Numerical investigation of gaseous pollutant cross-transmission for single-sided natural ventilation driven by buoyancy and wind. (April 2020)

• Record Type: Journal Article
• Authors: Wang, Jihong; Huo, Qiannan; Zhang, Tengfei; Wang, Shugang; Battaglia, Francine
• Is Part Of: Building and environment. Volume 172(2020)
• Publication Date: 2020-04
• Subjects: Natural ventilation -- Buoyancy -- Wind -- Gaseous pollutant -- Cross-transmission -- Window configuration; Buildings -- Environmental engineering -- Periodicals; Building -- Research -- Periodicals; Constructions -- Technique de l'environnement -- Périodiques; Electronic journals; 696
• DOI: 10.1016/j.buildenv.2020.106705
• Languages: English
• ISSNs: 0360-1323

Abstract

Abstract: Single-sided natural ventilation was numerically investigated to determine the impact of buoyancy and wind on the cross-transmission of pollution by considering six window types commonly found in multistory buildings. The goal of this study was to predict the gaseous pollutant transmission using computational fluid dynamics based on the Reynolds-averaged Navier-Stokes equations and baseline k - ω turbulence equations. The results indicated that ventilation rates generally increased with increasing wind speeds if the effects of buoyancy and wind were not suppressed; however, the re-entry ratio representing the proportion of expelled air re-entering other floors and the corresponding risk of infection decreased. If the source of the virus was on a central floor, the risk of infection was the highest on the floors closest to the source. Different window types were also considered for determining their effectiveness in controlling cross-transmission and infection risk, depending on the source location and driving force (e.g., buoyancy and wind). Highlights: Pollutant cross-transmission via buoyancy- and wind-driven ventilation are identified. Window styles, source locations and driving forces act together in cross-transmission. Performances of various windows in controlling the infection risk are not consistent. Application of different window types in a building is viable to reduce infection. The infection risk on the floor closest to the source location is the highest.