Probabilistic occupancy forecasting for risk-aware optimal ventilation through autoencoder Bayesian deep neural networks.

Ventilation plays a noteworthy role in maintaining a healthy, comfortable and energy-efficient indoor environment and mitigating the risk of aerosol transmission and disease infection (e.g., SARS-COV-2). In most commercial and office buildings, demand-controlled ventilation (DCV) systems are widely utilized to conserve energy based on occupancy. However, as the presence of occupants is often inherently stochastic, accurate occupancy prediction is challenging. This study, therefore, proposes an autoencoder Bayesian Long Short-term Memory neural network (LSTM) model for probabilistic occupancy prediction, taking account of model misspecification, epistemic uncertainty, and aleatoric uncertainty. Performances of the proposed models are evaluated using real data in an educational building at the University of Cambridge, UK. The models trained on data of one open-plan space are used to predict occupant numbers for other spaces (with similar layout and function) in the same building. The probabilistic occupant profiles are then used for estimating optimal ventilation rates for two scenarios (i.e., normal DCV mode for energy conservation and anti-infection mode for virus transmission prevention). Results show that, during the test period, for the 1-h ahead prediction, the proposed model achieved better performance with up to 5.8% mean absolute percentage error reduction than the traditional LSTM model. More flexible alternatives for ventilation can be offered by the proposed risk-aware decision-making schemes serving different purposes under real operation. The findings from this study provide new occupancy forecasting solutions and explore the potential of probabilistic decision making for building ventilation optimization.

The influence of temperature and genomic variation on intracranial EEG measures in people with epilepsy.

Heatwaves have serious impacts on human health and constitute a key health concern from anthropogenic climate change. People have different individual tolerance for heatwaves or unaccustomed temperatures. Those with epilepsy may be particularly affected by temperature as the electroclinical hallmarks of brain excitability in epilepsy (inter-ictal epileptiform discharges and seizures) are influenced by a range of physiological and non-physiological conditions. Heatwaves are becoming more common and may affect brain excitability. Leveraging spontaneous heatwaves during periods of intracranial EEG recording in participants with epilepsy in a non-air-conditioned telemetry unit at the National Hospital for Neurology and Neurosurgery in London from May to August 2015-22, we examined the impact of heatwaves on brain excitability. In London, a heatwave is defined as three or more consecutive days with daily maximum temperatures ≥28°C. For each participant, we counted inter-ictal epileptiform discharges using four 10-min segments within, and outside of, heatwaves during periods of intracranial EEG recording. Additionally, we counted all clinical and subclinical seizures within, and outside of, heatwaves. We searched for causal rare genetic variants and calculated the epilepsy PRS. Nine participants were included in the study (six men, three women), median age 30 years (range 24-39). During heatwaves, there was a significant increase in the number of inter-ictal epileptiform discharges in three participants. Five participants had more seizures during the heatwave period, and as a group, there were significantly more seizures during the heatwaves. Genetic data, available for eight participants, showed none had known rare, genetically-determined epilepsies, whilst all had high polygenic risk scores for epilepsy. For some people with epilepsy, and not just those with known, rare, temperature-sensitive epilepsies, there is an association between heatwaves and increased brain excitability. These preliminary data require further validation and exploration, as they raise concerns about the impact of heatwaves directly on brain health.

School building energy efficiency and NO2 related risk of childhood asthma in England and Wales: Modelling study.

BACKGROUND: Climate change legislation will require dramatic increases in the energy efficiency of school buildings across the UK by 2050, which has the potential to affect air quality in schools. We assessed how different strategies for improving the energy efficiency of school buildings in England and Wales may affect asthma incidence and associated healthcare utilization costs in the future. METHODS: Indoor concentrations of traffic-related NO2 were modelled inside school buildings representing 13 climate regions in England and Wales using a building physics school stock model. We used a health impact assessment model to quantify the resulting burden of childhood asthma incidence by combining regional health and population data with exposure-response functions from a recent high-quality systematic review/meta-analysis. We compared the effects of four energy efficiency interventions consisting of combinations of retrofit and operational strategies aiming to improve indoor air quality and thermal comfort on asthma incidence and associated hospitalization costs. RESULTS: The highest childhood asthma incidence was found in the Thames Valley region (including London), in particular in older school buildings, while the lowest concentrations and health burdens were in the newest schools in Wales. Interventions consisting of only operational improvements or combinations of retrofit and operational strategies resulted in reductions in childhood asthma incidence (547 and 676 per annum regional average, respectively) and hospital utilization costs (£52,050 and £64,310 per annum regional average, respectively. Interventions that improved energy efficiency without operational measures resulted in higher childhood asthma incidence and hospital costs. CONCLUSION: The effect of school energy efficiency retrofit on NO2 exposure and asthma incidence in schoolchildren depends critically on the use of appropriate building operation strategies. The findings from this study make several contributions to fill the knowledge gap about the impact of retrofitting schools on exposure to air pollutants and their effects on children's health.

