Articles | Volume 20, issue 2
https://doi.org/10.5194/acp-20-1021-2020
https://doi.org/10.5194/acp-20-1021-2020
Research article
 | 
27 Jan 2020
Research article |  | 27 Jan 2020

Dimensionality-reduction techniques for complex mass spectrometric datasets: application to laboratory atmospheric organic oxidation experiments

Abigail R. Koss, Manjula R. Canagaratna, Alexander Zaytsev, Jordan E. Krechmer, Martin Breitenlechner, Kevin J. Nihill, Christopher Y. Lim, James C. Rowe, Joseph R. Roscioli, Frank N. Keutsch, and Jesse H. Kroll

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Cited articles

Abeleira, A., Pollack, I. B., Sive, B., Zhou, Y., Fischer, E. V., and Farmer, D. K.: Source characterization of volatile organic compounds in the Colorado Northern Front Range Metropolitan Area during spring and summer 2015, J. Geophys. Res.-Atmos., 122, 3595–3613, https://doi.org/10.1002/2016JD026227, 2017. 
Aumont, B., Szopa, S., and Madronich, S.: Modelling the evolution of organic carbon during its gas-phase tropospheric oxidation: development of an explicit model based on a self generating approach, Atmos. Chem. Phys., 5, 2497–2517, https://doi.org/10.5194/acp-5-2497-2005, 2005. 
Bar-Joseph, Z., Gifford, D. K., and Jaakkola, T. S.: Fast optimal leaf ordering for hierarchical clustering, Bioinformatics, 17, S22–S29, https://doi.org/10.1093/bioinformatics/17.suppl_1.S22, 2001. 
Bloss, C., Wagner, V., Jenkin, M. E., Volkamer, R., Bloss, W. J., Lee, J. D., Heard, D. E., Wirtz, K., Martin-Reviejo, M., Rea, G., Wenger, J. C., and Pilling, M. J.: Development of a detailed chemical mechanism (MCMv3.1) for the atmospheric oxidation of aromatic hydrocarbons, Atmos. Chem. Phys., 5, 641–664, https://doi.org/10.5194/acp-5-641-2005, 2005a. 
Bloss, C., Wagner, V., Bonzanini, A., Jenkin, M. E., Wirtz, K., Martin-Reviejo, M., and Pilling, M. J.: Evaluation of detailed aromatic mechanisms (MCMv3 and MCMv3.1) against environmental chamber data, Atmos. Chem. Phys., 5, 623–639, https://doi.org/10.5194/acp-5-623-2005, 2005b. 
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Short summary
Oxidation chemistry of organic compounds in the atmosphere produces a diverse spectrum of products. This diversity is difficult to represent in air quality and climate models, and in laboratory experiments it results in large and complex datasets. This work evaluates several methods to simplify the chemistry of oxidation systems in environmental chambers, including positive matrix factorization, hierarchical clustering analysis, and gamma kinetics parameterization.
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