2024 - Sustainable Industrial Processing Summit
SIPS 2024 Volume 2. Anastassakis Intl. Symp / Mineral Processing
| Editors: | F. Kongoli, L. Andric, K. Aravossis, V. Chanturiya, I. Chatjigeorgiou, D. Fuerstenau, C. Kavalopoulos, C. O'Connor, V. Panayotov, J. Rubinstein |
| Publisher: | Flogen Star OUTREACH |
| Publication Year: | 2024 |
| Pages: | 384 pages |
| ISBN: | 978-1-998384-06-8 (CD) |
| ISSN: | 2291-1227 (Metals and Materials Processing in a Clean Environment Series) |
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MAFMINE ESG - AN INNOVATIVE TOOL FOR INDICATING SUSTAINABILITY IN MINING PROJECTS
Carlos Petter1; Weslei Ambros1; Upiragibe Pinheiro1; Rafael D'Arrigo1; Fernando Cantini1; Renato Petter1; João Oppermann1;1FEDERAL UNIVERSITY OF RIO GRANDE DO SUL, Porto Alegre, Brazil;
Type of Paper: Invited
Id Paper: 246
Topic: 5
Abstract:
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 For example, the following indicators are associated with the "water management" parameter: total water withdrawn, affected water sources, % of water reused/recycled, and quality and destination of effluents.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.