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Modeling Dissolved Oxygen Concentration for Optimizing Aeration Systems and Reducing Oxygen Consumption in Activated Sludge Processes: A Review

Journal

CHEMICAL ENGINEERING COMMUNICATIONS
Volume 201, Issue 8, Pages 983-1002

Publisher

TAYLOR & FRANCIS INC
DOI: 10.1080/00986445.2014.883974

Keywords

Modeling; Oxygen uptake rate (OUR); Activated sludge process (ASP); Oxygen transfer rate (OTR); Aeration; Optimization; Wastewater treatment; Volumetric mass transfer coefficient (K L a); Dissolved oxygen (DO)

Funding

  1. Zhejiang Province
  2. Key Project of Science and Technology of Zhejiang Province [2011C14023]
  3. National Natural Science Foundation of China [51108416]
  4. Ministry of Science and Technology of China [2010DFA92050]

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Aeration accounts for 30% to 75% of the total energy consumption in activated sludge processes (ASPs). This percentage can be significantly reduced since most aeration systems are not optimized for unsteady influent flow rates and oxygen requirements. Reconfiguration, replacement, and the application of optimal dissolved oxygen (DO) control strategies for current aeration systems within the facility and model-based optimization of DO in wastewater treatment plants can lead to impressive increased energy efficiency and savings and improved stability of the system. These measures increase the operational lifetime of the aeration equipment and improve effluent and activated sludge quality. This article provides a review of two critical nonlinear time-varying parameters that characterize the DO concentration dynamics in an ASP: the oxygen uptake rate (OUR), related to microorganism activity, and the volumetric oxygen mass transfer function, represented by the oxygen transfer rate (OTR). Second, the physico-chemical, geometric, and dynamic factors and aerator type affecting the oxygen mass transfer coefficient (K (L) a) are thoroughly discussed. The article concludes with model-based optimization, explaining the usefulness of accurate DO models in wastewater treatment, and provides examples for plant-wide or water chain cycle-focused optimizations.

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