Long-term ambient ozone, omega-3 fatty acid, genetic susceptibility, and risk of mental disorders among middle-aged and older adults in UK biobank.

BACKGROUND: Evidence linking ozone to depression and anxiety disorders remains sparse and results are heterogeneous. It remains unknown whether omega-3 fatty acid, or genetic susceptibility of mental disorders modify the impacts of ozone. The aim is to assess the associations of ambient ozone with depression and anxiety, and further explore the potential modification effects of omega-3 fatty acid and genetic susceptibility. METHODS: In total of 257,534 participants were enrolled from 2006 to 2010 and followed up to 2016. Depression and anxiety were assessed using mental health questionnaires, primary care records and hospital admission records. The annual average concentrations of ozone were calculated and linked to individuals by home address. Dietary intake and plasma concentration were selected to reflect levels of omega-3 fatty acid. Polygenetic risk scores were selected to reflect genetic susceptibility. We examined the associations of ozone and incident mental disorders, and potential modification of omega-3 fatty acid and genetic susceptibility. RESULTS: Incidences of depression (N = 6957) and anxiety (N = 6944) was associated with increase of ozone. Higher levels of omega-3 fatty acid might attenuate the ozone related depression risk. However, the modification effects of genetic susceptibility were not found. CONCLUSIONS: Long-term exposure to ambient ozone increase the risk of mental disorders among the middle aged and older adults, and omega-3 fatty acid could reduce the adverse effects of ozone on mental health. Higher intake of omega-3 fatty acid is a potential strategy to prevent the risks caused by ozone on public mental health.

Could the association between ozone and arterial stiffness be modified by fish oil supplementation?

BACKGROUND: Arterial stiffness (AS) is an important predicting factor for cardiovascular disease. However, no epidemiological studies have ever explored the mediating role of biomarkers in the association between ozone and AS, nor weather fish oil modified such association. METHODS: Study participants were drawn from the UK biobank, and a total of 95,699 middle-aged and older adults were included in this study. Ozone was obtained from Community Multiscale Air Quality (CMAQ) model matched to residential addresses, fish oil from self-reported intake, and arterial stiffness was based on device measurements. First, we applied a double robust approach to explore the association between ozone or fish oil intake and arterial stiffness, adjusting for potential confounders at the individual and regional levels. Then, how triglycerides, apolipoprotein B (Apo B)/apolipoprotein A (ApoA) and non-high-density lipoprotein cholesterol (Non-HDL-C) mediate the relationship between ozone and AS. Last, the modifying role of fish oil was further explored by stratified analysis. RESULTS: The mean age of participants was 55 years; annual average ozone exposure was associated with ASI (beta:0.189 [95%CI: 0.146 to 0.233], P < 0.001), and compared to participants who did not consume fish oil, fish oil users had a lower ASI (beta: 0.061 [95%CI: -0.111 to -0.010], P = 0.016). The relationship between ozone exposure and AS was mediated by triglycerides, ApoB/ApoA, and Non-HDL-C with mediation proportions ranging from 10.90% to 18.30%. Stratified analysis showed lower estimates on the ozone-AS relationship in fish oil users (P = 0.011). CONCLUSION: Ozone exposure was associated with higher levels of arterial stiffness, in contrast to fish oil consumption, which showed a protective association. The association between ozone exposure and arterial stiffness was partially mediated by some biomarkers. In the general population, fish oil consumption might provide protection against ozone-related AS.

Exposure to ambient air pollution and cognitive function: an analysis of the English Longitudinal Study of Ageing cohort.

