A study on carbon quota allocation in China's transportation sector with consideration of emission reduction potential

Regional disparities make the fair and efficient allocation of carbon reduction targets a critical issue for achieving global climate goals. The transportation sector is a major and fast-growing source of carbon emissions, and its quota allocation poses important challenges for emission reduction policy. This study explores how to reconcile efficiency and equity in the allocation of transport-related carbon quotas across China's regions under its 2030 carbon peak target. We estimate the carbon emissions of China's transportation sector across 30 provinces from 2010 to 2020 using the emission factor method, and predict the emissions for 2030 using the gray model first-order one-variable (GM[1,1] model). An initial carbon quota allocation scheme is developed using the zero-sum gain data envelopment analysis (ZSG-DEA) model, and regional carbon reduction potential is incorporated through a dynamic adjustment mechanism to optimize the quota distribution. The results show: (1) Transport carbon emissions in China are projected to reach 1.818 × 109 tons by 2030. (2) The efficiency-oriented ZSG-DEA model improves national carbon quota efficiency by 9.8% after five iterations, but it intensifies regional disparities in reduction burdens. (3) Incorporating reduction potential constraints balances regional quota adjustments, reduces overall reduction pressure, narrows the range by 26.04%, and the responsibility mismatch issue has been mitigated by 8.78%, demonstrating the feasibility of optimizing both efficiency and equity. These findings will provide a methodological reference for designing equitable and efficient transport carbon allocation schemes in China and other major economies.