AUTHOR=Pantuzzo Fernando Luís , Laureano Fernando Verassani , Cabral Caíque Lima , Salomão Gabriel Negreiros , Dall’Agnol Roberto , Pimenta Vitor Brognaro , Leão Lucas Pereira 

TITLE=Rapid and low-cost geochemical indices for tracing iron mining tailings within fluvial sediments: a case study from the Paraopeba River after the B1 Dam burst in Brumadinho, Minas Gerais, Brazil

JOURNAL=Frontiers in Soil Science

VOLUME=Volume 5 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/soil-science/articles/10.3389/fsoil.2025.1617526

DOI=10.3389/fsoil.2025.1617526

ISSN=2673-8619

ABSTRACT=The B1 dam failure at Córrego do Feijão mine in Brumadinho (Minas Gerais, Brazil) in January 2019 caused severe and long-lasting environmental impacts, particularly on the fluvial sediments of the Paraopeba River basin. Characterizing the geochemical signature of the iron tailings and, especially, distinguishing these materials from the river’s natural sediments remains a significant challenge. In this context, the present study investigates the geochemical signatures of major and minor elements in sediments affected by the tailings and proposes a set of geochemical indices capable of identifying the presence of tailings in impacted sediments. Six cores from a drilling program were extracted along the Paraopeba River bedload. A total of 54 samples were collected, and subsequently subjected to X-ray fluorescence analysis to determine the major and minor elements (Al2O3, CaO, Fe, MgO, Mn, P, SiO2, and TiO2). The main constituents in natural sediment samples were SiO2 and Al2O3, which together accounted for 52.7% to 96.6%, while Fe2O3 represented 1.1% to 42.7%. Conversely, in tailings samples, Fe2O3 concentrations ranged from 36.6% to 88.8%, followed by silica (8.4% to 34.4%) and alumina (0.87% to 19.1%). Fe2O3 levels were above 60% in most of the tailing’s samples. Natural sediment samples generally had higher TiO2, CaO, and MgO content than tailings samples, which, in turn, showed generally higher levels of MnO and P2O5. Based on the aforementioned data, we proposed two chemical compositional indices, IRS1 and IRS2, which are rapid and low-cost to calculate. Due to the compositional characteristics of tailings and sediments, IRS values spread on an opposite diagonally shape when dispersed on a binary IRS1 x IRS2 graph. The pair of indices was applied to stream sediment samples from the Paraopeba River, collected in 2019 as part of the Emergency Monitoring Program. The results indicated that samples classified as tailings were concentrated upstream of the UTE Igarapé reservoir spillway, reinforcing the importance of the reservoir in reducing the propagation of tailings along the Paraopeba River channel. Moreover, when the indices are applied to stream sediment samples collected in 2023 from affected areas where tailings have been subjected to dredging activities, low IRS1 and IRS2 values are observed. Thus, considering the large amount of data generated by the sediment monitoring activities in the Paraopeba River basin, the proposed indices serve as a graphical tool for tracking the dispersion of tailings on a spatial and temporal scale.