Understanding and managing the dynamic evolution of traffic emissions in urban road systems

Existing literature has extensively explored the day-to-day evolution of traffic flows. However, traffic-flow dynamics and emission dynamics are not equivalent, and research on the day-to-day dynamic evolution of traffic greenhouse gas (GHG) emissions remains insufficient due to their complex nonlinear relationship. This study investigates the evolutionary characteristics and reduction strategies of GHG emissions from urban road traffic. We propose a threedimensional nonlinear dynamic model that depicts the relationship among energy reserve, vehicle population, and road network area. Subsequently, the existence, uniqueness, and stability of the equilibrium solution for the urban road traffic network are investigated. Finally, from the perspective of macroscopic travel demand restrictions, the optimal authorized vehicle proportion (namely, the vehicles with the right to use the urban road traffic network) that minimizes traffic GHG emissions under several typical scenarios is proposed. Some key findings are obtained: (1) When the urban road traffic reaches a stable state, the three-dimensional nonlinear dynamic system achieves equilibrium, along with stable road network saturation, average vehicle speed, and traffic GHG emissions. (2) Taking a representative first-tier city in China as an example, it is found that adopting the optimal proportion of authorized vehicles significantly reduces GHG emissions from urban road traffic.