Wave convergence principles of agricultural carbon emission efficiency: a multi-level urban agglomeration study.

Agriculture plays a pivotal role in global greenhouse gas emissions. This study focuses on the quantitative simulation and validation of the wave convergence patterns of agricultural carbon emission efficiency, aiming to deeply understand the process of collaborative governance between central and surrounding cities within urban agglomerations, thereby achieving stable and sustainable development goals for the carbon emission system. Based on the dynamic DEA model, this paper employs an enhanced common frontier dynamic super-efficiency SBM model to quantitatively evaluate the agricultural carbon emission efficiency of urban agglomerations and their constituent cities. Subsequently, a gravity model is introduced to measure the changes in the joint intensity of agricultural carbon emission efficiency within urban agglomerations, and a wave-like convergence curve function model is employed to validate the proposed regularity. The findings indicate: (1) The agricultural carbon emission efficiency exhibits a fluctuating downward trend, with a distribution depicted by higher efficiencies in the northern and southern regions and lower efficiencies in the rest part. (2) The joint intensity of agricultural carbon emission efficiency tends towards a wave-like increase and exhibits joint threshold effects, with the outcomes for national urban agglomerations significantly surpassing other groups. (3) The evolutionary curves of agricultural carbon emission efficiency in Chinese urban agglomerations essentially show wave-like converging changes over time and in conjunction with urban joint development, with the fitted curves of carbon emission efficiency across different urban agglomerations showing high degrees of similarity.