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Road traffic emissions are often considered the main source of ultrafine particles (UFP, diameter smaller than 100 nm) in urban environments. However, recent studies worldwide have shown that – in high-insolation urban regions at least – new particle formation events can also contribute to UFP. In order to quantify such events we systematically studied three cities located in predominantly sunny environments: 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, origin and atmospheric evolution of the particles. By applying k-means clustering analysis, we categorized the collected aerosol size distributions into three main 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 variation of the average UFP concentrations for a typical nucleation 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 midday showed nucleation events. The photochemically nucleated particles' burst lasted 1–4 h, reaching sizes of 30–40 nm. On average, the occurrence of particle size spectra dominated by nucleation events was 16% of the time, showing the importance of this process as a source of UFP in urban environments exposed to high solar radiation. Nucleation events lasting for 2 h or more occurred on 55% of the days, this extending to > 4 h in 28% of the days, demonstrating that atmospheric conditions in urban environments are not favourable to the growth of photochemically nucleated particles. In summary, although traffic remains the main source of UFP in urban 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, nucleation events will likely increase in urban areas, due to the reduced urban condensation sinks.
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Atmos. Chem. Phys., 15, 5929–5945, 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
, M. Dall’Osto
, D. C. S. Beddows
, R. M. Harrison
, F. Gómez-Moreno
, L. Núñez
, B. Artíñano
F. Costabile
, G. P. Gobbi
, F. Salimi
, L. Morawska
, C. Sioutas
, and X. Querol
Institute of Environmental Assessment and Water Research (IDÆA) Consejo Superior de Investigaciones Científicas (CSIC),
C/ Jordi Girona 18–26, 08034 Barcelona, Spain
Department of Astronomy and Meteorology, Faculty of Physics, University of Barcelona, C/ Martí i Franquès 1,
08028 Barcelona, Spain
Institute of Marine Sciences (ICM) Consejo Superior de Investigaciones Científicas (CSIC), Pg. Marítim de la Barceloneta
37–49, 08003 Barcelona, Spain
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
Department of Environmental Sciences/Center of Excellence in Environmental Studies, King Abdulaziz University,
Jeddah, 21589, Saudi Arabia
CIEMAT, Environment Department, Unidad Asociada CSIC-CIEMAT, Av. Complutense 40, 28040 Madrid, Spain
CNR – Institute for Atmospheric Sciences and Climate, via Fosso del Cavaliere, 100, Rome, Italy
International Laboratory of Air Quality and Health, Queensland University of Technology, G.P.O. Box 2434,
Brisbane QLD 4001, Australia
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 (
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
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
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–
). 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
). 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- Atmos. Chem. Phys., 15, 5929–5945, 2015
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-
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
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
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
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
C) (%) (mm) (Wm
) (cm
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
240± 337 6000± 7000
Rome 19± 7 59± 17 732
203± 274 5000± 3000
Los Angeles 19± 6 (19
) 58± 20 (71
) 126 (452
) (225
) 12000± 7000
Australian Government Bureau of Meteorology;
National Oceanic and
Atmospheric Administration (NOAA);
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
, 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
), followed by Bris-
bane, Madrid and Barcelona (6000 ± 7000, 7000± 8000 and
7500± 5000cm
, respectively). The highest concentra-
tions corresponded to the city of LA (12000 ± 7000 cm
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
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,
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
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 Atmos. Chem. Phys., 15, 5929–5945, 2015
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
Meteorological (temperature, relative humidity, wind com-
ponents and solar radiation), gaseous pollutants (NO, NO
, CO, SO
) and other parameters (PM
, 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
els. In contrast, Nucleation clusters are seen at midday, under
high temperature, solar radiation and ozone levels and low
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
Atmos. Chem. Phys., 15, 5929–5945, 2015
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
. 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,
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
, BC
and CO (see Figs. S1a and S2). Regarding particle mass con-
centrations, T1 is associated with high values of PM
Fig. S2). We attribute this cluster to freshly emitted traffic
particles. Atmos. Chem. Phys., 15, 5929–5945, 2015
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
Category Subcategory Barcelona Madrid Brisbane
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 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.,
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
et al., 2014). The pattern of this factor is similar to the local
traffic factor found in Beijing in previous study (Wang et al.,
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
ratio from
Atmos. Chem. Phys., 15, 5929–5945, 2015
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
. 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
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-
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. Atmos. Chem. Phys., 15, 5929–5945, 2015
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-
Atmos. Chem. Phys., 15, 5929–5945, 2015
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
, 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
), low
relative humidity and relatively high levels of SO
although still low SO
levels in absolute concentra-
tion values (see Fig. S2). It presents the highest PN
(12000± 8000 cm
) 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- Atmos. Chem. Phys., 15, 5929–5945, 2015
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
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
for Madrid represent NO
/2 and for Los Angeles NO
/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-
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
Atmos. Chem. Phys., 15, 5929–5945, 2015
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
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. Atmos. Chem. Phys., 15, 5929–5945, 2015
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.,
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
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... The particle number size distribution (PNSD) is a key property of an aerosol particle population that provides valuable insights into the formation, transformation and removal processes of particles and the potential aerosol sources (Beddows et al., 2009;Rivas et al., 2020). Analyzing the shape of the PNSD makes possible to identify atmospheric aerosol sources (Brines et al., 2015;Charron et al., 2008;Costabile et al., 2009;Salimi et al., 2014), while the temporal evolution of the PNSD makes possible to observe atmospheric processes such as nucleation, coagulation, condensation and/or deposition (Tunved et al., 2004). To assess the impact on climate and health of the large variety of aerosol sources and processes, several PNSD source apportionment methods have been developed and used to identify aerosol sources (e.g., Beddows et al., 2009Beddows et al., , 2015Cai et al., 2020;Casquero-Vera et al., 2021;Rivas et al., 2020;Rodríguez and Cuevas, 2007). ...
