809 Electricity-related emissions Electricity-related carbon intensity for each scenario was calculated using scenario-specific energy and a representative emission factor, as shown in Eq. (1): sZ 2H2D,E = JYE ×YU2H2D (Eq.1) where sZ2H2D,E is electricity-related carbon intensity (kg CO₂e/t ore), JYE is scenario-specific energy consumption (kWh/t ore), and YU2H2DE is the electricity emission factor (kg CO₂e/kWh). Consumables-related emissions Consumable-related emissions were calculated from mass-based consumable intensities normalised to throughput and combined with cradle-to-gate emission factors. Consumables include grinding media and mill liners associated with the two primary ball mills and the VTM. For each scenario s, total consumable-related carbon intensity was calculated as shown in Eq. (2): sZ DC$E,E = ∑(ï ) ),E × YU)) (Eq.2) where sZDC$E,E is consumable-related carbon intensity (kg CO₂e/t ore), ï),E is mass intensity of consumable i (kg/t ore), and YU) is the cradle-to-gate emission factor (kg CO₂e/kg). Consumable mass intensities were derived from operational data and normalised to the functional unit, ensuring consistency with both process optimisation outputs and life cycle inventory requirements. Operational basis for consumable mass estimation Mill liners were treated as maintenance-driven consumables, with consumption estimated from installed liner mass and scheduled replacement intervals, resulting in a constant mass flow when normalised to throughput. Grinding media consumption was considered operation-driven. Media addition responds to mill power and operating intensity; therefore, wear-rate relationships reported in the literature and practice were applied and converted to mass-based intensities (kg/t ore) for inventory purposes. Although data pathways differ, both converge on a consistent mass-based representation compatible with carbon calculations. Combined carbon results by scenario Total carbon intensity for each scenario was obtained by summing electricity- and consumablerelated contributions. Table 3 presents combined results for selected scenarios. Table 3 – Consumable and electricity emission Across Selected Scenarios Scenario Through put (tph) Specific Energy (kWh/t) CO₂e Consu mables (kg/t) CO₂e Electricity (kg/t) Total CO₂e (kg/t) Δ vs Base (%) Base Case 86.6 19.60 2.10 13.33 15.4 Sim 1 92.4 18.83 2.01 12.81 14.8 -3.9% Sim 5 96.6 18.36 1.96 12.49 14.4 -6.3% Sim 7 96.6 20.08 2.14 13.66 15.8 2.5% Sim 8 101.0 20.51 2.18 13.94 16.1 4.7% 4.4.2 Interpretation of Results Including consumables increases absolute carbon intensity by approximately 15% relative to electricity-only results. Incorporating material-related emissions reduces differentiation between scenarios. While ranking remains consistent with specific energy trends, integration of material-related emissions establishes a structural emissions baseline that cannot be reduced through energy optimisation alone.
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