# Measurement report: Size-resolved chemical characterisation of aerosols in low-income urban settlements in South Africa

Constance Segakweng, Pieter van Zyl, Catherine Liousse, Johan Beukes, Jan-Stefan Swartz, Eric Gardrat, Maria Dias-Alves, Brigitte Language, Roelof Burger, Stuart Piketh

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To cite this version:

Constance Segakweng, Pieter van Zyl, Catherine Liousse, Johan Beukes, Jan-Stefan Swartz, et al. Measurement report: Size-resolved chemical characterisation of aerosols in low-income urban settlements in South Africa. Atmospheric Chemistry and Physics, 2022, 22 (15), pp.10291-10317. 10.5194/acp-22-10291-2022. hal-03875682

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# Measurement report: Size-resolved chemical characterisation of aerosols in low-income urban settlements in South Africa

Constance K. Segakweng¹, Pieter G. van Zyl², Cathy Liousse³, Johan P. Beukes², Jan-Stefan Swartz², Eric Gardrat³, Maria Dias-Alves³, Brigitte Language¹, Roelof P. Burger¹, and Stuart J. Piketh¹

¹Unit for Environmental Sciences and Management, North-West University, Potchefstroom Campus, South Africa

²Chemical Resource Beneficiation, North-West University, Potchefstroom Campus, South Africa

³Laboratoire d'Aérologie, Université Paul Sabatier, Toulouse III, France

**Correspondence:** Pieter G. van Zyl (Pieter.VanZyl@nwu.ac.za)

Received: 9 December 2021 – Discussion started: 16 February 2022

Revised: 11 May 2022 – Accepted: 31 May 2022 – Published: 11 August 2022

**Abstract.** 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.

# 1 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 ultra-fine particulates (aerodynamic diameter <1 µm, 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; Pačyna, 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 dom-
inates 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 character-
istics 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 particu-
late inorganic ions, trace elements, and OC and EC were de-
termined to better understand the importance of the sources
contributing to the various chemical species in these settle-
ments.

2 Experiment

2.1 Site 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).

The South African Highveld is characterised by a dis-
tinct dry and wet season, with the dry season typically oc-
curring from mid-May to mid-October which coincides with
the South African winter from June to August. More pro-
nounced inversion layers and increased anticyclonic recircu-
lation 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 Octo-
ber, typically peaking during spring in September (Laban et
al., 2018). Furthermore, the removal rate of atmospheric pol-
lutants associated with precipitation is also reduced during
the dry season (Venter et al., 2018).

Kwadela is situated in the Mpumalanga Province, be-
tween 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 pol-
lution, this low-income settlement is also exposed to traf-
fic emissions from the nearby (~ 500 m) N17 national high-
way. 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 prox-
imity to the town Sasolburg in the Free State Province, in the
densely populated and highly industrialised Vaal Triangle re-
gion (Fig. 1). Sources within this region include a large petro-
chemical 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 (approx-
imately 180 km south-west of the Johannesburg-Pretoria
conurbation). The main anthropogenic activities in this re-
gion 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).

## 2.2 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 <0.25 µm 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 dur-
<figure><img src="image_5.png" /><figcaption>**Figure 1.** Map of South Africa indicating the location of the four low-income urban settlements and major large point sources within the north-eastern interior.</figcaption></figure>

ing 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.

## 2.3 Chemical analyses

### 2.3.1 Inorganic 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 ≈ 18.2 MΩ) in an ultrasonic bath for 30 min. The extracted aqueous samples were then analysed by suppressed conductivity with a Dionex ICS 3000 ion chromatograph.
graph (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 $SO_4^{2-}$, $NO_3^-$, $Cl^-$, $F^-$, $Na^+$, $NH_4^+$, $K^+$, $Mg^{2+}$, and $Ca^{2+}$, while water-soluble organic acids (OA) include formic ($COO^-$), acetic ($CH_3COO^-$), propionic ($C_2H_5COO^-$), and oxalic acid ($C_2O_4^{2-}$). 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.

### 2.3.2 Trace 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 $HNO_3$ 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 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.

### 2.3.3 Carbonaceous aerosol

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.

## 3 Results and discussion

### 3.1 Mass 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.

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
<table><caption>**Table 1.** DLs (ppb) of inorganic ions and water-soluble organic acids determined in this study.</caption><thead><tr><th>SO<sub>4</sub><sup>2-</sup></th><th>NO<sub>3</sub><sup>-</sup></th><th>Cl<sup>-</sup></th><th>F<sup>-</sup></th><th>Na<sup>+</sup></th><th>NH<sub>4</sub><sup>+</sup></th><th>K<sup>+</sup></th><th>Mg<sup>2+</sup></th><th>Ca<sup>2+</sup></th></tr></thead><tbody><tr><td>5.699</td><td>52.581</td><td>17.456</td><td>10.750</td><td>33.584</td><td>20.128</td><td>27.244</td><td>21.047</td><td>18.718</td></tr><tr><td>COO<sup>-</sup></td><td>CH<sub>3</sub>COO<sup>-</sup></td><td>C<sub>2</sub>H<sub>5</sub>COO<sup>-</sup></td><td>C<sub>2</sub>O<sub>4</sub><sup>2-</sup></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>18.202</td><td>28.147</td><td>15.73</td><td>17.242</td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>

<table><caption>**Table 2.** DLs (ppb × 10⁻²) of trace elements determined in this study.</caption><thead><tr><th>Be</th><th>B</th><th>Na</th><th>Mg</th><th>Al</th><th>P</th><th>K</th><th>Ca</th><th>Ti</th><th>V</th><th>Cr</th><th>Mn</th><th>Fe</th><th>Co</th></tr></thead><tbody><tr><td>1.165</td><td>19.04</td><td>29.58</td><td>22.09</td><td>65.07</td><td>377.3</td><td>406.9</td><td>93.2</td><td>1.432</td><td>4.466</td><td>359.9</td><td>4.156</td><td>60.72</td><td>0.625</td></tr><tr><th>Ni</th><th>Cu</th><th>Zn</th><th>As</th><th>Se</th><th>Rb</th><th>Sr</th><th>Mo</th><th>Pd</th><th>Ag</th><th>Cd</th><th>Sb</th><th>Ba</th><th>Pt</th></tr><tr><td>3.229</td><td>4.186</td><td>6.212</td><td>5.686</td><td>8.559</td><td>0.268</td><td>1.238</td><td>0.681</td><td>0.246</td><td>2.447</td><td>1.119</td><td>0.712</td><td>1.670</td><td>0.381</td></tr><tr><th>Au</th><th>Hg</th><th>Tl</th><th>Pb</th><th>Bi</th><th>Th</th><th>U</th><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>2.156</td><td>2.836</td><td>0.411</td><td>0.587</td><td>0.309</td><td>0.160</td><td>0.113</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>

Zamdela, where the PM<sub>2.5–10</sub> 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.

