Deciphering the origins and transformations of atmospheric ... · SOA fractions agree for TAG and...
Transcript of Deciphering the origins and transformations of atmospheric ... · SOA fractions agree for TAG and...
Deciphering the origins and transformations of atmospheric organics:
CalNex2010 Bakersfield
A. Goldstein, D. Gentner, G. Isaacman, D. Worton,
Y. Zhao, R. Weber, R. Sellon, A. Guha (UC Berkeley)
N. Kreisberg, S. Hering (Aerosol Dynamics Inc.)
B. Williams (Washington University, St. Louis)
T. Hohaus, A. Lambe, J. Jayne, L. Williams,
D. Worsnop (Aerodyne Research Inc)
J-L. Jimenez (University of Colorado)
L. Russell, S. Liu, D. Day (UC San Diego)
CalNex Bakersfield Science Team
CalNex Pasadena Science Team
SPECIAL THANKS TO:
John Karlik, Rick Ramirez
UC Cooperative Extension Kern County Staff
R. Cohen, S. Pusede UC Berkeley (PI and site organization)
Funding: Contracts #08-316 and #09-316
Bakersfield
Fig from R. Cohen
PM2.5 Nonattainment Areas in U.S.
Worst Cities (PM2.5)
1) Bakersfield, CA
2) Fresno, CA
3) Hanford, CA
4) Los Angeles, CA
5) Modesto, CA
6) Pittsburgh, PA
7) Salt Lake City, UT
8) Logan, UT
9) Fairbanks, AK
10) Merced, CA
U.S. EPA & American Lung Assoc. (2012)
Ozone Nonattainment Areas in U.S. Worst Cities (O3)
1) Los Angeles, CA
2) Visalia, CA
3) Bakersfield, CA
4) Fresno, CA
5) Hanford, CA
6) Sacramento, CA
7) San Diego, CA
8) Houston, TX
9) San Luis
Obispo, CA
10) Merced, CA
U.S. EPA & American Lung Assoc. (2012)
1980 1985 1990 1995 2000 2005 20100
50
100
150
200
250
Year
Days E
xceedin
g U
S 8
hr
O3 S
tandard
South Coast (LA)
San Joaquin Valley
SF Bay Area
Air Quality Control Has Been More Effective
in LA than San Joaquin Valley D
ays
Exc
eed
ing
US
8-h
r O
3 S
tan
dar
d
Year
Data from www.arb.ca.gov
CalNex2010 was designed to investigate why.
Differences in ozone and particle precursors?
Differences in chemistry?
NOx 2010 CARB Emission Inventory
Anthropogenic Emission Projections (%) (Bakersfield is in Kern County)
Kern County Los Angeles County
DIESEL TRUCKS, 50
OFF-ROAD EQUIPMENT,
12
MINING- CEMENT
MANUFACT., 8
PASSENGER CARS, 5
OIL & GAS PRODUCTION,
5
TRAINS, 5
OTHER, 16
DIESEL TRUCKS, 25
OFF-ROAD EQUIPMENT, 22
PASSENGER CARS, 17
TRAINS, 2
SHIPS AND COMMERCIAL
BOATS, 12
OTHER, 21
Data from www.arb.ca.gov
OIL AND GAS PRODUCTION,
34
PASSENGER CARS, 9 DIESEL
TRUCKS, 7
PESTICIDES, 7
CONSUMER PRODUCTS, 5
LIVESTOCK, 4
OFF-ROAD EQUIPMENT, 4
OTHER, 30
PASSENGER CARS, 25
DIESEL TRUCKS, 3
CONSUMER PRODUCTS, 19
OFF-ROAD EQUIPMENT,
12
OTHER, 42
Reactive Organic Gas (ROG)
2010 CARB Emission Inventory
Anthropogenic Emission Projections (%)
EXTREMELY DIFFERENT
Kern County Los Angeles County
Data from www.arb.ca.gov
Organic Aerosol
Global Scale
OVOC
Oxidation
by OH, O3, NO3
Direct
Emission
Terpenes
Nucleation or Condensation
Hydrocarbons
OC
Isoprene
Cloud
Processing
FF: ~5 TgC/yr
BB: ~11 TgC/yr
SOA: ~140 TgC/yr
Fossil Fuel Biomass
Burning
Heterogeneous Reactions
Oligomerization
Hallquist et al 2009
(Goldstein & Galbally 2007
Hallquist et al 2009
Heald et al 2010 )
MOSTLY SOA
DIESEL TRUCKS, 12
CEMENT MANUFACT, 8
FARM DUST, 7
RES. FUEL COMBUSTION, 7
WIND DUST, 6
ROAD DUST, 11
PASSENGER CARS, 2
OTHER, 46
Primary PM2.5
2010 CARB Emission Inventory
Anthropogenic Emission Projections (%)
Kern County Los Angeles County
Data from www.arb.ca.gov
Primary versus Secondary PM
SOAR 2005 Aerosol in Riverside:
Organic is dominant component of submicron aerosol.
