Near-road Dispersion Modeling Of Mobile Source Air Toxics (msats) In Florida

There is a growing public concern that emissions of mobile source air toxics (MSATs) from motor vehicles may pose a threat to human health. At present, no state or federal agencies require dispersion modeling of these compounds, but many agencies are concerned about potential future requirements. Current air pollution professionals are familiar with Federal Highway Administration (FHWA) and U.S. Environmental Protection Agency (EPA) requirements for dispersion modeling to produce predicted concentrations for comparison with appropriate standards. This research examined a method in which the potential near-road concentrations of MSATs were calculated. It was believed that by assessing MSATs in much the same way that are used for other pollutants, the model and methods developed in this research could become a standard for those quantifying MSAT concentrations near-roadways. This dissertation reports on the results from short-term (1-hour) and long-term (annual average) MSATs dispersion modeling that has been conducted on seven intersections and seven freeway segments in the state of Florida. To accomplish the modeling, the CAL3QHC model was modified to handle individual MSAT emissions input data and to predict the concentrations of several MSATs around these roadway facilities. Additionally, since the CAL3MSAT model is DOS based and not user-friendly, time was invested to develop a Windows® graphical user interface (GUI). Real-world data (traffic volumes and site geometry) were gathered, worst-case meteorology was selected, mobile source emission factors (EFs) were obtained from MOVES2010a, and worst-case modeling was conducted. Based on a literature search, maximum acceptable concentrations (MACs) were proposed for comparison with the modeled results, for both a short-term (1-hour) averaging time and a long-term (1-year) averaging time. iv Results from this CAL3MSAT modeling study indicate that for all of the intersections and freeway segments, the worst-case 1-hour modeled concentrations of the MSATs were several orders of magnitude below the proposed short-term MACs. The worst-case 1-year modeled concentrations were of the same order of magnitude as the proposed long-term MACs. The 1-year concentrations were first developed by applying a persistence factor to the worst-case 1-hour concentrations. In the interest of comparing the predicted concentrations from the CAL3MSAT persistence factor approach to other dispersion models, two EPA regulatory models (CAL3QHCR and AERMOD) with the ability to account for yearly meteorology, traffic, and signal timing were used. Both hourly and annual MSAT concentrations were predicted at one large urban intersection and compared for the three different dispersion models. The shortterm 1-hour results from CAL3MSAT were higher than those predicted by the two other models due to the worst-case assumptions. Similarly, results indicate that the CAL3MSAT persistence factor approach predicted a worst-case annual average concentration on the same order of magnitude as the two other more refined models. This indicated that the CAL3MSAT model might be useful as a worst-case screening approach