ACPAtmospheric Chemistry and PhysicsACPAtmos. Chem. Phys.1680-7324Copernicus PublicationsGöttingen, Germany10.5194/acp-16-8559-2016Time-resolved characterization of primary particle emissions and secondary
particle formation from a modern gasoline passenger carKarjalainenPanuhttps://orcid.org/0000-0003-2824-0033TimonenHilkkahttps://orcid.org/0000-0002-7987-7985SaukkoErkkaKuuluvainenHeinoSaarikoskiSannaAakko-SaksaPäiviMurtonenTimoBlossMatthewDal MasoMiikkahttps://orcid.org/0000-0003-3040-3612SimonenPauliAhlbergErikSvenningssonBirgittaBruneWilliam Henryhttps://orcid.org/0000-0002-1609-4051HillamoRistoKeskinenJormahttps://orcid.org/0000-0002-2807-8593RönkköTopitopi.ronkko@tut.fiAerosol Physics Laboratory, Department of Physics, Tampere
University of Technology, P.O. Box 692, 33101 Tampere,
FinlandAtmospheric Composition Research, Finnish Meteorological
Institute, P.O. Box 503, 00101, Helsinki, FinlandVTT Technical Research Centre of Finland Ltd., P.O. Box
1000, 02044 VTT, Espoo, FinlandCentre for Environmental and Climate research, Lund
University, Box 118, 22100 Lund, SwedenDivision of Nuclear Physics, Lund University, Box 118,
22100 Lund, SwedenDepartment of Meteorology, Pennsylvania State University,
University Park, PA, USATopi Rönkkö (topi.ronkko@tut.fi)14July201616138559857010November201525November201523May201621June2016This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://acp.copernicus.org/articles/16/8559/2016/acp-16-8559-2016.htmlThe full text article is available as a PDF file from https://acp.copernicus.org/articles/16/8559/2016/acp-16-8559-2016.pdf
Changes in vehicle emission reduction technologies significantly affect
traffic-related emissions in urban areas. In many densely populated areas the
amount of traffic is increasing, keeping the emission level high or even
increasing. To understand the health effects of traffic-related emissions,
both primary (direct) particulate emission and secondary particle formation
(from gaseous precursors in the exhaust emissions) need to be characterized.
In this study, we used a comprehensive set of measurements to characterize
both primary and secondary particulate emissions of a Euro 5 level gasoline
passenger car. Our aerosol particle study covers the whole process chain in
emission formation, from the tailpipe to the atmosphere, and also takes into
account differences in driving patterns. We observed that, in mass terms,
the amount of secondary particles was 13 times higher than the amount of
primary particles. The formation, composition, number and mass of secondary
particles was significantly affected by driving patterns and engine
conditions. The highest gaseous and particulate emissions were observed at
the beginning of the test cycle when the performance of the engine and the
catalyst was below optimal. The key parameter for secondary particle
formation was the amount of gaseous hydrocarbons in primary emissions;
however, also the primary particle population had an influence.
Introduction
Vehicular emissions deteriorate the air quality locally (Wehner et al., 2002;
Pirjola et al., 2012; Lähde et al., 2014) and contribute significantly to
the air pollution levels in urban areas. Air pollution components like
particulate matter contribute to adverse health effects of people (e.g.,
Pope III and Dockery, 2006). The human exposure to pollutants in urban
environments is the highest in the vicinity of traffic. In order to reduce
the adverse health effects and exposure of people by pollutants, the emission
regulation for vehicles with direct injection engines include limits for
particulate mass (PM), and in Europe for some vehicle types, particle number
(PN) (Dieselnet, 2016), of which the PN limit is considered to be stricter. Limits
for gaseous compounds cover total hydrocarbon emissions, nitrogen oxides and
carbon monoxide. Both particulate and gaseous emissions are strongly affected
by technology development (e.g., catalysts and filters), driven by legislation
activities. This technology development also has, in general, other effects
than required by emission legislation; for example, fuel sulfur content
limitations affect the emissions of nanoparticles. It should be noted that,
e.g., semi-volatile compounds (e.g., low-volatility organics, sulfuric
compounds) are not directly regulated even though they are partially detected
in the gravimetric PM determination as particles or adsorbed gas phase
artefacts (Chase et al., 2004; Högström et al., 2012). Although not
directly regulated, low-volatility organics are likely to be affected by
gaseous hydrocarbon limits.