Organic aerosol is ~70% secondary in summer. (Williams et al., 2010 ACP; Docherty et al, 2008 ES&T)
Questions for CalNex 2010 Bakersfield and LA:
Primary versus secondary PM?
Sources of Primary and Secondary Precursors?
Current Major Issues & Questions • Why are models under-predicting organic aerosol
(missing precursors or formation pathways)? [Hodzic et al. ACP (2010), de Gouw et al. JGR (2008), Dzepina et al. (2011)]
• Importance of diesel vs. gasoline vehicles in urban
areas (hotly debated issue)? [Bahreini et al. GRL (2012), Robinson et al. Science (2007), Weitkamp et al.
ES&T (2008)]
• Importance of non-traditional SOA precursors that
have not been measured (e.g. intermediate volatility
organic compounds)? [Robinson et al. Science (2007), Kroll & Seinfeld Atmos. Env. (2008), Jimenez et
al. Science (2009)]
How do we measure and model (represent) emission,
oxidation and fate of 1000’s of individual compounds?
Key Challenge: Atmospheric Organics
Williams et al 2006
TAG Aerosol Gas Chromatogram
“Unresolved Complex Mixture” (UCM)
50-80% of mass (e.g. Diesel) Schauer et al 1999
UCM
characterization
must be
improved
Tkacik et al (Robinson group) 2012
SOA production from diesel exhaust
Field Measurements of Organic Carbon Urban (Bakersfield & LA) and on-road tunnel measurements
Gasoline and Diesel fuel samples (52 across CA)
In-Situ GCMS C1-C17 VOCs
In-Situ TAG speciated PM2.5 organics & I/SVOCs
Offline Filter Analysis using novel techniques
(GCxGC-VUV-HRTOFMS)
Caldecott Tunnel, Oakland, CA Bakersfield, CA
Speciated Organics Observed Spans 15 orders of Magnitude in Volatility!
Gentner et al
Robinson et al 2007
TAG
Focus on quantifying “inferred” IVOCs/SVOCs
Robinson et al 2007
(flipped to match GC)
TAG
Gentner et al
Gas
Chromatograph
Mass
Spectrometer
Aerosol Collector
&
Thermal
Desorption Cell
Cyclone Precut
(PM2.5)
Filter
x
Valveless
injector
Den
ud
er
TAG
= Thermal desorption Aerosol Gas chromatograph
Hourly In Situ Measurements
Speciated Organics in Aerosols
Williams et al AS&T 2006, Goldstein et al J Chrom A 2009, Zhao et al AS&T 2013
CalNex Bakersfield:160 compounds
measured hourly by TAG
Semi-volatile organic
compounds
0.5
0.4
0.3
0.2
0.1
0.0
O:C
Rati
o
10-13 10
-11 10-9 10
-7 10-5 10
-3
Subcooled Vapor Pressure (atm, 25C)
Alkanes PAHs and Branched PAHs Hopanes Alkyl-cyclohexanes Lactones Esters Acids Carbonyls Others
Zhao et al ES&T In Press
Semi-volatile organic
compounds
0.5
0.4
0.3
0.2
0.1
0.0
O:C
Rat
io
10-13 10
-11 10-9 10
-7 10-5 10
-3
Subcooled Vapor Pressure (atm, 25ºC)
Alkanes PAHs and Branched PAHs Hopanes Alkyl-cyclohexanes Lactones Esters Acids Carbonyls Others Phthalic acid Pinonaldehyde 6, 10, 14-Trimethylpentadecanone
Examine Partitioning of Typical
Compounds
Zhao et al ES&T In Press
Are additional gas-to-particle partitioning
pathways important
beyond traditional partitioning theory?
Pankow, 1994; Jang et al., 2002; Tillmann et al., 2010
Fraction in particle phase > model prediction
Zhao et al ES&T In Press
Evidence for additional formation pathways:
Fraction in particle higher than model prediction
Pinonaldehyde
1) Chamber studies have shown that
dimers of pinonaldehyde can form in
the presence of sulfuric acid (Liggio
and Li, 2006)
2) Oligomerization increases with
acidity (Liggio and Li, 2006)
Phthalic acid
1) Organic acids can react with
ammonia (Na et al., 2007)
2) Phthalic acid ammonium salts
can be thermally desorbed
back to phthalic acid and
ammonia (Hajek et al.,1971)
Zhao et al ES&T In Press
What else does particle-phase
pinonaldehyde depend on?
