116 results found
Scales J, Chavda J, Ikeda E, et al., 2023, Device-Measured Change in Physical Activity in Primary School Children During the UK COVID-19 Pandemic Lockdown: A Longitudinal Study., J Phys Act Health, Pages: 1-9
BACKGROUND: Lockdown measures, including school closures, due to the COVID-19 pandemic have caused widespread disruption to children's lives. The aim of this study was to explore the impact of a national lockdown on children's physical activity using seasonally matched accelerometry data. METHODS: Using a pre/post observational design, 179 children aged 8 to 11 years provided physical activity data measured using hip-worn triaxial accelerometers worn for 5 consecutive days prepandemic and during the January to March 2021 lockdown. Multilevel regression analyses adjusted for covariates were used to assess the impact of lockdown on time spent in sedentary and moderate to vigorous physical activity. RESULTS: A 10.8-minute reduction in daily time spent in moderate to vigorous physical activity (standard error: 2.3 min/d, P < .001) and a 33.2-minute increase in daily sedentary activity (standard error: 5.5 min/d, P < .001) were observed during lockdown. This reflected a reduction in daily moderate to vigorous physical activity for those unable to attend school (-13.1 [2.3] min/d, P < .001) during lockdown, with no significant change for those who continued to attend school (0.4 [4.0] min/d, P < .925). CONCLUSION: These findings suggest that the loss of in-person schooling was the single largest impact on physical activity in this cohort of primary school children in London, Luton, and Dunstable, United Kingdom.
Bos B, Barratt B, Batalle D, et al., 2023, Prenatal exposure to air pollution is associated with structural changes in the neonatal brain., Environ Int, Vol: 174
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.
Karamanos A, Lu Y, Mudway IS, et al., 2023, Associations between air pollutants and blood pressure in an ethnically diverse cohort of adolescents in London, England, PLoS One, Vol: 18, Pages: 1-18, ISSN: 1932-6203
Longitudinal evidence on the association between air pollution and blood pressure (BP) in adolescence is scarce. We explored this association in an ethnically diverse cohort of schoolchildren. Sex-stratified, linear random-effects modelling was used to examine how modelled residential exposure to annual average nitrogen dioxide (NO2), particulate matter (PM2.5, PM10) and ozone (O3), measures in μg/m3, associated with blood pressure. Estimates were based on 3,284 adolescents; 80% from ethnic minority groups, recruited from 51 schools, and followed up from 11–13 to 14–16 years old. Ethnic minorities were exposed to higher modelled annual average concentrations of pollution at residential postcode level than their White UK peers. A two-pollutant model (NO2 & PM2.5), adjusted for ethnicity, age, anthropometry, and pubertal status, highlighted associations with systolic, but not diastolic BP. A μg/m3 increase in NO2 was associated with a 0.30 mmHg (95% CI 0.18 to 0.40) decrease in systolic BP for girls and 0.19 mmHg (95% CI 0.07 to 0.31) decrease in systolic BP for boys. In contrast, a 1 μg/m3 increase in PM2.5 was associated with 1.34 mmHg (95% CI 0.85 to 1.82) increase in systolic BP for girls and 0.57 mmHg (95% CI 0.04 to 1.03) increase in systolic BP for boys. Associations did not vary by ethnicity, body size or socio-economic advantage. Associations were robust to adjustments for noise levels and lung function at 11–13 years. In summary, higher ambient levels of NO2 were associated with lower and PM2.5 with higher systolic BP across adolescence, with stronger associations for girls.
Wood D, Evangelopoulos D, Beevers S, et al., 2022, Exposure to Ambient Air Pollution and the Incidence of Dementia in the Elderly of England: The ELSA Cohort, INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, Vol: 19
Vu TV, Stewart GB, Kitwiroon N, et al., 2022, Assessing the contributions of outdoor and indoor sources to air quality in London homes of the SCAMP cohort, Building and Environment, Vol: 222, Pages: 1-8, ISSN: 0360-1323
Given that many people typically spend the majority of their time at home, accurate measurement and modelling of the home environment is critical in estimating their exposure to air pollution. This study investigates the fate and impact on human exposure of outdoor and indoor pollutants in London homes, using a combination of sensor measurements, outdoor air pollution estimated from the CMAQ-urban model and indoor mass balance models. Averaged indoor concentrations of PM2.5, PM10 and NO2 were 14.6, 24.7 and 14.2 μg m−3 while the outdoor concentrations were 14.4, 22.6 and 21.4 μg m−3, respectively. Mean infiltration factors of particles (0.6–0.7) were higher than those of NO2 (0.4). In contrast, higher loss rates were found for NO2 (0.5–0.8 h−1) compared to those for particles (0.1–0.3 h−1). The average concentrations of PM2.5, PM10 and NO2 in kitchen environments were 22.0, 33.7 and 20.8 μg m−3, with highest hourly concentrations (437, 644 and 136 μg m−3, respectively) during cooking times (6–7 pm). Indoor sources increased the indoor concentrations of particles and NO2 by an average of 26–37% in comparison to the indoor background level without indoor sources. Outdoor and indoor air exchange plays an important role in reducing air pollution indoors by 65–86% for particles and 42–65% for NO2.
