Computational fluid dynamics-based optimal installation strategy of air purification system to minimize NOX exposure inside a public bus stop

Fomite disinfection using spray systems: A computational multi-physics framework

Disinfecting inanimate objects or materials carrying infectious agents, i.e., fomites, using spray systems reduces healthcare-associated infections in medical settings and community-acquired infections in non-medical environments. However, an accurate prediction of such systems is challenging as these systems embrace multi-physics phenomena depending on several parameters. Therefore, this paper presents a computational modeling-based multi-physics framework to evaluate the performance and effectiveness of spray systems employed in disinfecting fomites with non-porous hydrophilic surfaces. The framework includes four key phases: (i) atomizing the liquid disinfectant jet into the disinfectant droplets; (ii) interactions between disinfectant droplets and the surrounding air; (iii) impingements created by the disinfectant droplets on the fomite surface; (iv) interactions between the disinfectant depositions and pathogens causing fomite disinfection. The accuracy of the framework is evaluated using two sets of experimental data on the reduction of viable Bacillus atrophaeus spores over an 1800-second period. The results show that the framework can predict fomite disinfection via spray systems, with the deviations from the measured data being 2.73% and 2.38%. By presenting a detailed perception of the dynamics involved in fomite disinfection, this framework has the potential to improve public health practices and lead to the development of more effective and targeted disinfection strategies in diverse settings.

Indoor pollution control based on surrogate model for residential buildings

Individuals typically spend most of their lives indoors, predominantly in spaces like offices and residences. Consequently, prolonged indoor exposure underscores the critical significance of maintaining optimal indoor air quality (IAQ) to safeguard one's health. The primary impediment to attaining efficient regulation of Indoor Air Quality (IAQ) is the challenge of monitoring the IAQ parameters, particularly within the immediate vicinity of an individual's breathing space. Current heating, ventilation, and air conditioning systems lack the ability to rapidly predict and optimize the quality of indoor air. The objective of this study is to acquire the distribution features of indoor pollutants and precise indoor environment data in order to efficiently forecast and enhance the IAQ. To achieve this objective, a proposed surrogate model was developed using computational fluid dynamics (CFD). Notably, the Kriging surrogate model can rapidly predict IAQ while using a limited number of CFD runs. CFD are widely used as numerical simulation methods to obtain the accurate information. Surrogate models can rapidly forecast indoor environmental conditions using CFD simulation data simultaneously. Optimization algorithms can efficiently achieve desirable indoor ambient conditions, offering highly effective and intelligent control techniques for indoor atmospheric ventilation.

Susceptibility and exposure risk to airborne aerosols in intra-urban microclimate: Evidence from subway system of mega-cities

The health of intra-urban population in modern megacities relies largely on the biosafety within the microclimate of subway system, which can be vulnerable to epidemical challenges brought by virus-laden bioaerosols under varying factors. The literature has yet to address the association between the exposure risks to infectious pathogens and the dynamic changes of boundary conditions in this densely populated microclimate. This study aims at characterizing the bioaerosol dispersion, evaluating the exposure risks under various train arrival scenarios and hazard releasing positions in a real-world double-decker subway station. The results provide the evidence for the dominating airflow pattern, bioaerosols dispersion behaviors, exposure risk, and evacuation guidance in a representative microclimate of mega-cities. The tunnel effects of nearby pedestrian passageways are found to be dominating the airflow pattern, leading to the discharging of airborne bioaerosols. At least 60 % increasing of discharging rate of bioaerosol is attributed to the arrival of one or two trains at the subway platform compared with the scenario with no train arriving. Results from risk assessment with improved Wells-Riley model estimate 57.62 % of maximum infectivity probability with no train arriving. Large areas near the source at the platform floor still cannot be considered safe within 20 min. For the other two scenarios where trains arrive at the platform, the maximum probability of infection is below 5 %. Moreover, the majority of train carriages can be regarded as safe zones, as the ventilation across the screen door are mostly directed towards the platform. Additionally, releasing the bioaerosols at the platform floor poses the most severe threats to human health, and the corresponding evacuation strategies are suggested. These findings offer practical guidance for the design of the intra-urban microclimate, reinforcing the need for exposure reduction device or contingency plans, and providing potential evacuation strategy towards improved health outcomes.