Abstract
Abstract. Carbonaceous aerosols are related to adverse human health effects. Therefore, identification of their sources and analysis of their chemical composition is important. The offline AMS (aerosol mass spectrometer) technique offers quantitative separation of organic aerosol (OA) factors which can be related to major OA sources, either primary or secondary. While primary OA can be more clearly separated into sources, secondary (SOA) source apportionment is more challenging because different sources – anthropogenic or natural, fossil or non-fossil – can yield similar highly oxygenated mass spectra. Radiocarbon measurements provide unequivocal separation between fossil and non-fossil sources of carbon. Here we coupled these two offline methods and analysed the OA and organic carbon (OC) of different size fractions (particulate matter below 10 and 2.5 µm – PM10 and PM2.5, respectively) from the Alpine valley of Magadino (Switzerland) during the years 2013 and 2014 (219 samples). The combination of the techniques gave further insight into the characteristics of secondary OC (SOC) which was rather based on the type of SOC precursor and not on the volatility or the oxidation state of OC, as typically considered. Out of the primary sources separated in this study, biomass burning OC was the dominant one in winter, with average concentrations of 5.36 ± 2.64 µg m−3 for PM10 and 3.83 ± 1.81 µg m−3 for PM2.5, indicating that wood combustion particles were predominantly generated in the fine mode. The additional information from the size-segregated measurements revealed a primary sulfur-containing factor, mainly fossil, detected in the coarse size fraction and related to non-exhaust traffic emissions with a yearly average PM10 (PM2.5) concentration of 0.20 ± 0.24 µg m−3 (0.05 ± 0.04 µg m−3). A primary biological OC (PBOC) was also detected in the coarse mode peaking in spring and summer with a yearly average PM10 (PM2.5) concentration of 0.79 ± 0.31 µg m−3 (0.24 ± 0.20 µg m−3). The secondary OC was separated into two oxygenated, non-fossil OC factors which were identified based on their seasonal variability (i.e. summer and winter oxygenated organic carbon, OOC) and a third anthropogenic OOC factor which correlated with fossil OC mainly peaking in winter and spring, contributing on average 13 % ± 7 % (10 % ± 9 %) to the total OC in PM10 (PM2.5). The winter OOC was also connected to anthropogenic sources, contributing on average 13 % ± 13 % (6 % ± 6 %) to the total OC in PM10 (PM2.5). The summer OOC (SOOC), stemming from oxidation of biogenic emissions, was more pronounced in the fine mode, contributing on average 43 % ± 12 % (75 % ± 44 %) to the total OC in PM10 (PM2.5). In total the non-fossil OC significantly dominated the fossil OC throughout all seasons, by contributing on average 75 % ± 24 % to the total OC. The results also suggested that during the cold period the prevailing source was residential biomass burning while during the warm period primary biological sources and secondary organic aerosol from the oxidation of biogenic emissions became important. However, SOC was also formed by aged fossil fuel combustion emissions not only in summer but also during the rest of the year.
Highlights
The field deployment of the time-of-flight aerosol mass spectrometer (HR-ToF-AMS, Canagaratna et al, 2007) has advanced our understanding of aerosol chemistry and dynamics
The seasonal variation along with the two size-segregated measurements (PM10 and PM2.5) gave insights into the source apportionment, by for example quantifying the resuspension of road dust or asphalt concrete and estimating its contribution to the organic carbon (OC) or by identifying secondary OC (SOC) based on SOC precursors
The non-fossil primary sources were dominating during autumn and winter, with BBOC exhibiting by far the highest concentrations
Summary
The field deployment of the time-of-flight aerosol mass spectrometer (HR-ToF-AMS, Canagaratna et al, 2007) has advanced our understanding of aerosol chemistry and dynamics. The application of positive matrix factorization (PMF, Paatero, 1997) techniques has demonstrated that the collected OA mass spectra contain sufficient information to quantitatively distinguish aerosol sources. The cost and intensive maintenance requirements of this instrument significantly hinder its systematic, long-term deployment as part of a dense network and most applications are limited to few weeks of measurements (Jimenez et al, 2009; El Haddad et al, 2013; Crippa et al, 2013). This information is critical for model validation and policy directives. The Aerodyne aerosol chemical speciation monitors (ACSM, Ng et al, 2011; Fröhlich et al, 2013) were developed as a lowcost, low-maintenance alternative to the AMS; their reduced chemical resolution can limit the factor separation achievable by source apportionment
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