A solution-processed radiative cooling glass.

Passive daytime radiative cooling materials could reduce the energy needed for building cooling up to 60% by reflecting sunlight and emitting long-wave infrared (LWIR) radiation into the cold Universe (~3 kelvin). However, developing passive cooling structures that are both practical to manufacture and apply while also displaying long-term environmental stability is challenging. We developed a randomized photonic composite consisting of a microporous glass framework that features selective LWIR emission along with relatively high solar reflectance and aluminum oxide particles that strongly scatter sunlight and prevent densification of the porous structure during manufacturing. This microporous glass coating enables a temperature drop of ~3.5° and 4°C even under high-humidity conditions (up to 80%) during midday and nighttime, respectively. This radiative "cooling glass" coating maintains high solar reflectance even when exposed to harsh conditions, including water, ultraviolet radiation, soiling, and high temperatures.

Ceiling impact on air disinfection performance of Upper-Room Germicidal Ultraviolet (UR-GUV).

This study used Computational Fluid Dynamics (CFD) to investigate air disinfection for SARS-CoV-2 by the Upper-Room Germicidal Ultraviolet (UR-GUV), with focus on ceiling impact. The study includes three indoor settings, i.e., low (airport bus), medium (classroom) and high (rehearsal room) ceilings, which were ventilated with 100% clean air (CA case), 80% air-recirculation with a low filtration (LF case), and 80% air-recirculation with a high filtration (HF case). According to the results, using UR-GUV can offset the increased infection risk caused by air recirculation, with viral concentrations in near field (NF) and far field (FF) in the LF case similar to those in the CA case. In the CA case, fraction remaining (FR) was 0.48-0.73 with 25% occupancy rate (OR) and 0.49-0.91 with 45% OR in the bus, 0.41 in NF and 0.11 in FF in the classroom, and 0.18 in NF and 0.09 in FF in the rehearsal room. Obviously, UR-GUV performance in NF can be improved in a room with a high ceiling where FR has a power relationship with UV zone height. As using UR-GUV can only extend the exposure time to get infection risk of 1% (T 1% ) to 8 min in NF in the classroom, and 47 min in NF in the rehearsal room, it is necessary to abide by social distancing in the two rooms. In addition, T 1% in FF was calculated to be 18.3 min with 25% OR and 21.4% with 45% OR in the airport bus, showing the necessity to further wear a mask.

Characterization of aerosol plumes from singing and playing wind instruments associated with the risk of airborne virus transmission.

The exhalation of aerosols during musical performances or rehearsals posed a risk of airborne virus transmission in the COVID-19 pandemic. Previous research studied aerosol plumes by only focusing on one risk factor, either the source strength or convective transport capability. Furthermore, the source strength was characterized by the aerosol concentration and ignored the airflow rate needed for risk analysis in actual musical performances. This study characterizes aerosol plumes that account for both the source strength and convective transport capability by conducting experiments with 18 human subjects. The source strength was characterized by the source aerosol emission rate, defined as the source aerosol concentration multiplied by the source airflow rate (brass 383 particle/s, singing 408 particle/s, and woodwind 480 particle/s). The convective transport capability was characterized by the plume influence distance, defined as the sum of the horizontal jet length and horizontal instrument length (brass 0.6 m, singing 0.6 m and woodwind 0.8 m). Results indicate that woodwind instruments produced the highest risk with approximately 20% higher source aerosol emission rates and 30% higher plume influence distances compared with the average of the same risk indicators for singing and brass instruments. Interestingly, the clarinet performance produced moderate source aerosol concentrations at the instrument's bell, but had the highest source aerosol emission rates due to high source airflow rates. Flute performance generated plumes with the lowest source aerosol emission rates but the highest plume influence distances due to the highest source airflow rate. Notably, these comprehensive results show that the source airflow is a critical component of the risk of airborne disease transmission. The effectiveness of masking and bell covering in reducing aerosol transmission is due to the mitigation of both source aerosol concentrations and plume influence distances. This study also found a musician who generated approximately five times more source aerosol concentrations than those of the other musicians who played the same instrument. Despite voice and brass instruments producing measurably lower average risk, it is possible to have an individual musician produce aerosol plumes with high source strength, resulting in enhanced transmission risk; however, our sample size was too small to make generalizable conclusions regarding the broad musician population.

