Passenger exposure to respiratory aerosols in a train cabin: Effects of window, injection source, output flow location

Reducing the contaminant dispersion and infection risks in the train cabins by adjusting the inlet turbulence intensity: A study based on turbulence simulation

Existing studies on ventilation in closed spaces mainly considered the average inlet velocity and ignored the influence of inlet turbulent fluctuation. However, the variation in inlet turbulence intensity (TI) is considerable and significantly affects the dispersion of contaminants. This study conducts numerical simulations verified by experiments to investigate the effect of the inlet TI on train contaminants dispersion and analyze infection probability variation. Firstly, the unsteady Reynolds-averaged Navier-Stokes (URANS) method and improved delayed detached eddy simulation (IDDES) method are compared in simulating the internal airflow characteristics based on the on-site measurement. The results indicate that the latter dominates in capturing airflow pulsations more than the former, although the mean airflow results obtained from both methods agree well with experimental results. Furthermore, the IDDES method is employed to investigate the effect of the inlet TI on contaminant dispersion, and the infection risks are also assessed using the improved probability model. The results show that, with the increase of TI from 5 % to 30 %, the contaminant removal grows considerably, with the removal index rising from 0.23 to 1.86. The increased TI leads to the overall and local infection risks of occupants descending significantly, wherein the former decreases from 1.53 % to 0.88 % with a reduction rate of 42 %, and the latter drops from 3.30 % to 2.16 % with a mitigation rate of 35 %. The findings can serve as solid guidelines for numerical method selection in accurately capturing the indoor dynamic airflow distribution and for the ventilation parameters design regarding TI inside trains to mitigate the airborne infection risk.

COVID-19 transmission and control in land public transport: A literature review

Land public transport is an important link within and between cities, and how to control the transmission of COVID-19 in land public transport is a critical issue in our daily lives. However, there are still many inconsistent opinions and views about the spread of SARS-CoV-2 in land public transport, which limits our ability to implement effective interventions. The purpose of this review is to overview the literature on transmission characteristics and routes of the epidemic in land public transport, as well as to investigate factors affecting its spread and provide feasible measures to mitigate the infection risk of passengers. We obtained 898 papers by searching the Web of Science, Pubmed, and WHO global COVID database by keywords, and finally selected 45 papers that can address the purpose of this review. Land public transport is a high outbreak area for COVID-19 due to characteristics like crowding, inadequate ventilation, long exposure time, and environmental closure. Different from surface touch transmission and drop spray transmission, aerosol inhalation transmission can occur not only in short distances but also in long distances. Insufficient ventilation is the most important factor influencing long-distance aerosol transmission. Other transmission factors (e.g., interpersonal distance, relative orientation, and ambient conditions) should be noticed as well, which have been summarized in this paper. To address various influencing factors, it is essential to suggest practical and efficient preventive measures. Among these, increased ventilation, particularly the fresh air (i.e., natural ventilation), has proven to effectively reduce indoor infection risk. Many preventive measures are also effective, such as enlarging social distance, avoiding face-to-face orientation, setting up physical partitions, disinfection, avoiding talking, and so on. As research on the epidemic has intensified, people have broken down many perceived barriers, but more comprehensive studies on monitoring systems and prevention measures in land public transport are still needed.

Numerical performance of CO2 accumulation and droplet dispersion from a cough inside a hospital lift under different ventilation strategies

The impact of mechanical ventilation on airborne diseases is not completely known. The recent pandemic of COVID-19 clearly showed that additional investigations are necessary. The use of computational tools is an advantage that needs to be included in the study of designing safe places. The current study focused on a hospital lift where two subjects were included: a healthy passenger and an infected one. The elevator was modelled with a fan placed on the middle of the ceiling and racks for supplying air at the bottom of the lateral wall. Three ventilation strategies were evaluated: a without ventilation case, an upwards-blowing exhausting fan case and a downwards-blowing fan case. Five seconds after the elevator journey began, the infected person coughed. For the risk assessment, the CO2 concentration, droplet removal performance and dispersion were examined and compared among the three cases. The results revealed some discrepancies in the selection of an optimal ventilation strategy. Depending on the evaluated parameter, downward-ventilation fan or no ventilation strategy could be the most appropriate approach.

