ME-2 source apportionment
The ME-2 analysis on the three data sets resulted in a total of nine source
profiles as shown in Fig. (values in Supplement
Tables S1–S3), with the factor time series for each site in Supplement
Figs. S6–S8 (PM10–2.5, PM2.5–1.0 and
PM1.0–0.3, respectively). The coarse fraction yielded the source
factors (notable elements in brackets) brake wear (Cu, Zr, Sb, Ba), other
traffic-related (Fe), resuspended dust (Si, Ca), sea/road salt (Cl), aged sea
salt (Na, Mg) and industrial (Cr, Ni). The intermediate fraction yielded the
same factors except for the industrial, instead yielding an S-rich (S) factor. In the
fine fraction a traffic-related (Fe, Cu, Zr, Sb, Ba) factor was found as well
as resuspended dust, sea/road salt, aged sea salt, reacted Cl (Cl), S-rich
and solid fuel (K, Pb). The other elements (Al, P, Ti, V, Mn, Zn, Br, Sr, Mo,
Sn) are not uniquely emitted by a particular emission source and are
attributed to several factors. It should be noted that the concentrations for
the factor time series reported below reflect only the elements measured by
SR-XRF analysis and not the other constituents associated with the various
source types. In particular the lighter elements (H, C, N, O) are not
included and may in some cases dominate the total mass associated with
a source. The relative contribution to the factors discussed herein are also
relative to the measured elemental mass resolved. Although the analysis below
includes only trace elements, which constitute a minor fraction of the total
mass, the results are important for determining source temporal
characteristics and interpreting trends in bulk particle properties such as
total PM mass.
Brake wear and other traffic-related
Factors related to brake wear were resolved in PM10–2.5 and
PM2.5–1.0 size fractions; the profiles are shown in
Fig. , with time series and diurnal variations in
Fig. . The relative contribution to this factor
is more than 70 % for V, Cu, Zn, Zr, Sn, Sb and Ba in both size
fractions, and more than 70 % for Cr, Ni, Sr and Mo in
PM2.5–1.0. Zn can be emitted both from brake and tyre wear,
indicating that these factors might be a mixture of various wearing processes
. Factors for other traffic-related emissions in these two
size fractions (Figs. and )
are dominated by Fe, with around 86 % of the mass explained by this
element. The fine-fraction analysis retrieved one traffic factor with
a mixture of brake wear and other traffic-related emissions with 84 % of
the mass explained by Fe (relative contributions more than 70 % for Fe,
Cu, Zr, Sb and Ba). This mixed factor is similar to that reported by
and although the ratio of
Fe to other elements is variable between studies. V and Sr are typically not
attributed to traffic factors but rather to industrial or oil combustion
emissions (V) and dust resuspension (Sr) .
However, both elements are found in trace amounts in fuel additives and brake
lining, and showed enhanced Sr and V concentrations
inside a tunnel compared with ambient concentrations outside. In the absence
of other sources, the relative contribution of these elements might dominate
these traffic factors.
Source profiles of ME-2 results on combined data of the MR-NK-DE
sites. The bars (left y axis) represent the average element intensity to
each factor in ng ng-1; circles (right y axis) represent the
fraction of the total predicted concentration for a given element. Data are
given as mean of good solutions ±1 SD from the anchor sensitivity
analysis. Note that not all factors are retrieved in all size fractions. See
Supplement Tables S1–S3 for the values.
For the brake wear and the PM1.0–0.3 traffic factors, the
Cu / Sb ratios of 6.3–7.1 fall within the range of 5.7–8.2 for previous
measurements at MR and NK by and depend on brake pad
compositions and contributions of metals from other sources .
The Cu / Ba ratios of 1.1–1.4 are in good agreement with the median
ratio of 1.2 obtained by .
All the traffic-related factors are strongly influenced by local traffic
emissions with steep MR to NK to DE concentration gradients
(Figs. –).
Concentrations at MR are 3.6–6.8 and 9.9–28 times higher than at NK and DE,
respectively. The diurnal variations show a double maximum during the day
corresponding to rush hours. Most of the mass is emitted in the coarse
fraction, with concentrations at MR being 2.6–3.6 and 7.5 times higher than
in PM2.5–1.0 and PM1.0–0.3, respectively. The time
series correlate well across sizes (Pearson's R 0.67–0.81), indicating
similar emission processes. Both traffic sources are well correlated with
NOx across sites and sizes (Pearson's R 0.53–0.72) as shown in
Fig. for MR (NK and DE in Supplement Fig. S9).