BACKGROUND: An increasing number of studies suggest adverse effects of exposure to ambient air pollution on cognitive function, but the evidence is still limited. We investigated the associations between long-term exposure to air pollutants and cognitive function in the English Longitudinal Study of Ageing (ELSA) cohort of older adults. METHODS: Our sample included 8,883 individuals from ELSA, based on a nationally representative study of people aged ≥ 50 years, followed-up from 2002 until 2017. Exposure to air pollutants was modelled by the CMAQ-urban dispersion model and assigned to the participants' residential postcodes. Cognitive test scores of memory and executive function were collected biennially. The associations between these cognitive measures and exposure to ambient concentrations of NO2, PM10, PM2.5 and ozone were investigated using mixed-effects models adjusted for time-varying age, physical activity and smoking status, as well as baseline gender and level of education. RESULTS: Increasing long-term exposure per interquartile range (IQR) of NO2 (IQR: 13.05 µg/m3), PM10 (IQR: 3.35 µg/m3) and PM2.5 (IQR: 2.7 µg/m3) were associated with decreases in test scores of composite memory by -0.10 (95% confidence interval [CI]: -0.14, -0.07), -0.02 [-0.04, -0.01] and -0.08 [-0.11, -0.05], respectively. The same increases in NO2, PM10 and PM2.5 were associated with decreases in executive function score of -0.31 [-0.38, -0.23], -0.05 [-0.08, -0.02] and -0.16 [-0.22, -0.10], respectively. The association with ozone was inverse across both tests. Similar results were reported for the London-dwelling sub-sample of participants. CONCLUSIONS: The present study was based on a long follow-up with several repeated measurements per cohort participant and long-term air pollution exposure assessment at a fine spatial scale. Increasing long-term exposure to NO2, PM10 and PM2.5 was associated with a decrease in cognitive function in older adults in England. This evidence can inform policies related to modifiable environmental exposures linked to cognitive decline.

The longitudinal associations between ambient air pollution exposure and dementia in the UK: results from the cognitive function and ageing study II and Wales.

BACKGROUND: Air pollution has been recognised as a potential risk factor for dementia. Yet recent epidemiological research shows mixed evidence. The aim of this study is to investigate the longitudinal associations between ambient air pollution exposure and dementia in older people across five urban and rural areas in the UK. METHODS: This study was based on two population-based cohort studies of 11329 people aged ≥ 65 in the Cognitive Function and Ageing Study II (2008-2011) and Wales (2011-2013). An algorithmic diagnosis method was used to identify dementia cases. Annual concentrations of four air pollutants (NO2, O3, PM10, PM2.5) were modelled for the year 2012 and linked via the participants' postcodes. Multistate modelling was used to examine the effects of exposure to air pollutants on incident dementia incorporating death and adjusting for sociodemographic factors and area deprivation. A random-effect meta-analysis was carried out to summarise results from the current and nine existing cohort studies. RESULTS: Higher exposure levels of NO2 (HR: 1.04; 95% CI: 0.94, 1.14), O3 (HR: 0.90; 95% CI: 0.70, 1.15), PM10 (HR: 1.17; 95% CI: 0.86, 1.58), PM2.5 (HR: 1.41; 95% CI: 0.71, 2.79) were not strongly associated with dementia in the two UK-based cohorts. Inconsistent directions and strengths of the associations were observed across the two cohorts, five areas, and nine existing studies. CONCLUSIONS: In contrast to the literature, this study did not find clear associations between air pollution and dementia. Future research needs to investigate how methodological and contextual factors can affect evidence in this field and clarity the influence of air pollution exposure on cognitive health over the lifecourse.

Investigating the impact of London's ultra low emission zone on children's health: children's health in London and Luton (CHILL) protocol for a prospective parallel cohort study.

BACKGROUND: Air pollution harms health across the life course. Children are at particular risk of adverse effects during development, which may impact on health in later life. Interventions that improve air quality are urgently needed both to improve public health now, and prevent longer-term increased vulnerability to chronic disease. Low Emission Zones are a public health policy intervention aimed at reducing traffic-derived contributions to urban air pollution, but evidence that they deliver health benefits is lacking. We describe a natural experiment study (CHILL: Children's Health in London and Luton) to evaluate the impacts of the introduction of London's Ultra Low Emission Zone (ULEZ) on children's health. METHODS: CHILL is a prospective two-arm parallel longitudinal cohort study recruiting children at age 6-9 years from primary schools in Central London (the focus of the first phase of the ULEZ) and Luton (a comparator site), with the primary outcome being the impact of changes in annual air pollutant exposures (nitrogen oxides [NOx], nitrogen dioxide [NO2], particulate matter with a diameter of less than 2.5micrograms [PM2.5], and less than 10 micrograms [PM10]) across the two sites on lung function growth, measured as post-bronchodilator forced expiratory volume in one second (FEV1) over five years. Secondary outcomes include physical activity, cognitive development, mental health, quality of life, health inequalities, and a range of respiratory and health economic data. DISCUSSION: CHILL's prospective parallel cohort design will enable robust conclusions to be drawn on the effectiveness of the ULEZ at improving air quality and delivering improvements in children's respiratory health. With increasing proportions of the world's population now living in large urban areas exceeding World Health Organisation air pollution limit guidelines, our study findings will have important implications for the design and implementation of Low Emission and Clean Air Zones in the UK, and worldwide. CLINICALTRIALS: GOV: NCT04695093 (05/01/2021).

