Marylebone Road Research Articles

Analysis of new particle formation (NPF) events at nearby rural, urban background and urban roadside sites

Abstract. New particle formation (NPF) events have different patterns of development depending on the conditions of the area in which they occur. In this study, particle size distributions in the range of 16.6–604 nm (7 years of data) were analysed and NPF events occurring at three sites of differing characteristics – rural Harwell (HAR), urban background North Kensington (NK), urban roadside Marylebone Road (MR), London, UK – were extracted and studied. The different atmospheric conditions in each study area not only have an effect on the frequency of the events, but also affect their development. The frequency of NPF events is similar at the rural and urban background locations (about 7 % of days), with a high proportion of events occurring at both sites on the same day (45 %). The frequency of NPF events at the urban roadside site is slightly less (6 % of days), and higher particle growth rates (average 5.5 nm h−1 at MR compared to 3.4 and 4.2 nm h−1 at HAR and NK respectively) must result from rapid gas-to-particle conversion of traffic-generated pollutants. A general pattern is found in which the condensation sink increases with the degree of pollution of the site, but this is counteracted by increased particle growth rates at the more polluted location. A key finding of this study is that the role of the urban environment leads to an increment of 20 % in N16–20 nm in the urban background compared to that of the rural area in NPF events occurring at both sites. The relationship of the origin of incoming air masses is also considered and an association of regional events with cleaner air masses is found. Due to lower availability of condensable species, NPF events that are associated with cleaner atmospheric conditions have lower growth rates of the newly formed particles. The decisive effect of the condensation sink in the development of NPF events and the survivability of the newly formed particles is underlined, and influences the overall contribution of NPF events to the number of ultrafine particles in an area. The other key factor identified by this study is the important role that pollution, both from traffic and other sources in the urban environment (such as heating or cooking), plays in new particle formation events.

Interpretation of particle number size distributions measured across an urban area during the FASTER campaign

Abstract. Particle number size distributions have been measured simultaneously by scanning mobility particle sizers (SMPSs) at five sites in central London for a 1 month campaign in January–February 2017. These measurements were accompanied by condensation particle counters (CPCs) to measure total particle number count at four of the sites and Aethalometers measuring black carbon (BC) at five sites. The spatial distribution and inter-relationships of the particle size distribution and SMPS total number counts with CPC total number counts and black carbon measurements have been analysed in detail as well as variations in the size distributions. One site (Marylebone Road) was in a street canyon with heavy traffic, one site (Westminster University) was on a rooftop adjacent to the Marylebone Road sampler, and a further sampler was located at Regent's University within a major park to the north of Marylebone Road. A fourth sampler was located nearby at 160 m above ground level on the BT tower and a fifth sampler was located 4 km to the west of the main sampling region at North Kensington. Consistent with earlier studies it was found that the mode in the size distribution had shifted to smaller sizes at the Regent's University (park) site, the mean particle shrinkage rate being 0.04 nm s−1 with slightly lower values at low wind speeds and some larger values at higher wind speeds. There was evidence of complete evaporation of the semi-volatile nucleation mode under certain conditions at the elevated BT Tower site. While the SMPS total count and black carbon showed typical traffic-dominated diurnal profiles, the CPC count data typically peaked during night-time as did CPC∕SMPS and CPC∕BC ratios. This is thought to be due to the presence of high concentrations of small particles (2.5–15 nm diameter) probably arising from condensational growth from traffic emissions during the cooler night-time conditions. Such behaviour was most marked at the Regent's University and Westminster University sites and less so at Marylebone Road, while at the elevated BT Tower site the ratio of particle number (CPC) to black carbon peaked during the morning rush hour and not at night-time, unlike the other sites. An elevation in nucleation mode particles associated with winds from the west and WSW sector was concluded to result from emissions from London Heathrow Airport, despite a distance of 22 km from the central London sites.

