Abstract: Investigating the influence of spatial factors on urban net carbon sinks is crucial for optimizing urban spatial patterns and achieving carbon neutrality to. By using the Exploratory Spatial Data Analysis (ESDA) method and Theil indices, this study examined the spatial distribution characteristics of net carbon sinks across 296 prefecture-level cities in China in 2022. The Geographically Weighted Regression (GWR) model was employed to identify the socioeconomic and spatial factors affecting urban net carbon sinks. The key findings were as follows: Significant spatial heterogeneity existed in urban net carbon sinks, exhibiting a general pattern of "higher in the west and lower in the east". Strong spatial autocorrelation was observed, with high-high clusters concentrated in western regions and low-low clusters primarily located in the Beijing-Tianjin-Hebei metropolitan area, as well as in Shanxi and Henan provinces. Regional disparities were prominent, with substantial intraregional imbalances in the spatial distribution of urban net carbon sinks. The eastern region showed the greatest variation, accounting for 42.3% of the total disparity. Spatially varying effects were evident in how socioeconomic and spatial structural factors influence net carbon sinks, indicating significant spatial non-stationarity. The overall inhibitory effect of GDP and population size was formed, while technological progress had a promoting effect on net carbon sinks, which was more significant in the southeastern coastal areas. The expansion of built-up areas and discrete development suppressed net carbon sink, while the complexity of shapes promoted net carbon sink formation, which was more significant in the eastern region. In terms of ecological spatial factors, high-quality patch expansion, stable and continuous landscape boundaries, and moderate landscape fragmentation collectively formed the core mechanisms for enhancing net carbon sinks.