Estimation of kinetic rate constants for biodegradation of chemicals in activated sludge wastewater treatment plants using short term batch experiments and μg/L range spiked concentrations

Chemosphere ◽  
1996 ◽  
Vol 33 (5) ◽  
pp. 851-864 ◽  
Author(s):  
N. Nyholm ◽  
F. Ingerslev ◽  
U.T. Berg ◽  
J.P. Pedersen ◽  
H. Frimer-Larsen
Keyword(s):  
Wastewater Treatment ◽  
Activated Sludge ◽  
Rate Constants ◽  
Wastewater Treatment Plants ◽  
Batch Experiments ◽  
Short Term ◽  
Kinetic Rate ◽  
Kinetic Rate Constants

A model for predicting nitrous oxide production during denitrification in activated sludge

1996 ◽  
Vol 34 (5-6) ◽  
pp. 99-106 ◽  
Author(s):  
H. Wicht
Keyword(s):  
Nitrous Oxide ◽  
Wastewater Treatment ◽  
Activated Sludge ◽  
Wastewater Treatment Plants ◽  
Batch Experiments ◽  
Monod Kinetics ◽  
Influence Of Temperature ◽  
Influent Concentration ◽  
Oxide Production ◽  
Nitrous Oxide Production

To examine the importance of certain conditions on the production of nitrous oxide during denitrifications batch experiments with activated sludge were conducted. With the obtained parameters and a Monod kinetics based model the nitrous oxide concentrations in a CSRT were calculated. The influence of temperature, pH, nitrate influent concentration, readily biodegradable COD influent concentration, H2S and oxygen inhibitor concentrations are discussed. The presented model helps in understanding some previously described phenomena of nitrous oxide production in wastewater treatment plants.

scholarly journals Removal efficiencies and kinetic rate constants of xenobiotics by ozonation in tertiary treatment

2017 ◽  
Vol 75 (12) ◽  
pp. 2737-2746 ◽  
Author(s):  
Baptiste Mathon ◽  
Marina Coquery ◽  
Cécile Miege ◽  
Ywann Penru ◽  
Jean-Marc Choubert
Keyword(s):  
Rate Constants ◽  
Wastewater Treatment Plants ◽  
Batch Reactor ◽  
Chemical Oxidation ◽  
Secondary Effluent ◽  
Kinetic Rate ◽  
Kinetic Rate Constants ◽  
Removal Efficiencies ◽  
Elimination Pathway

This study gives a full overview of the chemical oxidation by ozone of selected xenobiotics usually present in effluents of conventional wastewater treatment plants. A qualitative and quantitative overview of literature data was made, and describes the ozonation efficiency and processes for the elimination of 12 xenobiotics (pesticides and pharmaceuticals). A database was built, compiling literature results of experimental ozonation assays in laboratory and real-scale conditions. Special attention was paid to selecting the data and compiling reliable results on removal efficiencies and kinetic parameters. An original study was performed in a semi-batch reactor applying ozone on secondary effluent spiked beforehand with a cocktail of 12 xenobiotics. The results of this study were compared with the literature data to evaluate the influence of the kinetic competition of xenobiotics in spiked wastewater in the determination of kinetic rate constants. These 12 xenobiotics were classified into three groups (high-/medium-/low-oxidizable) according to the ranges of their direct kinetic rate constants (kO3). A best effective ozone dose between 0.2 and 0.4 gO3 gDOC−1 is proposed for the elimination of xenobiotics. The predominant elimination pathway between direct and indirect oxidation was identified for each xenobiotic.

scholarly journals The capacity of wastewater treatment plants drives bacterial community structure and its assembly

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Young Kyung Kim ◽  
Keunje Yoo ◽  
Min Sung Kim ◽  
Il Han ◽  
Minjoo Lee ◽  
...  
Keyword(s):  
Wastewater Treatment ◽  
Community Structure ◽  
Bacterial Community ◽  
Activated Sludge ◽  
Community Assembly ◽  
Bacterial Communities ◽  
Wastewater Treatment Plants ◽  
High Capacity ◽  
Operating Conditions ◽  
Rrna Gene