Wang W, Fecht D, Beevers S, et al., 2022, Predicting daily concentrations of nitrogen dioxide, particulate matter and ozone at fine spatial scale in Great Britain, Atmospheric Pollution Research, Vol: 13, Pages: 101506-101506, ISSN: 1309-1042
Short-term exposure studies have often relied on time-series of air pollution measurements from monitoring sites. However, this approach does not capture short-term changes in spatial contrasts in air pollution. To address this, models representing both the spatial and temporal variability in air pollution have emerged in recent years. Here, we modelled daily average concentrations of nitrogen dioxide (NO2), particulate matter (PM2.5 and PM10) and ozone (O3) on a 25 m grid for Great Britain from 2011 to 2015 using a generalised additive mixed model, with penalised spline smooth functions for covariates. The models included local-scale predictors derived using a Geographic Information System (GIS), daily estimates from a chemical transport model, and daily meteorological characteristics. The models performed well in explaining the variability in daily averaged measured concentrations at 48–85 sites: 63% for NO2, 77% for PM2.5, 80% for PM10 and 85% for O3. Outputs of the study include daily air pollution maps that can be applied in epidemiological studies across Great Britain. Daily concentration values can also be predicted for specific locations, such as residential addresses or schools, and aggregated to other exposure time periods (including weeks, months, or pregnancy trimesters) to facilitate the needs of different health analyses.
Drysdale WS, Vaughan AR, Squires FA, et al., 2022, Eddy covariance measurements highlight sources of nitrogen oxide emissions missing from inventories for central London, Atmospheric Chemistry and Physics, Vol: 22, Pages: 9413-9433, ISSN: 1680-7316
During March–June 2017 emissions of nitrogen oxides were measured via eddy covariance at the British Telecom Tower in central London, UK. Through the use of a footprint model the expected emissions were simulated from the spatially resolved National Atmospheric Emissions Inventory for 2017 and compared with the measured emissions. These simulated emissions were shown to underestimate measured emissions during the daytime by a factor of 1.48, but they agreed well overnight. Furthermore, underestimations were spatially mapped, and the areas around the measurement site responsible for differences in measured and simulated emissions were inferred. It was observed that areas of higher traffic, such as major roads near national rail stations, showed the greatest underestimation by the simulated emissions. These discrepancies are partially attributed to a combination of the inventory not fully capturing traffic conditions in central London and both the spatial and temporal resolution of the inventory not fully describing the high heterogeneity of the urban centre. Understanding of this underestimation may be further improved with longer measurement time series to better understand temporal variation and improved temporal scaling factors to better simulate sub-annual emissions.
Shoari N, Beevers S, Brauer M, et al., 2022, Towards healthy school neighbourhoods: a baseline analysis in Greater London, Environment International, Vol: 165, ISSN: 0160-4120
Creating healthy environments around schools is important to promote healthy childhood development and is a critical component of public health. In this paper we present a tool to characterize exposure to multiple urban environment features within 400 m (5-10 minutes walking distance) of schools in Greater London. We modelled joint exposure to air pollution (NO2 and PM2.5), access to public greenspace, food environment, and road safety for 2,929 schools, employing a Bayesian non-parametric approach based on the Dirichlet Process Mixture modelling. We identified 12 latent clusters of schools with similar exposure profiles and observed some spatial clustering patterns. Socioeconomic and ethnicity disparities were manifested with respect to exposure profiles. Specifically, three clusters (containing 645 schools) showed the highest joint exposure to air pollution, poor food environment, and unsafe roads and were characterized with high deprivation. The most deprived cluster of schools had a median of 2.5 ha greenspace, 29.0 µg/m3 of NO2, 19.3 µg/m3 of PM2.5, 20 fast food retailers, and five child pedestrian crashes over a three-year period. The least deprived cluster of schools had a median of 21.8 ha greenspace, 15.6 µg/m3 of NO2, 15.1 µg/m3 of PM2.5, 2 fast food retailers, and one child pedestrian crash over a three-year period. To have a school-level understanding of exposure levels, we then benchmarked schools based on the probability of exceeding the median exposure to various features of interest. Our study accounts for multiple exposures, enabling us to highlight spatial distribution of exposure profile clusters, and to identify predominant exposure to urban environment features for each cluster of schools. Our findings can help relevant stakeholders, such as schools and public health authorities, to compare schools based on their exposure levels, prioritize interventions, and design local policies that target the schools most in need.