## 3.2 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 PM<sub>10</sub>, and Fig. 4b presents the normalised concentration distribution of each of these ionic species in the three size fractions. Concentrations of COO<sup>-</sup>, CH<sub>3</sub>COO<sup>-</sup>, C<sub>2</sub>H<sub>5</sub>COO<sup>-</sup>, and C<sub>2</sub>O<sub>4</sub><sup>2-</sup> 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.

It is evident from Figs. 3 and 4a that the highest concentration was determined for SO<sub>4</sub><sup>2-</sup> at each site during the respective sampling campaigns, while NH<sub>4</sub><sup>+</sup> and NO<sub>3</sub><sup>-</sup> were the second most abundant species. Moderately higher Ca<sup>2+</sup> levels were also measured, especially during the winter outdoor and the summer indoor campaigns, with the mean Ca<sup>2+</sup> concentration determined for the latter sampling campaign being higher than the average NH<sub>4</sub><sup>+</sup> concentration measured during this campaign. Concentrations of other ionic species were at

least an order of magnitude lower compared to SO<sub>4</sub><sup>2-</sup>, NH<sub>4</sub><sup>+</sup>, and NO<sub>3</sub><sup>-</sup> levels. The highest SO<sub>4</sub><sup>2-</sup> concentrations were determined during the summer and winter outdoor campaigns conducted at Zamdela, while similar SO<sub>4</sub><sup>2-</sup> levels were determined for the other two summer outdoor campaigns and the summer indoor campaign. NO<sub>3</sub><sup>-</sup> 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 NH<sub>4</sub><sup>+</sup> concentration recorded for the winter outdoor campaign was significantly higher compared to NH<sub>4</sub><sup>+</sup> levels determined for other sampling campaigns. NH<sub>4</sub><sup>+</sup> concentrations were higher than NO<sub>3</sub><sup>-</sup> levels for the three summer outdoor campaigns, while NO<sub>3</sub><sup>-</sup> concentrations exceeded NH<sub>4</sub><sup>+</sup> levels during the winter outdoor and summer indoor campaign. SO<sub>4</sub><sup>2-</sup> concentrations for the four summer (outdoor and indoor) campaigns were nearly 4 times higher compared to NH<sub>4</sub><sup>+</sup> levels, while being approximately 2 times higher than NH<sub>4</sub><sup>+</sup> concentrations determined for the winter outdoor campaign. NO<sub>3</sub><sup>-</sup> concentrations were approximately 3 times lower than SO<sub>4</sub><sup>2-</sup> levels measured during the winter outdoor and summer indoor campaigns, and almost an order of magnitude lower compared to SO<sub>4</sub><sup>2-</sup> concentrations determined for the three summer outdoor campaigns.

SO<sub>4</sub><sup>2-</sup> and NH<sub>4</sub><sup>+</sup> levels in the PM<sub>1</sub> 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 PM<sub>1</sub> were approximately 5 times higher than levels thereof in PM<sub>1–2.5</sub> and PM<sub>2.5–10</sub>. NO<sub>3</sub><sup>-</sup> concentrations in samples collected during the winter outdoor and summer indoor campaign were also an order of magnitude higher in the PM<sub>1</sub> size fraction, while also being marginally higher
<figure><img src="image_6.png" /><figcaption>**Figure 2.** 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.</figcaption></figure>

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
<figure><img src="image_7.png" /><figcaption>**Figure 3.** 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.</figcaption></figure>
<figure><img src="image_8.png" /><figcaption>**Figure 4.** (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.</figcaption></figure>

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.

