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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Kononenko, Denys |
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Petrov, R. H. | Madrid |
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Alshaaer, Mazen | Brussels |
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Bih, L. |
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Casati, R. |
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Muller, Hermance |
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Kočí, Jan | Prague |
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Šuljagić, Marija |
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Kalteremidou, Kalliopi-Artemi | Brussels |
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Azam, Siraj |
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Ospanova, Alyiya |
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Blanpain, Bart |
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Ali, M. A. |
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Popa, V. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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Vollprecht, Daniel
University of Augsburg
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (13/13 displayed)
- 2022Evaluation of improvements in the separation of monolayer and multilayer films via measurements in transflection and application of machine learning approachescitations
- 2022Qualitative analysis of post-consumer and post-industrial waste via near-infrared, visual and induction identification with experimental sensor-based sorting setupcitations
- 2020Dense glass‐ceramics by fast sinter‐crystallization of mixtures of waste‐derived glassescitations
- 2020X-ray fluorescence sorting of non-ferrous metal fractions from municipal solid waste incineration bottom ash processing depending on particle surface propertiescitations
- 2020Recovery of Molybdenum, Chromium, Tungsten, Copper, Silver, and Zinc from Industrial Waste Waters Using Zero-Valent Iron and Tailored Beneficiation Processescitations
- 2019Quality assessment of nonferrous metals recovered from landfill mining: a case study in Belgiumcitations
- 2019QUALITY ASSESSMENT OF NONFERROUS METALS RECOVERED BY MEANS OF LANDFILL MININGcitations
- 2019RELATING MAGNETIC PROPERTIES OF MUNICIPAL SOLID WASTE CONSTITUENTS TO IRON CONTENT – IMPLICATIONS FOR ENHANCED LANDFILL MININGcitations
- 2019Potential of sensor-based sorting in enhanced landfill miningcitations
- 2019CASE STUDY ON ENHANCED LANDFILL MINING AT MONT-SAINTGUIBERT LANDFILL IN BELGIUMcitations
- 2018Recovery of Metals from Industrial Waste Waters
- 2018Potential and main technological challenges for material and energy recovery from fine fractions of landfill mining: A critical reviewcitations
- 2018Characterization of Fine Fractions from Landfill Mining: A Review of Previous Investigationscitations
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article
Potential of sensor-based sorting in enhanced landfill mining
Abstract
In landfill mining, simple technologies and processing chains are frequently applied to excavated material in order to extract recyclable metals and high-calorific fractions used in energy recovery. Sensor-based sorting is one way to extract more and better material from a landfill. Two testing series have been performed using state-of-the-art technology to assess the technical feasibility of classifying and sorting landfill material with the aid of near-infrared spectroscopy. Fractions were classified as inert and combustible and sorted by particle sizes ranging from 90-30 mm, from 30-10 mm and from 10-4.5 mm for water content levels of 0 wt% and of 15 wt%, respectively. Additional tests applied different landfill mining materials. Polypropylene (PP), polyethylene (PE) and polyvinyl chloride (PVC) products were produced, using sensor-based sorting, from a mixed fraction of particle sizes ranging from 60-200 mm. Both test series applied air-classified heavy fractions gained from two distinct processing schemes of landfill mining projects in Belgium and in Austria. Results show that the separation and classification of inerts and combustibles is feasible, enriching inert fractions with purities of 97.7 wt% to 99.6 wt% derived from inputs whose inert contents achieved 85.6 to 98.8 wt%. Efficient sorting is a function of the level of pre-processing, water content, relative amounts of adhesive fines, input composition and particle size ranges of the input material. Results from the second test series show that PP, PE, PVC and other materials can be successfully distinguished, achieving correct classification and ejection into respective product fractions of 91.8-99.7 wt%.