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Atmos. Chem. Phys., 15, 5929–5945, 2015
www.atmos-chem-phys.net/15/5929/2015/
doi:10.5194/acp-15-5929-2015
© Author(s) 2015. CC Attribution 3.0 License.
Traffic and nucleation events as main sources of ultrafine particles
in high-insolation developed world cities
M. Brines
1,2
, M. Dall’Osto
3,4
, D. C. S. Beddows
4
, R. M. Harrison
4,5
, F. Gómez-Moreno
6
, L. Núñez
6
, B. Artíñano
6
,
F. Costabile
7
, G. P. Gobbi
7
, F. Salimi
8
, L. Morawska
8
, C. Sioutas
9
, and X. Querol
1
1
Institute of Environmental Assessment and Water Research (IDÆA) Consejo Superior de Investigaciones Científicas (CSIC),
C/ Jordi Girona 18–26, 08034 Barcelona, Spain
2
Department of Astronomy and Meteorology, Faculty of Physics, University of Barcelona, C/ Martí i Franquès 1,
08028 Barcelona, Spain
3
Institute of Marine Sciences (ICM) Consejo Superior de Investigaciones Científicas (CSIC), Pg. Marítim de la Barceloneta
37–49, 08003 Barcelona, Spain
4
National Centre for Atmospheric Science Division of Environmental Health & Risk Management School of Geography,
Earth & Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom
5
Department of Environmental Sciences/Center of Excellence in Environmental Studies, King Abdulaziz University,
Jeddah, 21589, Saudi Arabia
6
CIEMAT, Environment Department, Unidad Asociada CSIC-CIEMAT, Av. Complutense 40, 28040 Madrid, Spain
7
CNR – Institute for Atmospheric Sciences and Climate, via Fosso del Cavaliere, 100, Rome, Italy
8
International Laboratory of Air Quality and Health, Queensland University of Technology, G.P.O. Box 2434,
Brisbane QLD 4001, Australia
9
University of Southern California, Sonny Astani Department of Civil and Environmental Engineering, 3620 S Vermont Ave.,
Los Angeles, CA, 90089, USA
Correspondence to: M. Brines (mariola.brines@idaea.csic.es)
Received: 27 August 2014 – Published in Atmos. Chem. Phys. Discuss.: 22 October 2014
Revised: 26 April 2015 – Accepted: 29 April 2015 – Published: 28 May 2015
Abstract. Road traffic emissions are often considered the
main source of ultrafine particles (UFP, diameter smaller
than 100nm) in urban environments. However, recent stud-
ies worldwide have shown that – in high-insolation urban re-
gions at least – new particle formation events can also con-
tribute to UFP. In order to quantify such events we systemat-
ically studied three cities located in predominantly sunny en-
vironments: Barcelona (Spain), Madrid (Spain) and Brisbane
(Australia). Three long-term data sets (1–2 years) of fine
and ultrafine particle number size distributions (measured
by SMPS, Scanning Mobility Particle Sizer) were analysed.
Compared to total particle number concentrations, aerosol
size distributions offer far more information on the type, ori-
gin and atmospheric evolution of the particles. By apply-
ing k-means clustering analysis, we categorized the collected
aerosol size distributionsinto threemain categories:“Traffic”
(prevailing 44–63% of the time), “Nucleation” (14–19%)
and “Background pollution and Specific cases” (7–22%).
Measurements from Rome (Italy) and Los Angeles (USA)
were also included to complement the study. The daily vari-
ation of the average UFP concentrations for a typical nucle-
ation day at each site revealed a similar pattern for all cities,
with three distinct particle bursts. A morning and an evening
spike reflected traffic rush hours, whereas a third one at mid-
day showed nucleation events. The photochemically nucle-
ated particles’ burst lasted 1–4 h, reaching sizes of30–40nm.
On average, theoccurrence of particle size spectra dominated
by nucleation events was 16% of the time, showing the im-
portance of this process as a source of UFP in urban envi-
ronments exposed to high solar radiation. Nucleation events
lasting for 2h or more occurred on 55% of the days, this ex-
tending to > 4 h in 28 % of the days,demonstrating that atmo-
spheric conditions in urban environments are not favourable
to thegrowthof photochemically nucleated particles. Insum-
Published by Copernicus Publications on behalf of the European Geosciences Union.
5930 M. Brines et al.: Traffic and nucleation events as main sources of ultrafine particles
mary, although traffic remains the main source of UFP in ur-
ban areas, in developed countries with high insolation urban
nucleation events are also a main source of UFP. If traffic-
related particle concentrations are reduced in the future, nu-
cleation events will likely increase in urban areas, due to the
reduced urban condensation sinks.
1 Introduction
Largely populated urban areas are hotspots of urban air pol-
lution due to the many and highly complex pollution sources
of particulate matter and gaseous co-pollutants. Current reg-
ulations address the amount of ambient particulate matter
expressed as a mass concentration of particles, and not par-
ticle number concentrations. However, the European Union
(EU) has recently taken initial steps to set particle number
concentrations emission regulations for vehicular emissions
(EU, 2012). It is worthy of note that ultrafine particles – the
main source of particles by number – are ubiquitous in urban
environments (Kumar et al., 2014), and typically are of high
number concentration and negligible mass. They have a great
potential for lung deposition and are associated with respira-
tory and cardiovascular diseases (Atkinson et al., 2010; Ober-
dorster et al., 2005). There is increasing scientific evidence
that removal of particles deposited in the lung is size-related
(Salma et al., 2015).
A number of studies have focused on the source appor-
tionment of number and size characteristics of submicron
particles in urban ambient air (Pey et al., 2009; Costabile
et al., 2009; Harrison et al., 2011; Dall’Osto et al., 2012;
Hussein et al., 2014; Liu et al., 2014; Salimi et al., 2014).
The main source of primary ultrafine particles in urban ar-
eas is traffic activity. These particles can be formed in the
engine or in the atmosphere after emission from the tailpipe
(Shi and Harrison, 1999; Charron and Harrison, 2003). Pri-
mary particles related to traffic are emitted during the dilu-
tion and cooling of road vehicle exhaust (Charron and Har-
rison, 2003; Kittelson et al., 2006) or as carbonaceous soot
agglomerates formed by fuel combustion (Kittelson, 1998;
Shi et al., 2000). Other combustion sources such as waste
incinerators are minor contributors to UFP loading in urban
environments (Buonanno and Morawska, 2015). Nucleation
mode particles related to traffic are formed behind the ex-
haust tailpipeas theexhaustgases arediluted andcooled with
ambient air (Charron and Harrison, 2003). The most cru-
cial aspect of particle formation behind the exhaust tailpipe
is the three-dimensional representation of the dilution pat-
tern, which involves varying length and timescales (Zhu et
al., 2002; Uhrner et al., 2007; Wehner et al., 2009; Huang
et al., 2014). Strictly speaking, these particles are secondary,
but as they form so close to source, most works regard them
as primary.
