On the evaluation of transport properties for droplet evaporation problems

This article presents an improved method to evaluate the average gas phase fluid properties to more accurately predict the evaporation rate of liquid droplets. Compared to the current widely applied method (known as the one-third rule), the new method is shown to reduce the evaporation rate errors from potentially in excess of 14% with an average of 6.1%, to within 3.5% and with an average of 1.4%. The method is derived analytically by equating the solution with constant transport properties and the solution with transport properties proportional to the square-root of temperature. Therefore, this method has a theoretical foundation and is not based on any fitting parameters or empirical coefficients. This work provides an essential link between the well-known constant property solution to droplet evaporation, and the more complex numerical solution with variable properties. The presented method allows the computational speed and simplicity of constant properties, while approaching the high accuracy of variable fluid properties.</p

Inferring ventilation rates with quantified uncertainty in operational rooms using point measurements of carbon dioxide: classrooms as a case study

We present a robust integral method to estimate the daily mean per-person ventilation rate Q¯pp based on carbon dioxide (CO2) concentration measurements in operational spaces, and limited other data. The method makes no assumptions regarding the ventilation provision throughout the day, nor requires the room to be in a steady state, nor the air within to be well-mixed. We demonstrate that several integral parameters remain reliably close to a value of unity, despite large variations in room conditions. Evaluating the likely distributions of integral parameters provides a method to quantify the uncertainty bounds and therefore assess the reliability of these ventilation estimates. Taking school classrooms as a case study, estimates of Q¯pp based on measured CO2 are shown to exhibit uncertainty bounds (of 95% confidence intervals) of approximately ±24% if no other data than the classroom timetable is available. Deploying four CO2 sensors within a classroom is expected to halve the uncertainty bounds to around ±12%. Moreover, the framework presented herein evidences that when the same classroom experiences similar usage on two different days, the relative per-person ventilation rate achieved during these two days can be simply determined by the ratio of their integral excess CO2 concentrations. These significant findings offer great scope to facilitate more reliable ventilation estimates, particularly from large-scale data sets of CO2 measured in operational spaces, to better inform assessments of indoor air quality.</p

Schools’ air quality monitoring for health and education: methods and protocols of the SAMHE initiative and project

Background: Children spend significant amounts of time at school, making the school environment a potentially important contributor to air quality exposure.  Aim: The SAMHE initiative has a dual aim: 1) to develop and test a bespoke citizen science framework for collecting environment and indoor air quality data in classrooms, alongside contextual data capable of enriching analysis, at an unprecedented scale; and, 2) to simultaneously use these methods to raise awareness among communities regarding their exposure to air pollution in the school environment.  Methodology: To achieve this dual aim, the SAMHE project was initiated to deploy more than 2 000 low-cost indoor air quality monitors in school classrooms. A Web App has been co-designed with schools to support collecting a large comprehensive dataset (including school buildings characteristics, operation, and behavioural patterns) and to enable students and teachers to interact with the data gathered in their school. Results and outlook: We present the design of the interface and visuals that have been co-designed with 20+ schools and tested with 120+ schools. Within one week of the SAMHE launch week, 537 schools had registered to join the project, and at the time of writing (just seven weeks later) this number had grown to around 800 schools. This highlights the potential for this novel initiative to provide a step-change in the way that indoor air quality datasets are gathered at a national and, potentially, international level while simultaneously enabling schools to better manage their indoor environment and empowering students and teachers to reduce their environmental health risks.</p