Assessment of iron-rich tailings via portable X-ray fluorescence spectrometry: the Mariana dam disaster, southeast Brazil

Gabriel W.D. Ferreira, Bruno T. Ribeiro, David C. Weindorf, Barbara I. Teixeira, Somsubhra Chakraborty, Bin Li, Luiz Roberto G. Guilherme, José Roberto S. Scolforo

Research output: Contribution to journalArticlepeer-review

Abstract

On November 5, 2015, the Fundão dam collapsed and released > 60 million m3 of iron-rich mining sediments into the Doce river basin, covering >1000 ha of floodplain soils across ~80 km from the rupture. The characterization of alluvial mud covering and/or mixed with native soil is a priority for successful environmental rehabilitation. Portable X-ray fluorescence (pXRF) spectrometry was used to (1) assess the elemental composition of native soils and alluvial mud across impacted riparian areas; and 2) predict fertility properties of the mud and soils that are crucial for environmental rehabilitation and vegetation establishment (e.g., pH, available macro and micronutrients, cation exchange capacity, organic matter). Native soils and alluvial mud were sampled across impacted areas and analyzed via pXRF and conventional laboratory methods. Random forest (RF) regression was used to predict fertility properties using pXRF data for pooled soil and alluvial mud samples. Mud and native surrounding soils were clearly differentiated based on chemical properties determined via pXRF (mainly SiO2, Al2O3, Fe2O3, TiO2, and MnO). The pXRF data and RF models successfully predicted pH for pooled samples (R2 = 0.80). Moderate predictions were obtained for soil organic matter (R2 = 0.53) and cation exchange capacity (R2 = 0.54). Considering the extent of impacted area and efforts required for successful environmental rehabilitation, the pXRF spectrometer showed great potential for screening impacted areas. It can assess total elemental composition, differentiate alluvial mud from native soils, and reasonably predict related fertility properties in pooled heterogeneous substrates (native soil + mud + river sediments).

Original languageEnglish
Article number203
JournalEnvironmental Monitoring and Assessment
Volume193
Issue number4
DOIs
StatePublished - Apr 2021

Keywords

  • Environmental monitoring
  • Mining activities
  • PXRF
  • Proximal sensors
  • Random forest
  • Samarco dam collapse

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