Association between air pollution exposure and mental health service use among individuals with first presentations of psychotic and mood disorders: retrospective cohort study.

BACKGROUND: Growing evidence suggests that air pollution exposure may adversely affect the brain and increase risk for psychiatric disorders such as schizophrenia and depression. However, little is known about the potential role of air pollution in severity and relapse following illness onset. AIMS: To examine the longitudinal association between residential air pollution exposure and mental health service use (an indicator of illness severity and relapse) among individuals with first presentations of psychotic and mood disorders. METHOD: We identified individuals aged ≥15 years who had first contact with the South London and Maudsley NHS Foundation Trust for psychotic and mood disorders in 2008-2012 (n = 13 887). High-resolution (20 × 20 m) estimates of nitrogen dioxide (NO2), nitrogen oxides (NOx) and particulate matter (PM2.5 and PM10) levels in ambient air were linked to residential addresses. In-patient days and community mental health service (CMHS) events were recorded over 1-year and 7-year follow-up periods. RESULTS: Following covariate adjustment, interquartile range increases in NO2, NOx and PM2.5 were associated with 18% (95% CI 5-34%), 18% (95% CI 5-34%) and 11% (95% CI 3-19%) increased risk for in-patient days after 1 year. Similarly, interquartile range increases in NO2, NOx, PM2.5 and PM10 were associated with 32% (95% CI 25-38%), 31% (95% CI 24-37%), 7% (95% CI 4-11%) and 9% (95% CI 5-14%) increased risk for CMHS events after 1 year. Associations persisted after 7 years. CONCLUSIONS: Residential air pollution exposure is associated with increased mental health service use among people recently diagnosed with psychotic and mood disorders. Assuming causality, interventions to reduce air pollution exposure could improve mental health prognoses and reduce healthcare costs.

Mental health consequences of urban air pollution: prospective population-based longitudinal survey.

PURPOSE: The World Health Organisation (WHO) recently ranked air pollution as the major environmental cause of premature death. However, the significant potential health and societal costs of poor mental health in relation to air quality are not represented in the WHO report due to limited evidence. We aimed to test the hypothesis that long-term exposure to air pollution is associated with poor mental health. METHODS: A prospective longitudinal population-based mental health survey was conducted of 1698 adults living in 1075 households in South East London, from 2008 to 2013. High-resolution quarterly average air pollution concentrations of nitrogen dioxide (NO2) and oxides (NOx), ozone (O3), particulate matter with an aerodynamic diameter < 10 µm (PM10) and < 2.5 µm (PM2.5) were linked to the home addresses of the study participants. Associations with mental health were analysed with the use of multilevel generalised linear models, after adjusting for large number of confounders, including the individuals' socioeconomic position and exposure to road-traffic noise. RESULTS: We found robust evidence for interquartile range increases in PM2.5, NOx and NO2 to be associated with 18-39% increased odds of common mental disorders, 19-30% increased odds of poor physical symptoms and 33% of psychotic experiences only for PM10. These longitudinal associations were more pronounced in the subset of non-movers for NO2 and NOx. CONCLUSIONS: The findings suggest that traffic-related air pollution is adversely affecting mental health. Whilst causation cannot be proved, this work suggests substantial morbidity from mental disorders could be avoided with improved air quality.

Emulation and Sensitivity Analysis of the Community Multiscale Air Quality Model for a UK Ozone Pollution Episode.