Figure also shows traffic flows at MR of light-
(LDV) and heavy-duty vehicles (HDV) (vehicles <5.2 m long, LDV;
vehicles >5.2 m long, HDV). The diurnal variations are much stronger for
NOx and HDV than for the traffic factors and LDV. The ratios between
values at 08:00 and 02:00 UTC are about 4.1 for the former and 2.0
for the latter, probably caused by more strongly enhanced emissions between
HDV and LDV for NOx (factor of ∼37) relative to brake wear (factor
of ∼10), as identified by . NOx seems
therefore more directly related to HDV numbers, while the traffic factors are
more influenced by total vehicle number.
Time series (left) and diurnal variations (right) of the brake wear
factor at MR, NK and DE for PM10–2.5 and PM2.5–1.0.
Time series show the mean of all good solutions ±1 SD as shaded areas.
Diurnals show the mean of the time series ±1 SD as whiskers, with the
hour being the start of a 2 h sampling period (00:00 UTC
means sampling from 00:00 to 02:00 UTC).
Time series (left) and diurnal variations (right) of the other
traffic-related factor at MR, NK and DE for PM10–2.5,
PM2.5–1.0 and PM1.0–0.3. Time series show the mean
of all good solutions ±1 SD as shaded areas. Diurnals show the mean of
the time series ±1 SD as whiskers, with the hour being the start of
a 2 h sampling period (00:00 UTC means sampling from 00:00 to
02:00 UTC).
Resuspended dust
Resuspended dust factors were resolved in all size fractions; the profiles
are shown in Fig. , with time series and diurnal
variations in Fig. . The source profiles are very
similar across sizes and the mass is dominated by Si, Ca and Fe, consistent
with the upper continental crust composition and previous
source apportionment studies .
The scaled residuals (eij/σij) ratios exceed ±3 for Na, Si
and Ca (coarse); Na, Al, Si and Ca (intermediate); and Al and Si (fine) and/or
are skewed at the sites relative to each other. This spread in the scaled
residuals for these dust-related elements may indicate different dust
profiles across sites, especially at DE relative to the city sites. This is
potentially caused by varying dust compositions or emission processes.
Resuspension in the city is dominated by road dust influenced by
anthropogenic activities and by other dust-generating activities, such as
construction works, in contrast to influences from natural soils at DE. This
is in line with , where city-specific soil profiles are
constrained in the ME-2 analysis on data of combined cities, and with
, where ME-2 yielded a road dust resuspension distinct from
a mineral dust factor. In the current study, increasing p yielded factors
with high relative intensities of Ca and of Al and Si. However,
Q/Qexp and structures in eij/σij remain unaffected,
indicating that temporal co-variance and emission source strengths of these
elements are too similar across sites for the model to retrieve more than one
dust factor.
Diurnal variations in the brake wear (PM10–2.5 –
coarse, PM2.5–1.0 – intermediate) and other traffic-related (coarse,
intermediate, PM1.0–0.3 – fine) factors at MR compared to diurnal
variations of NOx (left) and traffic flow (right). Hour of day is start
of a 2 h sampling period (00:00 UTC means sampling from 00:00
to 02:00 UTC). Note the scaling applied to several tracers.
Time series (left) and diurnal variations (right) of the resuspended
dust factor at MR, NK and DE for PM10–2.5,
PM2.5–1.0 and PM1.0–0.3. Time series show the mean
of all good solutions ±1 SD as shaded areas. Diurnals show the mean of
the time series ±1 SD as whiskers, with the hour being the start of
a 2 h sampling period (00:00 UTC means sampling from 00:00 to
02:00 UTC).
Similar to the factor termed “traffic-related”, dust is mainly emitted in
PM10–2.5 with up to 13.6 times higher concentrations than in the
smaller fractions. The factor time series (Fig. )
indicate enrichment at MR relative to NK and DE, especially for the coarse
fraction (MR / NK ratio of 3.4 and MR / DE of 7.8) and are well
correlated among all sizes (Pearson's R 0.62–0.78). The diurnal variations
show strong daytime maxima, most likely from anthropogenic activities (mainly
traffic) throughout the day. The increase at 08:00 UTC (sampling
08:00–10:00 UTC) occurs 2 h after increasing traffic numbers,
NOx and traffic-related source emissions
(Fig. ). The delay is probably caused by
a combination of two effects. On the one hand, the RH still increases during
morning hours, resulting in wetter road surfaces than later in the day
(Supplement Fig. S10). On the other hand, increasing traffic flows induce
increased wind movements in the street canyon, resulting in enhanced particle
resuspension .
