Data center

Data centers are usually classified according to their ownership model, scale and intended use. Distribution of computing workloads across these four categories has shifted dramatically over the past decade, with hyperscale and colocation collectively accounting for approximately 74% of U.S. server energy consumption in 2023, up from less than 40% in 2014; this share is projected to reach 85% by 2028. They used to be essential infrastructures as in 2014, enterprise data centers accounted for over 60% of the U.S. server energy consumption, but this share fell sharply to approximately 10% by 2023 as workloads migrated to hyperscale and colocation facilities. Energy efficiency at an enterprise data center tends to be significantly lower than at hyperscale facilities due to its cooling, which can account for over 30% of electricity consumption at enterprise sites, compared to roughly 7% at efficient hyperscale data centers. This shift away from those enterprise facilities toward cloud and colocation infrastructure is one of the defining structural trends of the previous decade. Colocation Colocation centers provide shared physical infrastructure, such as power, cooling, space, etc., to multiple tenants who lease space rather than building their own facilities. and this category accounted for approximately 22% of worldwide data center capacity as of 2024, making them the second-largest category by capacity after hyperscale facilities. meet-me rooms for connecting customers together Internet exchange points, and landing points and terminal equipment for fiber optic submarine communication cables, which are critical to connecting the internet. Hyperscale Hyperscale data centers are large-scale facilities, typically exceeding 100 megawatts of power capacity, designed to support massive, scalable computing workloads for cloud services, AI training, and large-scale data processing. As a growing trend, hyperscale data centers represented approximately 41% of worldwide data center capacity in 2024 and are projected to exceed 60% by 2029 as enterprise on-premises infrastructure continues to decline. and they are positioned closer to end users or data sources in order to reduce network latency and support real-time applications They are typically located near the data source to reduce communication delays, as their small size allows several MDCs to be spread out over a wide area. MDCs are well suited to user-facing, front end applications. They are commonly used in edge computing and other areas where low latency data processing is needed. Modularity and flexibility Modularity and flexibility are key elements in allowing for a data center to grow and change over time. Data center modules are pre-engineered, standardized building blocks that can be easily configured and moved as needed. A modular data center may consist of data center equipment contained within shipping containers or similar portable containers. Components of the data center can be prefabricated and standardized which facilitates moving if needed. These modular data centers are useful for IT disaster recovery. Mobile data centers are also used to move very large quantities of data by physically transporting the hardware that contains it, and in cryptocurrency mining where fleets of mobile data centers are transported to take advantage of cheap sources of energy. ==History==

Data centers have their roots in the huge computer rooms of the 1940s, typified by ENIAC, one of the earliest examples of a data center. Early computer systems, complex to operate and maintain, required a special environment in which to operate. Many cables were necessary to connect all the components, and methods to accommodate and organize these were devised such as standard racks to mount equipment, raised floors, and cable trays (installed overhead or under the elevated floor). A single mainframe required a great deal of power and had to be cooled to avoid overheating. Security became important – computers were expensive, and were often used for military purposes. Basic design guidelines for controlling access to the computer room were therefore devised. During the microcomputer industry boom of the 1980s, users started to deploy computers everywhere, in many cases with little or no care about operating requirements. However, as information technology (IT) operations started to grow in complexity, organizations grew aware of the need to control IT resources. The availability of inexpensive networking equipment, coupled with new standards for the network structured cabling, made it possible to use a hierarchical design that put the servers in a specific room inside the company. The use of the term data center, as applied to specially designed computer rooms, started to gain popular recognition about this time. During the dot-com bubble (1997–2000), there was a boom in data center construction, when companies needed fast Internet connectivity and non-stop operation to establish their Internet presence. Many companies started building very large facilities, called internet data centers (IDCs), which provide enhanced capabilities, such as crossover backup: "If a Bell Atlantic line is cut, we can transfer them to ... to minimize the time of outage." In 2024, global