Airborne respiratory aerosol transport and deposition in a two-person office using a novel diffusion-based numerical model.

BACKGROUND: The COVID-19 pandemic was caused by the SARS-CoV-2 coronaviruses transmitted mainly through exposure to airborne respiratory droplets and aerosols carrying the virus. OBJECTIVE: To assess the transport and dispersion of respiratory aerosols containing the SARS-CoV-2 virus and other viruses in a small office space using a diffusion-based computational modeling approach. METHODS: A 3-D computational model was used to simulate the airflow inside the 70.2 m3 ventilated office. A novel diffusion model accounting for turbulence dispersion and gravitational sedimentation was utilized to predict droplet concentration transport and deposition. The numerical model was validated and used to investigate the influences of partition height and different ventilation rates on the concentration of respiratory aerosols of various sizes (1, 10, 20, and 50 µm) emitted by continuous speaking. RESULTS: An increase in the hourly air change rate (ACH) from 2.0 to 5.6 decreased the 1 µm droplet concentration inside the office by a factor of 2.8 and in the breathing zone of the receptor occupant by a factor of 3.2. The concentration at the receptor breathing zone is estimated by the area-weighted average of a 1 m diameter circular disk, with its centroid at the center of the receptor mannequin mouth. While all aerosols were dispersed by airflow turbulence, the gravitational sedimentation significantly influenced the transport of larger aerosols in the room. The 1 and 10 µm aerosols remained suspended in the air and dispersed throughout the room. In contrast, the larger 20 and 50 µm aerosols deposited on the floor quickly due to the gravitational sedimentation. Increasing the partition between cubicles by 0.254 m (10") has little effect on the smaller aerosols and overall exposure. IMPACT: This paper provides an efficient computational model for analyzing the concentration of different respiratory droplets and aerosols in an indoor environment. Thus, the approach could be used for assessing the influence of the spatial concentration variations on exposure for which the fully mixed model cannot be used.

Characterizing respiratory aerosol emissions during sustained phonation.

OBJECTIVE: To elucidate the role of phonation frequency (i.e., pitch) and intensity of speech on respiratory aerosol emissions during sustained phonations. METHODS: Respiratory aerosol emissions are measured in 40 (24 males and 16 females) healthy, non-trained singers phonating the phoneme /a/ at seven specific frequencies at varying vocal intensity levels. RESULTS: Increasing frequency of phonation was positively correlated with particle production (r = 0.28, p < 0.001). Particle production rate was also positively correlated (r = 0.37, p < 0.001) with the vocal intensity of phonation, confirming previously reported findings. The primary mode (particle diameter ~0.6 µm) and width of the particle number size distribution were independent of frequency and vocal intensity. Regression models of the particle production rate using frequency, vocal intensity, and the individual subject as predictor variables only produced goodness of fit of adjusted R2 = 40% (p < 0.001). Finally, it is proposed that superemitters be defined as statistical outliers, which resulted in the identification of one superemitter in the sample of 40 participants. SIGNIFICANCE: The results suggest there remain unexplored effects (e.g., biomechanical, environmental, behavioral, etc.) that contribute to the high variability in respiratory particle production rates, which ranged from 0.2 particles/s to 142 particles/s across all trials. This is evidenced as well by changes in the distribution of participant particle production that transitions to a more bimodal distribution (second mode at particle diameter ~2 µm) at higher frequencies and vocal intensity levels.

Is Meteorology a Factor to COVID-19 Spread in a Tropical Climate?

It was speculated that fewer COVID-19 infections may emerge in tropical countries due to their hot climate, but India emerged as one of the leading hotspot. There is no concrete answer on the influence of meteorological parameters on COVID-19 even after more than a year of outbreak. The present study examines the impacts of Meteorological parameters during the summer and monsoon season of 2020, in different Indian mega cities having distinct climate and geography. The results indicate the sign of association, but it varies from one climatic zone to another. The principal component analysis revealed that humidity is strongly correlated with COVID-19 infections in hillocky city Pune (R = 0.70), dry Delhi (R = 0.50) and coastal Mumbai (R = 0.46), but comparatively weak correlation is found in arid climatic city of Ahmedabad. As against the expectations, no discernible correlation is found with temperature in any of the cities. As the virus in 2020 in India largely travelled with droplets, the association with absolute humidity in the dry regions has serious implications. Clarity in understanding the impact of seasonality will greatly help epidemiological research and in making strategies to control the pandemic in India and other tropical countries around the world.