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The Kirki project aimed to identify, among the mining waste abandoned at a mine and processing plant, the most critical potential pollution sources, the exposed milieus and the main pathways for contamination of a littoral area. This was accompanied by the definition of a monitoring network and remedial options. For this purpose, field analytical methods were extensively used to allow a more precise identification of the source, to draw relevant conceptual models and outline a monitoring network. Data interpretation was based on temporal series and on a geographical model. A classification method for mining waste was established, based on data on pollutant contents and emissions, and their long-term pollution potential. Mining waste present at the Kirki mine and plant sites comprises (A) extraction waste, mainly metal sulfide-rich rocks; (B) processing waste, mainly tailings, with iron and sulfides, sulfates or other species, plus residues of processing reagents; and (C) other waste, comprising leftover processing reagents and Pb—Zn concentrates. Critical toxic species include cadmium and cyanide. The stormy rainfall regime and hilly topography favour the flush release of large amounts of pollutants. The potential impacts and remedial options vary greatly. Type C waste may generate immediate and severe chemical hazards, and should be dealt with urgently by careful removal, as it is localised in a few spots. Type B waste has significant acid mine drainage potential and contains significant amounts of bioavailable heavy metals and metalloids, but they may also be released in solid form into the surface water through dam failure. The most urgent action is thus dams consolidation. Type A waste is by far the most bulky, and it cannot be economically removed. Unfortunately, it is also the most prone to acid mine drainage (seepage pH 1 to 2). This requires neutralisation to prevent acid water accelerating heavy metals and metalloids transfer. All waste management options require the implementation of a monitoring network for the design of a remediation plan, efficiency control, and later, community alert in case of accidental failure of mitigation/remediation measures. A network design strategy based on field measurements, laboratory validation and conceptual models is proposed.

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