THE IMPORTANCE OF DIRECTLY EMITTED NITROGEN DIOXIDE FROM ROAD VEHICLES TO URBAN AIR QUALITY IN THE UK

ABSTRACT Recent analyses of comprehensive ambient air pollution measurements in London have quantified the proportion of nitrogen oxides (NO X ) in vehicle exhausts that is emitted as nitrogen dioxide (NO 2 ). The analyses show that a greater proportion of NO X is emitted directly as NO 2 than previously thought. For the 43 monitoring sites considered, the mean primary NO 2 volume fraction was calculated to be 11.2 %. Emissions of primary NO 2 of this magnitude appear to explain approximately 21 % of measured NO 2 concentrations on average. However, at many congested locations with a high proportion of diesel vehicles, primary NO 2 emissions are thought to explain over 30 % of observed concentrations. For high percentile values of NO 2 , the primary NO 2 contribution can dominate ambient concentrations. These results have implications for the management of air quality in urban areas since it is likely that directly emitted NO 2 would respond differently to NO X control measures compared with that chemically produced in the atmosphere. In particular, the source apportionment of NO 2 concentrations can be very different to NO X close to roads in London. The results also have implications for dispersion modelling studies of NO 2 , where it is generally assumed that a fixed 5.0 % of the NO X emitted by vehicles is in the form of NO 2 . The implications of the increased use of particle traps on the London bus fleet that produce NO 2 to assist in the oxidation of particles is also assessed, together with the potential effects of the London Congestion Charging Scheme

Linking e-health records, patient-reported symptoms and environmental exposure data to characterise and model COPD exacerbations: protocol for the COPE study.

INTRODUCTION: Relationships between exacerbations of chronic obstructive pulmonary disease (COPD) and environmental factors such as temperature, humidity and air pollution are not well characterised, due in part to oversimplification in the assignment of exposure estimates to individuals and populations. New developments in miniature environmental sensors mean that patients can now carry a personal air quality monitor for long periods of time as they go about their daily lives. This creates the potential for capturing a direct link between individual activities, environmental exposures and the health of patients with COPD. Direct associations then have the potential to be scaled up to population levels and tested using advanced human exposure models linked to electronic health records. METHODS AND ANALYSIS: This study has 5 stages: (1) development and deployment of personal air monitors; (2) recruitment and monitoring of a cohort of 160 patients with COPD for up to 6 months with recruitment of participants through the Clinical Practice Research Datalink (CPRD); (3) statistical associations between personal exposure with COPD-related health outcomes; (4) validation of a time-activity exposure model and (5) development of a COPD prediction model for London. ETHICS AND DISSEMINATION: The Research Ethics Committee for Camden and Islington has provided ethical approval for the conduct of the study. Approval has also been granted by National Health Service (NHS) Research and Development and the Independent Scientific Advisory Committee. The results of the study will be disseminated through appropriate conference presentations and peer-reviewed journals.This work is funded by the Medical Research Council (MR/L019744/1). MRC-PHE funding has been obtained for a pilot study to collect blood and sputum samples on a subset of 20 participants. Enrolment will take place at The Royal Brompton and Harefield (RBH) and Guy's and St Thomas' (GSTT) NHS Foundation Trusts. Support will be provided by the Respiratory Clinical Research Facility at RBH and the Lane Fox Unit at GSTT. The project is a portfolio adopted by the National Institute for Health Research (NIHR) UK Clinical Research Network (CRN). Additional support was provided by the NIHR Biomedical Research Centre based at GSTT and King's College London.This is the final version of the article. It first appeared from the BMJ Publishing Group via http://dx.doi.org/10.1136/bmjopen-2016-01133

Long-term traffic air and noise pollution in relation to mortality and hospital readmission among myocardial infarction survivors.