Generative design for COVID-19 and future pathogens using stochastic multi-agent simulation

We propose a generative design workflow that integrates a stochastic multi-agent simulation with the intent of helping building designers reduce the risk posed by COVID-19 and future pathogens. Our custom simulation randomly generates activities and movements of individual occupants, tracking the amount of virus transmitted through air and surfaces from contagious to susceptible agents. The stochastic nature of the simulation requires that many repetitions be performed to achieve statistically reliable results. Accordingly, a series of initial experiments identified parameter values that balanced the trade-off between computational cost and accuracy. Applying generative design to a case study based on an existing office space reduced the predicted transmission by around 10% to 20% compared with a baseline set of layouts. Additionally, a qualitative examination of the generated layouts revealed design patterns that may reduce transmission. Stochastic multi-agent simulation is a computationally expensive yet plausible way to generate safer building designs.

Numerical investigation of airborne infection risk in an elevator cabin under different ventilation designs

Airborne transmission of SARS-CoV-2 via virus-laden aerosols in enclosed spaces poses a significant concern. Elevators, commonly utilized enclosed spaces in modern tall buildings, present a challenge as the impact of varying heating, ventilation, and air conditioning (HVAC) systems on virus transmission within these cabins remains unclear. In this study, we employ computational modeling to examine aerosol transmission within an elevator cabin outfitted with diverse HVAC systems. Using a transport equation, we model aerosol concentration and assess infection risk distribution across passengers' breathing zones. We calculate the particle removal efficiency for each HVAC design and introduce a suppression effect criterion to evaluate the effectiveness of the HVAC systems. Our findings reveal that mixing ventilation, featuring both inlet and outlet at the ceiling, proves most efficient in reducing particle spread, achieving a maximum removal efficiency of 79.40% during the exposure time. Conversely, the stratum ventilation model attains a mere removal efficiency of 3.97%. These results underscore the importance of careful HVAC system selection in mitigating the risk of SARS-CoV-2 transmission within elevator cabins.

A review on indoor airborne transmission of COVID-19– modelling and mitigation approaches

In the past few years, significant efforts have been made to investigate the transmission of COVID-19. This paper provides a review of the COVID-19 airborne transmission modeling and mitigation strategies. The simulation models here are classified into airborne transmission infectious risk models and numerical approaches for spatiotemporal airborne transmissions. Mathematical descriptions and assumptions on which these models have been based are discussed. Input data used in previous simulation studies to assess the dispersion of COVID-19 are extracted and reported. Moreover, measurements performed to study the COVID-19 airborne transmission within indoor environments are introduced to support validations for anticipated future modeling studies. Transmission mitigation strategies recommended in recent studies have been classified to include modifying occupancy and ventilation operations, using filters and air purifiers, installing ultraviolet (UV) air disinfection systems, and personal protection compliance, such as wearing masks and social distancing. The application of mitigation strategies to various building types, such as educational, office, public, residential, and hospital, is reviewed. Recommendations for future works are also discussed based on the current apparent knowledge gaps covering both modeling and mitigation approaches. Our findings show that different transmission mitigation measures were recommended for various indoor environments; however, there is no conclusive work reporting their combined effects on the level of mitigation that may be achieved. Moreover, further studies should be conducted to understand better the balance between approaches to mitigating the viral transmissions in buildings and building energy consumption.

Finding the proper position of supply and return registers of air condition system in a conference hall in term of COVID-19 virus spread

The outbreak of the COVID-19 has affected all aspects of people's lives around the world. As air transmits the viruses, air-conditioning systems in buildings, surrounded environments, and public transport have a significant role in restricting the transmission of airborne pathogens. In this paper, a computational fluid dynamic (CFD) model is deployed to simulate the dispersion of the COVID-19 virus due to the coughing of a patient in a conference hall, and the effect of displacement of supply and return registers of the air conditioning system is investigated. A validated Eulerian-Lagrangian CFD model is used to simulate the airflow in the conference hall. The particles created by coughing are droplets of the patient's saliva that contain the virus. Three cases with different positions of supply and return registers have been compared. The simulation results show that case1 has the best performance; since after 80 s in case 1 that the inlet registers are in the longitudinal wall, the whole particles are removed from space. However, in other cases, some particles are still in space.

