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US data centers under construction by Amazon, Google, Meta and Microsoft will emit CO₂ equal to 24 million cars

US data centers under construction by Amazon, Google, Meta and Microsoft will emit CO₂ equal to 24 million cars

A new analysis of the 60 largest data centers currently under construction in the United States by Amazon, Google, Meta and Microsoft estimates that once fully operational, these facilities could produce a cumulative 101.5 million tons of carbon dioxide annually. This is equivalent to running 27 coal power plants or putting 24 million additional gasoline-powered cars on the road, according to the Financial Times.

The projected emissions would account for roughly 7% of all 2025 US power-sector emissions. The findings come amid growing backlash against America's data center and artificial intelligence boom, which has already sparked protests over water use, land grabs, and noise complaints. Environmental activist Erin Brockovich has been mapping communities affected by data center construction, and recent polls show that most Americans do not want AI factories near their homes.

The carbon problem adds to a list of environmental concerns surrounding Big Tech's rapid infrastructure expansion. Just five years ago, major technology companies appeared publicly committed to cutting emissions, but the new data suggests a notable reversal. The Financial Times found that Amazon's emissions climbed 16% from 2024 to 2025, driven by data center construction and a 34% jump in electricity purchases. Microsoft reported a 25% increase in estimated emissions over the same period, while Alphabet, Google's parent company, reported an 18% year-over-year increase in its emissions figure according to its own adjusted metric.

Researchers point to a mix of causes, including the sheer scale of demand for AI infrastructure and a political environment under the Trump administration that has weakened environmental regulations. The analysis underscores the tension between Big Tech's climate pledges and the reality of building energy-intensive AI infrastructure at an unprecedented scale.

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