energy consumption from data centers was 620 TWh, with 80% of that consumption being concentrated in the United States, China, and the United Kingdom. Colocation centers were the most common category worldwide, with 4799 colocation centers in 127 countries. In that year, the largest data center in the world was Citadel, owned by Switch, at the Tahoe Reno Industrial Center in Reno, NV, occupying 7.2 million sq ft. A 2026 poll by Politico suggested that resistance to growth of the industry would make candidates' stance on data centers a significant issue for voters in the United States. In the United States The United States hosted 5,381 data centers in March 2024, the highest number of any country worldwide and accounting for 40% of the global market in 2023. Local governments have responded to the growing industry in Georgia with a variety of local ordinances to guide permitting of these facilities. The consultancy firm McKinsey & Co., projected US demand to double to 35 gigawatts (GW) by 2030, up from 17 GW in 2022. A study published by the Electric Power Research Institute (EPRI) in May 2024 estimated that data centers could consume between 4.6% and 9.1% of the country's electricity generation by 2030. In 2025, it was estimated that the U.S. GDP growth was only 0.1% without the investments in data centers for artificial intelligence. ==Design==

Data centers house critical computing resources in a controlled environment and must generally operate with very high availability. Key design elements include providing power for the equipment, temperature and humidity control, cabling, fire safety, and security. Information security is also a concern, and for this reason, a data center has to offer a secure environment that minimizes the chances of a security breach. Obsolescence and modernization Industry research company International Data Corporation (IDC) puts the average age of a data center at nine years old. Gartner, another research company, says data centers older than seven years are obsolete. The growth in data (163 zettabytes by 2025) is one factor driving the need for data centers to modernize. Focus on modernization is not new: rapid obsolescence of data center equipment was a concern by at least 2007, and in 2011 Uptime Institute was concerned about aging equipment. Industry standards The Telecommunications Industry Association's Telecommunications Infrastructure Standard for Data Centers specifies the minimum requirements for telecommunications infrastructure of data centers and computer rooms including single tenant enterprise data centers and multi-tenant Internet hosting data centers. The topology proposed in this document is intended to be applicable to any size data center. Telcordia GR-3160, NEBS Requirements for Telecommunications Data Center Equipment and Spaces, provides guidelines for data center spaces within telecommunications networks, and environmental requirements for the equipment intended for installation in those spaces. These criteria were developed jointly by Telcordia and industry representatives. They may be applied to data center spaces housing data processing or Information Technology (IT) equipment. The equipment may be used to: • Operate and manage a carrier's telecommunication network • Provide data center based applications directly to the carrier's customers • Provide hosted applications for a third party to provide services to their customers • Provide a combination of these and similar data center applications Reliability of electrical power supply Power supplies, either back up or continuous onsite power consists of one or more uninterruptible power supplies, battery banks, diesel, gas turbine, gas engine generating sets.Greater primary fuel energy efficiency can be achieved with the use of cogeneration technology, generating electricity, heating and cooling onsite. To prevent single points of failure, all elements of the electrical systems, including backup systems, are typically given redundant copies, and critical servers are connected to both the A-side and B-side power feeds. This arrangement is often made to achieve N+1 redundancy in the systems. Static transfer switches are sometimes used to ensure instantaneous switchover from one supply to the other in the event of a power failure. Low-voltage cable routing Options for low voltage cable routing might include: data cabling that is routed through overhead cable trays; raised floor cabling, both for security reasons and to avoid the extra cost of cooling systems over the racks; anti-static tiles for flooring, especially in low-cost data centers. Environmental control Maintaining suitable temperature and humidity levels is critical to preventing equipment damage caused by overheating. Overheating can cause components, usually the silicon or copper of the wires or circuits to melt, causing loose connections and fire hazards. Typical temperature control methods include: • Air conditioning • Indirect cooling, such as the use of outside air, indirect evaporative cooling units, and seawater cooling. Airflow management is the practice of achieving data center cooling efficiency by preventing the recirculation of hot exhaust air and by reducing bypass airflow. Common approaches include hot-aisle/cold-aisle