Naturally and anthropogenically emitted aerosols, which are determined by
their physical and chemical properties, have an impact on both air quality
and the radiative properties of the earth. An important source of
atmospheric particulate matter (PM) in South Africa is household combustion
for space heating and cooking, which predominantly occurs in low-income
urban settlements. The aim of this study was to conduct a detailed
size-resolved assessment of chemical characteristics of aerosols associated
with household combustion through the collection of particulates in
low-income urban settlements in South Africa to quantify the extent
of the impacts of atmospheric pollution. Outdoor (ambient) and indoor
aerosols in different size fractions were collected during summer and winter
in four low-income urban settlements located in the north-eastern interior
on the South African Highveld, i.e. Kwadela, Kwazamokuhle, Zamdela, and
Jouberton. Mass concentration and chemical composition was determined
for three size fractions, namely, PM1, PM2.5, and PM2.5-10.
The highest concentrations of particulates were measured indoors with the
highest mass concentration determined in the indoor PM2.5-10 (coarse)
size fraction. However, the highest mass concentrations were determined in
PM1 in all outdoor aerosol samples collected during winter and summer,
and in indoor samples collected during summer.
Significantly higher concentrations were determined for SO4-2 in
outdoor and indoor particulates compared to other ionic species, with
NH4+ and NO3- being the second most abundant.
SO4-2 and NH4+ almost exclusively occurred in the
PM1 size fraction, while NO3- was the major constituent in
the larger size fractions. The highest SO4-2 levels were recorded
for the winter and summer outdoor campaigns conducted at Zamdela, while
NO3- and NH4+ concentrations were higher during the
winter outdoor campaign. The combined concentrations of trace elements were
higher for indoor particulates compared to outdoor aerosols, while the total
trace element concentrations in PM1 were substantially higher than
levels thereof in the two larger size fractions of particulates collected
during all sampling campaigns.
No distinct seasonal trend was observed for the concentrations of trace
elements. Na, Ca, and Cr had the highest concentrations in particulates
collected during outdoor and indoor sampling campaigns. Ni concentrations in
outdoor and indoor aerosols exceeded the annual average European standard.
PM1 collected during all sampling campaigns in low-income urban
settlements had the highest organic carbon (OC) and elemental carbon (EC)
concentrations. The highest OC and EC levels were determined in PM1 collected during the winter indoor campaign. OC and EC concentrations were
highest during winter, which can be attributed to changes in meteorological
patterns and increased household combustion during winter. Low OC/EC ratios
determined for particulates collected in low-income urban settlements are
indicative of OC and EC being mainly associated with local sources of these
species. OC concentrations determined in this study were an order of
magnitude lower than OC concentrations determined for ambient aerosols
collected in the north-eastern interior of South Africa, while similar EC
levels were measured. According to estimated dust concentrations, it was
indicated that dust is the major constituent in all size ranges of
particulates collected in this study, while trace elements were the second
most abundant. However, trace elements made the highest contribution to
indoor PM1 and PM1-2.5 mass. Mass concentrations and chemical
concentrations determined for aerosols collected in low-income settlements
reflect the regional impacts of anthropogenic sources in the north-eastern
interior of South Africa and the influence of local sources.
Introduction
Atmospheric aerosols or particulate matter (PM) are either emitted into the
atmosphere directly as primary aerosols by anthropogenic activities (e.g.
incomplete combustion of fossil fuels, vehicular traffic, industrial
processes, and household combustion) and natural (e.g. volcanic eruptions,
sea salts, and wind-blown dust) sources, or form in the atmosphere as
secondary aerosols (Pöschl, 2005). The environmental impacts of
atmospheric aerosols are mainly related to climate change and air quality,
which include direct and indirect effects on cooling/warming of the
atmosphere and adverse influences on human health, especially
related to respiratory diseases (Guinot et al., 2007).
The impacts of atmospheric PM on health and radiative forcing are determined
by their physical (e.g. size, mass, optical density) and chemical
properties. Larger particles can, for instance, be filtered in the nose and
throat, while smaller particles can penetrate through the gas exchange
sections of the lungs and affect other organs (Pope et al., 2002). In
addition, the chemical composition of aerosols can influence radiative
forcing, since lighter coloured aerosols (e.g. sulfate, SO42-)
reflect incoming solar radiation causing net cooling of the atmosphere,
while darker absorbing particulates (e.g. black carbon) contribute to
warming of the atmosphere. PM is typically classified according to size
fractions, which include course (aerodynamic diameter 2.5–10 µm,
PM10-2.5), fine (aerodynamic diameter 1–2.5 µm, ≤ PM2.5-1), and ultrafine particulates (aerodynamic diameter <1µm, PM1) (Venter et al., 2017; Pope and Dockery, 2006; Seinfeld and Pandis, 2006). Atmospheric aerosols comprise numerous organic and
inorganic compounds, which also influence their physical characteristics.
Many studies have been conducted to chemically characterise atmospheric
aerosols from various sources in order to reduce uncertainties associated
with their impacts (Sciare et al., 2005; Kulmala et al., 2011).
Inorganic species in PM include trace elements and inorganic ions, while
organic species are generally categorised into organic and elemental
carbon (OC and EC, respectively). The major inorganic ionic species
generally considered include SO42-, nitrate (NO3-),
ammonium (NH4+), sodium (Na+), potassium (K+), chloride
(Cl-), calcium (Ca2+), magnesium (Mg2+), and fluoride
(F-) (Venter et al., 2017; Ibrahim and Habbani, 2013; Pöschl,
2005). These inorganic ions in atmospheric PM have a significant influence
on the acidity potential of the atmosphere, which will also have an impact
on ecological systems through wet and dry deposition (Conradie et al.,
2016). Atmospheric aerosols comprise various trace elements, which include
sodium (Na), silicon (Si), magnesium (Mg), aluminium (Al), potassium (K),
calcium (Ca), titanium (Ti), chromium (Cr), manganese (Mn), iron (Fe),
arsenic (As), barium (Ba), cadmium (Cd), copper (Cu), nickel (Ni), zinc
(Zn), vanadium (V), molybdenum (Mo), mercury (Hg), and lead (Pb) (Adgate et
al., 2007; Pacyna, 1998). Atmospheric PM also comprises a large number of
organic compounds (Goldstein and Galbally, 2007), which are generally
reported as a collective due to the complexities associated with identifying
individual organic compounds (Chiloane et al., 2017; Maritz et al., 2019;
Booyens et al., 2015). A detailed chemical characterisation of atmospheric
aerosols allows for chemical mass closure, which is an important tool in
establishing major sources and impacts of these species, as well as chemical
transformation processes involved in local, regional, and global scales
(Guinot et al., 2007; Sciare et al., 2005).
South Africa has one of the largest industrialised economies in Africa with
significant industrial, mining, and agricultural activities (Josipovic et
al., 2019), while being regarded a significant source region of atmospheric
pollutants (Venter et al., 2017). In addition, coal-fired power stations
produce >90 % of the electricity in South Africa, while
seasonal open biomass burning (wildfires) also has a large impact on air
quality in this region (Vakkari et al., 2014). An important source of
atmospheric pollutants in South Africa revealed through various studies is
household combustion for space heating and cooking, predominantly occurring
in low-income urban settlements (e.g. Venter et al., 2012; Chiloane et al.,
2017; Maritz et al., 2019; Laban et al., 2018). Most households in these
settlements use low-grade fuels, such as coal or wood to meet their energy
demands (Adesina et al., 2020; Xulu et al., 2020). These practices
contribute significantly to emissions of atmospheric pollutants on a local
and regional scale, while serious health risks associated with indoor and
outdoor exposure are posed for people within these communities (Language et
al., 2016; Xulu et al., 2020). Several studies have shown that indoor air
pollution often dominates human exposure in these settlements to atmospheric
pollutants, since health effects are not only determined by air pollution
levels, but also by the extent of exposure, i.e. the time spent within close
proximity of polluted air (Bruce et al., 2000).
In addition to household combustion, waste burning within these settlements
also contributes to poor ambient air quality in these low-income communities
(Language et al., 2016).
In this study, an assessment of the chemical characteristics of aerosol
species in different size fractions, namely, (PM1, PM1-2.5,
PM2.5-10) in low-income urban settlements in South Africa, is conducted.
The concentrations of particulate inorganic ions, trace elements, and
OC and EC were determined to better understand the importance of
the sources contributing to the various chemical species in these
settlements.
ExperimentSite descriptions
Aerosol samples were collected at four low-income urban settlements located
in the north-eastern interior on the South African Highveld, i.e. Kwadela (26.463200∘ S–29.663124∘ E), Kwazamokuhle (26.138252∘ S, 29.738953∘ E), Zamdela
(26.8373100∘ S, 27.843500∘ E), and Jouberton (26.906231∘ S, 26.584010∘ E) as indicated in Fig. 1. This is the largest industrialised area in South
Africa, with this region holding several pyrometallurgical industries,
mines, coal dumps, two large petrochemical plants, and a cluster of
coal-fired power stations (11 of 13 South African coal-fired power stations
are located in this region) (Laban et al., 2018). In addition, this area is
also influenced by large-scale seasonal open biomass burning (wildfires)
during the dry season (Vakkari et al., 2014), while household combustion is
also an important source of atmospheric pollutants in this relatively
densely populated area (Chiloane et al., 2017; Laban et al., 2018).
Measurements at Kwadela, Kwazamokuhle, and Zamdela were conducted within the
framework of the air quality offset programme, a legal measure
introduced by the South African government whereby industries receive
leniency for complying with emission standards by reducing ambient
pollution levels through interventions in low-income urban settlements
(Langerman et al., 2018). Aerosols sampled at Jouberton were part of the
Prospective Household cohort study of Influenza, Respiratory Syncytial virus
and other respiratory pathogens community burden and Transmission dynamics
in South Africa (PHIRST) (NICD, 2018).
Map of South Africa indicating the location of the four low-income
urban settlements and major large point sources within the north-eastern
interior.
