratospheric water vapour from CH4

Surface albedo

{

Direct effect

Total Aerosol Cloud a.lbedo

ef1ect

Linear contrai!s

Solar irradiance

-2

Stra ospheric J (-0.05) I I

Land use

(0.01 }

-1 0 Radiative Forcing

Climate efficacy

1'.0

1.0 - 1.2 I

Halo carbons

Tropospheric 0.5

0.

1.0 - .

o.·

(see caption)

- 10 -100 yrs

Days

Global High

Global High

to global

Hours Continental Low

Radiative forcing of climate between 1750 and 2005

Ch. 2 summary: “The total direct aerosol [radiative forcing] as derived from models and observations is estimated to be –0.5 [±0.4] W/m2, with a medium-low level of scientific understanding”

AEROSOLS

MATTER!

Intergovernmental Panel on Climate Change (2007) Working Group I: The Physical Science Basis of Climate Change

Organic aerosol is typically largest fraction (Tropospheric non-refractory PM1 via Aerosol Mass Spectrometer)

“Ubiquity and Dominance of Oxygenated Species in Organic Aerosols in Anthropogenically-Influenced Northern Hemisphere Midlatitudes”, Zhang et al. Geophysical Research Letter, 34 (2007)

Org 2-SO4 -NO3

+NH4

Organic aerosol Characterization methods

Sampling method continuum

bulk ���� size classified ���� single particle

Organic aerosol Characterization methods

Sampling method continuum

bulk ���� size classified ���� single particle

filter impactor In-situ mass spectrometry

��� ���

Organic aerosol Characterization methods

Sampling method continuum

bulk � size classified � single particle

filter In-situ mass spectrometryimpactor

Characterization methods

• group properties – OC/EC, FTIR (bonds), water soluble OC

• molecular level – GC/MS, LC/MS, some single particle MS

Organic aerosol Characterization methods

Sampling method continuum

Characterization methods

• group properties – OC/EC, FTIR (bonds), water soluble fraction

• molecular level – GC/MS, LC/MS, some single particle MS (e.g. UVI)

In-situ mass spectrometry

Solvent extraction/ thermal desorption

bulk ���� size classified ���� single particle

filter impactor In-situ mass spectrometry

��� ���

Organic aerosol Characterization methods

Sampling method continuum

bulk � size classified � single particle

filter In-situ mass spectrometryimpactor

Manual collection Automated time – integrated sampling Time-resolved, continuous often on selected days only

No molecular level Detailed speciation possible characterization

Genesis of TAG: in-situ field instrument

Past PM2.5 organic measurements: In-Situ particle (no individual compound separation) Filter collection (12 to 24-hour time resolution)

Need an instrument capable of: Separating / Identifying / Quantifying individual organic marker compounds from ambient PM2.5 with hourly time resolution (to track diurnal changes)

Genesis of TAG: in-situ field instrument

Goldstein et al. methods for VOCs:

“In situ measurements of C2-C10 volatile organic compounds

above a Sierra Nevada ponderosa pine plantation”

M.S. Lamanna and A.H. Goldstein, J.Geophys. Res. 104 (1999)

“VOC measurements at Trinidad Head, CA …Analysis of sources,

atmospheric composition and aerosol residence times” D.B. Millet, A.H. Goldstein et al., J.Geophys. Res. 109 (2004)

Hering et al. methods for inorganic aerosols:

“A new method for the automated measurement of atmospheric fine particle nitrate”

M.R. Stolzenburg and S.V. Hering, Environ. Sci. and Technol. 34 (2000)

“Hourly concentrations and light scattering cross sections for fine particle sulfate at Big Bend National Park”

S.V. Hering et al. Atmospheric Environment 37 (2003)

TAG= Thermal desorption Aerosol Gas chromatograph (MS/FID)

Gas Chromatograph

Mass Spectrometer

6-port valve

Aerosol Collector &

Thermal Desorption Cell

Cyclone Precut (PM2.5)

Humidifier (adhesion)

Filter (field blank)

x

1

2 3 4

1. Collection technique:

– Inertial Impaction (30°C) 2. Sample transfer:

– Thermal Desorption (50-300°C ) 3. Chemical separation:

– Gas Chromatography 4. Compound quantification:

– Mass Spectrometry (and/or FID) 5. Compound identification:

– Spectrum + Retention Time Matching

TIC: RVR 392.DTIC: RVR 385.DTIC: RVR 394.D

TAG urban ambient data

500000

450000

400000

350000

300000

250000

200000

150000

100000

50000

0

>

_ _ _

Ambient Air

Pure Air

Filtered Air

Particle = Ambient – Filtered

20.00 25.00 30.00 35.00 40.00 45.00 50.00 55.00

Time Resolution: 1 hour Collection: 0.5 hour Sample Volume: 0.25 m 3

Thermal Desorption: 50-300 0C GC oven temp. range shown here: ~ 45 0C to 3000C

Resolved compounds will determine the aerosol source (i.e. markers)

Total Ion Abundance

0 i i I I ~ i i I I I ~ -!!:a= 2-F Ura nm eiha rlol ' · ' · · ' ' '

