of Antwerp (14,133 km; 31 days) was modelled using vessel-specific operational data, with emissions allocated by mass fraction relative to the vessel’s deadweight tonnage. Inland transport and pyro-hydrometallurgical processing were included using operator-reported Scope 1 and Scope 2 emission intensities (kgCO₂eq/kg boards treated), calculated under ISO-compliant internal LCA procedures. Metal content estimations were based on PCBspecific characterization data. However, as industrial refining in Western Europe typically processes whole mobile phones (excluding batteries), where plastics and resins contribute to the thermal and reduction processes, this PCB-based modelling approach likely represents a conservative estimate compared to full-device industrial conditions. 3.4. Carbon footprint calculation and extrapolation GHG emissions were calculated using IPCC 2006 [29] emission factors and location-based electricity grid factors. Emissions were aggregated as tCO₂eq, using GWP100 values. For the BAU scenario, carbon footprint values were derived from secondary data obtained from sustainability reports and annual reports of five of the largest mining companies operating in Peru, ensuring representativeness of conventional primary mining practices [29], [30], [31], [32], [33], [34]. For the R&R scenario, total emissions were allocated to recovered metals based on measured metal outputs. These metal-specific emissions were then summed to represent a multi-metal urban mining system, reflecting the economic and operational reality that recovery viability depends on the joint extraction of several metals rather than a single element. For the R&R-MP scenario, metal outputs were recalculated using reported concentration ranges for mobile phone PCBs, which exhibit significantly higher gold and silver contents than mixed electronic boards. This approach isolates the effect of material composition on carbon intensity while maintaining identical energy and transport inputs. 4. RESULTS 4.1. GHG emission hotspots in R&R-based recovery systems (cradle-to-gate) This subsection presents a cradle-to-gate GHG emission hotspot analysis for the recovery and reuse (R&R) system, identifying the life cycle stages that contribute most significantly to total emissions. Figure 1 shows the relative contribution of transport, electricity consumption, thermal treatments, and direct emissions to the overall carbon footprint of the R&R system. The total carbon footprint of the R&R process amounts to 28.69 tCO₂eq for 20.39 tons of electronic boards, with metal treatment and recovery at the EMCR facility being the dominant contributor (27.07 tCO₂eq; 94.34%). Maritime transport of WEEE from Peru to Europe represents a secondary hotspot (1.47 tCO₂eq; 5.13%), while upstream activities such as mobile combustion during collection and loading (0.10 tCO₂eq; 0.36%) and electricity consumption at the Comimtel plant (0.05 tCO₂eq; 0.17%) contribute marginally to total emissions.
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