There is no single water or electricity figure for a data center: its footprint depends on how much computing equipment it runs, how hard that equipment works, how it is cooled, and the local climate and power system. For a U.S.-wide view, Lawrence Berkeley National Laboratory’s 2026 estimate puts data-center electricity use at 192 terawatt-hours in 2024, or 4.7% of U.S. electricity consumption. That is an aggregate estimate, not a typical building’s bill. Water is harder to summarize: direct cooling use and water consumed to generate electricity are separate quantities, and the primary sources discussed here do not establish a comparable current national total for both.
What the electricity estimates measure
A data center’s electricity use is the electricity consumed by its computing equipment and the facility systems needed to operate it. The national figures below combine estimates across many facilities; they are not readings from one representative site. LBNL’s June 2026 update uses a bottom-up model based on equipment shipments, device power use, facility types, and locations. Its U.S. historical estimate excludes cryptocurrency mining.
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| Measure | Estimate | How to read it |
|---|---|---|
| U.S. electricity use, 2024 | 192 TWh; 4.7% of U.S. electricity consumption | LBNL estimate for the historical year 2024, excluding cryptocurrency mining. |
| U.S. 2030 Reference Case | 649 TWh; 11.8% of forecast U.S. electricity use | LBNL’s modeled reference scenario, not a guaranteed outcome. |
| U.S. 2030 combined uncertainty range | 521–843 TWh; 9.5–15.3% of forecast U.S. electricity use | LBNL’s range reflects uncertainty in assumptions, including server deployment and operating patterns. |
The distinction between historical estimate and forecast matters. The 2024 figure describes modeled electricity use in a past year; the 2030 values describe possible futures. A reference case is a central scenario for analysis, not a promise that demand will land on that number. The range is broad because assumptions about how many servers are deployed and how intensively they operate can materially change the result.
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Why one facility can differ sharply from another
At the building level, electricity use is shaped first by the amount and type of IT equipment installed, then by how much of its capacity is being used. A facility running a large fleet at high utilization will have a different load from a smaller site or one with more idle capacity. Cooling and other supporting systems also require energy, and their demand changes with the design, operating settings, and conditions around the facility.
A useful way to think about the arithmetic is average electrical load multiplied by operating time. A continuously sustained average load of 1 megawatt over a 365-day year corresponds to 8.76 gigawatt-hours. Actual facilities do not necessarily run at a perfectly constant load, so a measured or modeled annual total is more informative than a single peak-power figure. When comparing two claims, check whether each describes a facility, a company’s portfolio, a region, or a national total—and whether the figures are annual consumption, peak demand, or a forecast.
- Scale: the quantity of equipment and the facility’s total IT load affect how much electricity must be supplied.
- Utilization: operating assumptions influence the modeled energy use of installed equipment.
- Cooling design and climate: the method of removing heat and the local conditions affect both cooling energy and water demand.
- Accounting boundary: a figure for the facility’s electricity is not the same thing as a full accounting of resources used to generate that electricity.
Where data-center electricity comes from
“Where the power comes from” can mean the physical generation supplying a local grid, electricity generated onsite, or an operator’s contractual purchases. Those are related but not interchangeable descriptions. The International Energy Agency’s 2025 analysis estimates the physical generation mix serving data centers, including onsite generation and supply through local grids. It does not treat a company’s renewable-energy contracts as proof that the same share of its electricity was physically generated from renewables at every hour.
For example, an operator may sign a power purchase agreement or buy renewable-energy certificates while its facility draws electricity from a grid whose generation varies over time. Such procurement claims describe contractual arrangements; the IEA’s supply mix describes the physical sources in its accounting. To evaluate a claim, identify which meaning is being used rather than assuming that “powered by” always refers to the same thing.
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Global generation mix and demand outlook
| Global data-center electricity measure | IEA estimate or scenario |
|---|---|
| Electricity generation serving data centers, 2024 | About 460 TWh |
| Generation mix, current assessment | Coal about 30%; renewables about 27%; natural gas 26%; nuclear 15% |
| Base Case, 2030 | More than 1,000 TWh |
| Base Case, 2035 | 1,300 TWh |
These are global estimates and a scenario outlook, not a description of every country or facility. The IEA stresses that generation shares differ substantially by region. The listed shares are rounded; together they do not necessarily add to exactly 100% because of rounding and categories not displayed in this summary.
How the U.S. mix differs
The IEA’s 2025 U.S. analysis gives a different current mix: natural gas supplies over 40% of data-center electricity, renewables 24%, nuclear around 20%, and coal around 15%. In its Base Case, the IEA projects that natural-gas generation for data centers will add over 130 TWh of annual generation between 2024 and 2030, while renewables add 110 TWh. These are scenario projections for generation, not a guaranteed buildout or a direct forecast of any one operator’s supply contracts.