~-t?hthalic acidNicotine g r-

s g

Nicotyrine Levogl ucosane

1 ,2 diphenylcyclopropane

;o ~ ~ g

Myri sti c acid 1 ,4-0iphenyl-1 , 3-butadi ene

Hmdecaooic acid, methyl estec . . / I 11 I i i I i i 11 ~======::....::__:_:.::._£Palm1t1c acid / 8 .....

m ::, ..... 0 "-I ::, 0

::1 g 3 m --~- ~ ::, I

- g

~ g

~

g g

I

,' ~ ]":;:-:::=~ Cocaine

Oleic acid / i ~i:;;~~====~======~site;;aric acid / ~

~~~------ Docosane a1r=-Tricosane -------------------------------Tricosane

Tetracosane

Pentacosane Hexacosane ------------------------- 7

5 Heptacosane \ \

i

~ 8 ~ 8

Cyclic alkane? Octacosane ~ . = Non acosane

I

~ 8

""' Stigmasta~~j~~~d11Ane

~

t aryl l_a\.lr~ineitriacontane D01tnacontane

ritriaconta ne Tet ratriaco ntane

Hexatriaco ntane

Heptatri acontan e

I I I ~

8 I I I,

~ ~ I 8 ! \ "4 I !' ~ 8 I , I I ,

~8 I

' \

phen anthreneca rb oxylic acid ester

Benzly butyl phthalate

Eicosene T etracosa ne

=====-?

Z-12-Pentacose ne - Pentacosane

Dronabinol

~ ()

~ c

Bis(2-ehtylhexyl) p hthalate

::-=::::--- C~n nabi nol Hexacosane

TA

G

Ex

amp

le Ch

rom

ato

gram

B

erkeley

Am

bien

t Air

Feb

ruary

7, 2006 22:30-24:00

100’s of id

entifiab

le co

mp

ou

nd

s

TAG Applications To Date

• Field Sampling

– ICARTT 2004, Chebogue Point, Nova Scotia

• Ambient sampling downwind of United States and Canada

– SOAR 2005, Riverside, California

• Ambient sampling downwind of Los Angeles

– BEARPEX 2007, Blodgett Forest, California

• Ambient sampling within a forest canopy

– Pittsburgh Toxics Study 2008, Pittsburgh, Pennsylvania

• Ambient sampling within urban center

– Carnegie Mellon University

• Reaction chamber studies

020

060

010

000

24

68

100

510

15

020

0060

000

24

68

100

510

15221188 222200 222222 222244 222266 222288 221188 222200 222222 222244 222266 222288

Individual TAG Compounds vs. Aerosol Mass Spectrometer (AMS) Total Organics and Total SO4

2-

Chebogue Point Nova Scotia 2004 Compound: A Compound: B

4-Pentenoic acid, 2-acetyl-2,3-dimethyl-,ethyl ester

)(C11H18O3

TAG Compound A

218 220 222 224 226 228 Day of Year 2004

Event Type 2

Event Type 1 No SO4

Rel

ati

ve

Ab

un

da

nce

(dif

fere

nt

sca

les)

Rel

ati

ve

Ab

un

da

nce

(dif

fere

nt

sca

les)AMS SO4

1,6-Dioxaspiro[4,4]nonane-2,7-dione

(C7H8O4)

218 220 222 224 226 228 Day of Year 2004

Event Type 2

TAG Compound B

Event Type 1 No SO4

AMS Total Organics

SO4 SO4

AMS data (Aerodyne Research, Inc.: Worsnop et al.)

□ 0 .0000 - 0.0012

0 0 .0012 - 0.0018

0 0 .0018 - 0.0027

0 0 ,0027 - 0,0040

□ 0 .0040 - 0.0060

□ 0 .0060 - 0.0090

■ 0 .0090 - 0.0136

■ 0 .0136 - 0.0203

□ 0 .0203 - 0.0305

■ 0 .0105 - 0.0458

■ 0 .0458 - 0.0686

■ 0 ,0686 - 0,1030

■ > 0 .1030

Study of Organic Aerosols at Riverside (SOAR)

Location: University of California, Riverside

50 Miles : 80 Kilometers

Los Angeles Riverside

N

PM2.5 Gridded Emissions (short tons/ozone season day/grid cell)

NOAA http://map.ngdc.noaa.gov/website/al/emissions/Run.htm

SOAR 2005

2 Measurement Periods

• Summer (July 18 – August 15, 2005)

• Fall (October 28 – November 30, 2005)

Instrumentation

• Meteorological, radiation, trace gas, and aerosol measurements

• TAG, VOC-GC/MS, O3 (x2), CO (x2), NOx (x2), Aerodyne AMS (x5), Thermal desorption particle beam MS, ATOFMS (x3), CPC (x8), EC/OC (x2), PILS-WSOC, High Volume filter samplers (multiple), aethelometer (multiple), nephelometer (multiple), OPC, DMA, MAAP, SMPS (multiple), APS, TEOM (multiple),Hg speciation, DMT CCN, meteorological and radiation equipment

• See study website for more details: (http://cires.colorado.edu/jimenez-group/Field/Riverside05/)

a)

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((uugg

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SOAR Measurement Periods

a) Summer (July 17-August 15)

2000 150Focus Period40

AM

SO

rgan

ics

(ug

m-3

)

150030

100020

50010

CO

(ppb

)

CO

(ppb

)

100

50

0 0 0

195

200

205

210

215