The Trade-Off between Airborne Pandemic Control and Energy Consumption Using Air Ventilation Solutions

Airborne diseases cause high mortality and adverse socioeconomic consequences. Due to urbanization, more people spend more time indoors. According to recent research, air ventilation reduces long-range airborne transmission in indoor settings. However, air ventilation solutions often incur significant energy costs and ecological footprints. The trade-offs between energy consumption and pandemic control indoors have not yet been thoroughly analyzed. In this work, we use advanced sensors to monitor the energy consumption and pandemic control capabilities of an air-conditioning system, a pedestal fan, and an open window in hospital rooms, classrooms, and conference rooms. A simulation of an indoor airborne pandemic spread of Coronavirus (COVID-19) is used to analyze the Pareto front. For the three examined room types, the Pareto front consists of all three air ventilation solutions, with some ventilation configurations demonstrating significant inefficiencies. Specifically, air-conditioning is found to be efficient only at a very high energy cost and fans seem to pose a reasonable alternative. To conclude, a more informed ventilation policy can bring about a more desirable compromise between energy consumption and pandemic spread control.

Numerical modeling of sneeze airflow and its validation with an experimental dataset

In this study, we aimed at providing datasets using experimental results to validate the sneeze airflow. In addition, the boundary conditions for the sneeze simulation that could reproduce the sneeze airflow in the experimental results are presented and reviewed. The validation datasets were created by performing ensemble-average analysis with the experimental results of particle image velocimetry, and these were used to explore the boundary conditions to reproduce the sneeze airflow. As a result of the sneeze airflow reproduced by computational fluid dynamics simulation, the magnitude ranges of maximum velocity at the interface were observed to be 21.1-23.9 m/s for males and 17.9-20.3 m/s for females, which were higher than those of coughing. Compared with the experimental results, the root-mean-square error range for the overall airflow distribution was 0.19-0.23 m/s, whereas the error range for the magnitude of the maximum velocity at a criterion point was 0.03-0.08 m/s. The total sneezing airflow volume was in the range of 0.36-0.48 L, which was relatively low compared with that of coughing. Thus, this study provides important fundamental boundary conditions for computational fluid dynamics analysis, validated by experimental results, to interpret the spread of infectious particles by sneezing.

A numerical approach for preventing the dispersion of infectious disease in a meeting room

Airborne transmission of respiratory aerosols carrying infectious viruses has generated many concerns about cross-contamination risks, particularly in indoor environments. ANSYS Fluent software has been used to investigate the dispersion of the viral particles generated during a coughing event and their transport dynamics inside a safe social-distance meeting room. Computational fluid dynamics based on coupled Eulerian-Lagrangian techniques are used to explore the characteristics of the airflow field in the domain. The main objective of this study is to investigate the effects of the window opening frequency, exhaust layouts, and the location of the air conditioner systems on the dispersion of the particles. The results show that reducing the output capacity by raising the concentration of suspended particles and increasing their traveled distance caused a growth in the individuals' exposure to contaminants. Moreover, decreasing the distance between the ventilation systems installed location and the ceiling can drop the fraction of the suspended particles by over 35%, and the number of individuals who are subjected to becoming infected by viral particles drops from 6 to 2. As well, the results demonstrated when the direction of input airflow and generated particles were the same, the fraction of suspended particles of 4.125%, whereas if the inputs were shifted to the opposite direction of particle injection, the fraction of particles in fluid increased by 5.000%.

Evaluating risk of SARS-CoV-2 infection of the elderly in the public bus under personalized air supply

In developing countries, public transportation is the first choice for the elderly because of its convenience and cheapness. The high density population of public transportation increases the risk of passengers contracting infectious diseases, so it is extremely critical to determine healthy transportation systems to safeguard the health of passengers. The propagation characteristics of droplets in the ZK-type public bus were studied by computational fluid simulation employing the Realizable k-ε turbulence model and discrete phase model. The modified Wells-Riley model was used to quantitatively assess the infection risk of SARS-CoV-2 spread by droplets on the elderly. The risk assessment shows that when the personalized air supply angle is 30°, the number of infected passengers is the least, reaching 14, which shows that the infection risk of passengers can be reduced through the design of personalized air supply angle. Regardless of the angle of the personalized air supply, the rear seats are in a low-risk area. Therefore, it's recommended that elderly passengers choose the rear seats of the public bus during the epidemic to prevent being infected. This study can provide a reference for healthy transportation systems to construct a healthy environment inside the public bus.

