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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). [ABSTRACT FROM AUTHOR]

The poor air quality in the London metropolis has sparked our interest in studying the time series dynamics of air pollutants in the city. The dataset consists of roadside and background air quality for seven standard pollutants: nitric oxide (NO), nitrogen dioxide (NO2), oxides of nitrogen (NOx), ozone (O3), particulate matter (PM10 and PM2.5) and sulphur dioxide (SO2), using fractional integration to investigate issues such as persistence, seasonality and time trends in the data. Though we notice a large degree of heterogeneity across pollutants and a persistent behaviour based on a long memory pattern is observed practically in all cases. Seasonality and decreasing linear trends are also found in some cases. The findings in the paper may serve as a guide to air pollution management and European Union (EU) policymakers. [ABSTRACT FROM AUTHOR]

This paper describes one example of how the UK National Air Quality Strategy (NAQS) is implemented in a local urban environment. The paper reviews the beginning of this process, by examining the review and assessment procedures of the NAQS in the London Borough of Barnet. By the application of available UK tools of local air quality management (LAQM), the process began through analysis of the levels of local emissions and progressed onto modelling of current and future air quality. A map showing combined emission hotspot areas for the Borough indicated and higher emission rates occur in the south of the Borough and along the major transport corridors, as road sources dominate emissions. Dispersion modelling studies were also conducted for this purpose, using the screening models GRAM, PGRAM and ADMS Urban for an in-depth assessment. These analyses found that some local point sources and the majority of Borough roads with over 20,000 vehicles per day produced exceedances of the future objectives for air quality for some pollutants. Recommendations for the progression of LAQM in the Borough are made and include the update and expansion of the emissions information held for use in future modelling studies. The paper demonstrates the experience of implementing the Strategy, using the tools and procedures available for this purpose, in a local urban environment that is similar to many in the UK. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Abstract: Air pollution in urban areas has important implications for health and environmental management. Consequently, various methodologies have been developed for its assessment. Traditionally, simple approaches such as the box model or the Gaussian plume have been used to assess urban air quality. The use of Eulerian grid models, which provide a more realistic and comprehensive description of the urban atmosphere, has been increasing over the past few years. This paper reports on the use of the MM5–CMAQ modelling system to predict hourly ozone levels over London, UK. This work represents the first application of MM5–CMAQ in the UK for predicting air pollution levels in London. Domain resolutions of 9km, 3km and 1km (innermost) have been employed for this study. Summer periods in July and August 2002 have been simulated and the predicted results have been compared to several urban background stations across London. Input data for emissions have been derived from the UK National Emissions inventory and from the outputs of the EMIMO emission model. The CBM-IV chemical scheme has been used to simulate the atmospheric reactions for ozone. The model performance has been evaluated with measured data through a range of statistical measures. Although, the MM5–CMAQ model reproduces the ozone temporal trends it was not able to simulate the peak magnitudes consistently. Furthermore, for nighttime the model overestimated the ozone concentrations. The paper discusses the model performance and reasons for these discrepancies in terms of the various input data including emissions and meteorological parameters. [Copyright &y& Elsevier]

Authoritative, trustworthy, continual, automatic hourly air quality monitoring is a relatively recent innovation. The task of reliably identifying long-term trends in air quality is therefore very challenging, as well as complex. Ports are major sources of atmospheric pollution, which is linked to marine traffic and increased road traffic congestion. This study investigated the long-term trends and drivers of atmospheric pollution in the port cities of Houston, London, and Southampton in 2000–2019. Authoritative air quality and meteorological data for seven sites at these three locations were meticulously selected alongside available traffic count data. Data were acquired for sites close to the port and sites that were near the city centre to determine whether the port emissions were influencing different parts of the city. Openair software was used for plots and statistical analyses. Pollutant concentrations at Houston, Southampton and Thurrock (London) slowly reduced over time and did not exceed national limits, in contrast to NO2 and PM10 concentrations at London Marylebone Road. Drivers of atmospheric pollution include meteorology, geographical and temporal variation, and traffic flow. Statistically significant relationships (p < 0.001) between atmospheric pollution concentration and meteorology across most sites were found, but this was not seen with traffic flows in London and Southampton. However, port emissions and the other drivers of atmospheric pollution act together to govern the air quality in the city. [ABSTRACT FROM AUTHOR]

