AI数据中心散热导致周边地表温度上升2℃，形成局部热岛效应。
The data heat island effect: quantifying the impact of AI data centers in a warming world
- 利用遥感数据测量全球数据中心周边地表温度变化。
- 数据中心运行后周边平均升温2℃，影响超3.4亿人。
- 揭示了AI发展对局部气候的隐性环境代价，适合政策与可持续计算研究者关注。
AI服务的持续增长导致全球人工智能数据中心数量激增，伴随其能源消耗的不断上升。目前尚不清楚这种计算需求带来的能源消耗会对周边环境产生何种影响。本文聚焦于超大规模数据中心的热量排放问题，利用过去数十年来遥感平台获取的地表温度数据，对全球范围内数据中心周边区域的温度变化进行了稳健评估。结果表明，数据中心投入运营后，其周边地表温度平均上升2℃，形成了局部微气候区，我们称之为“数据热岛效应”。该效应可能影响超过3.4亿人口的生存环境。研究显示，数据热岛效应对未来社区福祉和区域可持续发展具有显著影响，应纳入全球绿色人工智能讨论之中。
原文摘要 · Abstract (English)
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.
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