office of research and development 6 october 2008 updates to the treatment of secondary organic...

6 October 2008Office of Research and Development

Updates to the Treatment of Secondary Organic Aerosol in CMAQv4.7

Sergey L. Napelenok, Annmarie G. Carlton, Prakash V. Bhave, Golam Sarwar, George Pouliot, Robert W. Pinder, Edward O. Edney, Marc Houyoux, Kristen M. Foley

U.S. Environmental Protection AgencyResearch Triangle Park, NC

7th Annual CMAS ConferenceChapel Hill, NC

2

Office of Research and Development

Covered Topics

• Previous SOA module (CMAQv4.6)

• Updated SOA module (CMAQv4.7)

• Additions/Enhancements– New precursors– SOA from aromatics under low-NOx conditions– Acid catalyzed SOA– Oligomerization of semi-volatile material– SOA from in-cloud oxidation– Parameterization changes

• Preliminary Results

3


Previous Modeled Reactive Organic Gases and SOA (CMAQv4.6)

Sources

Anthropogenic:

Alkanes

Xylene

Cresol

Toluene

Biogenic:

Monoterpenes

5 Precursors

Products

Aitken Mode ASOA (AORGAI)

Accumulation Mode ASOA (AORGAJ)

Aitken Mode BSOA (AORGBI)

Accumulation Mode BSOA (AORGBJ)

4 SOA Species

4


Current Reactive Organic Gases and SOA (CMAQv4.7)

Sources

Anthropogenic:AlkanesXyleneTolueneBenzene

Biogenic:MonoterpenesIsopreneSesquiterpenes

Cloud:Glyoxal/Methylglyoxal

8 Precursors

Products (Accumulation Mode Only)

AALKJAXYL1J, AXYL2J, AXYL3JATOL1J, ATOL2J, ATOL3JABNZ1J, ABNZ2J, ABNZ3J

AOLGAJ

ATRP1J, ATRP2JAISO1J, AISO2J, AISO3JASQTJ

AOLGBJ

AORGCJ

19 SOA Species

low-NOx

high-NOx

acid catalyzed

2-product model

“aged” SOA

cloud produced

unchanged

MEGAN emission factors in BEIS 3.14

density update

5


NOx Dependence

• Under low-NOx conditions, aromatic peroxy radicals preferentially react with HO2 (and not NO)

• The resulting SOA formed from these reactions is considered non-volatile• For example, benzene:

• The pathway determines the type of SOA formed– ΔBENZENENO partitions according to the 2-product Odum model– ΔBENZENEHO2 becomes non-volatile SOA

• Parameterization was adapted from Ng et al. (2007)• Implemented for SAPRC99 and CB05• Changes to emissions processing are required to produce “delumped” benzene

emissions

2

222

2

2

HO

k

NOk

OHk

BENZENEHOBENZRO

BENZENENOBENZRO

productsotherBENZROOHBENZENE

HO

NO

OH

6


Acid Catalyzed Reactions

• Under acidic conditions, SOA production from isoprene is enhanced • CMAQ parameterization is based on a series of chamber experiments

where the acidity of the seed aerosol was controlled (Surratt et al., 2007)• Acidity enhancement is approximated by

normalizing the empirical relationship:

• The hydrogen ion concentration is computed from a charge balance and limited by the range of the experimental conditions [ 0.0, 530.0 ] nmol/m3

HSOCSOC isopisop 733.10

0389.010

7


Condensed-Phase Reactions

• Semi-volatile SOA is converted to low-volatility products through polymerization processes

• Kalberer et al. (2004) estimated that after 20 hours of aging, 50% of organic particle mass consists of polymers

• CMAQ semi-volatile species are “aged” by transferring the mass into two separate non-volatile species:

– Anthropogenic Oligomers from alkanes, xylene, toluene, and benzene

– Biogenic Oligomers from monoterpenes, isoprene, sesquiterpenes• The SOA/SOC ratio for these products was set at 2.1 according to Turpin

& Lim (2001) for non-urban areas

8


Cloud-Produced SOA

• Most air quality models predict lower OC concentrations aloft than are suggested by measurements

• Models also predict less spatial and temporal variability • CMAQ implementation:

– Glyoxal and Methylglyoxal as precursors, based on Carlton et al. (2007) and Altieri et al. (2008)

)()( // aqk

g MGLYGLYMGLYGLY H

productsotherSOAcloudOHMGLYGLY aqaq )()(/

• Yield is estimated to be 4% based on laboratory data• OM/OC = 2.0• Cloud-produced SOA is considered non-volatile

