The nexus between in-car aerosol concentrations, ventilation and the risk of respiratory infection

Multi-scale risk assessment and mitigations comparison for COVID-19 in urban public transport: A combined field measurement and modeling approach

The outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has caused an unparalleled disruption to daily life. Given that COVID-19 primarily spreads in densely populated indoor areas, urban public transport (UPT) systems pose significant risks. This study presents an analysis of the air change rate in buses, subways, and high speed trains based on measured CO₂ concentrations and passenger behaviors. The resulting values were used as inputs for an infection risk assessment model, which was used to quantitatively evaluate the effects of various factors, including ventilation rates, respiratory activities, and viral variants, on the infection risk. The findings demonstrate that ventilation has a negligible impact on reducing average risks (less than 10.0%) for short-range scales, but can result in a reduction of average risks by 32.1%-57.4% for room scales. When all passengers wear masks, the average risk reduction ranges from 4.5-folds to 7.5-folds. Based on our analysis, the average total reproduction numbers (R) of subways are 1.4-folds higher than buses, and 2-folds higher than high speed trains. Additionally, it is important to note that the Omicron variant may result in a much higher R value, estimated to be approximately 4.9-folds higher than the Delta variant. To reduce disease transmission, it is important to keep the R value below 1. Thus, two indices have been proposed: time-scale based exposure thresholds and spatial-scale based upper limit warnings. Mask wearing provides the greatest protection against infection in the face of long exposure duration to the omicron epidemic.

The effect of activity and face masks on exhaled particles in children

Importance

Despite the high burden of respiratory infections among children, the production of exhaled particles during common activities and the efficacy of face masks in children have not been sufficiently studied.

Objective

To determine the effect of type of activity and mask usage on exhaled particle production in children.

Methods

Healthy children were asked to perform activities that ranged in intensity (breathing quietly, speaking, singing, coughing, and sneezing) while wearing no mask, a cloth mask, or a surgical mask. The concentration and size of exhaled particles were assessed during each activity.

Results

Twenty-three children were enrolled in the study. Average exhaled particle concentration increased by intensity of activity, with the lowest particle concentration during tidal breathing (1.285 particles/cm3 [95% CI 0.943, 1.627]) and highest particle concentration during sneezing (5.183 particles/cm3 [95% CI 1.911, 8.455]). High-intensity activities were associated with an increase primarily in the respirable size (≤ 5 µm) particle fraction. Surgical and cloth masks were associated with lower average particle concentration compared to no mask (P = 0.026 for sneezing). Surgical masks outperformed cloth masks across all activities, especially within the respirable size fraction. In a multivariable linear regression model, we observed significant effect modification of activity by age and by mask type.

Interpretation

Similar to adults, children produce exhaled particles that vary in size and concentration across a range of activities. Production of respirable size fraction particles (≤ 5 µm), the dominant mode of transmission of many respiratory viruses, increases significantly with coughing and sneezing and is most effectively reduced by wearing surgical face masks.

Dynamic ventilation certificate for smart universities using artificial intelligence techniques

The issue of room ventilation has recently gained momentum due to the COVID-19 pandemic. Ventilation is in fact of particular relevance in educational environments. Smart University platforms, today widespread, are a good starting point to offer control services of different relevant indicators in universities. This study advances a Ventilation Quality Certificate (VQC) for Smart Universities. The certificate informs the university community of the ventilation status of its buildings and premises. It also supports senior management's decision-making, because it allows assessing preventive measures and actions taken. The VQC algorithm models the adequacy of classroom ventilation according to the number of persons present. The input used is the organisation's existing data relating to CO₂ concentration and number of room occupants. AI techniques, specifically Artificial Neural Networks (ANN), were employed to determine the relationship between the different data sources included. A prototype of value-added services was developed for the Smart University platform of the University of Alicante, which allowed to implement the resulting models, together with the VQC. The prototype is currently being replicated in other universities. The case study allowed us to validate the VQC, demonstrating both its usefulness and the advantage of using pre-existing university services and resources.

