AI carbon footprint in China sets to double post-2030 carbon peaking

Zhan-Ming Chen, Qiyang Xiong, Jiahui Duan, Jianhong Ma, Zhuo Chen and Shan Guo

Energy Economics, 2025, vol. 150, issue C

Abstract: The unprecedented advancements in artificial intelligence (AI) have significantly increased energy consumption, raising global concerns about AI carbon footprint. As a global AI leader, China stands at a crucial juncture where its AI development intersects with national energy transition and climate strategies, particularly concerning its Carbon Peaking and Carbon Neutrality Goals. This study employs an uncertainty-based Architectural Carbon Modeling Tool and scenario analysis to quantify the energy consumption and carbon footprint of AI data centers in China from 2022 to 2050. Our projections indicate that the electricity consumption of AI data centers will surpass 1000 TWh by 2030, exerting pressure on the power system and driving a significant increase in emissions. The carbon footprint is projected to double after 2030, peaking at 695 Mt. in 2038 and declining to 474 Mt. by 2050, with manufacturing emissions contributing approximately 18 % of the total. Geospatial analysis reveals that under the Business as Usual scenario, energy demand remains concentrated in the eastern provinces, whereas the Advanced Green scenario redistributes AI computing demand to the west, creating new carbon hotspots. Increasing the proportion of internal green electricity is identified as the most effective strategy, with the potential to reduce operational emissions by 42 %. This study comprehensively examines AI's energy implications and provides policy-relevant insights for balancing technological advancements with long-term energy sustainability.

Keywords: AI data center; Carbon footprint; Architectural carbon modeling; Scenario analysis (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:150:y:2025:i:c:s0140988325007078

DOI: 10.1016/j.eneco.2025.108880

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