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

Takahama, Satoshi; Ruggeri, Giulia; Dillner, Ann M.

doi:https://doi.org/10.5194/amt-9-3429-2016

Articles | Volume 9, issue 7

https://doi.org/10.5194/amt-9-3429-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/amt-9-3429-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 9, issue 7

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, Giulia Ruggeri, and Ann M. Dillner

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Final revised paper (published on 28 Jul 2016)
Supplement to the final revised paper
Preprint (discussion started on 18 Feb 2016)
Supplement to the preprint

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Review of Takahama et al', Anonymous Referee #1, 16 Mar 2016
- AC1: 'Response to Anonymous Referee #1', Satoshi Takahama, 14 Jun 2016
RC2: 'A thorough analysis of 4 sparse calibration models for quantitative predictions of FGs and TOR OC and EC in ambient samples', Anonymous Referee #2, 21 Mar 2016
- AC2: 'Response to Anonymous Referee #2', Satoshi Takahama, 14 Jun 2016
AC3: 'Revised manuscript', Satoshi Takahama, 14 Jun 2016

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.