Assessing global carbon sequestration and bioenergy potential from microalgae cultivation on marginal lands leveraging machine learning

This comprehensive study unveils the vast global potential of microalgae as a sustainable bioenergy source, focusing on the utilization of marginal lands and employing advanced machine learning techniques to predict biomass productivity. By identifying approximately 7.37 million square kilometers of marginal lands suitable for microalgae cultivation, this research uncovers the extensive potential of these underutilized areas, particularly within equatorial and low-latitude regions, for microalgae bioenergy development. This approach mitigates the competition for food resources and conserves freshwater supplies. Utilizing cutting-edge machine learning algorithms based on robust datasets from global microalgae cultivation experiments spanning 1994 to 2017, this study integrates essential environmental variables to map out a detailed projection of potential yields across a variety of landscapes. The analysis further delineates the bioenergy and carbon sequestration potential across two effective cultivation methods: Photobioreactors (PBRs), and Open Ponds, with PBRs showcasing exceptional productivity, with a global average daily biomass productivity of 142.81mgL