Air pollution exposure in early life may be associated with an increased risk of bronchiolitis in children, but evidence for long-term exposures (over weeks or months) is limited. We estimated associations between fine particulate matter (PM2.5) and nitrogen dioxide (NO2) exposure during pregnancy and in the first year of life and bronchiolitis-related hospital admissions in a London birth cohort. We used a national birth cohort to identify London-resident mothers whose children were born in London from 2010 to 2013 and extracted information from birth and death registrations and maternal and child longitudinal Hospital Episode Statistics. We linked modeled PM2.5 and NO2 data to residential postcode histories during pregnancy and infancy. We applied a landmark approach with Cox proportional hazard models, adjusted for sociodemographic characteristics and housing energy efficiency, to estimate associations between time-varying monthly PM2.5 or NO2 exposure and first bronchiolitis admission. Among 415,311 children, we found inconclusive evidence overall, with suggestive signals of increased risk associated with pregnancy and exposures in the final month of infancy to PM2.5 and NO2 and time to first bronchiolitis-related hospital admission. There were modest increases in risk in the first month after birth, corresponding to prenatal exposures, for PM2.5 (adjusted Hazard ratio [HRa] = 1.07, 95% confidence interval [CI]: 0.70, 1.61 per 5 ug/m(3)) and NO2 (HRa = 1.15, 95% CI: 0.98, 1.35 per 10 ug/m(3)). We found a similar estimated increased risk in the last month of follow-up (PM2.5 HRa = 1.12, 95% CI: 0.94, 1.34; NO2 HRa = 1.31, 95% CI: 1.00, 1.71), corresponding to late infancy exposures. These findings highlight the uncertainty about critical windows of susceptibility during infancy. Future studies should examine the association between air pollution and bronchiolitis in emergency departments and primary care settings.

Exposure to particles with a diameter smaller than 2.5 mu m (PM2.5) poses a threat to human health. Monitoring of PM2.5 often relies on sparse networks of standardized instruments, but in many locations, official networks are supplemented by networks of low-cost PM sensors operated by members of the community. This study aims to evaluate the open low-cost PM2.5 sensor networks across Europe by analysing data from Sensor.Community and OpenAQ, assessing completeness and reliability as well as growth, coverage, locations, and correlation in comparison with official measurements. As of 2023, there were 8735 low-cost PM2.5 sensors in Europe publicly sharing data on these networks, or more than three times the number of official stations. Results indicate these sensors are primarily in residential urban areas with higher population densities, higher income levels, and average levels of ambient PM2.5. The analysis shows that although official measurement stations provide more consistent coverage across Europe, in many cities the low-cost PM2.5 sensor network is denser and can potentially complement the official network and provide insights for authorities, researchers and citizens. The rapid growth of openly available low-cost PM2.5 sensor data presents a growing opportunity to enhance the spatial coverage of monitored PM2.5 exposure estimates and understanding of local PM2.5 sources, both indoors and outdoors. However, challenges exist with inconsistent methods for data quality control, absent metadata, and sensor placement and location biases which need to be addressed for example through harmonized measurement protocols, collecting more complete metadata and with advanced data cleaning and processing methods.