Additionally, new particle formation of regional origin
(Kulmala et al., 2004; Wehner et al., 2007; Costabile et al.,
2009) has also been detected in urban areas. This is in con-
trast to what was assumed in the past, which is that pho-
tonucleation events only occur in background and regional
environments such as clean coastal (O’Dowd et al., 2010),
forest areas (Boy and Kulmala, 2002), semi-clean savannah
(Vakkari et al., 2011), high-altitude locations (Sellegri et al.,
2010) and regional background sites (Wiedensohler et al.,
2002). This is usually attributed to the fact that such natural
environments are characterized by a low condensation sink
(CS), thus facilitating nucleation. By contrast,urban environ-
ments are often characterized by high CS, so that a lower fre-
quency of nucleation events is expected. Nevertheless, there
are studies showing that these events in fact can be detected
in urban areas, as originally demonstrated in Atlanta, USA
(Woo et al., 2001), Birmingham, UK (Alam et al., 2003) and
Pittsburgh, USA (Stanier et al., 2004), and subsequently in
many cities worldwide (Pey et al., 2008, 2009; Wu et al.,
2008; Costabile et al., 2009; Rimnácová et al., 2011; Salma
et al., 2011; Dall’Osto et al., 2013; Betha et al., 2013; Che-
ung et al., 2013; Brines et al., 2014).
High insolation and wind speed, low relative humidity,
available SO
2
and low pre-existing particle surface area are
common features that enhance new particle formation events
(Kulmala and Kerminen, 2008), characterized by a great in-
crease in particle number concentrations (PN) in the nucle-
ation mode and subsequent particle growth, if conditions
are favourable. Within northern Europe, nucleation events
in many urban areas are not very often detected (Alam et
al., 2003; Wegner et al., 2012; von Bismarck-Osten et al.,
2013). However, Reche et al. (2011) showed that a different
behaviour was observed in southern European cities, where
new particle formation processes at midday did occur with
higher frequency than in northern European cities. The main
cause for this difference is likely to be the higher intensity of
solar radiation in the southern European areas, and/or possi-
ble site-specific chemical precursors.
In this regard it is worth remembering that UFP and black
carbon (BC – primary traffic particles emitted from incom-
plete combustion) often share the same combustion-related
emission sources in urban environments (Peters et al., 2014;
Ruths et al., 2014).In other words,different pollutantmetrics
are being evaluated to accurately characterize traffic-related
particle emissionsin urban areas. However, whilst the combi-
nation of particle number and BC concentrations might be a
promising approach to assess the spatio-temporal behaviour
of traffic-related particle concentrations (Dall’Osto et al.,
2013; Ruths et al., 2014), Reche et al. (2011) clearly show
that particle number concentration alone is not sufficient to
accurately demonstrate a traffic-related emission, since high
number concentrations of particles can also be associated
with new particle formation events. Recently, Dall’Osto et
al. (2013) demonstrated the complexity of the evolution of
Atmos. Chem. Phys., 15, 5929–5945, 2015 www.atmos-chem-phys.net/15/5929/2015/
M. Brines et al.: Traffic and nucleation events as main sources of ultrafine particles 5931
traffic particles and the different types of nucleation events
occurring in the Mediterranean Basin.
Hence, the objective of this study is to categorize sources
of UFP in urban environments situated in temperate regions
affected by high solar radiation levels. Specifically, we aim
to assess the frequency and influence of nucleation events on
UFP levels and variability, as well as the atmospheric con-
ditions facilitating such events. Reche et al. (2011) demon-
strated that with aerosol number concentration and BC con-
centration measurements, useful information can be drawn
on the differences in primary emissions and nucleation en-
hancements across European cities. The present work con-
siders not only PN, but also aerosol size distribution. This is
one of the mostimportant properties of particles, which helps
in understanding aerosol dynamics, as well as determining
their sources (Harrison et al., 2011; Salimi et al., 2014; Bed-
dows et al., 2015). In the present work, size-resolved particle
number concentration measurements using a Scanning Mo-
bility Particle Sizer (SMPS, see Table S2 in the Supplement
for details) sampled in a number of urban areas are presented
and discussed. The complexity of the data is further reduced
by applying k-means clustering analysis (Beddows at al.,
2009, 2014; Dall’Osto et al., 2011b, 2012; Sabaliauskas et
al., 2013; Brines et al., 2014; Salimi et al., 2014). This clus-
tering technique classifies aerosol size spectra into a reduced
number of categories or clusters that can be characterized
considering their size peaks, temporal trends and meteoro-
logical and gaseous pollutants average values (Beddows et
al., 2009). Salimi et al. (2014) showed that the k-means clus-
tering technique was found to be the preferred one among
several used, and Väänänen et al. (2013) showed that clus-
tering analysis is a good tool for studying aerosol dynamics
and new particle formation events. In other words, we use a
wide aerosol size distribution (10.2–17.5/ 101.8–615.3nm)
and not only the total particle number concentrations to as-
sess the source of ultrafine particles in the urban atmosphere,
leading to a better apportionment. The identification of the
main pollution sources contributing to ultrafine particles af-
fecting urban environments enables quantitative estimation
of the temporal prevalence of each source.
Our main databases are taken from two cities in south-
ern Europe (Barcelona and Madrid, Spain) and one in east-
ern Australia (Brisbane). To complement the study, two ad-
ditional data sets from high-insolation areas (also located in
temperate climatic areas) are analysed: 2 years of data from
a regional background site regularly impacted by the Rome
(Italy) pollution plume and 3 months of data from an urban
background site in Los Angeles (USA).
2 Methodology
2.1 Site locations
Following previous work (Reche et al., 2011; Kumar et al.,
2014) we selected four cities (Barcelona, Madrid, Rome
and Los Angeles), all located in Mediterranean climatic re-
gions according to the Köppen climate classification (Fig. 1).
The Mediterranean climate is categorized as dry-summer
subtropical (type Csa/b) due to its mild winters and warm
summers with scarce rainfall. It is characterized by an-
nual average temperatures of 12–18
◦
C, with dominant clear
sky conditions (annual global irradiance intensity of 180–
190Wm
−2
). Precipitation is concentrated in autumn and
spring and is very scarce during summer; its annual average
is about 600mm. Although it prevails in the coastal Mediter-
ranean Sea Basin areas, it is also present in other parts of
the world, such as southwestern USA, the west and southern
Australia coast, southwestern South Africa and central Chile
(see Fig. 1). Three cities in the western Mediterranean Basin
were selected for this study: Barcelona, Madrid and Rome.
For the American continent the city of Los Angeles was cho-
sen (it is also located in a Mediterranean climate region). Fi-
nally, the city of Brisbane (Australia) was also included. Its
climate is categorized as humid subtropical (type Cfa) due
to the higher mean annual rainfall (1150 vs. 600mm for the
Mediterranean climate), although it otherwise presents many
climatological similarities to the Mediterranean regions with
mild winters and warm summers with prevalent sunny days
(average annual global irradiance of 208Wm
−2
). A detailed
description of the five selected cities is given below:
1. Barcelona (BCN), Spain: located in the northwestern
Mediterranean Basin, it has 1.7 million inhabitants al-
though the metropolitan area exceeds 4 million. The
SMPS sampling site (Palau Reial) can be classified as
urban background and is located close (350m) to a
major highway (Diagonal Avenue: 90000 vehicles per
working day), which is primarily used by commuters
(see Table S1). Previous work in the study area has
demonstrated that 65–69% of ultrafine particles are
emitted by traffic and that photonucleation events con-
tribute remarkably to the annual average total PN (Pey
et al., 2008, 2009; Dall’Osto et al., 2012).
