Identification of contaminant sources in enclosed spaces by a single sensor

Role of pathogen-laden expiratory droplet dispersion and natural ventilation explaining a COVID-19 outbreak in a coach bus

The influencing mechanism of droplet transmissions inside crowded and poorly ventilated buses on infection risks of respiratory diseases is still unclear. Based on experiments of one-infecting-seven COVID-19 outbreak with an index patient at bus rear, we conducted CFD simulations to investigate integrated effects of initial droplet diameters(tracer gas, 5 μm, 50 μm and 100 μm), natural air change rates per hour(ACH = 0.62, 2.27 and 5.66 h^-1 related to bus speeds) and relative humidity(RH = 35% and 95%) on pathogen-laden droplet dispersion and infection risks. Outdoor pressure difference around bus surfaces introduces natural ventilation airflow entering from bus-rear skylight and leaving from the front one. When ACH = 0.62 h^-1(idling state), the 30-min-exposure infection risk(TIR) of tracer gas is 15.3%(bus rear) - 11.1%(bus front), and decreases to 3.1%(bus rear)-1.3%(bus front) under ACH = 5.66 h^-1(high bus speed).The TIR of large droplets(i.e., 100 μm/50 μm) is almost independent of ACH, with a peak value(∼3.1%) near the index patient, because over 99.5%/97.0% of droplets deposit locally due to gravity. Moreover, 5 μm droplets can disperse further with the increasing ventilation. However, TIR for 5 μm droplets at ACH = 5.66 h^-1 stays relatively small for rear passengers(maximum 0.4%), and is even smaller in the bus middle and front(<0.1%). This study verifies that differing from general rooms, most 5 μm droplets deposit on the route through the long-and-narrow bus space with large-area surfaces(L∼11.4 m). Therefore, tracer gas can only simulate fine droplet with little deposition but cannot replace 5-100 μm droplet dispersion in coach buses.

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

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.