Globally, numerous pollution hotspots have been identified using satellite-based instruments. One of these hotspots is the prominent NO2 hotspot over
the South African Highveld. The tropospheric NO2 column density of this area is comparable to that observed for central and northern Europe, eastern
North America and south-east Asia. The most well-known pollution source in this area is a large array of coal-fired power stations. Upon closer inspection,
long-term means of satellite observations also show a smaller area, approximately 100 km west of the Highveld hotspot, with a seemingly less substantial
NO2 column density. This area correlates with the geographical location of the Johannesburg–Pretoria conurbation or megacity, one of the 40
largest metropolitan areas in the world. Ground-based measurements indicate that NO2 concentrations in the megacity have diurnal peaks in the early
morning and late afternoon, which coincide with peak traffic hours and domestic combustion. During these times, NO2 concentrations in the megacity are
higher than those in the Highveld hotspot. These diurnal NO2 peaks in the megacity have generally been overlooked by satellite observations because the
satellites have fixed local overpass times that do not coincide with these peak periods. Consequently, the importance of NO2 over the megacity has been
underestimated. We examined the diurnal cycles of NO2 ground-based measurements for the two areas – the megacity and the Highveld hotspot –
and compared them with the satellite-based NO2 observations. Results show that the Highveld hotspot is accompanied by a second hotspot over the
megacity, which is of significance for the more than 10 million people living in this megacity.
Satellite-based instruments such as the Global Ozone Monitoring Experiment (GOME 1 & 2),1 the Scanning Imaging Absorption spectroMeter for
Atmospheric CHartographY (SCIAMACHY)2 and the Ozone Monitoring Instrument (OMI)3 have been used to quantify trends of various atmospheric
trace gas concentrations on a global scale.4 Of interest here are the observations of tropospheric nitrogen dioxide (NO2) column
densities5,6,7,8 and the identification of global NO2
pollution hotspots.9,10 NO2 plays a key role as a precursor for tropospheric ozone (O3), aerosol nitrate
(NO3-), and the hydroxyl radical (OH•).
One prominent NO2 hotspot seen in global maps from satellite retrievals is over the South African Highveld (referred to hereafter as the
Highveld hotspot). The tropospheric NO2 column density of this area (shown in Figure 1) is comparable to that observed for central and northern Europe,
eastern North America and south-east Asia.9 In addition to the well-known source of NO2 – 11 coal-fired power stations – there
are also other widespread area sources, such as road transport, biomass burning and human settlement, as well as other large point sources including
metallurgical, mining and petrochemical operations.11 A total of 90% of the industrial NOx emissions in South Africa originate from the
Highveld hotspot.12 In a recent assessment of global emissions, South African emissions amounted to 420 kt/year of nitrogen, which constituted 1.6%
of global anthropogenic NO2 emissions.13
FIGURE 1: Satellite image of the tropospheric vertical NO2 column (in 1015 molecules/cm2) over the South African highveld.
Located 100 km west from the Highveld hotspot is the largest conurbation in southern Africa, which developed around Johannesburg and Pretoria, with a population
of over 10 million.14 Conurbations of this magnitude have been defined as Megacities.15 The Johannesburg–Pretoria conurbation or
megacity is the central hub of economic activity and growth in southern Africa. The main pollution sources in this conurbation are traffic emissions, biomass
and domestic combustion (space heating and cooking), and industrial activities.16
In Figure 1, an area smaller than the Highveld hotspot, with a less substantial NO2 column density, is seen to correspond with the geographical
location of the megacity. Ground-based measurements conducted in this study indicate that satellite observations may underestimate the importance of this
conurbation to local NOx pollution as a result of specific diurnal cycles of emissions. However, ground-based measurements cannot be compared directly
to satellite-based column measurements because satellite measurements reflect on the total column, whereas ground-based measurements do not indicate the total
column density. Nonetheless, the aim of this study was to evaluate the potential contribution of the megacity to the NO2 Highveld hotspot. The diurnal
cycles of ground-based measurements of NOx were evaluated for the megacity and the Highveld hotspot, and compared to satellite-based NO2
Multi-year NO2 retrievals obtained from (1) SCIAMACHY (Max Planck Institute retrieval,8 for the years 2003–2009) and (2) OMI
(Dutch OMI NO2 product DOMINO (v1.02)7, available from the Tropospheric Emission Monitoring Internet Service for the years 2005–2009)
were used. Both instruments orbit earth in a polar, sun-synchronous orbit, with a local South African observation time of 10:00 (SCIAMACHY) or 13:30 (OMI). Thus,
the comparison of NO2 measurements from SCIAMACHY and OMI holds limited information on diurnal cycles.17
From the spectral measurements of the satellite instruments, slant column densities (SCDs), that is, integrated concentrations along the effective light path, of
NO2 were derived. The stratospheric slant column is subtracted from the total slant column, yielding the tropospheric slant column density (TSCD).
