Leak of fuels and lubricants occurring during exploration, distribution, refining and storage operations is the major cause of environmental pollution due to petroderivatives dispersion. The quick use of a series of physicochemical and biological techniques is needed to drastically reduce the magnitude of damage provoked by these pollutants. Among them, soil washing proved to be an effective alternative to the remediation of hydrocarbon-polluted sites, mainly if combined with surfactant utilization. However, the direct use of surfactants can lead to problems related to the toxicity and dispersion of the resulting by-products, as the majority of marketed surfactants are produced from oil derivatives. In this context, green surfactants appear as a promising alternative to their synthetic counterpart. In the present study, two green surfactants, i.e., a chemically synthesized biobased surfactant and a Starmerella bombicola biosurfactant, were applied in soil decontamination tests using a concrete mixer-type Mobile Soil Remediation System (MSRS). The system was designed and developed with 3D printing based on bench-scale results. A commercial biosurfactant was formulated based on the microbial surfactant, which was compared with the biobased surfactant in various experimental conditions. A set of factorial designs combined with Response Surface Methodology was used to select the optimal conditions for pollutant removal using the prototype. The following variables were tested: Surfactant type, Surfactant volume, Surfactant dilution, Contaminant concentration, Soil type, Soil mass, Washing duration, Tank tilt angle, Mixing speed, and Type of basket. Under the optimized experimental condition, the commercial biosurfactant allowed to remove 92.4% of the motor oil adsorbed in the sand. These results demonstrate the possibility of using natural surfactants and the development of novel mechanical technologies to degrade hydrocarbons with economic earnings for oil industry.

Treatment of Motor Oil-Contaminated Soil with Green Surfactant Using a Mobile Remediation System

Converti A.;
2023-01-01

Abstract

Leak of fuels and lubricants occurring during exploration, distribution, refining and storage operations is the major cause of environmental pollution due to petroderivatives dispersion. The quick use of a series of physicochemical and biological techniques is needed to drastically reduce the magnitude of damage provoked by these pollutants. Among them, soil washing proved to be an effective alternative to the remediation of hydrocarbon-polluted sites, mainly if combined with surfactant utilization. However, the direct use of surfactants can lead to problems related to the toxicity and dispersion of the resulting by-products, as the majority of marketed surfactants are produced from oil derivatives. In this context, green surfactants appear as a promising alternative to their synthetic counterpart. In the present study, two green surfactants, i.e., a chemically synthesized biobased surfactant and a Starmerella bombicola biosurfactant, were applied in soil decontamination tests using a concrete mixer-type Mobile Soil Remediation System (MSRS). The system was designed and developed with 3D printing based on bench-scale results. A commercial biosurfactant was formulated based on the microbial surfactant, which was compared with the biobased surfactant in various experimental conditions. A set of factorial designs combined with Response Surface Methodology was used to select the optimal conditions for pollutant removal using the prototype. The following variables were tested: Surfactant type, Surfactant volume, Surfactant dilution, Contaminant concentration, Soil type, Soil mass, Washing duration, Tank tilt angle, Mixing speed, and Type of basket. Under the optimized experimental condition, the commercial biosurfactant allowed to remove 92.4% of the motor oil adsorbed in the sand. These results demonstrate the possibility of using natural surfactants and the development of novel mechanical technologies to degrade hydrocarbons with economic earnings for oil industry.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1119536
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