Air quality expert group - Fine particulate matter (PM2.5) in ... - Defra

PM2.5 in the UK
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measurements and gas phase pollutant data in the model will also assist
in identifying the location of sources. The combined dataset of sizeresolved
and chemically-speciated particle concentrations, together with
meteorological data and gaseous pollutant concentrations, will be a very
powerful probe into the sources.
65. Receptor modelling in Europe has used a number of methods and lacks overall
co-ordination (Viana et al., 2008). Compositional data for PM10 and PM2.5
are available from a sizeable number of European sites (Putaud et al., 2010),
but there have been rather few substantial studies in Europe, largely because
of the lack of suitable measurement datasets. One of the best recent studies
(Mooibroek et al., 2011) applied the multivariate PMF method to PM2.5 data
from the Netherlands, generating a seven factor solution. The sources identified
were nitrate-rich secondary aerosol, sulphate-rich secondary aerosol, traffic and
resuspended road dust, industrial (metal) activities/incineration, sea spray, crustal
material and residual oil combustion. The necessary comprehensive chemical
composition datasets for UK sites are very limited and the only substantial study
is Yin et al. (2010) which applied the chemical mass balance (CMB) model
to specially collected datasets from one urban and one rural site in the West
Midlands.
66. The main advantage of the CMB model is that unlike multivariate models,
no deductions are needed to establish the identity of sources. The model is
able to quantify unassigned mass and therefore gives a clear indication, not
readily available from the multivariate models, of whether sources are missing.
One of the main weaknesses of the CMB modelling approach is the need for
locally relevant source profiles, which are frequently not available from recent
measurements in Western Europe. Consequently, source chemical profiles
from North America are used and these may not be wholly representative of
UK sources, hence contributing to error. Another main weakness is that CMB
can only account for those sources which are included and, whilst as indicated
above it will quantify unassigned mass, it will give no clues as to the origins of
that mass. In addition, CMB does not readily account for secondary pollutants
or for the chemical modification of primary pollutants between source and
receptor.
67. The main advantage of multivariate statistical models is that they are able to
take account of secondary pollutants or chemical change between source and
receptor and require no a priori knowledge of the contributing sources or their
source profiles. On the other hand, there are disadvantages following from
an inability to distinguish sources of similar composition or sources whose
concentrations vary in a similar manner. It is notable from the literature that
many of the source signatures generated by multivariate methods are extremely
difficult to assign unequivocally to a given source type. This leads to uncertain
assignments and the problems which flow from that.
4.5.1 Markers of primary sources
68. There are few sources for which a single chemical tracer can be used as a
marker. Frequently sources can only be identified and quantified by use of a
combination of chemical components. Commonly used elemental tracers are
silicon or aluminium (soil and crustal dust), sodium (sea salt), barium (vehicular