Sea/road salt, aged sea salt and reacted Cl
Sea/road salt and aged sea salt were resolved in all sizes;
Fig. shows the profiles, with time series and diurnal
variations in
Figs. –. The mass
of sea/road salt comes almost exclusively from Na and Cl, whereas aged sea
salt is largely driven by Na. The crustal component of Na is less than
1 % in this study, based on the Na / Si ratio found in the upper
continental crust . Therefore, the combination of Na with
relative contributions of more than 50 % for coarse Mg, S and K, but
depleted Cl supports aged particles with a sea salt origin, in which the Na
is neutralized by compounds not resolved by our analysis (e.g. nitrate). The
Mg / Na mass ratio of the sea/road salt factor is only 0.054 in
PM10–2.5 (theoretical sea salt ratio is 0.12;
). De-icing salt was applied on the roads in London
during the measurement campaign, and this salt is typically composed of
coarse NaCl, resulting in enriched coarse Na relative to Mg concentrations
after the particles are resuspended in the air. The low concentrations of
fine sea salt are in line with , since sea salt is mainly
emitted as particles with d>1.0 µm.
Time series (left) and diurnal variations (right) of the sea/road
salt factor at MR, NK and DE for PM10–2.5,
PM2.5–1.0 and PM1.0–0.3. Time series show the mean
of all good solutions ±1 SD as shaded areas. Diurnals show the mean of
the time series ±1 SD as whiskers, with the hour being the start of
a 2 h sampling period (00:00 UTC means sampling from 00:00 to
02:00 UTC).
Time series (left) and diurnal variations (right) of the aged sea
salt factor at MR, NK and DE for PM10–2.5,
PM2.5–1.0 and PM1.0–0.3. Time series show the mean
of all good solutions ±1 SD as shaded areas. Diurnals show the mean of
the time series ±1 SD as whiskers, with the hour being the start of
a 2 h sampling period (00:00 UTC means sampling from 00:00 to
02:00 UTC).
The data suggest that a fraction of the aged sea salt is directly
transported from the sea, while part comes from resuspended sea salt
particles after deposition on roads. Direct transport is indicated by the
diurnal variations
(Figs. –), which
have no obvious pattern – peaks occur at different hours of the day
throughout the entire time series, whereas resuspension would likely peak
during the day with vehicle use. Additional support is provided by NAME
dispersion modelling and wind direction analyses, which indicate that high
concentration episodes in the aged sea salt factor coincide with air masses
from the sea. The sea salt concentrations also increase with increasing wind
speed, consistent with other Na observations in the UK (Supplement Fig. S11;
). However, the PM10–2.5 concentrations of
the aged sea salt factor are enhanced by a factor of 1.3 and 2.2 at the
kerbside (MR) site relative to the urban background (NK) and rural (DE)
sites, respectively. This suggests that aged sea salt concentrations are also
significantly modulated by human activity in the form of resuspension.
Time series (left) and diurnal variations (right) of the reacted Cl
factor at MR, NK and DE for PM1.0–0.3. Time series show the mean
of all good solutions ±1 SD as shaded areas. Diurnals show the mean of
the time series ±1 SD as whiskers, with the hour being the start of
a 2 h sampling period (00:00 UTC means sampling from 00:00 to
02:00 UTC).
Time series (left) and diurnal variations (right) of the S-rich
factor at MR, NK and DE for PM2.5–1.0 and
PM1.0–0.3. Time series show the mean of all good solutions ±1 SD as shaded areas. Diurnals show the mean of the time series ±1 SD
as whiskers, with the hour being the start of a 2 h sampling period
(00:00 UTC means sampling from 00:00 to 02:00 UTC).
