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In this paper a numerical methodology for close proximity exposure (<2m) is applied to the analysis of aerosol airborne dispersion and SARS-CoV-2 potential infection risk during short journeys in passenger cars. It consists of a three-dimensional transient Eulerian-Lagrangian numerical model coupled with a recently proposed SARS-CoV-2 emission approach, using the open-source software OpenFOAM. The numerical tool, validated by Particle Image Velocimetry (PIV), is applied to the simulation of aerosol droplets emitted by a contagious subject in a car cabin during a 30-minute journey and to the integrated risk assessment for SARS-CoV-2 for the other passengers. The effects of different geometrical and thermo-fluid-dynamic influence parameters are investigated, showing that both the position of the infected subject and the ventilation system design affect the amount of virus inhaled and the highest-risk position inside the passenger compartment. Calculated infection risk, for susceptible passengers in the car, can reach values up to 59%. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.
RESUMEN
The airborne transmission in indoor environments represents the main pathway of respiratory pathogens, and most of the indoor environments do not have adequate ventilation to contain the risk of infection. This is particularly relevant for gathering spaces such as restaurants, schools, offices, etc. due to the long exposure times and high crowding levels. In this paper we investigated the effectiveness of a novel patented personal air cleaner in reducing the airborne transmission of respiratory pathogens both in close proximity (considering a typical face-to-face configuration at a conversational distance) and in shared indoor environments despite maintaining distancing (lecture room). The effectiveness of the portable protection device was investigated using complex transient 3D Computational Fluid Dynamics (CFD) numerical simulations. The mathematical model employed, validated through experimental measurements, is based on a Eulerian-Lagrangian approach, describing the air flow as the continuous phase and infectious respiratory particles as the discrete phase. The CFD analyses revealed that the air cleaner could strongly reduce the inhalation of respiratory pathogens in both the investigated scenarios. The air cleaner effectiveness in the case of a close proximity scenario, expressed as relative reduction of volume of infectious respiratory particles inhaled by the exposed subject, resulted >92%. In the case of use in a shared indoor environment, instead, during a 2-h lesson, the relative reduction of volume concentration of infectious particles in the breathing zone of the exposed subject was >99%. © 2023 Elsevier Ltd
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Public transport environments are thought to play a key role in the spread of SARS-CoV-2 worldwide. Indeed, high crowding indexes (i.e. high numbers of people relative to the vehicle size), inadequate clean air supply, and frequent extended exposure durations make transport environments potential hotspots for transmission of respiratory infections. During the COVID-19 pandemic, generic mitigation measures (e.g. physical distancing) have been applied without also considering the airborne transmission route. This is due to the lack of quantified data about airborne contagion risk in transport environments.In this study, we apply a novel combination of close proximity and room-scale risk assessment approaches for people sharing public transport environments to predict their contagion risk due to SARS-CoV-2 respiratory infection. In particular, the individual infection risk of susceptible subjects and the transmissibility of SARS-CoV-2 (expressed through the reproduction number) are evaluated for two types of buses, differing in terms of exposure time and crowding index: urban and long-distance buses. Infection risk and reproduction number are calculated for different scenarios as a function of the ventilation rates (both measured and estimated according to standards), crowding indexes, and travel times. The results show that for urban buses, the close proximity contribution significantly affects the maximum occupancy to maintain a reproductive number of <1. In particular, full occupancy of the bus would be permitted only for an infected subject breathing, whereas for an infected subject speaking, masking would be required. For long-distance buses, full occupancy of the bus can be maintained only if specific mitigation solutions are simultaneously applied. For example, for an infected person speaking for 1 h, appropriate filtration of the recirculated air and simultaneous use of FFP2 masks would permit full occupancy of the bus for a period of almost 8 h. Otherwise, a high percentage of immunized persons (>80%) would be needed.(c) 2022 China University of Geosciences (Beijing) and Peking University. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).
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With the COVID-19, telepresence robots have re-gained a particular attention as tool to keep in contact with people remotely. Over the years, a lot of studies have demonstrated the efficacy of telepresence robots for communication with respect to other typologies of devices. However, most of the works have focused on the short-term interaction between the robot and the users. Herein, we put the effort to design telepresence robots for continuously caring elderly people in the domestic scenario. With this purpose, in this work, we integrate different AI-driven services, developed inside the SI-Robotics project, to enhance the capabilities of a commercial robotic platform and to provide ecological interaction over time. © 2021 Copyright for this paper by its authors.
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Car cabin micro-environment represents a potential hotspot for transmission of respiratory infections related to possible high concentration levels of viruses and bacteria and to reduced social distance between occupants. Since Heating, Ventilation and Air Conditioning (HVAC) system in a vehicle influences velocity and temperature fields, the position of inlet air vents, the air flow rate entering the car cabin, the air recirculation, the passenger number and location etc. highly influence the thermal comfort and potential health risks for occupants. In this paper, a Eulerian-Lagrangian model is adopted to numerically analyse transient non-isothermal aerosol airborne dispersion in a passenger car cabin. Numerical results are validated against PIV measurements and the performances of different turbulence models are analysed. The validated numerical model is applied to the simulation of aerosol droplets emitted by a contagious subject in a car cabin during a 15-min journey. Two occupants are present in the car cabin and different scenarios for the ventilation system and the occupants’ position are investigated. The aim of the present paper is to provide a properly validated numerical tool that can be applied on one side to the assessment of thermal comfort of occupants and, on the other side, to the analysis of potential infection risk with aerosol transmissible pathogens (e.g. SARS-CoV-2 virus) during short journeys.
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Among more dramatic effects, the COVID-19 scenario also raised the need for new online information and communication services, promoting the spread of software solutions whose usefulness will last well beyond the pandemic situation. Particularly in the cultural heritage domain, it has been unveiled the relevance of new AI-based approaches, able to dynamically aggregate information and making them available for a customized fruition aimed to the individual cultural growth. Here, we integrate machine learning techniques for the automatic generation of contents for an intelligent tutoring system grounded on automated planning techniques. We present a solution for semantic, intelligent creation of personalized cultural contents, born as a lesson-making assistant, but developed as to become a multi-function “cultural crossover”, useful in the frame of a wide range of planning, dissemination, and managing activities for cultural heritage contents. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
RESUMEN
Although the interpersonal distance represents an important parameter affecting the risk of infection due to respiratory viruses, the mechanism of exposure to exhaled droplets remains insufficiently characterized. In this study, an integrated risk assessment is presented for SARS-CoV-2 close proximity exposure between a speaking infectious subject and a susceptible subject. It is based on a three-dimensional transient numerical model for the description of exhaled droplet spread once emitted by a speaking person, coupled with a recently proposed SARS-CoV-2 emission approach. Particle image velocimetry measurements were conducted to validate the numerical model. The contribution of the large droplets to the risk is barely noticeable only for distances well below 0.6 m, whereas it drops to zero for greater distances where it depends only on airborne droplets. In particular, for short exposures (10 s) a minimum safety distance of 0.75 m should be maintained to lower the risk below 0.1%; for exposures of 1 and 15 min this distance increases to about 1.1 and 1.5 m, respectively. Based on the interpersonal distances across countries reported as a function of interacting individuals, cultural differences, and environmental and sociopsychological factors, the approach presented here revealed that, in addition to intimate and personal distances, particular attention must be paid to exposures longer than 1 min within social distances (of about 1 m).