The ability of an atmospheric aerosol particle to impact climate by acting as a cloud condensation nucleus (CCN) or an ice nucleus (IN), as well as scatter and absorb solar radiation is determined by its physicochemical properties at the single particle level, specifically size, morphology, and chemical composition. The identification of the secondary species present in individual aerosol particles is important as aging, which leads to the formation of these species, can modify the climate relevant behavior of particles. Raman microspectroscopy has a great deal of promise for identifying secondary species and their mixing with primary components, as it can provide detailed information on functional groups present, morphology, and internal structure. However, as with many other detailed spectroscopic techniques, manual analysis by Raman microspectroscopy can be slow, limiting single particle statistics and the number of samples that can be analyzed. Herein, the application of computer-controlled Raman (CC-Raman) for detailed physicochemical analysis that increases throughput and minimizes user bias is described. CC-Raman applies automated mapping to increase analysis speed allowing for up to 100 particles to be analyzed in an hour. CC-Raman is applied to both laboratory and ambient samples to demonstrate its utility for the analysis of both primary and, most importantly, secondary components (sulfate, nitrate, ammonium, and organic material). Reproducibility and precision are compared to computer controlled-scanning electron microscopy (CCSEM). The greater sample throughput shows the potential for CC-Raman to improve particle statistics and advance our understanding of aerosol particle composition and mixing state, and, thus, climate-relevant properties.
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