7,8 For translation of the TSCD into a tropospheric vertical column density, tropospheric air mass factors (AMF) are generally needed. This translation
requires prior assumptions on the ground albedo, as well as the vertical profiles of aerosols, clouds and NO2, which makes it the most uncertain step
within satellite retrievals.
To compare SCIAMACHY and OMI data sets meaningfully (including differences in viewing geometry, local time, ground pixel size and the AMF calculations), we (1)
focused on TSCDs (which are far less uncertain than TVCDs) and (2) investigated relative patterns (i.e. ratios of TSCDs for the megacity versus the Highveld).
This approach mostly eliminated potential systematic biases caused by the use of different satellite instruments and retrievals.
Hourly near-surface concentrations of NO2 were obtained from four air-quality monitoring stations within the megacity and at five stations in the Highveld hotspot for a period of 3 months in autumn 2009 (March to May). These stations were specifically chosen as their locations are regarded to be representative of the ambient concentrations of these areas.
Figure 2 indicates the locations of these measurement stations within the megacity and the Highveld hotspot. These stations are operated in the megacity and
the Highveld hotspot by the town council of Johannesburg and the industries, respectively. Apart from their strategic positioning, these stations also complied
with the South African Air Quality Information System quality-control requirements. Data received were also manually checked to identify possible errors and
FIGURE 2: A map of the sampling sites showing the major point sources, with ‘M‘ denoting the Johannesburg-Pretoria megacity and ‘H‘ the Highveld hotspot. The area
shaded in grey indicates the Johannesburg–Pretoria megacity.
Ground-based NO2 measurements were made with chemiluminescence instruments using molybdenum oxide converters. NO2 is catalytically
converted to NO on a heated molybdenum surface and then measured as NO by means of chemiluminescence in the reaction with ozone. This method not only converts the
NO2 to NO, but also partially converts other oxidised nitrogen compounds and can therefore cause overestimations of NO2 by between 17% and
30%.18 However, this technique is still widely applied and measurements with these instruments currently provide the only available near-surface data
for the regions under discussion.
Figure 3 shows the NO2 diurnal cycles for each of the ground-based stations in the megacity and the Highveld hotspot for the 3-month period.
FIGURE 3: Median diurnal NO2 mixing ratios for each of the ground-based stations for the period from March to May 2009 and the medians over each region. ‘M‘ denotes
a megacity station and ‘H‘ a Highveld hotspot station, with numbers corresponding to the locations indicated in Figure 2.
It is evident from Figure 3 that the NO2 mixing ratios of the megacity and the Highveld hotspot were mostly of the same order of magnitude. The megacity diurnal cycles were characteristic of urban areas dominated by traffic emissions, with maximum atmospheric NO2 levels during peak traffic periods in the early morning and late afternoon (Figure 3). In contrast, the NO2 diurnal cycles measured in the Highveld hotspot were less pronounced. This difference can be ascribed to the fact that the industrial activities that are mainly responsible for NO2 emissions operate 24 h per day. Measurement station H2, however, was an exception, as it showed a distinct diurnal cycle, presumably because it is relatively close to a city (Witbank) and is influenced by traffic emissions.
In order to facilitate the comparison of NO2 levels of the two areas, the ratio of the median concentration of the four megacity stations versus the
median concentration of the five Highveld stations was computed, and is plotted in Figure 4 as a function of the time of day. Ratios greater than 1 indicate
higher NO2 concentrations over the megacity than the Highveld, while ratios less than 1 signify higher NO2 concentrations over the Highveld
than the megacity.
