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RISK ANALYSIS AND MANAGEMENT: NANOSCIENCE David M. Berube Professor of Science Communication, STS, and CRDM (Communication, Rhetoric and Digital Media), North Carolina State University Director: NCSU Public Communication of Science and Technology (PCOST) Project. Manager, Center for Converging Technologies, LLC – social media consultancy (trade assns and food industry). PI: NSF NIRT #0809470 – Intuitive Toxicology and Public Engagement, 2007-2011 http://pcost.org Society for Risk Analysis© Berube December 7, 2010 – Salt Lake City, UT
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Status Quo – regulate under current rules (EPA). Enhanced regulation Occup. EHS – promulgate rules for types of nanoparticles. Product related – promulgate rules by agency mandate – USDA, FDA & CPSC. NANO-GOVERNANCE (1)
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Stipulated regulation. Safety Data Sheet. Labeling. Restricted regulation. Import-export restrictions by application (WTO). Outright bans on some or all applications. NANO-GOVERNANCE (2)
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1. Hyper-acceleration. 2. Public complexity. 3. Digital obfuscation. 4. Suspect experts/expertise. 5. Fact/fictionality. UNCERTAINTY: OVER-ARCHING VARIABLES
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CHARACTERISTICS AND CLASSIFICATION OF NANOPARTICLES: EXPERT DELPHI SURVEY (Nanotoxicology 30 Sep 2010. doi:10.3109/17435390.2010.521633).
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EXPERT DELPHI SURVEY (Nanotoxicology 30 Sep 2010. doi:10.3109/17435390.2010.521633)
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RAND – cross-impact matrix (Dalkey 1971) IRGC – International Risk Governance Council. CBEN (Rice) and ICON. CET - Return on Investment. ORIGINS Future assessment tool used in identifying main forces in a firm's environment, and in estimating their collective impacts. Each force or factor is assigned a score (usually between -10 and +10) in a table (matrix) based on its own strength and the strength of its interactions. On adding up, the scores separate the 'driving' forces from 'inhibiting' forces.
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High Uncertainty/High Risk – ETC/Soil Association/FoE-A. Some Uncertainty/Some Risk – Voluntary Stewardship. Some Uncertainty/Low Risk – Best/Common/Good Practice. Low Uncertainty/Low Risk – Self- regulation/Asilomar Model. SCENARIO MODELING High Uncertainty/High Risk – ETC/Soil Association/FoE-A.
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R(θ,δ(x)) = ∫ L(θ, δ(x)) f(x|θ) dx δ(x) = estimator. Θ = parameter. L = loss function. x = observables. What constitutes data? How do we collect data? Are some data privileged over others? How do we resolve contradictions? When do we have enough data? ON FUZZINESS finite data
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IF we defined C = ~V then Violating the law of the Excluded Middle IF C = ~V CV y ON FUZZINESS
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I. I. Nomenclature. II. II. Classification. III. III. Monitoring. IV. IV. Characterization. 1.size, 2.composition, 3.surface area to volume, 4.surface coating, 5.shape and surface curvature, 6.surface charge, 7.contaminants and impurities, 8.surface hydrophobicity, 9.surface defects, 10.fibrosity, 11.porosity, and/or 12.density UNCERTAINTY: NANOPARTICLES SETS
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Multiple sets. About membership among/between sets. Value of membership from none to total.
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Landfill pollution. Soil and sediments pollution. Groundwater contamination. River water quality management. Hydrocarbon contamination. ON FUZZINESS Cadmium in surficial soils. Dredging. Flood control. Nitrate contamination. Highway bridge safety.
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Merge with cross-impact matrix (multi- dimensional) (1)Scientific reasoning model. (2)Human reasoning model. (Tesfemariam & Sadiz 2006)
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ON FUZZINESS - PROJECTS Decide on the sets appropriate for data management. Decide on the dimensions – characteristics, exposure, etc. Decide on the method(s) – hybrid approaches of fuzzy set theory in conjunction stochastic techniques. (Maybe, crossing fuzzy set theory with cross-impact matrices.) Experiment with rounds of estimations.
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Society for Risk Analysis© Berube December 7, 2010 – Salt Lake City, UT RISK ANALYSIS AND MANAGEMENT: NANOSCIENCE This work was supported in part by grants from the National Science Foundation, NSF 0809470, Nanotechnology Interdisciplinary Research Team (NIRT): Intuitive Toxicology and Public Engagement. NCSU, U Wisconsin, U Minnesota, U South Carolina, & Rice U. (6 grad. students). THANKS dmberube@ncsu.edu
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