Tradeoffs between ventilation, air mixing, and passenger density for the airborne transmission risk in airport transportation vehicles.

Airport transportation vehicles, such as buses, aerotrains, and shuttles, provide important passenger transfer services in airports. This study quantitatively investigated COVID-19 aerosol infection risk and identified acceptable operational conditions, such as passenger occupancy rates and duration of rides, given the performance of vehicle ventilation. The greatest risk to the largest number of passengers is from an index case whose exhaled breath would take the longest time to exit the vehicle. The study identified such a case based on ventilation patterns, and it tracked the spread of viral aerosols (5 µm) by using the Wells-Riley equation to predict aerosol infection risk distribution. These distributions allowed a definition of an imperfect mixing degree (δ) as the ratio of actual risk and the calculated risk under a perfect mixing condition, and further derived regression equations to predict δ in the far-field (FF) and near-field (NF) of each passenger. These results revealed an order of magnitude higher aerosol infection risk in NF than in FF. For example, with a ventilation rate of 58 ACH (air changes per hour) and a 45% occupancy rate, unmasked passengers should stay up to 15 min in the bus and 35 min in the shuttle to limit infection risk in NF within 10%. These also indicate that masking is an important and effective risk reduction measure in transportation vehicles, especially important in NF. Overall, the analysis of imperfect air mixing allows direct comparison of risks in different transportation vehicles and a structured approach to development of policy recommendations.

Measurements and Simulations of Aerosol Released while Singing and Playing Wind Instruments.

Outbreaks from choir performances, such as the Skagit Valley Choir, showed that singing brings potential risk of COVID-19 infection. There is less known about the risks of airborne infection from other musical performances, such as playing wind instruments or performing theater. In addition, it is important to understand methods that can be used to reduce infection risk. In this study, we used a variety of methods, including flow visualization, aerosol and CO2 measurements, and computational fluid dynamics (CFD) modeling to understand the different components that can lead to transmission risk from musical performance and risk mitigation. This study was possible because of a partnership across academic departments and institutions and collaboration with the National Federation of State High School Associations and the College Band Directors National Association. The interdisciplinary team enabled us to understand the various aspects of aerosol transmission risk from musical performance and to quickly implement strategies in music classrooms during the COVID-19 pandemic. We found that plumes from musical performance were highly directional, unsteady and varied considerably in time and space. Aerosol number concentration measured at the bell of the clarinet was comparable to that of singing. Face and bell masks attenuated plume velocities and lengths and decreased aerosol concentrations measured in front of the masks. CFD modeling showed differences between indoor and outdoor environments and that the lowest risk of airborne COVID-19 infection occurred at less than 30 min of exposure indoors and less than 60 min outdoors.

Ventilation and laboratory confirmed acute respiratory infection (ARI) rates in college residence halls in College Park, Maryland.

