Data for Environmental Sustainability Books

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Data Statistics and Useful Numbers for Environmental Sustainability


Data  Statistics  and Useful Numbers for Environmental Sustainability
  • Author : Benoit Cushman-Roisin
  • Publisher : Elsevier
  • Release : 2021-06-07
  • ISBN : 9780128230114
  • Language : En, Es, Fr & De
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Data, Statistics, and Useful Numbers for Environmental Sustainability: Bringing the Numbers to Life is an accessible reference for researchers working in environmental and sustainability fields who need to communicate the latest data and statistics to reinforce their own research or message. The book compiles the most-needed numbers into one resource and covers a variety of relevant topics, including materials, energy, environment, city planning, electronics, and waste. This handbook is clearly indexed and full of comprehensive tables, making it easy to find answers. Researchers in environmental and sustainability-related fields will find it an invaluable resource. Collects and presents important environmental data in one accessible resource Provides key information needed for effectively communicating environmental and sustainability issues Offers a clear index Includes detailed tables throughout for ease of access

Data Science Applied to Sustainability Analysis


Data Science Applied to Sustainability Analysis
  • Author : Jennifer Dunn
  • Publisher : Elsevier
  • Release : 2021-05-28
  • ISBN : 9780128179772
  • Language : En, Es, Fr & De
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Data Science Applied to Sustainability Analysis focuses on the methodological considerations associated with applying this tool in analysis techniques such as lifecycle assessment and materials flow analysis. As sustainability analysts need examples of applications of big data techniques that are defensible and practical in sustainability analyses and that yield actionable results that can inform policy development, corporate supply chain management strategy, or non-governmental organization positions, this book helps answer underlying questions. In addition, it addresses the need of data science experts looking for routes to apply their skills and knowledge to domain areas. Presents data sources that are available for application in sustainability analyses, such as market information, environmental monitoring data, social media data and satellite imagery Includes considerations sustainability analysts must evaluate when applying big data Features case studies illustrating the application of data science in sustainability analyses

Big Data and Environmental Sustainability


Big Data and Environmental Sustainability
  • Author :
  • Publisher :
  • Release : 2014
  • ISBN : OCLC:1253563945
  • Language : En, Es, Fr & De
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Environmental Assessment on Energy and Sustainability by Data Envelopment Analysis


Environmental Assessment on Energy and Sustainability by Data Envelopment Analysis
  • Author : Toshiyuki Sueyoshi
  • Publisher : John Wiley & Sons
  • Release : 2018-01-29
  • ISBN : 9781118979297
  • Language : En, Es, Fr & De
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Introduces a bold, new model for energy industry pollution prevention and sustainable growth Balancing industrial pollution prevention with economic growth is one of the knottiest problems faced by industry today. This book introduces a novel approach to using data envelopment analysis (DEA) as a powerful tool for achieving that balance in the energy industries—the world’s largest producers of greenhouse gases. It describes a rigorous framework that integrates elements of the social sciences, corporate strategy, regional economics, energy economics, and environmental policy, and delivers a methodology and a set of strategies for promoting green innovation while solving key managerial challenges to greenhouse gas reduction and business growth. In writing this book the authors have drawn upon their pioneering work and considerable experience in the field to develop an unconventional, holistic approach to using DEA to assess key aspects of sustainability development. The book is divided into two sections, the first of which lays out a conventional framework of DEA as the basis for new research directions. In the second section, the authors delve into conceptual and methodological extensions of conventional DEA for solving problems of environmental assessment in all contemporary energy industry sectors. Introduces a powerful new approach to using DEA to achieve pollution prevention, sustainability, and business growth Covers the fundamentals of DEA, including theory, statistical models, and practical issues of conventional applications of DEA Explores new statistical modeling strategies and explores their economic and business implications Examines applications of DEA to environmental analysis across the complete range of energy industries, including coal, petroleum, shale gas, nuclear energy, renewables, and more Summarizes important studies and nearly 800 peer reviewed articles on energy, the environment, and sustainability Environmental Assessment on Energy and Sustainability by Data Envelopment Analysis is must-reading for researchers, academics, graduate students, and practitioners in the energy industries, as well as government officials and policymakers tasked with regulating the environmental impacts of industrial pollution.

Big Data for Urban Sustainability


Big Data for Urban Sustainability
  • Author : Stephen Jia Wang
  • Publisher : Springer
  • Release : 2018-03-22
  • ISBN : 9783319736105
  • Language : En, Es, Fr & De
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This book presents a practical framework for the application of big data, cloud, and pervasive and complex systems to sustainable solutions for urban environmental challenges. It covers the technologies, potential, and possible and impact of big data on energy efficiency and the urban environment. The book first introduces key aspects of big data, cloud services, pervasive computing, and mobile technologies from a pragmatic design perspective, including sample open source firmware. Cloud services, mobile and embedded platforms, interfaces, operating system design methods, networking, and middleware are all considered. The authors then explore in detail the framework, design principles, architecture and key components of developing energy systems to support sustainable urban environments. The included case study provides a pathway to improve the eco-efficiency of urban transport, demonstrating how to design an energy efficient next generation urban navigation system by leveraging vast cloud data sets on user-behavior. Ultimately, this resource maps big data’s pivotal intersection with rapid global urbanization along the path to a sustainable future.