Large eddy simulation of vehicle emissions dispersion: Implications for on-road remote sensing measurements
Computational fluid dynamics, Exhaust plume dispersion, Near-wake region, On-road emission test
© 2020 Elsevier Ltd On-road remote sensing technology measures the concentration ratios of pollutants over CO2 in the exhaust plume in half a second when a vehicle passes by a measurement site, providing a rapid, non-intrusive and economic tool for vehicle emissions monitoring and control. A key assumption in such measurement is that the emission ratios are constant for a given plume. However, there is a lack of study on this assumption, whose validity could be affected by a number of factors, especially the engine operating conditions and turbulence. To guide the development of the next-generation remote sensing system, this study is conducted to investigate the effects of various factors on the emissions dispersion process in the vehicle near-wake region and their effects on remote sensing measurement. The emissions dispersion process is modelled using Large Eddy Simulation (LES). The studied factors include the height of the remote sensing beam, vehicle speed, acceleration and side wind. The results show that the measurable CO2 and NO exhaust plumes are relatively short at 30 km/h cruising speed, indicating that a large percentage of remote sensing readings within the measurement duration (0.5 s) are below the sensor detection limit which would distort the derived emission ratio. In addition, the valid measurement region of NO/CO2 emission ratio is even shorter than the measurable plume and is at the tailpipe height. The effect of vehicle speed (30–90 km/h) on the measurable plume length is insignificant. Under deceleration condition, the length of the valid NO/CO2 measurement region is shorter than under cruising and acceleration conditions. Side winds from the far-tailpipe direction have a significant effect on remote sensing measurements. The implications of these findings are discussed and possible solutions to improve the accuracy of remote sensing measurement are proposed.
Huang, Y.,Ng, E.,Surawski, N.,Yam, Y.,Mok, W.,Liu, C.,Zhou, J.,Organ, B.,& Chan, E. (2020). Large eddy simulation of vehicle emissions dispersion: Implications for on-road remote sensing measurements. Environmental Pollution, 259. http://dx.doi.org/10.1016/j.envpol.2020.113974