In the gasoline vehicle fleet, the port-fuel injection (PFI) techniques has
been widely replaced by gasoline direct injection (GDI) technologies due to
the need to decrease fuel consumption and NOx emissions of passenger
cars (e.g., Alkidas, 2007; CARB, 2010). The disadvantage of GDI technologies
is the increased primary particle emission (Aakko and Nylund, 2003; Mohr et
al., 2006; Braisher et al., 2010). The GDI vehicle exhaust particle number
concentrations are typically significantly lower than the diesel exhaust
particle concentrations without a diesel particulate filter (DPF) but higher
than concentrations with a DPF (Mathis et al., 2005). The GDI engine exhaust
particle size distribution has been observed to be bimodal (Barone et al.,
2012; Sementa et al., 2012; Sgro et al., 2012; Maricq et al., 1999;
Karjalainen et al., 2014; Pirjola et al., 2015a) and the emission is
dominated by elemental carbon (EC) (Maricq et al., 2012). Organic carbon (OC)
constitutes only a small fraction of particle emissions. Particles are (in
number) mainly in ultrafine sizes (e.g., Maricq et al., 1999; Harris
and Maricq, 2001; Khalek et al., 2010; Karjalainen et al., 2014). According
to the study of Karjalainen et al. (2014), the GDI exhaust particles can be
divided into four different types: spherical amorphous particles consisting
of carbon with mean particle size between 10 and 20 nm (see also Sgro et
al., 2012; Barone et al., 2012); agglomerated soot-like particles with mean
particle size between 30 and 60 nm; lubricant oil originating particles
consisting of metallic ash components (Rönkkö et al., 2014); and
semivolatile nucleation particles (see also Mathis et al., 2005; Li et al.,
2013). The highest emissions of primary particles take place under
acceleration and deceleration conditions (Karjalainen et al., 2014).
Secondary aerosol formation happens in the atmosphere through oxidation
processes that tend to lower the saturation vapor pressures of organic
species. Thus, more oxidized compounds, mostly organic compounds, are more
likely found in the particle phase (Robinson et al., 2007). Fresh exhaust
emissions contain a variety of different organic compounds, in the scale of
hundreds or thousands of different components (Rogge et al., 1993). Part of
those have low saturation vapor pressure already when emitted and thus they
are observed in primary particulate emission or in particulate phase after
the exhaust has been diluted rapidly into the atmospheric conditions (Tobias
et al., 2001; Sakurai et al., 2003; Arnold et al., 2012; Pirjola et al.,
2015b). However, even the majority of organic compounds in the exhaust are
primarily emitted to the atmosphere in the gaseous phase. Also, sulfur compounds
such as SO2, as well as nitrogen oxides, can play a role in the secondary
aerosol formation processes in the atmosphere.
There are studies of engine-exhaust-related secondary organic aerosol (SOA)
formation for gasoline (Suarez-Bertoa et al., 2015; Nordin et al., 2013;
Platt et al., 2013; Gordon et al., 2014) and diesel vehicles (e.g., Weitkamp
et al., 2007; Chirico et al., 2010; Gordon et al., 2013). In these, the
secondary particulate emissions of gasoline vehicles have been studied using
a smog chamber so that diluted exhaust gas has been led to the smog chamber
during a test cycle, a constant speed operation or idling condition (Chirico
et al., 2010; Nordin et al., 2013). However, in the emission's perspective,
this represents only the average over the test, and more detailed analysis of
the effect of driving pattern and engine conditions on SOA formation is
lacking. With the potential aerosol mass (PAM) concept (Kang et al., 2007,
2011) SOA emissions can be studied in a shorter timescale (minutes). The PAM
is a flow-through-type reactor that uses UV lamps to form oxidants (O3,
OH, HO2). Secondary aerosol formation processes are accelerated so that
a few minutes' residence time corresponds to the atmospheric aging of several days
or even weeks. In principle, the PAM reactor enables real-time measurements
of secondary particulate emissions during the driving cycle. The PAM concept
has been previously applied in vehicular exhaust studies, e.g., by Tkacik et
al. (2014) who used the reactor in a traffic tunnel to study the secondary
aerosol properties, and by Pourkhesalian et al. (2015) who used the PAM
reactor in connection with diesel exhaust particle volatility and reactive
oxygen species (ROS) studies. High oxidant concentrations, (100–1000 times
atmospheric concentrations of O3, OH, HO2) and UV lights used in
the chamber are shown to simulate SOA formation in the atmosphere (Kang et
al., 2007, 2011). The aging as the sample flows through the
chamber is shown to represent several days' aging in the atmosphere (Kang et
al., 2011; Ortega et al., 2013).
In this work, the aim is to show how the driving conditions of modern
gasoline vehicles affect the emissions, especially the secondary particulate
emission. To meet this goal, comprehensive set of real-time instruments was
used to study the physical and chemical characteristics of primary and
secondary particle emissions as well as gaseous emissions of a modern GDI
passenger car. The sampling of exhaust for primary emission measurements was
conducted by mimicking the real-world atmospheric dilution. Secondary
emission was studied by using a PAM reactor designed to mimic atmospheric
aging of aerosol. Experiments were performed for the official European test
cycle for passenger cars that is the New European Driving Cycle (NEDC).
Special attention was paid to the temporal behavior of primary and secondary
particle emissions, e.g., emissions during the engine cold start and in
different driving patterns.
