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This study explores the potential contribution of secondary production of OH radicals in aerosols and cloud/fog conditions arising from brown carbon (BrC) triplet state chemistry. For this purpose, extracts of brown carbon from atmospheric aerosols from Grenoble, France, were analyzed for their ability to produce triplet states from the degradation of a common triplet state probe, 2,4,6-trimethylphenol (TMP). This ability of brown carbon to produce triplet states was compared to that of three photosensitizers, where it was found that vanillin (VL) showed a similar rate of degradation of the probe and was hence chosen as an alternative to BrC in aqueous aerosols to investigate OH formation from triplet states. The rates of OH formation from the triplet states were compared to those from nitrate anions (NO3−) and hydrogen peroxide (H2O2), which are well-known sources of OH radicals in the aqueous phase, and a species that is structurally similar to VL, 4-hydroxybenzaldehyde (4HB). VL and 4HB both showed a 1–2 orders of magnitude higher rate of secondary OH formation than NO3−, while it was similar or one order of magnitude smaller than H2O2. To evaluate the influence of the different OH radical sources in aqueous aerosols and cloud/fog conditions, the concentrations of the species were summarized from the literature. Considering the concentrations of HULISs in aerosols, the rates of secondary OH formation from BrC triplet states could potentially represent a significant source of OH in the atmospheric aqueous phase under some circumstances. This study shows the relevance of further investigations into the role of triplet states in impacting atmospheric oxidative capacity and studying other effects of triplet states in aerosols, a field that is, until now, still not fully understood.

The objective of this research was to evaluate the role of atmospheric microorganisms in chemical transformations occurring within clouds. To achieve this objective, we measured in the laboratory the rates of biodegradation for four chemical compounds of interest in atmospheric chemistry (formic and acetic acids, formaldehyde and hydrogen peroxide). We implemented them in an explicit model of cloud chemistry simulating the exchange processes between air and droplets and chemical reactivity in both phases. The biodegradation rates were not kept constant; rather, they depended on the concentration of the four targeted species. For this purpose, a series of incubation experiments were performed in the laboratory with microbial strains isolated from cloud water by modulating the initial concentration of the substrate and ambient temperature (5 °C and 17 °C). Different simulations were carried out to investigate the role of biological activity in contrasting environmental conditions (season, day/night). Sensitivity tests were also performed on parameters controlling the chemical reactivity and exchanges between phases such as the cloud liquid water content or acidity. Analysis revealed that biodegradation in the aqueous phase was competitive with the abiotic processes of transformations for the four compounds, especially in summer (up to 94% in terms of relative contribution). The concentration of formic acid exerted the most significant impact in both the aqueous phase and in terms of total concentration in the cloud. In summer, biodegradation had a strong impact, during both day and night, on formic acid concentration, inducing a loss of 23 and 65%, respectively. At night, in summer, biodegradation was the main sink for formic acid, acetic acid and formaldehyde (81, 56 and 98%, respectively). Sensitivity tests (pH and liquid water content – LWC) further demonstrated the added value of modulating the biodegradation efficiency according to the concentrations of each compound. For instance, the decrease of formic acid aqueous concentration due to biodegradation is between 50 and 70% more important when LWC is reduced by a factor of 3.

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.

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. Clouds were sampled on top of the Puy de Dôme mountain in France to study their chemical composition. Cloud droplets were collected by impaction with samplers specifically designed for that. The seven samples, collected from May to October 2018, were characterized by a high‐resolution mass spectrometry method, revealing thousands of organic compounds carrying carbon, hydrogen, nitrogen, sulfur, and phosphorus atoms, belonging to both natural and anthropogenic sources. Using a recently developed classification method, organic compounds were shared into classes based on their respective numbers of elements to lipids, proteins, amino sugars, carbohydrates, and aromatic compounds. To better understand the variability of the molecular fingerprints of each collected sample, we applied statistical analysis which enabled us to link the history of the air‐masses calculated with a three‐dimensional kinematic trajectory code and the chemical composition of the clouds. For example, proteins were related to the time spent by the air mass above continental surfaces at low altitude (in the boundary layer). Amino sugars and aromatic compounds were strongly correlated with anthropogenic sources. Finally, lipids were correlated with the time spent over the ocean in the free troposphere, confirming potential long‐range transport from marine source. Analyzing cloud water by high resolution‐mass spectrometry shows the presence of non‐polar, semi‐polar and phosphorus‐containing compoundsA multidimensional stoichiometric constraint classification was applied to assign molecular formulas according to six main categoriesA statistical study highlights correlations between these categories and air mass history, such as proteins with continental boundary layer Analyzing cloud water by high resolution‐mass spectrometry shows the presence of non‐polar, semi‐polar and phosphorus‐containing compounds A multidimensional stoichiometric constraint classification was applied to assign molecular formulas according to six main categories A statistical study highlights correlations between these categories and air mass history, such as proteins with continental boundary layer

Chemical processes in clouds and fogs can substantially alter atmospheric oxidant budgets and lead to aerosol mass formation. However, many regional and global models do not include detailed aqueous‐phase chemical mechanisms due to the (a) lack of complete understanding of the chemical processes and (b) computational burden of adding constituents. Current gas‐aqueous chemistry 0‐dimensional models were evaluated in a cloud‐chemistry box model intercomparison based on a mid‐September 2016 cloud chemistry event at Whiteface Mountain, New York. Multiphase mechanisms in the five participating models ranged from those appropriate for 3‐d models to highly complex with thousands of reactions. This study focused on oxidant levels in both phases and aqueous‐phase sulfate and organic acid formation. Comparison of gas‐phase‐only chemistry gives very similar oxidant predictions at night but shows significant differences during daytime with the hydroxyl radical (OH) variability of about an order of magnitude. The variability in the model results increases substantially with aqueous chemistry due to different Henry's Law constants, aqueous‐phase reaction rate constants, and chemical mechanisms. Using a prescribed liquid water content and pH value of 4.5, modeled aqueous OH, aldehyde, and organic acid concentrations differ by over an order of magnitude in daytime. Simulations were also conducted at a pH = 5.1, predicted variable pH, and with added transition metal ion chemistry. While we compare predicted and measured inorganic anions and water‐soluble organic carbon, we cannot do so for aqueous‐phase oxidant concentrations due to the lack of measurements. We highlight a need for recommended equilibrium and aqueous‐phase rate constants. Accurate description of cloud chemistry is needed in models used to predict air quality and climate. A comprehensive international cloud box model intercomparison with physical and chemical observational constraints from mountain top sampling highlights the need for a concerted effort to develop robust aqueous‐phase chemical mechanisms. Prediction of some key species differ among the models by orders of magnitude. We investigate the underlying, fundamental chemical explanations for the discrepancy as a diagnosis to understand the chemical parameters most in need of further investigation efforts. Five box models participated in a cloud chemistry intercomparison representing a case at Whiteface Mountain ObservatoryModel results were often quite different indicating a need for recommended equilibria and aqueous‐phase reaction rate constantsComparisons of simple to detailed chemistry schemes show need for development of effective simplified organic aqueous chemistry schemes Five box models participated in a cloud chemistry intercomparison representing a case at Whiteface Mountain Observatory Model results were often quite different indicating a need for recommended equilibria and aqueous‐phase reaction rate constants Comparisons of simple to detailed chemistry schemes show need for development of effective simplified organic aqueous chemistry schemes

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