Strategies to protect building occupants from the risk of acute respiratory infection (ARI) need to consider ventilation for its ability to dilute and remove indoor bioaerosols. Prior studies have described an association of increased self-reported colds and influenza-like symptoms with low ventilation but have not combined rigorous characterization of ventilation with assessment of laboratory confirmed infections. We report a study designed to fill this gap. We followed laboratory confirmed ARI rates and measured CO2 concentrations for four months during the winter-spring of 2018 in two campus residence halls: (1) a high ventilation building (HVB) with a dedicated outdoor air system that supplies 100% of outside air to each dormitory room, and (2) a low ventilation building (LVB) that relies on infiltration as ventilation. We enrolled 11 volunteers for a total of 522 person-days in the HVB and 109 volunteers for 6069 person-days in the LVB, and tested upper-respiratory swabs from symptomatic cases and their close contacts for the presence of 44 pathogens using a molecular assay. We observed one ARI case in the HVB (0.70/person-year) and 47 in the LVB (2.83/person-year). Simultaneously, 154 CO2 sensors distributed primarily in the dormitory rooms collected 668,390 useful data points from over 1 million recorded data points. Average and standard deviation of CO2 concentrations were 1230 ppm and 408 ppm in the HVB, and 1492 ppm and 837 ppm in the LVB, respectively. Importantly, this study developed and calibrated multi-zone models for the HVB with 229 zones and 983 airflow paths, and for the LVB with 529 zones and 1836 airflow paths by using a subset of CO2 data for model calibration. The models were used to calculate ventilation rates in the two buildings and potential for viral aerosol migration between rooms in the LVB. With doors and windows closed, the average ventilation rate was 12 L/s in the HVB dormitory rooms and 4 L/s in the LVB dormitory rooms. As a result, residents had on average 6.6 L/(s person) of outside air in the HVB and 2.3 L/(s person) in the LVB. LVB rooms located at the leeward side of the building had smaller average ventilation rates, as well as a somewhat higher ARI incidence rate and average CO2 concentrations when compared to those values in the rooms located at the windward side of the building. Average ventilation rates in twenty LVB dormitory rooms increased from 2.3 L/s to 7.5 L/s by opening windows, 3.6 L/s by opening doors, and 8.8 L/s by opening both windows and doors. Therefore, opening both windows and doors in the LVB dormitory rooms can increase ventilation rates to the levels comparable to those in the HVB. But it can also have a negative effect on thermal comfort due to low outdoor temperatures. Simulation results identified an aerobiologic pathway from a room occupied by an index case of influenza A to a room occupied by a possible secondary case.

A radiative cooling structural material.

Reducing human reliance on energy-inefficient cooling methods such as air conditioning would have a large impact on the global energy landscape. By a process of complete delignification and densification of wood, we developed a structural material with a mechanical strength of 404.3 megapascals, more than eight times that of natural wood. The cellulose nanofibers in our engineered material backscatter solar radiation and emit strongly in mid-infrared wavelengths, resulting in continuous subambient cooling during both day and night. We model the potential impact of our cooling wood and find energy savings between 20 and 60%, which is most pronounced in hot and dry climates.

Modeling Sustainability: Population, Inequality, Consumption, and Bidirectional Coupling of the Earth and Human Systems.

Over the last two centuries, the impact of the Human System has grown dramatically, becoming strongly dominant within the Earth System in many different ways. Consumption, inequality, and population have increased extremely fast, especially since about 1950, threatening to overwhelm the many critical functions and ecosystems of the Earth System. Changes in the Earth System, in turn, have important feedback effects on the Human System, with costly and potentially serious consequences. However, current models do not incorporate these critical feedbacks. We argue that in order to understand the dynamics of either system, Earth System Models must be coupled with Human System Models through bidirectional couplings representing the positive, negative, and delayed feedbacks that exist in the real systems. In particular, key Human System variables, such as demographics, inequality, economic growth, and migration, are not coupled with the Earth System but are instead driven by exogenous estimates, such as UN population projections. This makes current models likely to miss important feedbacks in the real Earth-Human system, especially those that may result in unexpected or counterintuitive outcomes, and thus requiring different policy interventions from current models. The importance and imminence of sustainability challenges, the dominant role of the Human System in the Earth System, and the essential roles the Earth System plays for the Human System, all call for collaboration of natural scientists, social scientists, and engineers in multidisciplinary research and modeling to develop coupled Earth-Human system models for devising effective science-based policies and measures to benefit current and future generations.

Advanced computational modeling for in vitro nanomaterial dosimetry.

