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This study introduces the Enhanced Truck Dispersion Framework, an innovative approach to modeling emissions from idling and moving trucks in urban environments. The framework integrates the Behavior, Energy, Autonomy, and Mobility (BEAM) model for the regional transportation model; the Emission Factors (EMFAC) model and the Motor Vehicle Emission Simulator (MOVES) for emission calculations; and the Research LINE (RLINE) source model with a grid-based point-source model for dispersion analysis. Field data collected at a distribution center in Ontario, California, U.S., is used to calibrate and validate the model, particularly for idling trucks. The study simulates traffic patterns in Inland Southern California, focusing on moving vehicles and idling trucks and based on real-world data. Results reveal significant pollutant concentrations near major highways and warehouse districts, highlighting the impact of both moving and idling truck emissions on urban air quality. This comprehensive approach provides valuable insights for policymakers and urban planners in developing targeted strategies to mitigate the environmental and health impacts of truck emissions in urban areas. 

Urban air quality and the impact of mobile source pollutants on human health are of increasing concern in transportation studies. Existing research often focuses on reducing traffic congestion and carbon footprints, but there's a notable gap in understanding the health impacts of traffic from an environmentally-just perspective. Addressing this, our paper introduces an integrated simulation platform that models not only traffic-related air quality but also the direct health implications at a microscopic level. This platform integrates five modules: SUMO for traffic modeling, MOVES for emissions modeling, a 3D grid-based dispersion model, a Matlab-based visualizer for pollutant concentrations, and a human exposure model. We emphasize the transportation-health pathway, examining how different mobility strategies impact human health. Our case study on multimodal on-demand services demonstrates that a distributed pickup strategy can reduce cancer risk from PM 2 . 5 exposure by 33.4% compared to centralized pickup. This platform offers insights into traffic-related air quality and health impacts, providing valuable data for improving transportation systems and strategies with a focus on health outcomes.