Copyright of Bulletin of the Faculty of Forestry, University of Banja Luka / Glasnik Šumarskog Fakulteta Univerziteta u Banjoj Luci is the property of University of Banja Luka, Faculty of Forestry and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Air pollution contributes to 9400 deaths annually in London and diesel vehicles are considered a major source of lethal air pollutants. Consequently, the UK government announced its intention to ban diesel vehicles by 2040 to achieve a sustainable zero-carbon road transport system. Since no empirical studies have used a bottom-up approach to seek Londoners' views, it is therefore worth investigating the public opinion regarding this forthcoming ban. This paper aims to fill this research gap by taking London as a case study. A survey was designed, and fieldwork was conducted to distribute questionnaires to Londoners. Completed questionnaires were analysed using both quantitative and qualitative methods. The findings revealed that the majority of Londoners would be in favour of the ban if they were sufficiently exposed to the appropriate sources of information and were favourably disposed towards environmental protection measures. The results also showed that Londoners were more likely to switch to electric vehicles (EVs) if they were offered generous incentives and encouraged to use scrappage schemes. The present study makes a strong case for enforcing the ban well before 2040. The significance of this research is to provide clearer signals regarding the future of diesel vehicles, which in turn will strengthen the EV policy and uptake. [ABSTRACT FROM AUTHOR]

The large eddy simulation (LES) code Fluidity was used to simulate the dispersion of NOx traffic emissions along a road in London. The traffic emissions were represented by moving volume sources, one for each vehicle, with time-varying emission rates. Traffic modelling software was used to generate the vehicle movement, while an instantaneous emissions model was used to calculate the NOx emissions at 1 s intervals. The traffic emissions were also modelled as a constant volume source along the length of the road for comparison. A validation of Fluidity against wind tunnel measurements is presented before a qualitative comparison of the LES concentrations with measured roadside concentrations. Fluidity showed an acceptable comparison with the wind tunnel data for velocities and turbulence intensities. The in-canyon tracer concentrations were found to be significantly different between the wind tunnel and Fluidity. This difference was explained by the very high sensitivity of the in-canyon tracer concentrations to the precise release location. Despite this, the comparison showed that Fluidity was able to provide a realistic representation of roadside concentration variations at high temporal resolution, which is not achieved when traffic emissions are modelled as a constant volume source or by Gaussian plume models. [ABSTRACT FROM AUTHOR]

One of the biggest challenges of the COVID-19 pandemic is the heterogeneity in disease severity exhibited amongst patients. Among multiple factors, latest studies suggest vitamin D deficiency and pre-existing health conditions to be major contributors to death from COVID-19. It is known that certain urban form attributes can impact sun exposure and vitamin D synthesis. Also, long-term exposure to air pollution can play an independent role in vitamin D deficiency. We conducted a correlational analysis of urban form and air quality in relation to the demographics and COVID-19 incidence and mortality across 32 London boroughs between March 2020 and January 2021. We found total population, number of residents of Asian ethnicity, 4-year average PM10 levels and road length to be positively correlated with COVID-19 cases and deaths. We also found percentage of households with access to total open space to be negatively correlated with COVID-19 deaths. Our findings link COVID-19 incidence and mortality across London with environmental variables linked to vitamin D status. Our study is entirely based on publicly available data and provides a reference framework for further research as more data are gathered and the syndemic dimension of COVID-19 becomes increasingly relevant in connection to health inequalities within large urban areas. [ABSTRACT FROM AUTHOR]