BACKGROUND: Accurate and meaningful dose metrics are a basic requirement for in vitro screening to assess potential health risks of engineered nanomaterials (ENMs). Correctly and consistently quantifying what cells "see," during an in vitro exposure requires standardized preparation of stable ENM suspensions, accurate characterizatoin of agglomerate sizes and effective densities, and predictive modeling of mass transport. Earlier transport models provided a marked improvement over administered concentration or total mass, but included assumptions that could produce sizable inaccuracies, most notably that all particles at the bottom of the well are adsorbed or taken up by cells, which would drive transport downward, resulting in overestimation of deposition. METHODS: Here we present development, validation and results of two robust computational transport models. Both three-dimensional computational fluid dynamics (CFD) and a newly-developed one-dimensional Distorted Grid (DG) model were used to estimate delivered dose metrics for industry-relevant metal oxide ENMs suspended in culture media. Both models allow simultaneous modeling of full size distributions for polydisperse ENM suspensions, and provide deposition metrics as well as concentration metrics over the extent of the well. The DG model also emulates the biokinetics at the particle-cell interface using a Langmuir isotherm, governed by a user-defined dissociation constant, K(D), and allows modeling of ENM dissolution over time. RESULTS: Dose metrics predicted by the two models were in remarkably close agreement. The DG model was also validated by quantitative analysis of flash-frozen, cryosectioned columns of ENM suspensions. Results of simulations based on agglomerate size distributions differed substantially from those obtained using mean sizes. The effect of cellular adsorption on delivered dose was negligible for K(D) values consistent with non-specific binding (> 1 nM), whereas smaller values (≤ 1 nM) typical of specific high-affinity binding resulted in faster and eventual complete deposition of material. CONCLUSIONS: The advanced models presented provide practical and robust tools for obtaining accurate dose metrics and concentration profiles across the well, for high-throughput screening of ENMs. The DG model allows rapid modeling that accommodates polydispersity, dissolution, and adsorption. Result of adsorption studies suggest that a reflective lower boundary condition is appropriate for modeling most in vitro ENM exposures.

Numerical Modeling of Indoor Environment with a Ceiling Fan and an Upper-Room Ultraviolet Germicidal Irradiation System.

This study proposes a numerical modeling method for the indoor environment with ceiling fans and upper-room ultraviolet germicidal irradiation (UR-UVGI) fixtures. The numerical modeling deployed steady-state Computational Fluid Dynamics (CFD) with a rotating reference frame to simulate the rotation of fan blades. CFD was validated with experimental data of velocity field and fraction of microorganism remaining at the exhaust diffuser. The fraction of microorganism remaining represented the ratio of the concentration of airborne microorganisms measured with UVGI turned on to the one measured with UVGI turned off. According to the validation results, the CFD model correctly reproduced the air movement induced by the rotation of ceiling fan. When the ambient ventilation rate was 2 ACH (air changes per hour) or 6 ACH, the CFD model accurately predicted the average vertical speeds in the section 2.44 m above the floor with the errors less than 10%, regardless of the ceiling fan's rotational direction or speed. In addition, the simulation results showed that the fraction of microorganism remaining increased with the ambient air exchange rate when the fan blew air downward with a rotational speed as high as 235 rpm, which corresponded with the experimental results. Furthermore, the simulation results accurately predicted the fraction of microorganism remaining when the ambient air exchange rate was 2 ACH. We conclude that this novel numerical model can reproduce the effects of ceiling fans and UR-UVGI fixtures on indoor environment, and should aid in the investigation of the impact of ceiling fans on UR-UVGI disinfection efficacy.

Numerical investigation of upper-room UVGI disinfection efficacy in an environmental chamber with a ceiling fan.

