C/N ratio effect on oily wastewater treatment using column type SBR: machine learning prediction and metagenomics study

Abstract

Abstract The sequencing batch reactor has emerged as a promising technology in treating wastewater; however, its application in the treatment of generated water still needs to be explored. This research gap led to the investigation of various carbon-to-nitrogen (C/N) ratios in a column-type sequencing batch reactor (cSBR). The resulting data and model demonstrated that augmenting the SND process with an external carbon source is effective until the C/N ratio reaches 15, ultimately eliminating nitrogen in the produced water. Conversely, a reduced C/N ratio can limit the ability of polyphosphate-accumulating organisms to incorporate carbon into polyphosphate synthesis, thereby decreasing phosphorus removal efficiency within the cSBR. When the C/N ratio ranged from 6 to 8, and the mixed liquor suspended solids concentration was high, the average phosphate removal was approximately 55%, compared to only around 25% when the C/N ratio was less than 6.

Keywords

• Coastal wastewater
• Sequencing batch reactor
• Stress intensity
• Artificial neural network
• Interactive effect
• Circular economy