[1] The sources and transport of cloud condensation nuclei (CCN) over southern Africa have been investigated using in situ measurements collected during the Aerosol Recirculation and Rainfall Experiment (ARREX) wet season projects and during the Southern African Regional Science Initiative (SAFARI-2000) intensive dry season campaign. CCN concentrations over the subcontinent are generally higher in the dry season than in the wet season and exceed 2000 cm À3 in highly polluted air masses. In the late dry season, CCN concentrations are highest in the northern regions of the subcontinent due to the burning of savanna biomass. Emissions from industries and power plants on the South African Highveld are a prolific year-round source of CCN and are sufficient to account for CCN levels south of 20°S throughout the year. Most CCN are contained within the mixing layer, which extends to an altitude of 3000-4000 m over the plateau and is capped by a temperature inversion. Multiple inversions and absolutely stable layers control the stratification of aerosols and CCN. Biomass burning particles are efficient CCN, and the median diameter of the accumulation mode is large (up to 0.19 mm). Recently emitted industrial aerosols are less soluble and have a smaller median diameter (0.11 mm). Twice as many aerosols act as CCN in the dry season (68%) than in the wet season (34%). The fraction is highest in the dry season over the tropical regions (>80%), where smoke aerosol predominates. Elevated aerosol and CCN concentrations are expected to have implications for direct radiative forcing, especially in the dry season, and for indirect forcing in the wet season.

Experiment (UAE 2 ) was conducted in the southern Arabian Gulf region. We present atmospheric thermodynamic and aerosol data collected on 18 flights by the South African Aerocommander aircraft. In the first few kilometers, we observed high concentrations of both regional dust (from 100 to 300 mg m À3 in background, to over 1.5 mg m À3 in events) and ubiquitous sulfate based pollution from the Gulf's prevalent petroleum industry (10-100 mg m À3 ). Smoke and pollution from Europe and possibly Africa were found at levels between 1.5 and 5 km. Inland, classic deep over desert boundary layer characteristics were found. Over the Arabian Gulf, dust and pollution were most often either trapped below or sequestered above a strong stable boundary. However, there were cases where a well-distributed aerosol layer crossed the inversion uniformly. Data suggest that the observed vertical profiles can be explained by the rapid formation of stable marine boundary layers as air moves offshore. This can decouple aerosol layers from within the boundary layer to those aloft in regions of vertical wind shear. In the case of pollution, the ability of flaring plumes to penetrate the inversion may also in part determine layering. In coastal regions without vertical wind shear, uniform concentrations with height across the inversion are a result of internal boundary layer development. We conclude that the bulk of the observed variability in particle vertical distribution appear to be controlled by mesoscale and microscale processes, such as the sea/land breeze.

We present a comprehensive overview of particulate air quality across the five major metropolitan areas of South Africa (Cape Town, Bloemfontein, Johannesburg and Tshwane (Gauteng Province), the Industrial Highveld Air Quality Priority Area (HVAPA), and Durban), based on a decadal (1 January 2000 to 31 December 2009) aerosol climatology from multiple satellite platforms and detailed analysis of ground-based data from 19 sites throughout Gauteng Province. Satellite analysis was based on aerosol optical depth (AOD) from MODIS Aqua and Terra (550 nm) and MISR (555 nm) platforms, Ångström Exponent (α) from MODIS Aqua (550/865 nm) and Terra (470/660 nm), ultraviolet aerosol index (UVAI) from TOMS, and results from the Goddard Ozone Chemistry Aerosol Radiation and Transport (GOCART) model. At continentally influenced sites, AOD, α, and UVAI reach maxima (0.12–0.20, 1.0–1.8, and 1.0–1.2, respectively) during austral spring (September–October), coinciding with a period of enhanced dust generation and the maximum integrated intensity of close-proximity and subtropical fires identified by MODIS Fire Information for Resource Management System (FIRMS). Minima in AOD, α, and UVAI occur during winter. Results from ground monitoring indicate that low-income township sites experience by far the worst particulate air quality in South Africa, with seasonally averaged PM10 concentrations as much as 136 % higher in townships that in industrial areas. We report poor agreement between satellite and ground aerosol measurements, with maximum surface aerosol concentrations coinciding with minima in AOD, α, and UVAI. This result suggests that remotely sensed data are not an appropriate surrogate for ground air quality in metropolitan South Africa.

An innovative approach to studying the effects of cloud seeding on precipitation is to focus on understanding the natural variability of precipitation and the microphysical responses to aerosol.