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 sum-
<table><caption>**Table 3.** 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.</caption><thead><tr><th>Source</th><th>Date</th><th>Place</th><th>SO<sub>4</sub><sup>2-</sup></th><th>NO<sub>3</sub><sup>-</sup></th><th>Cl<sup>-</sup></th><th>F<sup>-</sup></th><th>OA</th><th>Na<sup>+</sup></th><th>NH<sub>4</sub><sup>+</sup></th><th>K<sup>+</sup></th><th>Mg<sup>2+</sup></th><th>Ca<sup>2+</sup></th></tr></thead><tbody><tr><td rowspan="12">This study</td><td rowspan="12">03/2015-03/2017</td><td rowspan="3">Kwadela<sup>a</sup></td><td>Mean PM<sub>1</sub></td><td>1.84</td><td>0.097</td><td>0.08</td><td>0.0001</td><td>0.033</td><td>0.02</td><td>0.61</td><td>0.02</td><td>0.026</td><td>0.06</td></tr><tr><td>Mean PM<sub>1-2.5</sub></td><td>0.04</td><td>0.021</td><td>0.03</td><td>0.0001</td><td>0.004</td><td>0.01</td><td>0.01</td><td>0.001</td><td>0.011</td><td>0.02</td></tr><tr><td>Mean PM<sub>2.5-10</sub></td><td>0.06</td><td>0.044</td><td>0.03</td><td>0.0012</td><td>0.006</td><td>0.01</td><td>0.01</td><td>0.004</td><td>0.015</td><td>0.04</td></tr><tr><td rowspan="3">Kwazamokuhle<sup>a</sup></td><td>Mean PM<sub>1</sub></td><td>2.06</td><td>0.11</td><td>0.02</td><td>0.0006</td><td>0.056</td><td>0.03</td><td>0.77</td><td>0.03</td><td>0.008</td><td>0.07</td></tr><tr><td>Mean PM<sub>1-2.5</sub></td><td>0.05</td><td>0.05</td><td>0.01</td><td>0.0005</td><td>0.012</td><td>0.02</td><td>0.01</td><td>0.003</td><td>0.003</td><td>0.02</td></tr><tr><td>Mean PM<sub>2.5-10</sub></td><td>0.06</td><td>0.10</td><td>0.02</td><td>0.0021</td><td>0.012</td><td>0.02</td><td>0.02</td><td>0.01</td><td>0.005</td><td>0.04</td></tr><tr><td rowspan="3">Zamdela<sup>a</sup></td><td>Mean PM<sub>1</sub></td><td>2.80</td><td>0.70</td><td>0.06</td><td>0.006</td><td>0.049</td><td>0.03</td><td>1.27</td><td>0.11</td><td>0.012</td><td>0.14</td></tr><tr><td>Mean PM<sub>1-2.5</sub></td><td>0.11</td><td>0.17</td><td>0.03</td><td>0.010</td><td>0.007</td><td>0.02</td><td>0.05</td><td>0.01</td><td>0.012</td><td>0.12</td></tr><tr><td>Mean PM<sub>2.5-10</sub></td><td>0.12</td><td>0.27</td><td>0.03</td><td>0.008</td><td>0.007</td><td>0.02</td><td>0.07</td><td>0.02</td><td>0.011</td><td>0.14</td></tr><tr><td rowspan="3">Jouberton<sup>b</sup></td><td>Mean PM<sub>1</sub></td><td>1.64</td><td>0.92</td><td>0.05</td><td>0.003</td><td>0.07</td><td>0.06</td><td>0.60</td><td>0.06</td><td>0.017</td><td>0.22</td></tr><tr><td>Mean PM<sub>1-2.5</sub></td><td>0.07</td><td>0.27</td><td>0.04</td><td>0.001</td><td>0.03</td><td>0.05</td><td>0.05</td><td>0.02</td><td>0.010</td><td>0.19</td></tr><tr><td>Mean PM<sub>2.5-10</sub></td><td>0.16</td><td>0.30</td><td>0.07</td><td>0.001</td><td>0.02</td><td>0.09</td><td>0.04</td><td>0.04</td><td>0.020</td><td>0.47</td></tr><tr><td colspan="13">South Africa</td></tr><tr><td>Aurela et al. (2016)</td><td>9-5/10/2007 &amp; 01-02/2008</td><td>Botsalano, rural<sup>a</sup></td><td>Mean PM<sub>1</sub></td><td>3.92</td><td>0.03</td><td>—</td><td>—</td><td>—</td><td>0.05</td><td>1.02</td><td>0.18</td><td>—</td><td>—</td></tr><tr><td rowspan="2">Titta et al. (2014)</td><td rowspan="2">09/2010-08/2011</td><td rowspan="2">Welgegund, regional<sup>a</sup></td><td>Mean PM<sub>1</sub></td><td>2.4</td><td>0.5</td><td>0.03</td><td>—</td><td>—</td><td>—</td><td>0.9</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Median PM<sub>2.5</sub></td><td>1.83</td><td>0.27</td><td>0.07</td><td>—</td><td>—</td><td>0.09</td><td>0.55</td><td>0.09</td><td>0.02</td><td>0.08</td></tr><tr><td rowspan="2">Venter et al. (2018)</td><td rowspan="2">11/2008-10/2009</td><td rowspan="2">Marikana<sup>a</sup>, industrial</td><td>Median PM<sub>2.5-10</sub></td><td>0.37</td><td>0.40</td><td>0.06</td><td>—</td><td>—</td><td>0.07</td><td>0.09</td><td>0.03</td><td>0.04</td><td>0.17</td></tr><tr><td>Median PM<sub>1</sub></td><td>1.35</td><td>0.02</td><td>0.005</td><td>0.015</td><td>—</td><td>0.16</td><td>0.44</td><td>0.032</td><td>0.003</td><td>0.019</td></tr><tr><td rowspan="2">Adon et al. (2020)</td><td rowspan="2">07/2015-01/2017</td><td rowspan="2">Welgegund<sup>a</sup>, regional</td><td>Median PM<sub>1-2.5</sub></td><td>0.1</td><td>0.04</td><td>0.0055</td><td>&gt;0.005</td><td>—</td><td>0.21</td><td>0.04</td><td>0.004</td><td>0.005</td><td>0.014</td></tr><tr><td>Median PM<sub>2.5-10</sub></td><td>0.05</td><td>0.057</td><td>0.007</td><td>&gt;0.005</td><td>—</td><td>0.019</td><td>0.005</td><td>0.005</td><td>0.006</td><td>0.025</td></tr><tr><td