Evaluation of airborne infection risk with different window airing strategies in classroom

The coronavirus disease may spread by airborne aerosols, especially in a poorly ventilated enclosure. Natural ventilation can reduce the transmission of infection. The WHO suggested the minimum ventilation rate of 10 L/s/person in non-residential settings. The objective was to evaluate risk of airborne infection with different settings in natural ventilated classroom. The risk was evaluated by using the modified Wells-Riley equation associated with the variation of contaminant concentration simulated by a multi-zone airflow model. The results provide the guidance of natural ventilation strategy in the classroom to reduce the transmission of airborne infection disease. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

Development of an automatic window opening system to control the ventilation rate

Under the influence of COVID-19, it is recommended to ventilate to reduce the risk of infection in the room. In an air-conditioned room, window open can increased the ventilation rate that caused by indoor and outdoor temperature difference. However, there is a concern that opening window in the air-conditioned room will increase the heating and cooling load due to air leakage. In addition, it is difficult to maintain the appropriate ventilation rate because the outdoor air temperature changes time to time. To solve this problem, we have developed an automatic window opening system to control the natural ventilation rate. In this study, actual measurements were conducted to understand the operating performance of the system, and its effect on the indoor thermal environment. As a result, it was confirmed that the ventilation rate could be controlled by this system. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

Gravity Settling of Particles and Ventilation Characteristics by Natural Ventilation Method

It has been suggested that COVID-19 causes airborne infection by fine particles called droplet nuclei and reducing the risk of indoor infection by ventilation is attracting attention as an infection control measure. However, the characteristics of fine particles are not considered in indoor ventilation plans, and the behavior and removal effect of particles by ventilation have not been sufficiently clarified. Therefore, in this study, numerical analysis using a single aperture model is performed under various conditions to evaluate how indoor concentration trends and ventilation rates are affected by these factors in order to properly evaluate the outflow characteristics of chemical species and particulate matter due to ventilation. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

Digital twin for healthy indoor environment: A vision for the post-pandemic era

Indoor environment has significant impacts on human health as people spend 90% of their time indoors. The COVID-19 pandemic and the increased public health awareness have further elevated the urgency for cultivating and maintaining a healthy indoor environment. The advancement in emerging digital twin technologies including building information modeling (BIM), Internet of Things (IoT), data analytics, and smart control have led to new opportunities for building design and operation. Despite the numerous studies on developing methods for creating digital twins and enabling new functionalities and services in smart building management, very few have focused on the health of indoor environment. There is a critical need for understanding and envisaging how digital twin paradigms can be geared towards healthy indoor environment. Therefore, this study reviews the techniques for developing digital twins and discusses how the techniques can be customized to contribute to public health. Specifically, the current applications of BIM, IoT sensing, data analytics, and smart building control technologies for building digital twins are reviewed, and the knowledge gaps and limitations are discussed to guide future research for improving environmental and occupant health. Moreover, this paper elaborates a vision for future research on integrated digital twins for a healthy indoor environment with special considerations of the above four emerging techniques and issues. This review contributes to the body of knowledge by advocating for the consideration of health in digital twin modeling and smart building services and presenting the research roadmap for digital twin-enabled healthy indoor environment.

Indoor Air Quality during Lockdown: A Monitoring-based Simulation-assisted Study in London

The Covid-19 outbreak has resulted in new patterns of home occupancy, the implications of which for indoor air quality (IAQ) and energy use are not well-known. In this context, the present study investigates 8 flats in London to uncover if during a lockdown, (a) IAQ in the monitored flats deteriorated, (b) the patterns of window operation by occupants changed, and (c) more effective ventilation patterns could enhance IAQ without significant increases in heating energy demand. To this end, one-year's worth of monitored data on indoor and outdoor environment along with occupant use of windows has been used to analyse the impact of lockdown on IAQ. Moreover, using on-site CO2 data, monitored occupancy and operation of windows, the team has calibrated a thermal performance model of one of the flats to investigate the implications of alternative ventilation strategies. The results suggest that despite the extended occupancy during lockdown, occupants relied less on natural ventilation, which led to significantly higher CO2 and PM10 concentrations. However, simple natural ventilation patterns or use of mechanical ventilation with heat recovery proves to be very effective to maintain acceptable IAQ. © International Building Performance Simulation Association, 2022

Thermal Comfort Analysis Using System Dynamics Modeling—A Sustainable Scenario Proposition for Low-Income Housing in Brazil

