Cost – Benefit Analysis through Stochastic Risk Assessment on Mining Waste Management

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 3R’s 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 project’s 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. CBA’s evaluation involves each case scenario’s parameters converted into monetary terms. CBA’s extracted results are calibrated through Bayesian Analysis to provide more accurate Financial Risk (FR) estimation. The physical meaning of Bayesian Analysis’s provided calibration to the CBA is to obtain the ability to implement stochastic risk in realistic conditions.