ABSTRACT
A modelling approach is proposed to study ozone distribution and destruction in indoor spaces. The level of ozone gas concentration in the air, confined within an indoor space during an ozone-based disinfection process, was modelled. The emission and removal of ozone from the air volume were carried out using a generator located in the middle of the room. The computational fluid dynamics (CFD) model proposed accounts for ozone generation and decay kinetics, and buoyancy variations in the airflow. This framework was validated against experimental measurements at different locations in the room during the disinfection cycle. The model was then applied to a more challenging environment and demonstrated the suitability of ozone circulation as a disinfection process. The study also highlights the need for a well-controlled ozone removal process. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Purpose: Limited data exists on CT chest abnormalities during acute Coronavirus disease 2019 (COVID-19) infection and associated post-illness loss of lung function among lung transplant (LT) patients. Method(s): The institutional database was interrogated for any LT patient diagnosed with COVID-19 during a one-year period (March 2020 to Feb 2021;n=54). 44 patients with acute COVID-19 were alive at 3-month follow up (COVID-survivors: 81.5%). Of the survivors, 34 had a CT chest during the first two weeks of acute illness. A validated CT score was used to quantify the parenchymal abnormalities due to COVID-19. Each lung was divided into 10 separate regions which were scored 0-2 based on the severity and extent of parenchymal opacification (maximum score per lung=20). To avoid confounding from underlying lung disease, only the allograph was assessed in single LT. The average score of both lungs was calculated in bilateral LT. The primary outcome measure was sustained decline of FEV1 or FVC >10% from pre-infection spirometry. Result(s): Abnormal CT score and lung opacities on CT chest were nearly ubiquitous during acute COVID-19 illness (>0;36/37, 97.3%, median score with IDR: 7.25, 4.625-10.125). The lower lobes (LL) were more affected by COVID-19 than the upper and middle lobes (UML) (median CT score in LL: 4, 2.75-6 vs 3.5, 1.25-5 in UML). A >10% decline in FEV1 or FVC was common after COVID-19 pneumonia (38.2%). The overall CT score correlated with amount of lung function loss (r=0.36, p=0.03) although the association was modest and limited to regions reflecting the UML. On ROC curve, CT score was modestly predictive of lung function decline (Fig 1). CT score from UML had the highest area under the curve (78.2%, 61.1-95.4%;p=0.006) with a score of 4.5 being the best cut-off (sensitivity 71%, specificity 85% for post-COVID lung function loss >10%). An UML CT score >4.5 was strongly associated with respiratory failure during acute illness (69% vs 24%;OR: 7.2, 1.5-33.8;p=0.01) and lung function decline >10% (77% vs 19%;OR: 14.2, 2.6-76.7;p=0.001). Conclusion(s): The CT score during acute COVID-19 infection provides prognostic information regarding loss of lung function among LT patients who survive COVID-19. Parenchymal abnormalities in the UML best predict subsequent lung function loss.
ABSTRACT
Purpose: A novel modelling approach is proposed to study ozone distribution and destruction in indoor spaces. The level of ozone gas concentration in the air, confined within an indoor space during an ozone-based disinfection process, is analysed. The purpose of this work is to investigate how ozone is distributed in time within an enclosed space. Design/methodology/approach: A computational methodology for predicting the space- and time-dependent ozone concentration within the room across the consecutive steps of the disinfection process (generation, dwelling and destruction modes) is proposed. The emission and removal of ozone from the air volume are possible by means of a generator located in the middle of the room. This model also accounts for ozone reactions and decay kinetics, and gravity effect on the air. Finding: This work is validated against experimental measurements at different locations in the room during the disinfection cycle. The numerical results are in good agreement with the experimental data. This comparison proves that the presented methodology is able to provide accurate predictions of the time evolution of ozone concentration at different locations of the enclosed space. Originality/value: This study introduces a novel computational methodology describing solute transport by turbulent flow for predicting the level of ozone concentration within a closed room during a COVID-19 disinfection process. A parametric study is carried out to evaluate the impact of system settings on the time variation of ozone concentration within the space considered. © 2021, Emerald Publishing Limited.