containment and the deployment of in-row cooling units which position cooling directly between server racks to intercept exhaust heat before it mixes with room air. Humidity control not only prevents moisture-related issues: importantly, excess humidity can cause dust to adhere more readily to fan blades and heat sinks, impeding air cooling leading to higher temperatures. Aisle containment Cold aisle containment is done by exposing the rear of equipment racks, while the fronts of the servers are enclosed with doors and covers. This is similar to how large-scale food companies refrigerate and store their products. Computer cabinets/Server farms are often organized for containment of hot/cold aisles. Proper air duct placement prevents the cold and hot air from mixing. Rows of cabinets are paired to face each other so that the cool and hot air intakes and exhausts do not mix air, which would severely reduce cooling efficiency. Alternatively, a range of underfloor panels can create efficient cold air pathways directed to the raised-floor vented tiles. Either the cold aisle or the hot aisle can be contained. Another option is fitting cabinets with vertical exhaust duct chimneys. Hot exhaust pipes/vents/ducts can direct the air into a Plenum space above a Dropped ceiling and back to the cooling units or to outside vents. With this configuration, traditional hot/cold aisle configuration is not a requirement. Fire protection fire suppression tanks Data centers feature fire protection systems, including passive and active design elements, as well as implementation of fire prevention programs in operations. Smoke detectors are usually installed to provide early warning of a fire at its incipient stage. Although the main room usually does not allow Wet Pipe-based Systems due to the fragile nature of circuit boards, there still exist systems that can be used in the rest of the facility or in cold/hot aisle air circulation systems that are closed systems, such as: • Sprinkler systems • Misting, using high pressure to create extremely small water droplets, which can be used in sensitive rooms due to the nature of the droplets. However, there also exist other means to put out fires, especially in Sensitive areas, usually using Gaseous fire suppression, of which Halon gas was the most popular, until the negative effects of producing and using it were discovered.Security Physical access is usually restricted. Layered security often starts with fencing, bollards and mantraps. Video camera surveillance and permanent security guards are almost always present if the data center is large or contains sensitive information. Fingerprint recognition mantraps are starting to be commonplace. Logging access is required by some data protection regulations; some organizations tightly link this to access control systems. Multiple log entries can occur at the main entrance, entrances to internal rooms, and at equipment cabinets. Access control at cabinets can be integrated with intelligent power distribution units, so that locks are networked through the same appliance. Transformation Data center transformation takes a step-by-step approach through integrated projects carried out over time. This differs from a traditional method of data center upgrades that takes a serial and siloed approach. The typical projects within a data center transformation initiative include standardization/consolidation, virtualization, automation and security. Data center consolidation consists in reducing the number of data centers and avoiding server sprawl (both physical and virtual), often includes replacing aging data center equipment. Likewise, this process is aided by standardization which makes these systems follow a uniform set of configurations in order to simplify and improve efficiency. Lastly, security initiatives integrate the protection of virtual systems with existing security of physical infrastructures. Raised floor The first raised floor computer room was made by IBM in 1956 to allow access for wiring. During the 1970s, raised floors became more common because they allow cool air to circulate more efficiently. A raised floor standards guide (GR-2930) was developed by Telcordia Technologies, a subsidiary of Ericsson. Lights out The lights-out data center, also known as a darkened or a dark data center, is a data center that, ideally, has all but eliminated the need for direct access by personnel, except under extraordinary circumstances. Because of the lack of need for staff to enter the data center, it can be operated without lighting. All of the devices are accessed and managed by remote systems, with automation programs used to perform unattended operations. In addition to the energy savings, reduction in staffing costs and the ability to locate the site further from population centers, implementing a lights-out data center reduces the threat of malicious attacks upon the infrastructure. Noise levels Generally speaking, local authorities prefer noise levels at data centers to be "10 dB below the existing night-time background noise level at the nearest residence." OSHA regulations require monitoring of noise levels inside data centers if noise exceeds 85 decibels. The average noise level in server areas of a data center may reach as high