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RECORD NUMBER: 20 OF 84

OLS Field Name OLS Field Data
Main Title Development Work for Improved Heavy-Duty Vehicle Modeling Capability Data Mining, FHWA Datasets.
Author C. E. LINDHJEM ; S. Shepard
CORP Author ENVIRON International Corp., Novato, CA.; Environmental Protection Agency, Research Triangle Park, NC. Air Pollution Prevention and Control Div.
Year Published 2007
Report Number EPA/600/R-07/096
Stock Number PB2008-111683
Additional Subjects Data sources ; Exhaust emissions ; Air pollution ; Motor vehicles ; On road vehicles ; Data bases ; Regional aggregation ; Regional variations ; Temporal variations ; Quality assurance ; Quality control ; Modeling ; Recomendations ; Vehicle weight distributionw ; Heavy-duty vehicles ; Weight bin distributions ; Vehicle class fractions ; Federal Highway Administration (FHWA) ; Motor Vehicle Emissions Simulator (MOVES) model
Holdings
Library Call Number Additional Info Location Last
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Status
NTIS  PB2008-111683 Most EPA libraries have a fiche copy filed under the call number shown. Check with individual libraries about paper copy. NTIS 03/10/2010
Collation 138p
Abstract
Heavy-duty vehicles have been seen as contributing a large fraction of emissions from on-road vehicles and are coming under more intense scrutiny because light-duty emissions have been controlled to a greater extent than heavy-duty vehicle emissions. A heavy-duty vehicle can produce 10 to 100 times the emissions (of NO(sub x) and PM emissions especially) of a light-duty vehicle. Thus, heavy-duty vehicle activity needs to be better characterized. Key uncertainties with the use of MOBILE6 regarding heavy-duty vehicle emissions include the fraction of heavy-duty vehicles on all types of roadways at all times of day. In addition, there may be regional variability in both the fraction of different vehicle classes and the vehicle weights within each class. With the Motor Vehicle Emissions Simulator (MOVES) model, greater emphasis is given to physical parameters affecting the engine loads and therefore the emissions from individual vehicles. One primary factor affecting the engine load is the vehicle weight; the weight of the vehicle on the road is needed to estimate its in-use emissions. Because the effect of vehicle weight may be nonlinear for certain types of driving, it is important to incorporate the weight distribution of vehicles into emission estimates. Databases collected by the Federal Highway Administration (FHWA) include vehicle count and classification from the Highway Performance Monitoring System (HPMS) using automated traffic recorders (ATR) used to produce the Travel Volume Trends (TVT) reports. Other data sets compile the results of data collection from weigh in motion (WIM) sensors, and other data sources (visual observation, weigh stations, and other special projects) maintained by the FHWA and compiled in the Vehicle Travel Information System (VTRIS). A discussion of these data sources including original sources, representativeness, and quality and data reduction procedures used in this work are provided in Appendix A. This work consisted of an investigation and evaluation of these databases for the purpose of assisting in the development of improved emissions estimates of heavy-duty vehicles. The goal of the project was therefore to produce estimates of the fraction of heavy-duty vehicles of all vehicle traffic, and weight distributions for those vehicles according to the time of day, day of week, and other temporal variables, and an investigation of regional differences.