55 research outputs found
The application of frustrated total internal reflection devices to analytical laser spectroscopy
No full textAir quality study within steel works town in the UK
No full textIn April/May 2012, aerosol filter measurements were carried out in and around the coastal town of Port Talbot in South Wales which has an approximate population of 35,000 and is located on the M4 corridor (51 34' N and 3°46' W). The town sites one of the UK steel manufacturing plants owned by Tata and is the main source affecting air quality in the area (AQEG, 2010). The site covers approximately 28 km2, comprises of ~50km of roads, 100 km of railway, and 25,000 vehicle movements per day. The production capacity is around 5m tonnes per year with the main processes in the steelworks being iron-making (sintering, blast furnace and raw materials), steel-making (basic oxygen steel-making (BOS) and coking) and rolling mills (hot and cold mills) (Moreno et al., 2004; Dall’Osto et al., 2008).
Instruments were deployed at four sites around the perimeter of the steel works (one at a coastal site (Little Warren LW) and the remain in 3 inland sites placed along the length of the works (Fire Station FS, Prince Street PS and Dyffryn School DS) in the study area for a four-week campaign (16th April to 16th May, 2012) (see Figure 1). With a view to measuring elements and water soluble ions within the fine and coarse fraction, our main site was located at FS where we deployed: a micro-orifice uniform deposit impactor (MOUDI) (3 day samples); a Partisol Dichotomous sampler (daily sample); a Streaker sampler (hourly samples); an Aerosol time-of-flight Mass Spectrometry (ATOFMS); a GRIMM particle size spectrometer and an Aethalometer.
Figure 1. Overview of the sampling sites used in
Port Talbot.
Gaseous and meteorological data measured during the period of sampling were also collected from the Automatic Urban and Rural Network (AURN) located next to the FS site. This main site was in itself complemented by 3 other sampling sites where we deployed another 3 Partisol samples (24 hr sampling rate). At our coastal site, we ran a second Streaker sampler, which when paired with the FS Streaker, collected data to measures the increment in PM caused by the steel works.
An example the results with huge peaks of Fe and Mn detected in one of the sites nearby the steel works is reported in Figure 2
Given this large data set of elements, ions and chemical species, our aim was to assess the impact of the steel works on the local area and in particular understand the nature of PM episodes detected by ongoing continuous PM measurements within the area which were suspected to be generated by fugitive dusts.
References.
Dall'Osto, M., Booth, A, M.J., Smith, W., Fisher, R., Harrison, R.M., 2008. Study of the size distributions and the chemical characterization of airborne particles in the vicinity of a large integrated steelworks. Aerosol Science and Technology 42, 981–991.
Moreno, T., Jones, T.P., Richards, R.J., (2004), Characterisation of aerosol particulate matter from urban and industrial environments: examples from Cardiff and Port Talbot, South Wales, UK, Science of The Total Environment Volumes 334–335, 1 December 2004, Pages 337–346.
The National Centre for Atmospheric Science, University of Birmingham, is gratefully acknowledged for funding the fieldwork
Sensitive and selective spectrochemical analysis of metallic samples: the combination of laser-induced breakdown spectroscopy and laser-induced fluorescence spectroscopy
No full textThe effect of varying primary emissions on the concentrations of inorganic aerosols predicted by the enhanced UK Photochemical Trajectory Model
No full textAn enhanced Photochemical Trajectory Model (PTM) has been used to simulate concentrations of secondary inorganic aerosol (for the purposes of this work, sulphate, nitrate, chloride and ammonium) in PM over a two-month period at a rural site in central southern England (Harwell). Judged against a base year of 2007, emissions of precursor gases, SO, NO and NH have been varied over plausible ranges, occurring across the UK only, mainland Europe only, or the whole of Europe. The model is able to reproduce observed non-linearities and shows that abatement is less than proportional in all cases. Additionally, abatement of sulphur dioxide leads to increased nitrate concentrations. The combination of a weak response of nitrate to reductions in NO emissions, and the effect of sulphur dioxide reductions in increasing nitrate is consistent with the very small recent observed trends in nitrate concentrations over the UK. A scenario for 2020 in which emissions of SO, NO and NH fall to 64%, 75% and 96% respectively of their 2007 baseline levels across the whole of Europe shows a reduction of 2 μg m in secondary inorganic aerosol which is 13% below the baseline case for a two month period in 2007, due mostly to a fall in sulphate and ammonium. As this was a relatively high pollution period, it is estimated that over a full year, the reduction is more likely to be around 1 μg m