as 92–96 dB(A). Residents living near data centers have described the sound as "a high-pitched whirring noise 24/7", saying "It's like being on a tarmac with an airplane engine running constantly ... Except that the airplane keeps idling and never leaves." External sources of noise include HVAC equipment and energy generators.] Site selection Location factors include proximity to power grids, telecommunications infrastructure, networking services, transportation lines and emergency services. Other considerations should include flight paths, neighboring power drains, geological risks, and climate (associated with cooling costs). Local political considerations such as availability of subsidies and lack of opposition are also important factors in locating data centers.The costs of avoiding downtime should not exceed the cost of the downtime itself. Dynamic infrastructure Dynamic infrastructure provides the ability to intelligently, automatically and securely move workloads within a data center anytime, anywhere, for migrations, provisioning, to enhance performance, or building co-location facilities. It also facilitates performing routine maintenance on either physical or virtual systems all while minimizing interruption. A related concept is Composable Infrastructure, which allows for the dynamic reconfiguration of the available resources to suit needs, only when needed. Side benefits include • reducing cost • facilitating business continuity and high availability • enabling cloud and grid computing. Software/data backup Non-mutually exclusive options for data backup are: • Onsite • Offsite Onsite is traditional, and one of its major advantages is immediate availability. Offsite backup storage Data backup techniques include having an encrypted copy of the data offsite. Methods used for transporting data are: • Having the customer write the data to a physical medium, such as magnetic tape, and then transporting the tape elsewhere. • Directly transferring the data to another site during the backup, using appropriate links. • Uploading the data "into the cloud". Network infrastructure Communications in data centers today are most often based on networks running the Internet protocol suite. Data centers contain a set of routers and switches that transport traffic between the servers and to the outside world which are connected according to the data center network architecture. Redundancy of the internet connection is often provided by using two or more upstream service providers (see Multihoming). Some of the servers at the data center are used for running the basic internet and intranet services needed by internal users in the organization, e.g., e-mail servers, proxy servers, and DNS servers. Network security elements are also usually deployed: firewalls, VPN gateways, intrusion detection systems, and so on. Also common are monitoring systems for the network and some of the applications. Additional off-site monitoring systems are also typical, in case of a failure of communications inside the data center. ==Energy use==

, The Dalles, Oregon Energy consumption and the environmental impact it creates is a central issue for data centers. Power draw ranges from a few kilowatts (kW) for small server racks to several tens of megawatts (MW) for large facilities. Modern hyperscale data centers can exhibit power densities exceeding 100 times those of conventional office buildings, primarily due to the high concentration of servers and cooling systems required to manage continuous digital workloads. For higher power density facilities, electricity costs are a dominant operating expense and account for over 10% of the total cost of ownership (TCO) of a data center. As of 2024, data centers in the United States are primarily powered by natural gas, which supplies 40% of their electricity (with renewable energy at 24%, nuclear at about 20% and coal at about 15%). The Associated Press reported that electricity for AI data centers in the United States would likely come from natural gas or oil, as companies prefer using currently available power plants, which primarily use fossil fuels. Fossil energy is also often cheaper in locations where data centers are developed, and experts believe that energy demands from generative AI and data centers would be difficult to fulfill with renewable energy alone. Some companies such as Google, Amazon and Meta have expressed interest in nuclear power for their data centers. Now, according to the International Energy Agency, solar photovoltaic-generated electricity is the lowest cost in history. A recent study covered by Forbes also found that co-locating solar energy production on farm land (agrivoltaics) could produce all of the energy needed for data centers on less than 0.5% of farmland area using single axis trackers spaced apart so farm equipment could operate conventionally. Other data centers, including xAI's Colossus, OpenAI's Stargate, and Meta's Prometheus use their own off-grid natural gas plants. Electric vehicle and lithium-ion batteries have also been used for powering data centers, including for Colossus. Power utility companies make upgrades to their infrastructure to handle demands of new data centers, and the price for these changes typically falls on residential or