Articles | Volume 15, issue 6
https://doi.org/10.5194/acp-15-3173-2015
https://doi.org/10.5194/acp-15-3173-2015
Research article
 | 
20 Mar 2015
Research article |  | 20 Mar 2015

Explaining variance in black carbon's aging timescale

L. Fierce, N. Riemer, and T. C. Bond

Abstract. The size and composition of particles containing black carbon (BC) are modified soon after emission by condensation of semivolatile substances and coagulation with other particles, known collectively as "aging" processes. Although this change in particle properties is widely recognized, the timescale for transformation is not well constrained. In this work, we simulated aerosol aging with the particle-resolved model PartMC-MOSAIC (Particle Monte Carlo – Model for Simulating Aerosol Interactions and Chemistry) and extracted aging timescales based on changes in particle cloud condensation nuclei (CCN). We simulated nearly 300 scenarios and, through a regression analysis, identified the key parameters driving the value of the aging timescale. We show that BC's aging timescale spans from hours to weeks, depending on the local environmental conditions and the characteristics of the fresh BC-containing particles. Although the simulations presented in this study included many processes and particle interactions, we show that 80% of the variance in the aging timescale is explained by only a few key parameters. The condensation aging timescale decreased with the flux of condensing aerosol and was shortest for the largest fresh particles, while the coagulation aging timescale decreased with the total number concentration of large (D >100 nm), CCN-active particles and was shortest for the smallest fresh particles. Therefore, both condensation and coagulation play important roles in aging, and their relative impact depends on the particle size range.

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Short summary
The timescale for particles containing black carbon to age from hydrophobic to hygroscopic strongly influences black carbon's atmospheric lifetime and climate impact. This paper identifies the minimal set of independent variables needed to explain variance in this aging timescale. This work distills the complex interactions captured by a particle-resolved aerosol model to a few input variables and is a first step toward developing physically based parameterizations of aerosol aging.
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