Numerical studies of indoor particulate and gaseous micropollutant transport and its impact on human health in densely-occupied spaces.

Micropollutants (MPs) have increasingly become a matter of concern owing to potential health risks associated with human inhalation exposure, particularly in densely-occupied indoor environments. This study employed numerical simulations in a traditional built indoor workspace and a public transport cabin to elucidate the transport dynamics and health impacts of particulate and gaseous type of indoor MPs on varying groups of occupants. The risk of infection from pathogen-bearing MPs was evaluated in the workspace using the integrated Eulerian-Lagrangian and modified Wells-Riley model. In the cabin environment, the health impact of inhaled TVOC within the human nasal system was assessed via the integrated nasal-involved manikin model and cancer/non-cancer risk model. The results demonstrated that when ventilation layout was in favour of restricting particulate MPs spread, considerably high health risks (up to 17.22% infection possibility) were generally found in near-fields of emission source (< 2.25 m). Conversely, if the ventilated flow interacts robustly with emission source, every occupant has a minimum 5% infection risk. Incorporating the nasal cavity in the human model offers a nuanced understanding of gaseous MP distributions post-inhalation. Notably, the olfactory and sinus regions displayed heightened vulnerability to TVOC exposure, with a 62.5%-108% concentration increase compared to other nasal areas. Cancer risk assessment plausibly explained the rising occurrence of brain and central nervous system cancer for aircrew members. Non-cancer risk was found acceptable. This study was expected to advance the understanding of environmental pollution and the health risks tied to indoor MPs in densely-populated environments.

Semi-surrogate modelling of droplets evaporation process via XGBoost integrated CFD simulations.

The applications of machine learning (ML) based approach are emerging as possible tools to accelerate CFD simulations. This study proposed a semi-surrogate model for CFD with integration of the cutting-edge ML algorithm, eXtreme Gradient Boosting (XGB), which enlightened a possible pathway to effectively and efficiently solve and predict those costly but highly repetitive fluid dynamics-related problems. Droplet evaporation, a complex but essential phenomenon in respiratory droplets transport, was studied as the practical case using the proposed model. Droplets evaporation and dynamic size distributions were firstly tracked under various combinations of indoor humidity and temperature using traditional Eulerian-Lagrangian CFD framework, followed by generating several datasets for XGB training. The trained XGB was then used to interpret the evaporated droplets size over time under new combinations of indoor conditions. Outcomes revealed that well-trained XGB-base semi-surrogate model was capable of interpreting complex non-linear relationships between droplets dynamic parameters (diameter and time) and indoor parameters (humidity and temperature). For each specific parameter, the predictive error of well-trained XGB could retain below 5 % and its prediction speed was found nearly 1 million times faster than that of new CFD simulations. Successful applications of XGB in conjunction with CFD demonstrated its great potential on providing rapid and more efficient predictions of complex, costly and repetitive fluid dynamics-related phenomenons (e.g. droplets evaporation). Also, the XGB predicted droplets evaporation data from this study could be further applied as initial conditions into new simulations via the User-defined function (UDF).

A spatiotemporal assessment of occupants' infection risks in a multi-occupants space using modified Wells-Riley model.

Escalating demands of assessing airborne disease infection risks had been awakened from ongoing pandemics. An inhalation index linked to biomedical characteristics of pathogens (e.g. TCID 50 for coronavirus delta variant) was proposed to quantify human uptake dose. A modified Wells-Riley risk-assessment framework was then developed with enhanced capability of integrating biological and spatiotemporal features of infectious pathogens into assessment. The instantaneous transport characteristics of pathogens were traced by Eulerian-Lagrangian method. Droplets released via speaking and coughing in a conference room with three ventilation strategies were studied to assess occupants' infection risks using this framework. Outcomes revealed that speaking droplets could travel with less distance (0.5 m) than coughing droplets (1 m) due to the frequent interaction between speaking flow and thermal plume. Quantified analysis of inhalation index revealed a higher inhalation possibility of droplets with nuclei size smaller than 5 µ m , and this cut-off size was found sensitive to ventilation. With only 60-second exposure, occupants in the near-field of host started to have considerable infection risks (approximately 20%). This risk was found minimising over distance exponentially. This modified framework demonstrated the systematic analysis of airborne transmission, from quantifying particle inhalation possibility, targeting specific disease's TCID 50 , to ultimate evaluation of infection risks.

