Optimization of electrochemical nitrate detection on a commercial copper electrode using D-optimal response surface methodology

Accurate and reliable nitrate detection is essential for water quality monitoring, especially in the face of rising contaminant loads from human activities. Electrochemical sensors with copper electrodes present a promising alternative to conventional nitrate detection methods. However, their broader application is limited by electrode passivation, interference from coexisting species and the requirement for solution deaeration. This study presents a simple in-situ activation strategy that prevents passivation, removes the deaeration requirement and ensures stable sensor performance. A commercial copper electrode was used for nitrate detection via linear sweep voltammetry. A multi-factor interaction approach was employed to optimize four experimental factors based on a D-optimal response surface methodology (RSM) model, providing a deeper understanding of the synergistic effects among variables. Under optimized conditions, the sensor achieved a sensitivity of 2.86 µA/µM and a limit of detection (LOD) of 22.84 µM within a linear range of 100–800 µM. In addition, the sensor showed excellent reproducibility (RSD = 1.26 ± 0.33%) and maintained signal stability for 15 consecutive measurements at two different concentrations. Interference studies confirmed negligible effects from most ions, with nitrite enhancing the response via oxidation. Calculations showed a matrix effect (M.E.) of 10.61% and 6.82%, respectively for tap and river water with recoveries of 96–109%. Furthermore, Chow tests revealed no significant matrix effects. The sensor measurements were consistent with the spectrophotometric method, with an error of 3.35%. Collectively, these findings demonstrate the robustness, reliability, and practicality of this copper-based sensor for routine nitrate monitoring in environmental and drinking water systems. • In-situ activation prevents copper electrode passivation without deaeration. • D-optimal RSM enables efficient multi-factor optimization of nitrate sensor performance. • Sensor shows high nitrate selectivity and reproducibility. • Validation in real matrices with Chow tests, recovery calculation and comparison with spectrophotometric method.