Suchergebnisse

In an era when pressing environmental problems make collaboration across the divide between sciences and arts and humanities essential, this book presents the results of a collaborative analysis by an anthropologist and a physicist of four key junctures between science, society, and environment. The first focuses on the systemic bias in science in favour of studying esoteric subjects as distinct from the mundane subjects of everyday life; the second is a study of the fire-climax grasslands of Southeast Asia, especially those dominated by Imperata cylindrica (sword grass); the third reworks the idea of 'moral economy', applying it to relations between environment and society; and the fourth focuses on the evolution of the global discourse of the culpability and responsibility of climate change. The volume concludes with the insights of an interdisciplinary perspective for the natural and social science of sustainability. It argues that failures of conservation and development must be viewed systemically, and that mundane topics are no less complex than the more esoteric subjects of science. The book addresses a current blind spot within the academic research community to focusing attention on the seemingly common and mundane beliefs and practices that ultimately play the central role in the human interaction with the environment. This book will benefit students and scholars from a number of different academic disciplines, including conservation and environment studies, development studies, studies of global environmental change, anthropology, geography, sociology, politics, and science and technology studies.

To prepare for an urban influx of 2.5 billion people by 2050, it is critical to create cities that are low-carbon, resilient, and livable. Cities not only contribute to global climate change by emitting the majority of anthropogenic greenhouse gases but also are particularly vulnerable to the effects of climate change and extreme weather. We explore options for establishing sustainable energy systems by reducing energy consumption, particularly in the buildings and transportation sectors, and providing robust, decentralized, and renewable energy sources. Through technical advancements in power density, city-integrated renewable energy will be better suited to satisfy the high-energy demands of growing urban areas. Several economic, technical, behavioral, and political challenges need to be overcome for innovation to improve urban sustainability.

Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Acknowledgments -- 1 Introduction -- Defining Risk -- Structure of the Book -- Risk Analysis and Public Policy -- Problem 1-1. Getting Started -- Problem 1-2. Data Needs -- Problem 1-3. Using Data -- Problem I-A. Additional Cases -- Problem I-B. Additional Curves -- Problem l-C. Does the Dose Make the Poison? -- Problem I-D. One in a Million Risks -- Problem I-E. Surfing and Smoking -- Problem I-F. Risks of Nuclear Power -- References -- 2 Basic Models and Risk Problems -- Introduction -- Basic Modeling -- Problem 2-1. Volatile Organic Emissions from Household Materials: Wallpaper Glue -- Problem 2-2. Indoor Radon Exposure -- Problem 2-A. Problem 2-2 Revisited -- Problem 2-B. Equilibrium Concentration -- Problem 2-3. Simple PBPK Model-Continuous Dose -- Problem 2-C. Alternative Depictions -- Problem 2-4. PBPK-Finite Dose of Barium -- Problem 2-D. How Much Resolution Is Too Much? -- Problem 2-E. How Much Information Is Needed? -- Problem 2-F. Sensitivity Analysis -- Cause and Effect Relationships -- Problem 2-5. Radon and Cancer -- Mechanistic Models and Curve Fitting -- Problem 2-6. Conceiving "Mechanistic" Models -- Problem 2-7. Using the Wrong Mode~ Getting the Model Wrong -- Problem 2-8. Empirically Derived Dose Response -- Problem 2-9. Earthquakes versus Traffic Risks -- Conclusion -- References -- 3 Review of Statistics for Risk Analysis -- Introduction: Statistics and the Philosophy of Risk Assessment -- Problem 3-1. Average Radon Exposure -- Problem 3-A. Radon Exposures in Different Regions -- Problem 3-2. Working with Data -- Problem 3-3. Mean and Median: Why Wony? -- Problem 3-4. Sample Data Revisited -- Problem 3-5. Hypothesis Testing and Confidence Intervals -- Problem 3-6. Making Decisions -- Distributions -- Problem 3-7. Moving Away from Ignorance