Materials and methods
The test vehicle was a modern gasoline passenger car (model year 2011, 1.4 L
turbo-charged GDI engine, 7-gear dual clutch automatic transmission, weight
1557 kg, odometer reading 48 700 km, emission level Euro 5 with a
3-way catalytic converter). Test fuels comprised of regular commercial
E10 (max 10 % ethanol) with sulfur content being below 10 ppm. The
driving cycle used in the study was New European Driving Cycle (NEDC)
(Fig. 2a). The European exhaust emissions driving cycle NEDC is defined
in the UN ECE R83 regulation. The car was tested on a chassis dynamometer in
a climatic test cell at +23 ∘C. NEDC totals 11.0 km, here divided
into three test phases to study emissions at cold start and with warmed-up
engines. The first and second test phases (later called as cold start urban
driving cycle, CSUDC, and hot urban driving cycle, HUDC) each consisted of
2.026 km driving, and the third test phase, the extra-urban driving cycle
(EUDC), was 6.955 km.
As shown in Fig. 1, particle sampling was conveyed by a partial exhaust
sampling system (Ntziachristos et al., 2004) at thermally insulated and
externally heated exhaust transfer lines (stainless steel AISI 316L).
The sampling system consisted of a porous tube diluter (PTD) (dilution ratio
(DR) 12, dilution nitrogen temperature 30 ∘C), residence time
chamber (2.5 s) and secondary dilution conducted by Dekati diluter (DR 8).
In terms of exhaust nucleation particle formation, the sampling system mimics
the real exhaust dilution and nanoparticle formation processes in the atmosphere
(Rönkkö et al., 2006; Keskinen and Rönkkö, 2010).
Schematic of the experimental setup (MFC = mass flow
controller).
A potential aerosol mass (PAM) chamber is a small flow through chamber
developed to simulate aerosol aging in the atmosphere. The PAM chamber was
installed between the aging chamber and secondary dilution units of sampling
system. PAM chamber is thoroughly described by Kang et al. (2007, 2011) and
Lambe et al. (2011, 2015). Shortly, PAM chamber is a stainless steel cylinder
(length 46 cm, diameter 22 cm, volume ∼ 13 L). In an effort to
reduce wall effects, the PAM flow reactor was designed with a larger
radial/axial dimension ratio and a smaller surface-to-volume ratio relative
to other flow reactors (Lambe et al., 2011; Kang et al., 2011). Two UV lamps
(BHK Ink., Ca) were used to produce oxidants (O3, OH and HO2) as
well as UV light (185, 254 nm). The sample flow through the PAM chamber was
set to ∼ 9.75 L min-1 resulting average residence time of 84 s.
Voltage of the two UV lamps was at maximum value, 190 V. Relative humidity
(RH) and temperature were measured prior to the PAM with stable values of
60 % and 22 ∘C, respectively. Typically, ozone concentration
after the PAM was on average 6 ppm. The PAM chamber was calibrated using
average experiment conditions and following the same procedure described by
Lambe et al. (2011). The corresponding OH exposure was calculated to be
1.03 × 1012 molec. cm-3 s, representing approximately
8 days of aging in the atmosphere.
PAM chamber has been used in different ambient environments (Palm et al.,
2016; Ortega et al., 2016; Tkacik et al., 2014) and also thoroughly
characterized in the laboratory conditions via measurements and modeling
(e.g., Lambe et al., 2011, 2015; Peng et al., 2015; Ortega et al., 2013). The
oxidant concentrations in the PAM chamber are higher (100–1000 times) than
in the atmosphere (Kang et al., 2007); however, the ratios between oxidants are
similar to the atmosphere. Several studies (e.g., Kang et al., 2007, 2011) have
compared PAM results to atmospheric results. Kang et al. (2007, 2011) showed
that the yields of OA from individual organic precursor gases were similar to
those obtained in large environmental chambers and that the extent of OA
oxidation appears to be similar to that observed in the atmosphere and
greater than that observed in large environmental chambers and laboratory
flow tubes. Also, according to results of Tkacik et al. (2014), the chemical
evolution of the organic aerosol in the PAM reactor is similar to that
observed in the atmospheric measurements. Additionally, Tkacik et al. (2014) observed
that the mass spectrum of the unoxidized primary organic aerosol closely
resembles ambient hydrocarbon-like organic aerosol (HOA) and that aged PM
firstly resembles semivolatile oxygenated organic aerosol (SV-OOA) and then
low-volatility organic aerosol (LV-OOA) at higher OH exposures. In this
study, cycles were firstly run without the PAM chamber to measure primary
emissions and secondly with the PAM chamber in order to study the formation
of secondary particulate material. Before the experiment, the PAM chamber was
cleaned by running pure N2-O2 mixture with UV lights on.
