Articles | Volume 19, issue 14
Atmos. Chem. Phys., 19, 9333–9350, 2019
https://doi.org/10.5194/acp-19-9333-2019
Atmos. Chem. Phys., 19, 9333–9350, 2019
https://doi.org/10.5194/acp-19-9333-2019

Research article 22 Jul 2019

Research article | 22 Jul 2019

Optimization of process models for determining volatility distribution and viscosity of organic aerosols from isothermal particle evaporation data

Olli-Pekka Tikkanen et al.

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Cited articles

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Berkemeier, T., Ammann, M., Krieger, U. K., Peter, T., Spichtinger, P., Pöschl, U., Shiraiwa, M., and Huisman, A. J.: Technical note: Monte Carlo genetic algorithm (MCGA) for model analysis of multiphase chemical kinetics to determine transport and reaction rate coefficients using multiple experimental data sets, Atmos. Chem. Phys., 17, 8021–8029, https://doi.org/10.5194/acp-17-8021-2017, 2017. 
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We assessed how well the organic aerosol particle composition and viscosity can be captured by optimizing process models to match particle evaporation data. We performed the analysis for both artificial and real evaporation data and tested two optimization algorithms. Our findings show that the optimization method yields a good estimate for the studied properties. The timescale of the evaporation data and particle size was found to be important in identifying the volatility of organic compounds.
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