smaller commercial consumers. United States Secretary of Energy Chris Wright expressed support for un-retiring coal plants to power AI data centers. Electricity demands from AI data centers have slowed or reversed the retirement of peaking power plants in the United States. For example, in 2025, Southern Company announced that energy use from data centers would prevent the company from retiring coal-fired power plants as it had earlier promised. However, the rapid expansion is causing projections to rise sharply. Due to the accelerated demand from AI, data center's global electricity consumption is projected to more than double to around 945 TWh by 2030 in the IEA's base-case scenario, which represents just under 3% of 2030 total global electricity consumption. They also said that lifecycle emissions should be considered, that is including embodied emissions, such as in buildings. Global data center carbon dioxide emissions are projected to rise from an estimated 220 million tonnes in 2024 to 300–320 million tonnes by 2035. Google and Microsoft now each consume more power than some fairly big countries, surpassing the consumption of more than 100 countries. As a result, there is increasing industry pressure for decarbonization. Companies are pursuing direct clean energy agreements, such as Tencent who has pledged to be carbon neutral by 2030, and Microsoft's 2024 agreement to re-open the Three Mile Island nuclear power plant to provide 100% of the electric power for its AI data centers for 20 years. Economic analysis of energy use Energy efficiency and overhead Main article: Power usage effectiveness The most commonly used energy efficiency metric for data centers is power usage effectiveness (PUE), calculated as the ratio of total power entering the data center divided by the power used by IT equipment. :\mathrm{PUE} = {\mbox{Total Facility Power} \over \mbox{IT Equipment Power}} = 1 + {\mbox{Non IT Facility Energy} \over \mbox{IT Equipment Energy}} PUE measures the percentage of power used by overhead devices (cooling, lighting, etc.). The average U.S. data center has a PUE of 2.0, meaning two watts of total power (overhead + IT equipment) for every watt delivered to IT equipment. State-of-the-art data centers are estimated to have a PUE of roughly 1.2. Google publishes quarterly efficiency metrics from its data centers in operation. PUEs of as low as 1.01 have been achieved with two phase immersion cooling. The U.S. Environmental Protection Agency has an Energy Star rating for standalone or large data centers. To qualify for the ecolabel, a data center must be within the top quartile in energy efficiency of all reported facilities. The Energy Efficiency Improvement Act of 2015 (United States) requires federal facilities—including data centers—to operate more efficiently. California's Title 24 (2014) of the California Code of Regulations mandates that every newly constructed data center must have some form of airflow containment in place to optimize energy efficiency. The European Union also has a similar initiative: EU Code of Conduct for Data Centres. Efficiency improvements and renewable energy integration are helping offset some emissions, but fossil fuels remain a major electricity source for data center operations worldwide. In 2011, server racks in data centers were designed for more than 25 kW and the typical server was estimated to waste about 30% of the electricity it consumed. The energy demand for information storage systems is also rising. A high-availability data center is estimated to have a 1 MW demand and consume $20,000,000 in electricity over its lifetime, with cooling representing 35% to 45% of the data center's total cost of ownership. Calculations show that in two years, the cost of powering and cooling a server could be equal to the cost of purchasing the server hardware. Research in 2018 has shown that a substantial amount of energy could still be conserved by optimizing IT refresh rates and increasing server utilization. Research for optimizing task scheduling is also underway, with researchers looking to implement energy-efficient scheduling algorithms that could reduce energy consumption by anywhere between 6% and 44%. In 2011, Facebook, Rackspace and others founded the Open Compute Project (OCP) to develop and publish open standards for greener data center computing technologies. As part of the project, Facebook published the designs of its server, which it had built for its first dedicated data center in Prineville. Making servers taller left space for more effective heat sinks and enabled the use of fans that moved more air with less energy. By not buying commercial off-the-shelf servers, energy consumption due to unnecessary expansion slots on the motherboard and unneeded components, such as a graphics card, was also saved. In 2016, Google joined the project and published the designs of its 48V DC shallow data center rack. This design had long been part of Google data centers. By eliminating the multiple transformers usually deployed in data centers, Google had achieved a 30% increase in energy efficiency. In 2017, sales for data center hardware built to OCP designs topped $1.2 billion and are expected to reach $6 billion by 2021. Cooling at or below wastes money and