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Risk-based Classification System of Nanomaterials
Tervonen, Tommi ; Linkov, Igor ; Figueira, Jose R ; Steevens, Jeffery ; Chappell, Mark ; Merad, Myriam
2008
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Título:
Risk-based Classification System of Nanomaterials
Autor:
Tervonen, Tommi
;
Linkov, Igor
;
Figueira, Jose R
;
Steevens, Jeffery
;
Chappell, Mark
;
Merad, Myriam
Assuntos:
AGGLOMERATES
;
BIOACCUMULATION POTENTIAL
;
BIOAVAILABILITY
;
BIOLOGY
;
CHARGED PARTICLES
;
CLASSIFICATION
;
CONTAMINANT DISSOCIATION
;
CONTAMINANTS
;
DECISION AIDS
;
DISSOCIATION
;
FUNCTIONAL GROUPS
;
GOVERNANCE
;
LIFE CYCLES
;
MANUFACTURING
;
MANUFACTURING PROCESSES
;
MCDA(MULTI-CRITERIA DECISION ANALYSIS)
;
METRICS
;
Miscellaneous Materials
;
NANOMATERIALS
;
NANOTECHNOLOGY
;
PARTICLE SIZE
;
Physical Chemistry
;
PHYSICOCHEMICAL PROPERTIES
;
RISK ANALYSIS
;
RISK ASSESSMENT
;
SMAA(STOCHASTIC MULTICRITERIA ACCEPTABILITY ANALYSIS)
;
Statistics and Probability
;
STOCHASTIC PROCESSES
;
TOXICITY
;
Toxicology
;
UNCERTAINTY
Notas:
DTIC
Descrição:
Various stakeholders are increasingly interested in the potential toxicity and other risks associated with nanomaterials throughout the different stages of a product's life cycle (e.g., development, production, use, disposal). Risk assessment methods and tools developed and applied to chemical and biological materials may not be readily adaptable for nanomaterials because of the current uncertainty in identifying the relevant physico-chemical and biological properties that adequately describe the materials. Such uncertainty is further driven by the substantial variations in the properties of the original material due to variable manufacturing processes employed in nanomaterial production. To guide scientists and engineers in nanomaterial research and application as well as to promote the safe handling and use of these materials, we propose a decision support system for classifying nanomaterials into different risk categories. The classification system is based on a set of performance metrics that measure both the toxicity and physico-chemical characteristics of the original materials, as well as the expected environmental impacts through the product life cycle. Stochastic multicriteria acceptability analysis (SMAA-TRI), a formal decision analysis method, was used as the foundation for this task. This method allowed us to cluster various nanomaterials in different ecological risk categories based on our current knowledge of nanomaterial physico-chemical characteristics, variation in produced material, and best professional judgments. SMAA-TRI uses Monte Carlo simulations to explore all feasible values for weights, criteria measurements, and other model parameters to assess the robustness of nanomaterial grouping for risk management purposes. Published in the Journal of Nanoparticle Research, 2008. The original document contains color images. Prepared in cooperation with the Faculty of Economics and Business, Univ of Groningen, The Netherlands, CEG-IST, Centre for Management Studies, Instituto Superior Tecnico, Technical University of Lisbon, Portugal, LAMSADE, Universite Paris, Paris, France, and Societal Management of Risks Unit/Accidental Risks Division, INERIS BP 2, Verneuil-en-Halatte, France.
Data de criação/publicação:
2008
Idioma:
Inglês
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