... When the aerosol sources are well known, positive matrix factorization (PMF) or non-positive matrix factorization (NPMF) methods can determine the contribution of each source to the aerosol population (Crilley et al., 2017;Liang et al., 2021;Rivas et al., 2020). However, when aerosol sources are not known, clustering methods enable the identification of aerosol population types in terms of statistical similarities which can be related to sources or atmospheric processes (Atwood et al., 2019;Beddows et al., 2009;Brines et al., 2014Brines et al., , 2015Costabile et al., 2009;Ripamonti et al., 2013;Salimi et al., 2014;Tunved et al., 2004). This unsupervised machine-learning method has been performed satisfactorily in a wide variety of environments which are affected by different sources or processes such as marine sites (Atwood et al., 2017(Atwood et al., , 2019, rural sites (Beddows et al., 2009;Charron et al., 2008;Lee et al., 2021) and urban sites (Agudelo-Castañeda et al., 2019;Brines et al., 2014Brines et al., , 2015Wegner et al., 2012). ...
... However, when aerosol sources are not known, clustering methods enable the identification of aerosol population types in terms of statistical similarities which can be related to sources or atmospheric processes (Atwood et al., 2019;Beddows et al., 2009;Brines et al., 2014Brines et al., , 2015Costabile et al., 2009;Ripamonti et al., 2013;Salimi et al., 2014;Tunved et al., 2004). This unsupervised machine-learning method has been performed satisfactorily in a wide variety of environments which are affected by different sources or processes such as marine sites (Atwood et al., 2017(Atwood et al., , 2019, rural sites (Beddows et al., 2009;Charron et al., 2008;Lee et al., 2021) and urban sites (Agudelo-Castañeda et al., 2019;Brines et al., 2014Brines et al., , 2015Wegner et al., 2012). Among all sites, urban areas are the most interesting sites to be explored using clustering methods due to the high number of aerosol sources influenced by anthropogenic activity (traffic, industry, biomass burning or domestic heating systems) and the complex atmospheric processes which takes place (Wu and Boor, 2021). ...
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The indirect effect of aerosols on climate through aerosol-cloud-interactions is still highly uncertain and limits our ability to assess anthropogenic climate change. The foundation of this uncertainty is in the number of cloud condensation nuclei (CCN), which itself mainly stems from uncertainty in aerosol sources and how particles evolve to become effective CCN. We analyze particle number size distribution (PNSD) and CCN measurements from an urban site in a two-step method: (1) we use an unsupervised clustering model to classify the main aerosol categories and processes occurring in the urban atmosphere and (2) we explore the influence of the identified aerosol populations on the CCN properties. According to the physical properties of each cluster, its diurnal timing, and additional air quality parameters, the clusters are grouped into five main aerosol categories: nucleation, growth, traffic, aged traffic, and urban background. The results show that, despite aged traffic and urban background categories are those with lower total particle number concentrations (Ntot) these categories are the most efficient sources in terms of contribution to the overall CCN budget with activation fractions (AF) around 0.5 at 0.75 % supersaturation (SS). By contrast, road traffic is an important aerosol source with the highest frequency of occurrence (32 %) and relatively high Ntot, however, its impact in the CCN activity is very limited likely due to lower particle mean diameter and hydrophobic chemical composition. Similarly, nucleation and growth categories, associated to new particle formation (NPF) events, present large Ntot with large frequency of occurrence (22 % and 28 %, respectively) but the CCN concentration for these categories is about half of the CCN concentration observed for the aged traffic category, which is associated with their small size. Overall, our results show that direct influence of traffic emissions on the CCN budget is limited, however, when these particles undergo ageing processes, they have a significant influence on the CCN concentrations and may be an important CCN source. Thus, aged traffic particles could be transported to other environments where clouds form, triggering a plausible indirect effect of traffic emissions on aerosol-cloud interactions and consequently contributing to climate change.
... Shipping and aviation might also contribute to increasing UFP concentrations with a prevalence of the lowest mode (Diesch et al., 2013;Lorentz et al., 2019;Stacey et al., 2021). When focusing on European urban background and traffic sites, traffic UFP contributions dominate PNC, followed by nucleation or new particle formation (NPF), with NPF varying widely according to the climatic region (i.e., it is usually higher in the high-insolation areas; but not consistently) (Bousiotis et al., 2021;Brines et al., 2015;Harrison et al., 2011;Kerminen et al., 2018;Petäjä et al., 2007;Reche et al., 2011;Rivas et al., 2021;Salma et al., 2011;Sun et al., 2019). Focusing on NO x , several studies agree that one of the main sources of PNC and NO x are vehicle engines, suggesting that this could be one of the factors behind their strongly correlated (Beevers et al., 2012;Grundström et al., 2015;Johansson et al., 2007). ...
... Road traffic is also the main source of BC in European cities producing very high correlations of PNC and BC during traffic rush hours (Rodríguez and Cuevas, 2007;Sun et al., 2019). However, at traffic sites, this peak could also be in the Nucleation mode (Brines et al., 2015;Harrison et al., 2019Harrison et al., , 2011Hopke et al., 2022;Rivas et al., 2020;Wehner et al., 2002). The correlation of BC with N 100-800 was also high but lower than for N 25-100 (R 2 = 0.65, Figure S3), indicating a major traffic origin with partial contributions of other sources, such as regional aerosol transport (among others). ...