Multi-objective performance assessment of HVAC systems and physical barriers on COVID-19 infection transmission in a high-speed train

A computational fluid dynamics (CFD) simulation was performed to model and study the transmission risk associated with cough-related SARS-CoV-2 droplets in a real-world high-speed train (HST). In this study, the evaporating of the droplets was considered. Simulation data were post-processed to assess the fraction of the particles deposited on each passenger's face and body, suspended in air, and escaped from exhausts. Firstly, the effects of temperature, relative humidity, ventilation rate, injection source, exhausts' location and capacity, and adding the physical barriers on evaporation and transport of respiratory droplets are investigated in long distance HST. The results demonstrate that overall, 6–43% of the particles were suspended in the cabin after 2.7 min, depending on conditions, and 3–58% of the particles were removed from the cabin in the same duration. Use of physical barriers and high ventilation rate is therefore recommended for both personal and social protection. We found more exhaust capacity and medium relative humidity to be effective in reducing the particles' transmission potential across all studied scenarios. The results indicate that reducing ventilation rate and exhaust capacity, increased aerosols shelf time and dispersion throughout the cabin.

Data analytics during pandemics: a transportation and location planning perspective

The recent COVID-19 pandemic once again showed the value of harnessing reliable and timely data in fighting the disease. Obtained from multiple sources via different collection streams, an immense amount of data is processed to understand and predict the future state of the disease. Apart from predicting the spatio-temporal dynamics, it is used to foresee the changes in human mobility patterns and travel behaviors and understand the mobility and spread speed relationship. During this period, data-driven analytic approaches and Operations Research tools are widely used by scholars to prescribe emerging transportation and location planning problems to guide policy-makers in making effective decisions. In this study, we provide a review of studies which tackle transportation and location problems during the COVID-19 pandemic with a focus on data analytics. We discuss the major data collecting streams utilized during the pandemic era, highlight the importance of rapid and reliable data sharing, and give an overview of the challenges and limitations on the use of data.

Influence of indoor airflow on particle spread of a single breath and cough in enclosures: Does opening a window really 'help'?

The spread of respiratory diseases via aerosol particles in indoor settings is of significant concern. The SARS-CoV-2 virus has been found to spread widely in confined enclosures like hotels, hospitals, cruise ships, prisons, and churches. Particles exhaled from a person indoors can remain suspended long enough for increasing the opportunity for particles to spread spatially. Careful consideration of the ventilation system is essential to minimise the spread of particles containing infectious pathogens. Previous studies have shown that indoor airflow induced by opened windows would minimise the spread of particles. However, how outdoor airflow through an open window influences the indoor airflow has not been considered. The aim of this study is to provide a clear understanding of the indoor particle spread across multiple rooms, in a situation similar to what is found in quarantine hotels and cruise ships, using a combination of HVAC (Heating, Ventilation and Air-Conditioning) ventilation and an opening window. Using a previously validated mathematical model, we used 3D CFD (computational fluid dynamics) simulations to investigate to what extent different indoor airflow scenarios contribute to the transport of a single injection of particles ( 1 . 3 μ m ) in a basic 3D multi-room indoor environment. Although this study is limited to short times, we demonstrate that in certain conditions approximately 80% of the particles move from one room to the corridor and over 60% move to the nearby room within 5 to 15 s. Our results provide additional information to help identifying relevant recommendations to limit particles from spreading in enclosures.

Numerical Investigation on the Droplet Dispersion inside a Bus and the Infection Risk Prediction

COVID-19 can be easily transmitted to passengers by inhaling exhaled droplets from the infected person in a bus. Therefore, studying droplet dispersion would provide further insight into the mechanism of virus transmission and predict the risk of infection among passengers on a bus. In this research, a bus equipped with air-conditioning was employed as the research object. To determine the dispersion path, concentration distribution, and escape time of the droplets, computational fluid dynamic (CFD) was applied to simulate the flow field and the droplets’ dispersion. The effect of the air supply rate, the location of vents, and the location of infected persons on the dispersion were discussed. Based on the distribution of droplets in the cabin calculated by CFD, a superposition method was used to determine the number of virus particles inhaled by every individual passenger over a four-hour journey. Then, infection risk was assessed by the Wells-Riley equation for all the passengers in the cabin after the whole journey. The results show that the distribution of droplets in the cabin is greatly influenced by the location of the infected person, and the airflow pattern is highly associated with the air supply rate and the location of vents. The infection risk of passengers located at the droplet dispersion path and the distance from the infected persons less than 2.2 m is over 10%. The increase in the air supply rate could speed up the spread of the droplets but at the same time, it could reduce the infection risk.