Gaussian process emulation techniques have been used with the Community Multiscale Air Quality model, simulating the effects of input uncertainties on ozone and NO2 output, to allow robust global sensitivity analysis (SA). A screening process ranked the effect of perturbations in 223 inputs, isolating the 30 most influential from emissions, boundary conditions (BCs), and reaction rates. Community Multiscale Air Quality (CMAQ) simulations of a July 2006 ozone pollution episode in the UK were made with input values for these variables plus ozone dry deposition velocity chosen according to a 576 point Latin hypercube design. Emulators trained on the output of these runs were used in variance-based SA of the model output to input uncertainties. Performing these analyses for every hour of a 21 day period spanning the episode and several days on either side allowed the results to be presented as a time series of sensitivity coefficients, showing how the influence of different input uncertainties changed during the episode. This is one of the most complex models to which these methods have been applied, and here, they reveal detailed spatiotemporal patterns of model sensitivities, with NO and isoprene emissions, NO2 photolysis, ozone BCs, and deposition velocity being among the most influential input uncertainties.

Effect of Exhaust- and Nonexhaust-Related Components of Particulate Matter on Long-Term Survival After Stroke.

BACKGROUND AND PURPOSE: Outdoor air pollution represents a potentially modifiable risk factor for stroke. We examined the link between ambient pollution and mortality up to 5 years poststroke, especially for pollutants associated with vehicle exhaust. METHODS: Data from the South London Stroke Register, a population-based register covering an urban, multiethnic population, were used. Hazard ratios (HR) for a 1 interquartile range increase in particulate matter <2.5 µm diameter (PM2.5) and PM <10 µm (PM10) were estimated poststroke using Cox regression, overall and broken down into exhaust and nonexhaust components. Analysis was stratified for ischemic and hemorrhagic strokes and was further broken down by Oxford Community Stroke Project classification. RESULTS: The hazard of death associated with PM2.5 up to 5 years after stroke was significantly elevated (P=0.006) for all strokes (HR=1.28; 95% confidence interval [CI], 1.08-1.53) and ischemic strokes (HR, 1.32; 95% CI, 1.08-1.62). Within ischemic subtypes, PM2.5 pollution increased mortality risk for total anterior circulation infarcts by 2-fold (HR, 2.01; 95% CI, 1.17-3.48; P=0.012) and by 78% for lacunar infarcts (HR, 1.78; 95% CI, 1.18-2.66; P=0.006). PM10 pollution was associated with 45% increased mortality risk for lacunar infarct strokes (HR, 1.45; 95% CI, 1.06-2.00; P=0.022). Separating PM2.5 and PM10 into exhaust and nonexhaust components did not show increased mortality. CONCLUSIONS: Exposure to certain outdoor PM pollution, particularly PM2.5, increased mortality risk poststroke up to 5 years after the initial stroke.

Spatially resolved flux measurements of NOx from London suggest significantly higher emissions than predicted by inventories.

To date, direct validation of city-wide emissions inventories for air pollutants has been difficult or impossible. However, recent technological innovations now allow direct measurement of pollutant fluxes from cities, for comparison with emissions inventories, which are themselves commonly used for prediction of current and future air quality and to help guide abatement strategies. Fluxes of NOx were measured using the eddy-covariance technique from an aircraft flying at low altitude over London. The highest fluxes were observed over central London, with lower fluxes measured in suburban areas. A footprint model was used to estimate the spatial area from which the measured emissions occurred. This allowed comparison of the flux measurements to the UK's National Atmospheric Emissions Inventory (NAEI) for NOx, with scaling factors used to account for the actual time of day, day of week and month of year of the measurement. The comparison suggests significant underestimation of NOx emissions in London by the NAEI, mainly due to its under-representation of real world road traffic emissions. A comparison was also carried out with an enhanced version of the inventory using real world driving emission factors and road measurement data taken from the London Atmospheric Emissions Inventory (LAEI). The measurement to inventory agreement was substantially improved using the enhanced version, showing the importance of fully accounting for road traffic, which is the dominant NOx emission source in London. In central London there was still an underestimation by the inventory of 30-40% compared with flux measurements, suggesting significant improvements are still required in the NOx emissions inventory.

