Numerical investigation of airflow pattern and particulate matter transport in naturally ventilated multi-room buildings.

UNLABELLED This study reports on a numerical investigation of transport behavior of indoor airflow and size-dependent particulate matter (PM) in multi-room buildings. An indoor size-dependent PM transport approach, combining the Eulerian large-eddy simulation of turbulent flow with the Lagrangian particle trajectory tracking, was developed to investigate indoor airflow pattern and PM1/PM2.5/PM10 removal efficiency in naturally ventilated multi-room buildings. A displacement ventilation with a measured indoor PM10 profile in Taipei Metropolis as the initial condition was carried out to characterize spatial and temporal variations of indoor PM1/PM2.5/PM10 removal behavior. The effects of indoor airflow pattern on particle transport mechanisms, e.g., deposition, suspension, migration and escape, were analyzed. Two comparison scenarios, which considered the effects of no indoor partition and different air change rate, respectively, were also conducted. In comparison with the effectiveness of PM1/PM2.5/PM10 removal, the simulated results showed that coarse particles were easier to be removed out of the building than fine particles. Natural ventilation was not an effective way to remove fine particles such as PM1 and PM2.5 in a multi-room building. Indoor partitions can impede 12% of the mean streamwise velocities and significantly increase 30-50% turbulence intensities. However, indoor partitions increased particle deposition and decreased particle escape. As a result of the two opposite particle removal mechanisms, i.e., deposition and escape, the impact of indoor partitions on PM1/PM2.5/PM10 removal behavior was not as significant as the results of airflow velocities. PRACTICAL IMPLICATIONS This work developed a computational fluid dynamics technique to investigate indoor airflow patterns and PM1/PM2.5/PM10 removal ability in ventilated multi-room buildings. The results of this paper can help to identify adequate PM1/PM2.5/PM10 cleaning procedure and provide useful size-dependent PM control strategy in multi-room buildings.

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