The South African Highveld is characterised by a distinct dry and wet season,
with the dry season typically occurring from mid-May to mid-October which
coincides with the South African winter from June to August. More pronounced
inversion layers and increased anticyclonic recirculation of air masses
during winter trap pollutants near the surface causing, in conjunction with
reduced wet scavenging, pollution build-up over this region during this
period (Tyson and Preston-Whyte, 2000). In addition, the winter months are
also characterised by increased household combustion for space heating and
cooking, while seasonal open biomass burning generally occurs in the period
from August to October, typically peaking during spring in September (Laban
et al., 2018). Furthermore, the removal rate of atmospheric pollutants
associated with precipitation is also reduced during the dry season (Venter
et al., 2018).
Kwadela is situated in the Mpumalanga Province, between the towns Ermelo and
Bethal, approximately 180 km east-south-east of the Johannesburg–Pretoria
conurbation (Fig. 1). In addition to being influenced by regional air
pollution, this low-income settlement is also exposed to traffic emissions
from the nearby (∼500 m) N17 national highway. Kwazamokuhle
is located near the town Hendrina in the Mpumalanga Province, approximately
150 km east of the Johannesburg–Pretoria conurbation (Fig. 1). This
low-income settlement is located within close proximity of three large coal-fired
power stations, i.e. the Arnot, Komati, and Hendrina power stations, as indicated
in Fig. 1. Zamdela is situated on the south banks of the Vaal River in close
proximity to the town Sasolburg in the Free State Province, in the densely
populated and highly industrialised Vaal Triangle region (Fig. 1). Sources
within this region include a large petrochemical plant, a coal-fired power
station, and a number of pyrometallurgical smelters (Conradie et al., 2016).
Jouberton is a low-cost urban settlement near the town of Klerksdorp in the
North West Province, as indicated in Fig. 1 (approximately 180 km
south-west of the Johannesburg–Pretoria conurbation). The main anthropogenic
activities in this region of South Africa are related to large mining
industries and agriculture, while this area is also impacted by regional air
pollution associated with the north-eastern interior, as indicated by several
studies at the Welgegund atmospheric monitoring site approximately 80 km
east of Klerksdorp (e.g. Booyens et al., 2014; Venter et al., 2017).
Sample collection
All aerosol samples in this study were collected using a set of three
five-stage Sioutas Cascade Impactors (Josipovic et al., 2019), each connected
to a pump and running in parallel at a flow rate of 9 L min-1. These impactors
allowed for the collection of PM in the 2.5–10, 1.0–2.5, 0.50–1.0, 0.25–0.50, and <0.25µm aerodynamic diameter size ranges. One impactor was equipped
with Teflon filters for the determination of inorganic ions, water-soluble
organic acids, and trace elements, the second impactor with quartz filters
for OC and EC analysis, and the third impactor was loaded with Nuclepore
filters for the health tests. The third was beyond the scope of this paper
and is not discussed further. In each impactor, 25 mm filters and 37 mm back filters were used. Seventy-two h outdoor (ambient) aerosol samples were collected
during two-week periods, while 24 h indoor PM samples were collected for
a duration of seven days. These sampling times were chosen in order to
collect sufficient amounts of PM for chemical analysis. Filters were placed
in petri dishes after sampling, which were sealed and stored in a freezer
until they were analysed. A five-decimal Mettler Toledo microbalance was
used to weigh filters prior to and after sampling.
Outdoor aerosol samples collected during the three summer campaigns allowed
for a spatial assessment of outdoor aerosol characteristics associated with
low-income urban settlements located in the north-eastern interior of South
Africa, while the one winter campaign at Zamdela was considered indicative
of temporal variability associated with outdoor aerosols in these
settlements. Indoor measurements conducted at Jouberton through a summer and
winter campaign allowed for comparison between outdoor and indoor aerosol
characteristics. In spite of the above-mentioned challenges associated with
sampling in low-income settlements in South Africa, the results presented in
this paper can be considered a good representation of the chemical composition
of aerosols in these settlements.
At Kwadela, outdoor aerosol measurements were conducted at Kwadela Primary
School from 30 March to 14 April 2015. Outdoor aerosol samples were
collected inside the churchyard at Kwazamokuhle (the same site where compliance
air quality monitoring is being conducted) from 23 February until 7 March
2016. Measurements at Zamdela were conducted at the Theha Setjhaba primary
school. The summer sampling campaign at Zamdela was conducted from 9 to 23
March 2017, while the winter campaign occurred from 15 to 30 July 2016. The
summer and winter indoor sampling campaigns at Jouberton were performed at
three houses from 18 April to 19 May 2016 and 1 to 16 August
2016, respectively. Although these three houses were electrified, paraffin
was also burned as an alternative source of energy. Sampling was only
conducted at two of the three houses during the winter indoor campaign due
to logistical restraints. In addition, instrument failure contributed to one
of the Sioutas not being available for sampling during the winter sampling
campaign at Jouberton. It was decided to use the two available Sioutas to
collect PM samples for OC and EC analysis, as well as the health tests
during this campaign. These summer sampling periods can be considered
representative of summer since a recent study indicated that October to
March can be classified as summer months in South Africa (Van der Walt and
Fitchett, 2020).
In total, 134 aerosol samples were collected for this study, which included
43 outdoor samples at Kwadela (9), Kwazamokuhle (12), and Zamdela (24), while
91 indoor samples were collected at Jouberton.
Chemical analysesInorganic ions and water-soluble organic acids
Similar to the method described by Van Zyl et al. (2014) and Venter et al. (2014, 2017), sampled Teflon filters were divided into
two halves by a specially designed punch to allow for the analyses of trace
elements, inorganic ions, and water-soluble organic acids.
Inorganic ions and water-soluble organic acids in the collected PM samples
were extracted with 5 or 10 mL (depending on sample load) deionised water
(resistivity ≈18.2MΩ) in an ultrasonic bath for 30 min.
The extracted aqueous samples were then analysed by suppressed conductivity
with a Dionex ICS 3000 ion chromatograph (IC), with an IonPac AS18 (2 mm × 50 mm) analytical column, and an IonPac AG18 (2 mm × 50 mm) guard column.
Inorganic ionic species determined include SO42-, NO3-,
Cl-, F-, Na+, NH4+, K+, Mg2+, and Ca2+, while water-soluble organic acids
(OA) include formic (COO-), acetic (CH3COO-), propionic
(C2H5COO-), and oxalic acid (C2O42-). Standard
stock solutions for each ionic species analysed were obtained from
Industrial Analytical. The detection limits (DLs) of each of these species
are presented in Table 1 below.
DLs (ppb) of inorganic ions and water-soluble organic acids
determined in this study.
SO42-NO3-Cl-F-Na+NH4+K+Mg2+Ca2+5.69952.58117.45610.75033.58420.12827.24421.04718.718COO-CH3COO-C2H5COO-C2O42-18.20228.14715.7317.242Trace elements
The other half of the sampled Teflon filter was subjected to hot acid
leaching (Mouli et al., 2006), which entailed placing the filter in a 100 mL
Erlenmeyer flask with 20 mL concentrated HNO3 and 40 mL deionised
water. The mixture was boiled for 5 min and then refluxed for 3 h
after the addition of 5 mL concentrated HCl. The extract was cooled and then
diluted in 100 mL deionised water for subsequent analysis with an Agilent
7500c inductively coupled plasma mass spectrometer (ICP-MS). In total, 35
trace elements could be detected, which included Be, B, Na, Mg, Al, P, K,
Ca, Ti, V, Cr, Mn, Fe, Cu, Co, Ni, Zn, As, Se, Rb, Sr, Mo, Pd, Ag, Cd, Sb,
Ba, Pt, Au, Hg, Tl, Pb, Bi, Th, and U. Trace element concentrations below the
DL of the ICP-MS (DLs listed in Table 2) were considered to have
concentrations of half the detection limit of the species considered, which
is a precautionary assumption that is commonly used in health-related
environmental studies (e.g. Van Zyl et al., 2014). Be and Tl levels were
below the detection limit of the analytical technique in all three size
fractions for particulate samples collected during all sampling campaigns,
while concentrations of Cd, Sb, Ba, Cu, As, Se, Rb, Sr, Mo, Pd, Ag, Pb, Au,
Hg, Ti, Co, Pt, Bi, Th, and U were very low and below the detection limit in
75 % or more of the collected samples. Similar to inorganic ions and
water-soluble OAs, trace element concentrations could also not be determined
during the winter indoor campaign.
DLs (ppb × 10-2) of trace elements determined in this study.
OC and EC concentrations were determined from aerosols collected pre-fired
on quartz filters with a two-step thermal procedure developed by Cachier
et al. (1989) at the Laboratoire d'Aerologie. This procedure entailed
halving the filters with one part of the filter heated in a pre-combustion
oven under pure oxygen for 2 h at a relatively low temperature
(340 ∘C) to drive off all OC, after which, the sample was oxidised
in order to determine the EC content with a G4 ICARUS carbon analyser equipped
with a non-dispersive infrared detector (NDIR). The other part of the filter
was directly analysed for total carbon content with the carbon analyser
(Adon et al., 2020). OC content could then be obtained from the difference
between the measured total carbon (TC) and EC concentrations. The detection limit for the OC/EC analysis was 2 µgC cm-2.
Results and discussionMass concentration
The mass concentrations determined for the PM1, PM1-2.5, and
PM2.5-10 size fractions and for PM10 (combination of mass
concentrations of the three size fractions) at each site during the
different sampling campaigns are presented in Fig. 2 (S denotes a summer
campaign and W designates a winter campaign). It is evident from Fig. 2
that indoor PM2.5-10 samples collected during winter at Jouberton had
the highest mean mass concentration (59.6 µg m-3), while the
highest average PM10 mass concentration was also recorded during this
sampling campaign (108.3 µg m-3). Moderately lower mean PM mass
concentrations were determined during the summer indoor campaign in
comparison to the winter indoor campaign. In general, PM mass concentrations
were higher for indoor samples compared to aerosol mass concentrations
determined for outdoor samples. The average PM mass concentrations determined
for outdoor samples collected during winter at Zamdela were moderately lower
than the mean aerosol mass concentration determined during the summer indoor
campaign, and was higher (with higher mean mass concentrations in each
size fraction) than the average PM mass concentrations measured during the three
summer outdoor campaigns for which similar mean aerosol mass concentrations
were recorded.
