Conference Agenda

Respiratory aerosol emission size distribution measurement approaches used in prior research have multiple limitations which may result in underrepresentation of large particle (>3-5 μm) contributions to current models of particle number and mass distributions. Further, traditional approaches do not measure both hydrated particle distributions at the point of emission and the subsequent desiccated particle distribution from the same plume. Use of horizontal ducts to measure emissions may not adequately account for large particles that would desiccate and stay aloft in typical indoor settings (about 10-70 μm). Additionally, the aerodynamic particle sizer often used for respiratory aerosol measurement is known to undercount coarse hydrated particles. Understanding respiratory particle size distributions in detail is essential to engineering effective mitigation strategies.

Due to these measurement limitations, a new approach is proposed using a vertically oriented low-flow duct equipped with multiple sets of modern particle sizing instruments capable of measuring size distributions of hydrated particles at the point of the emission and desiccated particles towards the end of the duct, with a plume residence time of about 8 minutes. The duct is first purged using clean air, then respiratory emissions are introduced via coughing, sneezing, or speaking into a modified CPAP mask, and particles are monitored in at least 2 locations (top/bottom) continuously. This technique is proposed to allow the accurate tracking of particle size distribution changes during the desiccation process without biases due to particle settling. Results from pilot testing the apparatus are presented, and proposed improvements to the method are introduced, such as including temperature and humidity control, using a breathing manikin for respiratory emission simulation, and reducing wall losses. This approach will initially be leveraged in inter-instrument comparisons to better quantify potential biases, then is planned to be used in human respiratory emission measurement studies.

This study explores infection transmission in indoor environments by differentiating between individual and population-level risks, addressing a critical gap in existing methodologies. Using computational fluid dynamics (CFD) simulations, CO2 is employed as a tracer gas to model pathogen dispersion, enabling an analysis of infection transmission under varying ventilation configurations and seating arrangements. While prior studies predominantly examined pathogen concentration contours for specific infectious source locations—providing insights into individual risk—this research introduces a population-based approach to assess infection risk. Unlike traditional models such as Wells-Riley, which assume well-mixed air and overlook spatial factors, the proposed method leverages numerical data to capture population-level risk as an aggregate of the most hazardous exposure scenarios for all individuals.

Rather than quantifying risk with specific values, this approach evaluates the distribution of inhaled pathogens as a qualitative indicator of infection transmission risk. The findings demonstrate that population risk decreases with increased social distancing, aligning with established guidelines, while individual risk does not always follow the same trend. This framework provides a comprehensive understanding of how seating arrangements and ventilation designs influence infection dynamics, offering a robust tool for optimizing infection prevention strategies in shared indoor spaces.