Spatial association characteristics and evolutionary mechanisms of water pollution in China: A network structure dependence perspective

• China’s grey water footprint (GWF) exhibited significant spatial disparities and an overall decline. • The GWF spatial network has demonstrated progressive growth in internal connectivity and complexity. • The siphon effect within the GWF spatial network has weakened. • The temporal exponential random graph model is used to reveal the evolutionary mechanisms of the GWF spatial network. • Targeted policy recommendations are proposed to guide cross-regional collaborative water pollution control. Effective water pollution management requires coordinated efforts across the economy and society. A precise understanding of the spatial association characteristics and mechanisms of the grey water footprint (GWF) is critical to promoting cross-regional pollution control cooperation and achieving sustainable regional development. Based on calculated GWF data for 31 provinces, municipalities, and autonomous regions across China from 2006 to 2021, this study integrates a modified gravity model with social network analysis to examine the structural characteristics of the GWF spatial association network. Furthermore, the temporal exponential random graph model is employed to investigate the evolutionary mechanisms of the network. The findings reveal: (1) China’s overall GWF has declined, but significant spatial disparities persisted, characterized by a “northwest-southeast low and northeast-southwest high” pattern. (2) As regional cooperation strengthens, the interprovincial flow of resource elements has become more frequent, accompanied by an expansion in the scope and intensity of GWF spatial linkages. This has led to the emergence of a more complex and multilayered GWF spatial association network. The “siphon effect” observed within the network, predominantly associated with developed regions such as Shanghai, Beijing, Tianjin, Zhejiang, and Jiangsu, has gradually weakened. (3) The evolution of the network is driven by a combination of structure dependence, node attribute, exogenous environmental embeddedness, and time dependence. Interregional reciprocal relationships and transitive triadic closures are the main organizational structures facilitating the orderly flow of GWF. Under conditions of homophily in environmental regulation, heterophily in technological innovation, water use structure, population density, industrial structure, and digital infrastructure level, as well as geographic proximity, the long-term stable development of GWF spatial associations and the deepening of positive spatial interactions of resource elements through mechanisms such as market regulation are essential to advancing cross-regional collaborative water pollution governance.