colspan="13">Africa</td></tr><tr><td></td><td></td><td>Abijan, Côte Ivoire<sup>a</sup>, urban</td><td>Mean PM<sub>2.5</sub></td><td>1.23</td><td>0.86</td><td>5.73</td><td>—</td><td>0.39</td><td>0.34</td><td>2.79</td><td>1.99</td><td>0.18</td><td>0.55</td></tr><tr><td></td><td></td><td>Domestic fire site<sup>a</sup></td><td>Mean PM<sub>1-0.1/0.2</sub></td><td>0.64</td><td>1.36</td><td>1.31</td><td>—</td><td>0.27</td><td>0.76</td><td>0.11</td><td>0.39</td><td>0.44</td><td>0.98</td></tr><tr><td></td><td></td><td>Waste burning site<sup>a</sup></td><td>Mean PM<sub>2.5-1</sub></td><td>0.29</td><td>0.54</td><td>0.59</td><td>—</td><td>0.25</td><td>0.38</td><td>0.07</td><td>0.22</td><td>0.23</td><td>0.87</td></tr><tr><td></td><td></td><td>Adon et al. (2020)</td><td>Mean PM<sub>2.5-1</sub></td><td>1.88</td><td>0.89</td><td>0.37</td><td>—</td><td>0.24</td><td>0.06</td><td>0.96</td><td>0.64</td><td>0.03</td><td>0.37</td></tr><tr><td></td><td></td><td>Waste burning site<sup>a</sup></td><td>Mean PM<sub>1-0.1/0.2</sub></td><td>0.50</td><td>1.74</td><td>0.94</td><td>—</td><td>0.14</td><td>0.71</td><td>0.06</td><td>0.11</td><td>0.11</td><td>0.74</td></tr><tr><td></td><td></td><td>Adon et al. (2020)</td><td>Mean PM<sub>2.5-1</sub></td><td>0.27</td><td>0.75</td><td>0.66</td><td>—</td><td>0.10</td><td>0.48</td><td>0.08</td><td>0.06</td><td>0.06</td><td>0.39</td></tr><tr><td></td><td></td><td>Adon et al. (2020)</td><td>Mean PM<sub>2.5-1</sub></td><td>1.23</td><td>1.34</td><td>0.25</td><td>—</td><td>0.21</td><td>0.07</td><td>0.60</td><td>0.55</td><td>0.03</td><td>0.48</td></tr><tr><td></td><td></td><td>Adon et al. (2020)</td><td>Mean PM<sub>1-0.1/0.2</sub></td><td>0.41</td><td>1.52</td><td>0.85</td><td>—</td><td>0.12</td><td>0.65</td><td>0.14</td><td>0.09</td><td>0.08</td><td>0.79</td></tr><tr><td></td><td></td><td>Adon et al. (2020)</td><td>Mean PM<sub>2.5-1</sub></td><td>0.21</td><td>0.60</td><td>0.64</td><td>—</td><td>0.10</td><td>0.45</td><td>0.06</td><td>0.05</td><td>0.05</td><td>0.49</td></tr><tr><td></td><td></td><td>Adon et al. (2020)</td><td>Mean PM<sub>2.5-1</sub></td><td>2.14</td><td>1.50</td><td>0.47</td><td>—</td><td>0.29</td><td>0.25</td><td>0.34</td><td>0.68</td><td>0.07</td><td>1.89</td></tr><tr><td></td><td></td><td>Adon et al. (2020)</td><td>Mean PM<sub>1-0.1/0.2</sub></td><td>1.04</td><td>2.77</td><td>1.61</td><td>—</td><td>0.19</td><td>1.14</td><td>0.17</td><td>0.18</td><td>0.17</td><td>1.90</td></tr><tr><td></td><td></td><td>Adon et al. (2020)</td><td>Mean PM<sub>2.5-1</sub></td><td>0.39</td><td>0.91</td><td>0.94</td><td>—</td><td>0.10</td><td>0.65</td><td>0.08</td><td>0.06</td><td>0.07</td><td>1.13</td></tr><tr><td colspan="13">Other international locations</td></tr><tr><td>Bressi et al. (2013)</td><td>09/2009-09/2010</td><td>Paris, France<sup>a</sup></td><td>Mean PM<sub>2.5</sub></td><td>1.9</td><td>2.7</td><td>0.18</td><td>—</td><td>—</td><td>0.16</td><td>1.4</td><td>0.12</td><td>0.03</td><td>0.08</td></tr><tr><td>Szigeti et al. (2015)</td><td>06/2010-05/2013</td><td>Széna Square, Budapest, Hungary<sup>a</sup></td><td>Mean PM<sub>2.5</sub></td><td>2.84</td><td>2.14</td><td>0.11</td><td>—</td><td>—</td><td>0.22</td><td>1.33</td><td>0.18</td><td>0.05</td><td>0.16</td></tr><tr><td>Qiu et al. (2016)</td><td>03/2012-03/2013</td><td>Weinan, China<sup>a</sup></td><td>Mean PM<sub>2.5</sub></td><td>24.7</td><td>18</td><td>3</td><td>0.1</td><td>—</td><td>1.3</td><td>10</td><td>1.3</td><td>0.2</td><td>1.6</td></tr><tr><td>Shao et al. (2018)</td><td>12/2016-01/2017</td><td>Beijing, China<sup>a</sup></td><td>Mean PM<sub>2.5</sub></td><td>20.93</td><td>29.09</td><td>4.07</td><td>—</td><td>—</td><td>0.58</td><td>15.44</td><td>1.4</td><td>0.23</td><td>0.69</td></tr><tr><td>Gawhane et al. (2017)</td><td>04/2015-04/2016</td><td>Pune, India<sup>a</sup></td><td>Mean PM<sub>2.5</sub></td><td>4.8</td><td>0.98</td><td>3.42</td><td>—</td><td>—</td><td>1.98</td><td>0.51</td><td>0.47</td><td>0.28</td><td>0.51</td></tr><tr><td>Kumar and Raman (2016)</td><td>01/2012-12/2013</td><td>Van Vihar National Park (VVNP) Bhopal, central India<sup>a</sup></td><td>Mean PM<sub>2.5</sub></td><td>3.35</td><td>3.02</td><td>1.46</td><td>0.35</td><td>—</td><td>0.96</td><td>2.07</td><td>0.98</td><td>0.18</td><td>0.77</td></tr><tr><td>Castro et al. (2018)</td><td>03/2006-03/2006</td><td>Tecímac University, Mexico<sup>a</sup></td><td>Mean PM<sub>3.2</sub></td><td>3.42</td><td>1.81</td><td>0.73</td><td>—</td><td>—</td><td>—</td><td>1.09</td><td>0.97</td><td>0.23</td><td>1.08</td></tr></tbody></table>

