Articles | Volume 13, issue 3
https://doi.org/10.5194/amt-13-1517-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-13-1517-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Analysis of functional groups in atmospheric aerosols by infrared spectroscopy: method development for probabilistic modeling of organic carbon and organic matter concentrations
Charlotte Bürki
ENAC/IIE Swiss Federal Institute of Technology Lausanne (EFPL), Lausanne, 1015, Switzerland
Matteo Reggente
ENAC/IIE Swiss Federal Institute of Technology Lausanne (EFPL), Lausanne, 1015, Switzerland
Ann M. Dillner
Air Quality Research Center, University of California Davis, Davis, CA 95616, USA
Jenny L. Hand
Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO 80523, USA
Stephanie L. Shaw
Electric Power Research Institute, Palo Alto, CA 94304, USA
Satoshi Takahama
CORRESPONDING AUTHOR
ENAC/IIE Swiss Federal Institute of Technology Lausanne (EFPL), Lausanne, 1015, Switzerland
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Cited
13 citations as recorded by crossref.
- Quantification of major particulate matter species from a single filter type using infrared spectroscopy – application to a large-scale monitoring network B. Debus et al. 10.5194/amt-15-2685-2022
- Quantifying organic matter and functional groups in particulate matter filter samples from the southeastern United States – Part 2: Spatiotemporal trends A. Boris et al. 10.5194/amt-14-4355-2021
- Characterization of primary and aged wood burning and coal combustion organic aerosols in an environmental chamber and its implications for atmospheric aerosols A. Yazdani et al. 10.5194/acp-21-10273-2021
- Evaluation of CMIP6 model simulations of PM2.5 and its components over China F. Ren et al. 10.5194/gmd-17-4821-2024
- Osteogenic differentiation of pulp stem cells from human permanent teeth on an oxygen-releasing electrospun scaffold R. Samanipour et al. 10.1007/s00289-022-04145-x
- Quantifying functional group compositions of household fuel-burning emissions E. Li et al. 10.5194/amt-17-2401-2024
- NMR spectroscopic applications to atmospheric organic aerosol analysis – Part 1: A critical review of data source and analysis, potentialities and limitations S. Decesari et al. 10.1016/j.trac.2023.117516
- Algorithm for vertical distribution of boundary layer aerosol components in remote-sensing data F. Wang et al. 10.5194/amt-15-6127-2022
- Decadal Trends in the Temperature Dependence of Summertime Urban PM2.5 in the Northeast United States P. Vannucci & R. Cohen 10.1021/acsearthspacechem.2c00077
- Tracking Secondary Organic Aerosol Formation with Molecular Tracers: Contributions from Biogenic and Anthropogenic Precursors X. He et al. 10.1016/j.atmosenv.2025.121410
- Estimating mean molecular weight, carbon number, and OM∕OC with mid-infrared spectroscopy in organic particulate matter samples from a monitoring network A. Yazdani et al. 10.5194/amt-14-4805-2021
- Decreasing the Uncertainty in the Comparison of Molecular Fingerprints of Organic Aerosols with H/D Exchange Mass Spectrometry A. Zherebker et al. 10.1021/acs.est.4c06749
- Quantifying organic matter and functional groups in particulate matter filter samples from the southeastern United States – Part 1: Methods A. Boris et al. 10.5194/amt-12-5391-2019
12 citations as recorded by crossref.
- Quantification of major particulate matter species from a single filter type using infrared spectroscopy – application to a large-scale monitoring network B. Debus et al. 10.5194/amt-15-2685-2022
- Quantifying organic matter and functional groups in particulate matter filter samples from the southeastern United States – Part 2: Spatiotemporal trends A. Boris et al. 10.5194/amt-14-4355-2021
- Characterization of primary and aged wood burning and coal combustion organic aerosols in an environmental chamber and its implications for atmospheric aerosols A. Yazdani et al. 10.5194/acp-21-10273-2021
- Evaluation of CMIP6 model simulations of PM2.5 and its components over China F. Ren et al. 10.5194/gmd-17-4821-2024
- Osteogenic differentiation of pulp stem cells from human permanent teeth on an oxygen-releasing electrospun scaffold R. Samanipour et al. 10.1007/s00289-022-04145-x
- Quantifying functional group compositions of household fuel-burning emissions E. Li et al. 10.5194/amt-17-2401-2024
- NMR spectroscopic applications to atmospheric organic aerosol analysis – Part 1: A critical review of data source and analysis, potentialities and limitations S. Decesari et al. 10.1016/j.trac.2023.117516
- Algorithm for vertical distribution of boundary layer aerosol components in remote-sensing data F. Wang et al. 10.5194/amt-15-6127-2022
- Decadal Trends in the Temperature Dependence of Summertime Urban PM2.5 in the Northeast United States P. Vannucci & R. Cohen 10.1021/acsearthspacechem.2c00077
- Tracking Secondary Organic Aerosol Formation with Molecular Tracers: Contributions from Biogenic and Anthropogenic Precursors X. He et al. 10.1016/j.atmosenv.2025.121410
- Estimating mean molecular weight, carbon number, and OM∕OC with mid-infrared spectroscopy in organic particulate matter samples from a monitoring network A. Yazdani et al. 10.5194/amt-14-4805-2021
- Decreasing the Uncertainty in the Comparison of Molecular Fingerprints of Organic Aerosols with H/D Exchange Mass Spectrometry A. Zherebker et al. 10.1021/acs.est.4c06749
Latest update: 25 Jul 2025
Short summary
Infrared spectroscopy is a chemically informative method for particulate matter characterization. However, recent work has demonstrated that predictions depend heavily on the choice of calibration model parameters. We propose a means for managing parameter uncertainties by combining available data from laboratory standards, molecular databases, and collocated ambient measurements to provide useful characterization of atmospheric organic matter on a large scale.
Infrared spectroscopy is a chemically informative method for particulate matter...