QUEENSLAND UNIVERSITY OF TECHNOLOGY SCHOOL OF CHEMISTRY, PHYSICS AND MECHANICAL ENGINEERING STUDY OF NEW PARTICLE FORMATION IN SUBTROPICAL URBAN ENVIRONMENT IN BRISBANE, AUSTRALIA HING CHO CHEUNG A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS OF THE DEGREE OF DOCTOR OF PHILOSOPHY September 2012
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QUEENSLAND UNIVERSITY OF TECHNOLOGY
SCHOOL OF CHEMISTRY, PHYSICS AND MECHANICAL ENGINEERING
STUDY OF NEW PARTICLE FORMATION IN SUBTROPICAL URBAN ENVIRONMENT IN BRISBANE,
AUSTRALIA
HING CHO CHEUNG
A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS OF THE DEGREE OF DOCTOR OF PHILOSOPHY
September 2012
i
ABSTRACT
Atmospheric ultrafine particles play an important role in affecting human health,
altering climate and degrading visibility. Numerous studies have been conducted to
better understand the formation process of these particles, including field
measurements, laboratory chamber studies and mathematical modeling approaches.
Field studies on new particle formation found that formation processes were
significantly affected by atmospheric conditions, such as the availability of particle
precursors and meteorological conditions. However, those studies were mainly
carried out in rural areas of the northern hemisphere and information on new particle
formation in urban areas, especially those in subtropical regions, is limited. In
general, subtropical regions display a higher level of solar radiation, along with
stronger photochemical reactivity, than those regions investigated in previous studies.
However, based on the results of these studies, the mechanisms involved in the new
particle formation process remain unclear, particularly in the Southern Hemisphere.
Therefore, in order to fill this gap in knowledge, a new particle formation study was
conducted in a subtropical urban area in the Southern Hemisphere during 2009,
which measured particle size distribution in different locations in Brisbane, Australia.
Characterisation of nucleation events was conducted at the campus building of the
Queensland University of Technology (QUT), located in an urban area of Brisbane.
Overall, the annual average number concentrations of ultrafine, Aitken and
nucleation mode particles were found to be 9.3 x 103, 3.7 x 103 and 5.6 x 103 cm-3,
respectively. This was comparable to levels measured in urban areas of northern
ii
Europe, but lower than those from polluted urban areas such as the Yangtze River
Delta, China and Huelva and Santa Cruz de Tenerife, Spain. Average particle number
concentration (PNC) in the Brisbane region did not show significant seasonal
variation, however a relatively large variation was observed during the warmer
season. Diurnal variation of Aitken and nucleation mode particles displayed different
patterns, which suggested that direct vehicle exhaust emissions were a major
contributor of Aitken mode particles, while nucleation mode particles originated
from vehicle exhaust emissions in the morning and photochemical production at
around noon. A total of 65 nucleation events were observed during 2009, in which 40
events were classified as nucleation growth events and the remainder were nucleation
burst events. An interesting observation in this study was that all nucleation growth
events were associated with vehicle exhaust emission plumes, while the nucleation
burst events were associated with industrial emission plumes from an industrial area.
The average particle growth rate for nucleation events was found to be 4.6 nm hr-1
(ranging from 1.79-7.78 nm hr-1), which is comparable to other urban studies
conducted in the United States, while monthly particle growth rates were found to be
positively related to monthly solar radiation (r = 0.76, p <0.05). The particle growth
rate values reported in this work are the first of their kind to be reported for the
subtropical urban area of Australia.
Furthermore, the influence of nucleation events on PNC within the urban airshed was
also investigated. PNC was simultaneously measured at urban (QUT), roadside
(Woolloongabba) and semi-urban (Rocklea) sites in Brisbane during 2009. Total
PNC at these sites was found to be significantly affected by regional nucleation
iii
events. The relative fractions of PNC to total daily PNC observed at QUT,
Woolloongabba and Rocklea were found to be 12%, 9% and 14%, respectively,
during regional nucleation events. These values were higher than those observed as a
result of vehicle exhaust emissions during weekday mornings, which ranged from
5.1-5.5% at QUT and Woolloongabba. In addition, PNC in the semi-urban area of
Rocklea increased by a factor of 15.4 when it was upwind from urban pollution
sources under the influence of nucleation burst events.
Finally, we investigated the influence of sulfuric acid on new particle formation in
the study region. A H2SO4 proxy was calculated by using [SO2], solar radiation and
particle condensation sink data to represent the new particle production strength for
the urban, roadside and semi-urban areas of Brisbane during the period June-July of
2009. The temporal variations of the H2SO4 proxies and the nucleation mode particle
concentration were found to be in phase during nucleation events in the urban and
roadside areas. In contrast, the peak of proxy concentration occurred 1-2 hr prior to
the observed peak in nucleation mode particle concentration at the downwind semi-
urban area of Brisbane. A moderate to strong linear relationship was found between
the proxy and the freshly formed particles, with r2 values of 0.26-0.77 during the
nucleation events. In addition, the log[H2SO4 proxy] required to produce new
particles was found to be ~1.0 ppb Wm-2 s and below 0.5 ppb Wm-2 s for the urban
and semi-urban areas, respectively. The particle growth rates were similar during
nucleation events at the three study locations, with an average value of 2.7 ± 0.5 nm
hr-1. This result suggested that a similar nucleation mechanism dominated in the
study region, which was strongly related to sulphuric acid concentration, however the
iv
relationship between the proxy and PNC was poor in the semi-urban area of Rocklea.
This can be explained by the fact that the nucleation process was initiated upwind of
the site and the resultant particles were transported via the wind to Rocklea. This
explanation is also supported by the higher geometric mean diameter value observed
for particles during the nucleation event and the time lag relationship between the
H2SO4 proxy and PNC observed at Rocklea.
In summary, particle size distribution was continuously measured in a subtropical
urban area of southern hemisphere during 2009, the findings from which formed the
first particle size distribution dataset in the study region. The characteristics of
nucleation events in the Brisbane region were quantified and the properties of the
nucleation growth and burst events are discussed in detail using a case studies
approach. To further investigate the influence of nucleation events on PNC in the
study region, PNC was simultaneously measured at three locations to examine the
spatial variation of PNC during the regional nucleation events. In addition, the
impact of upwind urban pollution on the downwind semi-urban area was quantified
during these nucleation events. Sulphuric acid was found to be an important factor
influencing new particle formation in the urban and roadside areas of the study
region, however, a direct relationship with nucleation events at the semi-urban site
was not observed. This study provided an overview of new particle formation in the
Brisbane region, and its influence on PNC in the surrounding area. The findings of
this work are the first of their kind for an urban area in the southern hemisphere.
Ling, X. and He, C. (2009). JEM Spotlight: Environmental monitoring of
airborne nanoparticles. Journal of Environmental Monitoring, 11, 1758-1773.
1
TABLE OF CONTENTS
ABSTRACT………………………………………………...…………….…...……..i
KEYWORDS………………………………………………...………….……….…..v
LIST OF PUBLICATIONS…………………………………..….………………...vi
STATEMENT OF ORIGNAL AUTHORSHIP…………………...….…………...3
ACKNOWLEDGEMENTS………………………………………...………………4
CHAPTER1. INTRODUCTION………………………………….………………..5
CHAPTER 2. LITERATURE REVIEW…………….……………...……………18
CHAPTER 3. ENVIRONMENTAL MONITORING OF AIRBORNE
NANOPARTICLES……………………………………………………...………...68
CHAPTER 4. PARTICLE DETECTION EFFICIENCY FOR CPC’S
DEPENDS ON AMBIENT AEROSOL COMPOSITION AND
CONDENSATION MEDIUM……………………………………………...…....137
CHAPTER 5. OBSERVATION OF NEW PARTICLE FORMATION IN
SUBTROPICAL URBAN ENVIRONMENT……………………………..…….159
CHAPTER 6. INFLUENCE OF MEDIUM RANGE TRANSPORT OF
PARTICLES FORM NUCLEATION BURST ON PARTICLE NUMBER
CONCENTRATION WITHIN THE URBAN AIRSHED………………….….196
2
CHAPTER 7. INFLUENCE OF SUFLURIC ACID ON THE NEW PARTICLE
FORMATION IN SUBTROPICAL URBAN SOUTHERN HEMISPHERE...232
CHAPTER 8. GENERAL DISCUSSION……………………………...…….….258
APPENDIXES…………………………………………………………………….265
STATEMENT OF ORIGINAL AUTHORSHIP
The work contained in this thesis has not been previously submitted for a degree or
diploma at any other higher education institution. To the best of my knowledge and
belief, the thesis contains no material previously published or written by another
person except where due reference is made.
Signed:
Date: .... 3 .... .f.�p.t ...... -?.!!.l.v
3
QUT Verified Signature
4
ACKNOWLEDGEMENTS
I would like to express my sincere thanks to my supervisor, Lidia Morawska, for her
supervision in my scientific research and encouragement. I would like to thank my
co-supervisor, Zoran Ristovski, for his inspirational advice in my research and
guidance in field measurement. My gratitude also goes to my co-supervisor, David
Wainwright, who has provided me with valuable advice on the field measurement. I
would like to thank my teammates in International Laboratory for Air Quality and
Health (ILAQH) for their friendship and help throughout my study. Last but not
least, I would like to thank my wife, Celine, and family in their continuous support
and encouragement.
5
CHAPTER 1. INTRODUCTION
1.1 Description of Scientific Problem Investigated
The formation processes of ultrafine particles (UFP) in the atmosphere are difficult
to fully understand due to the multiplicity of sources and mechanisms involved. Also,
the scientific knowledge behind particle formation processes is still not fully
developed. Nucleation processes, such as binary nucleation (involving sulphuric acid
and water) and ternary nucleation (involving with sulphuric acid, water and ammonia)
are the major processes by which UFP are formed in the atmosphere. Other processes
which contribute to the formation of UFP are organics condensation and ion-induced
nucleation (IIN) (Kulmala and Kerinen 2008), however it is important to note that
UFP formation in the atmosphere may not solely governed by one of the above
mechanism, but involves other processes. Urban pollution sources, such as fossil fuel
combustion (including vehicles, industrial and power generation) and biomass
burning, significantly contribute to UFP concentrations (Morawska et al., 2008).
Furthermore, pollution plumes observed in the urban environment are often a
mixture originating from different emission sources. Thus, UFP formation in the
urban atmosphere is a complex process.
Due to the significant impact the UFPs have on human health and the environment,
many studies have been conducted on the various aspects and characteristics of these
particles (Kulmala et al., 2004, Morawska et al. 2004). A more detailed review of
these studies can be found in the Chapter 2. In summary, particle formation in the
atmosphere is highly depending on the existing chemical species in the atmosphere,
6
as well as local meteorological conditions. In general, discrepancies between the
observed and modelled results for nucleation rate also imply that different processes
and factors are involved (Weber et al., 1996, 1997 and 1998). Previous observational
studies focused on the physical properties of UFP, such as size and number
distributions and their temporal variation (e.g. Morawska et al., 1999), where the
formation of UFP was attributed to different processes depending on the
environmental conditions (Kulmala et al., 2004). The limitations of measurement
techniques for investigating the chemical composition of UFPs has impeded the
progress of research on health impact assessment, source sectors/ regions
apportionment and the species involved in the initial stages of the nucleation
processes (McMurry 2000; Kulmala and Kerinen 2008).
Particle formation processes have been widely studied in rural areas, boreal forests
and along coastal and marine boundaries (Kulmala et al. 2004). New particle
formation is often observed in clean environments, whereas the presence of a
coagulation sink was limited, indicating that the cluster molecule undergoes
nucleation process rather coagulating/condensing on pre-existing particles (Kulmala
2003). The majority of urban studies focused on roadside measurements, since
vehicle emissions are the major source of pollution in these areas. These studies
concluded that UFP concentration was associated with traffic density, especially
during the morning traffic peak period. Furthermore, new particle formation
associated with photochemical reactions was suggested to be another significant
source of the UFP concentrations during noontime, when the strongest solar radiation
was observed (Cheung et al., 2011c; Pey et al., 2008). However, identification of the
7
specific pollution sources which contribute to nucleation in the urban environment is
challenging due to the complexity of emission sources within the urban environment,
including vehicle, industrial and domestic emissions etc.
Therefore, the knowledge on UFP formation in the atmosphere is limited in urban
areas, particularly in the southern hemisphere, where its impact on regional
atmospheric quality is still unclear. Thus, more investigations are needed on the
influence of urban pollution on UFP formation in the atmosphere.
The major scientific topics that have been addressed by previous studies can be
summarised as follows:
- Intensive field measurements of neutral/charged clusters were mainly
conducted in clean environments, such as continental rural areas/boreal
forests, as well as arctic, marine environments and the upper troposphere.
These studies were mostly conducted in the northern hemisphere and they
showed that nucleation processes varied according to different environmental
settings.
- Several parameterisations of particle formation mechanisms were developed
for homogeneous binary/ternary nucleation, ion-induced nucleation etc.
Although some parameterisation studies showed a good agreement between
modelling results and the observation data, the modelling results of particle
8
formation rate were usually lower than the observation data, suggesting that
new particle formation may not be the result of a single mechanism.
However, to fully understand the atmospheric aerosol nucleation process, several
scientific gaps need to be further investigated, which include:
- Improvements in the instrumentation techniques used to measure the
chemical composition of nucleation particles;
- Characterisation of particle formation processes in the urban environment,
especially in the south hemisphere;
- Investigation of the key mechanisms involved in particle formation process;
and
- The inclusion of these findings in climate models for climatological
applications.
This work focuses on the characterisation of particle formation processes in the
subtropical urban areas of the southern hemisphere, which generally has stronger
solar radiation and relatively lower ambient particle concentrations compared to
other continental regions that provided favourable conditions for new particle
formation. Thus, a field measurement based study was conducted in urban area of
Brisbane, in South-East Queensland, Australia.
9
1.2 Aims of the Study
The aim of this study was to characterise the new particle formation process in a
subtropical urban environment as follows:
- To characterise the temporal and spatial variations of UFP;
- To quantify new particle formation events and their impact on particle
number concentrations (PNCs) within the urban airshed of Brisbane;
- To investigate the influence of sulphuric acid on nucleation in the study
region; and
- To summarise and draw conclusion based on the above findings and to
provide recommendations for the further study of nucleation processes in the
study region.
1.3 Specific Objectives of the Study
There were four main objectives in this work:
i) To investigate the capability of particle monitoring instruments, in order to select
the best particle counting instrument for use in this work.
- A literature review was conducted on particle measurement techniques, in
order to summarise the advantages and disadvantages of each technique. The
review discussed methods for the measurement of particle properties such as
number, concentration, size distribution and surface area. In addition, the
measurement of particle composition by direct and indirect techniques was
also discussed (Chapter 3).
10
- Laboratory testing for water-based and butanol-based condensation particle
counters (WCPC and BCPC) was conducted. The tests compared the WCPC
and BCPC with regard to their detection efficiencies for aerosols of different
composition. Furthermore, the effects of coincidence error on the
measurement of particle number were discussed and based on these findings,
a particle counting instrument was recommended for ambient particle
measurements (Chapter 4).
ii) To quantify UFP concentration, and examine their temporal and spatial
variations in South-East Queensland.
- The measurement of UFP concentrations was conducted at a campus building
of the Queensland University of Technology (QUT), which is located in the
central business district area of Brisbane, during January 2009 to December
2009. Furthermore, an intensive study was carried out at Woolloongabba and
Rocklea monitoring sites, representing roadside and semi-urban environments,
respectively, during the winter season of 2009. The temporal and spatial
variation of UFP concentrations within the Brisbane region were studied and
are presented in Chapter 5 and 6.
iii) To evaluate the impact of regional nucleation events on UFP concentrations
in the Brisbane region.
11
- The impact of regional nucleation events on UFP concentrations was studied
by conducting simultaneous measurements of UFP at three study locations.
The variation in UFP concentrations at three stations during regional
nucleation events provided evidence that the UFP concentration downwind of
the event was affected by nucleation process in the upwind area. This impact
was described and quantified in Chapter 6.
iv) To explain new particle formation processes in South-East Queensland.
- New particle formation (i.e. a nucleation) events are identified based on the
measured particle size distribution data. The relationship between nucleation
processes and other factors, including meteorological conditions and particle
precursors, were studied and described in Chapter 5. Furthermore, the
influence of sulphuric acid, an important contributor to the nucleation process,
on nucleation at the three study locations was investigated and is reported in
Chapter 7.
1.4 Account of Scientific Process Linking the Research Papers
As mentioned in the above sections, several manuscripts were published or submitted
to peer-reviewed journals based on the present work, which mainly focused on the
study of new particle formation in the sub-tropical urban area of Brisbane.
1. To better understand the capability of the instruments used for monitoring
UFP, a review of the current instruments used for particle monitoring was
carried and published in the Journal of Environmental Monitoring, with a title
12
of “JEM Spotlight: Environmental monitoring of airborne nanoparticles”.
This paper reviewed and concluded on the performance of the instruments
currently used to measure the physical and chemical properties of UFP.
Furthermore, a study of the particle detection efficiency of Condensation
Particle Counters (CPCs) was conducted to compare the detection
performance of butanol (BCPC) and water (WCPC) based CPCs (Cheung et
al. 2011a). Aerosols with different chemical composition were measured by
the CPCs and the results showed that the detected concentration of water
insoluble particles was underestimated by the WCPC. The findings of this
work allowed the selection of an appropriate instrument for measuring
ambient particle concentrations in the current work. The two manuscripts
which resulted from this work are presented in Chapter 3 and 4.
2. A year-long measurement campaign for measuring UFP concentration was
carried out at QUT campus during 2009, which developed a comprehensive
database for research on the issue of new particle formation (Cheung et al.,
2010, 2011c). This dataset was used to investigate the temporal variation of
UFP and its relationship with meteorological parameters and trace gaseous
pollutants. Although there have been other studies on new particle formation
conducted in the coastal, rural and forest areas of Australia (Johnson et al.,
2005, Guo et al., 2008, Modini et al., 2009 and Ristovski et al., 2010), studies
on new particle formation focusing on urban environments is limited. This
study provides the only database that records the continuous measurement
13
particle size distribution in a subtropical urban area of Australia. It also was
the first study which reported on the particle growth rate of nucleation events
in an urban area of Australia.
3. An intensive study of regional nucleation was carried out at different
environments around Brisbane, including urban (QUT), roadside
(Woolloongabba) and semi-urban (Rocklea) areas, during the winter season
of 2009. In this study, regional nucleation events were observed, and the
temporal and spatial variations of UFP concentration were investigated.
Condensation sink was found to be a factor which occasionally suppressed
the nucleation process at the roadside site. The enrichment factor of particle
number concentration at the semi-urban site was also calculated according to
the influence of upwind urban pollution during nucleation burst events
(Cheung et al., 2011c, 2012).
4. Sulphuric acid was proposed as a key component which contributes to the
nucleation process. Particle production strength could be represented by a
H2SO4 proxy, which is a function of sulphur dioxide, solar radiation and
condensation sink. The influence of the H2SO4 proxy on nucleation mode
particles was investigated (Cheung et al. 2011b) and a moderate to strong
linear relationship was found between H2SO4 proxies and freshly formed
particles (with a particle size 4-6 nm) during the nucleation growth events.
14
This result implied that the observed nucleation process was significantly
affected by the presence of sulphuric acid in the ambient atmosphere.
5. Furthermore, the database was used to study the dust storm event in relation
to UFPs which occurred in South-East Queensland in 2009, and the findings
were published in Atmospheric Environment, with a title of “Characteristics
of airborne ultrafine and coarse particles during the Australian dust storm of
23 September 2009” (Jayaratne et al., 2011). This manuscript is included in
the appendices of this thesis.
15
1.5 References
Cheung, H.C., Johnson, G.R., Morawska, L. and Ristovski, Z.D. (2011a). Particle detection efficiency for CPC’s depends on ambient aerosol composition and condensation medium. Submitted for publication in Atmospheric Environment.
