Data: The selective detection of individual respiratory droplets in air

Preventing the spread of airborne diseases in crowded indoor spaces is a global challenge. Infected individuals release virus-laden respiratory droplets (RDs) that can remain suspended in air and infectious for hours. Current monitoring methods cannot distinguish these droplets from airborne particulate matter (PM) in a real time. Here, we present a capacitive sensor that selectively detects and counts the individual droplets in indoor spaces, regardless the presence of PM. The device exploits the dielectric constant (ε) of water (78.2) to differentiate the droplets from solid PM particles (ε < 15). In a non-ventilated conference-room study, RDs concentrations (40–330 RDs/L) were found to be correlated with human occupancy, but not with PM2.5 levels. The developed technology enables a real-time monitoring of number concentration of RDs, which represent a potential health risk when they carry viral or bacterial infections. The detected increase in RD concentration can serve as a trigger for data-driven ventilation and infection-prevention measures, providing an effective tool for mitigating the spread of respiratory diseases in hospitals, schools and other public spaces.