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Quantifying Impacts of Aerosol Mixing State on Nucleation-Scavenging of Black Carbon Aerosol Particles

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Recent observational studies suggest that nucleation-scavenging is the principal path to removing black carbon-containing aerosol from the atmosphere, thus affecting black carbon’s lifetime and radiative forcing. Modeling the process of… Click to show full abstract

Recent observational studies suggest that nucleation-scavenging is the principal path to removing black carbon-containing aerosol from the atmosphere, thus affecting black carbon’s lifetime and radiative forcing. Modeling the process of nucleation-scavenging is challenging, since black carbon (BC) forms complex internal mixtures with other aerosol species. Here, we examined the impacts of black carbon mixing state on nucleation scavenging using the particle-resolved aerosol model PartMC-MOSAIC. This modeling approach has the unique advantage that complex aerosol mixing states can be represented on a per-particle level. For a scenario library that comprised hundreds of diverse aerosol populations, we quantified nucleation-scavenged BC mass fractions. Consistent with measurements, these vary widely, depending on the amount of BC, the amount of coating and coating material, as well as the environmental supersaturation. We quantified the error in the nucleation-scavenged black carbon mass fraction introduced when assuming an internally mixed distribution, and determined its bounds depending on environmental supersaturation and on the aerosol mixing state index χ . For a given χ value, the error decreased at higher supersaturations. For more externally mixed populations ( χ 75 %), the error was below 100% for the range of supersaturations (from 0.02% to 1%) investigated here. Accounting for black carbon mixing state and knowledge of the supersaturation of the environment are crucial when determining the amount of black carbon that can be incorporated into clouds.

Keywords: black carbon; mixing state; nucleation scavenging; carbon

Journal Title: Atmosphere
Year Published: 2018

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