BACKGROUND: There is relatively little evidence of health effects of long-term exposure to traffic-related pollution in susceptible populations. We investigated whether long-term exposure to traffic air and noise pollution was associated with all-cause mortality or hospital readmission for myocardial infarction (MI) among survivors of hospital admission for MI. METHODS: Patients from the Myocardial Ischaemia National Audit Project database resident in Greater London (n = 1 8,138) were followed for death or readmission for MI. High spatially-resolved annual average air pollution (11 metrics of primary traffic, regional or urban background) derived from a dispersion model (resolution 20 m × 20 m) and road traffic noise for the years 2003-2010 were used to assign exposure at residence. Hazard ratios (HR, 95% confidence interval (CI)) were estimated using Cox proportional hazards models. RESULTS: Most air pollutants were positively associated with all-cause mortality alone and in combination with hospital readmission. The largest associations with mortality per interquartile range (IQR) increase of pollutant were observed for non-exhaust particulate matter (PM(10)) (HR = 1.05 (95% CI 1.00, 1.10), IQR = 1.1 μg/m(3)); oxidant gases (HR = 1.05 (95% CI 1.00, 1.09), IQR = 3.2 μg/m(3)); and the coarse fraction of PM (HR = 1.05 (95% CI 1.00, 1.10), IQR = 0.9 μg/m(3)). Adjustment for traffic noise only slightly attenuated these associations. The association for a 5 dB increase in road-traffic noise with mortality was HR = 1.02 (95% CI 0.99, 1.06) independent of air pollution. CONCLUSIONS: These data support a relationship of primary traffic and regional/urban background air pollution with poor prognosis among MI survivors. Although imprecise, traffic noise appeared to have a modest association with prognosis independent of air pollution

Analysis of UK and European NOx and VOC emission scenarios in the Defra model intercomparison exercise

This is a PDF file of an unedited manuscript that has been accepted for publication. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertainSimple emission scenarios have been implemented in eight United Kingdom air quality models with the aim of assessing how these models compared when addressing whether photochemical ozone formation in southern England was NOx- or VOC-sensitive and whether ozone precursor sources in the UK or in the Rest of Europe (RoE) were the most important during July 2006. The suite of models included three Eulerian-grid models (three implementations of one of these models), a Lagrangian atmospheric dispersion model and two moving box air parcel models. The assignments as to NOx- or VOC-sensitive and to UK- versus RoE-dominant, turned out to be highly variable and often contradictory between the individual models. However, when the assignments were filtered by model performance on each day, many of the contradictions could be eliminated. Nevertheless, no one model was found to be the 'best' model on all days, indicating that no single air quality model could currently be relied upon to inform policymakers robustly in terms of NOx- versus VOC-sensitivity and UK- versus RoE-dominance on each day. It is important to maintain a diversity in model approaches.Peer reviewedFinal Accepted Versio

Long-term exposure to traffic pollution and hospital admissions in London.

Evidence on the effects of long-term exposure to traffic pollution on health is inconsistent. In Greater London we examined associations between traffic pollution and emergency hospital admissions for cardio-respiratory diseases by applying linear and piecewise linear Poisson regression models in a small-area analysis. For both models the results for children and adults were close to unity. In the elderly, linear models found negative associations whereas piecewise models found non-linear associations characterized by positive risks in the lowest and negative risks in the highest exposure category. An increased risk was observed among those living in areas with the highest socioeconomic deprivation. Estimates were not affected by adjustment for traffic noise. The lack of convincing positive linear associations between primary traffic pollution and hospital admissions agrees with a number of other reports, but may reflect residual confounding. The relatively greater vulnerability of the most deprived populations has important implications for public health

Recruitment of patients with Chronic Obstructive Pulmonary Disease (COPD) from the Clinical Practice Research Datalink (CPRD) for research.

