Intelligent operation, maintenance, and control system for public building: towards infection risk mitigation and energy efficiency

During the post-COVID-19 era, it is important but challenging to synchronously mitigate the infection risk and optimize the energy savings in public buildings. While, ineffective control of ventilation and purification systems can result in increased energy consumption and cross-contamination. This paper is to develop intelligent operation, maintenance, and control system by coupling intelligent ventilation and air purification systems (negative ion generators). Optimal deployment of sensors is determined by Fuzzy C-mean (FCM), based on which CO2 concentration fields are rapidly predicted by combing the artificial neural network (ANN) and self-adaptive low-dimensional linear model (LLM). Negative oxygen ion and particle concentrations are simulated with different number of negative ion generators. Optimal ventilation rates and number of negative ion generators are decided. A visualization platform is established to display the effects of ventilation control, epidemic prevention, and pollutant removal. The rapid prediction error of LLM-based ANN for CO2 concentration was below 10% compared with the simulation. Fast decision reduced CO2 concentration below 1000 ppm, infection risk below 1.5%, and energy consumption by 27.4%. The largest removal efficiency was 81% with number of negative ion generators was 10. This work can promote intelligent operation, maintenance, and control systems considering infection prevention and energy sustainability.

Intelligent operation, maintenance, and control system for public building: Towards infection risk mitigation and energy efficiency.

During the post-COVID-19 era, it is important but challenging to synchronously mitigate the infection risk and optimize the energy savings in public buildings. While, ineffective control of ventilation and purification systems can result in increased energy consumption and cross-contamination. This paper is to develop intelligent operation, maintenance, and control systems by coupling intelligent ventilation and air purification systems (negative ion generators). Optimal deployment of sensors is determined by Fuzzy C-mean (FCM), based on which CO2 concentration fields are rapidly predicted by combing the artificial neural network (ANN) and self-adaptive low-dimensional linear model (LLM). Negative oxygen ion and particle concentrations are simulated with different numbers of negative ion generators. Optimal ventilation rates and number of negative ion generators are decided. A visualization platform is established to display the effects of ventilation control, epidemic prevention, and pollutant removal. The rapid prediction error of LLM-based ANN for CO2 concentration was below 10% compared with the simulation. Fast decision reduced CO2 concentration below 1000 ppm, infection risk below 1.5%, and energy consumption by 27.4%. The largest removal efficiency was 81% when number of negative ion generators was 10. This work can promote intelligent operation, maintenance, and control systems considering infection prevention and energy sustainability.

Safety considerations of chloroquine in the treatment of patients with diabetes and COVID-19.

Patients with underlying diseases and coronavirus disease 2019 (COVID-19) are at increased risk of death. Using the recommended anti-COVID-19 drug, chloroquine phosphate (CQ), to treat patients with severe cases and type 2 diabetes (T2D) could potentially cause harm. We aimed to understand the safety of CQ in patients with T2D by administrating the recommended dose (63 mg/kg twice daily for 7 days) and a high dose (126 mg/kg twice daily for 7 days) of CQ in T2D rats. We found that CQ increased the total mortality of the T2D rats from 27.3% to 72.7% in the recommended and high-dose groups during the whole period. CQ also induced hematotoxicity of T2D rats in the high-dose group; the hepatic enzymes in T2D rats were significantly elevated. CQ also changed the electrocardiograms, prolonged the QTc intervals, and produced urinary leukocytes and proteins in the T2D rats. Histopathological observations revealed that CQ caused severe damage to the rats' heart, jejunum, liver, kidneys, spleen, and retinas. Furthermore, CQ significantly decreased the serum IL-1ß and IL-6 levels. In conclusion, the CQ dosage and regimen used to treat COVID-19 induced adverse effects in diabetic rats, suggesting the need to reevaluate the effective dose of CQ in humans.

Hypertension related toxicity of chloroquine explains its failure against COVID-19: Based on rat model.

