Carbon on the Ocean Surface: Temporal and Geographical Investigation

ACS EARTH AND SPACE CHEMISTRY(2023)

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摘要
The sea surface nanolayer (SSnL) is enriched with lipids and proteins; working together, these macromolecules create a unique region between the atmosphere and ocean. Lipids and proteins affect the ocean's surface chemistry, which causes surface tension suppression. Carbon enrichment is ultimately reflected in organic sea spray aerosols and wave damping mechanisms that impact micrometeorology. In the present work, we calculate and examine carbon in the SSnL with a global analysis of carbon that incorporates organic surfactant dynamics. Our carbon estimates are based on chlorophyll distributions deduced from Energy Exascale Earth System Model output data. We assume that chlorophyll can approximate phytoplankton and that phytoplankton are primary contributors to the dissolved organic carbon (DOC) pool. The model calculates the carbon concentration from phytoplankton and zooplankton concentrations, fits a Langmuir isotherm to determine fractional surface coverage, and converts from the fractional coverage to a mass using surface excess to estimate carbon in the SSnL. Organic geochemical diversity of the ocean surface is evidenced by monthly variability and global differences among carbon averages. The model is an estimation of carbon because of the limited data for carbohydrate co-adsorption and molecular behavior of the DOC and particulate organic carbon (POC) pool, but our results can be used as a benchmark throughout future works. Our results reveal large seasonal shifts across the major biomes and among regional interfacial totals. However, the total mass of similar to 10(-4) gigatons does not change significantly throughout the year. We propose based on our results that adsorptive equilibria control the organic content of the nanolayer. To the best of our knowledge, these calculations constitute the first example of SSnL organic carbon integrations performed on a planetary scale.
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关键词
ocean surface chemistry,sea surface nanolayer (SSnL),surfactants,proteins,lipids,global models
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