London Hybrid Exposure Model: Improving Human Exposure Estimates to NO2 and PM2.5 in an Urban Setting.

Here we describe the development of the London Hybrid Exposure Model (LHEM), which calculates exposure of the Greater London population to outdoor air pollution sources, in-buildings, in-vehicles, and outdoors, using survey data of when and where people spend their time. For comparison and to estimate exposure misclassification we compared Londoners LHEM exposure with exposure at the residential address, a commonly used exposure metric in epidemiological research. In 2011, the mean annual LHEM exposure to outdoor sources was estimated to be 37% lower for PM2.5 and 63% lower for NO2 than at the residential address. These decreased estimates reflect the effects of reduced exposure indoors, the amount of time spent indoors (∼95%), and the mode and duration of travel in London. We find that an individual's exposure to PM2.5 and NO2 outside their residential address is highly correlated (Pearson's R of 0.9). In contrast, LHEM exposure estimates for PM2.5 and NO2 suggest that the degree of correlation is influenced by their exposure in different transport modes. Further development of the LHEM has the potential to increase the understanding of exposure error and bias in time-series and cohort studies and thus better distinguish the independent effects of NO2 and PM2.5.

Road traffic noise is associated with increased cardiovascular morbidity and mortality and all-cause mortality in London.

AIMS: Road traffic noise has been associated with hypertension but evidence for the long-term effects on hospital admissions and mortality is limited. We examined the effects of long-term exposure to road traffic noise on hospital admissions and mortality in the general population. METHODS AND RESULTS: The study population consisted of 8.6 million inhabitants of London, one of Europe's largest cities. We assessed small-area-level associations of day- (7:00-22:59) and nighttime (23:00-06:59) road traffic noise with cardiovascular hospital admissions and all-cause and cardiovascular mortality in all adults (≥25 years) and elderly (≥75 years) through Poisson regression models. We adjusted models for age, sex, area-level socioeconomic deprivation, ethnicity, smoking, air pollution, and neighbourhood spatial structure. Median daytime exposure to road traffic noise was 55.6 dB. Daytime road traffic noise increased the risk of hospital admission for stroke with relative risk (RR) 1.05 [95% confidence interval (CI): 1.02-1.09] in adults, and 1.09 (95% CI: 1.04-1.14) in the elderly in areas >60 vs. <55 dB. Nighttime noise was associated with stroke admissions only among the elderly. Daytime noise was significantly associated with all-cause mortality in adults [RR 1.04 (95% CI: 1.00-1.07) in areas >60 vs. <55 dB]. Positive but non-significant associations were seen with mortality for cardiovascular and ischaemic heart disease, and stroke. Results were similar for the elderly. CONCLUSIONS: Long-term exposure to road traffic noise was associated with small increased risks of all-cause mortality and cardiovascular mortality and morbidity in the general population, particularly for stroke in the elderly.

Measurement of NO(x) fluxes from a tall tower in Central London, UK and comparison with emissions inventories.

Direct measurements of NOx concentration and flux were made from a tall tower in central London, UK as part of the Clean Air for London (ClearfLo) project. Fast time resolution (10 Hz) NO and NO2 concentrations were measured and combined with fast vertical wind measurements to provide top-down flux estimates using the eddy covariance technique. Measured NOx fluxes were usually positive and ranged from close to zero at night to 2000-8000 ng m(-2) s(-1) during the day. Peak fluxes were usually observed in the morning, coincident with the maximum traffic flow. Measurements of the NOx flux have been scaled and compared to the UK National Atmospheric Emissions Inventory (NAEI) estimate of NOx emission for the measurement footprint. The measurements are on average 80% higher than the NAEI emission inventory for all of London. Observations made in westerly airflow (from parts of London where traffic is a smaller fraction of the NOx source) showed a better agreement on average with the inventory. The observations suggest that the emissions inventory is poorest at estimating NOx when traffic is the dominant source, in this case from an easterly direction from the BT Tower. Agreement between the measurements and the London Atmospheric Emissions Inventory (LAEI) are better, due to the more explicit treatment of traffic flow by this more detailed inventory. The flux observations support previous tailpipe observations of higher NOx emitted from the London vehicle diesel fleet than is represented in the NAEI or predicted for several EURO emission control technologies. Higher-than-anticipated vehicle NOx is likely responsible for the significant discrepancies that exist in London between observed NOx and long-term NOx projections.