Cheung, H.C., Morawska, L. and Ristovski, Z.D. (2010). Observation of new particle formation in subtropical urban environment. Atmospheric Chemistry and Physics Discussions, 10, 22623-22652.
Cheung, H.C., Morawska, L. and Ristovski, Z.D. (2012). Influence of sulphuric acid on nucleation in subtropical urban area of Australia. Submitted for publication in Atmospheric Environment.
Cheung, H.C., Morawska, L. and Ristovski, Z.D. (2011b). Observation of new particle formation in subtropical urban environment. Atmospheric Chemistry and Physics, 11, 1-11.
Cheung, H.C., Morawska, L., Ristovski, Z.D. and Wainwright, D. (2011c). Influence of medium range transport of particles from nucleation burst on particle number concentration within the urban airshed. Atmospheric Chemistry and Physics, 12, 4951-4962.
Guo, H., Ding, A., Morawska, L., He, C., Ayoko, G., Li, Y., Hung, W. (2008). Size
distribution and new particle formation in subtropical eastern Australia,
Environmental Chemistry, 5, 382-390.
Jayaratne, E.R., Johnson, G.R., McGarry, P., Cheung, H.C. and Morawska L. (2011). Characteristics of airborne ultrafine and coarse particles during the Australian dust storm of 23 September 2009. Atmospheric Environment, 45, 3996-4001.
Johnson, G.R., Ristovski, Z.D., Anna, B.D., Morawska, L. (2005). The hygroscopic behaviour of partially volatilized coastal marine aerosols using the VH-TDMA technique, Journal of Geophysical Research, 110, (D20203), doi:10.1029/2004JD005657.
Kulmala, M. (2003). How Particles Nucleate and Grow. Science, 302, 1000-1001.
Kulmala, M. and Kerminen, V-M. (2008). On the formation and growth of atmospheric nanoparticles. Atmospheric Research, 90, 132 - 150.
Kulmala, M., Vehkamäki, H. Petäjä, T., Dal Maso, M., Lauri, A., Kerminen, V.-M., Birmili, W. and McMurry, P.H. (2004). Formation and growth rates of ultrafine
16
atmospheric particle: a review of observations. Journal of Aerosol Science, 35, 3729-3739.
McMurry, P.H. (2000). A review of atmospheric aerosol measurements. Atmospheric Environment 34, 1959-1999.
Suni, T., Kulmala, M. (2009). New particle formation and growth at a remote,
sub-tropical coastal location, Atmospheric Chemistry and Physics, 9 (19), 7607-
7621.
Morawska, L., Moore, M.R. and Ristovski, Z. (2004). Health Impacts of Ultrafine Particles: Desktop Literature Review and Analysis. Department of the Environment and Heritage, Australian Government.
Morawska, L., Ristovski, Z., Jayaratne, E.R., Keogh, D.U. and Ling X. (2008). Ambient nano and ultrafine particles from motor vehicle emissions: Characteristics, ambient processing and implications on human exposure. Atmospheric Environment, 42, 8113-8138.
Morawska, L., Wang, H., Ristovski, Z., Jayaratne, E.R., Johnson, G., Cheung, H.C., Ling, X. and He, C. (2009). JEM Spotlight: Environmental monitoring of airborne nanoparticles. Journal of Environmental Monitoring, 11, 1758-1773.
Pey, J., Rodiguez, S., Querol, X., Alastuey, A., Moreno, T., Pataud, J. P. and Van Dingenen, R. (2008). Variations of urban aerosols in the western Mediterranean. Atmospheric Environment, 42, 9052-9062.
Ristovski, Z.D., Suni, T., Kulmala, M., Boy, M., Meyer, N.K., Duplissy, J., Turnipseed, A., Morawska, L., Baltensperger, U. (2012). The role of sulphates and organic vapours in growth of newly formed particles in a eucalypt forest, Atmospheric Chemistry and Physics, 10, 2919-2926.
Weber, R.J., Marti, J.J., McMurry, P.H., Eisele, F.L., Tanner, D.J. and Jefferson, A. (1997). Measurements of new particle formation and ultrafine particle growth rates at a clean continental site. Journal of Geophysical Research, 102, 4375 – 4385.
Weber, R.J. and McMurry, P.H. (1996). Fine particle size distributions at the Mauna Loa observatory, Hawaii. Journal of Geophysical Research – Atmospheres, 101 (D9), 14767 – 14775.
17
Weber, R.J., McMurry, P.H., Mauldin, L., Tanner, D., Eisele, F., Brechtel, F., Kreidenweis, S., Kok, G., Schilawski, R. and Baumgardner, D. (1998). A study of new particle formation and growth involving biogenic trace gas species measured during ACE-1. Journal of Geophysical Research, 103, 16385 – 16396.
18
CHAPTER 2. LITERATURE REVIEW
This literature review introduces the topic of atmospheric particles, how they form
and their sources, followed by the environmental and human health impacts of urban
ultrafine particles (UFPs). The proposed nucleation mechanisms for atmospheric
particles and the controlling factors of nucleation are also discussed, together with
the findings of previous new particle formation studies conducted in urban
environments. Finally, the approaches to data analysis and the instrumentation
applied for new particle formation measurements are reviewed and the current gaps
in knowledge identified.
2.1 Introduction to atmospheric particles
Atmospheric particles (or particulate matter, PM) are defined as a mixture of liquid
and solid particles which are suspended in the atmosphere. They can originate from
natural activities such as volcanic eruptions, wind blown dust, sea spray and bushfire.
They can also be generated through anthropogenic sources such as vehicle exhaust
emissions, fuel combustion, domestic cooking and tobacco smoking. Particles can be
emitted directly from the above sources, and in that case they are referred to primary
particles, or they can be formed through a series of chemical reactions and gas to
particle partitioning where a gaseous precursor is emitted from the above sources,
and these particles are called secondary particles. Both primary and secondary
particles, once emitted into the atmosphere, will undergo physical processes of
growth, evaporation, condensation, coagulation, deposition and different chemical
reactions. Atmospheric particles can be classified by their size or formation
19
processes. Particles with a diameter less than 0.1 µm, 1 µm, 2.5 µm and 10 µm are
defined as ultrafine particles (UFP) (quantified in units of number concentration) and
PM1, PM2.5 and PM10 (quantified in units of mass concentration), respectively. Due
to the different measurement techniques for number and mass concentrations the
referred diameters are also different. The particle diameter referred to in number
measurement is the mobility diameter which is defined as the charged particles with
the same velocity as the spherical charged particles moving in an electric field; and
aerodynamic diameter for can be defined as the diameter of the particles with the
same settling velocity as spherical particles.
They can also be classified according to their formation processes, such as nucleation,
Aitken, accumulation and coarse modes etc. Nucleation mode particles, which range
in size from a few nanometres to tens of nanometres, are formed by nucleation
processes which start with formation of a molecular cluster and its subsequent
growth. Aitken mode particles, ranging from tens to hundreds nanometres, are
generated directly from primary sources or growth from nucleation mode particles.
Accumulation mode particles, ranging from tens of nanometres up to a few
micrometers in size, are mainly formed by the condensation of other gaseous species,
such as organics and sulphuric acid vapour on pre-existing particles, as well as by
coagulation with other existing particles. Coarse mode particles include wind blown
dust, sea salt particles and other larger particles generated by mechanical processes,
such as tire and engine wear particles. The above particle types also have different
physiochemical properties, such as growth, condensation and coagulation properties,
with different impacts on environment and human health.
20
2.2 Impact of atmospheric urban particles
Atmospheric particles, which originate from natural and anthropogenic sources, can
be found in both remote and urban areas. The emission rates of these sources in
terms of mass are listed in Table 2-1, which shows that natural source emissions
contributed almost 80-90% of total particle mass emissions. However, these natural
sources are widely distributed around the world, while the anthropogenic sources are
mainly located in densely populated areas. In urban areas, vehicle exhaust emissions
are the major contributor of total particle number concentration mainly in UFP size
range (Morawska et al., 2008).
Amount, Tg/yr [106 metric tons/yr] Source Range Best Estimate Natural
Total for anthropogenic sources 320-640 460 Table 2-1. Sources and Estimate of Global Emissions of Atmosphere Aerosol (Hinds 1999).
21
2.2.1 Impact on human health
Atmospheric particles have been found to have an adverse impact on human health.
According to a report by the United Nation Environment Program (UNEP) and
World Health Organisation (WHO), more than 500,000 people per year die from
diseases related to particulate air pollution (UNEP 2002). The health risk of these
particles was found to be related to their size, surface area and chemical composition.
A positive relationship was observed between mortality rate and the mass
concentration of PM2.5 and particle sulphate, but not total suspended particles (TSP)
(Pope 2000). Donaldson and Tran (2002) claimed that particles with a higher reactive
surface will induce a greater inflammatory response in the human lung. Nel (2005)
found that a number of illnesses on pulmonary were related to PM and that its ability
to obstruct the airway and decrease gas exchange can lead to the exacerbation of
asthma and chronic bronchitis. Furthermore, PM was also found to be related to
cardiovascular diseases, including heart attacks, stroke, heart rhythm disturbances
and sudden death.
In terms of the health implications of different PM size fractions, Pekkanen et al.
(1997) showed that the number concentration of UFP was more closely associated
with variations in peak expiratory flow than coarse particles. Similar findings were
obtained by Peters et al. (1997), who found that UFP were associated with a decrease
in peak expiratory flow and an increase in cough and feeling ill during the day.
Churg and Brauer (2000) indicated that UFP can penetrate deeper into the human
lung than fine and coarse particles, while the review by Morawska et al. (2004) on
the impact of UFP on human health has shown that the health impacts of particles
22
varied according to their size. In addition, Oberdörster and Utell (2002) suggested
that UFPs may cross the blood-brain and alveolar-capillary barriers and enter the
central nervous system. However, the nature and extent of the impact of UFP on the
central nervous system remains unclear, and further investigation is needed to fill the
scientific gaps in knowledge on this issue.
More recent epidemiological studies have shown the short-term and long-term
effects of UFP on human health. Belleudi et al. (2010) estimated the short-term
effects of UFP on hospital admissions for cardiac and respiratory diseases, using
case-crossover analysis with a time-stratified approach. The study found that the
PNC was associated with hospital admissions for heart failure (2.4% [0.2-4.7%]) and
chronic obstructive pulmonary disease (COPD) (1.6% [0.0-3.2%]) and those effects
were generally stronger for elderly people and during the winter season. Knol et al.
(2009) investigated the likelihood of health effects due to UFPs and suggested that
short term health effects, such as hospital admissions for cardiovascular and
respiratory diseases, aggravation of asthma symptoms and lung function decrements,
were related to the exposure of UFP. In contrast, the likelihood of an effect due to
long term UFP exposure was rated low to medium for those health effects.
2.2.2 Impact on environment
In addition to the impact on human health, atmospheric particles also influence the
environment, either directly or indirectly. For example, the interaction between
atmospheric particles and solar radiation can alter climate forcing by scattering light
back into the space which reduces the amount light reaching the earth and thus
23
results in a negative climate forcing (cooling) effect. At the same time, atmospheric
particles can also absorb solar radiation which causes a positive climate forcing
(warming) effect, with the overall effect on climate forcing depending on the
chemical composition of the atmospheric particles (Charlson et al., 1992). The
Intergovernmental Panel on Climate Change (IPCC) reviewed the estimation of
climate forcing for different major particulate matter components (IPCC 2007), the
findings of which are presented in Figure 2-1. The overall climate forcing from total
airborne particulate matter is estimated to be -0.5 ± 0.4 W m-2, while for individual
particle species, the estimates are as follows: sulphate, -0.4 ± 0.2 W m-2; fossil fuel
organic carbon, -0.05 ± 0.05 W m-2; fossil fuel black carbon, +0.2 ± 0.15 W m-2;
biomass burning, +0.2 ± 0.15 W m-2; nitrate, -0.1 ± 0.1 W m-2; and mineral dust, -
0.1±0.2 W m-2.
24
Figure 2-1. Radiative forcing estimated for different atmospheric components (IPCC 2007).
Besides the direct effect of atmospheric particles on climate forcing, atmospheric
particles can also influence the climate forcing indirectly by acting as cloud
condensation nuclei (CCN), hence altering the cloud formation (Twomey 1977).
Atmospheric particulates can alter the radiative budget of the Earth by modifying the
cloud droplet size spectrum and precipitation at the surface (Ramanathan et al., 2001).
Several studies investigated the indirect impact of urban particles on climate forcing.
For example, Rosenfeld (2000) found that anthropogenic CCN, which nucleate many
25
small cloud droplets, are highly inefficient at producing rain droplets, resulting in the
suppression of rain over urban areas. Kaufman and Koren (2006) estimated the
effect of urban pollution on cloud cover and found that an increase in cloud cover
followed increases in particle concentration in the aerosol column. The impact of
anthropogenic particles on temperature variation was also simulated in China and it
was found that during the daytime, temperature decreased by -0.7 ºC over the
industrial parts of China, due to the blockage of solar radiation by the clouds. In
contrast, the temperature increased by +0.7 ºC at night during the winter, due to the
long-wave surface warming effect (Huang et al., 2006).
In addition to the impact on climate forcing, atmospheric particles also impair
visibility. Particles with a diameter around 0.4-0.7 µm are the most effective at
scattering visible light, thus resulting in reduced visibility (Watson 2002).
Hygroscopic species, such as sulphate and organics, were found to be the major
components affecting visibility in urban environments (Dzubay et al., 1982). In
addition, urban pollution does not only affect local air quality, but it can also
significantly reduce visibility in downwind areas. For example, Cheung et al. (2005)
estimated that about 90 % of total light extinction in a downwind rural area was
attributable to upwind urban pollution plumes. Moreover, aerosols were also found to
be indirectly affecting the radiative forcing through the biogeochemical feedbacks
process (Mahowald 2011). Mahowald (2011) found that the biogeochemical cycle
had been modified by the deposition of aerosols which could supply either nutrients
or toxins suppressing growth.
26
2.3 New particle formation
With regard to the significant impact of atmospheric particles on human health and
the environment, scientists are interested on the formation processes of these
atmospheric particles. The new particle formation consists of two major processes: i)
nucleation and ii) growth. Firstly, the vapour molecules (e.g. sulphuric acid and
water) undergo a nucleation process to form a thermodynamically stable cluster
which can be in a neutral or charged state. Then the condensing vapours, such as low
volatile organics and inorganics (e.g. iodide, sulphuric and nitric acids), can
condense on those newly formed clusters to become larger particles. When combined,
the nucleation and growth processes can result in new particle formation, as
illustrated in Figure 2-2 (Kulmala 2003).
Figure 2-2. Illustration of particle formation process (Kulmala 2003).
27
Although the first particle measurements were conducted by Aitken in the late 19th
century, our understanding of particle formation processes was limited by lack of
adequate measurement techniques at the time. In the past decades, the advancement
of particle measurement techniques has allowed for measurements to be conducted to
an accuracy as low as 2.5 nm diameter (Kulmala et al. 2004). This improvement in
measurement techniques has enabled scientists to study the formation processes of
nucleation mode particles.
Kulmala and Kerminen (2008) summarised the various formation mechanisms which
have been proposed by previous studies, including:
i) Homogenous binary nucleation involving mixtures of water and sulphuric
acid;
ii) Homogeneous ternary nucleation involving water, sulphuric acid and
ammonia in the continental boundary layer;
iii) Ion-induced nucleation of binary, ternary or organic vapours which are found
in the upper troposphere and lower stratosphere; and
iv) Homogeneous nucleation involving iodide species in coastal environments.
2.3.1 Homogeneous binary nucleation
Homogenous binary nucleation consists of two substances, i) sulphuric acid (H2SO4)
and water (H2O). Sulphuric acid is formed by the oxidation of sulphur dioxide (SO2)
in the atmosphere. The product of H2SO4 and water has a lower vapour pressure than
28
the H2SO4 itself (Marti et al., 1997). In addition, water vapour and sulphuric acid are
widely present in the Earth’s atmosphere and therefore, the reaction between H2SO4
and water is likely to occur in the atmosphere. When the H2SO4 molecules collide
with other H2SO4 and H2O molecules, they will form a cluster and this cluster
continues to grow and overcomes the nucleation barrier. Then a thermodynamically
stable cluster is formed from the gas phase. This mechanism is called homogeneous
binary nucleation, because no other catalyst like a foreign surface is involved in the
formation.
Vehkamäki et al. (2002) developed a binary nucleation model which showed a good
agreement with the theoretical rate for nucleation within the temperature range 230-
300 K, at a relative humidity between 0.01-100 % and with a total sulphuric acid
concentration between 104-1011 cm-3. Brock et al. (1995) tested the volatility of
particles collected in the upper troposphere (~ 10 km altitude) and found that 90 % of
the particles with diameter below 40 nm were composed of H2SO4 and H2O. Based
on this finding, they went on to suggest that binary nucleation was a possible
mechanism for the new particle formation in upper troposphere.
However, nucleation rates for the binary nucleation of H2SO4 and H2O were often
underestimated compared to observational results, whereby the predicted nucleation
rate for H2SO4 and H2O nucleation was lower than the observed nucleation rate by
factors of 107 at low altitudes. Similar findings were obtained by Weber et al. (1996,
1997 and 1998), which showed that the binary nucleation model underestimated the
nucleation rate of nano-sized particles (with diameter of 3-10 nm). This discrepancy
29
between the modelling and observational results implies that an additional formation
mechanism must exist.
2.3.2 Homogeneous ternary nucleation
Homogenous ternary nucleation, which involves sulphuric acid, water and ammonia
(NH3), is proposed to explain the particle formation process, since NH3 is in
abundance in troposphere and is able to decrease the vapour pressure of sulphuric
acid, and therefore enhance the nucleation rate (Scott and Cattell 1979, Coffman and
Hegg 1995).
This hypothesis is supported by a number of modelling studies which have shown
that higher particle nucleation rates were predicted based on ternary nucleation, as
opposed to a binary nucleation mechanism. For example, Ball et al. (1999) reported a
modelling result which showed that the homogenous nucleation rate was enhanced
by several orders of magnitude with the presence of ammonia, which was in a good
agreement with the experimental results conducted at a temperature of 298 K. Napari
et al. (2002) also constructed a modified parameterisation of ternary nucleation and
showed that an increase of one order of magnitude in the ammonia mixing ratio can
increase the nucleation rate by several orders of magnitude. Recently, Jung et al.
(2008) compared six nucleation parameterisations, including the binary and ternary
nucleation, ion-induced nucleation, semi-empirical first order nucleation and barrier-
less nucleation, with observational data in a sulphur rich environment. The results
showed that only ternary nucleation correctly simulated the particle burst in all
nucleation events. However, the input value of the ammonia concentration for the
30
modelling was usually higher than that in the actual concentration in the atmosphere.
Larsen et al. (1997) estimated the particle formation rate by ternary nucleation using
an ammonia concentration of 500 ppb, however the general atmospheric ammonia
concentration was in a range 10-1000 ppt. Therefore, other mechanisms were
proposed to explain the particle formation process.
2.3.3 Ion induced nucleation
Ion-induced nucleation (IIN) is another possible mechanism for particle formation.
IIN has higher particle growth rates due to the presence of electrostatic forces, which
enhances the stability of the electrically charged cluster. Using ion-induced
nucleation model simulation, Yu and Turco (2000, 2001) showed that charged
clusters have a faster growth rate than neutral clusters in a range of different
environments, including the upper troposphere, lower stratosphere and boreal forests.
Laakso et al. (2007) conducted measurements of charged and neutral particles in the
boreal forests of Finland and found that charged particles outnumbered the neutral
particles during some nucleation events, therefore indicating that IIN was the
possible formation mechanism contributing these events. In addition, it was
suggested that IIN was also occurring in upper troposphere and lower stratosphere.