2. Madrid (MAD), Spain: located in the centre of the
Iberian Peninsula, it features 3.3 million inhabitants al-
though the metropolitan area accounts for more than
6 million. Its air pollution plume is fed mainly by traf-
fic emissions. The SMPS sampling site was located at
the CIEMAT facilities, NW of the city centre and con-
sidered as a suburban background area (see Table S1).
Previous work in the study area (Gómez-Moreno et al.,
2011) analysedthe influence of seasonality on two years
of SMPS data. They found that nucleation mode parti-
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5932 M. Brines et al.: Traffic and nucleation events as main sources of ultrafine particles
Figure 1. Location of the cities selected for the study. The 3 main cities Barcelona (BCN), Madrid (MAD) and Brisbane (BNE) are marked
in green, whereas the supporting cities of Los Angeles (LA) and Rome (ROM) are shown in black. The cities of BCN, MAD, ROM and
LA are located in Mediterranean climate regions, whereas BNE has a humid subtropical climate. Image source: US National Park Service
California Mediterranean Research Learning Center.
cles showed high PN at midday, especially during spring
and summer due to new particle formation.
3. Brisbane (BNE), Australia: located on the eastern Aus-
tralian coast, it has 2 million inhabitants although the
metropolitan area accounts for 3 million. Traffic ex-
haust emissions are the main pollution source, although
plumes coming from the airport, harbour and industrial
facilities can also contribute. The SMPS was deployed
on the top of a building owned by the Queensland Uni-
versity of Technology (QUT), in an area considered as
urban background (see Table S1). Previous work in the
study area (Cheung et al., 2011) analysed 1 year of
SMPS data in the ultrafine range, focusing on the nucle-
ation processes in the urban background. They reported
three main diurnal PN peaks: two related to traffic rush
hours and a third one occurring at midday related to nu-
cleation.
4. Rome (ROM), Italy: located 24 km inland from the
Mediterranean Sea, it features 2.7 million inhabitants
although the metropolitan area accounts for 4 million.
The sampling site is located in Montelibretti, 30km NE
from the Rome city centre (Table S1). Although con-
sidered as a regional background site, it is regularly im-
pacted by pollutants transported from the area of Rome,
due to the sea-breeze circulation (Ciccioli et al., 1999).
Previous work in the study area (Costabile et al., 2010)
applied a clustering analysis (principal component anal-
ysis, PCA) on 2 years of SMPS data, reporting three
main factors: an aged nucleation mode, an Aitken mode
and an accumulation mode factor (21, 40 and 28% of
the variance, respectively).
5. Los Angeles (LA), USA: located on the Pacific coast
of the United States, it is a metropolitan area that ex-
ceeds 15 million inhabitants. Road traffic, airplanes,
shipping and manufacturing activities account for the
highest contributions to air pollution. Smog periods are
common in the Los Angeles Basin, caused by frequent
atmospheric inversions. The SMPS data were sampled
at the University of Southern California (USC) site (see
Table S1). It is representative of the urban background
environment and is influenced by traffic emissions from
the I-110 freeway located 120m to the west. A previous
study (Hudda et al., 2010) analysed SMPS data sam-
pled at this as one of several in the Los Angeles urban
area. At the USC site two main PN peaks were observed
coinciding with traffic rush hours and a third one at mid-
day was attributed to secondary photochemical particle
formation.
Although the selected cities are located in similar cli-
matic environments, some differences regarding meteoro-
logical conditions were encountered (see Table 1). All
cities show mild annual temperatures, ranging from 15
◦
C
in Madrid (due to its inland location) to 20
◦
C in Bris-
bane (due to its latitude, closer to the equator, see Fig. 1).
Relative humidity varies by 10 % across the cities, show-
ing highest values in Brisbane (72%). This is probably
related to the higher precipitation rate registered in this
city (1072mm), 2 times higher than in BCN, MAD or
LA (430–450mm). As expected, the highest average an-
Atmos. Chem. Phys., 15, 5929–5945, 2015 www.atmos-chem-phys.net/15/5929/2015/
M. Brines et al.: Traffic and nucleation events as main sources of ultrafine particles 5933
Table 1. Average annual meteorological parameters for each site during the respective study periods. Due to the reduced data availability in
LA, values in parentheses represent annual values provided by NOAA or NASA.
City T RH Rain Solar radiation PN
17.5–100nm
(
◦
C) (%) (mm) (Wm
−2
) (cm
−3
)
Barcelona 18± 6 68± 16 432 190± 270 7500± 5000
Madrid 15± 7 66± 23 438 182± 265 7000± 8000
Brisbane 20± 5 72± 20 1072
a
240± 337 6000± 7000
Rome 19± 7 59± 17 732
b
203± 274 5000± 3000
Los Angeles 19± 6 (19
c
) 58± 20 (71
c
) 126 (452
c
) (225
d
) 12000± 7000
a
Australian Government Bureau of Meteorology;
b
http://www.weatherbase.com/weather/weatherall.php3?s=124261&refer=&units=metric;
c
National Oceanic and
Atmospheric Administration (NOAA);
d
National Aeronautics and Space Administration (NASA).
nual values of solar radiation are recorded in Brisbane and
the lowest in Madrid (240± 337 and 182± 265Wm
−2
, re-
spectively). UFP concentrations (common size range 17.5–
100nm) showed lowest levels in Rome (due to the location
of the sampling site, 5000 ± 3000cm
−3
), followed by Bris-
bane, Madrid and Barcelona (6000 ± 7000, 7000± 8000 and
7500± 5000cm
−3
, respectively). The highest concentra-
tions corresponded to the city of LA (12000 ± 7000 cm
−3
),
probably due to the proximity to the freeway and the limited
sampling time (3 months).
In addition to meteorological features, emission sources
also have an impact on UFP in urban environments,
especially traffic-related pollutants. The vehicle fleet com-
position is not homogeneous among the sampling sites,
as a tendency towards dieselization has been experienced
in some European countries over the last years, especially
in Spain (Amato et al., 2009), where 55% of vehicles are
diesel-powered vs. 44 % gasoline (Dirección General de
Tráfico, https://sedeapl.dgt.gob.es/IEST2/menu.do?path=
/vehiculos/parque/&file=inebase&type=pcaxis&L=0&js=1).
In Italy 37% of the vehicles used diesel fuel and 62 %
used gasoline in 2007 (Istituto Nazionali di Statis-
tica, 2009). On the other hand, in the USA or Aus-
tralia the diesel share represents only around 20%
(Gentner et al., 2012; Australian Bureau of Statistics,
http://www.abs.gov.au/ausstats/abs@.nsf/mf/9309.0).
Diesel vehicle engines are known to emit much higher PN
than gasoline ones (Harris and Maricq, 2001), which might
imply a higher concentration of primary UFP in European
countries in comparison to the USA and Australia. Another
relevant difference between the cities relates to their urban
structure. While both Brisbane and Los Angeles are exten-
sively suburbanizedcities with relativelylowpopulation den-
sities, favouring dilution and diffusion of pollutants, southern
European cities are dense urban agglomerates that favour the
trapping and accumulation of pollutants. The lower concen-
trations of UFP in Brisbane in comparison with European
cities are therefore likely due to lower primary diesel emis-
sions and higher precipitation rates, coupled with higher dif-
fusion and dilution of pollutants due to the urban geogra-
phy of the city. In the case of Madrid and Barcelona, the
higher proportion of diesel vehicles together with the high
urban density leads to an increase of UFP concentrations. In
the case of Los Angeles, the high readings are probably due
to both the proximity to the traffic source and the reduced
sampling period (3 months). Given these differencesbetween
the cities, we nevertheless view the climatic similarities to
be strong enough to consider the urban background environ-
ments in which the data have been sampled to be broadly
comparable.
