Assessing the Carbon Emissions and Energy Consumption of U.S. Hyperscale Data Centers
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arXiv:2606.05420v1 Announce Type: new Abstract: The rapid proliferation of hyperscale data centers (HDCs) in the US, mainly driven by the adoption of artificial intelligence, has raised concerns about this industry's environmental footprint. We compiled facility-level information on 403 US hyperscale data centers operating between May 2024 and April 2025 and estimated their electricity consumption, electricity sources, and attributable CO2 emissions. Across different facility-load scenarios, the
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✦ AI Summary· Claude Sonnet
Computer Science > Artificial Intelligence
[Submitted on 3 Jun 2026]
Assessing the Carbon Emissions and Energy Consumption of U.S. Hyperscale Data Centers
Gianluca Guidi, Francesca Dominici, Tiziano Squartini, Callaway Sprinkle, Jonathan Gilmour, Kevin Butler, Eric Bell, Scott Delaney, Falco J. Bargagli-Stoffi
The rapid proliferation of hyperscale data centers (HDCs) in the US, mainly driven by the adoption of artificial intelligence, has raised concerns about this industry's environmental footprint. We compiled facility-level information on 403 US hyperscale data centers operating between May 2024 and April 2025 and estimated their electricity consumption, electricity sources, and attributable CO2 emissions. Across different facility-load scenarios, these HDCs consumed approximately 68-99 TWh of electricity and were associated with about 37-54 million metric tons of CO2. Under the central scenario, HDC electricity demand corresponded to approximately 1.8% of total US electricity consumption, with roughly 54% of attributed generation supplied by fossil-fuel sources. The HDC electricity-weighted average carbon intensity was approximately 545 gCO2/kWh, about 48% above the contemporaneous US national grid-average carbon intensity of 370 gCO2/kWh. Our approach provides an attributional tool for assessing the environmental footprint of hyperscale data centers using the most recent EPA eGRID plant-level data.
Subjects: Artificial Intelligence (cs.AI); Applications (stat.AP)
Cite as: arXiv:2606.05420 [cs.AI]
(or arXiv:2606.05420v1 [cs.AI] for this version)
https://doi.org/10.48550/arXiv.2606.05420
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From: Gianluca Guidi [view email]
[v1] Wed, 3 Jun 2026 20:38:10 UTC (7,077 KB)
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