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Home / Environment / Datacentre Water Use: Shocking 50x Underestimation?

Datacentre Water Use: Shocking 50x Underestimation?

19 Dec

•

Summary

  • Datacentre water use could be 50 times higher than estimated.
  • Indirect water consumption linked to AI server energy demands.
  • Air pollution concerns from generators affect local communities.
Datacentre Water Use: Shocking 50x Underestimation?

Analysis indicates that the UK's largest proposed datacentre, a hyperscale campus by QTS in Northumberland, may be drastically understating its water consumption. While QTS estimates 2.3 million litres annually for its initial data halls, research suggests indirect water use for AI server electricity generation could exceed 124 million litres, over 50 times the operator's projection.

This "embedded" water footprint is a growing concern, similar to carbon emissions accountability for power-intensive industries. Furthermore, potential air pollution from the facility's nearly 600 backup diesel generators, intended for emergency use but subject to potential expanded operation, poses health risks to nearby communities, including Cambois primary school.

QTS maintains its operations are sustainable and within emissions limits, emphasizing that generators are primarily for emergency backup. However, environmental advocates warn of the potential for increased generator use, drawing parallels to situations in Virginia where backup systems face pressure for more frequent deployment.

Disclaimer: This story has been auto-aggregated and auto-summarised by a computer program. This story has not been edited or created by the Feedzop team.
Analysis suggests the Northumberland datacentre's indirect water consumption could be over 50 times higher than QTS's estimate, potentially reaching 124 million litres annually.
The datacentre's backup diesel generators could cause air pollution, impacting local areas like Cambois primary school, similar to issues seen in US datacentre hubs.
Embedded water footprint refers to the indirect water used in electricity generation to power datacentre operations, particularly for AI servers.

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