Computational characterization of the behavior of a saliva droplet in a social environment

1 Vol.:(0123456789) Scientific Reports | (2022) 12:6405 | https://doi.org/10.1038/s41598-022-10180-5 www.nature.com/scientificreports Computational characterization of the behavior of a saliva droplet in a social environment Ainara Ugarte‑Anero1, Unai Fernandez‑Gamiz1*, Koldo Portal‑Porras1, Ekaitz Zulueta2 & Oskar Urbina‑Garcia1 The conduct of respiratory droplets is the basis of the study to reduce the spread of a virus in society. The pandemic suffered in early 2020 due to COVID‑19 shows the lack of research on the evaporation and fate of droplets exhaled in the environment. The current study, attempts to provide solution through computational fluid dynamics techniques based on a multiphase state with the help of Eulerian–Lagrangian techniques to the activity of respiratory droplets. A numerical study has shown how the behavior of droplets of pure water exhaled in the environment after a sneeze or cough have a dynamic equal to the experimental curve of Wells. The droplets of saliva have been introduced as a saline solution. Considering the mass transferred and the turbulence created, the results has showed that the ambient temperature and relative humidity are parameters that significantly affect the evaporation process, and therefore to the fate. Evaporation time tends to be of a higher value when the temperature affecting the environment is lower. With constant parameters of particle diameter and ambient temperature, an increase in relative humidity increases the evaporation time. A larger particle diameter is consequently transported at a greater distance, since the opposite force it affects is the weight. Finally, a neural network‑based model is presented to predict particle evaporation time. After experiencing the biggest pandemic in the world, so far, of the twenty-first century, experts have focused on the investigation of the consequences of living this situation, both, economically and sanitarily. The state lived during these two years ago, has left a society very different from the one known before this phenomenon. Two years of uncertainty have developed several measures to combat this virus. The first measure was quarantine for approximately two months. Once on the street, the use of masks was forced. Different types of masks were designed. Notably, mathematical studies such as Ugarte-Anero etal.1 demonstrate through a Computational Fluid Dynamics (CFD) research that the face-shields, which cover the entire surface of the face, do not fully protect a person from sneezing. Later, and currently is developing, the invention of different vaccines. Although different vaccines designed by large pharmaceutical companies are known, the World Health Organization (WHO) differentiates between 3 types; those that use a virus or a whole bacterium, those that use fragments that introduce an immune system response and those that use only genetic material. But the situation got worse. As expected, the virus mutated, creating new variants. Variant B.1.617.2 (delta) identified in India and variant B.1.1.7 (Alpha) identified in England, show different behavior to vaccine efficacy, according to Bernal etal.2. Although, after several tests, between these two types of variants, a slight difference in effectiveness is observed when the two doses are given, on the other hand, there is a greater difference when only one dose has been applied. The study by Su etal.3 reports that protein S is the best antigen that should be included in vaccines against COVID-19 to achieve an effective and safe. This disease has given a boost to the field of research that drives aerosol studies. It has been researched with the aim of providing a solution to the famous SARS-CoV-2, but all these studies are based on explaining the functioning of the exhaled air to the environment, which is the route of contagion of all diseases, either by major droplets or by aerosols, according to Leung etal.4. The human body exhales particles between 10µm and 100µm of diameter in a sneeze, according to the numerical study of Chillón etal.4, but it is not considered aerosol until the particle reaches 5µm of diameter, Chatterjee etal.5. When a person coughs, speaks, or sneezes, exhales to the environment particles with great contagion power. These particles are formed of saliva and epithelial lining fluid (ELF), Pöhlker6. Saliva can vary its composition depending on the person, according to Almeida PDV etal.7. OPEN 1Nuclear Engineering and Fluid Mechanics Department, University of the Basque Country, UPV/EHU, Nieves Cano 12, 01006 Vitoria-Gasteiz, Araba, Spain. 2System Engineering and Automation Control Department, University of the Basque Country, UPV/EHU, Nieves Cano 12, 01006 Vitoria-Gasteiz, Araba, Spain. *email: unai.fernandez@ ehu.eus 2 Vol:.