In order to show averaged annual results we only consid-
ered in this study the cities of Barcelona, Madrid and Bris-
bane for several reasons. In Rome, the sampling site is not
located in an urban environment, although it is affected by
the Rome pollution plume. The monitoring sites in the cities
of Barcelona, Madrid, Brisbane and Los Angeles were clas-
sified as urban background, whereas the one in Rome was
further away from the city. Regarding Los Angeles, only
3 months of measurements were available, which was not
sufficient for studying the annual trends. However, we be-
lieve the sites of Rome and Los Angeles add some important
supporting information to further validate our findings.
2.2 Measurements
2.2.1 Particle number size distributions
The detailed characteristics of the sampling sites, sampling
periods, SMPS models and size ranges at each city can be
seen in Tables S1 and S2. Although the use of aerosol drier
is advisable (Swietlicki at al., 2008; Colbeck and Lazaridis,
2014), it was not possible at the time of sampling. Never-
theless, data were thoroughly checked to avoid possible hu-
midity influences (Costabile et al., 2010). The SMPS low-cut
point ranged from 10.2 to 17.5 nm whereas the SMPS high-
cut point varied from 101.8 to 615.3nm. The lack of mea-
surements below 10 nm does not allow for proper identifi-
cation of the start of new particle formation events, therefore
our so-called “nucleation events” reflect photochemically nu-
cleated particles that have grown over the low-cut detection
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5934 M. Brines et al.: Traffic and nucleation events as main sources of ultrafine particles
limits of each instrument. In addition, such events were eval-
uated visually by inspecting the trends of the SMPS size dis-
tributions. More information reporting a detailed analysis of
the aerosol size distributions used in this work can be found
in previous studies (Madrid: Gómez-Moreno et al., 2011;
Brisbane: Cheung et al., 2011; Rome: Costabile et al., 2010;
Los Angeles: Hudda et al., 2010). Due to the different time
resolution of each instrument, all measurements were aver-
aged to 1h resolution. All data herein reported should be read
as local time.
2.2.2 Meteorological parameters and other air
pollutants
Meteorological (temperature, relative humidity, wind com-
ponents and solar radiation), gaseous pollutants (NO, NO
2
,
O
3
, CO, SO
2
) and other parameters (PM
x
, PN, BC and par-
ticulate nitrate concentrations) were obtained at the site or
from the closest available air quality station (see Table S3).
These data were averaged to 1h resolution to match the
SMPS measurements.
2.3 Data analysis (k-means)
The large amount of data presented in this work (31448h
distributed across five sites) was simplified by applying
k-means clustering analysis (Beddows et al., 2009). This
methodology has already been successfully applied to a num-
ber of studies involving one (Dall’Osto et al., 2012) or mul-
tiple monitoring sites (Dall’Osto et al., 2011b; Brines et al.,
2014; Beddows et al., 2014). In a nutshell, this method cre-
ates manageable groups of clusters that can be classified into
aerosol size distributions types (i.e. characteristic of emis-
sion or formation processes) and permits a simplification of
the data analysis that facilitates its interpretation. To account
for the uncertainty of the method, the confidence limits µ
(99.9% confidence level) were calculated for all the cluster
size distributions at each city, and uncertainty bands were
plotted around each cluster size distribution. A detailed de-
scription of the method can be found in the Supplement.
3 Results
3.1 k-means clustering
A k-means clustering analysis was performed on each of the
five SMPS data sets, resulting in a number of representative
clusters for each city that ranged between 7 and 15. After
careful consideration, such results were further simplified to
4–7 clusters per monitoring site (see Figs. 2b–d, 3b–c). For
further information regarding cluster number reduction re-
fer to the Supplement. As recently discussed in Hussein et
al. (2014), it is not prudent to describe the size distributions
with either too few or too many clusters. Few clusters (2–
4) are not enough to explain variations and detailed differ-
ences in the particle number size distributions observed in
the urban atmosphere. However, using too many (>10) clus-
ters often makes the aerosol source attribution more chal-
lenging. It is important to note that the different aerosol size
distribution clusters were merged not only upon their simi-
lar size distributions among each other but also by consid-
ering strong correlations with other physical and chemical
parameters obtained with other instruments (Beddows et al.,
2009; Dall’Osto et al., 2011a). Additionally, the reduction to
three more-generic classifications, while not based on statis-
tics, is based on existing knowledge of distributions typically
observed and associated with these categories. The average
aerosol size distributions of the three aerosol categories (ob-
tained by averagingthe SMPS clustersof each individualcat-
egory) are presented in Fig. 4. The uncertainty bands plotted
for each cluster (Figs. 2b–d and 3b–c) show the 99.9 % confi-
dence limits for the hourly size distributions contained within
each cluster. This means that with a probability of 99.9%,
all hourly spectra contained in each cluster are found within
the uncertainty bands. The fact that none of the uncertainty
bands of the spectra overlap over the full size range at any of
the sites reflects the robust cluster classification achieved by
k-means analysis. To further characterize each k-means clus-
ter, its corresponding size peaks were extracted; and hourly,
weekly and annual cluster trends were analysed. Moreover,
the corresponding average values of meteorological parame-
ters and available air pollutants for each cluster at each site
were calculated. The analysis of each cluster’s characteristics
allows its classification into different categories depending
on the main pollution source or process contributing to it.
The majority of the clusters were found common to most
of the cities, although showing some site-specific charac-
teristics depending on the location of the site (proximity to
pollution sources), the sampling size range (low-cut 10.2–
17.5nm and upper-cut 101.8–615.3nm, see Table S2) and
the particular emission and atmospheric features of each city
(see Figs. 2b–d and 3b–c). To further simplify the results, the
clusters have been carefully divided in three main categories:
“Traffic”, “Nucleation” and “Background pollution and Spe-
cific cases”. The most relevant categories common to all sites
are Traffic and Nucleation, which display very different char-
acteristics. Broadly, Traffic clusters dominate the aerosolsize
distributions during rush hours, showing very high NO
x
lev-
els. In contrast, Nucleation clusters are seen at midday, under
high temperature, solar radiation and ozone levels and low
NO
x
levels. Detailed features of each k-means size distribu-
tions can be found in Tables 2, S4, S5, S6 and Figs. 2 and 3.
Finally, it is important to remember that the clustering results
can provide a much higher amount of information than that
presented here. Nevertheless, the objective of this study is to
present main aerosol size distribution categories in order to
quantify the impact of photochemical nucleation processes
in urban environments under high solar radiation. Therefore,
the following results are focused on the cities of Barcelona,
Madrid and Brisbane. Results from Rome and Los Angeles
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M. Brines et al.: Traffic and nucleation events as main sources of ultrafine particles 5935
Figure 2. Aerosol size distribution results of the k-means cluster analysis performed on the SMPS data at each selected city: (a) legend, (b)
Barcelona, (c) Madrid, (d) Brisbane. Shaded areas around the curves represent the confidence limits µ calculated for 99.9% confidence level.
