ACE efficiencies in different regions of the YEB.

As China’s second-largest source of greenhouse gas emissions, agriculture is essential to achieving the goal of "carbon peak" and "carbon neutrality." Based on the measurement of agricultural carbon emissions (ACE) and agricultural carbon intensity (ACI) in 19 regions along the Yangtze River Economic Belt (YEB) and Yellow River Basin (YRB) in China from 2001 to 2020, this paper first uses the super-efficiency SBM model to measure ACE efficiency from static and dynamic perspectives. Then, the coupling coordination degree (CCD) between ACE efficiency and green finance in each region of the two basins is explored. Finally, Grey Relation Analysis (GRA) is used to obtain the influencing factors of CCD. The following conclusions are drawn: (1) The ACE in the YEB is almost twice that of the YRB. The ACE of the two basins generally experienced a trend of first growth and then declined, but the peak time was different. The ACI of the two basins showed a trend of continuous decline, and the decline rate of the YRB was faster. (2) The ACE efficiency of the two basins showed an overall upward trend, and the growth degree of different regions was vastly different. From the factor decomposition, the technological progress (TP) of the two basins significantly impacts the total factor productivity (TFP). (3) The CCD of ACE efficiency and green finance in the two basins increased from near imbalance to barely coordination level, and the CCD of the YEB increased slightly faster. The CCD of the two basins has a spatial difference of "downstream > midstream > upstream." (4) Among the influencing factors of the CCD of the two systems, the influencing degree of the factors is as follows from large to small: quality of human capital, level of economic development, government regulation, scientific and technological innovation ability.

作为中国第二大温室气体排放源，农业对于实现“碳达峰”与“碳中和”目标至关重要。基于2001至2020年中国长江经济带（Yangtze River Economic Belt, YEB）与黄河流域（Yellow River Basin, YRB）沿线19个地区的农业碳排放（agricultural carbon emissions, ACE）与农业碳强度（agricultural carbon intensity, ACI）测算数据，本文首先采用超效率SBM模型从静态与动态双视角测算农业碳排放效率。随后，探究两大流域各地区农业碳排放效率与绿色金融间的耦合协调度（coupling coordination degree, CCD）。最后，运用灰色关联分析（Grey Relation Analysis, GRA）获取耦合协调度的影响因素。研究得出以下结论：（1）长江经济带的农业碳排放总量几乎为黄河流域的两倍。两大流域的农业碳排放整体呈现先增长后下降的趋势，但峰值出现时间存在差异；两大流域的农业碳强度均表现为持续下降态势，且黄河流域的下降速度更快。（2）两大流域的农业碳排放效率整体呈上升趋势，不同地区的增长幅度差异显著。从要素分解结果来看，两大流域的技术进步（technological progress, TP）对全要素生产率（total factor productivity, TFP）具有显著影响。（3）两大流域的农业碳排放效率与绿色金融的耦合协调度从濒临失调逐步提升至勉强协调水平，且长江经济带的耦合协调度增速略快。两大流域的耦合协调度存在“下游>中游>上游”的空间分异特征。（4）在两大系统耦合协调度的影响因素中，各因素的影响程度从大到小依次为：人力资本质量、经济发展水平、政府调控力度、科技创新能力。