Using meteorological normalisation to detect interventions in air quality time series

Interventions used to improve air quality are often difficult to detect in air quality time series due to the complex nature of the atmosphere. Meteorological normalisation is a technique which controls for meteorology/weather over time in an air quality time series so intervention exploration (and trend analysis) can be assessed in a robust way. A meteorological normalisation technique, based on the random forest machine learning algorithm was applied to routinely collected observations from two locations where known interventions were imposed on transportation activities which were expected to change ambient pollutant concentrations. The application of progressively stringent limits on the content of sulfur in marine fuels was very clearly represented in ambient sulfur dioxide (SO2) monitoring data in Dover, a port city in the South East of England. When the technique was applied to the oxides of nitrogen (NOx and NO2) time series at London Marylebone Road (a Central London monitoring site located in a complex urban environment), the normalised time series highlighted clear changes in NO2 and NOx which were linked to changes in primary (directly emitted) NO2 emissions at the location. The clear features in the time series were illuminated by the meteorological normalisation procedure and were not observable in the raw concentration data alone. The lack of a need for specialised inputs, and the efficient handling of collinearity and interaction effects makes the technique flexible and suitable for a range of potential applications for air quality intervention exploration.

A Two-Decade Anthropogenic and Biogenic Isoprene Emissions Study in a London Urban Background and a London Urban Traffic Site

A relationship between isoprene and 1,3-butadiene mixing ratios was established to separate the anthropogenic and biogenic fractions of the measured isoprene in London air in both urban background (Eltham) and urban traffic (Marylebone Road) areas over two decades (1997–2017). The average daytime biogenic isoprene mixing ratios over this period reached 0.09 ± 0.04 ppb (Marylebone Road) and 0.11 ± 0.06 ppb (Eltham) between the period of 6:00 to 20:00 local standard time, contributing 40 and 75% of the total daytime isoprene mixing ratios. The average summertime biogenic isoprene mixing ratios for 1997–2017 are found to be 0.13 ± 0.02 and 0.15 ± 0.04 ppb which contribute 50 and 90% of the total summertime isoprene mixing ratios for Marylebone Road and Eltham, respectively. Significant anthropogenic isoprene mixing ratios are found during night-time (0.11 ± 0.04 ppb) and winter months (0.14 ± 0.01 ppb) at Marylebone Road. During high-temperature and high-pollution events (high ozone) there is a suggestion that ozone itself may be directly responsible for some of the isoprene emission. By observing the positive correlation between biogenic isoprene levels with temperature, photosynthetically active radiation and ozone mixing ratios during heatwave periods, the Cobb-Douglas production function was used to obtain a better understanding of the abiotic factors that stimulate isoprene emission from plants. Other reasons for a correlation between ozone and isoprene are discussed. The long-term effects of urban stressors on vegetation were also observed, with biogenic isoprene mixing ratios on Marylebone Road dropping over a 20-year period regardless of the sustained biomass levels.

Trends of atmospheric black carbon concentration over the United Kingdom

The continuous observations over a period of 7 years (2009–2016) available at 7 locations show declining trend of atmospheric BC in the UK. Among all the locations, the highest decrease of 8 ± 3 percent per year was observed at the Marylebone road in London. The detailed analysis performed at 21 locations during 2009–2011 shows that average annual mean atmospheric BC concentration were 0.45 ± 0.10, 1.47 ± 0.58, 1.34 ± 0.31, 1.83 ± 0.46 and 9.72 ± 0.78 μgm−3 at rural, suburban, urban background, urban centre and kerbside sites respectively. Around 1 μgm−3 of atmospheric BC could be attributed to urban emission, whereas traffic contributed up to 8 μg m−3 of atmospheric BC near busy roads. Seasonal pattern was also observed at all locations except rural and kerbside location, with maximum concentrations (1.2–4 μgm−3) in winter. Further, minimum concentrations (0.3–1.2 μgm−3) were observed in summer and similar concentrations in spring and fall. At suburban and urban background locations, similar diurnal pattern were observed with atmospheric BC concentration peaks (≈1.8 μg m−3) in the morning (around 9 a.m.) and evening (7–9 p.m.) rush hours, whereas minimum concentrations were during late night hours (peak at 5 a.m.) and the afternoon hours (peak at 2 p.m.). The urban centre values show a similar morning pattern (peak at 9 a.m.; concentration - 2.5 μgm−3) in relation to background locations but only a slight decrease in concentration in the afternoon which remained above 2 μgm−3 till midnight. It is concluded that the higher flow of traffic at urban centre locations results in higher atmospheric BC concentrations throughout the day. Comparison of weekday and weekend daily averaged atmospheric BC showed maximum concentrations on Friday, having minimum levels on Sunday. This study will help to refine the atmospheric BC emission inventories and provide data for air pollution and climate change models evaluation, which are used to formulate air pollution mitigation policies.