Dimakopoulou K, Samoli E, Analitis A, et al., 2022, Development and Evaluation of Spatio-Temporal Air Pollution Exposure Models and Their Combinations in the Greater London Area, UK, INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, Vol: 19
Carruthers D, Stocker J, Stidworthy A, et al., 2022, DEFRA 2021 AIR QUALITY MODEL INTER-COMPARISON EXERCISE
The UK takes a combined measurement and modelling approach to reporting associated with the Air Quality Standards Regulations (AQSR, previously the EU Air Quality Directive) pollutant metrics, with modelling currently being performed on behalf of the UK Department for Environment, Food & Rural Affairs (Defra) by Ricardo using the Pollution Climate Mapping (PCM) system. The primary purpose of the Defra 2021 Air Quality Model Inter-Comparison Exercise was to assess the capabilities of four air quality modelling systems in terms of their suitability for AQSR reporting, specifically: PCM; the CMAQ-Urban model driven by WRF meteorology (Environmental Research Group at Imperial College, London); the Air Quality model within the UK Met Office's Unified Model (AQUM-SPPO); and a WRF-EMEP application for the UK (UK Centre for Ecology and Hydrology). This paper provides a project overview and presents key conclusions. All models were configured to calculate pollutant concentrations for 2018 at over 400 monitor locations, gridded concentrations at the models' highest resolution over all of the UK, and, for three of the four models, near-road concentrations associated with the major road network. A wide range of metrics were calculated to assess model performance using NOx, NO2, O3, PM2.5 and PM10 measurement datasets. In addition to visual comparison of air quality maps, derived statistics such as areas in exceedance were calculated separately for 28 agglomeration and 15 non-agglomeration zones. A documented assessment of the models' formulations, configurations and inputs led to an informed model inter-comparison. Meteorological model performance has been evaluated at seven sites over the UK (wind speed, direction and temperature), and the relationship between modelled wind and pollutant concentrations has been investigated. Technical diagnostics have been used to assess how well the models account for NOx chemistry, in addition to the models' ability to represent coarse a
Kelly F, scales J, Chavda J, et al., 2021, 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, medRxiv
Newbury JB, Stewart R, Fisher HL, et al., 2021, Association between air pollution exposure and mental health service use among individuals with first presentations of psychotic and mood disorders: retrospective cohort study, The British Journal of Psychiatry, Vol: 219, Pages: 678-685, ISSN: 0007-1250
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.
Desouza CD, Marsh DJ, Beevers SD, et al., 2021, A spatial and fleet disaggregated approach to calculating the NOX emissions inventory for non-road mobile machinery in London, Atmospheric Environment: X, Vol: 12, Pages: 1-8, ISSN: 2590-1621
The latest London atmospheric emissions inventory (2016), which is calculated using fuel consumption and construction employment, estimates that, the construction sector contributes 34% of the total PM10 emissions (the largest source), and 7% of the total NOX emissions (5th largest source). These contribute significantly to NO2 and PM2.5 pollution problems in London, which is a major concern for public health. Real-world emission factors from tail-pipe measurements were coupled to a register for construction machinery, to develop a novel ‘spatial and fleet disaggregated’ emissions inventory for the construction sector in London. This method estimated 1294 tonnes of NOX in 2018 and 1578 tonnes of NOX in 2019 from non-road mobile machinery in the construction sector, approximately 55% and 45% lower for 2018 and 2019 respectively, than the current (2016) London atmospheric emissions inventory (2850 tonnes). However, compared to the current London atmospheric emissions inventory, the new NOX emissions are higher in central London, under-estimating the importance of this source in central London. The fleet-disaggregated emissions inventory enables potential policy to be developed by focusing on high-emitters registered on the London database. As a demonstration, two emission abatement scenarios were modelled – first: by retrofitting older generators with a SCR-DPF system, a potential 53% reduction in overall NOX emissions was predicted from all NRMM; and second: by accelerating the excavator fleet-turnover – a more modest 2-tonne reduction in overall NOX emissions was predicted from all NRMM in London.
