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A study of the aerodynamic characteristics of aerosol expiration is important for understanding the size distribution of droplet concentration in COVID-19 disease transmission. This study measured the initial concentration and size distribution of droplets released during four breathing processes: nose breathing, mouth breathing, reading alphabets and counting numbers. Influencing factors on droplet generation were studied by statistical analyses. Significant differences in droplet concentration among the four breathing activities in pairs were found (p < 0.001), except for reading alphabets and numbers (p = 1). The droplet concentration during nose breathing (p < 0.05), but not mouth breathing (p = 0.136), of male subjects, was found significantly higher than that of female subjects. The droplet concentration generated by speaking during letters reading with special phonemes, for example, /i:/, was significantly (p < 0.05) higher than reading letters without phonemes. The discharged droplet sizes from four breathing activities were dominated by small droplets (d p < 1.037 μm of over 50% and d p < 2.642 μm of over 80%). Basically, no particles larger than 8 μm were detected by the aerodynamic particle sizer. The inference indicates a possible aerosol transmission of disease during non-symptomatic aerosol-producing activities such as breathing or speaking and may elucidate the disease transmission pathway of COVID-19. [ABSTRACT FROM AUTHOR]

The study presents the results of a numerical analysis of the effectiveness of the use of personal protective equipment of various designs on the spread of pollutants marked with CO2 emitted during human breathing. In the study of 3D geometry the upper part of the human torso and head was developed. The simulated person was supplied with different personal protective equipment covering the human face (PPE). Two types of face shields worn at a different distance from the face and one fabric face mask was analysed. The reference geometry with no personal protective equipment was also analysed. Transient calculation with full breathing model including breath-in and breath-out and species transport were simulated. The results showed that different PPE generates different airflow patterns in the vicinity of the human face. The most efficient in reducing infection risk is by wearing a face mask or face shields at a small distance from the face, as they most effectively reduce CO2 concentration in the surrounding air. However, they also increase the re-inhalation risk of high CO2 concentration which affects human well-being.

Respiratory fluid dynamics is integral to comprehending the transmission of infectious diseases and the effectiveness of interventions such as face masks and social distancing. In this research, we present our recent studies that investigate respiratory particle transport via high-fidelity large eddy simulation coupled with the Lagrangian particle tracking method. Based on our numerical simulation results for human respiratory events with and without face masks, we demonstrate that facial masks could significantly suppress particle spreading. The studied respiratory events include coughing and normal breathing through mouth and nose. Using the Lagrangian particle tracking simulation results, we elucidated the transport pathways of saliva particles during inhalation and exhalation of breathing cycles, contributing to our understanding of respiratory physiology and potential disease transmission routes. Our findings underscore the importance of respiratory fluid dynamics research in informing public health strategies to reduce the spread of respiratory infections. Combining advanced mathematical modeling techniques with experimental data will help future research on airborne disease transmission dynamics and the effectiveness of preventive measures such as face masks., Competing Interests: 7. Conflict of Interest Statement: The authors have no conflicts of interest to declare.

Ozone has adverse effects on human health. Skin oil on the human surface acts as an ozone sink indoors, producing oxidation products that can cause skin and respiratory irritations. Concentrations of ozone and oxidation products near human surfaces, including the breathing zone, can be modulated by indoor ventilation modes and human surface conditions. The objective of this study is to examine concentrations and spatial heterogeneity of ozone and ozonolysis products under representative ranges of indoor ventilation, clothing, and breathing conditions. Using computational fluid dynamics (CFD) simulation in conjunction with a chemical kinetic model, details of ozone reactions with the human surface and subsequent chemical reactions are examined. The results show that primary ozonolysis products are concentrated near the soiled clothing, while the secondary products are relatively well distributed throughout the room. Increasing indoor air mixing enhances the ozone deposition to the human surface, thereby resulting in higher emission rates of oxidation products in the room. Soiled clothing consumes more ozone than clean clothing and accordingly produces ~ 65% more primary products and ~15% more secondary products. The results also reveal that unsaturated hydrocarbons from the human breath, such as isoprene, contribute to only ~0.5% of ozone removal compared to ozone deposition to the human surface. [ABSTRACT FROM AUTHOR]

Measuring humidity in dynamic situation needs very high sensitive and fast response sensors. For this purpose, a new high sensitive humidity sensor based on ZnO/ITO (ZITO) composite nanostructure were designed on alumina substrate by sol-gel technique. Step by step monitoring of fabricated substrate after annealing at 400 °C was performed using scanning electron microscopy (SEM), energy dispersive X-ray (EDX), Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy and UV-Vis techniques. An oscilloscope and digital ohmmeter were applied to determine time-varying voltage and resistance signal of the fabricated sensors, respectively, while exposed to various humidity level. Sensitivity, response, recovery time, deposited layers thicknesses, composition ratio of ZnO:ITO and annealing temperature parameters were considered to achieve optimum conditions. The optimum conditions for maximum sensitivity were obtained as 1:1(ITO:ZnO) ratio, 400 °C annealing temperature, and three times layer by layer coating. Fabricated sensor has excellent response and recovery time (1.0 and 9 s) and long life time at room temperature (25 ± 1 °C) for monitoring human breath and dynamic situation. [ABSTRACT FROM AUTHOR]

