1. Global Simulation of Secondary Organic Carbon Aerosols Hong Liao California Institute of Technology GEOS-CHEM meeting, April 2005

2. Why is Secondary Organic Aerosol (SOA) Important?  It is the least well-quantified and understood aerosol in the atmosphere;  It may contribute to a large fraction of organic carbon, which in turn constitutes a large fraction of PM 2.5 that causes haze and adverse health effects;  It influences climate directly through light scattering or indirectly by serving as cloud condensation nuclei.

3. SOA Formation

4.  5 reactive biogenic hydrocarbon groups: HC1 =  -pinene,  -pinene, sabinene and terpenoid ketones, 3  carene HC2 = limonene HC3 =  -terpinene,  -terpinene, terpinolene HC4 = myrcene, terpenoid alcohols, ocimene HC5 = sesquiterpenes SOA Simulation in GEOS-CHEM  28 organic products from O 3, OH and NO 3 oxidation : 6 (3 gases + 3 aerosols) from each of first four HC groups = 24 4 (2 gases + 2 aerosols) from oxidation of sesquiterpenes = 4  9 tracers: 3 classes of biogenic VOCs: HC1, HC2, and HC4 SOG1 = lump of gas products from HC1, HC2, HC3 oxidation SOG2 = gas product from HC4 oxidation SOG3 = gas product from HC5 oxidation SOA1 = lump of aerosol products from HC1,HC2, and HC3 oxidation SOA2 = aerosol product from HC4 oxidation SOA3 = aerosol product from HC5 oxidation

5.  Concentrations of OH, O 3, and NO 3 from offline fields or online simulation  SOA Thermodynamic Equilibrium SOA Simulation in GEOS-CHEM (cont.)

6.  Wet deposition 80% of SOA dissolves into clouds [Limbeck and Puxbaum, 2000]  Dry deposition Dry deposition of HCs, gas-phase products, and SOAs follows the scheme in GEOS-CHEM.  Emission inventories Emissions of monoterpenes are based on the work of Guenther et al. [1995] and treated as a function of vegetation type, leaf area index, and temperature; Emissions of other reactive VOCs (ORVOCs) are also based on Guenther et al. [1995], but are monthly fields from Global Emissions Inventory Activities (GEIA). Emissions of monoterpenes and ORVOCs are distributed into each HC group following the study of Griffin et al. [1999]. SOA Simulation in GEOS-CHEM (cont.)

7. Predicted SOA Concentrations (ng m -3 ) GEOS-CHEM (online)GEOS-CHEM (offline)Unified Model (online)

8. Predicted Primary Organic Aerosol (POA) Concentrations (ng m -3 ) GEOS-CHEMUnified Model

9. Emission Inventories for POA GEOS-CHEM Unified Model Emission (TgC/yr) Fossil fuel 10.2 28.2 Biofuel 7.5 Biomass burning 22.4 53.0 Total 40.1 81.2 Burden (TgOM) 0.69 1.29

10. OC Concs Simulated in the Unified Model vs. Observations

11. Parent Hydrocarbon Contributions to Global SOA GEOS-CHEM (offline)Unified Model (online) HC1 HC2 HC3 HC4 HC5 52.0% 20.0% 0.7% 78.7% 10.3% 11.0% 10.3% 17.0% SOA Burden (TgOM) 0.16 0.23

12. Conclusions and Suggestions  Compared to the 33-tracer SOA scheme in the unified model, the simplified 9-tracer scheme in GEOS-CHEM predicts well the geographical distribution of SOA.  SOA concentrations predicted in the GEOS-CHEM model are lower than those predicted in the unified model, which can be explained by the differences in predicted POA concentrations.  Further investigation of SOA predicted in the upper troposphere is needed.  The specified emissions of ORVOCs should be replaced by a scheme that is similar to what the GEOS-CHEM has for monoterpenes. Coupling ORVOC emissions with meteorological variables is necessary for studying the effect of climate change on SOA formation.

13. Acknowledgements U.S. EPA STAR grant Bob Yantosca, Harvard University Colette Heald, Harvard University Rokjin Park, Harvard University