Articles | Volume 9, issue 2
https://doi.org/10.5194/amt-9-441-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-9-441-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Predicting ambient aerosol thermal–optical reflectance (TOR) measurements from infrared spectra: extending the predictions to different years and different sites
Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland
Ann M. Dillner
University of California, Davis, California, USA
Satoshi Takahama
Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland
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- Quantification of amine functional groups and their influence on OM/OC in the IMPROVE network M. Kamruzzaman et al. 10.1016/j.atmosenv.2017.10.053
2 citations as recorded by crossref.
- Thermal/optical reflectance equivalent organic and elemental carbon determined from federal reference and equivalent method fine particulate matter samples using Fourier transform infrared spectrometry A. Weakley et al. 10.1080/02786826.2018.1504161
- Ambient aerosol composition by infrared spectroscopy and partial least-squares in the chemical speciation network: Organic carbon with functional group identification A. Weakley et al. 10.1080/02786826.2016.1217389
Saved (final revised paper)
Latest update: 04 Nov 2024
Short summary
Organic carbon and elemental carbon are major components of atmospheric PM. Typically they are measured using destructive and relatively expensive methods (e.g., TOR). We aim to reduce the operating costs of large air quality monitoring networks using FT-IR spectra of ambient PTFE filters and PLS regression. We achieve accurate predictions for models (calibrated in 2011) that use samples collected at the same or different sites of the calibration data set and in a different year (2013).
Organic carbon and elemental carbon are major components of atmospheric PM. Typically they are...