Source quantitative identification and control for preferential contaminants in stream sediments from an abandoned lead/zinc mine

Abstract

Sediment is an important sink for metals within mining environments. This study employs a combination of positive matrix factorization (PMF), random forest (RF) and fuzzy analytic hierarchy process (FAHP) to investigate the source attribution and released effects of toxic elements in stream sediments originating from an abandoned lead/zinc mine. The results show that the integrated PMF-RF-FAHP approach allows for the quantitative identification of metal sources and the prioritization of control measures within the mine. The primary source of contamination in the mine stream sediments was identified as the toxic elements releasing from the ore sorting area, followed by contributions from the mining area. The transport of toxic elements from mine into stream sediments is influenced by surface water flows, of which the upstream ore sorting area is an important factor to the contamination of the tailings area, riparian zone and hazardous waste landfills. The levels of main toxic elements, such as As, Cd, Sb, and Tl in stream sediments significantly exceed the background values for stream sediments in China, respectively. The similarities in sources for As, Cd, Sb and Tl in both soils and sediments exceeded 60%. The ore sorting area accounted for 48% of As, 82% of Cd and 78% of Sb contamination, while the mining area accounted for 94% of Tl contamination. This study presents a valuable methodology for pinpointing pollutant sources in mines rich in toxic elements like As and Cd. It is valuable and helpful to provide insights into tracing metal contamination and facilitating regional environmental management, both during mine industrialization and after abandonment.