A mathematical, classical stratification modeling approach to disentangling the impact of weather on infectious diseases: A case study using spatio-temporally disaggregated Campylobacter surveillance data for England and Wales.

Disentangling the impact of the weather on transmission of infectious diseases is crucial for health protection, preparedness and prevention. Because weather factors are co-incidental and partly correlated, we have used geography to separate out the impact of individual weather parameters on other seasonal variables using campylobacteriosis as a case study. Campylobacter infections are found worldwide and are the most common bacterial food-borne disease in developed countries, where they exhibit consistent but country specific seasonality. We developed a novel conditional incidence method, based on classical stratification, exploiting the long term, high-resolution, linkage of approximately one-million campylobacteriosis cases over 20 years in England and Wales with local meteorological datasets from diagnostic laboratory locations. The predicted incidence of campylobacteriosis increased by 1 case per million people for every 5° (Celsius) increase in temperature within the range of 8°-15°. Limited association was observed outside that range. There were strong associations with day-length. Cases tended to increase with relative humidity in the region of 75-80%, while the associations with rainfall and wind-speed were weaker. The approach is able to examine multiple factors and model how complex trends arise, e.g. the consistent steep increase in campylobacteriosis in England and Wales in May-June and its spatial variability. This transparent and straightforward approach leads to accurate predictions without relying on regression models and/or postulating specific parameterisations. A key output of the analysis is a thoroughly phenomenological description of the incidence of the disease conditional on specific local weather factors. The study can be crucially important to infer the elusive mechanism of transmission of campylobacteriosis; for instance, by simulating the conditional incidence for a postulated mechanism and compare it with the phenomenological patterns as benchmark. The findings challenge the assumption, commonly made in statistical models, that the transformed mean rate of infection for diseases like campylobacteriosis is a mere additive and combination of the environmental variables.

Future temperature-related mortality in the UK under climate change scenarios: Impact of population ageing and bias-corrected climate projections.

BACKGROUND: Exposure to heat and cold poses a serious threat to human health. In the UK, hotter summers, milder winters and an ageing population will shift how populations experience temperature-related health burdens. Estimating future burdens can provide insights on the drivers of temperature-related health effects and removing biases in temperature projections is an essential step to generating these estimates, however, the impact of various methods of correction is not well examined. METHODS: We conducted a detailed health impact assessment by estimating mortality attributable to temperature at a baseline period (2007-2018) and in future decades (2030s, 2050s and 2070s). Epidemiological exposure-response relationships were derived for all England regions and UK countries, to quantify cold and heat risk, and temperature thresholds where mortality increases. UK climate projections 2018 (UKCP18)were bias-corrected using three techniques: correcting for mean bias (shift or SH), variability (bias-correction or BC) and extreme values (quantile mapping or QM). These were applied in the health impact assessment, alongside consideration of population ageing and growth to estimate future temperature-related mortality. FINDINGS: In the absence of adaptation and assuming a high-end emissions scenario (RCP8.5), annual UK temperature-related mortality is projected to increase, with substantial differences in raw vs. calibrated projections for heat-related mortality, but smaller differences for cold-related mortality. The BC approach gave an estimated 29 deaths per 100,000 in the 2070s, compared with 50 per 100,000 using uncorrected future temperatures. We also found population ageing may exert a bigger impact on future mortality totals than the impact from future increases in temperature alone. Estimating future health burdens associated with heat and cold is an important step towards equipping decision-makers to deliver suitable care to the changing population. Correcting inherent biases in temperature projections can improve the accuracy of projected health burdens to support health protection measures and long-term resilience planning.

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.

Changes in population susceptibility to heat and cold over time: assessing adaptation to climate change.

