Ergonomics-oriented operation, maintenance and control of indoor air environment for public buildings

In response to the construction process of Healthy China. it is rather important to create a safe, healthy and energy-efficient indoor environment for public buildings. The public building space is often densely populated, with a large flow of people and many types of air pollution, which presents non-uniform dynamic distribution characteristics. This brings great challenges to the control of indoor air safety, especially during the pandemic period of COVID-19. Excessive ventilation may not only cause large energy waste. but also lead to cross-contamination and even a cluster of infection. In this paper, an operation and maintenance (O&M) control system for indoor air safety is developed based on the core concepts and basic methods of human ergonomics. In this system, one of the important human environmental variables is focused for control, i.e.. indoor air pollution level. Especially after the outbreak of COVID-19. droplets and droplet nuclei from respiration are the most significant air pollution categories required for mitigation. Towards the efficient control of air pollution in large public buildings. it should further take into account the interaction of human, equipment and machines (i.e., ventilation_ air purification and disinfection and intelligent control system) and building environment. Firstly, on the basis of the online monitoring of indoor air pollution concentration and personnel flow, the non-uniform dynamic distribution of indoor pollutants and personnel can be obtained by using the non-uniform and low-dimensional rapid prediction models and computer vision processing. Then, the optimal setting results of ventilation parameters (e.g., ventilation modes, supply air rate. etc.) can be outputted by the environmental control decision system. Finally, based on a combination of monitoring sensors, controllers and actuator hardware equipment (at the location of fans or dampers), the intelligent regulation and control of ventilation system can be realized, aimed at minimizing energy consumption and reducing pollutant concentration and exposure level. Meanwhile, the air purification and disinfection system (especially for the disinfection of virus particles) are operated under the condition of the ventilated environment, which can serve as a powerful auxiliary to the maintenance of indoor air safety. The workflow and effect of the O&M control system are demonstrated by an engineering application case of the front hall in the International Convention and Exhibition Center. The results indicate that the non-uniform and low-dimensional rapid prediction model for pollutant concentration is effective for the ventilation control with the average prediction difference of 11.9%. The implementation of the intelligent ventilation system can reduce the risk of human infection to less than 4%. and its energy-saving ratio for the ventilation can be as high as about 45%. Through optimizing the layout strategies of disinfection devices based on the intelligent ventilation control, the space accessibility of negative oxygen ions can be well accepted, to further increase the removal efficiency of air pollution. The calculated value of space disinfection rate is more than 99%, which can further reduce the risk of infection by 1-2 orders of magnitude. This study can provide an important reference for the promotion and upgrading of O&M control system for indoor air safety.

Optimization of ventilation performance of side air supply for large indoor spaces using deflectors and slot air outlets

Due to the large height and span of indoor spaces, efficient indoor ventilation performance may be difficult to achieve using the side air supply for large halls, to control the indoor air pollutants or reduce the infection risk, such as the transmission of COVID-19 within the breathing zone of occupants. An efficient Ventilation Mode with Deflector and Slot air outlets (VMDS) was developed by this study. The use of a deflector with slot air outlets was introduced by utilizing jet collision and adhesion effect to accentuate the ventilation performance of the side air supply for the large space. The numerical simulation model used in this study was validated experimentally. The VMDS was compared with three other side air supply modes used in large spaces, and the results were evaluated comprehensively. The results show that VMDS is effective in reducing indoor air pollutant concentrations and transmission of infectious diseases in large spaces while satisfying the energy efficiency and thermal comfort requirements. Compared with the common side-supply and side-return ventilation modes, VMDS can reduce indoor air pollutant concentration by nearly 40%, reduce the transmission risk of infectious disease to less than 1% at a low air change rate and increase the ventilation efficiency from about 0.85 to about 1.2. In addition, VMDS can theoretically reduce ventilation energy consumption by about 85%. © The Author(s) 2022.