In Europe, remote work is increasing, driven by technological advances and behavioural shifts. Working from home may potentially reduce commuting-related greenhouse gas (GHG) emissions, but can also remove incidental physical activity during commutes. Alternative work locations, such as co-working spaces, are a third option, with potential impacts on travel-related emissions and physical activity. This paper examines commuting behaviours of remote workers in Finland to their employer and alternative work locations, assessing differences in distances, modes and active travel levels; characterising different types of remote workers; and mapping how co-working spaces can support 15-min cities in the Helsinki Metropolitan Area. A survey collected remote worker socio-demographic characteristics, and the mode and frequency of travel between home and work locations. Travel time, distance, and emissions were estimated and compared between work locations, and used to develop remote worker typologies using clustering analysis, while spatial analysis was used to locate potential future co-working spaces to leverage potential benefits. Results show those working from designated alternative workspaces had lower single-trip emissions and were more likely to use active travel than those travelling to employer offices. However, long-distance travel for remote work at cottages or holiday homes resulted in high emission rebound effects. POLICY RELEVANCE Remote working has the potential to reduce commuting-related GHG emissions, but may also increase sedentary behaviour as workers stay at home, and often with poor ergonomics. Alternative third workspaces such as co-working spaces appear to offer a compromise, with shorter commuting distances reducing potential emissions and increasing the likelihood of using active travel, as well as better ergonomic environments. However, remote working from third locations may also facilitate rebound travel behaviours, where individuals travel to distant remote work locations. Policies supporting local co-working spaces, and their strategic placement, may offer a potential remote work compromise which encourages more physical activity. Through understanding the types and travel behaviours of people who work remotely, it may be possible to strategically locate co-working spaces to encourage low emission and active commuting and help support the 15-min city concept by shifting work locations.

The widespread adoption of remote work, accelerated by the COVID-19 pandemic, has renewed interest in its environmental and health impacts as organisations reconsider office-based work. We adopt a systems perspective, combining causal loop modelling and network centrality analyses to examine interdependencies between remote work, transport, building energy use, and health. With this, we identify leverage points and impact pathways which affect emissions and health outcomes.In terms of carbon emissions, commuting reductions can be offset by increased non-commuting travel and residential energy use. Office space management, which is involved in several feedback loops, emerges as a critical determinant of whether energy savings in buildings are realised. Health impacts are similarly mixed and vary across behavioural and socio-demographic contexts. Home-based work is associated with adverse physical-health outcomes linked to reduced activity and poor ergonomics, emphasising the role of home work environments. Overall, the environmental and health effects of remote work are highly context-dependent and unlikely to deliver substantial benefits without complementary measures. Particularly, active travel promotion and flexible office space and energy management offer strong opportunities for environmental and health co-benefits.

BACKGROUND:Cold weather remains a serious health threat in the UK and elsewhere, particularly for older adults. The Winter Fuel Payment has been a key government strategy to mitigate health risks linked to cold homes in the UK, but recent policy shifts have raised questions about whether income-based eligibility criteria effectively identify those most at risk. METHODS:We analysed cold-related mortality in adults aged ≥75 across 324 local authority districts in England (2007-2019) using distributed lag non-linear models in a spatial Bayesian framework. Multivariate meta-regression was used to evaluate modification of cold effects by deprivation, income-based pension credit uptake, home energy efficiency and fuel poverty. RESULTS:Areas in the highest quartile of fuel poverty had significantly greater cold-related mortality risk than those in the lowest quartile, with a 15.3% versus 13.1% increase in mortality risk at the first compared with the 50th percentile of wintertime temperature, ie, an absolute difference of 2.2% (p<0.001). This effect was stronger than the corresponding differences for energy efficiency (1.7%, p=0.04), income as indicated by pension credit uptake (0.6%, p=0.39) and deprivation-based measures, for which differences were minimal. Overall, an estimated 17% of cold-related deaths among people aged ≥75 were attributable to fuel poverty. CONCLUSION:Fuel poverty, an indicator designed to capture both low-income and housing energy efficiency, is a stronger predictor of cold-related mortality than income (as indicated by pension credit update) or deprivation-based indicators alone. Winter energy support schemes should consider fuel poverty metrics in their targeting to more effectively reduce health risks associated with cold homes and improve equity.

