A significant challenge facing mankind is climate change driven by CO2 emissions from human activities. CO2 concentrations would be 50% higher than they already are if it was not for the ocean’s Biological Pump (BP), an important component of Earth’s carbon cycle. The BP starts with the production of organic matter by unicellular plants in the surface ocean. A fraction of this carbon sinks into the dark ocean below 1000 m depth, where it can be stored for 1000 years, contributing significantly to maintaining the air-sea balance of CO2. However, the current global estimates of the BP storage have a large uncertainty and vary up from 5 to 20 Gt C yr-1. The problem of CO2 emissions is a global problem, and understanding the role of the oceans in sequestering part of that CO2 is crucial to society’s understanding of the problem and in political decision-making. In Andalucía we must take a leading role in the world scenario, considering that due to its geographical location it will specially suffer the climate global changes.

POC flux, i.e. carbon export below the productive zone, is a key parameter in the study and quantification of the BP and climate predictions and models, and we will be presenting the first platform sharing global POC flux data, that will allow the community to have a systematic approach to the collection and use of these crucial data. For that, we will also build an observation platform of 234Th data in Andalucía coastal and marine environment. This is a well-established technique that has been used for more than 30 years to estimate POC fluxes, however, DEPOCARBON approach proposes the application of state-of-the-art, innovative new marine techniques.

It will include, for the first time, the automatization of the processes and calculations that lead to POC flux calculation from 234Th measurements: collecting the data, storing them into a universally usable format and analysing automatically the available large amount of data, through big data techniques. Our final aim is digitalize the results from more than 56 600 data points to create an open access platform of global carbon export data. Furthermore, the dense collection of data made available in the new platform would be re-worked using artificial intelligence, machine learning algorithms, to build a predictive tool for carbon export. We finally aim to convert this carbon export platform in a focal point for the scientific community, not only for sharing but also contributing with data, coordinated with other platforms in the most proficient way.