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Cost Benefit Bayesian Analysis for Mining Waste Management contributes positively to developing an alternative methodology that could be implemented on an industrial scale. Two case scenarios are examined. The first scenario refers to the presentation of mining activities without 3Rs policy (reduce, recover, reuse wastes) and non-implementation of environmental protection measures. The second scenario refers to the presentation of mining activities with full implementation of environmental protection requirements by a closed system of industrial units for metal recovery and avoiding free disposal of tailings in soil areas. Considering a) each projects aim and scope, b) legislative requirements for environmental protection, and c) escalation of penalty cost for non-compliance with the corresponding legislation, the total cost for each case scenario is extracted. Cost-benefit analysis (CBA) evaluates the sustainability of each case scenario by its Financial Risk. The scope of this paper is to ensure the adaptability of the CBA appraisal tool to each similar subject of study, in which the lowest Financial Risk indices characterize optimal business decisions. CBAs evaluation involves each case scenarios parameters converted into monetary terms. CBAs extracted results are calibrated through Bayesian Analysis to provide more accurate Financial Risk (FR) estimation. The physical meaning of Bayesian Analysiss provided calibration to the CBA is to obtain the ability to implement stochastic risk in realistic conditions.
Machairas et al. (Fri,) studied this question.