As a riveting example of social housing in Brazil, the Minha Casa Minha Vida program was set in 2009 to diminish the 6-million-home housing deficit by offering affordable dwellings for low-income families. However, recurrent thermal discomfort complaints occur among dwellers, especially in the Baltimore Residential sample in Uberlândia City. To avoid negative effects of energy poverty, such as family budget constraints from the purchase of electric appliances and extra costs from power consumption, a simulation based on system dynamics modeling shows a natural ventilation strategy with a mixed combination of sustainable and energy-efficient materials (tilting window with up to 100% opening, green tempered glass, and expanded polystyrene wall) to observe the internal room temperature variation over time. With a 50% window opening ratio combined with a 3 mm regular glass window and a 12.5 cm rectangular 8-hole brick wall, this scenario presents the highest internal room temperature value held during the entire period. From the worst to the best-case scenario, a substantial reduction in the peak temperature was observed from window size variation, demonstrating that natural ventilation and constructive elements of low complexity and wide availability in the market contribute to the thermal comfort of residential rooms.

Assessment of respiratory disease infection risk and natural ventilation intervention countermeasures in teaching spaces: A campus case study

The risk of indoor respiratory disease transmission can be significantly reduced through interventions that target the built environment. Several studies have successfully developed theoretical models to calculate the effects of built environment parameters on infection rates. However, current studies have mainly focused on calculating infection rate values and comparing pre- and post-optimization values, lacking a discussion of safe baseline values for infection rates with risk class classification. The purpose of this paper is to explore the design of interventions in the built environment to improve the ability of buildings to prevent virus transmission, with a university campus as an example. The study integrates the Wells-Riley model and basic reproduction number to identify teaching spaces with high infection risk on campus and proposes targeted intervention countermeasures based on the analysis of critical parameters. The results showed that teaching buildings with a grid layout pattern had a higher potential risk of infection under natural ventilation. By a diversity of building environment interventions designed, the internal airflow field of classrooms can be effectively organized, and the indoor virus concentration can be reduced. We can find that after optimizing the building mentioned above and environment intervention countermeasures, the maximum indoor virus infection probability can be reduced by 22.88%, and the basic reproduction number can be reduced by 25.98%, finally reaching a safe level of less than 1.0. In this paper, we support university campuses' respiratory disease prevention and control programs by constructing theoretical models and developing parametric platforms. © 2023 Elsevier Ltd

Designing Out the Risk of Infections via Aerosols by Updating Restrictions on Indoor Environments Depending on Local Incidence Rates and the Dominant SARS-Co V -2 Strain

The paper contributes to existing research on transmission of infectious diseases in indoor environments, with a focus on the SARS-Co V -2 virus, considered in an environment with a potentially high infectious risk, i.e. a university building. A multi-functional zone with variable occupancy schedules involving both students and staff is used as a case study. A computational fluid dynamics (CFD) model is developed to simulate and analyze three scenarios involving mixed, mechanical, and natural ventilation. Based on the physical and operational configuration of the selected zone, initial results show that mechanical ventilation involves areas of stagnant air (i.e. air velocity is less than 0.1m/s), while reliance on natural ventilation leads to increase in C02 levels. Hence, a mixed mode (natural and mechanical) ventilation is suggested. Then, based on the probability of the presence of (an) infected individual(s), considering the local COVID-19 incidence rate, initial estimates suggest that the Delta variant requires the air change rate (ACH) to be increased more than 1000 times, when compared to the original strain. The paper thus establishes a correlation between the prevalence of a given SARS-Co V -2 variant with the required air change rate, emphasizing the need to factor in not only the presence of infected individual(s), based on the local incidence rate, but also the viral charge of the dominant SARS-Co V -2 variant. The paper argues the need for a better controlled and optimized ventilation to ensure safer indoor environments. © 2022 IEEE.

Large-eddy simulations to define building-specific similarity relationships for natural ventilation flow rates

Natural ventilation can play an important role towards preventing the spread of airborne infections in indoor environments. However, quantifying natural ventilation flow rates is a challenging task due to significant variability in the boundary conditions that drive the flow. In the current study, we propose and validate an efficient strategy for using computational fluid dynamics to assess natural ventilation flow rates under variable conditions, considering the test case of a single-room home in a dense urban slum. The method characterizes the dimensionless ventilation rate as a function of the dimensionless ventilation Richardson number and the wind direction. First, the high-fidelity large-eddy simulation (LES) predictions are validated against full-scale ventilation rate measurements. Next, simulations with identical Richardson numbers, but varying dimensional wind speeds and temperatures, are compared to verify the proposed similarity relationship. Last, the functional form of the similarity relationship is determined based on 32 LES. Validation of the surrogate model against full-scale measurements demonstrates that the proposed strategy can efficiently inform accurate building-specific similarity relationships for natural ventilation flow rates in complex urban environments.