Traffic-related air pollution in relation to cognitive function in older adults.

BACKGROUND: Few epidemiologic studies have investigated associations of air pollution with cognition in older adults, and none has specifically compared associations across particle sources. We investigated whether exposure to particulate air pollution, characterized by size and source, was associated with cognitive function and decline in cognitive function. METHODS: We included participants of the Whitehall II cohort who were residents of greater London and who attended the medical examination in study wave 2007-2009 (n = 2867). Annual average concentrations of particulate matter (PM) (PM10 and PM2.5 from all sources and from traffic exhaust) were modeled at resolution of 20 × 20 m for 2003-2009. We investigated the relationship between exposure to particles and a cognitive battery composed of tests of reasoning, memory, and phonemic and semantic fluency. We also investigated exposure in relation to decline in these tests over 5 years. RESULTS: Mean age of participants was 66 (standard deviation = 6) years. All particle metrics were associated with lower scores in reasoning and memory measured in the 2007-2009 wave but not with lower verbal fluency. Higher PM2.5 of 1.1 µg/m (lag 4) was associated with a 0.03 (95% confidence interval = -0.06 to 0.002) 5-year decline in standardized memory score and a 0.04 (-0.07 to -0.01) decline when restricted to participants remaining in London between study waves. CONCLUSIONS: This study provides support for an association between particulate air pollution and some measures of cognitive function, as well as decline over time in cognition; however, it does not support the hypothesis that traffic-related particles are more strongly associated with cognitive function than particles from all sources.

Outdoor air pollution, subtypes and severity of ischemic stroke--a small-area level ecological study.

BACKGROUND: Evidence linking outdoor air pollution and incidence of ischemic stroke subtypes and severity is limited. We examined associations between outdoor PM10 and NO2 concentrations modeled at a fine spatial resolution and etiological and clinical ischemic stroke subtypes and severity of ischemic stroke. METHODS: We used a small-area level ecological study design and a stroke register set up to capture all incident cases of first ever stroke (1995-2007) occurring in a defined geographical area in South London (948 census output areas; population of 267839). Modeled PM10 and NO2 concentrations were available at a very fine spatial scale (20 meter by 20 meter grid point resolution) and were aggregated to output area level using postcode population weighted averages. Ischemic stroke was classified using the Oxford clinical classification, the Trial of Org 10172 in Acute Stroke Treatment (TOAST) etiological classification, National Institutes of Health Stroke Scale (NIHSS) score and a pragmatic clinical severity classification based on Glasgow coma score, ability to swallow, urinary continence and death <2 days of stroke onset. RESULTS: Mean (SD) concentrations were 25.1 (1.2) ug/m(3) (range 23.3-36.4) for PM10 and 41.4 (3.0) ug/m(3) (range 35.4-68.0) for NO2. There were 2492 incident cases of ischemic stroke. We found no evidence of association between these pollutants and the incidence of ischemic stroke subtypes classified using the Oxford and TOAST classifications. We found no significant association with stroke severity using NIHSS severity categories. However, we found that outdoor concentrations of both PM10 and NO2 appeared to be associated with increased incidence of mild but not severe ischemic stroke, classified using the pragmatic clinical severity classification. For mild ischemic stroke, the rate ratio in the highest PM10 category by tertile was 1.20 (1.05-1.38) relative to the lowest category. The rate ratio in the highest NO2 category was 1.22 (1.06-1.40) relative to the lowest category. CONCLUSIONS: We found no evidence of association between outdoor PM10 and NO2 concentrations and ischemic stroke subtypes but there was a suggestion that living in areas with elevated outdoor PM10 and NO2 concentrations might be associated with increased incidence of mild, but not severe, ischemic stroke.

Short-Term Nitrogen Dioxide Exposure and Emergency Hospital Admissions for Asthma in Children: A Case-Crossover Analysis in England.