Day of Year 2005 Fall (October 25-November 30)b)

325

220

330

225

335

AM

SO

rgan

ics

(ug

m-3

)

2000 150Focus Period40

150030 100

50 100020

50010

0 0 0

300

305

310

315

320

O3

(ppb

)

O3

(ppb

)

Day of Year 2005

Very different Photochemistry (and Meteorology)

\/ I✓ ._-... -1- _,. ,,,- \

/ I \_,, '-.z_ -----\

I '-... __ I __ _..

Summer Winds Fall Winds (11 days) (11 days)

N N

10 20

30 40

E W

S

S

5 10 15 20 25

EDay W

S

S

N N

Night W 5 10

15

E W 5 10 15 20 25

E

0.4 - 0.8 m/s 0.0 - 0.4 m/s 0.8 - 1.2 m/s >1.2 m/s Wind Speed = Frequency = Length of Wedge

SOAR TAG Measurements and Source Apportionment

• Resolved >300 organic marker compounds hourly

• Positive Matrix Factorization (PMF) – 128 of 300 resolved TAG organic compounds in Summer – 144 of 300 resolved TAG organic compounds in Fall

• Identified organic aerosol sources based on PMF groupings – 8 in Summer – 7 in Fall

San Francisco Bay

Northern CaliforniaNorthern California Sept. 6, 2007Sept. 6, 2007

‘Lick’ fire

‘Moonlight’ fire

Marker compounds for source identification

Wood combustion ~ retene

800

750

700

650

600

550

500

450

400

350

300

250

200

150

100

219 m/z

234 m/z

33.80 33.85 33.90 33.95 34.00 34.05 34.10 34.15 34.20 34.25 34.30 34.35

Bangkok

222111000 222111222 222111444 222111666 222111888 222222000

Examples of marker compounds for source

Motor vehicles ~ hopanes, steranes identification

Bangkok

Riverside

C30H52 MW 413

17α(H),21β(H)-30-Norhopane

210 212 214 216 218 220 Day of Year 2005

Day of Year 2005

28no

r17b

etah

.hop

ane

210 212 214 216 218 220210 212 214 216 218 220210 212 214 216 218 220

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Abu

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8/10

12-Hour Filter Collection Simulation

Riverside, 2005

0 10

0000

20

0000

30

0000

40

0000

210 212 214 216 218 220

7/29

7/30

7/31

8/01

8/02

8/03

8/04

8/05

8/06

8/07

8/09

Hourly (TAG) data captures dynamics missed by 12 hour filter collections

17α(H),21β(H)-30-Norhopane (Vehicle Emission Marker)

Day of Year 2005

28no

r17b

etah

.hop

ane

210 212 214 216 218 220210 212 214 216 218 220210 212 214 216 218 220

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0 10

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210 212 214 216 218 220

7/29

7/30

7/31

8/01

8/02

8/03

8/04

8/05

8/06

8/07

8/09

Riverside, 2005

Time resolved data captures dynamics

Large morning maxima Multiple maxima

within 12-hours

17α(H),21β(H)-30-Norhopane (Vehicle Emission Marker)

Riverside, CARiverside, CA

Biogenic vs.

Anthropogenic Alkanes

]2

)([

31

25

11

∑ =

+− +−= n

nn nwax

CCCC

Adapted from Simoneit 1989 J.Atmos.Chem.

SUMMER

0% 20% 40% 60% 80%

100%

210

211

212

213

214

215

216

217

218

219

220

Day of Year 2005

C25

-C31

Alk

ane

Mas

s (%

)

FALL

0 20 40 60 80

100

308

309

310

311

312

313

314

315

316

317

318

319

Day of 2005

C25

-C31

Alk

ane

Mas

s (%

)

Biogenic Wax Anthropogenic

Biogenic Wax Anthropogenic

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Relative Abundance dcpa

0 5*10^5 10^6 1.5*10^6

Relative Abundance 17alphah21betah.hopane

0 100000 200000 300000 400000 500000

Relative Abundance28nor17betah.hopane

0 100000 200000 300000 400000

210 212

214 216

218 220

Day

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215 216

5 W

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214210

212 214

216 218

220

Day

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)-hopane N SS

DO

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218 220

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210

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40Filtered30

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Meat Cooking

Burning

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210 212 214 216 218 220

Day of Year 20052

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215

216