Ambient air pollution poses a major global public health risk. Lower-cost air quality sensors (LCSs) are increasingly being explored as a tool to understand local air pollution problems and develop effective solutions. A barrier to LCS adoption is potentially larger measurement uncertainty compared to reference measurement technology. The technical performance of various LCSs has been tested in laboratory and field environments, and a growing body of literature on uses of LCSs primarily focuses on proof-of-concept deployments. However, few studies have demonstrated the implications of LCS measurement uncertainties on a sensor network's ability to assess spatiotemporal patterns of local air pollution. Here, we present results from a 2-year deployment of 100 stationary electrochemical nitrogen dioxide (NO 2) LCSs across Greater London as part of the Breathe London pilot project (BL). We evaluated sensor performance using collocations with reference instruments, estimating ∼ 35 % average uncertainty (root mean square error) in the calibrated LCSs, and identified infrequent, multi-week periods of poorer performance and high bias during summer months. We analyzed BL data to generate insights about London's air pollution, including long-term concentration trends, diurnal and day-of-week patterns, and profiles of elevated concentrations during regional pollution episodes. These findings were validated against measurements from an extensive reference network, demonstrating the BL network's ability to generate robust information about London's air pollution. In cases where the BL network did not effectively capture features that the reference network measured, ongoing collocations of representative sensors often provided evidence of irregularities in sensor performance, demonstrating how, in the absence of an extensive reference network, project-long collocations could enable characterization and mitigation of network-wide sensor uncertainties. The conclusions are restricted to the specific sensors used for this study, but the results give direction to LCS users by demonstrating the kinds of air pollution insights possible from LCS networks and provide a blueprint for future LCS projects to manage and evaluate uncertainties when collecting, analyzing, and interpreting data. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we have coupled the CMAQ and ADMS air quality models to predict hourly concentrations of NO X , NO2 and O3 for London at a spatial scale of 20 m × 20 m. Model evaluation has demonstrated reasonable agreement with measurements from 80 monitoring sites in London. For NO2 the model evaluation statistics gave 73% of the hourly concentrations within a factor of two of observations, a mean bias of −4.7 ppb and normalised mean bias of −0.17, a RMSE value of 17.7 and an r value of 0.58. The equivalent results for O3 were 61% (FAC2), 2.8 ppb (MB), 0.15 (NMB), 12.1 (RMSE) and 0.64 (r). Analysis of the errors in the model predictions by hour of the week showed the need for improvements in predicting the magnitude of road transport related NO X emissions as well as the hourly emissions scaling in the model. These findings are consistent with recent evidence of UK road transport NO X emissions, reported elsewhere. The predictions of wind speed using the WRF model also influenced the model results and contributed to the daytime over prediction of NO X concentrations at the central London background site at Kensington and Chelsea. An investigation of the use of a simple NO–NO2–O3 chemistry scheme showed good performance close to road sources, and this is also consistent with previous studies. The coupling of the two models raises an issue of emissions double counting. Here, we have put forward a pragmatic solution to this problem with the result that a median double counting error of 0.42% exists across 39 roadside sites in London. Finally, whilst the model can be improved, the current results show promise and demonstrate that the use of a combination of regional scale and local scale models can provide a practical modelling tool for policy development at intergovernmental, national and local authority level, as well as for use in epidemiological studies. [Copyright &y& Elsevier]

Abstract: This paper addresses the research question “Are more stringent exhaust emissions standards, as applied to light vehicle type approval, resulting in reduced vehicle pollution in an urban area?” The exhaust emissions of a sample of over fifty thousand road vehicles operating in London were measured using roadside remote sensing absorption spectroscopy techniques (infrared and ultraviolet), combined with Automatic Number Plate Recognition for vehicle identification. Levels of carbon monoxide (CO), hydrocarbons (HC), nitric oxide (NO), and smoke (particulate) exhaust emissions are reported by vehicle class, fuel type, and Euro emissions standard. Emissions from petrol cars of each pollutant were all observed to display a statistically significant reduction with the introduction of each successive Euro emissions standard from Euro 1 onwards. However, Euro 2 diesel cars were observed to emit statistically higher rates of NO than either Euro 1 or Euro 3 standard diesel cars. The study also confirms the continuing ‘dieselisation’ of the UK passenger car fleet. Mean NO emissions from Euro 4 diesel cars were found to be 6 times higher than Euro 4 petrol cars, highlighting the need to develop a sound understanding of the current and future ‘in-use’ emissions characteristics of diesel vehicles, and their influence on local air quality. Smoke emissions from TXII London taxis (black cabs) were found to be statistically higher than either earlier TX1 or later TX4 model variants, with possible implications for local air quality policy interventions such as maximum age limits for taxis. [Copyright &y& Elsevier]

Air quality indicators summarize overall concentrations of pollution for an urban area and are calculated from routine monitoring data comprising numerous pollutants measured at many locations. The indicator is constructed by aggregating these data over space and pollutants, typically using the sample mean, median or maximum. We propose an alternative approach based on geostatistical modelling, which allows intervals of uncertainty to be calculated for the spatial aggregation stage, and hence for the final indicator. We then extend our geostatistical model by allowing for the fact that the locations that are chosen for the pollution monitors may depend on the hypothesized concentrations at these locations, a phenomenon which is known as preferential sampling. We assess the effectiveness of our methods by simulation and use them to construct an air quality indicator for Greater London, England, for the month of August 2006. [ABSTRACT FROM AUTHOR]

