10th International Aerosol Conference September 2 - September 7, 2018 America's Center Convention Complex St. Louis, Missouri, USA
Abstract View
"Particle Formation" vs. "Particle Growth": Robust Metric for Determining the Onset of Condensational Growth of Nanoparticles
TINJA OLENIUS, Dominik Stolzenburg, Lukas Pichelstorfer, Paul M. Winkler, Kari Lehtinen, Ilona Riipinen, Stockholm University
Abstract Number: 805 Working Group: Aerosol Physics
Abstract Understanding the mechanisms of nanoparticle formation and growth from vapors is essential for resolving nucleation and condensation phenomena. Correct representation of these processes in atmospheric models is also a prerequisite for quantifying atmospheric aerosol particle loadings: Gas-to-particle conversion is assessed to make a substantial contribution to the total aerosol number, but these estimates are highly sensitive to assumptions on the growth dynamics of the smallest nanoparticles below ca. 5-10 nm in diameter. For large enough particles, the vapor-particle mass exchange driving particle growth or evaporation can be described assuming a continuous flux of vapor onto the particle surface. However, this description does not apply to the smallest nanoparticles. Instead, at the smallest end of the particle size spectrum, particle formation and growth involve stochastic fluctuations in particle size due to discrete molecular collision and decay processes. The size regime where the discrete effects become negligible, indicating the onset of condensation-driven growth, has not been addressed to date.
In this work, we derive a simple and robust metric for quantifying the size regime where stochastic effects cannot be omitted for arbitrary molecular systems, based on theoretical considerations on the particle size distribution function. The proposed metric is confirmed by application on synthetic data, generated by molecular-resolution simulations of sub-10 nm particle populations representative of atmospheric nanoparticles, as well as on laboratory observations of particle formation. The results show that the significance of stochastics can be reliably assessed based on the shape of a measured nanoparticle size distribution, with no need for knowledge of the properties of the nucleating and condensing vapors.
The results raise important points regarding the interpretation and utilization of observation data. For atmospheric nanoparticle formation, the size regime at which condensation flux modeling becomes inapplicable is estimated to be below sizes of typically a few nanometers, depending on the exact chemical system in question. At these very small sizes, interpretation of experimental observations relying on condensation modeling may lead to erroneous conclusions on (1) the properties of the condensing vapors when fitting a condensation model to experimental data, (2) "missing" condensing species when observations cannot be reproduced by the model, and (3) the thermodynamics of nanoparticle growth, including the presence and magnitude of Kelvin barriers, when the observed time evolution of the particle size distribution is used to deduce condensational growth rates. To avoid such misinterpretations and to reliably extract information on particle formation mechanisms from experiments, constraining the limits of condensation modeling is necessary. The approach presented in this work provides a means to quantify these limits with a reasonable accuracy, building on the development of robust and generalizable data analysis tools.