Dr. Miriam Aczel

Researcher @UNUINWEH 🇺🇳 | Affiliate @ucberkeley @UC_CIEE @citrisnews | @ImperialCollege @IC_CEP | @mcgillu alum | cofounder @aczelfoundation (she/her)

[Thomas Rocha @TRTRE62]

1/7 UN researchers are warning that data-center power and water use could double by 2030, driven by AI demand.

The EU energy-standard proposal is the policy response.

But the deeper question is architectural:

How much is useful compute?

How much is coordination waste?

#UN #AI #DataCenters #EnergyPolicy #WaterUse

[hasanfr @hasanfr_0rg]

AI is brilliant, but it is incredibly thirsty.

Behind every seamless workflow automation lies a physical infrastructure that is quietly draining our natural resources.

A new UN report just exposed the true cost of our tech.

🧵👇

[New Scientist @newscientist]

A UN report warns of the rapid growth in AI energy consumption, but suggests users can improve efficiency by making prompts more concise https://t.co/9pvZMJNGhw

[Massimo @Rainmaker1973]

Data centers powering artificial intelligence are projected to consume roughly twice as much electricity and water by 2030 as they do today, according to a new report from United Nations researchers.

Although AI is often perceived as intangible cloud-based technology, every query, image, or video relies on a massive physical infrastructure of servers, cooling systems, power grids, chips, land, and water.

In 2025, global data centers used approximately 448 terawatt-hours (TWh) of electricity, more than the total consumption of Saudi Arabia. AI accounted for about one-fifth of that demand. These facilities also consumed around 1.2 trillion gallons (4.5 trillion liters) of water and emitted roughly 189 million tons of carbon dioxide.

By 2030, researchers forecast that annual electricity consumption by data centers will rise to 945 TWh, roughly equivalent to Japan’s current total electricity use, with AI expected to drive 40% of the total. Water consumption is projected to double to about 2.5 trillion gallons (9.3 trillion liters) per year. The physical land footprint could also expand from roughly 2,664 square miles (6,900 km²) today to more than 5,600 square miles (14,500 km²).

The surge stems from the immense computational demands of training and running advanced AI models, which require powerful chips running continuously and generate substantial heat that must be managed through energy- and water-intensive cooling.

The report emphasizes that AI is not inherently unsustainable. The technology offers potential benefits for optimizing energy systems, reducing waste, and improving efficiency across industries. However, the rapid pace of AI infrastructure development risks outstripping environmental planning, particularly in regions already facing resource constraints. Massive new data centers could intensify competition for electricity and water with communities, agriculture, and natural ecosystems.

[Aczel, M., Chamanara, S., Matin, M., Farsi, A., Marwala, T., & Madani, K. (2026). Environmental Cost of AI’s Energy Use: Carbon, Water and Land Footprints. United Nations University Institute for Water, Environment and Health (UNU-INWEH)]

[New Scientist @newscientist]

A UN report warns of the rapid growth in AI energy consumption, but suggests users can improve efficiency by making prompts more concise https://t.co/4OAhNOMSVZ

[Tshilidzi Marwala チリツィ・マルワラ . 丸笑 @tmarwala]

AI is transforming our world — but it comes with real environmental costs. A new UNU-INWEH report highlights AI’s growing carbon, water, and land footprints. As AI scales, sustainability and transparency must remain central to its governance.
Read more: https://t.co/2OGO4b8X0J

[UN University-INWEH @UNUINWEH]

Hear from UNU-INWEH scientists and the rector of the United Nations University and Under-Secretary-General of the United Nations, on why there is a need for responsible AI use and why its unintended impacts must be addressed for a better tomorrow.

📖 https://t.co/KtBHJlLIqS

[Dion Harper @DionHarper15]

UN report warns AI could soon use 3% of world’s electricity and more water than we need to drink https://t.co/LxgAgM736c

[Dr. Miriam Aczel @MiriamAczel]

@spion @PLT_cheater @AndyMasley Yes 47 Wh is a mean estimate for short text generation electricity (measurements across 1,000 tasks from a paper by Sasha Luccioni et al)

[Kaveh Madani @KavehMadani]

Learn more about our latest investigation results.

