Characterization of Remotely Sensed, Modeled, and In-Situ Derived Ambient Aerosol Properties
AuthorSchlosser, Joseph Simon
sea salt aerosol
supermicrometer aerosol particles
transboundary haze pollution
MetadataShow full item record
PublisherThe University of Arizona.
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
EmbargoRelease after 11/10/2022
AbstractAmbient atmospheric aerosol particles impact human health, visibility, Earth’s radiation balance, and cloud formation. To better constrain the impacts of ambient aerosol particles, weather and climate forecast and reanalysis models require accurate and robust measurements from spaceborne remote sensing platforms. Prior to being utilized on spaceborne platforms, suborbital field campaigns (e.g., aircraft platforms) are being leveraged to design and validate the accuracy of aerosol particle properties that are retrieved from remote sensing instruments. Direct (i.e., in-situ) measurements of intrinsic and extrinsic aerosol particle properties serve as the primary method to validate the remote sensing retrievals and improve the assumptions that are used within weather and climate models. This work utilizes data from three intensive research campaigns to characterize the horizontal and vertical distribution and composition of several important natural and anthropogenic ambient aerosol types. The first study presented in this work utilizes in-situ aerosol concentration and meteorological data gathered from MONterey Aerosol Research Campaign (MONARC), which was carried out in May–June 2019 and featured 14 repeated identical flights off the California coast over the open ocean at the same time each flight day. This study identified four meteorological regimes during MONARC with each corresponding to different characteristic vertical and horizontal distributions of supermicrometer sea salt aerosol number and volume concentration (N>1 and V>1, respectively). Furthermore, machine learning analysis was used to show that the relative predictive strength of various marine boundary layer properties varied depending on predicting N>1 or V>1. Marine boundary layer depth was more highly ranked for predicting N>1 but turbulent kinetic energy was higher for predicting V>1. The second study presented in this work focuses on analyzing the presence and evolution primary and secondary anthropogenic aerosol species in Incheon and Seoul, South Korea. This work examines measurements of size-resolved aerosol composition at a ground site in Incheon along with other aerosol characteristics for contrast between Incheon (coastal) and Seoul (inland), South Korea, during a transboundary pollution event during the early part of an intensive sampling period between 4 and 11 March 2019. Select findings resulting from this analysis are (i) secondarily produced inorganic and organic acids exhibited significant mass concentrations above 0.94 μm during the pollution event and (ii) a high correlation (r = 0.95) between oxalate and sulfate was identified, which a marker of secondary aqueous production of oxalate. The final study presented in this work proposes a simple method to derive verticallyresolved aerosol particle number concentration (Na) using combined polarimetric and lidar remote sensing observations and validates it using collocated in-situ measurements taken in the first two Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) deployments. In this study, the lidar+polarimeter Na was found to agree to within 105% for 90% of the collocated in-situ Na data. This method provides a simple and direct approach to corroborate the results from such complex retrievals, particularly for simpler cases of single or two-layer aerosol systems.
Degree ProgramGraduate College