Transformation of the Earth's social and ecological systems is occurring at a rate and magnitude unparalleled in human experience. Data science is a revolutionary new way to understand human-environment relationships at the heart of pressing challenges like climate change and sustainable development. However, data science faces serious shortcomings when it comes to human-environment research. There are challenges with social and environmental data, the methods that manipulate and analyze the information, and the theory underlying the data science itself; as well as significant legal, ethical and policy concerns. This timely book offers a comprehensive, balanced, and accessible account of the promise and problems of this work in terms of data, methods, theory, and policy. It demonstrates the need for data scientists to work with human-environment scholars to tackle pressing real-world problems, making it ideal for researchers and graduate students in Earth and environmental science, data science and the environmental social sciences.

Environmental Systems Science: Theory and Practical Applications looks at pollution and environmental quality from a systems perspective. Credible human and ecological risk estimation and prediction methods are described, including life cycle assessment, feasibility studies, pollution control decision tools, and approaches to determine adverse outcome pathways, fate and transport, sampling and analysis, and cost-effectiveness. The book brings translational science to environmental quality, applying groundbreaking methodologies like informatics, data mining, and applications of secondary data systems. Multiple human and ecological variables are introduced and integrated to support calculations that aid environmental and public health decision making. The book bridges the perspectives of scientists, engineers, and other professionals working in numerous environmental and public health fields addressing problems like toxic substances, deforestation, climate change, and loss of biological diversity, recommending sustainable solutions to these and other seemingly intractable environmental problems. The causal agents discussed include physical, chemical, and biological agents, such as per- and polyfluoroalkyl substances (PFAS), SARS-CoV-2 (the COVID-19 virus), and other emerging contaminants. - Provides an optimistic and interdisciplinary approach, underpinned by scientific first principles and theory to evaluate pollutant sources and sinks, applying biochemodynamic methods, measurements and models - Deconstructs prior initiatives in environmental assessment and management using an interdisciplinary approach to evaluate what has worked and why - Lays out a holistic understanding of the real impact of human activities on the current state of pollution, linking the physical sciences and engineering with socioeconomic, cultural perspectives, and environmental justice - Takes a life cycle view of human and ecological systems, from the molecular to the planetary scale, integrating theories and tools from various disciplines to assess the current and projected states of environmental quality - Explains the elements of risk, reliability and resilience of built and natural systems, including discussions of toxicology, sustainability, and human-pollutant interactions based on spatial, biological, and human activity information, i.e. the exposome

Environmental Social Science offers a new synthesis of environmental studies, defining the nature of human-environment interactions and providing the foundation for a new cross-disciplinary enterprise that will make critical theories and research methods accessible across the natural and social sciences. Makes key theories and methods of the social sciences available to biologists and other environmental scientists Explains biological theories and concepts for the social sciences community working on the environment Helps bridge one of the difficult divides in collaborative work in human-environment research Includes much-needed descriptions of how to carry out research that is multinational, multiscale, multitemporal, and multidisciplinary within a complex systems theory context

The first comprehensive treatment of data science as a new and powerful way to understand and manage human-environment interactions.

The Holocene is unique when compared to earlier geological time in that humans begin to alter and manipulate the natural environment to their own needs. Domestication of crops and animals and the resultant intensification of agriculture lead to profound changes in the impact humans have on the environment. Conversely, as human populations began to increase geologic and climatic factors begin to have a greater impact on civilizations. To understand and reconstruct the complex interplay between humans and the environment over the past ten thousand years requires examination of multiple differing but interconnected aspects of the environment and involves geomorphology, paleoecology, geoarchaeology and paleoclimatology. These Springer Briefs volumes examine the dynamic interplay between humans and the natural environment as reconstructed by the many and varied sub-fields of the Earth Sciences.

Technological Trajectories and the Human Environment provides a surprising projection of a much greener planet, based on long-range analysis of trends in the efficient use of energy, materials, and land. The authors argue that we will decarbonize the global energy system and drastically reduce greenhouse gas emissions. We will dematerialize the economy by leaner manufacturing, better product design, and smart use of materials. We will significantly increase land areas reserved for nature by conducting highly productive and environmentally friendly agriculture on less land than is used today, even as global population doubles. The book concludes that the technological opportunities before us offer the possibility of a vastly superior industrial ecology. Rich in both data and theory, the book offers fresh analyses essential for everyone in the environmental arena concerned with global change, sustainable development, and profitable investments in technology.

Drawing on research from eleven countries across four continents, the 16 chapters in the volume bring perspectives from various specialties in anthropology and human ecology, institutional analysis, historical and political ecology, geography, archaeology, and land change sciences. The four sections of the volume reflect complementary approaches to HEI: health and adaptation approaches, land change and landscape management approaches, institutional and political-ecology approaches, and historical and archaeological approaches.

Data Analytics for Intelligent Transportation Systems provides in-depth coverage of data-enabled methods for analyzing intelligent transportation systems that includes detailed coverage of the tools needed to implement these methods using big data analytics and other computing techniques. The book examines the major characteristics of connected transportation systems, along with the fundamental concepts of how to analyze the data they produce. It explores collecting, archiving, processing, and distributing the data, designing data infrastructures, data management and delivery systems, and the required hardware and software technologies. Users will learn how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications, along with key safety and environmental applications for both commercial and passenger vehicles, data privacy and security issues, and the role of social media data in traffic planning. - Includes case studies in each chapter that illustrate the application of concepts covered - Presents extensive coverage of existing and forthcoming intelligent transportation systems and data analytics technologies - Contains contributors from both leading academic and commercial researchers - Explains how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications

Climate change is occurring, is caused largely by human activities, and poses significant risks for--and in many cases is already affecting--a broad range of human and natural systems. The compelling case for these conclusions is provided in Advancing the Science of Climate Change, part of a congressionally requested suite of studies known as America's Climate Choices. While noting that there is always more to learn and that the scientific process is never closed, the book shows that hypotheses about climate change are supported by multiple lines of evidence and have stood firm in the face of serious debate and careful evaluation of alternative explanations. As decision makers respond to these risks, the nation's scientific enterprise can contribute through research that improves understanding of the causes and consequences of climate change and also is useful to decision makers at the local, regional, national, and international levels. The book identifies decisions being made in 12 sectors, ranging from agriculture to transportation, to identify decisions being made in response to climate change. Advancing the Science of Climate Change calls for a single federal entity or program to coordinate a national, multidisciplinary research effort aimed at improving both understanding and responses to climate change. Seven cross-cutting research themes are identified to support this scientific enterprise. In addition, leaders of federal climate research should redouble efforts to deploy a comprehensive climate observing system, improve climate models and other analytical tools, invest in human capital, and improve linkages between research and decisions by forming partnerships with action-oriented programs.