School of Civil Engineering, Universiti Sains Malaysia, 14300 Nibong Tebal, Penang, Malaysia.
Water Sci Technol. 2011;63(4):618-26. doi: 10.2166/wst.2011.211.
Central composite design (CCD) and response surface methodology (RSM) were employed to optimize four important variables, i.e. amounts of oil, bacterial inoculum, nitrogen and phosphorus, for the removal of selected n-alkanes during bioremediation of weathered crude oil in coastal sediments using laboratory bioreactors over a 60 day experimentation period. The reactors contained 1 kg soil with different oil, microorganisms and nutrients concentrations. The F Value of 26.89 and the probability value (P < 0.0001) demonstrated significance of the regression model. For crude oil concentration of 2, 16 and 30 g per kg sediments and under optimized conditions, n-alkanes removal was 97.38, 93.14 and 90.21% respectively. Natural attenuation removed 30.07, 25.92 and 23.09% n-alkanes from 2, 16 and 30 g oil/kg sediments respectively. Excessive nutrients addition was found to inhibit bioremediation.
采用中心组合设计（CCD）和响应面法（RSM）优化了四个重要变量，即在实验室生物反应器中进行风化原油生物修复过程中，用于去除选定的正构烷烃的条件，分别为：油、细菌接种物、氮和磷的量。在 60 天的实验期间，生物反应器中含有 1 公斤土壤和不同的油、微生物和营养物浓度。26.89 的 F 值和概率值（P < 0.0001）表明回归模型具有显著性。对于浓度为 2、16 和 30 g 每公斤沉积物的原油和优化条件下，正构烷烃的去除率分别为 97.38%、93.14%和 90.21%。自然衰减分别从 2、16 和 30 g 油/公斤沉积物中去除了 30.07%、25.92%和 23.09%的正构烷烃。过多的营养物添加被发现会抑制生物修复。