Background:Metro systems are essential for urban mobility but often expose commuters to particulate matter (PM) at levels far above roadside air. The London Underground (LU), the world's oldest metro, supports ∼4 million daily journeys and has elevated PM2.5 concentrations dominated by iron-rich particles from mechanical abrasion. These exposures raise concerns about long-term health effects. Methods:Using the Office for National Statistics Longitudinal Study (ONS-LS), we analysed two retrospective cohorts of economically active adults (≥16 years) living and working in London and recorded in the 1991, 2001, or 2011 Censuses. Cohort 1 (n = 7,343) compared LU commuters with above-ground rail users. Cohort 2 (n = 4,094) examined dose-response patterns between externally linked cumulative LU PM2.5 exposure and health outcomes. Exposure estimates combined Transport for London data, PM2.5 measurements, and geospatial modelling. Outcomes were all-cause mortality (1991 to 2017) and cancer incidence (1991 to 2015). Analyses used inverse probability weighting and the parametric g-formula. Results:Most LU commuters were estimated to encounter hourly PM2.5 levels >100 μg/m3. LU users were 1.93% (95% CI: 0.58-3.66) less likely to survive the follow-up period than above-ground rail users, while cancer risk differences were negligible. No dose-response pattern emerged, and a hypothetical 50% PM2.5 reduction produced minimal survival change. Conclusions:LU commuters experience PM2.5 concentrations roughly 8-10 times higher than above-ground levels. Mortality risk appeared slightly elevated, though uncertainty remains. Findings highlight the need for better exposure assessment and further research on metro-related PM.

Abstract Background We examined whether two key housing quality indicators, energy efficiency and household overcrowding, were associated with lower respiratory tract infection (LRTI) hospital admissions in infants. Methods We used a cohort of all singleton births in Scotland 2010-2012, created through linked vital statistics and health data. LRTI admissions were characterised in hospital records. Overcrowding (defined using the national room standard) and median postcode-level energy efficiency were defined using maternal Census and postcode-level Energy Performance Certificate data linked to the cohort, respectively. We used logistic regression to model the odds of at least one infant LRTI admission. Results The cohort included 136,123 infants of whom 4.0% had at least one LRTI admission. Overcrowding was more common among infants of younger mothers and those in rented housing. Energy efficiency was lower among infants of older mothers, living in owner occupied homes, in less deprived areas. Compared with infants living in homes with excess rooms (under-occupied housing), those whose homes were below, or met, the minimum room standard had higher odds of LRTI admission (adjusted odds ratio 1.07, 95% CI 0.98–1.17; 1.10, 95% CI 1.03–1.17, respectively). Postcode-level energy efficiency was not associated with LRTI admission odds. Conclusion Overcrowding was more common in socioeconomically disadvantaged households and associated with increased risk of LRTI admission in infancy. Lower energy efficiency was associated with factors commonly linked to socioeconomic advantage and was not associated with LRTI admissions. Improving access to housing with adequate living space may reduce the burden of LRTIs in early life. Key messages xxxxx

Aim To create longitudinal postcode history datasets that allocate mothers to one postcode for each week of pregnancy and children to one postcode for each week of infancy for a study of air pollution and respiratory infections in infants. Datasets We used linked birth registrations and NHS birth notifications for all children born in London between 2010 and 2014, which constituted the spine for the Air Pollution, housing and respiratory tract Infections in Children: National Birth Cohort Study (PICNIC) study. The birth data were linked by NHS England to the Personal Demographics Service (PDS) in order to derive maternal and child postcode histories for each week of pregnancy and infancy. Challenges While the research team had extensive experience working with administrative data, including birth registrations and notifications, the postcode history data was a new resource and lacked meta-data, papers or reports from previous users. A substantial number of records were missing a move-in date, or both a move-in date and postcode, adding complexities when ascertaining an address history for study participants. Further, we encountered instances of incorrectly recorded postcodes and implausible numbers of postcodes recorded in a week. Lessons learned One half of children in this London-based cohort moved during infancy, and one third of their mothers moved during pregnancy. This highlights the importance of taking into account changes in residential address in studies examining the association between environmental exposures and health outcomes. Cleaned and validated longitudinal national address records are crucial for environmental health studies. However, they are also resource intensive, with implications for researchers and research funders.

