Higher air pollution exposure in early life is associated with worse health among older adults: A 72-year follow-up study from Scotland.

Air pollution increases the risk of mortality and morbidity. However, limited evidence exists on the very long-term associations between early life air pollution exposure and health, as well as on potential pathways. This study explored the relationship between fine particle (PM2.5) exposure at age 3 and limiting long-term illness (LLTI) at ages 55, 65 and 75 using data from the Scottish Longitudinal Study Birth Cohort 1936, a representative administrative cohort study. We found that early life PM2.5 exposure was associated with higher odds of LLTI in mid-to-late adulthood (OR = 1.10, 95% CI: 1.06, 1.14 per 10 µg m-3 increment) among the 2085 participants, with stronger associations among those growing up in disadvantaged families. Path analyses suggested that 15-21% of the association between early life PM2.5 concentrations and LLTI at age 65 (n = 1406) was mediated through childhood cognitive ability, educational qualifications, and adult social position. Future research should capitalise on linked administrative and health data, and explore causal mechanisms between environment and specific health conditions across the life course.

Early life PM2.5 exposure, childhood cognitive ability and mortality between age 11 and 86: A record-linkage life-course study from Scotland.

BACKGROUND: Living in areas with high air pollution concentrations is associated with all-cause and cause-specific mortality. Exposure in sensitive developmental periods might be long-lasting but studies with very long follow-up are rare, and mediating pathways between early life exposure and life-course mortality are not fully understood. METHODS: Data were drawn from the Scottish Longitudinal Study Birth Cohort of 1936, a representative record-linkage study comprising 5% of the Scottish population born in 1936. Participants had valid age 11 cognitive ability test scores along with linked mortality data until age 86. Fine particle (PM2.5) concentrations estimated with the EMEP4UK atmospheric chemistry transport model were linked to participants' residential address derived from the National Identity Register in 1939 (age 3). Confounder-adjusted Cox regression estimated associations between PM2.5 and mortality; regression-based causal mediation analysis explored mediation through childhood cognitive ability. RESULTS: The final sample consisted of 2734 individuals with 1608 deaths registered during the 1,833,517 person-months at risk follow-up time. Higher early life PM2.5 exposure increased the risk of all-cause mortality (HR = 1.03, 95% CI: 1.01-1.04 per 10 µg m-3 increment), associations were stronger for mortality between age 65 and 86. PM2.5 increased the risk of cancer-related mortality (HR = 1.05, 95% CI: 1.02-1.08), especially for lung cancer among females (HR = 1.11, 95% CI: 1.02-1.21), but not for cardiovascular and respiratory diseases. Higher PM2.5 in early life (≥50 µg m-3) was associated with lower childhood cognitive ability, which, in turn, increased the risk of all-cause mortality and mediated 25% of the total associations. CONCLUSIONS: In our life-course study with 75-year of continuous mortality records, we found that exposure to air pollution in early life was associated with higher mortality in late adulthood, and that childhood cognitive ability partly mediated this relationship. Findings suggest that past air pollution concentrations will likely impact health and longevity for decades to come.

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.

Modelling benzo(a)pyrene concentrations for different meteorological conditions - Analysis of lung cancer cases and associated economic costs.

Air pollution originating from the household presents a significant burden to public health, especially during the wintertime in countries, such as Poland, where coal substantially contributes to the energy market. One of the most hazardous components of particulate matter is benzo(a)pyrene (BaP). This study focusses on the impact of different meteorological conditions on BaP concentrations in Poland and associated impacts on human health and economic burdens. For this study, we used the EMEP MSC-W atmospheric chemistry transport model with meteorological data from the Weather Research and Forecasting model to analyze the spatial and temporal distribution of BaP over Central Europe. The model setup has two nested domains, with the inner domain at 4 km × 4 km over Poland, which is a hotspot for BaP concentrations. The outer domain covers countries surrounding Poland in coarser resolution (12 × 812 km), to ensure that transboundary pollution is properly characterized in the modelling. We investigated the sensitivity to variability in winter meteorological conditions on BaP levels and impacts using data from 3 years: 1) 2018, which represents average meteorological conditions during the winter season (BASE run), 2) 2010 with a cold winter (COLD), and 3) 2020 with a warm winter (WARM). The ALPHA-RiskPoll model was used to analyze the lung cancer cases and associated economic costs. The results show that the majority of Poland exceeds the target level of benzo(a)pyrene (1 ng m-3) mainly due to high concentrations during the cold months. High concentrations of BaP have serious health implications and the number of lung cancers in Poland due to BaP exposure varies from 57 to 77 cases for the WARM and COLD years, respectively. It is reflected in the economic costs, which ranged from 136, through 174 to 185 million euros/year for the WARM, BASE and COLD model runs, respectively.

