Puy de Dôme Station (France): A Stoichiometric Approach to Compound Classification in Clouds
Pascal Renard, Angelica Bianco, Janne Jänis, Timo Kekäläinen, Maxime C. Bridoux, Laurent Deguillaume
Abstract
Abstract Seven cloud water samples were collected from May to October 2018 at the Puy de Dôme station (PUY) in France and analyzed by positive‐ion atmospheric pressure photoionization [(+)APPI] Fourier transform ion cyclotron resonance mass spectrometry. The assigned formulas (ranging from 3,865 to 6,380) were attributed using the multidimensional stoichiometric constraint classification of Rivas‐Ubach et al. (2018, https://doi.org.10.1021/acs.analchem.8b00529 ) to six main categories (RUCs): LipidC, ProteinC, Amino‐sugarC, CarbohydrateC, NucleotideC, and OxyaromaticC. Back trajectories were calculated by the computing atmospheric trajectory tool (CAT) model to obtain information on the air mass history. Partial least square regressions were performed using chemical data, CAT back‐trajectory calculations and FT‐ICR MS data to analyze the environmental variability of the organic sample composition. ProteinC is correlated with the continental surface for air masses transported within the boundary layer, and Amino‐sugarC is strongly correlated with acetate, NO 3 − and NH 4 + , suggesting Anthropogenic sources for amino sugars and proteins. LipidC is correlated with the sea surface for air masses transported within the free troposphere, confirming the long‐range transport of marine biogenic sources. Concerning Oxy‐aromaticC, given the correlations with oxidants and pollutants, as well as anti‐correlations with local influence, we proposed a mechanism of oxidation from remote anthropogenic sources.