Surface ozone is a secondary air pollutant formed from reactions between nitrogen oxides (NO_x = NO + NO₂) and volatile organic compounds in the presence of sunlight. In this work we examine effects of the climate pattern known as the El Niño–Southern Oscillation (ENSO) and NO_x variability on surface ozone from 1990 to 2007 over the South African Highveld, a heavily populated region in South Africa with numerous industrial facilities. Over summer and autumn (December–May) on the Highveld, El Niño, as signified by positive sea surface temperature (SST) anomalies over the central Pacific Ocean, is typically associated with drier and warmer than normal conditions favoring ozone formation. Conversely, La Niña, or negative SST anomalies over the central Pacific Ocean, is typically associated with cloudier and above normal rainfall conditions, hindering ozone production. We use a generalized regression model to identify any linear dependence that the Highveld ozone, measured at five air quality monitoring stations, may have on ENSO and NO_x. Our results indicate that four out of the five stations exhibit a statistically significant sensitivity to ENSO at some point over the December–May period where El Niño amplifies ozone formation and La Niña reduces ozone formation. Three out of the five stations reveal statistically significant sensitivity to NO_x variability, primarily in winter and spring. Accounting for ENSO and NO_x effects throughout the study period of 18 years, two stations exhibit statistically significant negative ozone trends in spring, one station displays a statistically significant positive trend in August, and two stations show no statistically significant change in surface ozone.

Characterizing black carbon (BC) on a fine scale globally is essential for understanding its climate and health impacts. However, sparse BC mass measurements in different parts of the world and coarse model resolution have inhibited evaluation of global BC emission inventories. Here, we apply globally distributed BC mass measurements from the Surface Particulate Matter Network (SPARTAN) and complementary measurement networks to evaluate contemporary BC emission inventories. We use a global chemical transport model (GEOS-Chem) in its high-performance configuration (GCHP) for high-resolution simulations to relate BC emissions to ambient concentrations for comparison with measurements. Here we find that simulations using the Community Emissions Data System (CEDS) emission inventory exhibit skill (r² = 0.73) in representing variability in SPARTAN measurements across primarily developed regions with low BC concentrations but exhibit pronounced discrepancy (r² = 0.00019) across high-BC regions in the Global South, underestimating BC by 38%. Alternative inventories (EDGAR, HTAP) yield similar results. These findings motivate renewed attention to the challenging task of characterizing BC emissions from low- and middle-income countries.

Aircraft measurements of NO₂ using an imaging differential optical absorption spectrometer (iDOAS) instrument over the South African Highveld region in August 2007 are presented and compared to satellite measurements from OMI and SCIAMACHY. In situ aerosol and trace-gas vertical profile measurements, along with aerosol optical thickness and single-scattering albedo measurements from the Aerosol Robotic Network (AERONET), are used to devise scenarios for a radiative transfer modelling sensitivity study. Uncertainty in the air-mass factor due to variations in the aerosol and NO₂ profile shape is constrained and used to calculate vertical column densities (VCDs), which are compared to co-located satellite measurements. The lower spatial resolution of the satellites cannot resolve the detailed plume structures revealed in the aircraft measurements. The airborne DOAS in general measured steeper horizontal gradients and higher peak NO₂ vertical column density. Aircraft measurements close to major sources, spatially averaged to the satellite resolution, indicate NO₂ column densities more than twice those measured by the satellite. The agreement between the high-resolution aircraft instrument and the satellite instrument improves with distance from the source, this is attributed to horizontal and vertical dispersion of NO₂ in the boundary layer. Despite the low spatial resolution, satellite images reveal point sources and plumes that retain their structure for several hundred kilometres downwind.

Unabated emissions of precursor gases from coal-fired power stations in South Africa greatly contribute to ambient PM_2.5 concentration in the region, but estimates of the number of associated premature mortalities vary vastly. The application of the exposure-response function is one of the reasons for the differences in estimates of premature mortalities; since the relationship between mortality and PM_2.5 exposure flattens out at higher PM_2.5 concentrations, a smaller number of premature mortalities is calculated if a reduction in PM_2.5 concentration occurs at the actual ambient concentration (“avoidable deaths”), while a greater number of mortalities is calculated if other sources are not considered (at low ambient concentrations) (“single-source deaths”). It is more appropriate to attribute deaths to a source in proportion to the contribution made by the source to ambient PM_2.5 levels (“attributable deaths”). Total ambient PM_2.5 concentrations are extrapolated from 38 ambient monitoring stations in the north-eastern region of South Africa using a regression model based on household socio-economic factors, and PM_2.5 concentrations derived from power station emissions are estimated using a reduced-form intake fraction model. It is estimated that there are around 800 attributable premature mortalities per year due to PM_2.5 from coal-fired power station emissions in South Africa. The number of premature mortalities is 44% higher when calculating single-source deaths and 53% lower when calculating avoidable deaths. Using the attributable death approach is particularly important in highly polluted areas such as low-income residential areas where households use solid and liquid fuels.