(1234567890) Scientific Reports | (2022) 12:6405 | https://doi.org/10.1038/s41598-022-10180-5 www.nature.com/scientificreports/ Even if you focus on the same person, depending on what you eat during that day, it can vary the composition of saliva. Composed of 99% of water and 1% composed of other elements, notably sodium and chlorine for being more abundant, Almeida PDV etal.7, CFD studies make an approximation to saliva as a saline solution of 0.9 w/v, Xie etal.8, being the most accurate approximation of evaporation time to the aerosol, Ugarte-Anero etal.1. Even so, droplets of saliva have the same method of evaporation as a droplet of pure water. According to Bozic etal.9 , the droplet gradually evaporates over time, reducing its size. In this first stage it gets rid of water (H2O) molecules. Once that H2O has evaporated, the result is what is called droplet residue, which depends on non-water solutes inside the droplet. Lieber etal.10 indicates that the so-called droplet residue will remain in the environment for hours and will have a size that is 20% of the initial size of the particle studied. The latter result is what differentiates it from the evaporation mechanism of a droplet of pure water, becoming aerosol. The evaporation rate of pure water is higher than the evaporation rate of a drop of saline solution by the high solubility that NaCl has, affecting the vapor pressure of saturated water, Shahidzadeh etal.11. This phenomenon is marked by various characteristics that occur in the environment, such as, for example, relative humidity (RH) and ambient temperature among others, Ugarte-Anero etal.1, Wang etal.12 and Sen etal.13. Gregson etal.14 indicates two important factors in the evaporation rate of an aqueous sodium droplet, the temperature of the gaseous phase and the solute concentration in the starting droplet, deriving that a higher concentration of solute indicates a longer evaporation rate time. Stiti etal.15 shows that a droplet of an initial diameter of 21µm in 2s could become an aerosol when a temperature above 20°C and an RH below 80% occurs. Studies such as Xie etal.8 , Liu etal.16 and Ugarte-Anero etal.1 state that at higher relative humidity the evaporation time of these is longer. These same studies, observe that the larger diameter of size the evaporation time is greater. The study of Xie etal.8 shows us that a particle of pure water at 33°C in a space at a temperature of 18°C and a 0% RH evaporates in 2s when the initial diameter is 50µm, instead, with a diameter of 100µm the time amounts to 7.2s. As the size increases the evaporation time increases. According with the study of Shahidzadeh etal.11 the evaporation rate increases linearly with the diameter of the initial droplet. If the focus is shifted to investigate the reaction of these droplets to ambient temperature, the investigation of Wang etal.12 shows that the lifetime of a droplet in wet spaces is less when the temperature decreases. In dry environments, on the other hand, the shelf life of the droplet is longer when the temperature decreases. He also points out that average particles are very sensitive to relative humidity, and it might be different to study their precise behavior. Evaporation is important to study how long it takes to become aerosol and achieves a strong contagion capacity. Although, once you have that particle less than 5µm in diameter, you need to know where it’s going. This phenomenon depends on many factors; the speed at which it is generated, whether we are in a closed or open place, anyhow there is a high-speed wind or a soft breeze, regardless there is ventilation, etc. In fact, the study by Cravero etal.17, indicates that with adequate ventilation in an indoor environment completely changes the direction of exhaled flow. Stiti15 has found that a particular 80µm becomes solid waste before reaching the ground when the person exhaling it has a height of 1.6m from the mouth to the ground. CFD studies such as Dbouk etal.18 and Li etal.19 warn that with an external wind greater than 1.1m/s can reach up to 6m away. This current, if it is descending, can remove the infected droplets in just 10s, on the contrary, an ascending current helps to have a viral load of 50% around the height of people, according to de Oliveira20. Consequently, in a closed space, such as the study by Chillon etal.4 the particles do not exceed one and a half meters of distance. The study by Zhao etal.21 combines fate with RH and ambient temperature and ensures that in humid environments and low temperature droplets travel a greater space. In dry environments and high temperature, the number of aerosols is higher, underline what previously cited by the studies of Xie etal.8 and Wang etal.12 that in dry space the evaporation is slower. The aim of this work is to study through computational simulations the behavior of