Experimental characterization of respiratory droplet emission

The droplet-laden air cloud exhaled by humans during different respiratory activities plays a major role in infectious disease transmission. That exhaled droplets contain pathogen is a well-known fact in the scientific community since the 19th Century. Unfortunately, pandemics as COVID-19, SARS, and MERS, have recently brought back the attention to this issue, which is rather complex since multiple-scale phenomena and different disciplines (epidemiology, biology, fluid mechanics) are involved. Fluid mechanics plays a major role in the comprehension of droplet-laden air cloud dynamics and mitigation of the related risks. Indeed, the pathogens interact with fluids from their encapsulation within the droplets in the airways to their inhalation by susceptible individuals. The prediction of the fate of the droplets after their emission have widely been improved, especially in the past three years, by means of experiments and models. However, a lack of knowledge of the air and droplet properties at the emission (mouth) emerges from the literature. Providing precise information on emission characteristics to numerical or theoretical models that predict droplet dispersion is of striking importance to obtain reliable results. The present thesis aims to contribute to this field by improving the characterization of droplet emission, namely, their size and velocity distribution. A series of laboratory experiments have been conducted considering different respiratory activities, namely, speaking, coughing and breathing. The Interferometric Laser Imaging for Droplet Sizing (ILIDS) technique has been used for data collection. Both the setup and the related data processing have been improved with respect to ILIDS standard applications in order to detect droplets with size down to 2 μm and to measure all their three velocity components. Two experimental campaigns involving twenty-three volunteers have been carried out. The effects of protection masks and the variability in the results obtained for the same volunteer repeating the tests are also assessed. Finally, droplet size and velocity distributions have been used as input data for Computational Fluid Dynamics simulations in order to analyse their role in the dispersion process following their emission

Caractérisation expérimentale de l'émission de gouttelettes respiratoires

The droplet-laden air cloud exhaled by humans during different respiratory activities plays a major role in infectious disease transmission. That exhaled droplets contain pathogen is a well-known fact in the scientific community since the 19th Century. Unfortunately, pandemics as COVID-19, SARS, and MERS, have recently brought back the attention to this issue, which is rather complex since multiple-scale phenomena and different disciplines (epidemiology, biology, fluid mechanics) are involved. Fluid mechanics plays a major role in the comprehension of droplet-laden air cloud dynamics and mitigation of the related risks. Indeed, the pathogens interact with fluids from their encapsulation within the droplets in the airways to their inhalation by susceptible individuals. The prediction of the fate of the droplets after their emission have widely been improved, especially in the past three years, by means of experiments and models. However, a lack of knowledge of the air and droplet properties at the emission (mouth) emerges from the literature. Providing precise information on emission characteristics to numerical or theoretical models that predict droplet dispersion is of striking importance to obtain reliable results. The present thesis aims to contribute to this field by improving the characterization of droplet emission, namely, their size and velocity distribution. A series of laboratory experiments have been conducted considering different respiratory activities, namely, speaking, coughing and breathing. The Interferometric Laser Imaging for Droplet Sizing (ILIDS) technique has been used for data collection. Both the setup and the related data processing have been improved with respect to ILIDS standard applications in order to detect droplets with size down to 2 μm and to measure all their three velocity components. Two experimental campaigns involving twenty-three volunteers have been carried out. The effects of protection masks and the variability in the results obtained for the same volunteer repeating the tests are also assessed. Finally, droplet size and velocity distributions have been used as input data for Computational Fluid Dynamics simulations in order to analyse their role in the dispersion process following their emission.Le nuage d'air et gouttelettes exhalé par les humains lors de différentes activités respiratoires joue un rôle important dans la transmission des maladies infectieuses. Que les gouttelettes exhalées contiennent des agents pathogènes est un fait bien connu dans la communauté scientifique depuis le dix-neuvième siècle. Malheureusement, des pandémies comme COVID-19, SARS et MERS, ont récemment ramené l'attention sur cette question, qui est assez complexe puisque des phénomènes à plusieurs échelles et différentes disciplines (épidémiologie, biologie, mécanique des fluides) sont impliqués. La mécanique des fluides joue un rôle fondamental dans la compréhension de la dynamique des nuages d'air et gouttelettes et l'atténuation des risques associés. Les pathogènes interagissent d’ailleurs avec les fluides depuis leur encapsulation au sein des gouttelettes dans les voies respiratoires jusqu'à leur inhalation par des personnes sensibles. La prédiction de la dispersion des gouttelettes après leur émission a été largement améliorée, surtout pendant les trois dernières années, grâce aux nombreux expériences et modèles développés. Cependant, un manque de connaissance des propriétés de l'air et des gouttelettes à l'émission (bouche) ressort de la littérature. Fournir des informations précises sur les caractéristiques de l’émission aux modèles numériques ou théoriques qui prédisent la dispersion des gouttelettes est d'une importance capitale pour obtenir des résultats fiables. Cette thèse a l’objectif de contribuer à ce domaine en améliorant la caractérisation de l'émission de gouttelettes, notamment, de leur taille et de leur distribution de vitesse. Des expériences en laboratoire ont été effectuées pour investiguer différentes activités respiratoires, plus précisément parler, tousser et respirer. La granulométrie per imagerie interférométrique en défaut de mise au point (Interferometric Laser Imaging for Droplet Sizing, or ILIDS, en anglais) a été utilisée pour collecter les données. La configuration et le traitement des données associées ont été améliorés par rapport aux applications standard de l’ILIDS afin de détecter des gouttelettes d'une taille inférieure à 2 μm et de mesurer leurs trois composantes de vitesse. Deux campagnes expérimentales avec vingt-trois volontaires ont été réalisées. Les effets des masques de protection et la variabilité des résultats obtenus pour un même volontaire répétant les tests sont également évalués. Enfin, les distributions de taille et de vitesse des gouttelettes ont été utilisées comme données d'entrée pour les simulations numériques de dynamique des fluides (Computational Fluid Dynamics, or CFD, en anglais) afin d'analyser leur rôle dans le processus de dispersion suite à leur émission