Mean aerosol mass concentrations (± SD)
measured in PM1, PM1-2.5 and PM2.5-10 at each site (S
denotes a summer campaign and W designates a winter campaign). Average
PM10 mass concentrations are also indicated.
The PM mass concentrations determined in this study correspond to levels
determined for PM in other recent studies in low-income settlements, which
also include measurements at Kwadela and Kwazamokuhle (Adesina et al., 2020;
Langerman et al., 2018; Xulu et al., 2020; Language et al., 2016; Kapwata et
al., 2018). These studies also reported similar trends in PM mass
concentrations, i.e. higher mass concentrations in winter compared to
summer, while indoor PM mass concentration was also generally higher (in
some instances, significantly higher) than outdoor mass concentrations. As
mentioned above (Sect. 2.1), higher concentrations of pollutant species in
winter in this part of South Africa can be attributed to pollution build-up
associated with meteorological conditions and increased household combustion
for space heating.
Comparisons of aerosol mass concentrations of different size fractions
indicate that the PM1 size fraction had the highest mass concentration
in all outdoor aerosol samples collected during winter and summer, as well
as in indoor samples collected during summer. However, the PM2.5-10
size fraction had the highest mass concentration for indoor samples
collected during winter, as mentioned above. The lowest mass concentrations
were determined for the PM1-2.5 size fractions during all the sampling
campaigns at all the sites, with the exception of winter outdoor samples
collected at Zamdela, where the PM2.5-10 size fraction had the lowest mass
concentration. Ultrafine PM is indicative of secondary aerosol formation,
while coarse particulates are generally associated with terrigenous sources
(e.g. wind-blown dust). These mass concentration profiles observed for the
size fractions of aerosols collected during each sampling campaign in this
study will be explored in subsequent sections through an assessment of the
size-resolved chemical composition of PM.
Inorganic ions and water-soluble organic acids
In Fig. 3, the concentrations of each ionic species determined in the
three size fractions at each site during the respective sampling campaigns
are presented, Fig. 4a presents the concentrations of each of
these ionic species for PM10, and Fig. 4b presents the normalised
concentration distribution of each of these ionic species in the three size
fractions. Concentrations of COO-, CH3COO-,
C2H5COO-, and C2O42- were combined and
presented as a total for water-soluble OA (Conradie et al., 2016). As
mentioned previously (Sect. 2.1), inorganic ions and water-soluble OAs
were not determined during the winter indoor campaign at Jouberton due to
instrument failure.
Mean concentrations (± SD) of inorganic
ionic species and water-soluble OAs measured in PM1, PM1-2.5, and
PM2.5-10 at each site during respective sampling campaigns.
(a) Mean concentrations (± SD) of inorganic
ionic species and water-soluble OAs in PM10, and (b) normalised
concentration distributions of these species in PM1, PM1-2.5, and
PM2.5-10 at each site during respective sampling campaigns.
It is evident from Figs. 3 and 4a that the highest concentration was
determined for SO4-2 at each site during the respective sampling
campaigns, while NH4+ and NO3- were the second most
abundant species. Moderately higher Ca2+ levels were also measured,
especially during the winter outdoor and the summer indoor campaigns, with
the mean Ca2+ concentration determined for the latter sampling campaign
being higher than the average NH4+ concentration measured during
this campaign. Concentrations of other ionic species were at least an order
of magnitude lower compared to SO4-2, NH4+, and
NO3- levels. The highest SO4-2 concentrations were
determined during the summer and winter outdoor campaigns conducted at
Zamdela, while similar SO42- levels were determined for the other
two summer outdoor campaigns and the summer indoor campaign. NO3-
concentrations determined for the winter outdoor and summer indoor campaigns
were significantly higher compared to levels thereof measured during the
three summer outdoor campaigns, while the NH4+ concentration
recorded for the winter outdoor campaign was significantly higher compared
to NH4+ levels determined for other sampling campaigns.
NH4+ concentrations were higher than NO3- levels for the
three summer outdoor campaigns, while NO3- concentrations exceeded
NH4+ levels during the winter outdoor and summer indoor campaign.
SO42- concentrations for the four summer (outdoor and indoor) campaigns were
nearly 4 times higher compared to NH4+ levels, while being
approximately 2 times higher than NH4+ concentrations determined
for the winter outdoor campaign. NO3- concentrations were
approximately 3 times lower than SO42- levels measured during
the winter outdoor and summer indoor campaigns, and almost an order of
magnitude lower compared to SO42- concentrations determined for
the three summer outdoor campaigns.
SO42- and NH4+ levels in the PM1 size fraction were
an order of magnitude higher compared to their respective concentrations in
the two larger size fractions for aerosol samples collected during all
sampling campaigns, while OA concentrations in PM1 were approximately 5
times higher than levels thereof in PM1-2.5 and PM2.5-10.
NO3- concentrations in samples collected during the winter outdoor
and summer indoor campaign were also an order of magnitude higher in the
PM1 size fraction, while also being marginally higher in the submicron
fraction for particulates collected during the three summer outdoor
campaigns. Elevated levels were also observed for Cl- and K+ in
PM1 collected during the winter outdoor campaign, while Cl- also
exhibited higher concentrations in PM1 sampled during the summer
outdoor campaign at Kwadela. Cl- concentrations were higher in the
PM2.5-10 size fraction for the other outdoor and indoor sampling
campaigns. K+ levels in PM1 were marginally higher than levels
thereof in the other two size fractions for all sampling campaigns. The
corresponding increased concentrations of Cl- and K+ in the
PM1 size fraction for the winter outdoor campaign can be indicative of
the influence of open biomass burning in this region. Ca2+ and Na+
concentrations were relatively evenly distributed in all three size ranges,
with the exception of moderately higher Ca2+ and Na+ levels
determined in the PM2.5-10 size fraction during the summer indoor
campaign. As mentioned previously, very low concentrations were determined
for Mg2+ and F- concentrations, which were for most sampling
campaigns similar in all three size fractions.
It is evident from the normalised concentration distributions presented in
Fig. 4b for all sampling campaigns that PM1 is dominated by
SO42- and NH4+, with a slightly higher NO3-
contribution in PM1 collected during the summer indoor campaign
observed. A comparison between the summer and winter outdoor campaigns also
indicates a similar trend. In addition, a higher contribution from
NH4+ in the PM1 size fraction is evident for the winter
outdoor campaign compared to the three summer outdoor campaigns.
SO42-, NO3-, and Ca2+ had the highest contributions
in the two larger size fractions for all sampling campaigns, with the
exception of higher NH4+ contributions in the larger size
fractions of winter outdoor samples and higher contributions from Cl-
in the larger size fractions in summer outdoor samples collected at Kwadela.
In general, it can be concluded that PM1 was dominated by
SO42-, while NO3- was the major species in the large
size fractions. However, Ca2+ had the highest contribution to chemical
content in summer indoor PM2.5-10. Recent ambient aerosol measurements
conducted at a regional site located in the South African interior
(Welgegund) also indicated PM1 being dominated by SO42- and
the larger size fractions by NO3- (Venter et al., 2018). In
addition, PM1 measurements conducted with an aerosol chemical speciation monitor (ACSM) also indicated the highest contributions from SO42- and NH4+ to the
chemical content of submicron particulates (Tiitta et al., 2014). A higher
relative contribution of species in the larger size fractions can be
attributed to significantly lower SO42- and NH4+ levels
in these size fractions (Fig. 3).
In Table 3, the mean concentrations of ionic species determined in this study
is listed in relation to mean / median concentrations determined for inorganic
ions in other studies in South Africa, conducted at a rural, regional, and
industrial site (water-soluble organic acids were not determined in these
other studies), which indicate similar levels and concentration
distributions for inorganic ions as determined in this study conducted in
low-income urban settlements. In all these studies, SO42- had the
highest concentration, while NH4+ and NO3- were the
second and/or third most abundant species. Venter et al. (2018) also
indicated significantly higher SO42- concentrations in the
PM1 size fraction compared to its respective levels in larger size
fractions, as well as concentrations of other species in all size fractions
at a regional (Welgegund) and an industrial site (Marikana). Very low
NO3- concentrations were determined at the rural background site,
Botsalano, with K+ at this rural site having concentrations in the same
range as NH4+. As indicated by these previous studies conducted in
this region of South Africa, SO42- occurs predominantly in the
ultrafine size fraction and is generally considered a secondary pollutant
formed from the oxidation of atmospheric SO2 associated with industrial
emissions (Lourens et al., 2011). Particulate
NH4+ is almost exclusively a secondary pollutant formed from
emissions of gaseous NH3 (Seinfeld and Pandis, 2006). Atmospheric
particulate NO3- is related to the oxidation of gaseous NO2
associated with fossil fuel combustion, vehicular emissions, and domestic
fuel burning (Venter et al.,
2012). Very low NO3- concentrations in the ultrafine size fraction
can be attributed to high SO42- levels substituting NO3-
in NH4NO3. Venter et al. (2018) and Tiita et al. (2014)
attributed higher contributions from Ca, Na, and Cl in the larger size
fractions to larger particulates associated with marine (NaCl) and
terrigenous (e.g. wind-blown dust) sources. It is interesting to note that,
with the exception of a higher contribution of Ca2+ to ionic composition
in summer indoor PM2.5-10, inorganic ions in indoor aerosols had
similar concentration distributions to that of ambient aerosols collected
in this study and in other studies in this part of South Africa. This
signifies the regional impacts on indoor atmosphere of emissions associated
with the highly industrialised and densely populated north-eastern interior
of South Africa.
