David Dajnak

Development of an open-source road traffic noise model for exposure assessment

This paper describes the development of a model for assessing TRAffic Noise EXposure (TRANEX) in an open-source geographic information system. Instead of using proprietary software we developed our own model for two main reasons: 1) so that the treatment of source geometry, traffic information (flows/speeds/spatially varying diurnal traffic profiles) and receptors matched as closely as possible to that of the air pollution modelling being undertaken in the TRAFFIC project, and 2) to optimize model performance for practical reasons of needing to implement a noise model with detailed source geometry, over a large geographical area, to produce noise estimates at up to several million address locations, with limited computing resources. To evaluate TRANEX, noise estimates were compared with noise measurements made in the British cities of Leicester and Norwich. High correlation was seen between modelled and measured LAeq,1hr (Norwich: r?=?0.85, p?=?.000; Leicester: r?=?0.95, p?=?.000) with average model errors of 3.1?dB. TRANEX was used to estimate noise exposures (LAeq,1hr, LAeq,16hr, Lnight) for the resident population of London (2003-2010). Results suggest that 1.03 million (12%) people are exposed to daytime road traffic noise levels???65?dB(A) and 1.63 million (19%) people are exposed to night-time road traffic noise levels???55?dB(A). Differences in noise levels between 2010 and 2003 were on average relatively small: 0.25?dB (standard deviation: 0.89) and 0.26?dB (standard deviation: 0.87) for LAeq,16hr and Lnight. Display Omitted Adaptation of the Calculation of Road Traffic Noise method for exposure assessment.Freely available open-source software (R with PostgreSQL and GRASS GIS).Model estimates compared well to noise measurements (r: ~0.85-0.95).Noise level exposures modelled for 8.61 million London residents (2003-2010).Over 1 million residents exposed to high daytime and night-time noise levels.

Spatial and temporal associations of road traffic noise and air pollution in London: Implications for epidemiological studies

Road traffic gives rise to noise and air pollution exposures, both of which are associated with adverse health effects especially for cardiovascular disease, but mechanisms may differ. Understanding the variability in correlations between these pollutants is essential to understand better their separate and joint effects on human health. We explored associations between modelled noise and air pollutants using different spatial units and area characteristics in London in 2003-2010. We modelled annual average exposures to road traffic noise (LAeq,24h, Lden, LAeq,16h, Lnight) for ~190,000 postcode centroids in London using the UK Calculation of Road Traffic Noise (CRTN) method. We used a dispersion model (KCLurban) to model nitrogen dioxide, nitrogen oxide, ozone, total and the traffic-only component of particulate matter ≤2.5μm and ≤10μm. We analysed noise and air pollution correlations at the postcode level (~50 people), postcodes stratified by London Boroughs (~240,000 people), neighbourhoods (Lower layer Super Output Areas) (~1600 people), 1km grid squares, air pollution tertiles, 50m, 100m and 200m in distance from major roads and by deprivation tertiles. Across all London postcodes, we observed overall moderate correlations between modelled noise and air pollution that were stable over time (Spearmans rho range: |0.34-0.55|). Correlations, however, varied considerably depending on the spatial unit: largest ranges were seen in neighbourhoods and 1km grid squares (both Spearmans rho range: |0.01-0.87|) and was less for Boroughs (Spearmans rho range: |0.21-0.78|). There was little difference in correlations between exposure tertiles, distance from road or deprivation tertiles. Associations between noise and air pollution at the relevant geographical unit of analysis need to be carefully considered in any epidemiological analysis, in particular in complex urban areas. Low correlations near roads, however, suggest that independent effects of road noise and traffic-related air pollution can be reliably determined within London.

Long-Term Exposure to Primary Traffic Pollutants and Lung Function in Children: Cross-Sectional Study and Meta-Analysis

Background There is widespread concern about the possible health effects of traffic-related air pollution. Nitrogen dioxide (NO2) is a convenient marker of primary pollution. We investigated the associations between lung function and current residential exposure to a range of air pollutants (particularly NO2, NO, NOx and particulate matter) in London children. Moreover, we placed the results for NO2 in context with a meta-analysis of published estimates of the association. Methods and Findings Associations between primary traffic pollutants and lung function were investigated in 4884 children aged 9–10 years who participated in the Child Heart and Health Study in England (CHASE). A systematic literature search identified 13 studies eligible for inclusion in a meta-analysis. We combined results from the meta-analysis with the distribution of the values of FEV1 in CHASE to estimate the prevalence of children with abnormal lung function (FEV1<80% of predicted value) expected under different scenarios of NO2 exposure. In CHASE, there were non-significant inverse associations between all pollutants except ozone and both FEV1 and FVC. In the meta-analysis, a 10 μg/m3 increase in NO2 was associated with an 8 ml lower FEV1 (95% CI: -14 to -1 ml; p: 0.016). The observed effect was not modified by a reported asthma diagnosis. On the basis of these results, a 10 μg/m3 increase in NO2 level would translate into a 7% (95% CI: 4% to 12%) increase of the prevalence of children with abnormal lung function. Conclusions Exposure to traffic pollution may cause a small overall reduction in lung function and increase the prevalence of children with clinically relevant declines in lung function.

