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Benchmark Model for Wastewater Treatment Using an Activated Sludge Process

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This is benchmark model for wastewater treatment using an activated sludge process. The activated sludge process is a means of treating both municipal and industrial wastewater. The activated sludge process is a multi-chamber reactor unit that uses highly concentrated microorganisms to degrade organics and remove nutrients from wastewater, producing quality effluent.

This model provides pollutant concentrations, mass balance, electricity requirements, and treatment costs. This model will be continuously updated based on the latest data.

Citation Formats

Princeton University. (2022). Benchmark Model for Wastewater Treatment Using an Activated Sludge Process [data set]. Retrieved from https://dx.doi.org/10.7481/1844539.
Export Citation to RIS
Byun, Jaewon, Maravelias, Christos. Benchmark Model for Wastewater Treatment Using an Activated Sludge Process. United States: N.p., 21 Jan, 2022. Web. doi: 10.7481/1844539.
Byun, Jaewon, Maravelias, Christos. Benchmark Model for Wastewater Treatment Using an Activated Sludge Process. United States. https://dx.doi.org/10.7481/1844539
Byun, Jaewon, Maravelias, Christos. 2022. "Benchmark Model for Wastewater Treatment Using an Activated Sludge Process". United States. https://dx.doi.org/10.7481/1844539. https://data.openei.org/submissions/5641.
@div{oedi_5641, title = {Benchmark Model for Wastewater Treatment Using an Activated Sludge Process}, author = {Byun, Jaewon, Maravelias, Christos.}, abstractNote = {This is benchmark model for wastewater treatment using an activated sludge process. The activated sludge process is a means of treating both municipal and industrial wastewater. The activated sludge process is a multi-chamber reactor unit that uses highly concentrated microorganisms to degrade organics and remove nutrients from wastewater, producing quality effluent.

This model provides pollutant concentrations, mass balance, electricity requirements, and treatment costs. This model will be continuously updated based on the latest data.}, doi = {10.7481/1844539}, url = {https://data.openei.org/submissions/5641}, journal = {}, number = , volume = , place = {United States}, year = {2022}, month = {01}}
https://dx.doi.org/10.7481/1844539

Details

Data from Jan 21, 2022

Last updated Feb 11, 2022

Submitted Jan 29, 2022

Organization

Princeton University

Contact

Jaewon Byun

Authors

Jaewon Byun

Princeton University

Christos Maravelias

Princeton University

DOE Project Details

Project Name NAWI Integrated Data and Analysis

Project Lead Melissa Klembara

Project Number 36496

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