Determinants of CO Exposure in the English Housing Stock: Modelling Current and Future Risks

This report investigates the current distribution of low-level CO concentrations in the English housing stock, and prevalence of dwellings exceeding recommended background exposure levels, using advanced modelling techniques informed by empirical data from a number of disparate sources. By bringing these sources of data together in the models, it is possible to produce new insights into the variation in background CO exposure across dwelling types and geographical location. The model also considers the impact on indoor domestic CO concentrations of the application of energy efficiency measures on the same stock. Although the health effects of long-term low-level CO exposure are still uncertain, this report provides evidence for further discussion and research. There are a number of assumptions listed within the main report, that drive the results. These should be taken into consideration when interpreting outcomes

The effect of sampling techniques used in the multiconfigurational Ehrenfest method

In this paper, we compare and contrast basis set sampling techniques recently developed for use in the ab initio multiple cloning method, a direct dynamics extension to the multiconfigurational Ehrenfest approach, used recently for the quantum simulation of ultrafast photochemistry. We demonstrate that simultaneous use of basis set cloning and basis function trains can produce results which are converged to the exact quantum result. To demonstrate this, we employ these sampling methods in simulations of quantum dynamics in the spin boson model with a broad range of parameters and compare the results to accurate benchmarks

Identifying key experience-related differences in over-ground manual wheelchair propulsion biomechanics

OBJECTIVE: The purpose of this study was to investigate technique differences between expert and novice manual wheelchair users during over-ground wheelchair propulsion. METHOD: Seven experts (spinal cord injury level between T5 and L1) and six novices (non-wheelchair users) pushed a manual wheelchair over level ground, a 2.5% cross slope and up a 6.5% incline (7.2 m length) and 12% incline (1.5 m length). Push rim kinetics, trunk and shoulder kinematics and muscle activity level were measured. RESULTS: During the level and cross slope tasks, the experts completed the tasks with fewer pushes by applying a similar push rim moment over a greater push arc, demonstrating lower muscle activity. During the incline tasks, the experts required fewer pushes and maintained a greater average velocity, generating greater power by applying a similar push rim moment over a greater push arc with greater angular velocity, demonstrating greater trunk flexion and higher shoulder muscle activity. CONCLUSIONS: This study identifies experience-related differences during over-ground manual wheelchair propulsion. These differences are particularly evident during incline propulsion, with the experts generating significantly greater power to maintain a higher velocity

Exposure to indoor air pollution across socio-economic groups: A review of the literature and a modelling methodology

Disparities in outdoor air pollution exposure between populations of different socio-economic status is a growing area of research, widely explored in environmental health literature. However, in developed countries, around 80% of time is spent indoors, meaning indoor air pollution may be a better proxy for personal exposure. Building characteristics and occupant behaviour mean indoor air pollution may also vary across socio-economic groups, leading to health inequalities. Following the results of a review carried out into indoor air pollution disparities, we incorporate socio-economic information into an indoor air quality model in order to evaluate exposure disparities in the indoor environment. The building physics tool EnergyPlus was used to model the effect of two policy interventions on indoor exposure to PM2.5 in two socio-economically different populations. Results suggest that households of low socio-economic status may be disproportionately affected by building and/or environmental policies which are implemented without consideration of the wider socio-economic processes governing the space

Modelling population exposure to high indoor temperatures under changing climates, housing conditions, and urban environments in England

: The exposure of an individual to heat during hot weather depends on several factors including local outdoor temperatures and possible Urban Heat Island (UHI) effects, the thermal performance of the building they inhabit, and any actions that they are able to take in order to modify the indoor thermal conditions. There is an increasing body of research that seeks to understand how housing, UHI, and occupant profiles may alter the risk of mortality during hot weather. Housing overheating models have been of particular interest due to the amount of time spent indoors and the need to improve the energy efficiency of the UK housing stock. A number of housing overheating models have been created in order to understand how changes to the building stock and climate may alter heat exposure and risks of heatrelated mortality. We briefly describe the development of a metamodel – a model derived from the outputs of EnergyPlus dynamic thermal simulation models of building variants – and its application to a housing stock model representative of the West Midlands, UK. We model the stock under a ‘current’ scenario, as described by the 2010-2011 English Housing Survey, and then following a full energy-efficient building fabric retrofit or the installation of external window shutters. Initial results indicate a wide range of overheating risks inside dwelling variants in Birmingham, with flats and bungalows most vulnerable to overheating, and detached dwellings least vulnerable. Modelling of the full retrofit of buildings indicated that the stock would experience an overall increase in overheating, while external shutters were able to decrease overheating significantly

Modelling Long-Term Urban Temperatures with Less Training Data: A Comparative Study Using Neural Networks in the City of Madrid

In the last decades, urban climate researchers have highlighted the need for a reliable provision of meteorological data in the local urban context. Several efforts have been made in this direction using Artificial Neural Networks (ANN), demonstrating that they are an accurate alternative to numerical approaches when modelling large time series. However, existing approaches are varied, and it is unclear how much data are needed to train them. This study explores whether the need for training data can be reduced without overly compromising model accuracy, and if model reliability can be increased by selecting the UHI intensity as the main model output instead of air temperature. These two approaches were compared using a common ANN configuration and under different data availability scenarios. Results show that reducing the training dataset from 12 to 9 or even 6 months would still produce reliable results, particularly if the UHI intensity is used. The latter proved to be more effective than the temperature approach under most training scenarios, with an average RMSE improvement of 16.4% when using only 3 months of data. These findings have important implications for urban climate research as they can potentially reduce the duration and cost of field measurement campaigns

Use of a saliva-based diagnostic test to identify tapeworm infection in horses in the UK

Background: Anthelmintic resistance combined with limited chemotherapeutic options has prompted a change in approaches to control of equine helminth infections. Targeted selective treatment strategies use diagnostics to reduce anthelmintic use by treating individuals with worm burdens or egg shedding levels above a set threshold. While faecal egg count analysis has limitations for informing tapeworm treatment, a commercially available saliva-based diagnostic test accurately diagnoses horses with tapeworm infection. Objectives: Evaluation of a saliva-based diagnostic test to identify horses naturally infected with tapeworm and assess the impact of using the test to inform anthelmintic administration. Study design: Retrospective longitudinal study. Methods: Saliva was collected from horses (n = 237) at a UK welfare charity from autumn 2015 to autumn 2016. Horses diagnosed as positive for tapeworm infection using the EquiSal® Tapeworm test were anthelmintic treated according to weight. The number of horses that received anthelmintic treatment based on the test result was compared with an all-group treatment approach and the reduction in anthelmintic usage calculated. Incoming horses were also tested (n = 143) and the information was used to inform quarantine treatments. Results: In autumn 2015, 85% of 237 horses tested received no anthelmintic and the majority (71%) of these remained below the treatment threshold throughout the study. Of the 69 horses that received treatment, seven required treatment following three subsequent tests, while >50% of horses administered with anthelmintic fell below the treatment threshold at the following test. No increase in tapeworm prevalence within the 237 horses was observed during the study despite a substantial reduction in the application of antitapeworm treatments. A total of 41% of incoming horses required anticestode treatment. Main limitations: Other management practices were not included in the analysis. Conclusions: Compared with an all-group treatment strategy, the diagnostic-led approach used here considerably reduced application of anticestode anthelmintics. This could reduce selection pressure for anthelmintic resistance