Sustainable Energy - Without the Hot Air

Sustainable Energy - Without the Hot Air

Addressing the sustainable energy crisis in an objective manner, this book analyzes the relevant numbers and organizes a plan for change on both a personal level and an international scale—for Europe, the United States, and the world.

Publication date: 20 Feb 2009

ISBN-10: 0954452933

ISBN-13: 9780954452933

Paperback: 384 pages

Views: 2,396

Sustainable Energy - Without the Hot Air

Sustainable Energy - Without the Hot Air Addressing the sustainable energy crisis in an objective manner, this book analyzes the relevant numbers and organizes a plan for change on both a personal level and an international scale—for Europe, the United States, and the world.
Tag(s): Popular Science
Publication date: 20 Feb 2009
ISBN-10: 0954452933
ISBN-13: 9780954452933
Paperback: 384 pages
Views: 2,396
Document Type: N/A
Publisher: UIT Cambridge Ltd
License: Creative Commons Attribution-NonCommercial-ShareAlike 2.0 UK: England & Wales
Post time: 13 Apr 2016 02:00:00
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From the Back Cover:

Addressing the sustainable energy crisis in an objective manner, this enlightening book analyzes the relevant numbers and organizes a plan for change on both a personal level and an international scale—for Europe, the United States, and the world. In case study format, this informative reference answers questions surrounding nuclear energy, the potential of sustainable fossil fuels, and the possibilities of sharing renewable power with foreign countries. While underlining the difficulty of minimizing consumption, the tone remains positive as it debunks misinformation and clearly explains the calculations of expenditure per person to encourage people to make individual changes that will benefit the world at large.




About The Author(s)


David J. C. MacKay is Regius Professor of Engineering at Cambridge University Engineering Department. He works on Bayesian probability theory and its application to inference problems.

David J. C. MacKay

David J. C. MacKay is Regius Professor of Engineering at Cambridge University Engineering Department. He works on Bayesian probability theory and its application to inference problems.


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