ABSTRACT
Background: Asbestos mining and other activities have left a legacy of environmental contamination. Asbestos was used in a large number of manufactured products but little is documented about the nature and location of these products. Compliance with asbestos regulations depends on accurate identification of the presence of asbestos. The National Institute for Occupational Health (NIOH) has been identifying asbestos for regulatory purposes since 2003. Objective: To analyse a database of samples submitted for asbestos analysis to the NIOH. Methods: Asbestos was identified using scanning electron microscopy and energy dispersive spectroscopy. The data were analysed using STATISTICA version 11. Results: From 2003 to 2012; 1514 samples were analysed. Asbestos was identified in 59.9 of the bulk samples and crocidolite was present in 45.4 of these. Information about samples containing asbestos; including their origin and associated activities; are described. Conclusions: Although asbestos is no longer mined or used in South Africa; workers remain at risk of exposure due to asbestos-containing materials which persist in the environment. Knowledge of these materials gained from routinely collected data may assist in the safe removal of asbestos and prevent further adverse health =effects
Subject(s)
Asbestos , Data Collection , Environment and Public Health , Environmental Exposure , Environmental PollutionABSTRACT
The aim of this study was to conduct a comparative analysis using remote sensing and conventional sample analysis to assess asbestos pollution in rehabilitated former asbestos mining areas. The study focused on the Mafefe and Mathabatha areas of Limpopo Province; South Africa. Field-based remote sensing techniques were used to spectrally differentiate various types of asbestos minerals in order to determine their efficacy in assessing asbestos pollution. X-ray diffraction and scanning electron microscopy were employed for the identification and characterisation of traces of asbestos minerals in soil and water samples collected from the rehabilitated areas. The samples were also examined using in situ remote sensing. An Analytical Spectral Devices field spectrometer was used for spectral analysis of asbestos minerals and that of soil and water samples to compare and validate reflectance spectroscopy findings with laboratory results. Results show that in situ remote sensing techniques are able to reveal traces of asbestos minerals on rehabilitated dry surface areas; suggesting that they can play a significant role in monitoring the distribution of the asbestos minerals for epidemiological risk assessment. However; the spectral characteristics of asbestos minerals in the water medium were not as distinct as compared to laboratory methods. Overall; the results show potential for using remote sensing techniques in spatial epidemiology studies