Carnegie Mellon University
Environmental Decision Support Integrating Scientific Input Mode.pdf (27 MB)

Environmental Decision Support Integrating Scientific Input, Models, Economic Valuation, and Stakeholder Participation

Download (27 MB)
posted on 2011-12-01, 00:00 authored by Amanda P. Rehr

This dissertation presents and demonstrates three novel decision support tools aimed at assisting government and private organizations in tackling complex decisions involving multiple parties, affecting ecosystems and economies, and including choices made more difficult by significant uncertainty in relevant scientific knowledge.

The first tool integrates the economic input-output approach of life cycle assessment with environmental fate, exposure and risk assessment to estimate the spatial distribution of air toxic health risks due to sector-specific economic activity in the US. The model is used to relate the economic activity and exposure potential (population density and meteorology) associated with point source emissions of the heavy metal and carcinogen, hexavalent chromium, or Cr(VI), on a county basis. The results indicate that linking economic activity, emission estimates, and fate and transport models for air toxics can inform both life cycle impact and comparative health risk assessments, allowing us to better target emission reductions to minimize hot-spots of risk.

The second tool is a framework for science-based assessment and multi-stakeholder deliberation. The framework combines attributes of existing tools for environmental assessment and management, such as multiple criteria analysis, integrated assessment, and uncertainty analysis. It consists of two parts: a DPSIR (Drivers-Pressures-States-Impacts-Responses) analysis to identify the important causal relationships among anthropogenic environmental stressors, processes, and outcomes; and a Decision Landscape analysis which aims to ensure that relevant legal, institutional, and social factors affecting a decision, as well as the knowledge, values, and decision making of participants in the various elements of the DPSIR process, are recognized and considered. The framework is applied to coral reef protection and restoration in the Florida Keys National Marine Sanctuary, focusing on anthropogenic stressors, such as domestic wastewater. A structured elicitation of values and beliefs conducted at a coral reef management workshop held at Key West, Florida is used to develop information for an integrated DPSIR/Decision Landscape framework. The framework identifies key DPSIR relationships, current scientific understanding, and stakeholder perceptions, which can be used together to predict the outcomes of management options and to identify future research needed to resolve conflict among stakeholders over scientific understanding and preferred management options.

The third tool is aimed at identifying where additional scientific research may be needed to support better informed decisions and resolve possible conflicts over preferred management actions. The method combines and builds on aspects of multiple stakeholder deliberation, multiple criteria analysis, Bayesian Belief Networks, and value of information analysis. The method is applied to coral reef protection and restoration in the Guánica Bay Watershed, Puerto Rico, focusing on assessing and managing anthropogenic stressors, such as sedimentation and pollution from inland sources such as sewage, agriculture, and development. Structured elicitations of values and beliefs conducted at a coral reef management workshop held at La Parguera, Puerto Rico are used to develop information for demonstrating the method. Beliefs and preferred management options are examined for whether they exhibit greater coherence between stakeholders when informed by plausible study results. The results indicate that new scientific research is likely to bring people who initially disagree to agree. However, there can be situations where prior beliefs may be too different from the study results to shift perspectives and bring people to agreement. Though preliminary these results suggest that the method can provide useful insights on the social implications of a research program.




Degree Type

  • Dissertation


  • Engineering and Public Policy

Degree Name

  • Doctor of Philosophy (PhD)


Mitchell J. Small,Paul S. Fischbeck,Ines Azevedo,Kelly Black

Usage metrics


    Ref. manager