An innovative approach to characterizing the refractive indices and effective densities of internally mixed light-absorbing aerosol particles

一种表征内部混合吸光气溶胶粒子折射率和有效密度的创新方法

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Abstract

To improve our understanding of how light interacts with internally mixed light absorbing aerosol particles, we establish an integrated measurement platform enabling concurrent determinations of the complex refractive indices (m = n + ik) and effective densities (ρ) of aerosol particles. Cavity ring-down and photoacoustic spectroscopy are used to measure the extinction and absorption cross-sections, respectively, for aerosol particles classified by their aerodynamic size using the Cambustion Aerodynamic Aerosol Classifier. We report measurements on laboratory generated aerosol particles composed of ammonium sulfate (non-absorbing inorganic), sucrose (non-absorbing organic), nigrosin (strong light-absorbing organic), and two-component particles comprised of internal mixtures of nigrosin with each non-absorbing species. The accuracy and precision of measured cross-sections and retrieved m are assessed, and we demonstrate improved precision in these quantities retrieved for aerodynamically classified particles compared to approaches that utilize mobility classification. We show that accurate knowledge of the variations in ρ with mixture composition are essential for predicting m for internally mixed particles using mixing rules. For organic mixtures of sucrose and nigrosin, n and k are predicted accurately by mass fraction weightings of pure component values, and ideal mixing between components is observed. For organic-inorganic mixtures of nigrosin with ammonium sulfate, n varies non-linearly with composition and cannot be predicted by linear mixing rules. Instead, a mole fraction weighting of molar refraction, incorporating changes in particle mass density on mixing, is needed. These evaluations of refractive index models provide useful insights for researchers developing atmospheric models or inferring particle physicochemical properties from optical spectroscopy data.

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