Deconvolution of FIGAERO–CIMS thermal desorption profiles using positive matrix factorisation to identify chemical and physical processes during particle evaporation
Authors: Buchholz Angela , Ylisirniö Arttu , Huang Wei , Mohr Claudia , Canagaratna Manjula , Worsnop Douglas R. , Schobesberger Siegfried , Virtanen Annele 
Published: July 2020

Abstract. The measurements of aerosol particles with a filter inlet for gases and aerosols
(FIGAERO) together with a chemical ionisation mass spectrometer (CIMS) yield the overall chemical composition of the particle phase. In addition, the
thermal desorption profiles obtained for each detected ion composition
contain information about the volatility of the detected compounds, which is an
important property for understanding many physical properties like gas–particle
partitioning. We coupled this thermal desorption method with isothermal
evaporation prior to the sample collection to investigate the chemical
composition changes during isothermal particle evaporation and particulate-water-driven chemical reactions in α-pinene secondary organic aerosol (SOA) of three different
oxidative states. The thermal desorption profiles of all detected elemental
compositions were then analysed with positive matrix factorisation (PMF) to
identify the drivers of the chemical composition changes observed during
isothermal evaporation. The keys to this analysis were to use the error matrix
as a tool to weight the parts of the data carrying most information (i.e.
the peak area of each thermogram) and to run PMF on a combined data set of
multiple thermograms from different experiments to enable a direct comparison
of the individual factors between separate measurements. The PMF was able to identify instrument background factors and separate them
from the part of the data containing particle desorption information.
Additionally, PMF allowed us to separate the direct desorption of compounds
detected at a specific elemental composition from other signals with the same
composition that stem from the thermal decomposition of thermally instable
compounds with lower volatility. For each SOA type, 7–9 factors were needed
to explain the observed thermogram behaviour. The contribution of the
factors depended on the prior isothermal evaporation. Decreased
contributions from the factors with the lowest desorption temperatures were observed with increasing isothermal evaporation time. Thus, the factors identified
by PMF could be interpreted as volatility classes. The composition changes
in the particles due to isothermal evaporation could be attributed to the
removal of volatile factors with very little change in the desorption
profiles of the individual factors (i.e. in the respective temperatures of
peak desorption, Tmax). When aqueous-phase reactions took place, PMF
was able to identify a new factor that directly identified the ions affected by
the chemical processes. We conducted a PMF analysis of the FIGAERO–CIMS thermal desorption data for the
first time using laboratory-generated SOA particles. But this method can be applied to, for example, ambient FIGAERO–CIMS measurements as well. There, the PMF analysis of the thermal desorption data identifies organic aerosol (OA) sources (such as biomass burning or oxidation of different precursors) and types, e.g. hydrocarbon-like (HOA) or oxygenated organic aerosol (OOA). This information could also be obtained with the traditional approach, namely the PMF analysis of the mass spectra data integrated for each thermogram. But only our method can also obtain the volatility information for each OA source and type. Additionally, we can identify the contribution of thermal decomposition to the overall signal.