Ventilation and Low-cost Strategies on Mitigating COVID-19 Infection Disease Transmission in Indoor Environment

During the normalization phase of COVID-19 epidemic, it is gradually reverted to use building space, especially for office. Prevention of airborne pollutant has emerged as a major challenge. Ventilation strategies can mitigate the spread of airborne disease in indoor environment, such as increasing ventilation rate, modifying ventilation mode, etc. The larger ventilation rate can lead to higher energy consumption may not effectively reduce infection risk. The potential of ventilation modes for COVID-19 control should be explored. Furthermore, it is necessary to adopt low-cost strategies, such as physical barrier, to increase the prevention efficiency while combining the ventilation system. This study was to investigate the impact of physical barrier on the spread of particles and infection risk in an office with a sufficient ventilation rate, and then compare different ventilation strategies, including mixing ventilation (MV), zone ventilation (ZV), stratum ventilation (SV) and displacement ventilation (DV), for the optimal one. The simulation model was mainly used in this work and validated by the experiment to show a good agreement with the model prediction. The results showed that (1) the SV showed greater performance in mitigating infection disease spread than MV, ZV and DV, with a minimum infection risk of 13%;(2) a barrier height of at least 60 cm above the desk surface is needed to effectively prevent the transmission of viruses with the risk of infection reduced by about 72%. This work can provide a reference for development of ventilation strategies as well as low-cost prevention interventions in public space oriented the prevention of COVID-19. © The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/)

Ergonomics-oriented operation, maintenance and control of indoor air environment for public buildings

In response to the construction process of Healthy China. it is rather important to create a safe, healthy and energy-efficient indoor environment for public buildings. The public building space is often densely populated, with a large flow of people and many types of air pollution, which presents non-uniform dynamic distribution characteristics. This brings great challenges to the control of indoor air safety, especially during the pandemic period of COVID-19. Excessive ventilation may not only cause large energy waste. but also lead to cross-contamination and even a cluster of infection. In this paper, an operation and maintenance (O&M) control system for indoor air safety is developed based on the core concepts and basic methods of human ergonomics. In this system, one of the important human environmental variables is focused for control, i.e.. indoor air pollution level. Especially after the outbreak of COVID-19. droplets and droplet nuclei from respiration are the most significant air pollution categories required for mitigation. Towards the efficient control of air pollution in large public buildings. it should further take into account the interaction of human, equipment and machines (i.e., ventilation_ air purification and disinfection and intelligent control system) and building environment. Firstly, on the basis of the online monitoring of indoor air pollution concentration and personnel flow, the non-uniform dynamic distribution of indoor pollutants and personnel can be obtained by using the non-uniform and low-dimensional rapid prediction models and computer vision processing. Then, the optimal setting results of ventilation parameters (e.g., ventilation modes, supply air rate. etc.) can be outputted by the environmental control decision system. Finally, based on a combination of monitoring sensors, controllers and actuator hardware equipment (at the location of fans or dampers), the intelligent regulation and control of ventilation system can be realized, aimed at minimizing energy consumption and reducing pollutant concentration and exposure level. Meanwhile, the air purification and disinfection system (especially for the disinfection of virus particles) are operated under the condition of the ventilated environment, which can serve as a powerful auxiliary to the maintenance of indoor air safety. The workflow and effect of the O&M control system are demonstrated by an engineering application case of the front hall in the International Convention and Exhibition Center. The results indicate that the non-uniform and low-dimensional rapid prediction model for pollutant concentration is effective for the ventilation control with the average prediction difference of 11.9%. The implementation of the intelligent ventilation system can reduce the risk of human infection to less than 4%. and its energy-saving ratio for the ventilation can be as high as about 45%. Through optimizing the layout strategies of disinfection devices based on the intelligent ventilation control, the space accessibility of negative oxygen ions can be well accepted, to further increase the removal efficiency of air pollution. The calculated value of space disinfection rate is more than 99%, which can further reduce the risk of infection by 1-2 orders of magnitude. This study can provide an important reference for the promotion and upgrading of O&M control system for indoor air safety.