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The 2017–2019 hourly particle number size distributions (PNSD) from 26 sites in Europe and 1 in the US were evaluated focusing on 16 urban background (UB) and 6 traffic (TR) sites in the framework of Research Infrastructures services reinforcing air quality monitoring capacities in European URBAN & industrial areaS (RI-URBANS) project. The main objective was to describe the phenomenology of urban ultrafine particles (UFP) in Europe with a significant air quality focus.The varying lower size detection limits made it difficult to compare PN concentrations (PNC), particularly PN10-25, from different cities. PNCs follow a TR > UB > Suburban (SUB) order. PNC and Black Carbon (BC) progressively increase from Northern Europe to Southern Europe and from Western to Eastern Europe. At the UB sites, typical traffic rush hour PNC peaks are evident, many also showing midday-morning PNC peaks anti-correlated with BC. These peaks result from increased PN10-25, suggesting significant PNC contributions from nucleation, fumigation and shipping.Site types to be identified by daily and seasonal PNC and BC patterns are: (i) PNC mainly driven by traffic emissions, with marked correlations with BC on different time scales; (ii) marked midday/morning PNC peaks and a seasonal anti-correlation with PNC/BC; (iii) both traffic peaks and midday peaks without marked seasonal patterns. Groups (ii) and (iii) included cities with high insolation.PNC, especially PN25-800, was positively correlated with BC, NO2, CO and PM for several sites. The variable correlation of PNSD with different urban pollutants demonstrates that these do not reflect the variability of UFP in urban environments. Specific monitoring of PNSD is needed if nanoparticles and their associated health impacts are to be assessed. Implementation of the CEN-ACTRIS recommendations for PNSD measurements would provide comparable measurements, and measurements of
... Additionally, it consists of some molecules held by van der Waals interactions. In urban environments nucleation serves as the main source of ultrafine particles (Brines, Dall'Osto, Beddows, Gomez-Moreno, Nunez, & Querol, 2015). Subsequent, growth occurs by condensation and particle interaction via coagulation and collision, resulting in an increase in size (Madelaine, 1975). ...
Emerging African countries are characterized by explosive population growth and urbanization, which threaten environmental sustainability. This comparative cross sectional study of rural and urban sites/communities investigated the impact of vehicular emissions on air pollution/quality and respiratory health. We characterized ambient aerosols, assessed cytotoxicity, administered structured questionnaires and key informant guides, conducted respiratory assessments and reviewed road transportation data. Twenty-four air samples were collected at high and low-density traffic sites using polysulfone and stainless steel filters attached to an automated pump. The physico-chemical properties of particulate matter were determined using scanning electron microscopy and energy dispersive X-ray analysis (SEM-EDX). In vitro, toxicity was assessed using macrophages and cell fixation with staining. 150 adult respondents and 30 children comprised the study population. Structured interviewer administered questionnaire were used. Clinical respiratory examination and digital Spirometry were conducted. For the qualitative study, Thirty-five (35) respondents from multidisciplinary agencies were selected using purposive sampling. Informed written consent was obtained from all respondents in the language of choice; Hausa or English. All data were analyzed using thematic areas with Epi info statistical software version 7 (CDC Atlanta). Results showed 51.7% of particles as PM 2.5, with the highest particle concentration in mixed sites (urban and industrial). Particle classification into four groups by elemental composition and structure showed: sand particles (Si, Al, Fe, Ca, Mg, K, Na, Mo, Sr, Zr) 30–51 %; other fibers 0–3%; other particles (Si, Fe, S, Mo, Zn, and other metals) 22–40%; and silicone-based fibres 23-34%. The abundant elements are: Si, Al, Ca, Ce, Ti, Fe, Cl, Pb, and Mn. The lowest viability on cytotoxicity assessment was recorded in mixed site M2. The majority of households were located within 50 meters of air sampling sites. Proximity to traffic sites worsens health, as evidenced in cytotoxicity findings. The quantitative study showed; Mean age: (36.3± 12.9 years), Linear height: (median 1.65, range: 1.40 – 1.86). Male: female ratio 1:1 among adults. Average Distance of households to roads/highway: 36.03±23.79 meters and prevalent duration of daily transit 2- 5 hours. In urban settlements: distance to highway/road <50 meters (OR 32.4, 95% CI: 8.57- 122.3) and Non-use of protective devices (OR: 12.43, 95% CI: 2.60-59.34) showed significant associations. Twenty two (22) Spirometry results were within the obstructive index, with majority of abnormalities as Stage 2. Results for Spirometry in children were normal for age and sex. Respondents reside in close proximity to highways/ roads, Stakeholders indicated a need for improved enforcement of regulations and legislation regarding transportation and health. We recommended improved public awareness on air pollution and sources, introduction of large capacity public transport vehicles, improved urban planning, intensification of emissions control, use of greener sources of energy and increased focused research to facilitate improving environment and health policy.
... Traffic and various combustion emissions (cooking, biomass burning, industrial activities) drive the spatial variability in PNC [24][25][26]. Another source of PNC is nucleation, which is mainly a regional phenomenon [27,28], which is more uniformly distributed in space [29] and therefore contribute minimally to intraurban exposure disparities. In contrast, PM 2.5 mass concentrations have less spatial variability because the majority of PM 2.5 mass is regional and secondary particles (sulfate, nitrate, ammonium, and secondary organic aerosol, which are formed in the atmosphere from oxidation of inorganic and organic precursor gases). ...
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Ultrafine particles (“UFP"; <100 nm in diameter) are a subset of fine particulate matter (PM2.5); they have different sources and spatial patterns. Toxicological studies suggest UFP may be more toxic per mass than PM2.5. Racial-ethnic exposure disparities for PM2.5 are well documented; national exposure disparities for UFP remain unexplored due to a lack of national exposure estimates. Here, we combine high-spatial-resolution (census block level) national-scale estimates of long-term, ambient particle number concentrations (PNC; a measure of ultrafine particles) with publicly available demographic data (census block-group level) to investigate exposure disparities by race-ethnicity and income across the continental United States. PNC exposure for racial-ethnic minorities (Asian, Black, Hispanic) is 35% higher than the overall national mean. The magnitudes of exposure disparities vary spatially. Disparities are generally larger in densely populated metropolitan areas. The magnitudes of disparities are much larger for PNC than for PM2.5; PM2.5 exposure for racial-ethnic minorities is 9 % higher than the overall national mean. Our analysis shows that PNC exposure disparities cannot be explained by differences in income. Whites of all incomes, including low-income Whites, have substantially lower average PNC exposures than people of color of all incomes. A higher proportion of traffic and other PNC sources are located near many minority communities. This means that the exposure disparities are structural and strongly tied to where certain subsets of the population live and that simply reducing PNC emissions nationwide will not reduce these disparities.
