1. Implementing Online Marine Organic Aerosol Emissions into GEOS-Chem Implementing Online Marine Organic Aerosol Emissions into GEOS-Chem NASA Ames Research Center 7 th International GEOS-Chem Meeting May 5, 2015 B. Gantt 1, M. S. Johnson 2, M. Crippa 3, A. S. H. Prévôt 3, and N. Meskhidze 1 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

2. 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)

3.  Using GEOS-Chem v8-01-01  Presented at the 6 th 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 )

4. 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 10 ng m -2 s -1  Largest emission rates in high- latitude waters during the respective spring/summer seasons Gantt et al. (2015)

5. GEOS-Chem-predicted Global MOA Concentrations  MOA surface concentrations range from 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)

6. 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

7. 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 10 ng m -2 s -1, with largest values in high-latitude oceans during the summer season Model-predicted MOA concentrations range from 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

8. Additional Slides

9. Gantt et al. (2011) Emission Parameterization Gantt et al. (2011) Atmos. Chem. Phys.

10. Marine Primary Organic Aerosol Emission Rate (E POA ) sea-salt emissions based on Jaeglé et al. (2011) Gantt et al. (2012 ) 10m winds (U 10 ) [chl-a]

11. GEOS-Chem (v9-02) Model  Online sea-salt emissions  Power relationship with 10m winds speeds (Gong 2003) and 3 rd 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

12. 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)