Relating magnetic properties of municipal solid waste constituents to iron content : implications for enhanced landfill mining

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.%, 1 sigma). 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)

Influence of material alterations and machine impairment on throughput related sensor-based sorting performance

Experiments with sensor-based sorting (SBS) machinery provide insight into the effect of throughput rate and input composition on the sorting performance. For this purpose, material mixtures with certain compositions and particle size distributions were created from waste fractions and sorted at various throughput rates. To evaluate the sorting performance of the SBS unit (using near infrared technology) in dependence of the applied load, four assessment factors concerning the output fractions were studied: yield, product purity, recovery/product quantity and incorrectly discharged share of reject particles. The influences on the assessment parameters of light twodimensional (2D) particles in the input of a sorting stage and failing air valves in an SBS unit were evaluated for various input compositions at different throughput rates. It was found that a share of approximately 5 wt% 2D particles in the input had a similar negative effect on the yield as the malfunction of 20% of all air valves in an SBS machine at high throughput rates. Additionally, the failure of the air valves reduced the product purity of the sorting stage at increased throughput rates. Furthermore, qualitative observations concerning systematic effects of prior studies could be confirmed. Resulting graphs for a specific input composition of an SBS unit at varying throughput rates could be used to adjust the throughput rate to meet the exact demands for a sorting stage