This study investigated the disinfection efficacy of the upper-room ultraviolet germicidal irradiation (UR-UVGI) system with ceiling fans. The investigation used the steady-state computational fluid dynamics (CFD) simulations to solve the rotation of ceiling fan with a rotating reference frame. Two ambient air exchange rates, 2 and 6 air changes per hour (ACH), and four downward fan rotational speeds, 0, 80, 150 and 235 rpm were considered. In addition, the passive scalar concentration simulations incorporated ultraviolet (UV) dose by two methods: one based on the total exposure time and average UV fluence rate, and another based on SVE3* (New Scale for Ventilation Efficiency 3), originally defined to evaluate the mean age of the air from an air supply opening. Overall, the CFD results enabled the evaluation of UR-UVGI disinfection efficacy using different indices, including the fraction of remaining microorganisms, equivalent air exchange rate, UR-UVGI effectiveness and tuberculosis infection probability by the Wells-Riley equation. The results indicated that air exchange rate was the decisive factor for determining UR-UVGI performance in disinfecting indoor air. Using a ceiling fan could also improve the performance in general. Furthermore, the results clarified the mechanism for the ceiling fan to influence UR-UVGI disinfection efficacy.

An advanced numerical model for the assessment of airborne transmission of influenza in bus microenvironments.

A CFD-based numerical model was integrated with the Wells-Riley equation to numerically assess the risk of airborne influenza infection in a popular means of public transportation, e.g. the bus microenvironment. Three mixing ventilation methods, which are widely used in current bus configurations, and an alternative displacement ventilation method were numerically assessed in terms of their ability to limit the risk of airborne influenza infection. Furthermore, both the non air-recirculation and air-recirculation with filtration ventilation modes were investigated in terms of the influenza infection probability. According to the simulation results, air-recirculation mode with high efficiency filtration was found to cause almost the same infection risk as non air-recirculation mode (100% outdoor air supply), which indicated a potential benefit of filtration in reducing the infection risk. Additionally, for the commonly used mixing ventilation methods, air distribution method, location of return/exhaust opening and seat arrangement affected the airborne transmission of influenza between passengers. The displacement ventilation method was found to be more effective in limiting the risk of airborne infection. Overall, the developed numerical model can provide insights into how the micro-environmental conditions affect airborne infection transmission in buses. This numerical model can assist in developing effective control strategies related to airborne transmitted diseases for other frequently used public transportation systems, such as trains and airplanes.

Real-time identification of indoor pollutant source positions based on neural network locator of contaminant sources and optimized sensor networks.

A growing interest in security and occupant exposure to contaminants revealed a need for fast and reliable identification of contaminant sources during incidental situations. To determine potential contaminant source positions in outdoor environments, current state-of-the-art modeling methods use computational fluid dynamic simulations on parallel processors. In indoor environments, current tools match accidental contaminant distributions with cases from precomputed databases of possible concentration distributions. These methods require intensive computations in pre- and postprocessing. On the other hand, neural networks emerged as a tool for rapid concentration forecasting of outdoor environmental contaminants such as nitrogen oxides or sulfur dioxide. All of these modeling methods depend on the type of sensors used for real-time measurements of contaminant concentrations. A review of the existing sensor technologies revealed that no perfect sensor exists, but intensity of work in this area provides promising results in the near future. The main goal of the presented research study was to extend neural network modeling from the outdoor to the indoor identification of source positions, making this technology applicable to building indoor environments. The developed neural network Locator of Contaminant Sources was also used to optimize number and allocation of contaminant concentration sensors for real-time prediction of indoor contaminant source positions. Such prediction should take place within seconds after receiving real-time contaminant concentration sensor data. For the purpose of neural network training, a multizone program provided distributions of contaminant concentrations for known source positions throughout a test building. Trained networks had an output indicating contaminant source positions based on measured concentrations in different building zones. A validation case based on a real building layout and experimental data demonstrated the ability of this method to identify contaminant source positions. Future research intentions are focused on integration with real sensor networks and model improvements for much more complicated contamination scenarios.