Life cycle assessment of mining haulage systems: A systematic review of low-carbon and autonomous technologies

The mining sector faces increasing pressure to decarbonize while maintaining productivity, with haulage systems among its most energy- and emission-intensive components. Life Cycle Assessment (LCA) is increasingly used to quantify environmental impacts and support technology transition planning, including electrification and automation. However, the extent to which current LCA studies capture the complexity of emerging low-carbon and autonomous haulage systems remain unclear. This study conducts a PRISMA 2020 systematic review synthesizing evidence from 17 peer-reviewed studies assessing mining haulage technologies through life-cycle-based approaches. Results show a strong concentration on diesel and battery-electric haul trucks, while other equipment categories and system-level transport alternatives remain underrepresented. Most studies prioritize greenhouse gas emissions and energy consumption, with limited and inconsistent coverage of broader impact categories such as particulate matter formation, acidification, eutrophication, and human toxicity. Methodological heterogeneity persists across functional units, system boundaries, and inventory data sources, reducing comparability. Furthermore, autonomous haulage impacts, such as reduced idle time, improved cycle consistency, and lower fuel consumption, are typically inferred indirectly through simplified efficiency assumptions rather than modeled as an integrated cyber-physical system. Direct life-cycle evidence for automated or semi-automated equipment remains scarce, and no study models a fully autonomous system as its primary object of assessment; the available evidence on autonomous haulage therefore remains primarily directional and hypothesis-generating rather than conclusive. Overall, LCA applications for mining haulage remain largely static and equipment-focused, indicating the need for more standardized reporting and integrated modeling to support decision-making under evolving low-carbon and autonomous mining strategies.