Process Safety and Environmental Protection, Vol.126, 25-34, 2019
Decision tree for identification and prediction of filamentous bulking at full-scale activated sludge wastewater treatment plant
This study attempted to model sludge bulking in a full-scale wastewater treatment plant operated as a 3-stage Phoredox process. Principal component analysis and a regression tree model were employed to describe the correlations between influent wastewater characteristics and operational conditions (as inputs) and sludge volume index (SVI) as an output. A classification tree model was used to determine the environmental factors that affected the proliferation of filamentous microorganisms. Fluorescent in situ hybridisation analysis identified filamentous species of Microthrix parvicella, Thiothrix I & II, and Eikelboom Types 0041, 0092, and 021 N. It was found that SVI increased with an increment in sludge retention time, but it negatively correlated with soluble chemical oxygen demand (sCOD) and ammonium-nitrogen. The dominance of Microthrix parvicella was observed with a decline in temperature below 15.5 degrees C, causing an increase in SVI during the winter and spring seasons. The overgrowth of Thiothrix could be linked to the unbalanced ratio between readily biodegradable COD and nutrient species. The filament Type 0092 contributed to high SVI, and it prevailed with a decrease in food-to-microorganisms ratio below 0.08 1/d. Based on the satisfactory training, validation, and generalization procedures, the proposed models could be applied for the prediction of sludge bulking episodes. (C) 2019 Published by Elsevier B.V. on behalf of Institution of Chemical Engineers.
Keywords:Classification and regression trees;Filamentous detection;Sludge volume index;Sludge bulking;Wastewater characteristics