The state of activated sludge wastewater treatment process (AS WWTP) is conventionally identified by physico-chemical measurements which are costly, time-consuming and have associated environmental hazards. Image processing and analysis-based linear regression modeling has been used to monitor the AS WWTP. But it is plant- and state-specific in the sense that it cannot be generalized to multiple plants and states. Generalized classification modeling for state identification is the main objective of this work. By generalized classification, we mean that the identification model does not require any prior information about the state of the plant, and the resultant identification is valid for any plant in any state. In this paper, the generalized classification model for the AS process is proposed based on features extracted using morphological parameters of flocs. The images of the AS samples, collected from aeration tanks of nine plants, are acquired through bright-field microscopy. Feature-selection is performed in context of classification using sequential feature selection and least absolute shrinkage and selection operator. A support vector machine (SVM)-based state identification strategy was proposed with a new agreement solver module for imbalanced data of the states of AS plants. The classification results were compared with state-of-the-art multiclass SVMs (one-vs.-one and one-vs.-all), and ensemble classifiers using the performance metrics: accuracy, recall, specificity, precision, F measure and kappa coefficient (κ). The proposed strategy exhibits better results by identification of different states of different plants with accuracy 0.9423, and κ 0.6681 for the minority class data of bulking.
It was found that the operational temperature and the incorporation of microbial fuel cell (MFC) into anaerobic membrane bioreactor (AnMBR) have significant effect on AnMBRs' filtration performance. This paper addresses two issues (i) effect of temperature on AnMBR; and (ii) effect of MFC on AnMBRs' performance. The highest COD removal efficiency was observed in mesophilic condition (45°C). It was observed that the bioreactors operated at 45°C had the highest filtration resistance compared to others, albeit the excellent performance in removing the organic pollutant. Next, MFC was combined with AnMBR where the MFC acted as a pre-treatment unit prior to AnMBR and it was fed directly with palm oil mill effluent (POME). The supernatant from MFC was further treated by AnMBR. Noticeable improvement in filtration performance was observed in the combined system. Decrease in polysaccharide amount was observed in combined system which in turn suggested that the better filtration performance.
Three different sizes of powdered activated carbon (PAC) were added in hybrid anaerobic membrane bioreactors (AnMBRs) and their performance was compared with a conventional AnMBR without PAC in treating palm oil mill effluent. Their working volume was 1 L each. From the result, AnMBRs with PAC performed better than the AnMBR without PAC. It was also found that adding a relatively smaller size of PAC (approximately 100 μm) enhanced the chemical oxygen demand removal efficiency to 78.53 ± 0.66%, while the concentration of mixed liquor suspended solid and mixed liquor volatile suspended solid were 8,050 and 6,850 mg/L, respectively. The smaller size of PAC could also enhance the biofloc formation and biogas production. In addition, the smaller particle sizes of PAC incorporated into polyethersulfone membrane resulted in higher performance of membrane fouling control and produced better quality of effluent as compared to the membrane without the addition of PAC.
In this study, the differences on the physico-chemical parameters, lignocellulose degradation, dynamic succession of microbial community, gene expression of carbohydrate-active enzymes and antibiotics resistance genes were compared during composting systems of bagasse pith/pig manure (BP) and manioc waste/pig manure (MW). The results revealed that biodegradation rates of organic matter, cellulose, hemicellulose and lignin (29.14%, 17.53%,45.36% and 36.48%) in BP were higher than those (15.59%, 16.74%, 41.23% and 29.77%) in MW. In addition, the relative abundance of Bacillus, Luteimonas, Clostridium, Pseudomonas, Streptomyces and expression of genes encoding carbohydrate- active enzymes in BP were higher than those in MW based on metagenomics sequencing. During composting, antibiotics and antibiotic resistance genes were substantially reduced, but the removal efficiency was divergent in the both samples. Taken together, metagenomics analysis was a potential method for evaluating lignocellulose's biodegradation process and determining the elimination of antibiotic and antibiotic resistance genes from different composting sources of biomass.