Please note the different scales for dN / dlogD
p
. The corresponding cluster proximity diagram (CPD) is shown for the three main selected
cities: (e) Barcelona, (f) Madrid and (g) Brisbane.
are herein used only to complement the discussion, given
their limitations (site location and limited data availability,
respectively).
3.1.1 Traffic-related clusters
Traffic 1 (T1)
This cluster can be seen at all monitoring sites, occurring
27–24% of the time (Table S4). It exhibits a bimodal size
distribution, as typically found in vehicle exhausts, with a
dominant peak at 20–40 nm (traffic-related nucleated parti-
cles) and another at 70–130nm (soot particles) (see Table 2).
Its diurnal trends are driven by traffic rush hours and display
very high levels of traffic pollutants, such as NO, NO
2
, BC
and CO (see Figs. S1a and S2). Regarding particle mass con-
centrations, T1 is associated with high values of PM
10
(see
Fig. S2). We attribute this cluster to freshly emitted traffic
particles.
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5936 M. Brines et al.: Traffic and nucleation events as main sources of ultrafine particles
Table 2. Log-normal fitting peaks for each cluster category k-means size distribution at the main sites and the corresponding peak area
percentage.
Category Subcategory Barcelona Madrid Brisbane
Traffic
Traffic 1 (T1)
26± 1 nm (84%), 25± 1 nm (31%), 21± 1 nm (30%),
130± 4 nm (16%) 70± 6 nm (69%) 77± 1 nm (70%)
Traffic 2 (T2)
23± 2 nm (31%), 31± 3 nm (30%), –
36± 1 nm (8%), 83± 9 nm (70%)
75± 2 nm (61%)
Traffic 3 (T3)
11± 1 nm (21%), 21± 1 nm (24%), 14± 1 nm (18%),
48± 1 nm (79%) 92± 3 nm (76%) 52± 4 nm (82%)
Nucleation
Nucleation 16± 1 nm (53%), 19± 1 nm (24%), 13± 1 nm (74%),
(NU) 69± 2 nm (47%) 48± 2 nm (76%) 77± 1 nm (26%)
Urban 22± 1 nm (61%), 40± 1 nm (53%), 63 ± 2nm (100 %)
Background (UB) 96± 1nm (39 %) 119± 1 nm (47%)
Background pollution Summer – 44± 1 nm (100%) –
Background (SB)
and Specific cases (SC) Nitrate (NIT) 36± 1 nm (100%) 63 ± 1nm (100 %) –
Growth 1 (G1) – – 28± 1nm (100 %)
Growth 2 (G2) – – 37± 1nm (100 %)
Traffic 2 (T2)
This cluster is seen in Barcelona and Madrid, occurring 22–
24% of the time (Table S4). It shows a bimodal size distri-
bution with a minor peak at 20–40 nm and a dominant one
at 70–90nm (see Table 2). It is usually observed during the
evening and night, and contains high concentration of traf-
fic pollutants, like T1 (see Figs. S1a and S2). The main dif-
ference with T1 is that it accounts for particles with traffic
origin that might have undergone physicochemical processes
after being emitted, such as condensation or coagulation, and
that have resulted in a change of the size distribution with re-
spect to T1. This change can be appreciated for each city in
Fig. 2. The evolution of these aerosol size distribution modes
attributed to traffic have already been widely discussed in
previous studies (Dall’Osto et al., 2011b, 2012; Brines et al.,
2014).
Traffic 3 (T3)
This traffic-related cluster was found in all the monitored
cities 11–20% of the time (see Table S4). It presents a bi-
modal size distribution, with a low peak in the nucleation
mode at 10–20nm and a main peak at 50–90nm (see Ta-
ble 2). It occurs throughout the day, with a peak during day-
time, and it is associated with the lowest pollution levels of
all the Traffic clusters (see Fig. S1a). The shift to smaller
sizes of the 20–40nm peak of T1 and T2 towards the nu-
cleation mode in T3 might indicate particle evaporation in
Barcelona, Madrid and Brisbane (see Fig. 2b–d). More in-
formation on the evolution of traffic-related cluster T1–T2
towards traffic-related cluster T3 can be found in Brines et
al. (2014), where aerosol size distribution modes simulta-
neously detected at four monitoring sites during SAPUSS
were reported. As recently discussed in Kumar et al. (2014),
the volatile nature of the traffic nucleation mode particles
raises issues in relation to their reliable measurement and
may also enhance their spatio-temporal variability following
their emission into the atmospheric environment (Dall’Osto
et al., 2011b). A traffic-related cluster peaking during noon-
time was also related to the extension of the morning traffic
peak, which is similar to the diurnal variation of NO
x
(Liu
et al., 2014). The pattern of this factor is similar to the local
traffic factor found in Beijing in previous study (Wang et al.,
2013a).
3.1.2 Nucleation cluster
Nucleation (NU): the Nucleation cluster was found to be
common to all sites – stressing the importance of the occur-
rence of new particle formation processes in high-insolation
urban environments (see Table S4). It occurs between 14 and
19% of the measured periods and has a dominant nucleation
mode peak in the range 10–20nm and a minor size peak in
the Aitken mode at 50–80nm (see Table 2), the latter being
attributed to background aerosols. NU is observed at midday
or early afternoon more intensely during spring and summer
(see Fig. S1b). This cluster is generally characterized by very
high solar irradiance, high wind speed and low concentration
of traffic pollutants (see Fig. S2). The PN/ NO
x
ratio from
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M. Brines et al.: Traffic and nucleation events as main sources of ultrafine particles 5937
Figure 3. Aerosol size distribution results of the k-means cluster analysis performed on the SMPS data at the selected complementary cities:
(a) legend, (b) Rome and (c) Los Angeles. Shaded areas around the curves represent the confidence limits calculated for 3σ . Please note the
different scales for dN / dlogD
p
. Cluster proximity diagrams are shown for both cities: (d) Rome and (e) Los Angeles.
8 to 12 a.m. was calculated for the Nucleation and Traffic 1
clusters for each city. In all cases it was found to be higher
for the Nucleation than for the Traffic 1 clusters, highlighting
both the clean atmospheric conditions favouring nucleation
(low NO
x
levels) and the contribution of nucleated particles
to PN.
3.1.3 Background pollution and Specific cases clusters
Urban Background (UB)
The Urban Background cluster can be observed at all three
sites 6–22% of the time (see Table S4). The size distribu-
tions present a bimodal peak at 20–40nm and at 60–120 nm
(see Table 2). At Barcelona and Madrid – cities highly influ-
enced by road traffic emissions – the dominant peak is the
finest one, whereas in Brisbane the larger peak prevails (see
Table 2). Urban background clusters were usually observed
during the night time, associated with relatively clean atmo-
spheric conditions in the urban environment (see Figs. S1a
and S2).
Summer Background (SB)
This cluster occurred 7% of the time in Madrid (see Ta-
ble S4). The unimodal size distribution shows a peak in the
Aitken mode at 44± 1nm (see Table 2). It is seen during the
summer nights and is thus influenced by low levels of traffic
pollutants, pointing towards clean summer atmospheric con-
ditions.
Nitrate (NIT)
This cluster was observed in the two Spanish cities, occurring
7% of the time in Barcelona and 10% of the time in Madrid.