a single saliva particle exposed to different environmental characteristics in a social environment. Launch the particle, without velocity, from a height of 1.6m and study in a first case its evaporation time at 0°C, 14°C and 35°C in a relative humidity range of 0% to 80%. The diameter of the particle are 25µm, 50µm, 75µm and 100µm. Finally, the fate of droplets saliva (10–90µm) is studied at a temperature of 14°C and 35°C and relative humidity of 0%, 20%, 40%, 60% and 80%, with a velocity of 0m/s, affecting only the gravity and weight of the droplet of saliva. Materials and methods Computational domain and initial conditions. In order to analyze through CFD techniques the most remarkable properties of a droplet of saliva, the domain used has been a box of 2m X 2m X 1.6m (X, Y, Z). The generated computational domain, the cube, composed of a single boundary, taken as a wall. The six walls act as a barrier to stop the particle getting injected there. Enclosed space, study based on an indoor environment, without air or external wind affecting the particle. It should be noted that the value of Z is equal to 1.6m for the average height that can take the mouth of a human. Figure1 shows the bucket with the cone injector, placed in the central part of the upper face, specifically [1, 1, 1.6]. This injector launches a particle into outer space simulating a human cough. Instead of generating a particle size distribution, a particular particle will be studied, with a specific diameter the importance it has when exhaled. The injector will make as if it were a human mouth when generating a sneeze. First, taking as a reference the temperatures reached by European countries, the pure water particle has been subjected to 3 different temperatures: 0°C, 14°C and 35°C. In contrast, relative humidity varies from 0 to 80%. The diameter of the particle takes values of 25µm, 50µm 75µm and 100µm at 36°C. According to the study of Almeida PDV etal.7, saliva is composed of 99% water and the rest is formed by proteins, enzymes and electrolytes, among others. Also, the electrolytes, sodium and chloride stand out. Research by Xie etal.8 models saliva as a saline solution with a concentration of 150mM of ions and cations, affecting only saturation pressure. In Fig.2, you can see the process of evaporation of an exhaled droplet into the human environment. The current work 3 Vol.:(0123456789) Scientific Reports | (2022) 12:6405 | https://doi.org/10.1038/s41598-022-10180-5 www.nature.com/scientificreports/ has the limitation of not being able to study aerosol behavior. The process of complete evaporation of a droplet of saliva has been given as a droplet of pure water, without reaching the residue of the droplet. In the other hand, the behavior of the saliva particle in relation to the distance travelled has been studied. For this case, the temperatures are 14°C and 35°C and relative humidity of 0%, 20%, 40%, 60% and 80%, with a starting speed of 0m/s, so it has only affected the forces of gravity, the weight of the drop, according to Bozic9. According to the CFD model of Pendar etal.22, approximately the experimental average speed that can catch a sneeze is 20m/s, but when it is emitted to the environment in just a few seconds loses the speed adapting to that of the environment, Ugarte-Anero etal.1. Figure3 shows a sketch of the forces to which a particle is subjected. A generalized Richardson extrapolation method23,24 was performed to achieve the mesh independency study. This method consists of estimating the value of the analyzed parameter when the cell quantity tends to infinite from a minimum of three meshes. In the current study, a coarse mesh (1176 cells), a medium mesh (2528 cells), and a fine mesh (4360 cells) were considered. Figure4a shows the meshed domain and Fig.4b illustrates the plane through which the particle falls down. Appendix A shows a complete description of the mesh dependency study carried in the present work. The estimated values (RE) of the evaluated parameters are close to the ones obtained with the fine mesh for all cases. Note that a monotonic convergence is achieved since R values are positive and less than one. A mesh refinement ratio of approximately r = 2 has been chosen and p is the order-of-accuracy, see Stern etal.25. TablesA1 and A2 show the results of the Richardson Extrapolation based method. Numerical set up The study is solved as a two-phase flow situation, introducing the two-way coupling module. The droplet of pure water has form the Lagrangian phase. The particle, in question, has an initial temperature of 36°C but then will go down, taking the temperature of the external environment, according to the statement offered by Redow26. Saturation pressure follows Antoine equation, when the particle is pure water. The latter characteristic varies Figure1. Geometry of the domain. It consists of a box with measures of 2m × 2m × 1.6m (X, Y, Z). At a height of 1m × 1m × 1.6m a cone injector is collapsing simulating the particle. Figure2. Evaporation process of a droplet of saliva. Once the particle is exhaled into the environment, the evaporation process begins by evaporating saliva water. When it reaches 5µm of diameter it becomes aerosol, becoming droplet residue. 