<footnote><sup>a</sup> = Outdoor, <sup>b</sup> = Indoor.</footnote>
mer 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. SO₄²⁻ 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.

### 3.3 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:

$$ [NH_4^+]_{cal} \mu g m^{-3} = 18 g mol^{-1} \times \left\{ \left( 2 \times \frac{[SO_4^{2-}] \mu g m^{-3}}{96 g mol^{-1}} \right) + \frac{[NO_3^-] \mu g m^{-3}}{62 g mol^{-1}} + \frac{[Cl^-] \mu g m^{-3}}{35.5 g mol^{-1}} \right\} \quad (1) $$

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.

## 3.4 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.

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 sam-
<figure><img src="image_9.png" /><figcaption>**Figure 5.** $[NH_4^+]_{meas}$ in relation to $[NH_4^+]_{cal}$ for PM₁ collected during outdoor summer, outdoor winter, and indoor sampling campaigns.</figcaption></figure>

pling 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.

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.

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.
<table><caption>**Table 4.** 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).</caption><thead><tr><th rowspan="3">Element</th><th rowspan="3">limits (×10<sup>-5</sup>)</th><th colspan="8">South Africa</th><th colspan="3">Other countries</th></tr><tr><th colspan="2">ICP-MS detection</th><th colspan="2">Kwadela</th><th colspan="2">Kwazamokule (Outdoor)</th><th colspan="2">Zamdela</th><th rowspan="2">Annuat standards</th><th colspan="2">Welgegund</th><th colspan="2">Van Zyl et al. (2014)</th><th rowspan="2">Kleynhaus (2008)</th><th rowspan="2">Kgabi (2006)</th><th colspan="2">Bamako no desert dust</th><th colspan="2">Bamako with desert dust</th><th colspan="2">Dukar</th><th rowspan="2">Duan et al. (2012)</th><th colspan="2">Beijing, China</th><th colspan="2">Barcelona, Spain Indoor Outdoor</th></tr><tr><th>(this study)</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th></tr></thead><tbody><tr><td>Be</td><td>1.165</td><td>0.0001</td><td></td><td>1.12</td><td>0.0001</td><td></td><td>1.42</td><td>0.0004</td><td>3.17</td><td></td><td></td><td>0.0002</td><td>0.020</td><td></td><td></td><td></td><td>0.08</td><td>0.05</td><td>0.03</td><td></td><td>0.010</td><td></td><td></td><td></td><td></td></tr><tr><td>B</td><td>19.04</td><td>0.0001</td><td></td><td></td><td>0.002</td><td></td><td>1.42</td><td>0.0004</td><td>3.17</td><td></td><td></td><td>0.28</td><td>1.300</td><td></td><td></td><td></td><td>0.81</td><td>0.20</td><td>2.10</td><td></td><td>1.450</td><td>0.34</td><td>0.34</td><td></td><td></td></tr><tr><td>Na</td><td>29.58</td><td>4.75</td><td></td><td></td><td>7.72</td><td></td><td>2.69</td><td>13.75</td><td></td><td></td><td></td><td>0.38</td><td>1.410</td><td></td><td></td><td></td><td>0.96</td><td>0.28</td><td>0.41</td><td></td><td>0.637</td><td>0.16</td><td>0.19</td><td></td><td></td></tr><tr><td>Mg</td><td>22.09</td><td>0.25</td><td></td><td></td><td>1.16</td><td></td><td>0.75</td><td>3.12</td><td></td><td></td><td></td><td>0.23</td><td>2.040</td><td></td><td></td><td></td><td>7.32</td><td>2.47</td><td>1.20</td><td></td><td>2.180</td><td></td><td></td><td></td><td></td></tr><tr><td>Al</td><td>65.07</td><td>0.81</td><td></td><td></td><td>0.83</td><td></td><td>0.76</td><td>3.17</td><td></td><td></td><td></td><td>0.17</td><td>1.280</td><td></td><td></td><td></td><td>0.11</td><td>0.09</td><td>0.18</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>P</td><td>377.3</td><td>0.76</td><td></td><td></td><td>0.04</td><td></td><td>0.30</td><td>4.48</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.680</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>K</td><td>486.9</td><td>0.08</td><td></td><td></td><td>0.94</td><td></td><td>0.28</td><td>1.78</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>1.300</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Ca</td><td>95.2</td><td>2.66</td><td></td><td></td><td>9.50</td><td></td><td>6.70</td><td>3.13</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>1.080</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Ti</td><td>1.432</td><td>0.09</td><td></td><td></td><td>0.08</td><td></td><td>0.04</td><td>0.18</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.072</td><td>0.120</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>V</td><td>4.466</td><td>0.47</td><td></td><td></td><td>0.01</td><td></td><td>0.01</td><td>0.11</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.040</td><td>0.050</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Cr</td><td>359.9</td><td>9.16</td><td></td><td></td><td>0.07</td><td></td><td>0.47</td><td>9.00</td><td>2.5 × 10<sup>-5</sup></td><td>0.15<sup>b</sup></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.240</td><td>0.240</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Mn</td><td>4.156</td><td>0.21</td><td></td><td></td><td>0.05</td><td></td><td>0.06</td><td>0.17</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.060</td><td>0.120</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Fe</td><td>60.72</td><td>0.88</td><td></td><td></td><td>1.63</td><td></td><td>1.63</td><td>4.87</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.240</td><td>2.540</td><td>1.280</td><td></td><td>4.15</td><td>1.98</td><td>0.88</td><td></td></tr><tr><td>Co</td><td>0.625</td><td>0.11</td><td></td><td></td><td>0.13</td><td></td><td>0.19</td><td>0.19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.0035</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Ni</td><td>3.229</td><td>0.39</td><td></td><td></td><td>0.16</td><td></td><td>0.19</td><td>1.49</td><td>0.020<sup>c</sup></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.079</td><td>0.330</td><td>0.050</td><td></td><td></td><td></td><td></td></tr><tr><td>Cu</td><td>4.186</td><td>0.02</td><td></td><td></td><td>0.18</td><td></td><td>0.06</td><td>0.47</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.0069</td><td>0.180</td><td>0.090</td><td></td><td></td><td></td><td></td></tr><tr><td>Zn</td><td>6.212</td><td>0.16</td><td></td><td></td><td>0.24</td><td></td><td>0.31</td><td>0.68</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.053</td><td>0.490</td><td>0.090</td><td></td><td></td><td></td><td></td></tr><tr><td>As</td><td>5.686</td><td>0.07</td><td></td><td></td><td>0.002</td><td></td><td>0.002</td><td>0.03</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.0084</td><td>0.260</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Se</td><td>8.559</td><td>0.01</td><td></td><td></td><td>0.01</td><td></td><td>0.02</td><td>0.02</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.0074</td><td>0.580</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Rb</td><td>0.268</td><td>0.002</td><td></td><td></td><td>0.01</td><td></td><td>0.004</td><td>0.03</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.0017</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Sr</td><td>1.238</td><td>0.01</td><td></td><td></td><td>0.08</td><td></td><td>0.01</td><td>0.04</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.015</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Mo</td><td>0.681</td><td>0.01</td><td></td><td></td><td>0.01</td><td></td><td>0.03</td><td>0.03</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.0018</td><td>0.410</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Pd</td><td>0.246</td><td>0.01</td><td></td><td></td><td>0.01</td><td></td><td>0.01</td><td>0.03</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.0005</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Ag</td><td>2.447</td><td>0.03</td><td></td><td></td><td>0.58</td><td></td><td>0.05</td><td>0.05</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.0005</td><td>0.0004</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Cd</td><td>1.119</td><td>0.01</td><td></td><td></td><td>0.01</td><td></td><td>0.012</td><td>0.018</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.0013</td><td>0.0013</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Sb</td><td>0.712</td><td>0.001</td><td></td><td></td><td>0.001</td><td></td><td>0.005</td><td>0.005</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.0040</td><td>0.140</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Ba</td><td>1.670</td><td>0.09</td><td></td><td></td><td>0.17</td><td></td><td>0.109</td><td>0.088</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.0016</td><td>0.350</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Pt</td><td>0.381</td><td>0.003</td><td></td><td></td><td>0.01</td><td></td><td>0.032</td><td>0.016</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.0031</td><td>0.380</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Au</td><td>2.156</td><td>0.001</td><td></td><td></td><td>0.03</td><td></td><td>0.007</td><td>0.191</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.0002</td><td>0.550</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Hg</td><td>2.836</td><td>0.038</td><td></td><td></td><td>0.00004</td><td></td><td>0.00003</td><td>0.0001</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.0007</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Tl</td><td>0.411</td><td>0.00003</td><td></td><td></td><td>0.152</td><td></td><td>0.067</td><td>0.070</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.0078</td><td>0.25c,d</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Pb</td><td>0.587</td><td>0.080</td><td></td><td></td><td>0.003</td><td></td><td>0.002</td><td>0.001</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.0008</td><td>0.080</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Bi</td><td>0.309</td><td>0.008</td><td></td><td></td><td>0.003</td><td></td><td>0.002</td><td>0.001</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.001</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Th</td><td>0.160</td><td>0.00001</td><td></td><td></td><td>0.002</td><td></td><td>0.001</td><td>0.001</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.0002</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>U</td><td>0.113</td><td>0.0002</td><td></td><td></td><td>0.0017</td><td></td><td>0.001</td><td>0.002</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.0009</td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>

