Sen Nirvik, Singh Krishna Kumar
Chemical Engineering Division, Bhabha Atomic Research Centre, Trombay, Mumbai, 400085, India.
Environ Sci Pollut Res Int. 2025 Mar;32(14):9103-9124. doi: 10.1007/s11356-025-36245-2. Epub 2025 Mar 19.
We report a 3D Euler-Lagrangian CFD model to quantify the dispersion and transport of aerosols in a moving, semi-open auto rickshaw. The vehicle has a driver at the front, with two passengers seated behind in the rear section. This mode of transport is commonly seen in developing countries across Asia and Africa. Aerosol particles are generated due to the continuous, unmasked speaking of a passenger inside the auto rickshaw. The Eulerian portion of the model has been validated against reported experimental data on flow fields in enclosures with and without obstacles. Three RANS-based turbulence models-standard k-ε, realizable k-ε, and SST k-ω-are compared with experimental data, and the standard k-ε model is found to be the most suitable. Since the sides of the auto rickshaw are open, there is significant air exchange with the surroundings, which greatly affects the spread of aerosol particles. The presence of a partition between the driver and the passenger compartment reduces the probability of infection transmission from 1 to 0. A decrease in the auto rickshaw's speed from 60 to 20 km/h also reduces the probability of spread from 1 to 0. Additionally, a lateral wind (perpendicular or oblique to the direction of travel) further decreases the probability of transmission from 1 to 0. For all cases, the face velocity for all passengers is computed. The state of dispersion is significantly influenced by the location of aerosol generation. The relative importance of the different scenarios studied is quantified. Finally, a set of recommendations is outlined and compared with those reported for other modes of public transport.
我们报告了一个三维欧拉-拉格朗日计算流体动力学（CFD）模型，用于量化在行驶的半开放式自动人力车中气溶胶的扩散和传输。该车前部有一名司机，后部有两名乘客就座。这种交通方式在亚洲和非洲的发展中国家很常见。气溶胶颗粒是由于自动人力车内一名乘客持续、未戴口罩讲话而产生的。该模型的欧拉部分已根据有无障碍物的封闭空间内流场的实验数据进行了验证。将三种基于雷诺平均纳维-斯托克斯（RANS）的湍流模型——标准k-ε模型、可实现k-ε模型和剪切应力输运（SST）k-ω模型——与实验数据进行了比较，发现标准k-ε模型最为合适。由于自动人力车的侧面是开放的，与周围环境有大量的空气交换，这极大地影响了气溶胶颗粒的扩散。司机和乘客舱之间设置隔板会使感染传播的概率从1降至0。自动人力车速度从60公里/小时降至20公里/小时也会使传播概率从1降至0。此外，侧向风（垂直或斜向行驶方向）会进一步降低传播概率，从1降至0。对于所有情况，都计算了所有乘客的面部风速。气溶胶生成位置对扩散状态有显著影响。对所研究的不同场景的相对重要性进行了量化。最后，概述了一套建议，并与其他公共交通方式的建议进行了比较。
