Transcript Multi-Criteria Decision Analysis and Environmental Risk Assessment for Nanomaterials

Multi-Criteria Decision Analysis and
Environmental Risk Assessment for
Nanomaterials
Igor Linkov and Rick Pleus
Intertox Inc.
83 Winchester Street Suite 1
Brookline, MA 02446
[email protected]
Jeff Steevens and Elizabeth Ferguson
Environmental Laboratory
Engineering Research and Development Center
US Army Corps of Engineers
Waterways Experiment Station, Vicksburg MS
US Army Engineer Research and Development Center
# 1
Main Points
• Relation of pattern, structure-activity and physico-chemical
properties of nanoparticles on toxicity and risk is widely
unknown
• Challenges of risk assessment for situations with a limited
knowledge base and high uncertainty and variability
require coupling traditional risk assessment with multicriteria decision analysis (MCDA) to support regulatory
decision making
• Adaptive Management and Value of Information analysis
(VOI) would provide a systematic tool for the dynamic
linkage of Nanotechnology Risk Assessment and Risk
Management with nanomaterial development goals as well
as with new information on social and economic priorities
US Army Engineer Research and Development Center
# 2
EPA Nanotechnology White Paper:
Peer Review Panel Summary
• Risk Assessment Challenges
– Current risk assessment experience is for chemicals
and stable agents and not for engineered materials
– Relation of pattern, structure-activity and physicochemical properties of nanoparticles on toxicity and
risk is widely unknown
– Uncertainty in exposure assessment, risk
characterization and dose-response is unprecedented
• Regulatory Challenges
– Immediate regulatory need
– Environmental evaluations and decisions are growing
more complex and current RA paradigm may not be
appropriate
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# 4
Problem: Model Uncertainty
y = 3x - 0.6667
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Polynom ial Model
y = 2x2 - 5x + 6
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• Model Uncertainty
– Differences in model structure resulting
from:
 model objectives
 computational capabilities
 data availability
 knowledge and technical expertise of the
group
– Can be addressed by
 considering alternative model structures
 weighting and combining models
 Eliciting expert judgment
Linear Model
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Mechanistic models for nanoparticle toxicity and exposure are
very uncretain and expert judgement is required
US Army Engineer Research and Development Center
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Problem: Parameter Uncertainty
• Parameter Uncertainty
– Uncertainty and variability in
model parameters resulting from
 data availability
 expert judgment
 empirical distributions
– Can be addressed by
 Probabilistic Simulations (MonteCarlo)
 Analytical techniques (uncertainty
propagation)
 Expert estimates
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Nanomaterial properties are not well known, reported ranges
are large and often unquantifiable
US Army Engineer Research and Development Center
# 6
Decision-Making Processes for Nanomaterial Risk
Assessment and Regulation
Decision-Maker(s)
AD HOC Process
Include/Exclude?
•Detailed/Vague?
•Certain/Uncertain?
•Consensus/Fragmented?
• Iterative?
• Rigid/unstructured?
Quantitative?
Tools
Risk
Analysis
Qualitative?
Modeling /
Monitoring
Cost or
Benefits
Stakeholders’
Opinion
US Army Engineer Research and Development Center
# 7
Challenges to Complex Decision-making
• “Humans are quite bad at making complex, unaided
decisions” (Slovic et al., 1977).
• Individuals respond to complex challenges by using
intuition and/or personal experience to find the easiest
solution.
• At best, groups can do about as well as a well-informed
individuals if the group has some natural systems
thinkers within it.
• Groups can devolve into entrenched positions resistant
to compromise
• “There is a temptation to think that honesty and
common sense will suffice” (IWR-Drought Study p.vi)
US Army Engineer Research and Development Center
# 8
Evolving Decision-Making Processes
Decision-Maker(s)
Decision Analytical Frameworks
• Agency-relevant/Stakeholder-selected
• Currently available software
•Variety of structuring techniques
• Iteration/reflection encouraged
•Identify areas for discussion/compromise
Decision
Integration
Tool Integration
Risk
Analysis
Modeling /
Monitoring
Cost
Stakeholders’
Opinion
Sharing Data,Concepts and Opinions
US Army Engineer Research and Development Center
# 9
Multi-Criteria Decision Analysis and Tools
• Multi-Criteria Decision Analysis (MCDA) methods:
– Evolved as a response to the observed inability of people
to effectively analyze multiple streams of dissimilar
information
– Many different MCDA approaches based on different
theoretical foundations (or combinations)
• MCDA methods provide a means of integrating various
inputs with stakeholder/technical expert values
• MCDA methods provide a means of communicating
model/monitoring outputs for regulation, planning and
stakeholder understanding
• Risk-based MCDA offers an approach for organizing
and integrating varied types of information to perform
rankings and to better inform decisions
US Army Engineer Research and Development Center
# 10
How can CRA, MCDA and AM improve the quality and
acceptability of decisions?
Adaptive
Management
Problems
Alternatives
Criteria
Evaluation
MCDA
Feeds
RA
Decision Matrix
Weights
RA
Synthesis
RA
Feeds
MCDA
Decision
MCDA
Case Study 1: Use of MCDA to Select the
Best Nanomaterial
• Problem: Several nanomaterials have been identified
for specific application with varying costs and benefits
and potential risks
• Societal importance and public aceptability may be
important for selection/prioritization decision
US Army Engineer Research and Development Center
# 12
AHP : Case Study - Results
US Army Engineer Research and Development Center
# 13
Case Study 2: Use of MCDA to Support
Support Weight-of-evidence Evaluation for
Nanoparticle Toxicity
• Problem: Toxic effects of nanomaterials are uncertain.
Multiple experimental studies are available that results
in contradictory conclusions. Experimental studies
have varying degree of scientific credibility and trust
US Army Engineer Research and Development Center
# 14
Eco Risk Assessment:
Assessment Endpoints
US Army Engineer Research and Development Center
# 15
Summary: Essential Decision Ingredients
People:
Policy Decision Maker(s)
Scientists and Engineers
Stakeholders (Public, Business, Interest groups)
Process:
Identify criteria to
compare alternatives
Define Problem &
Generate Alternatives
Gather value judgments
on relative importance
of the criteria
Screen/eliminate
clearly inferior
alternatives
Determine
performance of
alternatives for
criteria
Rank/Select final
alternative(s)
Tools:
Environmental Assessment/Modeling (Risk/Ecological/Environmental Assessment and Simulation Models)
Decision Analysis (Group Decision Making Techniques/Decision Methodologies and Software)
US Army Engineer Research and Development Center
# 16
Main Points
• Relation of pattern, structure-activity and physico-chemical
properties of nanoparticles on toxicity and risk is widely
unknown
• Challenges of risk assessment for situations with a limited
knowledge base and high uncertainty and variability
require coupling traditional risk assessment with multicriteria decision analysis (MCDA) to support regulatory
decision making
• Adaptive Management and Value of Information analysis
(VOI) would provide a systematic tool for the dynamic
linkage of Nanotechnology Risk Assessment and Risk
Management with nanomaterial development goals as well
as with new information on social and economic priorities
US Army Engineer Research and Development Center
# 17