Airborne transmission of COVID-19 virus in enclosed spaces: An overview of research methods

Since the outbreak of COVID-19 in December 2019, the severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) has spread worldwide. This study summarized the transmission mechanisms of COVID-19 and their main influencing factors, such as airflow patterns, air temperature, relative humidity, and social distancing. The transmission characteristics in existing cases are providing more and more evidence that SARS CoV-2 can be transmitted through the air. This investigation reviewed probabilistic and deterministic research methods, such as the Wells-Riley equation, the dose-response model, the Monte-Carlo model, computational fluid dynamics (CFD) with the Eulerian method, CFD with the Lagrangian method, and the experimental approach, that have been used for studying the airborne transmission mechanism. The Wells-Riley equation and dose-response model are typically used for the assessment of the average infection risk. Only in combination with the Eulerian method or the Lagrangian method can these two methods obtain the spatial distribution of airborne particles' concentration and infection risk. In contrast with the Eulerian and Lagrangian methods, the Monte-Carlo model is suitable for studying the infection risk when the behavior of individuals is highly random. Although researchers tend to use numerical methods to study the airborne transmission mechanism of COVID-19, an experimental approach could often provide stronger evidence to prove the possibility of airborne transmission than a simple numerical model. All in all, the reviewed methods are helpful in the study of the airborne transmission mechanism of COVID-19 and epidemic prevention and control.

On male urination and related environmental disease transmission in restrooms: From the perspectives of fluid dynamics

Indoor transmission of COVID-19 is highly probable. Multiple sources have verified that the SARS-CoV-2 can be detected within toilets, and people can be infected in restrooms. There is a huge gap in the coronavirus transmission mechanism in restrooms. Understanding it can help to flatten the curve of the infected cases as well as prevent other viruses transmitted through the sewage or human body fluid. Previous studies have shown how simple actions in daily life (coughing, sneezing, or toilet flushing) contribute to virus transmission. This paper visually and quantitatively demonstrates that male urination, which is also a daily action, can agitate virus particles within the toilet and raise them, which may be the main promoter of cross-infection of COVID-19 in restrooms. Adopting numerical and experimental methods, we demonstrate that male urination can cause strong turbulent flow with an averaged urine impinging velocity of 2.3 m/s, which can act as an agitator to raise the virus particles. The climbing velocity of the airflow can be 0.75-1.05 m/s. The observed upwards flow will disturb and spread any lurking virus particles (not limited to SARS-CoV-2). Experiments demonstrated that the concentration of the airborne particle could be tripled during male urination. Corresponding precautions are offered as well to prepare the public to act properly when and after using facilities in restrooms for preventing emerging and re-emerging pandemics not limited to the current COVID-19, contributing to the sustainability of human society.

On the Critical Role of Human Feces and Public Toilets in the Transmission of COVID-19: Evidence from China

The surprising spread speed of the COVID-19 pandemic creates an urgent need for investigating the transmission chain or transmission pattern of COVID-19 beyond the traditional respiratory channels. This study therefore examines whether human feces and public toilets play a critical role in the transmission of COVID-19. First, it develops a theoretical model that simulates the transmission chain of COVID-19 through public restrooms. Second, it uses stabilized epidemic data from China to empirically examine this theory, conducting an empirical estimation using a two-stage least squares (2SLS) model with appropriate instrumental variables (IVs). This study confirms that the wastewater directly promotes the transmission of COVID-19 within a city. However, the role of garbage in this transmission chain is more indirect in the sense that garbage has a complex relationship with public toilets, and it promotes the transmission of COVID-19 within a city through interaction with public toilets and, hence, human feces. These findings have very strong policy implications in the sense that if we can somehow use the ratio of public toilets as a policy instrument, then we can find a way to minimize the total number of infections in a region. As shown in this study, pushing the ratio of public toilets (against open defecation) to the local population in a city to its optimal level would help to reduce the total infection in a region.