Elemental Composition of Airborne Particles in Traffic-Affected Brisbane Areas

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This is the author’s version of a work that was submitted/accepted for pub-
lication in the following source:
Ayoko, Godwin, Lim, Mckenzie, & Morawska, Lidia (2003) Elemental Com-
position of Airborne Particles in Traffic-Affected Brisbane Areas. In Winch,
B (Ed.) Proceedings of National Clean Air Conference, 23 - 27 November
2003, Newcastle City Hall, New South Wales.
This file was downloaded from: http://eprints.qut.edu.au/24340/
Notice: Changes introduced as a result of publishing processes such as
copy-editing and formatting may not be reflected in this document. For a
definitive version of this work, please refer to the published source:

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ELEMENTAL COMPOSITION OF AIRBORNE PARTICLES IN
BRISBANE

McKenzie C. H. Lim, Godwin A. Ayoko and Lidia Morawska
International Laboratory for Air Quality and Health
School of Physical and Chemical Sciences
Queensland University of Technology
2 George Street
Brisbane QLD 4001

Summary

Three urban sites (Woolloongabba, ANZ stadium and QUT M block) were selected
to study the elemental composition of Total Suspended Particles (TSP) and PM2.5
airborne particles. The results of the particles elemental concentrations were
submitted for multi-criteria decision making methods, which showed that all sites
were influenced by vehicular emission, local industrial activities or crustal matter.
Woolloongabba was associated with elements from vehicle emission (Fe, Cd, Cu,
and Zn) and local industrial activities (Co). ANZ was associated with crustal matter
(Si) and QUT with elements from oil combustion (Zr, V and Mo), crustal matter (Al)
and construction activities (Sr and Mn). ANZ is the least polluted of the sites.

Keywords: urban airborne particles, elemental compositions, multivariate analysis,
source apportionment.

1. Introduction

According to the Australian Bureau of Statistics
(2002), a total of 12.8 million motor vehicles were
registered in Australia by the end of March 2002.
Among the states of Australia, Queensland recorded the
highest annual increase in the registered motor vehicles
in the past five years. Due to the wide spread use of
metallic compounds as oil additive and anti-wear agents,
a significant proportion of airborne elements in urban
areas are from traffic related emissions. Therefore, there
is a growing concern about traffic-generated pollutants
in general and airborne elements in particular. To
address this, ongoing evaluations of air quality are being
undertaken by different government agencies throughout
Australia (Hinwood and Di Marco 2002).
Among the pollutants concerned, fine particles in the
size range 0.1 to 2.5 µm (PM2.5) have been targeted
recently because of their potential health effects
(Weckwerth 2001) and ability to be transported over
long distances (Wilson 1996). Airborne particles of the
0.01 to 100 µm of diameter size range hereafter referred
to as Total Suspended Particles (TSP) are also of interest
because of their organic and inorganic constituents.
Airborne particles carry metals with potential adverse
health and ecotoxicological effects. Therefore, the toxic
properties of particles are in part due to the biochemical
activities of the metals and it is important to monitor the
presence of airborne metals in the environment (Miller
1979). Verrall et. al. (1986), Chan et. al. (1997) as well
as Thomas and Morawska (2002a) have carried out
independent investigations of the elemental composition



of aerosols in Brisbane. A common feature of their
findings is that crustal matter; industrial dust, marine
aerosol and vehicular emissions are the main
contributors of pollutants to ambient air in Brisbane.
However, no elemental composition analysis of samples
from the vicinity of ANZ stadium or Woolloongabba
busway, which was constructed in Year 2000 has been
carried out to date. Chan et. al. (1997) acknowledged
that various methods including chemical mass balance,
multivariate analysis, enrichment factor analysis and
reconstructions of major components from observed
elemental composition have been used for source
apportionments but employed only the last method,
which led to considerable overestimation of crustal
elements. Since multi-criteria decision making methods
have not been previously employed to rationalize air
quality in Brisbane, this study reports the concentrations
of a variety of elements in PM2.5 and TSP samples from
three representative urban sites in Brisbane and the
application of the multi-criteria decision making
procedures, PROMETHEE
Organisation Method for Enrichment Evaluation) and
GAIA (Geometrical Analysis for Interactive Aid)
(Espinasse et. al. 1997) to air quality in Brisbane. These
procedures have previously been applied to analytical
and environmental problems (Espinasse et. al. 1997).


