5.2 New Approaches for SOA Modeling Based on Recent Experimental Results (Invited Presentation)

Thursday, 14 January 2016: 1:45 PM
Room 356 ( New Orleans Ernest N. Morial Convention Center)
Manishkumar Shrivastava, PNNL, Richland, WA; and A. Zelenyuk, R. C. Easter, J. D. Fast, C. Zhao, Y. Qian, P. Rasch, and S. Ghan

For the past two decades models have represented secondary organic aerosol (SOA) particles as rapidly mixing, low viscosity liquid-like solutions. In the past 5 years, several ground-breaking measurements have shown that under many atmospherically relevant conditions, these particles have much higher viscosities and exhibit orders of magnitude slower evaporation rates than previously assumed. In addition, these measurements point to the importance of particle-phase processes (e.g., oligomerization reactions) on SOA properties (e.g., volatility and viscosity) and loadings. Here we present new approaches to SOA modeling that combine insights from recent measurements and demonstrates large changes in predicted SOA compared to traditional modeling approaches. The extremely low effective volatility of SOA produces large increases in global SOA loadings and lifetimes in the atmosphere. In addition, while it has been established that a large source of semi-volatile/intermediate volatility precursor gases needs to be included in atmospheric models, multigenerational aging parameterizations have largely neglected fragmentation reactions. We show that fragmentation is a large potential sink of SOA precursors in the atmosphere, and is necessary for obtaining realistic SOA loadings when SOA precursor emissions are high (e.g. for biomass burning sources). We show that model predictions with the new approaches better agree with a suite of surface-based, aircraft, and satellite measurements. Compared to previous global modeling results, the new SOA treatment also significantly increases simulated direct radiative forcing. Using a regional model and case studies from a DOE field campaign, we use uncertainty quantification techniques to highlight the large sensitivity of SOA loadings to the particle-phase transformation of SOA volatility, which is neglected in most previous models.
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