Heavy-duty trucks (HDTs) are major contributors to urban traffic pollution. In China, HDTs emit 16.8% of carbon monoxide (CO), 6.9% of total hydrocarbon (THC), 57.8% of nitrogen oxides (NO_x), and 66.3% of particulate matter (PM) of the total motor vehicle emissions, despite only constituting 3.1% of the vehicle population [1]. Hence, to control urban traffic emissions, it is crucial to accurately assess and strictly monitor the emissions of heavy-duty diesel trucks (HDDTs). However, HDDTs have a wide load range—for example, diesel semi-trailer towing trucks (DSTTTs) have a load difference of 34 tons between unloaded and fully loaded conditions—and the variety in load states can significantly impact the accuracy of emissions estimates [2,3,4]. Few existing emission models are available to calculate the emissions of DSTTTs while considering different load states and, as a result, emissions are often misestimated, which may mislead or complicate emission control policies. HDDTs contribute the most NO_x in urban environments and it is predicted that their population and vehicle kilometers traveled will continue to rise, leading to ever-increasing emissions [5,6]. Thus, the accurate estimation of HDDTs emissions is crucial for the proper design of management and control schemes for HDDTs. This study sought to analyze the effect of load on emission assessments and attempted to widen the applicability of the HDDTs emission model.

HDDTs emissions measurements are typically performed using engine dynamometers, tunnel studies, remote sensing, and portable emissions monitoring systems (PEMS) [7,8,9]. The engine dynamometer test cycle is based on a specific driving cycle in the laboratory, and it is typically considered that such cycles do not represent the full range of real-world vehicle operating modes [10]. Meanwhile, tunnel testing is performed by installing devices within the tunnel to test the average emissions of all passing vehicles. In this regard, they may not be representative of emissions under all field operating conditions, and make it difficult to distinguish vehicle types [11]. Remote sensing measurements can offer a snapshot of active vehicle emission concentrations at a specific location and, therefore, might not represent an entire operating cycle [12]. As compared with the above emissions measurement methods, PEMS are able to obtain emissions data from vehicles operating in real-time on the field road network, taking into account the impact of changing traffic conditions.

Some researchers have studied emission characteristics based on PEMS to assess vehicle emissions better [13,14]. Still, as different vehicle loads have a critical role to play on the emissions of HDDTs [15,16], it is vital to explore the operating modes and emission characteristics of these trucks under varying loads. Yao et al. [17] tested the emissions of on-road HDDTs (with a gross vehicle weight of 16.0 tons) under 0%, 50%, and 100% loads using PEMS. The results showed that emission factors of NO_x and PM for the trucks when half-loaded were 43% and 59% higher than those obtained when the trucks were unloaded, and 62% and 44% higher when fully loaded. Elsewhere, Frey et al. [3] collected emissions data for diesel-fueled tandem trucks (with a gross vehicle weight of 29.0 tons) under different loads using PEMS and studied the emission variations between unloaded and fully loaded trucks. Their results indicated that the difference for loaded trucks versus unloaded trucks is 44% for CO₂, 78% for NO_x, 23% for PM, 30% for HC and 22% for CO. Song et al. [18] obtained the emissions data of two HDDTs (with a gross vehicle weight of 25.0 tons) with different loads (empty, half, and full loads). This study found that the NO_x, CO, and THC emission factors of the tested vehicles when half loaded and fully loaded were 18% to 41%, 6% to 67%, and 37% to 125% higher than those obtained when the trucks were not loaded, respectively. During the field testing, it is challenging to maintain the same transport scenario for vehicles for different loads based on the PEMS test alone. Therefore, it is impossible to perform a comparable and consistent analysis for HDDTs emissions at various load states.

The vehicle specific power (VSP) distributions could be used to further characterize traffic conditions and vehicle emissions. The VSP or STP was designed to reflect the engine power required for the vehicle to overcome aerodynamic, rolling resistance, and rotational forces, so as to move the vehicle forward on the actual road [19]. Song et al. [20] characterized the VSP distribution of light-duty vehicles on urban restricted-access roadways and established a relationship between the VSP distribution and the average operating speed. Lai et al. [21] constructed a city-specific driving cycle based on the STP distribution for transit buses and then estimated vehicle emissions. Li et al. [22] established VSP binning division using field data for urban transit buses to better reflect these vehicles’ operating characteristics. Zhang et al. [4] proposed a method for calculating the VSP values and developed an emissions model for heavy-duty refuse trucks (with a gross vehicle weight of 15.5 tons) to analyze the impact of empty and full loads on emissions.

It is only one-sided to consider the effect of changes in VSP distribution on the emissions of various loaded DSTTTs [23]. For DSTTTs equipped with a selective catalytic reduction (SCR) system, the exhaust temperature seriously affects the NO_x emission rate [24]. The activity level the catalyst rises and then falls with activity level changes in exhaust temperature, resulting in the variations in the NO_x conversion efficiency [25,26]. The heavier vehicle load causes the NOx concentration at the inlet of the SCR device to increase, and at the same time, it also leads the exhaust temperature to rise. Under the simultaneous effects of these two factors, the ultimate NO_x emission rate changes caused by various load conditions needs to be further analyzed.

Existing studies suggest that vehicle loads have a significant effect on the emissions of HDDTs. Most studies on HDDTs can be mainly divided into two categories, one is to analyze the emission characteristics directly based on the emission data, the other is to study the difference of VSP distribution based on the vehicle operation data. The studies based on emission data mainly uses the data collected by the engine dynamometer or PEMS. The former can hardly reflect the effect of truckloads on emissions in the real-world, and the latter approach does not ensure the accurate analysis of emissions for different load levels for the same traffic conditions. Meanwhile, a few VSP-based studies on HDDT emissions mainly concentrate on the influence of VSP distributions on emissions for different loaded trucks. It does not take into account the fluctuation of exhaust temperature, which affects the differences in emission rates corresponding to the VSP distributions. Besides, few studies have assessed the emission differences of DSTTTs with a wide load range.

In this context, the method for calculating the scaled tractive power (STP) and the emissions model for DSTTTs was developed based on second-by-second field speed data collected using on-board diagnostics (OBD) devices and emission data obtained by using PEMS instruments. Then, the operating modes and emission rates for DSTTTs were analyzed under various loads further to understand the effect of truck loads on emission factors. Finally, emission factor differences of CO₂, CO, THC, and NO_x under different load conditions were compared.