Transmission efficiency of gases (CO and SO2) in the PAM chamber has shown
that wall losses in the PAM chamber are very small (Lambe et al., 2011).
Primary particle losses for a PAM chamber (results shown in Fig. S1 in the
Supplement) are in general small especially in the particle sizes that
contain most of the aerosol mass: 25 % at 50 nm, 15 % at 100 nm and
below 10 % above 150 nm.
The particle instrumentation was located downstream of the secondary diluter.
The particle size distributions were measured on-line (1 Hz time resolution)
with a high-resolution low-pressure impactor (HRLPI) (Arffman et al., 2014),
fitted into an ELPI bodywork to replace the original charger and impactor,
and an engine exhaust particle sizer (EEPS, TSI Inc.) (Johnson et al., 2004).
The particle number concentration was also measured with an ultrafine
condensation particle counter (UCPC, TSI Inc. model 3025) that was located
downstream of a passive nanoparticle diluter (DR 42). A SP-AMS was used to
measure chemical composition (ions, organic carbon, refractory black carbon
and some metals) of emitted submicron (50–800 nm) particulate matter (PM).
SP-AMS is a high-resolution time-of-flight aerosol mass spectrometer
(HR-ToF-AMS) with added laser (intracavity Nd:YAG, 1064 nm) vaporizer
(Schwarz et al., 2008). The HR-ToF-AMS is described in detail by DeCarlo et
al. (2006) and Jayne et al. (2000), and SP-AMS is described by Onasch et al. (2012) and
Schwarz et al. (2008). Briefly, in the SP-AMS an aerodynamic lens is
used to form a narrow beam of particles that is transmitted into the
detection chamber, where the species are flash vaporized. Particles are
vaporized either by a normal tungsten vaporizer at 600 ∘C to analyze
inorganic ion and OC concentrations or with an SP laser (intracavity Nd:YAG,
1064 nm) in order to analyze black carbon and metals. The vaporized
compounds are ionized using electron impact ionization (70 eV). Ions formed
are guided to the time-of-flight chamber. A multi-channel plate (MCP) is used
as a detector. The time resolution of AMS measurements was 5 s.
The 1 min detection limits for submicrometer particles are
< 0.04 µg m-3 for all species in the V mode. The IGOR 6.11
(Wavemetrics, Lake Oswego, OR), Squirrel 1.53 (Sueper, 2013) and PIKA 1.12F
were used to analyze the SP-AMS data. Elemental analysis (based on Aiken et
al., 2008) was performed on the HR-ToF-AMS data to determine the aerosol
hydrogen-to-carbon (H / C) and oxygen-to-carbon (O / C) ratios.
CO2 concentrations during the measurement period were significantly
higher (up to 1450 ppm) than atmospheric values (400 ppm), thus CO2
time series was used to correct the artefact caused by gaseous CO2.
Collection efficiency (CE) value represents the fraction of sampled particle
mass that is detected by the detector and CE value is needed for the
calculation of aerosol mass concentration measured by the AMS. Previous
studies have shown that the CE of SP-AMS is affected by (i) particle losses
during transit through the inlet and lens, (ii) the particle beam
divergence for both tungsten and laser vaporizers and for tungsten vaporizer
also due to (iii) bounce effects from the vaporizer
(Huffman et al., 2009; Matthew et al., 2008; Onasch et al., 2012). It is
known that in the standard AMS with only the tungsten vaporizer the CE can depend
on the chemical composition and acidity of aerosol as well as sampling
relative humidity (Middlebrook et al., 2012), the default value for the CE
being 0.5. For the SP-AMS, the CE can vary significantly from the default
value of 0.5 due to the laser vaporizer. Onasch et al. (2012) estimated
collection efficiency of coated black particles in the SP-AMS to be 0.75,
whereas Willis et al. (2014) measured CE = 0.6 for bare regal black
(typically used as a surrogate for BC in laboratory) particles but they
observed a significant increase in CE with increasing coating thickness.
A CE of 1 was used in this study for all SP-AMS data. We acknowledge that it
is likely that the collection efficiency might be overestimated (and
calculated mass concentrations underestimated) for uncoated, primary
emissions, whereas for heavily coated spherical secondary aerosol, the CE is
probably closer to its real value. Due to the low contribution of inorganic
species, it was not relevant to use the method of Middlebrook et al. (2012)
for estimating the CE.
Equipment used in the measurement of the CO, HC, and NOx emissions
conforms to the specifications of the Directive 70/220/EEC and its
amendments. The true oxygen contents and densities of the fuels were used in
the calculation of the results. A flame ionization detector (FID) was used
for the measurement of hydrocarbons (all carbon-containing compounds, also
oxygenates) (Sandström-Dahl et al., 2010; Aakko-Saksa et al., 2014). The
calculation method chosen uses the density of 619 kg m-3 (different
from the EC regulation 692/2008). A number of gaseous compounds (19 in
total), nitrogen dioxide (NO2), ammonia (NH3),
nitrous oxide (N2O), ethanol, formaldehyde and acetaldehyde, amongst others, were
measured on-line with 2 s time resolution using Fourier transformation
infrared (FTIR) equipment (Gasmet Cr-2000).