Effect of flow structures on natural ventilation performance in office model.

The recent Coronavirus Disease 2019 pandemic has highlighted the importance of indoor ventilation. In particular, ventilation is crucial in residential spaces and workspaces, where people spent most of their day. Natural ventilation is a cost-effective method for improving indoor ventilation. It can provide safe and comfortable residential and working environments without additional energy consumption. In this study, the ventilation performance was experimentally studied by measuring the concentration of ultrafine particulate matter according to the opening conditions of the windows and door of an office model in a wind tunnel. Furthermore, the internal flow structure in the office model was quantitatively analyzed through particle image velocimetry to determine the factors that affected the ventilation performance. The mean velocity inside the model and the ventilation performance increased with the opening angle of the windows. In particular, the opening condition of the door strongly affected the ventilation performance. This study is expected to provide a guideline for effectively improving the ventilation performance in indoor spaces.

Natural ventilation as a healthy habit during the first wave of the COVID-19 pandemic: An analysis of the frequency of window opening in Spanish homes

Since SARS-CoV-2 spread worldwide in early 2020, many countries established lockdowns for protection. With a main transmission by aerosols, ventilation was promoted. This article analyses natural ventilation of Spanish housing during the spring 2020. An online questionnaire was launched, obtaining for this study 1502 responses. The comparative window opening before and during confinement, and households, dwellings and home activity variables, were analysed. The binary logistic regression model before pandemic indicated that ventilating properly related to: a worse perceived IAQ (OR = 1.56);thermal adaptation measures, especially those that prefer to open/close windows (OR = 1.45);not having heating system (OR = 1.15);and using power to heat water (OR = 1.60). For the confinement period, the model highlighted: being an employee (OR = 1.88);using heavy clothing in the home (OR = 2.36);and again, open/close windows for adaptation (OR = 2.24). According to specific tasks in quarantine, frequent ventilation was boosted by: an increasing use of oven (OR = 14.81);and alteration of work-habits (OR = 2.70), sport-habits (OR = 1.79), and outdoor-activities (OR = 1.60). Thus, an adequate natural ventilation pattern during the quarantine was linked to low environmental comfort in general, by virtue of indoor air quality. This is corroborated by less acoustic-thermal insulation, worse indicators of heating use, and the adaptive response to opening/closing windows when external temperature changed. © 2022 The Authors

Using the big data analysis and basic information from lecture Halls to predict air change rate

School lecture halls are often designed as confined spaces. During the period of COVID-19, indoor ventilation has played an even more important role. Considering the economic reasons and the immediacy of the effect, the natural ventilation mechanism becomes the primary issue to be evaluated. However, the commonly used CO2 tracer gas concentration decay method consumes a lot of time and cost. To evaluate the ventilation rate fast and effectively, we use the common methods of big data analysis - Principal Component Analysis (PCA), K-means and linear regression to analyze the basic information of the lecture hall to explore the relation between variables and air change rate. The analysis results show that the target 37 lecture halls are divided into two clusters, and the measured 11 lecture halls contributed 64.65%. When analyzing the two clusters separately, there is a linear relation between the opening area and air change rate (ACH), and the model error is between 6% and 12%, which proves the feasibility of the basic information of the lecture hall by calculating the air change rate. © 2023 Elsevier Ltd

Variations in classroom ventilation during the COVID-19 pandemic: Insights from monitoring 36 naturally ventilated classrooms in the UK during 2021

Seasonal changes in the measured CO2 levels at four schools are herein presented through a set of indoor air quality metrics that were gathered during the height of the COVID-19 pandemic in the UK. Data from non-intrusive environmental monitoring units were remotely collected throughout 2021 from 36 naturally ventilated classrooms at two primary schools and two secondary schools in England. Measurements were analysed to assess the indoor CO2 concentration and temperature. Relative to UK school air quality guidance, the CO2 levels within classrooms remained relatively low during periods of warmer weather, with elevated CO2 levels being evident during the colder seasons, indicating lower levels of per person ventilation during these colder periods. However, CO2 data from the cold period during the latter part of 2021, imply that the per person classroom ventilation levels were significantly lower than those achieved during a similarly cold weather period during the early part of the year. Given that the classroom architecture and usage remained unchanged, this finding suggests that changes in the ventilation behaviours within the classrooms may have altered, and raises questions as to what may have given rise to such change, in a year when, messaging and public concerns regarding COVID-19 varied within the UK. Significant variations were observed when contrasting data, both between schools, and between classrooms within the same school building;suggesting that work is required to understand and catalogue the existing ventilation provisions and architecture within UK classrooms, and that more work is required to ascertain the effects of classroom ventilation behaviours. © 2022 The Author(s)

