Abstract: Microscale pollutant dispersion models and field monitoring data from fixed stations at specific heights are often used to guide the development of emissions control strategies in the effort to attain National Ambient Air Quality Standards (NAAQS).  Plus, these models are typically used to evaluate the environmental and sustainable development impacts of new construction projects.  However, models currently in use often underestimate pollutant concentrations in micro-environments.  Because air quality standards are set to protect public health, attention must be given to real-world exposure levels.

A theoretical formulation of a stochastic model for prediction of pollutant dispersion in micro environments was previously introduced.1  The formulation of the new model can better predict the pollutant levels for urban roads located near high-rise buildings.  Model prediction results that vehicle pollutant concentrations can become significantly elevated under worst case scenarios (at lower wind speeds).  The model presented here can help road designers better estimate real-world emissions impacts.  This paper discusses the new model framework and presents preliminary model evaluation results.