4 Vol:.(1234567890) Scientific Reports | (2022) 12:6405 | https://doi.org/10.1038/s41598-022-10180-5 www.nature.com/scientificreports/ when it comes to simulating saliva. A saline solution of 0.9% w/v, have a saturation pressure in accordance with Raoult’s Law, as indicated by Xie8. where Pva,s is the saturation pressure of the droplet in the saline mixture, Pva is the saturation pressure indicated by the Antoine equation at an indicated temperature (in this case at 36°C) (Tw) and Xd is the mole fraction of the droplet, that is calculated as shown in Eq.(2). where ms the mass of solute in the droplet; dp is the diameter of the droplet studied; Mw is the molecular weight of water and Ms is the molecular weight of solute, the ion factor “i” is equal to 2. The Reynolds-averaged Navier–Stokes (RANS) equations with k-ω Shear Stress Transport (SST) turbulence model, developed by Menter etal.27 have been introduced in this work. The UpWind algorithm was employed for the pressure–velocity coupling and a linear upwind second order scheme was used to discretize the mesh. Figure3 shows the forces to which the droplet is subjected, which is initially assumed to be spherical. The influence of the gravity force was taken into account. The Taylor analogy breakup (TAB) model was implemented to provide a solution to particle distortion and break up. Also, the turbulent particle dispersion with the exact eddy interaction time is taken into account. The drag force takes the value according to Schiller-Naumann mathematics model. Model used in the numerical study of Wang etal.12 and in the investigation of de Oliveira etal.20. The model simulated the drag between the two current phases. Equation3 shows the expression to calculate the drag coefficient Cd. (1) Pva,s =XdPva(Tw) (2) Xd=  1+6imsMw πρ LMs ( dp )3 −1 Figure3. Forces that affect a droplet of saliva. Droplet falling freely affected by gravity, whether weight, and drag force. Figure4. Mesh distribution. (a) Geometry of the mesh cube; (b) plane through which the particle passes. 5 Vol.:(0123456789) Scientific Reports | (2022) 12:6405 | https://doi.org/10.1038/s41598-022-10180-5 www.nature.com/scientificreports/ where Re is the Reynolds number. Once the respiratory droplets are exhaled into the social environment where humans are found, the process of evaporation begins. For this, Busco etal.28 introduces the quasi-steady evaporation model, incorporated in this project. Formula 4 shows the equation in which the model is governed, subject to mass loss. where g∗ is the mass transfer conductance and As is the droplet surface area. B is the Spalding transfer number. g∗ and B are defined as: In the Eqs.(5 and 6), ρp is the density of the particle liquid phase, Dv and Dp are the molecular diffusivity of the vapor phase and of the liquid phase, respectively. Sh is the correlation for de Sherwood number. Yi,s is the vapor mass fraction at the surface and Yi,∞ is the vapor mass fraction inside the fluid phase. The second important part of this research is the simulation of the atmosphere. The cube has simulated this and have been solved by equations for the continuous phase expressed in Eulerian form. Non-reactive species that after determining their properties, the total binding property is calculated as a mass function of the components of the mixture. Busco etal.28 incorporates Eq.(7), based on the mass-weighted mixture method. where Yi is the mass fraction of air and water vapor and фi is the property values of mixture component. N is the total number of components in the mixture. Composed of dry air and water vapor, varying their mass composition gives rise to relative humidity. By observing the Kukkonen etal.29 appendix the density and viscosity of the water vapor air and liquid water have been taken as the value marked by the equations of that report when changing temperature. In the current work, the commercial CFD code STAR-CCM + v.14.02 (Siemens, London, UK) was used to define and solve the numerical model of aerosols. A personal server-clustered parallel computer with Intel Xeon © E5-2609 v2 CPU @ 2.5GHz (16 cores) and 45GB RAM were used to run all the simulations. Validation. In the case of computational simulations, validation with experimental results is required. The current work reports on the evaporation of pure water droplets and on the fate of saliva droplets, therefore, has validated both, evaporation and distance. The same method used by Redow26, Mowraska30, Li19 and