Abstract Bacterial communities in wastewater treatment plants (WWTPs) affect plant functionality through their role in the removal of pollutants from wastewater. Bacterial communities vary extensively based on plant operating conditions and influent characteristics. The capacity of WWTPs can also affect the bacterial community via variations in the organic or nutrient composition of the influent. Despite the importance considering capacity, the characteristics that control bacterial community assembly are largely unknown. In this study, we discovered that bacterial communities in WWTPs in Korea and Vietnam, which differ remarkably in capacity, exhibit unique structures and interactions that are governed mainly by the capacity of WWTPs. Bacterial communities were analysed using 16S rRNA gene sequencing and exhibited clear differences between the two regions, with these differences being most pronounced in activated sludge. We found that capacity contributed the most to bacterial interactions and community structure, whereas other factors had less impact. Co-occurrence network analysis showed that microorganisms from high-capacity WWTPs are more interrelated than those from low-capacity WWTPs, which corresponds to the tighter clustering of bacterial communities in Korea. These results will contribute to the understanding of bacterial community assembly in activated sludge processing.

Interfacial catalysis by phospholipase A2: determination of the interfacial kinetic rate constants

Biochemistry ◽  
1991 ◽  
Vol 30 (29) ◽  
pp. 7283-7297 ◽  
Author(s):  
Otto G. Berg ◽  
Bao Zhu Yu ◽  
Joe Rogers ◽  
Mahendra Kumar Jain
Keyword(s):  
Phospholipase A2 ◽  
Rate Constants ◽  
Kinetic Rate ◽  
Kinetic Rate Constants ◽  
Interfacial Catalysis

scholarly journals Forecasting Energy Consumption of Wastewater Treatment Plants with a Transfer Learning Approach for Sustainable Cities

Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1149
Author(s):  
Pedro Oliveira ◽  
Bruno Fernandes ◽  
Cesar Analide ◽  
Paulo Novais
Keyword(s):  
Wastewater Treatment ◽  
Energy Consumption ◽  
Transfer Learning ◽  
Short Term Memory ◽  
Wastewater Treatment Plants ◽  
Learning Approach ◽  
Sustainable Cities ◽  
Short Term ◽  
Long Short Term Memory ◽  
Gated Recurrent Units

A major challenge of today’s society is to make large urban centres more sustainable. Improving the energy efficiency of the various infrastructures that make up cities is one aspect being considered when improving their sustainability, with Wastewater Treatment Plants (WWTPs) being one of them. Consequently, this study aims to conceive, tune, and evaluate a set of candidate deep learning models with the goal being to forecast the energy consumption of a WWTP, following a recursive multi-step approach. Three distinct types of models were experimented, in particular, Long Short-Term Memory networks (LSTMs), Gated Recurrent Units (GRUs), and uni-dimensional Convolutional Neural Networks (CNNs). Uni- and multi-variate settings were evaluated, as well as different methods for handling outliers. Promising forecasting results were obtained by CNN-based models, being this difference statistically significant when compared to LSTMs and GRUs, with the best model presenting an approximate overall error of 630 kWh when on a multi-variate setting. Finally, to overcome the problem of data scarcity in WWTPs, transfer learning processes were implemented, with promising results being achieved when using a pre-trained uni-variate CNN model, with the overall error reducing to 325 kWh.

scholarly journals Do initial concentration and activated sludge seasonality affect pharmaceutical biotransformation rate constants?

2021 ◽  
Author(s):  
Tamara J. H. M. van Bergen ◽  
Ana B. Rios-Miguel ◽  
Tom M. Nolte ◽  
Ad M. J. Ragas ◽  
Rosalie van Zelm ◽  
...  
Keyword(s):  
Microbial Community ◽  
Activated Sludge ◽  
Community Composition ◽  
Rate Constants ◽  
Wastewater Treatment Plants ◽  
Microbial Community Composition ◽  
Amplicon Sequencing ◽  
Rrna Gene ◽  
Initial Concentration ◽  
Different Seasons

