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Funder: UK Research and Innovation; Id: http://dx.doi.org/10.13039/100014013, Experiments were conducted in an UK inter-city train carriage with the aim of evaluating the risk of infection to the SARS-CoV-2 virus via airborne transmission. The experiments included in-service CO2 measurements and the measurement of salt aerosol concentrations released within the carriage. Computational fluid dynamics simulations of the carriage airflow were also used to visualise the airflow patterns, and the efficacy of the HVAC filter material was tested in a laboratory. Assuming an infectious person is present, the risk of infection for a 1-h train journey was estimated to be 6 times lower than for a full day in a well-ventilated office, or 10-12 times lower than a full day in a poorly ventilated office. While the absolute risk for a typical journey is likely low, in the case where a particularly infectious individual is on-board, there is the potential for a number of secondary infections to occur during a 1-h journey. Every effort should therefore be made to minimize the risk of airborne infection within these carriages. Recommendations are also given for the use of CO2 sensors for the evaluation of the risk of airborne transmission on train carriages.

Supplementary material concerning the spread of COVID-19 focusing on: Natural inputs to ventilation provision, SARS-CoV-2 on hard surfaces, UVGI and COVID-19, and Aerosols in the context of singing, and woodwind & brass musical instruments.

Recently, the method of difference potentials has been extended to linear elastic fracture mechanics. The solution was calculated on a grid boundary belonging to the domain of an auxiliary problem, which must be solved multiple times. Singular enrichment functions, such as those used within the extended finite element method, were introduced to improve the approximation near the crack tip leading to near-optimal convergence rates. Now, the method is further developed by significantly reducing the computation time. This is achieved via the implementation of a system of basis functions introduced along the physical boundary of the problem. The basis functions form an approximation of the trace of the solution at the physical boundary. This method has been proven efficient for the solution of problems on regular (Lipschitz) domains. By introducing the singularity into the finite element space, the approximation of the crack can be realised by regular functions. Near-optimal convergence rates are then achieved for the enriched formulation. A solution algorithm using the fast Fourier transform is provided with the aim of further increasing the efficiency of the method.

Air pollution has been identified as a major problem in modern societies, threatening urban population health. Pedestrians, in particular, are directly exposed to one of the main sources of air pollutants: road transport, which is concentrated in proximity to the road, worsening the air. Green infrastructure (GI) has been promoted as a natural method for reducing exposure to local street air pollutants and providing additional Ecosystem Services with a range of environmental, social and economic benefits for citizens. The effectiveness of GI for improving air quality depends on the spatio-temporal context and the species-specific characteristics of the GI. Urban planting could maximise this benefit by a holistic understanding of the effects of GI in cities, balancing its benefits and constraints. However, little is currently known about the application of GI design and planning with regard to air pollution mitigation. Moreover, there is little agreement on the quantifiable effectiveness of GI in improving street air quality as its effectiveness is highly context dependent. Holistic guidance is therefore needed to inform practitioners of site- and species- specifics, trade-offs, and GI maintenance considerations for successful urban planting. This research reviews the academic literature addressing GI-related characteristics in streets, creating a holistic framework to help guide decision-makers on using GI solutions to improve air quality. Additionally, this research aims to understand how and which GI, along with other local characteristics, influence pedestrian air quality and how these characteristics are considered in real-world practice within the United Kingdom. This research progresses through three stages: First, the mechanisms by which GI is considered to influence air quality were identified through literature reviews. A specific literature review was then conducted for each mechanism to extract the associated GI and spatial characteristics that affect the potential for GI to mitigate urban air pollution. In the second stage, this list of characteristics, together with other Ecosystem Services, was discussed in consultation with practitioners in the UK. A survey was conducted to explore and evaluate the recommendations and resources available for planning plantings, as well as the practitioners’ knowledge about the characteristics associated with mitigating air pollution. Supported by results from the survey and the literature reviews, the third stage evaluated (validated) an easy-to-use computational model for its potential use in improving planting decisions for air pollution mitigation. Green infrastructure influences air quality by providing surfaces for pollutant deposition and absorption, effects on airflow and dispersion, and biogenic emissions. The relationship between the specific GI and the spatio-temporal context also influences air quality. Street structure, weather variables, and the type, shape and size of GI influence the dispersion of pollutants, with micro-and macro-morphological traits additionally influencing particulate deposition and gas absorption. In addition, maintaining GI lessens air quality deterioration by controlling biogenic emissions. According to participants in the survey, aesthetics were the principal drivers of urban planting, followed by improving well-being and increasing biodiversity and air pollution mitigation as a lesser priority. Characteristics such as airflow manipulation, leaf surface traits, and biogenic emissions were the less important influences in planting decisions in the UK, despite the fact that these characteristics influence air quality. Perhaps, a lack of communication of current information and low confidence about which specific characteristics have a tangible effect on air quality reduces the incorporation of GI for air pollution mitigation purposes. Uncertainties exist about the quantification of pollutants removed by GI. Field campaigns and computational models still need improvement to address the effectiveness of GI in real-world environments adequately and also to understand whether GI can exert a significant effect on pollutant levels under real-world conditions. This research showed that a promising and easy-to-use model used to evaluate the effectiveness of trees in removing particles was not an acceptable model to study the effect of GI on streets. The validation results showed a poor agreement between wind tunnel data and the model results. More effort is needed to develop better modelling tools that can quantify the actual effect of GI on improving street air quality. This research contributes to the air pollution mitigation field, explicitly helping to inform decision-making for more health-promoting urban settings by optimising the expected benefits of GI through a holistic understanding of their impacts. Facilitating the communication of current evidence through a holistic guide that considers both the benefits and trade-offs of planting decisions for air quality improvement. Improving information on air pollution mitigation to feed the decision-making process might maximise the benefits of GI planting for air pollution mitigation in streets. Open Access

The year 2020 has seen the emergence of a global pandemic as a result of the disease COVID-19. This report reviews knowledge of the transmission of COVID-19 indoors, examines the evidence for mitigating measures, and considers the implications for wintertime with a focus on ventilation., This work was undertaken as a contribution to the Rapid Assistance in Modelling the Pandemic (RAMP) initiative, coordinated by the Royal Society.