A large number of policy initiatives are being taken at the European level, across the United Kingdom and in London to improve air quality and reduce population exposure to harmful pollutants from ...traffic emissions. Trends in roadside increments of nitrogen oxides (NOX), nitrogen dioxide (NO2), particulate matter (PM), black carbon (CBLK) and carbon dioxide (CO2) were examined at 65 London monitoring sites for two periods of time: 2005–2009 and 2010–2014. Between 2005 and 2009 there was an overall increase in NO2 reflecting the growing evidence of real world emissions from diesel vehicles. Conversely, NO2 decreased by 10%·year−1 from 2010 onwards along with PM2.5 (−28%·year−1) and black carbon (−11%·year−1). Downwards trends in air pollutants were not fully explained by changes in traffic counts therefore traffic exhaust emission abatement policies were proved to be successful in some locations. PM10 concentrations showed no significant overall change suggesting an increase in coarse particles which offset the decrease in tailpipe emissions; this was especially the case on roads in outer London where an increase in the number of Heavy Good Vehicles (HGVs) was seen. The majority of roads with increasing NOX experienced an increase in buses and coaches. Changes in CO2 from 2010 onwards did not match the downward predictions from reduced traffic flows and improved fleet efficiency. CO2 increased along with increasing HGVs and buses. Polices to manage air pollution provided differential benefits across London's road network. To investigate this, k-means clustering technique was applied to group roads which behaved similarly in terms of trends to evaluate the effectiveness of policies to mitigate traffic emissions. This is the first time that London's roadside monitoring sites have been considered as a population rather than summarized as a mean behaviour only, allowing greater insight into the differential changes in air pollution abatement policies.
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•Short-term trends in roadside increments of air pollutants along 65 roads in London.•Great variability of response to abatement policies across London's roads.•General decrease of NOX and NO2 concentrations in 2010–2014.•Roads with increased NOX observed more buses and heavy good vehicles.•PM2.5 concentrations decreased along with black carbon; PM10 coarse increased.
Trends in roadside air pollutants in London: results from a large population of monitoring sites.
Paris and London are Europe's two megacities and both experience poor air quality with systemic breaches of the NO2 limit value. Policy initiatives have been taken to address this: some European-wide ...(e.g. Euro emission standards); others local (e.g. Low Emission Zone, LEZ). Trends in NOX, NO2 and particulate matter (PM10, PM2.5) for 2005–2016 in background and roadside locations; and trends in traffic increments were calculated in both cities to address their impact. Trends in traffic counts and the distribution in Euro standards for diesel vehicles were also evaluated. Linear-mixed effect models were built to determine the main determinants of traffic concentrations. There was an overall increase in roadside NO2 in 2005–2009 in both cities followed by a decrease of ∼5% year−1 from 2010. Downward trends were associated with the introduction of Euro V heavy vehicles. Despite NO2 decreasing, at current rates, roads will need 20 (Paris) and 193 years (London) to achieve the European Limit Value (40 μg m−3 annual mean). Euro 5 light diesel vehicles were associated with the decrease in roadside PM10. An increase in motorcycles in London since 2010 contributed to the lack of significant trend in PM2.5 roadside increment in 2010–16.
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•NO2 and PM concentrations from traffic decreased from 2010–16 in Paris and London.•Euro V diesel heavy vehicles induced downward trends in roadside NO2.•Effective reduction in traffic PM10 concentrations with of Euro 5 diesel lights.•London observed faster decrease on PM10 concentrations from traffic than Paris.•An increase in motorcycles in London caused higher roadside PM2.5 concentrations.
Trends in air pollutants in Europe's megacities.
A chronology of global air quality
Philosophical transactions - Royal Society. Mathematical, Physical and engineering sciences/Philosophical transactions - Royal Society. Mathematical, physical and engineering sciences,
10/2020
Journal Article
Vehicle-related particulate matter (PM) emissions may arise from both exhaust and non-exhaust mechanisms, such as brake wear, tire wear, and road pavement abrasion, each of which may be emitted ...directly and indirectly through resuspension of settled road dust. Several researchers have indicated that the proportion of PM2.5 attributable to vehicle traffic will increasingly come from non-exhaust sources. Currently, very little empirical data is available to characterize tire and road wear particles (TRWP) in the PM2.5 fraction. As such, this study was undertaken to quantify TRWP in PM2.5 at roadside locations in urban centers including London, Tokyo and Los Angeles, where vehicle traffic is an important contributor to ambient air PM. The samples were analyzed using validated chemical markers for tire tread polymer based on a pyrolysis technique. Results indicated that TRWP concentrations in the PM2.5 fraction were low, with averages ranging from < 0.004 to 0.10 µg/m3, representing an average contribution to total PM2.5 of 0.27%. The TRWP levels in PM2.5 were significantly different between the three cities, with significant differences between London and Los Angeles and Tokyo and Los Angeles. There was no significant correlation between TRWP in PM2.5 and traffic count. This study provides an initial dataset to understand potential human exposure to airborne TRWP and the potential contribution of this non-exhaust emission source to total PM2.5.
