The contamination of creek sediments near industrially nuclear dominated site presents significant environmental challenges, particularly in identifying and quantifying potentially toxic metal (loid)s (PTMs). This study aims to measure the extent of contamination and apportion related sources for nine PTMs in alpine creek sediments near a typical uranium tailing dam from China, including strontium (Sr), rubidium (Rb), manganese (Mn), lithium (Li), nickel (Ni), copper (Cu), vanadium (V), cadmium (Cd), zinc (Zn), using multivariate statistical approach and Sr isotopic compositions. The results show varying degrees of contamination in the sediments for some PTMs, i.e., Sr (16.1-39.6 mg/kg), Rb (171-675 mg/kg), Mn (224-2520 mg/kg), Li (11.6-78.8 mg/kg), Cd (0.31-1.38 mg/kg), and Zn (37.1-176 mg/kg). Multivariate statistical analyses indicate that Sr, Rb, Li, and Mn originated from the uranium tailing dam, while Cd and Zn were associated with abandoned agricultural activities, and Ni, Cu, and V were primarily linked to natural bedrock weathering. The Sr isotope fingerprint technique further suggests that 48.22-73.84% of Sr and associated PTMs in the sediments potentially derived from the uranium tailing dam. The combined use of multivariate statistical analysis and Sr isotopic fingerprint technique in alpine creek sediments enables more reliable insights into PTMs-induced pollution scenarios. The findings also offer unique perspectives for understanding and managing aqueous environments impacted by nuclear activities.
Keywords: Hydrometallurgy; Metal isotopes; Multivariate statistical analysis; Process safety; Uranium tailings.
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