Lee et al. (2003) simulated nucleation events by using in-situ measurement data of
ion-clusters and other particle precursors. The results showed that IIN was observed
under low surface area and low temperature conditions, however, the new particle
formation attributable to IIN only represented a small fraction of overall new particle
formation. Kulmala et al. (2007) also conducted measurements of neutral and ion
31
clusters down to a size below 1 nm in the boreal forests of Hyytiälä, Finland. In this
study, the results showed that both neutral and ion clusters (with a mean diameter ~
1.5-1.8 nm) were present almost all of the time during nucleation events. The
concentration of air ion clusters was found to be around 10-100 cm-3, which was
significantly lower than the concentration of neutral clusters, which ranged in order
of 1000 cm-3 during the study period. Therefore, it was suggested that less than 10 %
of the formation rate of particles with diameter of 2 nm was attributable to ion-
induced mechanisms under boreal forest conditions.
2.3.4 Organics involved nucleation
As mentioned in Section 2.3.1, although homogeneous binary nucleation is thought
to be one of the primary mechanisms involved in new particle formation, the particle
formation rate simulated by the nucleation model could not explain the observational
results. Therefore, it has been suggested that organic species may contribute to the
particle growth process, in order to enhance the particle production rate. One
possible pathway for particle formation involving organic species is that organic
species condense onto the stable cluster formed by H2SO4 and water, thus enhancing
the particle growth. Several studies have shown a positive relationship between the
mixing ratio of organic species and the particle formation rate (O’Dowd et al., 2002;
Tunved et al., 2006; Laaksonen et al., 2008). For example, O’Dowd et al. (2002)
found that, in a forest environment, most nucleation events occurred when an
elevated biogenic organic acid mixing ratio was also observed. Tunved et al. (2006)
also found that higher particle formation rates were linked to higher monoterpene
emissions. The evolution of organic aerosols have been studied by Jimenez et al.
32
(2009), using the high-time resolution measurement of aerosol chemical composition.
The result of the study shown that the organic aerosols in a downwind area were
increasingly oxidized, less volatile and more hygroscopic compared to the aerosols
measured in an upwind area. Therefore, both of these studies indicated that organic
species may have contributed to the particle formation process.
2.3.5 Iodide species involved nucleation in coastal environment
In coastal environments, iodide species were generated from macroalgal iodocarbon
emissions and iodide oxides were observed in the marine particles. Therefore, iodide
species were proposed as a possible contributor to the particle formation process in
marine environments. O’Dowd et al. (2002) suggested that particle formation rate
can be enhanced when condensation iodine vapours (CIVs) are present during
homogeneous nucleation. The research simulated homogenous binary nucleation of
H2SO4 and water with different concentrations of CIVs, the results of which showed
that the higher the CIVs concentration applied, the higher the particle formation rate
that was observed. The results suggested that CIVs could be one of the possible
candidates involved in marine particle formation.
2.3.6 Other possible nucleation mechanisms
In addition to the mechanisms mentioned above, several other species were found to
enhance particle formation rates, including amino acids and oxidation products of
isoprene (Froyd et al., 2009; Paulot et al., 2009; Loukonen et al., 2010).
33
In more recent studies, ammines were found in freshly formed particles (Makela et
al., 2001) and its presence was found to enhance particle formation rates in both
laboratory and modelling studies (Barsanti et al., 2009; Wang et al., 2010).
Furthermore, dimethylamine was found to have a greater effect (by lowering the
nucleation energy barrier) than ammonia at enhancing particle formation rates when
coupled with sulphuric acid when modelled using quantum chemistry (Loukonen et
al., 2010). However, the accurate measurement method of ammines close to the
cluster scale is still under development and more effort is needed to help understand
the impact of ammines on particle formation processes (Kurtén et al., 2011).
Similarly, the role of isoprene in new particle formation also remains unclear.
Although isoprene is a major component of biogenic organics, its oxidation products
were found in the composition of secondary organic aerosol (Froyd et al., 2009).
More recent studies on the effect of isoprene on particle formation using plant
chamber (a chamber with different kind of trees growing in it) found that isoprene
suppressed the particle formation rate (Kiendler-Scharr et al., 2009). In this plant
chamber experiment, the authors found that PNC decreased while the isoprene
mixing ratio increased. To further support this finding, Kanawade et al., (2011)
conducted field measurements in a Michigan forest (United States) to study the
relationship between particle nucleation and isoprene. They found that no nucleation
events were observed while the ratio of isoprene/monoterprene was higher than 10.
In contrast, a low isoprene/monoterprene ratio (< 0.5) was observed in the boreal
forests of Finland, where nucleation events frequently occurred (Spirig et al., 2004).
These findings indicate that isoprene has a negative effect on particle formation rate.
34
However, further research is required to fully understand these recently proposed
nucleation mechanisms.
In the above discussion, it was shown that either binary or ternary nucleation
mechanisms cannot fully explain the observed particle formation rates under ambient
atmospheric conditions. Whilst the IIN mechanism has been observed in the
atmosphere, it only contributed a small fraction to total particle formation rates. Also,
the role of organics species in the nucleation process remains unclear, and therefore,
more effort is needed to investigate fundamental nucleation mechanisms.
2.4 Field studies of new particle formation
In Section 2.1 and 2.2, the emission sources of atmospheric particles in different
urban and rural environments were discussed and although total particle emissions
from anthropogenic activities were lower than that of natural sources, anthropogenic
emissions were more concentrated in populated areas, where people are more
exposed to the polluted atmosphere. Also, urban and rural atmospheric conditions are
usually different in terms of particle formation precursors and the diurnal profile of
the emission sources etc. These differences have a direct impact on the particle
formation processes which occur in these environments. For example, Kulmala et al
(2004) found that the level of pre-existing particles was higher in urban areas
compared to rural areas, which served to suppress the new particle formation process.
In addition, the dominant precursors are often different in urban and rural areas,
which lead to different formation and growth properties of the atmospheric particles.
Therefore, the investigation of urban particle formation is important for gaining a
35
better understanding of the specific nucleation processes which occur in these
environments.
This section will discuss the classification scheme used for nucleation events,
according to changes in particle size distribution, as well as how meteorological,
physio-chemical and other factors affect the nucleation process in urban areas.
Furthermore, the analysis techniques applied in the study of particle nucleation,
including data analysis and instrumentation approaches will also be discussed.
2.4.1 Classification of nucleation events
Statistical analysis of nucleation event/non-event data with other measured
parameters is a basic approach to study the factors governing the particle formation
process. Identifying nucleation events is the first step, whereby a nucleation event is
usually characterised by an increase in the number of nucleation particles which
gradually grow to larger particles. Based on the above system, different researchers
use different approach to the classification of events, and therefore, Dal Maso et al.
(2005) established a scheme for classifying nucleation events, which has been
applied in a number of nucleation studies (e.g. Lee et al., 2008; Sogacheva et al.,
2008; Vana et al., 2008). According to this scheme, a nucleation event is classified
by measuring the new nucleation mode particles (< 25 nm size) that are formed over
a one hour period, as well as quantifying the subsequent particle growth. When the
particle size distribution data is presented in a contour plot, the shape of the
propagation should look like a "banana" (see Figure 2-3 as an example). This
“banana” shape is a typical feature of the nucleation event. Furthermore, nucleation
36
events can be defined as Class I, Class II, a Non-Event or an undefined group,
depending on several criteria used. Further information about this event classification
procedure are provided by Dal Maso et al. (2005). In the urban environment,
nucleation events have been observed with and without particle growth (Park et al.,
2008; Gao et al., 2009). For example, in addition to nucleation events, observation of
increases in nucleation mode particle concentration during the daytime, where the
particles did not grow into larger particles (indicated by the near constant geometric
median diameter (GMD) value during the event period), which is classified as a
nucleation burst event.
Figure 2-3. Example of a contour plot of particle size distribution during a nucleation event (Bottom). The propagation of the particle size distribution displays a “banana” shape. (Dal Maso et al. 2005).
37
2.4.2 Factors favouring urban nucleation
2.4.2.1 Solar radiation
When investigating the meteorological conditions which affect the nucleation
process, solar radiation was directly linked to new particle formation due to its
positive relationship with photochemical reactions. For example, the amount of
hydroxyl radicals was positively related to the strength of solar radiation. In previous
studies, nucleation events were often observed during late mornings when precursors
were present in the atmosphere and solar radiation was close to reaching its daily
maximum (see Figure 2-4, Woo et al., 2001; Qian et al., 2007). These photochemical
activities also enhanced photo-oxidation reactions which led to a higher particle
growth rate. The seasonal variation of particle growth rate was also positively related
to the strength of solar radiation, with higher particle growth rates observed during
the warmer summer season (see Figure 2-5, Salma et al., 2011).
38
Figure 2-4. Time series plot of i) particle number concentration (size ranging from 3-10 nm), SO2, NO2 and O3 (bottom), and ii) solar radiation (upper) (Woo et al. 2001).
39
Figure 2-5. Seasonal variation of the particle growth rate observed during nucleation events in 2008-2009 at Budapest, Hungary. (Salma et al. 2011).
2.4.2.2 Temperature
Temperature affects the condensation and volatilisation of particles, such that cooler
conditions enhance the condensation process of organic vapours on the cluster
molecule, as well as the nucleation resulting from vehicle exhaust during morning
hours (Morawska et al., 2008). In contrast, warmer conditions may induce the
volatilisation of particles during the nucleation growth process. The volatile species
of a particle will be volatilised under high temperatures, reflected by a decrease in
particle size after the particles have been formed in the atmosphere (Yao et al., 2010).
This particle volatilisation process is called the particle shrinkage. Figure 2-6 is an
example of particle shrinkage observed during a late afternoon nucleation event
which suggests that the semi-volatile species of particles will undergo evaporation or
gas/ particle repartitioning (Yao et al., 2010). Although higher solar radiation is
40
supposed to be associated with higher temperatures, the principle of particle
shrinkage is still not well understood and needs further investigation.
Figure 2-6. Observation of particle growth followed by particle shrinkage. (Yao et al., 2010).
2.4.2.3 Relative humidity
Relative humidity is another meteorological parameter affecting nucleation events.
For example, condensation onto particles is enhanced under high relative humidity
conditions, which leads to an increase in accumulation mode particles, as well as
total particle volume (Yue et al., 2009). Therefore, high relative humidity suppresses
new particle formation by increasing the condensation sink of the atmosphere. Since
variation in relative humidity is usually inverse to variation in solar radiation, low
relative humidity is often observed during particle formation events, due to the
photochemical reactions which occur during high solar radiation conditions. This
phenomenon was also observed during nucleation growth events which occurred at
noon in urban areas of New York, United States, with minimum relative humidity
observed during these events (Jeong et al., 2004).
41
2.4.2.4 Wind direction and speed
The influence of wind on the particle formation process can be discussed in terms of
both wind direction and wind speed. Firstly, observed pollution plumes are often
related to wind direction, which can transport pollution from the emission source
regions, as well as clean air masses to the measurement site. In urban environments,
PNC is contributed by different sources, such as traffic emissions, industrial
activities and power generation, which are mixed together in the urban airshed. A
number of studies have investigated the impact of different pollution sources on
PNCs. For example, Bein et al. (2007) estimated the impact of industrial pollution
sources on an urban site in Pittsburgh, United States by using the unique source
markers of coal combustion with back-trajectory analysis. The results showed that
PNC could reach orders of magnitude of 1015-1017 particles/cm3 when the
measurement site was downwind from the coal burning pollution plume. This result
was higher than the PNC attributable to traffic emissions, with an order of magnitude
around 1012 particles/cm3.
In contrast to wind direction, wind speed mainly impacts the dispersion and
coagulation of particles. The relationship between wind speed and the PNC is often
presented by a “U” shaped curve (Charron and Harrison 2003; Hussein et al., 2006).
This phenomena can be explained by the fact that sub-micrometer particles consist of
two major components, i) UFPs which are generally diluted by increasing wind
speed, and ii) particles between 100 nm and 2.5 µm in diameter which are generally
proportional to wind speed due to the suspension and re-suspension of particles. This
42
relationship occasionally altered the condensation sink profile of the pre-existing
particles.
2.4.2.5 Sulphuric acid
Sulphuric acid (H2SO4) plays a critical role in binary and ternary nucleation, which is
mainly formed by oxidation reactions of SO2 in the atmosphere (Lovejoy et al., 1996;
Jayne et al., 1997). The heterogeneous chain reactions for SO2 to form H2SO4 are as
follows:
SO2 + OH + M -> HSO3 + M (R1)
HSO3 + O2 -> SO3 + HO2 (R2)
SO3 + H2O -> H2SO4 (R3) where M is catalyst
Although atmospheric H2SO4 is considered to play a major role in nucleation, the
measurement of H2SO4 is quite difficult and thus, SO2 is often used as an indirect
indication of the amount of H2SO4 in the atmosphere (Woo et al., 2001; Stanier et al.,
2004). Observational results have shown that nucleation bursts frequently occur at
the same time as increases in the SO2 mixing ratio (e.g. Woo et al., 2001; Park et al.,
2009; Salma et al., 2011). Figure 2-7 shows the temporal variation of SO2 during a
nucleation event in an urban area of Atlanta, United States and it can be seen that the
SO2 plume was usually observed at the same time as a nucleation burst. A product of
SO2 mixing ratio and solar radiation/UV can also be used to indicate the production
of H2SO4 (Gao et al. 2009), while a separate parameter, H2SO4 proxy, can also be
linked to the strength of particle precursors containing SO2, as well as to solar
43
radiation and the condensation sink (Petäjä et al., 2007; Salma et al., 2011). H2SO4
proxy is an approximation of the nucleation mode particles which have been formed
by H2SO4. It is calculated by the available H2SO4 (usually estimated by the ambient
SO2 and solar radiation) over the condensational sink of particles. Salma et al. (2011)
calculated the average H2SO4 proxy values for nucleation event days and non-event
days over four seasons. The results showed that SO2 values did not vary significantly
across the four seasons. By contrast, the H2SO4 proxy values showed higher values
during nucleation event days than non-event days.
Figure 2-7. Concentrations of selected gases during a 3 – 10 nm particle event on April 1, 1999 at Atlanta, United States. (Woo et al., 2001).
44
2.4.2.6 Volatile Organic Compounds (VOCs)
As mentioned in Section 2.3.3, organic species have been suggested as an important
factor for enhancing the particle formation process. A number of studies which were
conducted in the field, in the laboratory and by modelling, also found that particle
growth rates were related to the amount of organic species involved in the nucleation
(e.g. O’Dowd et al., 2002; Laaksonen et al., 2008). Laaksonen et al. (2008) analysed
the chemical composition of particles during and after nucleation events using a
variety of techniques. The mass spectra of the particles collected during and after the
nucleation were very similar, implying that similar secondary organic species were
condensing onto all particles. Furthermore, the particle growth rates during the
nucleation events were found to be related to the concentration of monoterpene
oxidation products (MTOP) and a linear fit was found based on the following
equation, [Growth rate] = 0.97 + 0.0043*[MTOP], with a coefficient of
determination (r2) of 0.965. Both these results provided evidence that VOC
oxidation products may play a key role in determining the strength and rate of the
nucleation process.
2.4.3 Formation and growth rates of atmospheric aerosol particles
Particle formation rate describes the amount of critical clusters formed during the
nucleation process, which can be used to estimate the activation coefficient (Kulmala
et al., 2006). Particle growth rate is defined as the change in particle size per unit of
time as a result of the particle growth process, which can be used to calculate the
concentration of the condensation vapour and its source rate (Kulmala et al., 2006).
Spracklen et al. (2008) also used particle growth rate to estimate the amount of cloud
45
condensation nuclei (CCN) in climate modelling. This section will present the
mathematical definitions of particle formation and growth rates, as well as their
observed values in urban environments.
2.4.3.1 Estimation of the particle formation and growth rates
Due to instrument limitations, it is not possible to quantitatively measure the critical
clusters which are formed during atmospheric nucleation. At present, it is only
possible to detect particles down to a size of ~ 2.5 nm. Therefore, the nucleation rate
of clusters cannot be measured, only estimated, based on the following equation
(Kulmala et al., 2004):
eq. (1)
where particle formation rate, JD, is defined by the flux of particles reaching the size
D as a result of the particle growth process, t is the time, and n(Dp, t) represents the
particle number size distribution. However, it is quite difficult to determine particle
number size distribution and particle growth rate at size D and therefore, instead of
estimating the instantaneous particle formation rate JD(t), the average particle
formation rate, JD, over time interval ∆𝑡 , which is the duration of the particle
formation event, is often used. After time averaging, the equation can be rewritten as
follows:
46
eq. (2)
In eq. (2), ND, Dmax is the total PNC in the size range [D, Dmax] and Dmax is the
maximum size the critical clusters can reach because of their growth during ∆𝑡. The
left hand side of eq. (2) is the observed change in ND, Dmax during ∆t and can be
obtained from particle size distribution or number concentration measurements. On
the right hand side of the equation, the first and second terms represent the loss of
particles by self-coagulation and coagulational scavenging to larger pre-existing
particles in the size range [D, Dmax]. The last term on the right hand side represents
the external influence of other air masses on ND, Dmax.
When the effect of transport are small, eq. (2) can be simplified to
However, it may significantly underestimate the actual particle production rate when
the nuclei PNC is very high (> 105 cm-3). Also, if the pre-existing particle
concentration is very high, JD values can be under-estimated.
47
To estimate the particle growth rate, GR, the time evolution (Δt) of the lowest
detectable particle diameter to the upper limit of the nucleation mode particle, ΔD
(e.g. 25 nm) is needed. The GR can be calculated by:
GR = ΔD/Δt eq. (4)
2.4.3.2 Observed particle formation and growth rates in urban environments
The observed particle formation and growth rates in urban areas varied depending on
atmospheric conditions. In Table 2-2, particle growth rates ranged from 0.5-16 nm h-
1 for urban sites and the reported values for regional and local nucleation events were
similar. These observed particle growth rates were lower than that in marine areas,
which reached values > 100 nm h-1 (O’Dowd et al., 2007; Ehn et al., 2010). Higher
particle formation rates have also been observed for regional nucleation events,
which can reach values of 70-80 cm-3 s-1 compared to values of 0.2-50 cm-3 s-1 for
local nucleation events.
48
Locations GR (nm h-1) J3 (cm-3 s-1) References
St. Louis, United States 0.5-9 1-80 (regional) Shi et al. (2007)
Atlanta, United States 2-6 20-70 (regional) McMurry et al. (2003)
Birmingham, United Kingdom 4 5-50 Shi et al. (2001)
Leipzig, Germany -a 13 (±1.2) Wehner and Wiedensohler (2002)
Luukki, Finland 4-6 -a Väkevä et al. (2000)
Manchester, United Kingdom 8 >>0.2 Williams et al. (1998)
Pittsburgh, United States 4-5 -a Stanier et al. (2002)
Vienna, Italy -a 2.5 Winklmayer (1987)
Atlanta, United States -a 10-15 Woo et al. (2001)
New Delhi, India 11.6-16 -a Kulmala et al. (2005)
Marseille, France 1.1-8.1 -a Kulmala et al. (2005)
Marseille, France 2-8 3-5.3 Petäjä et al. (2007)
Athens, Greece 2.3-11.8 -a Kulmala et al. (2005)
Athens, Greece 1.2-9.9 1.3-6.5 Petäjä et al. (2007)
Harrow, Canada 6.4 4.4 Jeong et al. (2010)
Ridgetown, Canada 4.7 3.3 Jeong et al. (2010)
Bear Creek, Canada 2.9 3.6 Jeong et al. (2010)
Egbert, Canada 5.1 4.7 Jeong et al. (2010)
Toronto, Canada 6.7 1.1 Jeong et al. (2010)
Budapest, Hungary 2.0-13.3 (7.7±2.4)
J6:1.65-12.5 (4.2±2.5) Salma et al. (2011)
Note: a) ‘-‘ Data not available
Table 2-2. Summary of particle growth and formation rates in urban areas.
49
Section 2.4 summarised the factors controlling the nucleation process, such as
meteorological parameters and the nucleation mode particle precursors. Nucleation
was found to be favoured under strong solar radiation, low temperature conditions,
with a wind direction that transported regional pollution plumes towards the
nucleation site. Sulphuric acid and H2SO4 proxy were also found to be positively
related to the level of PNC, but the contribution of organic species remains unclear.
