ABSTRACT
In this study, a method was proposed to predict the infection probability distribution rather than the room-averaged value. The infection probability by airborne transmission was predicted based on the CO2 concentration. The infection probability by droplet transmission was predicted based on occupant position information. Applying the proposed method to an actual office confirmed that it could be used for quantitatively predicting the infection probability by integrating the ventilation efficiency and distance between occupants. The infection probability by airborne transmission was relatively high in a zone where the amount of outdoor air supply was relatively small. The infection probability by droplet transmission varied with the position of the occupants. The ability of the proposed method to analyze the relative effectiveness of countermeasures for airborne transmission and droplet transmission was verified in this study. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.
ABSTRACT
To quantitatively evaluate the effect of increasing ventilation using the immediately practicable method on infection risk, the ventilation rate in a classroom was measured by the concentration decay method using CO2. The measured value was then substituted into the Wells-Riley model to evaluate aerosol infection risk in steady and non-steady states. In the classroom, the air change rate per hour (ACH) ranged from 3.1 to 10.2, and the local mean age of air tended to be larger near the outlet. It was also shown that opening the windows increased the ventilation rate the most, resulting in a more evenly distributed local mean age of air. We also showed that the aerosol infection risk in the classroom could be significantly reduced by increasing ventilation, suppressing vocalization, and wearing a mask, compared to some outbreaks of COVID-19. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.
ABSTRACT
With the global outbreak of infectious respiratory diseases COVID-19, it is critical to evaluate the indoor airborne infection risk. The ventilation strategies and air distribution methods may affect indoor cross-infection significantly. This study aims to evaluate the effect of 4-way active chilled beam ventilation system on airborne infection risk. An experimental study has been conducted in a test chamber to investigate airborne transmission in an office room with two different heat load conditions and two chilled beam types. Tracer gas technique was used to simulate the exhaled droplet nuclei from the infected person and the photoacoustic gas analyser (Gasera One) was used to monitor the concentration of SF6. The revised Wells-Riley model was used to calculate the infection probability with both spatial and temporal resolutions. One of the occupants was an infector, and the influence of three factors were explored, including the infector's location, air distribution patterns, and heat load levels. To evaluate the dynamics of airborne exposure, real-time and average exposure indices were proposed. The experimental results illustrated that the airborne infection risk increased linearly within 30 min of the exposure time, and then keep a constant state. Under the same heat load conditions, 2 pcs of 1200 chilled beam system directed the particles in the occupied zone to the outlet effectively and reduced the infection rate of personnel in occupied zone. The location of the infector had a significant impact on the infection probability for the active chilled beam ventilation system. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.
ABSTRACT
The risk of indoor respiratory disease transmission can be significantly reduced through interventions that target the built environment. Several studies have successfully developed theoretical models to calculate the effects of built environment parameters on infection rates. However, current studies have mainly focused on calculating infection rate values and comparing pre- and post-optimization values, lacking a discussion of safe baseline values for infection rates with risk class classification. The purpose of this paper is to explore the design of interventions in the built environment to improve the ability of buildings to prevent virus transmission, with a university campus as an example. The study integrates the Wells-Riley model and basic reproduction number to identify teaching spaces with high infection risk on campus and proposes targeted intervention countermeasures based on the analysis of critical parameters. The results showed that teaching buildings with a grid layout pattern had a higher potential risk of infection under natural ventilation. By a diversity of building environment interventions designed, the internal airflow field of classrooms can be effectively organized, and the indoor virus concentration can be reduced. We can find that after optimizing the building mentioned above and environment intervention countermeasures, the maximum indoor virus infection probability can be reduced by 22.88%, and the basic reproduction number can be reduced by 25.98%, finally reaching a safe level of less than 1.0. In this paper, we support university campuses' respiratory disease prevention and control programs by constructing theoretical models and developing parametric platforms. © 2023 Elsevier Ltd