FIGURE 4: Average diurnal cycle ratio, defined as the averaged NO2 diurnal mixing ratio of the four megacity measurement stations divided by the averaged NO2 diurnal
mixing ratio of the five monitoring stations in the Highveld hotspot, for a 3-month period (March–May 2009). The triangle and cross are the average ratios of the
tropospheric slant column density (TSCD) for the megacity divided by the TSCD for the Highveld hotspot, which were obtained from the Scanning Imaging Absorption
Spectrometer for Atmospheric Chartography (SCIAMACHY) and the Ozone Monitoring Instrument (OMI), respectively.
From this average diurnal cycle ratio, it is apparent that there are two distinct periods: 06:00–09:00 and 17:00–21:00, when near-surface megacity NO2 mixing ratios are higher than those of the Highveld hotspot. These time periods coincide with peak traffic hours in the megacity.
The ratios of the TSCD for the megacity divided by the TSCD for the Highveld hotspot are also shown in Figure 4, for measurements obtained from SCIAMACHY (2003–2009) and from OMI (2005–2009). The ratios were calculated from mean maps on a 0.35° × 0.35° grid. The actual numbers depend on the choice of the areas used for averaging. For the Highveld, an area of 3 × 3 pixels (i.e. ≈1°≈1°) was selected that contained all H stations. For the megacity, two different areas were considered: (1) 1 pixel (containing all M stations) and (2) 3 × 3 pixels (the same area as the Highveld). The upper ends of the error bars reflect the first choice, the lower end the second choice and the cross and triangle the averages of each ratio.
The ratios of the TSCDs could be biased if the AMFs for the Highveld and megacity were different. However, terrain height, aerosol load (MODIS aerosol optical density) and mean cloud fraction (from OMI) were similar for both regions.
The satellite-observed NO2 TSCDs over the Highveld hotspot were generally higher than those over the megacity. The 24-h average ratio of the ground-based observations is close to one (0.90), indicating that, at ground level, the overall NO2 pollution levels in the megacity were comparable to those of the well-known Highveld hotspot. Although the geographical area covered by the Highveld hotspot is larger than the area of pollution in the megacity, this area of the megacity deserves more attention than it has received, because of the large urban population that is affected by the pollution.
We have shown that the Highveld hotspot – well known in the international science community because of its prominence in satellite images – is
accompanied by a second South African hotspot over the Johannesburg–Pretoria megacity, with peak NO2 levels exceeding the maximum daily Highveld
values during the morning and evening traffic rush hours. This finding is of importance for the more than 10 million people living in this megacity. Although
satellite instruments have been valuable in pointing out hotspots worldwide, we have shown here a limitation as a result of their specific overpass times.
Satellite overpass times that coincide with the peak traffic hours of the megacity would be more ideal. However, early morning overpasses would not necessarily
be more suitable for satellite detection, as a result of the trapping of pollutants near the surface where satellite measurements do not provide a suitable
response. Early evening overpasses might be more feasible to detect gaseous concentrations because peak traffic emissions would be better mixed in the boundary
layer by evening. Further progress on this issue will require more ground-based and aircraft profile measurements of the region. Direct observation of
tropospheric NO2 vertical column densities with ground-based Multi AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements
19 or airborne instruments may be particularly valuable. Airborne DOAS measurements can be used for direct observation of tropospheric NO2.
20 A comprehensive study of the Highveld hotspot and the megacity is required in order to develop a better understanding of the true extent of the
NO2 hotspot over the interior of South Africa. An improved understanding, as well as greater public and political awareness of this pollution hotspot
will be valuable, especially in light of eventually determining the consequences of this additional hotspot for O3 production, impacts on health and
agriculture, and effective mitigation measures.
We acknowledge the use of the tropospheric NO2 column data from the OMI sensor; Sasol Technology Research and Development (South Africa) for additional financial support; the City of Johannesburg (Gideon Slabbert and Alfred Pheko) as well as Sasol and Eskom for the provision of ground-based data. This work also received funding from the European Union’s Seventh Framework Programme (FP/2007-2011) within the project MEGAPOLI (grant agreement #212520).
We declare that we have no financial or personal relationships which may have inappropriately influenced us in writing this paper.
A.S.M.L. conducted this work as part of her PhD study and was therefore the main investigator; T.M.B., J.P.B. and P.G.v.Z. were study leaders; S.B. assisted with satellite data interpretation; M.G.L., G.D.F., J.J.P., T.W. and K.-P.H. made conceptual contributions.
