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Open Access Green as soon as Postprint is submitted to ZB.
A nanomaterial release model for waste shredding using a Bayesian belief network.
J. Nanopart. Res. 20:33 (2018)
The shredding of waste of electrical and electronic equipment (WEEE) and other products, incorporated with nanomaterials, can lead to a substantial release of nanomaterials. Considering the uncertainty, complexity, and scarcity of experimental data on release, we present the development of a Bayesian belief network (BBN) model. This baseline model aims to give a first prediction of the release of nanomaterials (excluding nanofibers) during their mechanical shredding. With a focus on the description of the model development methodology, we characterize nanomaterial release in terms of number, size, mass, and composition of released particles. Through a sensitivity analysis of the model, we find the material-specific parameters like affinity of nanomaterials to the matrix of the composite and their state of dispersion inside the matrix to reduce the nanomaterial release up to 50%. The shredder-specific parameters like number of shafts in a shredder and input and output size of the material for shredding could minimize it up to 98%. The comparison with two experimental test cases shows promising outcome on the prediction capacity of the model. As additional experimental data on nanomaterial release becomes available, the model is able to further adapt and update risk forecasts. When adapting the model with additional expert beliefs, experts should be selected using criteria, e.g., substantial contribution to nanomaterial and/or particulate matter release-related scientific literature, the capacity and willingness to contribute to further development of the BBN model, and openness to accepting deviating opinions.
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
Bayesian Belief Network ; Shredding ; Recycling ; Release ; Nanomaterial ; Environmental Risk Assessment; Health-risk Assessment; Engineered Nanomaterials; Nanoparticle Emission; Inhalation Exposure; Conceptual-model; Carbon Nanotubes; Life-cycle; Environment; Challenges; Tio2
ISSN (print) / ISBN
1388-0764
e-ISSN
1572-896X
Journal
Journal of Nanoparticle Research
Quellenangaben
Volume: 20,
Issue: 2,
Article Number: 33
Publisher
Springer
Publishing Place
Dordrecht
Non-patent literature
Publications
Reviewing status
Peer reviewed
Institute(s)
Lung Health and Immunity (LHI)