Application of fingerprint-based multivariate statistical analyses in source characterization and tracking of contaminated sediment migration in surface water

作者：Chen Fei^*; Taylor William D; Anderson William B; Huck Peter M

来源：Environmental Pollution, 2013, 179: 224-231.

DOI：10.1016/j.envpol.2013.04.028

• Drinking water source protection
• Fingerprint analysis
• Multivariate statistical analysis
• Sediment transport

This study investigates the suitability of multivariate techniques, including principal component analysis and discriminant function analysis, for analysing polycyclic aromatic hydrocarbon and heavy metal-contaminated aquatic sediment data. We show that multivariate %26quot;fingerprint%26quot; analysis of relative abundances of contaminants can characterize a contamination source and distinguish contaminated sediments of interest from background contamination. Thereafter, analysis of the unstandardized concentrations among samples contaminated from the same source can identify migration pathways within a study area that is hydraulically complex and has a long contamination history, without reliance on complex hydrodynamic data and modelling techniques. Together, these methods provide an effective tool for drinking water source monitoring and protection.

• 出版日期2013-8