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    ABSTRACT: This paper develops the idea of bivariate polar plots as a method for source detection and characterisation. Bivariate polar plots provide a graphical method for showing the joint wind speed, wind direction dependence of air pollutant concentrations. Bivariate polar plots provide an effective graphical means of discriminating different source types and characteristics. In the current work we apply k-means clustering techniques directly to bivariate polar plots to identify and group similar features. The technique is analogous to clustering applied to back trajectories at the regional scale. When applied to data from a monitoring site with high source complexity it is shown that the technique is able to identify important clusters in ambient monitoring data that additional analysis shows to exhibit different source characteristics. Importantly, this paper links identified clusters to known emission characteristics to confirm the inferences made in the analysis. The approaches developed should have wide application to the analysis of air pollution monitoring data and have been made freely available as part of the openair R package.
    Environmental Modelling and Software 02/2013; 40:325 - 329. DOI:10.1016/j.envsoft.2012.09.005
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    ABSTRACT: The eruption of the Icelandic volcano Eyjafjallajökull in April 2010 resulted in an unprecedented flight-ban at many European airports for many days. While much of the scientific interest in the eruption was related to the chemical and physical properties of the ash cloud and how it dispersed, a secondary effect was the reduction in aviation emissions at airports around Europe and elsewhere. In this study we aim to quantify the impact the flight-ban had on concentrations of nitrogen oxides at measurement sites close to London Heathrow Airport. A technique based on boosted regression trees is used to build an explanatory model of NOx and NO2 concentrations based on hourly meteorological and aircraft emissions data in the 3-years preceding the flight-ban. We show that the airport closure resulted in an unambiguous effect on NOx and NO2 concentrations close to the airport, even though the ban only lasted six days. Furthermore, we estimate the annual impact airport emissions have on mean concentrations of NOx and NO2 for different years and compare these estimates with a detailed dispersion modelling study and previous work that was based on the analysis of monitoring site data. For the receptor most affected by the flight-ban approximately 200 m south of the airport we estimate the airport contributes about 13.5 μg m−3 NOx (≈23% of the total measured NOx concentration), which is similar in magnitude to detailed dispersion modelling estimates of 12.0 μg m−3, but approximately twice that of other estimates based on the analysis of ambient measurements. Other measurement sites showed more mixed results due to the prevailing meteorology at the time of the ban, which affected the extent to which these sites were affected by the flight-ban. The techniques developed and applied in this paper would have application to other short-term interventions that affect air quality.
    Atmospheric Environment 07/2012; 54:328-336. DOI:10.1016/j.atmosenv.2012.02.020
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    ABSTRACT: In this paper we have compared detailed road traffic NOx emissions with the equivalent trends in ambient roadside NOx measurements. This was undertaken separately in Great Britain and London, for all of the major roads, and by road type and location. The emissions trends were created using different emissions factors, those used in UK emissions inventories (Base case), the Swiss-German handbook (HBEFA), and those created from recent remote sensing measurements in the UK (RSD). An alternative assumption for use of Selective Catalytic Reduction (SCR) in the articulated Heavy Goods Vehicle (HGV) fleet was also tested. For all scenarios traffic flows, speeds and vehicle age were kept constant. Comparison between the emissions scenarios in Great Britain showed that by 2009, NOx emissions estimates from road traffic could be as much as 25% greater than current UK estimates and 31% greater in London. The RSD emissions inventory gave the smallest downward trend in NOx emissions, from 2004 to 2009, of between 3 and 4%/year and this compared with a reduction of ∼6%/year from the Base Case and HBEFA scenarios. All scenarios compared poorly with roadside NOx measurement trends from UK sites, which typically reduce by between 1% and 2%/year. We have shown that the differences in NOx emissions trends were driven, partially at least, by the relative contribution from light duty diesel vehicles. An analysis from 2700 NOx measurement sites throughout Europe has shown that this problem is unlikely to be limited to the UK, and identifies a difficulty in meeting EU limit values for NO2, obligations under the National Emission Ceilings Directive (NECD, 2001) and the Gothenburg Protocol (UNECE, 1999) and for forecasting future changes in PM2.5.
