Autonomous marine carbon system observations and measurements onboard Boaty McBoatface: Results and analysis from an 8-day mission in the Celtic Sea

Emily Hammermeister,Socratis Loucaides, Efstathios Papadimitriou,Allison Schaap,Martin Arundell, Edward Chaney,Matthew Mowlem

crossref(2023)

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摘要
<p>In a world where the climatic response to human carbon emissions has reached a critical point in time, understanding the ocean&#8217;s role in carbon cycling has become a major focus for scientific observation and intervention. The development of marine autonomous platforms provides observations of higher spatiotemporal resolution, which can be used to further measure, characterize, and model ocean carbon. As a part of the pioneering OCEANIDS programme, novel carbonate chemistry sensors were integrated on the Autosub Long Range (ALR) Autonomous Underwater Vehicle (Boaty McBoatface)<em> </em>and deployed in the Celtic Sea. The project utilized three autonomous Lab-On-Chip (LOC) sensors measuring pH, Total Alkalinity (TA), and Dissolved Inorganic Carbon (DIC). Together, these sensors enable characterisation of the marine carbonate system based on direct <em>in situ</em> measurements. This unprecedented technology has the potential to improve our understanding of the inorganic carbon cycle in the ocean and enable ocean acidification monitoring at a higher spatial and temporal resolution than currently possible. Additionally, it presents a powerful tool for CO<sub>2</sub> leak detection from sub-seafloor carbon captureand storage (CCS) sites and paves the way towards decarbonisation of ocean observations. Preliminary results collected in March 2022 during a multi-day ALR mission in the Celtic Sea from surface waters to 600m depth will be presented. Sensor data will be validated against discrete water samples collected along the ALR&#8217;s track. The performance of the new technology and its potential as an observing tool for ocean CO<sub>2</sub> observations and constraining the marine carbon cycle will be evaluated. Additionally, sensor post-processing analytical techniques and insights will be discussed.</p>
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