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

Abstract

This article introduces 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 method 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.

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [3]; ORCiD logo [2]; ORCiD logo [3]; ORCiD logo [2]; ORCiD logo [1]
  1. Univ. of Illinois at Urbana-Champaign, Urbana, IL (United States)
  2. Boston College, Chestnut Hill, MA (United States)
  3. Brookhaven National Lab. (BNL), Upton, NY (United States)
Publication Date:
Research Org.:
Brookhaven National Lab. (BNL), Upton, NY (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
OSTI Identifier:
1561250
Report Number(s):
BNL-212073-2019-JAAM
Journal ID: ISSN 0278-6826
Grant/Contract Number:  
SC0012704
Resource Type:
Accepted Manuscript
Journal Name:
Aerosol Science and Technology
Additional Journal Information:
Journal Volume: 53; Journal Issue: 11; Journal ID: ISSN 0278-6826
Publisher:
American Association for Aerosol Research
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES

Citation Formats

Shou, Chenchao, Riemer, Nicole, Onasch, Timothy B., Sedlacek, Arthur J., Lambe, Andrew T., Lewis, Ernie R., Davidovits, Paul, and West, Matthew. Mixing state evolution of agglomerating particles in an aerosol chamber: Comparison of measurements and particle-resolved simulations. United States: N. p., 2019. Web. doi:10.1080/02786826.2019.1661959.
Shou, Chenchao, Riemer, Nicole, Onasch, Timothy B., Sedlacek, Arthur J., Lambe, Andrew T., Lewis, Ernie R., Davidovits, Paul, & West, Matthew. Mixing state evolution of agglomerating particles in an aerosol chamber: Comparison of measurements and particle-resolved simulations. United States. doi:10.1080/02786826.2019.1661959.
Shou, Chenchao, Riemer, Nicole, Onasch, Timothy B., Sedlacek, Arthur J., Lambe, Andrew T., Lewis, Ernie R., Davidovits, Paul, and West, Matthew. Thu . "Mixing state evolution of agglomerating particles in an aerosol chamber: Comparison of measurements and particle-resolved simulations". United States. doi:10.1080/02786826.2019.1661959. https://www.osti.gov/servlets/purl/1561250.
@article{osti_1561250,
title = {Mixing state evolution of agglomerating particles in an aerosol chamber: Comparison of measurements and particle-resolved simulations},
author = {Shou, Chenchao and Riemer, Nicole and Onasch, Timothy B. and Sedlacek, Arthur J. and Lambe, Andrew T. and Lewis, Ernie R. and Davidovits, Paul and West, Matthew},
abstractNote = {This article introduces 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 method 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.},
doi = {10.1080/02786826.2019.1661959},
journal = {Aerosol Science and Technology},
number = 11,
volume = 53,
place = {United States},
year = {2019},
month = {9}
}

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    Works referencing / citing this record:

    Simulating the evolution of soot mixing state with a particle‐resolved aerosol model
    journal, January 2009

    • Riemer, N.; West, M.; Zaveri, R. A.
    • Journal of Geophysical Research, Vol. 114, Issue D9
    • DOI: 10.1029/2008jd011073

    Development and validation of a black carbon mixing state resolved three-dimensional model: Aging processes and radiative impact: BC MIXING STATE RESOLVED WRF-CHEM
    journal, March 2013

    • Matsui, H.; Koike, M.; Kondo, Y.
    • Journal of Geophysical Research: Atmospheres, Vol. 118, Issue 5
    • DOI: 10.1029/2012jd018446

    Weighted Flow Algorithms (WFA) for stochastic particle coagulation
    journal, September 2011

    • DeVille, R. E. L.; Riemer, N.; West, M.
    • Journal of Computational Physics, Vol. 230, Issue 23
    • DOI: 10.1016/j.jcp.2011.07.027

    Aerosol Mixing State: Measurements, Modeling, and Impacts
    journal, May 2019

    • Riemer, N.; Ault, A. P.; West, M.
    • Reviews of Geophysics, Vol. 57, Issue 2
    • DOI: 10.1029/2018rg000615

    Simulation optimization: a review of algorithms and applications
    journal, September 2015

    • Amaran, Satyajith; Sahinidis, Nikolaos V.; Sharda, Bikram
    • Annals of Operations Research, Vol. 240, Issue 1
    • DOI: 10.1007/s10479-015-2019-x

    Single particle diversity and mixing state measurements
    journal, January 2014

    • Healy, R. M.; Riemer, N.; Wenger, J. C.
    • Atmospheric Chemistry and Physics, Vol. 14, Issue 12
    • DOI: 10.5194/acp-14-6289-2014