Chloroquine was once thought to be a promising treatment for COVID-19 but it quickly failed due to its inefficiency and association with increased mortality. Further, comorbidities such as hypertension may have contributed this failure. The safety and toxicity of chloroquine at doses required for treating SARS-CoV-2 infection in hypertensive patients remain unknown. Herein, to investigate these effects, we performed a safety evaluation of chloroquine at the approved dose (63 mg/kg) and at a high dose (126 mg/kg) in hypertensive rats. We found that chloroquine increased the mortality of hypertensive rats to 18.2% and 100%, respectively, after 7 days. During the chloroquine exposure period, the bodyweight, feed, and water consumption of hypertensive rats were decreased significantly. In addition, we show that chloroquine induces prolongation of QTc interval, elevation of LDH and CK, and histopathological damage of the myocardium in hypertensive rats. Ocular toxicity was observed in hypertensive rats in the form of hemorrhage in the eyes and retinal damage. Furthermore, we also observed intestinal toxicity in hypertensive rats, which presented as thinning intestinal walls with hemorrhagic contents, and histopathological changes of the jejunum. Hepatotoxicity was also evidenced by elevated ALT, and vacuolization of hepatocytes was also observed. Nephrotoxicity was observed only in high dose chloroquine-treated hypertensive rats, presenting as alterations of urinalysis and renal function. Immune alterations were also found in high-dose chloroquine-treated hypertensive rats with elevation of serum IL-10, IL-1ß and GRO, and moderate damage to the spleen. In summary, this study partially explains the reason for the failure of chloroquine as a COVID-19 therapy, and underlines the importance of safety evaluation and medical supervision of chloroquine to avoid patient harm, especially to those with hypertension.

Ventilation impacts on infection risk mitigation, improvement of environmental quality and energy efficiency for subway carriages.

Subway carriages are enclosed for extended periods of time, with a high density of passengers. Providing a safe, healthy, and comfortable cabin environment is a great challenge, particularly during the COVID-19 pandemic. An increase in ventilation rate can potentially reduce infection probability, which may result in worsening environmental quality (e.g., thermal comfort) and larger energy consumption. Thus, exploring the trade-off among infection risk, environmental quality (with regard to ventilation, thermal comfort, and air quality), and energy consumption is important to optimize ventilation systems for carriages. The effect of different supply air parameters (e.g., velocity and temperature) and ventilation modes of mixing ventilation (MV) & Supply air from the Floor and Return air from the Ceiling (SFRC) was studied. The questionnaires were analyzed to explore passenger dissatisfaction with the carriage environment using a MV system. Simulations were performed to predict the velocity, temperature, and CO2 concentration fields. In addition, the comprehensive benefit was evaluated by analytic hierarchy process (AHP), based on infection probability from the revisited Wells-Riley equation, Air Diffusion Performance Index (ADPI), Predicted Mean Vote (PMV), Pollutant Removal Effectiveness (PRE) and energy consumption estimated by cooling load (Lcool). Compared with MV, the optimized SFRC provided softer draft sensation and decreased CO2 concentration by 42%. The SFRC achieved better comprehensive benefits, with an infection risk reduced to 0.4%, ADPI of 80%, PMV approaching zero, PRE up to 16, and energy efficiency increased by 30%. This work contributes to the optimal design of subway carriage ventilation systems in the post-epidemic era.

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%.

Metabolism-based ventilation monitoring and control method for COVID-19 risk mitigation in gymnasiums and alike places.

Gymnasiums, fitness rooms and alike places offer exercise services to citizens, which play positive roles in promoting health and enhancing human immunity. Due to the high metabolic rates during exercises, supplying sufficient ventilation in these places is essential and extremely important especially given the risk of infectious respiratory diseases like COVID-19. Traditional ventilation control methods rely on a single CO2 sensor (often placed at return air duct), which is often difficult to reflect the human metabolic rates accurately, and thus can hardly control the infection risk instantly. Thus, to ensure a safe and healthy environment in places with high metabolism, a real-time metabolism-based ventilation control method is proposed. A computer vision algorithm is developed to monitor human activities (regarding human motion amplitude and speed) and an artificial neural network is established for metabolic prediction. Case studies show that the proposed metabolism-based ventilation control method can reduce the infection probability down to 4.3-6.3% while saving 13% of energy in comparison with the strategy of fixed-fresh-air ventilation. In the development of healthy and sustainable society, gymnasiums and alike exercise places are essential and the proposed ventilation control method is a promising solution to decrease the risk of COVID-19 while preserving features of energy saving and carbon emission reduction.

Mitigating COVID-19 infection disease transmission in indoor environment using physical barriers.

