Quality control of Lagrangian indoor particle transport simulation: Effects of particle numbers, ventilation strategy, and sampling volume

Ye Seul Eom, Donghyun Rim

Research output: Contribution to journalArticlepeer-review


Airborne particle transport in indoor environments plays an important role in occupant exposure to aerosols and public health problems. Several studies have examined indoor airflow and particle transport using computational fluid dynamics models. For the Lagrangian particle tracking model, the minimum particle concentration necessary for accurate prediction may vary with the airflow regime and sampling volume. Nonetheless, only a few studies have systematically quantified suitable particle numbers and sampling volumes, according to indoor airflow and ventilation conditions. This study addresses this gap by exploring quality control strategies for a Lagrangian particle tracking model to reliably predict indoor particle transport. Based on transient simulations, we analyzed the spatiotemporal distributions of indoor particle trajectories while varying the number of particles, sampling volume, and ventilation strategy. The results indicate that in general a sampling volume of 5 L can predict the normalized mean concentrations better than a 1 L sampling volume, particularly when dealing with a smaller number of particles. Furthermore, the required particle number concentrations vary significantly depending on the chosen ventilation strategy. For instance, under the conditions of a 5 L sampling volume and an air exchange rate of 2.7 h−1, the minimum particle number concentrations for achieving reliable modeling predictions were observed to be 0.0075 cm−3 for displacement ventilation and 0.015 cm−3 for mixing ventilation. These results highlight the crucial role of the number of simulated particle trajectories in Lagrangian particle tracking models in determining prediction quality. The study findings suggest that quality control measures should acknowledge the significant variability in required particle numbers, which can often differ by an order of magnitude, contingent upon the specific combination of ventilation strategy and sampling volume.

Original languageEnglish (US)
Article number106346
JournalJournal of Aerosol Science
StatePublished - May 2024

All Science Journal Classification (ASJC) codes

  • Environmental Engineering
  • Pollution
  • Mechanical Engineering
  • Fluid Flow and Transfer Processes
  • Atmospheric Science

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