Proposed Road Pollution Alert System Based on Lagrangian Wall Model

Abstract

Despite significant improvements in fuel and engine technology, road traffic remains a major source of air pollutants, such as oxides of nitrogen, CO, particulate matter, and volatile organic compounds. Many recent studies have demonstrated associations between traffic-related air pollution and the adverse effects of exposure to traffic-related air pollution in a wide variety of situations. This paper describes the components of a proposed road pollution modeling-and-alert system that can be deployed by local authorities on sections of roads that are under the continuous risk of exceeding thresholds of acceptable air quality. The system features the use of real-time traffic data from intelligent transportation systems and related sources; a power-based model for the calculation of emissions that takes into account the driving mode of the vehicle as well as characteristics of the road segment; a Lagrangian wall model (LWM) to simulate the dispersion of pollutants from different sources; and an alert-and-response system that will need further input from government authorities, industry, and the community. The ability to combine emissions estimates from a power-based motor vehicle emissions model with the LWM dispersion and chemical transformation capabilities significantly enhances the capacity to minimize population exposure and reduce health impacts of pollution from particular roads of interest. This paper discusses development of the LWM and summarizes outcomes of a verification study performed with the California Department of Transportation Highway 99 tracer dispersion data set. It also presents results of a case study performed to demonstrate capabilities of the LWM.