The main purpose of this ongoing blog will be to track planetary extreme, or record temperatures related to climate change. Any reports I see of ETs will be listed below the main topic of the day. I’ll refer to extreme or record temperatures as ETs (not extraterrestrials).😜
Here is a new feature for this blog, which I will add daily. This is the latest inciteful Green News Report from my friends Desi Doyen and Brad Friedman at Progressive Voices. Hit ‘continue reading,’ listen, then hit return to see my daily topics:
Main Topic: UN Report Exposes Unfathomable Footprint of Data Centers as AI Booms
Dear Diary. Let us turn our attention back to artificial intelligence again today. Guilty as charged. I have discovered how useful AI is for some of my climate work in association with compiling statistics. It has saved me literally months of time and we’ll worth my subscription. Unfortunately, I and millions of other people are responsible for making AI a behemoth that is having dire effects on the environment. It is soaking up both vast amounts of energy to run and using trillions of liters of water to cool. It does seem like for every advancement made to produce more energy (and in the case in the 2020s from wind and solar), that energy is soaked up by new technology.
In any case, I do hope that green energy can more than take up the slack that any demands from new tech in the future. That may sooth my guilty conscience except I do know that as of 2026 going forward to 2030 and beyond AI will cause many people to lose jobs, just another societal upheaval to deal with besides climate.
Here are a few more details from Earth.org:
Data Centers Could Consume 9.3 Trillion Liters of Water By 2030
9.3 Trillion Liters of Water: UN Report Exposes Unfathomable Footprint of Data Centers as AI Booms
Jun 5th 2026
If treated as a country, data centers could rank sixth globally for electricity consumption by 2030. They would also require an amount of water equivalent to the annual needs of 1.3 billion people.
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By Martina Igini
Artificial intelligence (AI) is expanding at breakneck speed, used by hundreds of millions of users and processing billions of queries each day. AI is now one of the most significant drivers of that data center growth. But this growth comes at an unfathomable environmental toll that is at the center of a new United Nations report.
The report, compiled by the United Nations University Institute for Water, Environment and Health and published on Wednesday, used primary data from a range of sources to quantify the carbon, water and land footprints of AI’s electricity use across the globe. The numbers are staggering.
The AI market is expected to grow 25-fold in the coming decade, from $189 billion in 2023 to nearly $5 trillion by 2033. Generative AI – the subfield of AI that autonomously generates text, images, video, audio and code in response to user prompts – already accounts for about 20% of the global market share; by 2030, it is expected to reach 40%.
To function, generative AI needs massive training datasets to learn from. Training these models is an extremely resource-intensive process, but nothing compared to what it takes for them to process billions of interactions each day – not just in terms of the electricity needed to run these centers, but also in terms of the amount of water needed to keep them cool and the land footprint from energy infrastructure and supply chains.
The report estimates that global data centers consumed some 448 terawatt-hours of electricity in 2025, with AI accounting for a fifth of the total. This would make them the world’s 11th largest electricity consumer, if they were a country. This amount of electricity would also be enough to supply the annual residential electricity needs of the 1.3 billion people living in Sub-Saharan Africa for 2.6 years.
This amount of electricity consumption carries an enormous carbon footprint – 189 million tonnes of CO2 equivalent, which only 3.2 billion tree seedlings grown over 10 years would be able to offset.
In terms of water, data centers last year consumed enough to fill 1.8 million Olympic-sized pools – enough to cover the annual basic domestic water needs of over 600 million people in Sub-Saharan Africa.
In terms of land, data centers’ electricity demand covered an area nearly 4.5 times the size of Greater London.
“The public debate still often treats AI as software, but AI is also physical infrastructure: data centres, electricity generation, cooling systems, transmission networks, chips, minerals, land and water,” said Kaveh Madani, the institute’s Director and lead author of the report.
But these staggering numbers are nothing compared to a scenario where AI’s share of data center electricity consumption indeed rises to 40% by 2030. If that happens, the technology’s electricity consumption would make the AI industry one of largest consumers of electricity globally, behind only five countries. The associated water footprint would be 9.3 trillion liters – enough to cover the annual basic domestic water needs of over 1.3 billion people in Sub-Saharan Africa for a full year. And its land footprint would be about twice that of the Jakarta metropolitan area, the most populous metropolitan area in the world, home to over 32 million people.
If that wasn’t enough, the report also estimates e-waste from AI hardware to reach 2.5 million metric tons by the end of the decade – like discarding 250 Eiffel Towers every year.
“What we are showing here is probably just the tip of the iceberg,” Madani told AFP. “We need to require more transparency. We need the providers to provide that information.”
The report also calls on governments to require AI providers to disclose their environmental footprint and on users, organizations and public institutions to use AI intelligently by opting for low-footprint tasks – such as text generation over image or video – and conventional search tools.
Other more sustainable approaches to using generative AI tools include keeping prompts and outputs concise, batching related tasks, reusing previous results, and avoiding unnecessart iterations, according to the report. Meanwhile, AI providers should be transparent with users and inform them when their choices – such as asking for an image or video – can result in intensive energy demand.
Featured image: Wikimedia Commons.
Here are some “ETs” recorded from around the U.S. the last couple of days, their consequences, and some extreme temperature outlooks, as well as any extreme precipitation reports:
Here is More Climate News from Saturday:
(As usual, this will be a fluid post in which more information gets added during the day as it crosses my radar, crediting all who have put it on-line. Items will be archived on this site for posterity. In most instances click on the pictures of each tweet to see each article. The most noteworthy items will be listed first.)