[Agricultural Carbon Emission Efficiency： Re-measuring， Spatio-temporal Characterization and Convergence]

Agricultural carbon emission efficiency serves as a crucial indicator for evaluating low-carbon agricultural development. Accurately measuring the agricultural carbon emission efficiency and investigating its spatio-temporal evolution patterns can facilitate region-specific pathways for low-carbon agriculture development. The agricultural carbon emission efficiency was remeasured in China's 30 provinces （2012-2023） using the three-stage super-efficiency SBM-DEA model. The regional differences and dynamic evolution of the agricultural carbon emission efficiency were investigated by using the Dagum Gini coefficient and kernel density estimation， while its convergence was analyzed using the convergence model. The results show that： ① External environmental factors exerted significant effects on China's agricultural carbon emission efficiency. The mean agricultural carbon emission efficiency in China decreased from the initial 0.673 to 0.653 after eliminating the effects of external environmental factors and random errors. ② Significant regional differences were observed in China's agricultural carbon emission efficiency， with inter-regional differences accounting for the majority of the total differences. The kernel density curves of the agricultural carbon emission efficiency exhibited rightward shifts at both the national level and in four major regions. The kernel density curves exhibited multi-polar evolution patterns at the national level as well as in the eastern， central， and western regions， while showing alternating multi-polar and bipolar distributions in the northeastern region. ③ The σ-convergence was observed in the agricultural carbon emission efficiency at the national level as well as in the northeastern and western regions， whereas the agricultural carbon emission efficiency failed to achieve σ-convergence in the eastern and central regions. The agricultural carbon emission efficiency exhibited both absolute β-convergence and conditional β-convergence at both the national level and in four major regions； however， there were differences in the convergence speed， with the fastest in the central region and the slowest in the northeastern region. All regions should not only develop localized pathways to improve the agricultural carbon emission efficiency but also establish inter-regional cooperative mechanisms to promote the synergistic improvement in the agricultural carbon emission efficiency at the national level.