Reacted Cl is unique to PM1.0–0.3 (profile in
Fig. ) and is mainly driven by an event at MR and NK
lasting from 16:00 UTC on 5 February to 04:00 UTC on 7 February 2012 (time
series and diurnal variations in Fig. ; around
12 February concentrations at MR are high as well, but SR-XRF data at NK and
meteorological data at BT Tower are absent during this period, making it
impossible to study this episode in detail). Stagnant conditions prevailed in
the city with low average wind speed of 2.1 ms-1 at about
190 ma.g.l. (data from BT Tower). The NAME 24 h backwards
footprints show that the air sampled at MR and NK was dominated by local
London air. In contrast, during this episode the air mass at DE is dominated
by a mixture of London air and air from the southern UK. Although fine Cl can be
emitted by combustion sources such as waste incineration
and coal combustion , this factor does not correlate with
combustion-related species such as K, Zn, Pb and SO2. The event
discussed above does correlate with a strong peak in coarse-mode aged sea
salt (Figs. –). Sea
salt particles in all size fractions have likely reacted with nitric acid
(HNO3), forming hydrochloric acid (HCl). Due to stagnant conditions,
follow-up reactions between HCl and ammonia (NH3) could have taken
place, forming ammonium chloride (NH4Cl). These particles occur
mainly in the fine mode due to the highest surface-to-volume ratios.
NO3- and NH3 concentrations were high during this
event, favouring such reactions. AMS measurements also show this unique
Cl- episode at MR and NK (Cl- is negligible during the
rest of the IOP and at DE). For this specific period the AMS aerosol charge
balance in the city holds when Cl- is included, while this ion is
not needed at DE or during the rest of the time to balance NH4+
within the uncertainties of the measurements, indicating the presence of fine
NH4Cl particles.
Time series (left) and diurnal variations (right) of the solid fuel
factor at MR, NK and DE for PM1.0–0.3. Time series show the mean
of all good solutions ±1 SD as shaded areas. Diurnals show the mean of
the time series ±1 SD as whiskers, with the hour being the start of
a 2 h sampling period (00:00 UTC means sampling from 00:00 to
02:00 UTC).
Time series of the solid fuel factor at NK and DE compared to the
Aethalometer wood burning absorption coefficient at wavelength 470 nm
(babs,wb at 470 nm) and to the solid fuel organic
aerosol (SFOA) factors resolved with AMS-PMF.
S-rich and solid fuel
The S-rich factor, mainly composed of S, was resolved in
PM1.0–0.3; the profile is shown in Fig. ,
with time series and diurnal variations in Fig. .
This factor likely corresponds to secondary sulfates, consistent with the
results of many previous source apportionment studies
. All sites show similar
concentrations without any patterns visible in the diurnal variations,
consistent with regional sources. This factor correlates well with AMS
SO42- measurements (Pearson's R 0.61–0.86) and is elevated
with air masses from the European mainland, mainly occurring during the
second half of the campaign (Supplement Fig. S12).
The solid fuel factor was also resolved in the fine fraction (profile in
Fig. , time series and diurnal variations in
Fig. ). The mass of this factor is dominated by S
and K, while the relative contributions to this factor are more than 60 %
for K, Zn and Pb. Surprisingly, the time series are very similar at all sites
and are likely influenced by relatively fresh emissions from many point
sources surrounding the measurement stations, including wood, coal and peat
emissions in varying contributions . The
S / K ratio of 1.5 is well within the observed range of 0.5–8 for fresh
to transported and aged emissions
. The solid fuel source is
compared to particle light absorption data by Aethalometer measurements
(babs,wb in m-1; not available at MR) and solid fuel factors resolved by AMS-PMF on organic aerosol data
. The time series of the various
solid fuel tracers are very similar, especially for the light-absorbing
particles and organic aerosol as shown for NK and DE in
Fig. (tracers at MR are similar to NK). The
different correlations seen in this figure are caused by the sampling of air
containing various burning stages of solid fuel burning, emitting K and other
species in different ratios.
In the intermediate fraction S contributes around 58 % to the mass of the
S-rich factor (profile in Fig. , time series and diurnal
variations in Fig. ) and the relative contributions
of S, Br and Pb are >50 % in this factor. showed
that S is predominantly found in PM1, but particles of up to
several micron were identified to contain S as well. The intermediate
S-rich factor contains signatures of both fine-fraction S-rich and solid fuel
with similar concentrations at all sites and no obvious diurnal patterns.
