Energy and Carbon Constraints on China’s AI Compute Expansion: An EROI Analysis

Published: 1 June 2026| Version 1 | DOI: 10.17632/sgpy2zpdph.1
Contributor:
Wei-Ta Fang

Description

All numerical results in this paper are reproducible from the eight source CSV files listed in Supplementary Table S4 (sectoral panel, AI energy budget, net EROI summary, grid EROI, sectoral electricity trajectories, sectoral CO₂, sensitivity matrix). These files will be made available on Mendeley Data on acceptance, or on reasonable request to the corresponding author. CEADs MRIO data are available from https://www.ceads.net/; IEA Electricity Statistics and Energy and AI data are available via the IEA portal at https://www.iea.org/data-and-statistics.

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Steps to reproduce

“Direct” values are reported in the cited literature. “Derived” values are produced by applying the Brockway et al. (2019) convention: primary or mine-mouth EROI × thermal conversion efficiency × T&D efficiency = final-stage delivered-electricity EROI. Where the literature reports a range, a conservative central value is taken. Generation shares are from IEA Electricity 2025 and Ember Global Electricity Review.

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Categories

Energy Audit, Artificial Intelligence Governance

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