Data to support small area health impact modelling of air pollution in the United Kingdom.

The data presented in this article were used to estimate the impacts of air pollution policies on population health and health inequalities within a spatial microsimulation model, MicroEnv [1]. They provide a basis for comparison with similar models and allow researchers to integrate additional model components without duplication of effort. Relative risk estimates for the association between air pollution and rates of ischaemic heart disease (IHD) incidence, IHD case fatality and all-cause mortality were taken from a review of the epidemiological literature and meta-analyses [2]. Modelled small area air pollution data (PM2.5) for Greater London, UK were obtained from an environmental consultancy. All other data were collected from open source Governmental or Non-Government Organisation (NGO) data repositories. These include all-cause mortality rates; IHD incidence, prevalence and mortality rates; general fertility rates; small area socio-economic deprivation data; and relative risk estimates for the association between deprivation and all-cause mortality

Life Cycle Optimisation Study for Retrofitting an Archetype Building in New Cities in Egypt

This study aims to assess the potential environmental and economic benefits of retrofitting a residential archetype building under different scenarios. The study uses life cycle performance approaches to carry on a retrofitting scenario for an attached villa archetype in new cities in Egypt. After identifying three levels of energy retrofit measures (ERMs), a multi-objective optimisation framework was developed and carried out upon the case study model to optimise the Life Cycle Cost (LCC) and the Life Cycle Carbon Footprint (LCCF). The results of the study presented 4 different retrofitting scenarios with various investment costs and significantly improved operational costs and emissions

Analysis of inequalities in personal exposure to PM2.5: A modelling study for the Greater London school-aged population

Exposure to air pollution can lead to negative health impacts, with children highly susceptible due to their immature immune and lung systems. Childhood exposure may vary by socio-economic status (SES) due to differences in both outdoor and indoor air pollution levels, the latter of which depends on, for example, building quality, overcrowding and occupant behaviours; however, exposure estimates typically rely on the outdoor component only. Quantifying population exposure across SES requires accounting for variations in time-activity patterns, outdoor air pollution concentrations, and concentrations in indoor microenvironments that account for pollution-generating occupant behaviours and building characteristics. Here, we present a model that estimates personal exposure to PM2.5 for ~1.3 million children aged 4–16 years old in the Greater London region from different income groups. The model combines 1) A national time-activity database, which gives the percentage of each group in different residential and non-residential microenvironments throughout a typical day; 2) Distributions of modelled outdoor PM2.5 concentrations; 3) Detailed estimates of domestic indoor concentrations for different housing and occupant typologies from the building physics model, EnergyPlus, and; 4) Non-domestic concentrations derived from a mass-balance approach. The results show differences in personal exposure across socio-economic groups for children, where the median daily exposure across all scenarios (winter/summer and weekends/weekdays) is 17.2 μg/m3 (95%CIs: 12.1 μg/m3–41.2 μg/m3) for children from households in the lowest income quintile versus 14.5 μg/m3 (95%CIs: 11.5 μg/m3 – 27.9 μg/m3) for those in the highest income quintile. Though those from lower-income homes generally fare worse, approximately 57 % of London's school-aged population across all income groups, equivalent to 761,976 children, have a median daily exposure which exceeds guideline 24-h limits set by the World Health Organisation. The findings suggest residential indoor sources of PM2.5 are a large contributor to personal exposure for school children in London. Interventions to reduce indoor exposure in the home (for example, via the maintenance of kitchen extract ventilation and transition to cleaner cooking fuels) should therefore be prioritised along with the continued mitigation of outdoor sources in Greater London

Energy retrofit and passive cooling: overheating and air quality in primary schools

While building stock modelling has been used previously to investigate the space heating demand implications of national energy efficiency retrofitting, there are also implications for indoor overheating and air quality, particularly in schools, with highly intermittent occupancy patterns. This paper assesses indoor overheating risk and air quality within an English classroom stock model containing 111 archetypes, based on the analysis of the nationwide Property Data Survey Programme (PDSP) containing 9629 primary school buildings in England. Metrics for indoor temperatures, heating demand and concentrations of three contaminants (CO_{2}, NO_{2}, PM_{2.5}) were estimated in naturally ventilated classrooms, while exploring future climate projections, retrofit and overheating mitigation scenarios to analyse school stock resilience. Classrooms with a south-east orientation experience around four to six times the overheating-hours compared with those with a northern orientation. Post-1976 archetypes are most susceptible to overheating, indicative of the conflict between better insulated and airtight classrooms and overheating prevention. A range of retrofit and passive cooling measures can mitigate against overheating alone, although mechanically driven cooling and filtration may be required towards the 2080s. While no single measure predicted universally positive effects for building performance, night ventilation and overhangs were found to be particularly effective passive overheating mitigation methods across the school stock