Industrial
Constrained ME-2 analysis in the PM10–2.5 fraction on data
across sites revealed large residuals with clear structures at DE for Cr, Ni
and Mo, indicating that the data at the rural site were not fully explained.
The “ME2_seg_low_SNR” analysis on DE PM10–2.5 (see
Fig. and Supplement Fig. S5) successfully yielded
a factor, potentially industrial, containing mainly these three elements
without significant residuals.
Figure shows the source profile and
Fig. the time series and diurnal variations.
This source is mainly found at DE and consists of 70 % of Cr and Ni. The
time series at MR and NK show only a few single peaks and can therefore not
be attributed to this particular source. The spiky time series at DE are
typical indications for influences of one or several point sources close to
this rural site. These sources are possibly found in the southwest as concentrations
were elevated under these conditions (Supplement Fig. S13). The towns of
Detling and Maidstone are located towards the southwest of the Kent Showgrounds.
studied Cr, Ni and Mo in Sweden and found that road
traffic including road wear is the largest emitter of these elements,
followed by industries, incineration, agriculture and waste water treatment.
identified Pb, Ni and Cr in emissions from municipal
wastewater sludge incinerators. Except for agricultural fields, none of those
activities likely contribute to the emission source at DE. Probably some
local activities at the Kent Showgrounds or small-scale industry in Maidstone
like stainless steel production contributes to
this factor.
Time series (left) and diurnal variations (right) of the industrial
factor at MR, NK and DE for PM10–2.5. Time series show the mean
of all good solutions ±1 SD as shaded areas. Diurnals show the mean of
the time series ±1 SD as whiskers, with the hour being the start of
a 2 h sampling period (00:00 UTC means sampling from 00:00 to
02:00 UTC).
Synthesis
The trace element source apportionment results indicate the ability to
characterize the environment-dependent variability of emissions in and around
London. The analyses of data from the combined sites retrieve a single source
profile representative of all three sites, thus allowing a direct comparison
of the source strengths across sites. Source strengths strongly differ
between sites and sizes, as seen in Fig. . Most of
the analysed element mass is emitted in PM10–2.5 with 78 %
at MR, 73 % at NK and 65 % at DE, while only 17–22 % and
6–13 % is emitted in PM2.5–1.0 and PM1.0–0.3,
respectively.
The separate analyses on the three size fractions provide insights into the
emissions of sources to specific size fractions
(Fig. ). The regionally influenced S-rich and solid fuel factors are restricted to the smaller size fractions with concentration
ratios of 1.0–1.8 between sites roughly 50 km apart. These factors,
especially solid fuel, are affected by many anthropogenic point sources and
are influenced by emissions not only in and around London but also from
elsewhere in the UK and northern Europe. In contrast to other sources, solid
fuel is expected to be more prevalent in more rural parts of the UK than in
the smoke-controlled inner city areas. The industrial factor is restricted to
PM10–2.5 and affects the air quality under specific
meteorological conditions around the rural site, which is generally a region
characterized by much lower pollution.
The other sources, except reacted Cl, emit elements in all three size
fractions. London's city centre is a hotspot of anthropogenic activities,
resulting in high pollution levels of locally influenced sources directly
related to population density. Brake wear, other traffic-related and
resuspended dust factor concentrations are drastically different within
different micro-environments and size fractions, indicating major
heterogeneity in human exposure patterns. Concentrations at the kerbside are
up to 7 and 28 times higher than at NK and DE, respectively, and
PM10–2.5 concentrations are up to 4 and 14 times higher than
PM2.5–1.0 and PM1.0–0.3, respectively. During this
winter period the sea salt sources, although from natural origin and strongly
meteorologically driven, are enriched in the city in the form of sea salt
resuspension from the roads.