Hybrid Artificial Neural Network Models for Effective Prediction and Mitigation of Urban Roadside NO2 Pollution

Traffic-related air pollution has been a serious concern amongst policy-makers and the public due to its physiological and environmental impacts. An early warning system based on accurate forecasting tools must therefore be implemented to circumvent the adverse effects of exposure to major air pollutants. A multilayer perceptron neural network was trained and developed using air pollution and meteorological data over a two-year period from a monitoring site in Marylebone Road, Central London to predict roadside concentration values of NO2 24 hours ahead. Several hybrid models were also developed by applying feature selection techniques such as stepwise regression, principal component analysis, and Classification and Regression Trees to the neural network model. Most roadside pollutant variables, e.g., oxides of nitrogen, were found to be significant in predicting NO2. The statistical results reveal overall prediction superiority of the hybrid models to the standalone neural network model.

An Estimation of the Levels of Stabilized Criegee Intermediates in the UK Urban and Rural Atmosphere Using the Steady-State Approximation and the Potential Effects of These Intermediates on Tropospheric Oxidation Cycles.

ABSTRACTLevels of the stabilized Criegee Intermediate (sCI), produced via the ozonolysis of unsaturated volatile organic compounds (VOCs), were estimated at two London urban sites (Marylebone Road and Eltham) and one rural site (Harwell) in the UK over the period of 1998–2012. The steady‐state approximation was applied to data obtained from the NETCEN (National Environmental Technology Centre) database, and the levels of annual average sCI were estimated to be in the range of 30–3000 molecules cm−3 for UK sites. A consistent diurnal cycle of sCI concentration is estimated for the UK sites with increasing levels during daylight hours, peaking just after midday. The seasonal pattern of sCI shows higher levels in spring with peaks around May due to the higher levels of O3. The ozone weekend effect resulted in higher sCI in UK urban areas during weekend. The sCI data were modeled using the information provided by the Air Quality Improvement Research Program (AQIRP) and found that the modeled production was five‐ to six‐fold higher than our estimated data, and therefore the estimated sCI concentrations in this study are thought to be lower estimates only. Compared with nighttime, 1.3‐ to 1.8‐fold higher sCI exists under daytime conditions. Using the levels of sCI estimated at Marylebone Road, globally the oxidation rates of NO2 + sCI (22.4 Gg/yr) and SO2 + sCI (37.6 Gg/yr) in urban areas can increase their effect in the troposphere and potentially further alter the oxidizing capacity of the troposphere. Further investigations of modeled sCI show that CH3CHOO (64%) and CH2OO (13%) are dominant among all contributing sCI at the UK sites.

Air quality affected by trees in real street canyons: The case of Marylebone neighbourhood in central London

This paper discusses the combined influence of building morphology and trees on air pollutant concentrations in the Marylebone neighbourhood (central London). Computational Fluid Dynamics (CFD) simulations are performed with OpenFOAM using the k-ε model. Aerodynamic and deposition effects of Platanus acerifolia trees are considered. While aerodynamic effects are treated as typically done in the literature, i.e. as a porous media, for the deposition an enhanced model with an additional sink term was implemented. CFD results are compared with UK AURN (Automatic Urban and Rural Network) station concentrations. Several meteorological conditions are analysed based on London City Airport weather station data, with attention to prevailing winds.CFD simulations show that trees trap air pollution by up to about 7% at the Marylebone monitoring station in the spring, autumn and summer seasons, suggesting that the aerodynamic effects are similar over the different leaf seasons. Aerodynamic effects are more important at lower wind speeds causing little turbulent dispersion. Deposition effects are found to be 4 times less important with reductions of up to about 2%, with more deposition in summer due to a greater leaf area density. Furthermore, for winds parallel to Marylebone Road, the aerodynamic effects decrease concentrations suggesting that in such cases trees could be considered as a mitigation measures. This is different from perpendicular winds for which trees exacerbate trapping, as found in previous studies. The analysis of concentration levels obtained from CFD simulations across the whole street confirms a beneficial aerodynamic dispersive effect of trees of 0.7% in summer time for all wind directions averaged at a wind speed of 5m/s (yearly average wind speed observed in the area). Results highlight the need to account for both aerodynamic and dispersion effects of trees in CFD modelling to achieve a comprehensive evaluation and help city planners with a sustainable design of trees in urban environments.

Predicting the frequency of extreme air quality events.

