Abstract

Oil spills in the marine environment frequently reach the coastal zone where active cleanup strategies may become necessary if the rates of natural weathering and attenuation of the stranded oil are considered inadequate. The application of surface-washing agents (SWAs) is an operational technique that enhances the separation and removal of oil that is adhered to solid surfaces. This study presents a comprehensive review of the current and emerging technologies to treat oiled shorelines using SWAs. The literature review includes a brief description of the characteristics of shoreline oiling and the current available techniques for shoreline treatment or cleanup. It summarizes the basics of surface washing and state-of-the-art efforts to date on oil removal using SWAs at both laboratory and field scales. The development trends of green SWAs for shoreline treatment are further introduced.

To develop the novel green SWA, the use of nanocellulose-based nanofluid as a SWA was studied by investigating its reactivity and effectiveness. Salinity was found to be the most influencial factor to facilitate oil removal with the nanofluids. Cations from salt can promote the adsorption of nanocellulose on the oil/water interface by reducing the surface charges. The experimental results revealed the nanocellulose could be effective at low concentrations but an excess of nanocellulose hindered oil removal due to an increase in fluid viscosity. The biotoxicity tests showed that nanocellulose-based nanofluid did not have negative effects on algae growth and introducing nanocellulose into an oiled culture medium can actually mitigate the toxicity of the oil on algae. A comparison in removal efficiency with other surfactants demonstrated the potential value for shoreline cleanup due to the superior effectiveness of nanocellulose-based nanofluids. It was found that the nanocellulose has a high potential for application as a surface-washing agent for shoreline cleanup due to the low cost, low toxicity, and high efficiency.

In addition, the shoreline cleanup operation can generate large amount of oily waste which requires further treatment. It is necessary to develop a programming model for oily waste management. An inexact chance-constrained programming model (ICCP) was developed with the consideration of uncertain environments, which cannot only consider the probability distribution of random variable but also interval parameters. The developed model was applied to a hypothetical oily waste management system. The interval solutions obtained from ICCP model included facilities selection, waste flow allocations, and expected time length under different constraint-violation risks. It is an effective tool to minimize the system cost of oily waste management with uncertainties. The obtained solutions could support the managers for the trade-off between system cost and risk level.