This study is focused on determining the convenience of the use of displacement ventilation strategy in airborne infection isolation rooms (AIIRs). Thermal comfort of the occupants of the chamber, ventilation and contaminant performance indices and the exposure of the health worker (HW) to the contaminants exhaled by the confined patient (P) are considered in a typical AIIR set up with two thermal breathing manikins and a radiant wall simulating an external wall. Three air renewal rates are tested to determine their influence in the studied variables. Results show that ventilation performance, contaminants and general comfort indices for both manikins perform well in the cases studied. Lockup phenomenon associated with displacement ventilation occurs above P but it has a low influence on contaminant exposure of HW because of the influence of the convective boundary layer of HW. The influence of the radiant wall could lock the air path near the exhaust grille. [ABSTRACT FROM AUTHOR]

A fiber-optic humidity sensor based on excessively tilted fiber grating (Ex-TFG) wrapped with tin dioxide (SnO 2)/polyvinyl alcohol (PVA) hybrid nanofibers is presented. Relative humidity (RH) rise causes the changes both in refractive index (RI) and geometry size of the film. The transmitted spectrum of the Ex-TFG changes as a result, owing to the strong interaction of the excited forward propagating cladding modes to the surface coating. Experimental results demonstrate the maximum intensity sensitivity of 0.43 dB/%RH in RH range of 35%−75%. Compared with pure PVA film coated ones, the RH sensitivity of the SnO 2 /PVA wrapped grating is vastly enhanced by one order of magnitude. The reticular morphology of electrospun SnO 2 /PVA film around the Ex-TFG promises the unimpeded permeation of water molecules, and then the sensor exhibits an ultrafast response of ∼67 ms and recovery times of ∼83 ms, by monitoring the human breathing with different rhythms. Lastly, the negligible spectral deformation to temperature perturbations verifies the temperature de-correlation of the designed RH sensor. This work indicates that the proposed SnO 2 /PVA nanofibers wrapped Ex-TFG can provide a simple, robust and high-sensitive optic device for healthcare monitoring, environmental and biochemical sensing applications. • Wrapping SnO 2 /PVA nanofibers on an excessively tilted fiber grating. • High intensity sensitivity up to 0.43 dB/%RH with negligible temperature crosstalk. • Monitoring human breathing with ultrafast response speed of 67 ms. • Performing the merits of long-term stability, reliability, and easy fabrication. [ABSTRACT FROM AUTHOR]

Rapid spread of infectious diseases is a global threat and has an adverse impact on human health, livelihood, and economic stability, as manifested in the ongoing coronavirus disease 2019 (COVID-19) pandemic. Even though people wear a face mask as protective equipment, direct disinfection of the pathogens is barely feasible, which thereby urges the development of biocidal agents. Meanwhile, repetitive respiration generates temperature variation wherein the heat is regrettably wasted. Herein, a biocidal ZnO nanorod-modified paper (ZNR-paper) composite that is 1) integrated on a face mask, 2) harvests waste breathing-driven thermal energy, 3) facilitates the pyrocatalytic production of reactive oxygen species (ROS), and ultimately 4) exhibits antibacterial and antiviral performance is proposed. Furthermore, in situ generated compressive/tensile strain of the composite by being attached to a curved mask is investigated for high pyroelectricity. The anisotropic ZNR distortion in the bent composite is verified with changes in ZnO bond lengths and OZnO bond angles in a ZnO 4 tetrahedron, resulting in an increased polarization state and possibly contributing to the following pyroelectricity. The enhanced pyroelectric behavior is demonstrated by efficient ROS production and notable bioprotection. This study exploring the pre-strain effect on the pyroelectricity of ZNR-paper might provide new insights into the piezo-/pyroelectric material-based applications., (© 2022 Wiley-VCH GmbH.)

Non-invasive human sensing based on radio signals has attracted a great deal of research interest and fostered a broad range of innovative applications of localization, gesture recognition, smart health-care, etc., for which a primary primitive is to detect human presence. Previous works have studied the detection of moving humans via signal variations caused by human movements. For stationary people, however, existing approaches often employ a prerequisite scenario-tailored calibration of channel profile in human-free environments. Based on in-depth understanding of human motion induced signal attenuation reflected by PHY layer channel state information (CSI), we propose DeMan, a unified scheme for non-invasive detection of moving and stationary human on commodity WiFi devices. DeMan takes advantage of both amplitude and phase information of CSI to detect moving targets. In addition, DeMan considers human breathing as an intrinsic indicator of stationary human presence and adopts sophisticated mechanisms to detect particular signal patterns caused by minute chest motions, which could be destroyed by significant whole-body motion or hidden by environmental noises. By doing this, DeMan is capable of simultaneously detecting moving and stationary people with only a small number of prior measurements for model parameter determination, yet without the cumbersome scenario-specific calibration. Extensive experimental evaluation in typical indoor environments validates the great performance of DeMan in various human poses and locations and diverse channel conditions. Particularly, DeMan provides a detection rate of around 95% for both moving and stationary people, while identifies human-free scenarios by 96%, all of which outperforms existing methods by about 30%. [ABSTRACT FROM AUTHOR]