Authors: Deissmann, G; Kistinger, S

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DOI https://doi.org/10.36487/ACG_repo/852_47

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Deissmann, G & Kistinger, S 2008, 'Evaluation of Sustainable Remediation Measures for Mine Closure and Derelict Mining Sites — Application of Predictive Geochemical Models and Risk-Based Cost-Benefit Analyses for Decision Making', in AB Fourie, M Tibbett, I Weiersbye & P Dye (eds), Mine Closure 2008: Proceedings of the Third International Seminar on Mine Closure, Australian Centre for Geomechanics, Perth, pp. 521-529, https://doi.org/10.36487/ACG_repo/852_47

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Abstract:
Active and abandoned mining and milling sites can represent complex environmental situations, where health risks and environmental detriments may result from the discharge of contaminated mine waters into surface and ground waters, dust dispersion as well as from other mining related hazards like dam or slope failures. The sustainable closure of a mining site, as well as the clean-up of legacies of historic mining, requires appropriate methodologies to support the decision making and prioritization of remedial measures and their implementation. In this paper we describe a methodology employed to evaluate remediation measures within the framework of the closure of uranium mining and milling facilities in Eastern Germany. The decision-making process for the remediation of large waste rock dumps (total volume approximately 125 million m³) at a uranium mining site is used as an example. In the context of this approach, appropriate and sustainable remediation measures should (i) reduce the environmental impacts from the waste rock dumps to acceptable levels, and (ii) have the best cost/benefit ratio (i.e. the lowest overall costs). These overall costs comprise direct short-term capital costs for remediation measures (e.g. application of engineered covers, backfill of mine waste into open pits), medium to long-term costs (e.g. for monitoring, maintenance, seepage collection/treatment), as well as the monetary equivalents of residual risks for human health and impacts on the environment (e.g. impairments of ecosystems, land value or groundwater resources). In this context these factors are evaluated by geochemical modeling/air dispersion modeling. Uncertainties in the costs and benefits of the remediation measures are addressed by stochastic methods (Monte-Carlo simulations).

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