Machine learning application reveal dynamic interaction of polyphosphate-accumulating organism in full-scale wastewater treatment plant

2021 ◽  
Vol 44 ◽  
pp. 102417
Author(s):  
Seungdae Oh ◽  
Youngjun Kim
Keyword(s):  
Machine Learning ◽  
Wastewater Treatment ◽  
Wastewater Treatment Plant ◽  
Treatment Plant ◽  
Dynamic Interaction ◽  
Full Scale

Evaluating the treatment performance of a full scale Activated Sludge Plant in Islamabad, Pakistan

2012 ◽  
Vol 7 (1) ◽  
Author(s):  
S. S. Fatima ◽  
S. Jamal Khan
Keyword(s):  
Wastewater Treatment ◽  
Activated Sludge ◽  
Wastewater Treatment Plant ◽  
Suspended Solids ◽  
Treatment Plant ◽  
Oxygen Demand ◽  
Full Scale ◽  
Operational Parameter ◽  
Mixed Liquor ◽  
Treatment Performance

In this study, the performance of wastewater treatment plant located at sector I-9 Islamabad, Pakistan, was evaluated. This full scale domestic wastewater treatment plant is based on conventional activated sludge process. The parameters which were monitored regularly included total suspended solids (TSS), mixed liquor suspended solids (MLSS), mixed liquor volatile suspended solids (MLVSS), biological oxygen demand (BOD), and chemical oxygen demand (COD). It was found that the biological degradation efficiency of the plant was below the desired levels in terms of COD and BOD. Also the plant operators were not maintaining consistent sludge retention time (SRT). Abrupt discharge of MLSS through the Surplus Activated sludge (SAS) pump was the main reason for the low MLSS in the aeration tank and consequently low treatment performance. In this study the SRT was optimized based on desired MLSS concentration between 3,000–3,500 mg/L and required performance in terms of BOD, COD and TSS. This study revealed that SRT is a very important operational parameter and its knowledge and correct implementation by the plant operators should be mandatory.

Upgrading of a small wastewater treatment plant in a cold climate region using a moving bed biofilm reactor (MBBR) system

2000 ◽  
Vol 41 (1) ◽  
pp. 177-185 ◽  
Author(s):  
G. Andreottola ◽  
P. Foladori ◽  
M. Ragazzi
Keyword(s):  
Wastewater Treatment ◽  
Wastewater Treatment Plant ◽  
Treatment Plant ◽  
Internal Surface ◽  
Full Scale ◽  
Biofilm Reactor ◽  
Cold Climate ◽  
Moving Bed Biofilm Reactor ◽  
Moving Bed ◽  
North East

The aim of this study was to evaluate the performance of a full-scale upgrading of an existing RBC wastewater treatment plant with a MBBR (Moving Bed Biofilm Reactor) system, installed in a tank previously used for sludge aerobic digestion. The full-scale plant is located in a mountain resort in the North-East of Italy. Due to the fact that the people varied during the year's seasons (2000 resident people and 2000 tourists) the RBC system was insufficient to meet the effluent standards. The MBBR applied system consists of the FLOCOR-RMP®plastic media with a specific surface area of about 160 m2/m3 (internal surface only). Nitrogen and carbon removal from wastewater was investigated over a 1-year period, with two different plant lay-outs: one-stage (only MBBR) and two stage system (MBBR and rotating biological contactors in series). The systems have been operated at low temperature (5–15°C). 50% of the MBBR volume (V=79 m3) was filled. The organic and ammonium loads were in the average 7.9 gCOD m−2 d−1 and 0.9 g NH4−N m−2 d−1. Typical carbon and nitrogen removals in MBBR at temperature lower than 8°C were respectively 73% and 72%.

scholarly journals Niche Differentiation among Three Closely RelatedCompetibacteraceaeClades at a Full-Scale Activated Sludge Wastewater Treatment Plant and Putative Linkages to Process Performance

