Biosurfactants are microbial products that have been increasingly researched due to their many identified advantages, such as low toxicity and high activity at extreme temperatures, but more importantly, they are biodegradable and compatible with the environment. Biosurfactants are versatile products with vast applications in the clean-up of environmental pollutants through biodegradation and bioremediation. They also have applications in the food, pharmaceutical, and other industries. These advantages and wide range of applications have led to the continued interest in biosurfactants. In particular, there is a growing discussion around environmental sustainability and the important role that biosurfactants will increasingly play in the near future, for example, via the use of renewable by-products as substrates, waste reduction, and potential reuse of the treated waste. This has resulted in increased attention on these microbial products in industry. Research highlighting the potential of biosurfactants in environmental sustainability is required to drive efforts to make biosurfactants more viable for commercial and large-scale applications; making them available, cheaper and economically sustainable. The present review discusses the unique relationship between biosurfactants and environmental sustainability, especially the role that biosurfactants play in the clean-up of environmental pollutants and, therefore, increasing environmental protection.

This study presents the understanding of temporal dynamics of groundwater-surface water (GW-SW) interaction due to parameter uncertainty by using a physically-based and distributed gridded surface subsurface hydrologic analysis (GSSHA) model combined with a Monte Carlo simulation. A study area along the main stem of the Kiskatinaw River of the Kiskatinaw River watershed, Northeast British Columbia, Canada, was used as a case study. Two different greenhouse gas (GHG) emission scenarios (i.e., A2: heterogeneous world with self-reliance and preservation of local identities, and B1: a more integrated and environmental-friendly world) of the Special Report on Emissions Scenarios (SRES) from the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) for 2013 were used as case scenarios. Before conducting uncertainty analysis, a sensitivity analysis was performed to find the most sensitive parameters to the model output (i.e., mean monthly groundwater contribution to stream flow). Then, a Monte Carlo simulation was used to conduct the uncertainty analysis. The uncertainty analysis results under both case scenarios revealed that the pattern of the cumulative relative frequency distribution of the mean monthly and annual groundwater contributions to stream flow varied monthly and annually, respectively, due to the uncertainties of the sensitive model parameters. In addition, the pattern of the cumulative relative frequency distribution of a particular month’s groundwater contribution to the stream flow differed significantly between both scenarios. These results indicated the complexities and uncertainties in the GW-SW interaction system. Therefore, it is of necessity to use such uncertainty analysis results rather than the point estimates for better water resources management decision-making.