Uncertainty and Environmental Decision Making

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The 21st century promises to be an era dominated by international response to c- tain global environmental challenges such as climate change, depleting biodiversity and biocapacity as well as general atmospheric, water and soil pollution problems. Consequently, Environmental decision making (EDM) is a socially important ?eld of development for Operations Research and Management Science (OR/MS). - certainty is an important feature of these decision problems and it intervenes at very different time and space scales. The Handbook on Uncertainty and Environmental Decision Making provides a guided tour of selected methods and tools that OR/MS offer to deal with these issues. Below, we brie?y introduce, peer reviewed, chapters of this handbook and the topics that are treated by the invited authors. The ?rst chapter is a general introduction to the challenges of environmental decision making, the use of OR/MS techniques and a range of tools that are used to deal with uncertainty in this domain.

Presents the state of the art in a critically important area Environmental Decision Making Gathers the work of leading researchers in applying OR/MS techniques to EDM Filar and Haurie are leaders in the field; Filar is Editor-in-Chief of Springer journal Environmental Modeling and Assessment

Klappentext

Uncertainty and Environmental Decision Making: A Handbook of Research and Best Practice presents the state of the art in applying operations research and management science (OR/MS) techniques to a broad range of environmental decision making (EDM) challenges. Drawing on leading researchers in the field, it provides a guided tour of selected methods and tools to help deal with issues as climate change, depleting biodiversity and biocapacity, and more general atmospheric, water and soil pollution problems. Individual peer-reviewed chapters look at applying stochastic reasoning on difficult issues arising in EDM under uncertainty; applying stochastic or robust programming methods to techno-economic modeling of energy/environment interactions; important consequences of uncertainty inherent in weather patterns, the El Nino phenomenon and anticipated climate change; exploiting tools of decision analysis, utility theory and optimal control theory to account for differences in time scales between human development processes and the natural processes of the biosphere; and methods that combine statistical and decision analyses that can support a variety of environmental management problems.

This important new work will be of special interest to a wide range of researchers, students, and practitioners in environmental economics, OR/MS, environmental and earth sciences, climatologists, and risk assessment.


Inhalt
OR/MS and Environmental Decision Making under Uncertainty.- Modeling Uncertainty in a Large scale integrated Energy-Climate Model.- Robust Optimization for Environmental and Energy Planning.- Coping with Climate Risks in Indonesian Rice Agriculture: A Policy Perspective.- A Primer on Weather Derivatives.- Optimal Control Models and Elicitation of Attitudes towards Climate Damages.- A Stochastic Control/Game Approach to the Optimal Timing of Climate Policies.- Precautionary Effect and Variations of the Value of Information.- Comparative Forecasting and a Test for Persistence in the El Ni#x00F1;o Southern Oscillation.- Generation of Synthetic Sequences of Electricity Demand with Applications.- Models for Improving Management of Biosolids Odors.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09781441911285
    • Editor Jerzy A Filar, Alain Haurie
    • Sprache Englisch
    • Auflage 2010 edition
    • Größe H244mm x B164mm x T28mm
    • Jahr 2009
    • EAN 9781441911285
    • Format Fester Einband
    • ISBN 978-1-4419-1128-5
    • Veröffentlichung 14.12.2009
    • Titel Uncertainty and Environmental Decision Making
    • Untertitel A Handbook of Research and Best Practice
    • Gewicht 671g
    • Herausgeber SPRINGER NATURE
    • Anzahl Seiten 338
    • Lesemotiv Verstehen
    • Genre Biologie

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