Reduced-form and complex ACTM modelling for air quality policy development: A model inter-comparison.

Simulation models can be valuable tools in supporting development of air pollution policy. However, exploration of future scenarios depends on reliable and robust modelling to provide confidence in outcomes which cannot be tested against measurements. Here we focus on the UK Integrated Assessment Model, a fast reduced-form model with a purpose to support policy development with modelling of multiple alternative future scenarios, and the EMEP4UK model which is a complex Eulerian Atmospheric Chemistry Transport Model requiring significant computing resources. The EMEP4UK model has been used to model selected core scenarios to compare with UKIAM, and to investigate sensitivity studies such as the interannual variability in response to meteorological differences between years. This model intercomparison addresses total PM2.5, primary PM2.5 and Secondary Inorganic Aerosol concentrations for a baseline of 2018 and selected scenarios for projections to 2040. This work has confirmed the robustness of the UK Integrated Assessment Model for assessing alternative futures through a direct comparison with EMEP4UK. Both models have shown good agreement with measurements, and EMEP4UK shows an ability to replicate past trends. These comparisons highlight how a combination of reduced-form modelling (UKIAM) and complex chemical transport modelling (EMEP4UK) can be effectively used in support of air pollution policy development, informing understanding of projected futures in the context of emerging evidence and uncertainties.

Life-course exposure to air pollution and biological ageing in the Lothian Birth Cohort 1936.

BACKGROUND: Exposure to air pollution is associated with a range of diseases. Biomarkers derived from DNA methylation (DNAm) offer potential mechanistic insights into human health differences, connecting disease pathogenesis and biological ageing. However, little is known about sensitive periods during the life course where air pollution might have a stronger impact on DNAm, or whether effects accumulate over time. We examined associations between air pollution exposure across the life course and DNAm-based markers of biological ageing. METHODS: Data were derived from the Scotland-based Lothian Birth Cohort 1936. Participants' residential history was linked to annual levels of fine particle (PM2.5), sulphur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3) around 1935, 1950, 1970, 1980, 1990, and 2001; pollutant concentrations were estimated using the EMEP4UK atmospheric chemistry transport model. Blood samples were obtained between ages of 70 and 80 years, and Horvath DNAmAge, Hannum DNAmAge, DNAmPhenoAge, DNAmGrimAge, and DNAm telomere length (DNAmTL) were computed. We applied the structured life-course modelling approach: least angle regression identified best-fit life-course models for a composite measure of air pollution (air quality index [AQI]), and mixed-effects regression estimated selected models for AQI and single pollutants. RESULTS: We included 525 individuals with 1782 observations. In the total sample, increased air pollution around 1970 was associated with higher epigenetic age (AQI: b = 0.322 year, 95 %CI: 0.088, 0.555) measured with Horvath DNAmAge in late adulthood. We found shorter DNAmTL among males with higher air pollution around 1980 (AQI: b = -0.015 kilobase, 95 %CI: -0.027, -0.004) and among females with higher exposure around 1935 (AQI: b = -0.017 kilobase, 95 %CI: -0.028, -0.006). Findings were more consistent for the pollutants PM2.5, SO2 and NO2. DISCUSSION: We tested the life-course relationship between air pollution and DNAm-based biomarkers. Air pollution around birth and in young-to-middle adulthood is linked to accelerated epigenetic ageing and telomere-associated ageing in later life.