... PM with a diameter from 0.1 to 1 microns can be in the air for many weeks and, accordingly, be a subject of transboundary transport. Microparticles can be of natural (dust transport, soil erosion) and anthropogenic origin [1,2]. Internal combustion engines, combustion of various types of fuels (coal, brown coal, heavy oil, biomass) in stationary heat sources (boiler houses), construction, many types of production (especially cement, ceramics, bricks, smelting), and trans-shipment of bulk cargo are the main sources of suspended particles in the urban atmosphere. ...
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In most cities of the world, air pollution reaches critical levels. The air masses circulating over the Crimean Peninsula bring a significant amount of mineral dust, which contains soil particles, emissions from industrial enterprises, gases, etc. The purpose of this research is to study the processes and the factors influencing atmospheric pollution in Sevastopol (Crimea). Air pollutant concentration data, including elemental carbon, nutrients (inorganic fixed nitrogen, inorganic fixed phosphorus and silicon), PM10, and PM2.5, were collected during this research. Samples were collected at the station that is located at a distance from sources of pollution (background station). Our study has shown that even at the background site the daily-averaged concentrations of PM10 and PM2.5 particles in the atmosphere of Sevastopol reach and even exceed the maximum permissible concentrations in the case of dust transported from deserts. Values of the daily-averaged concentrations of microparticles have exceeded the European maximum permissible concentration (MPC) values in 17 cases for PM2.5 particles and in 6 cases for PM10. The impact of both local sources and long-distance atmospheric transport depends on weather conditions. Concentrations of elemental carbon in air samples have never exceeded the maximum allowed by regulations concentration limits during our research. However, the elemental carbon concentration in air samples collected near highways with a traffic intensity of approximately 500–1000 cars per hour has exceeded the background values by 30–50 times.
The 2017-2019 hourly particle number size distributions (PNSD) from 26 sites in Europe and 1 in the US were evaluated focusing on 16 urban background (UB) and 6 traffic (TR) sites in the framework of Research Infrastructures services reinforcing air quality monitoring capacities in European URBAN & industrial areaS (RI-URBANS) project. The main objective was to describe the phenomenology of urban ultrafine particles (UFP) in Europe with a significant air quality focus. The varying lower size detection limits made it difficult to compare PN concentrations (PNC), particularly PN10-25, from different cities. PNCs follow a TR>UB>Suburban (SUB) order. PNC and Black Carbon (BC) progressively increase from Northern Europe to Southern Europe and from Western to Eastern Europe. At the UB sites, typical traffic rush hour PNC peaks are evident, many also showing midday-morning PNC peaks anti-correlated with BC. These peaks result from increased PN10-25, suggesting significant PNC contributions from nucleation, fumigation and shipping. Site types to be identified by daily and seasonal PNC and BC patterns are: (i) PNC mainly driven by traffic emissions, with marked correlations with BC on different time scales; (ii) marked midday/morning PNC peaks and a seasonal anti-correlation with PNC/BC; (iii) both traffic peaks and midday peaks without marked seasonal patterns. Groups (ii) and (iii) included cities with high insolation. PNC, especially PN25-800, was positively correlated with BC, NO2, CO and PM for several sites. The variable correlation of PNSD with different urban pollutants demonstrates that these do not reflect the variability of UFP in urban environments. Specific monitoring of PNSD is needed if nanoparticles and their associated health impacts are to be assessed. Implementation of the CEN-ACTRIS recommendations for PNSD measurements would provide comparable measurements, and measurements of <10 nm PNC are needed for full evaluation of the health effects of this size fraction.
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La Paz and El Alto are two fast-growing high-altitude Bolivian cities forming the second largest metropolitan area in the country, located between 3200 and 4050 m a.s.l. Together they host a growing population of around 1.8 million people. The air quality in this conurbation is strongly influenced by urbanization. However, there are no comprehensive studies that have assessed the sources of air pollution and their impacts on health. Despite being neighboring cities, the drastic change in altitude and topography between La Paz and El Alto together with different socio-economic activities lead to different sources, dynamics and transport of particulate matter (PM). In this investigation, PM10 samples were collected at two urban background stations located in La Paz and El Alto between April 2016 and June 2017. The samples were later analyzed for a wide range of chemical species including numerous source tracers (OC, EC, water-soluble ions, sugar anhydrides, sugar alcohols, trace metals, and molecular organic species). The US-EPA Positive Matrix Factorization (PMF v.5.0) receptor model was then applied for source apportionment of PM10. This is the first source apportionment study in South America that incorporates a large set of organic markers (such as levoglucosan, polycyclic aromatic hydrocarbons – PAH, hopanes and alkanes) together with inorganic species. The multisite PMF resolved 11 main sources of PM. The largest annual contribution to PM10 came from two major sources: the ensemble of the four vehicular emissions sources (exhaust and non-exhaust), together responsible for 35 % and 25 % of the measured PM in La Paz and El Alto, respectively, and dust contributing 20 % and 32 % to the total. Secondary aerosols contributed 22 % (24 %) in La Paz (El Alto). Agriculture-related smoke from biomass burning originated in the Bolivian lowlands and neighboring countries contributed to 8 % (7 %) of the total PM10 mass annually. This contribution increased to 17 % (13 %) between August–October. Primary biogenic emissions were responsible for 13 % (7 %) of the measured PM10 mass. Finally, it was possible to identify a profile related to open waste burning occurring between the months of May and August. Despite the fact that this source contributed only to 2 % (5 %) of the total PM10 mass, it constitutes the second largest source of PAHs, compounds potentially hazardous to health. Our analysis resulted in the identification of two specific traffic-related sources. In addition, we also identified a lubricant source (not frequently identified) and a non-exhaust emissions source. This study shows that PM10 concentrations in La Paz and El Alto region are mostly impacted by a limited number of local sources. In conclusion, dust, traffic emissions, open waste burning and biomass burning are the main sources to target in order to improve air quality in both cities.
