After carbon dioxide (CO
Analyses of eBC and EC spatial mass concentration patterns across the eight
sites indicate that the mass concentrations in the South African interior are
in general higher than what has been reported for the developed world and
that different sources are likely to influence different sites. The mean eBC
or EC mass concentrations for the background sites (Welgegund, Louis
Trichardt, Skukuza, Botsalano) and sites influenced by industrial activities
and/or nearby settlements (Elandsfontein, Marikana, Vaal Triangle and
Amersfoort) ranged between 0.7 and 1.1, and 1.3 and
1.4
Possible contributing sources were explored in greater detail for
Elandsfontein, with five main sources being identified as coal-fired power
stations, pyrometallurgical smelters, traffic, household combustion, as well
as savannah and grassland fires. Industries on the Mpumalanga Highveld are
often blamed for all forms of pollution, due to the NO
Aerosol black carbon (BC) is the carbonaceous fraction of ambient
particulate matter that absorbs incoming short-wave solar radiation and
terrestrial long-wave radiation, which has a warming effect on the
atmosphere (IPCC, 2013). Although BC has a relatively short atmospheric
lifetime (days to weeks), it has significant regional effects on
temperature, cloud amount and precipitation. Over snow-covered areas, the
surface albedo can be significantly reduced due to the deposition of BC, and
this may considerably influence the local and regional climate (Ramanathan
and Carmichael, 2008; Jacobson, 2004). Direct observations of reduced albedo
resulting from long-range-transported BC into Arctic areas were reported by
Stohl (2006). It was estimated that BC may have contributed to more
than half of the observed Arctic warming since 1890, most of this occurring
during the last three decades (Shindell et al., 2008). After CO
Atmospheric BC is a primary species (Putaud et al., 2004; Pöschl, 2005)
that is emitted by combustion processes, particularly from fossil fuel
combustion, diesel engine exhaust, as well as open biomass fires and
household combustion (Cachier, 1995; Cooke and Wilson, 1996; Bond et al.,
2004; IPCC, 2013). Globally, approximately 20 % of BC is emitted from
residential biofuel burning, 40 % from fossil fuels and 40 % from open
biomass burning such as forest and savannah fires (Cooke and Wilson, 1996; Wolf and Cachier, 1998; Pope et al., 2002). BC from fossil
fuels is estimated to contribute a global mean radiative forcing of 0.04
watts per square metre (W m
There are large uncertainties associated with emissions of BC, its aging during atmospheric transportation and its removal by precipitation (Bond and Sun, 2004), which are reflected in uncertainties in the global effect of BC (e.g. Bond et al., 2013). Presently, the majority of aerosol radiative impact assessments are based on models (Bond et al., 2013; IPCC, 2013), both on local and global scales, which incorporate measured aerosol properties. However, this approach involves several assumptions (e.g. assuming aerosol properties and the use of global instead of regional emission inventories for under-sampled/characterised regions). Considering the relatively short atmospheric lifetime of BC, such assumptions could lead to significant uncertainties, especially on regional scales (Andreae and Gelencsér, 2006; Masiello, 2004; Bond et al., 2013; Kuik et al., 2015). For a better understanding of the transport, removal and climatic impacts of atmospheric BC, accurate and up-to-date measurements covering large spatial areas and long temporal periods are required.
Africa is one of the least studied continents, although it is regarded as
the largest source region of atmospheric BC (Liousse et al., 1996; Kanakidou
et al., 2005). Southern Africa is an important sub-source region, with
savannah and grassland fires (anthropogenic and natural) being prevalent
across this region, particularly during the dry season, when almost no
precipitation occurs (Formenti et al., 2003; Tummon et al., 2010; Laakso et
al., 2012; Vakkari et al., 2014; Mafusire et al., 2016). Studies by Swap et
al. (2004) indicated that savannah and grassland fire plumes from southern
Africa affect Australia and South America. South Africa is the economic and
industrial hub of southern Africa with large anthropogenic point sources
(Lourens et al., 2011). However, the relative importance of BC contributions
from these anthropogenic sources in South Africa is still largely unknown
and few BC-related papers have been published in the peer-reviewed public
domain. Venter et al. (2012) used BC mass concentration data collected at
the Marikana monitoring station to verify the origin of CO and PM
From the above-mentioned information, the need for improved BC mass concentration data for South Africa is evident. This paper presents spatial and temporal assessments of equivalent black carbon (eBC) derived from an optical absorption method and EC determined by an evolved carbon method (definitions according to Petzold et al., 2013) for mass concentrations over the northern interior of South Africa, as well as potential contributing sources of eBC at Elandsfontein, a site located on the South African Highveld.