The variation in particle growth and formation rates observed for different urban
areas is usually the result of the different atmospheric conditions in each area and
higher particle formation rates were generally observed during regional nucleation
events compared to local events.
2.5 Characterisation of particle formation processes
2.5.1 Temporal variation
Characterisation of the temporal variation of particle size distribution and other
relevant factors is a common approach to explain which factors control particle
formation. In past studies, researchers revealed that sulphuric acid plays an important
role in particle formation in rural areas, whereby an increase in particle number was
often observed about 1-2 hrs after an increase in sulphuric acid concentration (Weber
et al., 1995, 1997; Charron et al., 2007). The time lag between these two parameters
suggests that it took some time for the nucleation process to occur and for the
particles to grow to the minimum detectable size (Weber and McMurry 1996).
Statistical analysis of nucleation particles and meteorological parameters is another
technique to understand the favourable atmospheric conditions related to nucleation
burst events. Researchers have found that the temporal variation of nucleation events
50
did not show a clear seasonal pattern, with nucleation burst events occurring in
different seasons for different study areas (e.g. Boy et al., 2003; Hyvärinen et al.,
2008; Sogacheva et al., 2008). Based on the diurnal variation of observed parameters,
nucleation bursts usually started in late mornings when temperatures were relatively
high and humidity was relatively low.
2.5.2 Backward trajectory technique
To better understand the relationship between nucleation events and the origin of air
masses, a number of back trajectory studies were conducted (e.g. Hussein et al., 2009;
Hyvärinen et al., 2008; Kristensson et al., 2008). Several models were applied for
this trajectory analysis, including HYSPLIT and FLEXTRA. Detailed descriptions of
the models and their accuracy are described in Draxler and Hess (1998), Stohl et al.
(1995) and Stohl and Seibert (1998). Using backward trajectory analysis, Hyvärinen
et al. (2008) categorised the wind sectors corresponding to regional nucleation events
in Utö, Baltic Sea. The results showed that nucleation events were related to NW-
NNW wind sectors, which originated from the boreal forest areas in Finland. In
addition to the origin of the air masses, trajectory analysis provides the speed of the
air masses during transportation. Hyvärinen et al. (2008) also noticed that the air
masses had spent more than 10 hr over the Baltic Sea on only 19% of the nucleation
days. Although the authors did not find any clear correlation between these two
parameters, they demonstrated that after spending sufficient time over the sea, no
nucleation events were expected to take place when these air masses were
transported to the measurement site.
51
2.5.3 Modelling of particle formation mechanisms
Two types of modelling techniques were applied for the particle formation study: i)
the mathematical approach (i.e. parameterisation model) was used to explain the
relationship between the input variables by an empirical equation and the other is the
chemical model (i.e. Chemical Transport Model (CTM)/ Chemical Box Model
(CBM), which includes the consideration of physical, chemical and meteorological
processes in nucleation. The parameterisation of formation mechanisms has been
investigated by numerous groups, including ternary nucleation (Napari et al., 2002),
binary nucleation (Vehkamäki et al., 2002; Jaecker-Voirol and Mirabel 1989) and
ion-induced nucleation (Modgil et al., 2005), while others used parameterisation to
explain in-situ particle formation (e.g. Weber et al., 1999; Kulmala et al., 1998; Yu
2006; Jung et al., 2008). Binary nucleation is proposed to be a principle formation
mechanism, since H2SO4 and water are basically presented anywhere in the
atmosphere. Weber et al. (1999) predicted the binary nucleation rate in remote
troposphere regions at altitudes greater than ~ 4 km above sea level and found that
the concentration of sulphuric acid vapour observed in the atmosphere was sufficient
to reproduce the observed nucleation rate. However, this study also pointed out that
binary nucleation may not be valid for the warmer temperatures observed at lower
altitudes, where sulphuric acid concentration was lower due to the higher saturation
vapour pressure. This implied that ternary nucleation was a more significant
mechanism for particle formation. Further ground based nucleation studies were also
conducted which showed similar levels of particle formation due to ternary
nucleation (e.g. Birmili et al., 2000, Jung et al., 2008 Kulmala et al., 2000).
52
Therefore, it is clear that the dominant nucleation process varies under different
environmental conditions. Although, the parameterisation method can simulate the
new particle formation event, the calculated formation rates of particles were
underestimated by the input data which were observed in the ambient. Thus, the
CTM approach was applied to better simulate the nucleation including the physical,
chemical and meteorological processes. Zhang and Wexler (2002) conducted a
timescale analysis of aerosol dynamic under urban conditions. Their result have
shown that the process of condensation, coagulation, nucleation and emission were
the dominating factors affecting the particle size distribution in the urban
environment. A reasonably well matched result for the particle number concentration
and new particle formation events were obtained by the Weather Research and
Forecast model coupled with Chemistry (WRF-Chem), compared to the observation
data in lower troposphere of the eastern United States (Luo and Yu 2011). Although,
CTM needed a larger input dataset than that of the parameterisation model and
higher uncertainty was found for a large scale study (i.e. long-range transport from
outside the model domain) (Chang et al., 2009). This approach can provide however,
an insight to the nucleation mechanism in the local/ regional study. If the simulated
result does not fit with the observed data, this implies that there are some currently
unknown mechanisms/ theories involved in the nucleation.
Section 2.5 discussed several data analysis techniques applied in urban nucleation
studies, however there are still some areas of knowledge which need to be improved
53
in order to gain a better understanding of the nucleation process which occur in urban
environments. The backward trajectory technique is usually applied to trace the
medium and long range (from tens to hundreds of kilometres) transportation of air
masses, however the grid resolution is not accurate enough to identify the path of air
movement in a scale of 10 km (or lower). Usually urban emission sources are located
very close to each other, and the air masses contain a mixture of pollution from
different sources, which makes it hard to identify the primary pollution sources
affecting urban nucleation events. Further studies on particle source identification
during nucleation events could help to better understand the primary contributors to
new particle formation. Furthermore, the results of parameterisation studies showed
that different nucleation mechanisms can dominate in the same study location
depending on the atmospheric conditions. Therefore, more field studies are also
needed in different study environments, to better understand the nucleation process
in specific study areas.
2.6 Development of measurement techniques
The instrumental techniques for measuring UFP have improved significantly over the
past decades. The development of condensation particle counters (CPCs) was
initiated in the 1970s (Sinclair and Hoopes 1975; Bricard et al., 1976), and
commercialised in the 1980s (Kousaka et al., 1982). More recent CPCs, which can
detect particle as small as 2.5 nm, were developed by TSI Inc. (Models 3776 and
3786) and Scanning Mobility Particle Sizers (SMPS), which consisted of Differential
Mobility Analyser (DMA) and CPC, were also developed to measure the size
54
distribution of particles. After the DMA separates the particles in the selected size
range, the concentration of particles in the desired size range is measured by the CPC.
The complete size distribution of particles can be obtained by changing the size
window of the DMA. Since the development of the SMPS, numerous studies were
conducted to investigate the particle formation processes and many of the
observational based studies were reviewed by Kulmala et al. (2004).
A technique for measuring the size distribution of charged particles, which can detect
ion clusters down to ~2.5 nm in size, has only become available in recent years and
measurement results have provided insight into particle formation by ion-induced
nucleation (e.g. Kulmala et al., 2007; Vana et al., 2008). Three very recently
developed instruments have also been applied to measure neutral and charged ion
clusters with diameters down to 1 nm and 0.3 nm, respectively, namely a Balanced
Scanning Mobility Analyser (BSMA), an Air Ion Spectrometer (AIS), and a Neutral
Cluster Air Ion Spectrometer (NAIS). Using these instruments, Kulmala et al. (2007)
showed that both neutral and charged ion clusters (with a mean diameter ~1.5-1.8 nm)
were present almost all the time during nucleation events in the boreal forests of
Hyytiälä, Finland and suggested that atmospheric aerosol formation started with
particle ~1.5 nm in size. For < 3 nm clusters, the concentration of air ion clusters was
around 10-100 cm-3 which was significantly lower than the concentration of neutral
clusters, which was ranged from 1500-3000 cm-3 during the study period. Therefore,
the authors suggested that less than 10% of the particles formation rate was
contributed by ion-induced mechanisms under boreal forest conditions.
55
Chemical analysis of atmospheric UFP is limited, with Viana et al. (2008) pointing
out that only 1% of previous studies on airborne particulate pollution target UFPs
and hence, there is limited information available on the source profile of UFPs.
Traditional methods used to measure the chemical composition of UFP are based on
the offline technique of collecting the aerosol on the filter, followed by chemical
analysis in laboratory (McMurry 2000). More recently, several instruments have
been developed, based on the mass spectrometry technique, for measuring the real-
time chemical composition of UFPs (Suess and Prather 1999). Most of these mass
spectrometry instruments enable the measurement particles down to ~20 nm in size.
For the chemical characterisation of particles below 10 nm, the Thermal Desorption
Chemical Ionisation Mass Spectrometer (TDCIMS) is capable of measuring the
molecular composition of atmospheric aerosol in the range 4 -10 nm (Voisin et al.,
2003). The TDCIMS consists of an electrostatic precipitator for collecting charged
particles, which is equipped with a nanometre aerosol differential mobility analyser
to separate the sub-10 nm particles. After collection, the sample is analysed by the
evaporation-ionisation technique. A more detailed description of the system can be
found in Voisin et al. (2003).
Although several instruments are available to measure the chemical composition of
UFP, most of them are not commercially available. The Aerosol Mass Spectrometer
(AMS), which is available on the market, measures the chemical composition of UFP
down ~40 nm in size. Rhoads et al. (2003) used the AMS to measure the real-time
chemical composition of semi-volatile species in Atlanta, United States. In this study,
organic species contributed about two thirds of the total measured chemical mass of
56
UFP. It should be noted that sulphate was not measured in this study, which was also
an important component in atmospheric aerosols. Pakkanen et al. (2001) also
measured chemical composition of UFP in urban and rural areas in Helsinki, Finland
and found similar chemical compositions in both areas. In this study, the measured
components accounted for about 15-20% of total UFP mass. Sulphate and
ammonium were the major measured components which contributed about 6-8%,
and 4-5% of the total ultrafine masses (490-520 ng/m3), respectively. This suggested
that carbonaceous species contributed about 70% of the total ultrafine mass which
was not accounted in the composition measurement.
In conclusion, the techniques for measuring particle chemical composition have
improved significantly in recent years. This has allowed the study of the chemical
composition of particles down to 4 nm in size, however these instruments are still not
widely available, which limits the progress of the study of nucleation.
2.7 Research problems
Based on the above overview of previous research on particle formation, the major
scientific issues that have been identified can be summarised as follows:
- Intensive field measurements of neutral/charged clusters were mainly
conducted in clean environments, such as continental rural area/boreal forests,
arctic and marine environments, and the upper troposphere. These studies
were mostly conducted in the northern hemisphere and they showed that
nucleation processes were complex in different environmental settings; and
57
- Several parameterisations of particle formation were developed for
homogeneous binary/ternary nucleation, ion-induced nucleation etc.
Although some parameterisation studies showed a good agreement between
modelling results and the observed data, the modelling results for particle
formation rate were usually lower than the observed data, which suggested
that the particle formation may not be attributable to a sole mechanism.
In order to fully understand the atmospheric aerosol nucleation process, several gaps
in knowledge still need to be addressed, which include:
- Improvement of instrumentation techniques for measuring the chemical
composition of nucleation particles;
- Characterisation of the particle formation processes which occur in the urban
environment, especially in southern hemisphere, as there have been limited
nucleation studies conducted in this area. In addition, higher solar radiation
has been recorded in the southern hemisphere than in the northern hemisphere,
which can enhance photochemical activity;
- Investigation of the mechanisms involved in the particle formation process;
and
- The inclusion of findings from particle formation studies in climate models
for estimating climate change.
58
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CHAPTER 3
Environmental monitoring of airborne nanoparticles
L. Morawska, H. Wang, Z. Ristovski, E.R. Jayaratne, G. Johnson, H.C. Cheung, X.
Ling and C. He
International Laboratory for Air Quality and Health, Queensland University of
Technology
GPO Box 2434, Brisbane QLD 4001, Australia
Published by the Journal of Environmental Monitoring
69
STATEMENT OF JOINT AUTHORSHIP
Title: JEM Spotlight: Environmental monitoring of airborne nanoparticles
Authors: L. Morawska*, H. Wang, Z. Ristovski, E.R. Jayaratne, G. Johnson, H.C.
Cheung, X. Ling, and C. He
Morawska L.
Developed the structure of the paper, complied most of its contents and reviewed the
measurement techniques and common locations for particle concentration and
chemical composition studies.
Wang H.
Reviewed particle elemental composition measurement techniques and compared the
most commonly used measurement instruments.
Ristovski Z.
Reviewed the measurement techniques for particle surface area and elemental
composition and assisted in writing the manuscript.
Jayaratne E.R.
Reviewed the measurement techniques for particle concentration and size
distribution and compared the difference between CPC and SMPS measurements in
different environmental particle number monitoring studies.
Johnson G.
Reviewed the measurement techniques for particle concentration and size
distribution and compared the difference in particle number concentrations for the
different types of CPCs in measuring particle number concentrations.
Cheung H.C.
Assisted with comparing particle number concentration for the different types of
CPCs and assisted in writing the manuscript.
70
Ling X.
Reviewed the measurement techniques for particle concentration and size
distribution and compared the difference CPC and SMPS in different environmental
particle number monitoring studies.
He C.
Reviewed particle elemental composition measurement techniques and compared the
most commonly used measurement instruments
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CHAPTER 3. ENVIRONMENTAL MONITORING OF AIRBORNE
NANOPARTICES
L. Morawska*, H. Wang, Z. Ristovski, E.R. Jayaratne, G. Johnson, H.C. Cheung, X.
Ling, and C. He
International Laboratory for Air Quality and Health, Queensland University of
Technology, GPO Box 2434, Brisbane QLD 4001, Australia
Abstract
The aim of this work was to review the existing instrumental methods to monitor
airborne nanoparticles in different types of indoor and outdoor environments in order
to detect their presence and to characterise their properties. Firstly the terminology
and definitions used in this field are discussed, which is followed by a review of the
methods to measure particle physical characteristics including number, concentration,
size distribution and surface area. An extensive discussion is provided on the direct
methods for particle elemental composition measurements, as well as on indirect
methods providing information on particle volatility and solubility, and thus in turn
on volatile and semivolatile compounds of which the particle is composed. A brief
summary of broader considerations related to nanoparticle monitoring in different
environments concludes the paper.
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3.1. Introduction
3.1.1 Sources of Nanoparticles
The beginning of the twenty-first century has witnessed an explosion of interest in
the science and technology of engineered nanoparticles - structures that range in size
from a few, up to about 100 nm. These particles can escape into the environment,
and along with an increasing demand for nanomaterials in terms of both quantity and
quality, there have also been growing concerns regarding their potential impacts on
human health. However, nanomaterial engineering is not the only source of
nanoparticles in ambient air. To the contrary, there are many natural and
anthropogenic processes which can lead to the formation of large quantities of
nanoparticles, and as a result, they are omnipresent in both indoor and outdoor air.
The most significant sources of nanoparticles are combustion processes, both natural
and anthropogenic (the later including vehicle and industrial emissions, biomass
burning and tobacco smoking), but also natural processes, in particular those leading
to secondary particle formation via nucleation. In the urban environment, motor
vehicle combustion is the main source of secondary airborne nanoparticles, which
are not emitted directly by the source but formed in the air from precursors
originating from one or more sources. For example, considerable progress in engine
combustion technologies has led to more complete combustion, whereby the size of
primary black carbon soot particles in vehicle exhaust has decreased substantially
from the micrometer into the nanometre size range. These smaller soot particles have
a reduced surface area for the volatile organic compounds in vehicular exhaust to
condense upon and as a result, instead of condensing onto soot particles, these
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semivolatile species homogeneously nucleate to form high concentrations of
nanoparticles. Sometimes formation processes also involve photochemistry and in
such cases, light is an essential factor for the process to proceed. Examples of these
processes include the formation of secondary nanoparticles from biogenic emissions
in forest or marine environments, as well as from sources found in the indoor
environment, including modern office equipment (e.g. printer emissions) or
consumer products (e.g. detergents or paints).
3.1.2 Impacts of Nanoparticles
The potential hazards from the inhalation of nanoparticles by humans are very
different to those from the inhalation of larger particles because nanoparticles are not
readily removed from the airstream of inhaled air in the upper parts of the respiratory
tract and therefore, they are inhaled into much deeper regions of the lung1. When in
the small containments of the alveoli region, diffusional deposition of the particles on
the epithelium becomes an efficient physical mechanism, with an alveolar deposition
of about 40% for 50 nm particles compared to about 10% for 700 nm particles2. The
nanoparticles deposited in this oxygen/blood exchange region can penetrate very
quickly and efficiently into the blood stream. If these particles are charged, they pose
an added risk to human health, since inhaled charged particles have a five to six-fold
increased probability of depositing in the lung than uncharged particles of the same
size3.
To date, the toxicity of these nanoparticles, their penetration across the blood-brain
barrier and the pathways leading to nanoparticle-related cardiovascular diseases have
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been demonstrated. In addition to health effects, these man made nanoparticles have
also been shown to have significant impacts on the environment, more specifically
on atmospheric properties and climate modification, by providing seeds for
atmospheric nucleation processes, as well as changing the optical properties of the
atmosphere.
Considering these potential risks to human health and the environment, it is of
critical importance to not only monitor the presence of nanoparticles in the air, but
also to obtain a good quantitative understanding of their physical and chemical
properties, as well as spatial and temporal trends in indoor and outdoor environments.
The instrumental methods which are now available to monitor the presence of these
particles in the air, as well as characterise their properties, are the main focus of this
review.
3.2. Definition of ‘Nanoparticles’
Many terms have been used in relation to particles in the nanosize range, which
extends from about 1 to over 100 nm, with the most common terms being ultrafine
particles and nanoparticles. Within the field of aerosol science the term “ultrafine
particle” has been used in relation to particles smaller than 100 nm 4, while
nanoparticles are generally referred to as those smaller than 50 nm 4. Both these
terms constitute a somewhat arbitrary classification of particles in terms of their size,
indicating the significant role of this physical characteristic on particle fate in the air.
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Common to the various definitions of ultrafine particles was “at least one dimension
less than 100 nm” 5, 6. While there has not been universal agreement on these terms,
they have been used to differentiate between particles formed through different
mechanisms. In particular, in the field of vehicle emissions, primary particles, which
are generated during a combustion processes, are generally referred to as ultrafine
particles, while secondary particles (i.e. those that are not emitted from a source but
formed in the air) and those originating from homogenous or heterogeneous
nucleation are referred to as nanoparticles. In contrast to the fields of ambient aerosol
or combustion emissions science, the term “engineered nanoparticle” is the preferred
term when describing nanosize particles originating from various manufacturing or
engineering processes.
A more rigorous definition of these terms has been introduced by the International
Standards Organisation (ISO). In particular, ISO/TC 146/SC 2/WG1 N 320 defines a
nanoparticle as “A particle with a nominal diameter smaller than about 100 nm”, a
nanoaerosol as “An aerosol comprised of or consisting of nanoparticles and
nanostructured particles” and a nanostructured particle as “A particle with
structural features smaller than 100 nm, which may influence its physical, chemical
and/or biological properties”. This means that a nanostructured particle may have a
maximum dimension substantially larger than 100 nm, since a 500 nm diameter
agglomerate of nanoparticles would be considered a nanostructured particle. The
same document defines an ultrafine particle as “A particle sized about 100 nm in
diameter or less” and thus, an ultrafine aerosol would contain a majority of particles
of this diameter or less.
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It should be mentioned here that the 100 nm cut-off for nanoparticles is not derived
from particle behaviour in the respiratory tract following deposition, and therefore it
is not a health based metric 7. A health based metric will need to consider the fact
that as particles become smaller, surface curvature, the arrangement and percentage
of atoms on the particle surface, and the size dependent quantum effects, such as
quantum confinement, play an increasingly significant role in determining behaviour
7.
