Accurate Detection of Cd2+ and Pb2+ Concentrations in Soils by Stripping Voltammetry Peak Areas under the Mutual Interference of Multiple Heavy Metals

The accurate detection of Cd2+ and Pb2+ in soils by square-wave anodic stripping voltammetry (SWASV) faces great challenges because the interaction between multiple heavy metal ions (HMIs) interferes seriously with their SWASV signals. To detect high accuracy, an overlooked but informative signal, i.e., current peak area, was employed combined chemometric methods to suppress above mutual interference. An easy-to-prepare electrode, in-site electroplating bismuth film modified glassy carbon used sense HMIs. Two machine learning algorithms, including SVR PLSR, were establish models Pb2+. In addition, this study developed a homemade algorithm automatically acquire heights areas Zn2+, Cd2+, Pb2+, Bi3+, Cu2+, which acted as inputs models. Then, performance various PLSR compared based on R2 RMSE values validation dataset. Results showed that established algorithmically acquired presented best stability accuracy for detecting both concentrations under existence Zn2+ Cu2+. built using HMIs electrochemical workstation control software (Imanu-SVR) 0.7650 5.3916 μg/L 0.8791 20.0015 respectively; area (Aalgo-SVR) 0.9204 2.9906 0.9756 13.1574 respectively. More importantly, results proposed method real soil extracts close those ICP-MS, verifying its practicability. This provides new solution targeted metals co-existence method.