Dr. Stahl is currently a senior environmental scientist at the U.S. Environmental Protection Agency, specializing in environmental policy development and decision analysis. Her expertise includes air quality programs, integrated health and ecological analyses (including stakeholder participation), the construction and use of indicators in integrated analyses (including cumulative impact analysis), uncertainty in decision making, and making sustainability operable through good decision analytic principles. With A. Cimorelli, she is a co-developer of the Multi-criteria Integrated Resources Assessment (MIRA) open solution approach.

Mr. Cimorelli is currently retired from the U.S. Environmental Protection Agency. He is an internationally recognized expert in near-field atmospheric dispersion modeling.  During his 41 years of professional experience he served as a senior physical scientist and regional meteorologist at the U.S. Environmental Protection Agency with responsibilities that included, research and development in atmospheric dispersion modeling and other related analysis techniques.  Mr. Cimorelli is one of the principal developers of the AERMOD modeling system. His expertise also included the development of Agency guidance related to all aspect of air dispersion modeling, as well as the review and conduct of regulatory air modeling studies and air risk assessments.  Additional he has taught many undergraduate and graduate courses in advanced air quality modeling, environmental law and environmental engineering at both Drexel and Temple Universities. With Dr. Stahl, he is a co-developer of the Multi-criteria Integrated Resources Assessment (MIRA) open solution approach.

I. Environmental Policy: The current paradigm

This introductory chapter describes the dilemma of balancing science and stakeholder goals in environmental policy making and our current paradigm or conceptual model of policy decision making. How do we currently make policy decisions that affect the public and are we doing as well as we could? Is there something fundamental that we are missing in the various approaches or methodologies we use to examine possible solutions? Is the controversy about climate change really about the scientific facts as to whether climate has changed or is it about disagreements regarding possible strategies to address impacts from climate change? The current environmental policy making paradigm reflects a bias toward the approaches used in the physical and biological sciences where the more complex problem is broken down into smaller problems that are individually solved based on science rules. The presumption that the whole is the sum of its parts pervades this conceptual model. In addition, the presumption of deducing the truth in the physical and biological sciences, which has served the physical and biological sciences well in the past, when applied to social and policy problems, is problematic as it often leads to the wrong problem being solved and/or stakeholder disenfranchisement. In this chapter, the long-held presumption that solving science and technology problems solves environmental policy problems is challenged.

II. The missing element

Practitioners commonly fail to understand that decision making requires a set of value judgments that vary because they are situational. Value judgments characterize wicked problems. In wicked problems, there are many stakeholders with diverse perspectives making it difficult to define the problem, no single right answers, no stopping rules, no objective measures of success, while solutions require iteration, must often be discovered, and often have strong moral, political or professional dimensions. Environmental problems are classic wicked problems with diverse stakeholders, competing interests, often an overwhelming number of solution possibilities, and a strong moral dimension as in Hardin's "Tragedy of the Commons." Furthermore, all choice problems (and hence, all decision making problems) are wicked problems. Different spatial and temporal scales complicate public policy problems and choosing which scales to address also makes those problems wicked. Therefore, policy making utilizes factual information but how that factual information is combined is a wicked problem. When people disagree about environmental issues such as climate change, is the disagreement really about the facts or about what policy alternatives should be considered?

Written from a practitioner's perspective, the complexity of relying on detailed science and technical facts to inform stakeholder discussions and policy discussions is dissected and evaluated. The nexus among policy making, stakeholder priorities and objectives and the use/miss-use of scientific information is discussed. In this chapter, we discuss multi-criteria problems where decision makers and other stakeholders often misidentify the wicked problem with potentially bad results.

III. Wickedness: It's not just for decision making

This chapter introduces the first principles common to creating indices, doing alternatives ranking and multi-criteria decision analysis. Indices are often created in order to simplify the delivery of a message and have the shroud of objectivity. But how 'objective' are indices like the Dow Jones Industrial average, Consumer Reports' ratings for appliances, the OECD Better Life Index, or Sustainability indices? What is the balance between the facts and the values in these measures and how should these be critically viewed? The rules (i.e., context and the assumptions) used to create them determine their meaning. Do we understand what they are? In good public policy making, these rules are made with engaged stakeholders in a transparent process that produces agreement on the final rules. Because alternatives ranking and multi-criteria decision analysis effectively create indices as an intermediate step, it makes sense to consider how these different uses affect how we think about their utility in policy making. Using both scientific and common examples, this chapter seeks to illustrate how these complex activities can be synthesized to a few common principles. This chapter weaves concepts and practical experience from the environmental policy decision making literature in order to introduce readers to new opportunities for better policy making. Supported by the literature and with these principles in hand, readers will learn how to evaluate indices, policy analyses, and decision case studies to advance their own work.