Identification of specific sources of airborne particles emitted from within a complex industrial (steelworks) site
No full textA case study is provided of the development and application of methods to identify and quantify specific sources of emissions from within a large complex industrial site. Methods include directional analysis of concentrations, chemical source tracers and correlations with gaseous emissions. Extensive measurements of PM10, PM2.5, trace gases, particulate elements and single particle mass spectra were made at sites around the Port Talbot steelworks in 2012. By using wind direction data in conjunction with real-time or hourly-average pollutant concentration measurements, it has been possible to locate areas within the steelworks associated with enhanced pollutant emissions. Directional analysis highlights the Slag Handling area of the works as the most substantial source of elevated PM10 concentrations during the measurement period. Chemical analyses of air sampled from relevant wind directions is consistent with the anticipated composition of slags, as are single particle mass spectra. Elevated concentrations of PM10 are related to inverse distance from the Slag Handling area, and concentrations increase with increased wind speed, consistent with a wind-driven resuspension source. There also appears to be a lesser source associated with Sinter Plant emissions affecting PM10 concentrations at the Fire Station monitoring site. The results are compared with a ME2 study using some of the same data, and shown to give a clearer view of the location and characteristics of emission sources, including fugitive dusts
Urban aerosol size distributions over the Mediterranean city of Barcelona, NE Spain
No full textDifferential mobility particle sizer (DMPS) aerosol concentrations (N13-800) were collected over a one-year-period (2004) at an urban background site in Barcelona, North-Eastern Spain. Quantitative contributions to particle number concentrations of the nucleation (33-39%), Aitken (39-49%) and accumulation mode (18-22%) were estimated. We examined the source and time variability of atmospheric aerosol particles by using both K-means clustering and Positive Matrix Factorization (PMF) analysis. Performing clustering analysis on hourly size distributions, nine K-means DMPS clusters were identified and, by directional association, diurnal variation and relationship to meteorological and pollution variables, four typical aerosol size distribution scenarios were identified: traffic (69% of the time), dilution (15% of the time), summer background conditions (4% of the time) and regional pollution (12% of the time). According to the results of PMF, vehicle exhausts are estimated to contribute at least to 62-66% of the total particle number concentration, with a slightly higher proportion distributed towards the nucleation mode (34%) relative to the Aitken mode (28-32%). Photochemically induced nucleation particles make only a small contribution to the total particle number concentration (2-3% of the total), although only particles larger than 13 nm were considered in this study. Overall the combination of the two statistical methods is successful at separating components and quantifying relative contributions to the particle number population. © 2012 Author(s)
Transcriptomic identification of starfish neuropeptide precursors yields new insights into neuropeptide evolution
No full textPublished by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.This work was supported by a PhD studentship funded by QMUL and awarded to D.C.S. and a Leverhulme Trust grant (RPG-
2013-351) awarded to M.R.E. Sequencing of the A. rubens neural transcriptome was funded by an EPSRC grant (EP/J501360/1
Simplifying aerosol size distributions modes simultaneously detected at four monitoring sites during SAPUSS
No full textThe analysis of aerosol size distributions is a useful tool for
understanding the sources and the processes influencing particle number
concentrations (N) in urban areas. Hence, during the one-month SAPUSS
campaign (Solving Aerosol Problems by Using Synergistic Strategies, EU Marie
Curie Action) in autumn 2010 in Barcelona (Spain), four SMPSs (Scanning
Mobility Particle Sizer) were simultaneously deployed at four monitoring
sites: a road side (RSsite), an urban background site located in the
city (UBsite), an urban background site located in the nearby hills of the
city (Torre Collserola, TCsite) and a regional background site located
about 50 km from the Barcelona urban areas (RBsite). The spatial
distribution of sites allows study of the aerosol temporal variability as
well as the spatial distribution, progressively moving away from urban
aerosol sources. In order to interpret the data sets collected, a k-means
cluster analysis was performed on the combined SMPS data sets. This resulted
