A decision-directed approach for prioritizing research into the impact of nanomaterials on the environment and human health.

The emergence of nanotechnology has coincided with an increased recognition of the need for new approaches to understand and manage the impact of emerging technologies on the environment and human health. Important elements in these new approaches include life-cycle thinking, public participation and adaptive management of the risks associated with emerging technologies and new materials. However, there is a clear need to develop a framework for linking research on the risks associated with nanotechnology to the decision-making needs of manufacturers, regulators, consumers and other stakeholder groups. Given the very high uncertainties associated with nanomaterials and their impact on the environment and human health, research resources should be directed towards creating the knowledge that is most meaningful to these groups. Here, we present a model (based on multi-criteria decision analysis and a value of information approach) for prioritizing research strategies in a way that is responsive to the recommendations of recent reports on the management of the risk and impact of nanomaterials on the environment and human health.

Use of multicriteria decision analysis to support weight of evidence evaluation.

Weight of evidence (WOE) methods are key components of ecological and human health risk assessments. Most WOE applications rely on the qualitative integration of diverse lines of evidence (LOE) representing impact on ecological receptors and humans. Recent calls for transparency in assessments and justifiability of management decisions are pushing the community to consider quantitative methods for integrated risk assessment and management. This article compares and contrasts the type of information required for application of individual WOE techniques and the outcomes that they provide in ecological risk assessment and proposes a multicriteria decision analysis (MCDA) framework for integrating individual LOE in support of management decisions. The use of quantitative WOE techniques is illustrated for a hypothetical but realistic case study of selecting remedial alternatives at a contaminated aquatic site. Use of formal MCDA does not necessarily eliminate biases and judgment calls necessary for selecting remedial alternatives, but allows for transparent evaluation and fusion of individual LOE. It also provides justifiable methods for selecting remedial alternatives consistent with stakeholder and decision-maker values.

Application of stochastic multiattribute analysis to assessment of single walled carbon nanotube synthesis processes.

The unprecedented uncertainty associated with engineered nanomaterials greatly expands the need for research regarding their potential environmental consequences. However, decision-makers such as regulatory agencies, product developers, or other nanotechnology stakeholders may not find the results of such research directly informative of decisions intended to mitigate environmental risks. To help interpret research findings and prioritize new research needs, there is an acute need for structured decision-analytic aids that are operable in a context of extraordinary uncertainty. Whereas existing stochastic decision-analytic techniques explore uncertainty only in decision-maker preference information, this paper extends model uncertainty to technology performance. As an illustrative example, the framework is applied to the case of single-wall carbon nanotubes. Four different synthesis processes (arc, high pressure carbon monoxide, chemical vapor deposition, and laser) are compared based on five salient performance criteria. A probabilistic rank ordering of preferred processes is determined using outranking normalization and a linear-weighted sum for different weighting scenarios including completely unknown weights and four fixed-weight sets representing hypothetical stakeholder views. No single process pathway dominates under all weight scenarios, but it is likely that some inferior process technologies could be identified as low priorities for further research.

Prioritization of sediment management alternatives using stochastic multicriteria acceptability analysis.

Decision-making for sediment management is a complex task that requires the consideration of temporal and spatial impacts of several remedial alternatives as well as the associated economic, social and political impact. Multicriteria decision analysis (MCDA) is becoming increasingly recognized as an important environmental management tool that can be used to support the selection of suitable remediation alternatives and prioritization of management units in space and time. This paper proposes an MCDA framework for prioritizing sediment management alternatives. This framework involves identifying of a set of feasible options, as well as defining and evaluating criteria which integrate relevant technical, economic, social and environmental aspects of remedies. The methodology allows an explicit consideration of uncertainty in criteria scores and weights by assigning probability distributions and analyzing subsequent Monte-Carlo simulations. The consideration of different stakeholder simulated values is used to assess the robustness of alternative rankings and to guide the selection of remediation options. An application of this methodology to a case study in the Bay of Santander, Spain, is presented. An assessment is conducted for the case of unknown preferences as well as for hypothetical preferences profiles for four types of stakeholders: Idealist, Politician, Environmentalist and Balanced. The results are used to visualize stakeholder positions and potential disagreements, allowing for the identification of a group of least preferred alternatives for each stakeholder. Stakeholder involvement has the potential to ease the remedy selection process during all stages of the decision-making process and to eventually remedy implementation.