IV. Components of a Clumsy Solution Policy Framework

This chapter describes the components necessary for the new framework for policy making that incorporates the missing values element. Since the policy decision making process is wicked (i.e., contextual and value-laden and therefore no single, right solution), the components described here are not assumed to be known prior to analysis, as is generally the case in the present paradigm, but rather they are discovered, and sometimes created, as stakeholders iterate through the process. Values play a role in the policy components starting with problem formulation, identifying and selecting the specific group of participating stakeholders (including experts), determining which criteria are used to evaluate the problem, and determining how those criteria are used to formulate potential solutions. These eventually become the stakeholder agreed rules (context and assumptions) to be used to analyze and evaluate potential solutions. This chapter will also introduce other components that are necessary to construct a clumsy solution framework. These include: organizing criteria reflective of the stakeholder defined problem and facilitating expert engagement across various disciplines that are represented by those criteria. The clumsy solution policy framework is designed to facilitate stakeholders finding common ground through more contextual engagement and transparent communication, which creates better understanding, and increases the potential for consensus solutions.

V. Indicators

This chapter covers a familiar topic to many analysts but, in this chapter, indicators are viewed through the lens of decision analysis and policy making stakeholders. In addition, indices are composites of two or more indicators. Often, the indicators used in each of these settings are those historically used or easy to measure. However, thinking about indicators in the context of their specific use is a necessary part of the decision analysis construction process. What is the role of experts vs. stakeholders in the selection and construction of indicators? How are indicators connected to policy decision making process? Borrowing and building from previous works such as "Indicators and Information for Sustainable Development" (Meadows, 1999, http://www.iisd.org/pdf/s_ind_2.pdf), this chapter will challenge many stock understandings of indicators.

VI. Data

This chapter describes issues related to quantitative and qualitative data and data quality. Connection between data, indicators and the wicked decision problem will take readers into areas not typically addressed, such as including criteria in the quantitative decision analysis where there is no data or only qualitative data. As policy practitioners know, lack of data (including lack of quantitative data) often stymies the evaluation of the policy problem. Further, some of lack of data problems are due to the fact that it is not possible to conduct the kinds of studies needed to obtain that data because they would be unethical (for example, deliberate exposure of people to hazard substances or situations). Therefore, when there is a lack of data, this typically results in those concerns not being represented in the quantitative analysis. However, this chapter will describe strategies that could help fulfill this policy decision making need.

VII. Uncertainty

Uncertainty is a topic that is typically limited to that stemming from data or models. Even when discussions about uncertainty lead to questions about its impact on the choice of public policy alternatives, these are usually limited to data and model uncertainties. In this chapter, these types of uncertainties are discussed together with a more macro-view pertaining to decision uncertainty or uncertainties pertaining to how all the criteria organized, populated by data, and combined. Decision uncertainty can only be discussed when all the relevant parameters/criteria of an analysis are combined into a single framework. In this framework, data and model uncertainties along with uncertainties about expert judgment (e.g., when experts disagree) and stakeholder perspectives can be evaluated in a variety of combinations to better understand the robustness of each of the policy alternatives.

VIII. Transdisciplinary Learning for Clumsy Solutions

While the constituents of policy making were described in detail in the previous chapters, this chapter brings it all together in a discussion of why the policy making is more than the sum of its constituents. In this rendition of policy decision making, the process incorporates both analytical and discursive components. Transdisciplinary learning between and among experts and stakeholders occurs in this process because context is articulated and shared. Understanding and traversing the decision space, defined as all the possible combinations of expert judgments and stakeholder values, allows policy analysts and stakeholders greater opportunity to discover common ground through common understanding. The traditional rational-technical approach to policy decision making is challenged with this more holistic, stakeholders-focused, and values-driven approach to wicked policy problems.

IX. MIRA, the Approach

This chapter describes the Multi-criteria Integrated Resource Assessment (MIRA) approach, developed by the USEPA for environmental policy decision analysis. The MIRA approach is a manifestation of transdisciplinary learning in a single approach. Unlike research questions, which are solved with elegant solutions, wicked problems require clumsy approaches. MIRA, the approach, includes some custom components that facilitates analyses of complex environmental landscapes and problems. These components include the addition of land/water classifications in the application of indicator significance, similarity index, and weighted indicators based on starting environmental condition. The MIRA approach has been used to design the MIRA tool, which is a macro-driven spreadsheet. Illustrations of complex multi-criteria (i.e., wicked problem) environmental analyses that navigate the typical public policy making pitfalls are presented. This final chapter ties the concepts described in the earlier chapters together and presents an option for policy practitioners interested in evaluating and solving wicked problems.