When referring to nanoparticle measurements, an unspoken assumption is made that
the instrumental methods used provide information on particles in the specific size
range, which is below 100 nm. This is possible if the instrumental method enables
measurements of particle number size distribution, usually in a broader range, from
which the sections of data encompassing nanoparticles are then extracted. If, rather
than employing instrumentation for particle size distribution measurement, only a
particle counter is used, the outcome of the measurement is the total particle number
concentration in the detection size range of the instrument. This means that the
outcomes of the measurements are not specifically nanoparticle concentrations,
unless specific inlets are used which restrict the range of particles entering the
instrument’s sensing volume. While it is true that, in most typical environments,
particle number concentration is dominated by nanoparticles, it is important to keep
in mind that these are not the same and that there are environments where there are
significant particle modes outside the nanosize range.
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In the view of the fact that the instruments detecting nanoparticles do not strictly
restrict particle size (as discussed above), when discussing the instrumental
techniques for nanoparticle monitoring, it is generally not essential to use a rigorous
definition of the particles, and therefore, in relation to the review, there is no need to
accept a particular definition. For simplicity, through the paper only the term
“nanoparticle” is used, unless refereeing to published data using other terms.
3.3. Particle Concentration and Size Distribution
3.3.1 Particle number concentration measurements
The particle detection and counting techniques used in environmental monitoring
primarily employ optical detection methods and this is also true of nanoparticle
sampling. However particles smaller than about 50 nm do not interact strongly with
electromagnetic radiation of optical or near optical wavelength, and so are not
detected efficiently by light blocking or scattering. To overcome this range limitation,
environmental nanoparticle number concentration measurements must employ
Condensation Particle Counters (CPC’s) which effectively enlarge the particles to
detectable sizes by condensing a low vapour pressure material onto the original
particles from the gas phase. Condensation Particle Counters (CPCs) typically
contain water or butanol as the condensable species used to grow the particles to a
detectable size, although a small number, such as TSI’s PTrak, use propenol. A list
of water-based and butanol-based CPCs are provided in Table 3-1. The mass
diffusivity of condensable species dictates the design of the instrument and therefore,
instruments using species’ with a lower diffusivity than air, such as the butanol based
78
instruments, rely on the greater diffusivity of air to carry heat away from a warm
vapour enriched aerosol stream as it passes though a cooler condensing tube, thereby
increasing the vapour concentration to the super-saturation levels needed for particle
growth. In contrast, instruments relying on highly diffusive species for particle
growth, such as water vapour, may achieve super-saturation by passing a cooler
aerosol stream through a warm tube coated with the condensable species, so that the
more mobile condensable species carry heat to the cooler aerosol, thereby reaching
super-saturation8. Alternatively, such instruments may rely on the rapid mixing of
two flows, each saturated at different temperatures, to produce super-saturation9, 10.
For an insoluble species, the predicted lower detection size limit is the Kelvin
diameter corresponding to the super-saturation ratio achieved in the aerosol.
However, a species which is soluble in the condensing species will have an
associated equilibrium vapour pressure for the condensing species lower than that for
an inert particle such that the particles may be detectable at smaller sizes. Therefore,
the solubility of the aerosol in the condensable species can affect the lower detection
limit achieved by an instrument.
Several studies have been conducted to compare the performance of butanol and
water based CPCs for different types of aerosol. These have examined the relative
response of the instruments to aerosols for different particle sizes, compositions and
concentrations. Biswas et al.11 conducted a study comparing a butanol based CPC
(BCPC) with a water based instrument (WCPC) for NH4SO4, NH4NO3, glutaric acid,
and adipic acid aerosols generated in the laboratory. The concentration ratio
79
(WCPC/BCPC) recorded by the two instruments ranged from 1.0-1.1 for particles
sizes in the range 10-50 nm, while a slightly higher WCPC/BCPC ratio was obtained
for particle sizes of less than 15 nm. In addition, Hering et al.8 compared an ultrafine
water-based CPC TSI 3785 with a BCPC TSI 3025. Comparable results of WCPC
and BCPC (within ±3% differences) were observed for 80 nm Oleic acid, and 50 nm
NaCl particles. They also showed that the water based instrument responded with
varying sensitivity near the lower size limit depending on the composition of the
aerosol with detection efficiency for the smallest particles being greater when water
soluble species were present in the particles.
Iida et al.12 also compared the performance of the WCPC TSI 3786 and BCPC TSI
3025 under field conditions using different particle sizes. The tests were conducted in
freeway tunnels and ambient environments. For ambient air, the WCPC and BCPC
values were comparable for particles > 5 nm and at 3 nm, the BCPC showed higher
detection efficiency than the WCPC. In contrast, the tunnel data showed that the
WCPC/BCPC ratio was larger than 1.0 for the smaller particles. The authors
suggested that the difference in performance between the WCPC and BCPC, in
ambient and freeway tunnel environments, may be due to differences in the
instrumentation or differences in particle composition. In addition, Biswas et al.11
observed that the WCPC/BCPC ratio varied with particle concentration, with the
WCPC/BCPC ratio being > 1.0 when the particle concentration was below 3 x 104
cm-3 but < 1.0 for higher concentrations (3 x 104 – 8 x 104 cm-3). Similarly, Mordas et
al.13 used 15 and 30 nm silver particles to compare the performance of a WCPC with
respect to an electrometer. The results showed that WCPC/Electrometer ratio was >
80
1.0 for particle concentrations below 3 x103 cm-3, close to 1 for particle
concentrations in the range 3 x 103 - 5 x 104 cm-3 and < 1 for larger concentrations.
The results of the above studies do not support any firm conclusions regarding the
reasons behind the observed differences between the WCPC and BCPC. In Biswas et
al.11, the chemical composition of the aerosol did not affect the relative particle
concentrations recorded by the water and butanol based instruments, however Iida et
al.12 suggested that the chemical properties of the aerosol play a role near the
instruments lower size limit, showing a difference in performance for water and
butanol based instruments with the same 3 nm nominal detection limit when
measuring 3 nm ambient and freeway tunnel particles. Higher concentrations were
recorded by the butanol based instrument for ambient air but lower concentrations
were recorded for vehicle emissions. Consistent differences in response were
observed for a WCPC and BCPC in both Biswas et al.11 and Mordas et al.13, where
the WCPC consistently counted more particles than the BCPC under lower
concentrations, but counted fewer particles at higher concentrations. Further
comparisons of WCPC and BCPC performance are needed to investigate the impact
of differing aerosol types near the lower cut-off sizes of the instrument.
81
Table 3-1. Commercial CPCs and their specifications.
Water-Based CPCs
Manufacturer Model Size range (nm) 1Conc. range (p/cm3) Response time to 95% conc. (sec)
2Flow rate (lpm) Working fluid
From To From To Aerosol flow 5Inlet flow
TSI 3781 6 > 3000 0 5 x 105 < 2 0.12 ± 0.012 0.60 ± 0.12 water
TSI 33782 10 > 3000 0 5 x 104 < 3 0.60 ± 0.06 water
TSI 43785 5 > 3000 0 1 x 107 1.0 ± 0.1 water
TSI 3786 2.5 > 3000 0 1 x 105 < 2 0.3 0.60 ± 0.03 water
Alcohol-Based CPCs
TSI 3 3010 10 > 3000 0.0001 1 x 104 1.0 ± 0.1 N-butyl alcohol
Condensation Particle Counters (CPCs) are widely used for measuring the
number concentration of nanoparticles in outdoor and indoor environments and in
emissions from specific sources such as combustion engines industrial process and
laser printers (He et al., 2007; Morawska et al., 2008). They are also commonly used
in size distribution measurement systems such the Differential Mobility Analyser and
Scanning Mobility Particle Sizer (Hämeri et al., 2002; Cheung et al., 2010) as well as
physicochemical characterisation systems based on the tandem differential mobility
analysis technique (Rader and McMurry, 1986; Johnson et al., 2004). Although there
have been a number of CPCs available commercially with different specifications for
particle size range, concentration range, response time and sampling flow rate, the
basic working principle is similar in each case. Nanoparticles too small to be
detected directly by optical means are enlarged to detectable sizes by condensing a
low vapour pressure material onto their surfaces from the gas phase (Morawska et al.,
2009b). The two major types of condensable species commonly used are alcohols
(mostly butanol and isopropyl alcohol) and water. The lower detection size limit of
insoluble particles depends on the Kelvin diameter corresponding to the super-
saturation ratio achieved in the aerosol as it passes through the instrument. It is also
known that the condensation tube design of a CPC affects the minimum detectable
size at which a particle can be detected by the CPC. The detectable particles sizes are
governed by the temperature difference between the saturator and condenser inside
the CPCs so that the minimum detectable size can be varied to some extent by
changing that temperature difference (Metres et al., 1995; Hering and Stolzenburg,
2005).
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Soluble particles, however, effectively lower the saturation vapour pressure of
the condensing species above the particle surface, resulting in a smaller activation
diameter and hence a lower detection size limit compared to insoluble materials.
Therefore, divergence of detection efficiencies of different aerosols by water based
CPC (WCPC) and butanol based CPC (BCPC) are to be expected.
Several studies have demonstrated variations in CPC performance with
different aerosols. These studies have investigated the detection efficiencies of
WCPC and BCPC for different types of aerosol including lab-generated aerosols and
outdoor ambient aerosols. Biswas et al. (2005) found that the WCPC/BCPC
concentration ratio ranged from 1.0 to 1.1 for particle sizes in the range 10 to 50 nm
for ammonium sulphate ((NH4)2SO4), ammonium nitrate (NH4NO3), glutaric acid
and adipic acid. Hering et al. (2005) examined the detection efficiency of a WCPC
with respect to hydrophobic species including oleic acid and dioctyl sebacate (DOS)
as well as hydrophilic species including sodium chloride (NaCl), (NH4)2SO4 and
NH4NO3. The investigation showed that a lower D50 (diameter detected with 50 %
efficiency) was obtained for water-soluble species (3.6 nm < D50 < 4.8 nm) but
higher values for hydrophobic species (8 nm < D50 < 30 nm). Moreover, Iida et al.
(2008) conducted a comparison between a WCPC and a BCPC by measuring the
particle number concentrations at an urban location and in a freeway tunnel. The
results showed a WCPC/BCPC ratio < 1.0 for ambient urban particles with diameters
< 5 nm. In contrast, a WCPC/BCPC ratio > 1.0 was obtained for freeway tunnel
particles. The authors concluded that the differences observed between these two
types of particles could be due either to differences in the instrumentation used, or to
differences in particles composition. Franklin et al. (2010) compared the responses of
two different WCPC’s (WCPC1 and WCPC2) and one BCPC to diesel combustion
143
aerosols. They found that WCPC1 (Model: TSI 3782, with nominal D50 = 10 nm)
significantly undercounted particles compared to the BCPC (Model: TSI 3010, with
nominal D50 = 10 nm) while WCPC2 (Model: TSI 3786, with nominal D50 = 2.5 nm)
closely agreed with the BCPC and only undercounted for particle diameters
approaching the lower cut off size of the instrument. The differences in detection
efficiency between different CPC’s for different aerosol species were less
pronounced for particles with diameters larger than 30 nm (Hering et al., 2005;
Mordas et al., 2008). These previous studies indicate that the particle number
concentration measured by a WCPC depends on the aerosol composition and its
solubilities to the condensation medium. This understanding of the varying detection
ability of CPCs with different particulate species is especially important for source
specific measurement where the aerosol may be of a specific chemical composition
and size.
In previous studies, hydrophilic or hydrophobic aerosols were selected for the
CPC detection performance testing. However, little information is currently available
for species which are soluble both in water and alcohol. Therefore in this study, we
undertook a comprehensive comparison of the detection performance of WCPC’s
and BCPC’s for hydrophobic species as well as for citric acid which can dissolve in
both water and alcohol in order to develop an in-depth understanding of the influence
of particle composition CPC performance.
4.2 EXPERIMENTAL SETUP
In this study, four different types of particle were tested including hygroscopic
(NaCl), hydrophobic (DOS and Laser Printer Toner) and citric acid which can
144
dissolve in water and alcohol (Haynes ed., 2011). DOS and Laser printer toner
particles have been shown to be hydrophobic through VH-TDMA measurements
where the particles absorb no moisture when exposed to very high humidity (Johnson
et al., 2004; Morawska et al., 2009a). The response of different classes of CPC to
diesel combustion engine exhaust aerosols has previously been examined in some
detail by Franklin et al. (2000), so that aerosol was not included in the current study.
A list of the test particle composition and the equipment used in the experiment is
shown in Table 4-1.
Aerosols Solubility
Sodium Chloride (NaCl) Soluble in water; insoluble in alcohol
Dioctyl sebacate (DOS) Insoluble in water; soluble in alcohol
Laser Printer Toner Insoluble in water; slightly soluble in alcohol
Citric acid Soluble in water and alcohol
Instruments Manufacture/model Remarks
Electrostatic classifier TSI 3080 Size range coverage: 4 – 60 nm
TSI 3071 Size range coverage: > 60 nm
Water based CPC TSI 3781
TSI 3782
D50 ≥ 6 nm
D50 ≥ 10 nm
Butanol based CPC TSI 3010
TSI 3010*
D50 ≥ 10 nm
D50 ≥ 7.6 nm
TSI 3025 D50 ≥ 3 nm
Table 4-1. A list of testing aerosols and instrumentation applied in this study. Note: TSI 3010* The asterisk (*) indicates that the temperature difference between saturator and condenser of the CPC was increased into 21˚C to lower the D50 value to 7.6 nm (Mertes et al. 1995).
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4.2.1 Aerosol generation
Polydisperse NaCl, printer toner, citric acid and dioctyl sebacate (DOS)
particles were generated by three different methods (see Figure 4-1 a-c).
a) The NaCl, printer toner (note that an additional method was also used to
generate toner particles, see below) and citric acid particles were generated using the
tube furnace by heating up the materials to 680 ˚C for NaCl, 390 ˚C for toner and
175 ˚C for citric acid, respectively. The vaporized materials then condense to form
nanoparticles which follow the air stream to the particle measurement modules.
b) DOS aerosol was generated by a Condensation Monodisperse Aerosol
Generator (CMAG), Model: TSI 3475, operating in homogenous nucleation mode by
heating up the DOS inside the saturator to vaporise it and then passing through a
condensation tube to form homogeneous DOS nano-particles.
c) In addition to the toner aerosol generated by the tube furnace, toner aerosol
generated during laser printing was also examined. The commercial laser printer was
installed inside the air chamber and the CPC measurements were conducted during
the printing process. The laser toner particle generated during the printing process
was used to simulate the actual situation of indoor emission by the laser printer.
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Figure 4-1. Systematic diagram of the experimental. Left: aerosol generation; right: aerosol detection.
4.2.2 Particle measurement
After the particles were generated, the polydisperse particles were passed
through an Electrostatic Classifier (EC), Model: TSI 3080 (with Nano-DMA TSI
3085)/ TSI 3071 (with Long-DMA 3081). The polydisperse aerosol size was
classified by the EC according to the electrical mobility of the neutralised singly
charged particles to form a monodisperse aerosol for which the count median
diameter (CMD) could be selected by choosing the corresponding EC voltage. The
aerosol was then split into two streams, one going to the WCPC (Model: TSI 3781 or
TSI 3782), the other to the BCPC (Model: TSI 3010, TSI 3010* or TSI 3025), to
measure the particle number concentrations. Before the experiment, all the flow
147
paths of EC and the CPCs were calibrated using a bubble flow meter to ensure that
the flow rate was within instrument specification and the particle number
concentrations were corrected according to the actual flow rate of the CPCs. The
lengths of tubing used between the instruments were minimised to reduce deposition
losses and the tubing between the EC and each CPC was in each case the same (~ 40
cm).
This investigation focuses on the relative performance of the CPC’s. Hence the
comparison between the BCPC and WCPC reflects their relative responses and
neither instrument is assumed to be 100% efficient in detecting particles of a given
type. The sampling period for each sample was 5 mins (with data being logged every
second this yielded a total of 300 data points for each test) and a further 5 mins was
allowed for the monodisperse aerosol concentration to stabilize after changing the
EC voltage to a new particle size.
4.3 RESULTS AND DISCUSSION
4.3.1 BCPC/WCPC ratios for different aerosol compositions and particle sizes
Number concentrations of different particle types were measured by BCPC and
WCPC and the ratios BCPCi/WCPCj (where the indices i and j: represent models of
CPC) were then calculated. These BCPC/WCPC ratios were used to represent the
relative detection abilities of the CPCs. For example a higher BCPC/WCPC value
indicated that the BCPC had a higher detection efficiency than the WCPC for the
tested aerosol. In the following section, the results will be presented in two parts. In
part i) we consider the effect of particle composition and in part ii) the influence of
particle concentrations on the relative detection efficiency of the CPC’s.
148
Figure 4-2 shows the BCPC/WCPC ratios for different aerosols. The
combination of the BCPC and WCPC used for NaCl, DOS and toner were TSI 3010*
(BCPC) and TSI 3781 (WCPC). For Citric acid, TSI 3025 (BCPC) and TSI 3781
(WCPC) were used. Standard deviation calculated by the 300 data points was
represented by the error bar. The toner aerosols generated by two methods are
denoted TonerF (when generated by the tube furnace) and TonerC (when generated by
the printer in the chamber).
Figure 4-2. BCPC/WCPC ratios when exposed to different sizes of NaCl, DOS, toner and citric acid particles.
4.3.1.1 Hygroscopic - NaCl
BCPC3010*/WCPC3781 ratios for particles smaller than 8 nm were all below 0.79
(± 0.01–0.06). The discrepancy between the BCPC and WCPC was less for particles
in the range 12 – 100 nm. BCPC3010*/WCPC3781 ratios for these larger NaCl particles
ranged from 0.92 to 0.96 (±0.01-0.02). This result is comparable to that by Hering et
al. (2005) who found an enhanced response for NaCl in the WCPC for particles
smaller than 12 nm. The authors suggest that the water uptake effects of salt aerosol
149
in the conditioner reduced the diffusional loss of the aerosol which is greater for
smaller particles. In addition, the authors also noted that the reduction of equilibrium
vapour pressure of water above salt particle lowers the activation diameter for
droplet growth (Hering et al., 2005).
4.3.1.2 Hydrophobic - DOS and toner
For DOS particles, the WCPC3781 significantly undercounted at 10 nm
(BCPC3010*/WCPC3781: 2.7 ±1.7). The overall trend of the ratio was to approach unity
for particle sizes ≥ 12 nm. A similar result was found by Hering et al. (2005) who
showed that the D50 for a WCPC (Model: TSI 3785) for DOS particles was
approximately 10 nm for a contaminated DOS sample and 30 nm for a new sample.
The “contaminated” sample referred to a DOS sample which had been stored in the
nebuliser overnight and the “new” sample referred to one freshly decanted into a
clean nebuliser. The major difference of the DOS generation methods is the size
distribution of the aerosol that the DOS particles produced by the evaporator tends to
have smaller sizes while larger DOS particles will be generated by nebuliser method.
For toner particles, the result presented in Figure 4-2 shows that the
WCPC3781 is incapable of detecting toner particles at diameter below 18 nm. The
BCPC3010*/WCPC3781 ratios for the tube furnace and chamber methods of toner
particle generation were 4.2±0.5 at 18 nm and 9.6±2.6 at 15 nm. These ratios
decreased for particles size larger than 20 nm, ranging from 1.70 down to 1.19 for
TonerF and from 1.31 down to 1.21 to for TonerC. This result was not unexpected as
the particles emitted by the printing process of the laser printer have been shown to
be hydrophobic (Morawska et al., 2009b) and are believed to contain aromatic
150
organic compounds such as toluene, ethylbenzene, xylene and styrene oligomers
which are water insoluble compounds. These results are consistent with water
insoluble species having difficulty activating the condensation process with water
vapour.