<footnote><sup>a</sup> WHO guideline for Cr(VI) concentrations associated with an excess lifetime risk of 1:100000. <sup>b</sup> WHO air quality guidelines for Europe. <sup>c</sup> European Commission Air Quality Standards. <sup>d</sup> National Air Quality Act of the South African Department of Environmental Affairs. <sup>e</sup> 24h limit value.</footnote>
<figure><img src="image_10.png" /><figcaption>**Figure 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.</figcaption></figure>

plex, 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.
<figure><img src="image_11.png" /><figcaption>**Figure 7.** 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.</figcaption></figure>

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 : 1 000 000.

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.

## 3.5 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.

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
<figure><img src="image_12.png" /><figcaption>**Figure 8.** 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.</figcaption></figure>

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 $SO_4^{2-}/EC$ ratio also indicating significantly higher $SO_4^{2-}$ concentrations than EC levels in PM₁. However, substantially lower $SO_4^{2-}$ levels in PM₁-2.5 and PM₂.₅-₁₀ are also reflected in these ratios, with EC concentrations exceeding $SO_4^{2-}$ levels in most instances in the two larger size fractions. A larger contribution from EC in relation to $SO_4^{2-}$ 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.

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.

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 re-

mote site in the Himalayan region were still higher than levels thereof measured in low-income settlements in this study.

## 3.6 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 $Ca^{2+}$ levels and a conversion factor, f, which is the correlation coefficient between $Ca^{2+}$ 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 $Ca^{2+}$, 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:

$$ \text{dust} = 1.89[\text{Al}] + 2.14[\text{Si}] + 1.95[\text{Ca}] + 1.42[\text{Fe}] + 1.7[\text{Ti}] + 1.21[\text{K}] + 1.66[\text{Mg}], \quad (2) $$

with Si concentrations estimated by the relationship $2.03 \times \text{Al}$ 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 ($R^2 = 0.80$) is observed between
<table><caption>**Table 5.** 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.</caption><thead><tr><th>Source</th><th>Period</th><th>Place</th><th>Area</th><th>OC</th><th>EC</th></tr></thead><tbody><tr><td rowspan="12">This study</td><td rowspan="12">03/2015–03/2017</td><td rowspan="3">Kwadela</td><td>Mean PM<sub>1</sub></td><td>0.63</td><td>0.51</td></tr><tr><td>Mean PM<sub>1–2.5</sub></td><td>0.03</td><td>0.07</td></tr><tr><td>Mean PM<sub>2.5–10</sub></td><td>0.07</td><td>0.09</td></tr><tr><td rowspan="3">Kwazamokuhle</td><td>Mean PM<sub>1</sub></td><td>0.17</td><td>0.37</td></tr><tr><td>Mean PM<sub>1–2.5</sub></td><td>0.02</td><td>0.08</td></tr><tr><td>Mean PM<sub>2.5–10</sub></td><td>0.06</td><td>0.09</td></tr><tr><td rowspan="3">Zamdela</td><td>Mean PM<sub>1</sub></td><td>0.44</td><td>0.52</td></tr><tr><td>Mean PM<sub>1–2.5</sub></td><td>0.10</td><td>0.08</td></tr><tr><td>Mean PM<sub>2.5–10</sub></td><td>0.19</td><td>0.09</td></tr><tr><td rowspan="3">Jouberton</td><td>Mean PM<sub>1</sub></td><td>0.89</td><td>1.11</td></tr><tr><td>Mean PM<sub>1–2.5</sub></td><td>0.21</td><td>0.26</td></tr><tr><td>Mean PM<sub>2.5–10</sub></td><td>0.55</td><td>0.33</td></tr><tr><td colspan="6" style="text-align: center; font-weight: bold;">South Africa</td></tr><tr><td rowspan="5">Chiloane et al. (2017)</td><td rowspan="5">03/2009–04/2011</td><td>Louis Trichardt</td><td>Outdoor</td><td>Mean PM<sub>10</sub></td><td>0.90</td></tr><tr><td>Skukuza</td><td>Outdoor</td><td>Mean PM<sub>10</sub></td><td>1.10</td></tr><tr><td>Vaal Triangle</td><td>Outdoor</td><td>Mean PM<sub>10</sub></td><td>4.40</td></tr><tr><td>Amersfoort</td><td>Outdoor</td><td>Mean PM<sub>10</sub></td><td>1.40</td></tr><tr><td>Botsalano</td><td>Outdoor</td><td>Mean PM<sub>10</sub></td><td>0.90</td></tr><tr><td rowspan="5">Maritz et al. (2019)</td><td rowspan="5">03/2009–12/2015</td><td>Louis Trichardt</td><td>Outdoor</td><td>Mean PM<sub>2.5</sub></td><td>3.8</td><td>0.7</td></tr><tr><td>Skukuza</td><td>Outdoor</td><td>Mean PM<sub>2.5</sub></td><td>6.9</td><td>1.1</td></tr><tr><td>Vaal Triangle</td><td>Outdoor</td><td>Mean PM<sub>2.5</sub></td><td>9.3</td><td>3.2</td></tr><tr><td>Amersfoort</td><td>Outdoor</td><td>Mean PM<sub>2.5</sub></td><td>6.0</td><td>1.2</td></tr><tr><td>Vaal Triangle</td><td>Outdoor</td><td>Mean PM<sub>1</sub> WS</td><td>0.41</td><td>0.32</td></tr><tr><td rowspan="4">Josipovic et al. (2019)</td><td rowspan="4">03–10/2012</td><td></td><td></td><td>Mean PM<sub>1–>/=2.5</sub> WS</td><td>0.18</td><td>0.23</td></tr><tr><td></td><td></td><td>Mean PM<sub>1</sub> DS</td><td>0.66</td><td>0.51</td></tr><tr><td></td><td></td><td>Mean PM<sub>1–>/=2.5</sub> DS</td><td>0.43</td><td>0.24</td></tr><tr><td colspan="6" style="text-align: center; font-weight: bold;">Other countries</td></tr><tr><td rowspan="2">Djossou et al. (2018)</td><td rowspan="2">02/2015–03/2017</td><td>Abidjan. Côte d'Ivoire</td><td>Outdoor</td><td>Mean PM<sub>2.5</sub></td><td>31.0</td><td>8.67</td></tr><tr><td>Cotonou. Benin</td><td>Outdoor</td><td>Mean PM<sub>2.5</sub></td><td>8.0</td><td>2.0</td></tr><tr><td rowspan="2">Rivas et al. (2014)</td><td rowspan="2">0/2012–02/2013</td><td rowspan="2">Barcelona. Spain</td><td>Indoor</td><td>Mean PM<sub>2.5</sub></td><td>10</td><td>1.3</td></tr><tr><td>Outdoor</td><td>Mean PM<sub>2.5</sub></td><td>5.5</td><td>1.3</td></tr><tr><td rowspan="2">Ho et al. (2004)</td><td rowspan="2"></td><td rowspan="2">Hong Kong</td><td>Indoor</td><td>Mean PM<sub>2.5</sub></td><td>11.3</td><td>4.8</td></tr><tr><td>Outdoor</td><td>Mean PM<sub>2.5</sub></td><td>12.6</td><td>6.4</td></tr><tr><td rowspan="2">Cao et al. (2012)</td><td rowspan="2">07/2004–01/2005</td><td rowspan="2">Guangzhou. China</td><td>Indoor</td><td>Mean PM<sub>2.5</sub></td><td>21.75</td><td>7.6</td></tr><tr><td>Outdoor</td><td>Mean PM<sub>2.5</sub></td><td>21.9</td><td>7.9</td></tr><tr><td rowspan="2">Xu et al. (2015)</td><td rowspan="2">03/2015</td><td rowspan="2">Xi'an. China</td><td>Indoor</td><td>Mean PM<sub>2.5</sub></td><td>22.5</td><td>7.9</td></tr><tr><td>Outdoor</td><td>Mean PM<sub>2.5</sub></td><td>24.9</td><td>8.8</td></tr><tr><td rowspan="4">Joseph et al. (2012)</td><td rowspan="4">2007–2008</td><td>Coloba. Mumbai (India)</td><td>Outdoor</td><td>Mean PM<sub>2.5</sub></td><td>20.40</td><td>5.00</td></tr><tr><td>Dadar. Mumbai (India)</td><td>Outdoor</td><td>Mean PM<sub>2.5</sub></td><td>28.40</td><td>9.20</td></tr><tr><td>Khar. Mumbai (India)</td><td>Outdoor</td><td>Mean PM<sub>2.5</sub></td><td>31.30</td><td>7.70</td></tr><tr><td>Mahul. Mumbai (India)</td><td>Outdoor</td><td>Mean PM<sub>2.5</sub></td><td>29.10</td><td>7.20</td></tr><tr><td>Sharma et al. (2020)</td><td>10/2018–02/2019</td><td>Himalayan region. India</td><td>Outdoor</td><td>Mean PM<sub>10</sub></td><td>3.91</td><td>1.24</td></tr></tbody></table>
<figure><img src="image_13.png" /><figcaption>**Figure 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.</figcaption></figure>