Wang J, Alli AS, Clark S, et al., 2021, Nitrogen oxides (NO and NO2) pollution in the Accra metropolis: Spatiotemporal patterns and the role of meteorology, SCIENCE OF THE TOTAL ENVIRONMENT, Vol: 803, ISSN: 0048-9697
- Author Web Link
- Citations: 7
Karamanos A, Mudway I, Webb A, et al., 2021, Air pollution and Blood Pressure change over time in 3323 adolescents in London: differences by gender and ethnicity, 2021 Annual Scientific Meeting of the British and Irish Hypertension Society (BIHS), Publisher: SPRINGERNATURE, Pages: 2-2, ISSN: 0950-9240
Ashworth M, Analitis A, Whitney D, et al., 2021, Spatio-temporal associations of air pollutant concentrations, GP respiratory consultations and respiratory inhaler prescriptions: a 5-year study of primary care in the borough of Lambeth, South London, ENVIRONMENTAL HEALTH, Vol: 20
- Author Web Link
- Citations: 3
Karamanos A, Mudway I, Kelly F, et al., 2021, Air pollution and trajectories of adolescent conduct problems: the roles of ethnicity and racism; evidence from the DASH longitudinal study, Social Psychiatry and Psychiatric Epidemiology: the international journal for research in social and genetic epidemiology and mental health services, Vol: 56, Pages: 2029-2039, ISSN: 0933-7954
PurposeNo known UK empirical research has investigated prospective associations between ambient air pollutants and conduct problems in adolescence. Ethnic minority children are disproportionately exposed to structural factors that could moderate any observed relationships. This prospective study examined whether exposure to PM2.5 and NO2 concentrations is associated with conduct problems in adolescence, and whether racism or ethnicity moderate such associations.MethodsLongitudinal associations between annual mean estimated PM2.5 and NO2 concentrations at the residential address and trajectories of conduct problems, and the potential influence of racism and ethnicity were examined school-based sample of 4775 participants (2002–2003 to 2005–2006) in London, using growth curve models.ResultsOverall, in the fully adjusted model, exposure to lower concentrations of PM2.5 and NO2 was associated with a decrease in conduct problems during adolescence, while exposure to higher concentrations was associated with a flattened trajectory of conduct symptoms. Racism amplified the effect of PM2.5 (β = 0.05 (95% CI 0.01 to 0.10, p < 0.01)) on adolescent trajectories of conduct problems over time. At higher concentrations of PM2.5, there was a divergence of trajectories of adolescent conduct problems between ethnic minority groups, with White British and Black Caribbean adolescents experiencing an increase in conduct problems over time.ConclusionThese findings suggest that the intersections between air pollution, ethnicity, and racism are important influences on the development of conduct problems in adolescence.
Reuben A, Arseneault L, Beddows A, et al., 2021, Association of Air Pollution Exposure in Childhood and Adolescence With Psychopathology at the Transition to Adulthood, JAMA NETWORK OPEN, Vol: 4, ISSN: 2574-3805
- Author Web Link
- Citations: 11
Latham RM, Kieling C, Arseneault L, et al., 2021, Childhood exposure to ambient air pollution and predicting individual risk of depression onset in UK adolescents, JOURNAL OF PSYCHIATRIC RESEARCH, Vol: 138, Pages: 60-67, ISSN: 0022-3956
- Author Web Link
- Citations: 13
Hicks W, Beevers S, Tremper A, et al., 2021, Quantification of non-exhaust particulate matter traffic emissions and the impact of COVID-19 lockdown at London Marylebone Road, Atmosphere, Vol: 12, Pages: 1-19, ISSN: 2073-4433
This research quantifies current sources of non-exhaust particulate matter traffic emissions in London using simultaneous, highly time-resolved, atmospheric particulate matter mass and chemical composition measurements. The measurement campaign ran at Marylebone Road (roadside) and Honor Oak Park (background) urban monitoring sites over a 12-month period between 1 September 2019 and 31 August 2020. The measurement data has been used to determine the traffic increment (roadside – background) and covers a range of meteorological conditions, seasons and driving styles, as well as the influence of the COVID-19 ‘lockdown’ on non-exhaust concentrations. Non-exhaust PM10 concentrations are calculated using chemical tracer scaling factors for brake wear (barium), tyre wear (zinc) and resuspension (silicon) and as average vehicle fleet non-exhaust emission factors, using a CO2 ‘dilution approach’. The effect of lockdown, which saw a 32% reduction in traffic volume and a 15% increase in average speed on Marylebone Road, resulted in lower PM10 and PM2.5 traffic increments and brake wear concentrations, but similar tyre and resuspension concentrations, confirming that factors that determine non-exhaust emissions are complex. Brake wear was found to be the highest average non-exhaust emission source. In addition, results indicated that non-exhaust emission factors are dependent upon speed and road surface wetness conditions. Further statistical analysis incorporating a wider variability in vehicle mix, speeds and meteorological conditions, as well as advanced source apportionment of the PM measurement data, will be undertaken to enhance our understanding of these important vehicle sources.
