The data heat island effect: quantifying the impact of AI data centers in a warming world

TL;DR

This study quantifies the local temperature increase caused by AI data centers, revealing a 2°C rise that affects over 340 million people and highlights environmental impacts of AI infrastructure.

Contribution

It provides the first global assessment of the heat dissipation impact of AI data centers using remote sensing data, introducing the concept of the data heat island effect.

Findings

Average land surface temperature increases by 2°C near AI data centers.

Over 340 million people could be affected by the temperature rise.

The data heat island effect influences local microclimates and regional welfare.

Abstract

The strong and continuous increase of AI-based services leads to the steady proliferation of AI data centres worldwide with the unavoidable escalation of their power consumption. It is unknown how this energy demand for computational purposes will impact the surrounding environment. Here, we focus our attention on the heat dissipation of AI hyperscalers. Taking advantage of land surface temperature measurements acquired by remote sensing platforms over the last decades, we are able to obtain a robust assessment of the temperature increase recorded in the areas surrounding AI data centres globally. We estimate that the land surface temperature increases by 2{\deg}C on average after the start of operations of an AI data centre, inducing local microclimate zones, which we call the data heat island effect. We assess the impact on the communities, quantifying that more than 340 million people could be affected by this temperature increase. Our results show that the data heat island effect could have a remarkable influence on communities and regional welfare in the future, hence becoming part of the conversation around environmentally sustainable AI worldwide.