Improving estimates of transportation emissions: Modeling hourly truck traffic using period-based car volume data

• Published in: Transportation research. Part D, Transport and environment Transport and environment, 2014-01, Vol.26, p.32-41
• Main Authors: Liu, Y.L., Ge, Y.E., Gao, H. Oliver
• Format: Article
• Language: English
• Subjects: Applied sciences; Atmospheric pollution; Exact sciences and technology; Ground, air and sea transportation, marine construction; Pollution; Pollution sources. Measurement results; Road transportation and traffic; Transportation emissions inventory; Transports; Truck arrivals; Truck fraction; Weigh-in-motion
• ISSN: 1361-9209; 1879-2340
• DOI: 10.1016/j.trd.2013.10.007

•Vehicle classification data from weigh-in-motion stations in California are used to examine method across days and areas.•Mixed vehicle-miles traveled provide poor inventory estimates.•Heavy-duty trucks generate orders of magnitudes higher emission rates than light duty vehicles.•The models identified provide satisfactory and statistically robust estimates of truck traffic. We estimate hourly truck traffic using period-based car volumes that are usually available from travel demand models. Due to the lack of local or regional data, default vehicle-miles traveled mix by vehicle class in mobile emission inventory models is usually used in transportation emissions inventory estimates. Results from such practice, however, are often far from accurate. Heavy-duty trucks generate orders of magnitudes higher emission rates than light duty vehicles. Vehicle classification data collected from weigh-in-motion stations in California are used to examine the performance of various forms of the method across days of week and geographic areas. We find that the models identified provide satisfactory and statistically robust estimates of truck traffic.