Kenneth S. Docherty, Ph.D.
Postdoctoral Research Associate
Cooperative Institute for Research in Environmental Science
University of Colorado, UCB 216
CIRES Bldg., Room 318
Boulder, CO 80309-0216
kenneth.docherty(at)colorado.edu
Ph.D., Environmental Toxicology (2004)
University of California, Riverside,
California
B.S., Biology (1997)
University
of New Mexico, Albuquerque, New Mexico
A variety of techniques are utilized in order to study these reactions. Central to my research is the use of thermal desorption particle beam mass spectrometry (TDPBMS), a newly developed technique allowing real-time analysis of particle chemical composition. The TDPBMS is interfaced to a 7000 liter environmental smog chamber that is used to conduct the gas-phase monoterpene ozonolysis reactions. Size distribution information of resulting aerosol is also monitored using a scanning mobility particle sizer (SMPS).
My research also emphasizes the development of novel instruments and techniques to study SOA chemistry. For instance, I have developed and successfully tested a variable residence time laminar flow reactor (LFTR) in order to study stable monodisperse aerosol distributions at very small particle sizes (< 100 nm). Using this instrument, the production of stable distributions with mean diameters as small as 40 nm has been achieved. The goal of this instrument will be to try and identify those chemical species directly causing nucleation in these systems, which will allow future ambient quantitation studies in order to more accurately determine the contribution of monoterpene ozonolysis to atmospheric SOA burdens.
I have also developed, evaluated, and used novel techniques in order to qualitatively and quantitatively analyze SOA components by gas chromatography (GC). In analyzing SOA composition, GC techniques are limited by potential artifacts, such as analyte-matrix interactions and decomposition of labile compounds, which require the use of intensive pre-column derivatization procedures as a result. The techniques that have been developed during my graduate research have focused on allowing faster and more accurate analysis of various SOA components by this widely available analytical technique.
