Abstract
The much publicised problem with major asbestos pollution and related health issues in South Africa, has called for action to be taken to negate the situation. The aim of this project was to establish a prioritisation index that would provide a scientifically based sequence in which polluted asbestos mines in Southern Africa ought to be rehabilitated. It was reasoned that a computerised database capable of calculating such a Rehabilitation Prioritisation Index (RPI) would be a fruitful departure from the previously used subjective selection prone to human bias. The database was developed in Microsoft Access and both quantitative and qualitative data were used for the calculation of the RPI value. The logical database structure consists of a number of mines, each consisting of a number of dumps, for which a number of samples have been analysed to determine asbestos fibre contents. For this system to be accurate as well as relevant, the data in the database should be revalidated and updated on a regular basis.
Similar content being viewed by others
Avoid common mistakes on your manuscript.
Introduction
Asbestos occurs naturally in almost 60–70% of the earth’s crust and is found in two varieties: serpentine and amphibole asbestos. The most common asbestos types are chrysotile (white asbestos), which is a fibrous serpentine asbestos; and amosite (brown asbestos) and crocidolite (blue asbestos), which are amphiboles. Other forms of amphibole asbestos include actinolite, anthophyllite and tremolite (NICNAS 1999).
Asbestos has a number of applications in construction and manufacturing processes due to several industrially desirable characteristics, including: high tensile strength, fire and heat resistance, durability and versatility (Harris and Kahwa 2003). However, due to the harmful health effects of asbestos dust mining (McDonald and McDonald 1997; Tossavainen et al. 2001), the use of asbestos materials in developed nations has been decreasing. During the twentieth century, evidence suggested that asbestos fibres could lead to serious health disorders, such as asbestosis, lung cancer and mesothelioma. Subsequently, asbestos became the focus of extensive scientific and medical research. Research indicated that all asbestos fibres are not alike and that fibre length and type, dose and exposure play a significant role in the health risk associated with occupational and environmental exposure to asbestos fibres (Harris and Kahwa 2003; Natural Resources Canada 2000). Scientific consensus exists on the fact that fibres in the amphibole group are more harmful (100–500 times) to health than chrysotile, particularly for mesothelioma (Anon. 2004).
Asbestos mining waste poses a significant health risk to those living in surrounding areas and has received much attention in recent years (Harris and Kahwa 2003). Despite the fact that all the asbestos mines and mills in South Africa are now effectively closed, this industry has left a legacy of pollution that continues to poison former mining areas as well as surrounding areas, including school yards, roads, gardens and homes of residents (Anon. 2001). The much publicised problem with major asbestos pollution and related health issues in South Africa, has called for action to be taken to negate this situation. The development of a prioritisation index for the rehabilitation of South Africa’s asbestos mining waste sites is a step in that direction.
Synthetic methodology and data
Synopsis
The database was developed in Microsoft Access and both qualitative and quantitative data were considered for calculation of the rehabilitation prioritisation index (RPI) value. The logical database structure consists of a number of mines (in the respective provinces), each consisting of a number of dumps, for which a number of samples have been analysed to determine asbestos fibre contents. The database structure is outlined by the diagram in Fig. 1. For demonstration purposes two mines from within the database were selected. First, Whitebank mine, Northern Cape Province, South Africa (27°25,75′S; 23°17,75′E) and second Senekal mine, Mpumalanga Province, South Africa (25°33, 5′S; 31°28′E). Senekal is smaller in size than Whitebank, but due to differences in the asbestos hazard and related variables, both have quite high RPI values. Whitebank has a RPI value of 69.33% while Senekal 71.33%. This serves to indicate that size of the site alone will not determine the overall associated risk.
Enumeration of asbestos risk parameters
To collect all relevant information pertaining to a specific mine’s pollution source technical personnel conducted site visits during which both qualitative data and samples for quantitative analysis were gathered. Qualitative data included variables such as demographic, geographic, safety and aesthetical considerations that were very difficult to quantify exactly and will always be subjective depending on the experience of the individual who collected the information. A set of definitions describing what was meant by each qualitative data parameter, how this information was obtained and validated, as well as the conversion factors used to incorporate these values into the database was established and are available for use with the database. A summary of these definitions is provided in Table 1. During each site visit a 10-kg sample was collected from every potential mine pollution source and quantitatively analysed in the mini-asbestos processing plant to determine the total percentage of free asbestos fibre in the sample. The percentage of short fibres within the extracted free asbestos fibre was determined by means of a Canadian shake box.
Table 1 contains the definitions of parameters used and assumptions made during the calculation of the RPI value. In addition to the parameters indicated in the table the following were also considered:
Safety
This information focused on the presence and number of dangerous highwalls and/or adits, which could serve as a potential source of danger to both humans and animals. The exact numbers of highwalls and/or adits were noted and normalised for incorporation in the calculation of the RPI value.
Aesthetics
This information focused on whether past mining activities and indications thereof represent a negative aesthetical impact on the natural environment.
