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

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Date
2017-06-30Type
- Journal Article
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Cited 22 times in
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Abstract
We present a Monte Carlo genetic algorithm (MCGA) for efficient, automated, and unbiased global optimization of model input parameters by simultaneous fitting to multiple experimental data sets. The algorithm was developed to address the inverse modelling problems associated with fitting large sets of model input parameters encountered in state-of-the-art kinetic models for heterogeneous and multiphase atmospheric chemistry. The MCGA approach utilizes a sequence of optimization methods to find and characterize the solution of an optimization problem. It addresses an issue inherent to complex models whose extensive input parameter sets may not be uniquely determined from limited input data. Such ambiguity in the derived parameter values can be reliably detected using this new set of tools, allowing users to design experiments that should be particularly useful for constraining model parameters. We show that the MCGA has been used successfully to constrain parameters such as chemical reaction rate coefficients, diffusion coefficients, and Henry's law solubility coefficients in kinetic models of gas uptake and chemical transformation of aerosol particles as well as multiphase chemistry at the atmosphere–biosphere interface. While this study focuses on the processes outlined above, the MCGA approach should be portable to any numerical process model with similar computational expense and extent of the fitting parameter space. Show more
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https://doi.org/10.3929/ethz-b-000191761Publication status
publishedExternal links
Journal / series
Atmospheric Chemistry and PhysicsVolume
Pages / Article No.
Publisher
Copernicus PublicationsOrganisational unit
03517 - Peter, Thomas (emeritus) / Peter, Thomas (emeritus)
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Citations
Cited 22 times in
Web of Science
Cited 24 times in
Scopus
ETH Bibliography
yes
Altmetrics