The Pandora spectrometer that uses direct‐Sun measurements to derive total column amounts of gases provides an approach for (1) validation of satellite instruments and (2) monitoring of total column (TC) ozone (O3) and nitrogen dioxide (NO2). We use for the first time Pandora and Ozone Monitoring Instrument (OMI) observations to estimate surface NO2 over marine and terrestrial sites downwind of urban pollution and compared with in situ measurements during campaigns in contrasting regions: (1) the South African Highveld (at Welgegund, 26°34′10″S, 26°56′21″E, 1,480 m asl, ~120 km southwest of the Johannesburg‐Pretoria megacity) and (2) shipboard U.S. mid‐Atlantic coast during the 2014 Deposition of Atmospheric Nitrogen to Coastal Ecosystems (DANCE) cruise. In both cases, there were no local NOx sources but intermittent regional pollution influences. For TC NO2, OMI and Pandora difference is ~20%, with Pandora higher most times. Surface NO2 values estimated from OMI and Pandora columns are compared to in situ NO2 for both locations. For Welgegund, the planetary boundary layer (PBL) height, used in converting column to surface NO2 value, has been estimated by three methods: co‐located Atmospheric Infrared Sounder (AIRS) observations; a model simulation; and radiosonde data from Irene, 150 km northeast of the site. AIRS PBL heights agree within 10% of radiosonde‐derived values. Absolute differences between Pandora‐ and OMI‐estimated surface NO2 and the in situ data are better at the terrestrial site (~0.5 ppbv and ~1 ppbv or greater, respectively) than under clean marine air conditions, with differences usually >3 ppbv. Cloud cover and PBL variability influence these estimations.

This paper investigates trends of historical and projected future South African coal-fired power station criteria (total primary Particulate Matter (PM), Sulphur Dioxide (SO2) and Nitrogen Oxides (NOx)) and Carbon Dioxide (CO2) emissions. It was found that an energy restricted environment has an increasing effect on emissions, as emissions per energy unit increased from the onset of the South African energy crisis. PM emissions particularly, increased during the energy crisis period, due to increased pressure on PM abatement and lowered maintenance opportunity. Projections of future coal-fired power station criteria and CO2 emissions are made for four different future scenarios for the period 2015 to 2030. Three of the four scenarios are based on the lower projected energy demand baseline case as published in the updated Integrated Development Plan (IRP). The difference between these three scenarios is different retrofit rates of power stations with emissions abatement technologies. The fourth scenario is a worst case scenario and assumes high energy demand (and therefore no decommissioning of power stations), high emission rates (similar to worst past emission rates during the period 1999-2012) and no further abatement of emissions above and beyond current mitigation efforts. This scenario gives an indication of what South African coal-fired power station emissions could look like if the energy crisis persists. There is a marked difference between projected best and worst case PM emissions during the entire projected period, but especially during 2030 when worst case PM emissions compared to a 2015 baseline value are expected to rise by 40% and best case PM emissions are projected to decline by 40%. Worst case NOx emissions are expected to increase by 40% in 2030 from a 2015 baseline value whereas best case emissions are expected to decline 10% from the same level in 2030. Worst case SO2 emissions are predicted to increase by around 38% in 2030 and best case emissions are expected to decrease by around 20% in 2030 from a 2015 baseline value. Relative emissions used in the projection of future CO2 emissions in this paper differ from that used in the energy demand and energy mix modelling done for the updated IRP baseline case. The reason for this is that the modelling for the updated IRP assumed relative CO2 emission factors for supercritical boilers, whereas only Kusile and Medupi fall in this category and relative emissions from all other stations are, in fact, between 5% and 16% higher. For this reason, it seems unlikely that the South African climate commitment target for 2030 will be made.

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We present a comprehensive overview of particulate air quality across the five major metropolitan areas of South Africa (Cape Town, Bloemfontein, Johannesburg and Tshwane (Gauteng Province), the Industrial Highveld Air Quality Priority Area (HVAPA), and Durban), based on a decadal (1 January 2000 to 31 December 2009) aerosol climatology from multiple satellite platforms and detailed analysis of ground-based data from 19 sites throughout Gauteng Province. Satellite analysis was based on aerosol optical depth (AOD) from MODIS Aqua and Terra (550 nm) and MISR (555 nm) platforms, Ångström Exponent (α) from MODIS Aqua (550/865 nm) and Terra (470/660 nm), ultraviolet aerosol index (UVAI) from TOMS, and results from the Goddard Ozone Chemistry Aerosol Radiation and Transport (GOCART) model. At continentally influenced sites, AOD, α, and UVAI reach maxima (0.12-0.20, 1.0-1.8, and 1.0-1.2, respectively) during austral spring (September-October), coinciding with a period of enhanced dust generation and the maximum integrated intensity of close-proximity and subtropical fires identified by MODIS Fire Information for Resource Management System (FIRMS). Minima in AOD, α, and UVAI occur during winter. Results from ground monitoring indicate that low-income township sites experience by far the worst particulate air quality in South Africa, with seasonally averaged PM 10 concentrations as much as 136 % higher in townships that in industrial areas.We report poor agreement between satellite and ground aerosol measurements, with maximum surface aerosol concentrations coinciding with minima in AOD, α, and UVAI. This result suggests that remotely sensed data are not an appropriate surrogate for ground air quality in metropolitan South Africa.