2018 ◽  
Vol 85 (5) ◽  
Author(s):  
Veronica R. Brand ◽  
Laurel D. Crosby ◽  
Craig S. Criddle
Keyword(s):  
Wastewater Treatment ◽  
Activated Sludge ◽  
Wastewater Treatment Plant ◽  
Treatment Plant ◽  
Niche Differentiation ◽  
Full Scale ◽  
Pure Oxygen ◽  
Operational Parameters ◽  
Metabolic Potential ◽  
Operational Conditions

ABSTRACTMultiple clades within a microbial taxon often coexist within natural and engineered environments. Because closely related clades have similar metabolic potential, it is unclear how diversity is sustained and what factors drive niche differentiation. In this study, we retrieved three near-complete Competibacter lineage genomes from activated sludge metagenomes at a full-scale pure oxygen activated sludge wastewater treatment plant. The three genomes represent unique taxa within theCompetibacteraceae. A comparison of the genomes revealed differences in capacity for exopolysaccharide (EPS) biosynthesis, glucose fermentation to lactate, and motility. Using quantitative PCR (qPCR), we monitored these clades over a 2-year period. The clade possessing genes for motility and lacking genes for EPS biosynthesis (CPB_P15) was dominant during periods of suspended solids in the effluent. Further analysis of operational parameters indicate that the dominance of the CPB_P15 clade is associated with low-return activated sludge recycle rates and low wasting rates, conditions that maintain relatively high levels of biomass within the system.IMPORTANCEMembers of the Competibacter lineage are relevant in biotechnology as glycogen-accumulating organisms (GAOs). Here, we document the presence of threeCompetibacteraceaeclades in a full-scale activated sludge wastewater treatment plant and their linkage to specific operational conditions. We find evidence for niche differentiation among the three clades with temporal variability in clade dominance that correlates with operational changes at the treatment plant. Specifically, we observe episodic dominance of a likely motile clade during periods of elevated effluent turbidity, as well as episodic dominance of closely related nonmotile clades that likely enhance floc formation during periods of low effluent turbidity.

Prediction of effluent concentration in a wastewater treatment plant using machine learning models

2015 ◽  
Vol 32 ◽  
pp. 90-101 ◽  
Author(s):  
Hong Guo ◽  
Kwanho Jeong ◽  
Jiyeon Lim ◽  
Jeongwon Jo ◽  
Young Mo Kim ◽  
...  
Keyword(s):  
Machine Learning ◽  
Wastewater Treatment ◽  
Wastewater Treatment Plant ◽  
Treatment Plant ◽  
Learning Models ◽  
Effluent Concentration ◽  
Machine Learning Models

scholarly journals Plant-wide modelling for assessment and optimization of upgraded full-scale wastewater treatment plant performance

2018 ◽  
Vol 13 (3) ◽  
pp. 566-582 ◽  
Author(s):  
Nadja Hvala ◽  
Darko Vrečko ◽  
Cirila Bordon
Keyword(s):  
Wastewater Treatment ◽  
Simulation Model ◽  
Wastewater Treatment Plant ◽  
Performance Indicators ◽  
Treatment Plant ◽  
Full Scale ◽  
Plant Performance ◽  
Limit Values ◽  
Reject Water ◽  
Integrate State

Abstract This paper presents the design of a plant-wide CNP (carbon-nitrogen-phosphorus) simulation model of a full-scale wastewater treatment plant, which will be upgraded for tertiary treatment to achieve compliance with effluent total nitrogen (TN) and total phosphorus (TP) limit values. The plant-wide model of the existing plant was first designed and extensively validated under long-term dynamic operation. The most crucial step was a precise characterization of input wastewater that was performed by extending the plant performance indicators both to a water line and sludge line and systematically estimating identifiable wastewater characterization parameters from plant-wide performance indicators, i.e. effluent concentrations, biogas and sludge production, and sludge composition. The thus constructed simulation model with standard activated sludge model (ASM2d) and anaerobic digestion model (MantisAD) overpredicted ortho-P and ammonia-N on the sludge line, indicating a need to integrate state-of-the-art physico-chemical minerals precipitation models to simulate plant-wide interactions more precisely. The upgraded plant with multimode anaerobic/anoxic/oxic configuration shows limited denitrification potential. Therefore, additional reject water treatment was evaluated to improve effluent TN and TP performance.

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