Complexities in Modeling Organic Aerosol Light Absorption

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Abstract

Aerosol particles dynamically evolve in the atmosphere by physicochemical interactions with sunlight, trace chemical species, and water. Current modeling approaches fix properties such as aerosol refractive index, introducing spatial and temporal errors in the radiative impacts. Further progress requires a process-level description of the refractive indices as the particles age and experience physicochemical transformations. We present two multivariate modeling approaches of light absorption by brown carbon (BrC). The initial approach was to extend the modeling framework of the refractive index at 589 nm (nD), but that result was insufficient. We developed a second multivariate model using aromatic rings and functional groups to predict the imaginary part of the complex refractive index. This second model agreed better with measured spectral absorption peaks, showing promise for a simplified treatment of BrC optics. In addition to absorption, organic functionalities also alter the water affinity of the molecules, leading to a hygroscopic uptake and increased light absorption, which we show through measurements and modeling.

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Gorkowski, K., Benedict, K. B., Carrico, C. M., & Dubey, M. K. (2022). Complexities in Modeling Organic Aerosol Light Absorption. Journal of Physical Chemistry A, 126(29), 4827–4833. https://doi.org/10.1021/acs.jpca.2c02236

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