Atmospheric dry and wet deposition of sulphur and nitrogen species and assessment of critical loads of acidic deposition exceedance in South Africa

We tested the hypothesis that acidic atmospheric pollution deposition, originating from the South African central industrial area, poses an environmental threat across a larger region within the dispersal footprint. A network of 37 passive monitoring sites to measure SO2 and NO2 was operated from August 2005 to September 2007. The area extended over the entire northern and eastern interior of South Africa. Monitoring locations were chosen to avoid direct impacts from local sources such as towns, mines and highways. Dry deposition rates of SO2 and NO2 were calculated from the measured concentrations. Concentrations of sulphur and nitrogen species in wet deposition from a previous study were used in conjunction with measured rainfall for the years 2006 and 2007 to estimate the wet deposition over the region. The calculated total (non-organic) acidic deposition formed the basis for an assessment of exceedance of critical loads based on sensitivity of the regional soils. Regional soil sensitivity was determined by combining two major soil attributes available in the World Inventory of Soil Emission Potentials (International Soil Reference and Information Centre). Results indicate that certain parts of the central pollution source area on the South African Highveld have the potential for critical load exceedance, while limited areas downwind show lower levels of exceedance. Areas upwind and remote areas up and downwind, including forested areas of the Drakensberg escarpment, do not show any exceedance of the critical loads

Surface Ozone Variability and Trends over the South African Highveld from 1990 to 2007

Surface ozone is a secondary air pollutant formed from reactions between nitrogen oxides (NOx = 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 Nio-Southern Oscillation (ENSO) and NOx 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 Nio, 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 Nia, 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 NOx. 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 Nio amplifies ozone formation and La Nia reduces ozone formation. Three out of the five stations reveal statistically significant sensitivity to NOx variability, primarily in winter and spring. Accounting for ENSO and NOx 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

A perspective on South African coal fired power station emissions

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

A perspective on South African coal fired power station emissions

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

Fine PM emission factors from residential burning of solid fuels using traditional cast-iron coal stoves

Residential burning of solid fuels is a major source of fine particulate matter (PM2.5), which degrades indoor and ambient air quality in low-income settlements. The adverse impact of fine particulate emissions on the environment and human health is well-documented in other countries such as China and India; however, there is need for local studies to report on emission factors from residential burning of solid fuels. An emission factor quantifies the total mass of a pollutant emitted per amount of fuel burned. Emission factor is an input parameter in air quality modelling to forecast a pollutant concentrations over time and when calculating total emissions from a specific source. Local emission factors are central to managing air quality for they give results that are representative of the source compared with international emission factors. Quantifying emissions, understanding household fuel use patterns and interaction with the stove (stove operation behaviour) during a burning event is fundamental when designing emission control strategies. The aim of the study is to quantify fine particulate matter emissions from residential coal burning using systematic field measurements. The objectives of the study are (i) to characterize stove operation behavior effect on the emissions and (ii) to quantify PM2.5 emission factors using field measurements. Isokinetic (2015) and direct (2014) stack sampling tests were done to observe how PM emissions profiles change with stove operation behavior and to quantify PM2.5 emitted per kilogram of fuel burned. Fine PM emission profiles change with stove operation behavior with an emission factor ranging 6.8 g.kg-1 and 13.5 g.kg-1. The study results implies that residential coal burning is a major source of fine particulate matter in the residential area. As demonstrated that stove operation behaviour affect stove to fuel combination emissions; it is therefore suggested that those factors leading to increase emissions should be kept minimum

Smoke and clouds above the Southeast Atlantic: upcoming field campaigns probe absorbing aerosol’s impact on climate

ArticleFrom July through October, smoke from biomass burning fires on the southern African sub-continent are transported westward through the free troposphere over one of the largest stratocumulus cloud decks on our planet. Biomass burning aerosol (smoke) absorbs shortwave radiation efficiently. This fundamental property implicates smoke within myriad small-scale processes with potential large-scale impacts on climate that are not yet well-understood. A coordinated, international team of scientists from the United States, United Kingdom, France, South Africa and Namibia will provide an unprecedented interrogation of this smoke-and-cloud regime from 2016 to 2018, using multiple aircraft and surface-based instrumentation suites to span much of the breadth of the southeast Atlantic

Source apportionment of ambient PM10−2.5 and PM2.5 for the Vaal Triangle, South Africa

The Vaal Triangle Airshed Priority Area (VTAPA), like other priority areas in South Africa, has an air pollution problem. Understanding the sources contributing to air pollution in this priority area will assist in the selection and implementation of appropriate control strategies. For this study, aerosol samples in the coarse (PM10-2.5) and fine (PM2.5) fraction were collected at four sites in the VTAPA during summer/autumn, winter, and spring. The contributing sources were identified and characterised based on the elemental and ionic compositions obtained through X-ray fluorescence and ion chromatography analysis. The highest seasonal median concentrations of PM10-2.5 (116 μg/m3) and PM2.5 (88 μg/m3) were observed in Sharpeville during the winter. The lowest median concentrations of PM10-2.5 (25 μg/m3) and PM2.5 (18 μg/m3) were detected in Zamdela during the summer/autumn period. At all sites, there was a high abundance of crustal elements in PM10-2.5 and a dominance of coal and biomass combustion-related elements in PM2.5. The Positive Matrix Factorisation receptor model identified dust-related and secondary aerosols as the major contributing sources of PM10-2.5. PM2.5 contributions were predominantly from coal burning for Sebokeng and Sharpeville and from industry, wood and biomass burning, and secondary aerosols for Kliprivier and Zamdela. The results of this study identify the main sources contributing to particulate air pollution in the VTAPA and provide local authorities with valuable information for decision-making.Significance: Dust, industry, domestic coal burning, vehicles, and wood and biomass combustion are the key sources of particulate air pollution in the VTAPA that need to be prioritised by decision-makers. Although Sebokeng and Sharpeville are located within the vicinity of industries, domestic coal burning has a greater contribution to particulate loading at these sites. Results from this study will assist in the design of local municipality air quality management plans for the VTAPA

