Data: The selective detection of individual respiratory droplets in air

The published data correspond to the article The Selective Detection of Individual Respiratory Droplets in Air, which is currently under submission. 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 in real time. Here, we present a capacitive sensor that selectively detects and counts the individual RDs in ambient air (including those dispersing in indoor spaces), a critical capability for assessing the true transmission risks. The device exploits the dielectric constant (ε) of water (78.2) to differentiate the droplets from solid particles (ε < 15). In a conference-room study, droplet concentrations (40–330 RDs/L) were found to be correlated with human occupancy, but not with PM2.5 levels. The developed technology enables the real-time monitoring of airborne-transmission risks, facilitating data-driven ventilation strategies and infection-control measures, providing a tool for mitigating the spread of airborne diseases in hospitals, schools and other public spaces.本公开数据集对应于目前正在投稿的论文《空气中单个呼吸道飞沫的选择性检测》。 在拥挤的室内空间中遏制空气传播疾病的扩散是一项全球性挑战。感染者会释放携带病毒的呼吸道飞沫（Respiratory Droplets，RDs），此类飞沫可在空气中悬浮数小时且仍具传染性。当前的监测手段无法实时区分此类飞沫与空气颗粒物。本研究提出一种电容式传感器（capacitive sensor），可选择性检测并计数环境空气（包括室内扩散的飞沫）中的单个RDs，这一关键能力可用于评估真实的传播风险。该传感器利用水的介电常数（dielectric constant，ε）为78.2这一特性，将飞沫与固体颗粒物（ε<15）区分开来。在一项会议室研究中，研究人员发现飞沫浓度（40~330 RDs/L）与人员在场情况相关，但与PM2.5浓度无关。本研发的技术可实现空气传播风险的实时监测，助力数据驱动的通风策略与感染防控措施的制定，为遏制医院、学校及其他公共空间内空气传播疾病的扩散提供了有效工具。