In this paper, eBC or EC mass concentration data from eight measurement stations are presented. At three of these stations, continuous high-resolution eBC measurements were conducted, i.e. Elandsfontein, Welgegund and Marikana, while at the remaining five stations, i.e. Louis Trichardt, Skukuza, Vaal Triangle, Amersfoort and Botsalano, samples were collected once a month on a filter for a period of 24 h and analysed offline to yield EC. The locations of these sites within a regional context are indicated in Fig. 1. In order to contextualise all the sites, a brief description of each site is presented below.
The sites (Elandsfontein, Welgegund and Marikana) where continuous high-resolution data were gathered are indicated with blue stars, while the sites (Louis Trichardt, Skukuza, Vaal Triangle, Amersfoort and Botsalano) where filters were gathered and analysed offline are indicated with blue dots. Neighbouring countries, some major cities and South African provincial borders are also indicated for additional regional contextualisation (Provinces include WC – Western Cape; EC – Eastern Cape; NC – Northern Cape; FS – Free State; KZN – KwaZulu-Natal; NW – North West; GP – Gauteng; MP – Mpumalanga and LP – Limpopo).
The Elandsfontein monitoring station (26.25
The Marikana monitoring station (25.70
The Welgegund measurement station (
Maritz et al. (2015) introduced all the DEBITS sites for which data are
presented. Therefore, only synopses of the site descriptions, taken from the
aforementioned paper, are given here. The DEBITS project is an
international long-term project that mainly focuses on measuring atmospheric
deposition of pollutants (Galy-Lacaux et al., 2003; Mphepya et al., 2004, 2006;
Conradie et al., 2016). The Louis Trichardt (22.99
Aerosol BC mass concentration can be measured using both online and offline methods. In this paper, eBC was measured with a light-absorption method and EC with a thermo-optical method (Petzold et al., 2013).
eBC mass concentration was continuously measured at Elandsfontein, Marikana and Welgegund with a Thermo Scientific model 5012 multi-angle absorption photometer (MAAP) with time resolutions of 1 min that were converted to 15 min averages. The MAAP measures aerosol eBC with a filter-based method that uses a combination of reflection and transmission measurements together with a radiative transfer model to yield eBC concentration (Petzold and Schönlinner, 2004). However, if the automated filter change in MAAP occurs at a high eBC concentration, an artefact may occur (Hyvärinen et al., 2013). In this study, the MAAP eBC measurements were corrected for this artefact according to Hyvärinen et al. (2013). Furthermore, the MAAPs at Welgegund and Elandsfontein were operated at reduced flow rates, which decreased the number of such filter change artefacts.
There were 24 h PM
A number of products can be used to obtain savannah and grassland fire locations. Fire locations presented in this paper were obtained from the remote sensing observations of fires from the MODIS collection 5 burned area product (Roy et al., 2008).
The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT, 2014) model (version 4.8), developed by the National Oceanic and Atmospheric Administration (NOAA) Air Resources Laboratory (ARL), was used to calculate air mass histories (Draxler and Hess, 2004). Meteorological data from the GDAS archive of the National Centre for Environmental Prediction (NCEP) of the United States National Weather Service (USNWS) and archived by the ARL (Air Resources Laboratory, 2014a) were used as input. These data have a 40 or 80 km grid resolution, depending on the year considered (NASA, 2015), with all the data used in this study having 40 km grid resolution. All trajectories were calculated for 24 h backwards to arrive on the hour at an arrival height of 100 m above ground level. An arrival height of 100 m was chosen since the orography in HYSPLIT is not well defined, which could result in increased error margins on individual trajectory calculations if lower arrival heights are used (Air Resources Laboratory, 2014b). For such calculated back trajectories, maximum error margins of 15 to 30 % of the trajectory distance travelled have been estimated (Stohl, 1998; Riddle et al., 2006).