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220

215

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221100 221122 221144 221166 221188 222200

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210 212 214 216 218 220 S

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Biogenic Secondary

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Phthalic Acid N

5040

3020

10W E

210 212 214 216 218 220

215Day of Year 2005

216

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2

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11

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2

12

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13

213

Day of Year 2005

214

215

216

214

217

217

2

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5-pentyl-dihydro-2(3H)-furanone

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212

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214

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140

120

100

80

60

40

20 0

-20

-40

d in o n y lp h th a la te p e n o xa l in e

h e xa d e ca n o ic .a c id -m e th y le s te r d io c ty lp h th a la te

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3 -m e th y lp h th a l ic .a c id 4 -m e th y lp h th a l ic .a c id

p h th a l ic .a c id d im e th y l iso b e n zo fu ra n d io n e

5 -m e th y l-2 -n itro p h e n o l d ih yd ro -5 -e th y l-2 (3 H )fu ra n o n e

d o d e ca n e d io n e d -te tra d e c a la c to n e

d io xa sp iro n o n a n e d io n e u n d e ca n e d io n e

b u ty lb e n ze n e su lfo n a m id e o c ta d e ca n o n e

d e h yd ro a b ie tic .a c id -m e th y le s te r c h lo ro p h o s p h a te p ro p a n o l

2 -m e th y la n th ra ce n e n o n a d e ca n e

iso p ro p y l-d im e th y lp h e n a n th re n e te tra co s a n e

d ip h e n y l .e th a n e d io n e 2 -m e th y lo c ta d e ca n e

n o rh o p a n eh o p a n e

4 -m e th y lo c ta d e ca n e 3 -m e th y lo c ta d e ca n e 2 -m e th y lo c ta d e ca n e

la te .5 7 a n th ra c e n e

m o n o p a lm itin n o n a d e cy lcyc lo h e xa n e

n o n a d e ca n e m o n o s te a rin

o c ta d e c y lcy c lo h e x a n e c y c lo p e n ta (c d )p y re n e

e ico sy lcyc lo h e xa n e h e x a d e c a n o ic .a c id o c ta d e c a n o ic .a c id o c ta d e c a n e n itri le

h e xa d e c a n e n itri le d im e th o xyd ip h e n y l.e th a n o n e

e u p a to rio ch ro m e n e m e th y ld ia m a n ta n e

d -ca d in e n e e n ce ca l in

va n i l l in tria c o n ta n e

o c ta co s a n e h e n tria c o n ta n e

n o n a co sa n e h e xa co sa n e

h e p ta co s a n e m e th y lo xa a d a m a n ta n e

m e th o xyp y rid in e p e l le tie r in e

p -cym e n e n e d -3 -ca re n e

p e n ty lc yc lo h e x a n o n e a -p h e l la n d re n e

m e th o xyp h e n y lm e th y le n e .b e n ze n a m in e d io xa sp iro u n d e ca n o n e

l im o n e n e m e th y l fu ra n o n e

s a b in a .k e to n e d i.te rt.b u ty ln i tro p h e n o l

n o ra b ie ta .4 .8 .1 1 .1 3 .te tra e n e d ip h e n y la m in e

n o ra b ie ta te tra e n e -m ix tu re 7 -o xo d e h yd ro a b ie tic .a c id -m e th y le s te r

2 -m e th y lp y re n e

SO

AR

Su

mm

er Org

anic A

eroso

l Facto

r Pro

files

SOA1

SOA2

SOA3

RegionalPrimaryAnthro

LocalVehicle FoodC

ooking BioParticle+M

ixed BioSem

ivolatile Biom

assBurning Residual

~ -0.0012

□ 0 .0012 - 0.0018 0 0 .001B - 0.0027

□ 0 .0027. 0.0040

□ 0 .0040 - 0.0060

□ 0 .0060 - 0.0090 ■ 0,0090 - 0,0136 ■ o,orn; _ 0,0203

□ 0,0203 - 0,0305 ■ 0 ,0305 - 0 ,0458

■ 0 ,0458 - 0 ,0686

■ 0 ,0686 - o,i.o 3o ■ > 0 ,1030

SOA3SOA2SOA1NNN 20 2525

2015 20151510

10105 5WEW WE E

5

SSS

FoodCookingLocalVehicleRegionalPrimaryAnthroNNN 20 158

15 6 10410

525W WE EWE

SSS

BiomassBurningBioSemivolatileBioParticle+MixedN 15N15N

54 10 103

52 51

EWEWEW

SSSResidual N

10N

86 888000 k k kmmm4

2W RRRiiivvveeerrrsssiiidddeeeLLLooosss AAAnnngggeeellleeesssE

111333555 k k kmmmS

SSSaaannn DDDiiieeegggooo

