Geostatistical estimation of chemical contamination in stream sediments: The case study of Vale das Gatas mine (northern Portugal)

• Autor(a) principal: Salgueiro, Ana Rita Gonçalves Neves Lopes
• Data de Publicação: 2008
• Outros Autores: Ávila, P. Freire, Pereira, H. Garcia, Oliveira, J. M. Santos
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da Universidade Federal do Ceará (UFC)
• Texto Completo: http://www.repositorio.ufc.br/handle/riufc/64707
• topic: Abandoned mines; Environmental remediation; Global Contamination Index; Indicator Block Kriging

Based on an environmental geochemistry case study carried out in the neighbourhood of a W–Sn abandoned mine, the pollution in stream sediments was modelled through a Global Contamination Index. Such an index permits one to summarize the combination of deleterious elements in a single variable, obtained by the projection of samples onto the first axis of a PCASD (Principal Components Analysis of Standardized Data) applied to the entire n×p matrix containing the available concentrations of p=16 elements in the set of n=220 collected samples. In order to provide a sound basis for a coherent planning of the remediation process which will be put in operation in the affected area, it is necessary to balance the costs of reclaiming with the probabilities of exceeding the upper limits accepted for concentrations of environmentally harmful elements in sediments. Given these limits, they are back-transformed in the index values, providing a practical threshold between ‘clean’ and ‘contaminated’ samples. On the other hand, the minimum dimension of the cell to be reclaimed is restrained by the selected remediation process to be applied in the affected area. Hence, to meet the constraints of such a remediation process, it is required to estimate the probabilities of exceeding the index threshold in technologically meaningful sub-areas. For this end, the Indicator Block Kriging technique was applied, producing a series of maps where sub-areas to be reclaimed can be spotted for different probability levels. These maps, on which the decision making remediation agency can rely for its cost-benefit analysis, take into account both the spatial structure of ‘clean’ vs. ‘contaminated’ samples and the constraints of the reclaiming process.