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Advancing Alternative Analysis: Integration of Decision Science

Malloy TF, Zaunbrecher VM, Batteate CM, Blake A, Carroll WF, Jr., Corbett CJ, Hansen SF, Lempert RJ, Linkov I, McFadden R, Moran KD, Olivetti E, Ostrom NK, Romero M, Schoenung JM, Seager TP, Sinsheimer P, Thayer KA.
Environmental Health Perspectives (2017) DOI: https://doi.org/10.1289/ehp483 PMID: 28669940


Publication


Abstract

BACKGROUND:
Decision analysis-a systematic approach to solving complex problems-offers tools and frameworks to support decision making that are increasingly being applied to environmental challenges. Alternatives analysis is a method used in regulation and product design to identify, compare, and evaluate the safety and viability of potential substitutes for hazardous chemicals.

OBJECTIVES:
We assessed whether decision science may assist the alternatives analysis decision maker in comparing alternatives across a range of metrics.

METHODS:
A workshop was convened that included representatives from government, academia, business, and civil society and included experts in toxicology, decision science, alternatives assessment, engineering, and law and policy. Participants were divided into two groups and were prompted with targeted questions. Throughout the workshop, the groups periodically came together in plenary sessions to reflect on other groups' findings.

RESULTS:
We concluded that the further incorporation of decision science into alternatives analysis would advance the ability of companies and regulators to select alternatives to harmful ingredients and would also advance the science of decision analysis.

CONCLUSIONS:
We advance four recommendations: a) engaging the systematic development and evaluation of decision approaches and tools; b) using case studies to advance the integration of decision analysis into alternatives analysis; c) supporting transdisciplinary research; and d) supporting education and outreach efforts.

Figures


Figure 1. Decision frameworks.

Compares the process for decision making under sequential, simultaneous, and mixed frameworks. Conceptual diagram.

Figure 2. Multiple decision tool use in mixed decision framework.

Demonstrates one potential scenario for using multiple decision tools in one chemical selection process. (Derived from Jacobs et al. 2016).Conceptual diagram.

Figure 3. Sample output from MAUT decision tool comparing alternatives to lead solder.

SnPb is a solder alloy composed of 63% Sn/37% Pb; SAC (Water) is a solder alloy composed of 95.5% Sn/3.9% Ag/0.6% Cu; water quenching is used to cool and harden solder; SAC (air) is a solder alloy composed of 95.5% Sn/3.9% Ag/0.6% Cu; air is used to cool and harden solder; SnCu (water) is a solder alloy composed of 99.2% Sn/0.8% Cu; water quenching is used to cool and harden solder; SnCu (air) solder alloy composed of 99.2% Sn/0.8% Cu; air is used to cool and harden solder [Malloy et al. 2013 with permission from Wiley Online Library http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1551-3793/homepage/Permissions.html)]. Note: Ag, silver; Cu, copper; Pb, lead; Sn, tin.

Supplemental Materials


Supplemental Material