Hyperlocal air quality maps are becoming increasingly common, as they provide useful insights into the spatial variation and sources of air pollutants. In this study, we produced several high-resolution concentration maps to assess the spatial differences of three traffic-related pollutants, Nitrogen dioxide (NO2), Black Carbon (BC) and Ultrafine Particles (UFP), in Amsterdam, the Netherlands, and Copenhagen, Denmark. All maps were based on a mixed-effect model approach by using state-of-the-art mobile measurements conducted by Google Street View (GSV) cars, during October 2018 – March 2020, and Land-use Regression (LUR) models based on several land-use and traffic predictor variables. We then explored the concentration ratio between the different normalised pollutants to understand possible contributing sources to the observed hyperlocal variations. The maps developed in this work reflect, (i) expected elevated pollution concentrations along busy roads, and (ii) similar concentration patterns on specific road types, e.g., motorways, for both cities. In the ratio maps, we observed a clear pattern of elevated concentrations of UFP near the airport in both cities, compared to BC and NO2. This is the first study to produce hyperlocal maps for BC and UFP using high-quality mobile measurements. These maps are important for policymakers and health-effect studies, trying to disentangle individual effects of key air pollutants of interest (e.g., UFP).
Better knowledge of the sources of black carbon (BC) and ultrafine particles (UFPs) in urban roadway region will provide helpful information for improving road air pollution caused by vehicle emissions. For this purpose, we conducted daily observation of BC and UFPs at two trafficked sites (intersection and roadside), and a background site in Xi'an, China. The concentration data of BC and UFPs measured were combined with Aethalometer model and UFPs source apportion model, to determine and analyze the sources of BC in an urban road region. Further, the source and variation characteristics of primary and secondary UFPs at the roadside sites were clarified. The results showed that average BC concentrations at the intersection, roadside, and background were respectively 3577 ± 2771, 3078 ± 2343, and 1914 ± 1229 ng/m³. The BC source apportionment results revealed contribution rates of on-board fossil fuel combustion (BCff) at the intersection and near the road of ca. 78.7% and 73.6%, respectively. Moreover, the proportion of particles number concentrations directly emitted from vehicles and nucleated upon emission (47%) was lower than that of particles formed during the dilution and cooling of vehicle emissions and by in-situ new particle formation (53%) at the roadside site. At 49%, the proportion of primary particles number was slightly higher at the intersection. The impacts of new particle-formation events on the diurnal variation of secondary particles were explored. Generally, the majority of BC originated from traffic exhausts, while the secondary particles from non-traffic sources are dominant at the road intersections. By providing a better understanding of near-road pollution issues, this study's findings can be useful for taking effective regulatory efforts to improve air quality and reduce people's exposure to traffic-pollutants in an urban environment.
In the past several decades, a variety of efforts have been made in the United States to improve air quality, and ambient particulate matter (PM) concentrations have been used as a metric to evaluate the efficacy of environmental policies. However, ambient PM concentrations result from a combination of source emission rates and meteorological conditions, which also change over time. Dispersion normalization was recently developed to reduce the influence of atmospheric dispersion and proved an effective approach that enhanced diel/seasonal patterns and thus provides improved source apportionment results for speciated PM mass and particle number concentration (PNC) measurements. In this work, dispersion normalization was incorporated in long-term trend analysis of 11–500 nm PNCs derived from particle number size distributions (PNSDs) measured in Rochester, NY from 2005 to 2019. Before dispersion normalization, a consistent reduction was observed across the measured size range during 2005–2012, while after 2012, the decreasing trends slowed down for accumulation mode PNCs (100–500 nm) and reversed for ultrafine particles (UFPs, 11–100 nm). Through dispersion normalization, we showed that these changes were driven by both emission rates and dispersion. Thus, it is important for future studies to assess the effects of the changing meteorological conditions when evaluating policy effectiveness on controlling PM concentrations. Before and after dispersion normalization, an evident increase in nucleation mode particles was observed during 2015–2019. This increase was possibly enabled by a cleaner atmosphere and will pose new challenges for future source apportionment and accountability studies.
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Understanding the particle number size distributions in diversified atmospheric environments is important in order to design mitigation strategies related to submicron particles and their effects on regional air quality, haze and human health. In this study, we conducted 15 different field measurement campaigns between 2007 and 2011 at 13 individual sites in China, including five urban sites, four regional sites, three coastal/background sites and one ship cruise measurement along eastern coastline of China. Size resolved particles were measured in the 15–600 nm size range. The median particle number concentrations (PNCs) were found to vary in the range of 1.1−2.2 × 104 cm−3 at urban sites, 0.8−1.5 × 104 cm−3 at regional sites, 0.4−0.6 × 104 cm−3 at coastal/background sites, and 0.5 × 104 cm−3 during cruise measurement. Peak diameters at each of these sites varied greatly from 24 to 115 nm. Particles in the 15–25 nm (nucleation mode), 25–100 nm (Aitken mode) and 100–600 nm (accumulation mode) range showed different characteristics at each sites, indicating the features of primary emissions and secondary formation in these diversified atmospheric environments. Diurnal variations show a build-up of accumulation mode particles belt at regional sites, suggesting the contribution of regional secondary aerosol pollution. Frequencies of new particle formation (NPF) events were much higher at urban and regional sites than at coastal sites and during cruise measurement. The average growth rates (GRs) of nucleation mode particles were 8.0–10.9 nm h−1 at urban sites, 7.4–13.6 nm h−1 at regional sites and 2.8–7.5 nm h−1 at coastal sites and during cruise measurement. The high gaseous precursors and strong oxidation at urban and regional sites not only favored the formation of particles, but also accelerated the growth rate of the nucleation mode particles. No significant difference in condensation sink (CS) during NPF days were observed among different site types, suggesting that the NPF events in background areas were more influenced by the pollutant transport. In addition, average contributions of NPF events to potential cloud condensation nuclei (CCN) at 0.2% super-saturation in the afternoon of all sampling days were calculated as 11% and 6% at urban sites and regional sites, respectively. On the other hand, NPF events at coastal sites and during cruise measurement had little impact on potential production of CCN. This study provides a large data set of particle size distribution in diversified atmosphere of China, improving our general understanding of emission, secondary formation, new particle formation and corresponding CCN activity of submicron aerosols in Chinese environments.
