9. Exploring the Use of Renewable Resources for Processing of Deep-Sea Minerals

Assessment of deep-sea polymetallic nodules processing technologies has assumed renewed importance in the context of the current thrust for supply of metals such as Cu, Ni, Co, and Mn that are required for clean energy transition processes. Because of similarity of suggested nodules processing operations to nickel laterite processing from land ores, the energy intensity of the operations is high. Process energy consumption data are scarce although process energy costs have been referred. The chapter elaborates an approach for minimum gross energy estimation (GER) and subsequent CO₂ emissions based on key process steps of existing flow sheets based on both foreground and background processes. For example, for hydrometallurgical processes, estimated emissions for slurry heating may vary between 0.11 T CO₂/T and 0.34 T CO₂/T nodules, with addition of 0.25 T CO₂/T nodules for downstream process using electricity to produce metals and a marketable manganese slag product. Key process emission for pyrometallurgical process is estimated at 0.67 T CO₂/T nodules. The chapter examines the possibilities of lowering such process emissions by replacing fossil fuel-based reductants with less carbon intensive inputs such as methane and renewable hydrogen, recycling CO₂ and other innovative options of using renewable energy. For hydrometallurgical flow sheets, minimizing reagent recycle such as ammonia, use of lower temperature sulfuric acid leach, combination of multiple input reactants are the possible options. Use of grid electricity with lower emission value and use of renewable electricity such as hydropower for meeting electrical energy requirements will play important role in future plant flow sheet design. The chapter provides estimates of energy and emission values for integration of renewable energy options for existing flow sheets. Although there is considerable potential for use of renewable energy for a hypothetical polymetallic nodules plant design, additional data based on industry parallels/experiments need to be generated.