Acidity doesn’t
increase as RH
increases
Fraction of
Pinonaldehyde in
particles increases
as RH increases
0.9
0.6
0.3
0.0
Fra
ctio
n i
n t
he
par
ticl
e phas
e
6050403020
RH (%)
1.30
1.25
1.20
1.15Cat
ion-t
o-a
nio
n r
atio
706050403020
RH (%)
Sampling Period I Sampling Period II
Zhao et al
ES&T In Press
Formation of particle-phase phthalic acid
in the atmosphere
Phthalic acid ammonium salts thermally desorb to phthalic acid and ammonia (Hajek et al.,1971)
Some of the particle phase phthalic acid was actually an ammonium salt.
Particle phase uptake of phthalic acid enhanced by availability of ammonia in Bakersfield.
1.0
0.8
0.6
0.4
0.2
Fra
ctio
ns
in t
he
par
ticl
e p
has
e
3530252015
Gas-phase Ammonia (ppbv)
R2=0.8
Zhao et al ES&T In Press
Partitioning
Take Home Messages
Additional pathways of gas-to-particle partitioning are
important beyond absorptive partitioning in SJV:
1) Reactions of phthalic acid with ammonia form
SOA
2) Reactive uptake of pinonaldehyde into particles
does not need the presence of inorganic acids.
Organic Aerosol (OA) PMF to Examine Sources
6 Contributing Factors Identified with TAG
0.18
0.09
0.00
He
xa
de
ca
ne
He
pta
de
ca
ne
Octa
de
ca
ne
No
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de
ca
ne
Eic
osa
ne
He
ne
ico
sa
ne
Prista
ne
Ph
yta
ne
Ph
en
an
thre
ne
Flu
ora
nth
en
eP
yre
ne
No
nylb
en
ze
ne
Dim
eth
yln
ap
hth
ale
ne
Dim
eth
yln
ap
hth
ale
ne
2(3
H)-
Fu
ran
on
e, 5
-bu
tyd
ihyd
ro2
(3H
)-F
ura
no
ne
, 5
-pe
nty
ldih
yd
roD
ibe
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fura
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en
zo
ph
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no
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Xa
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ore
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9.1
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nth
race
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dio
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2-P
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tad
eca
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, 6
, 1
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4-t
rim
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2H
-1-B
en
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pyra
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hyd
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ieth
ylp
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ala
teB
is(2
-me
thylp
rop
yl)p
hth
ala
teD
ibu
tylp
hth
ala
teP
hth
alic
Acid
Me
thylp
hth
alic
acid
0.100.050.000.12
0.06
0.00
0.600.300.00
Con
trib
utio
n t
o F
acto
r (e
ach
fa
cto
r p
rofile
su
ms t
o 1
)
0.200.100.000.30
0.15
0.00
Local POA
A mixture ofOA sources
SOA1
SOA2
SOA3
SOA4(Nighttime SOA)
Zhao et al
in review
OA PMF factor Diurnal Cycles
(Small)
(Morning local)
Primary
Secondary
(Daytime regional)
OA PMF Factor
Wind Roses
(small) (local)
(regional)
ADD MAP HERE
Daytime Wind
Nighttime Wind
(higher wspd,
regional)
Diurnal Cycle of OA Source Contributions
SOA fractions agree for TAG and AMS PMF’s
(a) Daytime SOA
TAG = SOA2 + SOA3
AMS = high O/C aromatic
+ high O/C alkane
+ petroleum SOA
(Liu et al., JGR 2012,
SOA from fossil fuel sources
contributes majority of OA)
(b) Nighttime SOA
TAG = SOA1 + SOA4
AMS = low O/C alkane +
nighttime OA.
TAG shifted right for clarity
Vertical bars = Std Deviation
Organic Aerosol PMF Analysis
Policy Relevant Messages
1) SOA accounts for approximately 75% of OA in
Bakersfield (TAG and AMS PMFs agree)
2) SOA has multiple different sources, with daytime
and nighttime SOA dominated by different primary
precursor sources, chemical transformation, and
partitioning processes.
3) Ammonia emission control could be important for
SOA control in San Joaquin Valley due to
formation of acid-ammonia salts.