The tectonic history of the Tasman Sea: A puzzle with 13 pieces

We present a new model for the tectonic evolution of the Tasman Sea based on dense satellite altimetry data and a new shipboard data set. We utilized a combined set of revised magnetic anomaly and fracture zone interpretations to calculate relative motions and their uncertainties between the Australian and the Lord Howe Rise plates from 73.6 Ma to 52 Ma when spreading ceased. From chron 31 (67.7 Ma) to chron 29 (64.0 Ma) the model implies, transpression between the Chesterfield and the Marion plateaus, followed by strike-slip motion. This transpression may have been responsible for the formation of the Capricorn Basin south of the Marion Plateau. Another major tectonic event took place at chron 27 (61.2 Ma), when a counterclockwise change in spreading direction occurred, contemporaneous with a similar event in the southwest Pacific Ocean. The early opening of the Tasman Sea cannot be modeled by a simple two-plate system because (1) rifting in this basin propagated from south to north in several stages and (2) several rifts failed. We identified 13 continental blocks which acted as microplates between 90 Ma and 64 Ma. Our model is constrained by tectonic lineaments visible in the gravity anomaly grid and interpreted as strike-slip faults, by magnetic anomaly, bathymetry and seismic data, and in case of the South Tasman Rise, by the age and affinity of dredged rocks. By combining all this information we derived finite rotations that describe the dispersal of these tectonic elements during the early opening of the Tasman Sea

Optimal retrofit solutions considering thermal comfort and intervention costs for the Mediterranean social housing stock

There is an impending need to retrofit the existing social housing stock to improve thermal comfort and to reduce energy demand. This research proposes calibrated building stock models to assess thermal comfort of the social housing stock of southern Spain (Mediterranean area). Several retrofit strategies are optimised using a genetic algorithm to obtain the best retrofit solutions, considering three objectives: annual overheating hours (%), annual undercooling hours (%) and investment costs (€/m2). Results are shown for four different climatic areas in southern Spain. This study finds that it is possible to retrofit the aforementioned stock considering investment costs from approximately 20–200 €/m2. The percent- age of improvements for each climatic area are as follows: in Sevilla (B4 climatic area), investments costs up to 50 €/m2 led to 40% and 20% annual overheating and undercooling hours. In Cádiz, (A3 climatic area), 15% and 22% overheating and undercooling hours were achieved with medium-cost solutions (50–100 €/ m2). In Almería (A4 climatic area), also medium-cost strategies reported approximately 15% and 30% overheating and undercooling hours. In Granada (C3 climatic area), 15% and 38% overheating and under- cooling hours were obtained with medium-cost measures. Yet, applying high-cost solutions (100–200 €/ m2) only significantly improved thermal comfort in Almería and Sevill

Overheating in English dwellings: comparing modelled and monitored large-scale datasets

Monitoring and modelling studies of the indoor environment indicate that there are often discrepancies between simulation results and measurements. The availability of large monitoring datasets of domestic buildings allows for more rigorous validation of the performance of building simulation models derived from limited building information, backed by statistical significance tests and goodness-of-fit metrics. These datasets also offer the opportunity to test modelling assumptions. This paper investigates the performance of domestic housing models using EnergyPlus software to predict maximum daily indoor temperatures over the summer of 2011. Monitored maximum daily indoor temperatures from the English Housing Survey's (EHS) Energy Follow-Up Survey (EFUS) for 823 nationally representative dwellings are compared against predictions made by EnergyPlus simulations. Due to lack of information on the characteristics of individual dwellings, the models struggle to predict maximum temperatures in individual dwellings and performance was worse on days when the outdoor maximum temperatures were high. This research indicates that unknown factors such as building characteristics, occupant behaviour and local environment makes the validation of models for individual dwellings a challenging task. The models did, however, provide an improved estimate of temperature exposure when aggregated over dwellings within a particular region

Improving indoor air quality and occupant health through smart control of windows and portable air purifiers in residential buildings

