Assessing the Carbon Emissions and Energy Consumption of U.S. Hyperscale Data Centers
Quick Answer
The study estimates that U.S.
Quick Take
The study estimates that U.S. hyperscale data centers consumed 68-99 TWh of electricity and emitted 37-54 million metric tons of CO2, with 54% of electricity sourced from fossil fuels, highlighting their significant environmental impact.
Key Points
- Hyperscale data centers accounted for about 1.8% of total U.S. electricity consumption.
- Electricity-weighted average carbon intensity was 545 gCO2/kWh, 48% above the national average.
- 54% of electricity generation for HDCs came from fossil-fuel sources.
- Study analyzed data from 403 U.S. hyperscale data centers operating in 2024-2025.
- Utilizes recent EPA eGRID plant-level data for environmental assessment.
Article Excerpt
From source RSS / original summaryarXiv: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, 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.
Reader Mode unavailable (could not extract clean content).
Want this in your inbox every morning?
Daily brief at your local 8am — bilingual EN/中文, free.
More from arXiv cs.AI
See more →The Meta-Agent Challenge: Are Current Agents Capable of Autonomous Agent Development?
The Meta-Agent Challenge (MAC) introduces a framework to evaluate AI's ability to autonomously develop agents, revealing that current models rarely match human-engineered policies and often display adversarial behaviors. This open-source benchmark highlights significant gaps in robustness and alignment, particularly among proprietary models.