Revealing Emission Patterns of Urban Traffic Flows: A Complex Network Theory Perspective

Traffic emissions resulting from vehicle travel across origin–destination (OD) pairs pose significant challenges to sustainable urban development, necessitating a systematic understanding of emission patterns to inform effective mitigation policies. Existing studies often focus on the locations where emissions occur, overlooking emission flows between OD pairs, which could lead to incomplete policy formulation. This study proposes a new emission pattern analysis framework. Specifically, we construct the Urban Traffic Emission Flow Network (UTEFN) based on comprehensive individual vehicle data, and then systematically analyze its spatiotemporal characteristics and network structure by using complex network theory. Our findings show that the node weighted degree captures emissions attributable to specific nodes, revealing that critical emission sources may be overlooked in traditional analyses. Edge weights identify high-emission OD edges and associated travel behaviors. Furthermore, the emission distributions for different vehicle types and gases exhibit heavy-tailed scaling laws, indicating that emission reduction policies targeting a few key nodes or edges could impact a notable proportion of traffic emissions. In structural analysis, community detection revealed distinct clusters of emission flows, with the formation of high-emission communities associated with specific spatial configurations and travel behaviors. The findings provide valuable insights into strategic planning for clean traffic systems and urban emission reduction.