Assessing the Carbon Emissions and Energy Consumption of U.S. Hyperscale Data Centers

2026-06-03

AI Summary

This study addresses growing concerns over the high energy consumption and carbon emissions associated with the rapid proliferation of hyperscale data centers in the United States, driven by artificial intelligence. Leveraging facility-level data from 403 data centers and power plant–level grid information from the EPA’s eGRID database, the authors propose a refined methodology for attributing electricity sources, enabling the first precise assessment of these facilities’ electricity mix and carbon footprint. Findings indicate that between May 2024 and April 2025, these data centers consumed 68–99 TWh of electricity, resulting in CO₂ emissions of 37–54 million metric tons, with a weighted average carbon intensity of 545 gCO₂/kWh—significantly exceeding the national average. These results underscore the urgent need for targeted policy interventions to mitigate the environmental impact of this rapidly expanding sector.

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.

Problem

• hyperscale data centers
• carbon emissions
• energy consumption
• environmental footprint
• AI-driven growth

Innovation

• attributional analysis
• hyperscale data centers
• carbon intensity
• eGRID data
• energy consumption