Abstract Pharmaceuticals find their way to the aquatic environment via wastewater treatment plants (WWTPs). Biotransformation plays an important role in mitigating environmental risks; however, a mechanistic understanding of involved processes is limited. The aim of this study was to evaluate potential relationships between first-order biotransformation rate constants (kb) of nine pharmaceuticals and initial concentration of the selected compounds, and sampling season of the used activated sludge inocula. Four-day bottle experiments were performed with activated sludge from WWTP Groesbeek (The Netherlands) of two different seasons, summer and winter, spiked with two environmentally relevant concentrations (3 and 30 nM) of pharmaceuticals. Concentrations of the compounds were measured by LC–MS/MS, microbial community composition was assessed by 16S rRNA gene amplicon sequencing, and kb values were calculated. The biodegradable pharmaceuticals were acetaminophen, metformin, metoprolol, terbutaline, and phenazone (ranked from high to low biotransformation rates). Carbamazepine, diatrizoic acid, diclofenac, and fluoxetine were not converted. Summer and winter inocula did not show significant differences in microbial community composition, but resulted in a slightly different kb for some pharmaceuticals. Likely microbial activity was responsible instead of community composition. In the same inoculum, different kb values were measured, depending on initial concentration. In general, biodegradable compounds had a higher kb when the initial concentration was higher. This demonstrates that Michealis-Menten kinetic theory has shortcomings for some pharmaceuticals at low, environmentally relevant concentrations and that the pharmaceutical concentration should be taken into account when measuring the kb in order to reliably predict the fate of pharmaceuticals in the WWTP. Key points • Biotransformation and sorption of pharmaceuticals were assessed in activated sludge. • Higher initial concentrations resulted in higher biotransformation rate constants for biodegradable pharmaceuticals. • Summer and winter inocula produced slightly different biotransformation rate constants although microbial community composition did not significantly change. Graphical abstract

scholarly journals Deep learning-based morphology classification of activated sludge flocs in wastewater treatment plants

2021 ◽  
Author(s):  
Hisashi Satoh ◽  
Yukari Kashimoto ◽  
Naoki Takahashi ◽  
Takashi Tsujimura
Keyword(s):  
Wastewater Treatment ◽  
Deep Learning ◽  
Activated Sludge ◽  
Morphological Change ◽  
Wastewater Treatment Plants ◽  
Filamentous Bacteria ◽  
Sludge Flocs

A deep learning-based two-label classifier 1 recognized a 20% morphological change in the activated flocs. Classifier-2 quantitatively recognized an abundance of filamentous bacteria in activated flocs.

Controlling the Settling of Activated Sludge in Pulp and Paper Wastewater Treatment Plants

1999 ◽  
Vol 40 (11-12) ◽  
pp. 223-229 ◽  
Author(s):  
Frédéric Clauss ◽  
Christel Balavoine ◽  
Delphine Hélaine ◽  
Gaëtan Martin
Keyword(s):  
Wastewater Treatment ◽  
Activated Sludge ◽  
Wastewater Treatment Plants ◽  
Pulp And Paper ◽  
Organic Load ◽  
Forest Industry ◽  
Filamentous Bulking ◽  
Mineral Particles ◽  
Mineral Powder

Forest industry wastewaters are difficult to clean: hydraulic and organic load variations, filamentous bulking or pin-point flocs negatively impact depollution processes. The addition of a fine, mineral, talc-based powder, Aquatal, into the aeration tanks of wastewater treatment plants connected to pulp and paper factories has been successfully tested since end of '97. The first case-study presents full results obtained over a period of 18 months in a 20,000 p.e. plant connected to a paper factory. The mineral powder was regularly added to control sludge volume index, thereby ensuring low suspended solids concentration in the outfluent. Plant operators could easily adapt biomass concentration to match organic load variation, thereby maintaining pollution micro-organisms ratio constant. In a second case study, a trouble-shooting strategy was implemented to counteract filamentous bulking. A one-off, large dosage enabled the plant operator to deal effectively with poor settleability sludge and rapidly control sludge blanket expansion. In both cases, the main common characteristics observed were an increase in floc aggregation and the production of heavier and well-structured flocs. The sludge settling velocity increased and an efficient solid/liquid separation was obtained. After a few days, the mineral particles of Aquatal were progressively integrated into the sludge floc structure. When the mineral powder was added to the activated sludge in the aeration basin, chemical interactions frequently encountered with other wastewater treatment additives did not pose a problem. Moreover, with this mineral additive, the biological excess sludge displayed good thickening properties and dewatering was improved. Despite the addition of the insoluble mineral particles, the amount of wet sludge expelled did not increase. Aquatal offers a rapid solution to floc settleability problems which so frequently arise when physical or biological disorders appear in forest industry wastewater treatment plants.

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