This cluster is characterized by its prevalence at night during
the colder months (see Fig. S1b). Moreover, in Madrid a mi-
nor peak was also seen during midday. Although the Nitrate
cluster occurs more frequently at night, photochemically in-
duced nitrate formation accounts for higher mass concentra-
tions during the day, especially in winter in Madrid (Gómez-
Moreno et al., 2007; Revuelta et al., 2012).
The two size distributions associated with nitrate in
Barcelona and Madrid are unimodal although presenting dif-
ferent modes. BCN_NIT shows a finer mode at 36± 1 nm,
whereas MAD_NIT shows a larger size mode at 63± 1 nm.
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5938 M. Brines et al.: Traffic and nucleation events as main sources of ultrafine particles
This might be due to the location of the sampling sites, closer
to traffic sources in Barcelona (urban background) than in
Madrid (suburban background).
Growth 1 and 2 (G1, G2)
These clusters were found to be exclusive to the Brisbane
monitoring site and both accounted for 10% of the time.
They show a unimodal peak at 28± 1 and 37± 1nm, respec-
tively. These are frequently seen in the afternoon after pho-
tonucleation occurs (BNE_G2 follows BNE_G1), and are
likely related to further growth of nucleated or traffic par-
ticles (see Sect. 3.2 and Fig. 3d).
3.2 Supporting k-means cluster results from Rome and
Los Angeles
Both Rome and Los Angeles clusters were classified into the
same categories as the main cities, thus similar characteris-
tics regarding meteorological parameters and gaseous pol-
lutants as in the main cities apply. Due to its location in a
regional background area under the influence of the Rome
pollution plume, the Rome clusters showed some differences
with respect to those of Barcelona, Madrid and Brisbane.
For Rome, the Traffic (T1–T3) and Nucleation clusters dis-
played a lower occurrence (41 and 6%, respectively) as well
as a shift in its peaks to larger sizes, reflecting their aged
nature (see Tables S5, S6). Indeed, previous studies have
showed that an aged nucleation mode of particles in the size
range 20–33nm is related to photochemically nucleated par-
ticles downwind of Rome growing in size while being trans-
ported to the sampling site (Costabile et al., 2010). More-
over, in addition to the Urban Background cluster, a unique
Regional Background cluster occurring 28% of the time (Ta-
ble S4) was found specific to this site, and corresponded to
the Regional Background PCA factor described in Costabile
et al. (2010). Regarding Los Angeles, although this site was
located in an urban background environment, aerosol size
distributions were only measured from September to Decem-
ber (see Table S2). Two Traffic clusters and an Urban Back-
ground cluster were identified (representing 61 and 6 % of
the time, respectively), reflecting the proximity of the sam-
pling site to main roads. The Nucleation cluster was found
to occur 33% of the time, due to the enhancement of pho-
tochemical nucleation events during warm months (see Ta-
ble S4).
3.3 k-means clustering results explained by the cluster
proximity diagram
Another way of looking at the k-means results is through the
cluster proximity diagram (CPD), which is obtained using
the Silhouette Width (Beddows et al., 2009). This diagram
positions each cluster according to the similarity with therest
of the clusters (Fig. 2e–g). The closer nodes represent similar
clusters, although not sufficiently alike to form a new clus-
Table 3. Cluster categories (Traffic, Nucleation, Background and
Specific cases, SC) and their occurrence at the main sites.
Category Barcelona Madrid Brisbane
Traffic 63% 58% 44%
Nucleation 15% 19% 14%
Background and SC 22% 23% 42%
100% 100% 100%
ter. Conversely, the more distant nodes represent the most
dissimilar clusters. The average cluster modal diameter in-
creases from left to right.
Figure 2e–g show the corresponding CPDs for the main
selected cities. The Nucleation clusters NU are located in the
far left side of the diagram, as they account for a very fine
size mode (see Table 2). Traffic clusters (T1–T3) are posi-
tioned next to NU, although their location within the CPD
varies depending on the city. In general, T3 and T1 are con-
fined closer to the NU clusters than T2, given their associa-
tion with primary traffic emissions (T1) and evaporation of
traffic particles or nucleation (T3). Clusters T2 are an inter-
mediate step between fresh traffic emissions (T1) and the Ur-
ban Background clusters (UB). Regarding the Background
Pollution clusters (UB and SB), their location on the right
side of the graphs suggests that the sources/processes loading
the Nucleation and Traffic clusters develop and contribute to
this category. Barcelona and Madrid (Fig. 2e and f, respec-
tively) show site-specific clusters. The SB cluster in Madrid
is loaded with traffic particles from T1 and T2 before it con-
tributes to the Nitrate (NIT) cluster. Other site-specific clus-
ters such as Nitrate (NIT) are only observed in Barcelona and
Madrid (Fig. 2e and f, respectively). In the case ofBarcelona,
NIT is linked to the Traffic clusters T1 and T2, highlight-
ing its urban nature. On the other hand, although the Traf-
fic clusters T2 and T3 contribute to the formation of Nitrate
in Madrid, both Background Pollution clusters UB and SB
add to its loading, thus resulting in a higher modal diameter
for the NIT cluster in Madrid than in Barcelona (Table 2).
The remaining Growth clusters in Brisbane (G1 and G2) are
positioned in the centre of the CPD (Fig. 2f) and represent
particle growth from NU or the Traffic clusters (T1 and T3)
before contributing to the UB. This is also supported by their
time occurrence after the NU or T clusters.
4 Discussion
The results described in Sect. 3.1 (for the cities of BCN,
MAD and BNE) can be summarized and simplified in the
three main categories:
– Background pollution and Specific cases: these clus-
ters characterize the urban background and regional
background pollution of the sites. They are likely com-
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M. Brines et al.: Traffic and nucleation events as main sources of ultrafine particles 5939
Table 4. k-means cluster categories average size distribution size mode peaks and corresponding area percentage. Only the main cities BCN,
MAD and BNE were considered. Note the two Aitken modes for Urban Background.
Category Nucleation Aitken Accumulation
Traffic – 31± 1 nm (86%) 120± 2 nm (14%)
Nucleation 17± 1nm (43%) 53 ± 7 nm (57%) –
Urban Background – 38± 3nm (71 %), 168± 14 nm (4%)
72± 2 nm (25%)
Figure 4. Average aerosol size distributions for the main k-means
cluster category: Traffic, Nucleation and Urban Background. Only
the main cities BCN, MAD and BNE were considered.
posed of a mixture of aerosol particle types with differ-
ent sources and origins. The Urban Background clus-
ter usually describes the cleanest conditions encoun-
tered at the urban sites, ranging from 6 to 22% of the
time (see Table S4). The resulting average spectra for
all Urban Background clusters (Fig. 4) show a trimodal
size distribution, with two peaks in the Aitken mode
(at 38± 3 and 72± 2nm) and a minor one in the accu-
mulation mode at 168 ± 14nm, reflecting aged aerosols
mostly of an anthropogenic origin (see Table 4). Spe-
cific cases were associated with “Nitrate” containing
aerosol particles, and “Growth” of new particle forma-
tion events. The Nitrate cluster was observed in Madrid
and Barcelona, whereas the Growth clusters were only
seen in Brisbane. Each cluster represents around 10%
of the time at their respective sites (see Table S4). The
difference in the Nitrate size distributions of Barcelona
and Madrid might be due to the urban site characteris-
tics of this cluster in Barcelona, while in Madrid it is
also enriched with Background clusters (see Fig. 2b, c).
