Organic aerosol source apportionment in Zurich using an extractive electrospray ionization time-of-flight mass spectrometry (EESI-TOF): Part II, biomass burning influences in winter

Abstract

<p><strong>Abstract.</strong> Real-time, in situ molecular composition measurements of the organic fraction of fine particulate matter (PM<sub>2.5</sub>) remain challenging, hindering a full understanding of the climate impacts and health effects of PM<sub>2.5</sub>. In particular, the thermal decomposition and ionization-induced fragmentation affecting current techniques has limited a detailed investigation of secondary organic aerosol (SOA), which typically dominates OA. Here we deploy a novel extractive electrospray ionization time-of-flight mass spectrometer (EESI-TOF-MS) during winter 2017 in downtown Zurich, Switzerland, which overcomes these limitations, together with an Aerodyne high resolution time of flight aerosol mass spectrometer (HR-TOF-AMS) and supporting instrumentation. Positive matrix factorization (PMF) implemented within the Multilinear Engine (ME-2) was applied to the EESI-TOF data to quantify the primary and secondary contributions to OA. An 11-factor solution was selected as the best representation of the data, including 5 primary and 6 secondary factors. Primary factors showed influence from cooking, cigarette smoke, biomass burning (2 factors) and a special local unknown event occurred only during two nights. Secondary factors were affected by biomass burning (3 factors, distinguished by temperature and/or wind direction), organonitrates, monoterpene oxidation, and undetermined regional processing, in particular the contributions of wood combustion. While the AMS attributed slightly over half the OA mass to SOA but did not identify its source, the EESI-TOF showed that most (> 70 %) of the SOA derived from biomass burning. Together with significant contributions from less aged biomass burning factors identified by both AMS and EESI-TOF, this firmly establishes biomass burning as the single most important contributor to OA mass at this site during winter. High correlation was obtained between EESI-TOF and AMS PMF factors where specific analogues existed, as well as between total signal and POA/SOA apportionment. This suggests the EESI-TOF apportionment can be approximately taken at face value, despite ion-by-ion differences in relative sensitivity. The apportionment of specific ions measured by the EESI-TOF (e.g. levoglucosan, nitrocatechol, and selected organic acids), and utilize a cluster analysis-based approach to identify key marker ions for the EESI-TOF factors are investigated. The interpretability of the EESI-TOF results and improved source separation relative to the AMS within this pilot campaign validate the EESI-TOF as a promising approach to source apportionment and atmospheric composition research.</p>

Organic aerosol source apportionment in Zurich using extractive electrospray ionization time-of-flight mass spectrometry (EESI-TOF): Part I, biogenic influences and day/night chemistry in summer

“…On the other hand the H:C ratios are slightly higher for the EESI-TOF measurements with values of ~1.6, ~1.7, and ~1.8 for SOA, CS-OA, and COA, respectively, compared to ~1.3, ~1.4, and ~1.6, respectively for the AMS analysis. Similar results were also observed for winter aerosol in Zurich (Qi et al, 2019) and for aging experiments of wood burning emissions in an environmental chamber (Bertrand et al, in preparation). This could suggest a reduced sensitivity of the EESI-TOF to low H:C compounds (e.g.…”

“…The AMS/EESI-TOF correlation for CS-OA further suggests that even though nicotine does not ionize by adduct formation with Na + , this alternate pathway does not introduce significant nonlinearities in its detection, at least under the conditions encountered in Zurich during summer. Similar performance was obtained for nicotine detection during winter measurements in Zurich (Qi et al, 2019). Note that the slopes retrieved from the linear correlation in Fig.…”

Sources of organic aerosols in Europe: A modelling study using CAMx with modified volatility basis set scheme

“…The underestimation of winter OOA was also found at all the other studied sites (Marseille, Bologna and Paris SIRTA), while the summer OOA showed good agreement with the PMF results ( Fig. 4a and 4d), indicating a possible underestimation of SOA from biomass burning (Gilardoni et al, 2014;Gilardoni et al, 2016;Paglione et al, 2019;Qi et al, 2019). The NEW parameterization improved the OA modelling by increasing winter OOA by 29.3% (SIRTA) to 41.7% (Bologna).…”