    Atmospheric Environment 07/2012; 54:107–116. DOI:10.1016/j.atmosenv.2012.02.028
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    ABSTRACT: openair is an R package primarily developed for the analysis of air pollution measurement data but which is also of more general use in the atmospheric sciences. The package consists of many tools for importing and manipulating data, and undertaking a wide range of analyses to enhance understanding of air pollution data. In this paper we consider the development of the package with the purpose of showing how air pollution data can be analysed in more insightful ways. Examples are provided of importing data from UK air pollution networks, source identification and characterisation using bivariate polar plots, quantitative trend estimates and the use of functions for model evaluation purposes. We demonstrate how air pollution data can be analysed quickly and efficiently and in an interactive way, freeing time to consider the problem at hand. One of the central themes of openair is the use of conditioning plots and analyses, which greatly enhance inference possibilities. Finally, some consideration is given to future developments.
    Environmental Modelling and Software 01/2012; 27--28:52-61. DOI:10.1016/j.envsoft.2011.09.008
  • Atmospheric Environment 07/2011; 45(23):3911-3912. DOI:10.1016/j.atmosenv.2011.04.067
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    ABSTRACT: In recent years sophisticated technologies have been developed to control vehicle speed based on the type of road the vehicle is driven on using Global Positioning Systems and in-car technology that can alter the speed of the vehicle. While reducing the speed of road vehicles is primarily of interest from a safety perspective, vehicle speed is also an important determinant of vehicle emissions and thus these technologies can be expected to have impacts on a range of exhaust emissions. This work analyses the results from a very large, comprehensive field trial that used 20 instrumented vehicles with and without speed control driven almost 500,000 km measuring vehicle speed at 10 Hz. We develop individual vehicle modal emissions models for CO2 for 30 Euro III and Euro IV cars at a 1-Hz time resolution. Generalized Additive Models were used to describe how emissions from individual vehicles vary depending on their driving conditions, taking account of variable interactions and time-lag effects. We quantify the impact that vehicle speed control has on-vehicle emissions of CO2 by road type, fuel type and driver behaviour. Savings in CO2 of ≈6% were found on average for motorway-type roads when mandatory speed control was used compared with base case conditions. For most other types of road, speed control has very little effect on emissions of CO2 and in some cases can result in increased emissions for low-speed limit urban roads. We also find that there is on average a 20% difference in CO2 emission between the lowest and highest emitting driver, which highlights the importance of driver behaviour in general as a means of reducing emissions of CO2.
    Atmospheric Environment 07/2010; DOI:10.1016/j.atmosenv.2010.04.046
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    ABSTRACT: Adverse cardiorespiratory health is associated with exposure to ambient particulate matter (PM). The highest PM concentrations in London occur in proximity to waste transfer stations (WTS), sites that experience high numbers of dust-laden, heavy-duty diesel vehicles transporting industrial and household waste. Our goal was to quantify the contribution of WTS emissions to ambient PM mass concentrations and oxidative potential. PM with a diameter < 10 microm (PM10) samples were collected daily close to a WTS. PM10 mass concentrations measurements were source apportioned to estimate local versus background sources. PM oxidative potential was assessed using the extent of antioxidant depletion from a respiratory tract lining fluid model. Total trace metal and bioavailable iron concentrations were measured to determine their contribution to PM oxidative potential. Elevated diurnal PM10 mass concentrations were observed on all days with WTS activity (Monday-Saturday). Variable PM oxidative potential, bioavailable iron, and total metal concentrations were observed on these days. The contribution of WTS emissions to PM at the sampling site, as predicted by microscale wind direction measurements, was correlated with ascorbate (r = 0.80; p = 0.030) and glutathione depletion (r = 0.76; p = 0.046). Increased PM oxidative potential was associated with aluminum, lead, and iron content. PM arising from WTS activity has elevated trace metal concentrations and, as a consequence, increased oxidative potential. PM released by WTS activity should be considered a potential health risk to the nearby residential community.