The analysis of OH exposure and non-OH chemistry was performed with the
calculator tool developed by Peng et al. (2016). The inputs to the model are
humidity, OH reactivity (OHR) and photon flux or ozone concentrations. The OHR
is estimated based on volatile organic compound (VOC) and CO
measurements. During the measurements, there were PVF bags that were analyzed
for VOCs of special interest for gasoline vehicles with gas chromatograph (HP
5890 Series II, AL2O3, KCl/PLOT column, an external standard method).
Separate samples were analyzed for CSUDC, HUDC and EUDC, and these results
are presented Table S2 in the Supplement. To find the total external (input)
OHR, the sum of all analyzed concentrations (VOCs and CO) multiplied with the
corresponding rate constants (Atkinson and Arey, 2003) was calculated.
Results and discussionPrimary particulate and gaseous emissions of gasoline passenger
carParticle size distributions
The driving cycle used in the study was NEDC, a statutory cycle in
emission testing in Europe. The cycle consists of several patterns describing
typical driving in urban environments and highway driving (Fig. 2a), with the
total duration and length of the cycle 1200 s and 11.0 km, respectively.
Figure 2 shows the speed of the test vehicle during the test cycle and
particle number concentration, particle volume concentration and particle
size distribution of vehicle exhaust, all measured with high time resolution
(1 s).
Speed profile, primary particle number (measured by the CPC) and
volume concentrations (measured by HRLPI) and primary particle size
distributions (HRLPI) for the studied gasoline passenger car during the NEDC
test cycle.
Temporal behavior of rBC, organics, SO4, NO3 and NH4
concentrations measured by the SP-AMS for the primary emissions (without the
PAM chamber) during the NEDC test cycle.
The exhaust particle number concentration was strongly dependent on driving
condition (Fig. 1b). Large particle number concentrations were observed
during accelerations, especially during the first two accelerations when the
engine had not yet reached steady temperature conditions, and they were
therefore associated with high engine loading and altering combustion
conditions. In addition to soot particles (particle diameters of 30–100 nm,
see Fig. 1c), there were also frequent observations of small particles
(Dp< 10 nm), especially in the middle part of the cycle.
These nanoparticles are most likely associated with deceleration and engine
braking conditions (Rönkkö et al., 2014; Karjalainen et al., 2014).
The largest particle volume concentrations were observed at the beginning,
just after ignition and, on the other hand, at the end of the test cycle when
the driving was at high speed and engine load. High total particle volume
concentrations were strongly linked with the existence of soot-mode particles
in the exhaust.
Chemical composition
Figure 3 shows the chemical composition of primary exhaust particles during
the NEDC cycle. The lower pane shows the major components, revealing that the
large particle emission at the beginning of the cycle consists mainly of
organic compounds and refractory black carbon (rBC). When compared to Fig. 2,
it can be seen that the organic compounds together with rBC form the so-called
soot mode, which dominates the particle volume concentration due to its
large particle size. While the rBC has formed in the engine due to the
incomplete combustion of fuel-forming agglomerated soot particles (Heywood,
1988), the organic compounds have likely been condensed onto the soot
particle surface mainly during cooling dilution process of exhaust. Figure 3
shows that later, after the starting phase of the test cycle, the relative
concentration of rBC decreases and remains at low levels with the exception
of the accelerations at the highway part of the cycle. Interestingly, the
concentration of organic compounds was very significant in the middle part of
the cycle, i.e., when the emissions of nanoparticles (see Fig. 2) were
observed to be high. Thus, while the high emission of organic compounds seems
to be linked with high soot/rBC emission at the beginning of the cycle, in
the middle part the organics and rBC emissions seemed not to be interlinked.
Time series of the exhaust concentrations of total hydrocarbons,
ammonia and NOx.
Concentrations of inorganic species (SO4, NH4, NO3, Cl) are
shown in the upper pane of Fig. 3. Note that the concentration axes differ.
In general, the highest sulfate and nitrate concentrations existed during
accelerations, and had a good correlation with soot/rBC emissions. The
sulfate concentration increases also during certain periods in the middle
part of the cycle, clearly linked with similar peaks in organic compounds
concentration (see Fig. 3). Interestingly, during highway driving and the
following deceleration, significant concentration of ammonium, nitrate
and chloride ions were also observed.
