Mixing state evolution of agglomerating particles in an aerosol chamber: Comparison of measurements and particle-resolved simulations

Abstract

This article presents a validation study of the stochastic particle-resolved aerosol model PartMC with experimental data from an aerosol chamber experiment. For the experiment, a scanning mobility particle sizer and a single-particle soot photometer were used to monitor the aerosol mixing state evolution of two initially externally mixed aerosol populations of ammonium sulfate and black carbon particles undergoing agglomeration. We applied an efficient optimization algorithm (ProSRS) to determine several unconstrained simulation parameters and were able to successfully reproduce number concentrations and size distributions of mixed particles that formed by agglomeration. The PartMC modeling approach in conjunction with the optimization procedure provides a tool for detailed comparisons of chamber experiments and modeling, where aerosol mixing state is the focus of investigation.

Copyright © 2019 American Association for Aerosol Research

EDITOR:

• Yannis Drossinos

Notes

1 ProSRS code is publicly available at https://github.com/compdyn/ProSRS.

2 Blue Waters: https://bluewaters.ncsa.illinois.edu.

Additional information

Funding

We acknowledge DOE-ASR funding from grants DE-SC0011771, DE-SC0019192, DE-SC0012704, DE-SC0006980, and DE-SC0011935. M. W. acknowledges support from NSF CMMI 11-50490. N. R. acknowledges funding from NSF AGS 1254428. This research is part of the Blue Waters sustained-petascale computing project, which is supported by the National Science Foundation (awards OCI-0725070 and ACI-1238993) and the state of Illinois. Blue Waters is a joint effort of the University of Illinois at Urbana-Champaign and its National Center for Supercomputing Applications.