关键词: 农业碳排放, LMDI分解法, Tapio脱钩模型, C-D生产函数

Abstract: The reduction of agricultural emission plays an important role in realizing the dual-carbon goals. It is thus of great significance to examine the characteristics and drivers of regional agricultural carbon emission. We measured agricultural carbon emission in Jiangxi Province from the perspective of input-output and production processes, and explored the drivers and decoupling dynamics of agricultural carbon emission by using the LMDI decomposition method together with the Tapio decoupling model modified by time-varying parameter C-D production function. The results showed that agricultural carbon emission in Jiangxi increased by 26.4% from 2010 to 2021, and the carbon emission intensity decreased year by year with an average annual rate of 4.9%. Factors such as agricultural carbon intensity, labor input, and capital stock collectively reduced carbon emission by a total of 61.05 Mt, with a contribution of 27.0%, 44.5% and 28.5%, respectively. Level of agricultural economic development, agricultural structure, and technological progress had strong driving effects, which accounted for 75.7%, 5.6% and 18.8%, respectively. Agricultural carbon emission in Jiangxi was weakly decoupled from economic development, capital stock, and technological progress factors, but was negatively decoupled from labor input. Moreover, the decoupling state was more desirable in the later period than in the earlier period. Our results suggested that the application of the time-varying parameter C-D production function is innovative and applicable by incorporating technology, labor, and capital factors in the examination of carbon emission drivers and decoupling effects.

Key words: agricultural carbon emission, LMDI decomposition method, Tapio decoupling model, Cobb-Douglas production function