Electroanalytical Sensing of Lead in Drinking Water: Optimization of Voltammetry Conditions and Matrix Effects on Detection and Quantification

Abstract

Lead (Pb2+) contamination in drinking water remains a persistent public health threat due to corrosion of aging distribution infrastructure. This study develops and optimizes an electroanalytical method for Pb2+ detection using anodic stripping voltammetry and differential pulse voltammetry (ASV/DPV) with a 2 mm boron-doped diamond (BDD) electrode. Deposition potential, deposition time, and DPV waveform parameters were optimized in acetate-buffered electrolyte (pH ~4.5) with KCl as a supporting electrolyte to control ionic strength, maximizing sensitivity while minimizing background. Under optimal conditions (20 min deposition at -1.8 VAg/AgCl), the method achieved a limit of detection of 1.8 µg L-1 and a limit of quantification of 5.3 µg L-1, satisfying the USEPA action level requirements. Matrix effects, including ionic strength, pH buffering, and natural organic matter (NOM), on sensor performance were evaluated. In unbuffered conditions, no measurable Pb response was observed, and increasing KCl improved signal magnitude and repeatability. Fulvic and humic acids suppressed Pb response substantially at 1–2 mg L-1, consistent with reduced labile Pb due to complexation. To assess potential interferences, Pb2+ was measured in synthetic solutions containing 22 coexisting elements and only Cd and Cu produced distinct stripping peaks within the scanned window and the Pb peak remained resolvable. Application of the method to a real drinking water sample (2.3 µg L-1 Pb2+) demonstrated underestimation by ASV/DPV due to NOM interference. Overall, BDD-based ASV/DPV provides sensitive Pb detection for low-cost, point-of-use Pb monitoring, while highlighting the need for preconditioning steps to mitigate complexation effects in natural water matrices.

Keywords: Anodic stripping voltammetry, Differential pulse voltammetry, Lead sensor, Boron-doped diamond, Electroanalytical sensor, Drinking water quality monitoring