Informing Building Strategies to Reduce Infectious Aerosol Transmission Risk by Integrating DNA Aerosol Tracers with Quantitative Microbial Risk Assessment

Using aerosol-based tracers to estimate risk of infectious aerosol transmission aids in the design of buildings with adequate protection against aerosol transmissible pathogens, such as SARS-CoV-2 and influenza. We propose a method for scaling a SARS-CoV-2 bulk aerosol quantitative microbial risk assessment (QMRA) model for impulse emissions, coughing or sneezing, with aerosolized synthetic DNA tracer concentration measurements. With point-of-emission ratios describing relationships between tracer and respiratory aerosol emission characteristics (i.e., volume and RNA or DNA concentrations) and accounting for aerosolized pathogen loss of infectivity over time, we scale the inhaled pathogen dose and risk of infection with time-integrated tracer concentrations measured with a filter sampler. This tracer-scaled QMRA model is evaluated through scenario testing, comparing the impact of ventilation, occupancy, masking, and layering interventions on infection risk. We apply the tracer-scaled QMRA model to measurement data from an ambulatory care room to estimate the risk reduction resulting from HEPA air cleaner operation. Using DNA tracer measurements to scale a bulk aerosol QMRA model is a relatively simple method of estimating risk in buildings and can be applied to understand the impact of risk mitigation efforts.

Evaluation of indoor environmental quality, personal cumulative exposure dose, and aerosol transmission risk levels inside urban buses in Dalian, China

The transmission of pollutants in buses has an important impact on personal exposure to airborne particles and spread of the COVID-19 epidemic in enclosed spaces. We conducted the following real-time field measurements inside buses: CO₂, airborne particle concentration, temperature, and relative humidity data during peak and off-peak hours in spring and autumn. Correlation analysis was adopted to evaluate the dominant factors influencing CO₂ and particle mass concentrations in the vehicle. The cumulative personal exposure dose to particulate matter and reproduction number were calculated for passengers on a one-way trip. The results showed the in-cabin CO₂ concentrations, with 22.11% and 21.27% of the total time exceeding 1000 ppm in spring and autumn respectively. In-cabin PM_2.5 mass concentration exceeded 35 μm/m³ by 57.35% and 86.42% in spring and autumn, respectively. CO₂ concentration and the cumulative number of passengers were approximately linearly correlated in both seasons, with R value up to 0.896. The cumulative number of passengers had the most impact on PM_2.5 mass concentration among tested parameters. The cumulative personal exposure dose to PM_2.5 during a one-way trip in autumn was up to 43.13 μg. The average reproductive number throughout the one-way trip was 0.26; it was 0.57 under the assumed extreme environment. The results of this study provide an important basic theoretical guidance for the optimization of ventilation system design and operation strategies aimed at reducing multi-pollutant integrated health exposure and airborne particle infection (such as SARS-CoV-2) risks.

Assessment of aerosol persistence in ICUs via low-cost sensor network and zonal models

The COVID-19 pandemic raised public awareness about airborne particulate matter (PM) due to the spread of infectious diseases via the respiratory route. The persistence of potentially infectious aerosols in public spaces and the spread of nosocomial infections in medical settings deserve careful investigation; however, a systematic approach characterizing the fate of aerosols in clinical environments has not been reported. This paper presents a methodology for mapping aerosol propagation using a low-cost PM sensor network in ICU and adjacent environments and the subsequent development of the data-driven zonal model. Mimicking aerosol generation by a patient, we generated trace NaCl aerosols and monitored their propagation in the environment. In positive (closed door) and neutral-pressure (open door) ICUs, up to 6% or 19%, respectively, of all PM escaped through the door gaps; however, the outside sensors did not register an aerosol spike in negative-pressure ICUs. The K-means clustering analysis of temporospatial aerosol concentration data suggests that ICU can be represented by three distinct zones: (1) near the aerosol source, (2) room periphery, and (3) outside the room. The data suggests two-phase plume behavior: dispersion of the original aerosol spike throughout the room, followed by an evacuation phase where "well-mixed" aerosol concentration decayed uniformly. Decay rates were calculated for positive, neutral, and negative pressure operations, with negative-pressure rooms clearing out nearly twice as fast. These decay trends closely followed the air exchange rates. This research demonstrates the methodology for aerosol monitoring in medical settings. This study is limited by a relatively small data set and is specific to single-occupancy ICU rooms. Future work needs to evaluate medical settings with high risks of infectious disease transmission.

