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International audience; 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, NO3- and NH4+, 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.

A cloud water sample collected at the puy de Dôme observatory (PUY) has been incubated under dark conditions, with its endogenous microbiota at two different temperatures (5 and 15 °C), and the change in the molecular organic composition of this sample was analyzed by Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). Microorganisms were metabolically active and strongly modified the dissolved organic matter since they were able to form and consume many compounds. Using Venn diagrams, four fractions of compounds were identified: (1) compounds consumed by microbial activity; (2) compounds not transformed during incubation; (3) compounds resulting from dark chemistry (i.e., hydrolysis and Fenton reactions) and, finally, (4) compounds resulting from microbial metabolic activity. At 15 °C, microorganisms were able to consume 58% of the compounds initially present and produce 266 new compounds. For this cloud sample, the impact of dark chemistry was negligible. Decreasing the temperature to 5 °C led to the more efficient degradation of organic compounds (1716 compounds vs. 1094 at 15 °C) but with the less important production of new ones (173). These transformations were analyzed using a division into classes based on the O/C and H/C ratios: lipid-like compounds, aliphatic/peptide-like compounds, carboxylic-rich alicyclic molecule (CRAM)-like structures, carbohydrate-like compounds, unsaturated hydrocarbons, aromatic structures and highly oxygenated compounds (HOCs). Lipid-like, aliphatic/peptide-like and CRAMs-like compounds were the most impacted since they were consumed to maintain the microbial metabolism. On the contrary, the relative percentages of CRAMs and carbohydrates increased after incubation.

High resolution mass spectrometry (HRMS) can resolve thousands of compounds in complex mixtures such as natural organic matter. However, HRMS is seldom sufficient to fully resolve the molecular heterogeneity of Humus in the soil matrix, especially if no preliminary simplification of Humus complexity is applied and if a single ionization technique is used. Here we show that HRMS, when applied with both photoionization (APPI) and electrospray ionization (ESI) and combined with the extensive molecular simplification provided by a humeomic fractionation, significantly increases identification of the molecular composition of soil Humus. Different sequential extractions separate the soil Humeome in three organosoluble fractions (ORG1-3) and two hydrosoluble fractions (AQU2 and RESOM), which showed distinct molecular characteristics. The ORG fractions were particularly homogeneous and rich in alkyl compounds including unsaturated hydrocarbons and lipid compounds found mainly in ORG 1 and ORG 3, but also aromatic compounds comprising lignin-like molecules and condensed structures mainly detected in ORG2. The AQU2 fractions revealed greater complexity and heterogeneity due to the simultaneous detection of sugars, amino sugars, tannins and N-containing compounds not detectable in appreciable concentrations in other fractions. The most recalcitrant RESOM fraction contained highly reduced molecules and condensed structures. The combined use of APPI and ESI showed a marked selectivity in the detection of chemically different molecules separated in each fraction, thereby enhancing their molecular characterization. Specifically, APPI tended to ionize less oxidized and N-containing molecules, and compounds with high concentrations of unsaturation or aromatics, while ESI was more prone to detect highly oxidized compounds consisting of large O/C ratios. Our findings indicate that the combination of a soil Humeome fractionation with a detailed high resolution characterization of differently ionized molecules in the separated fractions enables a far deeper understanding of the molecular composition of soil Humus and the comprehension of its environmental reactivity.

A statistical analysis of 295 cloud samples collected at the Puy de D&ocirc, me station in France (PUY), covering the period 2001&ndash, 2018, was conducted using principal component analysis (PCA), agglomerative hierarchical clustering (AHC), and partial least squares (PLS) regression. Our model classified the cloud water samples on the basis of their chemical concentrations and of the dynamical history of their air masses estimated with back-trajectory calculations. The statistical analysis split our dataset into two sets, i.e., the first set characterized by westerly air masses and marine characteristics, with high concentrations of sea salts and the second set having air masses originating from the northeastern sector and the &ldquo, continental&rdquo, zone, with high concentrations of potentially anthropogenic ions. It appears from our dataset that the influence of cloud microphysics remains minor at PUY as compared with the impact of the air mass history, i.e., physicochemical processes, such as multiphase reactivity.