Housing, health and energy: a characterisation of risks and priorities across Delhi's diverse settlements.

Improved housing has the potential to advance health and contribute to the Sustainable Development Goals. Research examining housing, health and energy use in low-income countries is limited; understanding these connections is vital to inform interventions for healthy sustainable human settlements. This paper investigates the low-income setting of Delhi, where rapid urbanisation, a varied climate, high pollution levels, and a wide variation in housing quality could result in significant energy use and health risks. Drawing on approaches from health and the built environment and existing data and literature, a characterisation of energy use and health risks for Delhi's housing stock is completed. Four broad settlement types were used to classify Delhi housing and energy use calculations and health risk assessment were performed for each variant. Energy use is estimated to be nearly two times higher per household among planned housing compared with other settlement types. Health risks, however, are found to be largest within informal slum settlements, with important contributions from heat and particulate matter across all settlements. This paper highlights intervention priorities and outlines the need for extensive further research, particularly through data gathering, to establish evidence to accelerate achieving healthy, sustainable and equitable housing in Delhi.

The summer indoor temperatures of the English housing stock: Exploring the influence of dwelling and household characteristics.

As the high temperatures experienced during the summer of 2018 may become commonplace by 2050, adaptation to higher indoor temperatures while minimising the need for mechanical cooling is required. A thorough understanding of the factors that influence indoor temperatures can enable the design of healthier and safer dwellings under a warming climate. The aim of this paper is to provide further insight into the topic of indoor overheating through the analysis of the largest recent sample of English dwellings, the 2011 Energy Follow-Up Survey, comprised of 823 dwellings. Following the pre-processing stage, the indoor overheating risk of 795 living rooms and 799 bedrooms was quantified using the criteria defined within CIBSE's Technical Memorandum 59. Approximately 2.5% of the dwellings were found to exceed Criterion 1, with this figure approaching 26% when Criterion 2 was considered. Subsequently, the indoor temperatures were standardised against external weather conditions and the correlation of 11 dwelling and 9 household characteristics was examined. Factors such as the main heating system, tenure and occupant vulnerability were all found to have a statistically significant association with the indoor temperatures. Further analysis revealed multiple correlations between household and dwelling characteristics, highlighting the complexity of the indoor overheating problem. Practical application : By applying the criteria in CIBSE's TM59, 26% of the dwellings monitored during the 2011 Energy Follow-Up Survey were found to overheat. Since 2011 was a cool summer and future temperatures are expected to be warmer, even more dwellings are expected to fail these criteria in the future. Multiple dwelling and household characteristics were associated with higher indoor temperatures, including: dwellings with a SAP rating > 70, more recently built and with communal heating. Thus, it is crucial to consider indoor overheating risk at the building design or refurbishment stage to prevent the possible consequences of uncomfortably high indoor temperatures.

Comparison of built environment adaptations to heat exposure and mortality during hot weather, West Midlands region, UK.

There is growing recognition of the need to improve protection against the adverse health effects of hot weather in the context of climate change. We quantify the impact of the Urban Heat Island (UHI) and selected adaptation measures made to dwellings on temperature exposure and mortality in the West Midlands region of the UK. We used 1) building physics models to assess indoor temperatures, initially in the existing housing stock and then following adaptation measures (energy efficiency building fabric upgrades and/or window shutters), of representative dwelling archetypes using data from the English Housing Survey (EHS), and 2) modelled UHI effect on outdoor temperatures. The ages of residents were combined with evidence on the heat-mortality relationship to estimate mortality risk and to quantify population-level changes in risk following adaptations to reduce summertime heat exposure. Results indicate that the UHI effect accounts for an estimated 21% of mortality. External shutters may reduce heat-related mortality by 30-60% depending on weather conditions, while shutters in conjunction with energy-efficient retrofitting may reduce risk by up to 52%. The use of shutters appears to be one of the most effective measures providing protection against heat-related mortality during periods of high summer temperatures, although their effectiveness may be limited under extreme temperatures. Energy efficiency adaptations to the dwellings and measures to increase green space in the urban environment to combat the UHI effect appear to be less beneficial for reducing heat-related mortality.

