Issue 8, 2014

Evaluation of bioaugmentation and biostimulation effects on the treatment of refinery oily sludge using 2n full factorial design

Abstract

Bioremediation approaches for the treatment of oily sludge from a refinery were evaluated using a 23 factorial design. The three strategies tested were bioaugmentation with indigenous microbial consortia (MO) isolated from oily sludge, biostimulation with nutrients (NP) and biostimulation with the surfactant Triton X-100 (TX). Eight experimental runs were conducted in triplicate with factor settings ± (high/low) as per the 23 design. The main effects and the effects of various interactions of the factors on oil degradation and microbial growth in suspension were evaluated during a 30 day study. Multifactor ANOVA could reveal the significant effects while the normal order score approach failed in this scenario. The main effect of biostimulation with nutrients in the form of nitrate and phosphate, as well as biostimulation with Triton X-100, was positive and significant when both oil degradation and microbial growth in suspension were chosen as the response variables. However, the main effect of bioaugmentation was only significant for oil degradation but was insignificant for microbial growth at a 90% confidence level. The MO–NP binary interaction and the MO–NP–TX ternary interactions were positive and significant, indicating the synergistic effect of these strategies on oil degradation and microbial growth. All other binary interactions were found to be insignificant.

Graphical abstract: Evaluation of bioaugmentation and biostimulation effects on the treatment of refinery oily sludge using 2n full factorial design

Article information

Article type
Paper
Submitted
22 Feb 2014
Accepted
17 Apr 2014
First published
17 Apr 2014
This article is Open Access
Creative Commons BY-NC license

Environ. Sci.: Processes Impacts, 2014,16, 1889-1896

Author version available

Evaluation of bioaugmentation and biostimulation effects on the treatment of refinery oily sludge using 2n full factorial design

J. Jasmine and S. Mukherji, Environ. Sci.: Processes Impacts, 2014, 16, 1889 DOI: 10.1039/C4EM00116H

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