Use of Multiple Low Cost Carbon Dioxide Sensors to Measure Exhaled Breath Distribution with Face Mask Type and Wearing Behaviour

• Published in: Sensors (Basel, Switzerland) Vol. 21; no. 18; p. 6204
• Main Authors: Salman, Naveed, Khan, Muhammad Waqas, Lim, Michael, Khan, Amir, Kemp, Andrew H., Noakes, Catherine J.
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 16.09.2021; MDPI
• Subjects: Aerosols; Application programming interface; Batteries; Carbon dioxide; CO2 sensors; Coronaviruses; COVID-19; data interpolation; Disease transmission; face mask; Mortality; Respiration; Sensors; Severe acute respiratory syndrome coronavirus 2; Statistical analysis; Ventilation
• DOI: 10.3390/s21186204
• ISSN: 1424-8220

The use of cloth face coverings and face masks has become widespread in light of the COVID-19 pandemic. This paper presents a method of using low cost wirelessly connected carbon dioxide (CO2) sensors to measure the effects of properly and improperly worn face masks on the concentration distribution of exhaled breath around the face. Four types of face masks are used in two indoor environment scenarios. CO2 as a proxy for exhaled breath is being measured with the Sensirion SCD30 CO2 sensor, and data are being transferred wirelessly to a base station. The exhaled CO2 is measured in four directions at various distances from the head of the subject, and interpolated to create spatial heat maps of CO2 concentration. Statistical analysis using the Friedman’s analysis of variance (ANOVA) test is carried out to determine the validity of the null hypotheses (i.e., distribution of the CO2 is same) between different experiment conditions. Results suggest CO2 concentrations vary little with the type of mask used; however, improper use of the face mask results in statistically different CO2 spatial distribution of concentration. The use of low cost sensors with a visual interpolation tool could provide an effective method of demonstrating the importance of proper mask wearing to the public.