Microbial biosurfactants are surface-active molecules that are naturally produced by a range of microorganisms. They have certain advantages over chemical surfactants, such as lower toxicity, higher biodegradability, anti-tumor, and anti-microbial properties. Sophorolipids (SLs) in particular are one of the most promising biosurfactants, as they hold the largest share of the biosurfactant market. Currently, researchers are developing novel approaches for SL production that utilize renewable feedstocks and advanced separation technologies. However, challenges still exist regarding consumption of materials, enzymes, and electricity, that are primarily fossil based. Researchers lack a clear understanding of the associated environmental impacts. It is imperative to quantify and optimize the environmental impacts associated with this emerging technology very early in its design phase to guide a sustainable scale-up. It is necessary to take a collaborative perspective, wherein life cycle assessment (LCA) experts work with experimentalists, to quantify environmental impacts and provide recommendations for improvements in the novel waste-derived SL production pathways. Studies that have analyzed the environmental sustainability of microbial biosurfactant production are very scarce in literature. Hence, in this work, we explore the possibility of applying LCA to evaluate the environmental sustainability of SL production. A dynamic LCA (dLCA) framework that quantifies the environmental impacts of a process in an iterative manner, is proposed and applied to evaluate SL production. The first traversal of the dLCA was associated with the selection of an optimal feedstock, and results identified food waste as a promising feedstock. The second traversal compared fermentation coupled with alternative separation techniques, and highlighted that the fed-batch fermentation of food waste integrated with the in-situ separation technique resulted in less environmental impacts. These results will guide experimentalists to further optimize those processes, and improve the environmental sustainability of SL production. Resultant datasets can be iteratively used in subsequent traversals to account for technological changes and mitigate the corresponding impacts before scaling up.
Scopus Subject Areas
- Health, Toxicology and Mutagenesis
- Dynamic life cycle assessment
- Feedstock optimization
- In-situ separation
- Life cycle assessment