Analysis of functional groups in atmospheric aerosols by infrared spectroscopy: systematic intercomparison of calibration methods for US measurement network samples

Reggente, Matteo; Dillner, Ann M.; Takahama, Satoshi

doi:https://doi.org/10.5194/amt-12-2287-2019

Articles | Volume 12, issue 4

https://doi.org/10.5194/amt-12-2287-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/amt-12-2287-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 12, issue 4

Research article

|

12 Apr 2019

Research article |

| 12 Apr 2019

Analysis of functional groups in atmospheric aerosols by infrared spectroscopy: systematic intercomparison of calibration methods for US measurement network samples

Matteo Reggente, Ann M. Dillner, and Satoshi Takahama

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Final revised paper (published on 12 Apr 2019)
Supplement to the final revised paper
Preprint (discussion started on 16 Nov 2018)
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 Analysis of functional groups in atmospheric aerosols by infrared spectroscopy: functional group quantification in US measurement networks"', Anonymous Referee #1, 16 Dec 2018
- AC1: 'Response to reviewer comments', Satoshi Takahama, 09 Mar 2019
RC2: 'Anonymous reviewer comments on Reggente 2018', Anonymous Referee #2, 19 Dec 2018
- AC2: 'Response to reviewer comments', Satoshi Takahama, 09 Mar 2019

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Satoshi Takahama on behalf of the Authors (09 Mar 2019) Author's response Manuscript

ED: Referee Nomination & Report Request started (11 Mar 2019) by Charles Brock

RR by Anonymous Referee #1 (19 Mar 2019)

ED: Publish as is (19 Mar 2019) by Charles Brock

Short summary

We compare state-of-the-art models for predicting functional group composition in atmospheric particulate matter across urban and rural samples collected in a US monitoring network. While trends across models are consistent, absolute abundances can be sensitive to selection of calibration standards, spectral processing procedures, and calibration algorithms. Recommendations for further method development for reducing uncertainties are outlined.