SOA1 SOA2 SOA3 N N N20 2525

2015 20151510

1010 5 5 E WW E W E

5

SOAR Summer Organic Aerosol

S S S

RegionalPrimaryAnthro LocalVehicle FoodCooking SourcesN N N20 15

815 6 10

410525

W E W EE W

SS S

BioSemivolatile BiomassBurningBioParticle+Mixed N

5 N 15 N 15

4 10 103 52 51

EE WWEW

S SS Residual N

N 108

6 80 km42

W RiversideE Los Angeles

135 kmS

San Diego

■

l ~~ ■

D

i ~'

l ~ ', I

■

■

D

■

; ~ ! ! i

! I I I

~ ; .! ! ! ~ I

7

Po

sitive

Matrix

Fa

ctorizatio

n(P

MF

)R

esults

F a c to r C o n trib u tio n s to P a ra m e te r C o n c e n tra tio n s (%

nitrop he ny lben z e nam ine oc tad ec ano ic .a c id

o le ic .a c id te trad ec ano ic .a c id

p e lle tie r ine he x ad ec ano ic .a c id

do dec an ed ione 4 -n itro phe no l

ben z y lbe nz o a te d iox as p iro un dec an one

he n tr iac on tane n ona na l

m o no s te a r in p h th a lim id e

o c ta de c an en itr ile he x a de c an en itr ile

un dec an ed ione x a n th one

pen tad ec ene na ph tho fu ra nd ione

m o no pa lm itin d -oc ta lac tone

d ih y d ro - 5 -e thy l-2 ( 3H ) fu ran one d -no na lac tone

r im u ene c y c lope n ta (d e f)p he nan th r en one

3 - m e thy lph tha lic .ac id s ab ina .k e ton e

ph tha lic .a c id 1 ,8 -n ap h th a lic anh y d r ide

d ih y d ro - 5 -d ode c y l-2 ( 3H ) fu ran one m e thy lfu ran one

be nz o ic .a c id a n th raq u in one

c um in ic .a ldeh y d e no nad ec ane

4 -m e th y loc tad ec ane 2 -m e th y loc tad ec ane

hen e ic os ane te tr ade c y lc y c loh ex ane

pe n tade c y lc y c loh ex ane 3 -m e th y loc tad ec ane

h op ane n o rh op ane

c y c lop en ta (c d ) py r ene ac e ph ena n th ry lene

la te .57 eup a to r io c h r om en e

oc tade c y lc y c loh ex ane e ic o s y lc y c loh ex ane

n ona de c y lc y c loh ex ane d io c ty lph tha la te

c h ry s ene he p tade c y lc y c loh ex ane

a n th rac ene m e th ox y ph en y lm e th y le ne .ben z e nam in e

a - phe lla nd r ene e thy lm e th y lfu ran

g - te r p in ene m e thy lox aad am an tan e

d -do de c a lac tone no rab ie ta .4 .8 .1 1 .1 3 .te tra ene

is op ro py l.d im e th y lp he nan th r ene re tene

no r ab ie ta te tr aen e - m ix tu r e d eh y d r oa b ie tic .a c id -m e th y le s te r

7 -o x od eh y d r oa b ie tic .a c id -m e th y le s te r d im e thy lbu ty lp he ny l.ben z e ned iam in e

p inon a ld eh y de

SO

AR

Fall O

rgan

ic Aero

sol F

actor P

rofiles

-60.0

-40.0

-20.0

0.0

20.0

40.0

60.0

80.0

100.0

120.0

140.0

160.0

SOA+FoodC

ooking1 SO

A+FoodCooking2

RegionalPrimaryAnthro

LocalVehicle BioSem

ivolatile Biom

assBurning Residual

V \/ / \.

,,-, '> \. I ..._ -,; I

'- I--.. ~ I ,; - -I....._ ...._ I

- -'

I

- - L

I - I- '

I / ' I '\ .,..,....

/ \

I

' > I I -<

-7\--l\--f~=-= I \ ,..- "\ I ~

\ /,.... ( y..

.,., .... \ '/-....._1 ) '- I I-~ \

'7,

~ 0 - 0.0012

□ 0.0012 - 0.0018

□ 0 .0018 - 0 .0027

□ 0.0027 - 0.0040

□ 0.0040 - 0.0060

□ 0.0060 - 0.0090

■ 0.0090 - 0.0136

■ 0.0136 - 0.0203

□ 0 .0203 - 0 .0305

■ 0 .0305 - 0 .0458

■ 0 .0458 - 0.0686

■ 0 .0686 - 0 .1030

■ > 0 .1030

SOA+FoodCooking1 SOA+FoodCooking2 RegionalPrimaryAnthro10N N N 25108 8 20

6 156104 4

2 2E WW E W E

5

S S S

BioSemivolatileLocalVehicle BiomassBurningNN N

88 1566 104

224

5

W E WWE E

SSSaaannn DDDiiieeegggooo

S S S

ResidualN

64 N

2

W E 888000 kkkmmm

LLLooosss AAAnnngggeeellleeesss RRRiiivvveeerrrsssiiidddeee

S

111333555 kkkmmm

SOA+FoodCooking1 SOA+FoodCooking2 RegionalPrimaryAnthro N 10 N N 25

10

8 8 206 156

104 42 2

E WW E W E5 SOAR Fall

Organic S S S Aerosol

LocalVehicle BioSemivolatile BiomassBurningN N N

88 15 Sources66 104

2 2 4

5

W E WE W E

San Diego

S S S

ResidualN

6 4 N

2

W E 80 km

Los Angeles Riverside

S

135 km

□ □ ■

■ ■ □ ■

□ ■ ■

■ □ ■

□ ■ □ ■

1------·

Org

anic

Aer

osol

(ug

m-3

)O

rgan

icA

eros

ol(u

gm

-3)

Fri. Sat. Sun. Mon. Tues. Wed. Thur. Fri. Sat. Sun. Mon.30

AAMSMS OOrrggaanniiccss

20

10