Mitigating the impact of air pollution on dementia and brain health: Setting the policy agenda.

BACKGROUND: Emerging research suggests exposure to high levels of air pollution at critical points in the life-course is detrimental to brain health, including cognitive decline and dementia. Social determinants play a significant role, including socio-economic deprivation, environmental factors and heightened health and social inequalities. Policies have been proposed more generally, but their benefits for brain health have yet to be fully explored. OBJECTIVE AND METHODS: Over the course of two years, we worked as a consortium of 20+ academics in a participatory and consensus method to develop the first policy agenda for mitigating air pollution's impact on brain health and dementia, including an umbrella review and engaging 11 stakeholder organisations. RESULTS: We identified three policy domains and 14 priority areas. Research and Funding included: (1) embracing a complexities of place approach that (2) highlights vulnerable populations; (3) details the impact of ambient PM2.5 on brain health, including current and historical high-resolution exposure models; (4) emphasises the importance of indoor air pollution; (5) catalogues the multiple pathways to disease for brain health and dementia, including those most at risk; (6) embraces a life course perspective; and (7) radically rethinks funding. Education and Awareness included: (8) making this unrecognised public health issue known; (9) developing educational products; (10) attaching air pollution and brain health to existing strategies and campaigns; and (11) providing publicly available monitoring, assessment and screening tools. Policy Evaluation included: (12) conducting complex systems evaluation; (13) engaging in co-production; and (14) evaluating air quality policies for their brain health benefits. CONCLUSION: Given the pressing issues of brain health, dementia and air pollution, setting a policy agenda is crucial. Policy needs to be matched by scientific evidence and appropriate guidelines, including bespoke strategies to optimise impact and mitigate unintended consequences. The agenda provided here is the first step toward such a plan.

Abating ammonia is more cost-effective than nitrogen oxides for mitigating PM2.5 air pollution.

Fine particulate matter (PM2.5, particles with a mass median aerodynamic diameter of less than 2.5 micrometers) in the atmosphere is associated with severe negative impacts on human health, and the gases sulfur dioxide, nitrogen oxides, and ammonia are the main PM2.5 precursors. However, their contribution to global health impacts has not yet been analyzed. Here, we show that nitrogen accounted for 39% of global PM2.5 exposure in 2013, increasing from 30% in 1990 with rising reactive nitrogen emissions and successful controls on sulfur dioxide. Nitrogen emissions to air caused an estimated 23.3 million years of life lost in 2013, corresponding to an annual welfare loss of 420 billion United States dollars for premature death. The marginal abatement cost of ammonia emission is only 10% that of nitrogen oxides emission globally, highlighting the priority for ammonia reduction.

Quantifying the impact of ozone on crops in Sub-Saharan Africa demonstrates regional and local hotspots of production loss.

Tropospheric ozone can have a detrimental effect on vegetation, including reducing the quantity of crop yield. This study uses modelled ozone flux values (POD3IAM; phytotoxic ozone dose above 3 nmol m-2 s-1, parameterised for integrated assessment modelling) for 2015, together with species-specific flux-effect relationships, spatial data on production and growing season dates to quantify the impact of ozone on the production of common wheat (Triticum aestivum) and common beans (Phaseolus vulgaris) across Sub-Saharan Africa (SSA). A case study for South Africa was also done using detailed data per province. Results suggest that ozone pollution could decrease wheat yield by between 2 and 13%, with a total annual loss of 453,000 t across SSA. The impact on bean production depended on the season; however, estimated yield losses were up to 21% in some areas of SSA, with an annual loss of ~300,000 t for each of the two main growing seasons. Production losses tended to be greater in countries with the highest production, for example, Ethiopia (wheat) and Tanzania (beans). This study provides an indication of the location of areas at high risk of crop losses due to ozone. Results emphasise that efforts to reduce ozone precursors could contribute to reducing the yield gap in SSA. More stringent air pollution abatement policies are required to reduce crop losses to ozone in the future.