Both direct emissions and resuspension have been identified above as
important sources of trace elements. The trend in coarse aged sea salt across
the three sites provides insight into the relative importance of these
processes. We assume that all aged sea salt originates from a regional,
site-independent source, and that the concentration gradient in this factor
between sites thus reflects the effect of local resuspension processes of
naturally deposited aged sea salt. Although sea salt emissions are typically
considered a natural process, human activities (vehicle-induced resuspension)
enhance the concentrations of the coarse aged sea salt by 1.7–2.2 in the
city relative to the rural site (Fig. ). These
ratios provide an upper limit for the resuspension enhancement (and thus
a lower limit for the enhancement due to direct emissions) for the
anthropogenically influenced factors, whose concentrations at DE may already
be increased by local emissions. The lower limits for direct emission
enhancement ratios in the coarse fraction at MR relative to DE are 3.5 to
12.7 for brake wear, other traffic-related, dust and sea/road salt factors
(1.4–5.5 for NK / DE). Direct emissions for the traffic-related factor
show similar enhancement in all size fractions, whereas enhancement of the
other anthropogenically influenced factors are a factor of 1.5–3.0 lower in
the smaller size fractions. These results indicate that direct source
emission processes occur mainly for coarse particles and are dependent on the
micro-environment. The S-rich and solid fuel factors have negligible
resuspension influences (similar concentrations across sites). Air quality in
London can be improved by the development of policies aiming to reduce
resuspension processes.
Mean, median and 25–75th percentile concentrations of the nine
different ME-2 factor time series at MR, NK and DE for PM10–2.5,
PM2.5–1.0 and PM1.0–0.3. Note that not all factors
are retrieved in all size fractions.
Trace elements are often used as chemically conserved source markers. Here we
assess the ability of elements measured herein to serve as unique tracers for
specific sources. For a tracer to be considered good, we require that a given
source has a high relative contribution (>70 %) to a specific element,
i.e. that the element is mainly attributed to a single source
(Fig. ). We suggest Cu, Zr, Sb or Ba as markers for
brake wear in PM10–2.5 and PM2.5–1.0. The relative
contributions are >93, 83, 93 and 96 % for Cu, Zr, Sb and Ba,
respectively. The attribution of these elements to the traffic factor in
PM1.0–0.3 with relative contributions between 69 and 84 %
also suggests brake wear emissions in this size fraction. Fe is typically
also attributed to brake wear emissions
. However, we observed no Fe
in the brake wear factors; instead 86 and 65 % of Fe were attributed to
other traffic-related processes in PM10–2.5 and
PM2.5–1.0 (74 % of Fe to the traffic-related factor in
PM1.0–0.3). Furthermore, around 19 % of Fe contributed to
the resuspended dust factors in all three size fractions. We therefore
recommend attributing Fe only to a specific source in combination with other
markers. Si and Ca in all size fractions can be used as a surrogate for
resuspended dust with relative contributions between 72 and 75 % for Si
and between 80 and 85 % for Ca. Coarse and intermediate
fraction Cl (relative contributions >87 %) are markers for fresh sea
salt (preferably combined with Na and Mg), while fine-fraction Cl is not
a unique source indicator. Depending on the data set it can indicate waste
incineration , coal combustion or reacted
Cl as NH4Cl particles (current study, relative contribution
59 %). A combination of fine-fraction K and Pb with relative
contributions of around 80 % indicates solid fuel in this study, but can
also be attributed to wood, coal or peat burning separately. Fine-fraction S
can typically be attributed to regionally transported secondary sulfate
(here only a 65 % relative contribution). Other elements can also be used
as source markers, but rather as a combination of elements than individually,
and preferably combined with measurements of other species.
The analysis herein clearly shows the advantages of rotationally controlled
analyses relative to an unconstrained PMF solution. Supplement Figs. S1–S4
show the best solutions retrieved from unconstrained analyses for the
separate size fractions (four-, four-, and five-factor solutions for
PM10–2.5, PM2.5–1.0, and PM1.0–0.3,
respectively). The unconstrained PM10–2.5 solution (Supplement
Figs. S1 and S4) yields high residuals of Ni, Cr, and Mo and does not resolve
a brake wear factor. The unconstrained PM2.5–1.0 solution
(Supplement Figs. S2 and S4) likewise does not yield brake wear and
additionally fails to resolve aged (reacted) sea salt from regionally
transported sulfate and solid fuel, despite strong evidence for this
processing in the raw time series. Finally, the unconstrained
PM1.0–0.3 solution (Supplement Figs. S3 and S4) mixes secondary
sulfur and solid fuel sources. It also fails to explain major events
contained in the Cl-rich factor, apportioning significant Na to these events,
leading to high Na residuals. Higher-order solutions do not resolve these
problems, instead leading to uninterpretable splitting of the dust factor,
factors consisting only of single elements, and unstable solutions that are
highly dependent on algorithm initialization (seed).