CombiMo:
Combining the sediment geochemistry of molybdenum with machine learning to identify anoxic-sulfidic seafloor environments along the German Baltic Sea coast
- Duration:
- 01.07.2026 - 30.06.2029
- Project coordinated by:
- Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI)
- Contact (IOW):
- Dr. René Friedland
- Funding:
- BMFTR - Bundesministerium für Forschung, Technologie und Raumfahrt
- Partner:
Objectives:
(1) Use existing Mo concentration data and newly acquired Mo isotope data for sediments from Kiel Bight and Schlei Fjord to validate a novel concept, according to which elevated Mo concentrations and seawater-like Mo isotope compositions of surface sediments in the coastal Baltic Sea are indicative of sulfidic conditions at the sediment-water interface.
(2) Acquire Mo concentration and isotope data for well-distributed surface sediments from Flensburg Firth and Mecklenburger Bight.
(3) Train a machine learning approach with the data collected in (1) and (2) to map areas where H2S is intermittently present at the sediment-water interface. Validate the redox-maps at selected sites using a more comprehensive set of pore water and solid phase data.
(1) Use existing Mo concentration data and newly acquired Mo isotope data for sediments from Kiel Bight and Schlei Fjord to validate a novel concept, according to which elevated Mo concentrations and seawater-like Mo isotope compositions of surface sediments in the coastal Baltic Sea are indicative of sulfidic conditions at the sediment-water interface.
(2) Acquire Mo concentration and isotope data for well-distributed surface sediments from Flensburg Firth and Mecklenburger Bight.
(3) Train a machine learning approach with the data collected in (1) and (2) to map areas where H2S is intermittently present at the sediment-water interface. Validate the redox-maps at selected sites using a more comprehensive set of pore water and solid phase data.