The feedbacks among aerosols, clouds, and radiation are important components for understanding Earth's climate system and quantifying human-induced climate change, yet the magnitude of these feedbacks remain highly uncertain. Since every cloud droplet in the atmosphere begins with water condensing on a pre-existing aerosol particle, characterizing the ability of aerosols to uptake water vapor and form cloud condensation nuclei (CCN) are key to understanding the microphysics behind cloud formation, as well as assess the impact aerosols have on the Earth system. Through a combination of controlled laboratory experiments and field measurements, this thesis characterizes the ability of atmospheric aerosols to uptake water vapor and become CCN at controlled levels of water vapor supersaturation. The origin of the particle water uptake, termed hygroscopicity, is also explored, being from either the presence of deliquescent soluble material and/or adsorption onto insoluble surfaces. The data collected and presented is comprehensive and includes (1) ground samples of volcanic ash, collected from six recent eruptions re-suspended in the laboratory for analysis, (2) laboratory chamber and flow-tube studies on the oxidation and uptake of surface active organic compounds, and (3) in-situ aircraft measurements of aerosols from the Arctic background, Canadian boreal forests, fresh and aged biomass burning, anthropogenic industrial pollution, and from within tropical cyclones in the Atlantic basin. Having a more thorough understanding of aerosol water uptake will enable more accurate representation of cloud droplet number concentrations in global models, which can have important implications on reducing the uncertainty of aerosol-cloud-climate interactions, as well as additional uncertainties in aerosol transport, atmospheric lifetime, and impact on storm dynamics.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/50112 |
| Date | 18 October 2012 |
| Creators | Lathem, Terry Lee |
| Contributors | Nenes, Athanasios |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
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