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.

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.

Relationship-building around a policy decision-support tool for urban health.

Contemporary challenges linked to public health and climate change demand more effective decision-making and urban planning practices, in particular by taking greater account of evidence. In order to do this, trust-building relationships between scientists and urban practitioners through collaborative research programmes is required. Based on a policy-relevant research project, Complex Urban Systems for Sustainability and Health (CUSSH), this project aims to support the transformation of cities to meet environmental imperatives and to improve health with a quantitative health impact assessment. A case study in Rennes, France, focuses on the role of a policy decision-support tool in the production and use of knowledge to support evidence-informed decision-making. Although the primary objective of informing decision-making through evidence-based science is not fulfilled, the use of a decision-making support tool can lay the foundations for relationship-building. It can serve as a support for boundary-spanning activities, which are recognised for their effectiveness in linking science to action. This case study illustrates that the path of knowledge transfer from science to policy can be challenging, and the usefulness of using models may not be where it was thought to have been.

Systemic inequalities in indoor air pollution exposure in London, UK.

Deprived communities in many cities are exposed to higher levels of outdoor air pollution, and there is increasing evidence of similar disparities for indoor air pollution exposure. There is a need to understand the drivers for this exposure disparity in order to develop effective interventions aimed at improving population health and reducing health inequities. With a focus on London, UK, this paper assembles evidence to examine why indoor exposure to PM2.5, NOx and CO may disproportionately impact low-income groups. In particular, five factors are explored, namely: housing location and ambient outdoor levels of pollution; housing characteristics, including ventilation properties and internal sources of pollution; occupant behaviours; time spent indoors; and underlying health conditions. Evidence is drawn from various sources, including building physics models, modelled outdoor air pollution levels, time-activity surveys, housing stock surveys, geographical data, and peer-reviewed research. A systems framework is then proposed to integrate these factors, highlighting how exposure to high levels of indoor air pollution in low-income homes is in large part due to factors beyond the control of occupants, and is therefore an area of systemic inequality. POLICY RELEVANCE: There is increasing public and political awareness of the impact of air pollution on public health. Strong scientific evidence links exposure to air pollution with morbidity and mortality. Deprived communities may be more affected, however, with limited evidence on how deprivation may influence their personal exposure to air pollution, both outdoors and indoors. This paper describes different factors that may lead to low-income households being exposed to higher levels of indoor air pollution than the general population, using available data and models for London (i.e. living in areas of higher outdoor air pollution, in poor-quality housing, undertaking more pollution-generating activities indoors and spending more time indoors). A systems approach is used to show how these factors lead to systemic exposure inequalities, with low-income households having limited opportunities to improve their indoor air quality. This paper can inform actions and public policies to reduce environmental health inequalities, considering both indoor and outdoor air.

The CUSSH programme: supporting cities' transformational change towards health and sustainability.

This paper describes a global research programme on the complex systemic connections between urban development and health. Through transdisciplinary methods the Complex Urban Systems for Sustainability and Health (CUSSH) project will develop critical evidence on how to achieve the far-reaching transformation of cities needed to address vital environmental imperatives for planetary health in the 21st Century. CUSSH's core components include: (i) a review of evidence on the effects of climate actions (both mitigation and adaptation) and factors influencing their implementation in urban settings; (ii) the development and application of methods for tracking the progress of cities towards sustainability and health goals; (iii) the development and application of models to assess the impact on population health, health inequalities, socio-economic development and environmental parameters of urban development strategies, in order to support policy decisions; (iv) iterative in-depth engagements with stakeholders in partner cities in low-, middle- and high-income settings, using systems-based participatory methods, to test and support the implementation of the transformative changes needed to meet local and global health and sustainability objectives; (v) a programme of public engagement and capacity building. Through these steps, the programme will provide transferable evidence on how to accelerate actions essential to achieving population-level health and global climate goals through, amongst others, changing cities' energy provision, transport infrastructure, green infrastructure, air quality, waste management and housing.

Exposure to indoor air pollution across socio-economic groups in high-income countries: A scoping review of the literature and a modelling methodology.

Disparities in outdoor air pollution exposure between individuals of differing socio-economic status is a growing area of research, widely explored in the 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 - such as build quality, volume and ventilation - and occupant behaviour, mean indoor air pollution may also vary across socio-economic groups, leading to health inequalities. Much of the existing literature has focused on inequalities in exposure to outdoor air pollution, and there is thus a lack of an evidence base reviewing data for indoor environments. In this study, a scoping review of the literature on indoor air pollution exposures across different socio-economic groups is performed, examining evidence from both monitoring and modelling studies in the developed world. The literature was reviewed, identifying different indoor pollutants, definitions for socio-economic status and pre- and post- housing interventions. Based on the review, the study proposes a modelling methodology for evaluating the effects of environmental policies on different socio-economic populations. Using a sample size calculation, obstacles in obtaining sufficiently large samples of monitored data are demonstrated. A modelling framework for the rapid quantification of daily home exposure is then outlined as a proof of concept. While significant additional research is required to examine inequalities in indoor exposures, modelling approaches may provide opportunities to quantify exposure disparities due to housing and behaviours across populations of different socio-economic status.

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.

A tool for assessing the climate change mitigation and health impacts of environmental policies: the Cities Rapid Assessment Framework for Transformation (CRAFT).

