Toward the development of an in silico human model for indoor environmental design

Spatial distributions of airborne transmission risk on commuter buses: Numerical case study using computational fluid and particle dynamics with computer-simulated persons

Commuter buses have a high passenger density relative to the interior cabin volume, and it is difficult to maintain a physical/social distance in terms of airborne transmission control. Therefore, it is important to quantitatively investigate the impact of ventilation and air-conditioning in the cabin on the airborne transmission risk for passengers. In this study, comprehensive coupled numerical simulations using computational fluid and particle dynamics (CFPD) and computer-simulated persons (CSPs) were performed to investigate the heterogeneous spatial distribution of the airborne transmission risk in a commuter bus environment under two types of layouts of the ventilation system and two types of passenger densities. Through a series of particle transmission analysis and infection risk assessment in this study, it was revealed that the layout of the supply inlet/exhaust outlet openings of a heating, ventilation, and air-conditioning (HVAC) system has a significant impact on the particle dispersion characteristics inside the bus cabin, and higher infection risks were observed near the single exhaust outlet in the case of higher passenger density. The integrated analysis of CFPD and CSPs in a commuter bus cabin revealed that the airborne transmission risk formed significant heterogeneous spatial distributions, and the changes in air-conditioning conditions had a certain impact on the risk.

Breathing zone and exhaled air re-inhalation rate under transient conditions assessed with a computer-simulated person

The breathing zone of an individual indoors is usually defined as a finite region steadily formed in front of a face. Assuming the steady formation of the breathing zone, we propose a procedure for quantitatively identifying a breathing zone formed in front of a human face in the transient condition. This assumption is reasonable considering that the ventilation time scale of human respiration is sufficiently short compared to the ventilation time scale of a room. We used steady-state computational fluid dynamics (CFD) and a computationally simulated person (CSP). We present the probabilistic size of the breathing zone for various postures and breathing conditions. By analyzing unsteady inhalation and exhalation airflow characteristics via a CSP with a respiratory system, we also estimated the direct re-inhalation rate of the exhaled air. The results can be used for developing methods to control the long-term and low-contaminant concentration exposures.

A numerical investigation of the potential effects of e-cigarette smoking on local tissue dosimetry and the deterioration of indoor air quality

Electronic (e)-cigarette smoking is considered to be less harmful than traditional tobacco smoking because of the lack of a combustion process. However, e-cigarettes have the potential to release harmful chemicals depending on the constituents of the vapor. To date, there has been significant evidence on the adverse health effects of e-cigarette usage. However, what is less known are the impacts of the chemicals contained in exhaled air from an e-cigarette smoker on indoor air quality, the second-hand passive smoking of residents, and the toxicity of the exhaled air. In this study, we develop a comprehensive numerical model and computer-simulated person to investigate the potential effects of e-cigarette smoking on local tissue dosimetry and the deterioration of indoor air quality. We also conducted demonstrative numerical analyses for first-hand and second-hand e-cigarette smoking in an indoor environment. To investigate local tissue dosimetry, we used newly developed physiologically based pharmacokinetic/toxicokinetic models that reproduce inhalation exposure by way of the respiratory tract and dermal exposure through the human skin surface. These models were integrated into the computer-simulated person. Our numerical simulation results quantitatively demonstrated the potential impacts of e-cigarette smoking in enclosed spaces on indoor air quality.