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Advanced monitoring of high-rate anaerobic reactors through quantitative image analysis of granular sludge and multivariate statistical analysis
Authors:Costa J C  Moita I  Abreu A A  Ferreira E C  Alves M M
Institution:Institute for Biotechnology and Bioengineering (IBB), Centre of Biological Engineering, University of Minho, 4710-057 Braga, Portugal.
Abstract:Four organic loading disturbances were performed in lab-scale EGSB reactors fed with ethanol. In load disturbance 1 (LD1) and 2 (LD2), the organic loading rate (OLR) was increased between 5 and 18.5 kg COD m(-3) day(-1), through the influent ethanol concentration increase, and the hydraulic retention time decrease from 7.8 to 2.5 h, respectively. Load disturbances 3 (LD3) and 4 (LD4) were applied by increasing the OLR to 50 kg COD m(-3) day(-1) during 3 days and 16 days, respectively. The granular sludge morphology was quantified by image analysis and was related to the reactor performance, including effluent volatile suspended solids, indicator of washout events. In general, it was observed the selective washout of filamentous forms associated to granules erosion/fragmentation and to a decrease in the specific acetoclastic activity. These phenomena induced the transitory deterioration of reactor performance in LD2, LD3, and LD4, but not in LD1. Extending the exposure time in LD4 promoted acetogenesis inhibition after 144 h. The application of Principal Components Analysis determined a latent variable that encompasses a weighted sum of performance, physiological and morphological information. This new variable was highly sensitive to reactor efficiency deterioration, enclosing variations between 27% and 268% in the first hours of disturbances. The high loadings raised by image analysis parameters, especially filaments length per aggregates area (LfA), revealed that morphological changes of granular sludge, should be considered to monitor and control load disturbances in high rate anaerobic (granular) sludge bed digesters.
Keywords:anaerobic granular sludge  quantitative image analysis  organic loading disturbances  principal component analysis
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