BACKGROUND: In the context of a warming climate and increasing urbanisation (with the associated urban heat island effect), interest in understanding temperature related health effects is growing. Previous reviews have examined how the temperature-mortality relationship varies by geographical location. There have been no reviews examining the empirical evidence for changes in population susceptibility to the effects of heat and/or cold over time. The objective of this paper is to review studies which have specifically examined variations in temperature related mortality risks over the 20(th) and 21(st) centuries and determine whether population adaptation to heat and/or cold has occurred. METHODS: We searched five electronic databases combining search terms for three main concepts: temperature, health outcomes and changes in vulnerability or adaptation. Studies included were those which quantified the risk of heat related mortality with changing ambient temperature in a specific location over time, or those which compared mortality outcomes between two different extreme temperature events (heatwaves) in one location. RESULTS: The electronic searches returned 9183 titles and abstracts, of which eleven studies examining the effects of ambient temperature over time were included and six studies comparing the effect of different heatwaves at discrete time points were included. Of the eleven papers that quantified the risk of, or absolute heat related mortality over time, ten found a decrease in susceptibility over time of which five found the decrease to be significant. The magnitude of the decrease varied by location. Only two studies attempted to quantitatively attribute changes in susceptibility to specific adaptive measures and found no significant association between the risk of heat related mortality and air conditioning prevalence within or between cities over time. Four of the six papers examining effects of heatwaves found a decrease in expected mortality in later years. Five studies examined the risk of cold. In contrast to the changes in heat related mortality observed, only one found a significant decrease in cold related mortality in later time periods. CONCLUSIONS: There is evidence that across a number of different settings, population susceptibility to heat and heatwaves has been decreasing. These changes in heat related susceptibility have important implications for health impact assessments of future heat related risk. A similar decrease in cold related mortality was not shown. Adaptation to heat has implications for future planning, particularly in urban areas, with anticipated increases in temperature due to climate change.

Attribution of mortality to the urban heat island during heatwaves in the West Midlands, UK.

BACKGROUND: The Urban Heat Island (UHI) effect describes the phenomenon whereby cities are generally warmer than surrounding rural areas. Traditionally, temperature monitoring sites are placed outside of city centres, which means that point measurements do not always reflect the true air temperature of urban centres, and estimates of health impacts based on such data may under-estimate the impact of heat on public health. Climate change is likely to exacerbate heatwaves in future, but because climate projections do not usually include the UHI, health impacts may be further underestimated. These factors motivate a two-dimensional analysis of population weighted temperature across an urban area, for heat related health impact assessments, since populations are typically densest in urban centres, where ambient temperatures are highest and the UHI is most pronounced. We investigate the sensitivity of health impact estimates to the use of population weighting and the inclusion of urban temperatures in exposure data. METHODS: We quantify the attribution of the UHI to heat related mortality in the West Midlands during the heatwave of August 2003 by comparing health impacts based on two modelled temperature simulations. The first simulation is based on detailed urban land use information and captures the extent of the UHI, whereas in the second simulation, urban land surfaces have been replaced by rural types. RESULTS AND CONCLUSIONS: The results suggest that the UHI contributed around 50 % of the total heat-related mortality during the 2003 heatwave in the West Midlands. We also find that taking a geographical, rather than population-weighted, mean of temperature across the regions under-estimates the population exposure to temperatures by around 1 °C, roughly equivalent to a 20 % underestimation in mortality. We compare the mortality contribution of the UHI to impacts expected from a range of projected temperatures based on the UKCP09 Climate Projections. For a medium emissions scenario, a typical heatwave in 2080 could be responsible for an increase in mortality of around 3 times the rate in 2003 (278 vs. 90 deaths) when including changes in population, population weighting and the UHI effect in the West Midlands, and assuming no change in population adaptation to heat in future.

Health and climate related ecosystem services provided by street trees in the urban environment.