Mean / median concentrations (µg m-3) of inorganic ionic
species and water-soluble organic acids determined at low-income settlements
in this study and in other studies in South Africa and the rest of
the world.
SourceDatePlaceSO42-NO3-Cl-F-OANa+NH4+K+Mg2+Ca2+This study03/2015–03/2017KwadelaaMean PM11.840.0970.080.00010.0330.020.610.020.0260.06Mean PM1-2.50.040.0210.030.00010.0040.010.010.0010.0110.02Mean PM2.5-100.060.0440.030.00120.0060.010.010.0040.0150.04KwazamokuhleaMean PM12.060.110.020.00060.0560.030.770.030.0080.07Mean PM1-2.50.050.050.010.00050.0120.020.010.0030.0030.02Mean PM2.5-100.060.100.020.00210.0120.020.020.010.0050.04ZamdelaaMean PM12.800.700.060.0060.0490.031.270.110.0120.14Mean PM1-2.50.110.170.030.0100.0070.020.050.010.0120.12Mean PM2.5-100.120.270.030.0080.0070.020.070.020.0110.14JoubertonbMean PM11.640.920.050.0030.070.060.600.060.0170.22Mean PM1-2.50.070.270.040.0010.030.050.050.020.0100.19Mean PM2.5-100.160.300.070.0010.020.090.040.040.0200.47South AfricaAurela et al. (2016)9–5/10/2007 & 01–02/2008Botsalano, ruralaMean PM13.920.03–––0.051.020.18––Titta et al. (2014)09/2010–08/2011Welgegund, regionalaMean PM12.40.50.03–––0.9–––Venter et al. (2018)11/2008–10/2009Marikanaa, industrialMedian PM2.51.830.270.07––0.090.550.090.020.08Median PM2.5-100.370.400.06––0.070.090.030.040.1724/11/2010–28/12/2011Welgegunda, regionalMedian PM11.350.020.0050.015–0.160.440.0320.0030.019Median PM1-2.50.10.040.0055>0.005–0.210.040.0040.0050.014Median PM2.5-100.050.0570.007>0.005–0.0190.0050.0050.0060.025AfricaAdon et al. (2020)07/2015–01/2017Abijan, Côte I'voirea, urbanMean PM<0.21.230.865.73–0.390.342.791.990.180.55Domestic fire siteaMean PM1-0.1/0.20.641.361.31–0.270.760.110.390.440.98Mean PM>2.5-10.290.540.59–0.250.380.070.220.230.87Waste burning siteaMean PM<0.21.880.890.37–0.240.060.960.640.030.37Mean PM1-0.1/0.20.501.740.94–0.140.710.060.110.110.74Mean PM>2.5-10.270.750.66–0.100.480.080.060.060.39Traffic siteaMean PM<0.21.231.340.25–0.210.070.600.550.030.48Mean PM1-0.1/0.20.411.520.85–0.120.650.140.090.080.79Mean PM>2.5-10.210.600.64–0.100.450.060.050.050.49Cotonou, Benin (traffic site)a, urbanMean PM<0.22.141.500.47–0.290.250.340.680.071.89Mean PM1-0.1/0.21.042.771.61–0.191.140.170.180.171.90Mean PM>2.5-10.390.910.94–0.100.650.080.060.071.13Other international locationsBressi et al. (2013)09/2009–09/2010Paris, FranceaMean PM2.51.92.70.18––0.161.40.120.030.08Szigeti et al. (2015)06/2010–05/2013Széna Square, Budapest, HungaryaMean PM2.52.842.140.11––0.221.330.180.050.16Qiu et al. (2016)03/2012-03/2013Weinan, ChinaaMean PM2.524.71830.1–1.3101.30.21.6Shao et al. (2018)12/2016–01/2017Beijing, ChinaaMean PM2.520.9329.094.07––0.5815.441.40.230.69Gawhane et al. (2017)04/2015–04/2016Pune, IndiaaMean PM2.54.80.983.42––1.980.510.470.280.51Kumar and Raman (2016)01/2012–12/2013Van Vihar National Park (VVNP) Bhopal, central IndiaaMean PM2.53.353.021.460.35–0.962.070.980.180.77Castro et al. (2018)03/2006–03/2006Tecámac University, MexicoaMean PM3.23.421.810.73–––1.090.970.231.08
a= Outdoor, b= Indoor.
Also listed in Table 3 are the mean levels determined for inorganic ions
and water-soluble organic acids in other parts of Africa and the rest of the
world. Aerosol measurements conducted at a site in close proximity to wood burning
in Abidjan, Côte d'Ivoire indicated that Cl-, NH4+, and
K+ had the highest concentrations in the PM1 size fraction, with
NH4+ levels being at least 3 times higher and Cl-
concentrations an order of magnitude higher compared to levels thereof
determined in PM1 in this study. SO42- levels at this West
African site impacted by household wood combustion were similar to
SO42- concentrations determined in this study conducted in
low-income urban settlements, while the relative contribution of
NO3- compared to SO42- in PM1 was larger at this
site in Abidjan. SO42- and NO3- in PM1 were similar
to levels determined for these species in PM1 during the summer indoor
campaign in this study. Concentrations of other ionic species (including
OAs) in the PM1 size fraction of aerosols collected at this site in
Abidjan in close proximity to wood burning were an order of magnitude higher than
their respective concentrations determined for most of the sampling
campaigns conducted in this study. Also, Ca2+ levels determined in
PM1 during the winter outdoor and summer indoor campaigns in PM1
were 5 and 2.5 times lower, respectively, than Ca2+ concentrations
determined at the domestic burning site in Abidjan. SO42- and
NO3- had the highest concentrations in PM1 at a waste burning
site at Abidjan, while higher contributions are also observed for
NH4+, Cl-, and K+. A comparison with two sites in West
Africa in close proximity to vehicular traffic (Abidjan and Cotonou, Benin)
indicated that NO3- dominated the PM1 size fraction, while
SO42- and NH4+ concentrations were similar to levels
determined for these species in this study. Larger contributions are also
observed for Cl- and K+ at these sites in West Africa, impacted by
traffic. Concentrations of all ionic species in the PM2.5-10 size
fraction at all these sites in Abidjan and Cotonou were an order of
magnitude higher than levels determined for these species in low-income
settlements in South Africa. NO3- and Ca2+ concentrations
determined in PM2.5-10 in this study were closer to levels thereof
determined at Abidjan and Cotonou, but still lower. In addition, the
concentrations of all ionic species in the PM1 size fraction were
higher than their corresponding levels in the PM2.5-10 size fraction at
all sites in West Africa. The influence of marine air masses on atmospheric
composition is evident at these two coastal West African cities.
The mean concentrations determined for inorganic ions in PM2.5
collected at two European (Paris and Budapest), two Chinese (Beijing and
Weinan), two Indian (Pune and Bhopal), and one Latin
American city (Mexico) are listed in Table 3. SO42- and
NO3- had the highest concentrations in PM2.5 at the two
European cities, with NH4+ being the second most abundant.
SO42- and NH4+ levels at the two European urban sites
were similar to concentrations determined for these species at low-income
urban settlements, while higher NO3- levels are reported for the
European sites, with NO3- concentrations at Budapest exceeding
SO42- levels. Concentrations of other ionic species were also
higher at the two European urban sites compared to levels thereof determined
in this study, with the exception of Ca2+ levels. Similar to the two
European cities, SO42- and NO3- were also the most
abundant species at the two urban sites in China, while NH4+ was
the second most abundant species. However, the concentrations of
SO42-, NO3-, and NH4+ were approximately 10
times higher than levels determined for these species at the European urban
sites and at the low-income settlements in this study. Concentrations of other
inorganic ions were at least an order of magnitude higher at these two
Chinese cities. The highest ionic concentrations were also reported for
SO42- and NO3- at Bhopal in India, with NH4+
having the second highest concentration. SO4- levels at Bhopal
were slightly higher than levels thereof in low-income settlements in the
South African interior, while NO3- and NH4+
concentrations were substantially higher at Bhopal. SO42- had the
highest concentration at Pune in India, which were 4 times higher than
SO42- levels determined in this study. NO3- and
NH4+ concentrations at Pune were similar to levels thereof in the
low-income settlement in South Africa. However, NO3- and
NH4+ levels at Pune were significantly lower compared to Cl-
and Na+ concentrations that were the second and third most abundant
species respectively at Pune – Cl- levels at Pune were two orders of
magnitude higher than levels thereof determined in this study.
Concentrations of other inorganic ions were also higher at the Indian urban
sites compared to levels of these species at low-income settlements in South
Africa. Similar to the concentration distribution observed in the South African
sites, SO42- was the most abundant species, with NO3- and
NH4+ being the second most abundant at the urban site in Mexico.
Moderately higher concentrations were reported for SO42-,
NO3-, and NH4+ in Mexico compared to levels thereof
determined in this study, while the concentrations of other inorganic ions
were at least an order of magnitude higher at the site in Mexico.
Acidity
Similar to Tiitta et al. (2014) and Venter et al. (2018) who reported
acidity for ambient PM1 sampled at Welgegund in South Africa, the
acidity of the outdoor and indoor PM1 collected in low-income urban
settlements was estimated by relating the measured NH4+
concentrations ([NH4+]meas) to the NH4+ levels
required to completely neutralise SO42-, NO3-, and
Cl-. This was calculated as follows:
NH4+calµgm-3=18gmol-1×2×SO42-µgm-396gmol-1+NO3-µgm-362gmol-1+Cl-µgm-335.5gmol-1.
