Data Science Applied to Sustainability Analysis

<p>I. Introduction<br>1. Overview of Data Science and Sustainability Analysis and State of their Co-Application</p> <p>II. Enironmental Health and Sustainability<br>2. Applying AI for Conservation<br>3. Water balance characterization<br>4. Machine Learning in the Australian Critical Zone</p> <p>III. Energy and Water<br>5. A Clustering Analysis of Energy and Water Consumption in U.S. States from 1985 to 2015<br>6. Energy footprint of big data evaluated with data science<br>7. Solar PV rooftop disaprities by race and ethnicity in US<br>8. Screening materials for solar pv</p> <p>IV. Sustainable Systems Analysis<br>9. Machine Learning in life cycle analysis<br>10. Industry sustainable supply chain management with data science</p> <p>V. Society and Policy<br>11. Machine Learning to Inform Enhance Environmental Enforcement <br>12. Sociologically informed use of remote sensing data to predict rural household poverty<br>13. Trade-offs Between Environmental and Social Indicators of Sustainability</p> <p>VI. Conclusion<br>14. Research and Development for Increased Application of Data Science in Sustainability analysis</p>