Towards Net-Zero Targets

Usage of Data Science for Long-Term Sustainability Pathways

Prithwis Kumar De, Neha Sharma

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Springer Nature Singapore img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Allgemeines, Lexika

Beschreibung

This book discusses the use of technology, data science and open data to achieve the net-zero carbon emissions target set up by the Paris Agreement on climate change. There have been many discussions around sustainability and climate change solutions to mitigate the negative impact. However, using technology levers to tackle climate challenges is rarely seen as the most significant catalyst. The available research in this field is generally qualitative in nature, where technology and data have not yet been leveraged. By using AI/ML, the book predicts the climate change consequences arising due to investment in fossil fuel sectors, estimates CO2 emissions from the transport sector, forecasts average land temperature due to non-renewable sources of energy, and segments Indian states on the basis of household carbon emissions. The researchers, policymakers, students, teachers, educational institutions, governments, regulators, companies, international organizations, etc., will benefit immensely by referring to this book. Moreover, the endeavour of this book is to provide a decarbonized environment and a better tomorrow to the next generation.

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Schlagwörter

CLASSIFICATION, MACHINE LEARNING, CLIMATE RISKS, CLUSTERING, PARIS CLIMATE AGREEMENT, CARBON NEUTRAL, NET-ZERO EMISSIONS, GREEN HOUSE GAS EMISSIONS, DATA SCIENCE, GLOBAL EMISSIONS, DECARBONIZATION, CLIMATE CHANGE, ENVIRONMENT, SUSTAINABLE DEVELOPMENT GOALS, CARBON FOOTPRINT, CORRELATION, ARTIFICIAL INTELLIGENCE, PREDICTION