in nine clusters describing all aerosol size distributions from the four
sites. In summary there were three main categories (with three clusters in
each category): "Traffic" (Traffic 1, "Tclus_1" – 8%;
Traffic 2, "Tclus_2" – 13%; and Traffic 3,
"Tclus_3" – 9%) "Background Pollution" (Urban
Background 1, "UBclus_1" – 21%; Regional Background 1,
"RBclus_1" – 15%; and Regional Background 2,
"RBclus_2" – 18%) and "Special Cases" (Nucleation,
"NUclus" – 5%; Regional Nitrate, "NITclus" – 6%; and
Mix, "MIXclus" – 5%). As expected, the frequency of traffic clusters
(Tclus_1–3) followed the order RSsite, UBsite,
TCsite, and RBsite. These showed typical traffic modes mainly
distributed at 20–40 nm. The urban background sites (UBsite and
TCsite) reflected also as expected urban background number
concentrations (average values, N = 1.0 × 104 cm−3
and N = 5.5 × 103 cm−3, respectively, relative to
1.3 × 104 cm−3 seen at RSsite). The cluster
describing the urban background pollution (UBclus_1)
could be used to monitor the sea breeze circulation towards the regional
background study area. Overall, the RBsite was mainly characterised by
two different regional background aerosol size distributions: whilst both
exhibited low N (2.7 × 103 for RBclus_1
and 2.2 × 103 cm−3 for RBclus_2),
RBclus_1 had average PM10 concentrations higher
than RBclus_2 (27 vs. 23 μg m−3). As regards
the minor aerosol size distribution clusters, the "Nucleation" cluster was
observed during daytime, whilst the "Regional Nitrate" was mainly seen at
night. The ninth cluster ("Mix") was the least well defined and likely
composed of a number of aerosol sources.
When correlating averaged values of N, NO2 and PM (particulate mass)
for each k-means cluster, a linear correlation between N and NO2 with
values progressively increasing from the regional site RBsite to the
road site RSsite was found. This points to vehicular traffic as the
main source of both N and NO2. By contrast, such an association does
not exist for the case of the nucleation cluster, where the highest N is
found with low NO2 and PM.
Finally, the clustering technique allowed study of the impact of
meteorological parameters on the traffic N emissions. This study confirms
the shrinking of freshly emitted particles (by about 20% within 1 km in
less than 10 min; Dall'Osto et al., 2011a) as particles
are transported from the traffic hot spots towards urban background
environments. Additionally, for a given well-defined aerosol size
distribution (Tclus_2) associated with primary aerosol
emissions from road traffic we found that N5–15 nm concentrations can
vary up to a factor of eight.
Within our measurement range of SMPSs (N15–228 nm) and Condensation
Particle Counters (CPCs, N>5 nm), we found that ultrafine particles
within the range 5–15 nm in urban areas are the most dynamic, being a
complex ensemble of primary evaporating traffic particles, traffic tailpipe
new particle formation and non-traffic new particle formation
On the contribution of organics to the North East Atlantic aerosol number concentration
No full textk-means statistical-cluster analysis of submicron aerosol size distributions is combined with coincident humidity tandem differential mobility analyser data, leading to five unique aerosol categories for hygroscopic growth factors (HGFs): low sea-salt background marine, high sea-salt background marine, coastal nucleation, open ocean nucleation and anthropogenically influenced scenarios. When considering only marine conditions, and generic aerosol species associated with this environment (e.g. non-sea-salt sulfate, sea-salt, partly soluble organic matter and water insoluble organic matter), the two-year annual average contribution to aerosol number concentration from the different generic species was made up as follows: 46% (30-54%) of partially modified ammonium sulfate particles; 23% (11-40%) of partially modified sea-salt; and the remaining 31% (25-35%) contribution attributed to two distinct organic species as evidenced by different, but low, HGFs. The analysis reveals that on annual timescales, ∿30% of the submicron marine aerosol number concentration is sourced from predominantly organic aerosol while 60% of the anthropogenic aerosol number is predominantly organic. Coastal nucleation events show the highest contribution of the lowest HGF mode (1.19), although this contribution is more likely to be influenced by inorganic iodine oxides. While organic mass internally mixed with inorganic salts will lower the activation potential of these mixed aerosol types, thereby potentially reducing the concentration of cloud condensation nuclei (CCN), pure organic water soluble particles are still likely to be activated into cloud droplets, thereby increasing the concentration of CCN. A combination of dynamics and aerosol concentrations will determine which effect will prevail under given conditions. © 2012 IOP Publishing Ltd
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