Numerical Study of the Effect of Ventilation Pattern on Coarse, Fine, and Very Fine Particulate Matter Removal in Partitioned Indoor Environment

Abstract

An indoor size-dependent particulate matter (PM) transport approach is developed to investigate coarse PM (PM₁₀), fine PM (PM_2.5), and very fine PM (PM₁) removal behaviors in a ventilated partitioned indoor environment. The approach adopts the Eulerian large eddy simulation of turbulent flow and the Lagrangian particle trajectory tracking to solve the continuous airflow phase and the discrete particle phase, respectively. Model verification, including sensitivity tests of grid resolution and particle numbers, is conducted by comparison with the full-size experiments conducted previously. Good agreement with the measured mass concentrations is found. Numerical scenario simulations of the effect of ventilation patterns on PM removal are performed by using three common ventilation patterns (piston displacement, mixing, and cross-flow displacement ventilation) with a measured indoor PM₁₀ profile in the Taipei metropolis as the initial condition. The temporal variations of suspended PM₁₀, PM_2.5, and PM₁ mass concentrations and particle removal mechanisms are discussed. The simulated results show that for all the of the three ventilation patterns, PM_2.5 and PM₁ are much more difficult to remove than PM₁₀. From the purpose of health protection for indoor occupants, it is not enough to only use the PM₁₀ level as the indoor PM index. Indoor PM_2.5 and PM₁ levels should be also considered. Cross-flow displacement ventilation is more effective to remove all PM₁₀, PM_2.5, and PM₁ than the other ventilation patterns. Displacement ventilation would result in more escaped particles and less deposited particles than mixing ventilation.