0210 211 212 213 214 215 216 217 218 219 220 221

Day of Year 2005 (PST)

SSOOA1A1 RReeggiioonnaallPPrriimmaarryyAAnntthhrroo BBiiooPPaarrttiiccllee++MMiixxeeddSSOOA2A2 LLooccaallVVeehhiiccllee BBiiooSSeemmiivvoollaattiilleeSSOOA3A3 FFooooddCCooookkiinngg BBiioommaassssBuBurrnniinngg

RReessiidduuaall

Tues. Wed. Thur. Fri. Sat. Sun. Mon.Mon.Sun.Fri. Sat.

AAMMSS OOrrggaanniiccss20

15

10

5

0308 309 310 311 312 313 314 315 316 317 318 319

Day of Year 2005 (pst)

SSOOAA+F+FooooddCCooookkiinngg11 BBiiooSSeemmiivvoollaattiilleeSSOOAA+F+FooooddCCooookkiinngg22 BBiioommaassssBuBurrnniinnggRReeggiioonnaallPPrriimmaarryyAAnntthhrroo RReessiidduuaallLLooccaallVVeehhiiccllee

SOAR Summer

SOAR Fall

Org

anic

Aer

osol

(ug

m-3

) O

rgan

ic A

eros

ol (

ug m

-3)

Fri. Sat. Sun. Mon. Tues. Wed. Thur. Fri. Sat. Sun. Mon. 30

AMS Organics

20

10

0 210 211 212 213 214 215 216 217 218 219 220 221

Day of Year 2005 (PST)

SOA1 RegionalPrimaryAnthro BioParticle+Mixed SOA2 LocalVehicle BioSemivolatile SOA3 FoodCooking BiomassBurning

Residual

Fri. Sat. Sun. Mon. Tues. Wed. Thur. Fri. Sat. Sun. Mon.

AMS Organics 20

15

10

5

0 308 309 310 311 312 313 314 315 316 317 318 319

Day of Year 2005 (pst)

SOA+FoodCooking1 BioSemivolatile SOA+FoodCooking2 BiomassBurning RegionalPrimaryAnthro Residual LocalVehicle

■ □

■

□ □ ■

□ ■ ■

□ ■ □ ■

2:00

4:

8:00

00

:

2:00

4:

8::00

00

13.6

13.5

14.5

16.5

20.220.2

21.3

19.8

13.1

10.0

15.0

20.8

--OOrgrgaanniiccss ( (µµgg mm--33)) NONO3322-- ++SSOO44 NHNH44

30.6 26.3 µg m-3

22.9 28.7

33.8 32.9

40.242.1

AMS Total Organic Aerosol = 10.0 - 20.8 µg m-3

44.6

20.6

0:00

00

6:00

00

10:0012:00

14:00

16

18:00

20:

22:00

26.3

36.3 44.6

20.6

0:00 2:00

4:00

6:00

8:00

10:0012:00

14:00

16:00

18:00

20:00

22:00

13.6

13.5

14.5

16.5

20.220.2

21.3

19.8

13.1

10.0

15.0 26.3

20.8

36.3

-Organics (µg m-3) NO3 2- +SO4 NH4

30.6 26.3 µg m-3

TAG-defined Organic Aerosol Sources 22.9 28.7

33.8 32.9

42.1 40.2

AMS Total Organic Aerosol = 10.0 - 20.8 µg m-3

SOAR Summer

13.5

13.6 µg m-3

14.5

16.5

20.8

20.220.2

21.3

19.8

13.1

10.0

15.0

0:00

00

6:00

00

10:0012:00

14:00

16:

18:00

20:

22 00

AMS Total Organic Aerosol = 10.0 - 20.8 µg m-3

SOA1SOA2SOA3

RegionalPrimaryAnthroLocalVehicleFoodCooking

BioParticle+MixedBioSemivolatileBiomassBurningResidual

13.5

13.6 µg m-3

14.5

16.5

20.8

20.220.2

21.3

19.8

13.1

10.0

15.0

0:00 2:00

4:00

6:00

8:00

10:0012:00

14:00

16:00

18:00

20:00

22:00

AMS Total Organic Aerosol = 10.0 - 20.8 µg m-3

SOA1 SOA2 SOA3

RegionalPrimaryAnthro LocalVehicle FoodCooking

BioParticle+Mixed BioSemivolatile BiomassBurning Residual

ChlorideChlorideChloride

■ □

■

■ ■ □ ■

■ □ ■

2:00

4:

8:00

00

9.9

11.3

10.3

11.6

10.5

10.26.0

6.2

8.2

10.0

10.8

10.3

2:00

4:

8:00

00

9.9

11.3

10.3

11.6

10.5

10.26.0

6.2

8.2

10.0

10.8

10.3

2:00

4:

8:00

00

2233..11 µµgg mm--332244..4424.4 23.1 µg m-3

SOAR Fall

TAG-defined Organic Aerosol Sources

Organics (µg m-3)SO4

2-NO3

-

NH4+

Chloride

AMS Total Organic Aerosol = 6.0 – 11.6 µg m-3

26.0

24.7

27.7

25.4

24.515.0

16.0

21.5

25.3

25.4

0:00

00

6:00

00

10:0012:00

14:00

16:

18:00

20:

22:00

Organics (µg m-3)SO4

2-NO3

-

NH4+

ChlorideOrganics (µg m-3) SO4

2-NO3

-

NH4 +

Chloride

AMS Total Organic Aerosol = 6.0 – 11.6 µg m-3

26.0

24.7

27.7

25.4

24.515.0

16.0

21.5

25.3

25.4

0:00

00

6:00

00

10:0012:00

14:00

16:

18:00

20:

22:00

26.0

24.7

27.7

25.4

24.515.0

16.0

21.5

25.3

25.4

0:00 2:00

4:00

6:00

8:00

10:0012:00

14:00

16:00

18:00

20:00

22:00

9.9

11.3

10.3

11.6

10.5

10.26.0

6.2

8.2

10.0

10.8

10.3 9.9

11.3

10.3

11.6

10.5

10.26.0

6.2

8.2

10.0

10.8

10.3

AMS Total Organic Aerosol = 6.0 – 11.6 µg m-3

11.3

9.9 µg m-3

10.3

11.6

10.5

10.26.0

6.2

8.2

10.0

10.8

10.3

0:00

00

6:00

00

10:0012:00

14:00

16:

18:00

20:

22:00

SOA+FoodCooking1SOA+FoodCooking2RegionalPrimaryAnthroLocalVehicle

