Particle release and transport from human skin and clothing: A CFD modeling methodology

Abstract

Particle release from human skin and clothing has been identified as an important contributor to particulate matter burden indoors. However, knowledge about modeling the coarse particle release from skin and clothing is limited. This study developed a new empirically validated CFD modeling methodology for particle release and transport from seated occupants in an office setting. We tested three modeling approaches for particle emissions: Uniform; Uniform + Localized; and Uniform + Localized with Body Motion; applied to four office scenarios involving a single occupant and two occupants facing each other at 1‐ and 2‐m distances. Uniform particle emissions from skin and clothing underpredicted personal inhalation exposure by as much as 55%–80%. Combining uniform with localized emissions from the armpits drastically reduced the error margin to <10%. However, this modeling approach heavily underestimated particle mass exchange (cross‐contamination) between the occupants. Accounting for the occupant's body motion—by applying the momentum theory method—yielded the most accurate personal exposure and cross‐contamination results, with errors below 12%. The study suggests that for accurate modeling of particle release and transport from seated occupants indoors, localized body emissions in combination with simplified bodily movements need to be taken into account.

Modeling Clothing as a Vector for Transporting Airborne Particles and Pathogens across Indoor Microenvironments

“…An additional limitation of our study was the model’s relatively simplified representation of particle mass-transfer mechanisms. A more accurate representation could be accomplished with a physics-based computational fluid dynamics model, especially for scenarios involving close proximity between occupants (<1.4–1.6 m). , However, the substantial data and computational requirements of such models generally limit their applicability to deterministic scenarios involving a single, well-characterized environment with minimal human influence. In comparison, the approach used in this study was consistent with the limited data available for parameterization and facilitated a probabilistic characterization of variability requiring tens of thousands of executions of the algorithm.…”

“…As such, an occupant’s thermal plume can be readily disrupted when they engage in nonsedentary activity. , Particles within the personal cloud of one occupant can also be transported into the breathing zones of other occupants (or “bystanders”) in the same microenvironment. This phenomenon has been referred to as “cross-contamination”. , …”

“…This phenomenon has been referred to as "crosscontamination". 15,33 An additional, though less understood, factor that can influence particle exposure and variability is that occupants can visit multiple microenvironments (e.g., work, car, and home) throughout a typical day. Potential implications of visiting multiple microenvironments are twofold.…”

Research on National Costume Design Based on Virtual Reality Technology

“…Clothing manufacturing mode based on a 3D model is also helpful for enterprises to realize exible production and reduce inventory pressure and capital chain tension. For consumers, a more intuitive clothing display can help them accurately judge whether the clothing is suitable for their own conditions, which greatly promotes clothing consumption [7][8][9][10]. For schools, 3D clothing simulation can serve teaching well.…”

Longitudinal assessment of personal air pollution clouds in ten home and office environments

“…This excess of air pollution beyond room background levels could be linked to proximity to air pollutant sources and personal activities (e.g., cooking, cleaning). 36 Beyond field campaigns, recent empirical studies in simulated offices revealed that human dermal emissions of particles 30,37 and respiratory emissions of CO 2 31 are also notable constituents of human personal clouds.…”