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 an agricultural powerhouse and achieving the dual carbon goals. Focusing on Guangxi, where located in karst region, this study employs the emission factor method to estimate agricultural carbon emissions in Guangxi from 2000 to 2022 across three dimensions: agricultural land use, rice cultivation, and livestock farming. A systematic analysis of the temporal characteristics of agricultural carbon emissions was conducted across three dimensions: total volume, intensity, and structure. The LMDI model was used 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 a dual- reduction in both the total volume and intensity of agricultural carbon emissions. Total emissions exhibited a fluctuating downward trend, decreasing by an average of 0.95% annually, while emission intensity declined steadily at an average rate of 5.77% per year. (2) Livestock farming is 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 ranks as the second-largest source, averaging 33.98% annually, with late rice being the dominant contributor. Carbon emissions from agricultural land use account for an average annual share of 24.82%, with chemical fertilizers being the largest contributor. (3) The level of agricultural economic development has a positive driving effect on agricultural carbon emissions. Conversely, agricultural production efficiency, agricultural industrial structure, and the scale of agricultural employment have negative inhibitory effects. The magnitude of these effects ranks as follows: agricultural economic development level > agricultural production efficiency > scale of agricultural employment > agricultural industrial structure. (4) The decoupling state between agricultural carbon emissions and agricultural economic growth in Guangxi was mainly characterized as weak decoupling. However, this decoupling lacks stability and is prone to fluctuations and reversals. Agricultural production efficiency demonstrates the strongest decoupling potential, while the agricultural industrial structure shows minimal decoupling effort and has a negligible impact on agricultural carbon reduction. Guangxi should further control carbon emissions from livestock and poultry 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 productivity tailored to enhance production efficiency and advance agricultural carbon reduction.