In recent years, vehicle emissions have become one of the important pollutant sources of the urban atmosphere. Scholars and decision-makers are constantly expected to accurately grasp the dispersion of vehicle pollutants to formulate a series of policies and strategies which can facilitate a friendly and sustainable urban environment, such as controlling the total number of vehicles, requiring higher emission standards, promoting new energy vehicles, improving public transit service, and optimizing non-motorized transportation systems. This paper provides a review of the mechanism research methods and mathematical modeling approaches for urban vehicle pollutant dispersion. The mechanism research methods reviewed include field measurements, wind tunnel experiments, and numerical simulations. The modeling approaches involve two kinds of popular models: Box models (STREET, CPBM, AURORA, PBM) and Gaussian models (CALINE, HIWAY, OSPM, CALPUFF, R-LINE, ADMS series, EPISODE, CityChem, SIRANE, MUNICH). Moreover, this paper clarifies the basic assumption, fundamental principle, related research, applicable conditions, and limitations of these mechanism research methods and modeling approaches.

Urban transit systems are crucial for modern cities, providing sustainable and efficient transportation solutions for residents’ daily commutes. Extensive research has been conducted on optimizing the design of transit systems. Among these studies, designing transit line trajectories and setting operating frequencies are critical components at the strategic planning level, and they are typically implemented in an urban integrated transportation network. However, its computational complexity grows exponentially with the expansion of urban integrated transportation networks, resulting in challenges to global optimization in large-scale cities. To address this problem, this study investigates the layout planning of a basic public transit network (BPTN) to simplify the urban integrated transportation network by filtering out road segments and intersections that are unattractive for both users and operators. A non-linear integer programming model is proposed to maximize the utility of the BPTN, which is defined as a weighted sum of expected travel times (from a user perspective) and transportation efficiency (from an operator perspective). An expected transit flow distribution (ETFD) analysis method is developed, combining different assignment approaches to evaluate the expected travel time and transportation efficiency of the BPTN under various types of transit systems. Moreover, we propose an objective–subjective integrated weighting approach to determine reasonable weight coefficients for travel time and transportation efficiency. The problem is solved by a heuristic solution framework with a topological graph simplification (TGS) process that further simplifies the BPTN into a small-scale graph. Numerical experiments demonstrate the efficacy of the proposed model and algorithm in achieving desirable BPTN layouts for different types of transit systems under variable demand structures. The scale of the BPTN is significantly reduced while maintaining a well-balanced trade-off between expected travel time and transportation efficiency.