Estimation of Traffic Emissions in a Polycentric Urban City Based on a Macroscopic Approach

This paper presents a macroscopic dynamic modeling framework for road traffic emissions in an urban city that has numerous central business districts (CBDs). The framework combines a two-dimensional (2D) continuum dynamic traffic assignment (DTA) model that captures macroscopic features of traffic flow and an instantaneous emission model associated with instantaneous speed and acceleration of traffic flow. A heterogeneous traveling population continuously distributed in space is classified according to the trip destinations chosen by travelers. Each copy of flow tends to select an optimal route with the minimum cost to destination by means of instantaneous traffic information. For each copy of flow, an unstructured finite volume method as well as a fast sweeping method is designed to solve the continuum DTA model. In order to validate the feasibility of the model and algorithm, a case study is taken as an example to study some macroscopic characteristics of traffic flow and predict traffic-related pollutants like NOx, VOC, CO2 and PM in urban areas