Book Description

Air quality has been an issue of growing importance to the transportation sector since the enactment of the Clean Air Act Amendments of 1990 and the Transportation Equity Act for the 21st Century in 1998. According to these acts, states and local governments are required to attain and maintain National Ambient Air Quality Standards. The MOBILE model is the mobile emission factor model used in estimating air pollutants generated by mobile sources. In order to obtain accurate emission estimates, MOBILE must be provided with sound input data that accurately reflect local conditions. Among many input factors, vehicle miles traveled (VMT) fractions - the percentage of VMT for each vehicle type by roadway functional class - play a critical role. In this study a new methodology for estimating locally specific VMT fractions as an input to the MOBILE model was developed. Based on this methodology, VMT fractions were computed for the six non-attainment areas in Virginia: Frederick County, Fredericksburg, Hampton Roads, Northern Virginia, Richmond, and Roanoke. These estimates were compared with fractions estimated using existing methodologies. The comparison revealed significant differences. These differences, coupled with the fact that the proposed methodology uses significantly more local data and requires fewer assumptions than existing methods, illustrate the need for the Virginia Department of Transportation (VDOT) to reconsider its approach to applying the MOBILE model. Based on the results of this research effort, it is recommended that VDOT's Environmental Division use the proposed VMT fraction estimation methodology to generate input to the MOBILE model for mobile source emission estimates. This methodology will benefit VDOT by estimating mobile source emissions that better reflect local conditions. The cost of implementing the recommendation is minimal. Estimation of VMT fractions is a current activity, and the new methodology requires equivalent or less effort to the existing approach. In addition, required data for the proposed methodology can be obtained at no additional cost.