(Preference Ranking

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2. Experimental Methods


2.1. Description of the Sampling Sites

Samplings were performed in the months of June to
July, 2002 during which ambient temperatures ranged
between 15 – 28oC in the day times and fell down to
10oC during the night. The south east coast of Australia
usually received a southwesterly wind of 11 to 20 km/hr
speed during this period.
Woolloongabba Concourse Area was on the street level
at a height of 7 metres away from passing buses and
opposite the main street. Samplings were conducted at
the peak hours in the morning and late afternoon.
Samples were obtained for TSP and PM2.5 on five
consecutive days. Sampling lines were positioned on a
portable trolley at the height of 0.8 metre from the
concrete floor. High flow sampling system of 0.02
m3/min flow rate was used for the collection of TSP and
PM2.5. In general, Woolloongabba urban is surrounded
by a very busy traffic flow and a range of business
activities like panel beating, cement processing and car
paint spraying. The Southeast Freeway runs through it to
the north and south while several busy urban roads
perpendicular to the Freeway connect Woolloongabba to
the eastern suburbs.
ANZ stadium is located near a busy intersection between
Kessel Road and Main Road. Sampling was carried out
at about 20 m from the intersection close to the ANZ
stadium with a forest reserve in its background. The
samplers were mounted at a height of 1.8 m high on a
sampling chamber standing on a lawn field adjacent to a
drive way. Each sample of the TSP and PM2.5 was
obtained every four consecutive days. Up to 2000
vehicles per hour travel at peak hours between 6:30 am
and 5:30 pm every day. Otherwise, less than 500
vehicles per hour were recorded. The percentages of the
types of vehicles recorded on a particular day are 88.7%
(light vehicles), 3.5% (small trucks), 3.9% (medium
trucks), 3.0% (large trucks) and 0.8% (unclassified).
QUT M Block is located on the 6th level of a building
facing the Southeast Freeway in the Queensland
University of Technology (QUT) Gardens Point
Campus. The site is within the Brisbane City and is at a
distance of 210 m from the Southeast Freeway. It is
surrounded by a Botanical Garden and Brisbane River to
the north and east respectively. Samples were obtained
over five consecutive days.

2.2. Sample Preparation and Analysis

TF-200 Teflon membrane filters of diameter 47 mm
and nominal pore-size 0.2 µm were obtained from Pall
Corporation and used as received for the collection of
total suspended particle (TSP) and PM2.5. A simple
sampling system using Pall Corporation 47 mm in-line
polycarbonate filter holder and Dekati PM10 cascade
impactor was used to collect the TSP and PM2.5
respectively. The TSP and PM2.5 filters were weighed on
a Mettler Toledo analytical balance in a room of constant
humidity (50%) and temperature (23oC). Collected
samples were stored in a glass vial at -15oC. Each vial
was wrapped with aluminium foil.
Each filter was digested in a Teflon digestion vessel
by 70% Aristar grade nitric acid and analytical reagent
grade concentrated hydrofluoric acid in a ratio of 3:1.
The digestion method is an adaptation of the nitric acid
digestion (Thomas and Morawska 2002b) and an aqua-
regia acidic mixture (Wang et. al. 1998) methods. All
samples were placed in Teflon digestion vessels with the
acidic mixture. Digestion was carried out in a CEM
microwave oven (Matthews, NC, USA) at 75 psi and
60% of 650 W power for 30 min and followed by 100%
power for 15 min. A further 60% power at 20 psi for 30
min digestion was used to ensure complete dissolution of
the elements. After digestion, the solution was diluted to
25 mL in a standard flask and stored in a polyethylene
vial. The elemental analysis was performed using
Thermal Inductively Coupled Plasma Atomic Emission
Spectrometry (ICPAES). EM Science standard element
diluted solutions at 0, 0.5, 1, 2.5 and 5 ppm were used
for calibration according to the optimized instrumental
parameters described below. The carrier gas, coolant gas
and plasma gas was argon gas at a pressure of 35 Psi. Its
monochromator was calibrated by ICP profile solution of
10 ppm of sulfur, copper and potassium to give 8400
steps. The same instrumental calibration was done on
polychromator to give about 10070 steps for sulfur and
5630 steps for copper. A correlation coefficient close to
unity was observed for linear calibration curves of all the
elements. The detection limits of all the elements were
taken as three times the standard deviation of the field
blank samples, which ranged from 3 ng/sample to 186
ng/sample for the elements studied.
To validate the digestion method, a National Institute
Standards and Technology Standard Reference Material
1648 Urban Particulate Matter was digested as described
above after overnight drying at 120oC and analyzed
together with the samples. The blank was subtracted
from the obtained elemental concentrations in the air
samples and by taking into account the sampling time
and flow rates. Mass concentrations in ngm-3 were
obtained.

