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Three-dimensional numerical modeling for assessing airborne infection risk in hospital waiting rooms with various ventilation approaches
(2026-06-01)
Suebyat, Kewalee
;
Pochai, Nopparat
;
Sooknum, Jenjira
;
Oyjinda, Pravitra
Airborne infectious diseases, such as COVID-19, TB, MERS, and SARS, constitute a profound threat to public health and quality of life. These pathogens are transmitted primarily via atmospheric particles, especially within clinical environments, where they often circulate. Effective ventilation controls to mitigate pathogens and air pollution are thus essential for reducing hospital-based transmission of airborne infections. The purpose of this research is to assess the risk of airborne infectious diseases within a hospital in Thailand using a mathematical model. Specifically, the finite difference technique is employed to estimate carbon dioxide (CO<inf>2</inf>) concentration as a proxy for indoor air quality to indicate and assess the risk of airborne infectious diseases. The hospital layout is categorized into waiting areas and circulation areas with disparate occupant densities. Three simulation scenarios are conducted, accounting for variations in ventilation rates and architectural structure of hospitals. The results of this research demonstrate that CO<inf>2</inf> concentration can be effectively quantified as a proxy for indoor air quality within hospital environments. These calculated CO<inf>2</inf> levels are subsequently used to model the risk of airborne infection at a hospital, providing a robust framework for assessing this risk. Crucially, by integrating ventilation dynamics that reflect the physical constraints and structure of the hospital, this research enables precise evaluation of infection risks. The findings indicate that ventilation control can reduce the incidence of airborne infection, with significant practical utility in real-world clinical settings.
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A mathematical model for the risk analysis of airborne infectious disease in an outpatient room with personal classification factor
(2020-12-01)
Suebyat, Kewalee
;
Oyjinda, Pravitra
;
Konglok, Sureerat A.
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Pochai, Nopparat
Every day, a large number of people will use a hospital, creating a main air quality problem which may mean the risk of airborne infectious disease contamination in outpatient rooms, and affects human health. TB, COVID-19, MERS, and SARS are a hazardous communicable disease which are spread from person to person through the air or the aerosol in different ways, such as through coughing, spitting, sneezing, speaking, or through wounds. US scientists in the laboratory have shown that the virus can live in an aerosol and remain infectious for at least 3 hours. A new human coronavirus now known as the serious acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (formerly known as HCoV-19) emerged in late 2019 in Wuhan, China, and is now triggering a pandemic. COVID-19, TB, MERS and SARS-threats and opportunities progress against deadly infection make more people sick in the hospital. Therefore, we should be aware of the care and control of these diseases. Consequently, good air quality management is required to control and reduce possible infected air, such as carbon dioxide (CO2) concentration. In this research, a mathematical model for the risk analysis of airborne infectious disease in an outpatient room is proposed. Not only considering one type of person but also in this research, people are considered according to personal classifications. There are 4 types-patient, relative, worker, and outsider, staying in an outpatient room, which is in accordance with the real world. Air quality control manipulations are simulated using the inlet and outlet ventilation rates adjustment under the condition of a number of surrounding people with a personal classified factor. The fourth-order Runge-Kutta (RK4) is used to approximate the model solution. The proposed numerical model can be used to describe the dynamical dispersion of airborne infectious disease in an outpatient room. The results of the model are satisfactory, and it will be able to control airborne disease in more complicated structures.
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Three-dimensional air quality assessment simulations inside sky train platform with airflow obstacles on heavy traffic road
(2018-07-01)
Suebyat, Kewalee
;
Pochai, Nopparat
Air pollutant levels in Bangkok are generally high in street tunnels. They are particularly elevated in almost closed street tunnels such as an area the Bangkok sky train platform with high traffic volume where dispersion is limited. This area has no air quality measurement stations even though there is a high percentage of people living around this vicinity. We are interested to conduct a research the Bangkok sky train platform due to the traffic density and enormous polluted areas. Therefore, we proposed a numerical modeling of air pollution concentration in sky train platform with airflow obstacles on heavy traffic road as an approximated solution of the three-dimensional advection-diffusion equation by using the finite difference methods. Our research presentation is based on how air pollution model depends on the flow of air pollution and wind directions including the governing equation of the corresponding three-dimensional advection-diffusion equation is presented. This also includes the initial condition and boundary conditions of traffic and polluted areas. In order to illustrate the performance of the model, the numerical experiments are presented. The comparison between the two methods and the simulations of air pollution control are proposed. The three-dimensional advection-diffusion equation is solved by using the Forward Time, Centered Space (FTCS) and Forward Time, Backward Space (FTBS) schemes. The results obtained indicate that the FTCS method provides a better result than FTBS method. Furthermore, the proposed experimental variations of the boundary condition in the entrance gate do affect the air pollutant concentration of each floor.
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Numerical simulation for a three-dimensional air pollution measurement model in a heavy traffic area under the Bangkok sky train platform
(2018-01-01)
Suebyat, Kewalee
;
Pochai, Nopparat
Air pollutant levels in Bangkok are generally high in street tunnels. They are particularly elevated in almost closed street tunnels such as an area under the Bangkok sky train platform with high traffic volume where dispersion is limited. There are no air quality measurement stations in the vicinity, while the human population is high. In this research, the numerical simulation is used to measure the air pollutant levels. The three-dimensional air pollution measurement model in a heavy traffic area under the Bangkok sky train platform is proposed. The finite difference techniques are employed to approximate the modelled solutions. The vehicle air pollutant emission due to the high traffic volume is mathematically assumed by the pollutant sources term. The simulation is also considered in averaged and moving pollutant sources due to manner vehicle emission. The proposed approximated air pollutant concentration indicators can be replaced by user required gaseous pollutants indices such as NOx, SO2, CO, and PM2.5.
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A numerical simulation of a three-dimensional air quality model in an area under a Bangkok sky train platform using an explicit finite difference scheme
(2017-11-01)
Suebyat, Kewalee
;
Pochai, Nopparat
One of the air pollution problems in areas under Bangkok sky train platforms are caused by the pollutant coming from the entrance to the tunnel. It increases the concentration of pollutant. This affects the well-being of humans and the environment. In this research, the governing equation of the air quality model in a considered area is a three-dimensional advection-diffusion equation with time dependence. A finite difference technique is employed to approximate the solution of the governing equation. This model is solved by using an explicit forward difference in time and central difference in space (FTCS). We consider the wind inflow in two cases: there is wind inflow only in x-direction and there are wind inflow in x- direction and y-direction. In addition, we added obstacles such as the columns along the middle into the tunnel. The results of the model are satisfactory. It will be able to be implemented on a problem of air pollution control in a more complicated tunnel.

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