Evaluation of SARS-CoV-2 Aerosol Infection Risks Based on Bayesian Calibration Analysis of CO2 Concentrations in Canadian School Buildings
Concordia University, Canada
The COVID-19 pandemic has led to a dramatic inconvenience and loss of human activities worldwide. Its impact on society and economy becomes more significant and dreadful. An unprecedented challenge is presented not only to the health system but also to the educational system. Maintaining students’ learning performance while keeping their health during the crisis has gained attention from governors, educators, parents, etc. In this paper, first, monitored information about two classrooms during a typical day of the crisis was presented. The occupants’ information (students’ age, number, activities), ventilation system status, window status, and indoor CO2 concentration are included. Then a developed CO2 concentration model was introduced. Sensitivity analysis was conducted to identify the importance rank of model inputs and parameters. Finally, the measurements were employed to calibrate the CO2 concentration model with Bayesian inference. The calibrated model parameters, such as ventilation rate, could be used to estimate its impact on COVID-19 infection risk.
Indoor Particles We Generate: Measurements of Size Distribution and Spatio-temporal Distribution
1Mechanical and Aeronautical Engineering, Clarkson University, NY, USA; 2TelosAir Cooperation, Potsdam, NY, USA
With the COVID-19 pandemic, airborne transmission of particles has been a major concern. Particle transmission in indoor environments has been a major consideration to determine occupancy level and changes to ventilation systems in workspaces, classrooms, and commercial buildings. The current understanding of particle transmission in indoor spaces is largely based on well-mixed assumptions. These assumptions ignore unsteadiness in air supply and inhomogeneity in the distribution of air vents in a room. These practical considerations can significantly alter particle transmission characteristics, and hence, the safety guidelines in indoor spaces. In this study, we measure size distribution of particles emitted by human occupants in a classroom with an integrated system of aerosol instruments consisting of Condensation Particle Counter, Ultra-High Sensitivity Aerosol Spectrometer (60 nm – 1 µm), Aerodynamic Particle Sizer (0.5 µm – 20 µm) and a Scanning Mobility Particle Sizer (10 nm to 300 nm). Additionally, a system of low-cost optical sensors will be deployed throughout the room to understand the spatio-temporal distribution of particles and the distribution of effective air exchanges in a room as a function of operating conditions. We will compare our results against well-mixed models to highlight similarities and differences and implications for next generation ventilation control.
Modeling The Fate And Transport Of Particles In A Classroom Using High-Fidelity CFD Models
Clarkson University, United States of America
Ventilation in buildings is one of the critical mitigation tools available to us to help minimize the spread of infection. Modeling the impact of ventilation on airborne particles is primarily done using well-mixed models such as CONTAM, which assume a constant ventilation supply over time, spread uniformly over space. These models provide an average picture of the fate of particles and may not capture the entire risk profile for an individual in a typical space. In our research, we study the fate of airborne particles in a classroom considering realistic conditions of intermittent fresh air supply from a discrete number of vents. The study is conducted using high-fidelity computational fluid dynamics (CFD) simulations and a full-size lecture hall. Our preliminary results show that the fate of particles can be very different from that predicted by well-mixed models. The fate of airborne particles is strongly dependent on the characteristics of supply flow, injection location, and monitoring location. In our presentation, we will discuss the modeling approach, major results obtained, and the implications for ventilation control to minimize infection risk.
Respiratory Characteristics, Thermal Comfort and Productivity with Wearing a Mask
Shinshu university, Japan
The purpose of this study is to clarify the respiratory characteristics and productivity with wearing a mask, and to propose the indoor control strategy to maintain the thermal comfort. With the worldwide spread of biological hazards including COVID-19, it has become common to wear a mask as a countermeasure against infection in public places. Because of this influence, it is necessary to take measures against health hazards caused by wearing a mask (suffocation due to wearing a mask for a long time, heat stroke in summer). In this study, there are two stages of methods; (1) clarification the characteristics of exhalation and inspiration when wearing a mask, (2) understanding the causes of reduced work efficiency that cause oxygen deficiency and destruction of the human body heat balance. Respiratory characteristics from the human body differ depending on the type of mask, the amount of metabolism due to exercise, and the surrounding environment. Therefore, we measure changes in respiratory characteristics (respiratory cycle, oxygen concentration, temperature, humidity) and build a predictable numerical model. By measuring changes in work efficiency and intellectual productivity due to various changes in the indoor environment, the effects of oxygen deficiency and destruction of the human body heat balance due to wearing a mask are clarified, and indoor air and thermal environment control that can respond to them It will be a great achievement for the proposal of the law.