There is plenty of evidence to suggest that global carbon emission transfer has evolved into a mutually related system, where a realistic and complex network is formed. To profile the structures and features in the global carbon emission transfer network, a carbon-connectedness network model is adapted and combined with the multiregional input–output analysis framework, on the basis of massive and multi-layer global carbon flow data. This study formulates the topological features, spatio-temporal features, dynamic features and core–periphery features from a brand-new perspective on China. Meanwhile, this study identifies the network effects in the global carbon transfer network, including spillover, spillin and spillback effects. In general, an increase in China’s carbon emission transfer would lead to significant spillover effects on most economies worldwide, especially on developing economies and those with weaker tertiary industry or situated at the upstream of the global value chain. Simultaneously, China itself would also face substantial spillback effects. Spillovers and spillbacks underscore a broader negative impact that exceeds its initial magnitude. Focused on the connectedness network centered on China, this study is complementary to traditional insights, helping to comprehend the connections and relationships of carbon emissions among economies. This understanding is of substantive significance for the formulation of multi-national mitigation strategies and fostering global climate governance cooperation.