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.
Citation
ID:
233624
Ref Key:
takahama2017atmospherictechnical