Bakolis I, Hammoud R, Stewart R, et al., 2020, Mental health consequences of urban air pollution: prospective population-based longitudinal survey, Social Psychiatry and Psychiatric Epidemiology: the international journal for research in social and genetic epidemiology and mental health services, Vol: 56, Pages: 1587-1599, ISSN: 0933-7954
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.
Clark S, Alli AS, Brauer M, et al., 2020, High-resolution spatiotemporal measurement of air and environmental noise pollution in sub-Saharan African cities: Pathways to Equitable Health Cities Study protocol for Accra, Ghana, BMJ Open, Vol: 10, ISSN: 2044-6055
Introduction: Air and noise pollution are emerging environmental health hazards in African cities, with potentially complex spatial and temporal patterns. Limited local data is a barrier to the formulation and evaluation of policies to reduce air and noise pollution. Methods and analysis: We designed a year-long measurement campaign to characterize air and noise pollution and their sources at high-resolution within the Greater Accra Metropolitan Area, Ghana. Our design utilizes a combination of fixed (year-long, n = 10) and rotating (week-long, n = ~130) sites, selected to represent a range of land uses and source influences (e.g. background, road-traffic, commercial, industrial, and residential areas, and various neighbourhood socioeconomic classes). We will collect data on fine particulate matter (PM2.5), nitrogen oxides (NOx), weather variables, sound (noise level and audio) along with street-level time-lapse images. We deploy low-cost, low-power, lightweight monitoring devices that are robust, socially unobtrusive, and able to function in the Sub-Saharan African (SSA) climate. We will use state-of-the-art methods, including spatial statistics, deep/machine learning, and processed-based emissions modelling, to capture highly resolved temporal and spatial variations in pollution levels across Accra and to identify their potential sources. This protocol can serve as a prototype for other SSA cities. Ethics and dissemination: This environmental study was deemed exempt from full ethics review at Imperial College London and the University of Massachusetts Amherst; it was approved by the University of Ghana Ethics Committee. This protocol is designed to be implementable in SSA cities to map environmental pollution to inform urban planning decisions to reduce health harming exposures to air and noise pollution. It will be disseminated through local stakeholder engagement (public and private sectors), peer-reviewed publications, contribution to policy documents, media, a
Samoli E, Butland BK, Rodopoulou S, et al., 2020, The impact of measurement error in modeled ambient particles exposures on health effect estimates in multilevel analysis: A simulation study, ENVIRONMENTAL EPIDEMIOLOGY, Vol: 4
- Author Web Link
- Citations: 7
Butland BK, Samoli E, Atkinson RW, et al., 2020, Comparing the performance of air pollution models for nitrogen dioxide and ozone in the context of a multilevel epidemiological analysis, ENVIRONMENTAL EPIDEMIOLOGY, Vol: 4
- Author Web Link
- Citations: 14
Desouza CD, Marsh DJ, Beevers SD, et al., 2020, Real-world emissions from non-road mobile machinery in London, Atmospheric Environment, Vol: 223, ISSN: 1352-2310
The 2016 London atmospheric emissions inventory estimates that, the construction sector contributes 34% of the total PM10 and 7% of the total NOX – the largest and 5th largest sources, respectively. Recent on-road light duty diesel vehicle emission tests have shown significant differences between real-world NOX emissions compared with results from laboratory based regulatory tests. The aim of this study was therefore to quantify the ‘real-world’ tail-pipe NOX, CO2, and particle emissions, for 30 of the most commonly used construction machines in London under normal working conditions. The highest NOX emissions (g/kWh) were from theolder engines (Stage III-A ~4.88 g/kWh and III-B ~4.61 g/kWh), these were reduced significantly (~78%) in the newer (Stage IV ~1.05 g/kWh) engines due to more advanced engine management systems and exhaust after treatment. One Stage IV machine emitted NOX similar to a Stage III-B machine, the failure of this SCR was only detectable using PEMS as no warning