Demonstrates efficient carbon allowance allocation in cities, suggesting a new framework for emissions management.
Reasonable carbon allowance allocation for power transmission and transformation projects is critical for regional emission reduction, yet existing methods rarely address spatial heterogeneity or the fairness-efficiency trade-off at the city level. This study proposes a framework integrating entropy weighting with Zero-Sum Gains Data Envelopment Analysis (ZSG-DEA), applied to cities in Liaoning, China, to achieve objective initial distribution and efficiency-driven adjustments under a binding carbon cap. Empirical results reveal that regional quota levels are shaped not by economic scale or historical emissions alone, but by grid hub functions, load intensity, new energy transmission demand, and network density. The integrated approach avoids subjective bias and optimizes allocation efficiency, offering a replicable pathway for carbon quota allocation in similar contexts.
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Guo et al. (2026) studied this question.
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