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Number concentrations of atmospheric aerosol particles were measured by a flow-switching type differential mobility particle sizer in an electrical mobility diameter range of 6–1000 nm in 30 channels near central Budapest with a time resolution of 10 min continuously from 3 November 2008 to 2 November 2009. Daily median number concentrations of particles varied from 3.8 × 10<sup>3</sup> to 29 ×10<sup>3</sup> cm<sup>−3</sup> with a yearly median of 11.8 × 10<sup>3</sup> cm<sup>−3</sup>. Contribution of ultrafine particles to the total particle number ranged from 58 to 92% with a mean ratio and standard deviation of (79 ± 6)%. Typical diurnal variation of the particle number concentration was related to the major emission patterns in cities, new particle formation, sinks of particles and meteorology. Shapes of the monthly mean number size distributions were similar to each other. Overall mean for the number median mobility diameter of the Aitken and accumulation modes were 26 and 93 nm, respectively, which are substantially smaller than for rural or background environments. The Aitken and accumulation modes contributed similarly to the total particle number concentrations at the actual measurement location. New particle formation and growth unambiguously occurred on 83 days, which represent 27% of all relevant days. Hence, new particle formation and growth are not rare phenomena in Budapest. Their frequency showed an apparent seasonal variation with a minimum of 7.3% in winter and a maximum of 44% in spring. New particle formation events were linked to increased gas-phase H<sub>2</sub>SO<sub>4</sub> concentrations. In the studied area, new particle formation is mainly affected by condensation sink and solar radiation. The formation process seems to be not sensitive to SO<sub>2</sub>, which was present in a yearly median concentration of 6.7 μg m<sup>−3</sup>. This suggests that the precursor gas was always available in excess. Formation rate of particles with a diameter of 6 nm varied between 1.65 and 12.5 cm<sup>−3</sup> s<sup>−1</sup> with a mean and standard deviation of (4.2 ± 2.5) cm<sup>−3</sup> s<sup>−1</sup>. Seasonal dependency for the formation rate could not be identified. Growth curves of nucleated particles were usually superimposed on the characteristic diurnal pattern of road traffic direct emissions. The growth rate of the nucleation mode with a median diameter of 6 nm varied from 2.0 to 13.3 nm h<sup>−1</sup> with a mean and standard deviation of (7.7 ± 2.4) nm h<sup>−1</sup>. There was an indicative tendency for larger growth rates in summer and for smaller values in winter. New particle formation events increased the total number concentration by a mean factor and standard deviation of 2.3 ± 1.1 relative to the concentration that occurred immediately before the event. Several indirect evidences suggest that the new particle formation events occurred at least over the whole city, and were of regional type. The results and conclusions presented are the first information of this kind for the region over one-year long time period.
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The present paper investigates the diurnal and seasonal variability of the aerosol total number concentration, number and volume size distribution between 10 nm and 10 μm, from a combination of a scanning mobility particle sizer (SMPS) and an optical counter (OPC), performed over a two-year period (January 2006–February 2008) at the Nepal Climate Observatory-Pyramid (NCO-P) research station, (5079 m a.s.l.). The annual average number concentration measured over the two-year period at the NCO-P is 860 cm<sup>−3</sup>. Total concentrations show a strong seasonality with maxima during pre-monsoon and post-monsoon seasons and minima during the dry and monsoon seasons. A diurnal variation is also clearly observed, with maxima between 09:00 and 12:00 UTC. The aerosol concentration maxima are mainly due to nucleation processes during the post-monsoon season, as witnessed by high nucleation mode integrated number concentrations, and to transport of high levels of pollution from the plains by valley breezes during the pre-monsoon season, as demonstrated by high accumulation mode integrated number concentrations. Night-time number concentration of particles (from 03:00 to 08:00 NST) are relatively low throughout the year (from 450 cm<sup>−3</sup> during the monsoon season to 675 cm<sup>−3</sup> during the pre-monsoon season), indicating the of high altitudes background level, as a result of downslope winds during this part of the day. However, it was found that these background concentrations are strongly influenced by the daytime concentrations, as they show the same seasonal variability. If nighttime concentrations were presumed to be representative of free troposphere (FT)/residual layer concentrations, they would be found to be two times higher than at other lower altitudes European sites, such as the Jungfraujoch. However, BL intrusions might contaminate the free troposphere/residual layer even at this altitude, especially during regional air masses influence. Night-time measurements were subsequently selected to study the FT composition according to different air masses, and the effect of long range transport to the station.