Urban tree planting initiatives are being actively promoted as a planning tool to enable urban areas to adapt to and mitigate against climate change, enhance urban sustainability and improve human health and well-being. However, opportunities for creating new areas of green space within cities are often limited and tree planting initiatives may be constrained to kerbside locations. At this scale, the net impact of trees on human health and the local environment is less clear, and generalised approaches for evaluating their impact are not well developed.In this review, we use an urban ecosystems services framework to evaluate the direct, and locally-generated, ecosystems services and disservices provided by street trees. We focus our review on the services of major importance to human health and well-being which include 'climate regulation', 'air quality regulation' and 'aesthetics and cultural services'. These are themes that are commonly used to justify new street tree or street tree retention initiatives. We argue that current scientific understanding of the impact of street trees on human health and the urban environment has been limited by predominantly regional-scale reductionist approaches which consider vegetation generally and/or single out individual services or impacts without considering the wider synergistic impacts of street trees on urban ecosystems. This can lead planners and policymakers towards decision making based on single parameter optimisation strategies which may be problematic when a single intervention offers different outcomes and has multiple effects and potential trade-offs in different places.We suggest that a holistic approach is required to evaluate the services and disservices provided by street trees at different scales. We provide information to guide decision makers and planners in their attempts to evaluate the value of vegetation in their local setting. We show that by ensuring that the specific aim of the intervention, the scale of the desired biophysical effect and an awareness of a range of impacts guide the choice of i) tree species, ii) location and iii) density of tree placement, street trees can be an important tool for urban planners and designers in developing resilient and resourceful cities in an era of climatic change.

Unequal distributions of crowdsourced weather data in England and Wales.

Personal weather stations (PWS) can provide useful data on urban climates by densifying the number of weather measurements across major cities. They do so at a lower cost than official weather stations by national meteorological services. Despite the increasing use of PWS data, little attention has yet been paid to the underlying socio-economic and environmental inequalities in PWS coverage. Using social deprivation, demographic, and environmental indicators in England and Wales, we characterize existing inequalities in the current coverage of PWS. We find that there are fewer PWS in more deprived areas which also observe higher proportions of ethnic minorities, lower vegetation coverage, higher building height and building surface fraction, and lower proportions of inhabitants under 65 years old. This implies that data on urban climate may be less reliable or more uncertain in particular areas, which may limit the potential for climate adaptation and empowerment in those communities.

The potential of urban trees to reduce heat-related mortality in London.

Increasing temperatures and more frequent heatwave events pose threats to population health, particularly in urban environments due to the urban heat island (UHI) effect. Greening, in particular planting trees, is widely discussed as a means of reducing heat exposure and associated mortality in cities. This study aims to use data from personal weather stations (PWS) across the Greater London Authority to understand how urban temperatures vary according to tree canopy coverage and estimate the heat-health impacts of London's urban trees. Data from Netatmo PWS from 2015-2022 were cleaned, combined with official Met Office temperatures, and spatially linked to tree canopy coverage and built environment data. A generalized additive model was used to predict daily average urban temperatures under different tree canopy coverage scenarios for historical and projected future summers, and subsequent health impacts estimated. Results show areas of London with higher canopy coverage have lower urban temperatures, with average maximum daytime temperatures 0.8 °C and minimum temperatures 2.0 °C lower in the top decile versus bottom decile canopy coverage during the 2022 heatwaves. We estimate that London's urban forest helped avoid 153 heat attributable deaths from 2015-2022 (including 16 excess deaths during the 2022 heatwaves), representing around 16% of UHI-related mortality. Increasing tree coverage 10% in-line with the London strategy would have reduced UHI-related mortality by a further 10%, while a maximal tree coverage would have reduced it 55%. By 2061-2080, under RCP8.5, we estimate that London's current tree planting strategy can help avoid an additional 23 heat-attributable deaths a year, with maximal coverage increasing this to 131. Substantial benefits would also be seen for carbon storage and sequestration. Results of this study support increasing urban tree coverage as part of a wider public health effort to mitigate high urban temperatures.

Valuing the health benefits of nature-based recreational physical activity in England.

Physical activity (PA) reduces the risk of several non-communicable diseases (NCDs). Natural environments support recreational PA. Using data including a representative cross-sectional survey of the English population, we estimated the annual value of nature-based PA conducted in England in 2019 in terms of avoided healthcare and societal costs of disease. Population-representative data from the Monitor of Engagement with the Natural Environment (MENE) survey (n = 47,580; representing 44,386,756) were used to estimate the weekly volume of nature-based recreational PA by adults in England in 2019. We used epidemiological dose-response data to calculate incident cases of six NCDs (ischaemic heart disease (IHD), ischaemic stroke (IS), type 2 diabetes (T2D), colon cancer (CC), breast cancer (BC) and major depressive disorder (MDD)) prevented through nature-based PA, and estimated associated savings using published costs of healthcare, informal care and productivity losses. We investigated additional savings resulting from hypothetical increases in: (a) visitor PA and (b) visitor numbers. In 2019, 22million adults > 16 years of age in England visited natural environments at least weekly. At reported volumes of nature-based PA, we estimated that 550 cases of IHD, 168 cases of IS, 1,410 cases of T2D, 41 cases of CC, 37 cases of BC and 10,552 cases of MDD were prevented, creating annual savings of £108.7million (95 % uncertainty interval: £70.3million; £150.3million). Nature-based recreational PA in England results in reduced burden of disease and considerable annual savings through prevention of priority NCDs. Strategies that increase nature-based PA could lead to further reductions in the societal burden of NCDs.

