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<p>This study investigates the dispersion of infectious particles generated during a human coughing event in a consultation clinic. The objective is to identify ventilation strategies that minimize particle exposure to healthcare personnel. A simplified computational fluid dynamics model was developed to represent the consultation clinic environment and its occupants. A customizable coding approach was implemented using user-defined functions to replicate realistic, time-dependent coughing behavior. This approach overcomes the limitations of simplified steady injection methods commonly used in previous studies. The RNG k–ε turbulence model was applied to simulate airflow. The discrete phase model was used to track particle transport. The selection of these models was supported by comprehensive validation against published data. Several ventilation configurations were evaluated to examine their impact on particle concentration near the doctor’s workspace. Results show that a conventional mixing ventilation system effectively reduces particle concentration across the doctor’s working zone. It achieves a minimum value of approximately 1.0 × 10⁻<sup>5</sup>&#xa0;kg/m<sup>3</sup> within a horizontal distance of 0.728&#xa0;m from the cough source. Compared to other ventilation schemes reporting a higher concentration of 1.0 × 10⁻<sup>4</sup>&#xa0;kg/m<sup>3</sup>, the mixing ventilation scheme achieves a tenfold reduction. In contrast, displacement ventilation shows localized particle accumulation near the monitor, despite improved removal along the cough jet path. Overall, the findings indicate that mixing ventilation provides a more uniform and comprehensive reduction in airborne particle concentration. The outcomes offer practical guidance for optimizing ventilation design in hospital consultation environments.</p>

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Airborne transmission of cough droplets: evaluating mitigation strategies and ventilation optimization in consultation clinics

  • 期刊论文

  • 发表日期：

    2026年7月19日

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  • Sien Jie Wong,
  • Hong Yee Kek,
  • Huiyi Tan,
  • Mohd Hafiz Dzarfan Othman,
  • Yee Van Fan,
  • Kok Sin Woon,
  • Bohong Wang,
  • Kai Ying Tan,
  • Nur Dayana Ismail,
  • Keng Yinn Wong

摘要

This study investigates the dispersion of infectious particles generated during a human coughing event in a consultation clinic. The objective is to identify ventilation strategies that minimize particle exposure to healthcare personnel. A simplified computational fluid dynamics model was developed to represent the consultation clinic environment and its occupants. A customizable coding approach was implemented using user-defined functions to replicate realistic, time-dependent coughing behavior. This approach overcomes the limitations of simplified steady injection methods commonly used in previous studies. The RNG k–ε turbulence model was applied to simulate airflow. The discrete phase model was used to track particle transport. The selection of these models was supported by comprehensive validation against published data. Several ventilation configurations were evaluated to examine their impact on particle concentration near the doctor’s workspace. Results show that a conventional mixing ventilation system effectively reduces particle concentration across the doctor’s working zone. It achieves a minimum value of approximately 1.0 × 10⁻5 kg/m3 within a horizontal distance of 0.728 m from the cough source. Compared to other ventilation schemes reporting a higher concentration of 1.0 × 10⁻4 kg/m3, the mixing ventilation scheme achieves a tenfold reduction. In contrast, displacement ventilation shows localized particle accumulation near the monitor, despite improved removal along the cough jet path. Overall, the findings indicate that mixing ventilation provides a more uniform and comprehensive reduction in airborne particle concentration. The outcomes offer practical guidance for optimizing ventilation design in hospital consultation environments.