4.3.1.3 Citric Acid
Citric acid is an organic acid which is a solid at room temperature. It dissolves
both in water and in butanol. Less variability of the BCPC3025/WCPC3781 ratio was
obtained for citric acid compared to that for the other aerosols. The ratio for 8 nm
particles was 1.20±0.27 and this showed larger variability than that for particles
larger than 20 nm (1.07 – 1.19 ± 0.06-0.14). Since citric acid dissolves readily both
in water and butanol, the particles should readily undergo condensational growth by
both water and butanol. However these CPC’s have somewhat different nominal D50
values. The BCPC3025 has a lower D50 (3 nm) value than WCPC3781 (D50 = 6 nm) so
that a higher count for smaller particles is to be expected. The slightly higher
BCPC/WCPC ratios observed for particles large than 20 nm is probably due to
differences in the slope of the detection efficiency curves of the two instruments. For
example the WCPC3781 is claimed to have a detection efficiency of 50% at 6 nm
rising to 90% at 20 nm while the WCPC3025 detection efficiency is claimed to rise
rapidly from 50% at 3 nm to 90% at 5 nm.
From the results of NaCl and citric acid, the WCPC showed a capability to
detect those water soluble particles even for particles smaller than 10nm. These
results could be due to the hygroscopic properties of the aerosols as this would
enhance water uptake and so increase the size of otherwise undetectable small
151
particles beyond the Kelvin diameter in the CPC’s condenser so that they are then
able to grow to detectable sizes.
4.4 The effect of particle concentration
Figure 4-3 shows the BCPC/WCPC ratios obtained with different sizes of
NaCl particles in three concentration ranges, a) low: Cn < 1000 cm-3, b) medium:
1000 < Cn < 10000 cm-3 and c) high: Cn > 10000 cm-3. In this experiment, the TSI
3010 and TSI 3782 were used to represent the BCPC and WCPC because these two
CPCs have identical nominal D50 values of 10 nm. Irrespective of the concentration,
the BCPC/WCPC ratios decline sharply as the particle size is reduced below 14 nm.
This result is consistent with the explanation given in Section 4.3.1.1 which shows
that the BCPC/WCPC ratios were lower for small NaCl particles due to the enhanced
response to hygroscopic particles at very small sizes in the WCPC.
152
Figure 4-3. BCPC/WCPC ratio as a function of NaCl particle concentration.
Average BCPC/WCPC ratios for particles sizes in the range 6.7 – 100 nm
were 0.96 (±0.15), 0.90 (±0.15) and 0.78 (±0.14) for the low, medium and high
concentrations ranges respectively. These differences could probably be due to
coincidence errors which tend to occur in all CPCs at high concentrations. Under
normal operation, no more than one particle is assumed to be present in the
measuring volume at any given time. However a coincidence error will occur under
conditions of high particle concentration whenever more than one particle enters the
measuring volume at the same time and this will result in undercounting (Sachweh et
al., 1998). According to the instrument manuals, the upper concentration limit of the
BCPC3010 is 1 x 104 cm-3 (±10% accuracy) while that of WCPC3782 is 5 x 104 cm-3
(±10% accuracy). The lower upper limit in the case of the BCPC3010 is therefore the
most likely reason for the decreasing BCPC/WCPC ratio at high concentrations. The
dependence on particle size of the BCPC/WCPC ratio for low and medium
concentration ranges was similar, but for the high concentration range the
BCPC/WCPC ratio fluctuated when the particle sizes was in the range 10-20 nm.
When comparing the low and medium concentration range results, the variation in
the differences for particles in the size range from 6.7 to 100 nm ranged from 2% to
10%. Because the relationship between coincidence error and particle number
concentration is non-linear (Hermann and Wiedensohler, 2001), higher rates of
coincidence error occurred close to the CPC’s upper concentration limit. Therefore,
the coincidence error rate would have been greater for the BCPC3010 than for the
WCPC3782 when exposed to the same particle concentration. The observed variation
153
of the WCPC/BCPC ratios at low and medium concentrations therefore appears to be
consistent with these expected different rates of coincidence error.
To further evaluate the influences of particle number concentration on the
detection performance differences between BCPC and WCPC we calculated the
Pearson’s correlation coefficient (r) for a possible correlation between the
BCPC/WCPC ratio and the challenge aerosol particle number concentration for
various particle sizes of NaCl (see Figure 4-4). Particle number concentrations
below 1000 cm-3 were used in this analysis in order to minimize the effects of
coincidence error. Weak correlations between BCPC/WCPC and number
concentration were found for various particle sizes. The |r| values ranged from 0.03
to 0.77 with an averaged value of 0.31±0.21 (with p values < 0.01). The signs of
slopes of the ratio versus particle concentration curves (these curves are not shown)
varied in an apparently random manner between positive and negative values. This
lack of any clear consistent relationship between the correlation coefficient and
particle size implies that the relative detection performance of the CPCs does not
depend strongly on particle number concentration provided the concentration is not
so great as to produce significant coincidence error in either CPC.
154
Figure 4-4. Product of Pearson’s correlation coefficient, r, between BCPC/WCPC ratios and particle concentration varies with particles sizes.
4.5 CONCLUSION
In this study, number concentration measurements of NaCl, DOS, laser toner
and citric acid particles were tested by using BCPC and WCPC. The BCPC/WCPC
ratios for each type of particles were used to examine the relative detection
efficiencies of the CPCs.
The effect of water insoluble composition seems to be, to suppress the activation of
condensation for water vapour in the WCPC. Hydrophobic aerosol smaller than 20
nm were significantly undercounted by the WCPC and this undercounting was
reduced for particles larger than 20 nm as indicated by a decrease of the
BCPC/WCPC ratio for DOS from 1.2 down to 0.98, and for laser toner particles
from 1.70 down to 1.19 (TonerF) and from 1.31 down to 1.21 (TonerC). For NaCl,
the BCPC/WCPC ratio was close to unity for particle with diameters larger than 12
nm. This result suggests that the hygroscopic nature of NaCl, by reducing the
equilibrium vapour pressure above the particle surface, effectively acts to lower the
155
activation diameter for droplet growth in such particles and this produces a
corresponding improvement in the lower detection size limit.
For citric acid particles larger than 8 nm, the BCPC/WCPC ratio varied within a
narrow range (1.07 – 1.20). Although citric acid particles were only slightly
undercounted by the WCPC compared to the BCPC, the WCPC was unable to detect
smaller citric acid particles close to the instruments nominal lower diameter limit.
The results presented showed that the detection capability of CPCs is strongly
dependant on the solubility of the target aerosol in the condensation medium. In
addition, BCPC/WCPC ratios were obtained for a range of particle number
concentrations. Apart from the effects of coincidence errors which occur in all CPCs,
the results did not show a strong correlation between the BCPC/WCPC ratio and the
particle number concentration. According to the findings of this study, the BCPC
should be chosen when for measuring ambient concentrations of water insoluble
particles. Both the BCPC and WCPC appear to be suitable for ambient particle
concentration measurements provided that the particles are known to be at least
somewhat hygroscopic. WCPC’s should be used with care in ambient measurements
and only after first verifying that the aerosol is not hydrophobic. In addition, the
discrepancies of the detection abilities between both the BCPC and WCPC can be
applied to the study of the composition of particles.
Acknowledgements
This project was supported by the Australian Research Council and Queensland
Ling, X., He, C., 2009b. Environmental monitoring of airborne nanoparticles.
Journal of Environmental Monitoring, 11:1758-1773.
Mordas, G., Manninen, H.E., Petäjä, T., Aalto, P.P., Hämeri, K., Kulmala, M., 2008.
On Operation of the Ultra-Fine Water-Based CPC TSI 3786 and Comparison with
Other TSI Models (TSI 3776, TSI 3772, TSI 3025, TSI 3010, TSI 3007). Aerosol
Science and Technology, 40, 1090-1097.
Rader, D.J., McMurry, P.H., 1986. Application of the tandem differential mobility
analyzer to studies of droplet growth or evaporation. Journal of Aerosol Science,
17:5, 771-787.
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Sachweh, B., Umhauer, H., Ebert, F., Buttner, H., Friehmelt, R., 1998. In situ optical
particle counter with improved coincidence error correction for number
concentration up to 107 particle cm-3. Journal of Aerosol Science, 29, 1075-1086.
159
CHAPTER 5
Observation of new particle formation in subtropical urban environment
H.C. Cheung, L. Morawska and Z.D. Ristovski
International Laboratory for Air Quality and Health, Queensland University of
Technology
GPO Box 2434, Brisbane QLD 4001, Australia
Published by the Journal of Atmospheric Chemistry and Physics
160
STATEMENT OF JOINT AUTHORSHIP
Title: Observation of new particle formation in subtropical urban environment.
Authors: H.C. Cheung, L. Morawska*, Z.D. Ristovski
H.C. Cheung
Designed and developed the methodology, conducted the field measurement,
analysed and interpreted the data, and wrote the manuscript.
L. Morawska
Contributed to the development of the methodology, analysed and interpreted the
data, and the manuscript writing.
Z.D. Ristovski
Contributed to the development of the methodology, analysed and interpreted the
data, and the manuscript writing.
161
CHAPTER 5. OBSERVATION OF NEW PARTICLE FORMATION IN
SUBTROPICAL URBAN ENVIRONMENT.
H.C. Cheung, L. Morawska and Z.D. Ristovski
International Laboratory for Air Quality and Health, Queensland University of
Technology, GPO Box 2434, Brisbane QLD 4001, Australia
Abstract
The aim of this study was to characterise the new particle formation events in a
subtropical urban environment in the southern hemisphere. The study measured the
number concentration of particles and its size distribution in Brisbane, Australia
during 2009. The variation of particle number concentration and nucleation burst
events were characterised as well as the particle growth rate which was first reported
in urban environment of Australia. The annual average NUFP, NAitken and NNuc were
9.3 x 103, 3.7 x 103 and 5.6 x 103 cm-3, respectively. Weak seasonal variation in
number concentration was observed. Local traffic exhaust emissions were a major
contributor of the pollution (NUFP) observed in morning which was dominated by the
Aitken mode particles, while particles formed by secondary formation processes
contributed to the particle number concentration during afternoon. Overall, 65
nucleation burst events were identified during the study period. Nucleation burst
events were classified into two groups, with and without particles growth after the
burst of nucleation mode particles observed. The average particle growth rate of the
nucleation events was 4.6 nm hr-1 (ranged from 1.79 – 7.78 nm hr-1). Case studies of
162
the nucleation burst events were characterised including i) the nucleation burst with
particle growth which is associated with the particle precursor emitted from local
traffic exhaust emission, ii) the nucleation burst without particle growth which is due
to the transport of industrial emissions from the coast to Brisbane city or other
possible sources with unfavourable conditions which suppressed particle growth and
iii) interplay between the above two cases which demonstrated the impact of the
vehicle and industrial emissions on the variation of particle number concentration
and its size distribution during the same day.
163
5.1 Introduction
Understanding the formation process of atmospheric particles is vital because of the
significant impact of particulate matter on human health and climate change
(Charlson et al., 1992, Donaldson et al., 1998). Atmospheric particles can be formed
by nucleation process via a number of different mechanisms (e.g. Kulmala 2003;
Kulmala et al., 2004), such as binary nucleation (involving H2SO4 and water vapour),
ternary nucleation (involving NH3, H2SO4 and water vapour) and ion-induced
nucleation for charged particles, depending on the environmental conditions. To date,
numerous studies have been conducted in different locations, in order to investigate
particle formation processes in different environmental settings, including the free
troposphere (e.g. Weber et al., 2001), boreal forests (e.g. Vehkamäki et al., 2004) and
coastal areas (e.g. O’Dowd et al., 1999; Lee et al., 2008). However, most of these
studies focused on particle formation in rural settings and in colder climates, with
very few studies conducted in urban environments, especially in the southern
hemisphere (Kulmala et al., 2004). A limited number of studies were conducted in
continental (e.g. Woo et al., 2001; Moore et al., 2007; Wu et al., 2008) and coastal
(Pey et al., 2008; Rodríguez et al., 2008; Fernández-Camacho et al., 2010; Pérez et
al., 2010) urban areas. These studies examined the variation of particle number
concentration in urban environments. The major influence on particle number
concentration was vehicle exhaust emissions during the traffic peak hours (e.g. Pey
et al., 2008; Pérez et al., 2010) and new particle formation by photochemical
reactions (e.g. Pey et al., 2009), as well as the influence of power plant and industrial
emissions from an area upwind from the urban site (Gao et al., 2009). The few
examples include studies on particle formation associated with natural emissions
from a Eucalypt forest in South-East Australia (Ristovski et al., 2010; Suni et al.,
2008), which concluded that natural emissions were in fact a source of particle
164
formation. In addition, new particle formation was observed in the coastal area of
Eastern Australia (Johnson et al., 2005; Modini et al., 2009), the result of which
showed that new particles were formed by the condensation of sulphate and/or
organic vapours onto sulphate clusters to form an observable particle. Guo et al.
(2008) conducted a short-term intensive study on particle formation in the rural
environment of Eastern Australia, in which particle formation was suggested to be
influenced by the photochemical processes of the urban air plume. The findings of
Guo et al. (2008) provided an insight to the impact of urban pollution on nucleation
processes. For the urban environment, Mejía et al. (2009) characterised the
favourable atmospheric conditions for nucleation burst events in a coastal urban area
in Brisbane, which is the only nucleation study conducted in an urban area in the
southern hemisphere to date. The study showed that the nucleation events mostly
occurred during the summer and it also suggested cleaner air masses of a local origin
mixing with traffic exhaust emission after the events. However, Mejía et al. (2009)
did not investigate the nucleation growth process after the nucleation burst events,
and thus particle formation parameters, such as particle growth rate, are not available
for the urban environment in southern hemisphere. The particle growth rate is an
important factor for the calculation of climate forcing.
To further investigate the characteristics of the particle formation processes in a
subtropical urban environment, we conducted a one year-long measurement of the
size distribution of particles in the size range 4 – 110 nm, at an urban area of
Brisbane, Australia. The aim of this study was to characterise the temporal variation
of particle number concentration, and to explain the controlling factors that
influenced new particle formation processes in the subtropical urban environment.
165
5.2 Methodology
5.2.1 The topography and meteorology of Brisbane region
Brisbane is the capital city of the state of Queensland, Australia, located at 27’30oS
and 153oE. Brisbane city is surrounded by mountains from south to north, and faces
the Pacific Ocean to the East. It is the fastest growing urban region in Australia (2
million inhabitants). The major pollution sources affecting the CBD region are traffic
exhaust emissions generated in the inner city, and aircrafts, ships and industrial
emissions transported from the lower reaches of Brisbane River, approximately 15-
18 kms NE of the CBD. The Brisbane River meanders through the Brisbane region.
Morawska et al. (1998) provided a description of the wind patterns in the Brisbane
region, which are mostly governed by synoptic flows from the SE. A NE sea breeze
is also a daily feature throughout the year. In addition, an overnight SW drainage
flow from the mountain range to the West carries air parcels from the plateau region
and the Western coastal plain towards the city. On the rare occasion when gradient
winds are blowing from the NW, the combination of the light synoptic NW flow and
the overnight SW drainage flow can sufficiently delay the onset of the sea breeze to
cause recirculation of the city emissions, leading to photochemical smog events.
5.2.2 The QUT study site
The measurements were conducted at the International Laboratory of Air Quality and
Health (ILAQH), Queensland University of Technology (QUT), which is within the
CBD of Brisbane (Figure 5-1). The monitoring site was about 10 m above ground
level on the top floor of a QUT campus building, located to the SE of the city centre,
with a major highway (the Pacific Motorway) situated along the SW side of the
campus. Therefore, the pollution associated NE winds could be attributed to
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industrial emissions (from the airport, oil refinery and Port of Brisbane), while the
pollution associated with S to NW winds could be attributed to local traffic exhaust
emissions.
5.2.3 Measurement techniques
The size distribution of ultrafine particles (UFPs) was measured at the QUT
monitoring site from 1st January to 31st December 2009. Particle size distribution in
the range 4 - 110 nm was measured by a Scanning Mobility Particle Sizer (SMPS)
system, which consisted of two parts, an Electrostatic Classifier (EC) (TSI 3080) and
a Condensation Particle Counter (CPC) (TSI 3781). The EC was equipped with a
nano-differential mobility analyser, which can separate the poly-disperse particles
into selected mono-disperse particles according to their particle mobility. The
number concentration of the mono-disperse particles was then counted by the CPC.
Each ambient sample was drawn into the SMPS system from outside the building
through a 0.635 cm (inner diameter) conductive tube and a sampling duration of 5
mins was adopted for each particle size distribution sample. Multiple charge
correction was applied to the particle size distribution measurements by using an
internal algorithm from the Aerosol Instrument Manager Software.
In this study, the size distribution data was classified into three groups, i) UFPs,
including particles ranging from 4 - 110 nm (NUFP); ii) Aitken mode with particles
(NAitken), which ranged from 30 - 110 nm; and iii) nucleation mode particles, which
were < 30 nm (Nnuc). In addition to the above particle measurements, meteorological
parameters, including wind speed and direction, temperature and relative humidity
(RH) were monitored at Kangaroo Point (1 km East of QUT) by the Queensland
Bureau of Meteorology. The QUT and Kangaroo Point sites were not blocked by
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high rise buildings and therefore the use of wind data measured at Kangaroo Point
was representative of the synoptic wind direction of the study region. It should be
noted that global solar radiation was measured at the Queensland Environmental
Protection Agency site (Rocklea), about 10 km south of QUT.
Figure 5-1: Map of Brisbane.
5.2.4 Data processing and analysis
In this study, the raw particle size distribution and meteorological data were
synchronised into 10 min averaged data for data analysis and figure plotting.
According to Mejía et al. (2007) the lower limit of the particle size distribution
dataset was set to 1 cm-3. The upper limit was set to 5 x 105 cm-3. Some data were
removed from the database based on several criteria such as i) zero value for particle
concentration; ii) particle concentration higher than 5 x 105 cm-3 and iii) data
collected during instrument malfunction. During the one year measurement
campaign, 28 % of the data was removed based on the above data reduction
procedures and due to instrument maintenance. Correlations between the parameters
were tested using the Pearson-product moment correlations test with a 95%
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confidence level (p < 0.05). The linearity of the tested parameters was indicated by
Pearson’s coefficient, r, with a perfect linear correlation between two parameters
indicated by an r value close to 1.
5.3 Results and Discussion
5.3.1 Overall results
The overall average concentration of ultrafine particles (NUFP), Aitken mode (NAitken)
and nucleation mode (Nnuc) measured in this study were 9.3 x 103 (±15.3 x 103), 3.7 x
103 (±5.1 x 103) and 5.6 x 103 cm-3 (±12.6 x 103), respectively. The values obtained in
this study are similar to those observed in similar environments in Northern Europe
(Hussein et al., 2004). The few studies conducted in Southern European countries
showed much higher concentrations than those which were reported in this study
(Pey et al., 2008, Rodríguez et al., 2008; Fernández-Camacho et al., 2010). Similar
values of NAitken and Nnuc were obtained in the urban areas of Helsinki, Finland,
which were 4.0 x 103 – 6.5 x 103 cm-3 and 5.5 x 103 – 7.0 x 103 cm-3, respectively
(Hussein et al., 2004). The NUFP measured in Brisbane was relatively lower than that
in other coastal urban areas, including the Yangtze River Delta, China (Gao et al.,
2009), Barcelona (Pey et al., 2008) and Huelva and Santa Cruz de Tenerife, Spain
(Rodríguez et al., 2008; Fernández-Camacho et al., 2010), which were 28.5 x 103,
14.2 x 103 and 22.0 – 26.3 x 103 cm-3, respectively.
The results of this study were also compared to those of a previous study conducted
in the Brisbane urban region from 1995 to 2000 (Mejía et al., 2007). The NUFP and
Nnuc measured in this study were about 8% and 60% higher than those measured by
Mejía et al. (2007), being 8.6 x 103 cm-3 (for particles in the size range 15 - 100 nm)
and 3.5 x 103 cm-3 (for particles in the size range 15 - 30 nm), respectively. In
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relation to Nnuc, it should be noted that the nucleation mode particle concentration in
this study covered particles in the size range 4 - 30 nm, and therefore, it is expected
to be higher than the earlier result reported by Mejía et al. (2007).