Abstract: Street-level mean flow and turbulence govern the dispersion of gases away from their sources in urban areas. A suitable reference measurement in the driving flow above the urban canopy is needed to both understand and model complex street-level flow for pollutant dispersion or emergency response purposes. In vegetation canopies, a reference at mean canopy height is often used, but it is unclear whether this is suitable for urban canopies. This paper presents an evaluation of the quality of reference measurements at both roof-top (height = H) and at height z = 9H = 190 m, and their ability to explain mean and turbulent variations of street-level flow. Fast response wind data were measured at street canyon and reference sites during the six-week long DAPPLE project field campaign in spring 2004, in central London, UK, and an averaging time of 10 min was used to distinguish recirculation-type mean flow patterns from turbulence. Flow distortion at each reference site was assessed by considering turbulence intensity and streamline deflection. Then each reference was used as the dependent variable in the model of which decomposes street-level flow into channelling and recirculating components. The high reference explained more of the variability of the mean flow. Coupling of turbulent kinetic energy was also stronger between street-level and the high reference flow rather than the roof-top. This coupling was weaker when overnight flow was stratified, and turbulence was suppressed at the high reference site. However, such events were rare (<1% of data) over the six-week long period. The potential usefulness of a centralised, high reference site in London was thus demonstrated with application to emergency response and air quality modelling. [Copyright &y& Elsevier]

Abstract: The paper describes a field study focused on the dispersion of a traffic-related pollutant within an area close to a busy intersection between two street canyons in Central London. Simultaneous measurements of airflow, traffic flow and carbon monoxide concentrations ([CO]) are used to explore the causes of spatial variability in [CO] over a full range of background wind directions. Depending on the roof-top wind direction, evidence of both flow channelling and recirculation regimes were identified from data collected within the main canyon and the intersection. However, at the intersection, the merging of channelled flows from the canyons increased the flow complexity and turbulence intensity. These features, coupled with the close proximity of nearby queuing traffic in several directions, led to the highest overall time-average measured [CO] occurring at the intersection. Within the main street canyon, the data supported the presence of a helical flow regime for oblique roof-top flows, leading to increased [CO] on the canyon leeward side. Predominant wind directions led to some locations having significantly higher diurnal average [CO] due to being mostly on the canyon leeward side during the study period. For all locations, small changes in the background wind direction could cause large changes in the in-street mean wind angle and local turbulence intensity, implying that dispersion mechanisms would be highly sensitive to small changes in above roof flows. During peak traffic flow periods, concentrations within parallel side streets were approximately four times lower than within the main canyon and intersection which has implications for controlling personal exposure. Overall, the results illustrate that pollutant concentrations can be highly spatially variable over even short distances within complex urban geometries, and that synoptic wind patterns, traffic queue location and building topologies all play a role in determining where pollutant hot spots occur. [Copyright &y& Elsevier]

In this paper we introduce a new method of analysing the relationship between nitrogen dioxide (NO2) and oxides of nitrogen (NOx) concentrations using data from the UK National Air Quality Archive. The study includes analyses of measurements from two different types of site in London, a kerbside site: Cromwell Rd, and three background sites: Bridge Place, London Bloomsbury and West London, over several years (1991–7). The data in some years showed that hourly NO2 concentrations exceeded the UK Standard of 150 ppb. Data were binned, averaged, and polynomials fitted at each site. Analysis of the resulting polynomials was used to estimate reductions in NOx emission required to achieve the National Air Quality Strategy Objective. Examination of the empirical ratio NO2:NOx (the 'yield') gives an indication of the sensitivity of the NO2 to NOx controls and the amount of NO2 that would arise from modelled values of total oxides of nitrogen. The response of NO2 to emission changes is very non-linear, implying 30–45% controls on NOx may be required. [ABSTRACT FROM AUTHOR]

Public transport is commonly associated with benefits such as reducing road traffic congestion and improving air quality. This paper focuses on evaluating the causal impact of a new public transport provision in London, the Jubilee Line Extension (JLE) in 1999, on air quality. Using meteorological normalisation and a regression discontinuity design with time as the forcing variable, we show that the JLE led to only small changes in air pollution at some specific locations; detectable changes in NO x , NO 2 , and O 3 concentrations were found at 63%, 43% and 29% of air pollution monitoring sites, respectively. For those sites where a change in pollution was detected, the responses ranged from −2% to +1% for NO 2 and -1% to 0% for O 3. We calculate that the long-run effects are greater, ranging from −11% to +3% for NO 2 and from −2% to +2% for O 3 at sites that showed a response to the JLE. Aggregating across all sites in London for a city-wide effect, both short and long-run effects were less than 1% or insignificant. We find statistically significant increases in NO 2 and O 3 concentrations at some background sites, but the magnitude of effect is within +1% in the short-run and +3% in the long-run. Our analysis shows that the effect of the JLE on air pollution in some areas was greater than others, however across London the effect was small and this indicates that public transport provision on its own is not an effective strategy to improve air quality. • An increase in public transport supply did not improve air quality at all sites. • Public transport provision on its own is not effective to improve air quality. • Short-run changes in pollution concentrations ranged from −2% to +1%. • Long-run changes in pollution concentrations may range from −11% to +3%. [ABSTRACT FROM AUTHOR]