was given by the machine. Higher NOX conformity factors were observed for Stage IV machines, due to the lower NOX emission standards, which these machines must adhere to. On average, Stage III-B machines (~525 g/kWh) emitted the lowest levels of CO2 emissions, compared to Stage III-A (~875 g/kWh) and Stage IV (~575 g/kWh) machines. Overall, a statistically significant (~41%) decrease was observed in the CO2 emissions (g/kWh) between Stage III-A and III-B machines, while no statistically significant difference was found between Stage III-B and IV machines. Particle mass measurements, which were only measured from generators, showed that generators of all engine sizes were within their respective Stage III-A emission standards. A 95% reduction in NOX and 2 orders of magnitude reduction in particle number was observed for a SCR-DPF retrofitted generator, compared to the same generator prior to exhaust gas after-treatment strategy.
Pettit C, Wentz E, Randolph B, et al., 2020, Tackling the Challenge of Growing Cities: An Informed Urbanisation Approach, OPEN CITIES | OPEN DATA: COLLABORATIVE CITIES IN THE INFORMATION ERA, Editors: Hawken, Han, Pettit, Publisher: PALGRAVE MACMILLAN, Pages: 197-219, ISBN: 978-981-13-6604-8
Beevers SD, Williams ML, 2020, Traffic-related air pollution and exposure assessment, Traffic-Related Air Pollution, Pages: 137-162, ISBN: 9780128181225
This chapter begins with a simple exposure definition, then discusses air pollution’s impacts on health and associated legislation, which frames the spatial and temporal scales needed to correctly address human exposure. It goes on to discuss exposure pathways, in particular living close to transport sources and to discuss the different microenvironments to which people are exposed; car, bus, train, underground, indoor and outdoor, and whilst walking and cycling. Using examples in London and the United Kingdom, the spatial and temporal variation of NOx, NO2, PM2.5, and O3 is then described. Finally, a section on exposure assessment methods covers fixed-site monitoring, land use regression (LUR), satellite remote sensing, atmospheric dispersion models, microenvironmental and personal exposure models, and personal monitoring.
Smith RB, Beevers SD, Gulliver J, et al., 2020, Impacts of air pollution and noise on risk of preterm birth and stillbirth in London, Environment International, Vol: 134, ISSN: 0160-4120
BackgroundEvidence for associations between ambient air pollution and preterm birth and stillbirth is inconsistent. Road traffic produces both air pollutants and noise, but few studies have examined these co-exposures together and none to date with all-cause or cause-specific stillbirths.ObjectivesTo analyse the relationship between long-term exposure to air pollution and noise at address level during pregnancy and risk of preterm birth and stillbirth.MethodsThe study population comprised 581,774 live and still births in the Greater London area, 2006–2010. Outcomes were preterm birth (<37 completed weeks gestation), all-cause stillbirth and cause-specific stillbirth. Exposures during pregnancy to particulate matter with diameter <2.5 μm (PM2.5) and <10 μm (PM10), ozone (O3), primary traffic air pollutants (nitrogen dioxide, nitrogen oxides, PM2.5 from traffic exhaust and traffic non-exhaust), and road traffic noise were estimated based on maternal address at birth.ResultsAn interquartile range increase in O3 exposure was associated with elevated risk of preterm birth (OR 1.15 95% CI: 1.11, 1.18, for both Trimester 1 and 2), all-cause stillbirth (Trimester 1 OR 1.17 95% CI: 1.07, 1.27; Trimester 2 OR 1.20 95% CI: 1.09, 1.32) and asphyxia-related stillbirth (Trimester 1 OR 1.22 95% CI: 1.01, 1.49). Odds ratios with the other air pollutant exposures examined were null or <1, except for primary traffic non-exhaust related PM2.5, which was associated with 3% increased odds of preterm birth (Trimester 1) and 7% increased odds stillbirth (Trimester 1 and 2) when adjusted for O3. Elevated risk of preterm birth was associated with increasing road traffic noise, but only after adjustment for certain air pollutant exposures.DiscussionOur findings suggest that exposure to higher levels of O3 and primary traffic non-exhaust related PM2.5 during pregnancy may increase risk of preterm birth and stillbirth; and a possible relationship between long-term traff