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.

Impact of London's road traffic air and noise pollution on birth weight: retrospective population based cohort study

Abstract Objective To investigate the relation between exposure to both air and noise pollution from road traffic and birth weight outcomes. Design Retrospective population based cohort study. Setting Greater London and surrounding counties up to the M25 motorway (2317 km2), UK, from 2006 to 2010. Participants 540 365 singleton term live births. Main outcome measures Term low birth weight (LBW), small for gestational age (SGA) at term, and term birth weight. Results Average air pollutant exposures across pregnancy were 41 μg/m3 nitrogen dioxide (NO2), 73 μg/m3 nitrogen oxides (NOx), 14 μg/m3 particulate matter with aerodynamic diameter <2.5 μm (PM2.5), 23 μg/m3 particulate matter with aerodynamic diameter <10 μm (PM10), and 32 μg/m3 ozone (O3). Average daytime (LAeq,16hr) and night-time (Lnight) road traffic A-weighted noise levels were 58 dB and 53 dB respectively. Interquartile range increases in NO2, NOx, PM2.5, PM10, and source specific PM2.5 from traffic exhaust (PM2.5 traffic exhaust) and traffic non-exhaust (brake or tyre wear and resuspension) (PM2.5 traffic non-exhaust) were associated with 2% to 6% increased odds of term LBW, and 1% to 3% increased odds of term SGA. Air pollutant associations were robust to adjustment for road traffic noise. Trends of decreasing birth weight across increasing road traffic noise categories were observed, but were strongly attenuated when adjusted for primary traffic related air pollutants. Only PM2.5 traffic exhaust and PM2.5 were consistently associated with increased risk of term LBW after adjustment for each of the other air pollutants. It was estimated that 3% of term LBW cases in London are directly attributable to residential exposure to PM2.5>13.8 μg/m3during pregnancy. Conclusions The findings suggest that air pollution from road traffic in London is adversely affecting fetal growth. The results suggest little evidence for an independent exposure-response effect of traffic related noise on birth weight outcomes.

Traffic pollution and the incidence of cardiorespiratory outcomes in an adult cohort in London.

Objectives The epidemiological evidence for adverse health effects of long-term exposure to air and noise pollution from traffic is not coherent. Further, the relative roles of background versus near traffic pollution concentrations in this process are unclear. We investigated relationships between modelled concentrations of air and noise pollution from traffic and incident cardiorespiratory disease in London. Methods Among 211 016 adults aged 40–79 years registered in 75 Greater London practices between 2005 and 2011, the first diagnosis for a range of cardiovascular and respiratory outcomes were identified from primary care and hospital records. Annual baseline concentrations for nitrogen oxide (NOx), particulate matter with a median aerodynamic diameter <2.5 μm (PM2.5) attributable to exhaust and non-exhaust sources, traffic intensity and noise were estimated at 20 m2 resolution from dispersion models, linked to clinical data via residential postcode. HRs were adjusted for confounders including smoking and area deprivation. Results The largest observed associations were between traffic-related air pollution and heart failure (HR=1.10 for 20 μg/m3 change in NOx, 95% CI 1.01 to 1.21). However, no other outcomes were consistently associated with any of the pollution indicators, including noise. The greater variations in modelled air pollution from traffic between practices, versus within, hampered meaningful fine spatial scale analyses. Conclusions The associations observed with heart failure may suggest exacerbatory effects rather than underlying chronic disease. However, the overall failure to observe wider associations with traffic pollution may reflect that exposure estimates based on residence inadequately represent the relevant pattern of personal exposure, and future studies must address this issue.

Air pollution, ethnicity and telomere length in east London schoolchildren: An observational study.

