Tracking the resource footprint of the data center buildout. Electricity consumption, water withdrawal, and per-query costs — sourced from IEA, LBNL, EPRI, and hyperscaler sustainability reports.
As percentage of total US power demand, monthly resolution
Sources: LBNL, IEA, EPRI, DOE. Monthly interpolation from annual anchors with seasonal adjustment (summer cooling peak). Pre-2014 data from Koomey 2007 / Shehabi et al. 2016.
Annual TWh consumed by US data centers, with projections to 2030
Sources: LBNL 2024 Data Center Energy Usage Report, IEA Energy and AI (2025), EPRI "Powering Intelligence" (2024). Dashed line marks start of projections.
IEA: consumption set to more than double by 2030
Source: IEA Energy and AI (2025). Global DC electricity was flat at ~200 TWh from 2015-2018, then grew ~15%/yr 2019-2024.
AI training + inference is the fastest-growing segment
Sources: IEA Energy and AI (2025), Epoch AI compute tracking. AI inference demand grows faster than training as deployed model usage scales.
By 2030, global data centers are projected to consume more electricity than every country except the US, China, and India.
Count of facilities by PUE range. Lower PUE = more efficient (1.0 is ideal).
Average PUE across ENERGY STAR certified data centers by year.
| # | Facility | Location | Score | PUE | IT Energy |
|---|---|---|---|---|---|
| 1 | Meta Data Center - Prineville | Prineville, OR | 99 | 1.08 | 520 GWh |
| 2 | Google Data Center - The Dalles | The Dalles, OR | 98 | 1.10 | 450 GWh |
| 3 | Google Data Center - Council Bluffs | Council Bluffs, IA | 97 | 1.11 | 380 GWh |
| 4 | Meta Data Center - Forest City | Forest City, NC | 96 | 1.12 | 310 GWh |
| 5 | Microsoft Azure - Quincy | Quincy, WA | 95 | 1.14 | 400 GWh |
| 6 | Equinix DC12 - Ashburn | Ashburn, VA | 88 | 1.22 | 280 GWh |
| 7 | QTS Data Centers - Atlanta | Atlanta, GA | 86 | 1.24 | 250 GWh |
| 8 | Digital Realty - Richardson | Richardson, TX | 85 | 1.25 | 200 GWh |
| 9 | CoreSite - Reston | Reston, VA | 84 | 1.26 | 160 GWh |
| 10 | CyrusOne - Chandler | Chandler, AZ | 82 | 1.28 | 180 GWh |
Source: EPA ENERGY STAR Portfolio Manager. PUE = Power Usage Effectiveness (total facility energy / IT equipment energy). An ideal PUE is 1.0.
Each AI interaction has an electricity, water, and carbon cost. A single ChatGPT query uses ~10x the resources of a Google search.
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