Face-masks save us from SARS-CoV-2 transmission

We present results on the infection risk from SARS-CoV-2 under different scenarios based on measured particle size-dependent mask penetration, measured total inward leakage, measured human aerosol emission for sizes from 10nm to 1mm, and re-hydration on inhalation. Well-mixed room models significantly underestimate the risk of infection for short and direct exposure. To this end, we estimate the upper bound for infection risk with the susceptible in the infectious exhalation cloud or wearing masks by having the masked susceptible inhale the entire exhalation of a masked infectious. Social distances without a mask, even at 3m between speaking individuals results in an upper bound of 90\% for risk of infection after a few minutes. If both wear a surgical mask, the risk of infection for the person speaking remains below 26\% even after 60 minutes. When both the infectious and susceptible wear a well-fitting FFP2 mask, the upper bound for risk is reduced by a factor of 60 compared to surgical masks. In both cases, face leakage is very important. For FFP2 masks, leakage is low in the nasal region and directed upward, which can be further reduced significantly by applying double-sided medical tape there. Considering that the calculated upper bound greatly overestimates the risk of infection, and the fact that with a poorly worn mask even the upper bound we calculated is very low, we conclude that wearing a mask, even with some leakage, provides excellent third party and self-protection

Population Distribution in the Wake of a Sphere

The fluid physics of the heat and mass transfer from an object in its wake has much importance for natural phenomena as well as for many engineering applications. Here, we report numerical results on the population density of the spatial distribution of fluid velocity, pressure, scalar concentration and scalar fluxes of a wake flow past a sphere in the steady wake regime (Reynolds number 25 to 285). We find the population density to be well described by a Lorentzian distribution. We observe this apparently universal form both in the symmetric wake regime and in the more complex three dimensional wake structure of the steady oblique regime with Reynolds number larger than 225. The population density distribution identifies the increase in dimensionless kinetic energy and scalar fluxes with the increase in Reynolds number, whereas the dimensionless scalar population density shows negligible variation with the Reynolds number

Shape matters: long-range transport of microplastic fibers in the atmosphere

Deposition of giant microplastic particles from the atmosphere has been observed in the most remote places on Earth. However, their deposition patterns are difficult to reproduce using current atmospheric transport models. These models usually treat particles as perfect spheres, whereas the real shapes of microplastic particles are often far from spherical. Such particles experience lower settling velocities compared to volume-equivalent spheres, leading to longer atmospheric transport. Here, we present novel laboratory experiments on the gravitational settling of microplastic fibers in air and find that their settling velocities are reduced by up to 76% compared to spheres of the same volume. An atmospheric transport model constrained with the experimental data shows that shape-corrected settling velocities significantly increase the horizontal and vertical transport of particles. Our model results show that microplastic fibers of about 1 mm length emitted in populated areas can reach extremely remote regions of the globe, including the High Arctic, which is not the case for spheres. We also calculate that fibers with lengths of up to 100 {\mu}m settle slowly enough to be lifted high into the stratosphere, where degradation by ultraviolet radiation may release chlorine and bromine, thus potentially damaging the stratospheric ozone layer. These findings suggest that the growing environmental burden and still increasing emissions of plastics pose multiple threats to life on Earth

Dynamic analysis of ash aggregates revealed through HS-HR imaging at Sakurajima volcano (Japan)

Ash aggregation processes during explosive eruptions can effectively influence volcanic plume dispersal and ash sedimentation. Recently, dedicated experiments have been carried out and numerical models have been developed in order to produce reliable forecasting of the ash dispersals. However, including ash aggregation processes in numerical simulations is to date a problematic task for volcanologists, because of the lack of solid field-based datasets required to scale, validate and calibrate models. A field-based dynamical investigation of ash aggregates collected at Sakurajima (Japan) with a High-Speed, High- Resolution camera is here presented. Three main types of ash aggregates are recognized to occur into all the examined samples (Single Particles, Coated Particles, Cored Clusters). Using image analysis techniques, clusters were characterized in terms of average dimension, grain size and shape features of the aggregating ash, pointing out important differences between the different cluster types. Dynamical analysis of falling aggregates allowed a significant set of measurements of terminal velocity, bulk density, and size of a large number of observed falling aggregates to be collected. The resulting data reveal the strong influence of aggregation processes in controlling ash deposition processes at Sakurajima

Epidemiological characteristics of coronavirus disease 2019 (COVID-19) patients in IRAN: A single center study.

