requiring more granular, activity-based data with clear boundary definitions. The mining sector has been noted as one where Scope 3 from purchased goods (consumables and services) can be disproportionately large yet underreported [1]. 2.2 Prior application of LCA to mineral processing ISO-aligned LCA has been applied to mineral processing in a number of published studies, though coverage is uneven across commodities. Copper beneficiation has attracted a lot of attention, with several gate-to-gate and cradle-to-gate analyses establishing that electricity and grinding media are primary impact drivers [8]. Iron ore processing LCAs are less common and frequently limited in boundary scope, while lithium processing studies have grown rapidly alongside battery supply-chain interest [9]. A gap identified across the literature is the inconsistent treatment of wear parts: many studies exclude mill liners and grinding media entirely or apply single generic emission factors (EFs) without location or manufacturing-route differentiation [5]. The present study directly addresses this gap by using a structured Scope 3 hierarchy and sensitivity analysis across three commodities. 2.3 Established GWP baselines for mineral processing Published GWP benchmarks for mineral processing vary considerably owing to differences in ore grade, location, process route, and system boundary. Published GWP benchmarks for copper mine-to-concentrate operations range from approximately 1,000 to 1,800 kg CO2e per tonne of concentrate [10], though these typically include mining operations. Gate-to-gate processing-only figures are less commonly reported in isolation. For iron ore, values per tonne of concentrate are substantially lower due to simpler beneficiation routes and, in the case of Brazil, a lower-carbon grid. Lithium processing benchmarks are still emerging but reflect high variability linked to process chemistry and geography [11]. The results presented in this paper (1,207 kg CO2e/t Cu con; 12.3 kg CO2e/t Fe con; 104.3 kg CO2e/t Li con) sit within these published ranges and are consistent with location-specific grid intensities, as shown in Table 1. Table 1 – Grid electricity emission factors (EFs) for case study countries (Ecoinvent) Case study Country Grid EF kg CO2e/kWh) Source opper concentrator Chile 0.563 coinvent (market-mix, medium oltage)* on ore oncentrator Brazil 0.213 coinvent (market-mix, medium oltage)* ithium plant Finland 0.146 coinvent (market-mix, medium oltage)* * Market-mix medium voltage category accounts for the emissions throughout the entire value chain of electricity, from generation, transmission, distribution, up until actual usage. 208
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