AI & Environment Resource HubGlobal Renewables Alliance · 2026-05-01
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Global Renewables Alliance. 2026-05-01. 24/7 Carbon-Free Energy for All: Towards a Resilient Energy System. https://globalrenewablesalliance.org/wp-content/uploads/2026/05/GRA-Report-24-7-carbon-free-energy.pdf (AI & Environment Resource Hub; record report-333; collection snapshot 2026-09-15).
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Source sheet: Policy Document · Row 337 · Original ID: report-333.
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Shared topics: Cross-cutting sustainability; Energy and electricity; Climate and greenhouse gases; Weather, hazards, and adaptation
Aurora is a large-scale AI foundation model that significantly outperforms traditional forecasting systems across multiple Earth system domains, like air quality and cyclone tracking, while using far less computational power, marking a major advancement in accessible, efficient environmental prediction.
Shared topics: Cross-cutting sustainability; Energy and electricity; Climate and greenhouse gases; Weather, hazards, and adaptation
This article examines how advanced digitalization and AI can enhance spatial energy planning and environmental assessments in Austria, offering solutions to data deficiencies that currently hinder biodiversity-friendly renewable energy transitions.
Shared topics: Cross-cutting sustainability; Energy and electricity; Climate and greenhouse gases; Weather, hazards, and adaptation
In the fourth episode of the SPRingBoard Environmental Law Podcast, host Ahlia Bethea dives into the urgent and complex intersection of artificial intelligence and environmental sustainability with guests Shaolei Ren (Associate Professor of electrical and computer engineering at the University of California, Riverside) and Will Kletter (COO at ClimateAi). Together, they explore the environmental costs and transformative potential of AI, from the resource demands of large language models to the promise of predictive modeling in enhancing climate resilience.
Shared topics: Cross-cutting sustainability; Energy and electricity; Climate and greenhouse gases; Weather, hazards, and adaptation
AI is being deployed across both generative and predictive applications, but while generative AI demands enormous energy and data center infrastructure, predictive AI offers more efficient, targeted tools for climate solutions, such as emissions tracking, renewable grid forecasting, and extreme weather nowcasting, highlighting a crucial trade-off between innovation and sustainability.