Press Release: Rising #Emissions, Depleting #Water and Vanishing #Land—UN Scientists: #AI Is Threatening #NaturalResources for Billions
By 2030, AI's water use will match the needs of 1.3 billion people while its power use triples that of 650 million, UN University investigation warns
Date Published
3 Jun 2026
Excerpt: "Inference, efficiency, and the rebound effect
"Public discussion has largely focused on the energy required to train massive models. Training GPT-3 was estimated to require 1.3 gigawatt-hours (GWh) of electricity, while estimates suggest GPT-4 consumed between 50 and 70 GWh. However, the report reveals this framing is outdated. Once a model is deployed, inference—the continuous running of models to answer everyday user prompts—becomes the dominant cost, accounting for 80 to 90 per cent of total #AI energy use. ChatGPT alone is estimated to process around 2.5 billion prompts per day, translating to roughly 383 GWh of electricity per year for a single product. Offsetting associated carbon emissions would require 2.6 million tree seedlings grown for 10 years, enough trees to cover a land area the size of Manhattan. The water footprint is equivalent to the minimum annual domestic water needs of roughly 500,000 people in Sub-Saharan Africa, and the land footprint is equal to over 800 football fields."
Read more:
https://unu.edu/inweh/news/environmental-cost-of-AIs-Enrgy-use-carbon-water-and-land-footprints
#AIBoom #Electricity #Hyperscale #BigTech #BigData #CarbonFootprint #EnvironmentalRacism #EnvironmentalDegradation #NoisePollution #LightPollution #WaterIsLife #AIAgents #BotTraffic #GreenSpaces #Farmland #Prairies #Woodland #TechGiants #ProtectNature #NoDatacenters #EnergyConsumption #USPol #WorldPol #Datacentres
#DatacenterMoratoriums #ArtificialIntelligence
The #EnvironmentalCost of #ArtificialIntelligence: #Carbon, #Water, and #LandFootprints
#AI’s rapid growth drives huge energy, water, and land use, raising environmental and equity challenges across its global infrastructure.
Date Published 3 Jun 2026
UNU-INWEH Report: Aczel, M., Chamanara, S., Matin, M., Farsi, A., Marwala, T., Madani, K. (2026).
"This report, Environmental Cost of Artificial Intelligence: Carbon, Water and Land Footprints, by the #UnitedNationsUniversity Institute for Water, Environment and Health (#UNU-#INWEH) on its 30th anniversary, examines one of the most underexplored consequences of AI’s rapid expansion: the environmental footprints of the energy required to power it. As artificial intelligence becomes embedded in economies, public services, research, communication, and everyday life, it depends on a growing physical infrastructure of #datacenters, advanced #chips, #CoolingSystems, #ElectricityGrids, #WaterResources, land, and #CriticalMineral supply chains. The report shows that AI is not only a digital technology, but also a material system with measurable #EnvironmentalCosts.
"The report moves beyond a carbon-only lens by quantifying the carbon, water, and land footprints associated with the electricity used to train, deploy, and operate AI systems at scale. Its central finding is that AI’s environmental costs depend not only on how much electricity is used, but also on where that electricity is generated and which energy sources power it. Every kilowatt-hour used by AI carries carbon, water, and land implications, and these footprints do not always move in the same direction: low-carbon electricity is not automatically low-water or low-land. The report also shows that AI’s footprint is shaped by both major infrastructure trends, including the rapid growth of data centers, and everyday use patterns, including model choice, output length, modality, and the growing use of text, image, and video generation.
"Importantly, the report frames AI’s environmental footprint as a governance and justice challenge, not only a technical problem. The benefits of AI often flow across borders and sectors, while the environmental burdens of data center siting, electricity demand, water withdrawals, #LandUse, MineralExtraction, and #EWaste can be concentrated in specific communities and regions. To address these risks, the report calls for a responsible AI ecosystem grounded in transparency, efficiency by design, equity and #EnvironmentalJustice, lifecycle responsibility, global cooperation, and sustainable use. By making AI’s carbon, water, and land footprints visible and comparable, the report provides a practical basis for integrating AI into energy, climate, water, and land-use planning, ensuring that innovation advances without shifting environmental costs onto vulnerable communities."
Download PDF:
https://unu.edu/inweh/collection/environmental-cost-of-AIs-Enrgy-Use-Carbon-water-and-land-footprints
#AIBoom #Electricity #Hyperscale #BigTech #BigData #CarbonFootprint #EnvironmentalRacism #EnvironmentalDegradation #NoisePollution #LightPollution #WaterIsLife #AIAgents #BotTraffic #GreenSpaces #Farmland #Prairies #Woodland #TechGiants #ProtectNature #NoDatacenters #EnergyConsumption #USPol #WorldPol #Datacentres
#DatacenterMoratoriums
The #AI boom is gobbling up power faster than ever
By Hannah Beckler, June 7, 2026
Excerpt: "The data center boom is accelerating.
"A Business Insider analysis of US data center permits reveals a staggering escalation in data center power use. Data centers across the US are growing in number and in size. If all data centers permitted through 2025 come online, they will use between 224.3 terawatt-hours and 358.8 terawatt-hours of electricity annually, an increase of 50% over the previous year across the range, Business Insider's analysis found.
"At the midpoint, that's more than all the #electricity used by any one US state in 2024, except Texas.
"The vast majority of this power use is driven by #hyperscale data centers, mammoth facilities that use 40 megawatts or more each, Business Insider estimates.
"#TechGiants have an insatiable appetite for more computing power to fund their AI ambitions. In 2025, permits were issued for 176 new data centers across 34 states — the most new permits in one year since the first was issued in 1976, Business Insider found. Many of them are mammoth facilities destined for rural areas — enormous complexes blanketing #prairies, #GreenSpaces, and #farmland.
"#AmazonCorp's planned 14-building data center complex in #RidgelandMS, would transform nearly 800 acres of rural #woodland. In the village of #MountPleasantWI, Microsoft's nine data center buildings would command a collective footprint of over 5.2 million square feet built on a property nearly the size of New York City's Central Park, according to planning documents. And just outside #EagleMountainOT, #QTS — one of the nation's biggest data center operators — is building one that is expected to demand between 1.9 and 3 terawatt-hours a year once fully online, according to Business Insider's estimate. On average, that's the same amount of electricity used by 227,000 US homes.
"The race by tech companies to reach ever-greater AI ambitions has sparked a sweeping backlash from local residents and state and local officials wary of #Datacenter impacts on the #environment, economy, and #communities. And development-friendly lawmakers could face a reckoning in this year's #midterms, in which data centers are emerging as a key issue for many voters."
https://www.businessinsider.com/us-ai-data-center-power-electricity-use-consumption-2026-6
Archived version:
https://archive.ph/hJXeS
#NoDatacenters #AIBoom #EnergyConsumption #NoisePollution #LightPollution #WaterIsLife #USPol #USMidTerms #Elections2026 #Datacentres #DatacenterMoratoriums #BigData #BigTech
Green Spaces of Aktau: Parks and Urban Landscaping in Western Kazakhstan
Aktau is often associated with the Caspian Sea, rocky coastlines, and desert landscapes. However, the city also features a growing network of parks, landscaped areas, and green public spaces that provide residents and visitors with places to relax and enjoy nature. Many of Aktau’s parks contain a variety of ornamental plants, evergreen trees, flowering shrubs, and carefully maintained walking paths. These green areas create a pleasant contrast to the dry climate of western Kazakhstan and […]
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