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Editor in Chief: RAFFAELLO COSSU

RELATING MAGNETIC PROPERTIES OF MUNICIPAL SOLID WASTE CONSTITUENTS TO IRON CONTENT – IMPLICATIONS FOR ENHANCED LANDFILL MINING

  • Daniel Vollprecht - Montanuniversität Leoben, Austria
  • Christin Bobe - Department of Environment, Ghent University, Belgium
  • Roman Stiegler - Montanuniversitat Leoben, Austria
  • Ellen van de Vijver - Department of Environment, Ghent University, Belgium
  • Tanja Wolfsberger - Montanuniversität Leoben, Austria
  • Bastian Küppers - Montanuniversität Leoben, Austria
  • Robert Scholger - Chair of Applied Geophysics, Montanuniversität Leoben, Austria

DOI 10.31025/2611-4135/2019.13876

Released under CC BY-NC-ND

Copyright: © 2019 CISA Publisher

Editorial History

  • Received: 07 Jun 2019
  • Revised: 09 Sep 2019
  • Accepted: 11 Sep 2019
  • Available online: 23 Dec 2019

Abstract

Ferrous metals are a main recyclable waste fraction in Enhanced Landfill Mining (ELFM) projects. However, prior to mining, the metal content of municipal solid waste (MSW) landfills is unknown. We investigate if the metal content of MSW landfills can be estimated by inverse modeling of geophysical measurements as the magnetic properties of the subsurface are particularly sensitive to ferromagnetic metal enrichments. We conducted magnetic total-field measurements on a MSW landfill in Austria and estimated the bulk magnetic susceptibility (MS) of the subsurface by inverse modelling. For validation of the subsurface MS values, 32 drill-core samples from multiple locations and depths within the landfill were obtained and manually sorted into 12 waste fractions including ferrous metals (2.3 ± 1.4 wt.%, 1σ). To investigate if bulk MS could be accurately predicted from inverse modeling when the exact composition of the waste is known, the MS of iron and other expected waste fractions were investigated in laboratory analysis using reference samples from waste treatment plants and another ELFM project. Laboratory analyses partly yielded significantly larger MS values for waste materials than those given for virgin materials in literature. The bulk MS for each sample from the ELFM project was computed using a weighted mean with respect to the waste composition derived from manual sorting. The bulk MS derived from inverse modelling of the field data (0.06 to 0.11 SI) exceeded the bulk MS derived from the material composition of waste samples and the MS values of reference samples (0.01 to 0.05 SI).

Keywords


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