Abstract. Particulate matter (PM) affects visibility, climate, and public health. Organic matter (OM), a uniquely complex portion of PM, can make up more than half of total atmospheric fine PM mass. We investigated the effect of aging on secondary organic aerosol (SOA) concentration and composition for wood burning (WB) and coal combustion (CC) emissions, two major atmospheric OM sources, using mid-infrared (MIR) spectroscopy and aerosol mass spectrometry (AMS). For this purpose, primary emissions were injected into an environmental chamber and aged using hydroxyl (diurnal aging) and nitrate (nocturnal aging) radicals to reach an atmospherically relevant oxidative age. A time-of-flight AMS instrument was used to measure the high-time-resolution composition of non-refractory fine PM, while fine PM was collected on PTFE filters before and after aging for MIR analysis. AMS and MIR spectroscopy indicate an approximately 3-fold enhancement of organic aerosol (OA) concentration after aging (not wall-loss corrected). The OM:OC ratios also agree closely between the two methods and increase, on average, from 1.6 before aging to 2 during the course of aging. MIR spectroscopy, which is able to differentiate among oxygenated groups, shows a distinct functional group composition for aged WB (high abundance of carboxylic acids) and CC OA (high abundance of non-acid carbonyls) and detects aromatics and polycyclic aromatic hydrocarbons (PAHs) in emissions of both sources. The MIR spectra of fresh WB and CC aerosols are reminiscent of their parent compounds with differences in specific oxygenated functional groups after aging, consistent with expected oxidation pathways for volatile organic compounds (VOCs) of each emission source. The AMS mass spectra also show variations due to source and aging that are consistent with the MIR functional group (FG) analysis. Finally, a comparison of the MIR spectra of aged chamber WB OA with that of ambient samples affected by residential wood burning and wildfires reveals similarities regarding the high abundance of organics, especially acids, and the visible signatures of lignin and levoglucosan. This finding is beneficial for the source identification of atmospheric aerosols and interpretation of their complex MIR spectra.

Abstract. Particulate matter (PM) affects visibility, climate, and public health. Organic matter (OM), a uniquely complex portion of PM, can make up more than half of total atmospheric fine PM. We investigated the effect of aging on secondary organic aerosol (SOA) concentration and composition for wood burning (WB) and coal combustion (CC) emissions, two major atmospheric OM sources, using mid-infrared (MIR) spectroscopy and aerosol mass spectrometry (AMS). For this purpose, primary aerosols were injected into an environmental chamber and aged using hydroxyl (diurnal aging) and nitrate (nocturnal aging) radicals to reach an atmospherically-relevant oxidative age. A time-of-flight AMS instrument was used to measure high-time-resolution composition of non-refractory fine PM, while fine PM was collected on PTFE filters before and after aging for MIR analysis. AMS and MIR spectroscopy indicate an approximately three-fold enhancement of organic aerosol (OA) concentration after aging (not wall-loss corrected). The OM : OC ratios also agree closely between the two methods and increase, on average, from 1.6, before aging, to 2, during the course of aging. MIR spectroscopy, which is able to differentiate among oxygenated groups, shows a distinct functional group composition for aged WB (high abundance of carboxylic acids) and CC OA (high abundance of non-acid carbonyls) and detects aromatics and polycyclic aromatic hydrocarbons (PAHs) in emissions of both sources. The MIR spectra of fresh WB and CC aerosols are reminiscent of their parent compounds with differences in specific oxygenated functional groups after aging, consistent with expected oxidation pathways for volatile organic compounds (VOCs) of each emission source. The AMS mass spectra also show variations with source and aging that are consistent the MIR functional group (FG) analysis. Finally, comparison of the MIR spectra of chamber WB OA with that of ambient samples affected by residential wood burning and wildfires reveals similarities regarding the high abundance of organics, especially acids, and visible signatures of lignin and levoglucosan. This finding is beneficial to source identification of atmospheric aerosols and interpretation of their complex MIR spectra.

Abstract. Organic matter (OM) is a major constituent of fine particulate matter which contributes significantly to degradation of visibility, radiative forcing, and causes adverse health effects. However, due to its sheer compositional complexity, OM is difficult to characterize in its entirety. Mid-infrared spectroscopy has previously proven useful in the study of OM by providing extensive information about functional group composition with high mass recovery. Herein, we introduce a new method for obtaining additional characteristics such as mean carbon number and molecular weight of these complex organic mixtures using the aliphatic C–H absorbance profile in mid-infrared spectrum. We apply this technique to spectra acquired non-destructively from Teflon filters used for fine particulate matter quantification at selected sites of Inter-agency Monitoring of PROtected Visual Environments (IMPROVE) network. Since carbon number and molecular weight are important characteristics used by recent models to describe evolution in OM composition, this technique can provide semi-quantitative, observational constraints of these variables at the scale of the network. For this task, multivariate statistical models are trained on calibration spectra prepared from atmospherically relevant laboratory standards and are applied to ambient samples. Then, the physical basis linking the absorbance profile of this relatively narrow region in the mid-infrared spectrum to the molecular structure is investigated using a classification approach. The multivariate statistical models predict mean carbon number and molecular weight that are consistent with previous values of organic-mass-to-organic-carbon (OM/OC) ratios estimated for the network using different approaches. The results are also consistent with temporal and spatial variations in these quantities associated with aging processes, and different source classes (anthropogenic, biogenic, and burning sources). For instance, the models estimate higher mean carbon number for urban samples and smaller, more fragmented molecules for samples in which substantial aging is anticipated.

Abstract. 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.

Abstract. Aerosol mass spectrometry (AMS) and mid-infrared spectroscopy (MIR) are two analytical methods for characterizing the chemical composition of OM. While AMS provides high-temporal-resolution bulk measurements, the extensive fragmentation during the electron impact (EI) ionization makes the characterization of OM components limited. The analysis of aerosols collected on PTFE filters using MIR, on the other hand, provides functional group (FG) 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 to achieve a better understanding of the AMS spectra and the OM chemical evolution by 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 (HR-TOF) AMS measured the bulk chemical composition of fine PM. 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 influential functional groups contributing to AMS OM mass for different aerosol sources and aging processes. We also identified the key mass fragments resulting from each functional group for the complex OM generated from biomass and fossil fuel combustion. Finally, we developed a statistical model that enables estimation of the high-time-resolution functional group composition of OM using collocated AMS and MIR measurements. Using this approach, AMS spectra can be used to interpolate the functional group measurements by MIR, allowing us to better understand the evolution of OM during the aging process.