Ugarte-Anero1 was used for the validation of evaporation. A study in which different diameters of droplets of pure water (1µm 10µm and 100µm) with a temperature of 310.15K are subjected to an environment of 293.15K and RH varies to see the evaporation time. The results obtained are similar to those shown by the aforementioned works, shown in Fig.5. Following the same philosophy, a pure water droplet and a saliva droplet only have difference in the vapor pressure in this study, therefore, affect the same forces and we can go ahead with studies like Hamey etal.31 and Spillman etal.32 that show the path of a droplet of pure water. Hamey study consists of two droplets of water, one of 110µm and another of 115µm of diameter, at a temperature of 289K in an environment at 293K and relative humidity of 70% and observe its path having let the droplet fall freely. With the same objective, the Spillman studio launches a 170µm of diameter particle at 25°C in a 31°C environment with a relative humidity of 68%. Figures5 and 6 show the results obtained by comparing our CFD data with the experimental studies. Instead, Table1 shows the error as a percentage between the experimental data of the Hamey and Spillman and the results obtained with CFD techniques. Results In a sneeze, a particle distribution of 10–100µm diameter is generated. The average diameters selected to study the case are: 25µm, 50µm, 75µm and 100µm. The human body is at a temperature of approximately 36°C, so the exhaled particles have an initial temperature of 36°C. With a minimum temperature of 0°C, a particle of 100µm of diameter, in an environment with relative humidity of 80%, reaches an evaporation time of 61.2s. In contrast, with a temperature of 14°C and constant RH the evaporation time is equal to 54.4s. And, with 35°C, and the same characteristics, 30.3s is the time it takes for that particle to evaporate. When it is a 50µm particle with a temperature of 14°C, in an environment with a relative humidity of 50% the evaporation time is 5,2s and RH 80% the evaporation time is equal to 13.7s. The distribution of evaporation of the test droplets is analyzed in Figs.7, 8 and 9. (3) C d    24 Re ,Re ≤1 24 Re � 1+0.15Re0.687 � , 0.44, Re >1000 1<Re ≤ 1000 (4) ˙mp=g∗×Asln(1+B) (5) g ∗=− ρ p D v Sh D p (6) B = Y i,s −Y i,∞ 1 − Yi,s (7) φ mix = N=2  i=1 φiY i 6 Vol:.(1234567890) Scientific Reports | (2022) 12:6405 | https://doi.org/10.1038/s41598-022-10180-5 www.nature.com/scientificreports/ By converting saliva into a saline solution, the evaporation time of saline solution droplet is 17s approximately more in comparison with pure water droplet. Both cases were performed under the conditions of a RH = 50% and an environment temperature of 14°C, and the diameters of the droplet was 50µm. Instead, as the diameter of the saline particle increases this difference is more notary. A particle of pure water with 100µm of diameter evaporates 50s before one of saline solution droplet. Figure10 shows the difference in the evaporation process between a droplet of pure water and a droplet of saline solution of a 50µm and 100µm droplet. In the case of studying the distance that the droplets generated in a sneeze or cough can travel, the law of gravity is kept, the more diameter the more weight, the longer distance traveled. An average particle of 50µm, at a relative humidity of 60% travels 0.24m, before evaporating. Rather, at a humidity of 20% the particle stays at a distance of 1.5m from the ground, all in an environment with a temperature of 14°C. With the same peculiarities, 0.1 1 10 100 Droplet diameter (µm) Time (s) Water pure droplets evaporaon RH 0% RH 20% RH 60% RH 80% Figure5. Water pure droplets evaporation. Particle diameter of 1µm, 10µm and 100µm at a temperature of 310.15K. Simulated in an environment with variable relative humidity of 0%, 20%, 60% and 80% at a constant temperature of 293.15K. 0 0.8 1.6 90 100 110 120 130140 150160 17 0 Distance (m) Droplet diameter (µm) CFD (Hamey 1982 (115 µm)) CFD (Hamey 1982 (110 µm)) Hamey 1982 exp. (115 µm) Hamey 1982 exp. (110 µm) Spillman exp. CFD (Spillman) Figure6. Water pure droplets fate. Droplets of 110µm and 115µm fall freely at an initial temperature of 289K in an environment of 293K to an RH of 70%, called as Hamey study. Spillman study with the same purpose as the above, of a particle of 170µm of diameter at a temperature of 25°C in an environment of 31°C temperature and HR of 68%. 