Commonly used indices disagree about the effect of moisture on heat stress.

Irrigation and urban greening can mitigate extreme temperatures and reduce adverse health impacts from heat. However, some recent studies suggest these interventions could actually exacerbate heat stress by increasing humidity. These studies use different heat stress indices (HSIs), hindering intercomparisons of the relative roles of temperature and humidity. Our method uses calculus of variations to compare the sensitivity of HSIs to temperature and humidity, independent of HSI units. We explain the properties of different HSIs and identify conditions under which they disagree. We highlight recent studies where the use of different HSIs could have led to opposite conclusions. Our findings have significant implications for the evaluation of irrigation and urban greening as adaptive responses to overheating and climate adaptation measures in general. We urge researchers to be critical in their choice of HSIs, especially in relation to health outcomes; our method provides a useful tool for making informed comparisons.

The contribution of demographic changes to future heat-related health burdens under climate change scenarios.

Anthropogenic climate change will have a detrimental impact on global health, including the direct impact of higher ambient temperatures. Existing projections of heat-related health outcomes in a changing climate often consider increasing ambient temperatures alone. Population growth and structure has been identified as a key source of uncertainty in future projections. Age acts as a modifier of heat risk, with heat-risk generally increasing in older age-groups. In many countries the population is ageing as lower birth rates and increasing life expectancy alter the population structure. Preparing for an older population, in particular in the context of a warmer climate should therefore be a priority in public health research and policy. We assess the level of inclusion of population growth and demographic changes in research projecting exposure to heat and heat-related health outcomes. To assess the level of inclusion of population changes in the literature, keyword searches of two databases were implemented, followed by reference and citation scans to identify any missed papers. Relevant papers, those including a projection of the heat health burden under climate change, were then checked for inclusion of population scenarios. Where sensitivity to population change was studied the impact of this on projections was extracted. Our analysis suggests that projecting the heat health burden is a growing area of research, however, some areas remain understudied including Africa and the Middle East and morbidity is rarely explored with most studies focusing on mortality. Of the studies pairing projections of population and climate, specifically SSPs and RCPs, many used pairing considered to be unfeasible. We find that not including any projected changes in population or demographics leads to underestimation of health burdens of on average 64 %. Inclusion of population changes increased the heat health burden across all but two studies.

Future impacts of O3 on respiratory hospital admission in the UK from current emissions policies.

Exposure to ambient ozone (O3) O3 is associated with impacts on human health. O3 is a secondary pollutant whose concentrations are determined inter alia by emissions of precursors such as oxides of nitrogen (NOx) and volatile organic compounds (VOCs), and thus future health burdens depend on policies relating to climate and air quality. While emission controls are expected to reduce levels of PM2.5 and NO2 and their associated mortality burdens, for secondary pollutants like O3 the picture is less clear. Detailed assessments are necessary to provide quantitative estimates of future impacts to support decision-makers. We simulate future O3 across the UK using a high spatial resolution atmospheric chemistry model with current UK and European policy projections for 2030, 2040 and 2050, and use UK regional population-weighting and latest recommendations on health impact assessment to quantify respiratory emergency hospital admissions associated with short-term effects of O3. We estimate 60,488 admissions in 2018, increasing by 4.2%, 4.5% and 4.6% by 2030, 2040 and 2050 respectively (assuming a fixed population). Including future population growth, estimated emergency respiratory hospital admissions are 8.3%, 10.3% and 11.7% higher by 2030, 2040 and 2050 respectively. Increasing O3 concentrations in future are driven by reduced nitric oxide (NO) in urban areas due to reduced emissions, with increases in O3 mainly occurring in areas with lowest O3 concentrations currently. Meteorology influences episodes of O3 on a day-to-day basis, although a sensitivity study indicates that annual totals of hospital admissions are only slightly impacted by meteorological year. While reducing emissions results in overall benefits to population health (through reduced mortality due to long-term exposure to PM2.5 and NO2), due to the complex chemistry, as NO emissions reduce there are associated local increases in O3 close to population centres that may increase harms to health.