A new method for predicting the frequency of extreme air quality events is proposed. The method is based on knowing the number of times a pollutant is measured at different concentrations during a period of data collection and fitting this data to a Weibull-type function. Extrapolation of the function to higher concentrations then allows the frequency of extreme events that did not occur during the collection period to be predicted, albeit with an unspecified uncertainty. Prediction of the frequency of events over a given concentration, which was exceeded during the period of data collection, has also been performed assuming Poisson statistics. The assumption of Poisson statistics enables the provision of an uncertainty statement to accompany the prediction. The methods are trialled on a data set of daily average PM10 mass concentrations recorded at Marylebone Road in London between 2007 and 2016, inclusive. Using the method it was predicted that a daily average PM10 mass concentration of over 100 μg m-3, corresponding to the highest UK Daily Air Quality Index band, should be expected once in just over three years and this agreed well with real observations, demonstrating the utility of this new technique.

Source apportionment of fine and coarse particles at a roadside and urban background site in London during the 2012 summer ClearfLo campaign

London, like many major cities, has a noted air pollution problem, and a better understanding of the sources of airborne particles in the different size fractions will facilitate the implementation and effectiveness of control strategies to reduce air pollution. Thus, the trace elemental composition of the fine and coarse fraction were analysed at hourly time resolution at urban background (North Kensington, NK) and roadside (Marylebone Road, MR) sites within central London. Unlike previous work, the current study focuses on measurements during the summer providing a snapshot of contributing sources, utilising the high time resolution to improve source identification. Roadside enrichment was observed for a large number of elements associated with traffic emissions (Al, S, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, As, Rb and Zr), while those elements that are typically from more regional sources (e.g. Na, Cl, S and K) were not found to have an appreciable increment. Positive Matrix Factorization (PMF) was applied for the source apportionment of the particle mass at both sites with similar sources being identified, including sea salt, airborne soil, traffic emissions, secondary inorganic aerosols and a Zn-Pb source. In the fine fraction, traffic emissions was the largest contributing source at MR (31.9%), whereas it was incorporated within an “urban background” source at NK, which had contributions from wood smoke, vehicle emissions and secondary particles. Regional sources were the major contributors to the coarse fraction at both sites. Secondary inorganic aerosols (which contained influences from shipping emissions and coal combustion) source factors accounted for around 33% of the PM10 at NK and were found to have the highest contributions from regional sources, including from the European mainland. Exhaust and non-exhaust sources both contribute appreciably to PM10 levels at the MR site, highlighting the continuing importance of vehicle-related air pollutants at roadside.

Hybrid Neural Networks and Boosted Regression Tree Models for Predicting Roadside Particulate Matter

This paper examines the application of artificial neural network (ANN) and boosted regression tree (BRT) methods in air quality modelling. The methods were applied to developing air quality models for predicting roadside particle mass concentration (PM10, PM2.5) and particle number counts (PNC) based on air pollution, traffic and meteorological data from Marylebone Road in London. Elastic net, Lasso and principal components analysis were used as feature selection methods for the ANN models to reduce the number of predictor variables and improve their generalisation. The performance of the ANN with feature selection (ANN hybrid) and the BRT models was evaluated and compared using statistical performance metrics. The performance parameters include root mean square error (RMSE), fraction of prediction within a factor of two of the observation (FAC2), mean bias (MB), mean gross error (MGE), the coefficient of correlation (R) and coefficient of efficiency (CoE) values. The input variables selected by the elastic net produced the best performing ANN models. The ANN hybrid produced models performed only slightly better than the BRT models. The R values of the ANN elastic net and BRT models were 0.96 and 0.95 for PM10, 0.96 and 0.96 for PM2.5 and 0.89 and 0.87 for PNC, respectively. Their corresponding CoE values were 0.72 and 0.70 for PM10, 0.74 and 0.76 for PM2.5 and 0.81 and 0.71 for PNC respectively. About 80–99% of all the model predictions are within a factor of two of the observed particle concentrations. The BRT models offer more advantages regarding model interpretation and permit feature selection. Therefore, the study recommends the use of BRT over ANN where the model interpretation is a priority.

Local and regional components of aerosol in a heavily trafficked street canyon in central London derived from PMF and cluster analysis of single-particle ATOFMS spectra.