Outdoor air pollution remains a major environmental threat to the public, especially those who reside in highly urbanised areas. Recent studies have revealed the effectiveness of early-warning mechanisms that enable the public reduce their exposure to air pollutants. This highlights the need for accurate air quality forecasts. However, air quality in many developing and highly urbanised countries remains unmonitored. Hence, a novel spatiotemporal interpolation modelling approach based on a deep learning and wavelet pre-processing technique was proposed in this paper. In more detail, Long Short-term Memory (LSTM) neural networks and Discrete Wavelet Transformation (DWT) were utilised to model the spatial variability of hourly NO 2 levels at six urban sites in Central London, the United Kingdom. The models were trained using only the NO 2 concentration data from the neighbouring sites. Benchmark models such as plain LSTM and Multilayer Perceptron (MLP) models were also developed to validate the effectiveness of the proposed models. The proposed wavelet-based spatiotemporal models were found to provide superior forecasting results, explaining 77% to 93% of the variability of the actual NO 2 concentration levels at most sites. The overall results reveal the very promising potential of the proposed models for the spatiotemporal characterisation of outdoor air pollution. [ABSTRACT FROM AUTHOR]

In July 2017 three research flights circumnavigating the megacity of London were conducted as a part of the STANCO training school for students and early career researchers organised by EUFAR (European Facility for Airborne Research). Measurements were made from the UK's Facility for Airborne Atmospheric Measurements (FAAM) BAe-146-301 atmospheric research aircraft with the aim to sample, characterise and quantify the impact of megacity outflow pollution on air quality in the surrounding region. Conditions were extremely favourable for airborne measurements, and all three flights were able to observe clear pollution events along the flight path. A small change in wind direction provided sufficiently different air mass origins over the 2 d such that a distinct pollution plume from London, attributable marine emissions and a double-peaked dispersed area of pollution resulting from a combination of local and transported emissions were measured. We were able to analyse the effect of London emissions on air quality in the wider region and the extent to which local sources contribute to pollution events. The background air upwind of London was relatively clean during both days; concentrations of CO were 88–95 ppbv, total (measured) volatile organic compounds (VOCs) were 1.6–1.8 ppbv and NOx was 0.7–0.8 ppbv. Downwind of London, we encountered elevations in all species with CO>100 ppbv, VOCs 2.8–3.8 ppbv, CH4>2080 ppbv and NOx>4 ppbv, and peak concentrations in individual pollution events were higher still. Levels of O3 were inversely correlated with NOx during the first flight, with O3 concentrations of 37 ppbv upwind falling to ∼26 ppbv in the well-defined London plume. Total pollutant fluxes from London were estimated through a vertical plane downwind of the city. Our calculated CO2 fluxes are within the combined uncertainty of those estimated previously, but there was a greater disparity in our estimates of CH4 and CO. On the second day, winds were lighter and downwind O3 concentrations were elevated to ∼39 –43 ppbv (from ∼32 to 35 ppbv upwind), reflecting the contribution of more aged pollution to the regional background. Elevations in pollutant concentrations were dispersed over a wider area than the first day, although we also encountered a number of clear transient enhancements from local sources. This series of flights demonstrated that even in a region of megacity outflow, such as the south-east of the UK, local fresh emissions and more distant UK sources of pollution can all contribute substantially to pollution events. In the highly complex atmosphere around a megacity where a high background level of pollution mixes with a variety of local sources at a range of spatial and temporal scales and atmospheric dynamics are further complicated by the urban heat island, the use of pollutant ratios to track and determine the ageing of air masses may not be valid. The individual sources must therefore all be well-characterised and constrained to understand air quality around megacities such as London. Research aircraft offer that capability through targeted sampling of specific sources and longitudinal studies monitoring trends in emission strength and profiles over time. [ABSTRACT FROM AUTHOR]