The seasonal variation of particle number concentrations is depicted in Figure 5-2.
The Pearson’s coefficients, r, between particle number concentration of different
modes and temperature were calculated which ranged from 0.00 - 0.03, which
indicates that there was no statistical seasonal variation in particle concentrations.
This result is similar to that presented by Mejía et al. (2007) for the same study
region, however larger variations in particle number concentrations were observed in
each mode during the summer season, as reflected by the large interquartile range
(see Figure 5-2).
Figure 5-2: Monthly variations of (a) mean temperature, and particle number concentration of ultrafine (UFP) (b), Aitken mode (c) and nucleation modes particles (d). The median number concentrations and the 1st and 3rd quartiles are presented.
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Figure 5-3 shows the diurnal variation of particle number concentration for different
modes with the diurnal variations of temperature and relative humidity also plotted.
Two peaks were observed for UFP during the day, the first of which occurred from
around 6 am to 8 am, possibly due to traffic exhaust emissions during the morning
peak hours (from around 6 am to 8 am) in Brisbane urban region (Mejía et al., 2007).
The second peak, which is much more important, was observed from around 12 noon
to 3 pm, and this may be due to the formation of new particles. During the period of
UFP morning peak, it was suggested that the Atiken mode particles contributed by
the direct diesel and petrol engine emissions, which produce particles in the size
range of about 20 – 130 nm and 20 – 60 nm, respectively (Morawska et al., 2008).
Also the nucleation mode particles could be formed during the dilution and cooling
of engine exhausted sulphuric and organic vapours by condensation onto sulphur
clusters (Meyer and Ristovski 2007). During the period of the second UFP peak, a
nucleation mode peak was also observed associated with highest level of solar
radiation, which implies that new particles were produced during the early afternoon
by photochemical reactions.
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Figure 5-3: Diurnal variation of (a) averaged solar radiaiton, (b) averaged wind direction/speed, (c) averaged temperature and RH, and (d) averaged UFP, nucleation mode and Aitken mode particle concentrations.
5.3.2 Relationship between particle number concentrations and meteorological parameters
5.3.2.1 Temperature, relative humidity and solar radiation
From Figure 5-3 it can be seen that temperature and relative humidity display an
anti-correlation, whereby increases in temperature were associated with decreases in
relative humidity. The influences of temperature on particle number concentration
were not confirmed in previous studies. Some studies found that high particle
concentration was related to relatively high temperatures (e.g. Kim et al., 2002),
whilst others found that they were associated with relatively low temperatures (e.g.
Olivares et al., 2007). In this study, a weak correlation between particle number
concentrations and temperature was observed (r = 0.36 - 0.53; p < 0.01), however
higher variations in NUFP, NAitken and Nnuc were observed during warmer and lower
humidity conditions (Figures 5-4 and 5-5). The highest number concentrations of all
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particle sizes were associated with temperature around 32˚C. The peaks of NAitken and
Nnuc observed in the early afternoon (under high temperature conditions) suggested
that the contribution by new particle formation processes was the greatest, followed
by particle growth to larger particles. In addition, another peak of NAitken was
observed with temperature around 10˚C (see Figure 5-4). Also higher NAitken
concentrations were observed under humid conditions (see Figure 5-5). This result
may be due to enhanced coagulation and condensation effects under high humidity
conditions.
In some cases, temperature data can not directly reflect the strength of photochemical
activities which occurred on warm cloudy days. In addition, condensation vapour
H2SO4 production was related to the solar radiation (Ristovski et al., 2010).
Therefore, solar radiation was used to indicate the reactivity of photochemical
reactions. The particle number concentration did not show a clear relationship with
the ambient temperature. In contrast, a positive relationship between particle number
concentration and solar radiation data was observed (r = 0.92-0.98; p < 0.01). This
result showed that the Nnuc was related to the photochemical reactions.
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Figure 5-4: Particle number concentrations of (a) ultrafine (UFP), (b) Aitken mode and (c) nucleation mode particles and their variation as a function of temperature. The median number concentrations and the 1st and 3rd quartiles are presented.
Figure 5-5: Number concentrations of (a) ultrafine (UFP), (b) Aitken mode and (c) nucleation mode particles and their variation as a function of relative humidity. The median number concentrations and the 1st and 3rd quartiles are presented.
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5.3.2.2 Wind direction and speed
Figure 5-6 shows the particle number concentration for different particle sizes under
different wind directions. For UFP, a sharp peak was associated with ENE wind
directions, and a lower broad peak was associated with SSE to WNW wind
directions. An interesting result was also obtained when dividing the data into Aitken
and nucleation modes. The sharp peak was observed in both of these two modes,
however the broad peak was only observed in the Aitken mode. From Figure 5-1, it
can be seen that the Brisbane Airport, oil refinery and Port of Brisbane were all
located to the NE of the monitoring site, whilst the CBD and Pacific Motorway were
located to the NW and SW of the monitoring site. Therefore, it is likely that the
nucleation mode particles were contributed by the industrial sources located to the
NE, while the Aitken mode particles were emitted from both industrial and vehicle
emission sources, as well as the coagulation/condensation of smaller particles under
humid conditions (see Section 5.2.1), which will contribute to the accumulation
mode. In addition, air masses blowing from the marine boundary (NE to SE
directions) were relatively clean. However, the inland air mass from the NE direction
was contaminated by industrial emissions. This interpretation can be supported by
higher NUFP in north-easterly air masses and lower NUFP in easterly or south-easterly
air masses (clean maritime air masses, which are thought to be much less loaded in
gaseous precursors). To better illustrate the directional dependence of the NUFP,
NAitken and Nnuc a wind rose plot of particle number concentration superimposed over
the location map is shown in the supplementary materials section (Figure 5-S1).
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Figure 5-6: Number concentration of (a) ultrafine (UFP), (b) Aitken mode and (c) nucleation mode particles and their variation as a function of wind direction. The median number concentrations and the 1st and 3rd quartiles are presented.
In general, a negative correlation was observed between UFP concentration and wind
speed, indicated by a Pearson coefficient of r = -0.97 (p < 0.01). Higher particle
number concentration was associated with lower wind speeds (see Figure 5-7),
which can be explained by the stronger dispersion associated with high wind speeds
(Hussein et al., 2006). Similar results were also observed for Aitken and nucleation
mode particles. In addition, a larger variation of Nnuc was associated with the
moderate wind speed (~ 4 ms-1). Nnuc usually reached it’s daily peak value during
early afternoon and the corresponding wind speed was ~ 4 ms-1 (see Figure 5-3).
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Figure 5-7: Number concentration of (a) ultrafine (UFP), (b) Aitken mode and (c) nucleation mode particles and their variation as a function of wind speed. The median number concentrations and the 1st and 3rd quartiles are presented.
5.3.3 Particle formation in subtropical urban atmosphere
5.3.3.1 Classification of nucleation events
The general definition of a nucleation event is a two-phase process involving the
burst of observed nucleation particles and the growth of these particles into
accumulation mode by condensation and/or coagulation (Kulmala et al., 2004). To
illustrate the nucleation event, a “banana” shape should be observed in the contour
plot of particle size distribution. The example of a nucleation event is shown in
Figure 5-8. Usually the lowest Nnuc is observed in the early morning, and then it
begins to increase at around 9 am. The geometric median diameter (GMD) of the
measured particles grows into an Accumulation mode during the day and the
evolvement of the particle size curve is often compared to a banana shape.
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Figure 5-8: The time series of nucleation events observed at QUT on 21 October 2009. From bottom to top, the parameters are: i) Geometric median diameter (GMD) and contour plot of size distribution; ii) Particle number concentration of nucleation and Aitken mode particles; iii) Particle number concentration of ultrafine particles (UFP); iv) Temperature and relative humidity; and v) wind direction and speed.
A number of nucleation events were observed during this study, which were
classified into different groups (Class Ia/b and II) according to the classification
scheme developed by Dal Maso et al. (2005). Class Ia/b events are defined as those
events where the particle growth rate can be determined. A typical Class Ia event
demonstrates clear and strong particle formation events with little or no pre-existing
particles obscuring the observation of the newly formed mode, while a Class Ib event
is any other event where the particle growth rate can be determined. Class II events
are defined as events where the banana shape still observable, but the data fluctuates
to such an extent that formation rate calculation is impractical.
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In the urban environment, nucleation burst events have been observed with and
without particle growth (Park et al., 2008; Gao et al., 2009). For example, in addition
to nucleation events, we occasionally observed increases in nucleation mode particle
concentration during the daytime, where the particles did not grow into larger
particles (indicated by the near constant GMD value during the event period). We
defined this kind of event as a nucleation burst event, and a total of 65 burst events
were identified. A more detailed discussion about the occurrence of nucleation
events, both with and without particle growth, is provided in Section 5.3.2 and 5.4
below.
5.3.3.2 Growth rate during nucleation events
During this study, there were several gaps in the dataset due to instrument
malfunction/maintenance. For example, if there were more than 3 hrs of missed data
between 8 am to 6 pm (the period during which the nucleation usually occurs), this
was not counted as a valid daily dataset. After the removal of invalid daily datasets, a
total of 252 days of data were counted.
Figure 5-9 shows the monthly averaged particle growth rate and solar radiation, as
well as the monthly occurrence of nucleation events. This data provided information
regarding the influence of photochemical activity on particle formation in Brisbane.
Higher particle growth rate was found to be associated with higher solar radiation
and the results showed a positive relationship (r = 0.76, p < 0.05) between the
particle growth rate of nucleation events and solar radiation. Similar findings were
obtained in previous studies, which showed that particle growth rates were associated
with the strength of solar radiation (e.g. Kulmala et al., 2004; Vehkamäki et al.,
2004). The number of nucleation events classified as Class Ia, Ib, and II were 4, 13,
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and 23, respectively. The nucleation events (Class I and II) occurred throughout most
of the year, except in November, and only one Class II event was observed in
December. Although infrequent nucleation events were observed during November
and December, the nucleation bursts (without particle growth) were found to be
closely associated with NE wind directions. In addition to the seasonal variation of
temperature, the dominant wind direction measured during November and December
was different to other months. NE winds dominated during these warmer months,
while the main wind direction was from the SE-SW during other months. The
influence of wind direction on the nucleation events will be discussed in the case
studies below. The mean growth rate for the nucleation events was calculated by the
slope of GMD against time during the period of particle growth under 30 nm. The
growth rates of Class I events measured in this study ranged from 1.79 - 7.78 nm hr-1
(average 4.6 nm hr-1), which are comparable to other urban studies such as those
conducted in Atlanta (2.86 - 22.0 nm hr-1) (Woo et al., 2001) and East St. Louis
(average 6.7 nm hr-1) (Qian et al., 2007).
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Figure 5-9: Seasonal variation in (a) particle growth rates and solar radiation and (b) number of class I event and the precentage ratio of class I event to total sampling days.
5.3.4 Case studies of nucleation burst events
In the above sections, it was shown that nucleation mode particle concentrations
were strongly associated with NE/SW winds. Further analysis of the daily variation
of particles and wind direction showed that nucleation events with particle growth
were usually associated with SW winds, while the nucleation burst events without
particle growth were associated with NW winds. In this section, case studies relating
to types of three nucleation events are discussed, including: i) new particle formation
by nucleation processes; ii) a nucleation burst without particle growth; and iii) the
interplay between these two situations.
5.3.4.1 Case I - Photochemical formation of nucleation particles
Case I nucleation events were observed during 28 - 29 April 2009. Significant strong
nucleation bursts were observed consecutively during these two days (peak 10 min
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and hourly averaged Nnuc during the nucleation events were 47 x 104 and 18 x 104
cm-3, respectively). The time series plots of the particle size distribution and
meteorological parameters are illustrated in Figure 5-10.
Figure 5-10: The nucleation events observed on 28-29 April 2009. From bottom to top, the parameters are: i) Geometric median diameter (GMD); ii) Particle number concentration of nucleation and Aitken mode particles; iii) Particle number concentration of ultrafine particles (UFP); iv) Temperature and relative humidity; v) Solar radiation; and vi) wind direction and speed.
During these two days, the highest temperature was about 30 ºC and relative
humidity was around 20-40 % at noon. Land and sea breeze wind circulation was
observed on both days, with a moderate (~ 4 ms-1) SW wind (from inland)
dominating in the morning and a moderate NE wind (from the coast) dominating in
the afternoon. The variation in concentration of nucleation and Aitken mode particles
clearly showed the influence of the nucleation burst on particle number
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concentrations. In the early morning (6 - 9 am) of 28 April 2009, an Aitken mode
peak was observed, which could be attributed to traffic exhaust emissions during the
morning peak hours. At around 10 am, a sharp peak of nucleation mode particles was
observed and the GMD reached the lowest value of the day (~ 8 nm). The wind
direction changed to NE at around 1 pm, and turned back to the SW again after
midnight. In terms of GMD, the nucleation mode particles were growing into larger
particles (GMD increased from 8 to 57 nm) until around midnight (~3 am on 29
April 2009). Another nucleation growth event was observed the following day, on 29
April 2009, with similar meteorological conditions to those which were observed on
the previous day. However, the concentration of nucleation particles during the
nucleation burst was lower than that observed on the previous day. This result
indicated that the higher number of pre-existing Aitken mode particles in the
atmosphere served to diminish the nucleation processes.
5.3.4.2 Case II - nucleation burst without growth into larger particles
A Case II nucleation event was observed on 11 November 2009. As shown in Figure
5-11, the variation in wind direction was similar to that observed during the Case I
nucleation events, whereby land and sea breeze circulation was observed, however,
the burst of nucleation particles did not appear with the SW wind (associated with
local traffic exhaust emissions). Instead, a nucleation burst was observed with the NE
wind at ~ 10 am. The GMD dropped from ~ 30 nm to 10 nm and Nnuc increased from
~ 7.0 x 103 to 10.0 x 104 cm-3 during the nucleation burst, while NAitken did not show
any significant variation, ranging from 2 - 5 x 103 cm-3. This plume disappeared at
around 6 pm and GMD rose to ~ 25 nm. Based on these findings, it was suggested
that the plume was not directly emitted from the local traffic exhaust emission or
183
ship emission from the Port of Brisbane, since the particles from vehicle and ship
emissions are in the range 20 -130 nm (Morawska et al., 2008) and 60 – 120 nm
(Sinha et al., 2003), respectively. However, the emissions of SO2 and VOCs from the
industrial sources located at the coast could be possible precursors to the formation
of new particles by nucleation process. Another possible source of this plume was
aircraft emissions from the Brisbane Airport, which was located in a NE direction
from the study site. Mazaheri et al. (2009) measured the particle size distribution
produced by commercial aircraft at Brisbane Airport and a very distinct peak of
nucleation mode particles was observed at around 15 nm. This result was comparable
to the average GMD measured during the nucleation burst events in this study, which
was 14 nm (ranging from 8 - 32 nm). In addition, the nucleation burst could be due to
the precursors of local emissions which were similar to that in the nucleation growth
event or the re-circulated aged plumes belonging to land and sea breeze; however the
particle growth process could have been suppressed due to unfavourable conditions,
the exact nature of which is not known.
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Figure 5-11: The nucleation bursts measured on 11 November 2009. From bottom to top, the parameters are: i) Geometric median diameter (GMD); ii) Particle number concentration of nucleation and Aitken mode particles; iii) Particle number concentration of ultrafine particles (UFP); iv) Temperature and relative humidity; v) Solar radiation; and vi) wind direction and speed.
5.3.4.3 Case III - Interplay between new particle formation and nucleation burst events
A Case III nucleation event was observed on 15 March 2009. During this study, it
was found that particle formation via nucleation processes was associated with SW
winds (Figure 5-10) and the subsequent particle growth (banana shape of particle
size distribution) was usually followed by the presence of a NE wind. In contrast, the
nucleation burst events without particle growth were most commonly related to
emission sources from the NE (Figure 5-11). In some events, a partial banana shape
was observed with a SW wind in the morning, but the observation of particle growth
was interrupted by a nucleation burst plume from the airport region (Figure 5-12).
185
Figure 5-12: Contour plot of particle size distribution observed on 15 March 2009. From bottom to top, the parameters are: i) Geometric median diameter (GMD) and contour plot of size distribution; ii) Particle number concentration of nucleation and Aitken mode particles; iii) Particle number concentration of ultrafine particles (UFP); iv) Temperature and relative humidity; v) Solar radiation; and vi)wind direction and speed.
It can be seen that the nucleation process commenced at 9 am and the particles kept
growing into Aitken mode particles until 12 pm (GMD rose from 20 to 35 nm). After
12 pm, the wind direction changed to a NE wind and an air plume enriched with
nucleation mode particles was observed, which interrupted the observation of a
banana shaped progression of the particle size distribution curve. After the
interruption, the GMD dropped suddenly to below 20 nm and several similar cases
were also observed during the one year study period at QUT. Overall, the results
showed that the nucleation mode particles originated from a variety of sources such
as traffic exhaust emission in Brisbane CBD and industrial emissions located NE to
Brisbane. Although the observation of a banana shape was interrupted by another air
mass, the particle growth process could continue in other regions.
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5.3.4.4 Source identification
Gaseous data measured at Pinkenba, which is located near the lower reaches of the
Brisbane River (close to the airport, oil refinery and port of Brisbane) and South
Brisbane (about 1km south to QUT) were used to conduct source analysis. These
gaseous measurements were conducted by the Queensland Environmental Protection
Agency. Also back-trajectories of the nucleation growth/ burst events were
calculated using the HYSPLIT model (Hybrid Single Particle Lagrangian Integrated
Trajectory, Version 4.9), in order to trace the origin of the air masses. It should be
noted that the grid resolution of the meteorological data used for back-trajectories
calculation was 1 x 1 degrees in latitude and longitude. The data resolution is not
accurate enough to trace the detailed air mass passage over the scale of this study
region, and therefore, it only provides an indication from which region the air mass
comes from.
The gaseous data available for Pinkenba included CO, NO2, and SO2, while only CO
and NO2 data were available for South Brisbane. The emission ratios of CO/NO2 and
SO2/NO2 were calculated. On average, the daily minimum of each gaseous species,
representing the background value, almost reached zero in our study region.
Therefore we did not subtract the background data for the emission ratio calculations,
as it was negligible. 48-h back trajectories were calculated for the first two sampling
hours of each event (see supplementary figures 5-S2 and 5-S3) and the average
CO/NO2 and SO2/NO2 concentrations measured at Pinkenba during the event period
were 89.7 and 0.57, respectively. Overall, the CO/NO2 ratio exceeded the ratios
reported in the 2008/2009 National Pollution Inventory (from www.npi.gov.au,
accessed on 15 January 2011) for other sources, such as vehicles (9.7), oil refineries
(6.4), ships (0.69) and wildfires (24.6). If the pollution plume was contributed by
single source, it was possible to identify the emission source by comparing these
emission ratios. For example, the ratio for SO2/NO2 (0.57) was very close to the ship
emission ratio of 0.69. Although back-trajectory analysis found that almost all
trajectories originated from the NE sector during the nucleation burst events, air
masses from the NE were influenced by a number of different sources, such as ship,
aircraft, oil refinery and the local vehicle emissions. Therefore, it was difficult to
identify the specific source/s which contributed to the nucleation burst events. In
addition, primary pollution plumes (e.g. CO and NO2) were observed at Pinkenba 1-3
hrs prior to the start of the nucleation burst events. From these results, we can
conclude that the nucleation burst events were most likely influenced by industrial
emissions from the area NE of the sampling site. As mentioned in Section 5.4.2, the
nucleation burst event could be associated to other possible sources, however the
particle growth process could have been suppressed by unfavourable conditions, the
exact nature of which is not known
For nucleation growth events, the CO/NO2 ratio obtained from South Brisbane was
10.2, which is close to the emission inventory data for vehicles (9.7). Back-trajectory
analysis also showed that the air masses originated from S-SW directions, except on
21/10/2009, which suggests that vehicle exhaust emissions contributed to the
nucleation growth event.
