Assessment of changes in concentrations of selected criteria pollutants in the Vaal and Highveld Priority Areas

Feig, Gregor; Garland, R. M.; Naidoo, Sasha; Maluleke, Amukelani; Merwe, Marna Van der

doi:10.17159/caj/2019/29/2.7464

Cited by 15 publications

(16 citation statements)

References 17 publications

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“…Furthermore, compliance with the annual ambient PM 10 standard was not achieved at all the monitoring stations except at Grootvlei monitoring station from 2007 to 2013. Feig et al (2019) found similar results in the HPA with the only exceedance of the annual ambient SO 2 standard at the Witbank monitoring station between 2008 and 2014, and an exceedance of the annual ambient PM 10 standard at all monitoring stations expect at the Hendrina and Middelburg stations.…”

Section: Discussionsupporting

confidence: 70%

“…A statistically significant increasing trend in PM 10 concentrations was found at Camden monitoring station. The increase in PM 10 levels at Camden contrasts with the decreasing trend observed by Feig et al (2019) in Ermelo, which suggests that activities at Camden may be affecting PM 10 concentrations downwind. In terms of compliance, this study indicates compliance with the annual SO 2 National Ambient Air Quality Standard at all monitoring stations except at Komati monitoring station in 2009.…”

Section: Discussionmentioning

confidence: 61%

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The impacts of commissioning coal-fired power stations on air quality in South Africa: insights from ambient monitoring stations

Morosele

Langerman

2020

Clean Air J.

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The South African electricity sector is known for its heavy reliance on coal. The aim of this study is to assess the impacts of increasing SO2 and PM emissions from the three return-to-service power stations (Komati, Camden and Grootvlei), and the newly constructed Medupi power station on ambient air quality measured in the vicinities of these power stations. Trends in ambient pollution concentrations were determined using Theil-Sen analysis. The correlation between the emissions and ambient pollution concentrations at nearby monitoring stations was determined with the Spearman partial rank correlation coefficient. Lastly, compliance of ambient pollution concentrations with the South Africa National Ambient Air Quality Standards was assessed. Few statistically significant trends in ambient SO2 and PM10 concentrations are found, and there is little correlation between increasing power station emissions and ambient pollutant concentrations in the vicinity. It is only at Camden monitoring station where there are increases in PM10 concentrations from the direction of Camden power station, and at Grootvlei monitoring station where increasing SO2 concentrations are from the directions of Grootvlei and Lethabo power stations. A strong, positive correlation between power station emissions and ambient concentrations exists only for SO2 at Grootvlei monitoring station and PM10 at Medupi monitoring station (although it is likely that the correlation at Medupi is related to construction and vehicle activity, and not emissions from Medupi power station stacks). It is concluded that the establishment of monitoring stations in the vicinities of power stations is necessary but not sufficient to monitor their impact on air quality in the surrounds.

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Section: Discussionsupporting

confidence: 70%

Section: Discussionmentioning

confidence: 61%

The impacts of commissioning coal-fired power stations on air quality in South Africa: insights from ambient monitoring stations

Morosele

Langerman

2020

Clean Air J.

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“…SO 2 is not a variable of concern in the Priority Areas (except for at eMalahleni) (Feig et al, 2019), but O 3 is of concern in the Vaal (Govender and Sivakumar, 2019). Perhaps surprisingly, Feig et al (2019) demonstrate that ambient SO 2 levels in the Priority Areas are lower than SO 2 levels in the large South African metropolitan centres in the 1960s.There is a statistically significant increasing trend in O 3 concentrations at two of the six monitoring sites, and no significant trends in monthly O 3 concentrations at the other four sites in the Vaal (Govender and Sivakumar, 2019). Since O 3 is a secondary pollutant, there is a need to understand the emission and transport of precursors in order to design effective initiatives to reduce ambient O 3 levels.…”

mentioning

confidence: 91%

“…The results of these studies show that there is still widespread non-compliance with ambient particulate matter levels in the Vaal Triangle and Highveld Priority Areas (there is noncompliance with the annual ambient PM 10 standard at seven of the eleven monitoring stations and non-compliance with the annual average PM 2.5 standard at eight of the eleven monitoring stations (Feig et al, 2019)). There are significant downward trends at most of the monitoring stations, however (PM 10 and PM 2.5 concentrations are declining at eight and nine of the eleven sites, respectively (Feig et al, 2019)). The annual rate of decline is generally small, ranging between 1 and 5 µg/m 3 /year.…”

mentioning

confidence: 98%

“…analyse long-term changes in PM 2.5 and O 3 concentrations in the Vaal Triangle Airshed Priority Area, while Feig et al (2019) examine trends in PM 10 , PM 2.5 and SO 2 in the Vaal Triangle Airshed and Highveld Priority Areas. For both studies, the ambient air quality data was extracted from the South Africa Air Quality Information System (SAAQIS) database and Theil-Sen trend analysis was performed using the Open Air Package in R (in addition to other analyses).…”

mentioning

confidence: 99%

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The use of long-term datasets for informing and evaluating air quality policy initiatives

Langerman

2019

Clean Air J.

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Political institutions generally desire to use the best available scientific evidence when formulating policy. In South Africa, the declaration of the Priority Areas where 'ambient air quality standards are being, or may be, exceeded' (according to the National Environmental Management: Air Quality Act, 2004) is an example of a policy initiative that was prompted by quantitative evidence-measurements of ambient air pollution levels. National Priority Areas have been declared in the Vaal Triangle in 2006, in the Highveld in 2007 and in the Waterberg-Bojanala region in 2012. The Department of Environment, Forestry and Fisheries (DEFF, formerly the Department of Environmental Affairs) established a network of 6 ambient air quality monitoring stations in the Vaal Triangle and 5 monitoring stations in the Highveld Priority Area to inform the emission reduction strategies and track progress in reducing ambient pollution levels. The summarised data from these monitoring stations is presented annually by the National Air Quality Officer in the State of the Air Report. In this issue of the Clean Air Journal, there are two papers (Feig et al., 2019 and Govender and Sivakumar, 2019) that have subjected the 10+ years of data from these monitoring stations to more rigorous trend analysis, which allows reflection on progress made to date and future regulatory priorities.

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The sensitivity of health impact assessments of PM2.5 from South African coal-fired power stations

Simelane,

Langerman

2023

Air Qual Atmos Health

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Unabated emissions of precursor gases from coal-fired power stations in South Africa greatly contribute to ambient PM2.5 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 PM2.5 exposure flattens out at higher PM2.5 concentrations, a smaller number of premature mortalities is calculated if a reduction in PM2.5 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 PM2.5 levels (“attributable deaths”). Total ambient PM2.5 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 PM2.5 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 PM2.5 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.

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Assessment of changes in concentrations of selected criteria pollutants in the Vaal and Highveld Priority Areas

Cited by 15 publications

References 17 publications

The impacts of commissioning coal-fired power stations on air quality in South Africa: insights from ambient monitoring stations

The impacts of commissioning coal-fired power stations on air quality in South Africa: insights from ambient monitoring stations

The use of long-term datasets for informing and evaluating air quality policy initiatives

The sensitivity of health impact assessments of PM2.5 from South African coal-fired power stations

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