energy. A power and cooling analysis, also referred to as a thermal assessment, measures the relative temperatures in specific areas as well as the capacity of the cooling systems to handle specific ambient temperatures. A power and cooling analysis can help to identify hot spots, over-cooled areas that can handle greater power use density, the breakpoint of equipment loading, the effectiveness of a raised-floor strategy, and optimal equipment positioning (such as AC units) to balance temperatures across the data center. Power cooling density is a measure of how much square footage the center can cool at maximum capacity. The cooling of data centers is the second largest power consumer after servers. The cooling energy varies from 10% of the total energy consumption in the most efficient data centers and goes up to 45% in standard air-cooled data centers. Energy efficiency analysis An energy efficiency analysis measures the energy use of data center IT and facilities equipment. A typical energy efficiency analysis measures factors such as a data center's Power Use Effectiveness (PUE) against industry standards, identifies mechanical and electrical sources of inefficiency, and identifies air-management metrics. However, the limitation of most current metrics and approaches is that they do not include IT in the analysis. Case studies have shown that by addressing energy efficiency holistically in a data center, major efficiencies can be achieved that are not possible otherwise. Computational Fluid Dynamics (CFD) analysis This type of analysis uses sophisticated tools and techniques to understand the unique thermal conditions present in each data center—predicting the temperature, airflow, and pressure behavior of a data center to assess performance and energy consumption, using numerical modeling. By predicting the effects of these environmental conditions, CFD analysis of a data center can be used to predict the impact of high-density racks mixed with low-density racks and the onward impact on cooling resources, poor infrastructure management practices, and AC failure or AC shutdown for scheduled maintenance. Thermal zone mapping Thermal zone mapping uses sensors and computer modeling to create a three-dimensional image of the hot and cool zones in a data center. This information can help to identify optimal positioning of data center equipment. For example, critical servers might be placed in a cool zone that is serviced by redundant AC units. Green data centers , France claims the attribute green. Data centers use a lot of power, consumed by two main usages: The power required to run the actual equipment and then the power required to cool the equipment. Power efficiency reduces the first category. Cooling cost reduction through natural means includes location decisions: When the focus is avoiding good fiber connectivity, power grid connections, and people concentrations to manage the equipment, a data center can be miles away from the users. Mass data centers like Google or Facebook do not need to be near population centers. Arctic locations that can use outside air, which provides cooling, are becoming more popular. Renewable electricity sources are another plus. Thus countries with favorable conditions, such as Canada, Finland, Sweden, Norway, and Switzerland are trying to attract cloud computing data centers. Singapore lifted a three-year ban on new data centers in April 2022. A major data center hub for the Asia-Pacific region, Singapore lifted its moratorium on new data center projects in 2022, granting 4 new projects, but rejecting more than 16 data center applications from over 20 new data centers applications received. Singapore's new data centers shall meet very strict green technology criteria including "Water Usage Effectiveness (WUE) of , Power Usage Effectiveness (PUE) of less than 1.3, and have a "Platinum certification under Singapore's BCA-IMDA Green Mark for New Data Centre" criteria that clearly addressed decarbonization and use of hydrogen cells or solar panels. Energy reuse It is very difficult to reuse the heat which comes from air-cooled data centers. For this reason, data center infrastructures are more often equipped with heat pumps. ==Regulation and policy responses==

In the 2020s, the rapid growth of constructions of data center has given rises to policy debates over tax incentives, electricity grid, water resources, and climate commitments. Virginia hosts the largest concentration of data centers in the United States, and a December 2024 audit by its Joint Legislative Audit and Review Commission (JLARC) put the industry's annual contribution at roughly 74,000 jobs and $9.1 billion in gross state product. The same audit of Virginia reported that the state's sales and use tax exemption was claimed by about 90% of operators and that reduced state revenue by an estimated $928 million in fiscal year 2023. Thus, JLARC concluded that ending the exemption would likely shrink Virginia's share of new data center investment. Further, research by Timothy Bartik of the Upjohn Institute has estimated that economic development incentives change firm location decisions in only 2 to 25% of cases. In another case in 2026, the Virginia Senate voted 28 to 12 to phase out the state's data