Life Course Air Pollution Exposure and Cognitive Decline: Modelled Historical Air Pollution Data and the Lothian Birth Cohort 1936.

BACKGROUND: Air pollution has been consistently linked with dementia and cognitive decline. However, it is unclear whether risk is accumulated through long-term exposure or whether there are sensitive/critical periods. A key barrier to clarifying this relationship is the dearth of historical air pollution data. OBJECTIVE: To demonstrate the feasibility of modelling historical air pollution data and using them in epidemiologicalmodels. METHODS: Using the EMEP4UK atmospheric chemistry transport model, we modelled historical fine particulate matter (PM2.5) concentrations for the years 1935, 1950, 1970, 1980, and 1990 and combined these with contemporary modelled data from 2001 to estimate life course exposure in 572 participants in the Lothian Birth Cohort 1936 with lifetime residential history recorded. Linear regression and latent growth models were constructed using cognitive ability (IQ) measured by the Moray House Test at the ages of 11, 70, 76, and 79 years to explore the effects of historical air pollution exposure. Covariates included sex, IQ at age 11 years, social class, and smoking. RESULTS: Higher air pollution modelled for 1935 (when participants would have been in utero) was associated with worse change in IQ from age 11-70 years (ß = -0.006, SE = 0.002, p = 0.03) but not cognitive trajectories from age 70-79 years (p > 0.05). There was no support for other critical/sensitive periods of exposure or an accumulation of risk (all p > 0.05). CONCLUSION: The life course paradigm is essential in understanding cognitive decline and this is the first study to examine life course air pollution exposure in relation to cognitive health.

The Role of Digital Technologies in Responding to the Grand Challenges of the Natural Environment: The Windermere Accord.

Digital technology is having a major impact on many areas of society, and there is equal opportunity for impact on science. This is particularly true in the environmental sciences as we seek to understand the complexities of the natural environment under climate change. This perspective presents the outcomes of a summit in this area, a unique cross-disciplinary gathering bringing together environmental scientists, data scientists, computer scientists, social scientists, and representatives of the creative arts. The key output of this workshop is an agreed vision in the form of a framework and associated roadmap, captured in the Windermere Accord. This accord envisions a new kind of environmental science underpinned by unprecedented amounts of data, with technological advances leading to breakthroughs in taming uncertainty and complexity, and also supporting openness, transparency, and reproducibility in science. The perspective also includes a call to build an international community working in this important area.

Alkaline air: changing perspectives on nitrogen and air pollution in an ammonia-rich world.

Ammonia and ammonium have received less attention than other forms of air pollution, with limited progress in controlling emissions at UK, European and global scales. By contrast, these compounds have been of significant past interest to science and society, the recollection of which can inform future strategies. Sal ammoniac (nushadir, nao sha) is found to have been extremely valuable in long-distance trade (ca AD 600-1150) from Egypt and China, where 6-8 kg N could purchase a human life, while air pollution associated with nushadir collection was attributed to this nitrogen form. Ammonia was one of the keys to alchemy-seen as an early experimental mesocosm to understand the world-and later became of interest as 'alkaline air' within the eighteenth century development of pneumatic chemistry. The same economic, chemical and environmental properties are found to make ammonia and ammonium of huge relevance today. Successful control of acidifying SO2 and NOx emissions leaves atmospheric NH3 in excess in many areas, contributing to particulate matter (PM2.5) formation, while leading to a new significance of alkaline air, with adverse impacts on natural ecosystems. Investigations of epiphytic lichens and bog ecosystems show how the alkalinity effect of NH3 may explain its having three to five times the adverse effect of ammonium and nitrate, respectively. It is concluded that future air pollution policy should no longer neglect ammonia. Progress is likely to be mobilized by emphasizing the lost economic value of global N emissions ($200 billion yr-1), as part of developing the circular economy for sustainable nitrogen management. This article is part of a discussion meeting issue 'Air quality, past present and future'.

A chronology of global air quality.

