Walking School Buses (WSBs) provide a safe alternative to being driven to school. Children benefit from the contribution the exercise provides towards their daily exercise target, it gives children practical experience with respect to road safety and it helps to relieve traffic congestion around the entrance to their school. Walking routes are designed largely based in road safety considerations, catchment need and the availability of parent support. However, little attention is given to the air pollution exposure experienced by children during their journey to school, despite the commuting microenvironment being an important contributor to a child's daily air pollution exposure. This study aims to quantify the air pollution exposure experienced by children walking to school and those being driven by car. A school was chosen in Bradford, UK. Three adult participants carried out the journey to and from school, each carrying a P-Trak ultrafine particle (UFP) count monitor. One participant travelled the journey to school by car while the other two walked, each on opposite sides of the road for the majority of the journey. Data collection was carried out over a period of two weeks, for a total of five journeys to school in the morning and five on the way home at the end of the school day. Results of the study suggest that car commuters experience lower levels of air pollution dose due to lower exposure and reduced commute times. The largest reductions in exposure for pedestrians can be achieved by avoiding close proximity to traffic queuing up at intersections, and, where possible, walking on the side of the road opposite the traffic, especially during the morning commuting period. Major intersections should also be avoided as they were associated with peak exposures. Steps to ensure that the phasing of lights is optimised to minimise pedestrian waiting time would also help reduce exposure. If possible, busy roads should be avoided altogether. By the careful design of WSB routes, taking into account air pollution, children will be able to experience the benefits that walking to school brings while minimizing their air pollution exposure during their commute to and from school.
The effectiveness of ultraviolet irradiation at inactivating airborne pathogens is well proven, and the technology is also commonly promoted as an energy-efficient way of reducing infection risk in comparison to increasing ventilation. However, determining how and where to apply upper-room Ultraviolet Germicidal Irradiation devices for the greatest benefit is still poorly understood. This article links multi-zone infection risk models with energy calculations to assess the potential impact of a Ultraviolet Germicidal Irradiation installation across a series of inter-connected spaces, such as a hospital ward. A first-order decay model of ultraviolet inactivation is coupled with a room air model to simulate patient room and whole-ward level disinfection under different mixing and ultraviolet field conditions. Steady-state computation of quanta-concentrations is applied to the Wells-Riley equation to predict likely infection rates. Simulation of a hypothetical ward demonstrates the relative influence of different design factors for susceptible patients co-located with an infectious source or in nearby rooms. In each case, energy requirements are calculated and compared to achieving the same level of infection risk through improved ventilation. Ultraviolet devices are seen to be most effective where they are located close to the infectious source; however, when the location of the infectious source is not known, locating devices in patient rooms is likely to be more effective than installing them in connecting corridor or communal zones. Results show an ultraviolet system may be an energy-efficient solution to controlling airborne infection, particularly in semi-open hospital environments, and considering the whole ward rather than just a single room at the design stage is likely to lead to a more robust solution.
Magnetic Resonance Imaging (MRI) is considered the gold standard of medical imaging technologies as it allows for accurate imaging of blood vessels. 4-Dimensional Flow Magnetic Resonance Imaging (4D-Flow MRI) is built on conventional MRI, and provides flow data in the three vector directions and a time resolved magnitude data set. As such it can be used to retrospectively calculate haemodynamic parameters of interest, such as Wall Shear Stress (WSS). However, multiple studies have indicated that a significant limitation of the imaging technique is the spatiotemporal resolution that is currently available. Recent advances have proposed and successfully integrated 4D-Flow MRI imaging techniques with Computational Fluid Dynamics (CFD) to produce patient-specific simulations that have the potential to aid in treatments,surgical decision making, and risk stratification. However, the consequences of using insufficient 4D-Flow MRI spatial resolutions on any patient-specific CFD simulations is currently unclear, despite being a recognised limitation. The research presented in this study aims to quantify the inaccuracies in patient-specific 4D-Flow MRI based CFD simulations that can be attributed to insufficient spatial resolutions when acquiring 4D-Flow MRI data. For this research, a patient has undergone four 4D-Flow MRI scans acquired at various isotropic spatial resolutions and patient-specific CFD simulations have subsequently been run using geometry and velocity data produced from each scan. It was found that compared to CFD simulations based on a $$1.5\,{\text {mm}} \times 1.5\,{\text {mm}} \times 1.5\,{\text {mm}}$$ 1.5 mm × 1.5 mm × 1.5 mm , using a spatial resolution of $$4\,{\text {mm}} \times 4\,{\text {mm}} \times 4\,{\text {mm}}$$ 4 mm × 4 mm × 4 mm substantially underestimated the maximum velocity magnitude at peak systole by $$110.55\%$$ 110.55 % . The impacts of 4D-Flow MRI spatial resolution on WSS calculated from CFD simulations have been investigated and it has been shown that WSS is underestimated in CFD simulations that are based on a coarse 4D-Flow MRI spatial resolution. The authors have concluded that a minimum 4D-Flow MRI spatial resolution of $$1.5\,{\text {mm}} \times 1.5\,{\text {mm}} \times 1.5\,{\text {mm}}$$ 1.5 mm × 1.5 mm × 1.5 mm must be used when acquiring 4D-Flow MRI data to perform patient-specific CFD simulations. A coarser spatial resolution will produce substantial differences within the flow field and geometry.
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