Impacts of emissions policies on future UK mortality burdens associated with air pollution.

Air pollution is the greatest environmental risk to public health. Future air pollution concentrations are primarily determined by precursor emissions, which are driven by environmental policies relating to climate and air pollution. Detailed health impact assessments (HIA) are necessary to provide quantitative estimates of the impacts of future air pollution to support decision-makers developing environmental policy and targets. In this study we use high spatial resolution atmospheric chemistry modelling to simulate future air pollution concentrations across the UK for 2030, 2040 and 2050 based on current UK and European policy projections. We combine UK regional population-weighted concentrations with the latest epidemiological relationships to quantify mortality associated with changes in PM2.5 and NO2 air pollution. Our HIA suggests that by 2050, population-weighted exposure to PM2.5 will reduce by 28% to 36%, and for NO2 by 35% to 49%, depending on region. The HIA shows that for present day (2018), annual mortality attributable to the effects of long-term exposure to PM2.5 and NO2 is in the range 26,287 - 42,442, and that mortality burdens in future will be substantially reduced, being lower by 31%, 35%, and 37% in 2030, 2040 and 2050 respectively (relative to 2018) assuming no population changes. Including population projections (increases in all regions for 30+ years age group) slightly offsets these health benefits, resulting in reductions of 25%, 27%, and 26% in mortality burdens for 2030, 2040, 2050 respectively. Significant reductions in future mortality burdens are estimated and, importantly for public health, the majority of benefits are achieved early on in the future timeline simulated, though further efforts are likely needed to reduce impacts of air pollution to health.

Spatially Explicit Correction of Simulated Urban Air Temperatures Using Crowdsourced Data.

Urban climate model evaluation often remains limited by a lack of trusted urban weather observations. The increasing density of personal weather sensors (PWSs) make them a potential rich source of data for urban climate studies that address the lack of representative urban weather observations. In our study, we demonstrate that carefully quality-checked PWS data not only improve urban climate models' evaluation but can also serve for bias correcting their output prior to any urban climate impact studies. After simulating near-surface air temperatures over London and south-east England during the hot summer of 2018 with the Weather Research and Forecasting (WRF) Model and its building Effect parameterization with the building energy model (BEP-BEM) activated, we evaluated the modeled temperatures against 402 urban PWSs and showcased a heterogeneous spatial distribution of the model's cool bias that was not captured using official weather stations only. This finding indicated a need for spatially explicit urban bias corrections of air temperatures, which we performed using an innovative method using machine learning to predict the models' biases in each urban grid cell. This bias-correction technique is the first to consider that modeled urban temperatures follow a nonlinear spatially heterogeneous bias that is decorrelated from urban fraction. Our results showed that the bias correction was beneficial to bias correct daily minimum, daily mean, and daily maximum temperatures in the cities. We recommend that urban climate modelers further investigate the use of quality-checked PWSs for model evaluation and derive a framework for bias correction of urban climate simulations that can serve urban climate impact studies.

Potential health impacts from sulphur dioxide and sulphate exposure in the UK resulting from an Icelandic effusive volcanic eruption.