BACKGROUND:High ambient temperatures lead to increased mortality, especially in older adults. Climate change will increase the frequency and severity of heatwaves globally. Most of the UK population lives in urban areas, which often have higher temperatures than rural areas (the urban heat island [UHI] effect) and higher rates of heat-related mortality. We estimated the mortality burden in terms of attributable mortality and years of life lost (YLLs), and social costs attributed to the UHI effect in summer 2018 in Greater London. METHODS:We estimated the UHI effect using advanced urban climate modelling. We applied a quantitative health impact assessment to estimate mortality and YLLs attributable to high air temperature. We estimated social costs using value of statistical life (VSL) and value of statistical life-years (VOLY) methods. FINDINGS:We attribute 785 (95% CI 655-919) deaths in summer 2018 in Greater London to high air temperature. Half of these (399 [350-446]) are attributable to the UHI effect, or approximately 5·0 (4·1-5·9) thousand YLLs. Social costs of the summer UHI effect due to mortality are estimated at £987 million (866 million-1·10 billion) using VSL or £453 million (367-533 million) using VOLY (2023 prices). INTERPRETATION:Monetised costs attributed to the UHI effect remain high using either VSL or VOLY approaches. The findings demonstrate the seriousness of heat as a public health risk, set a scale at which society may be willing to pay for urban heat mitigation, and give tangible support for large-scale urban heat mitigation and adaptation policies. FUNDING:Wellcome Trust.

Urban heat islands (UHI) modify building heating and cooling loads and public exposure to non-optimal temperatures, topics of increasing importance given climate change. This study uses personal weather stations (PWS) to investigate urban temperatures in Helsinki, Espoo, Vantaa and Tampere, Finland. Data from PWS within 50 km of municipal boundaries were acquired, cleaned and spatially linked to socio-economic, land-use and local climate zone (LCZ) classifications. Analyses evaluated for PWS location bias, including distributions across socio-economic and land-use categories. Temperatures were examined across LCZs and the urban influence on temperature, heating degree-days (HDD), cooling degree-days (CDD) and number of extreme hot or cold days calculated. Results indicate more PWS in residential open low-rise areas, but no consistent biases across incomes or ages. UHI intensities were, on average, 1.2 degrees C (interquartile range (IQR) = 0.6-1.2 degrees C) for Helsinki, 0.8 degrees C (IQR = 0.4-1.2 degrees C) for Espoo, 0.7 degrees C (IQR = 0.4-1.1 degrees C) for Vantaa and 0.5 degrees C (IQR = 0.1-0.8 degrees C) for Tampere, with differences greatest during spring and summer. Urban PWS have 112-281 fewer HDD and 30-50 more CDD than rural equivalents, suggesting a net benefit of the UHI for building energy consumption. Urban intensification of extreme heat was greater than extreme cold reduction.

Introduction:Early-life acute lower respiratory tract infections (LRTIs) have been associated with subsequent wheezing, asthma and mortality. Despite infants and young children spending much of their time at home, the association of housing circumstances, including housing ownership status, on acute LRTI hospital admissions is not well explored. Objective:To assess the association between housing tenure and the odds of hospital admission for acute LRTIs in children aged <2 years in Scotland. Methods:Scottish birth records were linked to maternal census data (2001 and 2011) to construct two birth cohorts: cohort 1 (C1; born 2000-2002) and cohort 2 (C2; 2010-2012). Linkage to hospital records provided information on acute LRTI admissions. Using multivariable logistic regression models, we estimated the association of housing tenure with the odds of ≥1 hospital admission for LRTI before the second birthday with adjustment for area of residence (urban/rural), maternal highest qualification level and maternal age. Results:There were 14 833 LRTI admissions in 12 527 children across both cohorts. 4.0% and 5.3% children in C1 and C2, respectively, had ≥1 LRTI admission. Compared with living in owned housing, the odds of LRTI admission were higher in children living in social rented housing (C1: OR 1.40, 95% CI 1.31 to 1.49; C2: 1.23, 1.16 to 1.31), private rented (C1: 1.24, 1.11 to 1.39; C2: 1.14, 1.06 to 1.21) and rent-free housing (C1: 1.53, 1.35 to 1.74; C2: 1.04, 0.80 to 1.36). Conclusion:Children living in rented housing had higher odds of early-childhood LRTI admission compared with those living in owned housing in Scotland. Further linkage to residential-level data could inform the design of LRTI prevention policies.