If [NH4+]cal≈ [NH4+]meas
particulates can be considered neutralised, whereas if
[NH4+]cal> [NH4+]meas aerosols
could be classified as acidic. This is a relatively simple approach that
assumes negligible influences from organic acids, metal species, and other
bases on NH4+ levels. Similar to Venter et al. (2018), only the
PM1 size fraction that contained the bulk of the ionic concentration
(i.e. SO42- and NH4+) were considered. In Fig. 5,
[NH4+]meas is plotted in relation to
[NH4+]cal for PM1 collected during outdoor summer,
outdoor winter, and indoor sampling campaigns (the three summer campaigns at
Kwadela, Kwazamokuhle, and Zamdela were combined and as indicated above, due
to instrument failure, ionic species were only measured for indoor
particulates collected during the summer campaign). The 1:1 line in this
figure corresponds to a bulk neutralised state. It is evident from Fig. 5
that all outdoor and indoor PM1 collected were acidic, with summer
outdoor PM1 being closer to a neutralised state compared to outdoor
winter and indoor summer PM1. The acidity of outdoor PM1 collected
in low-income urban settlements corresponds to previous observations reported
by Tiitta et al. (2014) and Venter et al. (2018). However, Venter et al. (2018) indicated that ambient PM1 collected during the dry months,
which corresponds to winter as previously mentioned, was closer to the
neutralised state, compared to PM1 measured during the wet season, i.e.
summer. This difference can be attributed to Welgegund being a regional site
with no local point sources that are impacted by aged air masses passing
over source regions in the north-eastern interior. Venter et al. (2018)
argued that cloud formation processes could contribute to the formation of secondary
SO42-, resulting in increased acidity of PM1 during the wet
summer. Ambient measurements in this study were conducted in low-income
urban settlements situated within close proximity of large point sources in the
north-eastern interior. As previously mentioned, this region is
characterised by increased levels of pollutants during winter, which include
higher concentrations of ambient SO2 and NO2 contributing to
elevated SO42- and NO3- levels, especially considering
SO42- being the main acidic ion (Collette et al., 2010; Lourens
et al., 2011). The acidity of the summer indoor PM1 at Jouberton was
similar to the acidity of the winter outdoor PM1 at Zamdela.
[NH4+]meas in relation to [NH4+]cal
for PM1 collected during outdoor summer, outdoor winter, and indoor
sampling campaigns.
Trace elements
There are limitations associated with using nitric digestion to extract and
dissolve metal species for ICP-MS analysis, which mainly relate to the
inability of the method to extract Si and silicate minerals. Therefore, Si
was not quantified in this study, while lower concentrations of metal
species associated with silicates e.g. Fe, Ca, Al, Mg, and K might be
reported. Crustal elements determined with ICP-MS could therefore be
underrepresented. Notwithstanding the limitation of this analytical method,
this technique is generally used to determine trace elements concentrations
in atmospheric aerosols (e.g. Venter et al., 2017).
The mean total trace elements concentrations determined in PM1,
PM1-2.5, and PM2.5-10 at each site during the respective sampling
campaigns are presented with a breakdown of individual trace element
concentrations in Fig. 6a, while the normalised trace element
compositions are shown in Fig. 6b. The combined concentrations of trace
elements that were below the detection limit in 75 % or more collected
samples (Sect. 2.3.2 and Fig. A1) are presented as “other” in Fig. 6.
(a) Mean trace element concentrations and (b) normalised
concentration distributions of individual trace element species determined
in PM1, PM1-2.5, and PM2.5-10 at each site during respective
sampling campaigns.
The highest total trace element concentrations were determined for aerosols
collected during the summer indoor campaign in each size fraction (Fig. 6a). The highest total trace element levels occurred in the PM1 size
fraction of indoor particulates, which were significantly higher than total
trace element levels determined in the two other size fractions of indoor
aerosols as well as total trace element concentrations measured in all
three size fractions of aerosols collected during the outdoor campaigns.
A comparison between the total trace element concentrations determined during
the summer and winter outdoor campaigns at Zamdela indicates higher total
trace element levels in all three size fractions during winter. However, the
total trace element concentrations determined in the three aerosol size
fractions collected during the two summer outdoor campaigns at Kwadela and
Kwazamokuhle were similar to levels thereof determined for the winter
outdoor campaign. The highest total trace element concentrations also
occurred in the PM1 size fraction of aerosols collected during the four
outdoor campaigns. Assessments of atmospheric trace elements conducted at
Welgegund and Marikana in South Africa indicated higher total trace element
concentrations during the dry winter season (Venter et al., 2017; Van Zyl et
al., 2014). As mentioned above, Welgegund is a regional site in the South
African interior, while Marikana is situated in the highly industrialised
western Bushveld Igneous Complex that holds a large number of
pyrometallurgical smelters. Measurements conducted at these sites over a
period of one year however, did not reveal a very strong seasonal trend for
atmospheric trace elements. Furthermore, it seemed from these studies that
wet removal of particulates was more significant to seasonal variability
than wind-generation thereof.
It is evident from Fig. 6a and b that Na and Ca had the highest
concentrations in all three size fractions of aerosols collected during the
outdoor campaigns conducted at Kwazamokuhle and Zamdela (with the exception
of the PM1-2.5 size fraction of aerosols collected during the summer
campaign at Zamdela, for which Ca and K had the largest contribution to total
trace element concentration and no Na was detected), while Na and Cr had the
highest levels in PM1, PM1-2.5, and PM2.5-10 collected during
the summer outdoor campaign at Kwadela and the summer indoor campaign at
Jouberton. The higher total trace element concentrations determined during
the winter outdoor campaign at Zamdela compared to the summer outdoor
campaign conducted at this site is mainly attributed to significantly higher
Ca levels measured during winter. Although similar Cr concentrations were
determined for the sampling campaigns conducted at Kwadela and Jouberton,
the Cr contribution to total trace element concentration was particularly
significant at Kwadela in all three size fractions. Relatively high Fe
concentrations were also determined in all three size fractions of
particulates collected during all sampling campaigns in this study.
Moderately higher P concentrations were also evident in aerosol samples
collected during the summer indoor campaign, while relatively high
contributions to total trace element concentrations were also observed for B
in particulates collected at Zamdela.
The mean size distributions of individual trace element species determined
at each site during the respective sampling campaigns are presented in
Fig. 7. It is evident that ∼40 % and more of each trace
element species occurred in the PM1 size fraction of aerosols collected
during the outdoor campaigns (with the exception of Mn and V at
Kwazamokuhle), while ∼50 % and more of each trace element
species were in the PM1 size fraction of summer indoor particulates. In
addition, 70 % and more of trace elements detected in aerosol samples
collected in low-income settlements (except for Zn and Mg at Kwadela)
occurred in the PM1 and PM1-2.5 size fraction. The mean size
distributions of trace element species observed in this study correspond to
average size distributions of trace elements determined at the regional site
Welgegund (Venter et al., 2017), where the largest percentage (>70 %) of individual trace elements occurring in the PM1 and
PM1-2.5 size fractions was attributed to the regional impacts of
industrial (high temperature) sources. Cr, Mn, V, Zn, and Ni are generally
related to pyrometallurgical activities. Van Zyl et al. (2014) indicated
that Cr, Mn, V, Zn, and Ni were almost completely in the PM2.5 size
fraction of aerosols collected in the highly industrialised Bushveld Igneous
Complex within close proximity to several pyrometallurgical smelters. Trace
element species occurring in the PM2.5-10 size fraction are generally
associated with wind-blown dust and typically include species such as Al,
Fe, Mg, and Ca. Trace element species in the PM2.5-10 size fraction at
Welgegund were also ascribed to the influence of wind-blown dust (Venter et
al., 2017), while Van Zyl et al. (2014) also considered wind-blown dust the
major source of Al, B, Fe, Na, K, and Mg in PM2.5-10. Therefore, the
regional impacts of industrial activities in the north-eastern interior are
also reflected by the mean trace element concentrations, and
normalised concentration and size distributions of individual trace element
species presented in this study for low-income urban settlements, while the
influence of wind-blown dust is also evident.
Size distributions of individual trace elements detected at each
site during respective sampling campaigns. Species are arranged by
increasing concentrations in the PM1 size fraction.
In Table 4, the average trace element concentrations determined in PM10
in this study (combined mean concentrations in PM1, PM1-2.5, and
PM2.5-10) in low-income settlements are contextualised with mean trace
element concentrations measured in other studies in South Africa and urban
areas in other parts of the world. As previously mentioned, Be and Tl were
below the detection limit of the analytical technique for the entire
sampling period in all the sites, while Sb, Ba, Cu, As, Se, Rb, Sr, Mo, Pd,
Ag, Pb, Au, Hg, Ti, Co, Pt, Bi, Th, and U were below the detection limit in
75 % or more of the collected samples. Therefore, concentrations of these species
listed in Table 4 are most likely overestimated.
Mean PM10 trace element concentrations determined during
sampling campaigns at low-income settlements in this study, annual average
standard limits, and mean trace element concentrations measured in studies
conducted in South Africa and other parts of the world. All concentrations
are presented in µg m-3. Bold typeface indicates concentrations of
species that were below the detection limit of the analytical technique in
75 % or more of the collected samples in all three size fractions (italic
typeface indicates species below the detection limit in all samples).
