Available online sensors can be used to create fingerprints for MABRs that characterize biofilm limiting conditions and serve as soft sensors. (10th October 2022)

• Record Type: Journal Article
• Authors: Yang, Cheng; Houweling, Dwight; He, Huanqi; Daigger, Glen T.
• Is Part Of: Water science and technology. Volume 86:Number 9(2022)
• Page Start: 2270
• Page End: 2287
• Publication Date: 2022-10-10
• Subjects: biofilm thickness control -- fingerprints -- MABR -- modeling -- soft sensor; Water -- Pollution; Sewage -- Purification; Water quality management; Periodicals; 628.168
• DOI: 10.2166/wst.2022.323
• Languages: English
• ISSNs: 0273-1223

Abstract

Abstract: Membrane aerated biofilm reactors (MABRs) are a promising biological wastewater treatment technology, whose industrial applications have dramatically accelerated in the last five years. Increased popularity and fast industrial adaptation are coupled with increased needs to monitor, optimize, and control MABRs with available online sensors. Observations of commercial scale MABR installations have shown a distinctive and repetitive pattern relating oxygen purity in MABR exhaust gas to reactor ammonia concentrations. This provides an obvious opportunity for process monitoring and control which this paper investigates with the help of modeling. The relationship plots between the bulk ammonia concentration and the oxygen purity are defined as MABR fingerprint plots, which are described in the form of steady-state curves and dynamic trajectories. This study systematically investigated, analyzed, and explained the behaviors and connections of steady-state curves and dynamic trajectories with a MABR model in SUMO ®, and proposed a hypothesis about utilizing the MABR fingerprint plots to characterize MABR system performance, identify the limiting factor of biofilms, and possibly develop a soft senor for MABR biofilm thickness monitoring and control. HIGHLIGHTS: Fingerprints of MABRs are proposed based on the relationships of available online sensor signals. With modeling, the behaviors of MABR fingerprints were analyzed under both steady-state and dynamic conditions. The MABR fingerprints can characterize MABR system performance and identify the limiting factor of biofilms. The MABR fingerprints can potentially be soft sensors for MABR biofilm thickness monitoring and control. Graphical Abstract