Boletín de la Sociedad Geológica Mexicana

Volumen 67, núm. 3, 2015, p. 493-508

Surface Complexation Modelling of Arsenic and Copper Immobilization by Iron Oxide Precipitates Derived from Acid Mine Drainage

Alba Otero-Fariña1, Raquel Gago2, Juan Antelo2,*, Sarah Fiol1, Florencio Arce1

1 Department of Physical Chemistry, University of Santiago de Compostela, Avenida de las Ciencias s/n, 15782 Santiago de Compostela, Spain.
2 Department of Soil Science and Agricultural Chemistry. University of Santiago de Compostela, Rúa Lope Gómez de Marzoa s/n, 15782 Santiago de Compostela, Spain.

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Abstract

Acid mine drainage (AMD) constitutes a serious environmental problem in mining areas due to the acidification of soils and aquatic systems, and the release of toxic metals. Many of the pollutants that occur in AMD display a high affinity for the surfaces of the aluminium and iron oxides that are typically present in systems affected by AMD. This binding affinity reduces the mobility of trace metals and metalloids, such as copper and arsenic, thus helping to mitigate contamination of aquatic systems. In the present study, water samples and iron-rich bed sediments were collected in areas affected by copper mining activities. A loose ochre-coloured precipitate occurring on the banks of a river close to an abandoned tungsten and tin mine was also sampled. The composition of the precipitate was established, and adsorption experiments were performed with copper and arsenate ions to determine the ability of natural iron precipitates to reduce the concentration of these ions in solution. Surface complexation models provided a good description of the behaviour of natural iron oxides in terms of copper and arsenate retention. Use of this type of model enables prediction of the distribution of pollutants between the solid and solution phases and analysis of their mobility in relation to environmental conditions (pH, ionic strength, presence of competing species, etc.).

Keywords: Acid mine drainage, iron oxides, adsorption, trace elements, arsenic, surface complexation model.