Assessing and mitigating carbon emission exposure in dynamic multimodal transport networks

On-road carbon emissions from heterogeneous traffic flows in multimodal urban transportation systems pose a significant risk to public health. Developing effective instruments to mitigate these emissions requires accurate modelling and assessment of their impact on the environment. To this end, this study establishes a holistic framework that integrates two interrelated components: 1) a multimodal dynamic traffic assignment model for obtaining equilibrated flow distributions, and 2) a Gaussian plume model, underpinned by a multi-category vehicle carbon emission model, to assess the spatiotemporal distribution of exposure. Numerical experiments demonstrate the model convergence and evaluate its performance under multiple scenarios. Results show that incorporating the proposed carbon emission cost and exposure cost into dynamic traffic assignment can simultaneously reduce carbon emissions and exposure risks, underscoring the necessity of jointly considering both factors in path choice modeling to achieve sustainable urban mobility and the broader development of low-carbon, healthy cities.