Molecular-resolution simulations of new particle formation: Evaluation of common assumptions made in describing nucleation in aerosol dynamics models

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Abstract

Aerosol dynamics models that describe the evolution of a particle distribution incorporate nucleation as a particle formation rate at a small size around a few nanometers in diameter. This rate is commonly obtained from molecular models that cover the distribution below the given formation size–although in reality the distribution of nanometer-sized particles cannot be unambiguously divided into separate sections of particle formation and growth. When incorporating nucleation, the distribution below the formation size is omitted, and the formation rate is assumed to be in a steady state. In addition, to reduce the modeled size range, the formation rate is often scaled to a larger size based on estimated growth and scavenging rates and the assumption that also the larger size is in a steady state. This work evaluates these assumptions by simulating sub-10 nm particle distributions in typical atmospheric conditions with an explicit molecular-resolution model. Particle formation is included either (1) dynamically, that is, the whole size range starting from single vapor molecules is modeled explicitly or (2) implicitly by using an input formation rate as is done in aerosol models. The results suggest that while each assumption can affect the outcome of new particle formation modeling, the most significant source of uncertainty affecting the formation rates and resulting nanoparticle concentrations is the steady-state assumption, which may lead to an overprediction of the concentrations by factors of approximately from two to even orders of magnitude. This can have implications for modeling and predicting atmospheric particle formation. Copyright © 2017 American Association for Aerosol Research.

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Olenius, T., & Riipinen, I. (2017). Molecular-resolution simulations of new particle formation: Evaluation of common assumptions made in describing nucleation in aerosol dynamics models. Aerosol Science and Technology, 51(4), 397–408. https://doi.org/10.1080/02786826.2016.1262530

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