9


Parameterization Changes - ΔHvap

• Enthalpy of vaporization has a role in the dependence of the partitioning coefficient, Kom, on temperature:

• Previously, 156kJ/mol was used for all SOA species in CMAQ • Values that appear in literature and are used in other models range from

15-88 kJ/mol, depending on the compound.• The old CMAQ value was too large and was partly to blame for

exaggerated night-time and wintertime SOA peaks

ref

ivap

refrefiomiom TTR

H

T

TTKTK

11exp ,

,,

10


Impact of New ΔHvapValues

CompoundEthalpy of

vaporization (kJ/mol)*

SV ALK 40

SV XYL 32

SV TOL 18

SV BNZ 18

SV TRP 40

SV ISO 40

SV SQT 40 *based on lab measurements (Offenberg et al., 2006)

11


Interpreting SOA Results – OM/OC ratios

• Model calculates total organic mass• OM/OC ratios are necessary for comparisons with measurements

CMAQv4.7 OM/OC

AALK 1.56

AXYL, ATOL, ABNZ 2.0

AISO1 & AISO2 1.6

AISO3 2.7

ATRP 1.4

ASQT 2.1

AORGC 2.0

AOLGA 2.1

AOLGB 2.1

AORGPA 1.0

CMAQv4.6 OM/OC

AORGA 1.67

AORGB 1.47

AORGPA 1.2

12


Preliminary Module Evaluation

• Seasonal comparisons over eastern United States

– January and August 2006

– More reasonably predicted higher concentrations in the summer (previously winter was higher)

• Model configuration:

– 12km resolution

– CMAQv4.6 “increment” with previous and new SOA treatment

– CB05 chemistry (EBI solver)

– “yamo” advection

– “acm2” diffusion

– “acm” clouds

13


Anthropogenic SOA (monthly average, μg/m3)

Change to enthalpy of vaporization

SOA model updates

August 2006January 2006

14


Biogenic SOA (monthly average, μg/m3)

Change to enthalpy of vaporization

SOA model updates

August 2006January 2006

15


Preliminary Module Evaluation (Part 2)

• Carbon Tracer comparison at a site in RTP, NC

– Four 48 hour measurements during August/September 2003

– Speciated biogenic SOA (isoprene, monoterpene, sesquiterpene) and aromatics

– Improvement over the old model is evident, but concentrations are still much lower than indicated by tracer measurements

– Uncertainty in the tracer measurements: can laboratory measured tracer/SOC ratios be applied to atmospheric conditions?

16


Comparison to Carbon Tracer Measurements – RTP 2003

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Summary

• Major changes to CMAQ SOA module– New precursors– New processes– Updated parameters– Only moderate CPU time requirement increase – 17%

• Preliminary evaluation suggests several improvements– Better seasonal trends– Better diurnal trends– Better science!

• Total OC mass did not increase much– TRP SOA is lower due to lower ΔHvap offsetting gains from new precursors– Intercontinental transport (boundary conditions) of longer-lived species?– Role of intermediate VOCs?

18


Current and Future Plans

• Continue SOA Module Evaluation

– RTP tracer data comparison

– LADCO data set analysis

– Sensitivity Analysis• Parameterization Updates

– Yields, Hvap, non-volatile rates, etc.

• Rosenbrock solver for aqueous chemistry • More sophisticated oligomerization treatment• Further investigation in current and possible new precursors

19


Contact: [email protected]

you are here!

20


BONUS SLIDES

21


Model CPU Time is Important! 17% increase

22


23


Results in Context with Other Work – Morris et al., 2006

• Identified several missing pathways for SOA formation in AQ models

• Implemented three of these into CMAQ v4.4:

– Polymerization • Based on Kalberer et al. (2004)

– Production from sesquiterpenes• Emissions split from BEIS3

TERP• SOA is nonvolatile

– Production from isoprene• New volatile species

24


Results in Context with Other Work – Henze et al., 2008

• Developed a mechanism to model competition between low and high-yield pathways of SOA formation from aromatics

– Toluene– Xylene– Benzene (new)

• CMAQv4.7 aromatic SOA parameters are based on this work

• Found benzene to be the most important aromatic species for SOA formation

• CMAQv4.7 ΔHvap values are lower than what was used here (42 kJ/mol)

25


Overview of the Underlying SOA Module

• Absorptive Partitioning Theory as adapted by Schell et al. (2001)• Generally:

• Some products, Ci,j, are condensable and contribute to SOA production:

• Stoichiometric yield coefficients, , are obtained from smog-chamber studies

nNOnNONONO

nOnOOO

nOHnOHOHOH

CCNOROG

CCOROG

CCOHROG

,,1,1,3

,,1,1,3

,,1,1,

3333

3333

...

