Using measurements of ccn activity to characterize the mixing state, chemical composition, and droplet growth kinetics of atmospheric aerosols to constrain the aerosol indirect effect

Atmospheric aerosols are known to exert a significant influence on the Earth's climate system; however, the magnitude of this influence is highly uncertain because of the complex interaction between aerosols and water vapor to form clouds. Toward reducing this uncertainty, this dissertation outlines a series of laboratory and in-situ field measurements, instrument technique development, and model simulations designed to characterize the ability of aerosols to act as cloud condensation nuclei (CCN) and form cloud droplets. Specifically, we empirically quantify the mixing state and thermodynamic properties of organic aerosols (e.g., hygroscopicity and droplet condensational uptake coefficient) measured in situ in polluted and non-polluted environments including Alaska, California, and Georgia. It is shown that organic aerosols comprise a substantial portion of the aerosol mass and are often water soluble. CCN measurements are compared to predictions from theory in order to determine the error associated with simplified composition and mixing state assumptions employed by current large-scale models, and these errors are used to constrain the uncertainty of global and regional cloud droplet number and albedo using a recently-developed cloud droplet parameterization adjoint model coupled with the NASA GMI chemical transport model. Quantifying the sensitivities of these cloud parameters to aerosol number is important because cloud droplet number and albedo are the main determinants of climate forcing.;We also present two novel techniques for fast measurements of CCN concentrations with high size, supersaturation, and temporal resolution that substantially improve the state of the art by several orders of magnitude. The first, called Scanning Flow CCN Analysis (SFCA) allows measurement of CCN supersaturation spectra (i.e., CCN concentrations over a range of supersaturations) in as little as 10-15 seconds (versus 30-60 minutes for the conventional technique). SFCA has been successfully deployed in a ground-based study in Atlanta during 2009 and in an airborne study in California during 2010, both with good success. In addition, we present Scanning Mobility CCN Analysis (SMCA) as a new technique for measuring size-resolved CCN concentrations and droplet growth kinetics by coupling a TSI Scanning Mobility Particle Sizer (SMPS) to a Droplet Measurement Technologies CCN counter. By applying the same inversion algorithm to the CCN data as used for the SMPS, size-resolved CCN distributions can be obtained concurrently with particle size distributions over the timescale of a typical SMPS scan (typically 60-120 seconds). Fast measurement techniques such as SFCA and SMCA are particularly important for airborne studies, where the aircraft may sample particles and pollution plumes over several kilometers in only a few tens of seconds.;The techniques developed in this dissertation provide the means to comprehensively characterize the aerosol-water interactions relevant for constraining the indirect effects of aerosols on climate; however, the current global dataset of CCN observations remains limited mostly to continental regions in the Northern Hemisphere, where we show that cloud properties are relatively insensitive to changes in the CCN-active aerosol number. In directing future field studies focusing on CCN, the results of this dissertation suggest that these efforts should be directed toward the pristine regions in the Alaska-Canadian Arctic and southern oceans, where cloud properties (i.e., droplet number and albedo) are most sensitive to small perturbations in aerosol number. Ultimately, this work represents a step toward better understanding how atmospheric aerosols influence cloud properties and Earth's climate.