Accurate Truck Activity Estimate for Roadway Link PM_(2.5) Emissions

摘要

Since diesel truck traffic is a major transportation on-road source of particulate matter (PM_(2.5)), roadway link-based modeling of the truck emissions greatly rely on accurate estimate of truck fractions of traffic volumes as partial input to the MOVES model. However, present aggregated traffic volume and unreliable truck activity data provided from today's practice are obviously a concern in estimating the truck-traffic-source emission. The daily truck traffic activity is usually not estimated accurately and cannot be disaggregated to hourly activity using the traditional methods. To address this problem, two innovative econometric methods have been successfully enhanced in this study to enable accurate truck activity based inputs for the emission estimation. The truck factor spatial panel model (TFSP) and multinomial probit hourly VMT (MNP-HVMT) models have been improved and tested using the Greater Cincinnati area's regional traffic data. The application of those models indicates that using MOVES default input data underestimates the regional PM_(2.5) inventory. The proposed methodology also enables plotting the spatiotemporal distribution of PM_(2.5) emissions in a subarea. Such an integrated method provides a very useful decision support tool for practitioners since they can also model PM_(2.5) emissions at a detailed level as required by project-level conformity analysis. The presented methodology is scalable and transferable and holds technical promise in its application for different regions and for different pollutants.