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