Spatial and temporal scales of variability for indoor air constituents

Abstract

Historically air constituents have been assumed to be well mixed in indoor environments, with single point measurements and box modeling representing a room or a house. Here we demonstrate that this fundamental assumption needs to be revisited through advanced model simulations and extensive measurements of bleach cleaning. We show that inorganic chlorinated products, such as hypochlorous acid and chloramines generated via multiphase reactions, exhibit spatial and vertical concentration gradients in a room, with short-lived ⋅OH radicals confined to sunlit zones, close to windows. Spatial and temporal scales of indoor constituents are modulated by rates of chemical reactions, surface interactions and building ventilation, providing critical insights for better assessments of human exposure to hazardous pollutants, as well as the transport of indoor chemicals outdoors.

Risk of SARS‐CoV‐2 in a car cabin assessed through 3D CFD simulations

“…However, for the 10% flow condition and mixed‐mode ventilation, the zero‐dimension well‐mixed approach produces quite similar results in terms of both the average risk (and thus R event ) and the probability distribution of secondary cases. The parameters under which well‐mixed approaches are most defensible requires further evaluation, using CFD and possibly field investigations (e.g., tracer tests) to inform such generalizations; nonetheless, it is clear that well‐mixed models can perform very well in scenarios characterized by low air exchange rates where the flow patterns are not able to provide a proper particle removal from the breathing zone of the exposed subject: this is also typical of other larger indoor environments, such as naturally‐ventilated buildings, 32 where well‐mixed models were shown to predict the attack rates of documented SARS‐CoV‐2 outbreaks. 21 , 27 …”

“…However, for the 10% flow condition and mixed-mode ventilation, the zero-dimension well-mixed approach produces quite similar results in terms of both the average risk (and thus R event ) and the probability distribution of secondary cases. The parameters under which well-mixed approaches are most defensible requires further evaluation, using CFD and possibly F I G U R E 1 3 Spatial particle distribution after 30 min in case of windshield defrosting ventilation mode at 50% (Q50%), breathing activity, and driver infected field investigations (e.g., tracer tests) to inform such generalizations; nonetheless, it is clear that well-mixed models can perform very well in scenarios characterized by low air exchange rates where the flow patterns are not able to provide a proper particle removal from the breathing zone of the exposed subject: this is also typical of other larger indoor environments, such as naturally-ventilated buildings, 32 where well-mixed models were shown to predict the attack rates of documented SARS-CoV-2 outbreaks. 21,27 We note the solutions here reported are very specific of the car cabin under investigation and of the boundary conditions set, as an example, we have not considered: (i) the effect of mitigation solutions, such as vaccination and face masks, 21 that could reduce the individual risk of infection of passengers, (ii) the presence of a possible fifth passenger sitting in the middle of the rear row typical of five-seater cars (please consider that his/her exposure could be different from the other passengers sitting on the rear seats due to limited shielding effect of the front seats), (iii) the effect of side window opening, (iv) the effect of the journey duration.…”

“…are not available. 27 , 29 Nonetheless, perfectly mixed conditions (hereinafter referred to as “well‐mixed”) are unlikely in spaces with high ventilation rates, 30 , 31 thus, such hypothesis is even less accurate for large indoor environments characterized by reduced mixing 32 or small confined spaces, as car cabins, where the position of inlet air vents of the HVAC system, the airflow rate entering the car cabin, the air recirculation and its filtration can significantly affect the airflow in the cabin, and then the exposure and risk of passengers. 33 , 34 Indeed, even if the average air exchange rate in car cabin can be quite high (e.g., >100 h −1 when high fan speeds are set or windows are kept open 33 , 35 ), stagnation regions can occur as a result of the specific airflows pattern across the cabin itself.…”

Link between SARS-CoV-2 emissions and airborne concentrations: Closing the gap in understanding

“…Nonetheless, several theoretical and numerical studies have demonstrated that the droplet and pollutant concentrations as well as the risk of infection are affected by the distance from the source only in the close proximity of the source, which was evaluated roughly equal to 1.5 m ( Cortellessa et al, 2021 , Chen et al, 2020 , Li, 2021 ). Beyond that distance the concentration/risk can be considered homogeneously distributed at least for distances higher than those characteristics of the investigated ward ( Lakey et al, 2021 ). In the case of initial concentration equal to 0, the indoor SARS-CoV-2 concentration can be estimated as: …”

A novel VOC breath tracer method to evaluate indoor respiratory exposures in the near- and far-fields

“…[15][16][17][18] A study of temporal and spatial scales suggests that chemical compounds as well as particles in the range of 1-10 µm with persistent residence time exhibit spatial gradients that are signi cantly controlled by ventilation rates. 19 Additionally, controlled experiments on participants who were diagnosed with COVID-19 were used to study the abundance of SARS-CoV-2 viral RNA copies in room aerosols. The authors found that the near-eld was associated with a higher number of virus RNA copies, and statistically higher carbon dioxide (CO 2 ), and particle counts of 0.3 µm -2.5 µm than in the far-eld.…”