Transmission characteristics of respiratory droplets aerosol in indoor environment: an experimental study

Li, Yanju; Wu, Chunbin; Cao, Guoqing; Guan, Dexing; Zhan, Chaoguo

doi:10.1080/09603123.2021.1910629

Cited by 9 publications

(7 citation statements)

References 57 publications

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“…Other types of experimental studies have also been conducted on virus transmission. For example, Li et al 116 used an active bacterial agent to study the spatial concentration distribution and airborne transmission of a respiratory droplet aerosol. Their experimental study also explored the effects of the ventilation rate and droplet aerosol production rate on infectious disease control.…”

Section: Studies Of Airborne Covid‐19 Transmission In Indoor Spacesmentioning

confidence: 99%

“…The results of the above experiments indicated that the experimental approach of using virus-laden particle substitutes, such as DEHS droplets or particles produced by sandalwood combustion, is suitable for studying the airborne transmission mechanism of the virus.Other types of experimental studies have also been conducted on virus transmission. For example, Li et al116 used an active bacterial agent to study the spatial concentration distribution and airborne transmission of a respiratory droplet aerosol. Their experimental study also explored the effects of the ventilation rate and droplet aerosol production rate on infectious disease control.…”

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confidence: 99%

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

et al. 2022

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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.

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Section: Studies Of Airborne Covid‐19 Transmission In Indoor Spacesmentioning

confidence: 99%

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confidence: 99%

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

et al. 2022

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“…7 Generally, increasing the ventilation rate helps dilute air containing infectious droplets and aerosols within spaces. [12][13][14] However, previous studies have revealed that increased ventilation rates could result in complex airflow distributions that exacerbate the dispersion of infectious particles. 15,16 Strategies that rely solely on elevating the ventilation rate based on the number of occupants within a space have been associated with an increased risk of local viral contamination.…”

Section: Introductionmentioning

confidence: 99%

An indoor airflow distribution predictor using machine learning for a real-time healthy building monitoring system in the tropics

Faridah,

Utami,

Wijaya

et al. 2024

Building Services Engineering Research and Technology

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Indoor air quality is the foundation of a good indoor environment. The COVID-19 pandemic further highlighted the importance of providing real-time airflow distribution information within the Building Environmental Monitoring System (BEMS) to minimize the risk of infectious airborne transmission. This paper discusses the process of developing a predictive model for indoor airflow distribution prediction with indoor and outdoor input parameters using machine learning and its implementation in healthy BEMS for a classroom in the tropical climate region of Yogyakarta, Indonesia. This paper encompassed field measurement and simulation involving outdoor climate conditions and the operational status of the classroom’s windows, Air Conditioning units, and fans. Three machine learning models were constructed using OLS, LASSO, and Ridge methods. Datasets for the modeling were generated from CFD model simulations in IES VE and were assessed for correlation. The mean temperature and velocity differences between the CFD model simulation and measurement results are 0.21°C and 0.083 m/s, respectively. Outdoor climate conditions and the operational status of the classroom’s utilities significantly influence the indoor airflow distribution characteristics. The three models indicate a relatively poor performance, where the classroom had a relatively low sensitivity to input changes. However, the best model performance was achieved using the LASSO method, with average values from post-normalization of [Formula: see text] and Root Mean Square Error (RMSE) of 0.336 and 0.077, respectively. The model was implemented in healthy BEMS on the “Platform for Healthy and Energy Efficient Building Management System.” Practical Application: This research proposed a machine learning model of indoor airflow characteristics of a classroom in Yogyakarta. The proposed model can be adapted to produce monitoring systems that best represent the related conditions. The method can be adopted to develop a relatively simple, low-cost sensor or model to monitor an indoor environment. Future studies may explore the results of the real-world implementation in a case study.

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“…Researchers have previously studied the relationship between indoor ventilation and airborne particle aerosol transmission at different locations, including elevators [ 6 , 7 ], conference rooms [ 8 ], large rooms [ 9 , 10 ], fever clinics [ 11 ], hospital isolation rooms [ 12 ], medical centers [ 13 ], and supermarkets [ 14 ]. Moreover, many studies have focused on the transmission characteristics and infection tendency of droplets exhaled by people in transportation environments such as airplanes [ 13 ], long-distance buses [ 13 , 15 ], and high-speed rail carriages [ 16 ].…”

Section: Introductionmentioning

confidence: 99%

Impacts of human movement and ventilation mode on the indoor environment, droplet evaporation, and aerosol transmission risk at airport terminals

Zhao

Yao

2022

Building and Environment

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Transmission characteristics of respiratory droplets aerosol in indoor environment: an experimental study

Cited by 9 publications

References 57 publications

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

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

An indoor airflow distribution predictor using machine learning for a real-time healthy building monitoring system in the tropics

Impacts of human movement and ventilation mode on the indoor environment, droplet evaporation, and aerosol transmission risk at airport terminals

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