Sunjae Lee, Narae Lee1, Minju Kim, Hyunwook Cho, Hyunbin Jo, Haeseok Lee, Jaeyoung Choi
언어
영어(ENG)
URL
https://www.earticle.net/Article/A457278
원문정보
초록
영어
Stream and lake sediments are often subject to contamination by heavy metals due to both natural processes and human activities, such as industrial waste disposal and steel production. Lead (Pb), one of the most concerning contaminants, is a potent neurotoxin that can accumulate to hazardous levels, threatening both aquatic ecosystems and human health. Pb has a strong affinity for binding to fine-grained sediments and organic matter, and its adsorption is highly dependent on factors such as pH and the organic content of the sediments. In this study, we aimed to assess Pb contamination in sediments by utilizing electrical resistivity measurements in combination with multivariate statistical techniques. Sediment samples were systematically collected and analyzed for Pb concentrations using aqua regia extraction. Electrical resistivity was measured using a Sample Core Induced Polarization (SCIP) device to evaluate the geophysical properties of the sediments. The resulting geochemical and geophysical data were then analyzed using multivariate statistical methods to explore the relationships between these datasets and derive regression models. These models were employed to estimate and verify Pb contamination levels based on the electrical properties of the sediments.