This method was introduced by Maritz et al. (2015) who used it to link ambient OC and EC concentrations to potential sources. The same method was applied here to assess if large point sources and informal or semiformal settlements contributed to ambient eBC concentrations at the sites where active eBC data were gathered (Elandsfontein, Welgegund and Marikana). The method was not applied to sites where 24 h composite EC samples were taken (Louis Trichardt, Skukuza, Vaal Triangle, Amersfoort and Botsalano). The method relates eBC concentrations measured at a particular sampling site with the closest distance between the hourly arriving trajectory and the aforementioned sources (large point sources, as well as informal and semiformal settlements). Figure 2 presents an illustration of the method applied for a specific sampling site to determine the shortest distance between a 24 h back trajectory and large point sources. The distances between the large point sources (indicated by the black markers) and a specific back trajectory were calculated for each of the hourly locations of the 24 h back trajectory (indicated by the red dots in Fig. 2). The red line indicates the shortest distance between hourly locations of this specific trajectory and large point sources (i.e. petrochemical operations, coal-fired power stations and pyrometallurgical smelters). A weakness of the aforementioned method was that downwind point sources and/or informal or semiformal settlements, very close to the monitoring site, could in some instances be the closest point source/informal or semiformal settlements. Additionally, dilution due to distance travelled by the trajectories was not considered.
Example to illustrate the method applied to determine the shortest distance that each 24 h back trajectory passed large point sources and/or informal or semiformal settlements. (Provinces include FS – Free State, KZN – KwaZulu-Natal, NW – North West, GP – Gauteng and MP – Mpumalanga).
In order to determine the relative strength of eBC mass concentration
sources, detailed correlation analyses were performed for eBC peaks. For
instance, it is well known that plumes from coal-fired power stations on the
Mpumalanga Highveld are characterised by a simultaneous increase in NO,
NO
Example to illustrate how species were correlated with eBC in order
to separate sources from one another. The excess eBC (
Several techniques were applied in this paper to characterise possible
sources of eBC mass concentrations measured at the various stations, e.g.
seasonal patterns, diurnal patterns, back-trajectory analyses and
identifying sources based on coincidental increases in species time series.
In an attempt to further critically evaluate deductions made from these
methods, multiple linear regression (MLR) analyses were conducted. Linear
regression is denoted by constants or known parameters (
Box-and-whisker plot indicating statistical eBC mass concentrations
at the Elandsfontein (EL), Welgegund (WE) and Marikana (MA) sites, as well as
EC mass concentrations at the Vaal Triangle (VT), Botsalano (BS), Louis
Trichardt (LT), Skukuza (SK) and Amersfoort (AF) sites. The red line of each
box indicates the median, the black dot the mean, the top and bottom edges of
the box the 25th and 75th percentiles and the whiskers
In Fig. 4, a box-and-whisker plot indicating the statistical eBC or EC
mass concentrations for each of the sites is presented. The significant
difference in number of samples (
Of all the sites considered, the highest mass concentrations were measured
at Vaal Triangle that had a median EC of 3.2
The eBC at Elandsfontein, as well as the EC at Marikana and Amersfoort sites
indicated similar levels with median and mean values of 0.8 and 1.3, 1.2 and
1.7, and 1.1 and 1.4
The background sites, i.e. Welgegund, Botsalano, Louis Trichardt and Skukuza,
had lower eBC or EC levels compared to other locations, with median and mean
concentrations of 0.4 and 0.7, 0.7 and 0.9, 0.8 and 0.9, and 0.9 and 1.1
The eBC and EC concentrations presented for all the sites considered (Fig. 4) should also be contextualised. The background site with the lowest
PM
Apart from the spatial information and possible indication of contributing
sources obtained from Fig. 4, it is also evident from the comparison of
the PM
Monthly statistical distribution of eBC concentrations at the three
sites where continuous measurement data were gathered, i.e. Elandsfontein,
Welgegund and Marikana. PM