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The Global Atmospheric Watch research station at Mace Head (Ireland) offers the possibility to sample some of the cleanest air masses being imported into Europe as well as some of the most polluted being exported out of Europe. We present a statistical cluster analysis of the physical characteristics of aerosol size distributions in air ranging from the cleanest to the most polluted for the year 2008. Data coverage achieved was 75% throughout the year. By applying the Hartigan-Wong k -Means method, 12 clusters were identified as systematically occurring. These 12 clusters could be further combined into 4 categories with similar characteristics, namely: coastal nucleation category (occurring 21.3 % of the time), open ocean nucleation category (occurring 32.6% of the time), background clean marine category (occurring 26.1% of the time) and anthropogenic category (occurring 20% of the time) aerosol size distributions. The coastal nucleation category is characterised by a clear and dominant nucleation mode at sizes less than 10 nm while the open ocean nucleation category is characterised by a dominant Aitken mode between 15 nm and 50 nm. The background clean marine aerosol exhibited a clear bimodality in the sub-micron size distribution, with although it should be noted that either the Aitken mode or the accumulation mode may dominate the number concentration. However, peculiar background clean marine size distributions with coarser accumulation modes are also observed during winter months. By contrast, the continentally-influenced size distributions are generally more monomodal (accumulation), albeit with traces of bimodality. The open ocean category occurs more often during May, June and July, corresponding with the North East (NE) Atlantic high biological period. Combined with the relatively high percentage frequency of occurrence (32.6%), this suggests that the marine biota is an important source of new nano aerosol particles in NE Atlantic Air.
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Nanoparticles emitted from road traffic are the largest source of respiratory exposure for the general public living in urban areas. It has been suggested that adverse health effects of airborne particles may scale with airborne particle number, which if correct, focuses attention on the nanoparticle (less than 100 nm) size range which dominates the number count in urban areas. Urban measurements of particle size distributions have tended to show a broadly similar pattern dominated by a mode centred on 20–30 nm diameter emitted by diesel engine exhaust. In this paper we report the results of measurements of particle number concentration and size distribution made in a major London park as well as on the BT Tower, 160 m aloft. These measurements taken during the REPARTEE project (Regents Park and BT Tower experiment) show a remarkable shift in particle size distributions with major losses of the smallest particle class as particles are advected away from the traffic source. In the Park, the traffic related mode at 20–30 nm diameter is much reduced with a new mode at <10 nm. Size distribution measurements also revealed higher number concentrations of sub-50 nm particles at the BT Tower during days affected by higher turbulence as determined by Doppler Lidar measurements and are indicative of loss of nanoparticles from air aged during less turbulent conditions. These results are suggestive of nanoparticle loss by evaporation, rather than coagulation processes. The results have major implications for understanding the impacts of traffic-generated particulate matter on human health.
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The analysis of aerosol size distributions is a useful tool for understanding the sources and the processes influencing particle number concentrations (N) in urban areas. Hence, during the one-month SAPUSS campaign (Solving Aerosol Problems by Using Synergistic Strategies, EU Marie Curie Action) in autumn 2010 in Barcelona (Spain), four SMPSs (Scanning Mobility Particle Sizer) were simultaneously deployed at four monitoring sites: a road side (RSsite), an urban background site located in the city (UBsite), an urban background site located in the nearby hills of the city (Torre Collserola, TCsite) and a regional background site located about 50 km from the Barcelona urban areas (RBsite). The spatial distribution of sites allows study of the aerosol temporal variability as well as the spatial distribution, progressively moving away from urban aerosol sources. In order to interpret the data sets collected, a k-means cluster analysis was performed on the combined SMPS data sets. This resulted in nine clusters describing all aerosol size distributions from the four sites. In summary there were three main categories (with three clusters in each category): "Traffic" (Traffic 1, "Tclus_1" – 8%; Traffic 2, "Tclus_2" – 13%; and Traffic 3, "Tclus_3" – 9%) "Background Pollution" (Urban Background 1, "UBclus_1" – 21%; Regional Background 1, "RBclus_1" – 15%; and Regional Background 2, "RBclus_2" – 18%) and "Special Cases" (Nucleation, "NUclus" – 5%; Regional Nitrate, "NITclus" – 6%; and Mix, "MIXclus" – 5%). As expected, the frequency of traffic clusters (Tclus_1–3) followed the order RSsite, UBsite, TCsite, and RBsite. These showed typical traffic modes mainly distributed at 20–40 nm. The urban background sites (UBsite and TCsite) reflected also as expected urban background number concentrations (average values, N = 1.0 × 104 cm−3 and N = 5.5 × 103 cm−3, respectively, relative to 1.3 × 104 cm−3 seen at RSsite). The cluster describing the urban background pollution (UBclus_1) could be used to monitor the sea breeze circulation towards the regional background study area. Overall, the RBsite was mainly characterised by two different regional background aerosol size distributions: whilst both exhibited low N (2.7 × 103 for RBclus_1 and 2.2 × 103 cm−3 for RBclus_2), RBclus_1 had average PM10 concentrations higher than RBclus_2 (27 vs. 23 μg m−3). As regards the minor aerosol size distribution clusters, the "Nucleation" cluster was observed during daytime, whilst the "Regional Nitrate" was mainly seen at night. The ninth cluster ("Mix") was the least well defined and likely composed of a number of aerosol sources. When correlating averaged values of N, NO2 and PM (particulate mass) for each k-means cluster, a linear correlation between N and NO2 with values progressively increasing from the regional site RBsite to the road site RSsite was found. This points to vehicular traffic as the main source of both N and NO2. By contrast, such an association does not exist for the case of the nucleation cluster, where the highest N is found with low NO2 and PM. Finally, the clustering technique allowed study of the impact of meteorological parameters on the traffic N emissions. This study confirms the shrinking of freshly emitted particles (by about 20% within 1 km in less than 10 min; Dall'Osto et al., 2011a) as particles are transported from the traffic hot spots towards urban background environments. Additionally, for a given well-defined aerosol size distribution (Tclus_2) associated with primary aerosol emissions from road traffic we found that N5–15 nm concentrations can vary up to a factor of eight. Within our measurement range of SMPSs (N15–228 nm) and Condensation Particle Counters (CPCs, N>5 nm), we found that ultrafine particles within the range 5–15 nm in urban areas are the most dynamic, being a complex ensemble of primary evaporating traffic particles, traffic tailpipe new particle formation and non-traffic new particle formation.