Urban particulate matter (PM) enhances airway dendritic cell (DC) maturation in vitro. However, to date, there are no data on the association between exposure to urban PM and DC maturation in vivo. We sought to determine whether exposure of school-age children (8 to 14 y) to PM was associated with expression of CD86, a marker of maturation of airway conventional DCs (cDC). Healthy London school children underwent spirometry and sputum induction. Flow cytometry was used to identify CD86 and CCR7 expression on cDC subsets (CD1c+ cDC2 and CD141+ cDC1). Tertiles of mean annual exposure to PM ≤ 10 microns (PM10) at the school address were determined using the London Air Quality Toolkit model. Tertiles of exposure from the 409 children from 19 schools recruited were; lower (23.1 to 25.6 μg/m3, n = 138), middle (25.6 to 26.8 μg/m3, n = 126), and upper (26.8 to 31.0 μg/m3, n = 145). DC expression was assessed in 164/370 (44%) children who completed sputum induction. The proportion (%) of cDC expressing CD86 in the lower exposure tertile (n = 47) was lower compared with the upper exposure tertile (n = 49); (52% (44 to 70%) vs 66% (51 to 82%), p<0.05). There was a higher percentage of cDC1 cells in the lower tertile of exposure (6.63% (2.48 to 11.64) vs. 2.63% (0.72 to 7.18), p<0.05). Additionally; children in the lower exposure tertile had increased FEV1 compared with children in the upper tertile; (median z-score 0.15 (-0.59 to 0.75) vs. -0.21 (-0.86 to 0.48), p<0.05. Our data reveal that children attending schools in the highest areas of PM exposure in London exhibit increased numbers of "mature" airway cDCs, as evidenced by their expression of the surface marker CD86. This data is supportive of previous in vitro data demonstrating an alteration in the maturation of airway cDCs in response to exposure to pollutants. [ABSTRACT FROM AUTHOR]

In recent years, every winter we face the problem of excessive air pollution in the cities in Poland. This phenomenon is usually called smog and is associated with the concept of acidic smog of London type. However, there is a fundamental difference between the Great Smog of London known from the literature and winter smog episodes in Poland. While in 1952 in London the smog occurred at low atmospheric pressure, in foggy and windless weather conditions, in Poland smog episodes occur most often at the influx of cold, high-pressure air masses from the east in sunny weather. There are also various harmful components of smog - in London it was dust (suspended particulate matter), sulfur dioxide and carbon monoxide, while in Poland it is suspended particulate matter and polyaromatic hydrocarbons, especially benzo(a)pyrene. A common factor is the inversion of temperature in the ground level of the atmosphere. The chemical composition of the "Polish smog" is analyzed in the study justifying the need to distinguish the two types of smog described. [ABSTRACT FROM AUTHOR]

Some air pollution datasets contain multiple variables with a range of measurement units, and combined analysis using positive matrix factorization (PMF) can be problematic but can offer benefits through the greater information content. In this work, a novel method is devised and the source apportionment of a mixed unit dataset (PM 10 mass and number size distribution, NSD) is achieved using a novel two-step approach to PMF. In the first step the PM 10 data are PMF-analysed using a source apportionment approach in order to provide a solution which best describes the environment and conditions considered. The time series G values (and errors) of the PM 10 solution are then taken forward into the second step, where they are combined with the NSD data and analysed in a second PMF analysis. This results in NSD data associated with the apportioned PM 10 factors. We exemplify this approach using data reported in the study of Beddows et al. (2015), producing one solution which unifies the two separate solutions for PM 10 and NSD data datasets together. We also show how regression of the NSD size bins and the G time series can be used to elaborate the solution by identifying NSD factors (such as nucleation) not influencing the PM 10 mass. [ABSTRACT FROM AUTHOR]

A coupled regional-to-local modelling system comprising a regional chemistry--climate model with 5 km horizontal resolution (EMEP4UK) and an urban dispersion and chemistry model with explicit road source emissions (ADMS-Urban) has been used to simulate air quality in 2012 across London. The study makes use of emission factors for NOx and NO2 and non-exhaust emission rates of PM10 and PM2:5 which have been adjusted compared to standard factors to reflect real-world emissions, with increases in total emissions of around 30%for these species. The performance of the coupled model and each of the two component models is assessed against measurements from background and near-road sites in London using a range of metrics concerning annual averages, high hourly average concentrations and diurnal cycles. The regional model shows good performance compared to measurements for background sites for these metrics, but under-predicts concentrations of all pollutants except O3 at near-road sites due to the low resolution of input emissions and calculations. The coupled model shows good performance at both background and near-road sites, which is broadly comparable with that of the urban model that uses measured concentrations as regional background, except for PM2:5 where the under-prediction of the regional model causes the coupled model to also under-predict concentrations. Using the coupled model, it is estimated that 13% of the area of London exceeded the EU limit value of 40 µg m-3 for annual average NO2 in 2012, whilst areas of exceedances of the annual average limit values of 40 and 25 µg m-3 for PM10 and PM2:5 respectively were negligible. [ABSTRACT FROM AUTHOR]

