Since the beginning of March 2022, a new round of COVID-19 outbreaks in Shanghai has led to a sharp increase in the number of infected people. It is important to identify possible pollutant transmission routes and predict potential infection risks for infectious diseases. Therefore, this study investigated the cross-diffusion of pollutants caused by natural ventilation, including external windows and indoor ventilation windows, under three wind directions in a densely populated building environment with the CFD method. In this study, CFD building models were developed based on an actual dormitory complex and surrounding buildings under realistic wind conditions to reproduce the airflow fields and transmission paths of pollutants. This paper adopted the Wells–Riley model to assess the risk of cross-infection. The biggest risk of infection was when a source room was located on the windward side, and the risk of infection in other rooms on the same side as the source room was large in the windward direction. When pollutants were released from room 8, north wind resulted in the highest concentration of pollutants in room 28, reaching 37.8%. This paper summarizes the transmission risks related to the indoor and outdoor environments of compact buildings.

Indoor radon exposure has been an increasing concern in recent years due to its health risks, like lung cancer and leukemia. Indoor radon exposure levels can be determined through measurement but with limitations. An increasing number of studies have started to apply simulation methods to assess indoor radon exposure levels in recent decades. To better understand currently available approaches for estimating indoor radon exposure, we conducted a systematic review of the current available methods for estimating the indoor radon levels. Through the search and screening of databases, a total of 28 related articles were included. The results show that the main methods for indoor radon estimation are mathematical models, statistical methods, and the geographic information system (GIS) method. The factors to consider include completion time, building type, floor area, number of floors, soil texture, building materials, and degree of urbanization. This paper, through its review of radon exposure level estimation and assessment methods, provides a more systematic understanding of this field, with important implications for accurately estimating the spatial and time distribution of indoor radon exposure and its health risks.

In real urban environments, wind velocities often exhibit significant time-dependent variations. However, the impact of these fluctuations on ventilation performance is not frequently addressed in the literature. To accurately predict the building ventilation performance, this paper intends to elucidate the influence of the unsteady approaching flow. Four distinct inflows, characterized by periodic sinusoidal fluctuations, are evaluated using large-eddy simulation (LES). A single-sided building model with natural ventilation is constructed and validated through a wind tunnel experiment. Four periodic inflows consist of combinations of two frequencies (f = 0.1 and 0.3 Hz) and two amplitudes (A = 0.06 and 0.09). This paper mainly compares the results of airflow patterns and ventilation performance with those of stable inflows. The results indicate that periodic inflows cause greater fluctuations in the velocity fields on the leeward side. At higher frequencies and lower amplitudes, the vertical distribution of indoor bottom vortices is relatively dispersed. It shows that periodic flows lead to noticeable changes in the ventilation rate, with a deviation between instantaneous and average Q* ranging from 13.8% to 16.5%. Compared to the stable inflow, the impacts of periodic inflows on ventilation performance vary over time; 6% and 9% variations in incoming velocities result in deviations of up to 17.5% in ventilation rates. The frequencies and amplitudes of the periodic inflows do not exhibit a linear relation with ventilation rate. Therefore, it is prudent to be cautious about adopting averaged incoming wind velocities in predicting ventilation performance. This study helps in the more accurate prediction of single-sided natural ventilation.

A ventilation system with a constant velocity air supply might form airflow stagnant zones in industrial plants, making it challenging to dilute hazardous gas effectively. In this study, a novel ventilation mode called pulsating ventilation, which can potentially dilute the hazardous gas better, was applied in a ventilated room with nozzle air supply. Three different scenarios of gas accumulation were assumed, with the location of gas accumulation situated at the rear, near the floor, and in the corners of the room. Both the distribution of CO2 concentration and the efficiency of reducing the indoor CO2 concentration to the safety threshold were analyzed to evaluate the ventilation performance of pulsating ventilation. The results showed that pulsating ventilation outperformed constant velocity air supply in expeditiously eradicating gas accumulation areas for equivalent total air volumes. When the gas accumulation areas were located at the rear of the room, close to the floor, and in the corner of the room, pulsation ventilation reduced the time for the indoor CO2 concentration to drop to the safety threshold by 36.19%, 27.23%, and 36.25%, respectively. Holding the period constant, an increased amplitude correlated with a swifter decrease in peak pollutant concentration. Except for the case where the gas accumulation areas are close to the floor, when the amplitude is constant, the larger the period, the faster the peak concentration in the gas accumulation areas decreases.

Natural ventilation, a critical passive design strategy for indoor environmental regulation and urban pollution mitigation, relies heavily on dynamic wind patterns. However, existing studies predominantly focus on steady or averaged wind directions, often overlooking transient effects caused by time-varying wind direction fluctuations. This study addresses this gap by proposing a novel dynamic wind direction meshing framework integrated into large eddy simulation in computational fluid dynamics simulations to investigate how time-dependent wind direction variations influence natural ventilation efficiency and pollutant dispersion in isolated buildings. The model divides the computational domain into a steady zone and a dynamically rotating zone, enabling realistic wind direction variability while preserving computational efficiency. Validation against wind tunnel experiments confirmed high accuracy. Results indicate that even minor directional fluctuations (1° amplitude) reduce ventilation rates by 13.13% compared to steady wind conditions, whereas larger amplitudes (40°) exacerbate pollutant retention, with relative concentration errors exceeding 150%. Frequency variations (5–40 s periods) exhibited negligible impacts relative to amplitude-driven effects. Dynamic wind fields altered airflow by suppressing shear layer separation and forming transient low-pressure vortices, which disrupted pollutant diffusion pathways. A linear regression model quantified amplitude-dependent ventilation decay, offering predictive capabilities for dynamic wind scenarios. These findings highlight the necessity of incorporating short-term wind direction variability into urban airflow models to enhance building ventilation efficiency and pollutant dispersion. The proposed framework establishes a scalable methodology for ventilation design, providing physical insights to optimize airflow patterns and pollutant dispersion under time-dependent wind variability.

Pulsating ventilation has been drawing extensive attention recently. Computational fluid dynamics (CFD), as a widely used and effective tool for investigating pulsating ventilation, often consumes significant computation time. To identify a suitable numerical scheme for this circumstance, we adopted the standard incremental pressure-correction (SIPC) method with higher-order temporal discretization schemes to simulate indoor airflow. To further improve the simulation efficiency, two adaptive time step size schemes were proposed and used to simulate both long-period and short-period pulsating ventilation conditions. Results showed that the SIPC scheme offers accuracy comparable to the PISO (pressure-implicit with splitting of operators) algorithm while saving about 40% of computation time. Higher-order temporal discretization schemes have minimal impact on the accuracy and stability of the SIPC scheme for simulating pulsating airflow, with the first-order Euler backward implicit scheme showing slightly higher efficiency. Compared to the conventional fixed time step size scheme (fixed scheme), both adaptive time step size schemes significantly reduce computation time with negligible impact on accuracy. The scheme that controls time step size based on a given maximum Courant number (MaxCo scheme) saves about 35% of computation time, while the scheme that combines a given maximum Courant number with the curvature of the inlet velocity-time curve (MaxCo+K scheme) to control time step size saves nearly 30%. Although the MaxCo+K scheme requires about 10% more computation time than the MaxCo scheme, it improved accuracy by approximately 10% by more accurately capturing the inlet velocity boundary condition in the short-period pulsating ventilation simulation.