In order to determine seasonal patterns, only the site where continuous measurements were conducted was considered. Monthly statistical distributions of eBC mass concentrations for Elandsfontein, Welgegund and Marikana measurement sites are presented in Fig. 5. As is evident from these figures, there is a distinct and similar seasonal pattern observed at all three sites, with the highest eBC mass concentrations measured from June to October. These months coincide with the colder winter months of June to August, as well as the dry season on the South African Highveld occurring between May and mid-October. Venter et al. (2012) previously indicated that household combustion for cooking and space heating in informal and semiformal settlements during winter could be a significant eBC mass concentration source on a local scale. However, it has not yet been determined whether such household combustion could also make a significant regional contribution in South Africa. During the dry season, increased savannah and grassland wild fires occur, which contributed to increased atmospheric eBC concentrations (Bond et al., 2004; Saha and Despiau, 2009). The influence of both of these potential eBC sources, i.e. household combustion and wild fires, will be discussed later in Sect. 3.3. Obviously, increased atmospheric stability during the colder months (Garstang et al., 1996) will also lead to trapping of low-level emissions, hence resulting in possible higher eBC concentrations. This is discussed in greater detail in the next section.
Average diurnal plots as well as average seasonal diurnal plots (separate
for summer, autumn, winter and spring) for the stations where continuous eBC
mass concentration data were gathered, i.e. Elandsfontein, Marikana and
Welgegund (both PM
Overall (all the data) and seasonal (each season separately) average eBC diurnal patterns observed for Elandsfontein, Welgegund and Marikana. Summer: DJF, Autumn: MAM, Winter: JJA and Spring: SON.
The Elandsfontein diurnal plots indicate that the main source of eBC is not
high stack emissions. The area in which Elandsfontein is situated is a
well-known international NO
Fire pixels within the entire southern Africa domain (10–35
In contrast to Elandsfontein, eBC concentrations at Marikana peaked in the
early mornings (05:00–09:00 LT) and again in the early to late evenings
(17:30–22:00 LT). These times correlate with the peak times for household
combustion for space heating and cooking in the nearby informal and semiformal
settlements (Venter et al., 2012). Seasonal timing of the peak eBC
concentration in the diurnal plots confirms that household combustion is the
main source at this site. In winter, during which time daylight hours are
shorter, the peak morning eBC concentration is at
The eBC diurnal plots of Welgegund do not indicate well-defined peaks as observed for Marikana. This is expected since there are no semiformal or informal settlements located close to the Welgegund station. Additionally, there are also no large point sources close to Welgegund, as there are at Elandsfontein. Therefore, only sources that have a regional influence are likely to affect eBC levels at Welgegund. It is therefore likely that savannah and grassland fires, especially in the winter and early spring, are mainly responsible for eBC levels measured at Welgegund and mainly long-range transportation during the wet season. The lower PBL during the evenings and early mornings will concentrate the eBC and contribute to eBC levels rising in the evening and only decreasing 3–4 h after sunrise, as suggested by Korhonen et al. (2014). This effect is strongest in the winter months.
As has already been indicated, there are various possible sources for eBC,
e.g. industrial, household combustion, traffic and savannah and grassland
fires. In this section, possible significant contributing sources are
considered further. Figure 7 indicates the fire pixel counts calculated from
MODIS (collection 5 burned area product) (Roy et al., 2008) within the
entire domain of southern Africa (10–35
It is important to note that it is difficult to separate the influence of various sources at a specific site, since the measured eBC originates from a mixture of contributing sources. Therefore, Fig. 7 was considered first, since it provided guidance about which periods would be best to consider for the different sources. For instance, there are very few savannah and grassland fires from December to February every year in the northern interior of South Africa. The savannah and grassland fires that do occur during this period occur in the southern Western Cape, which will not influence eBC levels in the northern interior significantly. In addition, minimal household combustion for space heating takes place in December to February, since these are the warmest months. During this time, household combustion for cooking will still take place, but such daily emission periods are far shorter than the extended space heating period (typically early evening, throughout the night, until after sunrise the next day) occurring during the colder months. Considering the aforementioned information, it is best to isolate industrial and traffic related eBC sources from December to February.
