Analysis of the Organic Content of Marine Aerosols with X-ray Spectroscopy

Abstract:

The ocean is a major global source of aerosols and the seawater from which they are derived is a complex mixture of organic molecules from organisms including phytoplankton, bacteria, and viruses. Marine aerosols consist of any combination of these components and in different mixing states. The mixing state affects absorption and scattering efficiency as well as their ability to uptake water and form ice. Therefore, there is a need to spatially resolve the chemical composition of individual marine aerosols in order to study their potential effects on the climate.

Scanning Transmission X-ray Microscopy coupled with Near Edge X-ray Absorption Fine Structure spectroscopy (SXTM-NEXAFS) gives both spatial resolution as well as the sensitivity to molecular transitions that is necessary to correlate a position on an aerosol with a functional group or inorganic constituent. The morphology, mixing state, and chemical composition from STXM-NEXAFS can be used in conjunction with collocated measurements (light scattering, ice nucleation, etc.) to correlate the spatially resolved chemical composition of aerosols with their physical properties.

The goal of this project is to determine if there is a difference in the organic fraction between particles with clearly different morphology and mixing states. Three major classes of marine aerosols have been classified as sea salt, marine gels, and cell fragments. Sea salt is classified by having an inorganic core consisting of NaCl and a thin layer of organic coating on the outside. Marine gels consist of organic material in the form of lipids, polysaccharides, and proteins distributed throughout the aerosol alongside inorganic compounds, such as Ca²⁺, Mg²⁺, and K⁺, that help to stabilize the negative charge of the organic material. Cell fragments include fragments from phytoplankton and bacteria. Efforts are currently underway to quantitatively evaluate differences in NEXAFS spectra for these particle types using nonlinear least squares.