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Volume 9, issue 7
Atmos. Meas. Tech., 9, 3429–3454, 2016
https://doi.org/10.5194/amt-9-3429-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Atmos. Meas. Tech., 9, 3429–3454, 2016
https://doi.org/10.5194/amt-9-3429-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 28 Jul 2016

Research article | 28 Jul 2016

Analysis of functional groups in atmospheric aerosols by infrared spectroscopy: sparse methods for statistical selection of relevant absorption bands

Satoshi Takahama et al.

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Cited articles

Allen, D. T., Palen, E. J., Haimov, M. I., Hering, S. V., and Young, J. R.: Fourier-transform Infrared-spectroscopy of Aerosol Collected In A Low-pressure Impactor (LPI/FTIR) – Method Development and Field Calibration, Aerosol Sci. Tech., 21, 325–342, https://doi.org/10.1080/02786829408959719, 1994.
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Arlot, S. and Celisse, A.: A survey of cross-validation procedures for model selection, Statistics Surveys, 4, 40–79, https://doi.org/10.1214/09-SS054, 2010.
Barsanti, K. C. and Pankow, J. F.: Thermodynamics of the formation of atmospheric organic particulate matter by accretion reactions – Part 3: Carboxylic and dicarboxylic acids, Atmos. Environ., 40, 6676–6686, https://doi.org/10.1016/j.atmosenv.2006.03.013, 2006.
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Short summary
We introduce the application of statistical algorithms that allow us to associate various dimensions of aerosol composition to vibrational modes measured by infrared absorption spectroscopy. We demonstrate their use on four organic functional groups for which absorption bands are known and extend the application to interpret bands associated with ambient organic carbon and elemental carbon quantified by an independent measurement technique that is widely used in aerosol monitoring networks.
We introduce the application of statistical algorithms that allow us to associate various...
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