The global and U.S. percentages should not be combined or substituted for one another. They describe different geographies, and the fuel mix behind a particular data center depends on its grid and any onsite generation. A facility connected to a region with a different generation portfolio may have a different physical supply mix from the national U.S. summary.
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How data centers use water
Water can enter a data center’s footprint through two distinct pathways. Direct water use occurs at the facility, most notably when cooling towers evaporate water to release heat. Indirect water use occurs upstream when power plants consume water while generating electricity supplied to the facility. The amount of indirect use depends on the generation technologies and local electricity mix. Adding direct and indirect quantities is meaningful only when the accounting boundary and definitions are clear.
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Direct cooling water: evaporation and blowdown
The U.S. Department of Energy’s Federal Energy Management Program (DOE FEMP) describes a cooling path in which heat moves from IT equipment through cooling loops to a cooling tower. There, evaporation releases heat to the atmosphere. Some water is discharged as blowdown to manage the dissolved minerals that build up in the circulating water. Fresh makeup water replaces losses, including evaporation and blowdown.
The amount depends on the IT heat load and the efficiency of the stages that move and reject heat. A data center with a cooling tower can therefore have a very different direct water profile from one using another design or operating under different conditions. The broad label “data center” is not enough to infer a site’s water consumption. Local climate, cooling architecture, operating settings, and water-management practices all matter.
Water-usage effectiveness (WUE) is a site-based intensity metric commonly expressed in liters per kilowatt-hour. It relates facility water use to IT energy use, which can help compare direct water intensity when the measurement boundary and reporting period are consistent. WUE does not by itself account for water consumed to generate the electricity. A low direct-use figure is therefore not a complete water-footprint statement if upstream generation is outside the boundary.
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Withdrawal is water taken from a source. Consumption is water not returned to the same watershed in the same condition or time frame. A facility or power plant may withdraw water and return some of it; the two metrics describe different impacts. Treating them as interchangeable—or adding a withdrawal figure to a consumption figure—can misstate the amount of water removed from local availability.
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Any water comparison should state whether it reports withdrawal or consumption, whether it covers only the facility or also electricity generation, and the time period and location. This is especially important where a single number is presented as “the water used by data centers”: without a boundary and definition, readers cannot tell which pathway or water metric it represents.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Cooling choices involve water and energy trade-offs
Cooling systems do not offer a universal way to minimize every resource impact at once. DOE FEMP notes that air-side economizing—using cool outside air when conditions permit—can reduce cooling-system energy and water use. The potential depends on climate and operating set points, so the option is not equally useful in every location or throughout every season.
Cooling towers offer another example of how operating choices affect water demand. DOE FEMP says that increasing cooling-tower cycles of concentration from three to six can reduce makeup-water requirements by 20% and blowdown by 50%, citing its Cooling Tower Best Management Practice. These are system-level guidance examples, not guaranteed savings for every data center. Whether the adjustment is suitable depends on the cooling system and its operating conditions.
These examples show why “efficient” needs a stated measure. A change that reduces direct water consumption may have a different effect on electricity use, and an electricity-saving choice can alter upstream water consumption depending on the power sources involved. To compare designs fairly, keep direct facility water, power used for cooling, total electricity, and water used in power generation as distinct measures.
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Is there a single national water-use total?
The primary sources discussed here do not establish a current, comparable U.S. total that combines direct data-center water consumption with water consumed in electricity generation. LBNL’s 2024 report includes water analysis, but the accessible listing does not expose the water tables; LBNL’s June 2026 update is an electricity update. Without checking a comparable underlying table, a single national water number would overstate what these sources establish.
This limitation does not mean data centers use no water, nor does it mean facility-level water figures are unavailable. It means a national claim needs a clear and consistent accounting boundary, and the direct and indirect pathways cannot be collapsed into one well-supported total based on the sources identified here. A single facility’s water figure also cannot stand in for the national footprint: cooling systems, weather, IT load, and local power supply vary.
How to assess a data-center footprint claim
Before relying on a headline number, use these checks to see what it actually measures:
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- Time: Is the number measured or modeled for a historical year, or projected for a future year?
- Boundary: Does it count only direct facility use, or also upstream power-generation resources?
- Metric: For electricity, is it annual energy in TWh or a share of electricity consumption? For water, is it withdrawal or consumption?
- Supply accounting: Does the electricity mix describe physical local-grid and onsite generation, or contractual renewable procurement?
- Uncertainty: Is the figure a reference case, a sensitivity range, or a measured facility value?
When those details are absent, a number may still be a useful signal, but it is not enough to compare facilities or infer local impacts. The strongest claims make their geography, year, boundary, metric, and assumptions visible alongside the figure.
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