Combined organic and inorganic source apportionment on yearlong ToF-ACSM dataset at a suburban station in Athens

Abstract

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 ambient organic aerosol (OA) properties. Although OA constitutes a major fraction of ambient aerosol, its properties are determined to a great extent by the mixing characteristics of both organic and inorganic components of ambient aerosol. This work applies a new methodology to a year-long ACSM dataset to assess the sources of organic and total non-refractory species in the Athens background aerosol and provides insights into the interactions between organic and inorganic species. The use of innovative tools for applying positive matrix factorization (PMF, rolling window) enables the study of the temporal variability of the contribution of these sources and seasonal changes in their composition. The mass spectra of both organic and inorganic aerosol were obtained by a time-of-flight aerosol mass spectrometer (ToF-ACSM) for PMF analysis. The results revealed five factors when organic aerosol was analysed separately. Three of them were primary OA factors: hydrocarbon-like organic aerosol (HOA), cooking-related organic aerosol (COA) and biomass burning organic aerosol (BBOA). 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). When a combined organic and inorganic aerosol matrix was analysed, two additional factors were identified that were mainly composed of ammonium sulfate (83.5 %) and ammonium nitrate (73 %). Moreover, two secondary factors were resolved, containing both organics and inorganics and were named more (MOA) and less oxidized aerosol (LOA). The relative contributions on a yearly average of these factors were HOA 7 %, COA 9 %, BBOA 3 %, ammonium nitrate 3 %, ammonium sulfate 28 %, MOA 24 % and LOA 26 %.

Annual cycle of hygroscopic properties and mixing state of the suburban aerosol in Athens, Greece

“…S2), as well as at early afternoon (15:00-20:00 UTC+2). At the DEM station, the 30 nm particles are primarily related to traffic emissions and to a lesser extent to new particle formation (Vratolis et al, 2019;Zografou et al, 2022). This was also confirmed in the present study by the cluster analysis of the number size distributions.…”

“…Particle number size distributions vary across different regions and environments (Rose et al, 2021), and the structure of their patterns can be used as an indicator of the possible aerosol particle emission sources and formation processes. At the DEM station, secondary aerosol formation, mostly related to sulfate and organics (Kostenidou et al, 2015;Tsiflikiotou et al, 2019), and traffic-related emissions are the main sources of ambient aerosol (Zografou et al 2022), while biomass burning also constitutes a major source in winter (Vratolis et al, 2019;Bousiotis et al, 2021). In the present study, five clusters were identified which represent a combination of the major particle emission sources and formation/transformation processes.…”

Towards a Better Understanding of Fine Pm Sources: Online and Offline Datasets Combination in a Single Pmf

“…The Approach 1 results already represent an improvement with respect to the OA SA, which led to the identification of five OA sources: HOA, COA, BBOA, LO-OOA and MO-OOA as reported by Via et al (2021). The addition of the inorganic NR-PM 1 and BC species already proved advantageous in Zografou et al (2022) by identifying an additional factor. Similarly, the present SA solution consists of 6 factors, 3 purely primary, 2 secondary and a potentially mixed factor (Figure S4).…”

Oxidative potential apportionment of atmospheric PM1: A new approach combining high-sensitive online analysers for chemical composition and offline OP measurement technique

“…Some others performed source apportionment by including both organic and inorganic fractions from the AMS (Äijälä et al, 2019;McGuire et al, 2014;Sun et al, 2012), improving the factors resolution and their chemical nature. More recently, Zografou et al (2022) performed PMF analysis on combined organic and inorganic year-long dataset from a ToF-ACSM. Tong et al (2022) combined into a single dataset AMS and extractive electrospray ionisation time-of-flight mass spectrometer (EESI-ToF) measurements providing an optimised identification and quantification of the organic factors, more specifically the SOA fraction.…”