Positive matrix factorization (PMF) has been applied to single particle ATOFMS spectra collected on a six lane heavily trafficked road in central London (Marylebone Road), which well represents an urban street canyon. PMF analysis successfully extracted 11 factors from mass spectra of about 700,000 particles as a complement to information on particle types (from K-means cluster analysis). The factors were associated with specific sources and represent the contribution of different traffic related components (i.e., lubricating oils, fresh elemental carbon, organonitrogen and aromatic compounds), secondary aerosol locally produced (i.e., nitrate, oxidized organic aerosol and oxidized organonitrogen compounds), urban background together with regional transport (aged elemental carbon and ammonium) and fresh sea spray. An important result from this study is the evidence that rapid chemical processes occur in the street canyon with production of secondary particles from road traffic emissions. These locally generated particles, together with aging processes, dramatically affected aerosol composition producing internally mixed particles. These processes may become important with stagnant air conditions and in countries where gasoline vehicles are predominant and need to be considered when quantifying the impact of traffic emissions.

Estimation of Daytime NO3Radical Levels in the UK Urban Atmosphere Using the Steady State Approximation Method

The steady state approximation has been applied to the UK National Environment Technology Centre (NETCEN) data at three urban sites in the UK (Marylebone Road London, London Eltham, and Harwell) over the period of 1997 to 2012 to estimate the concentrations of daytime NO3. Despite the common assertion that NO3levels are negligible in the day as a consequence of photolysis, there are occasions where NO3reaches a few pptv. A seasonal pattern in NO3concentration was observed with higher levels in the spring with consistent peaks in April and May. A combination of temperature effects (the formation of NO3from the reaction of NO2with O3has a high activation energy barrier), a distinct pattern in O3concentration (peaking in spring), and loss via reaction with NO peaking in winter is responsible for this trend. Although reaction with OH is still the dominant loss process for VOCs during the day, there are VOCs (unsaturated) that will have an appreciable loss due to reaction with NO3in the daytime. Since the addition reaction of NO3with alkenes can lead directly to organic nitrate formation, there are implications for O3formation and secondary organic aerosol formation during daytime and these are discussed.

Twenty years of continuous high time resolution volatile organic compound monitoring in the United Kingdom from 1993 to 2012

Continuous, high frequency observations of C2 – C8 hydrocarbons began in the United Kingdom in 1993 and have continued through to the present day at a range of kerbside, urban background and rural locations. Most of the monitored hydrocarbons have shown dramatic declines in concentrations over the study period, with present levels close to an order of magnitude below their levels in the 1990s. The concentrations of 23 selected hydrocarbons have been aggregated up to give an estimate of the total VOC concentrations. These annual values have shown an exponential decline of −18% yr−1 at the London Marylebone Road kerbside site, −11% yr−1 at the London Eltham urban background site and −22% yr−1 at the rural Harwell site. Similar declines have been reported in UK road transport VOC emissions, demonstrating how the VOC emission inventories have apparently captured the salient features influencing real-world VOC emissions over the 1994–2012 period.

A dynamic approach to urban road deposited sediment pollution monitoring (Marylebone Road, London, UK)

The use of mineral magnetic measurements (χLF, χARM and SIRM) as a potential pollution proxy using road deposited sediment (RDS) is explored as an alternative means of monitoring pollution on a busy city road. Comparison of sediment-related analytical data by correlation analysis between mineral magnetic, particle size and geochemical properties is reported. Mineral magnetic concentration parameters (χLF, χARM and SIRM) reveal significant (p < 0.001; n = 61) associations with PM1.0, PM2.5 and PM10. Significant associations were also found with mineral magnetic concentrations (χLF and SIRM) and specific concentrations of the elements Fe, Ni, Cu, Zn and Mn (p < 0.001; n = 61). Inter-geochemical correlation analysis found strong associations (p < 0.001; n = 61) between Fe, Ni, Cu, Zn and Mn and suggest anthropogenic enrichment influences. Low χFD% measurements imply an influence of multi-domain mineralogy, indicative of anthropogenic combustion processes. SEM micrographs also support this, as all samples contain Fe spherules indicative of vehicular combustion processes. This study advocates rapid and simple initial assessment of urban pollution episodes using mineral magnetic measurements as a dynamic explorative technology.

Large-eddy simulation of approaching-flow stratification on dispersion over arrays of buildings

The study investigates thermal stratification effects of approach flows on dispersion in urban environments. This is in some ways analogous to a well-developed non-neutral flow (e.g. through a large urban area) approaching a neighbourhood-scale urban region, where the effect of the local heat transfer was assumed less important. A generic urban-type geometry, i.e. a group of staggered cubes, was taken as the first test case. The DAPPLE site, which was about a one-km2 region near the intersection of Marylebone Road and Gloucester Place in central London, was taken as the second test case. Only weakly unstable conditions (i.e. bulk Richardson number Rb≥−0.2) of approach flows were considered, with adiabatic boundary conditions at the ground and building surfaces. A number of numerical experiments were performed. The modelled mean concentration for Rb = −0.1 gave the best agreement with the field data at all DAPPLE stations. This suggests that stratification effects on dispersion in weakly unstable conditions (e.g. in London) are not negligible.

