Decarbonizing China's grid: provincial grid carbon footprint factors and export-embedded electricity emissions from 2020 to 2060

Abstract

Quantifying the dynamic evolution of grid carbon footprint factors (GCFFs) is crucial for evaluating electricity-related emissions and advancing China’s dual-carbon goals. This study develops a dynamic model for 30 provinces covering 2020-2060 under three renewable energy development scenarios. Results reveal substantial spatial heterogeneity: between 2020 and 2022, hydropower-rich provinces such as Sichuan and Yunnan maintained GCFF values more than 70% below the national average, whereas coal-dependent regions including Shanxi and Inner Mongolia remained over 40% higher. Under the “Ambitious renewable energy development” scenario (S2), the national average GCFF in 2060 declines by 4.53% relative to the “Business as usual” scenario (representing a 6.22% decrease relative to the “Conservative renewable energy development” (S1) scenario), with reductions exceeding 80% in Jilin and Hainan. Export-sector analysis shows that aluminum-related electricity emissions are highly sensitive to power decarbonization (62% reduction in Shandong under the S2 scenario), while cement emissions are primarily demand-driven. This study establishes the first long-term coupling framework of provincial GCFFs with export-sector emissions, incorporating both non-fossil electricity and upstream extraction. The findings provide a high-resolution evidence base for subnational carbon accounting and targeted low-carbon transition strategies.

Keywords

Electricity grid / generation optimization / grid carbon footprint factors / export-embedded electricity emissions

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