Increased risk of heat stress conditions during the 2022 Comrades Marathon

The Comrades Marathon is South Africa’s – and the world’s – most recognised and largest ultra-marathon event, with over 15 000 participants from across the globe competing in the 89-km road running event each year. Historically, the event has been held before the start of austral winter (20 May – 17 June). However, in 2022, organisers of the race moved the event to 28 August, when austral spring commences. We explore the climate, in particular the Universal Thermal Comfort Index (UTCI), of past Comrades events (1980-2019) and compare these data to UTCI data of the new proposed date (28 August) for the same period. The climatology for May, June, July and August was determined to identify periods with the lowest risk for ‘strong’ to ‘very strong’ heat stress. Results show that participants’ risk of exposure to ‘strong’ heat stress and ‘very strong’ heat stress periods will be more likely if the event is held in August as compared to the original event dates. Therefore, it is concluded that mid-June to mid-July has the lowest risk of heat stress exposure along the route. Runners and organisers should be aware of the higher risk of exertional heat illness during the 2022 Comrades Marathon to ensure safe participation. Significance: • The new proposed date for the Comrades Marathon will increase the risk of exposure to ‘strong’ and ‘very strong’ heat stress conditions, as defined by the Universal Thermal Comfort Index (UTCI). • The UTCI indicates that mid-June to mid-July has the lowest risk of heat stress exposure at the three reference points along the route. • Organisers should warn runners of the higher risk of exertional heat illness due to the possible exposure to high UTCI values or more unfavourable climatological conditions. Furthermore, runners should be informed of a variety of preventative strategies to ensure safe participation

Assessing the impact of Eskom power plant emissions on ambient air quality over KwaZamokuhle

Coal-fired power plants are considered a major source of criteria air pollutants. The existence of such activities close to densely populated areas has an impact on human health and more generally on the environment. The impact of a pollutant typically depends on its residence time and the existence of background concentration levels. This study evaluates the dispersion of PM2.5, SO2 and NOX emissions from Eskom power plants (Arnot, Hendrina, and Komati) located close to KwaZamokuhle Township. AERMOD was used to assess the contribution of each plant to the air quality of the township. This steady-state dispersion model was used to simulate surface concentrations (1-hour, 24-hour and annual average concentrations) on a 50km domain for 2015-2017. The modelled results together with data obtained from Eskom’s KwaZamokuhle monitoring site were used to estimate the extent to which these power plants contribute to the ambient air quality of KwaZamokuhle Township. The results confirm that the power plants do contribute to concentrations of PM2.5, SO2, and NOx in the ambient air of the township. However, based on a comparison between the modelled and monitored data, it was inferred that power plants are not the only significant source of these criteria pollutants. Evidence from temporal variations in the monitored data shows that domestic burning is likely the major contributor since the variability is more closely associated with burning habits. It is therefore likely that existing regulatory strategies that focus mostly on the industrial sector may not be successful in improving ambient air quality in low-income settlements like KwaZamokuhle

Quantifying potential particulate matter intake dose in a low-income community in South Africa

Understanding how exposure to particulate matter impacts human health is complex. Personal exposure is a function of the pollution concentrations measured at any given place and time. The health impacts of this exposure are, in part, determined by how high pollutant concentrations are and how much pollution can potentially enter the body. This study considered data gathered in the winter of 2013 in a low-income community on the Mpumalanga Highveld, South Africa, which is a geographical area known for its high air pollution levels. Data collected by GPS monitors worn by individuals in the community were used to understand in which microenvironments people spend most of their time. Participants spent time in five main micro-environments: (highest rank first) inside a house, directly outside a house, on a dirt road, on a tar road, and on an open field. Eight days’ worth of ambient, indoor and personal particulate matter measurements were paired with individual GPS positioning data for one study participant. We identified pollutant concentrations where the person spent time and how much particulate matter the person potentially inhaled. Highest concentrations were measured inside the dwelling and directly outside the dwelling of the individual. When comparing directly (ranging from 0.02 – 0.76 mg) - and indirectly (0.02 – 0.34 mg) derived time-weighted potential intake doses, directly derived intake doses were higher and more likely to represent how much particulate matter was potentially inhaled by the participant. This study suggests that people living in communities on the Mpumalanga Highveld are exposed to unacceptably high air pollution levels in places in which they spend most of their time. Direct exposure and intake dose assessments are an important element of environmental health studies to supplement data collected by stationary monitors in order to better understand exactly what people are breathing.https://cleanairjournal.org.zaam2022Geography, Geoinformatics and Meteorolog