Abstract
Background: The booming palm oil industry is in line with the growing population worldwide and surge in demand. This leads to a massive generation of palm oil mill effluent (POME). POME is composed of sterilizer condensate (SC), separator sludge (SS), and hydro-cyclone wastewater (HCW). Comparatively, SS exhibits the highest organic content, resulting in various environmental impacts. However, past studies mainly focused on treating the final effluent. Therefore, this pioneering research investigated the optimization of pollutant removal in SS via different aspects of bioremediation, including experimental conditions, treatment efficiencies, mechanisms, and degradation pathways. Methods: A two-level factorial design was employed to optimize the removal of chemical oxygen demand (COD) and turbidity using Aspergillus niger. Bioremediation of SS was performed through submerged fermentation (SmF) under several independent variables, including temperature (20-40 °C), agitation speed (100-200 RPM), fermentation duration (72-240 h), and initial sample concentration (20-100%). The characteristics of the treated SS were then compared to that of raw sludge. Results: Optimal COD and turbidity removal were achieved at 37 °C 100 RPM, 156 h, and 100% sludge. The analysis of variance (ANOVA) revealed a significant effect of selective individual and interacting variables (p < 0.05). The highest COD and turbidity removal were 97.43% and 95.11%, respectively, with less than 5% error from the predicted values. Remarkably, the selected optimized conditions also reduced other polluting attributes, namely, biological oxygen demand (BOD), oil and grease (OG), color, and carbon content. In short, this study demonstrated the effectiveness of A. niger in treating SS through the application of a two-level factorial design.