A New Heavy-duty Vehicle Visual Classification and Activity Estimation Method for Regional Mobile Source Emissions Modeling


Book Description

For Heavy-duty vehicles (HDVs), the distribution of vehicle miles traveled (VMT) by vehicle type is the most significant parameters for onroad mobile source emissions modeling used in the development of air quality management and regional transportation plans. There are two approaches for the development of the HDV VMT distribution; one approach uses HDV registration data and annual mileage accumulation rates, and another uses HDV VMT counts/observations collected with the FHWA truck classification. For the purpose of emissions modeling, the FHWA truck classes are converted to those used by the MOBILE6.2 emissions rate model by using either the EPA guidance or the National Research Council conversion factors. However, both these approaches have uncertainties in the development of onroad HDV VMT distributions that can lead to large unknowns in the modeled HDV emissions. This dissertation reports a new heavy-duty vehicle visual classification and activity estimation method that minimizes uncertainties in current HDV conversion methods and the vehicle registration based HDV VMT estimation guidance. The HDV visual classification scheme called the X-scheme, which classifies HDV/truck classes by vehicle physical characteristics (the number of axles, gross vehicle weight ratings, tractor-trailer configurations, etc.) converts FHWA truck classes into EPA HDV classes without losing the original resolution of HDV/truck activity and emission characteristics. The new HDV activity estimation method using publicly available HDV activity databases minimizes uncertainties in the vehicle registration based VMT estimation method suggested by EPA. The analysis of emissions impact with the new method indicates that emissions with the EPA HDV VMT estimation guidance are underestimated by 22.9% and 25.0% for oxides of nitrogen and fine particulate matter respectively within the 20-county Atlanta metropolitan area. Because the new heavy-duty vehicle visual classification and activity estimation method has the ability to provide accurate HDV activity and emissions estimates, this method has the potential to significantly influence policymaking processes in regional air quality management and transportation planning. In addition, the ability to estimate link-specific emissions benefits Federal and local agencies in the development of project (microscale), regional (mesoscale), and national (macroscale) level air quality management and transportation plans.













Study of the Driving Cycle for Heavy Duty Trucks in Hilly Terrain and Its Effect on Calculated Emissions, and Comparison of Two Mobile Emission Models


Book Description

Vehicle emissions were estimated using MOVES2010a and MOBILE6.2 for a Pittsburgh case study involving a modal shift in freight transportion. MOVES2010a (hereafter referred to as MOVES) is currently the USEPA official mobile source emissions computer model; it replaced the older model, MOBILE6.2. Changing the method of hauling freight from highway to waterway is the transport modal shift. Results from this part of the study showed that emission estimates for all vehicle types using MOVES were higher than emissions estimated using MOBILE6.2/NMIM for CO, NO[subscript X], PM10, PM2.5, and VOC, but emissions were lower for CO2 and NH3 using MOVES relative to MOBILE6.2. For heavy-heavy duty diesel (HHDD) vehicles, higher emissions were estimated using MOVES for all pollutants except for NH3 when compared to MOBILE6.2. The largest difference between the two models was seen in PM10 and PM2.5. The second part of this dissertation focused on driving cycles for HHDD vehicles in hilly terrain and its effect on emissions. The MOVES model incorporates 12 default driving schedules for HHDD vehicles. Each driving schedule represents different average vehicle speeds, which tend to over generalize the driving patterns for these vehicles in hilly terrain. The characteristics of HHDD vehicle driving cycles were analyzed by using actual GPS speed and terrain data from driving activity that occurred on a section of the Federal Interstate to demonstrate possible drawbacks of default driving schedules in the current version of MOVES. Profiles of speed versus time as well as road grades were constructed to validate this. Emissions were calculated using a MOVES' operating mode approach. Results showed that a wider range of speeds and higher scaled tractive power occurred in the driving cycles constructed from the real activity data in hilly terrain than the MOVES default driving schedules. NO[subscript X], PM2.5, and THC emissions and total energy consumption calculated using the synthetic driving cycles of the trucks with grades, associated with the hilly terrain, were 7.6%, 14%, 3%, and 11%, respectively, higher than when using the MOVES default driving schedules at the same average speed (63.9 mph) for 0.3% average road grade. On the other hand, CO emissions were 3.4% lower for the synthetic driving cycles. More analyses associated with the driving cycles were presented in this dissertation, and recommendations were made regarding an improvement of default driving schedules in MOVES as well.




A Methodology to Estimate Vehicle Miles Traveled (VMT) Fractions as an Input to the Mobile Emission Model


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.










The Greenhouse Gas Protocol


Book Description

The GHG Protocol Corporate Accounting and Reporting Standard helps companies and other organizations to identify, calculate, and report GHG emissions. It is designed to set the standard for accurate, complete, consistent, relevant and transparent accounting and reporting of GHG emissions.