Emission exposure optimum for a single-destination dynamic traffic network

Abstract In this paper, an integrated dynamic framework is applied to model human exposure to vehicular emissions. The framework contains three components: a time-dependent macroscopic emission model, a dynamic traffic flow model, and a line source Gaussian plume model to capture the spatial dispersion of emissions. A human exposure-based dynamic system-optimal problem is then formulated to minimize system-wide emission exposure. An illustrative network and the Sioux Falls network are used to test the proposed framework and to examine how traffic dynamics, population characteristics, and meteorological conditions affect emission exposure at various network locations. The results provide evidence that regional emission exposure can be reduced by dynamically managing network traffic. At least under the specific network setup, the paper provides a counterexample to the common conception that traffic congestion and emissions (exposure) can be minimized simultaneously, which implies that traffic system operators must properly leverage the tradeoff between congestion and emissions.