Журнал нефтяной и экологической биотехнологии

Абстрактный

Enhanced Bioremediation of Soil Artificially Contaminated with Kerosene: Optimization of Biostimulation Agents through Statistical Experimental Design

Agarry SE, Owabor CN and Yusuf RO

The main goals of this work were to study the enhanced bioremediation of soil artificially contaminated with kerosene via biostimulation strategy, evaluate the influence of biostimulating agents on the rate of degradation and to optimize the biostimulating agents for maximum kerosene removal. The study was carried out by artificially contaminating an un-impacted tropical soil with 10% (w/w) kerosene oil in earthen pots and various concentrations of NPK fertilizer, Tween 80 and hydrogen peroxide were added and then incubated for six weeks remediation period. To optimize the range of experimentation, Response Surface Methodology (RSM) with Box Behnken Design (BBD) was used with three factors and three levels of NPK fertilizer, Tween 80 and hydrogen peroxide as independent variables and kerosene oil (total petroleum hydrocarbon) removal as dependent variable (response). The results showed that there were significant variations in the kerosene oil biodegradation pattern with respect to NPK fertilizer, Tween 80 and hydrogen peroxide. A statistically significant (P < 0.0001) second-order quadratic regression model for kerosene oil removal (using Design-Expert Statistical program (v. 6.0.8) with a coefficient of determination, R (= 0.9992) was obtained. Numerical optimization technique based on desirability function was carried out to optimize the bioremediation process. The optimum values for biostimulating agents to achieve a predicted maximum kerosene removal of 75.06% were found to be: NPK fertilizer, 4.30 g (equivalent to 0.0215 μg/kg); Tween 80, 10.03 mg/l and hydrogen peroxide, 1.13 g/l. At this optimum point, the observed kerosene oil removal was found to be 73.95%. Thus, biostimulation of indigenous microbial density and activity can reduce the period for remediation of contaminated environment and subsequently the cost of remediation. Response Surface Methodology (RSM) is a reliable and powerful tool for modeling and optimizing of kerosene oil bioremediation processes.