5.4 Conclusion A year long measurement campaign of the size distribution of ultrafine particles was
conducted at subtropical urban area of Brisbane, Australia during 2009. The annual
average NUFP, NAitken and Nnuc were 9.3 x 103, 3.7 x 103 and 5.6 x 103 cm-3,
respectively. Small seasonal variation in number concentration was observed, with
188
higher particle concentrations observed during the warmer months. Diurnal variation
of NUFP, NAitken and Nnuc showed the influence of local traffic exhaust emissions on
the particle number concentration during morning peak hours, and elevated
nucleation mode particle levels suggested the contribution of new particle formation
during the early afternoon. In relation to wind direction, NAitken and Nnuc were
associated with NE winds, which pointed to the emission sources present at the lower
reaches of Brisbane river (such as Brisbane Airport, the oil refinery and the Port of
Brisbane). A broad peak of NAitken particles was also observed during SSE to WNW
winds, which suggested the influence of local traffic exhaust emissions, with particle
size ranging from 30 - 70 nm. Overall, two major sources of Nnuc were identified in
this study, which were new particle formation by nucleation and primary nucleation
mode particles emitted from aircraft at Brisbane Airport. New particle formation via
nucleation process was frequently observed in this study, and the particle growth rate
(average 4.6 nm hr-1) was positively related to the strength of global solar radiation.
The nucleation events with particle growth were associated with SW winds which
suggested the influence of precursors emitted from traffic exhaust emission in
Brisbane city. An interesting question arose during the course of this study regarding
the absence of nucleation particle growth in air masses originating from the coast. It
may due to lack of nucleation particles precursor associated with coastal air mass. To
tackle this question, a further study on the new particle formation, with parallel
measurements of particle chemical composition and gaseous pollutants, is needed.
Acknowledgements This project was supported by the Australian Research Council and Queensland
Transport through Linkage Grant LP0882544. We would also like to thank the
Queensland Bureau of Meteorology for providing the meteorological data.
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Supplmentary materials
Figure 5-S1. Wind rose plot of NUFP, NAitken and Nnuc superimposed over the location map. The origin of the wind rose is located at QUT. NUFP - red line; NAitken – blue line; Nnuc – green line. Unit in cm-3.
Figure 5-S2. Back-trajectories calculated during the nucleation burst events.
190
Figure 5-S3. Back-trajectories calculated during the class I nucleation growth events
Ü., Kulmala, M.: Atmospheric particle formation events at Värriö measurement
station in Finnish Lapland 1998-2002, Atmospheric Chemistry and Physics, 4,
2015-2023, 2004.
Weber, R.J., Moore, K., Kapustin, V., Clarke, A., Mauldin, R.L., Kosciuch, E.,
Cantrell, C., Eisele, F., Anderson, B., Thornhill, L.: Nucleation in the equatorial
pacific during PEM-tropics B: Enhanced boundary layer H2SO4 but no particle
production: NASA global tropospheric experiment Pacific Exploratory Mission
in the tropics phase B, Part 1: Measurement and analyses (PEM-Tropics B),
Journal of Geophysical Research, 106, 32767 – 32776, 2001.
Woo, K.S., Chen, D.R., Pui, D.Y.H., McMurry, P.H.: Measurements of Atlanta
aerosol size distributions: observations of ultrafine particle events, Aerosol
Science and Technology, 34, 75-87, 2001.
Wu, Z., Hu, M., Lin, P., Liu, S., Wehner, B., Wiedensohler, A.: Particle number size
distribution in the urban atmosphere of Beijing, China, Atmospheric
Environment, 42, 7967,7980, 2008.
196
CHAPTER 6
Influence of medium range transport of particles from nucleation burst on particle
number concentration within the urban airshed
H.C. Cheung, L. Morawska, Z.D. Ristovski and D. Wainwright
International Laboratory for Air Quality and Health, Queensland University of
Technology
GPO Box 2434, Brisbane QLD 4001, Australia
Published to the Journal of Atmospheric Chemistry and Physics
197
STATEMENT OF JOINT AUTHORSHIP
Title: Influence of medium range transport of particles from nucleation burst on
particle number concentration within the urban airshed.
Authors: H.C. Cheung, L. Morawska*, Z.D. Ristovski and D. Wainwright
H.C. Cheung
Designed and developed the methodology, conducted the field measurement,
analysed and interpreted the data, and wrote the manuscript.
L. Morawska
Contributed to the development of the methodology, analysed and interpreted the
data, and the manuscript writing.
Z.D. Ristovski
Contributed to the development of the methodology, analysed and interpreted the
data, and the manuscript writing.
D. Wainwright
Contributed to the development of the methodology and assess of the gaseous and
meteorological data.
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CHAPTER 6. INFLUENCE OF MEDIUM RANGE TRANSPORT OF
PARTICLES FROM NUCLEATION BURST ON PARTICLE NUMBER
CONCENTRATION WITHIN THE URBAN AIRSHED.
H.C. Cheunga, L. Morawska*,a, Z.D. Ristovskia and D. Wainwrightb
aInternational Laboratory for Air Quality and Health, Queensland University of
Technology, Brisbane, QLD 4001, Australia
bQueensland Department of Environmental Resource and Management
Abstract
An elevated particle number concentration (PNC) observed during nucleation events
could play a significant contribution to the total particle load and therefore to air
pollution in urban environments. Therefore, a field measurement study of PNC began
to investigate the temporal and spatial variations of PNC within the urban airshed of
Brisbane, Australia. In 2009, PNC was monitored at urban (QUT), roadside (WOO)
and semi-urban (ROC) areas around the Brisbane region. During the morning traffic
peak period, the highest relative fraction of PNC reached about 5% at QUT and
WOO on weekdays. PNC peaks were observed around noon, which correlated with
the highest solar radiation levels at all three stations, thus suggesting that high PNC
levels were likely to be associated with new particle formation caused by
photochemical reactions. Wind rose plots showed relatively higher PNC for the NE
direction, which was associated with industrial pollution, accounting for 12%, 9%
and 14% of overall PNC at QUT, WOO and ROC, respectively. Although there was
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no significant correlation between PNC at each station, the variation of PNC was
well correlated among three stations during regional nucleation events. In addition,
PNC at ROC was significantly influenced by upwind urban pollution during the
nucleation burst events, with the average enrichment factor of 15.4. This study
provides an insight into the influence of regional nucleation events on PNC in the
Brisbane region and it the first study to quantify the effect of urban pollution on
semi-urban PNC throughout nucleation events.
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6.1 Introduction
Atmospheric aerosols have been reported to be significantly associated with the
alteration of climate forcing and the degradation of visibility, as well as the
deterioration of human respiratory and cardiovascular systems (Charlson et al., 1992,
Donaldson et al., 1998, Watson 2002). Due to their small size (< 0.1 µm), ultrafine
particles (UFPs) only contribute a very small amount to the total mass of atmospheric
particles, however they are most abundant by number (~70-90%) and potentially
have a greater impact on human health than the larger particles (< 2.5 µm)
(Morawska et al., 2008).
In urban environments, vehicle exhaust emissions are the most significant source of
UFP and variations in particle number concentration (PNC) are strongly associated
with local urban traffic activity (Morawska et al., 1998, 2008). Aircraft/ship
emissions also contribute to elevated PNCs at a magnitude of 105 – 106 cm-3 (Sinha
et al., 2003, Mazaheri et al., 2009). In addition to direct emissions from the above
sources, new particles formed by nucleation processes are another source of UFPs in
the urban environment, with PNC reaching magnitudes as high as 104 - 105 cm-3
during nucleation events (Qian et al., 2007, Pey et al., 2009, Cheung et al., 2011). In
previous studies, particle mass concentration has been studied with regard to long
range transport in an intercontinental scale (Jaffe et al., 2003), however the size
distribution of and temporal-spatial variations in PNC have only been investigated on
a local scale (Morawska et al., 1998; Hussein et al., 2004). For example, although
regional nucleation has been observed in Helsinki, Finland (Hussein et al., 2008),
Atlanta and Pittsburgh, United States of America (Stolzenburg et al., 2005, Stanier et
al., 2004), spatial variations in PNC have been studied in urban areas in Australia
(Mejia et al., 2008) and in the United States (Hudda et al., 2010). These studies have
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not examined the impact of regional pollution on PNCs or the influence upwind
urban pollution has on PNC downwind during nucleation events.
This study aims to examine the effect of regional pollution on PNC in different
environments in the Brisbane region. After characterising the spatial variation of
PNC in three different urban locations, we investigated the influence of regional
nucleation on PNC in the same regions. Furthermore, the impact of urban pollution
on PNC downwind from a semi-urban area during a nucleation burst event is also
quantified. The results of this study are valuable for assessing the impact of
nucleation on PNC in an urban environment.
6.2 Methods and Techniques
6.2.1 Study design
Field measurements of particles and gaseous pollutants were conducted at three
locations in Brisbane in 2009, to represent the urban (1 January to 31 December
2009), roadside (21 May to 31 December 2009) and semi-urban environments (5
February to 31 December 2009).
6.2.2 The topography and meteorology of the Brisbane region
Brisbane is located at 27’30oS and 153oE, in Queensland, Australia. The Brisbane
city is surrounded by mountains from south to north, and faces the Pacific Ocean to
the East. Traffic exhaust emissions are the major pollution source affecting the
central business district (CBD). In addition, the aircraft, ship and industrial emissions
are occasionally transported from the lower reaches of the Brisbane River,
approximately 15-18 km NE of the CBD, by inland sea breezes. General wind
patterns in the Brisbane region are governed by land and sea breezes, which are
described in more detail by Morawska et al. (1998).
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6.2.2.1 Brisbane CBD (urban general)
The measurements were conducted at the International Laboratory of Air Quality and
Health (ILAQH), Queensland University of Technology (QUT), which is within the
Brisbane CBD (Figure 6-1). The monitoring site is on the sixth floor of a QUT
campus building, located SE of the city centre, with a major highway (the Pacific
Motorway) situated along the SW side of the campus. Therefore, the pollution
associated with NE winds could be attributed to industrial emissions (from the
airport, oil refinery and Port of Brisbane), while the pollution associated with S to
NW winds could be attributed to local traffic exhaust emissions.
Figure 6-1. Map of monitoring sites.
6.2.2.2 Woolloongabba (roadside)
The Woolloongabba (WOO) monitoring station is located 3 km south of the Brisbane
CBD and is a part of the South-East Queensland air monitoring network of the
Department of Environmental Resource and Management (DERM). The monitoring
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station is situated about 5 meters from the kerb of Ipswich Road, a road with a heavy
traffic flow volume of over 40,000, connecting the Southern Brisbane suburbs to the
CBD. A relatively higher PNC level was expected at this site due to the significant
impact of vehicle emission on PNC. In addition, a mutli-storey car park located 10
meters to the West of the station, and large scale road works surrounding the station,
could also influence particle pollution levels.
6.2.2.3 Rocklea (semi-urban)
The Rocklea (ROC) monitoring station is located around 10 km south of the
Brisbane CBD and is also operated by the DERM. This station is surrounded by an
open area, and the particle concentration was deemed to be free from the influence of
local emissions. The major emission sources are from light industrial (Brisbane
farmers markets) and residential (domestic cooking) sources in the Rocklea area.
6.2.3 Measurement techniques
UFP size distribution in the range 4-110 nm was measured at the QUT monitoring
site using a Scanning Mobility Particle Sizer (SMPS), which consists of two parts, an
Electrostatic Classifier (EC) (TSI 3080) equipped with a nano-Differential Mobility
Analyser (nano-DMA) and a Condensation Particle Counter (CPC) (TSI 3781).
Ambient air was drawn through a ~1m long conductive tubing connected to the EC.
The ratio of the aerosol/sheath air flow for the EC was kept at 1/10 (0.6 to 6L min-1),
and the scan time was five minutes. The size distribution data is then used to
calculate PNC for the QUT site. At the WOO and ROC stations, PNC is
continuously measured by a water-based CPC (TSI 3781) with a size-cut inlet of 1
nm, while particle mass concentrations of PM2.5 and PM10 are measured by a
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Tapered Element Oscillating Microbalance (TEOM) in 30-minute intervals at each
site.
Gaseous pollutants, such as carbon monoxide (CO) and nitrogen oxide (NOx), were
measured at WOO; and ozone (O3) and CO were measured at ROC using real-time
gaseous analysers (Ecotech ML9830 for CO; Ecotech ML9841/ API 200A for NOx;
Ecotech ML9812 for O3). Meteorological parameters including wind direction/speed,
temperature, relative humidity and solar radiation, have also been measured. The
data was collected and validated by the DERM.
6.2.4 Data processing and analysis
The raw particle size distribution measurements were transformed into 10 min
averaged data for figure plotting. The total PNC for QUT was calculated by adding
all of the particle counts in each size bin, which had a lower and upper limit of 1 cm-3
and 5 x 105 cm-3, respectively (Mejía et al., 2007). Approximately 28% of the data
removed from the database was based on the following criteria (the contribution of
each quality control is shown in brackets): i) if the particle concentration has a zero
value (~2%); ii) if the particle concentration is higher than 5 x 105 cm-3 (<1%); iii)
and if data has been collected during instrument malfunction (~26%). Since the time
resolutions of the particle mass concentration, gaseous and meteorological data
provided by the DERM were in 30 min intervals, all measurements were transformed
into 30 min averaged data for correlation analysis (Section 6.3.2). Since the PNCs
measured at three sites using SMPS and CPC, to remove the discrepancy of these
measurement methods, a relative PN contribution to total PNC has been used in
temporal and correlation analysis. Inter-comparison between the PNCs measured by
SMPS and CPCs has been shown in Figure-S1; moderate correlations have been
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obtained (r2 = 0.47- 0.81) with slopes of 0.55-0.65. This implies that the method of
measuring PNCs by SMPS and CPCs for correlation analysis is justifiable and the
ultrafine particles accounted for more than 50% of the PNC (by using CPC).
Correlations between the parameters were tested using the Pearson correlation test,
with a 95% confidence level (p < 0.05). The linearity of the tested parameters was
indicated by the product of Pearson’s coefficient, r2, with a perfect linear correlation
between two parameters indicated by an r2 value close to 1. It should be noted that
the PNC data for WOO is missing for the months from January to April due to
instrument malfunction.
The back-trajectory of various air masses was calculated by using the HYSPLIT
model (Hybrid Single Particle Lagrangian Integrated Trajectory, Version 4.9), in
order to trace their origin. The meteorological data used for back-trajectory
calculations was 1˚ x 1˚ in latitude and longitude. The calculated trajectory analysis
provided an indication of which region the air mass came from. Further details about
the principle and operation of the HYSPLIT model are referenced in these articles
(Draxler and Hess 1997, 1998; Draxler 1999).
6.3 Results and Discussion
Firstly, the variation in PNC within each location was investigated by analysing the
diurnal variation together with other measured parameters. Secondly, correlations
between the PNC for the different locations were examined, along with the influence
of wind direction on PNC. Finally, two cases which represented typical regional
nucleation events and the transport of urban pollution to the downwind semi-urban
site were investigated.
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6.3.1 Diurnal variation
Diurnal variations of the PNC measured at the three locations, which have been
classified into (a) weekdays and (b) weekends by all measured data, are illustrated in
Figure 6-2. It should be noted that the measurement periods at each site did not
overlap. The general meteorological conditions for weekdays and weekends were
similar, with SE-winds observed in the morning and NE-winds observed around
noon, while solar radiation reached a maximum at noon on all days. In contrast,
traffic volumes differed during the weekdays and on weekends, such that i) traffic
volumes were higher during weekdays than on weekends; ii) the daily traffic volume
pattern consisted of two peaks during weekdays, one in the morning (~ 6-7 am) and
one in the afternoon (around 3-6 pm); and iii) the daily pattern during weekends
consisted of a wider, broader peak.
In Figure 6-2a, it can be seen that the morning PNC peaks were observed both at
QUT and WOO. During that period, the measured relative fraction of PNC was
found to be nearly 5% for both sites however, they were not found at ROC. This
result suggests that the observed peaks are related to morning traffic activity on
nearby roads. Around noon, PNC peaks were observed at all three locations, as well
as the maximum solar radiation. The highest relative fraction of total PNC at noon is
7.6%, 6.0% and 8.9% for QUT, WOO and ROC locations, respectively. These peaks
are likely to be the result of new particle formation caused by photochemical
reactions (Cheung et al., 2011). It should be noted that the relative fraction of the
total PNC is affected by background PNC, traffic emissions and photochemical
particle production during the morning and noon periods. The maximum PNC
observed at QUT and WOO is at 12:00, and at 13:00 for ROC. The time lag at ROC
could be the result of the time the pollution plume requires to be transported from the
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upwind area (CBD area), to the downwind area (ROC). This is discussed in more
detail in Section 6.3.5.
One interesting observation is that the influence of traffic activity was weak during
the afternoon period (~15:00-18:00) for both weekdays and weekends, with the PNC
found to decrease gradually between 14:00-15:00, even though traffic volume
remained relatively unchanged. Similar observations were made in the urban area of
Helsinki, Finland (Hussein et al., 2004).
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Figure 6-2. Average diurnal variation of parameters measured for (a) weekdays and (b) weekends. From bottom to top: i) relative PNC measured at three sites, together with traffic volumes recorded at QUT; ii) wind vectors measured at the three sites; and iii) solar radiation (SR) measured at ROC.
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6.3.2 Correlation among measured parameters
A summary of the correlation coefficients (r2) for the measured parameters from the
entire period is provided in Table 6-1. The low r values, 0.05 < r2 < 0.19, showed
that the PNC at the three sites were not correlated, however PM2.5 and PM10 at WOO
and ROC were well correlated (0.60 < r2 < 0.88). These results imply that the PNC at
each site were generally influenced by local sources, such as vehicle exhaust
emissions (Morawska et al., 2008), while PM2.5 and PM10 were influenced by intra-
city pollution.
Although there was no correlation between the PNC between the three sites, the PNC
appeared to be influenced by regional pollution during the nucleation event
(discussed in Section 6.3.4). PNC at QUT and ROC did not show a significant
correlation with primary gaseous pollutants such as CO and NOx, but PNC did show
a moderate correlation with CO (r = 0.35) and NOx (r = 0.47) at WOO. The results
observed at QUT are in contrast to those reported by Morawska et al. (1998), where
PNC (5-1000 nm) at QUT was reasonably well correlated with CO (r = 0.45) and
NOx (r = 0.40), and was also influenced by vehicle exhaust emissions. This
discrepancy may be due to the different measurement periods, as the measurements
were only conducted during the morning and afternoon peak traffic hours in
Morawska et al. (1998). However, a continuous measurement approach was used in
the present study, which included a more complex mixture of emissions and a
significant contribution to the PNC by nucleation process, which may have masked
the influence of vehicle exhaust emissions on PNC.
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Tables
Instrument Site Period Operated on 23/09/2009 APS A 16h – 24h SMPS A All day CPC B 0h - 15h DustTrak B All day TEOM A All day Nephelometer A All day Met Parameters A All day
Table 1: The instruments, their locations and times of operation.
287
Figure Captions
1. Map of Australia, showing the source and dispersion of dust. All sampling
was carried out in Brisbane.
2. Light scattering coefficient of particles (Bsp) as a function of time (Site A).
3. Half-hourly averaged PM2.5 data from the DustTrak and the TEOM during the
dust storm, plotted against each other.
4. Hourly average PM10 and PM2.5 concentrations as a function of time (Site A).
5. Particle number (a) and volume (b) size distributions measured by the APS
(Site A).
6. Ultrafine particle number concentration together with the PM2.5 measured at
Site B.
7. Hourly average ultrafine particle number concentrations as a function of the
PM10 concentration.
8. Hourly average (a) particulate matter and (b) ultrafine particle number
concentrations shown as a function of the light scattering coefficient of
particles, Bsp.
9. Particle number concentration and geometrical mean diameter as measured
by the APS.
10. Ultrafine particle size distributions before and during the dust storm.