BioSemivolatileBiomassBurningResidual

AMS Total Organic Aerosol = 6.0 – 11.6 µg m-3

11.3

9.9 µg m-3

10.3

11.6

10.5

10.26.0

6.2

8.2

10.0

10.8

10.3

0:00 2:00

4:00

6:00

8:00

10:0012:00

14:00

16:00

18:00

20:00

22:00

SOA+FoodCooking1 SOA+FoodCooking2 RegionalPrimaryAnthro LocalVehicle

BioSemivolatile BiomassBurning Residual

Average Source Concentrations and Contributions to Total OA during SOAR 2005.

SUMMER FALL Average

Concentratio n (ug m-3)

Contribution to Total

Organics (%)

Average Concentratio

n (ug m-3)

Contribution to Total

Organics (%) SOA1 1.61 9.9 SOA+FoodCooking1 1.26 13.0 SOA2 3.06 18.9 SOA+FoodCooking2 5.47 56.3 SOA3 2.92 18.0 RegPrimAnthro 1.46 15.0

RegPrimAnthro 2.43 15.0 LocalVehicle 0.11 1.1 LocalVehicle 0.57 3.5 BioSemivolatile 0.18 1.9 FoodCooking 1.01 6.2 BiomassBurning 0.91 9.4

BioParticle+Mixed 1.10 6.8 Residual 0.33 3.4 BioSemivolatile 2.18 13.5

���

AMS O:C ~ TAG Compounds Measured during SOAR 2005 OOA1 (0.9) 300 Identified Hourly (~10-20% of organic mass)

Increasing oxidation � increasing measurement difficulty

OOA2 (0.55)

BBOA (0.35)

HOA (0.08)

0

0.1

0.2

0.3

0.4

0.5

0.6

15.0 20.0 25.0 30.0 35.0 40.0 45.0 50.0

Retention Time (min)

O:C

0

50

100

150

200

250

300

350

GC

Ove

n T

empe

ratu

re (

o C

)

C26

O0

O1

O2

O3

O4 C7

C9

C21 C17

C11

C14

Aiken et al., submitted ES&T Williams et al., in prep

60 ■ other ■ sum(halogens) 11 PANs ■ aromatics

50 E'd:I MVK+MACR □ i soprene □ monoterpenes □ formaldehyde

40 ~ acetaldehyde ■ formic acid ~ acetic acid ■ ethanol

30 ~ methanol □ acetone I'd:! butane ■ propane

20 ~ ethane ■ oc aerosol

(J ·-C n:s 10 O') a... 0

0

Total Observed Organic Carbon (TOOC)Organic aerosol = 3-17%

Total Observed Organic Carbon (TOOC) Organic aerosol = 3-17%

[Heald et al., ACP 2008]

05*

10^5

10^6

1.5*

10^6

02*

10^6

4*10

^66*

10^6

8*10

^60

5*10

^510

^62*

10^6

3*10

^6

TAG Particle+Gas Ambient Measurements

02*

10^5

4*10

^56*

10^5

8*10

^510

^60

5*10

^510

^61.

5*10

^62*

10^6

02*

10^6

6*10

^610

^71.

4*10

^7

02*

10^5

6*10

^510

^60

10^6

2*10

^63*

10^6

4*10

^60

2*10

^66*

10^6

10^7

210 212 214 216 218 220210 212 214 216 218 220210 212 214 216 218 220

210 212 214 216 218 220 210 212 214 216 218 220210 212 214 216 218 220

210 212 214 216 218 220210 212 214 216 218 220210 212 214 216 218 220

pent

acos

ane

nona

deca

ne

trid

ecan

e

0 5*

10^5

10

^6

1.5*

10^6

0

2*10

^6

4*10

^6

6*10

^6

8*10

^6

0 5*

10^5

10

^6

2*10

^6

3*10

^6

DOY>

TAG Particle+Gas Ambient Measurements C13 Alkane C15 Alkane C17 Alkane

nona

cosa

ne

tric

osan

e he

ptad

ecan

e

0 2*

10^5

4*

10^5

6*

10^5

8*

10^5

10

^6

0 5*

10^5

10

^6

1.5*

10^6

2*

10^6

0

2*10

^6

6*10

^6

10^7

1.

4*10

^7

hept

acos

ane

hene

icos

ane

pent

adec

ane

0 2*

10^5

6*

10^5

10

^6

0 10

^6

2*10

^6

3*10

^6

4*10

^6

0 2*

10^6

6*

10^6

10

^7

Particle+Gas Gas 210 212 214 216 218 220 210 212 214 216 218 220 210 212 214 216 218 220

Day of Year 2005 Day of Year 2005 Day of Year 2005

C19 Alkane C23 AlkaneC21

Alkane

210 212 214 216 218 220 210 212 214 216 218 220210 212 214 216 218 220

Day of Year 2005 Day of Year 2005Day of Year 2005

C27 Alkane C29 AlkaneC25 Alkane

214

215

216

210

212

214

215

216

210 212 214 216 218 220 210 212 214 216 218 220 210 212 214 216 218 220

Day of Year 2005 Day of Year 2005Day of Year 2005

214

215

216

211

213

217

218

219

220

210

211

212

213

217

218

219

220

210

211

212

213

217

218

219

220 DOY>DOY>

Williams et al in prep

.. ■

■ ... ..

•■ , ..

'II .. .. . -■

. ■ • ■ - - ---...

. , .. . , . , ,

■ .

' I . .

' ~ I/

••

- ... -- ... -

• - ... -- ... -- ... -- ... -- ... -

,■ ,

Gas-Particle Partitioning from TAGAmbient Measurements by Compound Class

Gas-Particle Partitioning from TAG Ambient Measurements by Compound Class

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