BACKGROUND Short telomeres are associated with chronic disease and early mortality. Recent studies in adults suggest an association between telomere length and exposure to particulate matter, and that ethnicity may modify the relationship. However associations in children are unknown. OBJECTIVES We examined associations between air pollution and telomere length in an ethnically diverse group of children exposed to high levels of traffic derived pollutants, particularly diesel exhaust, and to environmental tobacco smoke. METHODS Oral DNA from 333 children (8-9years) participating in a study on air quality and respiratory health in 23 inner city London schools was analysed for relative telomere length using monochrome multiplex qPCR. Annual, weekly and daily exposures to nitrogen oxides and particulate matter were obtained from urban dispersion models (2008-10) and tobacco smoke by urinary cotinine. Ethnicity was assessed by self-report and continental ancestry by analysis of 28 random genomic markers. We used linear mixed effects models to examine associations with telomere length. RESULTS Telomere length increased with increasing annual exposure to NOx (model coefficient 0.003, [0.001, 0.005], p<0.001), NO2 (0.009 [0.004, 0.015], p<0.001), PM2.5 (0.041, [0.020, 0.063], p<0.001) and PM10 (0.096, [0.044, 0.149], p<0.001). There was no association with environmental tobacco smoke. Telomere length was increased in children reporting black ethnicity (22% [95% CI 10%, 36%], p<0.001) CONCLUSIONS: Pollution exposure is associated with longer telomeres in children and genetic ancestry is an important determinant of telomere length. Further studies should investigate both short and long-term associations between pollutant exposure and telomeres in childhood and assess underlying mechanisms.

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.

Most London hospitals and clinics exceed air pollution limits

More than half of London’s NHS facilities are blanketed in air pollution that is above legal limits, shows new analysis jointly published by King’s College London and the UK Health Alliance on Climate Change. Health professionals are having to care for their patients in environments where air pollution could aggravate existing illnesses. NHS staff are among those exposed to this health risk, but it is patients’ health that is of most concern, especially children’s. Air pollutants, and in particular fine particles and nitrogen dioxide, damage our health throughout our lifetime, from before birth and well into old age. Robust scientific evidence has linked poor air quality to an increased prevalence of ischaemic heart disease, cerebrovascular accidents, chronic obstructive pulmonary disease, asthma, and lung cancer.1 Emerging evidence indicates a link between exposure to air pollution and type 2 diabetes, obesity, and dementia.2 Toxins and particulates are pumped into the air by our cars and power plants, damaging our health in the short term. In the long term the same activities produce …

The Lancet Countdown on health benefits from the UK Climate Change Act: a modelling study for Great Britain

BACKGROUND Climate change poses a dangerous and immediate threat to the health of populations in the UK and worldwide. We aimed to model different scenarios to assess the health co-benefits that result from mitigation actions. METHODS In this modelling study, we combined a detailed techno-economic energy systems model (UK TIMES), air pollutant emission inventories, a sophisticated air pollution model (Community Multi-scale Air Quality), and previously published associations between concentrations and health outcomes. We used four scenarios and focused on the air pollution implications from fine particulate matter (PM2·5), nitrogen dioxide (NO2) and ozone. The four scenarios were baseline, which assumed no further climate actions beyond those already achieved and did not meet the UKs Climate Change Act (at least an 80% reduction in carbon dioxide equivalent emissions by 2050 compared with 1990) target; nuclear power, which met the Climate Change Act target with a limited increase in nuclear power; low-greenhouse gas, which met the Climate Change Act target without any policy constraint on nuclear build; and a constant scenario that held 2011 air pollutant concentrations constant until 2050. We predicted the health and economic impacts from air pollution for the scenarios until 2050, and the inequalities in exposure across different socioeconomic groups. FINDINGS NO2 concentrations declined leading to 4 892 000 life-years saved for the nuclear power scenario and 7 178 000 life-years saved for the low-greenhouse gas scenario from 2011 to 2154. However, the associations that we used might overestimate the effects of NO2 itself. PM2·5 concentrations in Great Britain are predicted to decrease between 42% and 44% by 2050 compared with 2011 in the scenarios that met the Climate Change Act targets, especially those from road traffic and off-road machinery. These reductions in PM2·5 are tempered by a 2035 peak (and subsequent decline) in biomass (wood burning), and by a large, projected increase in future demand for transport leading to potential increases in non-exhaust particulate matter emissions. The potential use of biomass in poorly controlled technologies to meet the Climate Change Act commitments would represent an important missed opportunity (resulting in 472 000 more life-years lost from PM2·5 in the low-greenhouse gas scenario and 1 122 000 more life-years lost in the nuclear power scenario from PM2·5 than the baseline scenario). Although substantial overall improvements in absolute amounts of exposure are seen compared with 2011, these outcomes mask the fact that health inequalities seen (in which socioeconomically disadvantaged populations are among the most exposed) are projected to be maintained up to 2050. INTERPRETATION The modelling infrastructure created will help future researchers explore a wider range of climate policy scenarios, including local, European, and global scenarios. The need to strengthen the links between climate change policy objectives and public health imperatives, and the benefits to societal wellbeing that might result is urgent. FUNDING National Institute for Health Research.