A parent-school initiative to assess and predict air quality around a heavily trafficked school

Many primary schools in the UK are situated in close proximity to heavily-trafficked roads, yet long-term air pollution monitoring around such schools to establish factors affecting the variability of exposure is limited. We co-designed a study to monitor particulate matter in different size fractions (PM₁, PM_2.5, PM₁₀), gaseous pollutants (NO₂, O₃ and CO) and meteorological parameters (ambient temperature, relative humidity) over a period of one year. The period included phases of national COVID-19 lockdown and its subsequent easing and removal. Statistical analysis was used to assess the diurnal patterns, pollution hotspots and underlying factors driving changes. A pollution episode was observed early in January 2021, owing to new year celebration fireworks, when the daily average PM_2.5 was around three-times the World Health Organisation limit. PM_2.5 and NO₂ exceeded the threshold limits on 15 and 10 days, respectively, as the lockdown eased and the school reopened, despite the predominant wind direction often being away from the school towards the roads. The peak concentration levels for all pollutants occurred during morning drop-off hours; however, some weekends showed higher or comparable concentrations to those during weekdays. The strong disproportional Pearson correlation between CO and temperature demonstrated the possible contribution of local sources through biomass burning. The impact of lifting restrictions after removing the weather impact showed that the average pollution levels were low in the beginning and increased by up to 22.7 % and 4.2 % for PM_2.5 and NO₂, respectively, with complete easing of lockdown. The Prophet algorithm was implemented to develop a prediction model using an NO₂ dataset that performed moderately (R², 0.48) for a new monthly dataset. This study was able to build a local air pollution database at a school gate, which enabled an understanding of the air pollution variability across the year and allowed evidence-based mitigation strategies to be devised.

Micro-characteristics of a naturally ventilated classroom air quality under varying air purifier placements

A naturally-ventilated operational classroom was instrumented at 18 locations to assess spatial variations of classroom air pollution (CRAP), thermal comfort and ventilation indicators under 10 different scenarios (base scenario without air purifier (AP); three single AP scenarios; three scenarios with two APs at same locations; three scenarios with two APs at different locations). Unlike PM_2.5, monitored PM₁₀ and CO₂ concentrations followed the diurnal occupancy profile. Highest vertical variation (38%) in CO₂ was at the classroom entry zone at 40-300 cm height. CO₂ increased until 225 cm before stratifying further. PM₁₀ increased to highest levels at children sitting height (100 cm) before decreasing to adult breathing height (150 cm). Highest horizontal variations in CO₂ (PM₁₀) were 29% (22%) at 40 cm height between the entry and occupied zones. Teachers' exposure to CO₂ (PM₁₀) in breathing zone varied by up to 6% (3%); the corresponding variations across monitored locations were up to 14% (19%). Teachers' exposure to CO₂ was up to 13% higher than that of children and 18% lower for PM₁₀. Traffic emissions (PM_2.5 and NO_x), secondary pollutants (VOCs and O₃), thermal comfort parameters and noise level in the classroom varied insignificantly among scenarios. PM₁₀ reduction was not doubled by using two air purifiers, which were most effective when placed within the highest PM concentration zone. Cross-comparisons of scenarios showed: use of AP reduced classroom's spatial average PM₁₀ up to 14%; PM₁₀ was reduced by increasing the AP's filtration capacity; and AP had insignificant impact on spatial average CO₂. PM₁₀ showed a maximum reduction of 46% (teacher zone), 62% (occupied zone) and 50% (entry zone) at children's breathing height, depending on usage scenario. This study produced high-resolution data for validating the detailed numerical models for classrooms and informing decision-making on AP's placement to minimise children's exposure to CRAP and re-breathed CO₂.

