Modeling of In-vehicle PM(2.5) Exposure Using the Stochastic Human Exposure and Dose Simulation Model.

Abstract

Factors that influence in-vehicle PM(2.5) exposure are indentified and assessed. The methodology used in the current version of Stochastic Exposure and Dose Simulation model for Particulate Matter (SHEDS-PM) for in-vehicle PM(2.5) concentration is reviewed, and alternative modeling approaches are identified and evaluated. SHEDS-PM uses a linear regression model to estimate in-vehicle PM(2.5) concentration based on ambient PM(2.5) concentration, such as from a fixed site monitor (FSM) or a grid cell average concentration estimate from an air quality model. The ratio of in-vehicle to FSM concentration varies substantially with respect to location, vehicle type and other factors. SHEDS-PM was used to estimate PM(2.5) exposure for 1% of people living in Wake County, NC in order to assess the importance of in-vehicle exposures. In-vehicle PM(2.5) exposure can be as much as half of the total exposure for some individuals, depending on employment status and the time spent in-vehicle during commuting. An alternative modeling approach is explored based on the use of a dispersion model to estimate near-road PM(2.5) concentration based on FSM data and a mass balance model for estimating in-vehicle concentration.Recommendations for updating the input data to the existing model, and implementation of the alternative modeling approach are made.