Driving factors and decoupling effect of agricultural carbon emissions in Guangxi

Agriculture is a major carbon-emitting sector in China, and developing low-carbon agriculture is essential for building up China’s strength in agriculture and achieving the “dual carbon” goals. Focusing on Guangxi, where located in the karst region, this study employed the emission factor method to estimate agricultural carbon emissions in Guangxi from 2000 to 2022 across three dimensions: agricultural land use, rice cultivation, and animal farming. A systematic analysis of the temporal characteristics of agricultural carbon emissions was conducted across three dimensions: total amount, intensity, and structure. The Logarithmic Mean Divisia Index (LMDI) model was adopted to identify and analyze the driving factors of agricultural carbon emissions in Guangxi. Additionally, the Tapio decoupling model and the decoupling effort model were utilized to examine the decoupling effects between agricultural carbon emissions and the agricultural economic growth. Results indicate: 1) From 2000 to 2022, Guangxi achieved dual reductions in both the total amount and intensity of agricultural carbon emissions. The total carbon emissions exhibited a fluctuating downward trend, decreasing by an average of 0.95% annually, while the emission intensity declined steadily at an average rate of 5.77% per year. 2) Animal farming was the primary source of agricultural carbon emissions in Guangxi, accounting for an average annual share of 41.19%, with cattle being the largest contributor. Rice cultivation ranked as the second-largest source, averaging 33.98% annually, with late rice being the dominant contributor. Carbon emissions from agricultural land use accounted for an average annual share of 24.82%, with chemical fertilizers being the largest contributor. 3) The agricultural economic development level had a positive driving effect on agricultural carbon emissions. Conversely, agricultural production efficiency, agricultural industrial structure, and the scale of agricultural employment had negative inhibitory effects. The magnitude of these effects ranked as follows: agricultural economic development level > agricultural production efficiency > scale of agricultural employment > agricultural industrial structure. 4) Weak decoupling was the main state between agricultural carbon emissions and agricultural economic growth in Guangxi. However, this decoupling lacked stability and was prone to fluctuations and reversals. Agricultural production efficiency demonstrated the strongest decoupling effort with agricultural carbon emissions, while the agricultural industrial structure showed minimal decoupling effort and had a negligible impact on agricultural carbon reduction. Guangxi should further control carbon emissions from animal farming, promote green transformation in rice production, encourage the reduced use and increased efficiency of agricultural inputs such as fertilizers and pesticides, and develop new quality productive forces tailored to enhance production efficiency and advance agricultural carbon reduction.