Technical note: Relating functional group measurements to carbon types for improved model–measurement comparisons of organic aerosol composition

Abstract

Abstract. Functional group (FG) analysis provides a means by which functionalization in organic aerosol can be attributed to the abundances of its underlying molecular structures. However, performing this attribution requires additional, unobserved details about the molecular mixture to provide constraints in the estimation process. We present an approach for conceptualizing FG measurements of organic aerosol in terms of its functionalized carbon atoms. This reformulation facilitates estimation of mass recovery and biases in popular carbon-centric metrics that describe the extent of functionalization (such as oxygen to carbon ratio, organic mass to organic carbon mass ratio, and mean carbon oxidation state) for any given set of molecules and FGs analyzed. Furthermore, this approach allows development of parameterizations to more precisely estimate the organic carbon content from measured FG abundance. We use simulated photooxidation products of α-pinene secondary organic aerosol previously reported by Ruggeri et al. (2016) and FG measurements by Fourier transform infrared (FT-IR) spectroscopy in chamber experiments by Sax et al. (2005) to infer the relationships among molecular composition, FG composition, and metrics of organic aerosol functionalization. We find that for this simulated system, ∼ 80 % of the carbon atoms should be detected by FGs for which calibration models are commonly developed, and ∼ 7 % of the carbon atoms are undetectable by FT-IR analysis because they are not associated with vibrational modes in the infrared. Estimated biases due to undetected carbon fraction for these simulations are used to make adjustments in these carbon-centric metrics such that model–measurement differences are framed in terms of unmeasured heteroatoms (e.g., in hydroperoxide and nitrate groups for the case studied in this demonstration). The formality of this method provides framework for extending FG analysis to not only model–measurement but also instrument intercomparisons in other chemical systems.

Quantifying organic matter and functional groups in particulate matter filter samples from the southeastern United States – Part 1: Methods

“…Infrared absorption spectrometry has been used to quantify functional groups using a peak-fitting approach (Takahama et al, 2013), but factor-based calibration of spectra can more readily determine interferents and is strengthened by using multiple spectral bands at once (Naes et al, 2002). Specifically, partial least-squares (PLS) regression has been used in factor-based work.…”

“…We used a linear regression between COOH and noxCO to differentiate between carboxylic C=O and "naCO" (nonacid, non-oxalate, or other C=O; see Sect. S11 and Takahama et al, 2013). This was necessary because, although the C=O stretching bands of carboxylic acids are theoretically shifted to lower wavenumbers (∼ 1700-1710 cm −1 ) than an unperturbed C=O stretching band (∼ 1725-1740 cm −1 ; Mayo et al, 2003), there is not a clear separation between these two types of C=O in spectra of particles and this spectral range is not unique to carboxylic acids.…”

“…Carbonyls are a particularly informative functional group in infrared spectra of ambient OM due to their strong absorption coefficients and high abundance in the atmosphere. A strong, broad C=O stretching band at ∼ 1700-1800 cm −1 is observed in ambient OM spectra (Takahama et al, 2013). In particular, molecules containing carboxylic acids may contribute the majority of OM mass (Decesari et al, 2007), the most abundant of which are typically the C 2 -C 4 dicarboxylic acids (Kawamura and Bikkina, 2016).…”

Supplementary material to "Analysis of functional groups in atmospheric aerosols by infrared spectroscopy: functional group quantification in US measurement networks"

“…A value of 0.5 corresponds to the assumption that the carbon shares an aCOH bond with a single aCH bond, whereas a value of 0 corresponds to the assumption of a terminal saturated carbon in which it is accounted for by two aCH bonds. According to the analysis of Takahama and Ruggeri (2017), we use a value of 0.5.…”

An open platform for Aerosol InfraRed Spectroscopy analysis – AIRSpec

“…For example, inorganic salts (Cunningham et al, 1974;Allen et al, 1994), dust (Foster andWalker, 1984), organic functional groups (Allen et al, 1994;Maria et al, 2002Maria et al, , 2003bChen et al, 2016;Coury and Dillner, 2008;Takahama et al, 2013Takahama et al, , 2016Faber et al, 2017), and carbonaceous content (Dillner and Takahama, 2015a, b;Reggente et al, 2016) have been estimated by calibration models developed for FTIR spectra. Spectra clustering and factor analysis have been used to estimate source contributions from fossil fuels, vegetation, marine environments, and biomass burning (Russell et al, 2009aLiu et al, 2009;Takahama et al, 2011;Frossard et al, 2014).…”