7 Vol.:(0123456789) Scientific Reports | (2022) 12:6405 | https://doi.org/10.1038/s41598-022-10180-5 www.nature.com/scientificreports/ when RH = 60%, a particle of 90µm has travelled the 1.6m before evaporating and when the RH = 20% the distance traveled has been 0.95m. Considering Figs.7, 8 and 9, the effect of the evaporation process, a 50µm of diameter particle at ambient temperature of 35°C and a relative humidity of 60% passes through a distance of 0.13m before evaporating, from a height of 1.6m. Figures11 and 12 show the fate of the particles released from a height of 1.6m from the ground, corresponding to the average height of the mouth of an adult person. The heavier droplets manage to reach the soil instead, the smaller droplets evaporate into the air leaving the droplet residue in the environment. The droplet residue generated by the larger droplets would settle on the surface. Then, according with the results obtained by studying the particle dynamics, the results of the time of thirst determined by empirical formulas is studied. Equation8, provided by the study of Bozic etal.9 ,indicates the parameters that influence the sedimentation time. Table2 shows the results obtained from four examples at a relative humidity of 50%. It should be noted that a particle with a diameter of 80µm in an environment with a temperature of 35°C and RH = 80%, can be transported from a height of 1.6m, before evaporation, at a distance of 0.015m from the ground over a time of 7.9s. With the empirical formula we obtain that the sedimentation time of that droplet is 0.2s more than the evaporation time, time that would elapse to travel the distance of 0.015m previously mentioned. Only the 100μm particle has been evaporate after deposition in the soil, the others have evaporated in the air before reaching the marked distance. (8) tsedimentation =h÷(ξ ×  R droplet ) 2 Table 1. Calculated error between the results obtained by CFDs and the experimental data of the Hamey and Spillman studies. Hamey 1982 110µm Hamey 1982 115µm Spillman 0.000301% 0.034% 0.161% 1.160% 0.019% 0.287% 0.393% 0.554% 0.852% 3.615% 0.597% 1.348% 2.693% 1.645% 2.201% 2.955% 0.932% 3.114% 6.379% 4.083% 3.801% 3.532% 4.995% 0.1 1 10 100 01020304050607 080 Time (s) RH (%) Water pure droplet evaporaon at T=0ºC 100 75 50 25 Figure7. Water pure droplets evaporation. Time elapsed in the evaporation process of a droplet of pure water at an ambient temperature of 0°C, with variable relative humidity and particle diameter of 25µm, 50µm, 75µm and 100µm. 8 Vol:.(1234567890) Scientific Reports | (2022) 12:6405 | https://doi.org/10.1038/s41598-022-10180-5 www.nature.com/scientificreports/ where h = 1.6m, in this case since it is the average height of the human mouth, Rdroplet is the radius of the particle and the letter ξ equals to the number 1.2 ×108 m−1 s−1. ANN‑based evaporation time prediction model Aiming to obtain the evaporation time of the particles, an Artificial Neural Network (ANN) is developed. Deep Learning techniques, which include neural networks, are exceptional tools for modelling a wide variety of systems due to their properties and advantages in comparison with other traditional techniques, see Lopez-Guede 0.1 1 10 100 01020304050607 080 Time (s) RH (%) Water pure droplet evaporaon at T=14ºC 100 75 50 25 Figure8. Water pure droplets evaporation. Time elapsed in the evaporation process of a droplet of pure water at an ambient temperature of 14°C, with variable relative humidity and particle diameter of 25µm, 50µm, 75µm and 100µm. 0.1 1 10 100 01020304050607 080 Time (s) RH (%) Water pure droplet evaporaon at T=35ºC 100 75 50 25 Figure9. Water pure droplets evaporation. Time elapsed in the evaporation process of a droplet of pure water at an ambient temperature of 35°C, with variable relative humidity and particle diameter of 25µm, 50µm, 75µm and 100µm. 9 Vol.:(0123456789) Scientific Reports | (2022) 12:6405 | https://doi.org/10.1038/s41598-022-10180-5 www.nature.com/scientificreports/ etal.33,34. Among these advantages and properties, the most remarkable ones are their ability to learn and their fast computational speed. In the present paper a multi-layer model with two hidden layers is used. The evaporation time of the particle is calculated by Eq.(9), and the outputs of each neuron of the hidden layers follow a sigmoid function, which is defined in Eq.(10). The ANN with these parameters represents a typical Multilayer Perceptron with 0 20 40 60 80 100 120 01020304050607 080 Droplet diameter (μm) Time (s) Evaporaon process Water pure droplet Saline soluon droplet Figure10. Difference of evaporation process. Under conditions of relative humidity of 50% and ambient temperature of 14°C. A particle of pure water with 50µm of diameter evaporates 17s before one of saline solution droplet. However, a particle of pure water with 100µm of diameter evaporates 50s before one of saline solution droplet. 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 10 20 30 40 50 60 70 80 90 Distance (m) Droplet diameter (µm) TT==1144ººCC RH 0% RH 20% RH 40% RH 60% RH 80% Figure11. Distance covered by droplets of saliva (10µm, 20µm, 30µm, 40µm, 50µm, 60µm, 70µm, 80µm and 90µm) from a height of 1.6m at a temperature of 14°C and with a variable relative humidity.