center sales tax exemption as part of broader budget negotiations. Water usage Most large data centers use water for evaporative cooling of their servers, and the volumes involved have drawn growing scrutiny. A 2021 study in npj Clean Water estimated that data centers in the United States directly consume about 1.7 billion liters of water per day, with up to 57% of that drawn from potable supplies, and noted that fewer than one-third of operators measured their water use at the time. A separate study published in Environmental Research Letters found that about one-fifth of direct water use by U.S. data centers came from moderately or highly water-stressed watersheds, and that nearly half of the country's servers ran on electricity drawn from water-stressed regions. In Virginia, the December 2024 JLARC audit reported that data centers in the state consumed about 2.1 billion gallons of water in 2023, an 86% increase since 2019, and that roughly one-third of that came from reclaimed water rather than potable supplies. The audit recommended that local governments be authorized to require water-use estimates as part of the data center permitting process. Several U.S. states considered legislation in 2025 to require disclosure of data center water use, including bills in Virginia, California, and New Jersey, although each was vetoed by the state's governor that year. Electricity and grid policy The growth of data center electricity demand in the 2020s has prompted regulatory debates over grid capacity, transmission planning, and how the costs of new infrastructure should be allocated among customers. The 2024 Lawrence Berkeley National Laboratory (LBNL) report on U.S. data center energy use, prepared at the request of the U.S. Congress, estimated that data centers accounted for about 4.4% of national electricity consumption in 2023 and projected a rise to between 6.7% and 12% by 2028, depending on growth scenarios. The International Energy Agency projected in 2025 that data centers would account for nearly half of new U.S. electricity demand growth through 2030. And how the costs of meeting this demand are shared has become a central policy question. The JLARC audit in 2024 estimated that, without any changes to how rates are designed, typical residential customers of Dominion Energy Virginia could see their bills rise by $14 to $37 per month by 2040 because of data center–driven grid investment. As a result, the report recommended creating a separate customer rate class for large data centers. Climate policy alignment The growth of data centers has brought up questions about whether the renewable energy commitments made by their operators are consistent with broader climate goals. Many large operators report meeting electricity-related emissions targets through annual purchases of renewable energy certificates (RECs) or matching their total annual consumption with renewable generation. In 2022, a study by Nature Climate Change analyzed 115 companies with Science Based Targets. It found out that about 42% of their reported Scope 2 emissions reductions disappeared once REC-based claims were excluded. This directly suggests that some corporate climate progress reflected accounting choices rather than actual reductions in grid emissions. As a response, some operators and researchers have proposed 24/7 carbon-free energy matching. Under this approach, every hour of a facility's electricity use must be matched with carbon-free generation on the same regional grid. A 2024 Joule study modeled the idea. The authors found that annual or volumetric matching did little to cut grid emissions under current U.S. policy. Hourly 24/7 matching cut more, but it cost about $13 to $30 more per megawatt-hour. The tension between data center expansion and corporate climate goals has also become apparent in the operators' own disclosures of information. In 2024, Google reported that its greenhouse gas emissions had risen by about 48% since 2019, attributing the increase in large part to data center electricity use associated with artificial intelligence workloads. Microsoft similarly reported in 2024 that its emissions had risen by about 29% since 2020, citing the construction and operation of new data centers. Moreover, the International Energy Agency projected in 2025 that global data center carbon dioxide emissions could peak at around 320 million tonnes by 2030 before declining slightly through 2035, with the trajectory depending heavily on the carbon intensity of the electricity supplied to new facilities. == Social and environmental impacts ==