Caractérisation expérimentale de l'émission de gouttelettes respiratoires

Le nuage d'air et gouttelettes exhalé par les humains lors de différentes activités respiratoires joue un rôle important dans la transmission des maladies infectieuses. Que les gouttelettes exhalées contiennent des agents pathogènes est un fait bien connu dans la communauté scientifique depuis le dix-neuvième siècle. Malheureusement, des pandémies comme COVID-19, SARS et MERS, ont récemment ramené l'attention sur cette question, qui est assez complexe puisque des phénomènes à plusieurs échelles et différentes disciplines (épidémiologie, biologie, mécanique des fluides) sont impliqués. La mécanique des fluides joue un rôle fondamental dans la compréhension de la dynamique des nuages d'air et gouttelettes et l'atténuation des risques associés. Les pathogènes interagissent d’ailleurs avec les fluides depuis leur encapsulation au sein des gouttelettes dans les voies respiratoires jusqu'à leur inhalation par des personnes sensibles. La prédiction de la dispersion des gouttelettes après leur émission a été largement améliorée, surtout pendant les trois dernières années, grâce aux nombreux expériences et modèles développés. Cependant, un manque de connaissance des propriétés de l'air et des gouttelettes à l'émission (bouche) ressort de la littérature. Fournir des informations précises sur les caractéristiques de l’émission aux modèles numériques ou théoriques qui prédisent la dispersion des gouttelettes est d'une importance capitale pour obtenir des résultats fiables. Cette thèse a l’objectif de contribuer à ce domaine en améliorant la caractérisation de l'émission de gouttelettes, notamment, de leur taille et de leur distribution de vitesse. Des expériences en laboratoire ont été effectuées pour investiguer différentes activités respiratoires, plus précisément parler, tousser et respirer. La granulométrie per imagerie interférométrique en défaut de mise au point (Interferometric Laser Imaging for Droplet Sizing, or ILIDS, en anglais) a été utilisée pour collecter les données. La configuration et le traitement des données associées ont été améliorés par rapport aux applications standard de l’ILIDS afin de détecter des gouttelettes d'une taille inférieure à 2 μm et de mesurer leurs trois composantes de vitesse. Deux campagnes expérimentales avec vingt-trois volontaires ont été réalisées. Les effets des masques de protection et la variabilité des résultats obtenus pour un même volontaire répétant les tests sont également évalués. Enfin, les distributions de taille et de vitesse des gouttelettes ont été utilisées comme données d'entrée pour les simulations numériques de dynamique des fluides (Computational Fluid Dynamics, or CFD, en anglais) afin d'analyser leur rôle dans le processus de dispersion suite à leur émission.The droplet-laden air cloud exhaled by humans during different respiratory activities plays a major role in infectious disease transmission. That exhaled droplets contain pathogen is a well-known fact in the scientific community since the 19th Century. Unfortunately, pandemics as COVID-19, SARS, and MERS, have recently brought back the attention to this issue, which is rather complex since multiple-scale phenomena and different disciplines (epidemiology, biology, fluid mechanics) are involved. Fluid mechanics plays a major role in the comprehension of droplet-laden air cloud dynamics and mitigation of the related risks. Indeed, the pathogens interact with fluids from their encapsulation within the droplets in the airways to their inhalation by susceptible individuals. The prediction of the fate of the droplets after their emission have widely been improved, especially in the past three years, by means of experiments and models. However, a lack of knowledge of the air and droplet properties at the emission (mouth) emerges from the literature. Providing precise information on emission characteristics to numerical or theoretical models that predict droplet dispersion is of striking importance to obtain reliable results. The present thesis aims to contribute to this field by improving the characterization of droplet emission, namely, their size and velocity distribution. A series of laboratory experiments have been conducted considering different respiratory activities, namely, speaking, coughing and breathing. The Interferometric Laser Imaging for Droplet Sizing (ILIDS) technique has been used for data collection. Both the setup and the related data processing have been improved with respect to ILIDS standard applications in order to detect droplets with size down to 2 μm and to measure all their three velocity components. Two experimental campaigns involving twenty-three volunteers have been carried out. The effects of protection masks and the variability in the results obtained for the same volunteer repeating the tests are also assessed. Finally, droplet size and velocity distributions have been used as input data for Computational Fluid Dynamics simulations in order to analyse their role in the dispersion process following their emission