Experimental and numerical evaluation of a novel dual-channel windcatcher with a rotary scoop for energy-saving technology integration

With the increasing requirements for fresh air supply in buildings after the COVID-19 pandemic and the rising energy demand from buildings, there has been an increased emphasis on passive cooling techniques such as natural ventilation. While natural ventilation devices such as windcatchers can be a sustainable and low-cost solution to remove indoor pollutants and improve indoor air quality, it is not as reliable as mechanical systems. Integration with low-energy cooling, heating or heat recovery technologies is necessary for operation in unfavourable outdoor conditions. In this research, a novel dual-channel windcatcher design consisting of a rotary wind scoop and a chimney was proposed to provide a fresh air supply irrespective of the wind direction. The dual-channel design allows for passive cooling, dehumidification and heat recovery technology integration to enhance its thermal performance. In this design, the positions of the supply and return duct are "fixed” or would not change under changing wind directions. An open wind tunnel and test room were employed to experimentally evaluate the ventilation performance of the proposed windcatcher prototype. A Computational Fluid Dynamic (CFD) model was developed and validated to further evaluate the system's ventilation performance. The results confirmed that the system could supply sufficient fresh air and exhaust stale air under changing wind directions. The ventilation rate of the rotary scoop windcatcher was higher than that of a conventional 8-sided multidirectional windcatcher of the same size. © 2023 The Author(s)

Identification of source location in a single-sided building with natural ventilation: Case of interunit pollutant dispersion

A sudden outbreak of COVID-19 occurred in December 2019 and its rapid spread over the last two years caused a global pandemic. A special airborne transmission via aerosols called interunit dispersion is risky in a high-density urban environment, which needs more attention. In order to identify the source location of pollutants or viruses under the interunit transmission condition with natural ventilation, this study adopted the inverse Computational Fluid Dynamics (CFD) simulation with the adjoint probability method. The detailed process of the inverse modeling was presented. Also, the possible interunit transmission routes of the pollutants or viruses were analyzed. A three-story building model with single-sided openings was built. Six different combinations of fixed sensor locations were tested, and it was determined that setting sensors in the four corner regions of the building was the optimist strategy. A total of 25 cases with five different wind directions (0°, 45°, 90°, 135°, and 180°) were tested to verify the accuracy of the source location with inverse modeling. The results showed that 67%–78% of the rooms in the building can be identified with a limited number of pollutant sensors and all rooms can be identified with one additional sensor in the downstream room of the building under different wind direction. This research revealed that the inverse modeling method could be used to identify the pollutant source in the coupled indoor and outdoor environment. Further, this work can provide guidance for the pollutant monitor positions in the applications.

PREDICTION OF THE MAXIMUM WIND SPEED IN INDOOR ENVIRONMENTS FOR EFFICIENT NATURAL VENTILATION

The efficient natural ventilation in indoor environments is extremely important especially this period with the appearance of new hazardous viruses such as COVID-19. It is well known that the maximum wind speed causes the lowest individual exposure to hazardous substances in an environment (either indoor or outdoor) and as a result its reliable prediction by a numerical model (either simple or complex) becomes of utmost importance. In this study a deterministic model, that was developed for the outdoor environment, is examined as a possible candidate to predict the maximum wind speed in indoor environments. For the needs of the study a wind tunnel experiment is simulated by the LES methodology in order to acquire the maximum wind speed at various locations in an indoor environment. Then the deterministic model, without any change in its parameters, is validated successfully with the LES maximum wind speeds. The present deterministic model can be incorporated in simple methodologies (e.g. RANS) provided that the latest are able to predict the mean speed, the turbulent intensity and a hydrodynamic time scale. © British Crown Copyright (2022)

Investigating natural ventilation performance on apartment units in Jakarta based on field test measurements

The COVID-19 pandemic has changed the way of living of many people across the planet. In the beginning of the pandemic, when the strict lockdown was implemented, numbers of individual were encouraged to work from home. In the city living, high rise living was apparent and became a global phenomenon. This paper evaluates natural ventilation performances of existing apartment units in Jakarta, Indonesia by measuring the indoor temperature, indoor airflow and relative humidity. This research studied three different apartment units in Jakarta in the form of single-sided ventilation or cross ventilation. This study conducted by field test measurement on three different apartment units across Jakarta with various natural ventilation strategy and room volume. Statistical analysis was carried out to investigate the relationship and influence between the results of field test measurement and external weather data collected from ERA5. The results of the analysis suggested that external weather influence the indoor air condition, especially indoor temperature where significant influence was apparent. Furthermore, the field test data measurement in this paper contributed to validation study in predicting indoor airflow. © 2022, University of Malaya. All rights reserved.