Determining the contribution of wood smoke to air pollution in large cities such as London is becoming increasingly important due to the changing nature of domestic heating in urban areas. During winter, biomass burning emissions have been identified as a major cause of exceedances of European air quality limits. The aim of this work was to quantify the contribution of biomass burning in London to concentrations of PM2.5 and determine whether local emissions or regional contributions were the main source of biomass smoke. To achieve this, a number of biomass burning chemical tracers were analysed at a site within central London and two sites in surrounding rural areas. Concentrations of levoglucosan, elemental carbon (EC), organic carbon (OC) and K+ were generally well correlated across the three sites. At all the sites, biomass burning was found to be a source of OC and EC, with the largest contribution of EC from traffic emissions, while for OC the dominant fraction included contributions from secondary organic aerosols, primary biogenic and cooking sources. Source apportionment of the EC and OC was found to give reasonable estimation of the total carbon from non-fossil and fossil fuel sources based upon comparison with estimates derived from 14C analysis. Aethalometer-derived black carbon data were also apportioned into the contributions from biomass burning and traffic and showed trends similar to those observed for EC. Mean wood smoke mass at the sites was estimated to range from 0.78 to 1.0 μg m-3 during the campaign in January-February 2012. Measurements on a 160 m tower in London suggested a similar ratio of brown to black carbon (reflecting wood burning and traffic respectively) in regional and London air. Peaks in the levoglucosan and K+ concentrations were observed to coincide with low ambient temperature, consistent with domestic heating as a major contributing local source in London. Overall, the source of biomass smoke in London was concluded to be a background regional source overlaid by contributions from local domestic burning emissions. This could have implications when considering future emission control strategies during winter and may be the focus of future work in order to better determine the contributing local sources. [ABSTRACT FROM AUTHOR]

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/m3 (range 23.3-36.4) for PM10 and 41.4 (3.0) ug/m3 (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. [ABSTRACT FROM AUTHOR]

In the event of a release of toxic gas in the center of London, emergency services personnel would need to determine quickly the extent of the area contaminated. The transport of pollutants by turbulent flow within the complex streets and building architecture of London, United Kingdom, is not straightforward, and we might wonder whether it is at all possible to make a scientifically reasoned decision. Here, we describe recent progress from a major U.K. project. Dispersion of Air Pollution and its Penetration into the Local Environment (DAPPLE; information online at www.dapple.org. uk). In DAPPLE, we focus on the movement of airborne pollutants in cities by developing a greater understanding of atmospheric flow and dispersion within urban street networks. In particular, we carried out full-scale dispersion experiments in central London from 2003 through 2008 to address the extent of the dispersion of tracers following their release at street level. These measurements complemented previous studies because 1) our focus was on dispersion within the first kilometer from the source, when most ofthe material was expected to remain within the street network rather than being mixed into the boundary layer aloft; 2) measurements were made under a wide variety of meteorological conditions; and 3) central London represents a European, rather than North American, city geometry. Interpretation ofthe results from the full-scale experiments was supported by extensive numerical and wind tunnel modeling, which allowed more detailed analysis under idealized and controlled conditions. In this article, we review the full-scale DAPPLE methodologies and show early results from the analysis of the 2007 field campaign data. [ABSTRACT FROM AUTHOR]

Few published studies have looked at the health effects of air pollution in the primary care setting, and most have concentrated on lower rather than upper respiratory diseases. The authors investigated the association of daily consultations with general practitioners for allergic rhinitis with air pollution in London, United Kingdom. Generalized additive models were used to regress time series of daily numbers of patients consulting for allergic rhinitis against 1992-1994 measures of air pollution, after control for possible confounders and adjustment for overdispersion and serial correlation. In children, a 10th-90th percentile increase in sulfur dioxide (SO2 ) levels 2 3 4 days prior to consultation (13-31 µg/m³ ) was associated with a 24.5% increase in consultations (95% confidence interval: 14.6, 35.2; p < 0.00001); a 10th-90th percentile increase in averaged ozone (O3) concentrations on the day of consultation and the preceding 3 days (6-29 parts per billion) was associated with a 37.6% rise (95% confidence interval: 23.3, 53.5; p < 0.00001). For adults, smaller effect sizes were observed for SO2 and O3. The association with SO2 remained highly significant in the presence of other pollutants. This study suggests that air pollution worsens allergic rhinitis symptoms, leading to substantial increases in consultations. SO2 and O3 seem particularly responsible, and both seem to contribute independently. Am J Epidemiol 2001;153:704-14. [ABSTRACT FROM AUTHOR]

