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It is a matter of fact that exposure to persistently high concentrations of atmospheric particulate matter (PM) leads to respiratory, cardiovascular, and brain dementia diseases1. Establishing a direct link between the chemical composition of PM and its detrimental health effects could potentially inform policies to act on the sources of specific harmful compounds. Unfortunately, PM is composed of thousands of organic compounds, and for most of them, their sources, molecular structures, and fates are unknown2. Significant progress in investigating organic particles is successfully achieved by the application of ultra-high-resolution mass spectrometry, which allows for the determination of the exact mass of unknown substances3. Finally, non-target analysis leads to the assignment of molecular formulae of organic compounds, which is the first step in identification and understanding their behavior in the atmosphere4.Thus, we analyzed the fine fraction of PM with a soft ionization technique (heated electrospray ionization) and an Orbitrap mass spectrometer after a separation with an ultrahigh-performance liquid chromatograph. 1-year of PM2.5 samples were collected daily at two sites in the renowned European air pollution hot-spot, i.e. the Po Valley: Milan, the most populated city in the basin, and Schivenoglia, a rural background site representative of the countryside. Using a non-target screening approach, we identified more than 5000 features for each ionization mode, subsequently investigated alongside the meteorological conditions observed throughout the year. The results indicate pronounced seasonality in CHO compounds, with peaks during spring-summertime in both intensity and the number of features. Moreover, sulfur-containing compounds (in negative mode) exhibit a similar pattern, while N-containing compounds contribute significantly to overall intensity during the colder seasons. In the urban site, Milan, nitrogen-containing compounds intensity increased in mid-October, suggesting the influence of biomass burning as a heating source. This is further supported by an increase in mono- and polycyclic aromatic compounds. The CHN-group shows distinct behavior in positive mode: aliphatic compounds exhibit limited seasonality in number, while mono-aromatics experience a drastic increase in intensity (such as aliphatic ones) and number during wintertime. Finally, a detailed investigation of features contributing significantly to overall intensity was conducted for each site. This highlights variability in the chemical composition of the organic particle phase, and hypotheses regarding their identity were formulated based on their MS2 fragmentation spectra matches with the available libraries such as mzCloud and the Aerosolomic database5.1 Puris, E., et al. (2022). Air pollution exposure increases ABCB1 and ASCT1 transporter levels in mouse cortex. Environ Toxicol Pharmacol.2 Lpez, A., et al. (2022). Identification of Unknown Substances in Ambient Air (PM10), Profiles and Differences between Rural, Urban and Industrial Areas. Toxics3 Ma, J., et al. (2022). Nontarget Screening Exhibits a Seasonal Cycle of PM 2.5 Organic Aerosol Composition in Beijing. Environ. Sci. Technol.4 Nozire, B., et al. (2015) The Molecular Identification of Organic Compounds in the Atmosphere: State of the Art and Challenges. Chem. Rev.5 Thoma, M., et al. (2022). Mass spectrometry-based Aerosolomics: a new approach to resolve sources, composition, and partitioning of secondary organic aerosol. Atmos. Meas. Tech.
D’Angelo et al. (Fri,) studied this question.