Background: There is an increasing body of evidence associating short-term ambient nitrogen dioxide (NO2) exposure with asthma-related hospital admissions in children. However, most studies have relied on temporally resolved exposure information, potentially ignoring the spatial variability of NO2. We aimed to investigate how daily NO2 estimates from a highly resolved spatio-temporal model are associated with the risk of emergency hospital admission for asthma in children in England. Methods: We conducted a time-stratified case-crossover study including 111,766 emergency hospital admissions for asthma in children (aged 0-14 years) between 1st January 2011 and 31st December 2015 in England. Daily NO2 levels were predicted at the patients' place of residence using spatio-temporal models by combining land use data and chemical transport model estimates. Conditional logistic regression models were used to obtain the odds ratios (OR) and confidence intervals (CI) after adjusting for temperature, relative humidity, bank holidays, and influenza rates. The effect modifications by age, sex, season, area-level income deprivation, and region were explored in stratified analyses. Results: For each 10 µg/m³ increase in NO2 exposure, we observed an 8% increase in asthma-related emergency admissions using a five-day moving NO2 average (mean lag 0-4) (OR 1.08, 95% CI 1.06-1.10). In the stratified analysis, we found larger effect sizes for male (OR 1.10, 95% CI 1.07-1.12) and during the cold season (OR 1.10, 95% CI 1.08-1.12). The effect estimates varied slightly by age group, area-level income deprivation, and region. Significance: Short-term exposure to NO2 was significantly associated with an increased risk of asthma emergency admissions among children in England. Future guidance and policies need to consider reflecting certain proven modifications, such as using season-specific countermeasures for air pollution control, to protect the at-risk population.

Quantifying the change of brake wear particulate matter emissions through powertrain electrification in passenger vehicles.

With vehicle fleets transitioning from internal combustion engines (ICE) to electric powertrains, we have used friction brake power simulations, for different vehicle classes and driving styles, to predict the impact of regenerative braking systems (RBS) on brake wear particulate matter emissions (PM10 and PM2.5). Under the same powertrain, subcompact (SC) vehicles were predicted to require between 38 and 68% less friction brake power than heavier sports utility vehicles (L-SUV). However, despite electric and hybrid vehicles being heavier than ICE vehicles, the results show that RBS would reduce brake wear by between 64 and 95%. The study highlights the effect of aggressive braking on the amount of friction brake power required, with electric powertrains more likely to require friction braking to perform short, but aggressive braking compared with longer, slower braking events. Brake wear reductions varied under different driving conditions, as the level of mitigation depends on the complex interaction of several variables, including: vehicle speed, deceleration rate, regenerative braking technology and vehicle mass. Urban brake wear emission factors for electric powertrains ranged from 3.9 to 5.5 mg PM10/km and 1.5-2.1 mg PM2.5/km, providing an average reduction in PM emission factors of 68%. Rural and motorway driving conditions had lower brake wear emission factors, with plug-in hybrid electric vehicles (PHEV) and battery electric vehicles (BEV) emitting negligible PM10 and PM2.5 brake wear. Although electric powertrain uptake, vehicle mileage driven and driving styles are dependent upon national policies and strategies, by 2035, we project that total UK brake wear PM emissions would reduce by up to 39% compared with 2020 levels. This analysis supports the transition towards electric and hybrid vehicle fleets to reduce brake wear emissions, however increases in tyre wear, road wear, and resuspension due to increased vehicle mass may offset these benefits.

Can the UK meet the World Health Organization PM2.5 interim target of 10 µg m-3 by 2030?