Databases of electronic health records (EHR) are not only a valuable source of data for health research but have also recently been used as a medium through which potential study participants can be screened, located and approached to take part in research. The aim was to assess whether it is feasible and practical to screen, locate and approach patients to take part in research through the Clinical Practice Research Datalink (CPRD). This is a cohort study in primary care. The CPRD anonymised EHR database was searched to screen patients with Chronic Obstructive Pulmonary Disease (COPD) to take part in a research study. The potential participants were contacted via their General Practitioner (GP) who confirmed their eligibility. Eighty two practices across Greater London were invited to the study. Twenty-six (31.7%) practices consented to participate resulting in a pre-screened list of 988 patients. Of these, 632 (63.7%) were confirmed as eligible following the GP review. Two hundred twenty seven (36%) response forms were received by the study team; 79 (34.8%) responded 'yes' (i.e., they wanted to be contacted by the research assistant for more information and to talk about enrolling in the study), and 148 (65.2%) declined participation. This study has shown that it is possible to use EHR databases such as CPRD to screen, locate and recruit participants for research. This method provides access to a cohort of patients while minimising input needed by GPs and allows researchers to examine healthcare usage and disease burden in more detail and in real-life settings

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

Childhood exposure to ambient air pollution and predicting individual risk of depression onset in UK adolescents

Knowledge about early risk factors for major depressive disorder (MDD) is critical to identify those who are at high risk. A multivariable model to predict adolescents’ individual risk of future MDD has recently been developed however its performance in a UK sample was far from perfect. Given the potential role of air pollution in the aetiology of depression, we investigate whether including childhood exposure to air pollution as an additional predictor in the risk prediction model improves the identification of UK adolescents who are at greatest risk for developing MDD. We used data from the Environmental Risk (E-Risk) Longitudinal Twin Study, a nationally representative UK birth cohort of 2,232 children followed to age 18 with 93% retention. Annual exposure to four pollutants – nitrogen dioxide (NO(2)), nitrogen oxides (NO(X)), particulate matter <2.5μm (PM(2.5)) and <10μm (PM(10)) – were estimated at address-level when children were aged 10. MDD was assessed via interviews at age 18. The risk of developing MDD was elevated most for participants with the highest (top quartile) level of annual exposure to NO(X) (adjusted OR=1.43, 95% CI=0.96-2.13) and PM(2.5) (adjusted OR=1.35, 95% CI=0.95-1.92). The separate inclusion of these ambient pollution estimates into the risk prediction model improved model specificity but reduced model sensitivity – resulting in minimal net improvement in model performance. Findings indicate a potential role for childhood ambient air pollution exposure in the development of adolescent MDD but suggest that inclusion of risk factors other than this may be important for improving the performance of the risk prediction model

Associations between exhaust and non-exhaust particulate matter and stroke incidence by stroke subtype in South London

Background: Airborne particulate matter (PM) consists of particles from diverse sources, including vehicle exhausts. Associations between short-term PM changes and stroke incidence have been shown. Cumulative exposures over several months, or years, are less well studied; few studies examined ischaemic subtypes or PM source. Aims: This study combines a high resolution urban air quality model with a population-based stroke register to explore associations between long-term exposure to PM and stroke incidence. Method: Data from the South London Stroke Register from 2005–2012 were included. Poisson regression explored association between stroke incidence and long-term (averaged across the study period) exposure to PM2.5(PM b 2.5 μm diameter) and PM10(PM b 10 μm), nitric oxide, nitrogen dioxide, nitrogen oxides and ozone, at the output area level (average population=309). Estimates were standardised for age and sex and adjusted for socio-economic deprivation. Models were stratified for ischaemic and haemorrhagic strokes and further broken down by Oxford Community Stroke Project classification and Trial of ORG 10172 in Acute Stroke Treatment (TOAST) classification. Results: 1800 strokes were recorded (incidence= 42.6/100,000 person-years). No associations were observed between PM and overall ischaemic or haemorrhagic incidence. For an interquartile range increase in PM2.5, there was a 23% increase in incidence (Incidence rate ratio=1.23 (95%CI: 1.03–1.44)) of total anterior circulation infarcts (TACI) and 20% increase for PM2.5 from exhausts (1.20(1.01–1.41)). Therewere similar associations with PM10, overall (1.21(1.01–1.44)) and from exhausts (1.20(1.01–1.41)). TACI incidence was not associated with non-exhaust sources. There were no associations with other stroke subtypes or pollutants. Conclusion: Outdoor air pollution, particularly that arising from vehicle exhausts, may increase risk of TACI but not other stroke subtypes