Stability of SARS-CoV-2 in cold-chain transportation environments and the efficacy of disinfection measures

Background

Low temperature is conducive to the survival of COVID-19. Some studies suggest that cold-chain environment may prolong the survival of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and increase the risk of transmission. However, the effect of cold-chain environmental factors and packaging materials on SARS-CoV-2 stability remains unclear.

Methods

This study aimed to reveal cold-chain environmental factors that preserve the stability of SARS-CoV-2 and further explore effective disinfection measures for SARS-CoV-2 in the cold-chain environment. The decay rate of SARS-CoV-2 pseudovirus in the cold-chain environment, on various types of packaging material surfaces, i.e., polyethylene plastic, stainless steel, Teflon and cardboard, and in frozen seawater was investigated. The influence of visible light (wavelength 450 nm-780 nm) and airflow on the stability of SARS-CoV-2 pseudovirus at -18°C was subsequently assessed.

Results

Experimental data show that SARS-CoV-2 pseudovirus decayed more rapidly on porous cardboard surfaces than on nonporous surfaces, including polyethylene (PE) plastic, stainless steel, and Teflon. Compared with that at 25°C, the decay rate of SARS-CoV-2 pseudovirus was significantly lower at low temperatures. Seawater preserved viral stability both at -18°C and with repeated freeze-thaw cycles compared with that in deionized water. Visible light from light-emitting diode (LED) illumination and airflow at -18°C reduced SARS-CoV-2 pseudovirus stability.

Conclusion

Our studies indicate that temperature and seawater in the cold chain are risk factors for SARS-CoV-2 transmission, and LED visible light irradiation and increased airflow may be used as disinfection measures for SARS-CoV-2 in the cold-chain environment.

Impact of ionizers on prevention of airborne infection in classroom

Infectious diseases (e.g., coronavirus disease 2019) dramatically impact human life, economy and social development. Exploring the low-cost and energy-saving approaches is essential in removing infectious virus particles from indoors, such as in classrooms. The application of air purification devices, such as negative ion generators (ionizers), gains popularity because of the favorable removal capacity for particles and the low operation cost. However, small and portable ionizers have potential disadvantages in the removal efficiency owing to the limited horizontal diffusion of negative ions. This study aims to investigate the layout strategy (number and location) of ionizers based on the energy-efficient natural ventilation in the classroom to improve removal efficiency (negative ions to particles) and decrease infection risk. Three infected students were considered in the classroom. The simulations of negative ion and particle concentrations were performed and validated by the experiment. Results showed that as the number of ionizers was 4 and 5, the removal performance was largely improved by combining ionizer with natural ventilation. Compared with the scenario without an ionizer, the scenario with 5 ionizers largely increased the average removal efficiency from around 20% to 85% and decreased the average infection risk by 23%. The setup with 5 ionizers placed upstream of the classroom was determined as the optimal layout strategy, particularly when the location and number of the infected students were unknown. This work can provide a guideline for applying ionizers to public buildings when natural ventilation is used.

ELECTRONIC SUPPLEMENTARY MATERIAL ESM

the Appendix is available in the online version of this article at 10.1007/s12273-022-0959-z.

