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  • 1
    Publication Date: 2023-02-08
    Description: Since around the mid of the 18th century, the global atmospheric carbon dioxide (CO2) concentration has significantly increased due to anthropogenic activities. For 2018, around 11.5 GtC yr−1 were emitted by fossil fuel combustion and cement production, and land use changes. A sink for the atmospheric CO2 is the ocean, which has taken up around 2.6 GtC yr−1 in 2018. The relative good understanding of the current global mean oceanic uptake of anthropogenic CO2 is contrasted by a lack of knowledge how the natural carbon cycle will respond regionally to changes introduced by anthropogenic CO2 emissions, like global warming, ocean acidification or ocean deoxygenation. In view of the central role of the oceanic CO2 sink and its vulnerability to these changes, extensive ocean carbon observations are necessary. Over several years, the Ships of Opportunity (SOOP) network provides high-quality CO2 partial pressure (p(CO2)) data of the surface ocean, and, therefore, forms the backbone of the global observation system for the oceanic CO2 sink. However, to get full insight into the marine CO2 system, at least two of the four measurable carbonate variables are required, which are p(CO2), total alkalinity (AT), dissolved inorganic carbon (CT) and pH. The so far common workaround is the prediction of AT by using established temperature-salinity based parameterizations. However, compared with direct measurements, this procedure leads to higher uncertainties and spatiotemporal biases. Therefore, autonomous SOOP-based AT measurements are of great interest and, in the end, should enhance ocean carbon observations. In order to achieve this enhancement, this thesis goals to provide an example of a successful implementation of a novel autonomous analyzer for seawater AT, the CONTROS HydroFIA TA (-4H-JENA engineering GmbH, Germany), on a Carbon-SOOP station operating in the subpolar North Atlantic (together with fundamental guidelines and recommendations leading to high-quality AT data).
    Type: Thesis , NonPeerReviewed , info:eu-repo/semantics/other
    Format: text
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