South Africa Other countries ICP-MSKwadelaKwazamokuhleZamdelaJoubertonAnuualWelgegundMarikanaVaal TriangleRustenburgBamakoBamakoDakarBeiling, ChinaBarcelona, Spain detection(Outdoor)(Indoor)standardsno desert dustwith desert dustIndoorOutdoorElementlimits (×10-5)(this study) Venter et al. (2017)Van Zyl et al. (2014)Kleynhaus (2008)Kgabi (2006)Val et al. (2013) Duan et al. (2012)Rivas et al. (2014) Be1.1650.00010.00010.00010.00040.00020.0200.010B19.041.120.0021.423.170.281.3000.080.050.03Na29.584.757.722.6913.750.381.4102.8000.810.202.101.4500.340.34Mg22.090.251.160.753.120.232.0401.0000.960.280.410.6370.160.19Al65.070.810.830.763.170.171.2807.322.471.202.180P377.30.760.040.304.480.110.090.18K406.90.080.940.281.780.140.6801.3002.360.670.511.1700.370.4Ca93.22.669.506.703.131.11.0802.051.101.480.9961.60.82Ti1.4320.090.080.040.180.0720.1200.0200.1800.320.130.070.0690.0550.059V4.4660.470.010.010.111.000c.e0.0370.0400.1600.0090.0040.0300.00480.0059Cr359.99.161.070.479.002.5 × 10-5a,b0.50.2400.0501.3700.0220.00380.0034Mn4.1560.210.050.060.170.15b0.0260.0600.1204.3900.0630.0260.0260.0360.0120.016Fe60.720.882.131.634.871.22.5401.2809.7604.151.980.881.0900.420.58Co0.6250.110.0040.0030.190.00350.140<0.0010.000210.00022Ni3.2290.390.160.191.490.020c0.0790.3300.0400.7700.0140.0040.0120.0200.00260.0033Cu4.1860.020.180.060.470.00690.1800.0500.2100.0090.0050.0190.0100.00820.0088Zn6.2120.160.240.310.680.0530.4900.0900.3400.0370.0260.0420.0270.0520.055As5.6860.070.0020.0020.030.00840.2600.0030.0010.0050.0030.000460.0005Se8.5590.010.010.020.020.00740.5800.0010.000330.00037Rb0.2680.0020.010.0040.03Sr1.2380.010.080.010.040.00170.0100.00460.0028Mo0.6810.020.010.020.060.0150.007Pd0.2460.010.010.030.030.00180.410Ag2.4470.030.580.050.050.0005<0.001Cd1.1190.010.010.0120.0180.005b.c0.00040.030<0.0010.000140.00017Sb0.7120.0010.0010.0050.0050.0013<0.0010.000830.0011Ba1.6700.090.170.1090.0880.00400.1400.0180.0190.02Pt0.3810.0030.010.0320.0160.00160.350Au2.1560.0010.030.0070.1910.00310.380Hg2.8360.0380.0371.000b0.00020.550Tl0.4110.000030.000040.000030.00010.00070.270Pb0.5870.0800.1520.0670.0700.5b.c.d0.00780.0800.0400.4200.0130.00980.0090.0530.00730.0081Bi0.3090.0080.0030.0020.001Th0.1600.000010.0020.0010.001U0.1130.00020.00170.0010.0020.0009
a WHO guideline for Cr(VI) concentrations associated with an excess lifetime risk of 1:1000000. b WHO air quality guidelines for Europe. c European Commission Air Quality Standards. d National Air Quality Act of the South African Department of Environmental Affairs. e 24 h limit value.
Fe was the most abundant trace element species in particulates collected at
Welgegund, Marikana, and Rustenburg in South Africa, while Na had the highest
mean concentration in the Vaal Triangle. The city of Rustenburg is,
similar to Marikana, located in the western Bushveld Igneous Complex,
while the Vaal Triangle is a highly industrialised and densely populated
region south of the Johannesburg–Pretoria conurbation. Relatively higher
concentrations were reported for Mg, Na, B, Al, and Ca at Marikana, while Mn
and Cr were the second and third most abundant species in Rustenburg. Fe and
K had the second and third highest concentrations at the Vaal Triangle. Ca, Cr,
and Na were the second, third, and fourth most abundant species in Welgegund,
with trace element concentrations at Welgegund being generally lower
compared to levels thereof determined in urban areas in South Africa, including
trace element levels determined in low-income settlements. Relatively high B
levels were also reported for Welgegund. Total trace element concentrations
determined at other urban areas in South Africa were similar to total trace
element levels determined in outdoor aerosols collected in low-income urban
settlements. Ca, Na, and Cr concentrations determined in outdoor and indoor
particulates in this study were significantly higher than levels thereof
determined in the other South African regional and urban sites, especially
Na and Cr levels measured in indoor particulates. Although Fe was not the
most abundant species in aerosols collected in low-income settlements, its
concentrations were similar to levels thereof determined in other South
African sites, with the exception of Rustenburg, where a significantly higher
Fe concentration was reported. Fe and Ca had the highest concentrations in
all three size fractions of particulates collected in Welgegund, which is
the only other size-resolved assessment of atmospheric trace elements
conducted in South Africa. The highest total trace element concentrations
were also determined in PM1 in Welgegund, which were however,
dominated by Fe. Ca levels in Welgegund were higher in the PM1-2.5 and
PM2.5-10 size fractions.
Total trace element concentrations determined in outdoor aerosols collected
in low-income settlements were also similar to the total trace element levels
determined in other urban regions in Africa and the rest of the world.
However, total trace element concentrations were significantly lower in
outdoor and indoor particulates sampled in Barcelona, Spain. With the
exception of Ca, most trace element concentrations in Barcelona were at
least an order of magnitude lower than levels thereof determined in this
study and other studies listed in Table 4. Al, Fe, and Ca were the most
abundant species in Bamako, Mali, while the highest concentrations were
reported for Na, Ca, Al, and Fe in Dakar, Senegal. Measurements conducted at
a regional site within close proximity of Beijing, China indicate that Al, Na, K,
Fe, and Ca were the most abundant species. Al was the most abundant species
in Bamako and Beijing, with the Al concentration in Bamako being an order of
magnitude higher than levels thereof determined in this study. Ca had the
highest concentration in particulates collected in Dakar. Ca, Fe, K, and Na
had the highest concentrations in particulates collected during outdoor and
indoor campaigns in Barcelona. Although trace element concentrations
determined in Barcelona were lower than trace element levels determined in
low-income urban settlements in this study, higher trace element
concentrations are also reported for indoor particulates collected in
Barcelona. Wind-blown dust is considered the major source of atmospheric
trace elements at these sites in other parts of the world, while the
impacts of marine air masses are also evident in coastal cities (e.g.
Dakar).
Existing ambient air quality guidelines and standard limit values for trace
element species according to the WHO Air Quality guidelines (WHO, 2006), the
European commission Air Quality Standards (ECAQ, 2008), and the South African
National Air Quality Standards (DEA, 2009) are also listed in Table 4. Since
there are only annual average standard values for six of the seven trace elements
for which a standard limit value exists, mean trace element levels
determined during the respective sampling campaigns at each site in this
study cannot be directly compared to these standard limit values. V has a
24 h standard, which can be related to average V levels determined in
24 h samples collected during the indoor campaign. In addition, the
relatively high total atmospheric Cr concentrations measured in this study
in outdoor and indoor aerosols cannot be directly related to the WHO
guideline, which is only for atmospheric Cr(VI) with a lifetime risk of 1:1000000.
Average concentrations of Ni, As, and Cd in outdoor and indoor particulates
and average Mn levels determined during the indoor campaign were
higher than annual standard values for these species. However, As and Cd
concentrations are most-likely overestimated due to their levels being below
the detection limit of the analytical technique in 75 % or more of the
samples. Average Ni concentrations in indoor samples were two orders of
magnitude higher than the annual average European standard, while the
average concentration thereof in outdoor samples was an order of magnitude
higher. Annual average Ni concentrations determined in aerosols collected at
Welgegund and Marikana also exceeded annual standard limits, which was
attributed to base metal refining in the Bushveld Igneous Complex (Venter et
al., 2017; Van Zyl et al., 2014). In addition, the average Ni concentrations in
indoor PM10 were an order of magnitude higher than levels thereof
determined in Marikana located within close proximity of pyrometallurgical
smelters. Mean Mn levels in indoor particulates marginally exceeded the
annual average standard. The average V concentration in outdoor and indoor
PM10 was well below the 24 h V standard value.
Venter et al. (2017) and Van Zyl et al. (2014) also mentioned atmospheric
Pb and Hg concentrations determined in aerosols collected at Welgegund and
Marikana, respectively. Pb is the only trace element for which a South
African air quality standard exists, while it is foreseen that an air
quality standard limit for Hg will be prescribed in the very near future in
South Africa. Average Pb and Hg levels determined at each site during the
respective sampling campaigns were well below the annual average standard
limits of these species. In addition, Pb and Hg levels were only detected in
25 % or less of the collected samples. Pb concentrations were similar to
levels determined for Pb at Welgegund, which were at least 2 orders of
magnitude lower than Pb concentrations determined at Marikana, the Vaal Triangle,
and Rustenburg (Van Zyl et al., 2014; Kgabi, 2006; Kleynhans, 2008). Hg was
below the detection limit of the analytical technique for the entire
sampling periods at Welgegund and Marikana.
Carbonaceous aerosols
In Fig. 8, OC and EC concentrations determined in the three aerosol size
fractions at each site during the respective sampling campaigns are
presented, while the mean OC/EC ratios calculated are also indicated. The
highest average OC and EC concentrations were determined in the PM1
size fraction of all aerosol samples collected during respective sampling
campaigns conducted at each site in this study, with mean OC and EC levels
being significantly higher (4 times up to an order of magnitude higher) than
levels thereof in the PM1-2.5 and PM2.5-10 size fractions of
particulates collected during the two indoor campaigns, the winter outdoor
campaign, and the summer outdoor campaign at Kwadela. Similar OC and EC
levels were measured in PM1-2.5 and PM2.5-10 for all sampling
campaigns, with the exception of ∼3 times higher OC and EC
concentrations determined in these two larger size fractions during the
winter indoor campaign. The lowest average OC and EC concentrations were
determined in the PM1-2.5 size fraction for all sampling campaigns.
Mean OC and EC concentrations (± SD)
measured in PM1, PM1-2.5, and PM2.5-10 at each site during
respective sampling campaigns, together with mean OC/EC ratios.
