C59-12a: Integrating Light Scattering, Fluorescence, and Holography with Machine Learning toward Coarse and Biological Aerosol Characterization

Coarse mode aerosols have significant effects on aerosol-radiation interactions and the formation of warm and ice clouds. Common coarse mode aerosols—dust, sea salt, and bioaerosols—participate in important atmospheric processes such as cloud condensation nuclei (CCN) formation and ice nucleation, and they are often released from surface sources, making measurements close to the ground especially important, though they can be transported considerable distances if lofted sufficiently high. However, measurements of coarse mode atmospheric aerosols are challenging due to instrument limitations, lack of observations, and the complex processes involved in their generation and throughout their lifetime. This project will develop the Coarse Aerosol Detection System (CADS) consisting of a combination of three different optical techniques for aerosol characterization: (1) Angularly Resolved Elastic Scattering (ARES), (2) Digital In-Line Holography (DIH), and (3) Fluorescence Spectroscopy (FS), all integrated with a Machine Learning (ML) platform for particle classification. The three techniques complement each other well toward comprehensive aerosol characterization, allowing one of the broadest optical sizing capabilities available with aerosol sizing conservatively between ~0.5 to ~50 microns. The ensemble of CADS measurements will provide particle size, type, optical properties, and composition, including DIH images of particles. Phase I will demonstrate the feasibility of the three optical techniques for individual coarse and biological particle characterization: Angularly Resolved Elastic Scattering (ARES), Digital In-Line Holography (DIH), and Fluorescence Spectroscopy (FS). To assure that these three subsystems interrogate the same particles, aerosol sampling and data-trigger mechanisms will be perfected. Finally, a Machine Learning (ML) platform will be developed to provide data analysis and aerosol classification. The Coarse Aerosol Detection System (CADS) will merge three aerosol characterization techniques to provide a first-of-its-kind aerosol-characterization system that can monitor aerosols across one of the widest size-spectra on the market. CADS will have the capability to monitor particulate matter (PM) conservatively across the size range of ~0.5 to ~50 µm, which typically would require two or more instruments, such as a Scanning Mobility Particle Sizer (SMPS) and an Aerodynamic Particle Sizer (APS), as well as additional instrumentation to yield optical properties and composition of such particles. CADS will be portable and capable of detecting aerosol in situ while classifying in real-time.