AI data centres raise local land temperatures by up to 9.1°C

Data centres powering artificial intelligence are causing land surface temperatures to rise by an average of 2°C near their locations, with extremes reaching 9.1°C, according to researchers at the University of Cambridge. The heat effects extend up to 10 kilometres away, potentially impacting more than 340 million people worldwide. The findings come from a study analysing satellite data over the past two decades.

Researchers led by Andrea Marinoni at the University of Cambridge examined satellite measurements of land surface temperatures from the past 20 years, cross-referencing them with the locations of more than 8,400 AI data centres. To isolate the centres' impact, they focused on facilities situated away from densely populated areas, accounting for other potential influences on temperature readings. Their analysis revealed an average temperature increase of 2°C (3.6°F) in the months following a data centre's operational start, with the most extreme cases showing a rise of 9.1°C (16.4°F). The warming persisted up to 10 kilometres from the sites, diminishing by only 30 per cent at seven kilometres. Marinoni described the results as 'quite surprising' and warned, 'This could become a huge problem.' Real estate firm JLL forecasts that global data centre capacity will double between 2025 and 2030, with AI driving half of that growth amid surging energy demands. Using population data, the team estimated that over 340 million people reside within 10 kilometres of such facilities, experiencing warmer conditions than they otherwise would. Specific regions like Mexico's Bajío and Spain's Aragon province registered unexplained 2°C increases between 2004 and 2024. Chris Preist at the University of Bristol noted the findings' nuance, calling for further research to distinguish heat from computation versus the structures themselves absorbing sunlight. Marinoni maintained that data centres elevate ground temperatures regardless and urged caution in their design and development. The study appears on arXiv under DOI arXiv:2603.20897.

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