Accurate Measurement of Ammonia Nitrogen in Water Based on Ammonium Ion-Selective Electrodes with a Hydrophobic Layer and a Parameter Compensation Strategy

Ammonia nitrogen (NH₃-N) serves as a critical water quality indicator, with excessive levels posing risks to human health. Conventional detection methods like Nessler’s reagent and salicylate colorimetry suffer from toxic byproduct generation and operational complexity. Ammonium ion-selective electrodes (NH ₄ ⁺ -ISEs) offer advantages such as reagent-free and real-time monitoring. However, during practical detection, they are susceptible to interference from unknown conditions (primarily including pH value, temperature, and potassium ions) in complex aqueous environments. In this work, we developed an all-solid-state ammonium ion-selective electrode (ASS-NH ₄ ⁺ -ISE), and eliminated the aforementioned interferences through multi-sensor collaborative detection and parameter compensation. The electrode is characterized by a hydrophobic polyaniline (PANI) solid contact layer doped with perfluorooctanoic acid (PFOA), whose hydrophobicity can effectively suppress the formation of a water layer. The electrode exhibited a Nernstian slope of 58.57 mV/dec, a limit of detection (LOD) of 2.95 µM, meeting requirements for drinking water and seawater monitoring. Furthermore, by incorporating potassium ion-selective electrode (K⁺-ISE) calibration, pH compensation, and temperature coefficient correction, accurate NH₃-N quantification under diverse conditions was achieved. We tested the ammonia nitrogen concentration in actual water samples under different interference conditions, and the recovery rate ranged from 98.1% to 105.1%, which verified the effectiveness of the system for real-time monitoring of ammonia nitrogen in complex aquatic environments. In this study, we integrated a hydrophobic solid SC layer with a multi-parameter (K⁺/pH/temperature) compensation strategy, enabling reagent-free, real-time monitoring of NH₃-N in complex water bodies without any pretreatment. This approach overcomes the limitations of previous ISEs.