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.

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 ele-

ment 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 col-
<table><caption>**Table 6.** Dust concentrations (µg m⁻³) estimated according to the methods of Guinot et al. (2007) and Terzi et al. (2010).</caption><thead><tr><th>Site</th><th>Size fraction</th><th>Guinot et al. (2007)</th><th>Terzi et al. (2010)</th></tr></thead><tbody><tr><td rowspan="2">Kwadela-S</td><td>PM<sub>1–2.5</sub></td><td>0.9</td><td>1.9</td></tr><tr><td>PM<sub>2.5–10</sub></td><td>2.1</td><td>2.6</td></tr><tr><td rowspan="2">Kwazamokuhle-S</td><td>PM<sub>1–2.5</sub></td><td>1.7</td><td>8.3</td></tr><tr><td>PM<sub>2.5–10</sub></td><td>2.7</td><td>7.0</td></tr><tr><td rowspan="2">Zamdela-S</td><td>PM<sub>1–2.5</sub></td><td>1.4</td><td>1.4</td></tr><tr><td>PM<sub>2.5–10</sub></td><td>2.9</td><td>2.6</td></tr><tr><td rowspan="2">Zamdela-W</td><td>PM<sub>1–2.5</sub></td><td>8.3</td><td>9.6</td></tr><tr><td>PM<sub>2.5–10</sub></td><td>9.5</td><td>7.4</td></tr><tr><td rowspan="2">Jouberton-S</td><td>PM<sub>1–2.5</sub></td><td>7.9</td><td>7.3</td></tr><tr><td>PM<sub>2.5–10</sub></td><td>21.0</td><td>12.6</td></tr></tbody></table>

lected during the winter and summer outdoor campaigns at Zamdela.

