Co-evolution of PM_2.5 and O₃ pollution in China revealed by a tripartite migration-network-synergy framework

Addressing the synergistic air pollution of PM_2.5 and O₃ requires a comprehensive understanding of their co-evolution. This study developed an innovative tripartite framework integrating migration path tracking, network structure analysis, and synergistic effect assessment to decipher their spatiotemporal synergy in China from 2000 to 2023. Dynamic pollution centroids were used to extract migration paths, a BKA-GMM multidimensional clustering algorithm was employed to construct annual synergistic networks, and a novel Collaborative Prevention and Control Index (CPCI) system was created to quantify control demand. The framework revealed distinct dynamic patterns: PM_2.5 centroid migration was active at regional peripheries (total length >559 km) but stable in core areas (<26 km), with synergistic demand declining from 502.49 in 2007 to 79.69 in 2022; O₃ exhibited long-range transport in the west (>977 km) and stability in the east, with networks expanding persistently (NCPCI rising from 20.13 in 2013 to 272.67 in 2022); and compound pollution showed pronounced east-west differentiation and unstable synergistic demand (174.81 in 2016 and 4.99 in 2017). The analysis identified core hub cities (e.g., Suzhou, Wuxi), stable high-demand regions (North China Plain, Yangtze River Delta), and western discrete sources. This study provides a systemic methodology for analyzing compound air pollution. These findings reveal the differential driving mechanisms and imply distinct responses of PM_2.5 and O₃ to emission control measures, suggesting the need for differentiated management strategies. The identification of functionally distinct critical units provides a scientific basis for tiered regionally collaborative air quality management.