CO2 concentration as an indicator of indoor ventilation performance to control airborne transmission of SARS-CoV-2.

BACKGROUND: The Wells-Riley equation has been extensively used to quantify the infection risk of airborne transmission indoors. This equation is difficult to apply to actual conditions because it requires measurement of the outdoor air supply rate, which vary with time and are difficult to quantify. The method of determining the fraction of inhaled air that has been exhaled previously by someone in a building using a CO2 concentration measurement can solve the limitations of the existing method. Using this method, the indoor CO2 concentration threshold can be determined to keep the risk of infection below certain conditions. METHODS: Based on the calculation of the rebreathed fraction, an appropriate mean indoor CO2 concentration and required air exchange rate to control SARS-CoV-2 airborne transmission was calculated. The number of indoor occupants, ventilation rate, and the deposition and inactivation rates of the virus-laden aerosols were considered. The application of the proposed indoor CO2 concentration-based infection rate control was investigated through case studies in school classrooms and restaurants. RESULTS: In a typical school classroom environment with 20-25 occupants and an exposure time of 6-8 h, the average indoor CO2 concentration should be kept below 700 ppm to control the risk of airborne infection indoors. The ASHRAE recommended ventilation rate is sufficient when wearing a mask in classrooms. For a typical restaurant with 50-100 occupants and an exposure time of 2-3 h, the average indoor CO2 concentration should be kept below about 900 ppm. Residence time in the restaurant had a significant effect on the acceptable CO2 concentration. CONCLUSION: Given the conditions of the occupancy environment, it is possible to determine an indoor CO2 concentration threshold, and keeping the CO2 concentration lower than a certain threshold could help reduce the risk of COVID-19 infection.

Natural ventilation strategy and related issues to prevent coronavirus disease 2019 (COVID-19) airborne transmission in a school building.

The World Health Organization (WHO) announced that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may spread through aerosols, so-called airborne transmission, especially in a poorly ventilated indoor environment. Ventilation protects the occupants against airborne transmission. Various studies have been performed on the importance of sufficient ventilation for diluting the concentration of virus and lowering any subsequent dose inhaled by the occupants. However, the ventilation situation can be problematic in public buildings and other shared spaces, such as shops, offices, schools, and restaurants. If ventilation is provided by opening windows, the outdoor airflow rate depends strongly on the specific local conditions (opening sizes, relative positions, climatic and weather conditions). This study uses field measurements to analyze the natural ventilation performance in a school building according to the window opening rates, positions, and weather conditions. The ventilation rates were calculated by the tracer gas decay method, and the infection risk was assessed using the Wells-Riley equation. Under cross-ventilation conditions, the average ventilation rates were measured at 6.51 h-1 for 15% window opening, and 11.20 h-1 for 30% window opening. For single-sided ventilation, the ventilation rates were reduced to about 30% of the values from the cross-ventilation cases. The infection probability is less than 1% in all cases when a mask is worn and more than 15% of the windows are open with cross-ventilation. With single-sided ventilation, if the exposure time is less than 1 h, the infection probability can be kept less than 1% with a mask. However, the infection probability exceeds 1% in all cases where exposure time is greater than 2 h, regardless of whether or not a mask is worn. Also, when the air conditioner was operated with a window opening ratio of 15%, power consumption increased by 10.2%.