Energy emissions mitigation policies bring co-benefits for health and opportunities to drive sustainable development for rapidly transitioning economies in sub-Saharan Africa. Developing methods of quantifying these co-benefits in differing demographic groups is an area of interest for policymakers to support resource allocation efforts. Using synthetic populations of three municipalities in Kenya, we assessed the impact of policies to promote the use of clean cooking fuels on exposure to ambient and household air pollution and associated age- and gender-specific mortality. Exposure to household PM _2.5 for a range of cooking fuel types and informal and formal housing archetypes were simulated using the building physics software, EnergyPlus. A combined household and ambient PM _2.5 exposure was calculated for each individual by weighting PM _2.5 concentrations using national demographic-specific time-activity estimates. Exposure-response functions were applied to quantify the burden of mortality for six associated health outcomes. To compare the health impacts of energy policy implementation, a two-stage policy was tested through medium and long-term transitions towards successively cleaner cooking fuels prioritising liquid petroleum gas and ethanol. The resulting difference in mortality consecutively declined through the two-stage policy transition with the greatest impact after the first transition and an incremental but smaller impact after the second. The overall difference in mortality burden averted per 100 000 population relative to the baseline scenario was largest in Kisumu (males: 39.23; females: 18.09), with smaller decreases in Mombasa (males: 5.71; females: 3.03) and Nairobi (males: 1.82; females: 1.08). A sensitivity analysis showed reductions in PM _2.5 exposure under the policy scenarios may be overestimated in the presence of fuel stacking practices, where households rely on multiple fuels and stoves. This model provides a proof-of-concept for the use of individual-level modelling methods to estimate demographic-specific health impacts from environmental exposures and quantitatively compare health co-benefits of household fuel emission mitigation policies.

Driven by human-caused greenhouse gas emissions, climate change is increasingly claiming lives and harming people's health worldwide. Mean annual temperatures exceeded 1.5 degrees C above those of pre-industrial times for the first time in 2024. Despite ever more urgent calls to tackle climate change, greenhouse gas emissions rose to record levels that same year. Climate change is increasingly destabilising the planetary systems and environmental conditions on which human life depends. Authored by 128 multidisciplinary experts worldwide, the 2025 report of the Lancet Countdown on health and climate change is the ninth-and most comprehensive-assessment of the links between climate change and health. The data in this report reveal that, as the health risks and impacts of climate change break concerning new records, progress is being reversed across key areas, further threatening health and survival. However, the evidence in this report also exposes important opportunities to accelerate action and prevent the most catastrophic impacts of climate change.

BACKGROUND:Particulate matter emissions from residential wood burning are rising in many countries. Long-term exposure to fine particulate matter is strongly linked with adverse health effects including cardiovascular and respiratory disease. Policymakers and scientists need accurate tools to identify residential wood burning hotspots. However, current methods rely on spatially-misaligned, out-of-date data sources, reducing their practical utility and portability to other contexts. Furthermore, the socio-economic characteristics of residential wood burning in high income countries are poorly understood. METHODS:We used open data from 26 million Energy Performance Certificates (EPCs) for properties in England and Wales from 2009-2025 to map the concentration and prevalence of wood burners within small areas. We evaluated our method against the UK national wood burning emissions inventory using national air pollution monitoring networks. We used novel open data linkages to characterise associations between area-level prevalence of wood burners and socio-economic factors including deprivation, ethnicity, and age. FINDINGS:We identified substantial spatial heterogeneity in the concentration of wood burners, with the highest concentrations in affluent urban areas. Our concentration metric was more strongly correlated with peaks in winter PM2.5 at urban monitoring sites than estimates from the UK national emissions inventory. Prevalence of wood burners was positively correlated with age and negatively correlated with measures of social deprivation. Prevalence of wood burners in EPCs has increased since 2009. CONCLUSIONS:EPCs are a valuable data source which policymakers can use to target local interventions or extend existing restrictions on solid fuel burning. Our method is transparent, up-to-date, and portable to other countries where similar EPC data is available. The relationship between social deprivation and prevalence of wood burning heat sources highlights important issues of environmental justice. Epidemiological analyses of wood smoke exposures and health should carefully account for the confounding effects of age, deprivation, and ethnicity.