Calculation of the RPI value
Calculation of the RPI value entailed using a formula in which both the quantitative and qualitative data were taken into consideration, but not in a simple additive manner. For example, because of the non-subjectivity and direct relevance to human health the fibre hazard was considered to contribute 50% to the calculated RPI. Three important factors contribute to the fibre hazard: (1) the total percentage free fibre as determined by the mini-processing plant, (2) the estimated scale of the exposed surface area of the mine pollution source and (3) the percentage short fibre present in the total free fibre content. When the total percentage free fibre in a sample was equal to or exceeded 1.8% it could potentially contribute from 8–40% to the RPI value depending on the relative estimated exposed surface area of the pollution source. This fractional contribution was determined by the relative size of the exposed surface area that could vary between one and five, divided by five and multiplied by40. In relative terms the largest potential mine pollution source in the database was considered to be a five in size, being the Msauli complex, while a potential pollution source the size of Zukudu was considered to be a one in size. The percentage short fibre present in the total free fibre content contributed the remainder, up to a maximum of 10%, to the potential 50%. Of the qualitative data parameters; the potential for air pollution (composed of six variables), the potential for erosion and other general pollution (composed of nine variables), safety and aesthetics could potentially contribute 25, 19.5, 5 and 0.5%, respectively to the calculated RPI value. Actual and normalised values, their units and ascribed weights used during the calculation of the RPIvalue are indicated in Table 2.
Classification method and results
Two mine localities previously identified as high-risk localities were selected as case studies to illustrate the calculation of the RPI value (Table 3). The Whitebank mine is an amphibole asbestos mine, while the Senekal mine is a chrysotile asbestos mine. The calculated RPI value for both these mines indicated a high priority for rehabilitation.
Discussion
The development of the asbestos RPI means that for the first time there is a scientifically based method to determine the need for rehabilitation of asbestos pollution by quantifying the risk associated with a specific pollution site. It is important to realise that the success of rehabilitation necessarily depends on the sustainability of the rehabilitative measures applied. This is also applicable to the RPI and explains the importance of frequently revising the information used in the database to ensure relevant and accurate risk assessments.
The database contains information for 113 mines and 144 mine dumps from four provinces in South Africa (Gauteng, Mpumalanga, Northern Cape and Northern Province). Each mine was assessed according to a number of defined parameters and weighted factors as indicated in Tables 1 and 2. The cost of rehabilitation for each mine, as well as the total cost of rehabilitation of all the mines in a specific province can also be determined from the database.
Though the establishment of RPI is a fruitful departure from current, more subjective methods, it is dependant on the quality of the data in the database. In this regard there are some areas of concern in the current databases. The areas of concern pertain mainly to the qualitative data. For example, obtaining the correct rainfall figures and wind direction/speed relevant to a specific mine pollution source is not as simple as it seems, as the first and second order weather stations that gathered the relevant information were sometimes situated kilometres away from the specific mine pollution source in question and assumptions had to be made as described in the definitions. The qualitative data used for calculation of the RPI, included variables such as demographic, geographic, safety and aesthetical considerations that were very difficult to quantify exactly and will always be subjective depending on the experience of the individual who collected the information. Furthermore, it should be realised that some of the qualitative data collected, for example the number of inhabitants in the prevailing wind direction, are not static and will likely change with time necessitating constant updates.
Concluding remarks
The use of the asbestos RPI has been implemented by the South African Department of Minerals and Energy as part of the governments integrated and co-operative approach towards the rehabilitation of the asbestos legacies of the past. In accordance with this index, 145 derelict and ownerless asbestos mines/dumps have been identified, of which only 84 still need to be rehabilitated.
Abbreviations
- RPI:
-
Rehabilitation Prioritisation Index
References
Anon (2001) Asbestos-related disease in South Africa: opportunities and challenges remaining since the 1998 parliamentary asbestos summit. A report presented to The Parliamentary Portfolio Committee on Environmental Affairs and Tourism. 12 October 2001 http://www.brown.edu/Departments/African_American_Studies/Asbestos
Anon (2004) What is the logic being applied by anti-asbestos activists? The Asbestos Institute, Montreal, Canada. http://www.asbestos-institute.ca
Harris LV, Kahwa IA (2003) Asbestos: old foe in 21st century developing countries. Sci Total Environ 307:1–9
McDonald JC, McDonald AD (1997) Chrysotile, asbestos and carcinogenity. Ann Occup Hyg 41:669–705
Natural Resources Canada (2000) Chrysotile asbestos fact sheet. http://www.nrcan.gc.ca/mms/pdf/chry_e.pdf. Accessed June 2004
NICNAS (1999) National Industrial Chemicals Notification and Assessment Scheme. Chrysotile asbestos priority existing chemical no. 9—full public report. http://www.nicnas.gov.au/publications/CAR/PEC/PEC9/PEC9index.htm. Accessed June 2004
Tossavainen A, Kotilainen M, Takahashi K, Pan G, Vanhala E (2001) Amphibole fibres in chinese chrysotile asbestos. Ann Occup Hyg 45:145–152
Acknowledgments
The authors would like to acknowledge the input and vision of the personnel from Eco Rehab, in particular that of Dr J Booysen for his management of this project and Ms R Nel for her effort in compiling the database.
Open Access
This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Open Access This is an open access article distributed under the terms of the Creative Commons Attribution Noncommercial License (https://creativecommons.org/licenses/by-nc/2.0), which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
About this article
Cite this article
van Rensburg, L., Claassens, S., Bezuidenhout, J.J. et al. Rehabilitation of asbestos mining waste: a Rehabilitation Prioritisation Index (RPI) for South Africa. Environ Geol 57, 267–273 (2009). https://doi.org/10.1007/s00254-008-1250-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00254-008-1250-z