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AMT | Articles | Volume 12, issue 4
Atmos. Meas. Tech., 12, 2287–2312, 2019
https://doi.org/10.5194/amt-12-2287-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Atmos. Meas. Tech., 12, 2287–2312, 2019
https://doi.org/10.5194/amt-12-2287-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

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 et al.
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Cited articles  
Aiken, A. C., Decarlo, P. F., Kroll, J. H., Worsnop, D. R., Huffman, J. A., Docherty, K. S., Ulbrich, I. M., Mohr, C., Kimmel, J. R., Sueper, D., Sun, Y., Zhang, Q., Trimborn, A., Northway, M., Ziemann, P. J., Canagaratna, M. R., Onasch, T. B., Alfarra, M. R., Prevot, A. S. H., Dommen, J., Duplissy, J., Metzger, A., Baltensperger, U., and Jimenez, J. L.: O∕C and OM∕OC ratios of primary, secondary, and ambient organic aerosols with high-resolution time-of-flight aerosol mass spectrometry, Environ. Sci. Technol., 42, 4478–4485, https://doi.org/10.1021/es703009q, 2008. a, b, c
Allen, D. T. and Palen, E.: Recent advances in aerosol analysis by infrared spectroscopy, J. Aerosol Sci., 20, 441–455, https://doi.org/10.1016/0021-8502(89)90078-5, 1989. a, b
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. Technol., 21, 325–342, https://doi.org/10.1080/02786829408959719, 1994. a, b
Alsberg, B. K., Winson, M. K., and Kell, D. B.: Improving the interpretation of multivariate and rule induction models by using a peak parameter representation, Chemometr. Intell. Lab., 36, 95–109, https://doi.org/10.1016/S0169-7439(97)00024-5, 1997. a
Arlot, S. and Celisse, A.: A survey of cross-validation procedures for model selection, Stat. Surv., 4, 40–79, https://doi.org/10.1214/09-SS054, 2010. a
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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.
We compare state-of-the-art models for predicting functional group composition in atmospheric...
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