Real-time in situ auto-correction of K+ interference for continuous and long-term NH4+ monitoring in wastewater using solid-state ion selective membrane (S-ISM) sensor assembly

Abstract

Potassium ions (K⁺) present in wastewater has caused severe interference for NH₄⁺ monitoring, over-estimation of NH₄⁺ concentration and ultimately leads to extra energy consumption. Past effort for enhancing the selectivity of NH₄⁺ over K⁺ were oftentimes complex, costly, or compromised the selectivity and accuracy of the NH₄⁺ ion selective membrane (ISM) sensors. This study targeted this imminent challenge by developing an integrated NH₄⁺/K⁺ auto-correction solid-state ISM (S-ISM) sensor assembly combined with a data-driven model to monitor [NH₄⁺] under different [NH₄⁺] and [K⁺] concentrations. The results showed that the interference of K⁺ was substantially alleviated for NH₄⁺ measurement. The accuracy was enhanced by over 70% when examined using real wastewater and energy consumption was expected to reduce by 26% for a wastewater treatment plant, especially for wastewater with high [K⁺]. Furthermore, the uniquely structured S-ISMs were made by embedding the ionophores in a robust polyvinyl chloride (PVC) matrix containing plasticizers and a layer of carbon nanotubes (CNT) as ion-to-electron transducer, which maintained the selectivity and accuracy of the S-ISM sensor for 4 weeks in wastewater. NH₄⁺/K⁺ sensor assembly integrated with data-driven correction models poses great potential in high-efficiency and energy-saving wastewater treatment and water reuse processes.

Keywords: Ammonium; Data-driven model; Energy saving; Long-term continuous wastewater monitoring; Potassium interference; Solid-state ion-selective membrane (S-ISM).