It is clear from the overall southern African fire frequencies, as well as those around each site (Fig. 7), that August and September have the highest savannah and grassland fire intensities. This is the driest period, just before the onset of the first rains, usually in mid-October. We can therefore isolate savannah and grassland fires best in this period, since their effect is strongest. The influence of household combustion is also not that strong in this period, since it is already becoming warmer, and therefore less space heating is required. By considering aerosol particle concentrations at Marikana, Vakkari et al. (2013) proved that the evening peak associated with household combustion was significantly lower in September than from June to July.
Since it is coldest in June and July, the effect of household combustion for space heating is at its strongest, making the isolation of the household combustion effect better during these months.
In the following sections, eBC contributions from the above-mentioned sources, i.e. industrial, traffic, savannah and grassland fires, and household combustion, will be explored in greater detail for the Elandsfontein site only. This site was chosen since it can be affected by all the aforementioned sources, while the other sites where continuous high-resolution data were gathered will mainly be influenced by savannah and grassland fires (Welgegund) or household combustion (Marikana).
Numerous large industrial point sources linked to coal utilisation occur in the South African interior, e.g. coal-fired power stations that produce most of South Africa's electricity, large petrochemical operations utilising coal gasification and numerous pyrometallurgical smelters utilising coal and coal-related products as carbonaceous reductants for the production of various steels and alloys (Collet et al., 2010; Lourens et al., 2011; Beukes et al., 2012). However, the possible contributions of these large point sources to atmospheric BC have not yet been investigated.
Hourly average eBC concentrations plotted against the shortest distances that hourly arriving back trajectories had passed large point sources during the summer months, i.e. December to February, at Elandsfontein.
In Fig. 8, eBC concentrations measured at Elandsfontein were plotted against the shortest distances by which back trajectories had passed any large point source during the summer months (December to February) when minimal household combustion, as well as savannah and grassland fires, occur. Although there was no clear correlation (Fig. 8), the results indicated that at least some trajectories passing closer to these large industrial point sources had higher eBC concentrations. This suggests that eBC contributions from large industrial point sources cannot be ignored, notwithstanding the diurnal patterns, indicating that high stack industrial emissions were not the main source (Fig. 6).
Although it was indicated in Sect. 3.2.2 that it was unlikely that high stack
emissions were the main source of eBC at Elandsfontein, the possible
fractional contributions of industries still need to be assessed. In order
to quantify this, eBC peaks that coincided with peaks of other pollutants,
which are characteristic of large point sources in that area, were
considered for the December to February period. Two distinct types of
contributing sources were identified, i.e. eBC peaks that coincided with
SO
From the literature, it seems feasible to associate increased BC concentrations
with traffic emissions, particularly diesel-powered vehicles (Cachier, 1995;
Cooke and Wilson, 1996; Bond and Sun, 2005). The Mpumalanga Highveld around
Elandsfontein is the area where most thermal coal is mined in South Africa,
which is mostly transported by diesel trucks via various roads
criss-crossing the area, as indicated in Fig. 10a. However, the closest
tarred road, i.e. the R35, passes Elandsfontein approximately 4.7 km to the
east. This road is also one of the most utilised for coal road
transportation. Additionally, to the north of Elandsfontein, numerous such
tarred roads are located; e.g. the national N12 and N4 highways pass
Elandsfontein approximately 38 km to the north and northwest. It therefore
seems reasonable that the traffic-related eBC back-trajectory map (Fig. 10a,
which was for coincidental increases in eBC and NO
Venter et al. (2012) indicated that household combustion for space heating and cooking in informal and semiformal settlements contributes significantly to poor air quality in such settlements. In Fig. 11, the relationships between monthly average and median eBC, against monthly mean and median temperatures for Elandsfontein, are presented. As is evident from the results presented in Fig. 11, there is a significant correlation between eBC concentration and temperature if August and September are ignored (indicated with hollow markers in Fig. 11). During these months, significant eBC contributions can be expected from savannah and grassland fires (see Fig. 7). The correlation between eBC concentration and temperature indicates that household combustion for space heating contributes significantly to eBC levels measured at Elandsfontein, especially during the colder months when household combustion is used more frequently for space heating.