Air pollution has been recognized as a threat to human health since the time of Hippocrates, ca 400 BC. Successive written accounts of air pollution occur in different countries through the following two millennia until measurements, from the eighteenth century onwards, show the growing scale of poor air quality in urban centres and close to industry, and the chemical characteristics of the gases and particulate matter. The industrial revolution accelerated both the magnitude of emissions of the primary pollutants and the geographical spread of contributing countries as highly polluted cities became the defining issue, culminating with the great smog of London in 1952. Europe and North America dominated emissions and suffered the majority of adverse effects until the latter decades of the twentieth century, by which time the transboundary issues of acid rain, forest decline and ground-level ozone became the main environmental and political air quality issues. As controls on emissions of sulfur and nitrogen oxides (SO2 and NOx) began to take effect in Europe and North America, emissions in East and South Asia grew strongly and dominated global emissions by the early years of the twenty-first century. The effects of air quality on human health had also returned to the top of the priorities by 2000 as new epidemiological evidence emerged. By this time, extensive networks of surface measurements and satellite remote sensing provided global measurements of both primary and secondary pollutants. Global emissions of SO2 and NOx peaked, respectively, in ca 1990 and 2018 and have since declined to 2020 as a result of widespread emission controls. By contrast, with a lack of actions to abate ammonia, global emissions have continued to grow. This article is part of a discussion meeting issue 'Air quality, past present and future'.

Potential and limitation of air pollution mitigation by vegetation and uncertainties of deposition-based evaluations.

The potential to capture additional air pollutants by introducing more vegetation or changing existing short vegetation to woodland on first sight provides an attractive route for lowering urban pollution. Here, an atmospheric chemistry and transport model was run with a range of landcover scenarios to quantify pollutant removal by the existing total UK vegetation as well as the UK urban vegetation and to quantify the effect of large-scale urban tree planting on urban air pollution. UK vegetation as a whole reduces area (population)-weighted concentrations significantly, by 10% (9%) for PM2.5, 30% (22%) for SO2, 24% (19%) for NH3 and 15% (13%) for O3, compared with a desert scenario. By contrast, urban vegetation reduces average urban PM2.5 by only approximately 1%. Even large-scale conversion of half of existing open urban greenspace to forest would lower urban PM2.5 by only another 1%, suggesting that the effect on air quality needs to be considered in the context of the wider benefits of urban tree planting, e.g. on physical and mental health. The net benefits of UK vegetation for NO2 are small, and urban tree planting is even forecast to increase urban NO2 and NOx concentrations, due to the chemical interaction with changes in BVOC emissions and O3, but the details depend on tree species selection. By extrapolation, green infrastructure projects focusing on non-greenspace (roadside trees, green walls, roof-top gardens) would have to be implemented at very large scales to match this effect. Downscaling of the results to micro-interventions solely aimed at pollutant removal suggests that their impact is too limited for their cost-benefit analysis to compare favourably with emission abatement measures. Urban vegetation planting is less effective for lowering pollution than measures to reduce emissions at source. The results highlight interactions that cannot be captured if benefits are quantified via deposition models using prescribed concentrations, and emission damage costs. This article is part of a discussion meeting issue 'Air quality, past present and future'.

A Satellite-Based Spatio-Temporal Machine Learning Model to Reconstruct Daily PM2.5 Concentrations across Great Britain.

