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Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
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Volume 17, issue 12
Atmos. Chem. Phys., 17, 8021-8029, 2017
https://doi.org/10.5194/acp-17-8021-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Atmos. Chem. Phys., 17, 8021-8029, 2017
https://doi.org/10.5194/acp-17-8021-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Technical note 30 Jun 2017

Technical note | 30 Jun 2017

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

Thomas Berkemeier et al.
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AR: Author's response | RR: Referee report | ED: Editor decision
AR by Thomas Berkemeier on behalf of the Authors (09 May 2017)  Author's response    Manuscript
ED: Publish as is (21 May 2017) by David Topping
Publications Copernicus
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Short summary
Kinetic process models are efficient tools used to unravel the mechanisms governing chemical and physical transformation in multiphase atmospheric chemistry. However, determination of kinetic parameters such as reaction rate or diffusion coefficients from multiple data sets is often difficult or ambiguous. This study presents a novel optimization algorithm and framework to determine these parameters in an automated fashion and to gain information about parameter uncertainty and uniqueness.
Kinetic process models are efficient tools used to unravel the mechanisms governing chemical and...
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