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Arable land green and low-carbon utilization (ALGLU) is an important pathway to safeguard food safety and achieve the green transformation and progress of agriculture, playing a crucial role in promoting agricultural ecological protection and economic sustainability. This study takes the Yangtze River Delta region (YRD), where rapid urbanization is most typical, as the study area. On the basis of fully considering the carbon sink function of arable land, the study measures the green and low-carbon utilization level of arable land in the region using the Super-slack and based measure (Super-SBM) model, and analyzes its spatial and temporal evolution using the spatial autocorrelation model, the center of gravity, and the standard ellipsoid model, and then analyzes its impact with the help of the geographic detector and the geographically weighted regression model. We analyzed the multifactor interaction and spatial heterogeneity of the factors with the help of the geodetector and geographically weighted regression model. Results: (1) The ALGLU in the YRD has shown a fluctuating upward tendency, increasing from 0.7307 in 2012 to 0.8604 in 2022, with a growth rate of 17.75%. The phased changes correspond to national agricultural development policies and the stages of socio-economic development. (2) There are significant spatial differences in the level of ALGLU in the YRD, with high levels distributed in the southwest of Jiangsu, northern Zhejiang, and northwest Anhui, while low levels are distributed in the southwest of the YRD. Positive spatial autocorrelation exists in the level of ALGLU in the YRD. The spatial transfer trends of the gravity and standard deviation ellipses essentially align with changes in the spatial pattern. (3) The level of ALGLU in the YRD is affected by many factors, with the intensity of interaction effects far exceeding that of individual factors. When considering single-factor effects, precipitation, topography, and farmers' income levels are important factors influencing the level of ALGLU. In scenarios involving multiple-factor interactions, agricultural policies become the primary focus of interaction effects. Furthermore, the driving effects of influencing factors exhibit spatial heterogeneity, with significant differences in the direction and extent of driving effects of each factor in different cities. This study can provide valuable insights for future ALGLU in the YRD and regional sustainable development. [ABSTRACT FROM AUTHOR]