Epidemiological studies on the health effects of air pollution usually rely on measurements from fixed ground monitors, which provide limited spatio-temporal coverage. Data from satellites, reanalysis, and chemical transport models offer additional information used to reconstruct pollution concentrations at high spatio-temporal resolutions. This study aims to develop a multi-stage satellite-based machine learning model to estimate daily fine particulate matter (PM2.5) levels across Great Britain between 2008-2018. This high-resolution model consists of random forest (RF) algorithms applied in four stages. Stage-1 augments monitor-PM2.5 series using co-located PM10 measures. Stage-2 imputes missing satellite aerosol optical depth observations using atmospheric reanalysis models. Stage-3 integrates the output from previous stages with spatial and spatio-temporal variables to build a prediction model for PM2.5. Stage-4 applies Stage-3 models to estimate daily PM2.5 concentrations over a 1 km grid. The RF architecture performed well in all stages, with results from Stage-3 showing an average cross-validated R2 of 0.767 and minimal bias. The model performed better over the temporal scale when compared to the spatial component, but both presented good accuracy with an R2 of 0.795 and 0.658, respectively. These findings indicate that direct satellite observations must be integrated with other satellite-based products and geospatial variables to derive reliable estimates of air pollution exposure. The high spatio-temporal resolution and the relatively high precision allow these estimates (approximately 950 million points) to be used in epidemiological analyses to assess health risks associated with both short- and long-term exposure to PM2.5.

Impact of long-term nitrogen deposition on the response of dune grassland ecosystems to elevated summer ozone.

Nitrogen deposition and tropospheric ozone are important drivers of vegetation damage, but their interactive effects are poorly understood. This study assessed whether long-term nitrogen deposition altered sensitivity to ozone in a semi-natural vegetation community. Mesocosms were collected from sand dune grassland in the UK along a nitrogen gradient (5-25 kg N/ha/y, including two plots from a long-term experiment), and fumigated for 2.5 months to simulate medium and high ozone exposure. Ozone damage to leaves was quantified for 20 ozone-sensitive species. Soil solution dissolved organic carbon (DOC) and soil extracellular enzymes were measured to investigate secondary effects on soil processes. Mesocosms from sites receiving the highest N deposition showed the least ozone-related leaf damage, while those from the least N-polluted sites were the most damaged by ozone. This was due to differences in community-level sensitivity, rather than species-level impacts. The N-polluted sites contained fewer ozone-sensitive forbs and sedges, and a higher proportion of comparatively ozone-resistant grasses. This difference in the vegetation composition of mesocosms in relation to N deposition conveyed differential resilience to ozone. Mesocosms in the highest ozone treatment showed elevated soil solution DOC with increasing site N deposition. This suggests that, despite showing relatively little leaf damage, the 'ozone resilient' vegetation community may still sustain physiological damage through reduced capacity to assimilate photosynthate, with its subsequent loss as DOC through the roots into the soil. We conclude that for dune grassland habitats, the regions of highest risk to ozone exposure are those that have received the lowest level of long-term nitrogen deposition. This highlights the importance of considering community- and ecosystem-scale impacts of pollutants in addition to impacts on individual species. It also underscores the need for protection of 'clean' habitats from air pollution and other environmental stressors.

The influence of residential and workday population mobility on exposure to air pollution in the UK.

Traditional approaches of quantifying population-level exposure to air pollution assume that concentrations of air pollutants at the residential address of the study population are representative for overall exposure. This introduces potential bias in the quantification of human health effects. Our study combines new UK Census data comprising information on workday population densities, with high spatio-temporal resolution air pollution concentration fields from the WRF-EMEP4UK atmospheric chemistry transport model, to derive more realistic estimates of population exposure to NO2, PM2.5 and O3. We explicitly allocated workday exposures for weekdays between 8:00 am and 6:00 pm. Our analyses covered all of the UK at 1 km spatial resolution. Taking workday location into account had the most pronounced impact on potential exposure to NO2, with an estimated 0.3 µg m-3 (equivalent to 2%) increase in population-weighted annual exposure to NO2 across the whole UK population. Population-weighted exposure to PM2.5 and O3 increased and decreased by 0.3%, respectively, reflecting the different atmospheric processes contributing to the spatio-temporal distributions of these pollutants. We also illustrate how our modelling approach can be utilised to quantify individual-level exposure variations due to modelled time-activity patterns for a number of virtual individuals living and working in different locations in three example cities. Changes in annual-mean estimates of NO2 exposure for these individuals were considerably higher than for the total UK population average when including their workday location. Conducting model-based evaluations as described here may contribute to improving representativeness in studies that use small, portable, automatic sensors to estimate personal exposure to air pollution.