International audience; An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Secondary organic aerosols (SOA) produced in the atmosphere from sequential oxidation of biogenic or anthropogenic volatile organic compounds (VOC) represent a significant part of the atmospheric organic aerosol. Aerosol particles can act as cloud condensation nuclei or can be scavenged by cloud droplets, where organic carbon undergo chemical and biological transformations. Due to its high complexity, a nontargeted analysis by FT-ICR MS (Fourier-transform ion cyclotron resonance mass spectrometry) has been used to characterize the dissolved organic matter at a molecular level. SOA compounds have been detected in six aqueous samples collected in 2017 at the Puy de Dome station (PUY, France). SOA tracers, produced by VOC oxidation in environmental chambers or in ambient air and characterized in previous studies by mass spectrometry, were searched by FT-ICR MS in cloudwaters. Results clearly indicate the presence of oxidation products of isoprene, α- and β-pinene, and other monoterpenes and sesquiterpenes. I...

International audience; Cloud droplets contain dynamic and complex pools of highly heterogeneous organic matter, resulting from the dissolution of both water-soluble organic carbon in atmospheric aerosol particles and gas-phase soluble species, and are constantly impacted by chemical, photochemical, and biological transformations. Cloud samples from two summer events, characterized by different air masses and physicochemical properties, were collected at the Puy de Dôme station in France, concentrated on a strata-X solid-phase extraction cartridge and directly infused using electrospray ionization in the negative mode coupled with ultrahigh-resolution mass spectrometry. A significantly higher number (n = 5258) of monoisotopic molecular formulas, assigned to CHO, CHNO, CHSO, and CHNSO, were identified in the cloud sample whose air mass had passed over the highly urbanized Paris region (J1) compared to the cloud sample whose air mass had passed over remote areas (n = 2896; J2). Van Krevelen diagrams revealed that lignins/CRAM-like, aliphatics/proteins-like, and lipids-like compounds were the most abundant classes in both samples. Comparison of our results with previously published data sets on atmospheric aqueous media indicated that the average O/C ratios reported in this work (0.37) are similar to those reported for fog water and for biogenic aerosols but are lower than the values measured for aerosols sampled in the atmosphere and for aerosols produced artificially in environmental chambers.

Concentrations of 33 metal elements were determined by ICP-MS (Inductively Coupled Plasma Mass Spectrometry) analysis for 24 cloud water samples (corresponding to 10 cloud events) collected at the puy de Dôme station. Clouds present contrasted chemical composition with mainly marine and continental characteristics; for some cloud events, a further anthropogenic source can be superimposed on the background level. In this context, measurements of trace metals may help to evaluate the impact of anthropogenic and natural sources on the cloud and to better discriminate the origin of the air masses. The metal concentrations in the samples are low (between 16.4 µg L−1 and 1.46 mg L−1). This could be explained by the remoteness of the puy de Dôme site from local sources. Trace metals are then used to confirm and refine a previous sample classification. A principal component analysis (PCA) using the pH value and the concentrations of Cl−, NO3−, SO42−, Na+ and NH4+ is performed considering 24 cloud samples. This first analysis shows that 18 samples are of marine origin and 6 samples are classified as continental. The same statistical approach is used adding trace metal concentration. Zn and Mg elements are the most abundant trace metals for all clouds. A higher concentration of Cd is mainly associated to clouds from marine origins. Cu, As, Tl and Sb elements are rather found in the continental samples than in the marine ones. Mg, V, Mn and Rb elements mainly found in soil particles are also more concentrated in the samples from continental air mass. This new PCA including trace metal confirms the classification between marine and continental air masses but also indicates that one sample presenting low pH and high concentrations of SO42−, Fe, Pb and Cu could be rather attributed to a polluted event.