The recent United Kingdom (UK) Environment Act consultation had the intention of setting two targets for PM2.5 (particles with an aerodynamic diameter less than 2.5 µm), one related to meeting an annual average concentration and the second to reducing population exposure. As part of the consultation, predictions of PM2.5 concentrations in 2030 were made by combining European Union (EU) and UK government's emissions forecasts, with the Climate Change Committee's (CCC) Net Zero vehicle forecasts, and in London with the addition of local policies based on the London Environment Strategy (LES). Predictions in 2018 showed 6.4% of the UK's area and 82.6% of London's area had PM2.5 concentrations above the World Health Organization (WHO) interim target of 10 µg m-3, but by 2030, over 99% of the UK's area was predicted to be below it. However, kerbside concentrations in London and other major cities were still at risk of exceeding 10 µg m-3. With local action on PM2.5 in London, population weighted concentrations showed full compliance with the WHO interim target of 10 µg m-3 in 2030. However, predicting future PM2.5 concentrations and interpreting the results will always be difficult and uncertain for many reasons, such as imperfect models and the difficulty in estimating future emissions. To help understand the sensitivity of the model's PM2.5 predictions in 2030, current uncertainty was quantified using PM2.5 measurements and showed large areas in the UK that were still at risk of exceeding the WHO interim target despite the model predictions being below 10 µg m-3. Our results do however point to the benefits that policy at EU, UK and city level can have on achieving the WHO interim target of 10 µg m-3. These results were submitted to the UK Environment Act consultation. Nevertheless, the issues addressed here could be applicable to other European cities.

Associations between air pollution and mental health service use in dementia: a retrospective cohort study.

BACKGROUND: Little is known about the role of air pollution in how people with dementia use mental health services. OBJECTIVE: We examined longitudinal associations between air pollution exposure and mental health service use in people with dementia. METHODS: In 5024 people aged 65 years or older with dementia in South London, high resolution estimates of nitrogen dioxide (NO2) and particulate matter (PM2.5 and PM10) levels in ambient air were linked to residential addresses. Associations between air pollution and Community Mental Health Team (CMHT) events (recorded over 9 years) were examined using negative binomial regression models. Cognitive function was measured using the Mini Mental State Examination (MMSE) and health and social functioning was measured using the Health of the Nation Outcomes Scale (HoNOS65+). Associations between air pollution and both MMSE and HoNOS65+ scores were assessed using linear regression models. FINDINGS: In the first year of follow-up, increased exposure to all air pollutants was associated with an increase in the use of CMHTs in a dose-response manner. These associations were strongest when we compared the highest air pollution quartile (quartile 4: Q4) with the lowest quartile (Q1) (eg, NO2: adjusted incidence rate ratio (aIRR) 1.27, 95% CI 1.11 to 1.45, p<0.001). Dose-response patterns between PM2.5 and CMHT events remained at 5 and 9 years. Associations were strongest for patients with vascular dementia. NO2 levels were linked with poor functional status, but not cognitive function. CONCLUSIONS: Residential air pollution exposure is associated with increased CMHT usage among people with dementia. CLINICAL IMPLICATIONS: Efforts to reduce pollutant exposures in urban settings might reduce the use of mental health services in people with dementia, freeing up resources in already considerably stretched psychiatric services.

Prenatal exposure to air pollution is associated with structural changes in the neonatal brain.

BACKGROUND: Prenatal exposure to air pollution is associated with adverse neurologic consequences in childhood. However, the relationship between in utero exposure to air pollution and neonatal brain development is unclear. METHODS: We modelled maternal exposure to nitrogen dioxide (NO2) and particulate matter (PM2.5 and PM10) at postcode level between date of conception to date of birth and studied the effect of prenatal air pollution exposure on neonatal brain morphology in 469 (207 male) healthy neonates, with gestational age of ≥36 weeks. Infants underwent MR neuroimaging at 3 Tesla at 41.29 (36.71-45.14) weeks post-menstrual age (PMA) as part of the developing human connectome project (dHCP). Single pollutant linear regression and canonical correlation analysis (CCA) were performed to assess the relationship between air pollution and brain morphology, adjusting for confounders and correcting for false discovery rate. RESULTS: Higher exposure to PM10 and lower exposure to NO2 was strongly canonically correlated to a larger relative ventricular volume, and moderately associated with larger relative size of the cerebellum. Modest associations were detected with higher exposure to PM10 and lower exposure to NO2 and smaller relative cortical grey matter and amygdala and hippocampus, and larger relaive brainstem and extracerebral CSF volume. No associations were found with white matter or deep grey nuclei volume. CONCLUSIONS: Our findings show that prenatal exposure to air pollution is associated with altered brain morphometry in the neonatal period, albeit with opposing results for NO2 and PM10. This finding provides further evidence that reducing levels of maternal exposure to particulate matter during pregnancy should be a public health priority and highlights the importance of understanding the impacts of air pollution on this critical development window.