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Oceans emit large quantities of dimethyl sulfide (DMS) to the marine atmosphere. The oxidation of DMS leads to the formation and growth of cloud condensation nuclei (CCN) with consequent effects on Earth’s radiation balance and climate. The quantitative assessment of the impact of DMS emissions on CCN concentrations necessitates a detailed description of the oxidation of DMS in the presence of existing aerosol particles and clouds. In the unpolluted marine atmosphere, DMS is efficiently oxidized to hydroperoxymethyl thioformate (HPMTF), a stable intermediate in the chemical trajectory toward sulfur dioxide (SO 2 ) and ultimately sulfate aerosol. Using direct airborne flux measurements, we demonstrate that the irreversible loss of HPMTF to clouds in the marine boundary layer determines the HPMTF lifetime ( τ HPMTF < 2 h) and terminates DMS oxidation to SO 2 . When accounting for HPMTF cloud loss in a global chemical transport model, we show that SO 2 production from DMS is reduced by 35% globally and near-surface (0 to 3 km) SO 2 concentrations over the ocean are lowered by 24%. This large, previously unconsidered loss process for volatile sulfur accelerates the timescale for the conversion of DMS to sulfate while limiting new particle formation in the marine atmosphere and changing the dynamics of aerosol growth. This loss process potentially reduces the spatial scale over which DMS emissions contribute to aerosol production and growth and weakens the link between DMS emission and marine CCN production with subsequent implications for cloud formation, radiative forcing, and climate. 

Dimethyl sulfide (DMS), emitted from the oceans, is the most abundant biological source of sulfur to the marine atmosphere. Atmospheric DMS is oxidized to condensable products that form secondary aerosols that affect Earth’s radiative balance by scattering solar radiation and serving as cloud condensation nuclei. We report the atmospheric discovery of a previously unquantified DMS oxidation product, hydroperoxymethyl thioformate (HPMTF, HOOCH 2 SCHO), identified through global-scale airborne observations that demonstrate it to be a major reservoir of marine sulfur. Observationally constrained model results show that more than 30% of oceanic DMS emitted to the atmosphere forms HPMTF. Coincident particle measurements suggest a strong link between HPMTF concentration and new particle formation and growth. Analyses of these observations show that HPMTF chemistry must be included in atmospheric models to improve representation of key linkages between the biogeochemistry of the ocean, marine aerosol formation and growth, and their combined effects on climate. 

Cloud condensation nuclei (CCN) are mediators of aerosol‐cloud interactions, which contribute to the largest uncertainty in climate change prediction. Here, we present a machine learning (ML)/artificial intelligence (AI) model that quantifies CCN from model‐simulated aerosol composition, atmospheric trace gas, and meteorological variables. Comprehensive multi‐campaign airborne measurements, covering varied physicochemical regimes in the troposphere, confirm the validity of and help probe the inner workings of this ML model: revealing for the first time that different ranges of atmospheric aerosol composition and mass correspond to distinct aerosol number size distributions. ML extracts this information, important for accurate quantification of CCN, additionally from both chemistry and meteorology. This can provide a physicochemically explainable, computationally efficient, robust ML pathway in global climate models that only resolve aerosol composition; potentially mitigating the uncertainty of effective radiative forcing due to aerosol‐cloud interactions (ERF_aci) and improving confidence in assessment of anthropogenic contributions and climate change projections.

 

Acetone is one of the most abundant oxygenated volatile organic compounds (VOCs) in the atmosphere. The oceans impose a strong control on atmospheric acetone, yet the oceanic fluxes of acetone remain poorly constrained. In this work, the global budget of acetone is evaluated using two global models: CAM‐chem and GEOS‐Chem. CAM‐chem uses an online air‐sea exchange framework to calculate the bidirectional oceanic acetone fluxes, which is coupled to a data‐oriented machine‐learning approach. The machine‐learning algorithm is trained using a global suite of seawater acetone measurements. GEOS‐Chem uses a fixed surface seawater concentration of acetone to calculate the oceanic fluxes. Both model simulations are compared to airborne observations from a recent global‐scale, multiseasonal campaign, the NASA Atmospheric Tomography Mission (ATom). We find that both CAM‐chem and GEOS‐Chem capture the measured acetone vertical distributions in the remote atmosphere reasonably well. The combined observational and modeling analysis suggests that (i) the ocean strongly regulates the atmospheric budget of acetone. The tropical and subtropical oceans are mostly a net source of acetone, while the high‐latitude oceans are a net sink. (ii) CMIP6 anthropogenic emission inventory may underestimate acetone and/or its precursors in the Northern Hemisphere. (iii) The MEGAN biogenic emissions model may overestimate acetone and/or its precursors, and/or the biogenic oxidation mechanisms may overestimate the acetone yields. (iv) The models consistently overestimate acetone in the upper troposphere‐lower stratosphere over the Southern Ocean in austral winter. (v) Acetone contributes up to 30–40% of hydroxyl radical production in the tropical upper troposphere/lower stratosphere.