Ash, gases and particles emitted from volcanic eruptions cause disruption to air transport, but also have negative impacts on respiratory and cardiovascular health. Exposure to sulphur dioxide (SO2) and sulphate (SO4) aerosols increases the risk of mortality, and respiratory and cardiovascular hospital admissions. Ash and gases can be transported over large distances and are a potential public health risk. In 2014-15, the Bárðarbunga fissure eruption at Holuhraun, Iceland was associated with high emissions of SO2 and SO4, detected at UK monitoring stations. We estimated the potential impacts on the UK population from SO2 and SO4 associated with a hypothetical large fissure eruption in Iceland for mortality and emergency hospital admissions. To simulate the effects of different weather conditions, we used an ensemble of 80 runs from an atmospheric dispersion model to simulate SO2 and SO4 concentrations on a background of varying meteorology. We weighted the simulated exposure data by population, and quantified the potential health impacts that may result in the UK over a 6-week period following the start of an eruption. We found in the majority of cases, the expected number of deaths resulting from SO2 over a 6-week period total fewer than ~100 for each model run, and for SO4, in the majority of cases, the number totals fewer than ~200. However, the 6-week simulated period with the highest SO2 was associated with 313 deaths, and the period with the highest SO4 was associated with 826 deaths. The single 6-week period relating to the highest combined SO2 and SO4 was associated with 925 deaths. Over a 5-month extended exposure period, upper estimates are for 3350 deaths, 4030 emergency cardiovascular and 6493 emergency respiratory hospitalizations. These figures represent a worst-case scenario and can inform health protection planning for effusive volcanic eruptions which may affect the UK in the future.

Comparing temperature-related mortality impacts of cool roofs in winter and summer in a highly urbanized European region for present and future climate.

Human health can be negatively impacted by hot or cold weather, which often exacerbates respiratory or cardiovascular conditions and increases the risk of mortality. Urban populations are at particular increased risk of effects from heat due to the Urban Heat Island (UHI) effect (higher urban temperatures compared with rural ones). This has led to extensive investigation of the summertime UHI, its impacts on health, and also the consideration of interventions such as reflective 'cool' roofs to help reduce summertime overheating effects. However, interventions aimed at limiting summer heat are rarely evaluated for their effects in wintertime, and thus their overall annual net impact on temperature-related health effects are poorly understood. In this study we use a regional weather model to simulate the winter 2009/10 period for an urbanized region of the UK (Birmingham and the West Midlands), and use a health impact assessment to estimate the impact of reflective 'cool' roofs (an intervention usually aimed at reducing the UHI in summer) on cold-related mortality in winter. Cool roofs have been shown to be effective at reducing maximum temperatures during summertime. In contrast to the summer, we find that cool roofs have a minimal effect on ambient air temperatures in winter. Although the UHI in summertime can increase heat-related mortality, the wintertime UHI can have benefits to health, through avoided cold-related mortality. Our results highlight the potential annual net health benefits of implementing cool roofs to reduce temperature-related mortality in summer, without reducing the protective UHI effect in winter. Further, we suggest that benefits of cool roofs may increase in future, with a doubling of the number of heat-related deaths avoided by the 2080s (RCP8.5) compared to summer 2006, and with insignificant changes in the impact of cool-roofs on cold-related mortality. These results further support reflective 'cool' roof implementation strategies as effective interventions to protect health, both today and in future.

The winter urban heat island: Impacts on cold-related mortality in a highly urbanized European region for present and future climate.

Exposure to heat has a range of potential negative impacts on human health; hot weather may exacerbate cardiovascular and respiratory illness or lead to heat stroke and death. Urban populations are at increased risk due to the Urban Heat Island (UHI) effect (higher urban temperatures compared with rural ones). This has led to extensive investigation of the summertime UHI and its effects, whereas far less research focuses on the wintertime UHI. Exposure to low temperature also leads to a range of illnesses, and in fact, in the UK, annual cold-related mortality outweighs heat-related mortality. It is not clearly understood to what extent the wintertime UHI may protect against cold related mortality. In this study we quantify the UHI intensity in wintertime for a heavily urbanized UK region (West Midlands, including Birmingham) using a regional weather model, and for the first time, use a health impact assessment (HIA) to estimate the associated impact on cold-related mortality. We show that the population-weighted mean winter UHI intensity was +2.3 °C in Birmingham city center, and comparable with that of summer. Our results suggest a potential protective effect of the wintertime UHI, equivalent to 266 cold-related deaths avoided (~15% of total cold-related mortality over ~11 weeks). When including the impacts of climate change, our results suggest that the number of heat-related deaths associated with the summer UHI will increase from 96 (in 2006) to 221 in the 2080s, based on the RCP8.5 emissions pathway. The protective effect of the wintertime UHI is projected to increase only slightly from 266 cold-related deaths avoided in 2009 to 280 avoided in the 2080s. The different effects of the UHI in winter and summer should be considered when assessing interventions in the built environment for reducing summer urban heat, and our results suggest that the future burden of temperature-related mortality associated with the UHI is likely to increase in summer relative to winter.