Data centers have significant impacts on their local ecologies, as well as local politics and utility infrastructure. Fast growth in the data center industry has prompted several debates about their environmental impact, especially from their massive energy and water demands. Their supply chains, emissions, and e-waste also impose significant planetary impacts, raising questions of environmental injustice toward marginalized communities that frequently bear these burdens. Water use The rapid expansion of AI data centers has raised significant concerns over their water consumption, particularly in drought-prone regions. According to the International Energy Agency (IEA), a single 100-megawatt data center, using 2400 MWh of electricity per day, can use up to of water per day. The electricity use is equivalent to that of 60,000-120,000 households in the US (https://www.eia.gov/tools/faqs/faq.php?id=97&t=3), while its water use is equivalent about 6,500 households. Its water usage can be divided into three categories, on-site (direct usage from data centers), off-site (indirect usage from electricity), and supply-chain (water usage from manufacturing processes). On-site water use refers to the direct water consumed by the data center for the cooling of its equipment. Off-site water use is the indirect water usage from the electricity generated in data centers. It is estimated that 56% of U.S. data centers' electricity comes from fossil fuels in thermal power stations, which use water to generate power via steam. Lastly, data centers consume water through the process of AI chip and server manufacturing. These chips, specifically, consume a vast amount of ultrapure water for fabrication and cooling of semiconductor plants. In regions like Aragon, Spain, Amazon's planned data centers are licensed to withdraw of water per year, sparking conflicts with farmers who rely on the same dwindling supplies. Similar tensions have arisen in Chile, the Netherlands, and Uruguay, where communities protest the diversion of water for tech infrastructure. Tech companies, including Microsoft, Google, and Amazon, have pledged to become "water positive" by 2030, aiming to replenish more water than they consume. However, critics argue that such commitments often rely on water offsetting, which does not address acute local shortages. Globally, e-waste totaled 62 million metric tons in 2022, with generative AI projected to contribute 1.2 to 5 million metric tons annually by 2030, including valuable metals like copper and gold alongside hazardous substances such as lead and mercury. From a political ecology perspective, data center e-waste highlights power imbalances in resource management and environmental justice, as tech corporations benefit from tax incentives while externalizing costs to marginalized communities through toxic exports and landfill burdens. This ties into debates on the commons, where shared resources like metals are depleted without equitable governance. Mitigation strategies include modular hardware designs, secure data erasure for reuse, and extended producer responsibility policies to reduce waste by up to 86% in optimized scenarios. This has led to increased electricity prices in some regions, particularly in regions with lots of data centers like Santa Clara, California, and parts of upstate New York. Data centers have also generated concerns in Northern Virginia about whether residents will have to foot the bill for future power lines. It has also made it harder to develop housing in London. A Bank of America Institute report in July 2024 found that the increase in demand for electricity due in part to AI has been pushing electricity prices higher and is a significant contributor to electricity inflation. A Harvard Law School report in March 2025 found that because utilities are increasingly in competition to attract data center contracts from big tech companies, they are likely hiding subsidies to those trillion-dollar companies in power prices by raising costs for American consumers. Bitcoin used up 2% of U.S. electricity in 2023. Scholars argue that these facilities reshape urban and rural landscapes by locating in marginalized or post-industrial areas, often repurposing abandoned sites while promising economic revitalization through job creation and tax revenues. Critics from science and technology studies (STS) highlight how corporate sustainability pledges, such as carbon neutrality targets by companies like Microsoft and Google, often rely on offsets and renewable subsidies that privatize benefits while socializing environmental harms. community resistance to data center development has grown, with residents voicing concerns about water scarcity, rising utility bills, noise pollution, and urban sprawl. Facilities in rural areas of the US have been focal points for local resistance. Data Center Watch reported that multiple projects collectively worth $64 billion had been stopped or delayed between May 2024 and March 2025. An additional $98 billion worth of projects were blocked or delayed between March and June of 2025. Residents have been concerned about air, water and noise pollution, as well as property devaluation, traffic, and the risk of fires. Other environmental concerns involving AI data centers include e-waste and the embodied energy of construction materials that such as concrete and cement. ==Future==

Data centers in space have been proposed for low Earth orbit. The theoretical advantages are that of space-based solar power, in addition to aiding in weather forecasting and weather prediction computation from weather satellites, and the ability to freely scale up. Challenges include temperature fluctuations, cosmic rays, and micrometeorites. The design and shape of data centers could change very rapidly in the not-too-distant future with the advent of new technologies such as quantum computing, biocomputation, and synthetic DNA data storage, as examples. ==See also==