The personal exposure of children aged 9 – 11 years to particulate matter (PM10 and PM2.5) was carried out between January and September 1997 in the London Borough of Barnet. Personal sampling along with home, garden and classroom microenvironmental monitoring was completed for all ten children. Each child was monitored for five days during winter, spring and summer. All children completed daily time activity diaries to provide information on any potential activities that could influence their exposure to particulate matter. Each evening a household activity questionnaire was also completed by the parents. Personal Environmental Monitors were used to sample personal exposure to PM10 and PM2.5. Harvard Impactors were used for the microenvironmental sampling of both size fractions. The children's mean personal exposure concentrations for PM10 during winter, spring and summer were 72, 54 and 35 µg/m3 respectively and for PM2.5 22, 17 and 18 µg/m3 respectively. In order to determine the potential sources of particulate matter, analysis of the Teflon filters has been undertaken. The physical characteristics of the particles have been identified using Scanning Electron Microscopy. The relationships between personal exposure concentrations and the different microenvironments will be discussed. [ABSTRACT FROM AUTHOR]

The benefits of 'green infrastructure' are multi-faceted and well-documented, but estimating those of individual street-scale planting schemes at planning can be challenging. This is crucial to avoid undervaluing proposed schemes in cost–benefit analyses, and ensure they are resilient to 'value engineering' between planning and implementation. Here, we introduce prototype software enabling urban practitioners to estimate the site-specific air quality impacts of roadside vegetation barriers: highly localised changes in pollutant concentrations due to changes in the dispersion of vehicular emissions close to source. We summarise the recent shift in understanding regarding the impacts of vegetation on urban air pollution towards changes in pollutant dispersion (cf. deposition) and describe our prototype software, offering rapid estimates thereof. First tests of the underlying model's performance are promising, reproducing: annual mean NO2 and PM2.5 concentrations in a street canyon (Marylebone Road, London, UK) to within 10% and 25%, respectively; and changes in pollutant concentrations of the right order of magnitude behind roadside barriers in a wind tunnel simulation of a street canyon and a real open-road environment. However, the model underestimates the benefits of a barrier in a simulated street canyon under perpendicular wind conditions. The prototype software is a first step towards informing practitioners of the site-specific impacts of vegetation barriers, which should always be additional to (i.e., no substitute for) essential emission reductions. The code is open-source to engage further researchers in its continued development. [ABSTRACT FROM AUTHOR]

Studies the short-term associations between outdoor air pollution and mortality in London, England in 1992 to 1994. Use of Poisson regression to assess the daily mortality; Absence of relation between any pollutant and mortality; Association of the pollutants with respiratory mortality; Confirmation of a previous report that there are associations between various air pollutants and daily mortality in London, England.

Presents an alternative interpretation of John Evelyn's pamphlet about smoke pollution in London, England, entitled `Fumifugium.' Relation of proposals to political allegory; Writing of panegyrics to welcome newly restored Charles II in the seventeenth century; Motivation of the people for writing about pollution.

The author reflects on the status of ecosystems around the world and their inhabitants in 2010, such as London, England, which is the host of the Ecohealth 2010 conference. The author mentions the ecosystems in Latin America, highlighting the importance of biodiversity in health and well-being. Moreover, the author discusses the environmental condition of London such as its clean air and thriving ecological life.

Studies on the effects of air pollution and more generally environmental exposures on health require measurements of pollutants, which are affected by measurement error. This is a cause of bias in the estimation of parameters relevant to the study and can lead to inaccurate conclusions when evaluating associations among pollutants, disease risk and biomarkers. Although the presence of measurement error in such studies has been recognized as a potential problem, it is rarely considered in applications and practical solutions are still lacking. In this work, we formulate Bayesian measurement error models and apply them to study the link between air pollution and omic signals. The data we use stem from the "Oxford Street II Study", a randomized crossover trial in which 60 volunteers walked for two hours in a traffic-free area (Hyde Park) and in a busy shopping street (Oxford Street) of London. Metabolomic measurements were made in each individual as well as air pollution measurements, in order to investigate the association between short-term exposure to traffic related air pollution and perturbation of metabolic pathways. We implemented error-corrected models in a classical framework and used the flexibility of Bayesian hierarchical models to account for dependencies among omic signals, as well as among different pollutants. Models were implemented using traditional Markov Chain Monte Carlo (MCMC) simulative methods as well as integrated Laplace approximation. The inclusion of a classical measurement error term resulted in variable estimates of the association between omic signals and traffic related air pollution measurements, where the direction of the bias was not predictable a priori. The models were successful in including and accounting for different correlation structures, both among omic signals and among different pollutant exposures. In general, more associations were identified when the correlation among omics and among pollutants were modeled, and their number increased when a measurement error term was additionally included in the multivariate models (particularly for the associations between metabolomics and NO2). [ABSTRACT FROM AUTHOR]