ESG criteria have increasingly been used by investors to measure sustainability levels for investment in a company or business. In the mining sector, most, if not all, of the available commercial software used for decision-making support, does not include sustainability indicators such as carbon footprint, water consumption, social license, and other factors commonly associated with ESG practices. In this context, the present work presents the current development state of an open-use, cloud-based computational tool called MAFMINE ESG, which aims to incorporate environmental, social, and governance (ESG) sustainability indices to the usual technical-economical parameters used into the preliminary evaluation of mining projects.

The MAFMINE ESG consists of the expansion version of “MAFMINE 3”, an already existing tool developed for the economic evaluation of mining projects (available at https://www.mafmine.com.br/v3/). The core of MAFMINE ESG consists of using parametric models supported by a relatively simple set of inputs (process targets and technical coefficients specified by the user), providing preliminary estimates of sustainability indicators as model outputs. These indicators are quantitative indices associated with one of the following ESG model parameters: emissions, water management, land use, social conflicts, automation and digitalization, and governance. For example, the following indicators are associated with the "water management" parameter: total water withdrawn, affected water sources, % of water reused/recycled, and quality and destination of effluents. The parameterization of indices is established through regression analysis, within specific validation ranges, using available databases for each parameter, such as the historical series report databases from the Intergovernmental Panel on Climate Change (IPCC) for emissions and the Global Reporting Initiative (GRI) for water management.

In addition to presenting the general structure of the software under development, this paper aims to discuss the challenges associated with selecting the indexing factors linked to each index to compare project scenarios considering the realities of different countries together with a preliminary simulation for the case of a base metals mining venture.

In the mining industry, one of the main concerns is estimating costs in order to carry out projects efficiently and profitably. MAFMINE is a tool that provides quick and effective results for decision-making. My research was carried out using two parametric equation modeling methodologies, mainly manuals were studied (Bureau of Mines Cost Estimating System Handbook and Costs and Cost Estimation of T. Alan O'Hara and Stanley C. Suboleski), this work focuses on the area of mineral processing, the estimates for operations in processing plant. The parametric equations proposed and added in the plant area make it possible to estimate the processing costs of various circuits, which are fundamental for future plant facility design. These equations also make it possible to estimate the cost of implementations within mineral processing, which in turn allows the most appropriate option to be selected based on the characteristics of each ore. Each methodology has its own advantages and disadvantages, so it was necessary to select appropriate standardization factors. Once the cost estimation tool had been updated with the new parametric equations obtained, it was applied to specific case studies. The results obtained demonstrate the tool's reliability. In conclusion, the study of parametric equation modeling methodologies has made it possible to update a cost estimation tool in the area of mineral processing plants. The inclusion of more parametric equations to estimate mineral processing costs will enable better decisions to be made.