Abstract:Improving agricultural carbon productivity as a way to achieve low-carbon green development in agriculture has received widespread attention, but existing studies have focused on the impact of a single factor on agricultural carbon productivity, and few have explored the synergistic effects of multiple factors on agricultural carbon productivity. A sample of 31 provinces in China from 2006 to 2020 was selected to measure the total agricultural carbon emissions and carbon productivity at the provincial scale based on regional differences in carbon emission factors, and a single-factor and multi-factor analysis framework based on the configuration perspective was constructed to analyze the complex causal mechanisms and multiple enhancement paths affecting agricultural carbon productivity using fuzzy set qualitative comparative analysis. The results show that the overall trend of agricultural carbon productivity in China is increasing. The distribution pattern of agricultural carbon productivity is significantly higher in the east than in the middle and west, and the difference of agricultural carbon productivity between provinces is obvious. The configuration types that generate high agricultural carbon productivity are: regional economy driven type, agricultural technology driven type, planting structure-regional economy driven type, and planting structure-labor quality driven type. The configuration types that inhibit the improvement of agricultural carbon productivity include planting structure inhibition type, industrial structure-urbanization rate inhibition type, and industrial structure-regional economic level inhibition type. The planting structure has always been the core driving force for high agricultural carbon productivity. The driving effect of urbanization rate and agricultural policy support on agricultural carbon productivity has weakened over time. The role of regional economy and labor quality in improving agricultural high carbon productivity has been enhanced.