@justinmikulka.bsky.social:
New protest grafitti around town.
The data heat island effect: quantifying the impact of AI data centers in a warming world
- March 2026
- License
- CC BY-NC-ND 4.0
Preprints and early-stage research may not have been peer reviewed yet.
Abstract and Figures
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°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.
…
AI hyperscalers apparently is not limited to the immediate proximity of their locations. In fact, we computed the temperature increase over wider regions circularly arranged around the data centres, following the same procedure that we previously described. Figure 3displays the results of this analysis. Taking a look to these results, it is evident that the impact of LST increase reaches up to 10 km distance from the AI hyperscalers. The data heat island effect seems to reduce its intensity to 30% within 7 km around the data centres. In particular, an average monthly LST increase of 1 °C can be measured up to 4.5 km from the AI hyperscalers. This spatial extent is comparable to that observed in urban heat island effects [1,6,8]. The LST increase that is recorded in the area surrounding AI data centres seem consistent across various regions of the world, even if under diverse climatic conditions. …
5 Conclusions
The increasing demand for AI-based services, processes and operations led to the proliferation of data centres worldwide that are extremely power hungry. In this paper, we provide the first assessment of the environmental impact of AI hyperscalers. We focus our attention on the heat dissipation of data centres, which is directly connected to the energy consumption required for the operations of the AI hyperscalers. We investigate, by means of a multimodal multiscale architecture, the land surface temperature change occurred as a consequence of the start of operations of the data centres. Our analysis spans over the last decades (from 2004 to 2024), taking advantage of the plethora of remotely sensed temperature measurements acquired by satellites worldwide. Our study shows a non negligible and rather remarkable impact of the AI data centres on their local regions, which is consistent across the data centres worldwide and extends for several kilometers around the AI hyperscalers. The consistency, scale and extent of these effects lead to think that the creation of local climate zones induced by data centres – that we call the data heat island effect – is real and significant, especially in the context of global warming and climate transformation.
Consequently, the data heat island effect could affect the welfare, healthcare, energy, and demographic systems. Since the trends of data centre energy consumption are expected to show a steep growth in the foreseeable future, the data heat island effect could solidly become an additional factor for environmental and industrial sustainability in the changing climate, hence having a robust impact on communities at local, regional, and international level, thus demanding to be studied in complex multi-hazard systems. To this aim, in this paper we provide an overview of potential solutions to alleviate the data heat island effect, which could be further expanded into mitigation policies for future climate and socioeconomic scenarios.