Covid-19 mobility restrictions: impacts on urban air quality and health.

In 2020, Covid-19-related mobility restrictions resulted in the most extensive human-made air-quality changes ever recorded. The changes in mobility are quantified in terms of outdoor air pollution (concentrations of PM2.5 and NO2) and the associated health impacts in four UK cities (Greater London, Cardiff, Edinburgh and Belfast). After applying a weather-corrected machine learning (ML) technique, all four cities show NO2 and PM2.5 concentration anomalies in 2020 when compared with the ML-predicted values for that year. The NO2 anomalies are -21% for Greater London, -19% for Cardiff, -27% for Belfast and -41% for Edinburgh. The PM2.5 anomalies are 7% for Greater London, -1% for Cardiff, -15% for Edinburgh, -14% for Belfast. All the negative anomalies, which indicate air pollution at a lower level than expected from the weather conditions, are attributable to the mobility restrictions imposed by the Covid-19 lockdowns. Spearman rank-order correlations show a significant correlation between the lowering of NO2 levels and reduction in public transport (p < 0.05) and driving (p < 0.05), which is associated with a decline in NO2-attributable mortality. These positive effects of the mobility restrictions on public health can be used to evaluate policies for improved outdoor air quality. POLICY RELEVANCE: Finding the means to curb air pollution is very important for public health. Empirical evidence at a city scale reveals significant correlations between the reduction in vehicular transport and in ambient NO2 concentrations. The results provide justification for city-level initiatives to reduce vehicular traffic. Well-designed and effective policy interventions (e.g. the promotion of walking and cycling, remote working, local availability of services) can substantially reduce long-term air pollution and have positive health impacts.

Climate change projections for sustainable and healthy cities.

The ambition to develop sustainable and healthy cities requires city-specific policy and practice founded on a multidisciplinary evidence base, including projections of human-induced climate change. A cascade of climate models of increasing complexity and resolution is reviewed, which provides the basis for constructing climate projections-from global climate models with a typical horizontal resolution of a few hundred kilometres, through regional climate models at 12-50 km to convection-permitting models at 1 km resolution that permit the representation of urban induced climates. Different approaches to modelling the urban heat island (UHI) are also reviewed-focusing on how climate model outputs can be adjusted and coupled with urban canopy models to better represent UHI intensity, its impacts and variability. The latter can be due to changes induced by urbanisation or to climate change itself. City interventions such as greater use of green infrastructure also have an effect on the UHI and can help to reduce adverse health impacts such as heat stress and the mortality associated with increasing heat. Examples for the Complex Urban Systems for Sustainability and Health (CUSSH) partner cities of London, Rennes, Kisumu, Nairobi, Beijing and Ningbo illustrate how cities could potentially make use of more detailed models and projections to develop and evaluate policies and practices targeted at their specific environmental and health priorities. PRACTICE RELEVANCE: Large-scale climate projections for the coming decades show robust trends in rising air temperatures, including more warm days and nights, and longer/more intense warm spells and heatwaves. This paper describes how more complex and higher resolution regional climate and urban canopy models can be combined with the aim of better understanding and quantifying how these larger scale patterns of change may be modified at the city or finer scale. These modifications may arise due to urbanisation and effects such as the UHI, as well as city interventions such as the greater use of grey and green infrastructures.There is potential danger in generalising from one city to another-under certain conditions some cities may experience an urban cool island, or little future intensification of the UHI, for example. City-specific, tailored climate projections combined with tailored health impact models contribute to an evidence base that supports built environment professionals, urban planners and policymakers to ensure designs for buildings and urban areas are fit for future climates.