Creating individual level air pollution exposures in an anonymised data safe haven: a platform for evaluating impact on educational attainment.

INTRODUCTION: There is a lack of evidence on the adverse effects of air pollution on cognition for people with air quality-related health conditions. We propose that educational attainment, as a proxy for cognition, may increase with improved air quality. This study will explore whether asthma and seasonal allergic rhinitis, when exacerbated by acute exposure to air pollution, is associated with educational attainment. OBJECTIVE: To describe the preparation of individual and household-level linked environmental and health data for analysis within an anonymised safe haven. Also to introduce our statistical analysis plan for our study: COgnition, Respiratory Tract illness and Effects of eXposure (CORTEX). METHODS: We imported daily air pollution and aeroallergen data, and individual level education data into the SAIL databank, an anonymised safe haven for person-based records. We linked individual-level education, socioeconomic and health data to air quality data for home and school locations, creating tailored exposures for individuals across a city. We developed daily exposure data for all pupils in repeated cross sectional exam cohorts (2009-2015). CONCLUSION: We have used the SAIL databank, an innovative, data safe haven to create individual-level exposures to air pollution and pollen for multiple daily home and school locations. The analysis platform will allow us to evaluate retrospectively the impact of air quality on attainment for multiple cross-sectional cohorts of pupils. Our methods will allow us to distinguish between the pollution impacts on educational attainment for pupils with and without respiratory health conditions. The results from this study will further our understanding of the effects of air quality and respiratory-related health conditions on cognition. HIGHLIGHTS: This city-wide study includes longitudinal routinely-recorded educational attainment data for all pupils taking exams over seven years;High spatial resolution air pollution data were linked within a privacy protected databank to obtain individual exposure at multiple daily locations;This study will use health data linked at the individual level to explore associations between air pollution, related morbidity, and educational attainment.

Impact of climate change on the domestic indoor environment and associated health risks in the UK.

There is growing evidence that projected climate change has the potential to significantly affect public health. In the UK, much of this impact is likely to arise by amplifying existing risks related to heat exposure, flooding, and chemical and biological contamination in buildings. Identifying the health effects of climate change on the indoor environment, and risks and opportunities related to climate change adaptation and mitigation, can help protect public health. We explored a range of health risks in the domestic indoor environment related to climate change, as well as the potential health benefits and unintended harmful effects of climate change mitigation and adaptation policies in the UK housing sector. We reviewed relevant scientific literature, focusing on housing-related health effects in the UK likely to arise through either direct or indirect mechanisms of climate change or mitigation and adaptation measures in the built environment. We considered the following categories of effect: (i) indoor temperatures, (ii) indoor air quality, (iii) indoor allergens and infections, and (iv) flood damage and water contamination. Climate change may exacerbate health risks and inequalities across these categories and in a variety of ways, if adequate adaptation measures are not taken. Certain changes to the indoor environment can affect indoor air quality or promote the growth and propagation of pathogenic organisms. Measures aimed at reducing greenhouse gas emissions have the potential for ancillary public health benefits including reductions in health burdens related heat and cold, indoor exposure to air pollution derived from outdoor sources, and mould growth. However, increasing airtightness of dwellings in pursuit of energy efficiency could also have negative effects by increasing concentrations of pollutants (such as PM2.5, CO and radon) derived from indoor or ground sources, and biological contamination. These effects can largely be ameliorated by mechanical ventilation with heat recovery (MVHR) and air filtration, where such solution is feasible and when the system is properly installed, operated and maintained. Groups at high risk of these adverse health effects include the elderly (especially those living on their own), individuals with pre-existing illnesses, people living in overcrowded accommodation, and the socioeconomically deprived. A better understanding of how current and emerging building infrastructure design, construction, and materials may affect health in the context of climate change and mitigation and adaptation measures is needed in the UK and other high income countries. Long-term, energy efficient building design interventions, ensuring adequate ventilation, need to be promoted.