BackgroundAn outbreak of COVID-19 in Iran has spread throughout the country. Identifying the epidemiological characteristics of this disease will help to make appropriate decisions and thus control the epidemic. The aim of this study was characterization of the epidemiological features of COVID-19 in Iran.MethodsIn this retrospective study, data related to the epidemiological characteristics of COVID-19 patients admitted to Baqiyatallah Hospital in Tehran, Iran, from 19 February 2020 to 15 April 2020 have been analyzed and reported. Patient characteristics including age, gender and underlying diseases were investigated. Data were collected through patient records. Sex ratio, Case Fatality Rate (CFR) and daily trend of cases were also determined. A multiple logistic regression analysis was also performed to assess affecting factors on mortality.ResultsFrom February 19, 2020 to April 15, 2020, 12870 patients referred to the hospital emergency department, of which 2968 were hospitalized with COVID-19 diagnosis. The majority of cases were in the age group of 50 to 60 years of old. The male-to-female ratio was 1.93:1. A total of 239 deaths occurred among all cases for an overall CFR of 1.85% based on the total number of patients (both outpatient and inpatient) and 8.06% among hospitalized patients. Out of all patients 10.89% had comorbidity. Diabetes, chronic respiratory diseases, hypertension, cardiovascular diseases, chronic Kidney diseases and cancer were the most common comorbidities with 3.81, 2.02 , 1.99 , 1.25, 0.60 and 0.57 %, respectively. Male gender (OR=1.45, 95% CI: 1.08-1.96), older age (OR=1.05, 95% CI: 1.04-1.06) and having underlying diseases (OR=1.53, 95% CI: 1.04-2.24) were significantly associated with mortality.ConclusionsThe results of this study showed that Male gender, older age and having comorbidities were significantly associated with the risk of death among COVID-19 patients. It is important to pay special attention to male elderly patients with underlying diseases

Numerical and experimental investigation of particle terminal velocity and aggregation in volcanic plumes

Recent eruptions, such as Eyjafjallajökull 2010 (Iceland), have strikingly underlined the vulnerability of our highly globalized societies and highlighted significant shortcomings in schemes currently used to forecast the dispersal of volcanic ash. Thus, for the development of appropriate preparedness and mitigation strategies it is important to have a better assessment and understanding of particle sedimentation and aggregation. In this thesis, first a 4-meter high vertical wind tunnel is introduced that is designed to study the aero-dynamical behavior of non-spherical particles. In the next step, existing protocols for the study of size and shape of irregular particles are assessed and new strategies are introduced. In addition, a new general model for estimating the drag coefficient of freely falling non-spherical solid particles is presented. Finally, by applying a state-of-the-art combination of field and numerical strategies the aggregation of volcanic particles is investigated

On the drag of freely falling non-spherical particles

We present a new general model for the prediction of the drag coefficient of non-spherical solid particles of regular and irregular shapes falling in gas or liquid valid for sub-critical particle Reynolds numbers (i.e. Re 1000, tend to fall with their maximum projection area perpendicular to their falling direction, whereas in gases their orientation is random. Second, effects of small-scale surface vesicularity and roughness on the drag coefficient of non-spherical particles found to be < 10%. Finally, the effect of particle orientation on the drag coefficient is discussed and additional correlations are presented to predict the end members of drag coefficient due to change in the particle orientation

Risk assessment for airborne disease transmission by poly-pathogen aerosols

In the case of airborne diseases, pathogen copies are transmitted by droplets of respiratory tract fluid that are exhaled by the infectious and, after partial or full drying, inhaled as aerosols by the susceptible. The risk of infection in indoor environments is typically modelled using the Wells-Riley model or a Wells-Riley-like formulation, usually assuming the pathogen dose follows a Poisson distribution (mono-pathogen assumption). Aerosols that hold more than one pathogen copy, i.e. poly-pathogen aerosols, break this assumption even if the aerosol dose itself follows a Poisson distribution. For the largest aerosols where the number of pathogen in each aerosol can sometimes be several hundred or several thousand, the effect is non-negligible, especially in diseases where the risk of infection per pathogen is high. Here we report on a generalization of the Wells-Riley model and dose-response models for poly-pathogen aerosols by separately modeling each number of pathogen copies per aerosol, while the aerosol dose itself follows a Poisson distribution. This results in a model for computational risk assessment suitable for mono-/poly-pathogen aerosols. We show that the mono-pathogen assumption significantly overestimates the risk of infection for high pathogen concentrations in the respiratory tract fluid. The model also includes the aerosol removal due to filtering by the individuals which becomes significant for poorly ventilated environments with a high density of individuals, and systematically includes the effects of facemasks in the infectious aerosol source and sink terms and dose calculations.Comment: updated file with link to software on GitHu