A practical approach for preventing dispersion of infection disease in naturally ventilated room

During the ongoing COVID-19 pandemic period, the airborne transmission of viruses has raised widespread concern as daily activities are resumed in public buildings. It is essential to develop mitigation strategies of infection disease transmission (e.g., increase of ventilation rate) in different scenarios to reduce the infection risk. For classrooms in schools, natural ventilation is generally used to provide outdoor air into rooms. However, the supply air volume depends strongly on the local conditions, e.g., window opening size and outdoor wind speed. In this study, the optimal design of classroom window openings is investigated, based on which low-cost window-integrated fans are then employed to enhance the efficiency of natural ventilation and infection disease control. Taking infected students as pollutant sources, numerical simulations are carried out to predict the pollutant concentration under various scenarios of pollutant sources and window opening modes (with/without fans), and to calculate the infection risk. It is found that by redesigning window openings, the airflow distribution performance index (ADPI) can be increased by 17% with corresponding infection likelihood decreased by 27%. The window integrated fan has a significant effect on improving ventilation performance and prevention of infection disease transmission, leading to an ADPI of 99% and minimum infection probability of 11% for students sitting near the windows. This work can help to develop low-cost and effective mitigating measures of infection disease in classrooms by using hybrid ventilation systems.

CONTACT TRACING ENHANCES THE EFFICIENCY OF COVID-19 GROUP TESTING

Group testing can save testing resources in the context of the ongoing COVID-19 pandemic. In group testing, we are given n samples, one per individual, and arrange them into m < n pooled samples, where each pool is obtained by mixing a subset of the n individual samples. Infected individuals are then identified using a group testing algorithm. In this paper, we use side information (SI) collected from contact tracing (CT) within nonadaptive/single-stage group testing algorithms. We generate data by incorporating CT SI and characteristics of disease spread between individuals. These data are fed into two signal and measurement models for group testing, where numerical results show that our algorithms provide improved sensitivity and specificity. While Nikolopoulos et al. utilized family structure to improve nonadaptive group testing, ours is the first work to explore and demonstrate how CT SI can further improve group testing performance.

Non-uniform risk assessment methods for personalized ventilation on prevention and control of COVID-19

Ventilation is an important measure to prevent the transmission of COVID-19 in indoor environment. The protection effect of personalized ventilation in disease control has been preliminarily verified in previous studies. It is considered as one of the promising measures to control airborne transmission indoors due to its high ventilation efficiency with direct delivery of fresh and clean air to the occupant's breathing zone. Especially for vehicles like aircrafts and coaches, in which the personalized ventilation has been used for years, its applications in COVID-19 epidemic control should be further explored. However, most of the present airborne infection risk prediction models are based on the assumption that the exhaled pathogens are evenly distributed in the room. The non-uniform distribution of pathogens in indoor environment cannot be accurately predicted with these models when applying localized ventilation or considering the short-ranged transmission of airborne pathogens. In this study, five different non-uniform risk assessment models were verified by the tracer particle experiments with thermal manikins. The assessment methods included exposure risk index (epsilon(bz)), personal exposure effectiveness (PEE), intake fraction (IF), dose-response model (P(t)) and infection risk reduction ratio (eta). Two breathing thermal manikins were used to simulate two seated passengers in public transportation placed side by side. The nebulized aerosols with similar size distribution to human breathing were released from the source manikin's mouth. The concentration of the received particles at the receptor's breathing zone was sampled with an aerodynamic particle sizer (APS). The receptor's exposure level of droplets released by the exhalation of the infector was predicted accordingly considering the usage patterns of the personalized ventilation. The applicability of each model for predicting the risk of airborne transmission of SARS-CoV-2 was discussed. The results show that the five assessment methods are all based on the measurement results of the droplet concentration in the breathing zone of the exposed occupant. These models can predict the intervention effect of personalized ventilation on the airborne exposure or infection risk, and the trends of the predicted results are basically consistent. The relative exposure level can be predicted by exposure risk index epsilon(bz), PEE and IF, which can be used to simply assess the exposure risk of SARS-CoV-2. The dose-response model can directly assess the infection risk of specific airborne disease such as COVID-19, but only when the viability and infectivity of the virus are accurately determined. And infection risk index. can evaluate the infection risk reduction ratio due to the use of personalized ventilation. These assessment methods can all reflect the problems of risk increase caused by lateral spread and accelerated diffusion of the droplet-laden air due to the application of personalized ventilation to the infector. The protective effect for the exposed occupant can also be evaluated by these models when PV is used for the receptor. The exposure risk of the receptor can be lowered by using the personalized ventilation and the protection effect is increased by using higher volume of clean air. This study can provide support and reference for the evaluation and development of novel ventilation methods for airborne disease control in indoor environment and provide basis for assessment of the transmission risk of COVID-19 under non-uniform conditions.