Towards Net-Zero Targets : Usage of Data Science for Long-Term Sustainability Pathways / by Neha Sharma, Prithwis Kumar De.

Format:

Book

Author/Creator:

Sharma, Neha (Of Tufts University. School of Medicine), author.

De, Prithwis Kumar, author.

Series:

Advances in Sustainability Science and Technology, 2662-6837

Language:

English

Subjects (All):

Computational intelligence.

Sustainability.

Artificial intelligence.

Artificial intelligence--Data processing.

Machine learning.

Computational Intelligence.

Artificial Intelligence.

Data Science.

Machine Learning.

Local Subjects:

Computational Intelligence.

Sustainability.

Artificial Intelligence.

Data Science.

Machine Learning.

Physical Description:

1 online resource (258 pages)

Edition:

1st ed. 2023.

Place of Publication:

Singapore : Springer Nature Singapore : Imprint: Springer, 2023.

Summary:

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.

Contents:

Chapter 1. Climate Change and AI in the Financial, Energy, Domestic and Transport Sectors

Chapter 2. Role of Banking Sector in Climate Change – Literature Review and Data Preparation

Chapter 3. Application of Machine Learning to Predict Climate Change Consequences due to Investments by Banks in Fossil Fuel Sectors

Chapter 4. Effect of Non-Renewable Energy Sources on Climate Change in India- Literature Review and Data Preparation

Chapter 5. Using Machine Learning to Predict the Effect of Non-Renewable Energy Sources on Climate Change in India

Chapter 6. Impact of Household Emissions on Climate Change in India – Literature Review and Data Preparation

Chapter 7. Use of Unsupervised Learning Algorithms to Segment Indian States based on Primary Energy Household Emissions

Chapter 8. Application of Machine Learning in Climate Change for Transport Sector – Literature Review and Data Preparation

Chapter 9. Application of Machine Learning to Predict CO2 Emission from Transport Sector to Mitigate Climate Change

Chapter 10. Carbon Emission Calculator: Impact of AI on Climate Change.

Notes:

Includes bibliographical references and index.

Other Format:

Print version: Sharma, Neha Towards Net-Zero Targets

ISBN:

981-19-5244-2