3. Data Analysis

The statistical correlations were studied by using
linear regression method in Microsoft XP excel. Pairwise
comparison of the TSP
concentrations of all sites were conducted. Only detected
elements between the paired sites were used in the
regression method. The chemometrics analysis was
performed using a multi-criteria decision making system,
PROMCALC V3.2. The PROMETHEE II method is
coupled with GAIA in the software. The former provides
a full ranking of all objects from the best to the worst
based on their net outranking flows while the latter
and PM2.5 elemental

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displays PROMETHEE results visually as PCA biplots
and facilitates the interpretation of the global
performance of each object with reference to a decision
axis, π which appears in the biplot. Thus, useful
information about the underlying trends in the data
matrix such as clustering of objects and variables and
characterization of outliers may be obtained from GAIA
biplots. The longer the projected vectors of the variables,
the more variance they contain. Vectors oriented in the
same direction are correlated whereas vectors oriented in
the opposite directions are conflicting. When the
decision axis is long, the best objects are located in the
direction of the axis and as far as possible from the
origin of the GAIA biplots (Espinasse et. al. 1997).

4. Results and Discussion

The mass concentrations of TSP and PM2.5 are
discussed in comparison with local and overseas data.
The correlations between sites with respect to their PM2.5
and TSP mass concentrations are explained. The
significance of the data by means of multivariate
analysis is discussed below.

4.1. TSP and PM2.5 mass concentrations

This study reports PM2.5 average of (18.9 ± 4.9) µgm-3
from both ANZ stadium and QUT sites. Compared to an
annual average in Milan of 45.5 µgm-3 (Marcazzan et. al.
2001), the PM2.5 average concentration for Brisbane sites
is lower and is comparable with that found by Chan et.
al. (1997). In comparison with a developing country like
India (Negi et. al. 2002) and Taiwan (Wang et. al. 1998)
with a mean range of 22 µgm-3 to 600 µgm-3, the TSP
average concentration (16.6 ± 8.0 µgm-3) of the present
study was much lower.
Although the present mass concentrations of PM2.5
may not sufficiently warrant an elaborate action for the
reduction of particle mass concentrations, several
government agencies have taken steps to continuously
monitor its level over the last few years. For instance,
nearly a decade ago, the Environmental Protection
Agency (EPA) in Victoria reported that PM2.5 in
Brisbane averaged at an annual concentration of 6 µgm-3
(Robinson 1999) which is roughly equivalent to two
years average of 7.3 µgm-3 measured by Chan et. al.
(1997) from December 1993 to November 1995.
Unfortunately, monthly measurement performed by
Commonwealth Scientific and Industrial Research
Organization (CSIRO) in 1996 showed that there is an
increase of 46% in the mass concentration of PM2.5 in
Brisbane, although this was about 24% below national
monthly averages of other state capital cities (Robinson
1999). The mass concentration of PM2.5 continues to
climb over the years until recently which is probably
contributed by the increase in the vehicular registration
in South East Queensland. It is well known that since
1997, the Australian registrations of all motor vehicle
types has increased between 3% and 18%. Queensland
alone has an increase of 3.9% registered motor vehicles
from March 2001 to March 2002. Together with the
present on-road vehicles, there were a total of 12.8
million registered motor vehicles around Australia
(Australian Bureau of Statistics 2002).
Currently, there is no Australian standard for PM2.5.
As a result, several government agencies like CSIRO,
EPA, National Environment Protection Council (NEPC)
and other institutions have conducted studies and
reviewed the overseas standards as part of the Australian
guidelines. For instance, the United State of America and
Canada developed daily average standards for PM2.5 of
65 µgm-3 and 30 µgm-3 respectively. Recently, California
proposed an annual average standard of 12 µgm-3 and
New Zealand also proposed an interim guideline of 25
µgm-3 daily average (NEPC 2002). Due to potential
health problems caused by PM2.5, special efforts made
by various state agencies to obtain better understanding
of the fluctuations in the mass composition of the PM2.5
should continue.
A review by NEPC found that the PM10 could serve
as a surrogate for PM2.5 (NEPC 2002). The ratio of
PM2.5 to PM10 reflects a wide range of particle emission
sources of which PM2.5 is generally associated with
anthropogenic sources like motor vehicle exhaust and
combustion of fuels and other natural materials. A ratio
approaching unity will quite accurately pinpoint the
types of emission sources. By adopting the same
approach, it was predicted that the majority of particles
must have originated from anthropogenic sources
especially at QUT site where the ratio very close to one
(0.94). The larger ratio for the ANZ site (1.24) indicates
that there are sources other than traffic related emissions.

