Life-Cycle Assessment of Data-Driven Mineral Extraction: Environmental and Economic Trade Offs

Abstract

This study presents a comprehensive life-cycle assessment (LCA) comparing traditional and data-driven mineral extraction methods for critical minerals. The research quantifies both environmental impacts and economic implications across the entire extraction lifecycle, from exploration to site rehabilitation. Primary data collected from three operational mining sites with varying levels of technological implementation demonstrates that data-driven approaches reduce global warming potential by 26.7%, water consumption by 36.2%, and land disturbance by 31% compared to traditional methods. Economic analysis reveals that despite 34.2% higher initial capital investments, data-driven operations reduce operational expenditures by 22.8% with a payback period of approximately 4.3 years. The study identifies significant trade-offs between environmental performance, capital investment, social impacts, and extraction efficiency. The findings provide evidence-based guidance for industry stakeholders and policymakers seeking to optimize mineral extraction while balancing environmental sustainability and economic viability, particularly in the context of increasing demand for critical minerals needed for clean energy technologies.