Reconciling Organic Aerosol Volatility, Hygroscopicity, and Oxidation State During the Colorado DISCOVER-AQ Deployment

Tuesday, 16 December 2014
James Ricky Hite1, Richard Moore2, Robert Martin2, Kenneth Lee Thornhill II3, Edward Winstead3, Bruce E Anderson2 and Athanasios Nenes1, (1)Georgia Institute of Technology, Atlanta, GA, United States, (2)NASA Langley Research Center, Hampton, VA, United States, (3)Science Systems and Applications, Inc. Hampton, Hampton, VA, United States
The organic fraction of submicron aerosol can profoundly impact radiative forcing on climate directly, through enhancement of extinction, or indirectly through modulation of cloud formation. Semi-volatile constituents of organic ambient aerosol are of particular interest as their partitioning between the vapor and aerosol phases is not well constrained by current atmospheric models and appears to play an important role in the formation of cloud condensation nuclei (CCN) as suggested by recent research.

An experimental setup consisting of a DMT CCN counter and SMPS downstream of a custom-built thermodenuder assembly was deployed during the summer 2014 DISCOVER-AQ field campaign to retrieve simultaneous, size-resolved volatility and hygroscopicity – through the use of scanning mobility CCN analysis (SMCA). Housed in the NASA Langley mobile laboratory, a suite of complimentary measurements were made available onboard including submicron aerosol composition and oxidation state provided by an HR-ToF-AMS, and aerosol optical properties provided by a range of other instruments including an SP2.

Air masses sampled from locations across the Central Colorado region include influences from regional aerosol nucleation/growth events, long-range transport of Canadian biomass burning aerosols, cattle feedlot emissions and influences of the Denver urban plume – amidst a backdrop of widespread oil and gas exploration. The analysis focuses on the reconciliation of the retrieved aerosol volatility distributions and corresponding hygroscopicity and oxidation state observations, including the use of AMS factor analysis.