Numerical simulation of particle formation and evolution in a vehicle exhaust plume using the bimodal Taylor expansion method of moments

Shuyuan Liu, Tat Leung Chan, Huijie Liu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

4 Citations (Scopus)


The bimodal Taylor expansion method of moments (B-TEMOM) model scheme was developed to simulate the formation and evolution of vehicle exhaust particles. Two independent types of log-normal particle size distributions were selected in the B-TEMOM model scheme, comprising large and small particles to represent background (i.e., the surrounding environment) and vehicle exhaust particles, respectively. Concentration distributions of exhaust and background particles derived using this model scheme were verified against results from a moving sectional method and the bimodal quadrature method of moments, showing excellent agreement. The effects of vehicle tailpipe exit conditions (e.g., exhaust particle concentrations and velocity), sulfur content, and relative humidity on the evolution of particles were investigated numerically. Both two-dimensional and three-dimensional numerical simulations showed that tailpipe exit velocity and relative humidity did not greatly affect the steady-state concentrations or the diameters of particles in urban atmospheres. Although an increase in sulfur content had little effect on the particle concentration, it led to background particles with larger geometric average diameter entering the environment. This coupled CFD-B-TEMOM numerical model provides a simple but accurate and efficient method for studying bimodal aerosol dynamics.

Original languageEnglish
Pages (from-to)46-55
Number of pages10
Publication statusPublished - Apr 2019


  • Bimodal Taylor expansion method of moments
  • Coagulation
  • Homogeneous nucleation
  • Sulfur content and ambient relative humidity
  • Tailpipe exit velocity
  • Vehicle exhaust particles

ASJC Scopus subject areas

  • Chemical Engineering(all)
  • Materials Science(all)

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