Abstract
Abstract. An intercomparison of different aerosol chemical characterization techniques has been performed as part of a chamber study of biogenic secondary organic aerosol (BSOA) formation and aging at the atmosphere simulation chamber SAPHIR (Simulation of Atmospheric PHotochemistry In a large Reaction chamber). Three different aerosol sampling techniques – the aerosol collection module (ACM), the chemical analysis of aerosol online (CHARON) and the collection thermal-desorption unit (TD) were connected to proton transfer reaction time-of-flight mass spectrometers (PTR-ToF-MSs) to provide chemical characterization of the SOA. The techniques were compared among each other and to results from an aerosol mass spectrometer (AMS) and a scanning mobility particle sizer (SMPS). The experiments investigated SOA formation from the ozonolysis of β-pinene, limonene, a β-pinene–limonene mix and real plant emissions from Pinus sylvestris L. (Scots pine). The SOA was subsequently aged by photo-oxidation, except for limonene SOA, which was aged by NO3 oxidation. Despite significant differences in the aerosol collection and desorption methods of the PTR-based techniques, the determined chemical composition, i.e. the same major contributing signals, was found by all instruments for the different chemical systems studied. These signals could be attributed to known products expected from the oxidation of the examined monoterpenes. The sampling and desorption method of ACM and TD provided additional information on the volatility of individual compounds and showed relatively good agreement. Averaged over all experiments, the total aerosol mass recovery compared to an SMPS varied within 80 ± 10, 51 ± 5 and 27 ± 3 % for CHARON, ACM and TD, respectively. Comparison to the oxygen-to-carbon ratios (O : C) obtained by AMS showed that all PTR-based techniques observed lower O : C ratios, indicating a loss of molecular oxygen either during aerosol sampling or detection. The differences in total mass recovery and O : C between the three instruments resulted predominantly from differences in the field strength (E∕N) in the drift tube reaction ionization chambers of the PTR-ToF-MS instruments and from dissimilarities in the collection/desorption of aerosols. Laboratory case studies showed that PTR-ToF-MS E∕N conditions influenced fragmentation which resulted in water and further neutral fragment losses of the detected molecules. Since ACM and TD were operated in higher E∕N than CHARON, this resulted in higher fragmentation, thus affecting primarily the detected oxygen and carbon content and therefore also the mass recovery. Overall, these techniques have been shown to provide valuable insight on the chemical characteristics of BSOA and can address unknown thermodynamic properties such as partitioning coefficient values and volatility patterns down to a compound-specific level.
Highlights
Atmospheric organic aerosols (OA) represent a major contribution to submicrometer particulate matter (PM1), playing a key role in climate change and air quality (Kanakidou et al, 2005)
Comparison of the different aerosol chemical characterization techniques to the aerosol mass spectrometer (AMS) and scanning mobility particle sizer (SMPS) was performed by means of linear regression (Fig. 1)
SMPS organic mass concentration was calculated assuming a density of 1.4 g cm−3, a valid assumption for secondary OA (SOA) (Cross et al, 2007), which represented more than 98 % of the mass as observed from AMS
Summary
Atmospheric organic aerosols (OA) represent a major contribution to submicrometer particulate matter (PM1), playing a key role in climate change and air quality (Kanakidou et al, 2005). Due to thousands of individual compounds involved in SOA, the chemical characterization of OA still presents a huge analytical challenge (Goldstein and Galbally, 2007). The ability of these compounds to condense to the particulate phase or partition between the gas and particle phase and their volatility are thermodynamic parameters of interest that determine their atmospheric fate. Various techniques have been established in order to better quantify and chemically characterize SOA (Hallquist et al, 2009) These techniques optimize and compromise for time, size or chemical resolution combined with the percentage of OA mass they can detect. Like the Aerodyne aerosol mass spectrometer (AMS) (Canagaratna et al, 2007), provide high-time-resolution and size-resolved data, while less specific chemical composition information or molecular identification of the OA compounds is acquired
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