Exploring the processes governing roadside pollutant concentrations in urban street canyon

This paper describes an in-depth analysis to investigate the huge variation in the measured roadside air-pollutant concentrations of carbon monoxide and nitrogen dioxide in terms of the traffic flow levels, the orientation of the street to the prevailing wind, the wind speed, temperature and barometric pressure. The work has attempted to develop generic parameters that can be applied to other urban areas. However, in the absence of a measure of congestion at the site in Palermo (Italy), the methodological approach proposed used the simultaneous noise measurements, in units of decibels (B), to help parameterise a generic congestion indicator in terms of the traffic flow. The potential transferability of the approach was demonstrated for a site in Marylebone Road, London (UK), given the similarity of the two study sites, canyon shape, traffic characteristics and road orientation. The results showed that, within the range of data available, noise levels could be used as a proxy for flow change on the shoulders of the peak hour and hence congestion and a generic relationship with factors statistically significant at 99% confidence allows roadside concentrations due to traffic to be estimated with a regression coefficient of R(2) = 0.73 (R = 0.85). The research demonstrates that whilst there are indeed underlying relationships that can explain the roadside concentrations based on traffic and meteorological conditions, evidence is presented that confirms the complexity of the physical and chemical processes that govern roadside concentrations.

City breathability as quantified by the exchange velocity and its spatial variation in real inhomogeneous urban geometries: An example from central London urban area

The breathability capacity and its spatial variation within an inhomogeneous urban area is investigated by examining the air flow and the induced flow exchange processes inside a real neighbourhood area of central London. The variation of the exchange velocity (as an index of city breathability) is interpreted in association with the local urban geometrical parameters and hence geometrical inhomogeneity. Numerical studies addressing flow exchange processes in urban areas have addressed so far rather idealised homogeneous geometries (e.g. Hamlyn and Britter, 2005; Salizzoni et al., 2009; Buccolieri et al., 2010; Hang et al., 2009 and 2010). This work analyses the results obtained from a Computational Fluid Dynamics (CFD) simulation study using a Reynolds–Average–Navier–Stokes (RANS) solver to study the flow and induced exchange processes in the area around the Marylebone Road and Gloucester Place intersection modelled at a 1:200 scale, with the wind direction blowing in the direction of the Marylebone street axis. Flow visualisations from the numerical results confirm that the particular building shapes and street canyon geometries determine the shape and size of vortical structures that are present in the flow field and thereby the exchange processes with the flow above. By considering appropriate control volumes enclosing each building, the exchange velocities, UE, were deduced and found to range between 0.5% and 13% of the characteristic velocity above the urban canopy Uref, which was referenced at a height 2.5 times of the building height. The range of the exchange velocity coefficient UE/Uref is higher than that observed in idealised regular cube arrays, mainly due to the enhanced flow mixing associated with the inhomogeneity of the urban geometry and particularly with tall buildings. This work may provide useful insight to urban designers and planners interested in examining the variation of city breathability as a local dynamic morphological parameter with the local building packing density.

Estimation of the Contributions of Brake Dust, Tire Wear, and Resuspension to Nonexhaust Traffic Particles Derived from Atmospheric Measurements

Size-fractionated samples of airborne particulate matter have been collected in a number of campaigns at Marylebone Road, London and simultaneously at background sites either in Regents Park or at North Kensington. Analysis of these samples has enabled size distributions of total mass and of a number of elements to be determined, and roadside increments attributable to nonexhaust emissions arising from traffic activity have been calculated. Taking a novel approach, the combined use of size distribution information and tracer elements has allowed the separate estimation of the contributions of brake dust, tire dust, and resuspension to particle mass in the range 0.9-11.5 μm aerodynamic diameter and mean contributions (± s.e.) at the Marylebone Road sampling site are estimated as resuspended dust 38.1 ± 9.7%, brake dust 55.3 ± 7.0%, and tire dust 10.7 ± 2.3%, (accounting for a total of 104.1% of coarse particle mass in the traffic increment above background).

SHAW'S LONDON THEN AND NOW

SHAW'S LONDON THEN AND NOW