Monthly median and mean eBC (with bars indicating 25th and 75th percentiles) plotted against monthly median and mean temperatures for Elandsfontein.
Similar to the analysis performed for the large industrial point sources (Fig. 8), eBC concentrations were drawn as a function of the closest distance that back trajectories had passed informal and semiformal settlements for Elandsfontein. However, this was done only for the winter months of June and July for both years, since household combustion contributions could then be better isolated from savannah and grassland fire contributions during these periods. These results are presented in Fig. 12. Although not conclusive, the results presented indicate that, in general, higher eBC concentrations were observed when trajectories passed closer to informal and semiformal settlements in June and July.
eBC concentration plotted against the shortest distances that hourly arriving back trajectories had passed informal or semiformal settlements during the winter months of June and July at Elandsfontein.
Household combustion results in the emission of a number of different
species (Venter et al., 2012). In this work, tracers for household combustion
were determined from species that simultaneously increased with eBC,
including NO
Figure 13a indicates back trajectories associated with household combustion
contribution to eBC levels (for time periods with coincidental increases in
eBC with NO
Vakkari et al. (2014) relatively recently indicated how savannah and
grassland fire emission aerosols are changed via atmospheric oxidation in
South Africa. To positively identify savannah and grassland fire plumes, the
aforementioned authors used CO and eBC as coincidental increasing species.
However, CO was not measured at Elandsfontein, and therefore the positive
identification of savannah and grassland plumes could not be undertaken using
this method. Additionally, the plumes of savannah and grassland fires
occurring in neighbouring countries arriving at Elandsfontein will be
diluted and aged. Such regional fires lift the entire eBC baseline, rather
than exhibiting well-defined plumes that can be separated from the baseline
(Mafusire et al., 2016), as was done for the industrial, traffic and
household combustion sources. Thus far in the paper, we have considered
August and September as the months in which savannah and grassland fire
frequencies peak. However, some household combustion might still occur in
August. Therefore, to determine the overall baseline increase as a result of
savannah and grassland fires, only September was considered as being
representative of savannah and grassland fires, while the summer months
(December to February) can be considered as the baseline. By subtracting the
September eBC mean from the summer mean, the eBC baseline increased by 2.01
Up to now, the individual eBC sources for Elandsfontein were discussed, but
their strengths were not compared with one another. In Fig. 14, the
comparison of the
Vakkari et al. (2014) used
Ratio of
Four scenarios were investigated with MLR analyses. Firstly, MLR analysis was conducted for the entire monitoring period at Elandsfontein. As is evident from the top left panel in Fig. 16, the RMSE difference between the actual measured eBC concentration and the calculated eBC concentrations, if only one independent parameter was included in the optimum MLR solution, was approximately 1.54. The RMSE difference could be reduced by including more independent parameters in the optimum MLR solution. However, it was found that the inclusion of more than nine independent parameters did not further reduce the RMSE difference significantly.
RMSE difference between the MLR calculated eBC and the actual
measured eBC at Elandsfontein for the entire measurement period
Actual eBC compared with calculated eBC (using Eq. 2) for the entire monitoring period at Elandsfontein.
From the MLR analysis conducted for the entire measurement period at
Elandsfontein, the actual MLR equation could be obtained, which is presented
as Eq. (2). With this equation, eBC at Elandsfontein could be calculated.
The comparisons between actual and calculated (with Eq. 2) eBC
concentrations are presented in Fig. 17. From this comparison, it is
evident that Eq. (2) could be used to calculate eBC at Elandsfontein
relatively accurately.