Analysis of occupants' exposure risk of cough-expelled droplets in the workspace with various mixing ventilation layouts.

This study numerically investigated the transport characteristics of the cough-expelled droplets and their corresponding exposure risk of each occupant under various mixing ventilation layouts. Transient simulations were conducted in a conference room, while pathogen-bearing droplets were released by a standing speaker. The results showed that droplet residues (< 40 µm) had a high potential to reach occupant's breathing zone, among which the number fraction of aerosol residues (< 10 µm) could be nearly doubled compared with that of the rest droplet residues in the breathing zone. Occupants' exposure risks were found very sensitive to the ventilation layouts. The strong ventilated flow could significantly promote droplet dispersions when those inlets were closely located to the infectious speaker, resulting in all occupants exposed to a considerable fraction of aerosols and droplets within a given exposure time of 300 s. The mixing ventilation layout did not have a consistent performance on restricting the pathogen spread and controlling the occupant's exposure risk in an enclosed workspace. Its performance could be highly sensitive to the location of the infectious agent. Centralized vent layouts could provide relatively more consistent performance on removing droplets, whilst some local airflow recirculation with locked droplets were noticed.

Evaluation of cough-jet effects on the transport characteristics of respiratory-induced contaminants in airline passengers' local environments.

Urgent demands of assessing respiratory disease transmission in airliner cabins had awakened from the COVID-19 pandemics. This study numerically investigated the cough flow and its time-dependent jet-effects on the transport characteristics of respiratory-induced contaminants in passengers' local environments. Transient simulations were conducted in a three-row Boeing 737 cabin section, while respiratory contaminants (2 µm-1000 µm) were released by different passengers with and without coughing and were tracked by the Lagrangian approach. Outcomes revealed significant influences of cough-jets on passengers' local airflow field by breaking up the ascending passenger thermal plumes and inducing several local airflow recirculation in the front of passengers. Cough flow could be locked in the local environments (i.e. near and intermediate fields) of passengers. Results from comparative studies also revealed significant increases of residence times (up to 50%) and extended travel distances of contaminants up to 200 µm after considering cough flow, whereas contaminants travel displacements still remained similar. This was indicating more severe contaminate suspensions in passengers' local environments. The cough-jets was found having long and effective impacts on contaminants transport up to 4 s, which was 8 times longer than the duration of cough and contaminants release process (0.5 s). Also, comparing to the ventilated flow, cough flow had considerable impacts to a much wider size range of contaminants (up to 200 µm) due to its strong jet-effects.

Numerical investigation of indoor particulate contaminant transport using the Eulerian-Eulerian and Eulerian-Lagrangian two-phase flow models.

Transport of micron particles in a displacement ventilated room was simulated using both the Eulerian-Eulerian model and the Eulerian-Lagrangian model. The same inter-phase action mechanisms were included in both models. The models were compared against each other in the aspects of air velocity, particle concentration, and particle-wall interactions. It was found that the two models have similar accuracy in predicting the airflow field while each of them has its own advantage and drawback in modelling particle concentration and particle-wall interactions. The E-E model is capable of providing a mechanistic description of the inter-phase interactions, whilst the E-L model has obvious advantage in modelling particle-wall interactions. Advices were given for choosing an appropriate model for modelling particulate contaminant transport in indoor environments.

Thermal effect of human body on cough droplets evaporation and dispersion in an enclosed space.