Unresolved Complex Mixture
TAG
Need Better Baseline
Separation to Improve
Identification and
Quantification
Instrument Development
to Enhance Exploration
of Atmospheric Organics
Multi-dimensional Gas Chromatography with Vacuum
Ultraviolet Ionization and High Resolution Time of Flight
Mass Spectrometry (GCxGC-VUV-HRTOFMS)
Can Soft Ionization Improve Identifications?
GC-Vacuum Ultraviolet Ionization-MS
Electron Impact Ionization
(70 eV, harder ionization)
Lots of fragment ions
Hard to distinguish organic species
VUV Photoionization
(10.5 eV, softer ionization)
at Advanced Light Source
Very little fragmentation
Easy molecular identification
of organic species
eicosane EI
VUV
VUV
EI
Diesel Fuel Mass Spectrum versus GC retention time
eicosane
VUV
EI
alkanes
cycloalkanes
bicycloalkanes
benzenes
napthalenes
acenapthenes
higher order
PAHs
Diesel Fuel VUV Mass Spectrum versus GC retention time
“Classic Complex Hydrocarbon Mixture”
Former “UCM”
Isaacman et al Anal Chem 2012
Isomers Cleanly Separated
Isaacman et al Anal Chem 2012
alkanes
cycloalkanes bicycloalkanes
benzenes
methyl(B1)
dimethyl(B2)
trimethyl(B3)
tetramethyl(B4) n-alkane(B0) C19H40
Quantitatively Speciated Diesel Fuel
(No More Unresolved Complex Mixture)
Isaacman et al Anal Chem 2012; Gentner et al PNAS 2012
Chemical Speciation of Motor Vehicle Sources
• Diesel fuel fully characterized via
VUV soft ionization
mostly C10-C20, branched and cyclic
former “UCM” SOA yields largely
unstudied
• Gasoline 30% aromatics
mostly C4-C10
• Non-tailpipe gasoline almost all light
alkanes
mostly C4-C8
Gentner et al., PNAS 2012
Motor Vehicles
Precursor Emissions SOA Yields
~50% Aromatic
~99% Aromatic
100% Aromatic
Gentner et al., PNAS 2012
How Much SOA from Gasoline vs. Diesel?
(In the United States Diesel = Large Trucks)
Diesel emission factor ~2x gasoline
×Diesel SOA yield ~7x gasoline
Diesel forms 15x more SOA than
gasoline per liter of fuel burned
Diesel Forms 56-90% of Vehicular SOA
(90% in Bakersfield)
Gentner et al., PNAS 2012
Deciphering a Complex Mixture of Sources
Emissions
Mix of 1000’s of compounds
in the atmosphere Transport
Data!
(on 100’s of
compounds…)
• Profile of compounds emitted from each source is unique
• Source contributions calculated using source profiles and
atmospheric measurements
• Over-constrained source receptor model
Fossil Fuel Source Apportionment
Fossil Fuel Source Apportionment
Bakersfield Reactive Organic Gas (ROG)
Fossil Fuel Sources Receptor Model
• Petroleum associated gas major source of ROG emissions
Contributions to SOA are negligible since it’s comprised of
small hydrocarbons with very low SOA yields
Gentner et al., in prep
Locating Petroleum Gas Emissions
Use concentration data &
meteorological modeling to
locate emissions
Meteorological data is used
to calculate “footprint” (aka
back-trajectory) for each data
time point
Met footprints are weighted
by ground site concentration
data to construct map of
emissions for a region
Average footprint (or area of
influence) for 6 hrs before
transport to Bakersfield site
Average 6 hr Footprint
Location of
Oil/Gas Wells
Statistical Distribution of
Petroleum Gas Source
Gentner et al., in prep
Locating Petroleum Gas Emissions
Locating Dairy Emissions
Methane Non-Vehicular Ethanol
Policy Implications
Fossil Fuel VOC sources • Both gasoline & diesel vehicles are important urban sources
of fossil fuel SOA precursors, but diesel dominates (65-90%),
particularly in Bakersfield (90%)
• Further research on understudied SOA yields is necessary
• Fuel composition and potential SOA formation should be
considered in SOA control policies
• Gasoline dominates over diesel for emissions of organic
precursors to ozone [Gentner et al. ES&T, in review]
• Petroleum operations are a major source of ROG emissions
in Bakersfield (potentially important for ozone, but not SOA)
Gentner et al., PNAS (2012)
Thank you for listening!
No More
UCM
Diesel SOA > Gasoline SOA
Deciphering the
origins and
transformations of
atmospheric organics