Indoor exposure to PM2.5 (particulate matter with aerodynamic diameter less than 2.5 μm) has a substantial negative impact on people’s health. However, indoor PM2.5 can be controlled through effective ventilation and filtration. This study aimed to develop a smart control framework that (1) combines a portable home air purifier (HAP) and window control system to reduce indoor PM2.5 concentrations whilst maintaining thermal comfort; (2) evaluates the associated health impacts and additional energy use. The proposed framework was demonstrated through a simulation-based case study of a low-energy apartment. The simulation results showed that joint control of HAP and window openings has great potential to not only maintain thermal comfort but also achieve effective PM2.5 removal which, consequently, can lead to considerable health benefits at a low additional energy cost. Compared to similar previous studies, the strength of the proposed control framework lies in combining window operations and HAPs in the same system and including both thermal comfort and indoor PM2.5 as the control targets. This work also introduces a novel concept of linking a building control system with a health impact assessment, an important and innovative step in the creation of holistic and responsive building controls. Practical application: This study proposes a novel control framework that jointly controls portable home air purifiers (HAPs) and windows to maintain thermal comfort and achieve effective PM2.5 removal. The simulation results suggest that such a hybrid control strategy can result in considerable health benefits at low additional energy costs

Analysis of inequalities in personal exposure to PM2.5: A modelling study for the greater London school-aged population

Exposure to air pollution can lead to negative health impacts, with children highly susceptible due to their immature immune and lung systems. Childhood exposure may vary by socio-economic status (SES) due to differences in both outdoor and indoor air pollution levels, the latter of which depends on, for example, building quality, overcrowding and occupant behaviours; however, exposure estimates typically rely on the outdoor component only. Quantifying population exposure across SES requires accounting for variations in time-activity patterns, outdoor air pollution concentrations, and concentrations in indoor microenvironments that account for pollution-generating occupant behaviours and building characteristics. Here, we present a model that estimates personal exposure to PM2.5 for ~1.3 million children aged 4–16 years old in the Greater London region from different income groups. The model combines 1) A national time-activity database, which gives the percentage of each group in different residential and non-residential microenvironments throughout a typical day; 2) Distributions of modelled outdoor PM2.5 concentrations; 3) Detailed estimates of domestic indoor concentrations for different housing and occupant typologies from the building physics model, EnergyPlus, and; 4) Non-domestic concentrations derived from a mass-balance approach. The results show differences in personal exposure across socio-economic groups for children, where the median daily exposure across all scenarios (winter/summer and weekends/weekdays) is 17.2 μg/m3 (95%CIs: 12.1 μg/m3–41.2 μg/m3) for children from households in the lowest income quintile versus 14.5 μg/m3 (95%CIs: 11.5 μg/m3 – 27.9 μg/m3) for those in the highest income quintile. Though those from lower-income homes generally fare worse, approximately 57 % of London's school-aged population across all income groups, equivalent to 761,976 children, have a median daily exposure which exceeds guideline 24-h limits set by the World Health Organisation. The findings suggest residential indoor sources of PM2.5 are a large contributor to personal exposure for school children in London. Interventions to reduce indoor exposure in the home (for example, via the maintenance of kitchen extract ventilation and transition to cleaner cooking fuels) should therefore be prioritised along with the continued mitigation of outdoor sources in Greater London.Peer reviewe

Projecting the impacts of housing on temperature-related mortality in London during typical future years

Climate change means the UK will experience warmer winters and hotter summers in the future. Concurrent energy efficiency improvements to housing may modify indoor exposures to heat or cold, while population aging may increase susceptibility to temperature-related mortality. We estimate heat and cold mortality and energy consumption in London for typical (non-extreme) future climates, given projected changes in population and housing. Building physics models are used to simulate summertime and wintertime indoor temperatures and space heating energy consumption of London dwellings for 'baseline' (2005-2014) and future (2030s, 2050s) periods using data from the English Housing Survey, historical weather data, and projected future weather data with temperatures representative of 'typical' years. Linking to population projections, we calculate future heat and cold attributable mortality and energy consumption with demolition, construction, and alternative scenarios of energy efficiency retrofit. At current retrofit rates, around 168-174 annual cold-related deaths per million population would typically be avoided by the 2050s, or 261-269 deaths per million under ambitious retrofit rates. Annual heat deaths would typically increase by 1 per million per year under the current retrofit rate, and 12-13 per million under ambitious rates without population adaptation to heat. During typical future summers, an estimated 38-73% of heat-related deaths can be avoided using external shutters on windows, with their effectiveness lower during hotter weather. Despite warmer winters, ambitious retrofit rates are necessary to reduce typical annual energy consumption for heating below baseline levels, assuming no improvement in heating system efficiencies. Concerns over future overheating in energy efficient housing are valid but increases in heat attributable mortality during typical and hot (but not extreme) summers are more than offset by significant reductions in cold mortality and easily mitigated using passive measures. More ambitious retrofit rates are critical to reduce energy consumption and offer co-benefits for reducing cold-related mortality