...

...

ROGC iitot ,

26


Overview of the Underlying SOA Module (continued)

• Partitioning between gas and particle phase is based on saturation concentration,

• Considering a mixture of condensable compounds (Raoult’s Law), particle phase concentration of each can by calculated by:

– Important parameters:• Stoichiometric yield coefficients:• Saturation concentrations: (also T and ΔHvap)• Molecular weights:

*,isatC

*,isatC

n

j jjaerPOAPOA

iiaerisatitotiaer

MWCMWC

MWCCCC

1 ,

,*,,,

iMW

i

27


Seasonal Pattern Improves (SOAb)A

ug

ust

200

6Ja

nu

ary

2006

AERO5 AERO4 New - Old

28


Evaluation of TC results atDuke Forest (August 2006)

Monthly-averaged TC concentrations from SOA Increment are slightly lower than previous simulations.

Neither model version captures the peak on 25-Aug.

However, the SOA Increment exhibits several improvements relative to previous simulations:• lower coefficient of variation• lower daily amplitude

ObservationsPrevious Incr.SOA updates

Obs Previous SOA Incr. update

--------------------------------Total Carbon mean 4.039 2.654 2.292 stdev 1.614 1.650 1.176 CoV 0.400 0.622 0.513Daily amplitude [ug/m3] median 2.610 3.707 2.853 min 0.740 2.144 1.373 max 5.820 6.223 5.318--------------------------------# paired hours: 246# days with complete data: 25

29


Altieri, K.E., S.P. Seitzinger, A.G. Carlton, B.J. Turpin, G.C. Klein, A.G. Marshall, Oligomers formed through in-cloud methylglyoxal reactions: Chemical composition, properties, and mechanisms investigated by ultra-high resolution FT-ICR mass spectrometry, Atmos. Environ., 42, 1476-1490, 2008

Carlton, A.G., B.J. Turpin, K.E. Altieri, A. Reff, S. Seitzinger, H.J. Lim, and B. Ervens, Atmospheric Oxalic Acid and SOA Production from Glyoxal: Results of Aqueous Photooxidation Experiments, Atmos. Environ., 41, 7588-7602, 2007.

Henze, D.K., J.H. Seinfeld, N.L. Ng, J.H. Kroll, T.-M. Fu, D.J. Jacob, C.L. Heald, Global modeling of secondary organic aerosol formation from aromatic hydrocarbons: high- vs. low-yield pathways, Atmos. Chem. Phys., 8, 2405-2420, 2008.

Kalberer, M., D. Paulsen, M. Sax, M. Steinbacher, J. Dommen, A.S.H. Prevot, R. Fisseha, E. Weingartner, V. Frankevich, R. Zenobi, U. Baltensperger, Identification of polymers as major components of atmospheric organic aerosols, Science, 303, 1659-1662, 2004.

Morris, R.E., B. Koo, A. Guenther, G. Yarwood, D. McNally, T.W. Tesche, G. Tonnesen, J. Boylan, P. Brewer, Atmos. Environ., 40, 4960-4972, 2006.

Ng, N. L., J. H. Kroll, A. W. H. Chan, P. S. Chhabra, R. C. Flagan, and J. H. Seinfeld, Secondary organic aerosol formation from m-xylene, toluene, and benzene, Atmos. Chem. Phys., 7, 3909-3922, 2007.

Schell, B., I. J. Ackermann, H. Hass, F. S. Binkowski, and A. Abel, Modeling the formation of secondary organic aerosol within a comprehensive air quality modeling system, J. Geophys. Res., Vol 106, No D22, 28275-28293, 2001.

Surratt, J.D., M. Lewandowski, J.H. Offenberg, M. Jaoui, T.E. Kleindienst, E.O. Edney, J.H. Seinfeld, Effect of acidity on secondary organic aerosol formation from isoprene, Environ. Sci. Technol., 41, 5363-5369, 2007.

Turpin, B. J. and H.-J. Lim, Species contributions to PM2.5 mass concentrations: revisiting common assumptions for estimating organic mass, Aero. Sci. Technol., Vol 35, 602-610, 2001.

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