Mudway IS, Dundas I, Wood HE, et al., 2019, Impact of London's low emission zone on air quality and children's respiratory health, The Lancet Public Health, Vol: 4, Pages: e28-e40, ISSN: 2468-2667
BACKGROUND: Low emission zones (LEZ) are an increasingly common, but unevaluated, intervention aimed at improving urban air quality and public health. We investigated the impact of London's LEZ on air quality and children's respiratory health.METHODS: We did a sequential annual cross-sectional study of 2164 children aged 8-9 years attending primary schools between 2009-10 and 2013-14 in central London, UK, following the introduction of London's LEZ in February, 2008. We examined the association between modelled pollutant exposures of nitrogen oxides (including nitrogen dioxide [NO2]) and particulate matter with a diameter of less than 2·5 μm (PM2·5) and less than 10 μm (PM10) and lung function: postbronchodilator forced expiratory volume in 1 s (FEV1, primary outcome), forced vital capacity (FVC), and respiratory or allergic symptoms. We assigned annual exposures by each child's home and school address, as well as spatially resolved estimates for the 3 h (0600-0900 h), 24 h, and 7 days before each child's assessment, to isolate long-term from short-term effects.FINDINGS: The percentage of children living at addresses exceeding the EU limit value for annual NO2 (40 μg/m3) fell from 99% (444/450) in 2009 to 34% (150/441) in 2013. Over this period, we identified a reduction in NO2 at both roadside (median -1·35 μg/m3 per year; 95% CI -2·09 to -0·61; p=0·0004) and background locations (-0·97; -1·56 to -0·38; p=0·0013), but not for PM10. The effect on PM2·5 was equivocal. We found no association between postbronchodilator FEV1 and annual residential pollutant attributions. By contrast, FVC was inversely correlated with annual NO2 (-0·0023 L/μg per m3; -0·0044 to -0·0002; p=0·033) and PM10 (-0·0090 L/μg per m3; -0·0175 to -0·0005; p=0·038).INTERPRETATION: Within London's LEZ, a smaller lung volume in children was associated
Newbury JB, Arseneault L, Beevers S, et al., 2019, Association of Air Pollution Exposure With Psychotic Experiences During Adolescence, JAMA Psychiatry, Vol: 76, Pages: 614-623, ISSN: 2168-622X
Importance Urbanicity is a well-established risk factor for clinical (eg, schizophrenia) and subclinical (eg, hearing voices and paranoia) expressions of psychosis. To our knowledge, no studies have examined the association of air pollution with adolescent psychotic experiences, despite air pollution being a major environmental problem in cities.Objectives To examine the association between exposure to air pollution and adolescent psychotic experiences and test whether exposure mediates the association between urban residency and adolescent psychotic experiences.Design, Setting, and Participants The Environmental-Risk Longitudinal Twin Study is a population-based cohort study of 2232 children born during the period from January 1, 1994, through December 4, 1995, in England and Wales and followed up from birth through 18 years of age. The cohort represents the geographic and socioeconomic composition of UK households. Of the original cohort, 2066 (92.6%) participated in assessments at 18 years of age, of whom 2063 (99.9%) provided data on psychotic experiences. Generation of the pollution data was completed on October 4, 2017, and data were analyzed from May 4 to November 21, 2018.Exposures High-resolution annualized estimates of exposure to 4 air pollutants—nitrogen dioxide (NO2), nitrogen oxides (NOx), and particulate matter with aerodynamic diameters of less than 2.5 (PM2.5) and less than 10 μm (PM10)—were modeled for 2012 and linked to the home addresses of the sample plus 2 commonly visited locations when the participants were 18 years old.Main Outcomes and Measures At 18 years of age, participants were privately interviewed regarding adolescent psychotic experiences. Urbanicity was estimated using 2011 census data.Results Among the 2063 participants who provided data on psychotic experiences, sex was evenly distributed (52.5% female). Six hundred twenty-three participants (30.2%) had at least 1 psychotic experience from 12 to 18 years of ag
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