Do You Know Your Sludge Age?

Takács, I.; Stricker, Anne‐Emmanuelle; Achleitner, Stefan; Barrie, Ashley; Rauch, Wolfgang; Murthy, Sudhir

doi:10.2175/193864708788733486

Cited by 11 publications

(6 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For systems under complete sludge retention (without wastage), the duration of the experiment can be used to illustrate sludge age instead of the SRT as the latter cannot be calculated from standard equations ). In the current study the dynamic SRT was estimated to range from 4.0 to 51.5 days based on calculations suggested by Taka´cs et al (2008). (Dold, 2007).…”

Section: Resultsmentioning

confidence: 99%

Activated Sludge Production Parameters and Nutrient Content of Organic Sludge Components

Labelle

Dold

Gadbois³

et al. 2017

Water Environment Research

View full text Add to dashboard Cite

An important part of biological treatment system design is quantifying the sludge production and the nutrient removal capacity. Influent wastewater COD fractionation, biomass growth and endogenous respiration directly impacts the composition of the mixed liquor solids in activated sludge systems. The objectives of this project were to determine the model kinetic and stoichiometric parameters associated with activated sludge production and the nutrient content (N and P) of unbiodegradable organic matter components. A complete sludge retention experiment was conducted over 70 days in a pilot-scale membrane bioreactor fed with a real municipal wastewater, and operated with alternating growth and famine periods. Experimental results were simulated and compared using the default values from two well-accepted model parameter sets. The General ASDM parameter set was found to better fit the experimental data than the Metcalf and Eddy parameter set, mainly to characterize endogenous respiration and the heterotrophic biomass concentration. An influent unbiodegradable organic particulate fraction (fXU,Inf) value of 0.16 g COD/g COD was determined by calibration of the accumulated sludge total COD, suspended solids and heterotrophic biomass concentrations. The nutrient content of the accumulated endogenous residue (XE) and influent unbiodegradable organic particulate (XU,Inf) components were calibrated to 0.030 and 0.100 g N/g COD and 0.035 and 0.008 g P/g COD, respectively. These values are in the range of those reported in the literature except for the high P content found in the endogenous residue, possibly due to the presence of coagulants added for P removal in the accumulated sludge. These results were consistent under the wide range of dynamic conditions tested and could improve model prediction of sludge production and composition.

show abstract

Section: Resultsmentioning

confidence: 99%

Activated Sludge Production Parameters and Nutrient Content of Organic Sludge Components

Labelle

Dold

Gadbois³

et al. 2017

Water Environment Research

View full text Add to dashboard Cite

show abstract

“…The applied model, SUMO1, is based on ASM and additionally estimates the pH from the most relevant chemical speciation and gas-exchange processes (e.g., CO 2 stripping). The SRT is modeled as described by Takács et al The model was used to simulate synthetic pH, DO, and ammonium effluent data at a resolution of 10 s to understand the operational conditions influencing feature detection and to benchmark the soft-sensor performance. It is relevant to emphasize that the synthetic data were not used to calibrate the soft sensors.…”

Section: Methodsmentioning

confidence: 99%

Benchmarking Soft Sensors for Remote Monitoring of On-Site Wastewater Treatment Plants

Schneider

Furrer

Sprenger

et al. 2020

Environ. Sci. Technol.

View full text Add to dashboard Cite

On-site wastewater treatment plants are usually unattended, so undetected failures often lead to prolonged periods of reduced performance. To stabilize the good performance of unattended plants, soft-sensors could expose faults and failures to the operator. In a previous study, we developed softsensors and showed that soft-sensors with data from unmaintained physical sensors can be as accurate as soft-sensors with data from maintained ones. The quantities sensed were pH and dissolved oxygen (DO), and soft-sensors were used to predict nitrification performance. In the present study, we use synthetic data and monitor three plants to test these soft-sensors. We find that a long sludge age and a moderate aeration rate improve the pH soft-sensor accuracy, and that the aeration regime is the main operational parameter affecting the accuracy of the DO soft-sensor. We demonstrate that integrated design, monitoring, and control are necessary to achieve robust accuracy and to obviate case-specific fine-tuning. Additionally, we provide a unique labelled dataset for further feature and data-driven soft-sensor development. Our approach is limited to sequencing batch reactors. Moreover, nitrite accumulation and alkalinity limitation cannot be detected. The strength of the approach is that unmaintained sensors drastically reduce monitoring costs, enabling the monitoring of plants hitherto unchecked. AbbreviationsASM activated sludge model COD chemical oxygen demand DO dissolved oxygen DOC dissolved organic carbon SL standard-liter OST on-site wastewater treatment plant (small, unstaffed wastewater treatment plant) PE population equivalent SA sludge age SAC254 spectral absorption coefficient at 254 nanometers SBR sequencing batch reactor WWTP wastewater treatment plant

show abstract

“…Table summarizes the specific design parameters of the flash mix tank and the SBRs. SRT was controlled by adjusting the waste volumes weekly based on effluent and reactor solid concentrations, on the basis of the dynamic SRT model (Takács et al., ).…”

Section: Approachmentioning

confidence: 99%

Effect of solids residence time on dynamic responses in chemical P removal

Conidi

Parker

Smith

2019

Water Environment Research

View full text Add to dashboard Cite

The impact of solids residence time (SRT) on the dynamics of phosphorus (P) removal by hydrous ferric oxide (HFO) floc was characterized through experimental and modeling studies. Three abiotic process conditions were considered in systems operated over a range of SRTs (~3 to 27 days): uptake in sequencing batch reactors (SBRs) under (a) constant and (b) dynamic P loading conditions, and (c) uptake in batch sorption tests with preformed HFO solids. P removal under all conditions was characterized by an initial period of fast removal followed by a period of slower removal until pseudoequilibrium was reached. The initial removal rate increased with increasing P concentrations and was attributed to a larger concentration gradient between soluble-and adsorbed-phase concentrations. A kinetic model was developed and found to describe the dynamic behavior of P adsorption onto HFO floc under all conditions tested. A consistent mass transfer rate coefficient (k) was found to describe mass transfer over a range of SRTs for low initial P concentrations. At elevated SRTs (23-27 days) and elevated influent P concentrations, k values were found to deviate from those estimated at reduced SRTs. Differences in process mixing conditions were reflected in the estimated rate coefficients (k). Integration of the kinetic model with existing equilibrium models in wastewater process simulators will improve the ability to predict P uptake onto HFO floc under dynamic loading conditions in water resource recovery facilities. Models that consider the kinetics of P uptake will be particularly relevant for facilities that are required to achieve ultralow P concentrations. • Practitioner points• This work provides a kinetic model that can be integrated with existing equilibrium models in wastewater process simulators to improve the ability to predict P uptake onto HFO floc under dynamic loading conditions. • This research can be used to assist WRRFs to achieve ultralow effluent P requirements.

show abstract

Do You Know Your Sludge Age?

Cited by 11 publications

References 0 publications

Activated Sludge Production Parameters and Nutrient Content of Organic Sludge Components

Activated Sludge Production Parameters and Nutrient Content of Organic Sludge Components

Benchmarking Soft Sensors for Remote Monitoring of On-Site Wastewater Treatment Plants

Effect of solids residence time on dynamic responses in chemical P removal

Contact Info

Product

Resources

About