During the normalized phase of COVID-19, droplets or aerosol particles produced by infected personnel are considered as the potential source of infection with uncertain exposure risk. As such, in densely populated open spaces, it is necessary to adopt strategies to mitigate the risk of infection disease transmission while providing sufficient ventilation air. An example of such strategies is use of physical barriers. In this study, the impact of barrier heights on the spread of aerosol particles is investigated in an open office environment with the well-designed ventilation mode and supply air rate. The risk of infection disease transmission is evaluated using simulation of particle concentration in different locations and subject to a number of source scenarios. It was found that a barrier height of at least 60 cm above the desk surface is needed to effectively prevent the transmission of viruses. For workstations within 4 m from the outlet, a 70 cm height is considered, and with a proper ventilation mode, it is shown that the barriers can reduce the risk of infection by 72%. However, for the workstations further away from the outlet (beyond 4 m), the effect of physical barrier cannot be that significant. In summary, this study provides a theoretical analysis for implementing physical barriers, as a low-cost mitigation strategy, subject to various height scenarios and investigation of their effectiveness in reducing the infection transmission probability.

Indoor airborne disinfection with electrostatic disinfector (ESD): Numerical simulations of ESD performance and reduction of computing time.

Airborne transmissions of infectious disease (e.g. SARS-CoV-2) in indoor environments may induce serious threat to public health. Air purification devices are necessary to remove and/or inactivate airborne biological species from indoor air environment. Corona discharge in an electrostatic precipitator is capable of removing particulate matter and disinfecting biological aerosols to act as electrostatic disinfector (ESD). The ions generated by ESD can effectively inactivate bacteria/viruses. However, the available research rarely investigated disinfection effect of ESD, and it is urgent to develop quantitative ESD design methods for building mechanical ventilation applications. This study developed an integrated numerical model to simulate disinfection performance of ESD. The numerical model considers the ionized electric field, electrohydrodynamic flow, and biological disinfection. The model prediction was validated with the experimental data (E. coli): Good agreement was observed. The validated model then was used to study the influences of essential design parameters (e.g. voltage, inlet velocity) of ESD on disinfection efficiency. The effects of modeling of electrophoretic force and EHD (electrohydrodynamic) flow patterns on disinfection efficiency and computing time were also analyzed. The disinfection efficiency of well-designed ESD (with space charge density of 3.6 × 10-06 C/m3) could be as high as 100%. Compared with HEPA, ESD could save 99% of energy consumed by HEPA without sacrificing disinfection efficiency.

Occupant-density-detection based energy efficient ventilation system: Prevention of infection transmission.

Ventilation plays an important role in prevention and control of COVID-19 in enclosed indoor environment and specially in high-occupant-density indoor environments (e.g., underground space buildings, conference room, etc.). Thus, higher ventilation rates are recommended to minimize the infection transmission probability, but this may result in higher energy consumption and cost. This paper proposes a smart low-cost ventilation control strategy based on occupant-density-detection algorithm with consideration of both infection prevention and energy efficiency. The ventilation rate can be automatically adjusted between the demand-controlled mode and anti-infection mode with a self-developed low-cost hardware prototype. YOLO (You Only Look Once) algorithm was applied for occupancy detection based on video frames from surveillance cameras. Case studies show that, compared with a traditional ventilation mode (with 15% fixed fresh air ratio), the proposed ventilation control strategy can achieve 11.7% energy saving while lowering the infection probability to 2%. The developed ventilation control strategy provides a feasible and promising solution to prevent transmission of infection diseases (e.g., COVID-19) in public and private buildings, and also help to achieve a healthy yet sustainable indoor environment.

Disinfection technology of hospital wastes and wastewater: Suggestions for disinfection strategy during coronavirus Disease 2019 (COVID-19) pandemic in China.

Hospitals are important sources of pollutants resulted from diagnostic, laboratory and research activities as well as medicine excretion by patients, which include active component of drugs and metabolite, chemicals, residues of pharmaceuticals, radioactive markers, iodinated contrast media, etc. The discharge of hospital wastes and wastewater, especially those without appropriate treatment would expose the public in danger of infection. In particular, under the Coronavirus Disease 2019 (COVID-19) pandemic context in China, it is of great significance to reduce the health risks to the public and environment. In this study, technologies of different types of hospital wastes and wastewater disinfection have been summarized. Liquid chlorine, sodium hypochlorite, chlorine dioxide, ozone, and ultraviolet irradiation disinfection are commonly used for hospital wastewater disinfection. While incineration, chemical disinfection, and physical disinfection are commonly used for hospital wastes disinfection. In addition, considering the characteristics of various hospital wastes, the classification and selection of corresponding disinfection technologies are discussed. On this basis, this study provides scientific suggestions for management, technology selection, and operation of hospital wastes and wastewater disinfection in China, which is of great significance for development of national disinfection strategy for hospital wastes and wastewater during COVID-19 pandemic.