This study numerically investigated the thermal effect of human body on the time-dependent dispersion of cough droplets with evaporation process. The thermal flow of human body was imitated using a 3D thermal manikin with real body features, while a recent developed multi-component Eulerian-Lagrangian approach was used to address the effects of inhomogeneous temperature and humidity fields on droplet evaporation. By comparing the results yielded without and with the human body heat, the outcomes demonstrated strong impact of human body heat on the droplets mass fraction and local air velocity distributions. Inspirable droplets could potentially drop into respirable droplets by evaporation, although the evaporation rate was not significantly affected by body heat. The thermal effect of human body revealed its vital impacts on the time-dependent droplets dispersion. Due to the buoyancy driven thermal flow, both the vertical velocity and displacement of small droplets (≤20 µm) were completely reversed from descending to ascending, while the deposition time of large droplets (≥50 µm) were significantly delayed. With the reduced droplet size by evaporation and droplets lifted into breathing zone by human thermal effect, the inhalability and infection risks of cough droplets would be much higher in real occupied indoor spaces.

Characterisation and analysis of indoor tornado for contaminant removal and emergency ventilation.

As an essential emergency management strategy, innovative emergency ventilation schemes that can quickly remove infectious and fatal contaminants without further spreading are highly demanded for public and commercial buildings. This study numerically investigated a vortex flow driven ventilation in a model room to explore the dynamic characteristics and 3D visualisation of vortex-driven indoor tornados. Four approaches to identify the core region of the indoor tornado were developed and compared against each other. By successfully capturing the continuously changing centre of the vortex and significant core region size variations at different heights, the swirl vector method was recommended as a quantifiable approach to identify the core region of indoor tornados. The numerical outcomes also revealed a strong connection between the lift angle, vortex intensity, overall size of indoor tornado and maximum size of core region. The best contaminants control and removal was achieved at lift angle of 20° in this study and an optimum lift angle ranging from 10° to 20° was recommended for future study.

Modelling of evaporation of cough droplets in inhomogeneous humidity fields using the multi-component Eulerian-Lagrangian approach.

This study employed a multi-component Eulerian-Lagrangian approach to model the evaporation and dispersion of cough droplets in quiescent air. The approach is featured with a continuity equation being explicitly solved for water vapor, which allows comprehensively considering the effects of inhomogeneous humidity field on droplets evaporation and movement. The computational fluid dynamics (CFD) computations based on the approach achieved a satisfactory agreement with the theoretical models reported in the literature. The results demonstrated that the evaporation-generated vapor and super-saturated wet air exhaled from the respiratory tracks forms a "vapor plume" in front of the respiratory track opening, which, despite the short life time, significantly impedes the evaporation of the droplets captured in it. The study also revealed that due to the droplet size reduction induced by evaporation, both the number density of airborne droplets and mass concentration of inhalable pathogens remarkably increased, which can result in a higher risk of infection. Parametric studies were finally conducted to evaluate the factors affecting droplet evaporation. SUMMARY: The study demonstrated the importance of considering inhomogeneous humidity field when modelling the evaporation and dispersion of cough droplets. The multi-component Eulerian-Lagrangian model presented in this study provides a comprehensive approach to address different influential factors in a wide parametric range, which will enhance the assessment of the health risks associated with droplet exposure.

Evaluation of airborne disease infection risks in an airliner cabin using the Lagrangian-based Wells-Riley approach.

An urgent demand of assessing passengers' exposure risks in airliner cabins was raised as commercial airliners are one of the major media that carrying and transmitting infectious disease worldwide. In this study, simulations were conducted using a Boeing 737 cabin model to study the transport characteristics of airborne droplets and the associated infection risks of passengers. The numerical results of the airflow field were firstly compared against the experimental data in the literature to validate the reliability of the simulations. Airborne droplets were assumed to be released by passengers through coughing and their transport characteristics were modelled using the Lagrangian approach. Numerical results found that the particle travel distance was very sensitive to the release locations, and the impact was more significant along the longitudinal and horizontal directions. Particles released by passengers sitting next to the windows could travel much further than the others. A quantifiable approach was then applied to assess the individual infection risks of passengers. The key particle transport information such as the particle residence time yielded from the Lagrangian tracking process was extracted and integrated into the Wells-Riley equation to estimate the risks of infection. Compared to the Eulerian-based approach, the Lagrangian-based approach presented in this study is more robust as it addresses both the particle concentration and particle residence time in the breathing zone of every individual passenger.