The highest mean OC and EC levels were measured in PM1 collected during
the winter indoor campaign. Moderately lower average EC concentrations were
determined in the PM1 size fraction of particulates collected during
the summer indoor campaign, while mean OC levels in PM1 sampled during
the summer indoor campaign were significantly lower than average OC
concentrations determined for the winter indoor campaign. Mean OC and EC
levels measured in PM1 collected during the winter outdoor sampling
campaign at Zamdela were significantly higher than average OC and EC
concentrations determined during the summer outdoor campaigns at Zamdela and
Kwazamokuhle, where similar OC and EC levels were measured. Mean OC and EC
levels in PM1 collected during the summer outdoor campaign at Kwadela
were higher than OC and EC concentrations determined in PM1 during the
other two summer outdoor campaigns, but lower than OC and EC levels in
PM1 sampled during the winter outdoor campaign at Zamdela. Ambient EC
concentrations determined during winter at Zamdela were moderately lower
than EC levels measured during the summer indoor campaign, while higher
average OC concentrations were determined in aerosols collected during the
winter outdoor campaign at Zamdela compared to OC levels determined for the
summer indoor campaign at Jouberton. Ambient OC and EC concentrations
determined in PM2.5 collected at four sites regionally representative
of the north-eastern interior of South Africa indicated higher OC and EC
concentrations during the dry winter season compared to levels thereof
during the wet warmer season, especially at two sites, i.e. Vaal Triangle
and Amersfoort, within close proximity of anthropogenic sources (Maritz et al.,
2019). Josipovic et al. (2019) also reported higher OC and EC
concentrations during the dry season at Vaal Triangle. Higher OC and EC
concentrations during winter at these sites were attributed to changes in
meteorology (e.g. occurrence of low-level inversion layers) and
increased emissions associated with household combustion and open biomass
burning.
It is also evident from Fig. 8 and the OC/EC ratios that EC concentrations
were generally higher than OC levels in each size fraction of aerosols
collected during the three summer outdoor campaigns at low-income
settlements (with the exception of higher OC in PM1 collected at
Kwadela). An increase in OC concentrations in relation to EC levels is
observed in winter outdoor particulates when compared to summer (ambient)
aerosols in all three size fractions (especially in PM1-2.5 and
PM2.5-10). EC concentrations were higher than OC levels in the PM1
and PM1-2.5 size fractions of summer indoor aerosols, while an increase
in OC levels with regard to EC concentrations is also observed in all three
size fractions of indoor particulates collected during winter. Lower OC/EC
ratios are related to fresher emissions of OC and EC (e.g. Aurela et al.,
2016), since concentrations of primary emitted EC reduce due to deposition,
while secondary formation of OC contribute to increased OC levels in aged
air masses. Therefore, OC/EC ratios reported for aerosol samples collected
in low-income urban settlements in this study reflect OC and EC associated
with local sources of these pollutants. In addition, OC/EC ratios calculated
in this study also indicate a lower impact from traffic emissions (Adon et
al., 2020). OC/EC ratios reported for PM2.5 at four sites regionally
representative of the north-eastern interior of South Africa were lower for
sites within close proximity of anthropogenic sources (Maritz et al., 2019). In
addition, OC/EC ratios presented for these sites by Maritz et al. (2019)
were significantly higher (ranging between 2.9 and 6.4) than OC/EC ratios
reported in this study for low-income informal settlements, with the
exception of the OC/EC ratio calculated in PM2.5-10 collected during
the winter outdoor campaign (3.0), which were similar to the OC/EC ratio
determined at the highly industrialised and densely populated Vaal Triangle
site (2.9).
In Fig. 9, SO42-/EC, EC/total particulate matter (TPM), and
SO42-/TPM, which can also be indicative of sources of aerosols,
are presented for particulate samples collected during the respective
sampling campaigns at each site. The predominance of SO42- in the
PM1 size fraction is reflected by these ratios, with the
SO42-/EC ratio also indicating significantly higher
SO42- concentrations than EC levels in PM1. However,
substantially lower SO42- levels in PM1-2.5 and PM2.5-10
are also reflected in these ratios, with EC concentrations exceeding
SO42- levels in most instances in the two larger size fractions. A
larger contribution from EC in relation to SO42- and TPM is also
observed in indoor PM1 compared to outdoor PM1. Although the
impact of local sources associated with domestic fuel burning is evident for
aerosols collected in low-income urban settlements, the regional impacts of
emissions related to industrial combustion are also signified by these
ratios presented in Fig. 9.
Ratios between major compounds in PM1, PM1-2.5, and
PM10 collected during outdoor and indoor sampling campaigns. (a)SO42-/EC, (b)EC/TMP, and (c)SO42-/TMP in three size
fractions.
In Table 5, OC and EC concentrations determined for low-income settlements in
this study are contextualised with other OC and EC measurements conducted in
South Africa and other parts of the world. OC levels determined in
this study for outdoor and indoor particulates were an order of magnitude
lower than OC concentrations determined for ambient PM2.5 collected at
four sites located in the north-eastern interior of South Africa, while
similar EC concentrations were determined, with the exception of
significantly higher EC levels measured at the Vaal Triangle (Maritz et al.,
2019; Chiloane et al., 2017). However, OC and EC levels determined for
PM1 in this study were similar to OC and EC concentrations reported by
Josipovic et al. (2019) for PM1 collected at the Vaal Triangle.
Josipovic et al. (2019) also indicated higher OC and EC concentrations in
the PM1 size fraction compared to the larger size fractions. OC and EC
concentrations measured in PM1-2.5 and PM2.5-10 for low-income
settlements were significantly lower (by at least an order of magnitude) than
OC and EC levels determined in other sites in South Africa.
Mean OC and EC concentrations (µg m-3) determined at
low-income settlements in this study and in other studies in South
Africa and the rest of the world.
SourcePeriodPlaceAreaOCECThis study03/2015–03/2017KwadelaOutdoorMean PM10.630.51Mean PM1-2.50.030.07Mean PM2.5-100.070.09KwazamokuhleOutdoorMean PM10.170.37Mean PM1-2.50.020.08Mean PM2.5-100.060.09ZamdelaOutdoorMean PM10.440.52Mean PM1-2.50.100.08Mean PM2.5-100.190.09JoubertonIndoorMean PM10.891.11Mean PM1-2.50.210.26Mean PM2.5-100.550.33South Africa Chiloane et al. (2017)03/2009–04/2011Louis TrichardtOutdoorMean PM100.90SkukuzaOutdoorMean PM101.10Vaal TriangleOutdoorMean PM104.40AmersfoortOutdoorMean PM101.40BotsalanoOutdoorMean PM100.90Maritz et al. (2019)03/2009–12/2015Louis TrichardtOutdoorMean PM2.53.80.7SkukuzaOutdoorMean PM2.56.91.1Vaal TriangleOutdoorMean PM2.59.33.2AmersfoortOutdoorMean PM2.56.01.2Josipovic et al. (2019)03–10/2012Vaal TriangleOutdoorMean PM1 WS0.410.32Mean PM1->/=2.5 WS0.180.23Mean PM1 DS0.660.51Mean PM1->/=2.5 DS0.430.24Other countries Djossou et al. (2018)02/2015–03/2017Abidjan. Côte d'IvoireOutdoorMean PM2.531.08.67Cotonou. BeninOutdoorMean PM2.58.02.0Rivas et al. (2014)0/2012–02/2013Barcelona. SpainIndoorMean PM2.5101.3OutdoorMean PM2.55.51.3Ho et al. (2004)Hong KongIndoorMean PM2.511.34.8OutdoorMean PM2.512.66.4Cao et al. (2012)07/2004–01/2005Guangzhou. ChinaIndoorMean PM2.521.757.6OutdoorMean PM2.521.97.9Xu et al. (2015)03/2015Xi'an. ChinaIndoorMean PM2.522.57.9OutdoorMean PM2.524.98.8Joseph et al. (2012)2007–2008Coloba. Mumbai (India)OutdoorMean PM2.520.405.00Dadar. Mumbai (India)OutdoorMean PM2.528.409.20Khar. Mumbai (India)OutdoorMean PM2.531.307.70Mahul. Mumbai (India)OutdoorMean PM2.529.107.20Sharma et al. (2020)10/2018–02/2019Himalayan region. IndiaOutdoorMean PM103.911.24
Significantly higher OC and EC concentrations are determined for urban areas
in other countries in Africa and the rest of the world, than OC and EC levels
determined in this study and other studies in South Africa. OC and EC
concentrations determined at Abidjan, Côte d'Ivoire and Cotonou, Benin
were between an order and 2 orders of magnitude higher than levels
thereof measured in low-income urban settlements, especially with OC
concentrations being substantially higher. OC and EC levels in Barcelona,
Spain were similar to OC and EC concentrations determined at Cotonou, Benin.
OC and EC measured at urban regions in China and India were also between an
order and 2 orders of magnitude higher that levels thereof determined in
this study. This is also in agreement with studies in other parts of the
world where indoor and outdoor OC and EC concentrations were measured with
similar levels of OC and EC reported. However, outdoor OC and EC
concentrations determined in Barcelona, Spain were approximately 2 times
lower than indoor OC and EC concentrations determined in this study. OC and
EC levels at a remote site in the Himalayan region in India were
significantly lower than that measured in urban areas in other parts of the
world. However, OC and EC concentrations for this remote site in the
Himalayan region were still higher than levels thereof measured in
low-income settlements in this study.
Aerosol chemical mass closure
Concentrations of inorganic and organic species determined for particulates
collected in low-income urban settlements can be used to perform aerosol
chemical mass closure. However, as previously mentioned, a limitation of the
ICP-MS analytical technique used in this study to determine trace element
concentrations is that Si levels cannot be quantified, which is important to
establish the contribution of dust to the total aerosol load. There are
however, several methods to estimate dust concentrations by utilising
concentrations of other species determined with IC and ICP-MS. Two methods
commonly used to estimate dust concentrations are the methods described by
Guinot et al. (2007) and Terzi et al. (2010) (e.g. Adon et al., 2020).
Guinot et al. (2007) proposed a simplified method to perform chemical mass
closure for fine (PM1-2.5) and course (PM2.5-10) particulates, in
which the mass of EC, particulate organic matter (POM), inorganic ions, and
dust is considered. Experimentally determined OC concentrations are
converted to POM levels with a conversion factor, k, which was
fixed to 1.8 (Guinot et al., 2007; Adon et al., 2020) in this study. Dust concentrations
are calculated from Ca2+ levels and a conversion factor, f, which is the
correlation coefficient between Ca2+ concentrations and missing mass,
i.e. the mass difference between the weighted mass and the mass reconstructed
from analysed species (EC, POM, and inorganic ions). The total mass reported
for inorganic ions in this method excludes Ca2+, while water-soluble
organic acids are accounted for in the POM mass.