4.2. Source apportionment


4.2.1. Elemental relationship between sites

Because all three sites are within the distance of 12
km, it was expected that they might have the same
source of pollution. Therefore, correlations between
elements at different sites were analyzed and presented
in Table 1. Generally, strong positive correlations were
observed between elemental levels at different sites
especially for TSP contents. This indicates that these
sites experienced fairly similar sources of pollution.
However, the PM2.5 correlations between the elemental
levels at Woolloongabba and ANZ on one hand and
Woolloongabba and QUT on the other hand are very low
suggesting that the sources of the pollutants at each of
these sites were not the same. The correlations of PM2.5
bound elements at ANZ and QUT sites are strong
suggesting that they are influenced by relatively similar
pollution sources. Considering that the correlations of
Woolloongabba with QUT and ANZ are weak, it appears

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Table 1: Regression for the paired sites

Elemental Correlations
Woolloongabba Concourse & ANZ
Woolloongabba Concourse & QUT
ANZ & QUT
TSP
0.93
0.99
0.93
PM2.5
0.19
0.10
0.75

that the ambient air in Woolloongabba might not be only
associated with the vehicular emission but other types of
anthropogenic sources.

4.2.2. General assignment of the sources of
elements

The three most abundant elements (Fe, Si and Al)
have been associated with crustal matter. This
association is particularly reasonable because the TSP
Fe/Si ratios are found to be 0.01 to 0.08 with the average
of 0.04 which is an indication that local rock influences
the chemistry of the particles (Negi 2002). However,
their presence in smaller concentrations in PM2.5 fraction
might indicate that there are other sources of elements in
agreement with the finding by Chan et. al. (1997) that Fe
was also related to combustion activities. Similarly, Al is
a prominent element present in the metal compartment
within the vehicles engines (Bigard 1969, Brewer and
Belzer 2001) and Si might arise from frictional grinding
on the road (Weckwerth 2001).
The sources of other elements could also come from
the presence of various local industries such as paint
spraying, cement processing and other aerosol producing
activities during the course of samplings could also
affect the elemental concentrations considerably. Given
the large variation in Figure 1, the mean values of each
element in the TSP and PM2.5 from the sites are not
statistically significant. As the ANZ sampling site was
positioned close to the traffic flow, its PM2.5 elemental
levels could be reasonably attributed to the neighbouring
traffic pollution. Similar level was also observed at all
other sites. The opposite is observed for the TSP
elemental levels in which its level at Woolloongabba
concourse area is much higher than those at QUT and
ANZ. Therefore, it could be affirmed that the
Woolloongabba urban is not just affected by the busy
traffic but by other sources of pollutions from its
surrounding business centre.
One of the local activities in the vicinity of the
Woolloongabba site is the car paint spraying which was
located just about half kilometer away from the
Woolloongabba sampling point. This might have caused

Figure 1: Total average elemental concentrations for three
sites.

the elevated elemental levels at this site.

Whittaker et. al. (2003) listed a range of inorganic
chemicals like cadmium pigments, chromium oxide, iron
oxide, manganese pigments,
magnesium oxides and zinc sulfide as pigmentation
agents and colour enhancers in paints. In addition, other
activities like coal-fired cement works and vehicular
emission that generate a high amount of airborne
particles that could contribute to the relatively high
elemental concentrations at Woolloongabba site (Chan
et. al. 1997).

