ALBERT

Description: Improving the understanding of the health and climate impacts of PM1 remains challenging and is restricted by the limitations of current measurement techniques. Detailed investigation of secondary organic aerosol (SOA), which is typically the dominating fraction of the organic aerosol (OA), requires instrumentation capable of real-time, in situ measurements of molecular composition. In this study, we present the first ambient measurements by a novel extractive electrospray ionization time-of-flight mass spectrometer (EESI-TOF). The EESI-TOF was deployed along with a high resolution time of flight aerosol mass spectrometer (HR-ToF-AMS) during summer 2016 at an urban location (Zurich, Switzerland). Positive matrix factorization (PMF), implemented within the Multilinear Engine (ME-2), was applied to the data from both instruments to quantify the primary and secondary contributions to OA. From the EESI-TOF analysis, a 6-factor solution was selected as the most representative and interpretable solution for the investigated dataset, including two primary and four secondary factors. The primary factors are dominated by cooking and cigarette smoke signatures while the secondary factors are discriminated according to their daytime (two factors) and nighttime (two factors) chemistry. All four factors showed strong influence by biogenic emissions but exhibited significant day/night differences. Factors dominating during daytime showed predominantly ions characteristic of monoterpene and sesquiterpene oxidation while the nighttime factors included less oxygenated terpene oxidation products, as well as organonitrates which were likely derived from NO3 radical oxidation of monoterpenes. Overall, the signal measured by the EESI-TOF and AMS showed a good correlation. Further, the two instruments were in excellent agreement in terms of both the mass contribution apportioned to the sum of POA and SOA factors and the total SOA signal. However, while the OOA factors separated by AMS analysis exhibited a flat diurnal pattern, the EESI-TOF factors illustrated significant chemical variation throughout the day. The captured variability, inaccessible from AMS PMF analysis, was shown to be consistent with the variations in the physiochemical processes influencing chemical composition and SOA formation. The improved source separation and interpretability of EESI-TOF results suggest it to be a promising approach to source apportionment and atmospheric composition research.