Abstract
The current improvements in aerosol mass spectrometers in resolution and sensitivity, and the analytical tools for mass spectra deconvolution, have enabled the in depth analysis of organic aerosol (OA) properties. Although OA constitutes a major fraction of ambient aerosol, the overall aerosol properties are determined by the mixing characteristics of both organic and inorganic contents of ambient aerosol. In the present study, the mass spectra of both organic and inorganic aerosol were obtained by a time–of–flight aerosol mass spectrometer (ToF-ACSM) and further merged into one input matrix for Positive Matrix Factorization (PMF) analysis. The scope of this work was to assess the sources of organic aerosol and total non–refractory species in the suburbs of Athens, check their temporal variation and the interactions between organic and inorganic species, after reaching environmentally reasonable solutions for both matrices. The results revealed five factors in the case of the organic aerosol matrix. Three of them were primary OA factors: hydrocarbon–like (HOA), cooking related (COA) and biomass burning (BBOA), and the remaining two were secondary, less and more oxidized oxygenated organic aerosol (LO-OOA and MO-OOA, respectively). The relative contributions of these factors were HOA 15 %, COA 18 %, BBOA 9 %, MO-OOA 34 % and LO-OOA 24 % (yearly averaged). In the case of the combined aerosol matrix, two additional factors were identified that were mainly composed of ammonium sulfate (83.5 %) and ammonium nitrate (73 %). Moreover, the two secondary factors with both organics and inorganics were named as more (MOA) and less oxidized aerosols (LOA). The relative contributions on a yearly average of these factors were HOA 6 %, COA 9 %, BBOA 6%, Ammonium Nitrate 4 %, Ammonium Sulfate 28 %, MOA 23 % and LOA 24 %. The results showed a variation in secondary aerosols composition of organics and inorganics, mainly in less oxidized aerosol (LOA). This factor was composed primarily of organics during winter (80 %), while both organics and inorganics contributed equally to this factor in spring and summer; and in early autumn this factor presented more sulfate (70 %) than organics. This work presents a new methodology on ACSM data analysis, provides insights on the sources of the non–refractory species of ambient aerosols and using innovative tools for applying PMF (Rolling window) enables the study of the temporal variation of these sources and also the variability of their composition.
Highlights
The adverse effects of atmospheric aerosols on human health and the environment have been addressed by many studies (Ramanathan et al, 2009; Wilson and Suh., 1997; Pope et al, 2000; Jacobson et al, 2001)
The absence of precipitation and the increased production of biogenic volatile organic compounds in the forest near our station (Lappalainen et al, 2009) combined with enhanced photochemical activity may have led to higher formation of secondary organic aerosols (SOAs), resulting in higher organics concentrations (Tables S3, S5)
In comparison to the results reported in a previous study conducted in the centre of Athens (Stavroulas et al, 2019) by the National Observatory of Athens (NOA), the suburban site presented lower concentrations for all NRS in wintertime, which 285 is mainly attributed to the higher anthropogenic emissions generally occur in the urban area of Athens
Summary
The adverse effects of atmospheric aerosols on human health and the environment have been addressed by many studies (Ramanathan et al, 2009; Wilson and Suh., 1997; Pope et al, 2000; Jacobson et al, 2001). One of the latest advances in source apportionment modelling is the 75 rolling window technique (Parworth et al, 2015; Canonaco et al, 2021; Chen et al, 2021; Tobler et al, 2021) that is based on the modelling of a moving period of the initial dataset at each iteration This technique has been found useful in order to examine the temporal variation of the identified factors and especially for the oxygenated organic aerosols, whose chemical footprint can vary in different seasons. A few studies have included in source apportionment schemes both the organic fraction and the inorganics from mass spectrometric instruments (Sun et al, 2012; McGuire et al, 2014; Hao et al, 2014; 80 Äijälä et al, 2019) All of these studies revealed that the inclusion of inorganics in SA studies improves both the solution obtained and the understanding of atmospheric processes and mixing between species. The validity of the retrieved factors was assessed based on the model residuals, the statistical uncertainty of each one of the retrieved solutions 90 and their correlation with specific external data
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