I'm interested in developing a process-based approach to understanding air quality and climate change. My research has so far investigated a loss process for tropospheric ozone, dry deposition, as well as remote variability in an atmospheric oxidant, the hydroxyl radical.
Ozone dry deposition
Recent work by one of my advisor's past students, Olivia Clifton (now a post-doc at NCAR), highlighted strong interannual variability in ozone dry deposition at a mid-latitude forest, but most global chemical transport models assume a constant annual profile for this process. Using the AM3 chemistry-climate model, my work illustrates that accounting for variability in this sink shows may necessary to accurately attribute ozone abundances and production chemistry during the summer in the Southeast United States, a region with robust overestimates in simulated summertime surface ozone across models (manuscript in preparation).
(Anticipating) remote variability in the hydroxyl radical
The hydroxyl radical (OH) is often described as the 'detergent' of the atmosphere because it's an extremely reactive oxidant with a lifetime of less than a second. This short lifetime precludes the development of a space- and time-varying measurement network, but understanding OH variability is necessary for a wide array of chemistry and climate modeling objectives. I'm applying measurements from the Atmospheric Tomography (ATom) aircraft campaign, which sampled the remote atmosphere once in each season, to better understand how OH varies in space and time. Ultimately I aim to delineate the extent to which two potential proxies, formaldehyde (proposed by L. Valin) and a convolution of OH driving variables (Murray, et al., 2014; Wang & Jacob, 1998), might offer insight into OH variability from remote sensing observations.