Background: A growing number of cities, including Greater London, have set ambitious targets, including detailed policies and implementation plans, to reach global goals on sustainability, health, and climate change. Here we present a tool for a rapid assessment of the magnitude of impact of specific policy initiatives to reach these targets. The decision-support tool simultaneously quantifies the environmental and health impacts of specified selected policies. Methods: The 'Cities Rapid Assessment Framework for Transformation (CRAFT)' tool was applied to Greater London. CRAFT quantifies the effects of ten environmental policies on changes in (1) greenhouse gas (GHG) emissions, (2) exposures to environmental hazards, (3) travel-related physical activity, and (4) mortality (the number of attributable deaths avoided in one typical year). Publicly available data and epidemiological evidence were used to make rapid quantitative estimates of these effects based on proportional reductions in GHG emissions and environmental exposures from current baseline levels and to compute the mortality impacts. Results: The CRAFT tool estimates that, of roughly 50,000 annual deaths in Greater London, the modelled hazards (PM 2.5 (from indoor and outdoor sources), outdoor NO 2, indoor radon, cold, overheating) and low travel-related physical activity are responsible for approximately 10,000 premature environment-related deaths. Implementing the selected polices could reduce the annual mortality number by about 20% (~1,900 deaths) by 2050. The majority of these deaths (1,700) may be avoided through increased uptake in active travel. Thus, out of ten environmental policies, the 'active travel' policy provides the greatest health benefit. Also, implementing the ten policies results in a GHG reduction of around 90%. Conclusions: The CRAFT tool quantifies the effects of city policies on reducing GHG emissions, decreasing environmental health hazards, and improving public health. The tool has potential value for policy makers through providing quantitative estimates of health impacts to support and prioritise policy options.

Home energy efficiency and radon: An observational study.

Exposure to radon gas is the second leading cause of lung cancer worldwide behind smoking. Changing the energy characteristics of a dwelling can influence both its thermal and ventilative properties, which can affect indoor air quality. This study uses radon measurements made in 470 689 UK homes between 1980 and 2015, linked to dwelling information contained within the Home Energy Efficiency Database (HEED). The linked dataset, the largest of its kind, was used to analyze the association of housing and energy performance characteristics with indoor radon concentrations in the UK. The findings show that energy efficiency measures that increase the airtightness of properties are observed to have an adverse association with indoor radon levels. Homes with double glazing installed had radon measurements with a significantly higher geometric mean, 67% (95% CI: 44, 89) greater than those without a recorded fabric retrofit. Those with loft insulation (47%, 95% CI: 26, 69) and wall insulation (32%, 95% CI: 11, 53) were also found to have higher radon readings. Improving the energy performance of the UK's housing stock is vital in meeting carbon emission reduction targets. However, compromising indoor air quality must be avoided through careful assessment and implementation practices.

Application of an indoor air pollution metamodel to a spatially-distributed housing stock.

Estimates of population air pollution exposure typically rely on the outdoor component only, and rarely account for populations spending the majority of their time indoors. Housing is an important modifier of air pollution exposure due to outdoor pollution infiltrating indoors, and the removal of indoor-sourced pollution through active or passive ventilation. Here, we describe the application of an indoor air pollution modelling tool to a spatially distributed housing stock model for England and Wales, developed from Energy Performance Certificate (EPC) data and containing information for approximately 11.5 million dwellings. First, we estimate indoor/outdoor (I/O) ratios and total indoor concentrations of outdoor air pollution for PM2.5 and NO2 for all EPC dwellings in London. The potential to estimate concentration from both indoor and outdoor sources is then demonstrated by modelling indoor background CO levels for England and Wales pre- and post-energy efficient adaptation, including heating, cooking, and smoking as internal sources. In London, we predict a median I/O ratio of 0.60 (99% CIs; 0.53-0.73) for outdoor PM2.5 and 0.41 (99%CIs; 0.34-0.59) for outdoor NO2; Pearson correlation analysis indicates a greater spatial modification of PM2.5 exposure by housing (ρ = 0.81) than NO2 (ρ = 0.88). For the demonstrative CO model, concentrations ranged from 0.4-9.9 ppm (99%CIs)(median = 3.0 ppm) in kitchens and 0.3-25.6 ppm (median = 6.4 ppm) in living rooms. Clusters of elevated indoor concentration are found in urban areas due to higher outdoor concentrations and smaller dwellings with reduced ventilation potential, with an estimated 17.6% increase in the number of living rooms and 63% increase in the number of kitchens exceeding recommended exposure levels following retrofit without additional ventilation. The model has the potential to rapidly calculate indoor pollution exposure across large housing stocks and estimate changes to exposure under different pollution or housing policy scenarios.

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.

MicroEnv: A microsimulation model for quantifying the impacts of environmental policies on population health and health inequalities.

The Sustainable Development Goals (SDGs) recognise the critical need to improve population health and environmental sustainability. This paper describes the development of a microsimulation model, MicroEnv, aimed at quantifying the impact of environmental exposures on health as an aid to selecting policies likely to have greatest benefit. Its methods allow the integration of morbidity and mortality outcomes and the generation of results at high spatial resolution. We illustrate its application to the assessment of the impact of air pollution on health in London. Simulations are performed at Lower Layer Super Output Area (LSOA), the smallest geographic unit (population of around 1500 inhabitants) for which detailed socio-demographic data are routinely available in the UK. The health of each individual in these LSOAs is simulated year-by-year using a health-state-transition model, where transition probabilities from one state to another are based on published statistics modified by relative risks that reflect the effect of environmental exposures. This is done through linkage of the simulated population in each LSOA with 1 × 1 km annual average PM2.5 concentrations and area-based deprivation indices. Air pollution is a leading cause of mortality and morbidity globally, and improving air quality is critical to the SDGs for Health (Goal 3) and Cities (Goal 11). The evidence of MicroEnv is aimed at providing better understanding of the benefits for population health and health inequalities of policy actions that affect exposure such as air quality, and thus to help shape policy decisions. Future work will extend the model to integrate other environmental determinants of health.

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.