    Environmental Health Perspectives 04/2010; 118(4):493-8. DOI:10.1289/ehp.0901303
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    ABSTRACT: On 17th February 2003, a congestion charging scheme (CCS), operating Monday–Friday, 07:00–18:00, was introduced in central London along with a programme of traffic management measures. We investigated the potential impact of the introduction of the CCS on measured pollutant concentrations (oxides of nitrogen (NOX, NO and NO2), particles with a median diameter less than 10 microns (PM10), carbon monoxide (CO) and ozone (O3)) measured at roadside and background monitoring sites across Greater London. Temporal changes in pollution concentrations within the congestion charging zone were compared to changes, over the same time period, at monitors unlikely to be affected by the CCS (the control zone) and in the boundary zone between the two. Similar analyses were done for CCS hours during weekends (when the CCS was not operating).Based on the single roadside monitor with the CCS Zone, it was not possible to identify any relative changes in pollution concentrations associated with the introduction of the scheme. However, using background monitors, there was good evidence for a decrease in NO and increases in NO2 and O3 relative to the control zone. There was little change in background concentrations of NOX. There was also evidence of relative reductions in PM10 and CO. Similar changes were observed during the same hours in weekends when the scheme was not operating.The causal attribution of these changes to the CCS per se is not appropriate since the scheme was introduced concurrently with other traffic and emissions interventions which might have had a more concentrated effect in central London. This study provides important pointers for study design and data requirements for the evaluation of similar schemes in terms of air quality. It also shows that results may be unexpected and that the overall effect on toxicity may not be entirely favourable.
    Atmospheric Environment 11/2009; 43(34-43):5493-5500. DOI:10.1016/j.atmosenv.2009.07.023
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    ABSTRACT: London currently has the highest nitrogen dioxide (NO2) concentration recorded for any European city and for particulate matter (PM) it has some of the worst hot spots. Therefore overall, for these two pollutants, London is the worst in the UK and amongst the worst in Europe. Exposure to elevated concentrations of air pollutants such as PM and NO2 has well-established heath effects and most countries now have strict guidelines for air quality. London's air quality problems are driven largely by traffic. This, along with the high density of people in an urban area results in air quality guidelines being exceeded on a regular basis and large numbers of people being affected. In an attempt to combat London's air quality problems the Mayor of London introduced a series of measures to decrease traffic emissions. These included both a restriction on the number of vehicles entering central London each day--the Congestions Charging Scheme (CCS), and the discouragement of the most polluting heavy goods vehicles from entering--the London Low Emission Zone (LEZ). Together, it is hoped that these measures will lead to an improvement in air quality and provide a direct health benefit to Londoners. Research underway is charting the progress of this real world experiment.
    Biomarkers 07/2009; 14 Suppl 1(s1):5-11. DOI:10.1080/13547500902965252
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    ABSTRACT: We modelled exposure to traffic particles using a latent variable approach and investigated whether long-term exposure to traffic particles is associated with an increase in the occurrence of acute myocardial infarction (AMI) using data from a population-based coronary disease registry. Cases of individually validated AMI were identified between 1995 and 2003 as part of the Worcester Heart Attack Study. Population controls were selected from Massachusetts, USA, resident lists. NO(2) and PM(2.5) filter absorbance were measured at 36 locations throughout the study area. The air pollution data were used to estimate exposure to traffic particles using a semiparametric latent variable regression model. Conditional logistic models were used to estimate the association between exposure to traffic particles and occurrence of AMI. Modelled exposure to traffic particles was highest near the city of Worcester. Cases of AMI were more exposed to traffic and traffic particles compared to controls. An interquartile range increase in modelled traffic particles was associated with a 10% (95% CI 4% to 16%) increase in the odds of AMI. Accounting for spatial dependence at the census tract, but not block group, scale substantially attenuated this association. These results provide some support for an association between long-term exposure to traffic particles and risk of AMI. The results were sensitive to the scale selected for the analysis of spatial dependence, an issue that requires further investigation. The latent variable model captured variation in exposure, although on a relatively large spatial scale.
    Occupational and environmental medicine 07/2009; 66(12):797-804. DOI:10.1136/oem.2008.045047
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