## 4 Summary and conclusions

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 SO₄²⁻ at each site during the respective sampling campaigns, while NH₄⁺ and NO₃⁻ were the second most abundant species. SO₄²⁻ and NH₄⁺ almost exclusively occurred in the PM₁ size fraction, while NO₃⁻ was the major constituent in the larger size fractions. The highest SO₄²⁻ 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
<table><caption>**Table 7.** Chemical mass closure according to the method of Guinot et al. (2007).</caption><thead><tr><th>Site</th><th>Size fraction</th><th>EC (%)</th><th>POM (%)</th><th>Inorganic ions (%)</th><th>Dust (%)</th><th>Not determined (%)</th><th>PM mass (µg m<sup>-3</sup>)</th><th>Reconstructed mass (µg m<sup>-3</sup>)</th><th>Missing mass (µg m<sup>-3</sup>)</th></tr></thead><tbody><tr><td rowspan="2">Kwadela-S</td><td>PM<sub>1</sub>–2.5</td><td>4.1</td><td>3.2</td><td>7.6</td><td>46.6</td><td>38.5</td><td>1.8</td><td>1.1</td><td>0.7</td></tr><tr><td>PM<sub>2.5–10</sub></td><td>2.8</td><td>4.1</td><td>7.0</td><td>69.3</td><td>16.7</td><td>3.1</td><td>2.5</td><td>0.5</td></tr><tr><td rowspan="2">Kwazamokuhle-S</td><td>PM<sub>1</sub>–2.5</td><td>3.3</td><td>1.5</td><td>7.1</td><td>71.3</td><td>16.7</td><td>2.4</td><td>2.0</td><td>0.4</td></tr><tr><td>PM<sub>2.5–10</sub></td><td>2.2</td><td>3.1</td><td>6.8</td><td>64.4</td><td>23.5</td><td>4.2</td><td>3.2</td><td>1.0</td></tr><tr><td rowspan="2">Zamdela-S</td><td>PM<sub>1</sub>–2.5</td><td>2.8</td><td>2.0</td><td>11.9</td><td>64.6</td><td>18.8</td><td>2.2</td><td>1.8</td><td>0.4</td></tr><tr><td>PM<sub>2.5–10</sub></td><td>1.7</td><td>3.0</td><td>8.1</td><td>59.9</td><td>27.3</td><td>4.8</td><td>3.5</td><td>1.3</td></tr><tr><td rowspan="2">Zamdela-W</td><td>PM<sub>1</sub>–2.5</td><td>0.7</td><td>2.1</td><td>5.5</td><td>55.1</td><td>36.6</td><td>15.1</td><td>9.6</td><td>5.5</td></tr><tr><td>PM<sub>2.5–10</sub></td><td>0.8</td><td>4.4</td><td>7.8</td><td>75.8</td><td>11.2</td><td>12.5</td><td>11.1</td><td>1.4</td></tr><tr><td rowspan="2">Jouberton-S</td><td>PM<sub>1</sub>–2.5</td><td>1.6</td><td>1.6</td><td>5.5</td><td>59.5</td><td>31.8</td><td>13.3</td><td>9.1</td><td>4.2</td></tr><tr><td>PM<sub>2.5–10</sub></td><td>0.8</td><td>2.1</td><td>3.9</td><td>67.2</td><td>26.0</td><td>31.2</td><td>23.1</td><td>8.1</td></tr></tbody></table>

<table><caption>**Table 8.** Chemical mass closure according to the method of Terzi et al. (2010).</caption><thead><tr><th>Site</th><th>Size fraction</th><th>EC (%)</th><th>POM (%)</th><th>Inorganic ions (%)</th><th>Dust (%)</th><th>Trace elements (%)</th><th>Not determined (%)</th><th>PM mass (µg m<sup>-3</sup>)</th><th>Reconstructed mass (µg m<sup>-3</sup>)</th><th>Missing mass (µg m<sup>-3</sup>)</th></tr></thead><tbody><tr><td rowspan="3">Kwadela-S</td><td>PM<sub>1</sub></td><td>5.5</td><td>12.2</td><td>29.9</td><td>82.1</td><td>169.8</td><td>-199.5</td><td>9.3</td><td>28.6</td><td>-19.3</td></tr><tr><td>PM<sub>1–2.5</sub></td><td>4.1</td><td>3.2</td><td>7.6</td><td>103.4</td><td>244.9</td><td>-263.2</td><td>1.8</td><td>6.7</td><td>-4.9</td></tr><tr><td>PM<sub>2.5–10</sub></td><td>2.8</td><td>4.1</td><td>7.0</td><td>83.2</td><td>211.7</td><td>-211.7</td><td>3.1</td><td>9.6</td><td>-6.6</td></tr><tr><td rowspan="3">Kwazamokuhle-S</td><td>PM<sub>1</sub></td><td>5.6</td><td>4.7</td><td>40.0</td><td>186.2</td><td>92.6</td><td>-229.2</td><td>7.8</td><td>26.0</td><td>-18.2</td></tr><tr><td>PM<sub>1–2.5</sub></td><td>3.3</td><td>1.5</td><td>7.1</td><td>353.0</td><td>106.4</td><td>-371.3</td><td>2.3</td><td>11.1</td><td>-8.7</td></tr><tr><td>PM<sub>2.5–10</sub></td><td>2.2</td><td>3.1</td><td>6.8</td><td>166.9</td><td>67.9</td><td>-146.9</td><td>4.2</td><td>10.4</td><td>-6.2</td></tr><tr><td rowspan="3">Zamdela-S</td><td>PM<sub>1</sub></td><td>3.1</td><td>2.4</td><td>37.5</td><td>54.5</td><td>45.5</td><td>-43.0</td><td>10.2</td><td>14.7</td><td>-4.5</td></tr><tr><td>PM<sub>1–2.5</sub></td><td>2.8</td><td>2.0</td><td>12.0</td><td>66.1</td><td>34.9</td><td>-17.8</td><td>2.2</td><td>2.6</td><td>-0.4</td></tr><tr><td>PM<sub>2.5–10</sub></td><td>1.7</td><td>3.0</td><td>8.1</td><td>55.0</td><td>59.0</td><td>-26.8</td><td>4.8</td><td>6.1</td><td>-1.4</td></tr><tr><td rowspan="3">Zamdela-W</td><td>PM<sub>1</sub></td><td>2.7</td><td>4.9</td><td>23.8</td><td>61.7</td><td>25.9</td><td>-19.0</td><td>27.4</td><td>33.4</td><td>-5.9</td></tr><tr><td>PM<sub>1–2.5</sub></td><td>0.7</td><td>2.1</td><td>5.5</td><td>63.8</td><td>18.7</td><td>9.3</td><td>15.1</td><td>13.9</td><td>1.2</td></tr><tr><td>PM<sub>2.5–10</sub></td><td>0.8</td><td>4.4</td><td>7.8</td><td>59.7</td><td>19.7</td><td>7.6</td><td>12.5</td><td>11.8</td><td>0.6</td></tr><tr><td rowspan="3">Jouberton-S</td><td>PM<sub>1</sub></td><td>2.7</td><td>2.8</td><td>9.9</td><td>55.5</td><td>92.1</td><td>-63.0</td><td>36.9</td><td>60.8</td><td>-23.9</td></tr><tr><td>PM<sub>1–2.5</sub></td><td>1.6</td><td>1.6</td><td>5.5</td><td>55.3</td><td>78.9</td><td>-42.9</td><td>13.3</td><td>19.1</td><td>-5.8</td></tr><tr><td>PM<sub>2.5–10</sub></td><td>0.8</td><td>2.1</td><td>3.9</td><td>40.3</td><td>34.8</td><td>18.1</td><td>31.2</td><td>25.9</td><td>5.3</td></tr></tbody></table>

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.
<figure><img src="image_14.png" /><figcaption>**Figure A1.** 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.</figcaption></figure>

**Data availability.** The data set is available at https://doi.org/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 Henders 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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