Résumé
To assess risk factors for COVID-19 transmission and address the closure of mass gathering events since March 2020, the UK Government ran the Events Research Programme (ERP), following which it reopened live events in sports, music, and culture in July 2021. We report the rapid post-occupancy evaluation of Indoor Air Quality (IAQ) and associated long-range airborne transmission risk conducted in the Environmental Study of the ERP. Ten large venues around the UK were monitored with CO2 sensors at a high spatial and temporal resolution during 90 events. An IAQ Index based on CO2 concentration was developed, and all monitored spaces were classified in bands from A to G based on their average and maximum CO2 concentrations from all events. High resolution monitoring and the IAQ Index depicted the overall state of ventilation at live events, and allowed identification of issues with ventilation effectiveness and distribution, and of spaces with poor ventilation and the settings in which long-range airborne transmission risk may be increased. In numerous settings, CO2 concentrations were found to follow patterns relating to event management and specific occupancy of spaces around the venues. Good ventilation was observed in 90% of spaces monitored for given occupancies. Practical applications: High-resolution monitoring of indoor CO2 concentrations is necessary to detect the spatial variation of indoor air quality (IAQ) in large mass gathering event venues. The paper summarises COVID-19 ventilation guidance for buildings and defines a methodology for measurement and rapid assessment of IAQ during occupancy at live events that can be implemented by venue managers. Comparisons of the CO2 concentrations measured during the events identified the spaces at high risk of long-range transmission of airborne pathogens. Building operators should be mindful of the ventilation strategies used relative to the total occupancy in different spaces and the occupant's activities.
Résumé
We present the CarbonTracker Europe High-Resolution (CTE-HR) system that estimates carbon dioxide (CO2) exchange over Europe at high resolution (0.1 × 0.2∘) and in near real time (about 2 months' latency). It includes a dynamic anthropogenic emission model, which uses easily available statistics on economic activity, energy use, and weather to generate anthropogenic emissions with dynamic time profiles at high spatial and temporal resolution (0.1×0.2∘, hourly). Hourly net ecosystem productivity (NEP) calculated by the Simple Biosphere model Version 4 (SiB4) is driven by meteorology from the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5th Generation (ERA5) dataset. This NEP is downscaled to 0.1×0.2∘ using the high-resolution Coordination of Information on the Environment (CORINE) land-cover map and combined with the Global Fire Assimilation System (GFAS) fire emissions to create terrestrial carbon fluxes. Ocean CO2 fluxes are included in our product, based on Jena CarboScope ocean CO2 fluxes, which are downscaled using wind speed and temperature. Jointly, these flux estimates enable modeling of atmospheric CO2 mole fractions over Europe.We assess the skill of the CTE-HR CO2 fluxes (a) to reproduce observed anomalies in biospheric fluxes and atmospheric CO2 mole fractions during the 2018 European drought, (b) to capture the reduction of anthropogenic emissions due to COVID-19 lockdowns, (c) to match mole fraction observations at Integrated Carbon Observation System (ICOS) sites across Europe after atmospheric transport with the Transport Model, version 5 (TM5) and the Stochastic Time-Inverted Lagrangian Transport (STILT), driven by ECMWF-IFS, and (d) to capture the magnitude and variability of measured CO2 fluxes in the city center of Amsterdam (the Netherlands).We show that CTE-HR fluxes reproduce large-scale flux anomalies reported in previous studies for both biospheric fluxes (drought of 2018) and anthropogenic emissions (COVID-19 pandemic in 2020). After applying transport of emitted CO2, the CTE-HR fluxes have lower median root mean square errors (RMSEs) relative to mole fraction observations than fluxes from a non-informed flux estimate, in which biosphere fluxes are scaled to match the global growth rate of CO2 (poor person's inversion). RMSEs are close to those of the reanalysis with the CTE data assimilation system. This is encouraging given that CTE-HR fluxes did not profit from the weekly assimilation of CO2 observations as in CTE.We furthermore compare CO2 concentration observations at the Dutch Lutjewad coastal tower with high-resolution STILT transport to show that the high-resolution fluxes manifest variability due to different emission sectors in summer and winter. Interestingly, in periods where synoptic-scale transport variability dominates CO2 concentration variations, the CTE-HR fluxes perform similarly to low-resolution fluxes (5–10× coarsened). The remaining 10 % of the simulated CO2 mole fraction differs by >2 ppm between the low-resolution and high-resolution flux representation and is clearly associated with coherent structures ("plumes”) originating from emission hotspots such as power plants. We therefore note that the added resolution of our product will matter most for very specific locations and times when used for atmospheric CO2 modeling. Finally, in a densely populated region like the Amsterdam city center, our modeled fluxes underestimate the magnitude of measured eddy covariance fluxes but capture their substantial diurnal variations in summertime and wintertime well.We conclude that our product is a promising tool for modeling the European carbon budget at a high resolution in near real time. The fluxes are freely available from the ICOS Carbon Portal (CC-BY-4.0) to be used for near-real-time monitoring and modeling, for example, as an a priori flux product in a CO2 data assimilation system. The data are available at 10.18160/20Z1-AYJ2 .
Résumé
With the outbreak of the COVID-19, remote diagnosis, patient monitoring, collection, and transmission of data from electronic devices is rapidly taking share in the health sector. These devices are however limited on resources like energy, memory and processing power. Consequently, it is highly relevant to investigate minimizing the data, keeping intact the information content. The objective of this study is to thus observe the impact of pixel, intensity, & temporal resolution on automated scoring of LUS data. First, 448 videos from 20 patients were normalized to a common pixel resolution, i.e., the largest found over the dataset (841 pixels/cm2). Next, pixel and intensity resolution were further reduced by down-sampling factor of 2,3, and 4, and by quantization factor of 2,4, and 8 respectively. Furthermore, number of frames were down-sampled as a function of time by factor of 1 to 10 with step-size of 1. Resampled, quantized, and temporally reduced videos were evaluated using the DL algorithm (doi: 10.1109/TMI.2020.2994459) and frame, video, and prognostic-level results were obtained. It was found that no significant change in the prognostic results is observed when the data is reduced by 32 times to its original size and by 10 times to the original number of frames. © 2022 Acoustical Society of America.
Résumé
Given that ultrasound use is increasing in healthcare, operators must be familiar with its physics in order to optimise the image and interpret potential artifacts. Ultrasound are sound waves at frequencies above the range of human hearing, that are transmitted from and received by an ultrasound transducer with piezoelectric properties. As it propagates through tissues, some of the ultrasound waves are reflected at tissue boundaries, leading to its detection by the ultrasound transducer. These are processed by the ultrasound machine and result in the generation of an image. Various settings can be adjusted to optimise the image, such as the frequency of the transmitted ultrasound wave, depth of the focal zone and the gain. Artifacts are presentations on the monitor of the ultrasound machine which are added, omitted, or are of improper brightness, location, shape, and size compared with true anatomical features. It can result in falsely perceived objects, missing structures or degraded images. The presence or absence of such artifacts in lung ultrasound can be valuable in the interpretation of the resulting image. In the setting of COVID-19, lung ultrasound has become increasingly useful in evaluating disease progression and providing a point-of-care radiological adjunct in clinical decision making. © World Federation of Societies of Anaesthesiologists 2022.