Implementing Online Marine Organic Aerosol Emissions into GEOS-Chem

NASA Ames Research Center 7th International GEOS-Chem Meeting

May 5, 2015

B. Gantt1, M. S. Johnson2, M. Crippa3, A. S. H. Prévôt3, and N. Meskhidze1

Funding: Office of Science (BER), US Department of Energy Grant No. DE-FG0208ER64508, and the NASA Ames Research Center Earth Science Division

1 North Carolina State University

2 NASA Ames Research Center 3 Laboratory of Atmospheric Chemistry, Paul Scherrer Institute

Importance of Marine Organic Aerosols (MOA)

Need for improved climate assessments has led to increased emphasis on understanding emission sources and concentrations of natural aerosols

The majority of the Earth’s surface is covered by oceans Oceanic emissions of sea salt and organic matter, in particulate form, and of sulfur, halogens, and

volatile organic compounds, in gaseous form, affect the formation, number concentration, and composition of atmospheric cloud condensation nuclei (CCN) and ice nuclei (IN)

Rinaldi et al. (2010)

Using GEOS-Chem v8-01-01 Presented at the 6th Annual

GC Meeting

Evaluated 5 different organic sea spray emission schemes against hourly to monthly observations

Global MOA emission rates ranged from 0.1 to 11.9 Tg yr -1

Gantt et al. (2012)

Annual Average Emission Rates

Previous GEOS-Chem MOA Emission Modeling

Gantt et al. (2012)

GEOS-Chem-predicted Global MOA Emissions

Applying top-down emission scheme from Gantt et al. (2012)

Annual submicron MOA emissions of ~9.0 Tg was predicted for 2009 Falls within the range of previously predicted totals of MOA emissions

Emissions range from < 0.1 to > 10 ng m-2 s-1

Largest emission rates in high-latitude waters during the respective spring/summer seasons

Gantt et al. (2015)

GEOS-Chem-predicted Global MOA Concentrations

MOA surface concentrations range from < 0.1 µg m-3 to > 1.0 µg m-3

MOA concentrations are largest over regions of highest emission sources which are correlated with [chl-a] spatial distribution

The fraction of total submicron OA made up by primary MOA are largest (>80%) over marine regions and decreases rapidly over terrestrial regions

Gantt et al. (2015)

Improved Prediction of Global Total Organic Aerosol Concentrations in Clean Marine Regions

With online MOA emissions Without online MOA emissions

GEOS-Chem without MOA emissions tends to under-predict (normalized mean bias -79%) in situ measurements and displays poor correlation (0.16) when compared to observations Model simulations with MOA emissions included in the comparison had substantially lower model bias (normalized mean bias -12%) and improved correlation (0.28)

Gantt et al. (2015)

*Data is considered “clean marine” when [BC] < 50 ng m-3 and upwind fetch over the ocean

Conclusions Online emission parameterization of submicron primary MOA was implemented into the GEOS-Chem

model (v9-02) This model development was designed to be used in the default setting of GEOS-Chem with the following

characteristics: (1) adds minimal computational expense, (2) capable of being used for all GEOS-Chem model domains/simulation periods, and (3) treated with unique tracers for explicit atmospheric aging and tracking

GEOS-Chem predicts an annual submicron MOA total of ~9.0 Tg which is comparable to past predictions Emission rates range from < 0.1 ng m-2 s-1 to > 10 ng m-2 s-1, with largest values in high-latitude oceans

during the summer season Model-predicted MOA concentrations range from < 0.1 µg m-3 to > 1.0 µg m-3 and make up the majority of

total submicron OA over oceanic regions Model results are comparable with existing data sets and have been extensively discussed in scientific

literature; therefore proposed to be implemented in the default code

Please see our publication in Geosci. Model Dev.: http://www.geosci-model-dev.net/8/619/2015/gmd-8-619-2015.pdf

Additional Slides

Gantt et al. (2011) Emission Parameterization

Gantt et al. (2011) Atmos. Chem. Phys.

Marine Primary Organic Aerosol Emission Rate (EPOA)

OMSSA(chl a, U10, Dp) =

11+exp(3(−2.63[chl a])+3(0.18(U10))

1+0.03exp(6.81Dp) + 0.031+exp(3(−2.63[chl a])+3(0.18(U10))

EPOA(chl a, U10, Dp) = 6 ×VSSA×OMSSA×ρSSA

sea-salt emissions based on Jaeglé et al. (2011)

Gantt et al. (2012)

10m winds (U10) [chl-a]

GEOS-Chem (v9-02) Model Online sea-salt emissions

Power relationship with 10m winds speeds (Gong 2003) and 3rd order polynomial dependence on sea surface temperature (Jaeglé et al., 2011) Two bin sizes: fine mode (0.02 to 1.0 µm diameter)

and coarse mode (1.0 to 16.0 µm diameter) Online MOA emission scheme

Top-down emission parameterization developed from Gantt et al. (2012) applying in situ data at Mace Head, Ireland Dependence on: Monthly-averaged Aqua MODIS [chl-a] at 1/12°

which is spatially averaged online GEOS-5 10m wind speeds

2 additional tracers: 1) hydrophobic and 2) hydrophilic which is formed with an e-folding time of 1.15 days (identical to terrestrial OA)

3-D global chemical transport model (v9-02) Developed at Harvard University and other

institutions around the world Full chemistry configuration

SMVGEAR II chemistry solver package w/ SOA formation (Pye et al., 2010)

GEOS-5 meteorology Goddard Earth Observing System (GEOS) of

the NASA Global Modeling Assimilation Office Detailed emission inventories

Fossil fuel, biomass burning, biofuel burning, biogenic and anthropogenic aerosols

State-of-the-art transport (TPCORE) and deposition routines

2⁰ x 2.5⁰ global grid resolution 0.5⁰ x 0.67⁰ nested regional grid resolution 47 vertical grids

GEOS-Chem-predicted Nested MOA Concentrations

Nested-grid simulations (0.5° x 0.67°) for July 2009 demonstrate a sharp concentration gradient over Europe

Data from Paris (Crippa et al., 2013; AMS-derived MOA concentrations) was used to evaluate high-resolution GEOS-Chem simulations

The model demonstrates the ability to capture the temporal pattern and magnitude of observed inland MOA concentrations Correlation of 0.62 Mean bias of -120 ng m-3 Normalized mean bias of -36%

Gantt et al. (2015)