4.2.3. PROMETHEE and GAIA analysis of the
PM2.5 air quality of the sites.

Figure 2 and 3 show the respective GAIA scores and
loading plots obtained for the PM2.5 data matrix that
consisted of 10 objects and 16 variables (elements). The
scores plot shows that the three sites (Woolloongabba,
QUT and ANZ) are well separated. The Woolloongabba
objects are on negative PC1 axis while the QUT objects
are on positive PC1 axis. ANZ objects form a tight
cluster on both sides of PC1 axis. The decision axis
points towards the ANZ site showing that it is less
polluted than Woolloongabba and QUT sites. In keeping
with this, PROMETHEE II ranked Woolloongabba and
QUT objects as having the higher elemental pollution.

hydrated alumina,

Figure 2: PM2.5 score plot of matrix of 10 objects and
16 variables for Woolloongabba concourse, QUT and
ANZ

In Figure 3, the long vectors of Zr, Mo, V, Al, Mn and
Sr are oriented in the same direction and opposite QUT
objects, indicating they are mostly found at QUT site.
The first three elements could possibly come from the
0
5
10
15
20
Wolloongabba
Concourse
QUTANZ
TSP
PM2.5
-1.5
-1
-0.5
0
0.5
1
1.5
-2-1.5-1-0.500.511.52
PC1 (35.9%)
PC2 (26.9%)
π
ANZ
QUT
Woolloongabba
Concourse

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engine components and combustion fuels (Moldovan et.
al. 1999, Fukui et. al. 2001, Weckwerth 2001) whereas
the rest might originate from geological source or
construction dust (Cadle et. al. 1999, Qin et. al. 1997,
Brewer and Belzer 2001). Similarly, long vectors are
observed for the variables like Fe, Cd, Co, Sn, Cu, Zn
and Mg. Vehicular emission is a possible source
contributor for Cu, Zn and Mg (Fukui et. al. 2001,
Weckwerth 2001) and the rest could be from local
industrial activities (Cadle et. al. 1999, Kumar et. al.
2001 and Wang et. al. 2001). Since the vectors for these
elements are oriented in the opposite direction to
Woolloongabba objects, these objects have high
concentrations of Fe, Cd, Co, Sn, Cu, Zn and Mg in
accord with the proposition that elemental pollution at
Woolloongabba is influenced by vehicular emission and
local industrial activities. Significant concentrations of
Si and Fe are found at ANZ site, both of which are
crustal elements. Apparently, ANZ site is largely
influenced by the geological source over the vehicular
source in its fine particle as Negi et. al. (2002) and
Kumar et. al. (2001) have confirmed that the geological
origin of these elements. This is probably due to that the
sampling station was in the vicinity to a bushy
background.


Figure 3: PM2.5 loading plot for Woolloongabba
concourse, QUT and ANZ score plot of matrix of 10
objects and 16 variables

5. Conclusion

The TSP average elemental content showed that the
traffic-related emission source was not probably the sole
contributor to the ambient air at Woolloongabba urban.
There was an indication of the influence of other types of
anthropogenic sources from its surrounding commercial
centres. The PM2.5 elemental concentrations at all the
sites were either influenced by the vehicular emission,
local industrial sources or geological source.
The above statement is further confirmed by the
results of the chemometrics analysis. The analysis of the
PM2.5 elemental data showed that the vehicular emission
and local industry were the two most important emission
sources at the Woolloongabba site whereas QUT is
largely influenced by anthropogenic sources with a
prominence of vehicular emission source in addition to
the geological source possibly due to long range particle
transportation. Therefore, QUT site has the highest air
pollution in its PM2.5. Generally, the air quality at the
ANZ site was reasonably under the influence of
geological source, in addition to vehicular emission.
Overall, inorganic species contribute significantly to
the ambient air quality around Brisbane but they are not
of special environment concerns at the levels they were
found. Many of the elements have multiple sources.
Therefore, it was not possible to apportion them to
particular sources unequivocally. Future studies on these
and other sites are planned.

Acknowledgements

This work was performed with a Polaris Q GCMS
instrument donated by Thermo-Finnigan. The authors
would like to thank Maricela Yip and Pierre Madl of the
University of Salzburg, Austria for their assistance
during the fieldwork.

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