Near-field dynamics and plume dispersion after an on-road truck: Implication to remote sensing

Jingwei Xie; Chun-Ho Liu; Ziwei Mo; Yuhan Huang; Wai-Chuen Mok

doi:10.1016/j.scitotenv.2020.141211

Near-field dynamics and plume dispersion after an on-road truck: Implication to remote sensing

Sci Total Environ. 2020 Dec 15:748:141211. doi: 10.1016/j.scitotenv.2020.141211. Epub 2020 Jul 26.

Authors

Jingwei Xie¹, Chun-Ho Liu², Ziwei Mo¹, Yuhan Huang³, Wai-Chuen Mok⁴

Affiliations

¹ Department of Mechanical Engineering, The University of Hong Kong, Hong Kong.
² Department of Mechanical Engineering, The University of Hong Kong, Hong Kong. Electronic address: liuchunho@graduate.hku.hk.
³ Centre for Green Technology, School of Civil and Environmental Engineering, University of Technology Sydney, Australia; Jockey Club Heavy Vehicle Emission Testing and Research Centre, Vocational Training Council, Hong Kong.
⁴ Department of Mechanical Engineering, The University of Hong Kong, Hong Kong; Centre for Green Technology, School of Civil and Environmental Engineering, University of Technology Sydney, Australia.

PMID: 32814285
DOI: 10.1016/j.scitotenv.2020.141211

Abstract

Apart from the aerodynamic performance (efficiency and safety), the wake after an on-road vehicle substantially influences the tailpipe pollutant dispersion (environment). Remote sensing is the most practicable measures for large-scale emission control. Its reliability, however, is largely dictated by how well the complicated vehicular flows and instrumentation constraint are tackled. Specifically, the broad range of motion scales and the short sampling duration (less than 1 s) are the most prominent ones. Their impact on remote sensing has not been studied. Large-eddy simulation (LES) is thus employed in this paper to look into the dynamics and the plume dispersion after an on-road heavy-duty truck at speed U_∞ so as to elucidate the transport mechanism, examine the sampling uncertainty and develop the remedial measures. A major recirculation of size comparable to the truck height h is induced collectively by the roof-level prevailing flows, side entrainment and underbody wall jet. The tailpipe is enclosed by dividing streamlines so the plume is carried back to the truck right after emission. The recirculation augments the pollutant mixing, resulting in a more homogeneous pollutant distribution together with a rather high fluctuating concentration (over 20% of the time-averaged concentrations). The plume ascends mildly before being purged out of the major recirculation to the far field by turbulence, leading to a huge reduction in pollutant concentration (an order of magnitude) outside the near wake. In the far-field, the plume is higher than the tailpipe and disperses in a conventional Gaussian distribution manner. Under this circumstance, a sampling duration for remote sensing longer than h/U_∞ would be prone to underestimating the tailpipe emission.

Keywords: Dispersion models; Heavy-duty truck; Large-eddy simulation (LES); Remote sensing technology; Sampling inaccuracy; Tailpipe emission.