Vehicle loads have significant impacts on the emissions of heavy-duty trucks, even in the same traffic conditions. Few studies exist covering the differences in emissions of diesel semi-trailer towing trucks (DSTTTs) with different loads, although these vehicles have a wide load range. In this context, the operating modes and emission rates of DSTTTs were analyzed under varying loads scenarios to understand the effect of vehicle loads on emission factors. First, second-by-second field speed data and emission data of DSTTTs with different loads were collected. Then, the methods for calculating the scaled tractive power (STP) and the emissions model for DSTTTs were proposed to evaluate the effect of different loading scenarios. The STP distributions, emission rate distributions, and emission factor characteristics of different loaded trucks were analyzed and compared. The results indicated that the STP distributions of DSTTTs that under the unloaded state were more narrow than those under fully loaded or overloaded conditions. The emission rates of carbon dioxide (CO₂), carbon monoxide (CO) and total hydrocarbon (THC) for DSTTTs under a fully loaded state were significantly higher than those under an unloaded state. However, due to the influence of exhaust temperature, the emission rates of nitrogen oxides (NO_x) among fully loaded trucks were lower than those under the unloaded state when STP bin was above 4 kW/ton. The emission factors of CO₂, CO, THC, and NO_x for fully loaded trucks demonstrated the largest increases at low-speed intervals (0–30 km/h), which rose by 96.2%, 47.9%, 27.8%, and 65.2%, respectively.

With the rapid increase of automobile ownership, the city of Beijing, China, faces challenging issues with regard to traffic congestion and vehicle emissions. In seeking solutions to these issues, developing and improving public transportation systems is considered one of the most feasible and promising strategies because these systems have high passenger-carrying capacity and low pollution on a per passenger basis. Driving cycles reflect traffic conditions, and thus vehicle emissions, and form a scientific base to further improve bus operations. This paper is intended to develop city-specific driving cycles for transit buses for Beijing. The operational data of 126 buses were collected by using a portable global positioning system (GPS) for three types of bus routes: the bus rapid transit (BRT) line, express line, and regular line. Through analysis of the operating characteristics, a methodology for developing driving cycles is proposed based on the parameter of vehicle-specific power (VSP) distr...

The development of new fuel consumption and emission models creates the need to characterize traffic conditions by using vehicle-specific power (VSP) distribution. However, in existing transportation engineering, there has been a lack of knowledge of relationships between the VSP distribution and commonly used traffic parameters and a lack of models to develop the VSP distribution from traffic parameters. To examine how traffic conditions affect VSP distributions, this study uses large samples of floating car data collected from expressways in Beijing to associate VSP distributions with various average travel speeds. After a comprehensive analysis, regular patterns are found between the VSP distribution and the average travel speed. Specifically, when the average travel speed is more than 20 km/h, the VSP distribution comes close to a normal distribution. The mean of the VSP distribution is the VSP value when cruising at the average travel speed, and the standard deviation could be expressed as a power f...