关键词: 长江经济带, 耕地碳排放, 时空格局, 空间自相关, LMDI模型

Abstract: To clarify the green utilization of arable land, the IPCC carbon emission coefficient method was used to calculate the carbon emissions of arable land in 129 prefecture-level cities of the Yangtze River Economic Belt from 2000 to 2020. Spatial autocorrelation analysis was used to reveal the spatiotemporal evolution of arable land carbon emissions, and the LMDI model was used to decompose the contributions of various influencing factors. The results showed that from 2000 to 2020, the carbon emissions from arable land in the Yangtze River Economic Belt showed a downward trend over time, showing four stages, such as “maintaining stability—rapid growth—slow growth—slow decline”. In terms of space, there was a trend of high in the middle and east and low in the west, with significant global spatial autocorrelation. Local high-high clustering areas were distributed in the middle and lower reaches of the Yangtze River, low-high clustering areas were distributed in the middle reaches, and low-low clustering areas were mainly distributed in the upstream area. The promoting factor for agricultural carbon emissions within the region was the level of agricultural economy, while the inhibiting factor was mainly agricultural production efficiency, followed by agricultural production structure, and finally the scale of agricultural labor force. Therefore, there was a significant spatiotemporal difference in carbon emissions from arable land in the Yangtze River Economic Belt. Each region should develop carbon reduction strategies and land use control plans according to local conditions, improve agricultural production efficiency, optimize agricultural planting structure, strengthen regional linkage, and promote the coordinated development of low-carbon agriculture.

Key words: Yangtze River Economic Belt, carbon emissions from arable land, spatial-temporal pattern, spatial autocorrelation, LMDI model