Gaseous emissions
The time series of total hydrocarbons, ammonia and NOx during the NEDC
test cycle are presented in Fig. 4. The largest hydrocarbon emissions were
observed at beginning of the cycle due to low engine and exhaust gas
temperatures, which lowers the efficiency of the oxidation process in the
three-way catalytic converter, in addition to higher formation rates of
gaseous hydrocarbons during combustion. The hydrocarbon emissions are in line
with the measurements of the chemical composition of particles, which shows
that the highest emissions of particulate organic compounds occur at the
beginning of the cycle. However, during the middle part of the cycle, the
emissions of gaseous hydrocarbons and organic particulate matter did not
correlate; although in particle phase organics (see Fig. 3) the
concentrations reached high values also during middle part of the cycle, the
gaseous hydrocarbons remained at very low level until the highway driving
part of the cycle. The NOx emissions were the highest at the beginning
of the cycle and during the last part of the cycle when the driving speed and
combustion temperatures were high. Ammonia concentrations were at the level
of 10 ppm during most of the cycle; concentration even higher than 100 ppm
was measured during the accelerations at the end of the cycle. The highest
ammonia concentrations were clearly linked with acceleration, under
conditions when the air-to-fuel ratio can be below 1 (rich mixture). This is
in line with the findings by Mejia-Centeno et al. (2007) and Heeb et
al. (2006), showing ammonia formation in the three-way catalyst in slightly
rich air-to-fuel ratios, which are prevailing during acceleration.
Secondary particle formation from a gasoline passenger carParticle size distributions
Figure 4 shows the secondary particle number concentrations, volume
concentrations and size distributions of gasoline passenger car exhaust
during the NEDC cycle. In general, the volume and number concentrations as
well as mean particle size of secondary particles were significantly larger
than those of the primary particles, throughout the cycle. Periodic behavior
similar to that of the primary particles can be observed: first, a period with
large soot-mode particles, then a period with a large number of small
nanoparticles and finally the highway part of the cycle.
As shown above, after the ignition, the emissions of gaseous precursors
(hydrocarbons and nitrogen-containing species) and primary particles were
observed to be high (Fig. 4). This, combined with the information in
Fig. 5, indicates that the existence of gaseous precursors in the exhaust
significantly increases the secondary particulate matter formation, resulting
in a high volume concentration of large particles at the beginning of the
test cycle (Fig. 5). Compared to other periods of the cycle, at the beginning
the volume concentration of secondary particles was 3 times higher,
highlighting the role of cold starts in total secondary particle emission of
gasoline vehicles.
The high oxidant concentrations in the PAM chamber result also in high
concentrations of condensing compounds, which causes a possibility for
nucleation in the chamber. In this study, we measured higher particle number
concentrations for the sample treated by the PAM than for the untreated
sample. However, the increase of particle number was not very significant
and, in principle, may also be caused by the increase of particle size into
the measurement range on aerosol instruments. Interestingly, nanoparticles
were not observed in the primary emission during the first period of cycle
(Fig. 2), when both the precursor gas concentration and resulted volume of
secondary particulate matter was the highest. During the first period,
the mean particle number concentrations were also on a relatively similar
level, both in the primary and secondary aerosol. Instead, nanoparticles were
observed in the sample treated by the PAM during the second phase (starting
at 400 s) of the cycle. During this part of the test cycle the nanoparticles
existed also in primary emissions. Thus, the results indicate that
nanoparticles found after PAM chamber are obviously initially formed, already
before the sample was introduced into the PAM chamber. It should be kept in
mind that the existence and growth of nanoparticles in the PAM chamber can
slightly change the mean particle size and thus how effectively they are
detected by aerosol instruments; e.g., the particle size range of aerosol mass
spectrometers does not typically cover particles smaller than 50 nm, and in
several studies the particle number size distribution measurement is limited
to sizes above 10 nm.
Speed profile, secondary particle number (measured by the CPC) and
volume concentrations (measured by the HRLPI) and secondary particle number
size distributions (HRLPI) for the studied gasoline passenger car during the
NEDC test cycle.
Temporal behavior of rBC, organics, SO4, NO3, NH4 and
Cl concentrations measured by the SP-AMS downstream of the PAM chamber during
the NEDC test cycle.
As stated above, in the middle part of the cycle, a large number of primary
nanoparticles was introduced into the chamber from the exhaust. Figure 4
shows that these sub-5 nm particles grew in the chamber to particle sizes
similar to primary soot particles. This takes approximately 60–80 s,
corresponding to the mean residence time in the PAM. In general, it seems
that both the primary soot particles and primary nanoparticles can have an
important role in secondary particle formation dynamics resulting, e.g., in the
size distribution of aged exhaust aerosol.
Chemical composition of secondary particles
The secondary aerosol mass consisted mainly of organic compounds and rBC
(Fig. 6, lower panel). At the beginning of the test cycle, the concentrations
of organic compounds in the secondary particulate matter were about 100 times
higher than their concentrations in primary particles, while the O : C
ratio dipped below 0.5 (see Fig. S3). During other parts of the cycle, the
concentrations of the organic compounds were significantly lower and remained
relatively stable. The rBC concentration level did not change significantly
because rBC is a primary component.