The Growth clusters reflect the size mode increase of
nucleation particles due to subsequent growth (see Ta-
ble 2), since they are recorded after nucleation episodes.
– Traffic: this category includes all clusters directly re-
lated to traffic emission sources. It contains three sub-
categories (Traffic 1–Traffic 3) ranging from fresh traf-
fic emissions to aerosols that have been affected by
atmospheric processes after emission, such as coagu-
lation, condensation or evaporation (Dall’Osto et al.,
2011b). This is the dominant category at all sites, show-
ing the high prevalence of traffic emissions in the ultra-
fine PN concentration in urban background sites. This
category was found to be the main one in all the stud-
ied cities, ranging from 44% in Brisbane to 63% in
Barcelona (see Table 3). The average Traffic size dis-
tribution shows a main peak in the Aitken mode at
31± 1nm and a minor one in the accumulation mode at
120± 2nm (see Fig. 4 and Table 4). According to vehi-
cle emission studies, the Aitken mode corresponds with
grown nucleated particles associated with the dilution
of vehicle exhausts (Kittelson et al., 2006; Ntziachristos
et al., 2007), while the larger mode is associated with
solid carbonaceous compounds from exhausts (Shi et
al., 2000; Harrison et al., 2011). The clusters included
in this category are characterized by the highest levels
of traffic-related pollutants, such as NO, NO
2
, CO and
BC. These values are usually higher for clusters T1 and
T2 and decrease for T3 (see Fig. S2).
– Nucleation events: Nucleation events accounted for 14–
19% of the hourly observations, with an average of
16% of the time, indicating nucleation as an important
source of UFP in high-insolation urban areas (see Ta-
ble 3). The average Nucleation size distribution (Fig. 4)
is characterized by a high PN nucleation mode peak at
17± 1nm and a lower PN peak in the Aitken mode
at 53± 7 nm (Table 4). It occurs under intense so-
lar irradiance, clean air conditions (high wind speed
and low concentrations of CO, NO and NO
2
), low
relative humidity and relatively high levels of SO
2
,
although still low SO
2
levels in absolute concentra-
tion values (see Fig. S2). It presents the highest PN
(12000± 8000 cm
−3
) of all categories (see Fig. 4). In
the case of Madrid, the nucleation peak coincides with
a decrease in PN at the end of the morning rush hour,
while in Rome a minor peak can be observed around
3p.m., when the nucleated particles downwind of Rome
reach the sampling site.
Whilst the occurrence of an increase in PN levels related
to photochemical nucleation events at midday has been pre-
viously discussed (Reche et al., 2011), this work enables the
study of how new particle formation events evolve in the ur-
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5940 M. Brines et al.: Traffic and nucleation events as main sources of ultrafine particles
Figure5. MeanSMPS size distributions on a nucleation day at each selected city, NO
x
average concentration and the frequency of occurrence
of the Nucleation cluster for: (a) Barcelona, (b) Madrid, (c) Brisbane, (d) Rome and (e) Los Angeles. Please note that NO
x
concentrations
for Madrid represent NO
x
/2 and for Los Angeles NO
x
/10. These values are 30–65% lower on nucleation days than the corresponding
sampling period average levels.
ban areas considered. Figure 5 shows that new particle for-
mation events in high-insolation urban environments often
fail to grow to sizes larger than 30–40nm (Fig. 5a–c). Fur-
ther growth of these nucleated particles in urban environ-
ments following a banana-like shape is probably constrained
by the decrease in solar radiation intensity and the prevalence
of traffic emitted particles in the evening.
Although only 3 months of data are available, the same
conclusion can be extracted from the urban Los Angeles site,
whereas aged nucleated particles downwind of Rome (20–
40nm) reach the Rome regional site in the early afternoon
(Fig. 5d, e). Figure 6 shows aerosol size distribution data col-
lected in Barcelona, Madrid and Brisbane during the days
when nucleation events were detected (as k-means cluster
NU). Additionally, temperature, relativity humidity, solar ra-
diation and nitrogen oxide gaseous concentrations are plot-
ted. A clear burst of particles can be seen at midday when
gaseous pollutants are diluted and maximum insolation oc-
curs.
It is worthy of note that weekday / weekend ratios were
calculated for each cluster at each city in order to analyse the
impact of traffic/urban emissions on the clusters occurrence.
The highest average ratio (1.3) was found for the T1 clus-
ter, strengthening its relation to fresh traffic emissions. On
the other hand, T2 and T3 clusters average ratio was 1–1.1,
indicating relative independence on fresh traffic emissions,
in contrast to T1. The nucleation cluster was found to occur
more often during weekends (average ratio 0.9). The lowest
ratio was recorded for the UB cluster during weekends (av-
erage ratio 0.7) reflecting its background nature.
It is common in the literature to refer to the frequency of
nucleation events as the percentage of days such an event has
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M. Brines et al.: Traffic and nucleation events as main sources of ultrafine particles 5941
Figure 6. Daily average PN size distribution, temperature, relative
humidity, solar radiation and NO
x
levels on a nucleation day using
data from Barcelona, Madrid and Brisbane.
been detected. The size distribution time series need to be
visually inspected to certify that a distinct new mode start-
ing in the nucleation range appears, that the mode prevails
over some hours and that it shows signs of growth (Dal Maso
et al., 2005). This methodology has been proven to be very
useful to detect “banana-like” nucleation events, where dis-
tinct nucleation events and subsequent particle growth can be
observed. However, this is not the most common nucleation
event type detected in the studied urban environments, where
an increase in the particle condensation sink due to traffic
emissions might constrain the growth of nucleated particles.
Instead, nucleation events consist of particle bursts lasting for
3–4h with particle growth limited to 20–40 nm (see Figs. 5
and 6). Therefore, to adapt this methodology to our current
scenario, the percentage of days that presented nucleation
events were classified considering the prevalence of the Nu-
cleation cluster from 2 up to 4 consecutive hours for each
site. The results were found to be very homogeneous among
the main sampling sites (see Table 5). Nucleation events were
detected for 53–58 % of the days lasting for 2h or more, de-
creasing to 37–43% for 3 h or more and 27–30% for 4 h or
more. The decrease in occurrence of long nucleation events
is a consequence of the limitation for nucleated particles to
grow in high-insolation urban environments. Interrupted nu-
cleation events were not considered, which may have led to
slightly higher occurrence if considered.
5 Implications and Conclusions
This study shows that traffic is a main source of UFP in the
urban atmosphere, accounting for 44–63% of the time. The
quantified particle number concentration contribution of mo-
tor vehicle emissions was also the major source in other ur-
ban locations: 47.9% in Beijing (Liu et al., 2014), 69% in
Barcelona (Pey et al., 2009; Dall’Osto et al., 2012), 65% in
Table 5. Percentage of nucleation event days at the main cities
BCN, MAD and BNE, and the uninterrupted time prevalence of
these events.
City 2h or 3h or 4 h or
more more more
Barcelona 54% 43% 28%
Madrid 58% 41% 30%
Brisbane 53% 37% 27%
London (Harrison et al., 2011; Beddows et al., 2015), 69%
in Helsinki (Wegner et al., 2012), 42% in Pittsburgh and
45% in Rochester (Woo et al., 2001; Stanier et al., 2004).
