White Paper
Global Artificial Intelligence Environmental Impact
2025 White Paper: Data Center Siting Policy and Practice
The Green AI Institute is proud to release its 2025 white paper—a comprehensive exploration of how data centers, especially those designed for AI, are reshaping energy policy, infrastructure planning, and national strategy around the world.
Browse by chapter → Get Full PDF2024 White Paper: Global AI Environmental Impact
Introduces the Green AI Index framework for assessing carbon and water footprints of AI models and data centers. Includes policy analysis (US, EU, China) and lifecycle assessment methodology.
Browse by chapter → Get Full PDFGreen AI Index Framework
This white paper provides an in-depth framework for evaluating the environmental impacts of AI and data centers using the Green AI Index—a comprehensive assessment tool focusing on energy consumption, carbon emissions, and water use across the entire lifecycle of AI systems.
Data Centers — Carbon Emissions
Scope 1: Direct Carbon Emissions
Direct emissions from fuel combustion in generators and refrigerant leakage in cooling systems.
Scope 2: Indirect Carbon Emissions from Purchased Energy
Emissions associated with electricity, heating, or cooling purchased from external suppliers.
Scope 3: Other Indirect Carbon Emissions
Emissions throughout the value chain including manufacturing, transportation, and supply chain.
Data Centers — Water Use
Scope 1: Direct Water Use
On-site water consumption primarily in cooling systems.
Scope 2 & 3: Indirect Water Use
Water consumed through electricity generation and throughout the supply chain, including semiconductor manufacturing.
AI Models — Life Cycle Assessment
The LCA framework covers every stage from raw material extraction to final disposal. Key metrics include operational carbon footprint (training and inference energy), embodied carbon footprint (hardware production), and water footprint across the lifecycle.
For the complete white paper including regional policy analysis (China, US, EU) and detailed methodology, please access the full document.
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