Abstract. Peak fitting (PF) and partial least
squares (PLS) regression have been independently developed for estimation of
functional groups (FGs) from Fourier transform infrared (FTIR) spectra of
ambient aerosol collected on Teflon filters. PF is a model that quantifies
the functional group composition of the ambient samples by fitting individual
Gaussian line shapes to the aerosol spectra. PLS is a data-driven,
statistical model calibrated to laboratory standards of relevant compounds
and then extrapolated to ambient spectra. In this work, we compare the FG
quantification using the most widely used implementations of PF and PLS,
including their model parameters, and also perform a comparison when the
underlying laboratory standards and spectral processing are harmonized. We
evaluate the quantification of organic FGs (alcohol COH, carboxylic
COOH, alkane CH, carbonyl CO) and ammonium, using external
measurements (organic carbon (OC) measured by thermal optical reflectance
(TOR) and ammonium by balance of sulfate and nitrate measured by ion
chromatography). We evaluate our predictions using 794 samples collected in
the Interagency Monitoring of PROtected Visual Environments (IMPROVE) network
(USA) in 2011 and 238 laboratory standards from Ruthenburg et al. (2014)
(available at https://doi.org/10.1016/j.atmosenv.2013.12.034). Each model shows
different biases. Overall, estimates of OC by FTIR show high correlation with
TOR OC. However, PLS applied to unprocessed (raw spectra) appears to
underpredict oxygenated functional groups in rural samples, while other
models appear to underestimate aliphatic CH bonds and OC in urban samples. It
is possible to adjust model parameters (absorption coefficients for PF and
number of latent variables for PLS) within limits consistent with calibration
data to reduce these biases, but this analysis reveals that further progress
in parameter selection is required. In addition, we find that the influence
of scattering and anomalous transmittance of infrared in coarse particle
samples can lead to predictions of OC by FTIR which are inconsistent with TOR
OC. We also find through several means that most of the quantified carbonyl
is likely associated with carboxylic groups rather than ketones or esters. In
evaluating state-of-the-art methods for FG abundance by FTIR, we suggest
directions for future research.