Recent source contributions of ultrafine particles in the east-
ern United States also identified gasoline automobiles being
responsible for 40% of the ultrafine particle number emis-
sions, followed by industrial sources (33%), non-road diesel
(16%), on-road diesel (10 %), and 1 % frombiomass burning
and dust (Posner and Pandis, 2015). Vehicle emissions con-
sist of hot gases and primary particles, which are a highly dy-
namic and reactive in nature mixture(Kumar et al., 2011), re-
sulting in rapid physical and chemical transformations of the
emitted particles following atmospheric dilutionand cooling.
There is a need for more field studies to map traffic related
particle number concentrations and to understand the parti-
cle dynamics and their dispersion in urban areas (Goel and
Kumar, 2014).
However, the second major source of ultrafine particles in
the urban atmosphere of the developed urban areas herein
presented is secondary aerosol formation. It is important to
remember that nucleation events in northern European ur-
ban areas are found to be infrequent. In the Helsinki ur-
ban atmosphere they are usually observed during noon hours
with a maximum during spring and autumn (Hussein et
al., 2008), and overall representing only about 2% of the
time (Wegner et al., 2012). Additionally, these events were
regional because they were observed at Hyytiälä (250 km
north of Helsinki). By contrast, in southern Europe, Reche
et al. (2011) showed that new particle formation events
occur more frequently than in northern Europe. However,
only PN was reported in that study, making it harder to
link aerosol sources and processes. Nonetheless, this study
clearly showed how new particle formation events impact the
urban areas studied. In order to discuss this further, we link
our discussion to that reported in Dall’Osto et al. (2013). At
least two main different main types of new particle formation
event can be seen in the Mediterranean urban environment:
1. a regional type event, originating over the whole study
region and impacting almost simultaneously the city
and the surrounding urban background area;
2. an urban type event, which originates only within the
city centre but whose growth continues while trans-
ported away from the city to the regional background.
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5942 M. Brines et al.: Traffic and nucleation events as main sources of ultrafine particles
The main difference between these two types resides in
the origin of the nucleation events (regional scale in type 1
and urban origin in type 2). Moreover, the regional events
are found to start earlier in the morning than the urban type
and usually display the typical banana shape implying that
photochemically nucleated particles experience subsequent
growth. On the other hand, the urban type nucleated parti-
cles experience less growth, reaching sizes of 30–40 nm, as
clearly shown in Fig. 6.
The city of Brisbane exhibits new particle formation
events starting in the morning (see Fig. 5c), similar to the
regional nucleation event types discussed in Dall’Osto et
al. (2013) as they are often followed by particle growthshow-
ing a banana-shape (Cheung et al., 2011). This may be due
to the fact that the Brisbane site is located in a relatively
clean environment. By contrast we find that the majority of
new particle formation events detected in the other cities oc-
cur under the highest solar irradiance and thus around noon.
Such events are characterized by a burst of particles lasting
for about 3–4h (Figs. 5 and 6), as reported in Dall’Osto et
al. (2013).
It should be noted that many urban areas exposed to high
insolation are also characterized by high condensation sinks.
This is the case of many developing urban areas, where new
particle formation events are limited. For example, particle
bursts in the nucleation mode size range (5–25nm) followed
by a sustained growth in size were observed very rarely (only
5 out of 79 observation days) in a tropical southern India
site, less frequently than at most other locations around the
world during May–July (Kanawade et al., 2014a). New par-
ticle formation at two distinct Indian sub-continental urban
locations were observed with lower frequency at Kampur
(14%) than that at Pune (26%), due to the presence of pre-
existing large particles at the former site (Kanawade et al.,
2014b). Observations of new aerosol particle formation in
a tropical urban atmosphere (Betha et al., 2013) were also
found to be suppressed by very high pre-existing particle
concentrations during haze periods (Betha et al., 2014). Zhu
et al. (2014) reported fewer new particle formation events
in a severely polluted atmosphere (Qingdao, China) than in
Toronto (Canada). Long-term measurements of particle num-
ber size distributions in urban Beijing and in the North China
Plain showed homogeneous nucleation events characterized
by the co-existence of a stronger source of precursor gases
and a higher condensational sink of pre-existing aerosol par-
ticles than European cities (Wang et al., 2013a, b).
Regional nucleation can be seen in urban areas more fre-
quently over the weekend (Sabaliauskas et al., 2013). Raget-
tli et al. (2014) recently reported spatio-temporal variation of
urban ultrafine particle number concentrations, showing that
the most important predictor for all models was the subur-
ban background UFP concentration, explaining 50 and 38%
of the variability of the median and mean, respectively. Fre-
quencies of new particle formation (NPF) events in China
were much higher at urban and regional sites than at coastal
sites and during open ocean cruise measurement (Peng et al.,
2014).
This has important implications because the city seems to
be not only a source of primary UFP but also a driver for
nucleation events occurring only in the city. Little is known
about health effects of UFP in urban areas (HEI Review
Panel, 2013), the possible mechanisms and chemical compo-
nents responsible for such events, or if there are differences
in health impact between the two nucleation event types dis-
cussed here. Given that we are still in the early stages of our
understanding of the toxicology and epidemiology of urban
UFP, adoption of the precautionary principle in attempting
to reduce such emissions would seem wise. The urban nu-
cleation events described in this paper presumably have an
anthropogenic origin, or at least are influenced by anthro-
pogenic precursors, due to the fact that such events are seen
initiating in city hot spots and not in the nearby background
(Dall’Osto et al., 2013). On average, nucleation events last-
ing for 2h or more were detected in 55% of the days, this ex-
tending to over 4h in 28% of the days, demonstrating that the
atmospheric conditions in urban environments do not favour
photochemically nucleated particle growth. Traffic remains a
major source of ultrafine particles in the urban atmosphere,
and regional new particle formation can impact urban areas.
However, peaks of ultrafine particle number concentrations
at midday (Reche et al., 2011), due to localized urban nucle-
ation occurring in the city (Dall’Osto et al., 2013), and seen
also in a number of other urban areas as reported in Fig. 5
of this work, suggest it is an important phenomenon (occur-
ring on average 16% of the time), and should be taking into
account in the design and implementation of air quality mon-
itoring networks (Duyzer et al., 2015).
The Supplement related to this article is available online
at doi:10.5194/acp-15-5929-2015-supplement.
Acknowledgements. The gaseous pollutant data for Barcelona were
supported by Meteocat and the meteorological data by the Faculty
of Physics of the University of Barcelona. Ángeles Cristobal from
Ayuntamiento de Madrid is also acknowledged for providing
the data of Casa de Campo (Madrid). This study was partially
funded by the VAMOS project (CGL2010-19464) regarding the
Barcelona measurements. MICROSOL project (CGL2011-27020)
has partially funded this research and the Madrid measurements.
This study was partially supported by the Australian Research
Council through Discovery Project Grant DP0985726. The data
in Los Angeles were funded by the South Coast Air Quality
Management District (SCAQMD) (award #11527) and the USC
Provost’s PhD fellowships. The authors would also like to thank
Cristina Reche and Noemí Pérez for supporting the ancillary data
of Barcelona and for their valuable help in the correct functioning
of the SMPS and Wes Gibbons for revising the English usage in
this paper.
Edited by: R. Vecchi
Atmos. Chem. Phys., 15, 5929–5945, 2015 www.atmos-chem-phys.net/15/5929/2015/
M. Brines et al.: Traffic and nucleation events as main sources of ultrafine particles 5943
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