290 research outputs found
Source apportionment of wide range particle size spectra and black carbon collected at the airport of Venice (Italy)
No full textAtmospheric particles are of high concern due to their toxic properties and effects on climate, and large airports are known as significant sources of particles. This study investigates the contribution of the Airport of Venice (Italy) to black carbon (BC), total particle number concentrations (PNC) and particle number size distributions (PNSD) over a large range (14 nm to 20 μm). Continuous measurements were conducted between April and June 2014 at a site located 110 m from the main taxiway and 300 m from the runway. Results revealed no significantly elevated levels of BC and PNC, but exhibited characteristic diurnal profiles. PNSD were then analyzed using both k-means cluster analysis and positive matrix factorization. Five clusters were extracted and identified as midday nucleation events, road traffic, aircraft, airport and nighttime pollution. Six factors were apportioned and identified as probable sources according to the size profiles, directional association, diurnal variation, road and airport traffic volumes and their relationships to micrometeorology and common air pollutants. Photochemical nucleation accounted for ~44% of total number, followed by road+shipping traffic (26%). Airport-related emissions accounted for ~20% of total PNC and showed a main mode at 80 nm and a second mode beyond the lower limit of the SMPS (<14 nm). The remaining factors accounted for less than 10% of number counts, but were relevant for total volume concentrations: nighttime nitrate, regional pollution and local resuspension. An analysis of BC levels over different wind sectors revealed no especially significant contributions from specific directions associated with the main local sources, but a potentially significant role of diurnal dynamics of the mixing layer on BC levels. The approaches adopted in this study have identified and apportioned the main sources of particles and BC at an international airport located in area affected by a complex emission scenario. The results may underpin measures for improving local and regional air quality, and health impact assessment studies
Two step PMF data from London studies
No full textSome air pollution datasets contain multiple variables with a range of measurement units, and combined analysis by Positive Matrix Factorization (PMF) can be problematic, but can offer benefits from the greater information content. In this work, a novel method is devised and the source apportionment of a mixed unit data set (PM10 mass and Number Size Distribution NSD) is achieved using a novel two-step approach to PMF. In the first step the PM10 data is 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 PM10 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 PM10 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 PM10 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 PM10 mass
Sources of sub-micrometre particles near a major international airport
No full textThe international airport of Heathrow is a major source of nitrogen oxides, but its contribution to the levels of sub-micrometre
particles is unknown and is the objective of this study. Two sampling campaigns were carried out during warm and cold seasons at
a site close to the airfield (1.2 km). Size spectra were largely dominated by ultrafine particles: nucleation particles ( < 30 nm) were found to be ∼ 10 times higher than those commonly measured in urban background environments of London. Five
clusters and six factors were identified by applying k means cluster analysis and positive matrix factorisation (PMF), respectively, to
particle number size distributions; their interpretation was based on their modal structures, wind directionality, diurnal patterns,
road and airport traffic volumes, and on the relationship with weather and other air pollutants. Airport emissions, fresh and aged
road traffic, urban accumulation mode, and two secondary sources were then identified and apportioned. The fingerprint of Heathrow has
a characteristic modal structure peaking at < 20 nm and accounts for 30–35 % of total particles in both the
seasons. Other main contributors are fresh (24–36 %) and aged (16–21 %) road traffic emissions and urban accumulation from
London (around 10 %). Secondary sources accounted for less than 6 % in number concentrations but for more than 50 % in
volume concentration. The analysis of a strong regional nucleation event showed that both the cluster categorisation and PMF
contributions were affected during the first 6 h of the event. In 2016, the UK government provisionally approved the construction of
a third runway; therefore the direct and indirect impact of Heathrow on local air quality is expected to increase unless mitigation
strategies are applied successfully
Pinpointing sources of pollution using citizen science and hyperlocal low-cost mobile source apportionment
No full textCurrently, methodologies for the identification and apportionment of air pollution sources are not widely applied due to their high cost. We present a new approach, combining mobile measurements from multiple sensors collected from the daily walks of citizen scientists, in a high population density area of Birmingham, UK. The methodology successfully pinpoints the different sources affecting the local air quality in the area using only a handful of measurements. It was found that regional sources of pollution were mostly responsible for the PM2.5 and PM1 concentrations. In contrast, PM10 was mostly associated with local sources. The total particle number and the lung deposited surface area of PM were almost solely associated with traffic, while black carbon was associated with both the sources from the urban background and local traffic. Our analysis showed that while the effect of the hyperlocal sources, such as emissions from construction works or traffic, do not exceed the distance of a couple of hundred meters, they can influence the health of thousands of people in densely populated areas. Thus, using this novel approach we illustrate the limitations of the present measurement network paradigm and offer an alternative and versatile approach to understanding the hyperlocal factors that affect urban air quality. Mobile monitoring by citizen scientists is shown to have huge potential to enhance spatiotemporal resolution of air quality data without the need of extensive and expensive campaigns
Receptor modelling of both particle composition and size distribution from a background site in London, UK - a two step approach
No full textSome 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. </p
Two step PMF data from London studies
No full textSome air pollution datasets contain multiple variables with a range of measurement units, and combined analysis by Positive Matrix Factorization (PMF) can be problematic, but can offer benefits from the greater information content. In this work, a novel method is devised and the source apportionment of a mixed unit data set (PM10 mass and Number Size Distribution NSD) is achieved using a novel two-step approach to PMF. In the first step the PM10 data is 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 PM10 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 PM10 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 PM10 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 PM10 mass
Size distribution of airborne particles controls outcome of epidemiological studies
No full textEpidemiological studies typically using wide size range mass metrics (e.g. PM(10)) have demonstrated associations between airborne particulate matter and several adverse health outcomes. This approach ignores the fact that mass concentration may not correlate with regional lung dose, unlike the case of trace gases. When using measured particle size distributions as the basis for calculating regional lung dose, PM(10) mass concentration is found to be a good predictor of the mass dose in all regions of the lung, but is far less predictive of the surface area and particle number dose. On the other hand, measurements of particle number do not well predict mass dose, indicating that the chosen particle metric is likely to determine the health outcomes detectable by an epidemiological study. Consequently, epidemiological studies using mass metrics (PM(2.5) and PM(10)) may fail to recognise important health consequences of particulate matter exposure, leading to an underestimate of the public health consequences of particle exposure
History at Play in the Portrayal of Politicians in Canadian Drama
No full textThis thesis intends to focus on certain playwrights’ creative fascination and complex relationship with ‘politicians as subject’ who have been elevated to the rank of ‘greatness’ in part through their work. More specifically, it serves as a study into how playwrights mold certain politicians’ images, a type of creative investment that in turn helps craft, (re) affirm, or deconstruct the politician as a ‘cultural symbol.’ Using a historigraphic model based on Paul Ricoeur and Hayden White’s work, this thesis explores the dramaturgical approaches used by ‘artist-historian’ playwrights when creating dramatic figures inspired by Canadian politicians. In particular, it examines Linda Griffiths’ portrayal of Pierre Elliot Trudeau in Maggie and Pierre, David Fennario’s portrayal of René Lévesque in The Death of René Lévesque, and Allan Stratton’s portrayal of William Lyon Mackenzie King in Rexy
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
No full text11 pages, supporting information http://pubs.acs.org/doi/suppl/10.1021/es506249zPositive 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. © 2015 American Chemical SocietyPeer Reviewe
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