In order to use MLR to verify whether the eBC contribution sources were identified correctly in Sect. 3.3, MLR analyses were also conducted for the different time periods defined for isolation of the various sources, i.e. December to February for industrial and traffic sources, June and July for household combustion, and August and September for savannah and grassland fires.
As is indicated in Eq. (3) and the top right panel of Fig. 16, the
optimum MLR solution obtained for the December to February period included
seven independent variables in the equation. Firstly, the fact that fewer
independent variables were required to reduce the RMSE optimally, if
compared with the overall period (top left panel of Fig. 16), indicates
that the December to February period is influenced by fewer sources.
Secondly, the identity of the independent variables and the sign (positive
or negative) associated with them in Eq. (3) are noteworthy. Increased
O
This paper presents the most comprehensive eBC spatial and temporal, as well as source contribution, assessments for the South African interior that has been published in the peer-reviewed public domain to date. Limited EC data were also presented, which expanded the overall spatial extent covered in the paper.
Analyses of eBC and EC spatial concentration patterns at eight sites
indicate that concentrations in the South African interior are in general
higher than what has been reported for the developed world, e.g. western
Europe. The highest levels were observed at Vaal Triangle, which were
attributed to EC emissions from household combustion emanating from informal and
semiformal settlements, as well as traffic and large points sources. eBC or
EC levels at Elandsfontein, Amersfoort and Marikana were similar but likely
originated from different sources. Elandsfontein and Amersfoort lie within
the well-known NO
Similar seasonal patterns were observed at all three sites where high-resolution eBC data were collected, i.e. Elandsfontein, Marikana and Welgegund, with the highest eBC concentrations measured from June to October. These months coincide with the cold winter months of June to August that indicate possible contributions from household combustion, as well as the dry season on the South African Highveld occurring between May and mid-October, which indicates contributions from savannah and grassland fires.
Diurnal patterns indicated that at Elandsfontein industrial high stack emissions were not the most significant source, since no peaks were observed after the breakup of lower-level inversion layers. The diurnal patterns at Marikana revealed household combustion for space heating and cooking to be the most significant sources. At Welgegund, the most significant source contributions were most likely regional savannah and grassland fires.
Possible contributing eBC sources were explored in greater detail for
Elandsfontein only. Industrial sources could be isolated best during the
summer months of December to February, since very few savannah and grassland
fires, as well as household combustion for space heating occur then.
Coincidental plumes of SO
Although the source strengths of coal-fired power stations,
pyrometallurgical smelters and traffic emissions were lower than that of
household combustion, as well as savannah and grassland fires, the first
mentioned sources contribute year round, while the latter only contributed
significantly in May to August, and June to September, respectively. Of the
fresh industrial plumes, the highest eBC concentrations were associated with
pyrometallurgical smelters. This is a very significant finding, since
coal-fired power stations and petrochemical operations have in the past been
blamed for most of the pollution problems on the Mpumalanga Highveld (mainly
due to the NO
Lastly, the calculated emission ratios of eBC and gaseous species that were presented could be used in future studies to assess the eBC emission inventories for industrial and domestic sources in South Africa.
The data for this paper are available upon request from Paul Beukes (paul.beukes@nwu.ac.za) or Ville Vakkari (ville.vakkari@fmi.fi).
The authors declare that they have no conflict of interest.
The European Union Framework Programme 6 (EU FP6), Eskom Holdings SOC Ltd and Sasol Technology R&D (Pty) Limited are acknowledged for funding. V. Vakkari was a beneficiary of an AXA Research Fund postdoctoral grant. The financial support by the Saastamoinen Foundation is gratefully acknowledged for funding P. Tiitta. The National Research Foundation (NRF) is acknowledged for providing research financial assistance (bursaries/scholarships) to P. Maritz, A. D. Venter and K. Jaars. Opinions expressed and conclusions arrived at are those of the authors and are not necessarily attributed to those of the NRF.Edited by: A. Petzold Reviewed by: two anonymous referees