Characteristics of collection and inactivation of virus in air flowing inside a winding conduit equipped with 280 nm deep UV-LEDs

A general-purpose virus inactivation unit that can inactivate viruses was developed using deep ultraviolet (DUV) LEDs that emit DUV rays with a wavelength of 280 nm. The inside of the virus inactivation unit is a rectangular conduit with a sharp turn of 180° (sharp-turned rectangular conduit). Virus inactivation is attempted by directly irradiating the air passing through the conduit with DUV rays. The flow characteristics of air and virus particles inside the virus inactivation unit were investigated using numerical simulations. The air was locally accelerated at the sharp turn parts and flowed along the partition plate in the sharp-turned rectangular conduit. The aerosol particles moving in the sharp-turned rectangular conduit were greatly bent in orbit at the sharp turn parts, and then rapidly approached the partition plate at the lower part of the conduit. Consequently, many particles collided with the partition plates behind the sharp-turn parts. SARS-CoV-2 virus was nebulized in the virus inactivation unit, and the RNA concentration and virus inactivation rate with and without the emission of DUV-LEDs were measured in the experiment. The concentration of SARS-CoV-2 RNA was reduced to 60% through DUV-LED irradiation. In addition, SARS-CoV-2 passing through the virus inactivation unit was inactivated below the detection limit by the emission of DUV-LEDs. The virus inactivation rate and the value of the detection limit corresponded to 99.38% and 35.36 TCID₅₀/mL, respectively.

Modeling Clothing as a Vector for Transporting Airborne Particles and Pathogens across Indoor Microenvironments

Evidence suggests that human exposure to airborne particles and associated contaminants, including respiratory pathogens, can persist beyond a single microenvironment. By accumulating such contaminants from air, clothing may function as a transport vector and source of "secondary exposure". To investigate this function, a novel microenvironmental exposure modeling framework (ABICAM) was developed. This framework was applied to a para-occupational exposure scenario involving the deposition of viable SARS-CoV-2 in respiratory particles (0.5-20 μm) from a primary source onto clothing in a nonhealthcare setting and subsequent resuspension and secondary exposure in a car and home. Variability was assessed through Monte Carlo simulations. The total volume of infectious particles on the occupant's clothing immediately after work was 4800 μm³ (5th-95th percentiles: 870-32 000 μm³). This value was 61% (5-95%: 17-300%) of the occupant's primary inhalation exposure in the workplace while unmasked. By arrival at the occupant's home after a car commute, relatively rapid viral inactivation on cotton clothing had reduced the infectious volume on clothing by 80% (5-95%: 26-99%). Secondary inhalation exposure (after work) was low in the absence of close proximity and physical contact with contaminated clothing. In comparison, the average primary inhalation exposure in the workplace was higher by about 2-3 orders of magnitude. It remains theoretically possible that resuspension and physical contact with contaminated clothing can occasionally transmit SARS-CoV-2 between humans.

How can ventilation be improved on public transportation buses? Insights from CO2 measurements

Measurements of CO₂ and counting of occupants were carried out in 37 public bus trips during commuting rush hours in Barcelona (NE Spain) with the aim of evaluating parameters governing ventilation inside the vehicles and proposing actions to improve it. The results show that CO₂ concentrations (1039 and 934 ± 386 ppm, as average and median, during rush hours but with average reduced occupancy due to the fair to be infected by SARS-CoV-2 during the measurement period, and measured in the middle of the busses) are in the lower range of values recorded in the literature for public buses, however an improvement in ventilation is required in a significant proportion of the journeys. Thus, we found better ventilation in the older Euro 3+ (retrofitted with filter traps and selective catalytic reduction) and Euro 5 buses (average 918 ± 257 ppm) than in the hermetically closed new Euro 6 ones (1111 ± 432 ppm). The opening of the windows in the older buses yielded higher ventilation rates (778 ± 432 ppm). The opening of all doors at all stops increases the ventilation by causing a fall in concentrations of 200-350 ppm below inter-stop concentrations, with this effect typically lasting 40-50 s in the hermetically closed new Euro 6 hybrid buses. Based on these results a number of recommendations are offered in order to improve ventilation, including measurement of CO₂ and occupancy, and installation of ventilation fans on the top of the hermetically closed new buses, introducing outdoor air when a given concentration threshold is exceeded. In these cases, a CO₂ sensor installed in the outdoor air intake is also recommended to take into account external CO₂ contributions.