Ventilation might play an important role in airborne transmission. By using the computational fluid dynamics (CFD) method, ventilation modes, ventilation rates, and infection source’s face direction were considered in a multi-person indoor environment (10 m*10 m*3 m). The airflow patterns, virus concentration distribution, and infection probability were studied. The results showed that the virus concentration was lower with displacement ventilation (DV, lower in, upper out) than mixing ventilation (MV, top-centre in, upper out) or natural ventilation (NV, upper in, upper out). In 2 air changes per hour (ACH), the infection risk of susceptible persons in MV and NV might be about 2.43-fold and 1.30-fold more than that in DV. Increased ventilation usually reduces viral concentrations and the risk of infection. For the height of breathing zones, the average virus concentration at 12ACH was 49.78%-78.72% lower than that at 2ACH. For susceptible persons at a distance of about 2.8-4.2 m to a COVID-19 infector with 30 min exposure time, the long-range airborne infection probability might be 11.53% (±5.86) (2ACH), 4.96% (±1.82%) (6ACH), and 2.96% (±1.91%) (12ACH).
Since the outbreak of Coronavirus Disease 2019 , more than 500 million people have been infected by May 2022, causing severe health hazards and economic losses. 1 Many respiratory diseases (influenza, SARS, MERS, and COVID-19) can be transmitted by droplets and aerosols. 2,3 In poorly ventilated indoor environments, large droplets (>50 μm) tend to deposit in seconds to minutes, while small aerosols (<5-10 μm) can suspend for hours, posing a potential risk to susceptible persons. [4][5][6] Since nearly 80% of respiratory infections happen indoors, 7 epidemic control in indoor environments is essential. The transmission mechanisms of exhaled virus-laden droplets 8,9 in indoor environments (restaurants, 10 classrooms, 11 airliner cabins, 12 subway stations 13 ) have been investigated. Since virus concentration generally decreased with distance from the source, a safe distance of about 1.5-2.0 m was widely used. 4,14 In addition, exhaled jets might be locked at a certain height in thermal-stratification indoor environments, strengthening the disease transmission. 15,16 However, many studies only considered scenarios with fixed positions of people, while human movement could significantly change the indoor airflow field and the distribution of virus-laden droplets.The superposition of human-induced airflow and turbulence might
In workplaces such as steel, power grids, and construction, firefighters and other workers often encounter non-uniform high-temperature environments, which significantly increase the risk of local heat stress and local heat discomfort for the workers. In this paper, a multi-segment human bioheat model is developed to predict the human thermal response in asymmetric high-temperature environments by considering the sensitivity of the modeling to angular changes in skin temperature and the effects of high temperatures on human thermoregulatory and physiological responses simultaneously. The extended model for asymmetric high-temperature environments is validated with the current model results and experimental data. The result shows that the extended model predicts the human skin temperature more accurately. Under non-uniform high-temperature conditions, the local skin temperature predictions are highly consistent with the experimental data, with a maximum difference of 2 °C. In summary, the proposed model can accurately predict the temperature of the human core and skin layers. It has the potential to estimate human physiological and thermoregulatory responses under uniform and non-uniform high-temperature environments, providing technical support for local heat stress and local thermal discomfort protection.
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