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Measurements of airborne particle number size distributions, particle number and PM2.5 concentrations were conducted at two bus stations of different designs: open station and canyon station, operated according to the same timetables and fleet compositions, as well as at a reference point in Brisbane, Australia. Simultaneous traffic and meteorological parameters were also monitored, aiming to quantify particle characteristics and investigate the impact of station design and meteorological conditions on particle emissions at the two bus stations. It was found that there was no significant difference in average particle number concentrations in the size range 7-3000 nm (PN7-3000) between the two stations (fine days: p = 0.90 and rainy days: p = 0.80), and that PN50-120 contributed to the largest proportion of particle number concentrations. PN20-30 were observed to increase at the open station during all time periods, except 0:00-7:00, which is likely to be attributed to the lower average daily temperature at the open station (around 7 °C lower than at the canyon station). During precipitation, it was found that particle number concentration in the size range 25-250 nm decreased greatly, and the average daily reduction in PM2.5 concentration on rainy days compared to fine days was 44.2% and 22.6% at the open and canyon station, respectively. The effect of ambient wind speeds on particle number concentration was also examined, and no relationship was found between particle number concentration and wind speed for the entire measurement period. In addition, 33 pairs of average half-hourly PN7-3000 concentrations were calculated and identified at the two stations, during the same time of a day, and with the same ambient wind speeds and precipitation conditions. The results of a paired t-test showed that the average half-hourly PN7-3000 concentrations at the two stations were not significantly different at the 5% confidence level (t = 0.06, p = 0.96), which indicates that the different station designs were not a crucial factor for influencing PN7-3000 concentrations. This finding implies that the timescale of dispersion at the bus stations was comparatively long, and that the source contribution was more important compared to the atmospheric dispersions associated with different station designs.

A composite line source emission (CLSE) model was developed to specifically quantify exposure levels and describe the spatial variability of vehicle emissions in traffic interrupted microenvironments. This model took into account the complexity of vehicle movements in the queue, as well as different emission rates relevant to various driving conditions (cruise, decelerate, idle and accelerate), and it utilised multi-representative segments to capture the accurate emission distribution for real vehicle flow. Hence, this model was able to quickly quantify the time spent in each segment within the considered zone, as well as the composition and position of the requisite segments based on the vehicle fleet information, which not only helped to quantify the enhanced emissions at critical locations, but it also helped to define the emission source distribution of the disrupted steady flow for further dispersion modelling. The model then was applied to estimate particle number emissions at a bi-directional bus station used by diesel and compressed natural gas fuelled buses. It was found that the acceleration distance was of critical importance when estimating particle number emission, since the highest emissions occurred in sections where most of the buses were accelerating and no significant increases were observed at locations where they idled. It was also shown that emissions at the front end of the platform were 43 times greater than at the rear of the platform. Although the CLSE model is intended to be applied in traffic management and transport analysis systems for the evaluation of exposure, as well as the simulation of vehicle emissions in traffic interrupted microenvironments, the bus station model can also be used for the input of initial source definitions in future dispersion models.