ABSTRACT
The formation of stellar clusters dictates the pace at which galaxies evolve, and solving the question of their formation will undoubtedly lead to a better understanding of the Universe as a ...whole. While it is well known that star clusters form within parsec-scale overdensities of interstellar molecular gas called clumps, it is, however, unclear whether these clumps represent the high-density tip of a continuous gaseous flow that gradually leads towards the formation of stars, or a transition within the gas physical properties. Here, we present a unique analysis of a sample of 27 infrared dark clouds embedded within 24 individual molecular clouds that combine a large set of observations, allowing us to compute the mass and velocity dispersion profiles of each, from the scale of tens of parsecs down to the scale of tenths of a parsec. These profiles reveal that the vast majority of the clouds, if not all, are consistent with being self-gravitating on all scales, and that the clumps, on parsec-scale, are often dynamically decoupled from their surrounding molecular clouds, exhibiting steeper density profiles (ρ∝r−2) and flat velocity dispersion profiles (σ∝r0), clearly departing from Larson’s relations. These findings suggest that the formation of star clusters correspond to a transition regime within the properties of the self-gravitating molecular gas. We propose that this transition regime is one that corresponds to the gravitational collapse of parsec-scale clumps within otherwise stable molecular clouds.
We show that hydrodynamic turbulent cloud simulations naturally produce large filaments made up of a network of smaller and coherent subfilaments. Such simulations resemble observations of filaments ...and fibres in nearby molecular clouds. The subfilaments are dynamical features formed at the stagnation points of the turbulent velocity field where shocks dissipate the turbulent energy. They are a ubiquitous feature of the simulated clouds, which appear from the beginning of the simulation and are not formed by gradual fragmentation of larger filaments. Most of the subfilaments are gravitationally subcritical and do not fragment into cores, however, there is also a significant fraction of supercritical subfilaments which break up into star-forming cores. The subfilaments are coherent along their length, and the residual velocities along their spine show that they are subsonically contracting without any ordered rotation on scales of ∼0.1 pc. Accretion flows along the subfilaments can feed material into star-forming cores embedded within the network. The overall mass in subfilaments and the number of subfilaments increases as the cloud evolves. We propose that the formation of filaments and subfilaments is a natural consequence of the turbulent cascade in the complex multiphase interstellar medium. Subfilaments are formed by the high wavenumber, small-scale modes in the turbulent velocity field. These are then stretched by local shear motions and gathered together by a combination of low wavenumber modes and gravitational contraction on larger scales, and by doing so build up the extended filaments observed in column density maps.
The initial physical conditions of high-mass stars and protoclusters remain poorly characterized. To this end, we present the first targeted ALMA Band 6 1.3 mm continuum and spectral line survey ...toward high-mass starless clump candidates, selecting a sample of 12 of the most massive candidates ( ) within . The joint array maps have a high spatial resolution of ( , θsyn 0 8) and have high point-source mass-completeness down to at (or column density sensitivity of ). We discover previously undetected signposts of low-luminosity star formation from and bipolar outflows and other signatures toward 11 out of 12 clumps, showing that current MIR/FIR Galactic plane surveys are incomplete to low- and intermediate-mass protostars ( ), and emphasizing the necessity of high-resolution follow-up. We compare a subset of the observed cores with a suite of radiative transfer models of starless cores. We find a high-mass starless core candidate with a model-derived mass consistent with when integrated over size scales of . Unresolved cores are poorly fit by radiative transfer models of externally heated Plummer density profiles, supporting the interpretation that they are protostellar even without detection of outflows. A high degree of fragmentation with rich substructure is observed toward 10 out of 12 clumps. We extract sources from the maps using a dendrogram to study the characteristic fragmentation length scale. Nearest neighbor separations, when corrected for projection with Monte Carlo random sampling, are consistent with being equal to the clump average thermal Jeans length ( ; i.e., separations equal to ). In the context of previous observations that, on larger scales, see separations consistent with the turbulent Jeans length or the cylindrical thermal Jeans scale ( ), our findings support a hierarchical fragmentation process, where the highest-density regions are not strongly supported against thermal gravitational fragmentation by turbulence or magnetic fields.
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•Particle size distributions and noise levels were measured at two locations near Gatwick airport in 2018–19.•Peak particle number concentrations (PNC) were highest at the site closer ...to the runway.•Source apportionment identified six factors at each site with the airport source factor contributing 17%.•The largest source of noise above background was associated with sources of fresh traffic and urban particles depending on the site.•PNC is unlikely to be an important confounder in epidemiological studies of aircraft noise and health near airports.