1. Burrows J, Weber M, Buchwitz M, et al. The Global Ozone Monitoring Experiment (GOME): Mission concept and first scientific results. J Atmos Sci. 1999;56(2):151–175.
2. Bovensmann H, Burrows H, Buchwitz J, et al. SCIAMACHY: Mission objectives and measurement modes. J Atmos Sci. 1999;56(2):127–150.
3. Levelt PF, Gijsbertus HJ, Van den Oord G, et al. The Ozone Monitoring Instrument. IEEE Trans Geosci Remote Sens. 2006;10:1093–1101.
4. Wagner T, Beirle S, Brauers T, et al. Inversion of tropospheric profiles of aerosol extinction and HCHO and NO2 mixing ratios from MAX-DOAS
observations in Milano during the summer of 2003 and comparison with independent data sets. Atmos Meas Tech. 2011;4(3):2685–2715.
5. Leue C, Wenig M, Wagner T, Klimm O, Platt U, Jahhe B. Quantitative analysis of NOx emissions from Global Ozone Monitoring Experiment
satellite image sequences. J Geophys Res. 2001;106(D6):5493–5505.
6. Richter A, Eyring V, Burrows JP, et al. Satellite measurements of NO2 from international shipping emissions. Geophys Res Lett. 2004;31(L23110):1–4.
7. Boersma KF, Eskes HJ, Veefkind JP, et al. Near-real time retrieval of tropospheric NO2 from OMI. Atmos Chem Phys. 2007;7:2103–2128.
8. Beirle S, Kühl S, Pukite J, Wagner T. Retrieval of tropospheric column densities of NO2 from combined SCIAMACHY nidar/limb measurements.
Atmos Meas Tech. 2010;3:283–299.
9. Beirle S, Platt U, Wenig M, Wagner T. Highly resolved global distribution of tropospheric NO2 using GOME narrow swath mode data. Atmos Chem
10. Beirle S, Boersma KF, Platt U, Lawrence MG, Wagner T. Megacity emissions and lifetimes of nitrogen oxides probed from space. Science.
11. Freiman MT, Piketh SJ. Air transport into and out of the industrial Highveld region of South Africa. J Appl Meteor. 2003;42:994–1002.
12. Wells RB, Lloyd SM, Turner CR. National air pollution source inventory. In: Held G, Gore BJ, Surridge AD, Tosen GR, Walmsley RD. Air pollution and its impacts on the South African Highveld. Johannesburg: Environmental Scientific Association, 1996; p. 3–9.
13. Lamarque JF, Bond TC, Eyring V, et al. Historical (1850-2000) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols:
Methodology and application. Atmos Chem Phys. 2010;10:7017–7038.
14. Survey C. Statistics South Africa: Statistical survey [homepage on the Internet]. c2007 [cited 2011 April 12]. Available from:
15. Molina MJ, Molina LT. Megacities and atmospheric pollution. J Air Waste Manage Assoc. 2004;54(6):644–680.
16. Scorgie Y, Paterson G, Burger LW, Annegarn HJ, Kneen MA. Socio-economic impact of measures to reduce air pollution from combustion. Johannesburg: National Economic Development & Labour Council (NEDLAC); 2004.
17. Boersma KF, Jacobs DJ, Tranic M, et al. Validation of urban NO2 concentrations and their diurnal and seasonal variations observed from the
SCIAMACHY and OMI sensors using in situ surface measurements in Israeli cities. Atmos Chem Phys. 2009;9:3867–3879.
18. Steinbacher M, Zellweger C, Schwarzenbach B, et al. Nitrogen oxide measurements at rural sites in Switzerland: Bias of conventional measurement techniques. J Geophys Res. 2007;112(D11307):1–13.
19. Wagner T, Beirle S, Brauers T, et al. Inversion of tropospheric profiles of aerosol extinction and HCHO and NO2 mixing ratios from MAX-DOAS
observations in Milano during the summer of 2003 and comparison with independent data sets. Atmos Meas Tech Discuss. 2011;4(3):3891–3964.
20. Heue K-P, Wagner T, Broccardo SP. Direct observation of two dimensional trace gas distributions with an airborne imaging DOAS instrument. Atmos Chem Phys.