Environmental Decisions In The Face Of Uncertainty

The U.S. Environmental Protection Agency (EPA) is one of several federal agencies responsible for protecting Americans against significant risks to human health and the environment. As part of that mission, EPA estimates the nature, magnitude, and likelihood of risks to human health and the environment; identifies the potential regulatory actions that will mitigate those risks and protect public health1 and the environment; and uses that information to decide on appropriate regulatory action. Uncertainties, both qualitative and quantitative, in the data and analyses on which these decisions are based enter into the process at each step. As a result, the informed identification and use of the uncertainties inherent in the process is an essential feature of environmental decision making. EPA requested that the Institute of Medicine (IOM) convene a committee to provide guidance to its decision makers and their partners in states and localities on approaches to managing risk in different contexts when uncertainty is present. It also sought guidance on how information on uncertainty should be presented to help risk managers make sound decisions and to increase transparency in its communications with the public about those decisions. Given that its charge is not limited to human health risk assessment and includes broad questions about managing risks and decision making, in this report the committee examines the analysis of uncertainty in those other areas in addition to human health risks. Environmental Decisions in the Face of Uncertainty explains the statement of task and summarizes the findings of the committee.

Understanding and solving the pressing environmental problems that face us today requires application of the best scientific knowledge available. Most environmental managers currently are using books that focus on scientific methods, techniques, models and data that might be helpful. But as environmental problems become more complex, it is unclear to what extent scientific knowledge is adequate or appropriate as a basis for environmental decision-making. Because managers need to be aware that scientific results are based on probabilities rather than definitives, this book takes a case-study approach to the subject, with contributions from leading names in the field evaluating the implications of scientific uncertainty. Additionally, the contributors offer practical recommendations for how uncertainty can be factored into the environmental decision-making processes. Defines the problems and implications of scientific uncertainty for the environmental profession. Contains practical recommendations for how scientific uncertainty can be factored into environmental decision-making processes.

Many of the challenges that decision-makers grapple with in relation to climate change are governance related. Planning and decision-making is evolving in ambiguous institutional environments, in which many key issues remain unresolved, including relationships between different actors; funding arrangements; and the sources and procedures for vetting data. These issues are particularly acute at this juncture, as climate adaptation moves from broad planning processes to the management of infrastructure systems. Concrete decisions must be made. Adapting Infrastructure to Climate Change draws on case studies of three coastal cities situated within very different governance regimes: neo-corporatist Rotterdam, neo-pluralist Boston and semi-authoritarian Singapore. The book examines how infrastructure managers and other stakeholders grappling with complex and uncertain climate risks are likely to make project-level decisions in practice, and how more effective decision-making can be supported. The differences across governance regimes are currently unaccounted for in adaptation planning, but are crucial as best practices are devised. These lessons are also applicable to infrastructure planning and decision-making in other contexts. This book will be of great interest to scholars of climate change and environmental policy and governance, particularly in the context of infrastructure management.

Eco-pragmatism takes on the most critical controversies in environmental law today: how to weigh economic costs against environmental quality and human life, how to assess the long time horizons of environmental problems, and how to make appropriate decisions in the face of scientific uncertainty about the scope (or even the existence) of environmental problems. Farber discusses whether (and how) we should "discount" the values of future environmental benefits, how we should use economic measurements of environmental values, and how we can streamline the regulatory process to respond to rapidly changing scientific knowledge. The result is a pragmatic decision-making framework that is flexible enough to accommodate the unique challenges each case presents.

Risk assessment has become a dominant public policy tool for making choices, based on limited resources, to protect public health and the environment. It has been instrumental to the mission of the U.S. Environmental Protection Agency (EPA) as well as other federal agencies in evaluating public health concerns, informing regulatory and technological decisions, prioritizing research needs and funding, and in developing approaches for cost-benefit analysis. However, risk assessment is at a crossroads. Despite advances in the field, risk assessment faces a number of significant challenges including lengthy delays in making complex decisions; lack of data leading to significant uncertainty in risk assessments; and many chemicals in the marketplace that have not been evaluated and emerging agents requiring assessment. Science and Decisions makes practical scientific and technical recommendations to address these challenges. This book is a complement to the widely used 1983 National Academies book, Risk Assessment in the Federal Government (also known as the Red Book). The earlier book established a framework for the concepts and conduct of risk assessment that has been adopted by numerous expert committees, regulatory agencies, and public health institutions. The new book embeds these concepts within a broader framework for risk-based decision-making. Together, these are essential references for those working in the regulatory and public health fields.