Number of Carbon

Fra

ctio

n in

Par

ticle

Pha

se (

acco

rdin

gto

TA

G c

olle

ctio

n)

Alkanes

Alkanoic Acids Dihydro-2(3H)-Furanones

Cyclohexanes

PAHs

Phthalates Alkanones

___ Fall …... Summer

Williams et al in prep

Summary • Achieved hourly speciated organic aerosol measurements

during SOAR campaign for >300 compounds • Differentiated biogenic and anthropogenic contributions of

primary and secondary organic aerosol in Riverside, and quantified large diurnal cycles in source contributions

• Secondary compounds, many of which are semi-volatile, dominate the organic aerosol in Riverside in afternoon

• TAG measurements observe ambient gas-particle partitioning and hence offer insight to the formation of SOA

Future • Analyzing 2007 BEARPEX data from Blodgett Forest • Developing multi-dimensional TAG (2D-TAG) for improved

compound separation • Developing Semi-Volatile TAG (SV-TAG) for simultaneous

quantitative measurements of gas and particle composition • Planning additional urban and rural field measurements

Funding DOE STTR DOE SBIR

2D-TAG

TWO-DIMENSIONAL CHROMATOGRAPHY OF ATMOSPHERIC AEROSOLS: A NEW IN-SITU INSTRUMENT

Allen H. Goldstein, Brent J. Williams University of California, Berkeley

Susanne V. Hering, Nathan M. Kreisberg Aerosol Dynamics Inc.

Tadeusz Górecki, Ognjen Panic University of Waterloo

-Hourly, in-situ characterization of organic markercompounds in ambient aerosols

TAG (1D) Thermal desorption Aerosol GC -Hourly, in-situ characterization of organic marker compounds in ambient aerosols (Williams et al AS&T 2006)

2D-TAG 2-Dimensional Thermal desorption Aerosol GC -Vastly increase number of separated compounds -Classify compounds by chemical family and size

(Goldstein et al J Chrom A 2008)

- -

1-D Chromatography Separation limited by column capacity

Difficult separating highly complex samples

First dimension elution

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Solvent frontSolvent 2 front

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ent1

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2-D Chromatography Increased separation using orthogonal

column phases Se

cond

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ensi

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lutio

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olar

ity s

epar

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First dimension elution (e.g. boiling point separation)

1D vs 2D Separations with TAG EPA Standard Method 8270

2 5 0

2 0 0

1 5 0

1 0 0

5 0

0

2 6 0 2 8 0 3 0 0 3 2 0

x 1 0 6

1D 1 5 0

1 0 0

5 0

2 6 0 2 8 0 3 0 0 3 2

0

0

Separation of Diesel Fuel Using 2D-TAG VS 1D-TAG (note compound class structures)

di-aromatics

mono-aromatics

alkanes

20.00 25.00 30.00 35.00 40.00 45.00 50.00 55.00 0

2000

4000

6000

8000

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12000

14000

16000

18000

20000

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Polarity

2D-TAG-FID Berkeley Air

90 minute sample

12:00

Boiling Point

Polarity

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Polarity

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Polarity

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Boiling Point

Polarity

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Boiling Point

Polarity

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Boiling Point

Polarity

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Boiling Point

Polarity

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Boiling Point

Polarity

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Summary • 2D TAG-FID is now operational • Optimizing chromatography • Building 2D-TAG with TOF-MS (DOE STTR) • 2nd dimension aids identification and quantification • Goal – hourly quantitative timelines for extensive

range of marker compounds in ambient aerosols • Data analysis presents many challenges and also

opportunities to consider classes of compounds