(a) Chemical composition of primary PM,
(b) chemical composition secondary PM and (c) the
O : C ratios of primary and secondary particulate matter for different
parts of the NEDC cycle.
At the beginning of the cycle, the incomplete combustion causes high emissions
of rBC and gaseous hydrocarbons. Simultaneously, the temperature of the
three-way catalyst is low and thus the reduction of hydrocarbons is not
optimal. In the PAM reactor, the oxidation of hydrocarbons lowers their
volatility, which results in high emissions of secondary particulate matter
consisting of organic compounds. During the highway part of the cycle, the
incomplete combustion again causes the emission of soot/rBC during certain
acceleration phases. However, during the highway part, the temperature of the
catalyst used in the vehicle is very high, approximately 700 ∘C (see
Karjalainen et al., 2014), meaning that it keeps the emissions of gaseous
hydrocarbon emissions at a very low level. Thus, during the highway part the
concentration of organic precursors is low in the exhaust, resulting in a low
concentration of secondary organic particulate material.
In addition to rBC and organic compounds, during the middle part of the cycle
the concentrations of inorganic species were observed to be stable. Only a
slight increase in sulfate concentration was observed, simultaneously with
the existence of nanoparticles in secondary aerosol. This observation is in
line with primary particle measurements where sulfate peaks were observed
during the middle part of the cycle. During the highway part of the cycle the
concentrations of inorganic species in the secondary particulate matter
increases when compared to the previous parts of the cycle. This is seemingly
caused by high emissions of gaseous nitrogen compounds (see Fig. 4). Results
indicate that also these compounds may have a significant role in traffic-related
secondary aerosol formation. However, this kind of aerosol is very
specifically formed only at high vehicle speeds.
Influence of driving conditions to emission characteristics
The results presented above indicate that both the primary and secondary
emissions vary strongly as a function of the driving cycle. To clarify the
effects of driving conditions on the concentrations of secondary and primary
particles, the cycle was divided into three sections according to the engine
and speed profile conditions: CSUDC (0–391 s), HUDC (392–787 s) and EUDC
(788–1180 s). The CSUDC represents the cold start situation, the HUDC
represents typical city driving with a warm engine and the EUDC represents
typical highway driving. Figure 7 shows chemical composition and
O : C ratios of primary and secondary (primary components excluded) exhaust
particles for these three sections. O : C ratios were determined for
organic compounds based on chemical composition measured by the SP-AMS, so
that inorganic species and rBC were excluded. Emission factors for measured
compounds are presented in the Supplement (see Fig. S4 and
Table S1).
Primary particle emissions were dominated by rBC and organics. It should be
noted that although the CSUDC and HUDC were similar from the viewpoint of
driving conditions, the rBC concentration was 4 times higher during CSUDC.
Again, during the EUDC section of the cycle higher rBC concentration was
observed in the exhaust. In contrast, for the organics, similar differences
between the sections of the test cycle were not observed. Inorganic species
concentrations were relatively low in all cycle sections representing on
average 3.6 % of particulate mass.
On average, the secondary particulate emissions were 13 times higher than the
primary particle emissions. This value is higher or at similar level than
observed in previous studies. For instance, Suarez-Bertoa et
al. (2015) reported 2–4 times higher values for the secondary particle
emissions of gasoline vehicles when compared to the primary organics and BC.
In the diesel exhaust study of Chirico et al. (2010), the secondary and
primary particle emissions were at similar levels. However, in the study of
Platt et al. (2013) SOA emission was around 14 times higher than primary
organic aerosol (POA) emission when they measured the emissions of gasoline
vehicles for the NEDC cycle. All of these studies were conducted using a batch
chamber, while in our study a flow-through chamber was used. The differences
between the studies can be due to the differences in the emissions but also
due to the differences in wall losses, exhaust and oxidant concentrations
and photochemical ages.
The chemical composition of secondary particles differed significantly from
primary particles; in secondary particles most of the particulate matter
consisted of organics, in primary particles the role of rBC was significant.
The calculated secondary organics concentration was high especially during
CSUDC, even 9.9 mg m-3. This highlights the important role of primary
and secondary emissions followed by the cold start. It should be noted that
the emission factors of both primary and secondary particles were lowest
during the EUDC (see the Supplement).
O : C ratios were relatively stable for primary emissions; slightly higher
O : C ratio (0.27) was observed for the CSUDC. Similar O : C ratios have
been typically observed for fresh traffic emissions in urban ambient
measurements (Timonen et al., 2013; Carbone et al., 2014). For the secondary
emissions, the O : C ratios were between 0.5 and 0.6. Large hydrocarbon
emissions and probably differences in oxidation levels of primary gaseous
compounds at the beginning of the cycle, as well as
differences in oxidant levels in chamber are likely reasons for observed
differences. Previous studies for gasoline vehicles reported high
O : C ratios (up to 0.7) for secondary organic exhaust aerosol
(Suarez-Bertoa et al., 2015; Platt et al., 2013) but also lower ratios of
∼ 0.4 (Nordin et al., 2013).