This open access book focuses on both the theory and practice associated with the tools and approaches for decisionmaking in the face of deep uncertainty. It explores approaches and tools supporting the design of strategic plans under deep uncertainty, and their testing in the real world, including barriers and enablers for their use in practice. The book broadens traditional approaches and tools to include the analysis of actors and networks related to the problem at hand. It also shows how lessons learned in the application process can be used to improve the approaches and tools used in the design process. The book offers guidance in identifying and applying appropriate approaches and tools to design plans, as well as advice on implementing these plans in the real world. For decisionmakers and practitioners, the book includes realistic examples and practical guidelines that should help them understand what decisionmaking under deep uncertainty is and how it may be of assistance to them. Decision Making under Deep Uncertainty: From Theory to Practice is divided into four parts. Part I presents five approaches for designing strategic plans under deep uncertainty: Robust Decision Making, Dynamic Adaptive Planning, Dynamic Adaptive Policy Pathways, Info-Gap Decision Theory, and Engineering Options Analysis. Each approach is worked out in terms of its theoretical foundations, methodological steps to follow when using the approach, latest methodological insights, and challenges for improvement. In Part II, applications of each of these approaches are presented. Based on recent case studies, the practical implications of applying each approach are discussed in depth. Part III focuses on using the approaches and tools in real-world contexts, based on insights from real-world cases. Part IV contains conclusions and a synthesis of the lessons that can be drawn for designing, applying, and implementing strategic plans under deep uncertainty, as well as recommendations for future work. The publication of this book has been funded by the Radboud University, the RAND Corporation, Delft University of Technology, and Deltares.

This book outlines the creative process of making environmental management decisions using the approach called Structured Decision Making. It is a short introductory guide to this popular form of decision making and is aimed at environmental managers and scientists. This is a distinctly pragmatic label given to ways for helping individuals and groups think through tough multidimensional choices characterized by uncertain science, diverse stakeholders, and difficult tradeoffs. This is the everyday reality of environmental management, yet many important decisions currently are made on an ad hoc basis that lacks a solid value-based foundation, ignores key information, and results in selection of an inferior alternative. Making progress – in a way that is rigorous, inclusive, defensible and transparent – requires combining analytical methods drawn from the decision sciences and applied ecology with deliberative insights from cognitive psychology, facilitation and negotiation. The authors review key methods and discuss case-study examples based in their experiences in communities, boardrooms, and stakeholder meetings. The goal of this book is to lay out a compelling guide that will change how you think about making environmental decisions. Visit www.wiley.com/go/gregory/ to access the figures and tables from the book.

Geostatistical Error Management Geostatistical modeling conceptsand techniques have become daily practice in mining operations.That's because these precise analytical tools help professionalsquantify uncertainty and make objective decisions in the face ofthorny "real world" challenges. Geostatistical Error Management isthe first book to apply these proven quantitative tools toenvironmental challenges. The centerpiece of this working guide isan innovative decision-making framework, known as geostatisticalerror management (GEM). GEM integrates the related areas of DataQuality Objectives, Sampling Theory & Practice, andGeostatistical Appraisal to create an entirely new set of toolsthat help you more accurately assess resources for collectingenvironmental data, analyze sources of error in sampling, andquantify the extent and levels of contamination at environmentallyimpacted sites needing remediation. This practical,results-oriented resource * Focuses on the environmental applications of geostatisticaltechniques and how they fit into today's regulatory, legal, andengineering environments * Provides step-by-step explanations for applying error managementtools at every stage of an environmental site assessment * Points the way to applying GEM to environmental work beyond siteevaluation and characterization Geostatistical Error Management will enable environmentalspecialists to perform assessments of hazardous waste andenvironmentally impacted sites more accurately and to confidentlymanage uncertainty and error at every phase of a remediationproject.