The Terzi et al. (2010) method utilises concentrations of trace elements,
considered to be major constituents of dust, to estimate dust levels
according to the following expression:
dust=1.89[Al]+2.14[Si]+1.95[Ca]+1.42[Fe]+1.7[Ti]+1.21[K]+1.66[Mg],
with Si concentrations estimated by the relationship 2.03 × Al according to
Chiapello et al. (1997). A conversion factor of 1.8 was also used to
convert OC levels to POM concentrations. Trace element species not included
in the estimation of dust concentrations were converted to their
corresponding oxides and also considered for chemical mass closure.
Dust concentrations determined in PM1-2.5 and PM2.5-10 with the
two methods are listed in Table 6 (the Guinot et al., 2007, method can only be
applied to these two size fractions). As previously mentioned, the
concentrations of inorganic ions and trace elements could not be determined
for the winter indoor campaign at Jouberton due to instrument failure.
Therefore, chemical mass closure could not be performed for this sampling
campaign. In general, a relatively good correlation (R2=0.80) is
observed between dust concentration calculated with the two methods, with
the exception of moderately large differences in dust levels estimated for
the Kwazamokuhle summer outdoor campaign and in PM2.5-10 collected
during the summer indoor campaign at Jouberton. Higher dust concentrations
estimated with the Terzi et al. (2010) method compared to the Guinot et
al. (2007) method could be expected due to ICP-MS measuring soluble and
insoluble Ca, while the concentrations of other species are also considered
in the calculation. However, lower dust concentrations estimated with the
method of Terzi et al. (2010) in relation to the method of Guinot et al. (2007) can be attributed to ICP-MS measuring lower concentrations for trace
elements included in Eq. (2) due to these species being associated with
silicates, as previously mentioned.
Dust concentrations (µg m-3) estimated according to the
methods of Guinot et al. (2007) and Terzi et al. (2010).
SiteSize fractionGuinot et al. (2007)Terzi et al. (2010)Kwadela-SPM1-2.50.91.9PM2.5-102.12.6Kwazamokuhle-SPM1-2.51.78.3PM2.5-102.77.0Zamdela-SPM1-2.51.41.4PM2.5-102.92.6Zamdela-WPM1-2.58.39.6PM2.5-109.57.4Jouberton-SPM1-2.57.97.3PM2.5-1021.012.6
The results from the chemical mass closure performed with the two methods
described above are presented in Tables 7 and 8. Percentage contributions
from dust and trace elements calculated with the Terzi et al. (2010)
methods exceeding 100 % are due to overestimations of the concentrations
of these species, as indicated by the negative values of the missing mass
(reconstructed mass minus weighted mass). High Ca2+ concentrations
contributed to the overestimation of dust at Kwadela and Kwazamokuhle, while
high levels of the oxides of Na, Cr, and B especially lead to trace element
concentrations being overestimated at these two sites. In addition, high
concentrations were calculated for Ca, B, and Na oxides at Zamdela, while
the levels of the oxides of B, Na, Cr, and P were high at Jouberton. It is
evident that dust is the major constituent in all size fractions of aerosols
collected during respective outdoor and indoor campaigns according to these
estimations. The second largest contribution was from “not determined”
species according to the Guinot et al. (2007) method, while the Terzi et
al. (2010) method indicated the second most abundant species to be trace
elements. Therefore, the largest fraction of species not determined with the
Guinot et al. (2007) method are most likely trace elements. Trace elements
were the most abundant species in PM1 and PM1-2.5 collected during
the summer indoor campaign, with a substantially higher contribution to aerosol
mass. Inorganic ions were the third most abundant species calculated with
both methods, with a significantly larger contribution to aerosol mass
determined for these species with the Terzi et al. (2010) method in the
PM1 size fraction of aerosols collected during the outdoor campaigns.
EC and POM had the lowest contribution to aerosol mass in all size ranges of
particulates collected during all the respective sampling campaigns. No
significant differences are observed in the chemical composition of
particulates collected during the winter and summer outdoor campaigns at
Zamdela.
Chemical mass closure according to the method of Guinot et al. (2007).
Size-resolved concentrations of inorganic and water-soluble organic ions,
trace element species, as well as OC and EC were determined for outdoor and
indoor PM collected during winter and summer sampling campaigns conducted in
low-income urban settlements in South Africa. Particulate mass
concentrations were higher for indoor samples compared to aerosol mass
concentrations determined for outdoor samples, while higher PM mass
concentrations were measured for samples collected during winter. PM1
had the highest mass concentrations in all outdoor aerosol samples collected
during winter and summer, and in indoor samples collected during
summer. The highest aerosols mass concentration was, however, determined in
the PM2.5-10 size fraction of aerosols sampled during the winter indoor
campaign.
Significantly higher concentrations were determined for SO4-2 at
each site during the respective sampling campaigns, while NH4+ and
NO3- were the second most abundant species. SO4-2 and
NH4+ almost exclusively occurred in the PM1 size fraction,
while NO3- was the major constituent in the larger size fractions.
The highest SO4-2 levels were recorded for the winter and summer
outdoor campaigns conducted at Zamdela, while significantly higher
NO3- levels were determined for the winter outdoor and summer
indoor campaigns. NH4+ concentrations recorded for the winter
outdoor campaign were significantly higher than levels thereof determined in
PM collected during other sampling campaigns. Estimations of the acidity of
PM1 indicated that all outdoor and indoor PM1 was acidic. The
concentrations of inorganic ions and water-soluble OAs determined in this
study were similar to ambient levels thereof determined in other studies
conducted in South Africa, which signifies the regional impacts of
anthropogenic emissions in the north-eastern interior of South Africa. The
extent to which particulate inorganic ionic content is dominated by
SO42- in South Africa is unique and not observed for other parts
of the world. The influence of regional open biomass burning was also
observed through increased Cl- and K+ levels in PM1 collected
during the winter outdoor campaign.
The highest total trace element concentrations were determined for aerosols
collected during the indoor campaign, while total trace element levels in
PM1 were substantially higher than levels thereof in the two larger
size fractions of particulates collected during all sampling campaigns. More
than 70 % of trace element species occurred in the PM1 and
PM1-2.5 size fractions, which is also indicative of the regional
impacts of industrial sources. Although no significant seasonal pattern was
observed for trace element species, higher Ca levels contributed to
relatively higher total trace element concentrations during the winter
outdoor campaign at Zamdela. Na and Ca had the highest concentrations in all
three size fractions of aerosols collected during the outdoor campaigns
conducted at Kwazamokuhle and Zamdela, while Na and Cr had the highest
levels in particulates collected during the summer outdoor campaign at
Kwadela and the indoor campaign at Jouberton. In most other studies
conducted in South Africa, Fe was found to be the most abundant species in
ambient aerosols, while one other size-resolved study conducted also
indicated higher trace element concentrations in the PM1 size fraction.
Ni concentrations in outdoor and indoor PM exceeded the annual average
European standard, with Ni levels in indoor PM10 being an order of
magnitude higher than levels thereof determined at a site within close proximity
of large pyrometallurgical smelters. Indoor Mn also marginally exceeded the
annual average standard.
OC and EC concentrations were the highest in PM1 collected during each
sampling campaign conducted in this study, with the highest OC and EC levels
determined in PM1 collected during the winter indoor campaign. OC and
EC levels also revealed a seasonal pattern, with significantly higher
concentration measured during winter, which corresponds to other studies
conducted in South Africa that attributed trends in OC and EC concentrations
to changes in meteorological patterns and increased biomass burning during
winter. Low OC/EC ratios determined for particulates collected in low-income
urban settlements revealed that EC concentrations were generally higher than
OC levels, which is indicative of OC and EC being mainly associated with
local sources of these species. OC concentrations determined in this study
were an order of magnitude lower than OC concentrations determined for
ambient aerosols collected in the north-eastern interior of South Africa,
while similar EC levels were measured. However, OC and EC concentrations
determined for urban areas in other countries in Africa and the rest of the
world were significantly higher than OC and EC levels determined in general
for South Africa.
An estimation of chemical mass closure according to two methods revealed dust
to be the major constituent in all size fractions of particulates collected
during the respective outdoor and indoor campaigns, while trace element
species were the second most abundant. However, trace elements made the
highest contribution to aerosol mass in PM1 and PM1-2.5 collected
during the indoor campaign. No clear season pattern was observed in the
chemical composition of particulates sampled in low-income urban
settlements.
Mean concentrations of trace element species for which
significantly lower levels were determined in PM1, PM1-2.5, and
PM2.5-10 at each site during respective sampling campaigns.
Data availability
The data set is available at 10.6084/m9.figshare.17197247.v1 (Van Zyl, 2021).
Author contributions
CKS, PGvZ, CL, and JPB were the main investigators in
this study and wrote the manuscript. CKS conducted this study as part of her
PhD degree and performed most of the experimental work and data
processing. The project was led by PGvZ, CL, and JPB who were also study
leaders of the PhD. JSS, MDA, and EG assisted with analyses of aerosol
samples and BL assisted with aerosol sample collection. RPB and SJP
provided infrastructure for sampling campaigns and made conceptual
contributions.
Competing interests
The contact author has declared that none of the authors has any competing interests.
Disclaimer
Publisher’s note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Acknowledgements
The Prospective Household cohort study of Influenza, Respiratory Syncytial virus and other respiratory pathogens community burden and
Transmission dynamics in South Africa (PHIRST) study is appreciated. Jacques Adon is also thanked for his assistance with OC and EC analysis,
as well as Johan Hendriks for conducting ICP-MS analysis.
Financial support
This research has been supported by the National Research Foundation (NRF) in South Africa and the Atmospheric Research in Southern Africa and Indian Ocean (ARSAIO) project.
Review statement
This paper was edited by Lea Hildebrandt Ruiz and reviewed by two anonymous referees.
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