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.

Population exposure to high temperatures poses health risks and increases mortality. 'Cool roofs' (high-albedo roofs) and rooftop photovoltaics (RPV) may reduce temperatures in urban areas. Here, using advanced urban climate modeling, we model impacts of these measures on air temperature and heat-related mortality in London during the record-breaking hot summer of 2018. We estimate changes in mean near-surface air temperature of -0.3 degrees C in the RPV scenario and -0.8 degrees C in the cool roof scenario. We find that the heat-related mortality in this period (estimated 655-920) could have been reduced by 96 (12%) by RPV, or 249 (32%) by cool roofs, in scenarios where all roofs have these measures. Monetized using value of statistical life, we estimate benefits for RPV and cool roofs of 237 pound M and 615 pound M, respectively. We estimate that up to 20 TWh of electrical energy would be generated in the full RPV scenario. We show that, for conditions such as in London June-August 2018, RPV or cool roofs may reduce near-surface air temperatures and associated heat-related mortality, with cool roofs having a larger effect.

As people in the UK spend 95% of their time indoors, buildings are an important modifier of exposure to both non-optimal temperatures and air pollution. High ambient temperature and high PM2.5 (particulate matter) concentrations often occur together in urban areas. Residential building types prone to overheating (e.g. purpose-built flats) are often also more common in urban areas. Together, this may lead to spatial and demographic inequalities in indoor exposure to heat and PM2.5 from outdoor sources. By combining building simulations (EnergyPlus), a spatially distributed description of the residential building stock—from publicly available Energy Performance Certificate (EPC) data, ambient temperature, PM2.5 data and area-level (40–250 households) socio-demographic data—we estimated these inequalities in exposure for the population of England and Wales. Maximum indoor temperature was higher in areas with larger ethnic minority and infant populations, and lower in areas with a higher proportion of people aged ≥ 65 years. Indoor concentrations of outdoor-source PM2.5 were higher in areas with larger ethnic minority and low-income populations. With rising inequality in England and Wales, housing and environmental conditions play an important role in contributing to health inequalities from social disadvantage. Policy relevance Differences in environmental exposures may partly explain inequalities in health outcomes. These differences are mediated by dwelling type and quality. Identifying the driving factors for differences in environmental exposures may allow for the development of interventions to address health inequalities more effectively. This study finds differences in indoor exposure across socio-demographic groups due to both location and housing. This could be of interest to national, regional and local authorities responsible for targeting building retrofit interventions across the housing stock.

Background: High ambient temperatures lead to increased mortality, especially in older adults. Climate change will increase the frequency and severity of heatwaves globally. Most of the UK population lives in urban areas, which often have higher temperatures (the urban heat island (UHI)) and higher rates of heat-related mortality. We estimated the mortality burden in terms of attributable mortality and years of life lost (YLL), and social costs attributed to the UHI in summer 2018 in London. Methods: The UHI was estimated using state-of-the-art urban climate modelling. A quantitative health impact assessment was applied to estimate mortality and YLL. Social costs were estimated using value of statistical life (VSL) and value of statistical life years (VOLY) methods. Findings: We attribute 780 deaths in 2018 summer in London to high temperature. Half (403) of deaths attributed to heat in this period are attributed to the UHI, and approximately 5.1 thousand YLL. Social costs of the UHI due to mortality are estimated at £456 million (using VOLY) or £996 million (using VSL) (2023 prices). Interpretation: Monetized costs attributed to the UHI remain high when using YLL and VOLY approaches. The findings demonstrate the seriousness of heat as a public health risk, set a scale at which society may be willing to pay for urban heat mitigation, and give tangible support for large scale urban heat mitigation and adaptation policies.