Quantitative Sustainability Interdisciplinary Research for Sustainable Development Goals - Fantoni, Stefano; Casagli, Nicola; Solidoro, Cosimo; Cobal, Marina; SpringerLink (Online service) (Cham : Springer International Publishing : Imprint: Springer, 2024)
This open access book focuses on how scientific methodologies can help industrial managers, entrepreneurs and policymakers handle the 17 Sustainable Development Goals in an efficient and realistic way. It also offers an operative scheme for scientists to overcome their discipline barriers. Is interdisciplinarity an intrinsic research value or is it merely instrumental for handling the increasing flux of open problems that sustainability poses to science?Can these problems of sustainability be solved with what the authors already know? Is it just a matter of having the right people at the table and giving them sufficient resources, or is it something more? Is meeting the needs of the present without compromising those of future generations a scientific definition of sustainable development? Questions similar to those posed in the sixties regarding complexity must be asked about sustainability today. In addition, the new data science includes powerful tools for making novelquantitative predictions about future sustainability indicators, an open problem that the book discusses. This book is primarily addressed to Ph.D. students, postdocs and senior researchers in the Life and Hard Science (LHS) and Social Sciences and Humanities (SSH) disciplines, as well as professionals of the primary, secondary and tertiary industrial sectors.
Preface.-Forward.-Laboratory structure -- The blue planet and the ocean sustainable economy -- Food security and the health of the planet and its inhabitants -- Climate and environmental changes -- The new data science for sustainability and huiman ecology -- Energy transition and indiustrial product chains -- Sustainability frames and social equity and the right to sustainability -- Protection of the Earth habitats with Space tools.
Accessibility summary: This PDF does not fully comply with PDF/UA standards, but does feature limited screen reader support, described non-text content (images, graphs), bookmarks for easy navigation and searchable, selectable text. Users of assistive technologies may experience difficulty navigating or interpreting content in this document. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com.
No reading system accessibility options actively disabled
Publisher contact for further accessibility information: accessibilitysupport@springernature.com
Keywords: System theory; Sustainability; Artificial intelligence -- Data processing; Bioclimatology; Food security; Energy policy; Energy and state; Complex Systems; Sustainability; Data Science; Climate Change Ecology; Food Security; Energy Policy, Economics and Management