Sulfur trioxide (SO) is an important oxide of sulfur and a key intermediate in the formation of sulfuric acid (HSO, SA) in the Earth's atmosphere. This conversion to SA occurs rapidly due to the reaction of SO with a water dimer. However, gas-phase SO has been measured directly at concentrations that are comparable to that of SA under polluted mega-city conditions, indicating gaps in our current understanding of the sources and fates of SO.
View Article and Find Full Text PDFSea spray aerosols (SSA) greatly affect the climate system by scattering solar radiation and acting as seeds for cloud droplet formation. The ecosystems in the Arctic Ocean are rapidly changing due to global warming, and the effects these changes have on the generation of SSA, and thereby clouds and fog formation in this region, are unknown. During the ship-based Arctic Century Expedition, we examined the dependency of forced SSA production on the biogeochemical characteristics of seawater using an on-board temperature-controlled aerosol generation chamber with a plunging jet system.
View Article and Find Full Text PDFSea spray aerosol (SSA) particles strongly influence clouds and climate but the potential impact of ocean microbiota on SSA fluxes is still a matter of active research. Here-by means of in situ ship-borne measurements-we explore simultaneously molecular-level chemical properties of organic matter (OM) in oceans, sea ice, and the ambient PM aerosols along a transect of 15,000 km from the western Pacific Ocean (36°13'N) to the Southern Ocean (75°15'S). By means of orbitrap mass spectrometry and optical characteristics, lignin-like material (24 ± 5 %) and humic material (57 ± 8 %) were found to dominate the pelagic Pacific Ocean surface, while intermediate conditions were observed in the Pacific-Southern Ocean waters.
View Article and Find Full Text PDFAtmospheric aerosols are important drivers of Arctic climate change through aerosol-cloud-climate interactions. However, large uncertainties remain on the sources and processes controlling particle numbers in both fine and coarse modes. Here, we applied a receptor model and an explainable machine learning technique to understand the sources and drivers of particle numbers from 10 nm to 20 μm in Svalbard.
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