Evaluation of Lagrangian time scales and turbulent diffusivities by GPS equipped drifters

In this paper absolute dispersion of GPS-equipped drifters of the MREA14 campaign in the Mar Grande Basin of Taranto was investigated. Velocity variance and integral time scale were computed. Different procedures to infer the mean velocity from drifter data were examined. A comparison within experimental and theoretical values of the displacement variance is introduced pointing out limits and requirements of numerical dispersion models. Estimates of horizontal diffusivities are obtained and presente

Modellazione su scala di laboratorio della circolazione dell'aria e della dispersione di inquinanti in ambienti confinati

La pandemia di COVID-19 ha ampliato in modo drastico l’interesse della comunità scientifica riguardo le modalità con le quali le sostanze inquinanti diffondono negli ambienti confinati (e.g., abitazioni civili, ospedali, luoghi di lavoro e di svago). Nonostante i notevoli progressi compiuti negli ultimi anni nel campo della meccanica dei fluidi urbana e nei flussi d’aria indoor, una modellazione affidabile della qualità dell'aria negli ambienti confinati è ancora lontana dall'essere ottenuta. La causa di ciò va ricercata, da un lato, nelle oggettive difficoltà incontrate nella determinazione delle sorgenti di inquinanti indoor, come ad esempio quella legata alla scarsa conoscenza del diametro e della velocità delle particelle emesse dagli esseri umani durante le diverse attività respiratorie (e.g., Rosti et al., 2020), dall’altro nella complessità nel modellare le modalità con le quali tali particelle si disperdono a causa della natura multifase della “nuvola” di emissione (e.g., De Padova & Mossa, 2021). Un ulteriore difficoltà è associata alla complessa natura del flusso d’aria all’interno degli ambienti confinati, causata dall’ampia varietà di condizioni al contorno −ventilazione naturale, ventilazione forzata, gradienti termici, presenza delle persone, ecc. Nell’ambito di questa problematica ha preso vita il progetto VIEPI (Integrated Evaluation of Indoor Particulate Exposure; Pelliccioni et al., 2020), che ha tra i suoi obiettivi la valutazione della qualità dell'aria indoor. Durante il progetto sono state condotte campagne di misura di velocità dell’aria e concentrazione di inquinanti sia in laboratori di ricerca sia in aule universitarie situate in siti urbani e non urbani nell'area metropolitana di Roma. Nel corso del progetto è stata presa in esame l’aula Valerio Giacomini, posta al piano terra dell’edificio di Botanica e Genetica del Dipartimento di Biologia Ambientale dell’Università di Roma “La Sapienza”, sita nella città universitaria. Tale aula è frequentata da un elevato numero di studenti e presenta forma e dimensioni idonee per uno studio approfondito della circolazione dell’aria al suo interno e degli scambi indoor-outdoor di massa ed energia. Le misure su campo hanno riguardato, tra le altre cose, l’acquisizione della temperatura e della velocità dell’aria in vari punti dell’aula utili alla descrizione del campo fluidodinamico. Tali dati sono utilizzabili altresì come input per modellazioni di laboratorio, simulazioni numeriche e relativi test di validazione. In questo lavoro saranno mostrati alcuni risultati preliminari ottenuti con i dati acquisiti durante la prima campagna di misura del VIEPI e definite le condizioni al contorno utili per la modellazione in scala di laboratorio del flusso dell’aria e della concentrazione di traccianti passivi all’interno dell’aula. Dette modellazioni saranno condotte mediante tecniche di misura non intrusive basate sull’analisi di immagine

Interferometric laser imaging for respiratory droplets sizing

Due to its importance in airborne disease transmission, especially because of the COVID-19 pandemic, much attention has recently been devoted by the scientific community to the analysis of dispersion of particle-laden air clouds ejected by humans during different respiratory activities. In spite of that, a lack of knowledge is still present particularly with regard to the velocity of the emitted particles, which could differ considerably from that of the air phase. The velocity of the particles is also expected to vary with their size. In this work, simultaneous measurements of size and velocity of particles emitted by humans while speaking have been performed by means of Interferometric Laser Imaging Droplet Sizing (ILIDS). This technique allowed us to detect emitted particles with size down to 2 µm as well as to quantify all three components of the velocity vector and the particle concentration. The outcomes of this work may be used as boundary conditions for numerical simulations of infected respiratory cloud transmission. Graphical abstract: [Figure not available: see fulltext.