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The World Health Organization has pointed out that airborne transmission via aerosol particles can be a strong vector for the spread of SARS-CoV-2. Protecting occupants from infectious diseases or harmful particulate matter (PM) in general can be challenging. While experimentally outlining the detailed flow of PM in rooms may require complex setups, computational fluid dynamics (CFD) simulations can provide insights into improving the safety of the built environment and the most effective positioning of air-purifying devices. While previous studies have typically leveraged Reynolds-averaged Navier–Stokes (RANS) approaches for predicting particle propagation, the turbulence length scales accurately captured in these simulations may not be sufficient to provide a realistic spread and the mixing of particles under the effects of forced convection. In this paper, we experimentally validate a Lattice Boltzmann very large eddy simulation (VLES) approach including particle modeling. We also demonstrate how this simulation approach can be used to improve the effectiveness of air filtration devices in realistic office environments. [ABSTRACT FROM AUTHOR]

PM2.5 is an important global air pollution issue. PM2.5 causes various problems on the environment and human health. Even though PM2.5 of the outdoor air is eliminated by particulate air filters, the chemicals adsorbed on the filtered PM2.5 can be outgassed and introduced into the semiconductor manufacturing facilities and processes, thus causing defects on the semiconductor chips by producing particles and haze as airborne molecular contamination. Therefore, estimating the amount of the outgassing from PM2.5 is a very important factor to control gaseous contaminants in the semiconductor industry. In this paper, the PM2.5 samples at different PM2.5 mass loadings were collected in Xi’an, China and evaluated using the soft X-ray radiolysis method for determining the relation between the outgassing and the PM2.5 mass loading. The PM2.5 samples were also analyzed by several methods for quantifying organic and elemental carbons, water soluble ions, and organic compounds in the PM2.5 samples. The outgassing measured by the soft X-ray method increased linearly with the PM2.5 mass loading, and the chemical analyses explained that the organic carbon (OC) was dominantly detected by the soft X-ray method in the current study. Moreover, the sampling location of the PM2.5 affected on the organic compounds of the PM2.5. [ABSTRACT FROM AUTHOR]