Decoding Metal Associations in an Arid Urban Environment with Active and Legacy Mining: the Case of Copiapó, Chile

The urban and periurban area of Copiapó in the arid Atacama desert has more than 30 abandoned mine tailings, one active copper smelter, and 150,000 inhabitants. Fast development of the mining industry during the 19th century and unplanned growth has led to public concern about the presence of metals in soils and street dust. Recent floods and mud currents in the Copiapó watershed have introduced new solid material in about 40% of the urban area. We conducted a geochemical screening before and after the disaster in March 2015. We found concentrations as high as 1000 mg/kg of copper and 180 mg/kg of arsenic in urban soils. Since effective control measures require connecting sites of metal enrichment with the possible sources, we have performed a statistical analysis of metal association and complemented it with other analyses like x-ray diffraction. Cluster analyses of elemental compositions suggest that mud and tailing have different origins from the rest of the matrices, while soils and street dust have a similar one. Some clusters have a mix of matrices that suggest anthropogenic enrichment of some areas of Copiapó. Our initial results indicate that a correlation between observed enrichment and the copper smelter can be hypothesized for Cu, Pb, and Zn. Further spatial, statistical, and chemical analyses are needed to further confirm such findings, complemented with a thorough analysis of the baseline values that could be considered representative of the area. Future work include Principal Component Analysis (PCA) and Positive matrix factorization (PMF) to test the link contaminant sources and metal occurrence, while scanning electron microscopy can be used to identify the presence of smelter-related particles. The information generated by this research will be a necessary input for defining urban planning strategies and land use guidelines, defining health risk assessment studies, and for future evaluation of intervention priorities. Acknowledgements: Proyecto CONICYT/FONDAP 15110020