Fragment ion–functional group relationships in organic aerosols using aerosol mass spectrometry and mid-infrared spectroscopy - A. Yazdani; N. Dudani; S. Takahama; A. Bertrand; A. S. H. Prévôt; I. El Haddad; A. M. Dillner (Atmospheric Measurement Techniques, 2022)
Aerosol mass spectrometry (AMS) and mid-infrared spectroscopy (MIR) are two analytical methods for characterizing the chemical composition of organic matter (OM). While AMS provides high-temporal-resolution bulk measurements, the extensive fragmentation during the electron ionization makes the characterization of OM components limited. The analysis of aerosols collected on polytetrafluoroethylene (PTFE) filters using MIR, on the other hand, provides functional group information with reduced sample alteration but results in a relatively low temporal resolution. In this work, we compared and combined MIR and AMS measurements for several environmental chamber experiments of combustion-related aerosols to achieve a better understanding of the AMS spectra and the OM chemical evolution with aging. Fresh emissions of wood and coal burning were injected into an environmental simulation chamber and aged with hydroxyl and nitrate radicals. A high-resolution time-of-flight AMS measured the bulk chemical composition of fine OM. Fine aerosols were also sampled on PTFE filters before and after aging for the offline MIR analysis. After comparing AMS and MIR bulk measurements, we used multivariate statistics to identify the functional groups associated the most with the AMS OM for different aerosol sources and oxidants. We also identified the key fragment ions resulting from molecules containing each functional group for the complex OM generated from biomass and fossil fuel combustion. Finally, we developed a statistical model that enables the estimation of the high-time-resolution functional group composition of OM using collocated AMS and MIR measurements. AMS spectra can be used to interpolate the functional group measurements by MIR using this approach. The latter allows us to better understand the evolution of OM during the aging process.