There is increasing evidence of potential health impacts from both aircraft noise and aircraft-associated ultrafine particles (UFP). Measurements of noise and UFP are however scarce near airports and so their variability and relationship are not well understood. Particle number size distributions and noise levels were measured at two locations near Gatwick airport (UK) in 2018–19 with the aim to characterize particle number concentrations (PNC) and link PNC sources, especially UFP, with noise. Positive Matrix Factorization was used on particle number size distribution to identify these sources. Mean PNC (7500–12,000 p cm−3) were similar to those measured close to a highly trafficked road in central London. Peak PNC (94,000 p cm−3) were highest at the site closer to the runway. The airport source factor contributed 17% to the PNC at both sites and the concentrations were greatest when the respective sites were downwind of the runway. However, the main source of PNC was associated with traffic emissions. At both sites noise levels were above the recommendations by the WHO (World Health Organisation). Regression models of identified UFP sources and noise suggested that the largest source of noise (LAeq-1hr) above background was associated with sources of fresh traffic and urban UFP depending on the site. Noise and UFP correlations were moderate to low suggesting that UFP are unlikely to be an important confounder in epidemiological studies of aircraft noise and health. Correlations between UFP and noise were affected by meteorological factors, which need to be considered in studies of short-term associations between aircraft noise and health.
Due to a lack of routine monitoring, bespoke measurements are required to develop ultrafine particle (UFP) land use regression (LUR) models, which is especially challenging in megacities due to their ...large area. As an alternative, for London, we developed separate models for three urban residential areas, models combining two areas, and models using all three areas. Models were developed against annual mean ultrafine particle count cm−3 estimated from repeated 30-min fixed-site measurements, in different seasons (2016–2018), at forty sites per area, that were subsequently temporally adjusted using continuous measurements from a single reference site within or close to each area. A single model and 10 models were developed for each individual area and combination of areas. Within each area, sites were split into 10 groups using stratified random sampling. Each of the 10 models were developed using 90% of sites. Hold-out validation was performed by pooling the 10% of sites held-out each time. The transferability of models was tested by applying individual and two-area models to external area(s). In model evaluation, within-area mean squared error (MSE) R2 ranged from 14% to 48%. Transferring individual- and combined-area models to external areas without calibration yielded MSE-R2 ranging from −18 to 0. MSE-R2 was in the range 21% to 41% when using particle number count (PNC) measurements in external areas to calibrate models. Our results suggest that the UFP models could be transferred to other areas without calibration in London to assess relative ranking in exposures but not for estimating absolute values of PNC.
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•The first time that transferability of LUR models for UFP within a megacity has been evaluated•Repeated 30-min monitoring of UFP particle number at 40 sites in three residential areas in London•Single- and two-area models were transferred between residential areas in London.•Performance of models within areas for which they were developed was moderate to good•Models without calibration performed poorly when transferred to other areas due to increases in bias.
•Ultrafine particle sources were identified and quantified in four European cities.•Common sources were Photonucleation, different Traffic sources, and Secondary.•Maximum contribution of traffic ...sources ranged 71–94% of total particle number.•Airport emissions contributed to nucleation particles in urban background areas.
Ultrafine particles (UFP) are suspected of having significant impacts on health. However, there have only been a limited number of studies on sources of UFP compared to larger particles. In this work, we identified and quantified the sources and processes contributing to particle number size distributions (PNSD) using Positive Matrix Factorization (PMF) at six monitoring stations (four urban background and two street canyon) from four European cities: Barcelona, Helsinki, London, and Zurich. These cities are characterised by different meteorological conditions and emissions. The common sources across all stations were Photonucleation, traffic emissions (3 sources, from fresh to aged emissions: Traffic nucleation, Fresh traffic – mode diameter between 13 and 37 nm, and Urban – mode diameter between 44 and 81 nm, mainly traffic but influenced by other sources in some cities), and Secondary particles. The Photonucleation factor was only directly identified by PMF for Barcelona, while an additional split of the Nucleation factor (into Photonucleation and Traffic nucleation) by using NOx concentrations as a proxy for traffic emissions was performed for all other stations. The sum of all traffic sources resulted in a maximum relative contributions ranging from 71 to 94% (annual average) thereby being the main contributor at all stations. In London and Zurich, the relative contribution of the sources did not vary significantly between seasons. In contrast, the high levels of solar radiation in Barcelona led to an important contribution of Photonucleation particles (ranging from 14% during the winter period to 35% during summer). Biogenic emissions were a source identified only in Helsinki (both in the urban background and street canyon stations), that contributed importantly during summer (23% in urban background). Airport emissions contributed to Nucleation particles at urban background sites, as the highest concentrations of this source took place when the wind was blowing from the airport direction in all cities.
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