Experimental and numerical evaluation of a novel dual-channel windcatcher with a rotary scoop for energy-saving technology integration

With the increasing requirements for fresh air supply in buildings after the COVID-19 pandemic and the rising cost of energy, there has been an increased emphasis on natural ventilation techniques. While natural ventilation devices such as windcatchers can be a low-cost solution to remove indoor pollutants and improve indoor air quality, it is not as reliable as mechanical systems. Integration with low-energy cooling, heating or heat recovery technologies is necessary for operation in unfavourable outdoor conditions. In this research, a novel dual-channel windcatcher design consisting of a rotary wind scoop and a chimney was proposed to provide a fresh air supply irrespective of the wind direction. The dual-channel design allows for passive cooling, dehumidification and heat recovery technology integration to enhance its thermal performance. In this design, the positions of the supply and return duct are "fixed” or would not change under changing wind directions. An open wind tunnel and test room were employed to experimentally evaluate the ventilation performance of the proposed windcatcher prototype. A validated Computational Fluid Dynamic (CFD) model was developed to further evaluate the system's performance. The results confirmed that the system could supply sufficient fresh air and exhaust stale air under changing wind directions. The ventilation rate of the rotary scoop windcatcher was higher than that of a conventional 8-sided multidirectional windcatcher of the same size.

Evaluation of aerosol transmission risk during home quarantine under different operating scenarios: A pilot study.

SARS-CoV-2 has been recognized to be airborne transmissible. With the large number of reported positive cases in the community, home quarantine is recommended for the infectors who are not severely ill. However, the risks of household aerosol transmission associated with the quarantine room operating methods are under-explored. We used tracer gas technique to simulate the exhaled virus laden aerosols from a patient under home quarantine situation inside a residential testbed. The Sulphur hexafluoride (SF6) concentration was measured both inside and outside the quarantine room under different operating settings including, air-conditioning and natural ventilation, presence of an exhaust fan, and the air movement generated by ceiling or pedestal fan. We calculated the outside-to-inside SF6 concentration to indicate potential exposure of occupants in the same household. In-room concentration with air-conditioning was 4 times higher than in natural ventilation settings. Exhaust fan operation substantially reduced in-room SF6 concentration and leakage rate in most of the ventilation scenarios, except for natural ventilation setting with ceiling fan. The exception is attributable to the different airflow patterns between ceiling fan (recirculates air vertically) and pedestal fan (moves air horizontally). These airflow variations also led to differences in SF6 concentration at two sampling heights (0.1 m and 1.7 m) and SF6 leakage rates when the quarantine room door was opened momentarily. Use of natural ventilation rather than air-conditioning, and operating exhaust fan when using air-conditioning are recommended to lower exposure risk for home quarantine. A more holistic experiment will be conducted to address the limitations reflected in this study.

CO2 Levels in the Naso-Buccal Area Due to the Use of Different Face Masks in Different Ventilation Conditions

In this work, CO2 levels were estimated in the naso-buccal area due to the use of face masks. Tests were performed on a healthy volunteer subject sitting at rest and breathing regularly, who used five types of face masks in well-ventilated and poorly ventilated rooms. The ventilation conditions were determined by the natural ventilation of the room. Each of the tests lasted one hour. To estimate the CO2 level, a sensor based on the Non-dispersive Infrared (NDIR) principle was used. The results revealed that while wearing a face mask, the ventilation conditions affected the CO2 concentration levels in the naso-buccal area of the user, especially in those that offered a higher level of protection, and in those that best fit the face of the subject. A multiple comparison method (Tukey) revealed significant differences in the levels of CO2 between all the facemask tested (p < 0.0001). The CO2 levels were also compared with the exposure limits recommended by NIOSH, showing that the use of N95 for 1 h exceeded the recommended 5,000 ppm for an 8-h workday. None of the masks tested exceeded the NIOSH-recommended short-term limit in the first 15 min of use. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.