[Tshilidzi Marwala チリツィ・マルワラ . 丸笑 @tmarwala]

Pleased to have co-authored this new UNU-INWEH report on the environmental cost of AI. As AI scales, so do its carbon, water, and land footprints. Sustainable AI must be central to AI governance. 🌍⚡💧
🎥 https://t.co/sZqB2AcDA9
#AI #Sustainability #UNU

[Dr. Miriam Aczel @MiriamAczel]

@PLT_cheater @spion @AndyMasley it’s a great comparison. assuming roughly 30– 50 Wh to boil water for a cuppa, it’s in same ballpark as a short GPT text response at 47 Wh

[Tshilidzi Marwala チリツィ・マルワラ . 丸笑 @tmarwala]

United Nations University on the news ⁦@KavehMadani⁩

[Dr. Miriam Aczel @MiriamAczel]

@spion @PLT_cheater @AndyMasley Great idea!

[Shining Science @ShiningScience]

A new United Nations report warns that AI's immense appetite for electricity, water, and land is pushing the planet toward an unprecedented environmental crisis in the next few years.

The rapid expansion of artificial intelligence is placing an unprecedented strain on Earth's resources, prompting a direct warning from the United Nations University.

According to scientists, AI-related workloads accounted for 20% of data center electricity in 2025 and are projected to double to 40% by 2030

. By then, AI's global electricity consumption could power all of sub-Saharan Africa for over two years, generating a carbon footprint of 400 million tonnes of carbon dioxide. Furthermore, data centers are projected to consume a colossal 9.3 trillion liters of water annually for cooling by 2030—enough to satisfy the drinking water needs of the entire global population for more than a year and a half.

Beyond raw resource consumption, the UN warns of a widening digital divide and a massive pileup of up to 2.5 million tonnes of annual electronic waste by 2030. Currently, 90% of specialized AI cloud infrastructure is concentrated in just the United States and China, leaving over 150 nations with no sovereign AI capacity while they bear the brunt of mineral extraction and waste.

To counter these systemic issues, UN experts are urging governments, developers, and everyday users to embed environmental impacts into all AI decisions, emphasizing that even 'renewable-powered' data centers carry heavy environmental footprints that cannot be ignored.

source: Speare-Cole, R. (2026, June 3). UN issues AI warning after new data reveals major impact on the planet and its resources. The Independent.

[Remarks @remarks]

JUST IN: 🇺🇳 UN warns AI could soon use more water than everyone in the world needs to drink.

[Tshilidzi Marwala チリツィ・マルワラ . 丸笑 @tmarwala]

https://t.co/m1jMjHe0jl

[Kaveh Madani @KavehMadani]

The results of our recent report on the environmental impacts of AI and their implications for Canada’s 🇨🇦 AI strategy.

Our message is clear: investments in AI are necessary, but so are investments in sustainability, justice, and equity.

AI is not only digital. It also has real water, energy, land, and critical mineral footprints that cannot be ignored.

https://t.co/JvvgExyOHv

[Sky tg24 @SkyTG24]

Kaveh Madani, direttore dell’Istituto Universitario per l’Acqua, l’Ambiente e la Salute dell'Università dell’ONU, ha presentato il rapporto dedicato all’impatto che l’IA ha sull’ambiente, sottolineando come la situazione sia sottovalutata, ma con qualche accortezza di potrebbe imboccare la strada di quella che viene chiamata “IA responsabile”. Si legge su #SkyInsider https://t.co/X6gBf8xdNo

[United Nations University @UNUniversity]

The latest @UNUINWEH report unveils stark findings about the environmental cost of #AI’s energy use ⚡️

A responsible AI system — for people and planet — is urgently needed.

Access the full report: https://t.co/FKyQ5UZZzD

#WorldEnvironmentDay #NowForClimate