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An intensive aerosol characterization experiment was performed at the Taipei Aerosol and Radiation Observatory (TARO, 25.02° N, 121.53° E) in the urban area of Taipei, Taiwan, during July 2012. Number concentration and size distribution of aerosol particles were measured continuously, which were accompanied by concurrent measurements of mass concentration of submicron particles, PM1 (d ≤ 1 μm), and photolysis rate of ozone, J(O1D). The averaged number concentrations of total (Ntotal), accumulation mode (Nacu), Aitken mode (NAitken), and nucleation mode (Nnuc) particles were 13.9 × 103 cm−3, 1.2 × 103 cm−3, 6.1 × 103 cm−3, and 6.6 × 103 cm−3, respectively. Accordingly, the ultrafine particles (UFPs, d ≤ 100 nm) accounted for 91% of the total number concentration of particles measured in this study (10 ≤ d ≤ 429 nm), indicating the importance of UFPs to the air quality and radiation budget in Taipei and its surrounding areas. An averaged Nnuc / NOx ratio of 192.4 cm−3 ppbv−1 was derived from nighttime measurements, which was suggested to be the characteristic of vehicle emissions that contributed to the "urban background" of nucleation mode particles throughout a day. On the contrary, it was found that the number concentration of nucleation mode particles was independent of NOx and could be elevated up to 10 times of the "urban background" levels during daytime, suggesting a substantial amount of nucleation mode particles produced from photochemical processes. Averages (± 1σ) of the diameter growth rate (GR) and formation rate of nucleation mode particles, J10, were 11.9 ± 10.6 nm h−1 and 6.9 ± 3.0 cm−3 s−1, respectively. Consistency in the time series of the nucleation mode particle concentration and the proxy of H2SO4 production, UVB · SO2/CS, for new particle formation (NPF) events suggested that photooxidation of SO2 was likely one of the major mechanisms for the formation of new particles in our study area. Moreover, it was revealed that the particle growth rate correlated exponentially with the photolysis of ozone, implying that the condensable vapors were produced mostly from photooxidation reactions. In addition, this study also revealed that Nnuc exhibited a quadratic relationship with J10. The quadratic relationship was inferred as a result of aerosol dynamics and featured NPF processes in urban areas.
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A series of long-term and temporary measurements were conducted to study the improvement of air quality in Beijing during the Olympic Games period (8–24 August 2008). To evaluate actions taken to improve the air quality, comparisons of particle number and volume size distributions of August 2008 and 2004–2007 were performed. The total particle number and volume concentrations were 14 000 cm−3 and 37 μm−3 cm−3 in August of 2008, respectively. These were reductions of 41% and 35% compared with mean values of August 2004–2007. A cluster analysis on air mass history and source apportionment were performed, exploring reasons for the reduction of particle concentrations. Back trajectories were classified into five major clusters. Air masses from the south direction are always associated with pollution events during the summertime in Beijing. In August 2008, the frequency of air mass arriving from the south was 1.3 times higher compared to the average of the previous years, which however did not result in elevated particle volume concentrations in Beijing. Therefore, the reduced particle number and volume concentrations during the 2008 Beijing Olympic Games cannot be only explained by meteorological conditions. Four factors were found influencing particle concentrations using a positive matrix factorization (PMF) model. They were identified as local and remote traffic emissions, combustion sources as well as secondary transformation. The reductions of the four sources were calculated to 47%, 44%, 43% and 30%, respectively. The significant reductions of particle number and volume concentrations may attribute to actions taken, focusing on primary emissions, especially related to the traffic and combustion sources.
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Long-term measurements of particle number size distribution (PNSD) produce a very large number of observations and their analysis requires an efficient approach in order to produce results in the least possible time and with maximum accuracy. Clustering techniques are a family of sophisticated methods that have been recently employed to analyse PNSD data; however, very little information is available comparing the performance of different clustering techniques on PNSD data. This study aims to apply several clustering techniques (i.e. K means, PAM, CLARA and SOM) to PNSD data, in order to identify and apply the optimum technique to PNSD data measured at 25 sites across Brisbane, Australia. A new method, based on the Generalised Additive Model (GAM) with a basis of penalised B-splines, was proposed to parameterise the PNSD data and the temporal weight of each cluster was also estimated using the GAM. In addition, each cluster was associated with its possible source based on the results of this parameterisation, together with the characteristics of each cluster. The performances of four clustering techniques were compared using the Dunn index and Silhouette width validation values and the K means technique was found to have the highest performance, with five clusters being the optimum. Therefore, five clusters were found within the data using the K means technique. The diurnal occurrence of each cluster was used together with other air quality parameters, temporal trends and the physical properties of each cluster, in order to attribute each cluster to its source and origin. The five clusters were attributed to three major sources and origins, including regional background particles, photochemically induced nucleated particles and vehicle generated particles. Overall, clustering was found to be an effective technique for attributing each particle size spectrum to its source and the GAM was suitable to parameterise the PNSD data. These two techniques can help researchers immensely in analysing PNSD data for characterisation and source apportionment purposes.
Ultrafine particles (UFPs; diameter less than 100 nm) are ubiquitous in urban air, and an acknowledged risk to human health. Globally, the major source for urban outdoor UFP concentrations is motor traffic. Ongoing trends towards urbanisation and expansion of road traffic are anticipated to further increase population exposure to UFPs. Numerous experimental studies have characterised UFPs in individual cities, but an integrated evaluation of emissions and population exposure is still lacking. Our analysis suggests that the average exposure to outdoor UFPs in Asian cities is about four-times larger than that in European cities but impacts on human health are largely unknown. This article reviews some fundamental drivers of UFP emissions and dispersion, and highlights unresolved challenges, as well as recommendations to ensure sustainable urban development whilst minimising any possible adverse health impacts.