With all input parameters determined, the OH exposure and VOC fate in the PAM
was calculated based on the Peng et al. (2016) model. Much higher OHR values were
observed followed by the cold start. OHR, on average, for the CSUDC based on
the measured compounds was around 1000 s-1 (Table S2) which is overall
a riskier condition according to Peng et al. (2016). This means that about
30 % of total loss of toluene and benzene is due to photolysis at
185 nm, but for all other measured compounds the non-OH chemistry and
photolysis are minor or very minor (Peng et al., 2016, calculator in the
Supplement). For the HUDC and EUDC OHRs were 15 and 56 s-1,
respectively, indicating very minor photolysis and non-OH chemistry.
The average OH exposure during the CSUDC was approximately
1.2 × 1011 molec. cm-3 s according to the model. This
is about an order of magnitude lower than during SO2 calibration
experiments (1.03 × 1012 molec. cm-3 s, measured from
SO2 concentrations) where OHR was significantly lower, about
2 s-1. This indicates that during the experiment OH exposure varied
roughly in the scale of 1011–1012 molec. cm-3 s (1–8 days
equivalent atmospheric aging) depending on the exhaust pollutant levels.
Conclusions
In this study, we characterized primary particle and gaseous emissions and
secondary particle formation from a Euro 5 emission level direct injection
gasoline vehicle. All the measurements were made in real time with high time
resolution. Measurements were conducted under driving conditions representing
typical urban driving cycles. Our aim was to create a basis for understanding
the links between driving conditions, primary emissions of aerosols and their
precursors and the formation of secondary particulate material. We approached
this issue by using a potential aerosol mass (PAM) chamber enabling the
characterization of secondary emissions in real time, combined with
comprehensive characterization of PM and gaseous compounds.
Our results indicated higher- or similar-level secondary particulate matter
emissions compared to the previous studies (Suarez-Bertoa et al., 2015; Platt
et al., 2013). Compared to primary particle emissions, our study indicated 13
times higher secondary particulate emissions, dominated by organics. The
study of Suarez-Bertoa et al. (2015) indicated 2–4 times higher emissions
for secondary particles, instead, in the study of Platt et al. (2013) SOA
emission was around 9–15 times higher than POA emission for the NEDC cycle.
For reference, the primary particle emissions measured in this study were at
similar levels than in previous studies for modern gasoline vehicles
(Karjalainen et al., 2014).
We observed that during ignition and during the first few minutes of the
test cycle, i.e., when the engine and the catalyst had not reached normal
operation temperatures, the emissions of primary PM and precursor gases were
the largest and therefore a large amount of secondary organic emission was
formed. This was the case even though in the PAM chamber external OH
reactivity was high after the cold start, and photolysis degradation for
some VOCs was partially active. The following similar driving cycle with a
warmed engine produced significantly lower primary and secondary particulate
emissions. This indicates that the adverse effects of traffic are likely to
be largest in city areas where driving distances are typically short, near
houses and workplaces. However, we note that the formation of secondary
particulate matter is a longer-time atmospheric process and thus not
directly linked with human exposure and human health at the site of
emission. Also, it is reasonable to assume that this problem, at least from
the viewpoint of secondary aerosol precursor emissions, is magnified under
cold climatic conditions.
Both primary and secondary emissions were highly dependent on driving
conditions such as speed, acceleration and deceleration profiles. At high
speed (EUDC), both particulate mass and size distribution were different when
compared to low-speed driving (HUDC). In addition, under deceleration
conditions, very small nanoparticles were observed in primary exhaust. These
nanoparticles grew in particle size due to the condensation of highly
oxidized engine origin compounds. These oxidized compounds were formed in our
experiment in the PAM chamber but when forming in the atmosphere they likely
exhibit similar behavior and prefer to condense on the nanoparticles. Thus,
our results indicate that also nanoparticles can contribute to atmospheric
secondary aerosol formation, especially on size distribution of secondary
particles. Due to that, it is clear that current legislation focusing on
larger particles (PM mass or number of particles larger than 23 nm in
diameter) is not optimal from the viewpoint of realistic urban air quality,
since it takes into account only the largest primary particles.
Data availability
The data of this study are available from the authors upon request.
The Supplement related to this article is available online at doi:10.5194/acp-16-8559-2016-supplement.
Acknowledgements
We acknowledge support by Tekes (the Finnish Funding Agency for Technology
and Innovation), Cleen Ltd (MMEA project), the Academy of Finland (Grant
no. 259016), IEA-AMF Annex 44 and the Swedish Research Councils VR and
Formas. Edited by: G. McFiggans
Reviewed by: three anonymous referees
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