Spatial epidemiology risk assessment for rehabilitated former asbestos mining areas in Limpopo Province, South Africa, using remote sensing and conventional analytical methods

Article

Spatial epidemiology risk assessment for rehabilitated former asbestos mining areas in Limpopo Province, South Africa, using remote sensing and conventional analytical methods

DOI: 10.1080/10158782.2010.11441397
Author(s): B M Petja Department of Geography and Environmental Studies, South Africa , G T Tengbeh Department of Geography and Environmental Studies, South Africa , Y A Twumasi Department of Advanced Technologies, USA , M Atanasova Mineralogy Laboratory, Council for Geoscience, South Africa

Abstract

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 effcacy in assessing asbestos pollution. X-ray diffraction and scanning electron microscopy were employed for the identifcation 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 feld spectrometer was used for spectral analysis of asbestos minerals and that of soil and water samples to compare and validate refectance spectroscopy fndings 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 signifcant 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.

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